Intravascular large B-cell lymphoma(IVLBCL) is a rare and aggressive type of lymphoma with diverse and nonspecific clinical manifestations, often leading to misdiagnosis. This article reports a case of IVLBCL in a middle-aged male patient who initially presented with pulmonary arterial hypertension(PAH). The patient exhibited progressive hypoxemia and PAH, showing poor response to standard PAH therapy. Laboratory tests indicated a hyperinflammatory state and significantly elevated lactate dehydrogenase levels, while imaging revealed diffuse bilateral lung lesions. Random skin biopsy identified atypical B lymphocytes within subcutaneous capillaries, confirming the diagnosis of IVLBCL. Following treatment with the ZR-CHOP regimen, the patient's symptoms and laboratory parameters improved markedly. By reviewing relevant literature, this article systematically outlines the diagnostic and therapeutic process of this case, aiming to provide insights for the clinical recognition of such rare presentations.

Over the past two decades, genome-wide association study(GWAS) has identified numerous genetic variants and loci associated with heritable diseases. With the gradual maturation and saturation of GWAS methodologies, transcriptome-wide association study(TWAS) offers a novel perspective by linkinggenetic phenotypes to gene expression levels. By integrating TWAS with other multi-omics analyses, researchers can gain a deeper understanding of heritable diseases. This article provides an overview of recent groundbreaking and representative TWAS methods and tools, analyzes their strengths and limitations, and discusses future trends in TWAS development.

Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

Objective: To understand the current status and associated factors of sleep problems among preschool children in Hainan Province, so as to provide scientific evidence for improving sleep health in this population. Methods: From January 2021 to June 2022, a total of 4 105 preschool children aged 3-6 years from 62 kindergartens in Hainan Province were selected using stratified cluster random sampling method. Demographic information and lifestyle habits were collected through the Hainan Province Child Growth and Development Survey Questionnaire. The Children s Sleep Habits Questionnaire (CSHQ) was employed to assess sleep status. Unconditional binary Logistic regression model was applied to investigate the associated factors of sleep problems among preschool children. Results: The overall CSHQ score for children was 58.03±18.84, with 80.95% of preschool children exhibiting sleep related issues. The top three most prevalent sleep problem domains were bedtime resistance (72.42%), sleep anxiety ( 54.88 %), and parasomnias (38.86%). Logistic regression analysis revealed that higher family annual income ( OR=0.60, 95%CI = 0.45-0.79), higher maternal education level ( OR=0.53, 95%CI =0.32-0.89), regular or daily vitamin D supplementation ( OR=0.77, 95%CI =0.60-0.99), and fully self initiated eating behavior ( OR=0.71, 95%CI =0.59-0.85) were negatively related with children s sleep problems; in addition, screen exposure ( OR=1.27, 95%CI =1.06-1.51) and picky eating ( OR= 1.47 , 95%CI =1.21-1.78) were positively related to children s sleep problems (all P <0.05). Conclusion The high detection rate of sleep problems among preschool children in Hainan Province is multifactorially associated with family environment, dietary habits, and lifestyle behaviors.

Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

Objective To systematically evaluate the risk prediction models for acute kidney injury in patients with acute coronary syndrome (ACS) based on machine learning, providing a reference for clinical selection of appropriate risk assessment tools. Methods Clinical studies using machine learning methods for predicting the risk of acute kidney injury in ACS patients were retrieved from PubMed, Cochrane Library, Embase, Web of Science core database, CNKI, Wanfang Database, CBM, and VIP. The retrieval time was from the establishment of the database to May 24, 2025. The quality of the models were evaluated using the prediction model risk of bias assessment tool. Results Nine articles were included, and a total of 58 prediction models were constructed using 20 machine learning methods. The area under the receiver operating characteristic curve ranged from 0.733 to 0.894. The most commonly used predictors were age and creatinine. The overall bias risk of the included studies was relatively high, but the applicability was good.Conclusion Machine learning models can identify the risk of acute kidney injury in ACS patients. All models have good predictive potential, but they are still in the development stage. It is recommended that future studies adopt prospective design with external validation to improve the stability and predictive accuracy of the models.

