Overtreatment of axillary lymph node dissection (ALND) may occur in patients with axillary positive sentinel lymph node (SLN) but negative non-SLN (NSLN). Developing a magnetic resonance imaging (MRI)-based radiomics nomogram to predict axillary NSLN metastasis in patients with SLN-positive breast cancer could effectively decrease the probability of overtreatment and optimize a personalized axillary surgical strategy.This retrospective study included 285 patients with positive SLN breast cancer. Fifty five of them had metastatic NSLNs and 230 had non-metastatic NSLNs. MRI-based radiomic features of primary tumors were extracted and MRI morphologic findings of the primary tumor and axillary lymph nodes were assessed. Four models, namely, a radiomics signature, an MRI-clinical nomogram, and two MRI-clinical-radiomics nomograms were established based on MRI morphologic findings, clinicopathologic characteristics, and MRI-based radiomic features to predict the NSLN status. The optimal predictors in each model were selected using the 5-fold cross-validation (CV) method. Their predictive performances were determined by the receiver operating characteristic (ROC) curves analysis. The area under the curves (AUCs) of different models was compared by the Delong test. Their discrimination capability, calibration curve, and clinical usefulness were also assessed.vs. 0.806, P <0.001) and MRI-clinical nomogram . In addition, the MRI-clinical-radiomics nomogram without CA 15-3 showed a higher performance than that of the radiomics signature  and the MRI-clinical nomogram . The MRI-clinical-radiomics nomograms showed good discrimination and good calibration. Decision curve analysis demonstrated that the MRI-clinical-radiomics nomograms were clinically useful.The 5-fold CV analysis showed that the AUCs ranged from 0.770 to 0.847 for the radiomics signature, from 0.720 to 0.824 for the MRI-clinical nomogram, from 0.843 to 0.932 for the MRI-clinical-radiomics nomogram. The optimal predictive factors in the radiomics signature, MRI-clinical nomogram, and MRI-clinical-radiomics nomogram were one texture feature of diffusion-weighted imaging (DWI), two clinicopathologic features together with one MRI morphologic finding, and the DWI-based texture feature together with the two clinicopathologic features plus the one MRI morphologic finding, respectively. The MRI-clinical-radiomics nomogram with CA 15-3 included achieved the highest AUC compared with the radiomics signature (0.868 The MRI-clinical-radiomics nomograms developed in our study showed high predictive performance, which can be used to predict the axillary NSLN status in SLN-positive breast cancer patients before surgery. Breast cancer is the first high incidence of malignant tumor and the leading cause of death by cancer among female patients . AxillarPreviously, several clinicopathologic nomograms  and scoring systems  have been established to predict the NSLN status –14. HoweIn this study, a large cohort of patients with SLN-positive breast cancer was retrospectively included. Radiomic features of the primary breast tumor on pretreatment multiparametric MRI were extracted, and the MRI-based radiomics signature was constructed to predict the NSLN metastasis. In addition, predictive clinicopathologic features and MRI morphologic findings of breast tumors before treatment were identified to develop an integrative predictive MRI-clinical-radiomics nomogram. The purpose of this study was to develop an MRI-based radiomics model to predict the NSLN metastasis in breast cancer patients with positive SLNs.n = 55) and the non-metastatic NSLN group (n = 230) in which none of NSLN was metastasis pathologically.This study was approved by the Institutional Review Board of Sun Yat-sen Memorial Hospital, Sun Yat-sen University, and the informed consent was waived because of the nature of the retrospective study. A total of 306 consecutive women with pathologically confirmed primary breast carcinoma were collected from the hospital medical record system between April 2016 and September 2018. The patient enrollment workflow is shown in All patients were treated by surgery, namely, breast tumor resection, SLNB, and ALND. SLNB was performed by using the methylene blue technique, as previously described . The staMRI was performed on a 1.5 T MR scanner  with an 8-channel phased-array breast coil . The patients were placed in the prone position with a body parallel to the shoulders, and both breasts were naturally suspended in the coil. The sequences included axial T2-weighted imaging (T2WI), axial T1-weighted imaging (T1WI), axial diffusion-weighted imaging (DWI) with readout segmented echo planar imaging, followed by axial dynamic contrast-enhanced imaging (DCE), axial and coronal delayed contrast-enhanced T1WI (T1 + C). Two dynamic phases of DCE acquisition  were initially performed. And then, all patients underwent intravenous bolus injection of Gd-DTPA-BMA  through a high-pressure contrast agent injector . The T1 + C images were obtained immediately after the DCE imaging was finished. The detailed acquisition parameters are shown in Morphologic findings of MRI were assessed by two radiologists  who knew breast cancer diagnosis but were blinded to other clinicopathologic information. All MRI sequences of each patient were available during the morphologic assessment. Any disagreement between the two radiologists was resolved by consultation of another senior radiologist , and a final diagnosis was made by this senior radiologist. For morphologic analysis, MRI findings, namely, the quadrant of breast cancer, long diameter of breast cancer, presence of ALN metastasis, number of metastatic ALN, and short diameter of the largest ALN, were evaluated. The quadrant of breast cancer and the long diameter of breast cancer were measured on axial or coronal T1 + C image in which the primary tumor showed the largest section. All lymph nodes in the axilla were evaluated on axial and coronal T1 + C images. The ALN metastasis was assessed according to previously morphologic criteria as follows: the disappearance of hilum structure , lymphatn = 60) after 2 weeks, and investigator 2  independently performed the segmentation in these 60 patients using the same method as that of investigator 1. Second, radiomic feature extraction was performed using the PyRadiomics toolkit (version 3.0.1) written in Python (version 3.8.3). All the segmented images were interpolated to normalize the spatial resolution in X, Y, and Z directions. For each patient, 1,595 radiomic features were extracted from the initial VOIs and the wavelet filtered, and intensity transformed DWI, ADC, T2WI, and T1 + C images. A total of 6,380 radiomic features were extracted from the primary breast tumors of these four sequences. Details of radiomic features are shown in The flowchart and radiomics analysis workflow are shown in U test was used to compare the MRI morphologic findings and clinicopathologic characteristics between the metastatic NSLN group and the non-metastatic NSLN group. Multivariable logistic regression was then applied to select independent predictors of NSLN metastasis from the MRI morphologic findings and clinicopathologic characteristics. For radiomics analysis, the Mann–Whitney U test was performed to select the statistically significant radiomic features between metastatic NSLN group and non-metastatic NSLN group, followed by the least absolute shrinkage and selection operator (LASSO) regression to identify the NSLN metastasis-related radiomic features. The radiomics signature was presented as a radiomics score and constructed by combining the NSLN metastasis-related radiomic features, weighted by the corresponding coefficients of LASSO regression. To determine the optimal independent predictors in each model, a 5-fold cross-validation (CV) analysis was performed by training and testing five separate models to select the most robust predictors  was conducted respectively to assess the clinical use of the final predictive models presenting as the net benefit at different threshold probabilities .t-test. The categorical variables were compared between different groups using Pearson’s 2χ or Fisher exact test. The comparison of continuous and categorical variables and ICCs for the feature extraction of intra- and inter-investigator was conducted on SPSS 25. The Mann–Whitney U test, LASSO regression, multivariable logistic regression, 5-fold CV, ROC analysis with AUC values calculating, calibration curves, and DCA were performed using the R software (version 4.0.1). P <0.05 was considered statistically significant.Descriptive statistics were summarized as median (quartile range) for continuous variables or as frequencies with percentages for categorical variables. The continuous variables were compared between different groups by using the P <0.001), pathologic types of breast cancer (P = 0.005), lymphovascular invasion (P = 0.001), MRI-determined presence of ALN metastasis (P = 0.018), and MRI-determined short diameter of the largest ALN (P <0.001) between metastatic and non-metastatic NSLN groups. Most of the patients  had preoperative US results of ALN status. Among these 272 patients, 246 patients had negative results on axillary US examination, and 26 patients had positive results on axillary US examination but negative results US-guided FNAB. Based on the entire dataset of 285 patients, multivariable logistic regression showed that one MR-determined finding (MRI-determined short diameter of the largest ALN), and two clinicopathologic characteristics (CA 15-3 and lymphovascular invasion of breast cancer) were the independent predictors of the NSLN metastasis  and the MRI-clinical nomogram (P = 0.003–0.050). Although Fold 1 model of MRI-clinical-radiomics nomogram appeared to perform the best in training and also validation and in comparison with other models, the most robust variables selected by each CV fold were four features, namely, an MRI morphologic finding (short diameter of the largest ALN), two clinicopathologic features (CA 15-3 and lymphovascular invasion of breast cancer), and a texture feature of DWI , which were considered as the optimal independent predictors and used for final model construction.For the radiomics signature, the MRI-clinical nomogram and the MRI-clinical-radiomics nomogram, the selected independent predictors and their AUCs in each training and internal validation CV fold of the 5-fold CV analysis are shown in P <0.001) and MRI-clinical nomogram   but without CA 15-3 were also constructed. This MRI-clinical-radiomics nomogram had an AUC of 0.852, which was significantly higher than those of radiomics signature  and MRI-clinical nomogram  in predicting NSLN metastasis in the entire dataset . The comparison of radiomics scores between the two groups is shown in The final model of the MRI-clinical-radiomics nomogram is shown in patients Figure 4Additionally, since axillary US is the most robust axillary assessment tool, the 5-fold cross-validation analysis, where the US-reported ALN status was also included as a variable, was performed in 272 patients with negative axillary US examination (with or without FNAB). The results showed that the US-reported ALN status was not a strong clinical predictor Figure 6In this study, we developed two MRI-clinical-radiomics nomograms that incorporate one MR-determined finding (short diameter of the largest ALN), one or two clinicopathologic characteristics (i.e. lymphovascular invasion of breast cancer or CA 15-3 plus lymphovascular invasion of breast cancer), and the radiomics signature consisting of one DWI radiomic feature based on the entire dataset of 285 patients. These two MRI-clinical-radiomics nomograms demonstrated robust and high predictive performance (AUC = 0.868 and 0.852), which were both better than the radiomics signature alone and MRI-clinical nomogram. The developed MRI-clinical-radiomics nomograms can serve as novel and easy-to-popularized tools to predict axillary NSLN metastasis in breast cancer patients with positive SLNs.Invasive ALND is associated with potential postoperative morbidities such as pain, numbness, lymphedema, restricted arm movements, and high risk of infection , 