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Biomedical image analysis is fundamental for biomedical discovery. Holistic image analysis comprises interdependent subtasks such as segmentation, detection and recognition, which are tackled separately by traditional approaches. Here, we propose BiomedParse, a biomedical foundation model that can jointly conduct segmentation, detection and recognition across nine imaging modalities. This joint learning improves the accuracy for individual tasks and enables new applications such as segmenting all relevant objects in an image through a textual description. To train BiomedParse, we created a large dataset comprising over 6 million triples of image, segmentation mask and textual description by leveraging natural language labels or descriptions accompanying existing datasets. We showed that BiomedParse outperformed existing methods on image segmentation across nine imaging modalities, with larger improvement on objects with irregular shapes. We further showed that BiomedParse can simultaneously segment and label all objects in an image. In summary, BiomedParse is an all-in-one tool for biomedical image analysis on all major image modalities, paving the path for efficient and accurate image-based biomedical discovery., Competing Interests: Competing interests C.B. is a member of the scientific advisory board and owns stock in PrimeVax and BioAI; is on the scientific board of Lunaphore and SironaDx; has a consultant or advisory relationship with Sanofi, Agilent, Roche and Incendia; contributes to institutional research for Illumina, and is an inventor on US patent applications US20180322632A1 (Image Processing Systems and Methods for Displaying Multiple Images of a Biological Specimen) filed by Ventana Medical Systems, Providence Health and Services Oregon and US20200388033A1 (System and Method for Automatic Labeling of Pathology Images) filed by Providence Health and Services Oregon, Omics Data Automation. The other authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles 1-3 . Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context 4 . Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet 5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data 6 . With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology 7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling., (© 2024. The Author(s).)

Background: A national point prevalence survey (PPS) of healthcare-associated infections (HAI) and antibiotic use (AU) was carried out in Germany in 2022 in the framework of the European PPS conducted by the European Centre for Disease Prevention and Control (ECDC). The objective was to determine the prevalence of HAI and AU in German hospitals and to compare the obtained values with those of the most recent previous PPS, which was carried out in 2016., Methods: The German National Reference Center for the Surveillance of Nosocomial Infections was entrusted with the organization of the PPS of 2022. As recommended by the ECDC, each hospital in a representative sample of 50 hospitals was invited to participate, and all other interested hospitals in Germany were also able to participate if desired. The data were collected by specially trained hospital staff in May, June, and July 2022. The definitions and methods put forth by the ECDC were used., Results: Data from 66 586 patients in 252 hospitals were included. The prevalence of HAI in all participating hospitals was 4.9%, and that of AU was 26.9%. The HAI and AU prevalences were essentially unchanged in comparison to 2016. The most common types of HAI were surgical site infection (23.5%), lower respiratory tract infection (21.6%), and urinary tract infection (19.0%)., Conclusion: HAI were just as frequent in 2022 as in 2016, affecting approximately one in twenty hospitalized patients on any given day.

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Preclinical murine data indicate that fragment crystallizable (Fc)-dependent depletion of intratumoral regulatory T cells (Treg) is a major mechanism of action of anti-CTLA-4. However, the two main antibodies administered to patients (ipilimumab and tremelimumab) do not recapitulate these effects. Here, we investigate the underlying mechanisms responsible for the limited Treg depletion observed with these therapies. Using an immunocompetent murine model humanized for CTLA-4 and Fcγ receptors (FcγR), we show that ipilimumab and tremelimumab exhibit limited Treg depletion in tumors. Immune profiling of the tumor microenvironment (TME) in both humanized mice and humans revealed high expression of the inhibitory Fc receptor, FcγRIIB, which limits antibody-dependent cellular cytotoxicity/phagocytosis. Blocking FcγRIIB in humanized mice rescued the Treg-depleting capacity and antitumor activity of ipilimumab. Furthermore, Fc engineering of antibodies targeting Treg-associated targets (CTLA-4 or CCR8) to minimize FcγRIIB binding significantly enhanced Treg depletion, resulting in increased antitumor activity across various tumor models. Our results define the inhibitory FcγRIIB as an immune checkpoint limiting antibody-mediated Treg depletion in the TME, and demonstrate Fc engineering as an effective strategy to overcome this limitation and improve the efficacy of Treg-targeting antibodies., (©2023 The Authors; Published by the American Association for Cancer Research.)

