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Background: Rapid on-site evaluation (ROSE) plays an important role during transbronchial sampling, providing an intraoperative cytopathologic evaluation. However, the shortage of cytopathologists limits its wide application. This study aims to develop a deep learning model to automatically analyze ROSE cytological images. Methods: The hierarchical multi-label lung cancer subtyping (HMLCS) model that combines whole slide images of ROSE slides and serum biological markers was proposed to discriminate between benign and malignant lesions and recognize different subtypes of lung cancer. A dataset of 811 ROSE slides and paired serum biological markers was retrospectively collected between July 2019 and November 2020, and randomly divided to train, validate, and test the HMLCS model. The area under the curve (AUC) and accuracy were calculated to assess the performance of the model, and Cohen's kappa (κ) was calculated to measure the agreement between the model and the annotation. The HMLCS model was also compared with professional staff. Results: The HMLCS model achieved AUC values of 0.9540 (95% confidence interval [CI]: 0.9257–0.9823) in malignant/benign classification, 0.9126 (95% CI: 0.8756–0.9365) in malignancy subtyping (non-small cell lung cancer [NSCLC], small cell lung cancer [SCLC], or other malignancies), and 0.9297 (95% CI: 0.9026–0.9603) in NSCLC subtyping (lung adenocarcinoma [LUAD], lung squamous cell carcinoma [LUSC], or NSCLC not otherwise specified [NSCLC-NOS]), respectively. In total, the model achieved an AUC of 0.8721 (95% CI: 0.7714–0.9258) and an accuracy of 0.7184 in the six-class classification task (benign, LUAD, LUSC, NSCLC-NOS, SCLC, or other malignancies). In addition, the model demonstrated a κ value of 0.6183 with the annotation, which was comparable to cytopathologists and superior to trained bronchoscopists and technicians. Conclusion: The HMLCS model showed promising performance in the multiclassification of lung lesions or intrathoracic lymphadenopathy, with potential application to provide real-time feedback regarding preliminary diagnoses of specimens during transbronchial sampling procedures. Clinical trial number: Not applicable. [ABSTRACT FROM AUTHOR]

Necrotizing enterocolitis (NEC) is the most prevalent and potentially fatal intestinal injury mainly affecting premature infants, with significant long-term consequences for those who survive. This review explores the scale of the problem, highlighting advancements in epidemiology, the understanding of pathophysiology, and improvements in the prediction and diagnosis of this complex, multifactorial, and multifaced disease. Additionally, we focus on the potential role of metabolomics in distinguishing NEC from other conditions, which could allow for an earlier and more accurate classification of intestinal injuries in infants. By integrating metabolomic data with other diagnostic approaches, it is hoped to enhance our ability to predict outcomes and tailor treatments, ultimately improving care for affected infants. [ABSTRACT FROM AUTHOR]

Background: Cryptosporidium spp. is a ubiquitous, globally distributed intestinal protozoan infecting humans and at least 260 animal hosts. Due to close human contact with pet dogs and identification of zoonotic Cryptosporidium species and subtypes in these animals, dog health is not only a veterinarian issue but also a public health issue. This study aimed to understand occurrence and genetic characterization at both genotype and subtype levels in pet dogs in Yunnan Province, China. Results: A total of 589 fresh fecal specimens were collected from adult pet dogs in the rural areas of eight cities/autonomous prefectures of Yunnan Province, China. 16 fecal specimens were positive for Cryptosporidium spp. by polymerase chain reaction (PCR) amplification and sequence analysis of the small subunit ribosomal RNA (SSU rRNA) gene, with an average occurrence rate of 2.7% (16/589) being observed. Three zoonotic Cryptosporidium species were identified: C. parvum (n = 7), C. suis (n = 5) and C. canis (n = 4). At the 60-kDa glycoprotein (gp60) locus, only three C. parvum and two C. canis specimens were successfully amplified and sequenced, with subtype IIaA17G2R1 (n = 3) and subtypes XXa4 (n = 1) and XXa5 (n = 1) being identified, respectively. Conclusions: The present finding of three zoonotic Cryptosporidium species in dogs implied that dogs infected with Cryptosporidium spp. may pose a threat to human health. C. suis was identified in dogs in this study for the first time, expanding the host range of this species. Identification of C. parvum subtype IIaA17G2R1 and C. canis subtypes XXa4 and XXa5 will be helpful to explore the source attribution of infection/contamination and assess the transmission dynamics of C. parvum and C. canis in the investigated areas in the future. [ABSTRACT FROM AUTHOR]

Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample. We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes. The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation. Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms. [ABSTRACT FROM AUTHOR]

Purpose: To classify CVI subtypes and compare the added value of an extensive test battery over a limited test battery in subtype classification of cerebral visual impairment (CVI) in children. Methods: Seventy-five children with a clinical diagnosis of CVI (median [IQR] age: 9 [7–12] years) were identified from the medical records. The extensive test battery included visual acuity, contrast sensitivity, ocular alignment, eye movement analysis, visual field analysis, optic nerve head evaluation, and evaluation of visual perception. The limited test battery included visual acuity, contrast sensitivity, ocular alignment, and evaluation of visual perception. Principal component analysis (PCA) followed by cluster analysis was done, for both test batteries separately, to determine the optimum subtype classification for CVI. Results: Fifty-one participants with an extensive test battery with mild to moderate visual impairment were included in the main analysis. This resulted in four CVI subtypes for the extensive test battery (subtle characteristics, higher-level visual function deficits, lower-level visual function deficits, and higher- and lowerlevel visual function deficits) and three CVI subtypes for the limited test battery (subtle characteristics, higher-level visual function deficits, and higher- and lower- level visual function deficits). There were significant differences between the subtypes for 9 out of 10 measures of the extensive and all 4 measures of the limited test battery (p  <  0.05). The subtle characteristics subtype (extensive n  =  19, limited n  =  15) showed near normal lower and higher-level visual functions in both test batteries. The higher-level visual function deficits subtype (extensive n  =  18, limited n  =  24) showed near normal visual acuity combined with significant visual perceptual deficits in both test batteries; accompanied by visual pathways defects and abnormal eye movement behavior in the extensive test battery. The higher- and lower- level visual function deficits subtype (extensive n  =  4, limited n  =  12) showed both higher and lower-level visual function deficits in both test batteries, but application of the extensive test battery revealed additional visual pathways defects and abnormal eye movement behavior. The lower-level visual function deficits CVI subtype (extensive n  =  10) was a new subtype identified by the extensive test battery. This subtype showed lower-level visual function deficits together with abnormal eye movement measures. Conclusion: This data-driven study has provided meaningful CVI subtype classifications based on the outcomes of various key functional and structural measures in CVI diagnosis. Comparison of the extensive test battery to the limited test battery revealed the added value of an extensive test battery in classifying CVI. The outcomes of this study, therefore, have provided a new direction in the area of CVI classification. [ABSTRACT FROM AUTHOR]

