Systemic inflammation measured by the acute-phase protein CRP associates with poor outcome across cancer types. In contrast, local tumor-associated inflammation, primarily evaluated by T-lymphocytes, correlates with favorable prognosis. Yet, little is known whether these two responses are related or opposing processes and why elevated CRP in relation to cancer is detrimental for clinical outcome. As proof of concept, we developed a platform combining multiplexed IHC and digital imaging, enabling a virtual readout of both lymphoid and myeloid immune markers and their spatial patterns in the primary tumors of resected stage II and III colon cancer (CC) patients with and without accompanying systemic inflammation. Twenty-one patients with elevated CRP (>30 mg/l) and 15 patients with low CRP (<10 mg/l) were included in the analyses. Whole slides from the primary tumors were stained for markers of adaptive  and innate  immunity and the immune checkpoint molecule PD-L1. Associations between individual immune markers, preoperative CRP values, mismatch repair status (MMR), and risk of recurrence or death were assessed. Unsupervised hierarchical clustering was used to explore whether distinct immune phenotypes were present. Tumors from systemically inflamed patients (CRP >30 mg/l) displayed significantly more myeloid features in terms of higher densities of CD66b+neutrophils (p = 0.001) and CD68+macrophages (p = 0.04) and less lymphoid features  regardless of MMR status. Additionally, systemically inflamed patients harbored lower mean distances between neutrophils and tumor cells within the TME. Intriguingly, microsatellite instable (MSI) tumor status correlated with systemic inflammation. However, using a combinatorial approach, we found that regardless of an adaptive composite score (compounded CD4+ and CD8+ T cells), a high innate score (CD66b+ neutrophils and CD68+ macrophages) associated significantly with elevated CRP. In conclusion, tumor-associated systemic inflammation correlated with a myeloid-dominated TME in a small cohort of resectable CC patients. Our data highlight the importance of a comprehensive immune classification of tumors including players of innate immunity and support a role for CRP as an informative biomarker of the immune response taking place at the tumor site. SIR, as evidenced by circulating biomarkers such as the acute-phase protein C-reactive protein (CRP), has consistently been correlated with poor prognosis in many cancer types, including colon cancer -based platform combining chromogenic IHC staining with digital whole-slide imaging enabling simultaneous detection of six different lymphoid and myeloid immune cells in addition to the immune checkpoint molecule PD-L1. Using this platform, we were able to characterize the immune landscape and assess spatial relationships in the TME of the primary tumors. We further extended the application by combining the mIHC data with clinical information to investigate whether SIR and local tumor-associated inflammation are related processes and explore the hypothesis that SIR correlates with a myeloid-driven immune landscape in colon cancer patients.Forty-three stage II and III colon cancer patients, consisting of 20 patients with CRP < 10 and 23 patients with CRP > 30 treated at Sørlandet Hospital, Kristiansand, Norway, were selected from a prospective local colorectal cancer database covering extensive clinical information and follow-up data. The choice of CRP values was based on previous work using identical CRP thresholds  tumor tissues from the primary tumors were retrieved from the Department of Pathology, Sørlandet Hospital. Representative tumor blocks containing areas of both the invasive margin (IM) and tumor center (TC) were selected by a trained pathologist (MBN).The study was conducted according to approvals from the Regional Ethics Committee.FFPE colon cancer blocks were cut into 3 mm thick sections and prepared for the IHC-staining protocol. All staining procedures were performed on the Ventana Discovery Ultra autostainer .First, tissue sections were deparaffinized using xylene and rehydrated with ethanol followed by heat-induced antigen retrieval and blocking endogenous peroxidase activity. Then, mIHC with two different panels of antibodies were applied on two serial tumor sections. The first panel consisted of a 5-plex termed the adaptive or lymphoid immune profile with primary antibodies against CD8 (cytotoxic T lymphocytes), CD4 (T-helper cells), foxp3 (regulatory T cells), CD20 (B lymphocytes), and pan-cytokeratin (pan-CK) as an epithelial tumor marker. The second IHC panel, a 4-plex termed the innate or myeloid immune profile, consisted of antibodies against CD68 (pan-macrophages), CD66b (neutrophils), pan-CK, and finally PD-L1. The multiplex staining process consisted of sequential staining rounds with primary and secondary antibodies . Image analysis was performed using Visiopharm Integrator System software version 2019.02 .As shown in The two IHC-stained tumor sections and the hematoxylin-counterstained slide were scanned separately. Tumor slides were then digitally superimposed using an automated approach, but controlled and optimized manually, with the net effect of a single virtual slide capturing all seven immunostained markers with preserved tissue architecture.Digital analysis was performed using applications within the software particularly developed for this material. For segmentation, we used a Bayesian classifier followed by different post-processing steps  for optimizing the results. The preprocessed images in adaptive stains were based on color deconvolution of the chromogens DAB and silver in addition to features of the RGB color model. In innate stains, RGB and HSI models were utilized. The software-based classification of the immunostained markers was performed by assigning different pseudo-colors, enabling a visual output of the various immune markers within the tissue. Areas with mucin, artifacts, or tissue folds were manually excluded from the analysis.Immune cell densities were estimated as area of positively stained cells per region of interest (ROI) in percent quantifying cells at the IM and TC separately. Immune cells were classified as either intra-tumoral (IT) if they were directly infiltrating the tumor nests or stromal (S) if they were located within the stromal spaces. In addition, we calculated two forms of a composite score: one with the sum of IT and S immune cells divided by the total area of the ROI of interest, and one where the area of tumor tissue was subtracted to adjust for differences in total amount of tumor tissue which potentially could dilute the true immune cell estimate. PD-L1 expression on tumor cells and immune cells (primarily CD68+ macrophages) was assessed separately. Composite lymphoid and myeloid immune scores were estimated by compounding the densities of CD8+ and CD4+ T cells for the lymphoid score and CD68+ macrophages  and CD66b+ neutrophils for the myeloid score and categorized as high or low based upon the median value of the respective compounded scores.Using pan-CK in the mIHC panels, distances between tumor- and immune cells of interest could be estimated enabling spatial characterizations. Two different types of spatial analysis were performed: 1) proximity analysis estimating the density of immune cells of interest within the defined distance of 20 micron around the tumor islets and 2) nearest neighbor analysis calculating the average distance between immune cells of interest and nearest tumor cell.The tumor–stroma ratio was calculated by dividing the stromal area of the IM and TC by the total area of the two tumor compartments.Assessment of mismatch repair (MMR status) was performed by IHC evaluation of MHL1, MSH2, MSH6, and PMS2 protein expression. Tumors that were negative in one or more of the four stainings or inconsistent with IHC were verified with the Idylla MSI test, which is a fast-track PCR-based assay for determining microsatellite status in colorectal cancer .Differences in clinicopathological data between CRP-high and -low patients were evaluated by Fisher’s exact test and the two-sample t-test. Immune markers were analyzed on the logarithmic scale to obtain a normal distribution. Associations between immune markers, CRP, and survival were analyzed by Fisher’s exact test. Pearson’s correlations were used to analyze the correlation between individual immune markers. Medians and means were compared using the Kruskal–Wallis test and the one-way ANOVA-test, respectively. The Aalen–Johansen method was used to estimate the risk of recurrence or death by colon cancer, adjusting for death of other causes as competing risk, and compared between CRP groups using the log-rank test. For estimating the lymphoid and myeloid composite scores, data were log-transformed and standardized before summing the score of the respective immune markers (CD8+/CD4+ T cells and CD68+ macrophages/CD66b+ neutrophils). To define subgroups in our cohort, unsupervised hierarchical clustering was performed. Heat maps and hierarchical clusters were generated in R studio version 4.0 based on the logarithmic scale of the immune markers standardized to mean zero and variance 1. Two-sided p-values < 0.05 were considered statistically significant for all analyses. Statistical analysis was performed using STATA software version 16.A total of 36 stage II and III colon cancer patients were finally included in this study. Excluded patients (n= 7) were due to compromised tumor tissue quality, weak IHC staining, or other technical issues with the multiplex assays. Patient and tumor characteristics are listed in vs. 72%, respectively, p = 0.11).Different patterns of immune infiltration both between and within tumors were present in our cohort. Representative images are shown in With the notable exception of CD66b+ neutrophils, all other immune cells were more prominent at the IM than in the TC with CD68+ macrophages and CD4+ T lymphocytes being the most abundant types of immune cells  and high CD68+ macrophages (p=0.04 at the TC) remained significantly associated with elevated CRP in the univariate analysis, as shown in Despite the relatively low number of events in our cohort, survival analyses were performed, as shown in We hypothesized that a combinatorial approach based on the expression of two or more immune markers rather than single-cell analysis better could