33, whioriginal_GLDM_Small_Dependence_High_GrayLevel_Emphasis) ranged from 0.774 to 0.847 in the training CV fold and from 0.770 to 0.820 in the internal validation CV cohort. Moreover, DWI_original_GLDM_Small_Dependence_High_GrayLevel_Emphasis was a consistently selected variable during the 5-fold CV analysis, suggesting that this radiomic feature from DWI was a robust variable. As such, it was selected as the optimal predictor incorporated into the final predictive models. The final model of the one DWI feature-based radiomics signature had a favorable AUC of 0.806 in the entire cohort. This result suggested that the predictive capacity of radiomics features from DWI may be better than the radiomics features extracted from other sequences for predicting the NSLN metastasis. Moreover, this one feature-based radiomics signature might be more convenient for clinical use since fewer reproducible radiomic features imply better reproducibility  and the MRI-clinical nomogram  in the entire dataset. In addition, the MRI-clinical-radiomics nomogram without CA 15-3 incorporated also showed a higher performance than those of the radiomics signature  and the MRI-clinical nomogram  in the entire dataset. It is seemingly that the MRI-clinical-radiomics nomograms developed in our study may serve as a preferable approach to predicting NSLN status in patients with SLN metastasis but without NSLN metastasis. Notably, the MRI-clinical-radiomics nomograms developed in our study also did not need pathologic features that should be obtained from invasive SLNB.To further improve the predictive performance of radiomics signature, clinicopathologic information and MRI-determined morphologic findings were also assessed and incorporated to build an integrative radiomics-based predictive model in our study. Besides the radiomics signature, one MRI morphologic finding (short diameter of the largest ALN), and two clinicopathologic characteristics, including CA 15-3, lymphovascular invasion of breast cancer, were identified as the independent predictors by multivariable logistic regression for NSLN metastasis. The final model of the MRI-clinical-radiomics nomogram incorporating these predictors showed a higher performance than that of the radiomics signature  underwent preoperative US scan of ALN. Unfortunately, the results of axillary US examination in the remaining 13 patients were not available in our hospital database. This might result in slightly higher than expected SLN involvement in the entire cohort. The accuracy of NSLN prediction could be affected for the constructed predictive models. Third, the proportion of the patients with metastatic NSLN enrolled in our study was relatively small. In our study, the 5-fold CV analysis was used to select the optimal variables for the development of predictive models, as previously reported . Forth, In conclusion, two MRI-clinical-radiomics nomograms were developed in our study. The proposed integrative MRI-clinical-radiomics nomograms was one feature-based radiomics signature with one MRI-determined morphologic finding, and one or two clinicopathologic characteristic incorporated, which showed high performance in predicting the axillary NSLN metastasis in patients with SLN positive breast cancer. These MRI-clinical-radiomics nomograms can serve as novel tools to predict axillary NSLN status, which may help avoid unnecessary invasive procedures on the axilla, i.e., ALND, in breast cancer patients with positive SLN but negative NSLN.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Institutional Review Board of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, and the informed consent was waived because of the nature of the retrospective study. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.All authors conceived and execution of this study or analysis of the study data. YQ, XZ, and JS designed the study. YQ, XZ, ZW, SW, DW, HL, JM, GD, XT, RZ, JH, and LH participated in the collection of the clinical information and data analysis. ZW and ZY did the statistical analysis. XZ and JS provided critical comments and suggestions and revised the manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This work was supported by the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2017), the National Natural Science Foundation of China , the Key Areas Research and Development Program of Guangdong (2019B020235001), the Natural Science Foundation of Guangdong Province (2021A1515010385), the Medical Artificial Intelligence Project of Sun Yat-Sen Memorial Hospital (YXRGZN201905), and the Tianshan Youth Project of Xinjiang Uyghur Autonomous Region (2019Q144).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Children are prescribed second-generation antipsychotic (SGA) medications, such as olanzapine (OLZ) for FDA-approved and “off-label” indications. The long-term impact of early-life SGA medication exposure is unclear. Olanzapine and other SGA medications are known to cause excessive weight gain in young and adult patients, suggesting the possibility of long-term complications associated with the use of these drugs, such as obesity, diabetes, and heart disease. Further, the weight gain effects of OLZ have previously been shown to depend on the presence of gut bacteria and treatment with OLZ, which shifts gut bacteria toward an “obesogenic” profile. The purpose of the current study was to evaluate changes in gut bacteria in adult mice following early life treatment with OLZ and being fed either a high-fat diet or a high-fat diet supplemented with fish oil, which has previously been shown to counteract gut dysbiosis, weight gain, and inflammation produced by a high-fat diet. Female and male C57Bl/6J mice were fed a high fat diet without (HF) or with the supplementation of fish oil (HF-FO) and treated with OLZ from postnatal day (PND) 37–65 resulting in four groups of mice: mice fed a HF diet and treated with OLZ (HF-OLZ), mice fed a HF diet and treated with vehicle (HF), mice fed a HF-FO diet and treated with OLZ (HF-FO-OLZ), and mice fed a HF-FO diet and treated with vehicle (HF-FO). Following euthanasia at approximately 164 days of age, we determined changes in gut bacteria populations and serum LPS binding protein, an established marker of gut inflammation and dysbiosis. Our results showed that male HF-FO and HF-FO-OLZ mice had lower body weights, at sacrifice, compared to the HF group, with a comparable body weight across groups in female mice. HF-FO and HF-FO-OLZ male groups also exhibited lower serum LPS binding protein levels compared to the HF group, with no differences across groups in female mice. Gut microbiota profiles were also different among the four groups; the Bacteroidetes-to-Firmicutes (B/F) ratio had the lowest value of 0.51 in the HF group compared to 0.6 in HF-OLZ, 0.9 in HF-FO, and 1.1 in HF-FO-OLZ, with no differences in female mice. In conclusion, FO reduced dietary obesity and its associated inflammation and increased the B/F ratio in male mice but did not benefit the female mice. Although the weight lowering effects of OLZ were unexpected, FO effects persisted in the presence of olanzapine, demonstrating its potential protective effects in male subjects using antipsychotic drugs. Second-generation antipsychotics (SGAs) are an effective treatment option for adults suffering with psychiatric disorders and children suffering with schizophrenia and bipolar I disorder ,2,3. SGAVarious bioactives are known to prevent or reduce obesity. One of the bioactives of interest to us is fish oil (FO), which has beneficial effects in reducing obesity and related metabolic diseases in non-primate animals ,9,10,11.Bacteroidia is decreased while Gram-positive Clostridia is increased in obese rodents compared to lean ones [Akkermansia at the genus level is negatively correlated with glucose intolerance [Numerous studies suggest that diet-induced obesity and insulin resistance are associated with alteration of the gut microbiota composition in mice and humans ,17,18,19ean ones . Moreoveolerance ,25. Inteolerance . Additioolerance ,28,29,30In this study, we evaluated the effects of FO and OLZ, independently and in combination, on markers of inflammation and adiposity, and determined potential associations between previously established anti-inflammatory and weight reducing effects of FO and gut microbial composition . AccordiWe report here that FO reduced obesity-associated inflammation. This is the first report of FO and OLZ’s differential effects on gut microbiome. Surprisingly, OLZ exhibited beneficial metabolic effects such as FO and did not counteract protective effects of FO. FO increased B/F ratio in male mice, and these effects persisted in the presence of OLZ, warranting further studies in both animal and human subjects using antipsychotic drugs.n = 8 per group): HF (HF), HF with olanzapine (HF-OLZ), HF with fish oil (HF-FO), and HF with olanzapine and fish oil (HF-OLZ-FO). Male and female mice (n = 32 per sex at 4–5 weeks of age) were maintained on a high fat  diet, with fish oil, FO  or without FO supplementation   according to the manufacturer’s protocols. Serum and intestinal samples were collected at the end of the feeding trial for LBP and mic16S sequencing, respectively. All experimental procedures and animal care were approved and performed in accordance with the Texas Tech University Laboratory Animal Care under permit number 15007. Mice were randomized into four groups of mice (nc.) see , OlanzapLPS binding protein (LBP) was measured in serum using an ELISA kit , following the manufacturer’s protocols, and as we have previously described .http://www.mg-rast.org/, accessed on 6 December 2021) in September 2018. The standard processing pipeline of MG-RAST with default settings was used for filtering sequences based on length, number of ambiguous bases, and quality. The annotation source considered was the Greengenes database using the MG-RAST processing pipeline with default settings. The bacterial community richness and bacterial community diversity indices were calculated using phyloseq R package, version 1.34.0 [DNA was extracted from each sample, and the V4 region of the 16S rRNA gene was amplified and sequenced on an Illumina HiSeq 2000 Genome Sequencer. Sequencing was performed at the Argonne National Laboratory and at the Research and Testing Laboratory (RTL), Lubbock, TX. The samples in FASTQ format were deposited to the metagenomics analysis server . The one-way analysis of variance (ANOVA) test  and Studt-test  were useFinal body weight was calculated at sacrifice for the four groups in male and female mice. No significant differences in final body weights were observed between the four groups in male and female mice . In maleSerum levels of LBP in the HF group was compared to HF-OLZ, HF-FO, and HF-FO-OLZ, individually for both male and female mice. LBP levels were comparable between the HF-OLZ and HF groups, while the HF-FO and HF-FO-OLZ groups had significantly lower LBP levels compared to the HF group in male mice a. In femOn average, 536,873 sequences were obtained from each sample. Less than 1% of sequences failed to pass the QC pipeline, 87% of sequences contained predicted features with known functions, and 13% of sequences had predicted features with unknown functions.p = 0.65 for the observed OTU index and p = 0.55 for the Shannon index) (see p = 0.69 for the observed OTU index and p = 0.29 for the Shannon index) among the various groups  see . In femaoups see .Firmicutes was the most predominant phylum, followed by Bacteroidetes and Verrucomicrobia in HF, HF-FO, and HF-OLZ, while in HF-FO-OLZ, Bacteroidetes was the most predominant phylum, followed by Firmicutes and Verrucomicrobia  ratio was significantly increased in HF-FO (mean = 0.9) and HF-FO-OLZ (mean = 1.1) groups compared to HF (mean = 0.52) group  and HF-FO-OLZ (36%) relative to the HF (25%) and HF-OLZ (23%) groups  and HF-FO (33%) groups relative to the HF-OLZ (16%) and HF-FO-OLZ (16%) groups (see p = 0.18). A higher B/F ratio was observed in the HF (mean = 0.67) and HF-FO (mean = 0.69) groups relative to the HF-OLZ (mean = 0.56) and HF-FO-OLZ (mean = 0.48) groups (see Akkermansia was more enriched in HF (28%) and HF-FO (34%) relative to the other groups