Introduction: Major histocompatibility complex class II molecule (MHC-II) is pivotal in anti-tumor immunity, and targeting MHC-II in tumors may help improve patient survival. But function of MHC-II in the immunotherapy and prognosis of lung adenocarcinoma (LUAD) patients has not been thoroughly studied and reported. Methods: We selected LUAD-related MHC-II genes from public databases based on previous literature reports. We identified different subtypes according to expression differences of these genes in different LUAD samples through cluster analysis. We used R package to conduct a series of analyses on different subtypes, exploring their survival differences, gene expression differences, pathway enrichment differences, and differences in immune characteristics and immune therapy. Finally, we screened potential drugs from the cMAP database. Results: We identified two MHC-II-related LUAD subtypes. Our analyses presented that patients with cluster2 subtype showed better prognosis, higher immune scores, higher levels of immune cell infiltration and immune function activation. In addition, patients with this subtype had higher immunophenoscore, lower TIDE scores, and DEPTH scores. We also identified 10 small molecule drugs, such as lenalidomide, VX-745, and tyrphostin-AG-1295. Conclusion: Overall, MHC-II is not only a potential biomarker for accurately distinguishing LUAD subtypes but also a predictive factor for their survival. Our study offers novel insights into understanding of impact of MHC-II in LUAD and offers a new perspective for improving the accurate classification of LUAD patients and enhancing drug treatment. [ABSTRACT FROM AUTHOR]

Gliomas are highly heterogeneous in molecular, histology, and microenvironment. However, a classification of gliomas by integrating different tumor microenvironment (TME) components remains unexplored. Based on the enrichment scores of 17 pathways involved in immune, stromal, DNA repair, and nervous system signatures in diffuse gliomas, we performed consensus clustering to uncover novel subtypes of gliomas. Consistently in three glioma datasets (TCGA-glioma, CGGA325, and CGGA301), we identified three subtypes: Stromal-enriched (Str-G), Nerve-enriched (Ner-G), and mixed (Mix-G). Ner-G was charactered by low immune infiltration levels, stromal contents, tumor mutation burden, copy number alterations, DNA repair activity, cell proliferation, epithelial-mesenchymal transformation, stemness, intratumor heterogeneity, androgen receptor expression and EGFR, PTEN, NF1 and MUC16 mutation rates, while high enrichment of neurons and nervous system pathways, and high tumor purity, estrogen receptor expression, IDH1 and CIC mutation rates, temozolomide response rate and overall and disease-free survival rates. In contrast, Str-G displayed contrastive characteristics to Ner-G. Our analysis indicates that the heterogeneity between glioma cells and neurons is lower than that between glioma cells and immune and stromal cells. Furthermore, the abundance of neurons is positively associated with clinical outcomes in gliomas, while the enrichment of immune and stromal cells has a negative association with them. Our classification method provides new insights into the tumor biology of gliomas, as well as clinical implications for the precise management of this disease. [ABSTRACT FROM AUTHOR]

Abstract Background Rapid on-site evaluation (ROSE) plays an important role during transbronchial sampling, providing an intraoperative cytopathologic evaluation. However, the shortage of cytopathologists limits its wide application. This study aims to develop a deep learning model to automatically analyze ROSE cytological images. Methods The hierarchical multi-label lung cancer subtyping (HMLCS) model that combines whole slide images of ROSE slides and serum biological markers was proposed to discriminate between benign and malignant lesions and recognize different subtypes of lung cancer. A dataset of 811 ROSE slides and paired serum biological markers was retrospectively collected between July 2019 and November 2020, and randomly divided to train, validate, and test the HMLCS model. The area under the curve (AUC) and accuracy were calculated to assess the performance of the model, and Cohen’s kappa (κ) was calculated to measure the agreement between the model and the annotation. The HMLCS model was also compared with professional staff. Results The HMLCS model achieved AUC values of 0.9540 (95% confidence interval [CI]: 0.9257–0.9823) in malignant/benign classification, 0.9126 (95% CI: 0.8756–0.9365) in malignancy subtyping (non-small cell lung cancer [NSCLC], small cell lung cancer [SCLC], or other malignancies), and 0.9297 (95% CI: 0.9026–0.9603) in NSCLC subtyping (lung adenocarcinoma [LUAD], lung squamous cell carcinoma [LUSC], or NSCLC not otherwise specified [NSCLC-NOS]), respectively. In total, the model achieved an AUC of 0.8721 (95% CI: 0.7714–0.9258) and an accuracy of 0.7184 in the six-class classification task (benign, LUAD, LUSC, NSCLC-NOS, SCLC, or other malignancies). In addition, the model demonstrated a κ value of 0.6183 with the annotation, which was comparable to cytopathologists and superior to trained bronchoscopists and technicians. Conclusion The HMLCS model showed promising performance in the multiclassification of lung lesions or intrathoracic lymphadenopathy, with potential application to provide real-time feedback regarding preliminary diagnoses of specimens during transbronchial sampling procedures. Clinical trial number Not applicable.

Abstract Background Cryptosporidium spp. is a ubiquitous, globally distributed intestinal protozoan infecting humans and at least 260 animal hosts. Due to close human contact with pet dogs and identification of zoonotic Cryptosporidium species and subtypes in these animals, dog health is not only a veterinarian issue but also a public health issue. This study aimed to understand occurrence and genetic characterization at both genotype and subtype levels in pet dogs in Yunnan Province, China. Results A total of 589 fresh fecal specimens were collected from adult pet dogs in the rural areas of eight cities/autonomous prefectures of Yunnan Province, China. 16 fecal specimens were positive for Cryptosporidium spp. by polymerase chain reaction (PCR) amplification and sequence analysis of the small subunit ribosomal RNA (SSU rRNA) gene, with an average occurrence rate of 2.7% (16/589) being observed. Three zoonotic Cryptosporidium species were identified: C. parvum (n = 7), C. suis (n = 5) and C. canis (n = 4). At the 60-kDa glycoprotein (gp60) locus, only three C. parvum and two C. canis specimens were successfully amplified and sequenced, with subtype IIaA17G2R1 (n = 3) and subtypes XXa4 (n = 1) and XXa5 (n = 1) being identified, respectively. Conclusions The present finding of three zoonotic Cryptosporidium species in dogs implied that dogs infected with Cryptosporidium spp. may pose a threat to human health. C. suis was identified in dogs in this study for the first time, expanding the host range of this species. Identification of C. parvum subtype IIaA17G2R1 and C. canis subtypes XXa4 and XXa5 will be helpful to explore the source attribution of infection/contamination and assess the transmission dynamics of C. parvum and C. canis in the investigated areas in the future.