Background: Oral microbiome sequencing has revealed key links between microbiome dysfunction and dental caries. However, these efforts have largely focused on Western populations, with few studies on the Middle Eastern communities. The current study aimed to identify the composition and abundance of the oral microbiota in saliva samples of children with different caries levels using machine learning approaches., Methods: Oral microbiota composition and abundance were identified in 250 Saudi participants with high dental caries and 150 with low dental caries using 16 S rRNA sequencing on a NextSeq 2000 SP flow cell (Illumina, CA) using 250 bp paired-end reads, and attempted to build a classifier using random forest models to assist in the early detection of caries., Results: The ADONIS test results indicate that there was no significant association between sex and Bray-Curtis dissimilarity (p ~ 0.93), but there was a significant association with dental caries status (p ~ 0.001). Using an alpha level of 0.05, five differentially abundant operational taxonomic units (OTUs) were identified between males and females as the main effect along with four differentially abundant OTUs between high and low dental caries. The mean metrics for the optimal hyperparameter combination using the model with only differentially abundant OTUs were: Accuracy (0.701); Matthew's correlation coefficient (0.0509); AUC (0.517) and F1 score (0.821) while the mean metrics for random forest model using all OTUs were:0.675; 0.054; 0.611 and 0.796 respectively., Conclusion: The assessment of oral microbiota samples in a representative Saudi Arabian population for high and low metrics of dental caries yields signatures of abundances and diversity., (© 2023. The Author(s).)

Background: Endomyocardial biopsy (EMB) is currently considered the gold standard for diagnosing cardiac allograft rejection. However, significant limitations related to histological interpretation variability are well-recognized. We sought to develop a methodology to evaluate EMB solely based on gene expression, without relying on histology interpretation., Methods: Sixty-four EMBs were obtained from 47 post-heart transplant recipients, who were evaluated for allograft rejection. EMBs were subjected to mRNA sequencing, in which an unsupervised classification algorithm was used to identify the molecular signatures that best classified the EMBs. Cytokine and natriuretic peptide peripheral blood profiling was also performed. Subsequently, we performed gene network analysis to identify the gene modules and gene ontology to understand their biological relevance. We correlated our findings with the unsupervised and histological classifications., Results: Our algorithm classifies EMBs into three categories based solely on clusters of gene expression: unsupervised classes 1, 2, and 3. Unsupervised and histological classifications were closely related, with stronger gene module-phenotype correlations for the unsupervised classes. Gene ontology enrichment analysis revealed processes impacting on the regulation of cardiac and mitochondrial function, immune response, and tissue injury response. Significant levels of cytokines and natriuretic peptides were detected following the unsupervised classification., Conclusion: We have developed an unsupervised algorithm that classifies EMBs into three distinct categories, without relying on histology interpretation. These categories were highly correlated with mitochondrial, immune, and tissue injury response. Significant cytokine and natriuretic peptide levels were detected within the unsupervised classification. If further validated, the unsupervised classification could offer a more objective EMB evaluation., (© 2023 The Authors. Clinical Transplantation published by John Wiley & Sons Ltd.)

Background: Crohn's diseases and ulcerative colitis, both of which are chronic immune-mediated disorders of the gastrointestinal tract are major contributors to the overarching Inflammatory bowel diseases. It has become increasingly evident that the pathological processes of IBDs results from interactions between genetic and environmental factors, which can skew immune responses against normal intestinal flora., Methods: The aim of this study is to assess and analyze the taxa diversity and relative abundances in CD and UC in the Saudi population. We utilized a sequencing strategy that targets all variable regions in the 16 S rRNA gene using the Swift Amplicon 16 S rRNA Panel on Illumina NovaSeq 6000., Results: The composition of stool 16 S rRNA was analyzed from 219 patients with inflammatory bowel disease and from 124 healthy controls. We quantified the abundance of microbial communities to examine any significant differences between subpopulations of samples. At the genus level, two genera in particular, Veillonella and Lachnoclostridium showed significant association with CD versus controls. There were significant differences between subjects with CD versus UC, with the top differential genera spanning Akkermansia, Harryflintia, Maegamonas and Phascolarctobacterium. Furthermore, statistically significant taxa diversity in microbiome composition was observed within the UC and CD groups., Conclusions: In conclusion we have shown that there are significant differences in gut microbiota between UC, CD and controls in a Saudi Arabian inflammatory bowel disease cohort. This reinforces the need for further studies in large populations that are ethnically and geographically diverse. In addition, our results show the potential to develop classifiers that may have add additional richness of context to clinical diagnosis of UC and CD with larger inflammatory bowel disease cohorts., (© 2023. The Author(s).)