of HF-OLZ (17%) and HF-FO-OLZ (17%)  see . The current study investigated changes in gut microbiota in male and female C57BL/6J mice treated in early life with SGA medication OLZ and fed an HF diet or an HF diet supplemented with FO. In contrast to the increasing body weight in adult female and male mice , in the Gut dysbiosis is an important feature of metabolic dysregulation including obesity. Dietary intervention to modulate the microbial environment is of current interest. Hence, in this study, we identified how FO along with OLZ could modulate microbes to prevent/reduce obesity. We found varied classes of microbial species to be favorably altered with FO in males, but most of the alterations were absent in female mice.FO had a modulatory effect on the gut microbiome by increasing the B/F ratio compared to the HF mice. These data are in line with studies in rodents where obese rats had higher B/F ratio than lean mice . FurtherObesity is associated with chronic systemic inflammation in the adipose tissue. This chronic inflammation increases the levels of circulating pro-inflammatory mediators, which could in part contribute to intestinal inflammation. Conversely, gut microbiota could be a potential source of inflammation due to higher lipopolysaccharide (LPS). In line with this, we identified that FO was able to reduce the levels of LBP protein, a marker of intestinal inflammation. FO could reduce LBP through several possible pathways. One probable pathway is through the traditional NFKB pathway. Another probability is by the metabolites of FO such as resolvins, which are known to inhibit inflammation. This needs to be further investigated but studies indicate the resolvins levels are increased with intestinal inflammation.barnesiella [barnesiella was not altered in female mice, indicating the sexual dimorphic role of FO in the microbial environment. However, whether the improvements in barnesiella translate into increases in acetate levels remains to be tested.Acetate producing bacteria, nesiella , was impnesiella . Moreovenesiella . Furthernesiella . In addiakkermansia Sp is one of the few Sp which is intensively linked to obesity development. Lower levels of akkermansia are reported with obesity and insulin resistance [A.mucinphila reversed the HF diet induced obesity [A.mucinophila is also known to contribute to SCFA, which in turn regulates lipid metabolism.Interestingly, sistance . This is obesity ,44,45. Fclostridia levels were higher in female FO fed mice than HF fed mice. This is in line with human studies where the clostridia are shown to promote weight gain in individuals exposed to clostridia. However, in humans several patterns emerged with obesity, due to the differences in the levels of the different species within the class [clostridia is absent in rodents compared to humans, which still needs to be tested.Furthermore, to validate the beneficial role of FO, another species, clostridia, was reduced in male mice compared to the HF fed mice that did not receive FO. This was in line with rodent studies where clostridia were higher in obese mice compared to lean mice. However, we saw the opposite results in female mice, where he class . It is pFirmicutes, Bacteroidetes, and Verrucomicrobia in the gut microbiota and decreased the proportion of Lactobacillus and others, compared to HF. Additional studies are required to directly link FO and OLZ to changes in gut bacteria and subsequent reduction in obesity associated inflammation, using fecal matter transfer or treatment with the specific strains that were modified by FO and OLZ. Given that FO and OLZ are clinically used, these treatments could be repurposed for metabolic inflammatory diseases.In conclusion, our studies showed that supplementation of HF diets with FO (HF-FO) and combined FO and olanzapine (HF-FO-OLZ) reduces dietary obesity and inflammation and induced changes to gut microbiota composition. Specifically, FO supplementation and early-life OLZ treatment increased the abundance of the genera


Allergy constitutes a major health issue due to its large prevalence. The established therapeutic approaches  do not address the underlying causes of the pathology, highlighting the need for other long-term treatment options. Antigen-specific immunotherapy enables the long-term control of allergic diseases by promoting immunological tolerance to the allergen. However, efficacious immunotherapies are not available for all possible allergens, and the risk of undesired reactions during therapy remains a concern, especially in patients with severe allergic reactions. In this context, two types of therapeutic strategies appear especially promising for the future in the context of allergy: cell therapy and bio- or nano-material-based therapy. In this review, the main strategies developed this far in these two types of strategies are discussed, with several examples illustrating the different approaches. An allergic reaction is the useless response of the immune system toward a harmless substance  and is the consequence of a failure in the development of tolerance. It involves components of the innate and the adaptive immune responses as type 2 innate lymphoid cells (ILC2s), mast cells (MCs), eosinophils, and basophils, as well as CD4+ T helper type 2 (Th2) cells and IgE producing B cells . AllergyThe sensitization starts from allergen capture by dendritic cells (DCs) resident in the airway, skin, or gut. DCs internalize and process the antigen into peptides and present them to naïve CD4+ T cells, which become allergen-specific Th2 cells. Th2 cells, through surface molecules and secretion of type 2 cytokines , promote Ig isotype switch in B cells, which differentiate to plasma cells, producing allergen-specific IgE antibodies. Allergen-specific memory Th2 and B cell populations expand and are stimulated upon re-exposure to the allergen . I. I108]. ications . The comRegarding the comparison of tolerogenic co-delivery with other strategies, Liu et al. recently reported the efficacy of LSEC-targeted (liver-accumulating) OVA-loaded PLGA nanoparticles compared with non-targeted OVA-loaded PLGA nanoparticles that also include one immunomodulatory agent, either curcumin or rapamycin . SimilarTo end this section of the article, The key question in novel allergy therapy approaches is how to maintain and restore tolerance. Specific immunotherapy has evolved in many ways, and the reestablishment of tolerance is partially possible. The driving mechanism behind such therapeutic strategies is the induction of allergen-specific regulatory subsets of T and B cells. However, safety concerns in patients with severe reactions and low efficacy for some allergens highlight the need for more research in this area. For therapeutic use, cell therapies and bio- and nano-material-based strategies offer good promise for future development. A potential combination of both strategies, employing biomaterials for exogenous cell delivery in tolerance-generating therapy in the context of allergy, remains largely unexplored, although some works have already been performed in other areas, such as autoimmune diseases and allogeneic transplantation . On the


Among these, microRNAs have received widespread attention for their roles in osteoarthritis and rheumatoid arthritis. With evidence to suggest that long non-coding RNAs and circular RNAs function as competing endogenous RNAs to sponge microRNAs, the net effect on gene expression in specific disease contexts can be elusive. Studies to date have focused on elucidating individual long non-coding-microRNA-gene target axes and circular RNA-microRNA-gene target axes, with a paucity of data integrating experimentally validated effects of non-coding RNAs. To address this gap, we curated recent studies reporting non-coding RNA axes in chondrocytes from human osteoarthritis and in fibroblast-like synoviocytes from human rheumatoid arthritis. Using an integrative computational biology approach, we then combined the findings into cell- and disease-specific networks for in-depth interpretation. We highlight some challenges to data integration, including non-existent naming conventions and out-of-date databases for non-coding RNAs, and some successes exemplified by the International Molecular Exchange Consortium for protein interactions. In this perspective article, we suggest that data integration is a useful  Noncoding RNAs are key regulators of gene expression in the musculoskeletal system. These RNA molecules are transcribed from DNA but not translated into protein . Among tThere are multiple factors governing miRNA expression, from the level of the cell to the organism. MiRNA biogenesis involves several post-transcriptional processing steps and is under both temporal and spatial control that can introduce variability . Once prMiRNAs play both protective and destructive roles in the musculoskeletal system . Since ain silico strategy that can be tailored to cells, diseases, and other factors of interest. To illustrate this, we present two examples that integrate the recent literature on non-coding RNAs in OA and RA, focusing on chondrocytes and fibroblast-like synoviocytes (FLS), respectively. These examples are proof-of-concept of the relationships  that can be constructed using non-coding RNA axes that have been experimentally validated. In building these networks, we encountered key challenges, including inconsistency in annotation of non-coding RNAs. These challenges are discussed along with our perspectives on future directions needed to advance the non-coding RNA field.To improve our understanding of the biological and clinical context of non-coding RNA regulation in arthritis, there is an outstanding need for methods to identify the interactions among non-coding RNAs and their gene targets in specific cell types. Computational biology approaches to predict ceRNA activity among non-coding RNAs, as well as gene targets and pathways, is a useful To curate relevant literature reporting non-coding RNA axes in OA chondrocytes and RA FLS, we searched PubMed using combinations of key words including osteoarthritis, rheumatoid arthritis, microRNA, long non-coding RNA, and circular RNA. Articles were filtered for those with an experimentally validated lncRNA-miRNA-mRNA or circRNA-miRNA-mRNA axis in chondrocytes from OA subjects or FLS from RA subjects. We included 36 studies for OA and 10 studies for RA published between October 2019 and December 2020. The lncRNA/circRNA, miRNA, and mRNA targets were extracted from individual papers. Common groups of genes were fed into a network prepared in NAViGaTOR v3.0.14 . ProteinOA is a degenerative disease of the joints, causing pain and disability in 7% of the global population . Patholovia miR-146a and miR-145  , promoting inflammation and joint destruction in RA . Downreg (SIRT1) . As in OWe hold the perspective that non-coding RNAs function in tissue-specific networks that can be elucidated using curation and computational biology to integrate experimentally validated data from individual studies. Taking OA chondrocytes and RA FLS as two examples, we integrated non-coding RNA axes by connecting common molecules and produced networks highlighting connections that may have otherwise been unknown. In particular, miRNAs are shown to orchestrate the effects of lncRNAs and circRNAs on gene expression, which has implications for downstream signaling, including protein-protein interactions and regulation of biological processes. While we did not explore upstream factors regulating the expression of lncRNAs and circRNAs, nor the direct effects of lncRNAs and circRNAs on gene expression, these are equally important considerations for understanding the fine-tuning that non-coding RNAs drive in disease. Since non-coding RNAs are highly stable in circulation, they can be used as diagnostic biomarkers for patients with OA, RA, and other musculoskeletal diseases –43. AddiTo note limitations, our restricted literature search may have missed other reports on the molecules included in the networks, and therefore these are not exhaustive networks. Based on the high number of studies reporting non-coding RNA axes in OA chondrocytes and RA FLS, we focused on these cell types