An increased risk for human infection with avian influenza A(H5N1) viruses is of concern. We developed an internally controlled, dual-target reverse transcription PCR for influenza A(H5) subtyping. This test could be used to detect influenza A(H5) in clinical samples.

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Diarrheagenic Escherichia coli (DEC) is a kind of foodborne pathogen that poses a significant threat to both food safety and human health. To address the current challenges of high prevalence and difficult subtyping of DEC, this study developed a method that combined multiplex PCR with high-resolution melting (HRM) analysis for subtyping 5 kinds of DEC. The target genes are amplified by multiplex PCR in a single well, and HRM curve analysis was applied for distinct amplicons based on different melting temperature (Tm) values. The method enables discrimination of different DEC types based on characteristic peaks and distinct Tm values in the thermal melting curve. The assay exhibited 100% sensitivity and 100% specificity with a detection limit of 0.5 to 1 ng/μL. The results showed that different DNA concentrations did not influence the subtyping results, demonstrating this method owed high reliability and stability. In addition, the method was also used for the detection and subtyping of DEC in milk. This method streamlines operational procedures, shorts the detection time, and offers a novel tool for subtyping DEC. [ABSTRACT FROM AUTHOR]

Cryptosporidium infection is a common occurrence in rodents worldwide. In this study, 435 wild brown rats were captured from an animal feedlot in Xinjiang, China, with a fecal sample obtained directly from the rectal contents of each rat. The DNA extracted from these fecal samples was analyzed for Cryptosporidium spp. using PCR targeting the SSU rRNA gene. The prevalence of Cryptosporidium infection in brown rats was found to be 5.5% (24 out of 435). Interestingly, the infection rates varied among different animal enclosures, with rates of 0% in the chicken coop (0/51), cowshed (0/3), and varying rates in other areas including the sheepfold (6.1%, 6/98), the pigsty (7.6%, 10/132), the dovecote (7.0%, 5/71), and outdoor environments (3.8%, 3/80). The study identified three species and one genotype of Cryptosporidium, namely C. occultus (n = 10), C. parvum (n = 4), C. ditrichi (n = 1), and Cryptosporidium rat genotype IV (n = 9). Additionally, two of the C. parvum isolates were successfully subtyped as IIdA19G1 (n = 2) at the gp60 gene. These results offer valuable insights into the prevalence and genetic diversity of Cryptosporidium in brown rats within the region. [ABSTRACT FROM AUTHOR]

Tick‐borne encephalitis virus (TBEV) is a significant cause of flaviviral infections affecting the human central nervous system, primarily transmitted through tick bites and the consumption of unpasteurized milk. This study aimed to assess the prevalence of TBEV and identify new natural foci of TBEV in livestock milk. In this cross‐sectional study, unpasteurized milk samples were collected from livestock reared on farms and analysed for the presence and subtyping of TBEV using nested reverse transcription‐polymerase chain reaction , alongside the detection of anti‐TBEV total IgG antibodies using ELISA. The findings revealed that the highest prevalence of TBEV was observed in goat and sheep milk combined, whereas no TBEV was detected in cow milk samples. All identified strains were of the Siberian subtype. Moreover, the highest prevalence of anti‐TBEV antibodies was detected in sheep milk. These results uncover new foci of TBEV in Iran, underscoring the importance of thermal processing (pasteurization) of milk prior to consumption to mitigate the risk of TBEV infection. [ABSTRACT FROM AUTHOR]

The current study demonstrates that an individual's resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9–11, we identified four distinct RSFC subtypes. We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

Aim During the pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), many countries reported a significant decrease in the prevalence of influenza virus cases. The study aimed to characterize the flu seasons from 2018 to 2023 in Sarajevo Canton, Bosnia and Herzegovina (B&H), and to assess the possible impact of the SARS-CoV-2 pandemic on the influenza A and B virus circulation. Methods The CDC Human Influenza Virus Real-Time RT-PCR Diagnostic Panels were used for the detection of influenza virus A and B, and subtyping of influenza virus A (H1pdm09 virus and H3). The data for this regis-try-based retrospective study were collected at the Clinical Centre of the University of Sarajevo, Unit for Clinical Microbiology (the laboratory that acts as a referral for the detection and characterization of influenza virus and SARS-CoV-2 in Federation B&H).Results In the 2018/2019 and 2019/2020, an equal percentage of positive cases was recorded (148/410; 36%, and 182/504; 36%, respectively). The absence of the influenza virus was observed in 2020/2021. During 2021/2022, influenza virus was detected among 19/104 (18%) patients and slightly increased in 2022/2023 (45/269; 17%). The switch of the influenza B virus lineage was observed.Conclusion The SARS-CoV-2 virus had an impact on the prevalence of influenza virus infection among the population of the Sarajevo Canton, B&H. Since the interactions between these two viruses are not entirely clear, awareness of a possible threat to public health is crucial.

Summary: Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors. In this study, we develop a clinically useful computational pathology platform for NSCLC that can be a foundation for multiple downstream applications and provide immediate value for patient care optimization and individualization. We train the primary multi-class tissue segmentation algorithm on a substantial, high-quality, manually annotated dataset of whole-slide images with lung adenocarcinoma and squamous cell carcinomas. We investigate two downstream applications. NSCLC subtyping algorithm is trained and validated using a large, multi-institutional (n = 6), multi-scanner (n = 5), international cohort of NSCLC cases (slides/patients 4,097/1,527). Moreover, we develop four AI-derived, fully explainable, quantitative, prognostic parameters (based on tertiary lymphoid structure and necrosis assessment) and validate them for different clinical endpoints. The computational platform enables the high-precision, quantitative analysis of H&E-stained slides. The developed prognostic parameters facilitate robust and independent risk stratification of patients with NSCLC.

