Positive surgical margins (PSMs) are an independent risk factor of biochemical recurrence in patients with prostate cancer (PCa) after laparoscopic radical prostatectomy; however, limited MRI-based predictive tools are available. This study aimed to develop a novel nomogram combining clinical and multiparametric MRI (mpMRI) parameters to reduce PSMs by improving surgical planning.One hundred and three patients with PCa  were included in this retrospective study. The following parameters were obtained using GE Functool post-processing software: diffusion-weighted imaging (DWI); intravoxel incoherent motion model (IVIM); and diffusion kurtosis imaging (DKI). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to analyze the data set to select the optimal MRI predictors. Preoperatively clinical parameters used to build a clinical nomogram (C-nomogram). Multivariable logistic regression analysis was used to build an MRI nomogram (M-nomogram) by introducing the MRI parameters. Based on the MRI and clinical parameters, build an MRI combined with clinical parameters nomogram (MC-nomogram). Comparisons with the M-nomogram and MC-nomogram were based on discrimination, calibration, and decision curve analysis (DCA). A 3-fold cross-validation method was used to assess the stability of the nomogram.There was no statistical difference in AUC between the C-nomogram , the M-nomogram  and the MC-nomogram . The calibration curves of the three nomograms used to predict the risk of PSMs in patients with PCa showed good agreement. The net benefit of the MC-nomogram was higher than the others .The mpMRI-based nomogram can predict PSMs in PCa patients. Although its AUC (0.735) is not statistically different from that of the clinical-based nomogram AUC (0.683). However, mpMRI-based nomogram has higher specificity (88% VS. 63%), model stability, and clinical benefit than clinical-based nomogram. And the predictive ability of mpMRI plus clinical parameters for PSMs is further improved. Laparoscopic radical prostatectomy (LRP) has been widely used in clinical practice and is currently the main way to treat localized prostate cancer (PCa) . Of noteIn previous studies it was reported that there are some preoperative parameters correlate with PSMs after prostatectomy, including age, clinical stage, free prostate specific antigen (FPSA)/total PSA (TPSA), Gleason score, percent of positive cores (PPC), and extra-prostatic extension , 8. To pAn mpMRI is considered a common examination for the diagnosis of PCa; specifically, reduces false-negative biopsies  and idenThis single-center, retrospective study included 1055 consecutive male inpatients who underwent pelvic mpMRI between January 2016 and November 2021.Participants who met the following inclusion criteria were included in our study: ① confirmed diagnosis of PCa by systemic biopsies; ② patients with complete clinical data, including age, Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score, TPSA, biopsy-based Gleason score, PPC, clinical TNM (cTNM), postoperative Gleason score, pathologic TNM (pTNM), and PSMs locations; and ③ LRP performed on PCa patients by urologists who have performed 500 radical prostatectomies within 3 months after MRI and systemic biopsies. Urologists recommend systematic biopsy of patients before surgery based on PI-RADS and PSA levels. And referring to the mpMRI report to formulate a surgical plan.Of the participants, those who met at least one of the following criteria were excluded: ① history of PCa treatment; ② incomplete MRI sequences; ③ prostate lesions with poorly-defined boundaries on T2WI and apparent diffusion coefficient (ADC) images, according to PI-RADS v2 .PSMs were defined by cancer cells involving the inked surface of the specimen  and diviThe study was approved by the Institutional Review Board of First Affiliated Hospital of Dalian Medical University, informed consent was waived.b values (up to a maximum of 1000 s/mm2). IVIM with b values of 0, 20, 50, 100, 150, 200, 400, 800, 1200, 2000, and 3000 s/mm2 was performed with a single-shot echo planar (SS-EPI) sequence. DKI with b values of 0 and 1500 s/mm2 were performed in the oblique axial plane using a SS-EPI sequence with comparable parameters. The diffusion gradients were applied simultaneously along with 15 orthogonal directions. The MRI scanning parameters  are shown in A 3.0 T MRI scanner  with an eight-channel phased-array body-coil was used in this study. MRI scan was done before the biopsy. The MRI scanning protocol included T1-weighted imaging (T1WI), T2WI, DWI, intravoxel incoherent motion model (IVIM), and diffusion kurtosis imaging (DKI). Sagittal and axial high-definition T2WI sequences were used for prostate tumor location. DWI was performed with high For analysis of images obtained with DWI, parameter maps were generated by fitting the following models to the pixel signal intensities at the different b values, as follows.For the mono-exponential DWI model ,bS is the mean signal intensity with diffusion gradient b, 0S is the mean signal intensity without a diffusion gradient, the b value of ADCME is 0 and 1,000 s/mm2, and the b value of ADCBE is .where For the bi-exponential DWI model ,bSrepresents the mean signal intensity with diffusion gradient b and 0S is the mean signal intensity. When b = 0 s/mm2, D  is the true molecular diffusion coefficient. D*  is the pseudodiffusion coefficient and f  is the perfusion fraction.where For the stretched exponential DWI model ,where α represents an anomalous exponential term of the intra-voxel water molecule ranging and DDC represents a mean intra-voxel diffusion coefficient.For the DKI model ,bS is the MR signal intensity at the particular b value used, 0S is the MR signal intensity without a diffusion gradient, K  is the apparent diffusion kurtosis, and D  is the ADC revised for non-Gaussian behavior.where MRI measurements were performed by two experienced radiologists  using the double-blinding method. Prostate MRI interpretation was based on the PI-RADS v2 . The reghttps://www.R-project.org).All statistical analyses were performed using SPSS , MedCalc , and R software . Nominal variables are expressed as frequencies with percentages.The normality of the data was tested using the Shapiro-Wilk test. Normally distributed continuous variables are expressed as the means ± standard deviations. Non-normally distributed continuous variables are expressed as medians and ranges .P< 0.05 was considered statistically significant.The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to analyze the data set to select the optimal predictors among the mpMRI quantitative parameters. Then, preoperatively clinical parameters used to build a clinical nomogram (C-nomogram), multivariable logistic regression analysis was used to build an MRI nomogram (M-nomogram) and MRI combined with the clinical nomogram (MC-monogram). Further, several kinds of validation methods were used to estimate the accuracy of the nomograms. The receiver operating characteristic (ROC) curve was used to evaluate the discrimination abilities. The area under the curve (AUC) was compared using the DeLong test. The calibration curve was used to evaluate the calibration of the nomogram, and decision curve analysis (DCA) was used to assess the net benefit of nomogram-assisted decisions. A 3-fold cross-validation method was used to randomly split the training cohort into 3 sets, where every two sets were the training sets and the remaining set was the validation set. The average AUC values of the 3 results were used to assess the stability of the nomogram. A two-tailed P< 0.05), but not differences in age, PI-RADS v2 score, prostate volume, lesion diameter, biopsy-based Gleason score, cTNM, postoperative Gleason score and pTNM (P > 0.05). The clinical characteristics are shown in One hundred and three PCa patients with mean age of 71 years  were included in our study. The overall PSMs incidence was 46.6% (48/103). There were significant differences between the two groups with respect to TPSA, PPC and pathological extra-prostatic extension . However, the specificity of M-nomogram was better than that of C-nomogram, and the model was optimized after MRI parameters was combined with clinical parameters, and the optimal sensitivity and specificity were obtained .The ROC of the C-nomogram , the M-nomogram  and the MC-nomogram  were shown in The calibration curves of the three nomograms used to predict the risk of PSMs in patients with PCa also showed good agreement  compared to C-nomogram (0.683) for PSMs prediction, and suggested that lower Da, Dmono, DBi, and DDC were the key parameters that determined the risk of PSMs for PCa patients. Because as tumors grow, both cell overcrowding and changes in stroma production alter cell-stroma and cell-cell associations in an ongoing dynamic process that disturbs the microarchitecture . Comparison of the calibration curve and DCA, showed that MC-nomogram demonstrated relatively good calibration power and clinical net benefit. This finding indicates that the ability of MRI-based nomogram to predict PSMs was optimized after combining clinical indicators. He et al.  reportedOur study had some significant limitations. First, this was a single-center retrospective study, and thus, the limited sample size may cause selection bias and other confounding factors. Second, the MC-nomogram lacked external validation. Third, we constructed predictive models based on mpMRI parameters obtained from complex DWI models, which may have limited the application and multicenter generalization of the MC-nomogram. And more our study did not include robot-assisted LRP, so results could be not applicable in robotic-assisted LRP.The mpMRI-based nomogram can predict PSMs in PCa patients. Although its AUC (0.735) is not statistically different from that of the clinical-based nomogram AUC (0.683). However, mpMRI-based nomogram has higher specificity (88% VS. 63%), model stability, and clinical benefit than clinical-based nomogram. And the predictive ability of mpMRI plus clinical parameters for PSMs is further improved.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 the institutional review board of First Affiliated Hospital of Dalian Medical University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.SM and AL conceived of the presented idea. SM and LC performed the measurements. AL supervised the work. SM and QZ processed the experimental data and performed the analysis. SM drafted the manuscript and NW aided in working on the manuscript. 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.


