Objective: To investigate the status of condom use and its influencing factors among men who have sex with men (MSM), so as to provide a basis for improving condom utilization rates and AIDS prevention and control in this population. Methods: From May to October 2024, a snowball sampling method was employed to recruit MSM in Songjiang District, Shanghai Municipality. Self-administered questionnaires were used to collect data on demographic characteristics, AIDS-related knowledge, sexual behaviors, pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP), and condom use in the past six months. Multivariable logistic regression model was used to analyze the influencing factors for consistent condom use. Results: A total of 921 MSM were surveyed, with a median age of 29.00 (interquartile range, 9.00) years. Among them, 697 (75.68%) were aware of AIDS-related knowledge, 826 (89.69%) expressed willingness to use PrEP, and 835 (90.66%) were willing to use PEP. Additionally, 787 (85.45%) MSM reported their age at first homosexual intercourse as ≥18 years, while 519 (56.35%) reported consistent condom use in the past six months. Multivariable logistic regression analysis revealed that MSM who were aware of AIDS-related knowledge (OR=0.582, 95% CI: 0.423-0.801), willing to use PrEP (OR =0.611, 95% CI: 0.385-0.969), and whose age at first homosexual intercourse was <18 years (OR=0.480, 95% CI: 0.330-0.700) were less likely to consistent use condoms. Conclusion The proportion of consistent condom use among the MSM remains relatively low, which is primarily associated with AIDS-related knowledge, willingness to use PrEP, and the age at first homosexual intercourse.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Microbial-derived metabolites are important mediators of host-microbial interactions. In recent years, the role of intestinal microbial metabolites in colorectal cancer has attracted considerable attention. These metabolites, which can be derived from bacterial metabolism of dietary substrates, modification of host molecules such as bile acids, or directly from bacteria, strongly influence the progression of colitis-associated cancer (CAC) by regulating inflammation and immune response. Here, we review how microbiome metabolites short-chain fatty acids (SCFAs), secondary bile acids, polyamines, microbial tryptophan metabolites, and polyphenols are involved in the tumorigenesis and development of CAC through inflammation and immunity. Given the heated debate on the metabolites of microbiota in maintaining gut homeostasis, serving as tumor molecular markers, and affecting the efficacy of immune checkpoint inhibitors in recent years, strategies for the prevention and treatment of CAC by targeting intestinal microbial metabolites are also discussed in this review.
Humans ; Gastrointestinal Microbiome/physiology* ; Animals ; Carcinogenesis/metabolism* ; Colitis-Associated Neoplasms/microbiology* ; Fatty Acids, Volatile/metabolism* ; Bile Acids and Salts/metabolism* ; Colitis/microbiology*

Programmed cell death (PCD) is characterized as a cell death pathway governed by specific gene-encoding requirements, plays crucial roles in the homeostasis and innate immunity of organisms, and serves as both a pathogenic mechanism and a therapeutic target for a variety of human diseases. Z-DNA-binding protein 1 (ZBP1) functions as a cytosolic nucleic acid sensor, utilizing its unique Zα domains to detect endogenous or exogenous nucleic acids and its receptor-interacting protein homotypic interaction motif (RHIM) domains to sense or bind specific signaling molecules, thereby exerting regulatory effects on various forms of PCD. ZBP1 is involved in apoptosis, necroptosis, pyroptosis, and PANoptosis and interacts with molecules, such as receptor-interacting protein kinase 3 (RIPK3), to influence cell fate under various pathological conditions. It plays a crucial role in regulating PCD during infections, inflammatory and neurological diseases, cancers, and other conditions, affecting disease onset and progression. Targeting ZBP1-associated PCD may represent a viable therapeutic strategy for related pathological conditions. This review comprehensively summarizes the regulatory functions of ZBP1 in PCD and its interactions with several closely associated signaling molecules and delineates the diseases linked to ZBP1-mediated PCD, along with the potential therapeutic implications of ZBP1 in these contexts. Ongoing research on ZBP1 is being refined across various disease models, and these advancements may provide novel insights for studies focusing on PCD, potentially leading to new therapeutic options for related diseases.

OBJECTIVES: To summarize the clinical characteristics, diagnosis, and treatment outcomes of neonatal venous thrombosis. METHODS: A retrospective analysis was conducted on the clinical data of 11 neonates with venous thrombosis admitted to the Department of Neonatology of Anhui Children's Hospital from January 2019 to September 2024. The clinical characteristics, diagnostic approaches, treatments, and outcomes were analyzed. RESULTS: Among the 11 neonates diagnosed with venous thrombosis, 5 were male, and 6 were preterm infants, with a median gestational age of 35⁺⁶ weeks, birth weight of (2 322±1 069) g, and admission temperature of (36.6±0.4)°C. The median age at symptom onset was 6 days. Of the 11 cases, 8 limb venous thromboses and 1 portal vein thrombosis were confirmed by vascular ultrasound, and 2 cases of intracranial venous sinus thrombosis were confirmed by magnetic resonance imaging. Ten cases received low molecular weight heparin for anticoagulation, with a treatment duration of (24±15) days; 2 cases were treated with urokinase thrombolysis, and 4 cases received fresh frozen plasma transfusion. Thrombosis resolved in 7 cases before discharge. Partial resolution occurred in 2 cases before discharge (1 continued outpatient treatment until resolution and 1 resolved during follow-up). One case was transferred to another hospital after 1 day of treatment and was discharged after thrombosis reduction. No adverse reactions such as bleeding were observed. One neonate with cerebral infarction at admission did not receive heparin anticoagulation and was followed up as an outpatient. CONCLUSIONS Vascular ultrasound is the most commonly used diagnostic method for neonatal venous thrombosis. Heparin anticoagulation is the recommended treatment. The overall prognosis of neonatal venous thrombosis is favorable.
Humans ; Male ; Venous Thrombosis/drug therapy* ; Infant, Newborn ; Female ; Retrospective Studies