Background: Surveillance of surgical site infections (SSI) relies on access to data from various sources. Insights into the practices of German hospitals conducting SSI surveillance and their information technology (IT) infrastructures are scarce. The aim of this study was to evaluate current SSI surveillance practices in German hospitals with a focus on employed IT infrastructures., Methods: German surgical departments actively participating in the national SSI surveillance module "OP-KISS" were invited in August 2020 to participate in a questionnaire-based online survey. Depending on whether departments entered all data manually or used an existing feature to import denominator data into the national surveillance database, departments were separated into different groups. Selected survey questions differed between groups., Results: Of 1,346 invited departments, 821 participated in the survey (response rate: 61%). Local IT deficits (n = 236), incompatibility of import specifications and hospital information system (n = 153) and lack of technical expertise (n = 145) were cited as the most frequent reasons for not using the denominator data import feature. Conversely, reduction of workload (n = 160) was named as the main motivation to import data. Questions on data availability and accessibility in the electronic hospital information system (HIS) and options to export data from the HIS for the purpose of surveillance, yielded diverse results. Departments utilizing the import feature tended to be from larger hospitals with a higher level of care., Conclusions: The degree to which digital solutions were employed for SSI surveillance differed considerably between surgical departments in Germany. Improving availability and accessibility of information in HIS and meeting interoperability standards will be prerequisites for increasing the amount of data exported directly from HIS to national databases and laying the foundation for automated SSI surveillance on a broad scale., (© 2023. The Author(s).)

This position paper, developed by an interdisciplinary expert group of neonatologists, paediatric infectious disease physicians, clinical pharmacists and specialists for the prevention and control of nosocomial infections, describes the "Good handling practice of medicines parenterally administered to patients on NICUs". It takes equal account of patient safety and the specialties of neonatal intensive care regarding feasibility and proportionality. The overall concept is perceived as a "learning system", in which open communication within the health-care team relating to medication errors and critical incidents enables continuous development and improvement to ensure patient safety. In our opinion, pharmacists, who are responsible for the supply of ready-to-administer parenteral medicinal products for neonatal intensive care patients, as well as the hygiene staff responsible on site are integral parts of the interdisciplinary treatment team. Risks of the current clinical practice of parenteral treatment of NICU patients are discussed in detail and recommendations for safety-relevant procedures are given., Competing Interests: The authors declare that they have no competing interests., (Copyright © 2023 Krämer et al.)

Most detailed patient information in real-world data (RWD) is only consistently available in free-text clinical documents. Manual curation is expensive and time consuming. Developing natural language processing (NLP) methods for structuring RWD is thus essential for scaling real-world evidence generation. We propose leveraging patient-level supervision from medical registries, which are often readily available and capture key patient information, for general RWD applications. We conduct an extensive study on 135,107 patients from the cancer registry of a large integrated delivery network (IDN) comprising healthcare systems in five western US states. Our deep-learning methods attain test area under the receiver operating characteristic curve (AUROC) values of 94%-99% for key tumor attributes and comparable performance on held-out data from separate health systems and states. Ablation results demonstrate the superiority of these advanced deep-learning methods. Error analysis shows that our NLP system sometimes even corrects errors in registrar labels., Competing Interests: The scope of this work is strictly within research exploration and does not involve any Microsoft product or commercial sponsorship. However, by way of disclosure, S.P., M.W., R.R., R.T., N.U., M.L., Y.G., N.V., T.N., and H.P. are employees of Microsoft, as denoted in the authorship., (© 2023 The Authors.)