elucidate potential correlations between distinct immune phenotypes and systemic inflammation. For that purpose, densities of CD4+ and CD8+ T- lymphocytes (termed the adaptive composite score) and CD68+ macrophages and CD66b+ neutrophils (termed the innate composite scores) were compounded and categorized as high or low based on the median of the combined scores. Interestingly, we found that regardless of the adaptive score, tumors with a high innate score had increased risk of elevated CRP . Moreover, there was a tendency toward lower mean distance between neutrophils and tumor cells in the systemically inflamed patients. We found no significant differences in the spatial distribution of CD8+ lymphocytes between CRP-high and -low tumors. Based on the proof-of-concept approach of the study, further spatial analyses were not performed on this material.Given the assumption that the combined information on both the precise localization and density of immune cells reflects cell functionality and potential interactions taking place within the TME, we investigated the spatial distribution of CD8+ lymphocytes and CD66b+ neutrophils in CRP-high and -low patients. As shown in In this study, we explored the tumor-immune microenvironment in colon cancer patients related to the presence of SIR, covering important players of both adaptive and innate immunity and their spatial distribution within the primary tumors. By analyzing the immune contexture in patients with and without accompanying SIR, we revealed upregulation of myeloid features in the TME from systemically inflamed patients. Specifically, and in line with our hypothesis, tumor-infiltrating neutrophils and macrophages associated with systemic inflammation. Most strikingly, we found that regardless of an adaptive composite score (compounded CD4+ and CD8+ T cells), a high innate score (compounded CD66b+ neutrophils and CD68+ macrophages) significantly increased the risk of elevated CRP, indicating that it is the presence of a myeloid-inflamed and not the absence of a lymphoid-inflamed TME that associates with systemic inflammation.A strong impact of myeloid cells has also been demonstrated in a squamous head and neck cancer cohort revealing differential immune profiles, representing either lymphoid-, myeloid-, or hypo-inflamed tumors, where myeloid-enriched tumors associated with the shortest overall survival regardless of HPV status . AdditioThese results combined with the findings of our study highlight the strong role myeloid cells may play in the TME by creating an immunosuppressive state and even outperform the potential beneficial role of lymphoid cells and negatively affect prognosis. Although myeloid cells have been associated with poor survival and treatment outcome in several cancer types –24, theiIt is particularly interesting to see what happens under circumstances of chronic wounding, which might be analogous to the situation of the colon where tumors can arise in relation to a chronically inflamed and often injured epithelium . Using aAltogether, these exciting findings support the notion that neutrophils may fuel and shape tumors and highlight innate immune cells as a therapeutic target for immunotherapeutic approaches .By far, local and systemic tumor-associated inflammations have been regarded as separate processes with only few studies investigating their possible interrelationship –38. SimiAn intriguing and initially surprising finding of our study was the significant association between positive MSI status and systemic inflammation. Given the good prognosis related to MSI in early-stage colon cancer and the poor prognosis related to the SIR, one might rather expect an inverse or no association between the two entities. Nevertheless, we found that MSI CRP-high tumors not only were hyper-inflamed in terms of considerable lymphoid inflammation that previously has been shown to accompany MSI-positive tumors, but also were highly infiltrated by myeloid immune cells, particularly neutrophils. Moreover, MSI-high tumors exhibited upregulation of PD-L1, predominantly expressed by myeloid immune cells infiltrating the tumor stroma and to a lesser extent by the tumor cells themselves. This observation stands in contrast to other tumor types such as lung, bladder, and kidney cancer, where tumor PD-L1 expression is a common feature . HoweverIn an effort to decipher the complex TME and variable treatment outcomes to immunotherapy, emerging studies take into context the spatial aspect of the tumor immune landscape , 43, 44.Our study has several limitations. Due to the proof-of concept design, it covers a limited patient series. Thus, our findings need to be tested in a larger dataset before biologic conclusions can be drawn. We plan to enrich the cohort for confirmation and further analyses to expand our understanding of how systemic inflammation and localized tumor-associated inflammation influence each other. Another limitation owing to the IHC itself is the challenge of characterizing functional phenotypes. Myeloid cells exhibit a high degree of plasticity displaying a continuum of polarization states being more or less immuno-suppressive or stimulatory. This dynamic diversity is difficult to capture with IHC antibodies directed toward one or two fixed cell markers . AlthougTaken together, our data highlight the importance of a broader and more comprehensive immune characterization of tumors covering both lymphoid and myeloid cell populations. The concept of hot and cold tumors, categorizing tumors based on the infiltration of T cells, has been widely used to inform patient prognosis and predict immunotherapeutic efficacy . Within In conclusion, we herein provide a framework for expanding our understanding of the immune landscape in CC and explore the role of CRP as a systemic and informative biomarker of the immune responses taking place at the tumor site. Further deciphering distinct immune phenotypes and spatial features that associate with systemic inflammation may improve our understanding of inherent immune responses in CC and hold critical implications for therapeutic approaches.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Regional Committees for Medical and Health Research Ethics (REC) South East. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. AK, the first author, has performed lab work, planned and performed digital analyses, participated in statistics together with EP, written the draft for the manuscript, and driven the scientific discussions. PN assisted in performing, optimizing, and interpreting digital imaging. JG planned and performed laboratory work. MN reviewed and annotated tumor regions from FFPE tissue blocks and evaluated the MMR IHC-analysis. TS and CK participated in methodological and scientific discussions and had the main ideas behind the study. All authors have reviewed and commented the manuscript during the process and before submission. 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.


In drug trials, adverse events (AEs) burden can induce treatment non-adherence or discontinuation. The non-adherence and discontinuation induce selection bias, affecting drug safety interpretation. Nested case-control (NCC) study can efficiently quantify the impact of the AEs, although choice of sampling approach is challenging. We investigated whether NCC study with incidence density sampling is more efficient than NCC with path sampling under conditional logistic or weighted Cox models in assessing the effect of AEs on treatment non-adherence and participation in preventive antimalarial drug during pregnancy trial.Using data from a trial of medication to prevent malaria in pregnancy that randomized 600 women to receive chloroquine or sulfadoxine-pyrimethamine during pregnancy, we conducted a NCC study assessing the role of prospectively collected AEs, as exposure of interest, on treatment non-adherence and study non-completion. We compared estimates from NCC study with incidence density against those from NCC with path sampling under conditional logistic and weighted Cox models.Out of 599 women with the outcomes of interest, 474 (79%) experienced at least one AE before delivery. For conditional logistic model, the hazard ratio for the effect of AE occurrence on treatment non-adherence was 0.70  under incidence density sampling and 0.68  for path sampling. For study non-completion, the hazard ratio was 1.02  under incidence density sampling and 0.85  under path sampling. We obtained similar hazard ratios and standard errors under incidence density sampling and path sampling whether weighted Cox or conditional logistic models were used.NCC with incidence density sampling and NCC with path sampling are practically similar in efficiency whether conditional logistic or weighted Cox analytical methods although path sampling uses more unique controls to achieve the similar estimates.NCT01443130.ClinicalTrials.gov:  Treatment non-adherence and treatment discontinuation, in which patients either do not take their medication as prescribed or do not take it at all, is a challenge in analysis and interpretation of randomized controlled trials results since it can lead to underestimation of treatment effects . Adverseti in time interval  and exited after time tj in time interval . Under this second sampling approach the specified number of controls are randomly sampled from the path set without replacement until all the controls in that path set are selected and the path set can be replenished. Once the desired number of controls is achieved the path sampling is stopped. As defined elsewhere, in this paper we refer to this variation of nested case-control with incidence density sampling design as nested case-control study with path sampling design ) or median (inter-quartile range [IQR]) and proportion for categorical variables. We also summarized the distribution of AE occurrence within respective treatment arms based on AE grade and frequency. We plotted Kaplan Meier graph to characterise time to first AE occurrence between the IPTp arms.