and excluded articles reporting non-coding RNA axes in other cells or biofluids for these diseases. Similarly, to maximize physiological relevance, we chose to exclude studies that used only animal models or cell lines, instead focusing on studies that used primary human chondrocytes or FLS (often in addition to cell lines). By applying these criteria, our intention was to capture axes that were established in comparable biological contexts in order to justify integration across studies. While experimental validation of the networks shown in https://www.genenames.org/about/guidelines/)  released guidelines (elines/) . Unfortuelines/) , 48. Theelines/) , and thielines/) , miRNA nhttps://lncipedia.org) provides consistent nomenclature and links to alternative names, a feature that is useful for mapping different publications to the same molecule (https://www.picb.ac.cn/rnomics/circpedia/), a reference database for circRNAs, had a similar fate, with no up-to-date curations  is a database that is attempting to overcome such roadblocks, integrating data from multiple reference databases , but not for circRNAs, though some suggestions are provided . LNCipedmolecule . Unfortuurations . This laurations . RNAcentatabases . Howeverhttp://123.59.132.21/lncrna2target/index.jsp), with 2,189 lncRNA-target interactions derived from low-throughput experiments and 203,500 from high-throughput experiments, and with a recent update in 2021 (http://bio-annotation.cn/lncrna2target/) has annotated 421,501 predicted human circRNAs and provides predicted RNA-binding proteins and miRNA interactions with circRNAs  Consortium for protein interactions, for example , 61]. ThWhile overcoming data integration challenges is not trivial, the networks achieved can provide more complete and more precise insight into the molecular background of a disease of interest. We demonstrate this using an integrative computational biology approach, constructing lncRNA/circRNA-miRNA-mRNA networks in OA chondrocytes and RA FLS. Given the recent surge in studies exploring non-coding RNA axes in various diseases, placing findings of individual studies into a broader biological context while maintaining key parameters  is expected to advance our understanding of the net effect of manipulating a single non-coding RNA. From larger networks, sub-networks may be selected for future investigation based on a specific hypothesis, or simply based on the number or nature of connections. Moving forward, concerted efforts to unify nomenclature, maintain databases, and improve context-specific target predictions is expected to support integrative approaches that expedite prioritization of the most promising candidates for experimental exploration in specific biological contexts.Data available upon request to the authors as described in methods section.SA and IJ conceptualized the article. SA wrote the first draft with input from NK. CP contributed content on data integration. MP performed the literature search and contributed content on osteoarthritis. MO performed the literature search and contributed content on rheumatoid arthritis. IJ prepared the network figures. All authors critically revised the article and approved the final draft.via the Toronto General and Western Hospital Foundation, University Health Network. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.MP was supported through a Wellcome Trust Clinical Intermediate Fellowship (grant 107471/Z/15/Z). MJO was supported by VA Clinical Science Research and Development award (CDA #IK2 CX001269). IJ was supported in part by funding from Natural Sciences Research Council (NSERC #203475), Canada Foundation for Innovation , Ontario Research Fund (RDI #34876), IBM, Ian Lawson van Toch Fund, and the Schroeder Arthritis Institute SA declares a filed US Provisional Patent Application No. 63/033,463 titled “Circulating MicroRNAs in Knee Osteoarthritis and Uses Thereof”.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The present study aimed to compare the clinical effects of image-guided versus blind steroid injection to treat shoulder pain, which is always debatable. An electronic search of credible databases was conducted for randomized controlled trials (RCTs) comparing image-guided versus blind steroid injections. The continuous data were pooled as mean difference (MD) or standardized mean difference (SMD), and dichotomous data were grouped as odds ratio (OR) with 95% confidence interval (CI). Sensitivity analysis and leave-one-out analysis were performed. The meta-analysis of 20 RCTs comprising 1136 patients favored image-guided injection based on the MD of the visual analog score (VAS) and shoulder function scores, measured between six weeks follow-up and baseline . Meta-analysis did not favor either group regarding the shoulder disability scores or side effects . The image-guided approach was associated with significant improvement in pain and shoulder functionality. However, no significant difference was observed between the two approaches in terms of disability scores and side effects. Shoulder pain can cause significant morbidity and compromise the person's ability to carry out daily activities and work -2. The pIrrespective of the underlying etiology, glucocorticoid injections are widely used to treat shoulder pain and improve the functionality of shoulder movements. Two methods are used for drug delivery, a landmark-guided approach (i.e. blind) and an image-guided approach using ultrasonography . The lanA comprehensive study is required to assess the evidence available and determine the best approach for managing shoulder pain. In our systematic review and meta-analysis, we investigated the efficacy and safety of image-guided versus blind corticosteroid injections in adults with shoulder pain.Material and methodsAccording to the Cochrane Handbook of Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines, we carried out this study. No institutional review board approval was required for this systematic review.Search StrategyRelevant studies were identified through an extensive electronic search of databases such as PubMed, Web of Science, and Cochrane CENTRAL for reports till June 2021 from the inception. The search terms were  AND (steroid OR corticosteroid OR glucocorticoid OR triamcinolone OR methylprednisolone OR hydrocortisone OR prednisolone OR cortisone OR dexamethasone OR betamethasone) AND (frozen shoulder OR adhesive capsulitis OR shoulder pain OR shoulder impingement syndrome OR rotator cuff OR bursitis). Additionally, the reference lists of included studies were screened manually to identify additional articles, that are potentially relevant.Study SelectionWe included randomized controlled trials (RCTs) according to the PICO approach: P, patients with shoulder pain; I, ultrasound-guided corticosteroid (US-guided CS); C, comparison with blind or landmark injection of CS; and O, efficacy outcomes including changes of the visual analog score (VAS), shoulder function scores, shoulder abduction between baseline and six weeks follow-up, and safety outcomes included side effects. Exclusion criteria were observational studies, review articles, case reports, comments or guidelines, animal studies, non-English articles, and insufficient data to calculate. Disagreements were solved by consensus.Data ExtractionFor each paper, we extracted the following information: name of the first author, year of publication, country, number of patients, their mean age, percentage of females, type of shoulder disease, follow-up durations, and efficacy and safety outcomes.Quality Assessment and Data ExtractionWe used Cochrane Collaboration's tool for assessing the risk of bias of included RCTs . Risk ofStatistical AnalysisContinuous data were calculated as mean difference (MD) or standardized mean difference (SMD) with a 95% confidence interval (CI). Dichotomous data were pooled as odds ratio (OR), with 95% CI. Heterogeneity was assessed by visual inspection of the forest plots and measured by Q statistics and statistics. Significant statistical heterogeneity was indicated by a Q statistic P-value less than 0.1 or by more than 50%. In case of significant heterogeneity, a random effect model was employed. Otherwise, the fixed-effect model was used. All statistical tests were two-sided, and P < 0.05 was considered statistically significant. Leave-one-out-meta-analysis was performed to assess the contribution of each study to the overall model. The meta-analysis of all studies enrolled was conducted in OpenMeta[analyst] software.ResultsSearch StrategyA total of 2120 relevant papers were initially identified using the search strategy. A total of 324 duplicated papers were excluded by EndNote software, along with another 1750 papers that did not fit the criteria for analysis on the title and abstract screening. Based on full-text screening, 20 articles were finally included. The PRISMA flow process of study selection is shown in Figure Characteristics and Quality Assessment of the Included StudiesUltimately, 20 RCTs, conducted in a total of 1136 patients, were included in this meta-analysis -28. Of tThe summary of the risk of bias assessment is shown in Figure OutcomesVisual Analogue Score (VAS)2=85%, P < 0.001) . Significant heterogeneity was observed , which was resolved after excluding the study by Ucuncu et al. (2009) , as shown in Figure Nine studies reported on changes in shoulder function scores between baseline and six weeks. Four of them used the Constant-Murley Score, two studies used the Oxford score, and three studies used other scores. Meta-analysis showed that US-guided CS was associated with better shoulder function scores at six weeks than landmark CS  as shown in Figure Shoulder Pain and Disability Index (SPADI)2=77%, P < 0.012). Heterogeneity was resolved after excluding the study by Hsieh et al. (2013) , which is shown in Figure Three studies reported on changes of SPADI at the six weeks follow-up. Meta-analysis did not favor either group , as represented in Figure Shoulder Abduction Degree2=95%, P < 0.001) and is shown in Figure Eleven studies reported on changes in shoulder abduction at six weeks. Meta-analysis showed that US-guided CS was associated with larger shoulder abduction than landmark CS . Significant heterogeneity was observed , and are shown in Figure Nine studies have reported on adverse events, including infection and skin peeling. Meta-analysis showed no significant difference between the compared groups , and significant heterogeneity was observed ; therefore, a random-effects model was utilized. We conducted a leave-one-out meta-analysis to assess the contribution of each study to the overall model. No study affected the overall estimate in the leave-one-out-study analysis, and there was no marked difference in results, suggesting that the results of the current study were not driven by a single study or a supplementary file. The Forest plot of the leave-one-out meta-analysis of the visual analog score is shown in Figure Significant heterogeneity was observed in most outcomes , and we conducted a leave-one-out meta-analysis to assess the contribution of each study to the overall model. No study affected the overall estimate in the leave-one-out-study analysis, and there was no marked difference in results, suggesting that a single study did not drive the results of the current study. 2) There was marked variation in the functional scales used between studies ; therefore, we used SMD for all functional scores. 3) Due to the inadequate data in the literature, the correlation between injection accuracy and clinical improvement was not studied.Our study included large randomized controlled trials with moderate to high quality and large sample size, helping to understand better and evaluate the evidence clearly. We strictly adhered to the PRISMA checklist and carefully performed a precise search in the electronic database. Moreover, the mean changes between baseline and six weeks of follow-up were calculated, which offered a more accurate detection of changes at baseline. The limitations in our study included: 1) a substantial heterogeneity was observed in our analysis  on the outcomes and cost-effectiveness of the two approaches are desired.


