The high heterogeneity observed among patients with obsessive-compulsive disorder (OCD) underscores the need to identify neurophysiological OCD subtypes to facilitate personalized diagnosis and treatment. In this study, our aim was to identify potential OCD subtypes based on individualized functional connectome abnormalities. We recruited a total of 99 patients with OCD and 104 healthy controls (HCs) matched for demographic characteristics. Individualized functional connectome abnormalities were obtained using normative models of functional connectivity strength (FCS) and used as features to unveil OCD subtypes. Sensitivity analyses were conducted to assess the reproducibility and robustness of the clustering outcomes. Patients exhibited significant intersubject heterogeneity in individualized functional connectome abnormalities. Two subtypes with distinct patterns of FCS abnormalities relative to HCs were identified. Subtype 1 patients primarily exhibited significantly decreased FCS in regions including the frontal gyrus, insula, hippocampus, and precentral/postcentral gyrus, whereas subtype 2 patients demonstrated increased FCS in widespread brain regions. When all patients were combined, no significant differences were observed. Additionally, the identified subtypes showed significant differences in age of onset. Furthermore, sensitivity analyses confirmed the reproducibility of our subtyping results. In conclusion, the identified OCD subtypes shed new light on the taxonomy and neurophysiological heterogeneity of OCD.

The circulating androgens have a role in the pathogenesis of both acne vulgaris and androgenetic alopecia; an association between these two have been found previously. The aim of this study is to investigate the relationship of the severity of acne vulgaris lesions to the subtype of AGA; and to validate the relationship between severities of acne vulgaris and AGA. This study was conducted cross-sectionally at five different dermatology clinics. Male and female androgenetic alopecia patients with comorbid acne vulgaris have been included. The age, gender, severity of acne lesions, subtype of androgenetic alopecia and the severity of androgenetic alopecia were noted. The severity of acne lesions were graded according to the Global Acne Severity Scale and androgenetic alopecia was graded according to the Hamilton and Ludwig Scales. SPSS v 21 was used for the statistical analysis. A total of 101 patients have been included (12 male and 89 female). The mean age of the patients with severe acne was statistically significantly lower (p = 0.020). The difference in terms of gender was statistically insignificant (p = 0.388). The severity of acne vulgaris was found to be independent of the severity and of the subtype of AGA; p = 0.623 and 0.870 respectively. Neither a relationship between the severity of androgenetic alopecia and severity of acne; nor a relationship between acne severity and androgenetic alopecia subtype were found in this study. Thus we report that, acne severity is independent of the subtype and stage of the co-existing androgenetic alopecia.

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OBJECTIVE: To determine if subtypes of cam morphology on anteroposterior radiographs exist using statistical shape modeling (SSM), and to assess their association with incident radiographic hip osteoarthritis (RHOA) within 10 years.
METHODS: The nationwide prospective Cohort Hip and Cohort Knee (CHECK) study included 1002 participants aged 45-65 years with 10-year follow-up. Subtypes of cam morphology were defined as SSM-based shape variations of femoral head-neck junction that are associated with baseline cam morphology (alpha angle ≥60°). The association between each subtype in hips free of osteoarthritis at baseline (Kellgren & Lawrence (KL) grade <2) and incident RHOA (KL grade≥2, or a total hip replacement) was estimated using logistic regression at 10-year follow-up and stratified by sex.
RESULTS: In sex-combined group, but also for males and females separately, cam morphology subtypes were captured in modes 1, 3, 4, and 5 with odds ratios (ORs) ranging from 0.39 (0.27-0.58) to 2.25 (1.64-3.10). For sex-combined group, only mode 3, a flattened head-neck junction, was associated with incident RHOA (OR:1.14, 1.02-1.27). Males\' modes 1 and 3 and females\' modes 3 and 4 were associated with RHOA. Notably, the female mode 4, a slightly flattened neck but with subtle curvature, was significantly protective for RHOA (OR:0.88, 0.80-0.98).
CONCLUSIONS: We identified four distinct morphological subtypes of cam morphology defined by alpha angle. Only some subtypes were found acting as risk factors for RHOA at 10-year follow-up, which differed between males and females. This highlights the need to study cam morphology beyond the alpha angle alone.