Evidence of the relationship between dietary cost, diet quality, and socio-economic status is mixed. No studies have directly evaluated food-security status and dietary cost. This study investigated whether food-pantry clients with low and very low food-security status had less expensive daily diets than food-secure clients by comparing total cost, cost per gram, and cost per calorie of total daily dietary intake both per person and by individual food item, followed by evaluations of each food group. Mixed-model regression and Tukey–Kramer comparisons were used to compare food-security groups. There was no clear association between food-security status and cost of daily diet. Analyzed per person, total price and price per gram showed significant differences between low food-secure and food-secure groups. When analyzing individual food items, prices per calorie were significantly different between food-secure and very low food-secure groups. The directionality of the relationships by food-security status was inconsistent. Per person, those with lower food security had lower mean prices, and for individual foods this association was reversed. Therefore, the metric of food cost and the unit of analysis are critical to determining the relationship between food-security status and dietary cost.  Food insecurity is a situation households experience when there are not enough money or resources to maintain the quality or quantity of foods needed for all members to have an active, healthy life . In 2021Lack of resources to purchase a diet of sufficient quality and the expense of “healthful” food have been used as explanations of the relationship between food insecurity and poor dietary quality among low-income groups ,7,8. “HeThrough this analysis, we seek to analyze the problem of how food-security status could be linked to dietary cost. Food-insecure and food-secure food-pantry clients are expected to have daily diet costs that do not differ in terms of total cost, cost of diet per calorie, and cost of diet per gram for total daily dietary intake and for food-group intake, when analyzed both at the individual level and at the food-item level. The results of this investigation may be used to inform interventions, such as the Supplemental Nutrition Assistance Program (SNAP), the Special Supplemental Program for Women, Infants and Children (WIC), and the National School Lunch Program, to improve dietary intake among a vulnerable sub-population of food-pantry users. Therefore, the objectives of this study are to: (1) determine the daily dietary costs of adult food-pantry clients (both per person and per food) in the Midwest according to food-secure, low food-secure, and very low food-secure status for total diet and by food group and (2) evaluate whether differences in dietary costs for total diet and by food group exist between clients of various food-security status (per person) when dietary quality is held constant and among the foods reported by clients of these various food-security status groups (per food item). Cost in this study will not be the true cost paid by the individual (or not paid in the case of food-pantry foods) but rather the value of the foods as determined by the US Department of Agriculture. This secondary analysis utilizes the 2014 baseline dietary intake data from food-pantry client participants in the Voices for Food project (VFF), a collaborative intervention delivered through universities in six Midwestern states: Indiana, Michigan, Missouri, Nebraska, Ohio, and South Dakota. The long-term goal of VFF was to increase Midwestern food-pantry users’ food security and diet quality, a complete description of which has previously been published . A totalParticipants were recruited from August to November in 2014, either by trained research staff or through flyer promotion of the study at each selected pantry that met the previously described conditions ,19. ReseDemographic information as well as characteristics of pantry use for each participant were obtained through an interview with a research staff member at the participating pantries, and a 54-item questionnaire was delivered either electronically or via paper copy. The questionnaire inquired about participant characteristics and use of food pantries, the following of which were utilized in the analysis: state of residency, sex, age, ethnicity, race, highest level of education, work status, household income, and pantry-client participation in the following food-assistance programs: SNAP, Meals on Wheels, Soup Kitchens, and WIC. The food-security status of participants was queried via the US Household Food Security Survey Module, an 18-question survey that asks about the conditions, experiences, and behaviors related to household access to food due to limited resources. This was included in the participant questionnaire and was used to categorize responses into four levels: very low food-secure, low food-secure, marginally food-secure, and food-secure ,22. For In the ASA-24 dietary recall, each food reported was assigned a unique 8-digit USDA food code. This food code was matched with the same USDA food code in the 5th version of the Food and Nutrient Database for Dietary Studies (FNDDS) , chosen The USDA Center for Nutrition Policy and Promotion (CNPP) Food Price Database from 2003–2004 , the mosThe ASA24-2014 system is linked to the Food Patterns Equivalents Database 2011–2012 to allow the calculation of Healthy Eating Index (HEI)-2010 total and component scores. The HEI-2010, a scoring metric created by the USDA to determine the adherence of diets to the dietary guidance of the DGA, was used to derive dietary quality measures for food-pantry clients. The HEI-2010 includes nine “adequacy” categories , where a higher score indicates higher consumption of a particular type of food. There are also three “moderation” categories  which are reverse-scored so that a higher score indicates lower consumption. The scores from all twelve categories are combined to produce a total HEI score classifying an individual’s overall dietary quality, with higher scores indicating a mix of foods that aligns more closely with the guidance of the DGA, 100 being the highest possible score . The anap-values displayed are for log-transformed data, while means and standard deviations are shown for the untransformed data to allow for realistic applications. A linear mixed-effects model was used to compare the cost or price of foods consumed by food-security group, using separate models for the various price variables . Participant ID and region were included as random effects in the per-person analysis, and region was used as a random effect in the individual food analysis. Statistically discernible differences were assumed with p-values < 0.05. For dependent variables, where significant differences were observed, Tukey–Kramer pairwise comparisons were performed on the log-transformed data in order to determine which two groups differed, once again using an alpha = 0.05 to indicate statistical significance. SAS 9.4 was used to perform all statistical analyses. Participant characteristics among food-security groups were compared using chi-square analyses and included state of residency, age, sex, race, ethnicity, household income, employment status, diet quality (using HEI-2010 scores), and meal-assistance program participation. Significantly different characteristics among food-security groups, which included state, age, income, HEI-2010 score, and meal-assistance program use, were controlled for in all of the regression models. Sex and ethnicity were also controlled for in the models, although they were not significant because they were identified as appropriate adjustments. The independent variable of interest was food-security status classified into three groups: very low food-secure, low food-secure, and food-secure. The dependent variables representing the costs of foods consumed were total price, price per calorie, and price per gram. These three cost metrics were analyzed per person and by individual foods both for overall diet and for the following food groups: dairy, fruits, grains, protein, and vegetables. These five food groups represent the food groups recommended for inclusion by the 2020–2025 DGA . ResiduaThe pantry clients were predominately white (78%), female (60%), aged 45–64 (37%), and classified as food-insecure (77%), with 30% experiencing low food security and 47% experiencing very low food security . When stp = 0.004 and p = 0.03, respectively). For both categories, Tukey pairwise comparison showed a difference between low food-secure and very low food-secure groups. For total price per person, the low food-secure group had a higher untransformed mean ($2.89) than the very low food-secure group ($2.27). Price per gram per person followed the same trend, with low food-secure participants averaging $0.0015 per gram and very low food-secure participants averaging $0.0012 per gram. Regarding the estimates by individual food, prices per calorie were statistically different between groups (p = 0.006), but this time the difference was between the very low and food-secure groups, the food-secure group having a lower untransformed mean price per kilocalorie ($0.0038) compared to the very low food-secure group ($0.0043). Analyzing the three price metrics  for the 24-h recall period by mean cost of daily diet per person and mean cost of diet for individual foods showed varying significant differences between food-secure, low food-secure, and very low food-secure groups . Total pp = 0.04) (p = 0.01), with the very low food-secure group showing a higher untransformed mean at $0.0021 per gram compared to $0.0018 for the low food-secure group. A similar result was noted for price per gram of fruit for individual foods (p = 0.03), also between very low and low food-secure groups (p = 0.0001)  . Differe = 0.04)  were alse groups , with ve 0.0001) . This ti 0.0001) . This study evaluated costs, adjusting for dietary quality, among food-pantry clients by food-security status. The results showed that the relationship between dietary cost and food security was mixed, and that higher dietary costs were not consistently linked to food security or level of food insecurity. Although there were significant differences between certain dietary cost scenarios, the inconsistency among the different price metrics and units of analysis showed that there was no clear association between food-security status and cost of diet among adult food-pantry users when dietary quality was held constant. When considering all foods together, total price and price per gram were significantly different per person, and price per calorie was different for individual foods, but the two food-security groups responsible for the significance were not consistent. In the per person analysis of total price and price per gram, very low and low food-secure groups showed evidence of being significantly different, with the latter having a higher mean. However, individual food analysis showed a difference between very low and food-secure groups, with the latter having the lower mean. By performing the same statistical tests on the same data set per person and by individual food item and obtaining these varying results, the mixed relationship between these two variables was further exemplified. Analysis of individual food groups showed few significant differences between dietary cost metrics among food-secure groups, both per person and based on individual foods. The food groups found to exhibit differences were fruits and vegetables, which are commonly considered “healthy” food groups and foods that most Americans need to consume more of, as stated in the DGA . Fruits Prior studies have investigated the link between income and dietary cost and quality. Some have shown that more expensive and higher quality diets were consumed by higher socioeconomic status groups with better health outcomes compared with individuals of lower socioeconomic status . HoweverThese results are relevant to modeling the minimum expenses for foods required to obtain a nutritionally adequate diet. The Thrifty Food Plan, for example, is a USDA-created food plan that estimates the cost of a healthy diet at a low price point, and it is used to determine SNAP benefit amounts for American households . The Thrn = 588) from food pantries from a variety of Midwestern states, providing evidence that may be applicable to a larger population [By analyzing dietary cost in terms of total price, price per calorie, and price per gram, this secondary analysis was able to comparatively show various price metrics used in the prior literature regarding cost of diet and diet quality, all with a similar sample ,13,14,15pulation . p-values were found after normalizing the data with a log transformation, the raw means could be impacted by these outliers, even with the large sample size. Twenty-four-hour recalls are subject to errors by individuals, particularly under-reporting . FurtherThe results of this study did not establish a consistent relationship between the food-security statuses of food-pantry users and the costs of their diets. Evaluation of total prices, prices per calorie, and prices per gram, both by individual person and individual food item, yielded some significant relationships regarding food-security status, but the directionality varied according to the metrics and units of analysis used. Therefore, the metric of food cost and the unit of analysis are critical to determining the relationship between food-security status and dietary cost.By analyzing the costs of diets using a variety of metrics and revealing an inconsistent relationship between price and food-security status, this study showed that the cost of diet does not have a direct relationship to food insecurity. Furthermore, dietary costs can not only vary according to the way that prices are calculated , but also by the unit of analysis used, by foods or by individuals. Further studies should focus on the interesting relationship between food-security status and the cost of fruits and vegetables in the diet, for example, by potentially investigating the frequency of fresh, canned, and/or frozen fruit and vegetable consumption among certain groups and its relationship to dietary quality. Although there was no direct relationship found between cost and food-security status, total costs per day for all three food-security groups in this study were lower than those modeled by the Thrifty Food Plan. Such findings could indicate a need for greater government funding and resources for low-resource groups in poorer areas of the country. Since the sample data were obtained from Midwestern states, it would also be beneficial to compare these data with those of pantries in more urbanized parts of the nation and see how dietary costs and quality compare.