Objective To analyze the epidemiological characteristics of poisonous mushroom-related foodborne disease incidents in Chongqing from 2010 to 2024, and to provide a scientific basis for effective prevention and control of mushroom-related foodborne diseases. Methods Data of poisonous mushroom related foodborne disease incidents reported by the CDCs of 39 districts and counties in Chongqing from 2010 to 2024 were collected, and their epidemic characteristics were analyzed. Results A total of 264 poisonous mushroom poisoning outbreaks were reported in Chongqing from 2010 to 2024, resulting in 1 046 cases of illness, 543 hospitalizations, and 15 deaths, with a mortality rate of 1.43%. The peak of poisoning incidents was from June to October, accounting for 89.02% of the total number of incidents. The top three high-incidence areas were Pengshui Miao Tujia Autonomous County, Dianjiang County, and Nanchuan District. Poisonous mushroom poisoning incidents occurring in household settings, accidental picking and ingestion, and cases involving unidentified mushroom species accounted for 89.02%, 83.33%, and 90.15% of all foodborne disease outbreak incidents, respectively. Conclusion Foodborne disease incidents related to poisonous mushrooms in Chongqing City show an upward trend, and the effectiveness of prevention and control needs to be improved. Based on their seasonal, regional and household clustering characteristics, efforts should be made before the peak season of mushroom poisoning in high-risk areas, targeting key populations with health education, monitoring and early warning, food safety supervision, and medical treatment.

[Objective] To assess the data characteristics of quality monitoring indicators for red blood cell (RBC) preparations, so as to provide reference for continuous improvement of blood quality. [Methods] The quality inspection data of 6 types of RBC preparations from Chongqing blood center from 2019 to 2023 were summarized. For the same indicators, the numerical range of quality indicators was monitored by comparing different types of preparations with the national standard GB18469. The loss and/or damage to RBCs caused by different preparation process were compared, and the impact of different preparation processes on the quality of RBCs was discussed. [Results] The appearance and sterility test compliance rates of the six types of RBC preparations were both 100%, while the compliance rates of other items were all ≥75%. The compliance rate of hematocrit for suspended RBCs was the lowest at 75%, with a median of 0.52, which was close to the lower limit of GB18469, while the medians of hematocrit for the other types were all at the midline level of GB18469. The Hb content for different types of RBCs was significantly higher than the corresponding requirements of GB18469 (P<0.05). The hemolysis rate at the end of storage for different types of RBCs was significantly lower than the requirements of GB18469 (P<0.05). The 1 U leukoreduction process resulted in a hemoglobin content loss of about 5% and had a significant impact on the hemolysis rate at the end of storage (P<0.05). The washing process resulted in a hemoglobin content loss of <3% and had no significant impact on the hemolysis rate at the end of storage (P>0.05). The concentration process resulted in a hemoglobin content loss of <3% and had a significant impact on the hemolysis rate at the end of storage (P<0.05). [Conclusion] The impact of different processes on RBC preparations is within a controllable range and meets the requirements of GB18469. The quality monitoring data can provide a reference for clinical blood selection, effectiveness evaluation and revision of related standards.

Diabetes mellitus （DM） is a metabolic disease caused by absolute or relative insulin deficiency and reduced insulin sensitivity in peripheral cells， posing a serious threat to global health. Chronic complications arising in the later stages of DM can lead to the decline or even loss of function in multiple organs， including the eyes， heart， liver， kidneys， nerves， and feet， making them the primary cause of mortality in DM patients. Although modern medicine has made some progress in the treatment of these complications， challenges such as high costs and adverse drug reactions remain. Thus， identifying highly effective drugs with minimal adverse effects has become a top priority. Astragalus membranaceus is a shining gem in the treasure trove of Chinese medicine. Numerous studies have shown that its primary active component， astragaloside Ⅳ， possesses various biological activities， including anti-inflammatory， antioxidant， and antiviral effects， as well as benefits for cardiac and cerebral function， nerve conduction， and myocardial protection. Meanwhile， the phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway plays a crucial role in regulating oxidative stress， inflammatory responses， apoptosis， and autophagy. Extensive research has highlighted the significant role of this pathway in various DM complications， leading to widespread studies on its interaction with astragaloside Ⅳ. This review summarizes research findings on how astragaloside Ⅳ alleviates pancreatic cytotoxicity in DM patients by modulating the PI3K/Akt pathway. Additionally， it highlights its protective effects on basic cardiac function， inhibition of retinal cell damage， improvement of cerebral nerve dysfunction， reduction of chronic kidney and liver damage， and mitigation of neurovascular toxicity in the lower limbs. These insights provide a valuable reference for the clinical application of A. membranaceus and its active monomer， astragaloside Ⅳ， in the treatment of DM and its complications.