Inflammatory myofibroblastic tumor (IMT) of the uterus is a rare mesenchymal tumor with largely benign behavior; however, a small subset demonstrate aggressive behavior. While clinicopathologic features have been previously associated with aggressive behavior, these reports are based on small series, and these features are imperfect predictors of clinical behavior. IMTs are most commonly driven by ALK fusions, with additional pathogenic molecular alterations being reported only in rare examples of extrauterine IMTs. In this study, a series of 11 uterine IMTs, 5 of which demonstrated aggressive behavior, were evaluated for clinicopathologic variables and additionally subjected to capture-based next-generation sequencing with or without whole-transcriptome RNA sequencing. In the 6 IMTs without aggressive behavior, ALK fusions were the sole pathogenic alteration. In contrast, all 5 aggressive IMTs harbored pathogenic molecular alterations and numerous copy number changes in addition to ALK fusions, with the majority of the additional alterations present in the primary tumors. We combined our series with cases previously reported in the literature and performed statistical analyses to propose a novel clinicopathologic risk stratification score assigning 1 point each for: age above 45 years, size≥5 cm,≥4 mitotic figures per 10 high-power field, and infiltrative borders. No tumors with 0 points had an aggressive outcome, while 21% of tumors with 1 to 2 points and all tumors with ≥3 points had aggressive outcomes. We propose a 2-step classification model that first uses the clinicopathologic risk stratification score to identify low-risk and high-risk tumors, and recommend molecular testing to further classify intermediate-risk tumors., Competing Interests: Conflicts of Interest and Source of Funding: This study was funded by the UCSF Department of Pathology Clinical Research Endowment awards granted to N.R.L., K.G., and S.E.U. J.T.R. reports that his spouse receives salary and stock options from Merck and Co. For the remaining authors none were declared., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Tumor mutational burden (TMB), a surrogate for tumor neoepitope burden, is used as a pan-tumor biomarker to identify patients who may benefit from anti-program cell death 1 (PD1) immunotherapy, but it is an imperfect biomarker. Multiple additional genomic characteristics are associated with anti-PD1 responses, but the combined predictive value of these features and the added informativeness of each respective feature remains unknown. We evaluated whether machine learning (ML) approaches using proposed determinants of anti-PD1 response derived from whole exome sequencing (WES) could improve prediction of anti-PD1 responders over TMB alone. Random forest classifiers were trained on publicly available anti-PD1 data (n = 104), and subsequently tested on an independent anti-PD1 cohort (n = 69). Both the training and test datasets included a range of cancer types such as non-small cell lung cancer (NSCLC), head and neck squamous cell carcinoma (HNSCC), melanoma, and smaller numbers of patients from other tumor types. Features used include summaries such as TMB and number of frameshift mutations, as well as more gene-level features such as counts of mutations associated with immune checkpoint response and resistance. Both ML algorithms demonstrated area under the receiver-operator curves (AUC) that exceeded TMB alone (AUC 0.63 "human-guided," 0.64 "cluster," and 0.58 TMB alone). Mutations within oncogenes disproportionately modulate anti-PD1 responses relative to their overall contribution to tumor neoepitope burden. The use of a ML algorithm evaluating multiple proposed genomic determinants of anti-PD1 responses modestly improves performance over TMB alone, highlighting the need to integrate other biomarkers to further improve model performance., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)