Understanding the transcriptome has become an essential step towards the full interpretation of the biological function of a cell, a tissue or even an organ. Many tools are available for either processing, analysing transcriptome data, or visualizing analysis results. However, most existing tools are limited to data from a single sequencing platform and only several of them could handle more than one analysis module, which are far from enough to meet the requirements of users, especially those without advanced programming skills. Hence, we still lack an open-source toolkit that enables both bioinformatician and non-bioinformatician users to process and analyze the large transcriptome data from different sequencing platforms and visualize the results.https://github.com/dongxuemin666/RNA-combine.We present a Linux-based toolkit, RNA-combine, to automatically perform the quality assessment, downstream analysis of the transcriptome data generated from different sequencing platforms, including bulk RNA-seq (Illumina platform), single cell RNA-seq (10x Genomics) and Iso-Seq (PacBio) and visualization of the results. Besides, this toolkit is implemented with at least 10 analysis modules more than other toolkits examined in this study. Source codes of RNA-combine are available on GitHub: Our results suggest that RNA-combine is a reliable tool for transcriptome data processing and result interpretation for both bioinformaticians and non-bioinformaticians. In thisHere, we present a Linux-based command-line toolkit, RNA-combine, for the comprehensive analysis of bulk RNA-seq, scRNA-seq as well as Iso-Seq data, performing analyses for multiple modules . This toolkit represents the assembly of a wide range of routine and customized transcriptome analysis workflows and is free from the abovementioned issues and thus is friendly and easily implemented for users.Our RNA-combine consists of 16 modules and could process transcriptome data  from three sequencing platforms . All analysis modules are scripted in the form of bash command lines, which can be easily customized and launched by users.The usage of each module is provided in the user manual and the scheme of our toolkit is shown in Fig. The workflow of bulk RNA-seq data analysis starts with raw sequencing file preprocessing, including removing rRNA sequences using Sortmerna , removinRPKM (Reads Per Kilobase of transcript per Million mapped reads)/FPKM (Fragments Per Kilobase of exon model per Million mapped fragments) normalized data. In the module of splicing site detection, three methods with different strategies are adopted: DEXseq [In the variant calling module, two methods are introduced: the one is conducted by GATK , which h: DEXseq  based on: DEXseq  based on: DEXseq  based on: DEXseq , which m: DEXseq , which c: DEXseq  to the fCellranger  is used Currently, the library construction used for scRNA-seq often causes doublet artifacts , which may generate biased results. To overcome this limitation, we apply Scrublet  in the tWe use one of the most well-established pipeline-PacBio’s IsoSeq V3  to proceFor omics (e.g. transcriptome) analysis, one of the most labor-intensive and time-consuming processes is the formatting of input files for different tools. In our toolkit, we develop a layer of interface that could automatically format inputs for user-specified tools, guaranteeing that these tools could be linked smoothly. Under this environment, bioinformaticians and non-bioinformaticians could quickly link different tools to a reliable processing workflow without extra commands. More importantly, the users just need to input the workflow with raw transcriptome sequencing data and reference genomes. Our toolkit will start from initial preprocessing and load the modules of interest. For instance, in the analysis of bulk RNA-seq data, one can set up a workflow starting from raw sequencing data preprocessing, to the calculation of expression level of each gene or transcript, identification of differentially expressed gene or transcript, detection of alternative splicing event and differential splicing site, construction of co-expression network and sample-specific network, variant calling , and biological pathway annotation.Because each module of transcriptomic analysis involves thousands of genes and multiple dimensions , the data presentation with graphical visualization is in need to facilitate the result interpretation. However, this has been neglected in most of the previous tools. To address this issue, we develop a visualization plugin under the environment of R and Python, which realizes the visualization of the results for each module and can generate qualified graphs for publication.During the processing of large datasets (e.g. transcriptomes of multiple samples), spurious interruption might occur due to unexpected factors . This abolishes the entire workflow and users have to spend a lot efforts to manually check all the processes. To minimize this effect as much as possible, we develop a Backtracking Executor plugin in our toolkit. It automatically records the interrupted processes (i.e. error logs) in a user-specified directory. Based on these log files, it is easy for users to resume data processing from the interrupted points. As a consequence, the plugin enables users to keep tracking the processes and thus greatly reducing the efforts spent on debugging.MUC1, which has been approved by FDA as a diagnostic marker to monitor clinical course of patients with breast tumor during treatment [MUC1 in either tumor or normal tissues were shown in Fig. In this section, we focused on the assessments of reliability and automation of RNA-combine using several published transcriptome data. We first tested the workflow of the bulk RNA-seq analysis with a transcriptome dataset from three normal breast tissues and three breast tumor tissues . Startinreatment , was sigNKG7 for natural killer cells and T cells [PPBP for Megakaryocytes [CD79A for B cells [Next, using the pipeline of scRNA-seq data analysis in RNA-combine we analyzed a scRNA-seq dataset of 3k PBMCs  from a healthy donor generated from 10x Genomics (https://support.10xgenomics.com). The gene-barcode matrix was used for doublet detection, cell clustering, cell type annotation and cell connectivity analysis. The number of 35 candidates were detected as potential doublets among 2700 cells Fig. a and thu T cells , PPBP foryocytes , CD79A f B cells    to test Overall, these results suggested that our toolkit worked smoothly and automatically for real transcriptome data from different sequencing platforms and it could process the data with raw sequencing fastq files and reference genomes as inputs.We compared the features of RNA-combine with four toolkits  publishRegarding the analysis module, our toolkit covers all the analysis modules implemented in RNASeqR, RASflow, scGEAToolbox, and most modules in NASQAR , and it also includes nine extra modules  that are absent in the abovementioned software. One major difference between RNA-combine and other toolkits is that it implements the modules of raw data preprocessing, which enables users to use raw fastq files as input directly. Another difference is the development of the input formatting interface, which automatically formats inputs for different analysis modules, therefore enabling end-to-end analysis from raw sequencing files to direct graphic visualization of results. This is important because input formatting is both time- and labor-consuming, especially for users without advanced programming skills. RNA-combine is a Linux-based toolkit, enabling users to parallel jobs, thus speeding up the analysis processes. Collectively, RNA-combine is more comprehensive on data analysis and more user-friendly.We conclude that RNA-combine presented in this study is a user-friendly, reliable toolkit for the comprehensive analysis of transcriptome data generated from different sequencing platforms. It enables users to set up a customized workflow to analyze data from multiple platforms and generate analysis reports and result visualization. Importantly, this toolkit empowers researchers without advanced bioinformatics skills to analyze their data by working with human-readable configuration files. We will continue to provide user supports and feature enhancements in future releases.Project name: RNA-combinehttps://github.com/dongxuemin666/RNA-combineProject home page: The software and usage guideline are available online at Operating system(s): LinuxProgramming language: Python, R, ShellOther requirements: R 3.6, Python 3.7License: MIT, licenses for dependent packages, tools and methods are shown in Additional file Any restrictions to use by non-academics: license neededAdditional file 1. Estimated running time for each module, organization of all modules and functions, licenses for dependent packages of RNA-combine.