β be Lncc(β). Traditionally, estimates in nested case-control studies are derived by maximizing partial likelihood function that can be written asLet likelihood for the nested case-control for parameter Lncc(β) is likelihood for nested case-control for parameter β. The β represents a vector of the regression coefficients, such that β′ is a transposed vector corresponding to vector(s) of covariates. The XiXand j are the vectors of covariates for the individuals i and j. The sampled risk set Ȓi consists of case i and sampled m controls matched to the case on given time t since enrolment. The Ω represents the set of all the cases. The conditional likelihood under logistic regression coincides with Cox regression partial likelihood [ś (see the equationM2below)). The baseline hazard for the stratum at follow-up time t was considered as h0ś(t).Where kelihood . Therefoβ is similar to As already defined, the partial likelihood that is maximized to obtain the estimate for the regression coefficient M3, Ri is a set of all patients who have not failed or been censored but are at risk of failure at that time . The traditional analysis above, under M1 uses only the information from the sampled cases and controls such that the nested case-control study can sometimes be considered as a biased sample from the cohort. Weighting the partial likelihood with the inverse of the inclusion probability of being sampled mitigates this problem. The weighted Cox model partial likelihood can be written asHere under Si is the set of cases and controls in the nested case-control sample who are at risk at time ti. The Cox model obtained from the maximizing this likelihood (with inverse probability weights) to estimate the coefficient is defined as weighted Cox regression model. The weights were defined as pj is probability of a woman being in the nested case-control sample. The pj = 1 for all the cases. In this paper, we used Kaplan Meier (KM) method inclusion probabilities. Inclusion probabilities defined by KM method are called design based since they estimate actual sampling of the controls [Where controls . The R pcontrols , was useWe considered both conditional logistic model and weighted Cox model in our analysis. Overall, we fitted both the conditional logistic model (conditioned on risk sets) and weighted Cox regression to both the nested case-control sample with incidence density sampling and then to the nested case-control sample with path sampling This was done separately for non-adherence and study non-completion outcomes.In building each model, Firstly, we fitted univariate models to assess the unadjusted effects of the covariates. Then we fitted multivariable model that included the AE exposure and IPTp treatment adjusted for similar set of confounders that were significant in the univariate analysis at 0.25. Using the likelihood ratio test, we also assessed whether inclusion of interaction between the AE occurrence and treatment arm modified the observed effect. All the point estimates from the fitted models are presented with their respective 95% confidence interval. The interpretation of all the final models was made at 0.05 significance level.The cohort where our nested case-control sample designs were derived considered 599 women who were assigned to the two arms of the trial. The women in the cohort had a median follow-up time of 116 days . At enrolment, these women had a mean gestational age of 22.1 (SD = 2.1) weeks and a mean haemoglobin concentration of 11.7 (SD = 1.3) g/dL . A totalFor the study non-completion outcome, 64 (10.7%) women did not complete the study, with 37 (12.3%) in the IPTp-SP arm and 27(9.0%) in the IPTp-CQ arm. Based on the matching criteria defined in the methods section (matching each case to four controls), we found a total of 256 study non-completion controls. For the treatment non-adherence outcome, 106 (17.7%) women were non-adherent to trial medication, at least once during study follow-up, with 40(13.3%) in the IPTp-SP arm and 66 (22%) in the IPTp-CQ arm. After each incident case was matched to four controls, we yielded a total of 424 treatment non-adherence controls. These reported results of matching were obtained separately for the nested case-control with incidence density sampling and the nested case-control with path sampling.We report the hazard ratio (HR) estimates on exponentiated scale , in Tables We observed no statistically significant effect of AE occurrence on treatment non-adherence under both incidence density sampling and path sampling regardless of the method of analysis used. Using conditional logistic regression, the effect of AE occurrence on treatment non-adherence hazard ratio was 0.70  under incidence density sampling and under path sampling the hazard ratio was 0.68 . Using the weighted Cox regression, we observed a negligible departure from the overall trend where the path sampling yielded a slightly higher estimate of hazard ratio , compared to the incidence density sampling . The negligible exception could be explained as one of the expected scenarios that can arise due to sampling variation.Similarly, we observed no effect of AE occurrence on study non-completion under both incidence density sampling and path sampling regardless of the method of analysis used see . Using cAmong the adjusted potential confounders for the treatment non-adherence outcome, only treatment was associated with treatment non-adherence . We obseIn this study, we empirically compared the efficiency of incidence density sampling and path sampling for nested case-control studies under conditional logistic regression and weighted Cox regression analysis methods. The practical application focussed on determining the impact of AEs on treatment non-adherence or discontinuation. Practically, we established that the standard errors and hazard ratios for the two designs were similar. However, it should be noted that path sampling (by design) is based on more unique controls selected  implyingThe negligible gain in efficiency of weighted Cox regression model over conditional regression can be attributed to the homogeneity of the cohort that we used. Since our cohort comes from a randomized clinical trial whose baseline characteristics are similar, breaking the match in order to use more controls could not add much information to our nested case-control sample that was already using over 50% of the cohort sample. Most of the substantial gains for the inverse probability weighting have been established under large sample properties , especiaFrom practical perspective, based on the example data that we used, this study did not establish a significant role of AEs on IPTp treatment non-adherence and study discontinuation. Neither, conditional logistic regression model nor the weighted Cox regression model under incidence density sampling or path sampling suggested that AE occurrence impacted treatment non-adherence or study non-completion. Our findings are contrary to the hypothesized direction of AEs effect where we postulated that AE occurrence increases the risk of IPTp non-adherence and IPTp trial discontinuation. However, our findings support what has been previously observed in IPTp context whereby frequent adverse events do not reduce adherence . Our expWe observed increased risk of treatment non-adherence for the women in IPT-CQ treatment arm who were two times more likely to non-adhere compared to those in IPTp-SP arm. This is expected since the women in IPTp-CQ arm had more opportunities for non-adherence as they took two more doses compared to those on IPTp-SP arm. This agrees with previous studies that indicate that number of doses for a given regimen is inversely associated with treatment non-adherence ; increasUse of the nested case-control study design in the context of clinical trial data provided a great opportunity to assess the temporal relationship of adverse events and adherence or study non-completion . This fuThis study had some limitations. Firstly, the differences in treatment by dose schedule between the treatment arms could affect the observed differences. Secondly, we did not collect data on patient satisfaction. This made it hard it to make a conclusive statement on the unexpected observed effect of the AEs. Since non-adherence can be affected by the patient behaviour, collection of such patient satisfaction and perception in clinical trials would be helpful in elucidating the effect of AEs on non-adherence. Furthermore, the methodological conclusions in this study can be improved and extended by undertaking a full simulation study to understand the performance of the sampling and analysis methods under varying known scenarios.Assessment of safety in relation to IPTp adherence, even for less severe AEs, is an important topic in developing solutions towards improved IPTp safety profile and risk management plan in clinical trials. Nested case-control study can be considered as a useful tool in investigating the impact of AEs on treatment non-adherence and study non-completion because it offers an opportunity for an efficient sample where cases and controls are comparable, accounting for potential differences in follow-up time. We empirically demonstrated that incidence density sampling and path sampling practically yield similar estimates whether one uses weighted Cox regression or conditional logistic regression. However, by design, path sampling yields those similar estimates at the expense of more unique controls sampled compared to the incidence density sampling. The clinical findings indicated that AE occurrence did not impact treatment non-adherence or study non-completion. The insights from this study inform future trial designs and drug safety assessment. Future extension of this work can consider evaluating the impact of AEs on treatment non-adherence and study non-adherence accounting for patient perception on IPTp benefits since treatment non-adherence is associated with patient behaviour.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.


In response to the urgent need for virtual mental health treatments during the COVID-19 pandemic, an 8-week group intervention deliverable over video or telephone was developed and disseminated in March 2020. Manual content addressed social isolation and information related to COVID-19. In August 2020, a national web-based provider feedback survey was disseminated to evaluate feasibility of the manual. Respondents (n = 21) across a variety of geriatric mental health clinics reported this intervention to be effective and clinically useful with their patients in providing social support and in mitigating COVID-19 anxieties. The majority of respondents delivered the group in multiple cohorts and found the manual adaptable beyond the early pandemic period.