Abstract Background Monitoring of infectious diseases on swine farms requires a high diagnostic sensitivity and specificity of the test system. Moreover, particularly in cases of swine influenza A virus (swIAV) it is desirable to include characterization of the virus as precisely as possible. This is indispensable for strategies concerning prophylaxis of swIAV and furthermore, to meet the requirements of a purposeful monitoring of newly emerging swIAV strains in terms of vaccine design and public health. Within the present cross-sectional study, we compared the diagnostic value of group samples (wipes of surfaces with direct contact to mouth/nose, dust wipes, udder skin wipes, oral fluids) to individual samples (nasal swabs, tracheobronchial swabs) for both swIAV identification and characterization. Sampling included different stages of pig production on 25 sow farms with attached nursery considered as enzootically infected with swIAV. Firstly, samples were analyzed for IAV genome and subsequently samples with Ct-values

Abstract Introduction Papillary renal cell carcinoma (pRCC) is the second most common histology of renal cell carcinoma (RCC), accounting for 10–15% of cases. Traditionally, pRCC is divided into type 1 and type 2, although this division is currently debated as a prognostic factor of survival. Our aim was to investigate the epidemiology and survival of the pRCC subtypes in a whole nation cohort of patients during a 50-year period. Materials and methods A Population based retrospective study including consecutive cases of RCC in Iceland from 1971–2020. Comparisons were made between histological classifications of RCC, with emphasis on pRCC subtypes (type 1 vs. 2) for outcome estimation. Changes in RCC incidence were analyzed in 5-year intervals after age standardization. The Kaplan–Meier method and Cox regression were used for outcome analysis. Results A total of 1.725 cases were identified, with 74.4%, 2.1% and 9.2% having clear cell (ccRCC), chromophobe (chRCC), and pRCC, respectively. The age standardized incidence (ASI) of pRCC was 1.97/100.000 for males and 0.5/100.000 for females, and the proportion of pRCC increased from 3.7% to 11.5% between the first and last intervals of the study (p

Cryptosporidium spp., Giardia intestinalis and microsporidia are unicellular opportunistic pathogens that can cause gastrointestinal infections in both animals and humans. Since companion animals may serve as a source of infection, the aim of the present screening study was to analyse the prevalence of these intestinal protists in fecal samples collected from dogs living in 10 animal shelters in central Europe (101 dogs from Poland and 86 from the Czech Republic), combined with molecular subtyping of the detected organisms in order to assess their genetic diversity. Genus-specific polymerase chain reactions were performed to detect DNA of the tested species and to conduct molecular subtyping in collected samples, followed by statistical evaluation of the data obtained (using χ2 or Fisher's tests). The observed prevalence was 15.5, 10.2, 1 and 1% for G. intestinalis, Enterocytozoon bieneusi, Cryptosporidium spp. and Encephalitozoon cuniculi, respectively. Molecular evaluation has revealed the predominance of dog-specific genotypes (Cryptosporidium canis XXe1 subtype; G. intestinalis assemblages C and D; E. cuniculi genotype II; E. bieneusi genotypes D and PtEbIX), suggesting that shelter dogs do not pose a high risk of human transmission. Interestingly, the percentage distribution of the detected pathogens differed between both countries and individual shelters, suggesting that the risk of infection may be associated with conditions typical of a given location.

Prostate cancer impacts millions of men worldwide and causes significant disease burden. Glycosylation is the post-translational modification offering novel therapeutics for prostate cancer. The scRNA-seq data is combined with bulk RNA-seq data of prostate cancer to understand the glycosylation role and identify the therapeutic targets. This study aims to investigate the differences within tumor and the role of glycosylation. The findings confirm that glycosylation can establish multiple cell biomarkers and divide the cell subtypes of prostate cancer. The specific cell subtypes have diverse functions in cell interactions, transcript activity, prognosis and immunotherapy response, such as UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 7+ (GALNT7+) epithelial cells and UDP Glucose Ceramide Glucosyltransferase+ (UGCG+) cancer associated macrophages. These outcomes assist in the better understanding of prostate cancer and provide new approach of the targeted therapy.

IntroductionMuscle-invasive bladder cancer (MIBC) is a heterogeneous disease with several taxonomic molecular subtypes showing different genetic, clinical, and epidemiological profiles. It has been suggested that MIBC-subtypes follow different tumorigenesis pathways playing decisive roles at different stages of tumor development, resulting in distinct tumor microenvironment containing both innate and adaptive immune cells (T and B lymphocytes). We aim to characterize the MIBC tumor microenvironment by analyzing the tumor-infiltrating B and T cell repertoire according to the taxonomic molecular subtypes.MethodsRNAseq data from 396 MIBC samples included in TCGA were considered. The subtype information was collected from the international consensus taxonomic classification describing six subtypes: Basal/Squamous-like (Ba/Sq), Luminal papillary (LumP), Luminal non-Specify (LumNS), Luminal unstable (LumU), Stroma-rich, and Neuroendocrine-like (NE-like). Using MiXCR, we mapped the RNA read sequences to their respective B-cell receptor (BCR) and T-cell receptor (TCR) clonotypes. To evaluate the BCR and TCR differences among subtypes, we compared diversity measures (richness and diversity) using a Wilcoxon test and we performed a network analysis to characterize the clonal expansion. For the survival analysis stratified by subtypes, Cox regression models adjusted for age, region, and pathological stage were performed.ResultsOverall, we found different patterns of tumor-infiltrating immune repertoire among the different MIBC subtypes. Stroma-rich and Ba/Sq tumors showed the highest BCR and TCR infiltration while LumP showed the lowest. In addition, we observed that the Ba/Sq and Stroma-rich tumors were more clonally expanded than the Luminal subtypes. Moreover, higher TCR richness and diversity were significantly associated with better survival in the Stroma-rich and Ba/Sq subtypes.DiscussionThis study provides evidence that MIBC subtypes present differences in the tumor microenvironment, in particular, the Ba/Sq and the Stroma-rich are related with a higher tumoral-infiltrating immune repertoire, which seems to be translated into better survival. Determining the causes of the different tumoral-infiltrating immune repertoire according to the MIBC molecular subtypes will help to improve our understanding of the disease and the distinct responses to immunotherapy of MIBC.