The authors would like to make corrections to a recently published paper .In the original publication, the funder German Research Foundation (Deutsche Forschungsgemeinschaft), DFG FOR 2959, project-id: 409800133; grant number: DI 1757/2-1 to authors Jonas Lander and Marie-Luise Dierks was not included. The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original publication has also been updated.


Mycobacterium tuberculosis (Mtb) complex (MTBC). While they facilitate the processing of WGS data with minimal user expertise, they are either too general, providing little insights into bacterium-specific issues such as gene variations, INDEL/synonymous/PE-PPE (IDP family), and drug resistance from sample data, or are limited to specific objectives, such as drug resistance. It is understood that drug resistance and lineage-specific issues require an elaborate prioritization of identified variants to choose the best target for subsequent therapeutic intervention. Mycobacterium variant pipeline (MycoVarP) addresses these specific issues with a flexible battery of user-defined and default filters. It provides an end-to-end solution for WGS analysis of Mtb variants from the raw reads and performs two quality checks, viz, before trimming and after alignments of reads to the reference genome. MycoVarP maps the annotated variants to the drug-susceptible (DS) database and removes the false-positive variants, provides lineage identification, and predicts potential drug resistance. We have re-analyzed the WGS data reported by Whole-genome sequencing (WGS) provides a comprehensive tool to analyze the bacterial genomes for genotype–phenotype correlations, diversity of single-nucleotide variant (SNV), and their evolution and transmission. Several online pipelines and standalone tools are available for WGS analysis of  Mycobacterium tuberculosis (Mtb) strains against drugs contributes significantly to high mortality in tuberculosis patients. According to the global tuberculosis (TB) report-2020, drug-resistant TB became a major public threat, and half a million people developed rifampicin resistance, out of which 78% developed multidrug resistance to TB (MDR-TB) around the globe  to TB (Mtb to evade existing and recently approved drugs. Whole-genome sequencing (WGS) identifies sequence information of variants responsible for drug susceptibility (DS) and the emergence of drug resistance (DR) (Mtb (The emergence of resistance in he globe . The majhe globe . Recent R) to TB . Thus, tnce (DR) . WGS helDR) (Mtb . WGS stuDR) (Mtb  (SupplemDR)   in SISTANCE . HoweverSISTANCE , PhyResSSISTANCE , MUBII-TSISTANCE , MTBseq SISTANCE , CASTB (complex) , unifiedcomplex)  and Kvarcomplex) , etc (Sucomplex) . As MeehMtb has been utilized to reveal their relationship between its genome, transcriptome, methylome, identification of subspecies, associated lineages, transmission inference, and possible transmission within the host and interspecies. The molecular clock of Mtb has been delineated using WGS, which gives insights for deciphering the accurate phylogenetic relationship among different mycobacterial strains  protein family , removal of the IDP family of PE/PPE genes, and removing the false-positive variants. PE-PPE (IDP family) and repetitive regions have a high rate of mutation due to disordered regions. Therefore, it is difficult to sequence using short-read sequencing. The technical and use-case discussion of this tool MycoVarP, Mycobacterium Variant and Drug Resistance Prediction, are provided in the following sections. As stated, these methods rely on pipeline-specific constant parameters for analysis and do not provide the flexibility to tune them according to user requirements in view of the quality of the raw sequencing data and diversity in the strains of Mycobacterial isolates from different geographical regions. In the following sections, we review these issues specifically and present a novel pipeline to analyze lineage and DR patterns of clinical strains from WGS data. In the proposed pipeline, called MycoVarP, a number of steps have been automated based on best clinical outcomes, for example, SNVs related to repetitive regions have been excluded and rigorous downstream filtering after variant calling is included  of  strains . This ap strains . Several strains . WGS hasry cases . The epising WGS . ML-basesing WGS . In summsing WGS . One cavsing WGS  have pron family . Many ofn family . Realizin family . These cThe detailed steps of WGS analysis as used in MycoVarP have been given in viz., 1) for the selection of raw reads by quality check (QC) and 2) at the sequence alignment level. Quality is checked for G + C content, INDELs/repetitive regions, duplicates adapters, overrepresented sequences, genome coverage, and depth of coverage  using BWA . This project contains clinical samples of M. tb from India that showed genetic heterogeneity and variation specificity based on the geographical region , per-sequence quality score , per-base sequence content (difference of A and T or G and C is >20% in any position), per-base GC content: , per-sequence GC content: , per-base N Content: (N content >20% of the reads), sequence length distribution: (if any have zero length), duplicate sequences , overrepresented sequences , and overrepresented K-mers. Trimming of the 194 samples was carried out using Trimmomatic-0.39, and 36 samples were discarded due to low survival score <60. For each read, the survival rate was checked so that the samples with good quality were considered for further variant calling analysis.The 164 samples are submitted to the MycoVarP pipeline using an in-house developed shell script which is given in an additional file.37Rv genome , Lineage 1.2, EAI (1.0), CAS (0.86) || Beijing (0.82), Haarlem (1.0), CAS (0.85) || Beijing (0.81), Ural (0.95), and Lineage 4.1 and 4.3 are different from those in the previous reports  Supplem. LineageWGS pipelines in the public domain have so far helped us to identify the variants, predict their lineage, and DR association of the variant. However, there is a need to apply variant filters and prioritization steps to narrow down the most relevant variants from the raw data . vcf file . These fMtb strain H37Rv genome has been used as the reference genome. However, there are other complete Mtb genome sequences available that can be explored to analyze different strains having diverse lineages and accordingly, the most appropriate lineage reference genome can be defined.There is a need to select the reference genome according to the geographical region of the isolate. In most of the WGS analysis pipelines, the Mtb, there is large WGS data available, still the SNPs of its WGS data do not have ID like the human genome. Therefore, there are no standardized databases of SNPs that can be used to recalibrate and annotate variants while variant calling. Variant recalibrator takes the overlap of the training/reference/truth resource sets and query call set. The VQSLOD  score is added to the INFO field of each SNP and checks whether the obtained SNP is true or false under the trained Gaussian mixture model. Therefore, there is a need for a standardized Mtb_reference.vcf file for the recalibration step.The variants obtained from WGS analysis of human sequences have well-defined Rsid (reference SNP cluster ID) which is present in the single-nucleotide polymorphism database (dbSNP) and accession numbers for variations observed in human diseases available in the ClinVar database. However, in the case of The Mtb H37Rv genome consists of 99 PE, 69 PPE, and 61 PE-PGRS (polymorphic GC-rich) genes which have a variety of functions  analysis of Mtb by researchers less familiar with computational nuances.In the present work, WGS analysis steps have been carried out with stringent quality parameters to obtain significant results. The steps involved in the WGS analysis have been explained in detail in the abovementioned text, and additional information has been added to the adapter library of Trimmomatic. Our results on a case study indicate that the proposed pipeline can detect many variants that are missed from current public reports, and thereby a better treatment strategy informed by accurate identification of DS can be developed. Being a user-friendly and mostly fully automated pipeline, we believe that MycoVarP can be used to carry out WGS studies on the clinical data of


Modified pharyngeal electrical stimulation (mPES) is a novel therapeutic modality for patients with neurogenic dysphagia. However, the underlying neural mechanism remains poorly understood. This study aimed to use functional near-infrared spectroscopy (fNIRS) to explore the influence of mPES on swallowing-related frequency-specific neural networks and ethology.Twenty-two healthy right-handed volunteers participated in the study. Each participant was randomly assigned to either the sham or the mPES group and provided a 10-min intervention program every day for 5 days. Oxyhemoglobin and deoxyhemoglobin concentration changes verified by fNIRS were recorded on days 1, 3, and 5. Five characteristic frequency signals (0.0095–2 Hz) were identified using the wavelet transform method. To calculate frequency-specific functional connectivity, wavelet phase coherence (WPCO) was adopted. Furthermore, behavioral performance was assessed pre- and post-mPES using a 150 ml-water swallowing stress test.Compared with sham stimulation on day 1, the significantly decreased WPCO values were mainly associated with the dorsolateral prefrontal lobe, Broca's area, and middle temporal lobe. Compared with the sham mPES on day 1, the mPES showed a noticeable effect on the total swallow duration. Compared with the baseline, the WPCO values on days 3 and 5 showed a stepwise decrease in connectivity with the application of mPES. Furthermore, the decreased WPCO was associated with a shortened time per swallow after mPES.The mPES could modulate swallowing-related frequency-specific neural networks and evoke swallowing cortical processing more efficiently. This was associated with improved performance in a water swallowing stress test in healthy participants. The paropharynx . The neuopharynx –11. Howeopharynx , 13. Non2Hb) and deoxygenated hemoglobin (HHb) concentrations in natural physiological postures. The cerebral blood oxygen signal measured using fNIRS has obvious time-frequency characteristics  has been used to study cortical activity during swallowing