Blastocystis is one of the most common zoonotic intestinal protozoa with global distribution and can cause gastrointestinal syndrome mainly characterized by diarrhea. School children are the main susceptible population. No epidemiological data on Blastocystis among school children in Hainan, the only tropical island province in China. Between March 2021 and June 2023, 1973 fecal samples were collected from school children across three regions in Hainan province. Blastocystis was examined by amplifying the small subunit ribosomal RNA (SSU rRNA) gene via polymerase chain reaction (PCR), and subtypes were identified through DNA sequencing and phylogenetic analysis. The overall prevalence of Blastocystis was 7.3 % (144/1973). The differences in infection rates across different regions, nationalities, and educational stages are statistically significant (P < 0.001). Five subtypes were identified, of which ST3 was the dominant subtype (60.4 %; 87/144), followed by ST1 (27.8 %; 40/144), ST7 (10.4 %; 15/144), ST6 (0.7 %; 1/144), and ST2 (0.7 %; 1/144). 42 known sequences and 15 novel sequences were identified including eight new variations of the ST1 (ST1-16∼ST1-23) with similarities ranging from 98.3 % to 99.78 % and seven new variations of the ST7 (ST7-7∼ST7-13) with similarities ranging from 97.7 % to 99.79 % by intra-subtype genetic polymorphisms analysis. The results evaluate the public health risks of Blastocystis among school children in Hainan and the sources of infection were discussed, providing important basic data for the effective prevention and control of intestinal parasitic diseases in Hainan.

OBJECTIVE: In Guangdong Province, hepatitis C virus (HCV) had been found to confer resistance to direct-acting antivirals (DAAs). There were few studies of HCV subtypes and resistance-associated substitutions (RASs) of HCV in different high-risk populations. In this study, we aimed to determine the subtype distribution and the RASs in high-risk population groups, including drug users (DU), men who have sex with men (MSM), female sex workers (FSW), and male patients with sexually transmitted diseases (STD) in Guangdong Province (a highly developed province with a large population).
METHODS: Using a city-based sampling strategy,1356 samples were obtained from different population groups. Phylogenetic analyses determined subtypes based on Core, NS5B, or NS5A sequences. HCV subtype distribution and RASs in various risk groups and regions were analyzed.
RESULTS: Ten subtypes, of which 6 h and 6 k were novel in Guangdong, were identified. The primary subtype among all risk groups was 6a. RASs in 1b and 3a were different from those observed in other studies. Subtype 3b in western Guangdong was higher than the other three regions. No RASs were found in 6a or any other genotype 6.
CONCLUSIONS: The HCV subtypes are expanding in high-risk populations in Guangdong. Drug use by other risk groups and commercial sex by DU may bridge the dissemination of 6a from DU to other populations. The RAS profiles of 1b and 3a differed from those reported in studies conducted in southwestern China. Further research is required to determine the reason for this discrepancy. Moreover, the combination of RASs was high in subtype 3b. To guide HCV treatment of subtype 3b, pretreatment subtyping of HCV genotype 3 should be considered in western cities in the near future.

We isolated highly pathogenic avian influenza (HPAI) H5N5 and H5N1 viruses from crows in Hokkaido, Japan, during winter 2023-24. They shared genetic similarity with HPAI H5N5 viruses from northern Europe but differed from those in Asia. Continuous monitoring and rapid information sharing between countries are needed to prevent HPAI virus transmission.