Delayed start-of-care nursing visits in home health care (HHC) can result in negative outcomes, such as hospitalization. No previous studies have investigated why start-of-care HHC nursing visits are delayed, in part because most reasons for delayed visits are documented in free-text HHC nursing notes.The aims of this study were to (1) develop and test a natural language processing (NLP) algorithm that automatically identifies reasons for delayed visits in HHC free-text clinical notes and (2) describe reasons for delayed visits in a large patient sample.This study was conducted at the Visiting Nurse Service of New York (VNSNY). We examined data available at the VNSNY on all new episodes of care started in 2019 . An NLP algorithm was developed and tested to automatically identify and classify reasons for delayed visits.The performance of the NLP algorithm was 0.8, 0.75, and 0.77 for precision, recall, and F-score, respectively. A total of one-third of HHC episodes  had delayed start-of-care HHC nursing visits. The most prevalent identified category of reasons for delayed start-of-care nursing visits was no answer at the door or phone , followed by patient/family request to postpone or refuse some HHC services , and administrative or scheduling issues . In 40%  of HHC episodes, 2 or more reasons were documented.To avoid critical delays in start-of-care nursing visits, HHC organizations might examine and improve ways to effectively address the reasons for delayed visits, using effective interventions, such as educating patients or caregivers on the importance of a timely nursing visit and improving patients’ intake procedures. Over the last several decades in the United States, recognition has been growing of the importance of post–acute care settings, including long-term care hospitals, inpatient rehabilitation facilities, and skilled nursing facilities ,2. One sHHC consists of intermittent home visits conducted by skilled health care providers . Currently, over 6 million patients are admitted to more than 12,000 HHC agencies across the United States annually -9. DespiThe start-of-care nursing visit is one of the most critical steps of the HHC episode ,19. ThisThe CMS requires agencies to conduct a start-of-care visit within 48 hours of HHC referral or within 48 hours of the patient’s return home . HoweverNo previous study has investigated why start-of-care HHC nursing visits are delayed. One explanation may be that most delayed visit reasons are documented in free-text HHC nursing notes. Given a large volume of clinical notes , manual review is not feasible, calling for the use of data science methods.Fortunately, recent data science analytical techniques can extract insights from free-text documentation. Specifically, natural language processing (NLP) algorithms can be applied to large collections of clinical documents to identify a diverse range of concepts and extract meaning from documents . Often, An example of NLP algorithm use is the identification of social risk factors among patients discharged from hospitals using discharge summaries . The resIn HHC settings, previous applications of NLP focused on identifying patients who experienced falls , dementiThis study was conducted at Visiting Nurse Service of New York (VNSNY), the largest not-for-profit urban home care agency in the United States. The study research protocol was approved by the institutional review board of the VNSNY in October 2019.The study sample comprises all HHC patients admitted during the calendar year of 2019 following a hospitalization. The patients’ status of hospitalization prior to HHC was extracted from the M1000_3 variable on the Outcome and Assessment Information Set (OASIS), a patient-specific, standardized assessment required under Medicare HHC rules . The stuDates of hospital discharge and start-of-care HHC nursing visit were extracted from the OASIS. We calculated the difference in days between the following OASIS items: M1005: Inpatient Discharge Date and M0090: Date Assessment Completed. This study defined delayed start-of-care HHC nursing visits as visits conducted more than 2 days after hospital discharge. Approximately one-third  of episodes met this criterion.The electronic health record (EHR) had a standardized option that allowed HHC staff to document reasons for delayed visits. The standardized categories included no answer at the door or phone, administrative or scheduling issues, and patient/family request to postpone or refuse some HHC services.We extracted 118,767 clinical notes documented for HHC episodes with delayed visits. More than 1 note could be documented for an episode. There were 22 note types with the most common being narrative notes that included nursing and other HHC admission staff comments , initial welcome call notes that described the initial welcome telephone call to introduce HHC services to the patient , intake clinical comment notes that provided clinical details of the admitted patients , insurance and other additional information notes with information on patient insurance and additional clinical factors , telephone communication notes describing any phone contact between HHC staff and patients or family , and 17 other less frequent note categories .We developed an NLP algorithm using a regular expression technique  where alAs the first step of developing the NLP algorithm, the data preprocessing steps involved lowercasing, stripping (removing extra spaces), and removing special characters , ]). We did not remove stop words because they were important for identifying the reasons for delayed start-of-care. For example, negation indicators (such as no and not) or auxiliary words  were important for identifying if a patient requested to postpone the HHC services. We also did not perform lemmatization or stemming because keeping the original form of words, particularly the verbs, was important for identifying a pattern of late visit.As the second step of developing the NLP algorithm, we created regular expression rules to capture language describing patient or family requests to postpone HHC or refuse some HHC services. This included the following phrases: “pt declined VNS visit today,” “patient refused visit and asks for visit tomorrow,” “daughter asks to reschedule SOC for Friday.” These phrases have some word patterns, such as “patient/pt/family refused,” “asks for visit tomorrow,” and “reschedule SOC for Friday,” that were used to develop regular expression rules. To evaluate the accuracy of our NLP algorithm, we extracted 100 clinical notes from each of the 22 note types, resulting in 2200 clinical notes. Each note was reviewed independently by 3 HHC experts, who labeled the note with 1 or more of the 3 delayed start-of-care HHC nursing visit categories, where applicable. The experts included a PhD-prepared registered nurse, a social worker, and an experienced research analyst. There was a high level of initial interrater agreement between the experts (κ>0.8) . DisagreWe applied our NLP algorithm on the testing set and calculated the accuracy of NLP in identifying reasons for delayed visits. For each category of delayed visit reasons, we calculated the precision , recall , and F-score . These metrics vary between 0 and 100%, with higher values indicating better NLP algorithm concept identification performance; values above 75% indicate high performing NLP algorithms.The majority of patients admitted to VNSNY were aged over 65 years . Females comprised a larger fraction of the patient population compared to males. The proportion of non-Hispanic White patients was significantly higher than that of other races. Hypertension  was the most common disease among patients, followed by diabetes  and cancer . The majority of the patients  could receive support from their family members or their caregivers.The overall accuracy of NLP in detecting language related to reasons of delayed visits was high, as reflected by the total F-score of 0.77 . When apAlthough the total F-score of the NLP algorithm for identifying the reason of delayed start-of-care is promising, it also implies that the algorithm could not capture all variations for delayed start-of-care in clinical notes. For example, it did not identify the following notes indicating that the patient postponed the start-of-care: (1) “Pt will return call from [nurse], he prefers the soc after 3 (PM),” (2) “Spoke with patient’s caregivers, stated that they are moving to a new apartment and the patient would like to have soc in another time.”In total, 16,244 HHC episodes had a delayed start-of-care HHC visit. Among all 16,244 episodes with a delayed start-of-care nursing visit, 3097 (19.1%) had reasons for delayed start-of-care documented using standardized documentation. Of the 3097 cases with documentation, 5484 unique reasons for delayed start-of-care HHC nursing visits were found (a single HHC episode could have more than 1 reason documented).Overall, 72.2% of the delayed visit reasons , followed by “patient/family request to postpone or refuse some HHC services”  and “administrative or scheduling issues” .Further analysis showed that in more than 40% of episodes with delayed start-of-care HHC nursing visits, 2 or more reasons were documented. The analysis of cooccurrence of reasons for delayed start-of-care HHC nursing visits  indicateThis is the first study we are aware of that examines reasons for delayed start-of-care HHC nursing visits in a large population of HHC patients. Identifying reasons for delayed start-of-care is critical due to the association between delayed care and negative outcomes. The majority of patients requiring HHC are clinically complex and vulnerable older adults who were discharged from hospitals with a need for immediate post–acute care . DelayedThe findings of this study indicate that when a reason is provided, most reasons for delayed start-of-care HHC nursing visits  are documented exclusively in narrative clinical notes. Large-scale analysis of thousands of clinical notes can now be accomplished via innovative data science methods, including NLP.We developed and tested an NLP algorithm to identify patterns of documented delayed start-of-care HHC nursing visit reasons in clinical notes. The NLP algorithm achieved high accuracy in identifying documented reasons when tested on an expert-reviewed sample of clinical notes. NLP algorithms have a wide range of potential applications in extracting meaningful patterns from EHR clinical notes . We beliOur findings indicate that the most prevalent category of delayed start-of-care HHC nursing visits was “no answer at the door or phone.” Potential explanations include having incorrect phone or address information transmitted to the