because it has nonionizing radiation, arbitrary slice scanning, multi-parameter imaging, and excellent spatial resolution , 15. Acteristics , 23. ThiA method of peripheral nerve regulation could have a remote effect on the network connectivity of the entire cortical region and induce alterations in hemisphere region connectivity, and a valid mPES intervention biomarker captures the relevant neuroplasticity that contributes to behavioral change . FunctioA total of 22 right-handed healthy participants  participated in this study. The exclusion criteria included pregnancy; migraine; caffeinism; a history of neurological or psychiatric illness; taking any medications affecting the central nervous system; dementia; head and neck region radiation therapy; and prior surgery to the ear, nose, mouth, and throat region. The demographic characteristics and swallowing performance are shown in *Power 3.1.9.7 software was used for sample-size calculation of repeated measures ANOVA with parallel design. Power calculation identified a sample size of at least 20 participants to detect a 0.3 effect size with 0.8 power with significance level set at 0.05. A flowchart of the study is illustrated in All participants were randomly assigned to either the sham or the mPES group using central computer-generated randomization numbers in sealed opaque envelopes prepared by our consultant statistician. The principal investigator WHM was responsible for allocation concealment. A qualified physiatrist ZX was responsible for performing the mPES. A research assistant XH was responsible for the fNIRS monitoring process, while a second research assistant SYL was responsible for the functional evaluation process. The data collectors and participants were blinded throughout the study period. Based on the pre-experimental results and experimental design requirements, Gvia a 150 ml-water swallowing stress test ] (via the same nostril by the same experienced operator.The mPES current intensity (CI) was detected from the initial CI (0.5 mA), and the stimulus CI was gradually increased. The perception threshold (PT) was defined as the CI at which the participant began to feel the stimulus. The maximum tolerance threshold (MTT) was the CI at which the participant felt discomfort or pain and did not want the stimulus to ramp up further. The optimal CI was calculated as T − PT)] . The opeIn the mPES and sham groups, a continuous wave fNIRS device  with wavelengths of 730 nm, 808 nm, and 850 nm was used to measure cortical hemodynamic parameters . A total2Hb and HHb in each channel were calculated according to the modified Beer–Lambert law. Second, an independent component analysis was performed on the delta O2Hb and HHb signals of each channel to determine the components that might be related to noise and artifacts. Third, a moving average filter was used to eliminate the obvious abnormal points in the signal, and the artifact portion was removed using cubic spline interpolation. Furthermore, changes in scalp blood flow were taken from the signals using a short-separation channel with a 10 mm distance between the source and detector.The pre-processing method of fNIRS data has been proven in previous studies –31. FirsThe continuous wavelet transform can recognize the time-varying frequency and phase, which enables us to continuously derive the frequency content in time by adjusting the length of the wavelet windows. The Morlet wavelet can locate independent times and meet the requirements of frequency resolution, which can be used to analyze non-stationary cerebral blood oxygen signals.The local cerebral blood oxygen concentration change detected by fNIRS is derived from spontaneous cerebral cortex activity, which reflects changes in neural activity in the cerebral cortex. The following five frequency intervals corresponding to different physiological sources have been identified by the wavelet transform , 33: 0.6FC was calculated using wavelet phase coherence (WPCO), which can be used to explain the phase relation of brain function adjustments . The WPCp-value threshold was set at p < 0.0167 (0.05/3). Furthermore, covariance analysis was used to evaluate behavioral data from the 150 ml-water swallowing stress test. To further verify the relationship between brain functional network connectivity and swallowing function, we computed the region-based Pearson correlation coefficients between the mPES-related WPCO changes (WPCO = WPCOtask−WPCOrest) and EMG results in each group. The statistical significance level was set at p < 0.05.The data were presented as mean ± standard deviation (SD). The Kolmogorov–Smirnov and Levene tests were applied to test the variance normality and homogeneity of the data at the group level. For inter-group comparison, the parameters of the resting state were taken as covariables, and covariance analysis was used to evaluate the significant differences in parameters (region-wise WPCO) between the sham and mPES states. Repeated-measures ANOVA was used to assess the significance of intragroup parameter changes in both groups, and Bonferroni correction was used for multiple comparisons. In total, there were three inter-group pairwise comparisons, and the corrected The behavioral results are presented in F = 4.732, p = 0.044), rWernicke's-lMTL , and rDLPFC-lMTL  in interval III  and l-SFC-M1  in interval IV , bilateral S1 , r-DLPFC-MTL , r-DLPFC-S1 , lWernicke's-rS1 , rBroca's-lMTL , lBroca's-rMTL , lDLPFC-rMTL , lDLPFC-rFP , lPFC-rMTL , and r-DLPFC-Broca's  in interval V , l-S1-MTL , l-M1-MTL , rM1-lMTL , rWernicke's-lMTL , and L-Wernicke's-MTL  in interval III, and a significant increase between rS1-lMTL  in interval V  and r-DLPFC-Broca's  in the right hemisphere was positively correlated with the time per swallow. The results showed that decreased WPCO was associated with a shortened time per swallow after mPES.We examined the correlation between mPES-induced changes in WPCO values and the difference in time per swallow of post- and pre-task . SignifiThe present study investigated the impact of mPES on frequency-specific brain functional connectivity through 5-day tracing in healthy participants using fNIRS. The seminal findings were as follows: Compared with the sham group, significantly decreased WPCO values were mainly found in the DLPFC, Broca's, and MTL in the mPES group. Relative to the baseline, the WPCO values showed a stepwise decrease in connectivity mainly associated with MTL, Broca's, and Wernicke's in intervals III and V, along with the application of mPES. WPCO values  and shorter time per swallow after mPES were found to be significantly correlated.FC is defined as the temporal synchronicity between spatially independent neurophysiological activities . It is aA previous neuroimaging study demonstrated an extremely stable synchronization of spontaneous activity between homologous brain regions in all bilateral cerebral hemispheres , which wHemispheric specialization is an organizing principle of the human brain that has been hypothesized to contribute to fast and efficient information processing . In the Concerning the gradually decreased brain connectivity associated with MTL, Broca's, and Wernicke's with mPES application. Although the MTL, Broca's, and Wernicke's areas have overlapping anatomy of speech and swallowing , they maRegarding ethological behaviors, decreased functional connectivity was associated with better swallowing performance. Alterations in swallowing duration were minor but statistically significant, which could be attributed to healthy participants. Moreover, the shortened time per swallow was associated with decreased WPCO of bilateral S1 and r-DLPFC-Broca's, implying that mPES might modulate these brain regions to increase swallowing processing efficiency. As discussed above, lS1 and rDLPFC might be the major brain regions to be excluded to improve swallowing processing efficiency.The current study has some limitations. First, fNIRS, unlike fMRI, does not provide whole-brain measurements and is limited in measuring deep cortical and subcortical regions. Second, arterial pressure oscillations occur spontaneously as Mayer waves exist in conscious participants in the vicinity of a 0.1 Hz frequency, which might affect the FC in interval III (0.052–0.145 Hz). Therefore, the interference of the Mayer waves should be considered in future studies. Last, the study included healthy participants. As studies on patients with dysphagia would be of more interest in the field of neurorehabilitation, a follow-up study including patients would be carried out.Notwithstanding these limitations, this study provides evidence for the modulation of functional connectivity elicited by the mPES. Moreover, the mPES is relatively passive and involves minimal compliance. The method in this study could be extended to assess changes in brain activities induced by mPES in patients with dysphagia who cannot perform volitional swallowing.Our findings suggest that mPES could induce neuroplastic changes in the swallowing-related brain network that are associated with improved swallowing behaviors. Our study provided evidence that mPES could improve swallowing processing efficiency, and long-term mPES could further induce swallowing-related functional network reorganization. Further studies investigating the effects of this tool on the brain network and swallowing function in patients with dysphagia are necessary.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 the Ethics Committee of the Third Affiliated Hospital, Sun Yat-sen University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.ZD and HW: conceptualization and supervision. HW: methodology. XZ and HX: formal analysis, investigation, and writing–original draft preparation. XZ, HX, ZL, XW, RS, ZD, and HW: writing–review and editing. HW, ZL, and ZD: funding acquisition. XZ, HX, XW, XL, YS, CL, JC, JH, GW, YZ, and DA: resources. All authors contributed to the study conception and design.This project was supported by the National Key Research and Development Project (2020YFC2004205), the National Natural Science Foundation of China (Grant Numbers 81972159 and 81672259), the Natural Science Foundation of Guangdong Province of China (Grant Numbers 2019A1515010388 and 2020A1515010881), and the Clinical Research Special Fund Project of the Third Affiliated Hospital of Sun Yat-sen University (Voyage Plan) (YHJH201909).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.