Background: Monitoring of infectious diseases on swine farms requires a high diagnostic sensitivity and specificity of the test system. Moreover, particularly in cases of swine influenza A virus (swIAV) it is desirable to include characterization of the virus as precisely as possible. This is indispensable for strategies concerning prophylaxis of swIAV and furthermore, to meet the requirements of a purposeful monitoring of newly emerging swIAV strains in terms of vaccine design and public health. Within the present cross-sectional study, we compared the diagnostic value of group samples (wipes of surfaces with direct contact to mouth/nose, dust wipes, udder skin wipes, oral fluids) to individual samples (nasal swabs, tracheobronchial swabs) for both swIAV identification and characterization. Sampling included different stages of pig production on 25 sow farms with attached nursery considered as enzootically infected with swIAV. Firstly, samples were analyzed for IAV genome and subsequently samples with Ct-values < 32 were subtyped by multiplex RT-qPCR. Results: Nasal swabs of suckling piglets and nursery pigs resulted in a higher odds to detect swIAV (p < 0.001) and to identify swIAV subtypes by RT-qPCR (p < 0.05) compared to nasal swabs of sows. In suckling piglets, significant higher rates of swIAV detection could be observed for nasal swabs (p = 0.007) and sow udder skin wipes (p = 0.036) compared to contact wipes. In the nursery, group sampling specimens were significantly more often swIAV positive compared to individual samples (p < 0.01), with exception of the comparison between contact wipes and nasal swabs (p = 0.181). However, in general nasal swabs were more likely to have Ct-value < 32 and thus, to be suitable for subtyping by RT-qPCR compared to dust wipes, contact wipes, udder skin wipes and tracheobronchial swabs (p < 0.05). Interestingly, different subtypes were found in different age groups as well as in different specimens in the same holding. Conclusion: Although population-based specimens are highly effective for swIAV monitoring, nasal swabs are still the preferable sampling material for the surveillance of on-farm circulating strains due to significantly higher virus loads. Remarkably, sampling strategies should incorporate suckling piglets and different age groups within the nursery to cover as many as possible of the on-farm circulating strains. [ABSTRACT FROM AUTHOR]

Introduction: Papillary renal cell carcinoma (pRCC) is the second most common histology of renal cell carcinoma (RCC), accounting for 10–15% of cases. Traditionally, pRCC is divided into type 1 and type 2, although this division is currently debated as a prognostic factor of survival. Our aim was to investigate the epidemiology and survival of the pRCC subtypes in a whole nation cohort of patients during a 50-year period. Materials and methods: A Population based retrospective study including consecutive cases of RCC in Iceland from 1971–2020. Comparisons were made between histological classifications of RCC, with emphasis on pRCC subtypes (type 1 vs. 2) for outcome estimation. Changes in RCC incidence were analyzed in 5-year intervals after age standardization. The Kaplan–Meier method and Cox regression were used for outcome analysis. Results: A total of 1.725 cases were identified, with 74.4%, 2.1% and 9.2% having clear cell (ccRCC), chromophobe (chRCC), and pRCC, respectively. The age standardized incidence (ASI) of pRCC was 1.97/100.000 for males and 0.5/100.000 for females, and the proportion of pRCC increased from 3.7% to 11.5% between the first and last intervals of the study (p < 0.001). Age standardized cancer specific mortality (ASCSM) of pRCC was 0.6/100.000 and 0.19/100.000 for males and females, respectively. The annual average increase in ASI was 3.6% for type 1 pRCC, but the ASI for type 2 pRCC and ASCSM for both subtypes did not change significantly. Male to female ratio was 4.4 for type 1 pRCC and 2.3 for type 2. The average tumor size for type 1 and 2 was 58.8 and 73.7 mm, respectively. Metastasis at diagnosis was found in 8.7% in the type 1 pRCC, compared to 30.0% of patients with type 2 pRCC (p < 0.001). Estimated 5-year cancer-specific survival (CSS) were 94.4%, 80.7%, and 69.3% for chRCC, pRCC and ccRCC, respectively (p < 0.001). For the pRCC subtypes, type 1 was associated with better 5-year CSS than type 2 (86.3% vs. 66.0%, p < 0.001), although this difference was not significant after adjusting for cancer stage and grading. Conclusions: pRCC histology was slightly less common in Iceland than in other countries. Males are more than three times more likely to be diagnosed with pRCC, compared to other RCC histologies. The subtype of pRCC was not found to be an independent risk factor for worse survival, and as suggested by the most recent WHO Classification of Urinary Tumors, grade and TNM-stage seem to be the most important factors for estimation of survival for pRCC patients. [ABSTRACT FROM AUTHOR]

Cognitive aging is a complex and dynamic process characterized by changes due to genetics and environmental factors, including lifestyle choices and environmental exposure, which contribute to the heterogeneity observed in cognitive outcomes. This heterogeneity is particularly pronounced among older adults, with some individuals maintaining stable cognitive function while others experience complex, non-linear changes, making it difficult to identify meaningful decline accurately. Current research methods range from population-level modeling to individual-specific assessments. In this work, we review these methodologies and propose that population subtyping should be considered as a viable alternative. This approach relies on early individual-specific detection methods that can lead to an improved understanding of changes in individual cognitive trajectories. The improved understanding of cognitive trajectories through population subtyping can lead to the identification of meaningful changes and the determination of timely, effective interventions. This approach can aid in informing policy decisions and in developing targeted interventions that promote cognitive health, ultimately contributing to a more personalized understanding of the aging process within society and reducing the burden on healthcare systems. [ABSTRACT FROM AUTHOR]

Purpose: Cancer cells with stem cell-like properties may contribute to cancer development and therapy resistance. The advancement of multi-omics technology has sparked interest in exploring cancer stemness from a multi-omics perspective. However, there is a limited number of studies that have attempted to subtype cancer by combining different types of stem cell signatures. Methods: In this study, 10,323 cancer specimens from 33 TCGA cancer types were clustered based on the enrichment scores of six stemness gene sets, representing two types of stem cell backgrounds: embryonic stem cells (ESCs) and hematopoietic stem cells (HSCs). Results: We identified four subtypes of pan-cancer, termed StC1, StC2, StC3 and StC4, which displayed distinct molecular and clinical features, including stemness, genome integrity, intratumor heterogeneity, methylation levels, tumor microenvironment, tumor progression, responses to chemotherapy and immunotherapy, and survival prognosis. Importantly, this subtyping method for pan-cancer is reproducible at the protein level. Conclusion: Our findings indicate that the ESC signature is an adverse prognostic factor in cancer, while the HSC signature and ratio of HSC/ESC signatures are positive prognostic factors. The subtyping of cancer based on ESC and HSC signatures may provide insights into cancer biology and clinical implications of cancer. [ABSTRACT FROM AUTHOR]