OBJECTIVE: Symptoms are significant kind of phenotypes for managing and controlling of the burst of acute infectious diseases, such as COVID-19. Although patterns of symptom clusters and time series have been considered the high potential prediction factors for the prognosis of patients, the elaborated subtypes and their progression patterns based on symptom phenotypes related to the prognosis of COVID-19 patients still need be detected. This study aims to investigate patient subtypes and their progression patterns with distinct features of outcome and prognosis.
METHODS: This study included a total of 14,139 longitudinal electronic medical records (EMRs) obtained from four hospitals in Hubei Province, China, involving 2,683 individuals in the early stage of COVID-19 pandemic. A deep representation learning model was developed to help acquire the symptom profiles of patients. K-means clustering algorithm is used to divide them into distinct subtypes. Subsequently, symptom progression patterns were identified by considering the subtypes associated with patients upon admission and discharge. Furthermore, we used Fisher\'s test to identify significant clinical entities for each subtype.
RESULTS: Three distinct patient subtypes exhibiting specific symptoms and prognosis have been identified. Particularly, Subtype 0 includes 44.2% of the whole and is characterized by poor appetite, fatigue and sleep disorders; Subtype 1 includes 25.6% cases and is characterized by confusion, cough with bloody sputum, encopresis and urinary incontinence; Subtype 2 includes 30.2% cases and is characterized by dry cough and rhinorrhea. These three subtypes demonstrate significant disparities in prognosis, with the mortality rates of 4.72%, 8.59%, and 0.25% respectively. Furthermore, symptom cluster progression patterns showed that patients with Subtype 0 who manifest dark yellow urine, chest pain, etc. in the admission stage exhibit an elevated risk of transforming into the more severe subtypes with poor outcome, whereas those presenting with nausea and vomiting tend to incline towards entering the milder subtype.
CONCLUSIONS: This study has proposed a clinical meaningful approach by utilizing the deep representation learning and real-world EMR data containing symptom phenotypes to identify the COVID-19 subtypes and their progression patterns. The results would be potentially useful to help improve the precise stratification and management of acute infectious diseases.

The aim of this study is to establish a deep learning (DL) model to predict the pathological type of gastric adenocarcinoma cancer based on whole-slide images(WSIs). We downloaded 356 histopathological images of gastric adenocarcinoma (STAD) patients from The Cancer Genome Atlas database and randomly divided them into the training set, validation set and test set (8:1:1). Additionally, 80 H&E-stained WSIs of STAD were collected for external validation. The CLAM tool was used to cut the WSIs and further construct the model by DL algorithm, achieving an accuracy of over 90% in identifying and predicting histopathological subtypes. External validation results demonstrated the model had a certain generalization ability. Moreover, DL features were extracted from the model to further investigate the differences in immune infiltration and patient prognosis between the two subtypes. The DL model can accurately predict the pathological classification of STAD patients, and provide certain reference value for clinical diagnosis. The nomogram combining DL-signature, gene-signature and clinical features can be used as a prognostic classifier for clinical decision-making and treatment.

Using a comprehensive molecular epidemiological approach, we characterized the transmission dynamics of HIV-1 among the MSM population in Tianjin, China. Our findings revealed that 38.56% (386/1001) of individuals clustered across 109 molecular transmission clusters (TCs), with MSM aged 50 and below being the group most commonly transmitting HIV-1. Among the identified TCs, CRF01_AE predominated, followed by CRF07_BC. Notably, CRF07_BC demonstrated a higher propensity for forming large clusters compared to CRF01_AE. Birth-death skyline analyses of the two largest clusters indicated that the HIV/AIDS transmission may be at a critical point, nearly all had Re approximately 1 by now. A retrospective analysis revealed that the rapid expansion of these large clusters was primarily driven by the introduction of viruses in 2021, highlighting the crucial importance of continuous molecular surveillance in identifying newly emerging high-risk transmission chains and adapting measures to address evolving epidemic dynamics. Furthermore, we detected the transmission of drug-resistant mutations (DRMs) within the TCs, particularly in the CRF07_BC clusters (K103N, Y181C, and K101E) and CRF01_AE clusters (P225H and K219R), emphasizing the importance of monitoring to support the continued efficacy of first-line therapies and pre-exposure prophylaxis (PrEP). Recombination analyses indicated that complex recombinant patterns, associated with increased amino acid variability, could confer adaptive traits to the viruses, potentially providing a competitive advantage in certain host populations or regions. Our study highlights the potential of integrating molecular epidemiological and phylodynamic approaches to inform targeted interventions.