Porphyromonas gingivalis is a Gram-negative pathogenic bacterium associated with chronic periodontitis. The development of a chimeric peptide-based vaccine targeting this pathogen could be highly beneficial in preventing oral bone loss as well as other severe gum diseases. We applied a computational framework to design a multi-epitope-based vaccine candidate against P. gingivalis. The vaccine comprises epitopes from subunit proteins prioritized from the P. gingivalis reference strain  using several reported vaccine properties. Protein-based subunit vaccines were prioritized through genomics techniques. Epitope prediction was performed using immunoinformatic servers and tools. Molecular modeling approaches were used to build a putative three-dimensional structure of the vaccine to understand its interactions with host immune cells through biophysical techniques such as molecular docking simulation studies and binding free energy methods. Genome subtraction identified 18 vaccine targets: six outer-membrane, nine cytoplasmic membrane-, one periplasmic, and two extracellular proteins. These proteins passed different vaccine checks required for the successful development of a vaccine candidate. The shortlisted proteins were subjected to immunoinformatic analysis to map B-cell derived T-cell epitopes, and antigenic, water-soluble, non-toxic, and good binders of DRB1*0101 were selected. The epitopes were then modeled into a multi-epitope peptide vaccine construct (linked epitopes plus adjuvant) to enhance immunogenicity and effectively engage both innate and adaptive immunity. Further, the molecular docking approach was used to determine the binding conformation of the vaccine to TLR2 innate immune receptor. Molecular dynamics simulations and binding free energy calculations of the vaccine–TLR2 complex were performed to highlight key intermolecular binding energies. Findings of this study will be useful for vaccine developers to design an effective vaccine for chronic periodontitis pathogens, specifically P. gingivalis. Porphyromonas gingivalis is a rod-shaped, Gram-negative oral bacterium asserted as a pivotal pathogen in the growth of chronic periodontitis  was obtained from the National Center for Biotechnology Information database  requires additional stimulation from helper T lymphocytes (HTL) to avoid autoimmune responses. HTL recognizes epitopes loaded onto class II MHC proteins in B-cell membranes and other antigen-presenting cells. The HTL epitopes were predicted by using an online tool served by the Immune Epitope Database (IEDB) . This toThe IFNepitope webserver was used to predict the MHC-II (HTL) epitopes that can induce interferon-gamma with an 82% accuracy . The serhttps://pepcalc.com/peptide-solubility-calculator.php) were used to predict the toxicity, antigenicity, MHC binding affinity, and water solubility of each epitope, respectively. Epitopes predicted as non-toxic, antigenic, and water-soluble positive binders were selected for vaccine design.Predicted CTL and HTL epitopes were further shortlisted by applying multiple filters including toxicity, antigenicity, MHC binding affinity, and solubility. Online web servers VaxiJen , ToxinPrhttp://tools.iedb.org/population/) was used to estimate the world human population coverage by the predicted CTL and HTL epitopes (Human leukocyte antigen (HLA) pattern varies among ethnic groups and geographical areas. Thus, the estimation of population coverage by the predicted CTL and HTL epitopes is important to design an effective vaccine. The population coverage tool of IEDB . Further, the vaccine construct sequence was subjected to the PDBSUM server  were introduced to neutralize the simulated system. Subsequently, a truncated octahedral box of the TIP3P water model with buffer was submerged with the neutralized system  and MMGBSA , embedded in the MMPBSA.py module of Amber . The netThe terms in equation (1) include several energy calculations including van der Waals energy, internal energy from molecular mechanics, electrostatic energy, and polar and non-polar contribution towards solvation energy.P. gingivalis infection  were discarded subsequently. Selecting human homologs could initiate the autoimmune response, negatively impacting the host’s healthy cells and tissues  of the pooled virulent proteins were further evaluated to guide the selection of suitable vaccine candidates for experimental evaluation that can be readily used in vaccine development , 42. Vax tissues . Nine cyMHC-1 molecules are expressed on the cell surface of all nucleated cells. They present peptide fragments derived from intracellular proteins and play an important role in alerting the immune system against virally infected cells . NetCTL https://pepcalc.com/peptide-solubility-calculator.php), respectively. Subsequently, half-maximal inhibitory concentration (IC50) values of MHC-I epitopes binding to HLA DRB1*0101 were predicted using the MHCPred server  was linked to the N-terminal of the vaccine construct using the EAAAK linker. The final vaccine construct composed of 419 residues containing both T-cell and B-cell epitopes were designed  of the vaccine construct in yeast and Escherichia coli was >20 and >10 h, respectively. The aliphatic index indicates the thermostability of the vaccine and was calculated as 77.49, whereas the GRAVY was calculated as -0.488.The ProtParam tool  was emplThe secondary structure was generated by using the PSIPRED workbench . The vacab initio modeling to model the target sequence and generated five structures. Subsequently, model-1 was selected for additional analysis after a brief structural evaluation. Several computational tools were employed to validate the 3D structure of the vaccine construct. The ERRAT server . The evaluation of the refined vaccine structure on the Ramachandran plot showed that 88.4% of the residues were in most favored regions, 10.1% in additional allowed regions, 0.9% in generously allowed regions, and -0.6% in disallowed regions , thus allowing adaptive immunity and prompt response against the pathogen. The molecular dynamics simulations illustrated the highly stable molecular interactions and predicted the binding mode of the construct. Further, binding free energy calculations support the docking and simulation findings as a highly stable nature of the complex. The designed vaccine construct was immunogenic in our in silico evaluation; nevertheless, the extent to which it could prevent P. gingivalis infection is unknown. Immunoinformatics approaches have been successfully applied to a number of pathogens to screen for protective antigens, such as the Meningococcus B (MenB) vaccine developed recently. Similarly, Chlamydia, Staphylococcus aureus, and group A Streptococcus are successfully addressed using such in silico methods. The vaccine construct developed in this study is ready to be evaluated in experimental studies to disclose its immunogenicity against the P. gingivalis pathogen.We used immunoinformatic techniques in combination with subtractive proteomics to design a potent and safe multi-epitope vaccine that can be used against The original contributions presented in the study are included in the article/BS: project design, investigation, data curation, original draft preparation, figure preparation, and referencing. SA: Figure preparation, reference management, reviewing, and editing. JS: Figure preparation, reference management, reviewing, and editing. HWK: Supervision, conceptualization, methodology, and writing—reviewing and editing. DN: Supervision, conceptualization, methodology, patient’s sampling acquisition, writing—reviewing and editing, and project management. All authors contributed to the article and approved the submitted version.This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (grant number: HI21C1659). This research was also supported by the Chung-Ang University Research Grants, 2020.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Objective: The Inventory to Measure and Assess imaGe disturbance – Head and Neck (IMAGE-HN) is a validated patient-reported outcome measure of head and neck cancer-related body image-related distress (BID). However, the IMAGE-HN score corresponding to clinically relevant BID is unknown. The study objective is to determine the IMAGE-HN cutoff score that identifies head and neck cancer patients with clinically relevant BID.Methods: We conducted a cross-sectional study at six academic medical centers. Individuals ≥18 years old with a history of head and neck cancer treated with definitive intent were included. The primary outcome measure was the IMAGE-HN. A Receiver Operating Characteristic curve analysis was performed to identify the IMAGE-HN score that maximized sensitivity and specificity relative to a Body Image Scale score of ≥10 . To confirm the validity of the IMAGE-HN cutoff score, we compared the severity of depressive [Patient Health Questionnaire-9 (PHQ-9)] and anxiety symptoms [Generalized Anxiety Disorder-7 (GAD-7)], and quality of life [University of Washington-QOL (UW-QOL)] in patients with IMAGE-HN scores above and below the cutoff.Results: Of the 250 patients, 70.4% were male and the mean age was 62.3 years. An IMAGE-HN score of ≥22 was the optimal cutoff score relative to a Body Image Scale score of ≥10 and represents a clinically relevant level of head and neck cancer-related BID. Relative to those with an IMAGE-HN score of <22, patients with IMAGE-HN scores of ≥22 had a clinically meaningful increase in symptoms of depression (mean PHQ-9 score difference = 5.8) and anxiety (mean GAD-7 score difference = 4.1) as well as worse physical (mean UW-QOL score difference = 18.9) and social-emotional QOL (mean UW-QOL score difference = 21.5). Using an IMAGE-HN cutoff score ≥22, 28% of patients had clinically relevant BID.Conclusion: An IMAGE-HN score of ≥22 identifies patients with clinically relevant head and neck cancer-related BID. This score may be used to detect patients who could benefit from strategies to manage their distress, select patients for studies evaluating interventions to manage head and neck cancer-related BID, and improve our understanding of the underlying epidemiology of the disorder. There are nearly 500,000 head and neck cancer (HNC) survivors in the United States (US) and this population is growing exponentially . BecauseDue to its subjective nature and poor correlation with objective measures of disfigurement , BID is A cross-sectional study was conducted at six academic medical centers in the US . This study was approved by the institutional review board at each institution. Individuals ≥18 years old with a history of HNC  who had undergone definitive treatment and were free of known active disease were eligible for the study. Patients were excluded if they were unable to read English. Patients were recruited during routine follow-up or survivorship visits at multidisciplinary head and neck oncology clinics from November 2020 to August 2021 and enrolled face-to-face by a study team member following provision of written informed consent. Following enrollment, patients completed study assessments using an electronic tablet. Of 284 patients approached for participation, 23 declined and 11 did not provide demographic or oncologic data, leaving a sample of 250. Patients were compensated $10 for participation. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline .The primary outcome measure was the IMAGE-HN global score. The IMAGE-HN is a 24-item PROM that assesses multiple domains of HNC-related BID including other-oriented appearance concerns, personal dissatisfaction with appearance, distress with functional impairments, and social avoidance and isolation. Global IMAGE-HN scores range from 0 to 84, with higher scores indicating more severe HNC-related BID . The IMAThe Body Image Scale (BIS) is a 10-item PROM that assesses the affective, cognitive, and emotional aspects of body image due to cancer or its treatment over the prior 7 days . InitialDepression was measured using the Patient Health Questionnaire-9 (PHQ-9), a reliable and validated 9-item measure of depressive symptoms . The PHQThe Generalized Anxiety Disorder-7 (GAD-7) is a validated 7-item measure of anxiety symptoms. The GAD-7 was chosen because it is the recommended tool to screen for anxiety symptoms in patients with cancer by the ACS and ASCO . Scores The fourth version of the University of Washington-QOL (UW-QOL) is an HNC-specific questionnaire with 12 domains  that assesses QOL within the past 7 days . This toSelf-reported sociodemographic characteristics include age, gender, race, ethnicity, marital status, living situation, education, employment, rurality, and insurance coverage. Self-reported oncologic characteristics include tumor subsite, cancer treatment, and type of reconstructive surgery. Time since completion of treatment was collected in months.t-tests. We used Fisher’s Exact tests to compare these subgroups on the proportions of patients with moderate depressive symptoms (defined as PHQ-9 score of ≥10) and anxiety symptoms (defined as GAD-7 score of ≥10)  were used to characterize the sample. To determine the IMAGE-HN cutoff score that represents clinically meaningful HNC-related BID, we performed a Receiver Operating Characteristic (ROC) curve analysis to identify the IMAGE-HN score that maximized sensitivity and specificity relative to a BIS score of ≥10  . We did  of ≥10) . StatistA total of 250 patients were included in the study. An IMAGE-HN score of ≥22 was the optimal dichotomization value relative to a BIS score of ≥10 and represents a clinically relevant level of HNC-related BID . RelativSD = 6.2) vs. 2.5 (SD = 3.4); mean difference = 5.8] and more severe anxiety symptoms . These differences between those with and without HNC-related BID are both clinically and statistically significant. Patients were also more likely to experience worse physical QOL  and worse social-emotional QOL . These differences were also clinically and statistically significant between those with and without HNC-related BID. When analyzed using established cutoff scores for moderate depressive symptoms (PHQ ≥ 10) and moderate anxiety symptoms (GAD ≥ 10), patients with an IMAGE-HN score of ≥22 were more likely to have moderate or severe depressive symptoms (30.0% vs. 5.0%) and moderate or severe anxiety symptoms  relative to patients with an IMAGE-HN score of <22.Because of the strong association of HNC-related BID with psychological well-being and QOL, we evaluated the association of clinically relevant IMAGE-HN scores with symptoms of depression and anxiety and QOL . RelativAlthough BID has profound consequences in terms of psychosocial well-being and QOL for patients with HNC, HNC-related BID remains poorly understood in large part due to limitations in our ability to measure HNC-related BID and identify patients with this disorder . The BISThere are two important caveats to interpreting the optimal IMAGE-HN cutoff score. First, there is no gold standard for the diagnosis of HNC-related BID  against which to compare the diagnostic accuracy of IMAGE-HN. As a result, the process for determining score thresholds for HNC-related BID is not straightforward. However, the approach to IMAGE-HN development  ensured Findings from the current study can be applied to better characterize the epidemiology of HNC-related BID. A recent study by A second implication of our study is that the IMAGE-HN cutoff score can now be used in clinical practice and research studies to identify patients with clinically relevant HNC-related BID who might benefit from interventions to manage their distress. A recent national survey showed that body and self-image-related distress was the least likely of all survivorship topics to be addressed by head and neck oncology providers . Prior tAs part of a comprehensive and patient-oriented approach to managing HNC-related BID, the IMAGE-HN can be a powerful tool to help clinicians and patients identify unmet needs. However, there are several areas that still need to be addressed to enhance the clinical relevance of IMAGE-HN. First, the minimal important difference in IMAGE-HN scores over time and between groups are unknown; these values are necessary to evaluate the effectiveness of treatment . Second,Moreover, factors affecting the clinical implementation of IMAGE-HN are not known. HNC-related BID may be difficult to detect in the clinical setting as symptoms overlap with the adverse effects of cancer-related treatment. In addition, head and neck oncology providers are not readily trained to identify psychosocial concerns, and patients with HNC may be hesitant to express body image-related concerns . LesseniThis study has several strengths. It was conducted with a large sample size from 6 academic medical centers and captured a sample of patients diverse by certain demographic and oncologic characteristics, which enhances the generalizability of study findings. We also used validated PROMs of BID, depression, anxiety, and health related QOL. Finally, we used rigorous statistical methods and incorporated findings from recent advancements in the field of measuring BID among cancer patients to ensure that our cutoff score optimally identifies HNC patients with clinically relevant BID. Despite its strengths, several important limitations should be discussed. Most patients included in this study were white and non-Hispanic, limiting the external validity of the newly defined cutoff score for other races and ethnicities. We only included patients who had completed HNC treatment and were free of active disease. We are thus unable to account for the effect of body image concerns prior to cancer diagnosis and further study of the normative values of IMAGE-HN scores across the trajectory of HNC from diagnosis through treatment should be prioritized. This study relied on self-reported patient characteristics susceptible to recall or response bias. We did not confirm the optimal IMAGE-HN cutoff score in a separate validation cohort. However, this is not expected to be a concern because the study was not attempting to fit a model to our specific sample. Lastly, although no gold standard  for HNC-related BID exists, the rigorous study methodology we employed ensures the diagnostic accuracy of the IMAGE-HN.In this multi-institutional study, an IMAGE-HN score of ≥22 identified patients with clinically relevant HNC-related BID. Furthermore, we found HNC patients with clinically relevant BID suffered clinically meaningful increases in symptoms of depression and anxiety and worse QOL when compared to HNC patients without clinically relevant BID. This score may be used in clinical practice to identify patients with HNC-related BID who may benefit from interventions to manage their distress. Researchers may use the IMAGE-HN cutoff score to improve our understanding of the underlying epidemiology of the disorder and better stratify patients for accrual into clinical trials evaluating novel strategies to manage HNC-related BID.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Medical University of South Carolina Institutional Review Board, Washington University School of Medicine Institutional Review Board, University of Pittsburgh School of Medicine Institutional Review Board, Vanderbilt-Ingram Cancer Center Institutional Review Board, Henry Ford Health System Institutional Review Board, and Medical College of Wisconsin Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.DM, BH, and EG: full access to the data in the study and take responsibility for the integrity of the data and accuracy of the data analysis. DM and EG: concept and design and obtained funding. DM, BH, PP, AW, SC, JZ, MN, BR, AH, NO-P, SM, WB, HL, KR, KS, and EG: acquisition, analysis, or interpretation of data and critical revision of the manuscript for important intellectual content. DM and BH: drafting of the manuscript. BH and HL: statistical analysis. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: The disease burden of active tuberculosis (TB) is considerable, but systematic reviews of economic evaluations of active TB treatments are scarce.Methods: PubMed, EMBASE, and the Cochrane Library databases were used to search for articles on cost-effectiveness analysis or cost-utility analysis that economically evaluated active TB treatments, which were then systematically reviewed by two independent reviewers. We extracted vital components of the included studies, such as country, population, intervention/comparator, primary outcome, values of outcomes, thresholds, model type, time horizon, and health states included in the model.Results: Seventeen studies were included in this systematic review. Thirteen dealt with interventions of medications, and the remaining four compared care strategies. The Markov model was the most commonly used tool to compare medications, whereas studies on care plans mainly used decision trees. The most commonly used primary outcome was disability-adjusted life years, followed by quality-adjusted life years. For treatment-naïve TB, the 4-month regimen was more cost-effective than the 6-month regimen mainly in low- and middle-income countries. For multidrug-resistant TB, a bedaquiline-based regimen was cost-effective. For multidrug-resistant TB, decentralized care that employed the use of home or mobile devices was more cost-effective than hospital-based centralized care in low- and middle-income countries.Conclusion: New treatment strategies to improve therapeutic outcomes by enhancing treatment adherence, such as regimens with shorter durations (2 or 4 months) and decentralized care, or new anti-TB agents  have been suggested as cost-effective interventions for active TB. This review provides information on the economic evaluation of active TB from good-quality studies, thus aiding the future economic evaluation of active TB. Mycobacterium tuberculosis, the causative bacteria of TB, is the leading cause of death among infectious agents, with an estimated 10 million diagnoses of TB annually  is an infectious disease that has long been among the top 10 major causes of death worldwide. annually . Once Myatent TB .There have been many challenges in treating active TB, including low cure rates with the standard regimen due to its long duration, severe toxicity, and poor medication adherence . TreatmePrevious studies have focused on economic evaluations for latent TB  or activThis systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines .We included studies that conducted an economic evaluation of anti-TB medications or care strategies for active TB. To include active TB patients, studies that included at least one arm of patients treated with anti-TB medication were included. Studies in which subjects were only animals or patients with non-active TB  were excluded. If an article included active and latent TB patients simultaneously with separately presented results of active and latent TB, the article was selected. Studies evaluating the screening and diagnosis of and vaccination for TB were excluded. Articles published before 2010 or abstracts without full text were excluded.We searched for studies published between January 1, 2010, and January 29, 2020, that economically evaluated active TB treatment, using the PubMed, EMBASE, and Cochrane Library databases. Considering each database system, we combined terms related to the participants of interests and study types using Medical Subject Headings and title and abstract (tiab) as search fields. The search terms were as follows: the Medical Subject Headings term of “tuberculosis,” “Cost-Benefit Analysis,” and the text string of “cost,” “effective*,” “utility,” and “model.” The complete search strategy used for each database is included in Using an Excel sheet, two reviewers  independently extracted information from selected articles and discussed discrepancies during cross-checking. Data on the following characteristics of the included studies were extracted: target population, type of intervention, country, primary outcome, model type, time horizon, and health states included in the model. In addition, we extracted data on the key components of each economic evaluation using a predefined extraction format. The extracted components were intervention/comparator, outcome type, outcome values, cost-effectiveness thresholds, cost-effectiveness status of the outcomes, and funding information. We organized the status of cost-effectiveness of each outcome using stated thresholds or the author’s statements on cost-effectiveness. Two other reviewers (SH and HL) screened all the extracted data to confirm it was complete and accurate. Each cost-related outcome, based on various currencies depending on the country of the study, was converted into US dollars using the exchange rate of July 2020.To assess the methodological quality of all the selected studies, we used the Quality of Health Economic Studies (QHES) instrument, which has been validated for appraising the methodological quality of economic evaluations . The QHEA total of 971 citations were identified through a database search. After excluding 309 duplicates, we screened 662 articles by title and abstract, leaving 38 articles for full-text screening. Through full-text screening, 17 articles were eligible for inclusion. A flow chart of the study selection process is presented in Five studies conducted cost-effectiveness analyses using various scenarios or settings, including different treatment costs, and durations , populatIn terms of intervention types, most of the selected articles (13 out of 17) examined interventions of medications, comparing the standard 6-month regimen with longer (8-month)  or shortThe other four articles examined “care” types, which