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Cryptosporidium spp., an intracellular extra cytoplasmic localized protozoan, is one of the leading infectious agents in the etiology of neonatal diarrheal syndrome of ruminants. Cryptosporidiosis is a common disease seen all over the world. However molecular epidemiologic studies are limited on distribution of Cryptosporidium parvum subtypes in the world. To date, nearly 20 subtypes of C. parvum have been described. Gene sequence analysis of the glycoprotein 60 structural protein (GP60) is used to identify subtypes. It is reported that the GP60 gene sequence shows a high degree of genetic polymorphism among the strains. In this study, it was aimed to determine the subtypes of C. parvum parasite in cow and calf stool samples by using GP60 gene sequence analysis. A total of 109 stool samples from calves (<30 days) found to be Cryptosporidium spp. positive by Kinyoun Acid Fast staining were further studied for subtyping. Samples were obtained from farms in 2 regions of Türkiye (Burdur/Yesilova and Aydin provinces). DNA isolation from feces was done with the QIAamp Stool Mini Kit. Cryptosporidium specie identification was done by 18S gene sequences analysis. Nested PCR was performed to amplify GP60 gene and sequences of amplicons were used to identify subtypes. The repeat regions at the serine residue in the GP60 sequences were used to define the subtypes. The results of C. parvum subtyping study showed that IIaA13G2R1 subtype was the most common subtype. IIaA13G2R1 was detected in 73% (80/109) of 109 stool samples, followed by IIaA14G1R1 with 15 samples (14%), IIaA2R1 with 12 samples (11%), and IIaA16R1 and IIaA5G1R1 subtypes with one sample each (1%). In subtype studies based on the GP60 sequence, IIaA15G2R1 was found to be the most common in the world, however this subtype was not found among our samples. In our study, two new subtypes were found, IIaA2R1 and IIaA5G1R1 subtypes. These subtypes were defined for the first time. The subtype, IIaA16R1 was determined to be new in Türkiye. Molecular epidemiology studies are important for better understanding the dissemination of subtypes. IIaA13G2R1 is the most common subtype in Türkiye and the IIaA15G2R1 the most common subtype in the world were absent among our samples. The number of studies on Cryptosporidium parvum subtyping in Türkiye is limited. Our study, the first subtyping study was carried out among cattle in Aydın province. The IIaA2R1 and IIaA5G1R1 subtypes that we detected in our study were defined for the first time in the world and IIaA16R1 in Turkey. [ABSTRACT FROM AUTHOR]

Abstract Tick‐borne encephalitis virus (TBEV) is a significant cause of flaviviral infections affecting the human central nervous system, primarily transmitted through tick bites and the consumption of unpasteurized milk. This study aimed to assess the prevalence of TBEV and identify new natural foci of TBEV in livestock milk. In this cross‐sectional study, unpasteurized milk samples were collected from livestock reared on farms and analysed for the presence and subtyping of TBEV using nested reverse transcription‐polymerase chain reaction , alongside the detection of anti‐TBEV total IgG antibodies using ELISA. The findings revealed that the highest prevalence of TBEV was observed in goat and sheep milk combined, whereas no TBEV was detected in cow milk samples. All identified strains were of the Siberian subtype. Moreover, the highest prevalence of anti‐TBEV antibodies was detected in sheep milk. These results uncover new foci of TBEV in Iran, underscoring the importance of thermal processing (pasteurization) of milk prior to consumption to mitigate the risk of TBEV infection.

Necrotizing enterocolitis (NEC) is the most prevalent and potentially fatal intestinal injury mainly affecting premature infants, with significant long-term consequences for those who survive. This review explores the scale of the problem, highlighting advancements in epidemiology, the understanding of pathophysiology, and improvements in the prediction and diagnosis of this complex, multifactorial, and multifaced disease. Additionally, we focus on the potential role of metabolomics in distinguishing NEC from other conditions, which could allow for an earlier and more accurate classification of intestinal injuries in infants. By integrating metabolomic data with other diagnostic approaches, it is hoped to enhance our ability to predict outcomes and tailor treatments, ultimately improving care for affected infants.

Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ∼990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR+ subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization.

Aim: Primary hyperaldosteronism (PA) is an important cause of secondary hypertension. One of the most crucial steps in the management of patients with PA is the determination of the laterality of aldosterone production (unilateral or bilateral disease). This study aimed to determine the success rate of adrenal venous sampling (AVS) and the concordance between imaging and AVS laterality. Materials and Methods: The procedural, radiological, and laboratory data of the patients who underwent AVS were evaluated retrospectively. The Selectivity Index (SI) and Lateralization Index (LI) were used for catheterization success and laterality determination, respectively. The Contralateral Suppression Index (CSI) was used for laterality determination in cases of unilaterally failed AVS. Abdominal CT scans were evaluated for adrenal nodules and hyperplasia. Results: This study included 36 patients for catheterization success and 28 patients for laterality evaluation. The mean age was 56.08±9.01 years. The overall success rate was 88.9% (32 of 36 patients). The bilateral and unilateral successful catheterization rates were 52.8% and 36.2%, respectively. Unilateral disease was present in 15 (53.6%) patients based on AVS, right-sided in 9 (32.1%), and left-sided in 6 (21.4%) patients. Unilateral disease was present in 18 (64.3%) patients based on imaging, right-sided in 11 (39.3%), and left-sided in 7 (25%) patients. The proportion of agreement between imaging and AVS lateralization was 50% (14 of 28 patients). Conclusion: The overall success rate of AVS was high when unilateral success was included. In half of the patients with PA in this study, CT showed discordant disease laterality compared to AVS. [ABSTRACT FROM AUTHOR]

Context Primary aldosteronism (PA) is the most common endocrine cause of hypertension. The final diagnostic step involves subtyping, using adrenal vein sampling (AVS), to determine if PA is unilateral or bilateral. The complete PA diagnostic process is time and resource intensive, which can impact rates of diagnosis and treatment. Previous studies have developed tools to predict bilateral PA before AVS. Objective Evaluate the sensitivity and specificity of published tools that aim to identify bilateral subtypes of PA. Methods Medline and Embase databases were searched to identify published models that sought to subtype PA, and algorithms to predict bilateral PA are reported. Meta-analysis and meta-regression were then performed. Results There were 35 studies included, evaluating 55 unique algorithms to predict bilateral PA. The algorithms were grouped into 6 categories: those combining biochemical, radiological, and demographic characteristics (A); confirmatory testing alone or combined with biochemical, radiological, and demographic characteristics (B); biochemistry results alone (C); adrenocorticotropic hormone stimulation testing (D); anatomical imaging (E); and functional imaging (F). Across the identified algorithms, sensitivity and specificity ranged from 5% to 100% and 36% to 100%, respectively. Meta-analysis of 30 unique predictive tools from 32 studies showed that the group A algorithms had the highest specificity for predicting bilateral PA, while group F had the highest sensitivity. Conclusions Despite the variability in published predictive algorithms, they are likely important for decision-making regarding the value of AVS. Prospective validation may enable medical treatment upfront for people with a high likelihood of bilateral PA without the need for an invasive and resource-intensive test. [ABSTRACT FROM AUTHOR]