HHC organization, last minute decisions by patients to recover in a location other than their own home, and a lack of communication between the HHC organization and the patient about the patient’s availability. To address this issue, referring hospital clinicians may need to discuss the timing and importance of the first visit with the patient and family and obtain accurate contact information. In addition, it may be necessary to develop a clear communication plan with the HHC agency in the process of transferring the patient from the hospital to the HHC setting.Previous studies -42 and oThe second most prevalent reason for delayed start-of-care HHC nursing visits was “patient/family request to postpone or refuse some HHC services.” Although some related care delays are probably unavoidable, referring physicians and HHC clinicians may need to spend more time articulating the importance of start-of-care HHC nursing visits. Several recent studies indicate many patients may not understand the value of HHC and refuse care. A recent national study found that more than half of the patients referred to HHC from hospitals never receive HHC services . AnotherIn about 20% of HHC episodes, delayed start-of-care was due to “administrative or scheduling issues.” Some of the specific issues were inadequate or incomplete insurance coverage, lack of forms and documents, and a lack of available HHC nurses to complete a start-of-care visit on time. To resolve these issues, HHC organizations may need to develop better and more streamlined patient intake procedures and identify several ways to adjust schedules when a nurse calls in sick or is otherwise unavailable to take on new cases.Our results indicate that in more than 40% of HHC episodes, there were 2 or more reasons for delayed start-of-care HHC nursing visits. The most common cooccurring reasons indicated in about 20% of HHC episodes were “no answer at the door or phone” and “patient/family request to postpone or refuse some HHC services.” In a relatively small number of cases (7%), patients had a combination of all 3 reasons for delayed start-of-care HHC nursing visits. We hypothesize that patients with cooccurring reasons might be more likely to have a delayed start-of-care HHC nursing visit due to the challenges of addressing all reasons of delays in this group of patients. Clinicians may decide to prioritize patients with cooccurring reasons for appropriate interventions to reduce the likelihood of delayed start-of-care. The patient’s demographic and clinical factors might affect their risk for a delayed start-of-care HHC nursing visit. Identifying the relationship between these factors and reasons for delayed visits may help clinicians target patients at high risk for delayed visits with specific interventions. This is an area that requires further investigation.The findings of this study provide insight into the application of NLP techniques to identify reasons for delayed start-of-care in HHC agencies and potential interventions to address the delays and avoid subsequent negative outcomes. HHC administrators may begin considering the use of NLP techniques to analyze the HHC nursing visits for patients that were seen later than 48 hours post–hospital discharge date to identify the reasons for delays and potential interventions. Obtaining and maintaining accurate patient contact information, educating patients about the importance of timely HHC services, and improving the procedures of patient intake and the scheduling system are among the interventions we suggested to reduce the risk of delayed start-of-care due to the following reasons, respectively: “no answer at the door or phone,” “patient/family request to postpone or refuse some home health care services,” and “administrative or scheduling issues.”The findings of this study should be considered in light of several limitations. First, the data set was from a single HHC agency located in the northeast United States. Although the HHC agency is large, its services are limited to individuals residing in a particular catchment area. Therefore, the reasons for delayed visits may not be generalizable to HHC agencies in other locations. Second, the available data did not have information on the hour of discharge from the hospital, so the analysis was based on days, not hours as in the CMS regulations. Third, the NLP algorithms developed in this study had a total precision of 0.8 and recall of 0.75. These findings indicate that some reasons for delayed start-of-care HHC nursing visits identified by NLP were incorrect due to algorithm errors. It is unclear if additional reasons would have been identified if more information on these episodes was provided.To avoid delays in critical start-of-care nursing visits, HHC agencies and hospitals should consider examining and improving accurate patient or family contact information collection. In addition, HHC agencies should consider providing targeted education about the importance of the early initiation of HHC services to reduce patient and family refusals and/or requests to postpone care. Finally, HHC agencies should make efforts to reduce administrative and scheduling issues to enable timely and effective care.


Mammalian 2 orthobornavirus (VSBV-1) is an emerging zoonotic pathogen discovered in several exotic squirrel species and associated with fatal human encephalitis. The dynamics of VSBV-1 spread and evolution in its presumed natural hosts are unknown. Here, we present the phylogeny, micro-evolution, cross-species transmission and spread of VSBV-1 at a temporal and spatial resolution within the limits of animal husbandry. The results showed that VSBV-1 can be classified into six distinct groups and that the most recent common ancestor of the known German strains emerged at least 20 years ago. We here demonstrate that the genetic diversity of the VSBV-1 groups is shaped primarily by in situ evolution and most of the amino acid changes are deleterious polymorphisms removed by purifying selection. Evidence of adaptive evolution has been found in the G and L genes which might have an influence on transmission fitness. Furthermore, there was also evidence for some form of adaptive changes in the glycoprotein which suggests that many sites might be subjected to positive pressure evolving under episodic directional selection, indicating past occurrence of positive selection. Host switching events were detected as dominant evolutionary mechanisms driving the virus-host associations. Virus spread by animal trade followed by subsequent local micro-evolution in zoos and holdings is responsible for diversifying strains. Time-resolved phylogeny indicated that Prevost’s squirrels might be the original squirrel species carrying and seeding the virus in Germany. This study provides the first insight into the ecology and micro-evolutionary dynamics of this novel viral pathogen in the captive exotic squirrel population under artificial ecological conditions  and co-housing of different squirrel species. Mammalian 2 orthobornavirus) is an emerging zoonotic pathogen discovered in 2015 as the causative agent of fatal encephalitis of three men breeding exotic variegated squirrels in eastern Germany [Sciurus variegatoides; family Sciuridae, subfamily Sciurinae) are native to Central America, Prevost’s squirrels  are natural inhabitants of Southeast Asia. Epidemiological investigations in private holdings and zoological gardens in Germany and elsewhere in Europe detected VSBV-1 infection rates of 1.5% in captive Sciurinae and 8.5% in captive Callosciurinae squirrels, including one Asian Finlayson’s squirrel  and one Asian striped squirrel  [The variegated squirrel bornavirus 1  ,5. Both iurinae) ,7. The o−1 year−1), the time to most recent common ancestor (tMRCA) under a relaxed uncorrelated lognormal clock and a flexible demographic model (Gaussian Markov Random field Bayesian Skyride). An asymmetric model with Bayesian Stochastic Search Variable selection (BSSVS) was applied to identify statistically significant transition rates between host species. The Markov Chain Monte Carlo (MCMC) chain length was set to 50 million steps sampling after every 10,000 steps. The Bayesian maximum clade credibility (MCC) trees were visualized using FigTree v1.4.4 .All currently available 26 complete coding VSBV-1 sequences with known year of detection, host, and geographical origin available in databases were used in this study . SequencNd) to synonymous (Sd) nucleotide substitutions (Nd/Sd or ω ratio) per site for the detection of sites subjected to positive or negative selection or transient (episodic) selective pressures using four codon-based ML tools  implemented in the Datamonkey web interface . We also employed aBSREL (Adaptive branch-site random effects likelihood) which uses an adaptive random effects branch-site model framework to test whether each branch has evolved under positive selection, using a procedure which infers an optimal number of rate categories per branch [http://www.cbs.dtu.dk/services/; accessed on 17 April 2021).Codon-based models of evolution in an ML framework were used to evaluate the nature of the selection pressure acting on each VSBV-1 gene. It was estimated as a ratio of non-synonymous , a haplotype network was constructed using the Minimum Spanning Network (MSN) method inferred by PopART package v1.7.2 .cytochrome b gene reconstruction using PhyML and the GTR+G model. The calculations using Jane 4 and CoRe-Pa assign event-based model with co-speciation, duplication, sorting and host switching events. Cost values must be set a priori in Jane 4, whereas CoRe-PA uses a parameter-adaptive approach to search for optimal cost values. Both methods compute minimal-cost reconstruction of the evolutionary history between hosts and viruses. For Jane 4 statistical significance was established by 500 random tip mapping permutations and 500 random parasite tree permutations with Yule beta parameter equal to −1. For Core-Pa the evaluation was done using 10,000 different event cost models. For significance evaluation, a randomization test with 1000 instances with randomized host-virus associations was performed.To study the history of a possible co-speciation of VSBV-1 and its hosts or the alternative hypothesis of host switches, we performed event-based co-phylogenetic reconciliation using CoRe-PA  and JaneThe genetic variation across the genome of VSBV-1 strains  was relaHowever, the limited number of available sequences and the lack of VSBV-1 data back to the first known human case in 2007 reduces our ability to predict previous events and virus variant circulation between holding and zoos. The detailed analysis of the German strains demonstrated