were generally related to new methods of improving patient medication adherence, including comparing self-administered treatment or directly observed treatment (DOT) with other types of care in treatment naïve TB patients  or compaThe most frequently used primary outcome was disability-adjusted life years (DALYs), used in 10 studies . This waThe time horizon varied across studies, from 2 years  to a lifAmong the health states included in the models for each TB population, studies generally included health states related to cure/fail, lost to follow-up (defaulted), treatment completion, and retreatment for MDR-TB and treatment naïve TB. However, health states related to sputum conversion, end-of-life/palliative care, comorbidity of human immunodeficiency virus (HIV), and surgery were found in models for MDR-TB but rarely found in models for treatment-naïve TB patients.Six out of 7 studies which were conducted in sub-Saharan Africa were reflecting HIV status in their economic evaluation models. The 6 economic evaluation models used treatment outcomes according to HIV status and included cost for HIV treatment. To establish an economic evaluation model that is generally simulated by a hypothetical cohort, most of the included studies earned treatment outcome for each intervention and comparator mainly from published data of clinical trials, but The cost-effectiveness of regimens for MDR-TB patients is presented in Results of the cost-effectiveness analysis are presented in The results of the quality assessment are presented in Some studies did not fulfill all of the criteria of the QHES instrument. We found that there have been several economic evaluations that suggest a shortened duration of the anti-TB regimen from 6-month to 4 months or 2-month, and novel regimens with new combinations of existing drugs  or new drugs . In terms of care, decentralized care (home-based or mobile device-based) and DOT have been suggested against existing hospital-based centralized care and self-administered treatment mainly in LMICs. The studies we examined generally concluded that novel regimens with new medications or combinations, shorter regimens, and more decentralized care appeared more cost-effective than traditional anti-TB interventions.Given that the standard 6-month regimen for TB treatment has faced challenges regarding patient adherence, shortened regimens  have been suggested. Shortened regimens have the advantage of reducing the burden on patients and health systems. Moreover, patients have additional benefits, such as shortened length of interrupted daily life, a shorter period of side effects, and better adherence outcomes . AlthougThere have been concerns regarding low TB treatment adherence and outcomes in LMICs, arguing inaccessibility to treatment center, rural residence, lack of family support, and level of education to be risk factors . TherefoOf the LMICs, TB patients in sub-Saharan Africa are particularly suffering from concomitant HIV, with more than 50% of TB patients co-infected with TB and HIV in the region . Co-infeThough HICs bear only 5% of the global TB burden, HICs have long been interested in MDR-TB treatments . Most stA new regimen with diarylquinoline  leads to faster culture conversion . LikewisThroughout this review, DALYs, which present the impact of the intervention on patients’ lives, were most frequently used as a primary outcome (10 out of 17), followed by QALYs. Tuberculosis is one of the leading causes of global DALYs, rating 12th among 369 diseases and injuries in 2019 . Given tMost published economic evaluations tend to have favorable results for interventions, increasing the risk of bias. A previous systematic review of published cost-effectiveness analysis  revealedOur study is the first to conduct a systematic review of economic evaluation of treatments for active TB. Unlike some previous systematic reviews that did not assess the quality of articles , we carrOur study might have potential limitations. First, to cope with low treatment adherence in TB treatment, treatment strategies such as fixed-dose combinations of two or more anti-TB medications have been developed to simplify complexity in taking medication. Previous studies compared treatment outcomes, efficacy, or safety of fixed-dose combinations and single-drug formulations , but ecoEconomic evaluation studies of past 10 years have suggested new strategies to improve therapeutic outcomes by enhancing treatment adherence in active TB treatment. New regimens with shorter durations (2 or 4 months) and decentralized care have been suggested as cost-effective mainly in LMICs. Novel regimens with new anti-TB agents  have been suggested as cost-effective. This review provides information on the economic evaluation of treatments for active TB, which can help future research on the topic set up economic evaluation model.


Objective: The prevalence of Alzheimer’s disease and related dementias (ADRD) in women is higher than men. However, the knowledge of gender disparity in ADRD treatment is limited. Therefore, this study aimed to determine the gender disparities in the receipt of anti-dementia medications among Medicare beneficiaries with ADRD in the U.S.Methods: We used data from the Medicare Current Beneficiary Survey 2016. Anti-dementia medications included cholinesterase inhibitors  and N-methyl-D-aspartate (NMDA) receptor antagonists (including memantine). Descriptive analysis and multivariate logistic regression models were implemented to determine the possible gender disparities in the receipt of anti-dementia medications. Subgroup analyses were conducted to identify gender disparities among beneficiaries with Alzheimer’s disease (AD) and those with only AD-related dementias.Results: Descriptive analyses showed there were statistically significant differences in age, marital status, and Charlson comorbidities index (CCI) between Medicare beneficiaries who received and who did not receive anti-dementia medications. After controlling for covariates, we found that female Medicare beneficiaries with ADRD were 1.7 times more likely to receive anti-dementia medications compared to their male counterparts . Specifically, among Medicare beneficiaries with AD, females were 1.2 times more likely to receive anti-dementia medications , and among the Medicare beneficiaries with only AD-related dementias, females were 1.9 times more likely to receive anti-dementia medications .Conclusion: Healthcare providers should be aware of gender disparities in receiving anti-dementia medications among patients with ADRD, and the need to plan programs of care to support both women and men. Future approaches to finding barriers of prescribing, receiving and, adhering to anti-dementia medications by gender should include differences in longevity, biology, cognition, social roles, and environment. ADRD artes (US) . The tottes (US) . Since ttes (US) .Anti-dementia medications are a class of drugs used to slow the progression of ADRD . To dateGender disparities have always been an unresolved issue in patients with ADRD. Evidence has documented differences between men and women in terms of brain structure and function over the lifespan , and proThis study used a nationally representative database to determine the gender disparities in the receipt of anti-dementia medications among Medicare beneficiaries with ADRD. Given that evidence has shown that females are more likely to use preventive care services compared to males , we hypoWe conducted a retrospective cross-sectional study to determine gender disparities in the receipt of anti-dementia medications among Medicare beneficiaries. Data were derived from the Medicare Current Beneficiary Survey (MCBS) in 2016. MCBS is a nationally comprehensive and authoritative survey of Medicare beneficiaries, which is sponsored by the Centers for Medicare and Medicare Services (CMS) . The corPrevalent patients with ADRD aged 65 years or older were identified if any of their claims between January 1, 2016, through December 31, 2016 included the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for AD and AD-related dementias. Specifically, the ICD-10 CM codes for AD was G30. AD-related dementias included Lewy-body associated dementia (G31.83), mild cognitive impairment (G31.84), frontotemporal dementia (G31.0), vascular dementia (F01), and non-specific dementias . These codes were derived from the chronic conditions data warehouse algorithms .We excluded participants who were eligible for the Medicare program due to end-stage renal disease (ESRD) or disability, and those who joined the Health Maintenance Organization (HMO) during the study period.Anti-dementia medications were identified based on the U.S. FDA’s prescription database . The FDACovariates were based on previous research on similar topics using MCBS . We extrp < 0.05.Descriptive analysis was used to compare the difference in the characteristics between users and non-users of anti-dementia medications among Medicare beneficiaries with ADRD. Chi-square tests were used to compare the difference in the categorical variables. Multivariate logistic regression models were used to estimate the association between gender and the receipt of anti-dementia medications after controlling for covariates. We also conducted two subgroup analyses, one for beneficiaries with AD and the other for those with only AD-related dementias. SAS software  was used to perform the statistical analyses, and the level of statistical significance was set at p = 0.006), not married (p = 0.032), and have fewer comorbidities (p = 0.007).1,240 Medicare beneficiaries with ADRD were identified out of 14,778 beneficiaries in MCBS 2016 based on the inclusion and exclusion criteria . Among tAfter controlling for covariates, female Medicare beneficiaries with ADRD were 1.7 times more likely to receive anti-dementia medications compared to males , difficulty in activities of daily living (ADL), and instrumental activities of daily living (IADL). Second, this study was unable to measure the disease severity of cognitive impairment due to a lack of related information, which may influence anti-dementia drug use. Third, the results of this study only reflected the prescribing patterns of anti-dementia medication in older patients covered by Medicare in the US. The conclusion might not be generalized to other US populations covered by other public or private insurance plans and populations in other countries. Finally, due to the cross-sectional design, we could not draw a causal conclusion on the receipt of anti-dementia medication between male and female Medicare beneficiaries with ADRD.In conclusion, our study found that gender disparities exist in the receipt of anti-dementia medications among Medicare beneficiaries with ADRD. Gender is rooted in biology, but it is primarily shaped by environment and experience. Healthcare providers should understand the gender disparities in receipt of anti-dementia drugs and provide interventions to improve prescribing patterns and patient adherence, not only on biological gender, but also on education, nursing, and psychological health factors.


Social distancing measures put in place during the COVID-19 pandemic limited in-person interactions and may have increased the risk for social isolation and loneliness in older adults. Purpose: The purpose of this study was to understand the communication channels used by older adults (age 50+) during the COVID-19 pandemic to mitigate social isolation and loneliness. Methods: Older adults (n=22) who were selected from a longitudinal study, ‘Aging in the time of COVID,’ and who had self-reported they successfully avoided loneliness, participated in a semi-structured online interview. Participants were asked to describe the communication techniques and efforts they used to stay connected to family and friends during the pandemic. All interviews were recorded and transcribed verbatim. A thematic analysis approach was used to identify common approaches. Results: Participants were primarily female and white (100%) with a mean age of 64.7 years. Preliminary findings (n=5) suggest older adults relied heavily on technology to facilitate communication with family and friends including texting, phone calls, email, video calls or conferences , WhatsApp and social media, primarily Facebook. In-person communication strategies, including one-on-one and small group gatherings following social distancing guidelines, were preferred, but used less often than technology-based approaches. Living close to friends and family, and previous experience with technology were facilitators. Competing work and family demands, distance, and technology challenges limited communication. Conclusions: While older adults may adopt technology at a lower pace, they relied on digital communication technology to maintain social connections during COVID.