Parkinson’s Progression Markers Initiative (PPMI) from different sites with healthy controls (HC) and Parkinson’s disease (PD) patients. First, the investigation of radiomics measure discrepancies were assessed on healthy brain regions-of-interest (ROIs) via a classification pipeline based on LASSO feature selection and support vector machine (SVM) model. Then, a ComBat-based harmonization approach was applied to correct site-effects. Finally, a validation step on PD subjects evaluated diagnostic accuracy before and after harmonization of radiomics data. Results on healthy subjects demonstrated a dependence from site-effects that could be corrected with ComBat harmonization. LASSO regressor after harmonization was unable to select any feature to distinguish controls by site. Moreover, harmonized radiomics features achieved an area under the receiving operating characteristic curve (AUC) of 0.77 (compared to AUC of 0.71 for raw radiomics measures) in distinguish Parkinson’s patients from HC. We found a not-negligible site-effect studying radiomics of HC pre- and post-harmonization of features. Our validation study on PD patients demonstrated a significant influence of non-biological noise source in diagnostic performances. Finally, harmonization of multicenter radiomic data represent a necessary step to make analysis pipelines reliable and replicable for multisite neuroimaging studies.Radiomics is a challenging development area in imaging field that is greatly capturing interest of radiologists and neuroscientists. However, radiomics features show a strong non-biological variability determined by different facilities and imaging protocols, limiting the reproducibility and generalizability of analysis frameworks. Our study aimed to investigate the usefulness of harmonization to reduce site-effects on radiomics features over specific brain regions. We selected T1-weighted magnetic resonance imaging (MRI) by using the MRI dataset  Radiomics is a challenging development area in imaging field that is greatly capturing interest of radiologists and neuroscientists . AllowinDespite the outstanding results, radiomics features have showed a strong dependence from different research facilities or different acquisition protocols, limiting the reproducibility and generalizability of the proposed frameworks especially for application on multi-site dataset . Recent Parkinson’s Progression Markers Initiative (PPMI), sponsored by the Michael J. Fox Foundation, evaluating the sensitivity to site-related effects. In a second step, normalization and harmonization models defined on healthy subjects were applied on patients with PD to evaluate the classification performance pre- and post- site-effect correction.In the current study, we investigated the effectiveness of normalization and harmonization approaches to reduce site-effects on radiomics features from healthy brain ROIs. At first, we extracted radiomics features on T1-weighted MRI images of healthy subjects collected from different acquisition sites in the context of the 1 For up-to-date information on the study, visit ppmi-info.org. The T1-weighted MR images selected for this study were acquired using a 1.5–3 Tesla scanner from different manufactures . Acquisition protocols from each site are reported in Data used in the preparation of this study were obtained from the PPMI database.recon-all script included in Freesurfer v6.0.2 After removal of non-brain tissue and bias of each structural brain image, we used the non-uniform intensity corrected image (nu.mgz) in the Freesurfer space to compute radiomics features. An additional step of intensity normalization was performed using the Z-Score method by centering each pre-processed T1w volume at the mean with standard deviation. To identify and characterize the site effect on radiomic features, we extracted the ROIs using the Desikan–Killiany atlas cortical parcelation from the individual subcortical segmentation image (aparc + aseg.mgz)  . Then, wseg.mgz)  tools toData used for our analysis was collected from three ROIs, namely Caudate, Putamen and Thalamus, for both hemispheres, as a set of subcortical brain regions pertinent to PD . For eachttps://github.com/rpomponio/neuroHarmonize  model  considering only HC. To this end, classification performances were first evaluated using raw data. Next, we evaluated the impact of image normalization and ComBat harmonization on the classification performances. For each classification model, at each inner loop of LOOCV, we firstly reduced the burden of high dimensionality of radiomics set of features using least absolute shrinkage and selection operator (LASSO) . TherefoM) model  for eachAs second step of our framework, we implemented the same pipeline for PD detection. This procedure was implemented in a ten-times repeated 10-fold cross validation setting. At each of 100 bootstraps, nine folds was used to define a LASSO regression model to select optimal radiomics features. The selected features were saved in a vector to further analysis . These fpost-hoc comparisons. For all analyses, the corrected significance threshold was set at p < 0.05 after Bonferroni’s correction for multiple comparisons. Statistical analysis was performed by using R software .Demographic and clinical information of the dataset were provided with descriptive statistics (mean ± SD). Group differences in age, sex, MoCA , UPDRS-III  scales and H&Y (Hoehn and Yahr) stage were investigated through Chi-square test, one-way analysis of variance (ANOVA) and Kruskal–Wallis ANOVA followed by The Area Under the receiving operating characteristic Curves (AUCs) were used as evaluation metric for our “site vs. site” models. Classification performances for HC vs. PD models were evaluated by accuracy, sensitivity and specificity, mediated over the 100 bootstraps of classification. Finally, the diagnostic capabilities of the radiomics signatures were evaluated with Receiver Operating Characteristic (ROC) curve analysis.To assess the stability of radiomics features selected by LASSO regression over HC vs. PD model, we used a frequency-based criterion. For each round of the bootstraps, we stored as relevant features only those corresponding to non-zero weights assigned by LASSO. Subsequently, we selected as most stable radiomics features those that occurred in at least 95° percentile of the frequency vector.We selected MR images from seven sites of the PPMI database according with the number of enrolled HC. p-values < 0.001) between HC and PD patients.For each site, we also selected a set of age- and sex-matched PD. Data is reported in dim) from a principal component analysis (PCA)   and a hiis (PCA)  for no pAfter harmonization of radiomics features, LASSO regressions were unable to select any features for prediction of the outcomes. Indeed, LOOCV plots for each pairwise site comparison resulted in a penalty factor that shrinked all regression coefficients to zero see .As second step of our analysis, we evaluated goodness of classification of PD from HC in our three different radiomics approaches, namely without any pre-processing prior to radiomics features calculation, with normalization of image before radiomics computations and with harmonization from site-effect of radiomics features. We report results of each model in As shown in This study demonstrated the sensitivity of radiomic features to site-effects in multicenter neuroimaging study. We firstly investigated the problem of data variability due to non-biological effects on healthy brain regions. Then, implementing a ComBat-based harmonization procedure of radiomics features, we modelized site-related noise source reducing differences across healthy subjects. Lastly, as validation task, we evaluated the effectiveness of our harmonization approach for classification of PD patients.Site 19 and Site 52 reported an AUC close to random choice without using the harmonization approach, probably due to common scanner and protocol parameters used in MRI acquisition.The small sample size made necessary some methodological choices. First of all, it was mandatory to use a feature selection method to avoid a course of dimensionality problem due to the imbalance between the number of radiomic features and the sample size . On the These findings demonstrated an effective dependency of radiomics features from scanner and acquisition protocol that could not be eliminated with normalization of image intensity but only using a ComBat-based algorithm. Our results were in line with previous findings in radiomics, over both oncology and neuroimaging, that have demonstrated a better standardization capabilities of ComBat-based models compared with different intensity normalization techniques, such as normalization (Z-Score), WhiteStripe and Ravel .caudate + putamen)  , in PD pOur work has some limitations. Firstly, the limited sample size for each site could produce unstable LASSO regression results, as well as a possible overfitting in SVM training, that we have tried to overcome with a bootstrapped 10-fold CV. Overall, cohorts of subjects from other international neuroimaging studies can be added to solve these issues guarantying greater generalizability of the results. Second, we applied only one type of normalization and harmonization techniques limiting other possible comparisons and further optimizations of performances. Future works can consider more complex intensity normalization methods, such as RAVEL or WhiteStripe, and recently developed alternative versions of ComBat with improved flexibility (M-ComBat) and robustness (B-ComBat) .The harmonization of MRI data represents a crucial problem in several medical imaging applications due to non-biological effects determined by different acquisition sites, scanners and multiparametric sequences. Our study aimed to assess the variability of radiomics features extracted on T1w MR images collected in a multicentric context. We found a not-negligible site-effect comparing radiomics features of HC pre- and post-harmonization pipeline. Moreover, our study demonstrated a significant influence of scan noise in distinguishing controls from PD patients. Overall, harmonization of radiomic features represents a necessary requirement for reliable and replicable analysis frameworks in multicenter study.https://www.ppmi-info.org/access-data-specimens/download-data.Publicly available datasets were analyzed in this study. This data can be found here: https://www.ppmi-info.org/about-ppmi/ppmi-clinical-sites/) and written informed consent for imaging data and clinical questionnaires was obtained from each participant at the time of enrollmentThe PPMI study was approved by the local Institutional Review Boards of all participating sites (BT: conceptualization, formal analysis, methodology, software, visualization, and roles/writing – original draft. AL: conceptualization, methodology, validation, supervision, and writing – review and editing. SN: methodology, project administration, supervision, validation, and writing – review and editing. DU: data curation, resources, and writing – review and editing. AM, EP, and DD: data curation and writing – review and editing. RD: validation, visualization, and writing – review and editing. RB: project administration and writing – review and editing. ST: conceptualization, project administration, supervision, and writing – review and editing. GL: funding acquisition, conceptualization, project administration, supervision, and writing – review and editing. All authors contributed to the article and approved the submitted version.


Adverse drug reactions, including Fixed Drug Eruption (FDE) to TMP-SMX in CGD patients, are challenging as it may result in serious complications and difficulties in management.Chronic granulomatous disease (CGD) is a known Primary immunodeficiency disease that results in recurrent, life-threatening bacterial, fungal infections and granuloma formation which requires lifelong antibacterial and antifungal prophylaxis. Sulphamethoxazole-trimethoprim (TMP-SMX/Septrin) is the prophylactic antibacterial drug of choice.A seventeen-year-old Qatari female diagnosed with CGD was maintained on prophylactic TMP-SMX and itraconazole since childhood. She developed bullous skin lesions involving the face, neck, and trunk sparing the limbs. The skin lesion was confirmed to be FDE by skin biopsy. TMP-SMX was discontinued as it was suspected to be the causative agent. Atovaquone 1500 mg and clarithromycin 250 mg daily were started as an alternative, but the patient could not tolerate them. TMP-SMX slow graded challenge and desensitization were performed; however, the patient developed similar lesions in the previous affected areas on day 3 of desensitization, which responded well to discontinuation of TMP-SMX along with administration of steroid. FDE to TMP-SMX as the causative agent was confirmed. An MDT meeting was conducted to evaluate other available options for treatment. Also, the case was discussed with international immunology colleagues. The recommendation was to go for bone marrow transplantation to treat the primary disease. Six years post transplants, the patient is doing well and is not on any medications apart from the hormonal replacement therapy patch. TMP-SMX is an ideal antibiotic as it is relatively cheap with good coverage and orally available. In the medical literature, desensitization can be tried in FDE, especially if there is no alternative for the needed drug. FDE signs should be observed when administered TMP-SMX.CGD predisposes to several gram-positive, gram-negative bacterial  and fungal infections.