that VSBV-1 forms six major groups A definedP < 0.001) and the coefficient of rate variation supported the use of a relaxed clock model. By plotting root-to-tip divergence as a function of sampling time, an accumulation of nucleotide substitutions was observed over the sampling time  detected in the glycoprotein of VSBV-1 was present in two Prevost’s squirrels (KY488723 and KY488724) and one Swinhoe’s striped squirrel (KY488727), while another positively selected AA (Lys1191Leu/Arg) detected in the polymerase was present in two Prevost’s squirrels (LT594381 and KY488724), all originating from the same holding E  in the glycoprotein which suggests that many sites in the VSBV-1 genes  identified by FUBAR and MEME may be subjected to positive pressure evolving under episodic directional selection .The conservative AA change Lyselection . Using tUsing CoRe-PA and Jane 4, we tested the hypothesis of VSBV-1/host co-speciation by using reconciliation analysis, presented along with their tanglegram depicting host-virus associations A,B. EvenThe VSBV-1 phylogeny is notable for a clustering in which the dominant groups connect viruses sampled from multiple time points from the same source A. We useThe human impact on sylvatic or semi-sylvatic ecosystems as well as the trade of wild animal species facilitates contact of (novel) pathogens with susceptible (new) hosts. Understanding the ecology and genetic driving forces that contribute to the emergence and spread of zoonotic pathogens is important for the implementation of preventive strategies. In this study, we aimed to investigate the genomic and micro-evolutionary processes of VSBV-1 that were seen during infection of multiple exotic squirrel species and humans in the artificial but exemplary situation of animal husbandry and co-housing of squirrel species which live under natural conditions on different continents. Moreover, we aimed to shed more light on the possible origin of VSBV-1 infecting exotic squirrels in German holdings by novel phylogeny constructions, co-speciation analyses, transmission rate strength calculations, and haplotype network inferences.The phylogeny constructed here showed a spatial differentiation of VSBV-1 strains that resulted in the phylogenetic clustering in the form of six distinct groups defined by the geographic place of sampling . The existence of such groups is likely the result of adaptation to the local artificial ecological conditions. Hence, the adaptation of VSBV-1 to naïve host populations in captivity can lead to the emergence of local virus strains or variants, and the most likely scenario for VSBV-1 might be enzootic maintenance (in situ evolution). This assumption is further supported by the presence of some fixed AA residues involved in the formation of these six distinct groups defined by their geographic origin.The overall low ratio of non-synonymous to synonymous substitutions indicates that most AA changes are deleterious polymorphisms removed by purifying selection, likely as results of genetic drift. We found strong evidence of adaptive evolution only at codon 238 of the G gene and at codon 1191 of the L gene. Although the function of these residues remains to be determined, mutations in the G protein and/or L protein (polymerase) have exhibited enhanced neurovirulence in the related Borna Disease virus 1 (BoDV-1) in adult and newborn Lewis rats . In a reVSBV-1 infected captive exotic squirrel species of the Sciurinae and Callosciurinae subfamilies were shown to be asymptomatic, thus displaying characteristics of natural reservoir hosts ,5. The fBy co-phylogenetic reconciliation analysis, host switching was detected as the dominant mechanism driving the virus-host associations during animal trade and co-housing of different species in captivity. No hints for a co-speciation were found. When analyzed by host switching, both squirrel inter-genus and intra-genus transmissions have occurred. This suggests that VSBV-1 may switch its hosts (by spill-over infections) if the environmental conditionals are favorable, such as during co-housing or by contact to human caretakers, apparently without preferential transmission between closely or more distantly related host species. Our results do not exclude a possible co-speciation of VSBV-1 and different exotic squirrels or other host species in the wild. Field studies for the presence of VSBV-1 in wild exotic squirrel populations are therefore still essential to resolve the question of the virus’ natural host animal range and its geographic origin. This is underlined by recent investigations which showed that the animal trade to Germany was mainly fueled by a squirrel farm in Central America where Prevost’s squirrels were kept beside variegated squirrels . Thus, vOur analysis only represents a snapshot into the last evolutionary events identified and as such does not represent the complete evolutionary history of VSBV-1. It should also be noted that such events are dependent on the relationships observed in the reconstructed phylogeny trees and could appear differently once more VSBV-1 strains are found and compared with each other.Taking advantage of the artificial circumstances of animal husbandry, we were able to gain insights into adaptive and other micro-evolutionary processes in different exotic squirrel hosts that form the basis for future studies on the ecology and evolution of this zoonotic emerging viral pathogen under natural conditions. The limited number of available VSBV-1 sequences and the lack of virus data from other European countries and other continents reduce our ability to infer the spatio-temporal pattern of the virus’ spread and emergence, and thus the evolutionary history of VSBV-1.


The incidence of lymphoma is constantly increasing worldwide. The reasons for this increase are unclear and likely multiple. B cell lymphomas represent the majority of non-Hodgkin lymphomas. Primary orbital localization remains a rare entity to think about in order to avoid missing a therapeutic emergency. In this article, we report the case of a 52-year-old man who has been treated for five years for an inflammatory orbitopathy with steroids, but the worsening of the clinical condition and the installation of exophthalmia led to push investigations and the outcome was a primary orbital lymphoma marginal zone type. The patient was treated by systemic chemotherapy with immunotherapy (RCHOP protocol) with a very good evolution and complete disappearance of the lesion after chemotherapy. Lymphoma is a heterogeneous group of several subtypes of lymphoproliferative malignancies that are usually classified into two categories: Hodgkin lymphoma, and all other lymphomas into non-Hodgkin lymphoma (NHL). Primary ophthalmic malignancies are usually Non-Hodgkin’s lymphoma, with a rate of 1-2% of all NHL [Ocular adnexal NHL can arise from the conjunctiva, lachrymal gland, orbit, or eyelid. Extra-nodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT) type is the most common histologic type of primary ocular NHL . The ratWe report the case of a 52-year-old man with a long history of tobacco use who was treated over the course of five years for an inflammatory orbitopathy with corticosteroids without improvement. It's evolution was marked by the appearance of exophthalmia with decreased visual acuity.Physical examination found a painless eyelid swelling on the right eye’s internal angle with an important exophthalmia and excessive lachrymal non-purulent secretion. No inflammatory signs were found next to the tumor Figure . DecreasOphthalmological examination revealed a papillary edema of the right eye. Given the progressive nature of the disease, the patient benefited from an orbital magnetic resonance imaging (MRI) that revealed a right exophthalmia secondary to an extra-ocular intra-orbital lesion process that had infiltrated orbital muscles and encompassed the optic nerve Figure . A biopsThoraco-abdominal-pelvic computed tomography (CT) scan, bone marrow biopsy, cerebral MRI, and lumbar puncture had eliminated a secondary localization of lymphoma. Thus, the disease was classified as a stage IEA according to Ann Arbor classification and T3N0M0 according to TNM  classification. Given the long-term evolution, the possibility of metastasis masked by corticotherapy and difficulty to access to PET scan (positron emission tomography) in our context, the patient was treated with systemic chemotherapy following the R-CHOP protocol every 21 days for six cycles  scan, bone marrow biopsy, and cerebrospinal fluid in high grade of malignancy . It may The modified classification of Ann Arbor is typically used to classify orbital lymphoma. However, it has multiple weaknesses as it does not take into consideration the following criteria: laterality, the contiguity or lack thereof in the orbital annexes sites and the involvement of extra nodal sites such as the parotid or sub mandibular galls. Therefore, the TNM  classification was developed by the American Joint Committee on Cancer (AJCC) in 2009 to overcome these weaknesses and provide better precision of extension assessment .Optimal treatment of the early stage orbital adnexal lymphoma is unclear because of the rare cases of early-stage case reports, incomplete staging, or pseudo tumors. A few studies, mostly retrospective, demonstrate that for low-grade lymphoma, radiotherapy alone may provide excellent results with a five-year progression-free survival of 100%. For patients with aggressive lymphoma, chemotherapy with or without radiotherapy has shown better results compared to radiotherapy alone. The combination of chemotherapy and radiotherapy has yielded better results than chemotherapy alone in terms of progression-free survival. Although studies on chemotherapy benefits in early-stage orbital lymphoma are rare, the R-CHOP regimen has proven efficiency in the treatment of extra-nodal marginal zone lymphoma among other chemotherapy associations with anti-CD20 antibody molecules .Orbital adnexal marginal zone lymphoma is a rare affliction. Biopsy with immunohistochemical study should be practiced in the etiological assessment of inflammatory orbitopathy. While the Ann Arbor classification has multiple weaknesses, the TNM classification is better adapted to classify orbital lymphoma. There is no treatment consensus concerning early-stage orbital lymphoma.


Off-lead exerciseless commonly allowed off the lead in public , including: chow chow ; Siberian husky ; Pyrenean mountain dog ; Alaskan Malamute ; and St Bernard .Some breeds were The authors apologise for the error.This article was published with errors in the first sentence of the section ‘Off-lead exercise’ on page 5. The correct sentence is below.