Background: One-third of veterans returning from the 1990–1991 Gulf War reported a myriad of symptoms including cognitive dysfunction, skin rashes, musculoskeletal discomfort, and fatigue. This symptom cluster is now referred to as Gulf War Illness (GWI). As the underlying mechanisms of GWI have yet to be fully elucidated, diagnosis and treatment are based on symptomatic presentation. One confounding factor tied to the illness is the high presence of post-traumatic stress disorder (PTSD). Previous research efforts have demonstrated that both GWI and PTSD are associated with immunological dysfunction. As such, this research endeavor aimed to provide insight into the complex relationship between GWI symptoms, cytokine presence, and immune cell populations to pinpoint the impact of PTSD on these measures in GWI. Methods: Symptom measures were gathered through the Multidimensional fatigue inventory (MFI) and 36-item short form health survey (SF-36) scales and biological measures were obtained through cytokine & cytometry analysis. Subgrouping was conducted using Davidson Trauma Scale scores and the Structured Clinical Interview for Diagnostic and statistical manual of mental disorders (DSM)-5, into GWI with high probability of PTSD symptoms (GWIH) and GWI with low probability of PTSD symptoms (GWIL). Data was analyzed using Analysis of variance (ANOVA) statistical analysis along with correlation graph analysis. We mapped correlations between immune cells and cytokine signaling measures, hormones and GWI symptom measures to identify patterns in regulation between the GWIH, GWIL, and healthy control groups. Results: GWI with comorbid PTSD symptoms resulted in poorer health outcomes compared with both Healthy control (HC) and the GWIL subgroup. Significant differences were found in basophil levels of GWI compared with HC at peak exercise regardless of PTSD symptom comorbidity (ANOVA F = 4.7, P = 0.01,) indicating its potential usage as a biomarker for general GWI from control. While the unique identification of GWI with PTSD symptoms was less clear, the GWIL subgroup was found to be delineated from both GWIH and HC on measures of IL-15 across an exercise challenge (ANOVA F > 3.75, P < 0.03). Additional differences in natural killer (NK) cell numbers and function highlight IL-15 as a potential biomarker of GWI in the absence of PTSD symptoms. Conclusion: We conclude that disentangling GWI and PTSD by defining trauma-based subgroups may aid in the identification of unique GWI biosignatures that can help to improve diagnosis and target treatment of GWI more effectively. [ABSTRACT FROM AUTHOR]

Context Primary aldosteronism (PA) is one of the leading causes of secondary hypertension, and its diagnostic subtyping consistently presents a clinical challenge. Objective This study aimed to investigate the potential of 68Ga-Pentixafor positron emission tomography/computed tomography (PET/CT) in PA classification and its applicability in guiding the development of clinical treatment plans by increasing the sample size. Methods We prospectively enrolled 120 patients with either PA or nonfunctional adenoma (NFA) for analysis. All patients underwent 68Ga-Pentixafor PET/CT. Of these, 11 patients underwent adrenal venous sampling (AVS), 77 underwent adrenalectomy, 76 received pathological diagnoses, and 71 underwent immunohistochemical detection of aldosterone synthase (CYP11B2). Immunohistochemistry for C-X-C chemokine receptor 4 (CXCR4) was performed in 62 cases. Follow-up was conducted for all patients. Results Among the 120 patients, 66 were diagnosed with aldosterone-producing adenoma (APA), 33 with idiopathic hyperaldosteronism (IHA), and 21 with NFA. For APA patients, the sensitivity, specificity, and accuracy of visual analysis using 68Ga-Pentixafor PET/CT were 92.40%, 94.40%, and 93.33%, respectively. Furthermore, for APA patients with a nodule greater than 1 cm in diameter, when the maximum standard uptake value was 7.3 or greater, the specificity was 100%; and for APA patients with a nodule less than 1 cm in diameter, 68Ga-Pentixafor PET/CT also exhibited high sensitivity. AVS was successfully performed in 5 patients. Among the 5 patients, the concordance rate between the AVS and 68Ga-Pentixafor PET/CT for PA subtyping was 60%. In the 77 patients who underwent adrenalectomy, 61 PET/CT scans displayed positive lesions, all of which benefited from the surgery. Additionally, the concordance rate between 68Ga-Pentixafor PET/CT imaging and CYP11B2 was 81.69%. Conclusion 68Ga-Pentixafor PET/CT is a reliable and noninvasive functional imaging technique that demonstrates high accuracy in classifying PA and provides valuable guidance for clinical treatment decision-making. [ABSTRACT FROM AUTHOR]

Currently, HIV-1 displays a substantial level of genetic diversity on a global scale, partly attributed to its recombinant variants. This study seeks to identify and analyze HIV-1 recombinants in Russia during the last decade of the epidemic. A comprehensive examination was conducted, encompassing 3178 partial pol sequences. Subtyping was achieved through various programs including COMET, the Stanford Database, REGA, jpHMM, RIP, and RDP4 for recombination analysis. The study also involved phylogenetic analysis to trace the origins of the identified recombinants. Primary resistance (PrimDR) prevalence and Drug Resistance Mutations (DRMs) were assessed. The study uncovered an overall proportion of recombinants at 8.7%, with a statistically significant increase in their frequency observed over time (p < 0.001). The Northwestern (18.5%) and Siberian (15.0%) Federal Districts exhibited a high prevalence of recombinants, while the Volga (1.9%) and Ural (2.8%) Federal Districts had a lower prevalence. Among HIV-1 recombinants, a PrimDR prevalence of 11.4% was identified. Notably, significant differences in DRMs were observed, with a higher prevalence of M184V in sub-subtype A6 (p = 0.018) and K103N in CRF63_02A6 (p = 0.002). These findings underscore the increasing HIV-1 genetic diversity and highlight a substantial prevalence of PrimDR among its recombinant forms, emphasizing the necessity for ongoing systematic monitoring. [ABSTRACT FROM AUTHOR]