Breast cancer patients are at elevated risk of depression during treatment, thus provoking the chance of poor clinical outcomes. This retrospective cohort study aimed to investigate whether integrating Chinese herbal medicines citation(CHM) into conventional cancer therapy could decrease the risk of depression in the long-term breast cancer survivors.n = 1,450) and did not receive  CHM treatment were enrolled. The incidence rate and hazard ratio citation(HR) for depression between the two groups was estimated at the end of 2012. A Cox proportional hazard model was constructed to examine the impact of the CHM use on the risk of depression.A cohort of patients aged 20–70 years and with newly diagnosed breast cancer during 2000–2008 was identified from a nationwide claims database. In this study, we focused solely on survivors of breast cancer at least1 year after diagnosis. After one-to-one matching for age, sex, and baseline comorbidities, breast cancer patients who received ], and the adjusted HR remained significant at 0.74 (95% CI 0.58–0.94) in a Cox proportional hazards regression model. The corresponding risk further decreasing to 43% among those using CHM for more than 1 year.Finding from this investigation indicated that the lower risk of depression observed in breast cancer patients treated with CHM, suggesting that CHM treatment should be considered for disease management toward breast cancer. Yet, the optimal administered dose should be determined in further clinical trials. Depression is a chronic medical condition that impacts the cognitive, affective and physical wellbeing of a person . GloballBreast cancer is the most common form of malignancy in women, and affected patients are at a higher likelihood of experiencing depression, a condition aggravated by the necessity to undergo continuous life-saving treatments. After administering their cancer-related questionnaire to 179 women with breast cancer, via regulating HPA Axis and the level of amino acids neurotransmitters  has shown promising results in improving the body’s ability to fight malignant disease. Several of these herbs were further proven to improve cognitive function through the suppression of monoamine oxidase activity and oxidative stress as well as the modulation of the hypothalamic-pituitary-adrenal axis activation . Take ussmitters . In thisTaiwan’s NHI program, launched in 1995, is a single-payer government-operated compulsory health insurance program. As of 2015, up to 99.6% of Taiwan’s population was enrolled in the NHI program Research data for this retrospective cohort study were obtained from the Longitudinal Health Insurance Database citation(LHID) administered by the Ministry of Health and Welfare. The LHID contains data on one million beneficiaries randomly sampled from the Registry for Beneficiaries of the NHI Research Database. The use of multistage stratified systematic sampling ensures no significant deviations in the distribution of sex and age between the LHID enrollees and the general population . The clan = 3,512). Meanwhile, to reduce the potential for disease misclassification, only those with catastrophic illness certification due to breast cancer were recruited. In Taiwan, insured persons with major chronic conditions can apply for catastrophic illness certification that grants exemption from co-payment. The date on which the patient gained approval for catastrophic illness registration due to breast cancer was considered the index date  code for the identification of patients with breast cancer. Patients aged 20–70 years who were newly diagnosed with breast cancer (ICD-9-CM code: 174) were considered for enrollment in the study. To ensure the identification of new breast cancer cases, we employed a 4-year washout period (1996–1999) to exclude any patients who had been diagnosed with breast cancer before entering the cohort (dex date .n = 94), and those followed up for less than 1 year after diagnosis of breast cancer (n = 38). Afterward, the final cohort included 3,380 patients.The study outcome was the first diagnosis of depression, which included major depressive disorder (ICD-9-CM codes: 296.2 and 296.3), dysthymic disorder (ICD-9-CM code: 300.4), and depressive disorder not elsewhere classified (ICD-9-CM code: 311). In this study, the diagnosis of depression was determined if patients were treated with ≧ 3 outpatient treatment claims or ≧1 hospitalization due to depression. We then excluded those who had a prior diagnosis of depression before the breast cancer onset  17800, NTD 17,881–43,900, and ≥ NTD $43901. As to the urbanization level, it was calculated according to a published scheme that classified 359 communities in Taiwan into seven stratums, with a higher level indicating a higher degree of urbanization. The classification scheme included the population density, proportion of persons with a college-level education or higher, proportion of elderly residents, proportion of agricultural workers, and number of physicians per 100,000 population. In this work, the urbanization degree was grouped into three strata: urban (levels 1–2), suburban (levels 3–4), and rural (levels 5–7) . The inft-test. Then we conducted a Cox proportional hazards regression analysis to compute the adjusted hazard ratio citation(HR) with 95% confidence interval citation(CI) of risk of depression in association with CHM use, after adjusting for age, sex, insurance premium (an indicator of income), urbanization level, and CCI simultaneously in the model. To test the robustness of the relationship between CHM use and depression risk, all CHM users were divided into two groups based on time of CHM use: (1) 31–365 days, and (2) ≥ 366 days. The Kaplan–Meier method was used to estimate the cumulative risk of depression in each group, and the difference between groups was assessed using the log-rank test. The proportional hazards assumption was examined by plotting the log [–log ] vs. the log citation. A P < 0.05 was considered statistically significant.Data were analyzed using SAS version 9.3 software . Distributions of sociodemographic data and comorbidities between the CHM users and non-CHM users were compared by using the chi-square and Student’s n = 1,450) and non-CHM users . Demographic data are shown in Data were analyzed for CHM users (P < 0.01) , respectively. The incidence of depression was significantly lower among CHM users than non-CHM users   . The use < 0.01) .Puerariae Lobatae Radix), Xiang Fu citation(Cyperi Rhizoma), Bai-Hua-She-She-Cao citation(Hedyotidis Herba), Shao-Yao-Gan-Cao-Tang citation, and Yin-Qiao-San .The most commonly prescribed Chinese herbal products for breast cancer patients are summarized in In this evidence-based cohort study exploring the relationship between CHM use and subsequent depression risk in breast cancer patients, we found that patients receiving CHM had a nearly 25% lower risk of depression than did those not using CHM. Furthermore, those receiving CHM for more than 365 days were found to have a significantly lower risk of depression by 43%. Through the determination of dose-response relation between an exposure citation(CHM use) and the risk of an outcome citation(depression incident), it may indeed support the causal association between the intensity of CHM use and the resultant lower risk for depression among breast cancer patients.No previous studies have reported the long-term influence of CHM on depression risk in breast cancer patients, thus precluding comparison of results. Nevertheless, the positive therapeutic effect of CHM observed in this work adds to the accumulating evidence suggesting that CHM exerts antidepressant effects by modulating dysfunctional neurotransmission . ProposeA major contribution of this study is the identification of specific CHM products associated with the observed lower risk of depression in breast cancer patients. We found that three single-product CHM commonly used to treat breast cancer were associated with a lower sequent risk of depression, like use of Ge-gen, Xiang-fu, and Bai-hua-she-she-cao. A previous study using an animal model reports that Pueraria, the principal ingredient of Ge-gen, exerted marked anti-depressant effects by abating nuclear factor kappa beta (NF-κB) signaling . NF-κB iin vivo study by Xiang-fu is a cytotoxic herb that inhibits cell growth and promotes apoptosis of breast cancer cells . A recenAnother commonly used single-herb product, Bai-Hua-She-She-Cao (Hedyotis diffusa), is commonly used to relieve heat and toxicity in cancer patients . Recent With regard to multi-herb products, the use of Shao-Yao-Gan-Cao-Tang was observed to be associated with a decreased risk of depression in our cohort. A previous study reported that an active component of Shao-Yao-Gan-Cao-Tang decoction, such as glycyrrhizin, affected multiple biological processes and pathways that participate in neuron apoptosis and inflammatory responses , all of As previously described in “Materials and methods” section, the database used in this study has several strengths, including its large sample size, the use of electronic records from a national health insurance registry, and a uniform approach to outcome assessment, all of which could strengthen validity of the study findings. On top of that, the selection bias ought to be minimized to a great extent by using data from the NHI database, which included over 99% of insured persons in Taiwan. Nonetheless, several limitations of this study merit attention. First, our findings were derived from analysis of retrospective cohort data based on ICD-9-CM diagnostic codes. Thus, relevant cases may have been misclassified. To improve diagnostic accuracy and avoid overestimation of the prevalence of cases of interests, we applied a 4-year washout period for breast cancer, where patients with a diagnosis of breast cancer during that period were considered prevalent and, therefore, excluded from analyses. Medical records were confirmed by requiring at least 3 outpatient service claims, or at least 1 inpatient hospitalization claim during the study period. Additionally, the diagnostic inclusion of breast cancer was further verified by the catastrophi illness certification. The NHI of Taiwan randomly reviews the charts and audits medical charges to verify the accuracy of claims. Despite this procedure, we recognize that the misclassification of cases is always a risk in database research, but this would be expected to occur at random which would likely serve to only bias the overall HR observed toward the null value and thus provide a more conservative estimate of effect. Second, data used in this study were drawn from a claim-based database and, accordingly, no detailed clinical information regarding laboratory data, family history, physical activity, and individual social network relationship was available. Thus, future studies that examine the influence of these variables are worthy of pursuit. Nevertheless, to carefully address the confounding by indication that may arise in this real-world comparative effectiveness study, we have capitalized on propensity score—matched analysis to analyze the association of CHM use with the attack of depression. For each breast cancer patient who received CHM, one control patient was selected by 1:1 matching, based on a propensity score. Additionally, to more robustly assess if other treatments may affect the finding herein, we reanalyzed the relationships between CHM use and subsequent risk of depression by adjusting for the utilization numbers of radiotherapy after breast cancer onset. The rational underlying this procedure was based on the assumption that radiotherapy for breast cancer patients is an obligatory component of a breast-conserving treatment modality and could cause deleterious psychological symptoms in such a group of patients . The re-in vivo studies that attempt to uncover the main mechanisms of prescribed herbal formulae that may be beneficial for such groups.Individuals with breast cancer suffer from the mood disorders more frequently than the general population, especially depression. This is the first population-based survey that rigorously evaluated the impact of CHM use on the prevention of depression among them. We found that integration of CHM into the conventional treatment regimen for breast cancer for more than 2 years may reduce the subsequent risk of depression by nearly 50%. This noteworthy finding can provide an impetus for further research venues, such as focusing on factors associated with utilization of CHM, as well as The data supporting the conclusion of this study are available from the authors, but the raw data (NHIRD) needs to be obtained from the National Health Research Institute of Taiwan through an application process upon approval, further inquiries should be directed to the corresponding author.This study was approved by the Research of Ethics Committee of Dalin Tzuchi Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.SY-Y, C-CY, C-KW, and T-YT: conception and design. M-CL and T-YT: provision of study material and patients. HL and T-YT: collection and assembly of data. SY-Y, HL, JS-J, S-WY, C-KW, and T-YT: data analysis and interpretation. SY-Y, HL, JS-J, S-WY, H-LH, MC, C-CY, C-KW, and T-YT: manuscript writing. SY-Y, HL, JS-J, S-WY, H-LH, MC, M-CL, C-CY, C-KW, and T-YT: final approval of manuscript. All authors contributed to the article and approved the submitted version.