Background: [177Lu]-PSMA-617 (Lu-PSMA) therapy is a promising therapeutic option for end-stage prostate cancer patients. Early treatment response at the first restaging after two therapy cycles might correlate with high treatment efficacy and long overall survival (OS). Therefore, the aim of this study was to evaluate whether early reduction in tumor volume is a positive prognosticator for OS. To this end, PSMA PET prior to therapy (baseline) and at first restaging after two therapy cycles  were compared.Methods: Patients with metastatic castration-resistant prostate cancer who received Lu-PSMA therapy were reviewed for this analysis. All patients with available baseline and interim [68Ga]-PSMA-11 PET/CT were included in this analysis (n = 33). All PSMA avid metastases in baseline and interim PETs were semi-automatically segmented. The average PSMA expression , total tumor volume (PSMA-TV) and TLQ  were quantified at baseline and interim timepoints. Response in PSMA-TV was assumed when a decline > 30% was present. OS and biochemical response were available for all patients.Results: Baseline PSMA-TV was a statistically significant prognosticator of OS . Reduction in PSMA-TV was not a statistically significant positive prognosticator of OS in the total cohort . Likewise, there was no statistical difference in survival time comparing patients with PSMA-TV response to those without . In the subgroup of patients with PSMA-TV response, mean SUVmax was a statistically significant prognosticator of OS . If patients with low PSMA expression at baseline were excluded from the analysis, reduction in PSMA-TV became a positive prognosticator of OS in uni- and multivariable Cox regression .Conclusion: PSMA-TV reduction was a positive prognosticator of OS only if patients with low PSMA expression were excluded. This might indicate that the PSMA-PETs of patients with low PSMA expression may not be suited for assessing PSMA-TV reduction. Future studies investigating the interplay of PSMA-TV and low PSMA expression response are warranted. We showed previously that initially low PSMA expression may be a statistically significant negative prognosticator of overall survival (OS) Therefore, the aim of the present study was to compare baseline and interim PSMA PET derived PSMA-TV to assess whether prolonged OS is associated with PSMA-TV response. Additionally, the PSMA expression of patients with PSMA-TV response was investigated.All patients who received Lu-PSMA therapy in the Department of Nuclear Medicine of the University Hospital Münster were selected for this study if baseline and interim PSMA-11 PET CT were present. A total number of 33 patients met these inclusion criteria. Detailed patient characteristic data is provided in Table 68Ga]Gallium-PSMA-11 was employed for PET imaging. The PSMA-11 precursor was delivered by ABX . Image acquisition started 60 minutes after injection using a Biograph mCT . The PET scan area included the vertex to thigh. A mean dose of 163 (standard deviation: 24) MBq was administered. Whole-body low dose and abdominal full dose (contrast-enhanced) PET acquisitions were obtained.PSMA PET imaging and tracer synthesis was done as previously reported 177Lu]Lutetium . The Lu-PSMA therapy was administered at a 6-8 weeks interval.Prostate cancer patients referred to the Department of Nuclear Medicine Münster for Lu-PSMA therapy were treated with PSMA-617  conjugated with Lutetium-PSMA617 therapy was evaluated as a prognosticator for OS in the present study. To this end, the pretherapeutic (baseline) and interim PSMA PET/CTs after two cycles of Lu-PSMA therapy were compared. If the entire cohort was regarded, PSMA-TV reduction was surprisingly not a relevant prognosticator of OS. If patients with low PSMA expression were excluded from the analysis, PSMA-TV reduction was a statistically significant positive prognosticator of OS. Therefore, reduction of PSMA-TV appears to be a valuable parameter to prognosticate OS, but the clinician must carefully consider PSMA expression to avoid misleading interpretations of PSMA-TV reductions.The reduction in PSMA PET derived total tumor volume (PSMA-TV) in response to [Lu-PSMA therapy is a promising therapeutic option for patients with advanced prostate cancer and has been evaluated in several retrospective and prospective studies The present study indicates that baseline PSMA-TV is a statistically significant prognosticator of OS in patients treated with Lu-PSMA therapy. Surprisingly, the decrease of PSMA-TV was not a statistically significant prognosticator in the present cohort. To investigate these counterintuitive findings, the baseline PSMA expression of patients with tumor volume response and short overall survival was analyzed. We hypothesized that the reduction of PSMA-TV cannot be regarded without looking at the PSMA expression. The reason for this is that in advanced prostate cancer, cancer cells might undergo dedifferentiation and lose the ability to express PSMA The reduction of PSMA‑TV was a statistically significant prognosticator of OS in the present study in patients without low PSMA expression. This indicates that the reduction of PSMA‑TV in the interim PET can be erroneously interpreted as a treatment response in the presence of metastases with low PSMA expression at baseline Figure . PatientPatients with a biochemical response (PSA decline greater than 50%) had a longer OS compared to patients without. This seems contradictory to the finding that patients with tumor volume response did not show a longer OS in the total cohort. However, the PSA value might more robustly quantify the tumor volume and may not be influenced by metastases with low PSMA expression. It must be noted that different PSMA-TV response thresholds than the commonly employed 30% decline might identify patients with short overall survival. However, given the reproducibility of PSMA PET metrics in the range of +/- 30%, only the 30 % cutoff was used for PSMA-TV in the present study Grubmüller et al., who found PSMA-TV reduction to be associated with longer OS, might be partly explained by the more advanced cancer stages in our cohort , which could correlate with a larger fraction of patients who show low PSMA expression The present study faces some limitations. There might be a selection bias, as only patients with two cycles of Lu-PSMA therapy were included. The reason for this is because restaging after the start of therapy is generally performed after the administration of the second cycle of Lu-PSMA therapy. Patients with rapid progression of prostate cancer, who might therefore not have received a second cycle of Lu-PSMA therapy, were not included. This might impair the transferability of the results to larger patient cohorts. Additionally, the included patient cohort is still relatively small. Because we only included patients who received PSMA-11 PET/CT at baseline and follow-up, patients who received combinations of PSMA-11 and PSMA-1007 PET CTs were not included in this study. However, given the high rate of events (60%), we feel that this limitation should not impair the findings of this study. A limitation of the PSMA PET volumetry is that only metastases with elevated PSMA expression are captured. Due to dedifferentiation and decreasing PSMA expression, the tumor volume might erroneously appear regredient, while the actual tumor volume is progredient. The contrary report of Decline in PSMA PET derived total tumor volume is not a prognosticator of OS in patients treated with Lu-PSMA therapy, if patients with low PSMA expression were included in the cohort. If patients with low PSMA expression were excluded, reduction in PSMA-TV is a significant prognosticator of OS, even in multivariable analysis. Therefore, PSMA-TV alone is not suited to monitor the progression of disease in end-stage prostate cancer patients. This might be due to erroneously quantified interim tumor volume reduction in the event of low PSMA uptake. Further studies focusing on the tumor volume response of patients with advanced prostate cancer are warranted. Tumor volume reduction should be carefully regarded in conjunction with baseline PSMA expression to properly assess treatment response.Supplementary figure.Click here for additional data file.