Simple Summary: Pleural effusions are common clinical manifestations of pleural mesothelioma (PM) and often constitute the only available biological material for diagnosis. However, the cytological diagnosis of PM can be challenging. Over the years, ancillary tests, mainly based on the analysis of single biomarkers, have been developed to differentiate malignant from benign effusions, but their sensitivity is limited. In this study, we validated, on a consecutive series, a previously defined 117-gene expression panel as a diagnostic tool for the cytological diagnosis of PM. This gene panel proved to be useful not only in the differential diagnosis of PM and mesothelial hyperplasia but also in the discrimination of the two most common PM subtypes (epithelioid and biphasic) on cytology. Once the malignancy is assessed, the PM subtype definition strongly impacts therapy and prognosis. In this context, the 117-gene panel could be a powerful diagnostic tool to improve the clinical management of PM patients. Cytological diagnosis of pleural mesothelioma (PM) is controversial, even using ancillary markers (BAP1, MTAP and CDKN2A). Here, we aimed to prospectively validate a previously developed 117-gene expression panel for the differential cytological diagnosis of epithelioid, biphasic PM and mesothelial hyperplasia. Seventy-seven pleural effusions were classified using the 117-gene expression levels (NanoString system). Sixty-eight cases were also screened for ancillary markers. The performance of both gene panel and ancillary markers was evaluated using ROC metrics. A score using the top consistently deregulated genes between epithelioid and biphasic PM was built to subtype malignant effusions. The panel alone reached a diagnostic accuracy (0.89) comparable to the best marker combination (BAP1 plus MTAP: 0.88). Ancillary tests missed 8 PMs, 7 of which were correctly classified by the panel. The score built by averaging the expression levels of MSLN, CLDN15 and CFB showed an accuracy of 0.80 in subtyping epithelioid and biphasic effusions. The 117-gene panel is effective for PM cytological diagnosis of epithelioid and biphasic PM. This tool can be complementary to ancillary markers, reducing invasive procedures and allowing an earlier diagnosis. Finally, the possibility to subtype PM on effusions strengthens the panel's role in PM diagnosis and management. [ABSTRACT FROM AUTHOR]

Summary: Insomnia nosology has significantly evolved since the Diagnostic and Statistical Manual (DSM)‐III‐R first distinguished between 'primary' and 'secondary' insomnia. Prior International Classification of Sleep Disorders (ICSD) nosology 'split' diagnostic phenotypes to address insomnia's heterogeneity and the DSM nosology 'lumped' them into primary insomnia, while both systems assumed causality for insomnia secondary to health conditions. In this systematic review, we discuss the historical phenotypes in prior insomnia nosology, present findings for currently proposed insomnia phenotypes based on more robust approaches, and critically appraise the most relevant ones. Electronic databases PsychINFO, PubMED, Web of Science, and references of eligible articles, were accessed to find diagnostic manuals, literature on insomnia phenotypes, including systematic reviews or meta‐analysis, and assessments of the reliability or validity of insomnia diagnoses, identifying 184 articles. The data show that previous insomnia diagnoses lacked reliability and validity, leading current DSM‐5‐TR and ICSD‐3 nosology to 'lump' phenotypes into a single diagnosis comorbid with health conditions. However, at least two new, robust insomnia phenotyping approaches were identified. One approach is multidimensional‐multimethod and provides evidence for self‐reported insomnia with objective short versus normal sleep duration linked to clinically relevant outcomes, while the other is multidimensional and provides evidence for two to five clusters (phenotypes) based on self‐reported trait, state, and/or life‐history data. Some approaches still need replication to better support whether their findings identify true phenotypes or simply different patterns of symptomatology. Regardless, these phenotyping efforts aim at improving insomnia nosology both as a classification system and as a mechanism to guide treatment. [ABSTRACT FROM AUTHOR]

Purpose: Skin cutaneous melanoma (SKCM) is a highly aggressive melanocytic carcinoma whose high heterogeneity and complex etiology make its prognosis difficult to predict. This study aimed to construct a risk subtype typing model for SKCM. Methods: The study proposes a deep learning framework combining early fusion feature autoencoder (AE) and late fusion feature AE for risk subtype prediction of SKCM. The deep learning framework integrates mRNA, miRNA, and DNA methylation data of SKCM patients from The Cancer Genome Atlas (TCGA), and clusters the screened multi-omics features associated with survival prognosis to identify risk subtypes. Differential expression analysis and functional enrichment analysis were performed between risk subtypes, while SVM classifiers were constructed between differentially expressed genes (DEGs) obtained by Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression screening and risk subtype labels inferred from multi-omics data, and the predictive robustness of risk subtypes inferred from the risk subtype classification prediction model was validated using two independent datasets. Results: The deep learning framework that combined early fusion feature AE with late fusion feature AE distinguished the two best risk subtypes compared to the multi-omics integration approach with single strategy AE or PCA. A promising C-index (C-index = 0.748) and a significant difference in survival (log-rank P value = 4.61 × 10–9) were found between the identified risk subtypes. The DEGs with the top significance values together with differentially expressed miRNAs provided the biological interpretation of risk subtypes on SKCM. Finally, the framework was applied to predict risk subtypes in two independent test datasets of SKCM patients, all of which showed good predictive power (C-index > 0.680) and significant survival differences (log-rank P value < 0.01). Conclusion: The SKCM risk subtypes identified by integrating multi-omics data based on deep learning can not only improve the understanding of the molecular mechanisms of SKCM, but also provide clinicians with assistance in treatment decisions. [ABSTRACT FROM AUTHOR]

Blastocystis is a common enteric protist infecting humans, domestic animals, and wildlife worldwide. However, data on the prevalence and subtype diversity of Blastocystis in free-living wild birds in urban districts are rare. In this study, a total of 138 fresh fecal samples from free-living wild birds were collected from three universities and three communities in Xinxiang, China, to explore the infection rate, Blastocystis subtypes present and zoonotic potential of this protist. Blastocystis presence was determined with nested-PCR amplification based on the partial small ribosomal subunit (SSU rRNA) gene. Presence was detected from one community (Wupu) at an overall rate of 1.5% (2/136). Further DNA sequencing and phylogenetic analyses identified two ruminant-associated subtypes, ST10 (n = 1) and ST24 (n = 1), implying a cross-species transmission of Blastocystis from ruminants. This is the first report on the infection of ST10 and ST24 in free-living wild birds in an urban area in China. As potentially zoonotic subtypes, the occurrence of ST10 and ST24 suggests that these free-living birds could play a role in spreading Blastocystis to humans in Xinxiang. [ABSTRACT FROM AUTHOR]