Besides, other tumors, including breast cancer, have been shown to express somatostatin receptors. In this case, we presented a 63-year-old woman who underwent both 18F-FDG and 68Ga-DOTATATE PET/CT due to a rectal polyp. An endoscopic excision biopsy confirmed metastatic carcinoma of suspected breast origin, but subsequent ultrasound and MRI showed no signs of malignancy in the breast and adnexa uteri. PET/CT showed obvious 68Ga-DOTATATE activity in bilateral axillary and right inguinal lymph nodes with mild 18F-FDG uptake. Final histopathology at the left axillary, right inguinal lymph nodes, and rectum indicated metastases from breast cancer while the origin remained radiologically occult. Additionally, one uterine fibroids was found with positive uptake of 68Ga-DOTATATE and negative uptake of 18F-FDG. This case suggested that 68Ga-DOTATAE PET/CT may be an effective supplement in diagnosing OBC lymph node metastases with mild 18F-FDG uptake, and it may provide a new technology for the clinical diagnosis of occult breast cancer.Occult breast cancer is an uncommon type of breast cancer and its diagnosis is challenging. It is usually invisible on multiple imaging examines. Metastases to the rectum and inguinal lymph nodes from occult breast lobular cancer are even rarer.  Occult breast cancer (OBC) is described as an axillary metastatic carcinoma without detection of a primary breast lesion, which is uncommon . The inc18F-FDG PET/CT has been used in occult breast cancer, however, there are few case reports about that. Meanwhile, the imaging examination described above remains limited.Research on imaging examination for detecting the occult breast cancer has been ongoing. The American College of Radiology recommends the use of MRI in OBC patients who do not have evidence of a primary breast lesion on the traditional radiological examination like mammogram and ultrasound . In a co18F-FDG and 68Ga-DOTATATE PET/CT, and enlarged lymph nodes with obvious 68Ga-DOTATATE activity and mild 18F-FDG uptake were shown at bilateral axilla and right inguinal area. It suggested that 68Ga-DOTATAE PET/CT might be an effective method for the diagnosis of occult breast cancer.In our case, we described one case of occult breast cancer with rectum metastases who underwent both We present a case of a 63-year-old woman with a history of rectal polypectomy confirmed metastatic carcinoma for 2 months during a physical examination. Further immunohistochemical results showed that the estrogen receptor (ER), progesterone receptor (PR), and GATA Binding Protein 3 (GATA3) expression was positive, suggesting that the primary tumor may be from the female reproductive system, especially from the breast. However, the ultrasound and MRI showed no signs of malignancy in the breast and adnexa uteri, and multiple enlarged lymph nodes in the bilateral axilla and right inguinal area.18F-FDG PET/CT was performed for an unknown primary origin   . AnotherFDG-avid . About 5t tumors –17. Howe68Ga-DOTATAE PET/CT is as useful in the diagnosis of the origin of OBC as it is in the detection of OBC metastatic lesions.One previous study suggested that occult breast cancer may originate from ectopic breast tissue presented in axillary lymph nodes, and emphasized that the immunohistochemical subtype in OBC comprised various types similar to primary breast cancer . In our 68Ga-DOTATATE-avid lesion located in the uterus was found to be uterine fibroids by further ultrasound examination, corroborating the finding of a recent case report  for the publication of any potentially identifiable images or data included in this article.TH, RZ, JH, BW and ZZ: manuscript writing. LL and YZ: pathological review. TH, RZ, BZ, SH, ZZ, and PH: manuscript revision. All authors contributed to the article and approved the submitted version.


Triple negative breast cancer (TNBC) is an aggressive subtype of invasive breast cancer that disproportionately affects Black women and contributes to racial disparities in breast cancer mortality. Prior research has suggested that neighborhood effects may contribute to this disparity beyond individual risk factors.p-values < 0.05 were significant. Additional analyses examined area-level differences in exposure to metabolic risk factors, including unhealthy alcohol use and obesity.The sample included a cohort of 3316 breast cancer cases diagnosed between 2012 and 2020 in New Castle County, Delaware, a geographic region of the US with elevated rates of TNBC. Multilevel methods and geospatial mapping evaluated whether the race, income, and race/income versions of the neighborhood Index of Concentration at the Extremes (ICE) metric could efficiently identify census tracts (CT) with higher odds of TNBC relative to other forms of invasive breast cancer. Odds ratios (OR) and 95% confidence intervals (CI) were reported; The ICE-Race, -Income-, and Race/Income metrics were each associated with greater census tract odds of TNBC on a bivariate basis. However, only ICE-Race was significantly associated with higher odds of TNBC after adjustment for patient-level age and race , providing support for neighborhood effects. Higher counts of alcohol and fast-food retailers, and correspondingly higher rates of unhealthy alcohol use and obesity, were observed in CTs that were classified into the most disadvantaged ICE-Race quintile and had the highest odds of TNBC.The use of ICE can facilitate the monitoring of cancer inequities and advance the study of racial disparities in breast cancer.The online version contains supplementary material available at 10.1186/s13058-022-01533-z. Breast cancer mortality rates are 40% higher for Black than White women in the US  despite similar incidence rates  . HoweverBRCA1, BRCA2) factors [The neighborhood context is particularly relevant in the context of triple negative breast cancer (TNBC). TNBC is an aggressive subtype of invasive breast cancer with twice the incidence rates for Black relative to White women , 12. Com factors , 13, 14. factors –17. Furt factors causal architecture framework, neighborhood effects can be conceptualized as a system of exposure that contributes to variations in TNBC risk across residentially segregated populations [Viewed through a ulations , 20. In ulations . For exaulations New approaches are needed to efficiently identify systems of exposure that account for racial disparities in TNBC. Toward that end, the primary objective of this study was to test whether the Index of Concentration at the Extremes (ICE) metric could identify neighborhood-level systems of exposure associated with risk for TNBC in New Castle County, Delaware. Analyses were focused on this geographic region because Delaware has among the highest TNBC incidence rates in the US , with moThe secondary objective of this study was to test for cross-level interactions between patient-level race and the ICE-Race metric. Prior findings that have suggested Black women living in low-SES but predominantly White neighborhoods experienced a greater risk of TNBC relative to Black women in low-SES predominantly Black neighborhoods . We hypoThe tertiary objective of this study was to conduct a sensitivity check on the utility of the ICE metrics to efficiently identify neighborhoods with systems of exposure relevant to breast cancer risk. Specifically, we evaluated whether the ICE metrics were associated with metabolic risk factors, including census tract measures of alcohol and fast-food retailers, unhealthy alcohol use, and obesity. While alcohol is an established risk factor for certain breast cancer subtypes , its linPatient records came from the Helen F. Graham Cancer Center and Research Institute (HFGCCRI) cancer registry, a part of the Christiana Care Health System and based in New Castle County, Delaware. The HFGCCRI provides care to an average of more than 600 breast cancer cases annually. As detailed elsewhere, the HFGCCRI breast cancer population accounts for 85% of all cases from the surrounding county and are representative of the county population of cases in terms of age, race, receptor status, and stage .n = 776) or White (n = 2540), regardless of ethnicity. The time frame was selected to maximize the number of breast cancer cases where the subtype markers necessary for classifying patients with TNBC were routinely documented in the cancer registry. Patient residential address, demographic, insurance payer, and clinical data were abstracted from the registry. Patient addresses were manually cleaned and geocoded using ArcGIS 10.8 [This study population consisted of 3316 adult female New Castle County residents who were diagnosed with invasive breast cancer between the years of 2012 and 2020. To better understand Black–White disparities, the population was limited to women who self-reported as either Black  was used as a proxy for access to health care and socioeconomic status . ClinicaAi is the number of advantaged persons in a census tract, Di is the number of disadvantaged persons in a census tract, and Ti is the total population in the census tract i. For ICE-Income, advantaged and disadvantaged were defined as households with income ≥ $125,000 or < $20,000. For ICE-Race, advantaged and disadvantaged were defined as non-Hispanic White and non-Hispanic Black. For ICE-Race/Income, advantaged and disadvantaged were defined as non-Hispanic White households with income ≥ $125,000 and non-Hispanic Black households with income < $20,000. ICE values for geographic units range from − 1, indicating that 100% of the population can be classified into the most disadvantaged group, to + 1, indicating that 100% of the population can be classified into the most advantaged group. All ICE measures were classified into quintiles based on their distribution within New Castle County, setting Q5 (most advantaged) as the reference group.New Castle County is subdivided into 130 census tracts, which provide stable geographic units for reporting population statistics . All cenDiagnostic and Statistical Manual of Mental Disorders (5th edition) [Area-level measures were used to estimate the potential impact of environmental or neighborhood factors on rates of obesity and unhealthy alcohol use, similar to the conceptualization of ‘obesogenic’ environments . Census edition)  criteriaN = 221, alcohol retailer N = 160).Census tract measures of fast-food restaurants and alcohol retailers