Arabidopsis thaliana, however, the role of the rice PIN-FORMED (PIN) auxin efflux carriers in the regulation of the ammonium-dependent response remains elusive. Here, we analyzed the expression patterns in various organs/tissues and the ammonium-dependent response of rice PIN-family genes (OsPIN genes) via qRT–PCR, and attempted to elucidate the relationship between nitrogen (N) utilization and auxin transporters. To investigate auxin distribution under ammonium-dependent response after N deficiency in rice roots, we used DR5::VENUS reporter lines that retained a highly active synthetic auxin response. Subsequently, we confirmed that ammonium supplementation reduced the DR5::VENUS signal compared with that observed in the N-deficient condition. These results are consistent with the decreased expression patterns of almost all OsPIN genes in the presence of the ammonium-dependent response to N deficiency. Furthermore, the ospin1b mutant showed an insensitive phenotype in the ammonium-dependent response to N deficiency and disturbances in the regulation of several N-assimilation genes. These molecular and physiological findings suggest that auxin is involved in the ammonium assimilation process of rice, which is a model crop plant.Auxins play an essential role in regulating plant growth and adaptation to abiotic stresses, such as nutrient stress. Our current understanding of auxins is based almost entirely on the results of research on the eudicot  Arabidopsis carries eight members of this protein family, and the AtPIN proteins are divided into two types: one has a long hydrophilic loop (“long PIN proteins”) and the other contains a short hydrophilic loop (“short PIN proteins”). Both types have been reported to participate in various developmental processes IAA transport activity and auxin concentration decreased significantly at the root tip of the ospin1b knockout mutant g for 10


Existing class activation mapping (CAM) techniques extract the feature maps only from a single layer of the convolutional neural net (CNN), generally from the final layer and then interpolate to upsample to the original image resolution to locate the discriminative regions. Consequently these provide a coarse localization that may not be able to capture subtle abnormalities in medical images. To alleviate this, our work proposes a technique called high resolution class activation mapping (HR-CAMs) that can provide enhanced visual explainability to the CNN models.HR-CAMs fuse feature maps by training a network using the input from multiple layers of a trained CNN, thus gaining information from every layer that can localize abnormalities with greater details in original image resolution. The technique is validated qualitatively and quantitatively on a simulated dataset of 8,000 images followed by applications on multiple image analysis tasks that include (1) skin lesion classification  and (2) predicting bone fractures  (3) predicting Parkinson’s disease (PD) from neuromelanin sensitive MRI .We demonstrate that our model creates clinically interpretable subject specific high resolution discriminative localizations when compared to widely used CAMs and Gradient-CAMs.HR-CAMs provide finer delineation of abnormalities thus facilitating superior explainability to CNNs as has been demonstrated from its rigorous validation. Convolutional neural nets (CNNs) have demonstrated a superior performance on image based predictive tasks, particularly on large sample sizes when compared to statistical learning algorithms applied on hand-picked or empirically drawn features from the images . HoweverDiscriminative localization on images was earlier based on mapping the CNN activations back to the input space using the technique of deconvolution , by maskThe most prevailing issue with using CAMs is that they extract information only from a single layer of the CNN. Majority applications have employed the final layer as it entails the most abstract markers and can therefore facilitate more accurate maps than using any intermediate layer. However, especially in medical imaging where the original images itself are not super high-resolution, the final layer is usually a highly down sampled layer and therefore provides a low resolution CAM which when interpolated to the original image size results into a coarse map that fails to capture subtle and diffuse patterns of abnormalities that delineate the classes under consideration. To overcome these challenges, we propose a novel technique called HR-CAM to visualize and underscore the discriminative regions with high precision. We achieve this by capturing feature maps from multiple layers (pre-max-pooling layers) and aggregating these for a classifier. HR-CAMs have the ability to identify precise regions of delineation and can be employed via any CNN architecture. Unlike CAMs proposed by k number of convolutional layers L = {,…,}, such that the set L consists of convolutional layers which constitute the low-level, intermediate and high level of encoded information from the images. Let the feature maps corresponding to these layers be = {…}. The feature maps are outputs of various convolutional kernels applied on the feature maps of the preceding layers. The number of feature maps corresponding to the kth layer is given by N where N is given by The generation of HR-CAMs requires training the modified CNN architecture by setting the convolutional layers to non-trainable as described below. Arbitrarily, we choose S is number of samples and Following the concatenated layer is a single fully-connected layer which is trained to minimize the categorical cross entropy loss function  where \d= {…} to all the values in the concatenated layer and ultimately the corresponding feature maps according to their importance for classification. These resulting weights pertaining to every class, support weighted aggregation of the feature maps.This assigns new weights, ,…,…A can therefore demonstrate the most discerning regions in the image in high resolution.Finally, to obtain the discriminative activations, we forward propagate the input image to acquire the intermediate convolutional outputs , an international repository of dermoscopic images developed by the International Skin Imaging Collaboration (ISIC) which includes images belonging to eight classes of skin lesions as follows: Melanoma, Melanocytic nevus, Basal cell carcinoma, Actinic keratosis, Benign keratosis, Dermatofibroma, Vascular lesion, Squamous cell carcinoma. The ISIC archive is a collection of multiple databases and currently includes a total of 25,331 images from BCN_20000  and 35 age and gender matched controls. The NMS-MRI provides a good contrast in the substantia nigra pars compacta (SNc) and is useful in identifying PD as PD manifests depigmentation of the SNc (The PD dataset included neuromelanin sensitive MRI (NMS-MRI) scanned on Philips 3T Inginea the SNc .musculoskeletal radiographs) is one of the largest public radiographic image datasets collected from HIPAA-compliant images from the Picture Archive and Communication System (PACS) of Stanford Hospital (https://stanfordmlgroup.github.io/competitions/mura/) (MURA (s/mura/) . It conss/mura/) . The aimHR-CAMs were compared with the current state-of-art techniques: (1) GAP based CAMs by Gradient-weighted Class Activation Mapping (Grad-CAM), uses the gradients of the target class, flowing into any convolutional layer to produce a coarse localization map highlighting the important regions in the image for predicting that particular class. In our case we use a convolutional layer from the pre-final convolutional block to implement Grad-CAM . Any of the single intermediate convolutional layers can also be used in the implementation of Grad-CAM.Results for each of the datasets are provided in the following subsections.To obtain HR-CAMs, ResNet-50 architecture was employed as the base model. Data augmentation techniques involving shift, flip and rotation of images were used to increase the simulated dataset size and make the model robust. This setup was trained on 6,000 images and validated on 2,000 distinct simulated images to obtain a validation accuracy of 95% (AU-ROC = 0.99) using binary cross-entropy as the loss metric. The results for the CAMs are shown in p-value < 0.0001 and p-value < 0.0001 respectively) was significantly different however specificity between HR-CAM and Zhou’s CAM did not vary  conversely between HR-CAM and GradCAM it was highly significant .The ISIC dataset posed a multi-class classification problem. Since the data belonged to 8 different classes, categorical cross-entropy was used as the loss metric for two separate models under consideration. Model 1 used transfer learning on the ResNet-50  from 80 subjects . Augmentation techniques mentioned for the previous two datasets were employed to increase the size by 10 folds. The ResNet-50 base architecture was trained on the boxed regions around the brain-stem using binary cross entropy as the loss metric. The model performed with an accuracy of 76.02% on the testing set of images providing an F1-score of 0.81 and AU-ROC of 0.84. For the musculoskelatal radiographs dataset, two separate models were trained. Model 1 was the ResNet-50 architecture  while moTo evaluate the similar performance of HR-CAM model with CAMs from On the contrary, when we compared the weights from neuromelanin MRI-PD dataset (from “Neuromelanin MRI for PD”) the distribution of weights was more uniform over all the sampled convolutional layers for the HR-CAM model facilitating more accurate maps. As shown in In this work, we proposed a generalized approach called HR-CAMs for enhanced visual explanations from CNN based architectures. We extensively validated this technique on multiple radio-pathological images to demonstrate high precision in extracting the activation maps that could be significantly valuable for clinical interpretation of pathology. The validation was not only performed on simulated datasets but also on benchmark open datasets such as ISIC and MURA where we illustrated that HR-CAMs facilitated better discriminative representations than existing methods.Radiology images such as MRI and CT inherently have a lower resolution when compared to images captured from other sources such as digital cameras. Therefore, when a deep CNN model is applied to such radiological images, as a result of multiple max-pool layers, the image represented in the final layer is usually of poor resolution. Current CAM techniques such as from Initial validation was performed on a simulated dataset where the baseline abnormality was known. The classifier performed with a high accuracy and the CAMs produced by our technique focused on the fine patterns of abnormality that were induced as compared to coarse maps provided by the other two techniques. To demonstrate the consistency of our superior results on all types of simulated abnormalities  quantitative inference was provided in We also applied our technique on benchmark dataset of ISIC and illustrated similar findings as the simulated data, where HR-CAMs facilitated superior maps as shown in For the MURA data, we observed that the maps from HR-CAM and Zhou’s CAMs were similar while the ones given by GradCAM were inferior. To achieve a profound understanding of why HR-CAMs performed at par with CAMs were mapped all the trained weights to observe that the earlier layers were not weighted (zero weight) compared to the final layers implying that the sampled initial and intermediate convolutional layers did not focus on the intended area of interest. This was mainly due to the presence of artifacts/redundant information (in this case written information on x-rays such as “L” or “R” or other written information that varied from scan to scan) in the input data which the model learned with the initial and intermediate convolutional layers (as shown in Limitations of HR-CAM include freezing of layers that makes the framework a two-step procedure. Nonetheless, HR-CAMs are highly adaptable to the dataset under consideration and consequently facilitate superior CAMs compared to the existing methods. Overall, the technique with its validation on multiple datasets lends credence for clinical explanation and interpretation.10.7717/peerj-cs.622/supp-1Supplemental Information 1Click here for additional data file.