Introduction: Parenteral nutrition, usually indicated for preterm infants with a birthweight<1500 g and sick newborns, enables the supply with critical nutrients. As a high degree of therapy safety is required, a European guideline provides recommendations for safe therapy procedures. The present project aimed to evaluate the implementation of the European guideline in German perinatal centers and to identify possible barriers that impede its implementation. A further goal was to develop solution approaches to overcome possible barriers., Methods and Results: A multidisciplinary cooperation conducted an online survey questioning the current implementation procedures of the European guideline among pediatricians and hospital pharmacists. Results show barriers in the provisioning process of parenteral nutrition that hinder a guideline-compliant implementation in practice. Based on results of this survey, an expert network developed an interactive toolkit with simplified guideline recommendations, guideline-compliant advice for practice, best-practice examples, forms, and handouts. It seeks to encourage critical reflection of routine processes and provides concrete solutions to overcome barriers in practice., Conclusion: The current procedures related to parenteral nutrition deviate from guideline recommendations. The developed toolkit provides practice-oriented support aiming to enhance the guideline-compliant implementation of parenteral nutrition in perinatal centers., Competing Interests: EFCNI erhielt einen Educational Grant von Baxter zur Projektdurchführung. Es bestehen keine weiteren Interessenskonflikte., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objectives: To determine the influence of a national surveillance system for neonates (NEO-KISS) in neonatal intensive care units (NICUs) on consumption of antibacterial and to identify risk factors for prescriptions., Methods: Data on antibacterial use between 2013 and 2019 from 231 NICUs in Germany was analyzed in this longitudinal study after introduction of a mandatory module for surveillance of antibacterial consumption in preterm infants. 59,411 newborns with a birth weight under 1500 gs were under surveillance in NEO-KISS during the study period. We report the development of antibacterial consumption during the days of treatment (DOT)/1000 patient days (PD) including the name of the substance administered. Risk factors for antibacterial treatment over time were analyzed., Results: A total, 2,090,341 surveillance patient days were monitored. Antibacterial consumption was 430.4 DOT/1000PD (Median 380.3; IQR: 284.2-502.7). Antibacterial use significantly decreased by 19.5% from 2013, 474.3 DOT/1000PD to 382.1 DOT/1000PD in 2019. Use of penicillins with extended spectrum (J01CA), other aminoglycosides (J01GB), glycopeptide antibacterials (J01XA and J01DH), and third-generation cephalosporins (J01DD) decreased, while use of macrolides (J01FA) and combinations of penicillins, including beta-lactamase inhibitors (J01CR), increased over time. Regression analysis identified year of birth as an independent protective factor for the prescription of antibacterials in general., Conclusion: The implementation of a national mandatory surveillance system was associated with a reduction in antibacterial consumption in preterm infants with VLBW. Surveillance of antibacterial use is an integral part of targeting antimicrobial stewardship efforts., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2022. Published by Elsevier Ltd.)

Background: One possible transmission route for nosocomial pathogens is contaminated medical devices. Formation of biofilms can exacerbate the problem. We report on a carbapenemase-producing Klebsiella pneumoniae that had caused an outbreak linked to contaminated duodenoscopes. To determine whether increased tolerance to disinfectants may have contributed to the outbreak, we investigated the susceptibility of the outbreak strain to disinfectants commonly used for duodenoscope reprocessing. Disinfection efficacy was tested on planktonic bacteria and on biofilm., Methods: Disinfectant efficacy testing was performed for planktonic bacteria according to EN standards 13727 and 14561 and for biofilm using the Bead Assay for Biofilms. Disinfection was defined as ≥ 5log 10 reduction in recoverable colony forming units (CFU)., Results: The outbreak strain was an OXA-48 carbapenemase-producing K. pneumoniae of sequence type 101. We found a slightly increased tolerance of the outbreak strain in planktonic form to peracetic acid (PAA), but not to other disinfectants tested. Since PAA was the disinfectant used for duodenoscope reprocessing, we investigated the effect of PAA on biofilm of the outbreak strain. Remarkably, disinfection of biofilm of the outbreak strain could not be achieved by the standard PAA concentration used for duodenoscope reprocessing at the time of outbreak. An increased tolerance to PAA was not observed in a K. pneumoniae type strain tested in parallel., Conclusions: Biofilm of the K. pneumoniae outbreak strain was tolerant to standard disinfection during duodenoscope reprocessing. This study establishes for the first time a direct link between biofilm formation, increased tolerance to disinfectants, reprocessing failure of duodenoscopes and nosocomial transmission of carbapenem-resistant K. pneumoniae., (© 2022. The Author(s).)