in New Castle County were produced from commercial data and publicly available records. Fast-food retailer data were obtained from SICCODE.com, utilizing the North American Industry Classification System (NAICS) code 722513,  consistep-values, were used to compare TNBC versus Non-TNBC patient groups by the sociodemographic, clinical, and ICE variables derived from patient and census tract measures.Spatial data management and statistical analyses were performed in the R Statistical Computing Environment using various packages –63. DescMultilevel logistic regression models were used to examine the odds of TNBC (vs. Non-TNBC) before and after adjusting for patient (level-1) and census tract (level-2) variables. The multilevel logistic regression model included a census tract-level random effect to account for the clustering of patients within tracts. Patient-level variables included age at diagnosis, race , and insurance . Tract-level variables included the ICE-Race, -Income, and -Race/Income quintiles.p-values less than 0.05 were significant.Three univariate and multivariate models tested each ICE measure separately, with all models adjusting for patient-level age at diagnosis and race. Additional multivariate models tested cross-level interactions between patient-level race and tract-level ICE quintiles. Based on the results of these models, details of which are provided in the results, multivariate logistic regression models were stratified by Black and White race to examine differential effects of tract-level ICE-Race on odds of TNBC after adjustment for age of diagnosis. Odds ratios and 95% confidence intervals were reported; The spatial covariation of TNBC and ICE measures were visualized using bivariate choropleth maps. First, breast cancer patients were aggregated to their census tract of residence to create tract-level measures of the percentage of patients with TNBC. The % TNBC and ICE values were separated into quintiles based on their respective tract-level distributions within New Castle County. For the ICE measures, quintiles were coded such that lower ICE values (representing greater disadvantage) correspond to higher quintiles representing greater relative disadvantage. The quintiles of % TNBC and ICE were combined to create 5 × 5 classification systems that denote whether census tracts are relatively low, moderate, or high in each value. The resulting 25 classification values were symbolized using color and saturation to simultaneously show variation in both measures. For ease of visualization, only the highest/lowest quintile extremes of the classification system  were colored in the maps. Geocoding and final map preparations were conducted in ArcMap 10.8 .To begin to characterize place-based systems of exposure related to metabolic risk factors for TNBC, descriptive tables were created where census tracts were classified according to their quintiles of TNBC and ICE-Race  that were visualized in the bivariate choropleth map. Population data from the American Community Survey were used to describe race, poverty, and education levels for the census tract groups . Tract-lTNBC cases accounted for 14% of the invasive breast cancer cases in the study population (Table See Table p = 0.014), which was reduced and became non-significant in most models once covariates were included  were tested. For both ICE-Income and ICE-Race/Income, the fixed effects only and mixed effects models produced similar coefficient results with no change in inference. However, the ICE-Race mixed effects model resulted in a singular fit and coefficients could not be estimated. This was likely due to insufficient between tract variation to support estimation of a tract-level random effect. With no covariates in the model, the variance of the random effect (measuring between-tract variance) was significant but small . Quintiles Q1–Q4 of ICE-Race (corresponding to greater disadvantage relative to Q5) were associated with significantly higher odds of TNBC, even after adjustment for patient-level race and age of diagnosis, ranging from Q1 (AOR: 2.09) to Q4 (AOR: 1.76). Neither ICE-Income nor ICE-Race/Income quintiles were significantly associated with TNBC after covariate adjustment, though their adjusted odds ratios suggested positive associations with TNBC. No significant interactions were observed in models that included cross-level interaction terms between patient-level race and tract-level ICE . The magnitude of the adjusted odds ratios suggested a positive association, which the relatively small Black patient sample (N = 776) may be underpowered to detect. ICE-Income and -Race/Income quintiles were also not associated with TNBC for Black patients . Among White patients, ICE-Race quintiles Q1, Q2, and Q4 were associated with significantly greater odds of TNBC . This result would suggest that White women living in predominantly Black census tracts were more likely to be diagnosed with TNBC, relative to other forms of invasive breast cancer, compared to White women living in predominantly White census tracts. For ICE-Income, only quintile Q2 was significantly associated with TNBC , with a non-significant trend in the expected direction observed for Q1 . This would suggest that White women living in low-income census tracts are at an elevated risk for TNBC, relative to other forms of invasive breast cancer among White women living in higher-income census tracts. No significant associations with TNBC were observed for ICE-Race/Income among White women.The multilevel fixed-effects only model of age and ICE-Race was stratified by patient-level race to further characterize the relationship between patient race, area-level segregation, and TNBC Table . IncreasFigure The tract classifications based on quintiles of TNBC prevalence and ICE-Race appear to differentiate the affected populations and area-level systems of exposure Table . As expeIn a cohort of breast cancer patients from New Castle County, Delaware, a geographic area with among the highest rates of TNBC in the US, we tested whether different versions of the ICE metric could efficiently identify census tracts with greater odds of TNBC relative to other invasive subtypes of breast cancer. Consistent with prior epidemiological findings , women wBy including both patient- and census tract-level measures of race, our results help to clarify the extent to which the higher rates of TNBC observed in predominantly Black neighborhoods can be attributed to compositional or contextual effects. That is, if the relationship between ICE-Race and census tract odds of TNBC became nonsignificant when adjusting for patient-level race, we might infer that the apparent neighborhood effects were likely an artifact of the neighborhood composition. By contrast, our results suggest that the relationship between TNBC and area-level measures of race are a function of both composition and context. Stated differently, compared to predominantly White neighborhoods, predominantly Black neighborhoods may differ in some important ways that have relevance for TNBC risk. This interpretation is bolstered by the multilevel results stratified by patient-level race, which showed that White patients who lived in predominantly Black census tracts were also at greater odds of TNBC than White patients living in predominantly White census tracts.These results are in partial disagreement with the findings from two prior studies, which found higher odds of TNBC for Black women living in lower-SES, predominantly White neighborhoods , 64. TheThis study was limited by its single-site, cross-sectional design. Findings may not be generalizable to populations from other geographic areas. Nevertheless, given the notably elevated rates of TNBC in Delaware, the results of this study can help to inform local cancer control and prevention efforts while providing a methodological proof of concept that can be replicated for other geographic areas. Without patient residential histories, it is unclear to what degree prior neighborhood exposures may have been associated with TNBC risk. Furthermore, while we did have access to patient-level measures of race and insurance status, we did not have patient-level measures of other relevant exposures  and were not able to determine ethnicity (Hispanic vs. non-Hispanic) at the patient level. Further, we limited our investigation of neighborhood to include ICE measures, given there is no standard set of measures used to measure neighborhood deprivation. It is possible other socioeconomic indices  could also provide additional insights into the impact of neighborhood on TNBC . Future This study provides preliminary evidence to suggest that the ICE-Race metric can efficiently identify census tracts with higher odds of TNBC due to both compositional and contextual effects. Preliminary evidence also suggests that the contextual effects may be driven, at least in part, by potentially modifiable metabolic exposures, such as alcohol use and obesity. Krieger and colleagues have called for including ICE metrics in cancer registries to facilitate the monitoring of cancer inequities . Going fAdditional file 1: Tables S1. Variance of census tract random effect for breast cancer subtype (triple negative breast cancer vs. not), before and after covariate adjustment. Table S2. Comparison of fixed- and mixed-effects models for odds of triple negative breast cancer by age and census tract race-, income-, and race/income ICE. Table S3. Odds of triple negative breast cancer by race and census tract ICE interactions. Table S4. Census tract characteristics by TNBC prevalence and income-ICE quintiles. Table S5. Census tract characteristics by TNBC prevalence and ICE-Race/Income quintiles.Additional file 2: Figure S1. Retail exposures and comorbidity prevalence by ICE quintiles, New Castle County, DE. Shows place-based systems of exposure related to metabolic risk factors for triple negative breast cancer (TNBC) by census tract ICE quintiles in New Castle County, DE. Alcohol retailers (A) and alcohol use disorder prevalence (C) show a graded relationship with ICE, with both measures highest in tracts classified as Q1 (greatest ICE-measured disadvantage). Fast-food retailers (B) are most prevalent in Q3–Q4 ICE tracts, while obesity prevalence (D) varies little by ICE. All measures show similar variation by race-, income-, and race/income-ICE.