Tumor-infiltrating neoantigen-reactive T cells can mediate regression of metastatic gastrointestinal cancers yet remain poorly characterized. We performed immunological screening against personalized neoantigens in combination with single-cell RNA sequencing on tumor-infiltrating lymphocytes from bile duct and pancreatic cancer patients to characterize the transcriptomic landscape of neoantigen-reactive T cells. We found that most neoantigen-reactive CD8 + T cells displayed an exhausted state with significant CXCL13 and GZMA co-expression compared with non-neoantigen-reactive bystander cells. Most neoantigen-reactive CD4 + T cells from a patient with bile duct cancer also exhibited an exhausted phenotype but with overexpression of HOPX or ADGRG1 while lacking IL7R expression. Thus, neoantigen-reactive T cells infiltrating gastrointestinal cancers harbor distinct transcriptomic signatures, which may provide new opportunities for harnessing these cells for therapy., Competing Interests: Declaration of interests E.T. is on the scientific advisory board of PACT Pharma, Genocea Biosciences, and Turnstone Biologics. C.B.B. reports a consultant/advisory relationship with BMS, has stock ownership in and is on the scientific board of PrimeVax, and is on the scientific board of BioAI and LunaPhore. Other authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Cancer heterogeneity is a result of genetic mutations within the cancer cells. Their proliferation is not only driven by autocrine functions but also under the influence of cancer microenvironment, which consists of normal stromal cells such as infiltrating immune cells, cancer-associated fibroblasts, endothelial cells, pericytes, vascular and lymphatic channels. The relationship between cancer cells and cancer microenvironment is a critical one and we are just on the verge to understand it on a molecular level. Cancer microenvironment may serve as a selective force to modulate cancer cells to allow them to evolve into more aggressive clones with ability to invade the lymphatic or vascular channels to spread to regional lymph nodes and distant sites. It is important to understand these steps of cancer evolution within the cancer microenvironment towards invasion so that therapeutic strategies can be developed to control or stop these processes., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: Factors contributing to the spread of SARS-CoV-2 outside the acute care hospital setting have been described in detail. However, data concerning risk factors for nosocomial SARS-CoV-2 infections in hospitalized patients remain scarce. To close this research gap and inform targeted measures for the prevention of nosocomial SARS-CoV-2 infections, we analyzed nosocomial SARS-CoV-2 cases in our hospital during a defined time period., Methods: Data on nosocomial SARS-CoV-2 infections in hospitalized patients that occurred between May 2020 and January 2021 at Charité university hospital in Berlin, Germany, were retrospectively gathered. A SARS-CoV-2 infection was considered nosocomial if the patient was admitted with a negative SARS-CoV-2 reverse transcription polymerase chain reaction test and subsequently tested positive on day five or later. As the incubation period of SARS-CoV-2 can be longer than five days, we defined a subgroup of "definite" nosocomial SARS-CoV-2 cases, with a negative test on admission and a positive test after day 10, for which we conducted a matched case-control study with a one to one ratio of cases and controls. We employed a multivariable logistic regression model to identify factors significantly increasing the likelihood of nosocomial SARS-CoV-2 infections., Results: A total of 170 patients with a nosocomial SARS-CoV-2 infection were identified. The majority of nosocomial SARS-CoV-2 patients (n = 157, 92%) had been treated at wards that reported an outbreak of nosocomial SARS-CoV-2 cases during their stay or up to 14 days later. For 76 patients with definite nosocomial SARS-CoV-2 infections, controls for the case-control study were matched. For this subgroup, the multivariable logistic regression analysis revealed documented contact to SARS-CoV-2 cases (odds ratio: 23.4 (95% confidence interval: 4.6-117.7)) and presence at a ward that experienced a SARS-CoV-2 outbreak (odds ratio: 15.9 (95% confidence interval: 2.5-100.8)) to be the principal risk factors for nosocomial SARS-CoV-2 infection., Conclusions: With known contact to SARS-CoV-2 cases and outbreak association revealed as the primary risk factors, our findings confirm known causes of SARS-CoV-2 infections and demonstrate that these also apply to the acute care hospital setting. This underscores the importance of rapidly identifying exposed patients and taking adequate preventive measures., (© 2022. The Author(s).)