Objective: To develop a 24 hour physical activity index for school aged children, and to analyze the association of 24 hour physical activity index with screening myopia and obesity, so as to provide a more effective assessment tool for student health risk screening. Methods: From April to June 2024, a total of 451 students in Grades 3-4 from two monitored primary schools in Shanghai were selected using stratified cluster random sampling method. Data on eight core indicators, including daily moderate to vigorous physical activity time, total physical activity time, outdoor activity time, screen time, sleep duration, sleep efficiency, social jetlag and daytime sleepiness, were collected through questionnaires and accelerometer monitoring. Each indicator was standardized and synthesized into a 0-80 point school aged children s 24 hour physical activity index. Spearman correlation analysis and t-test were used to assess consistency between questionnaire and accelerometer derived indices. Multivariate Logistic regression was applied to analyze the association of strength of the composite index with single behavior indicators in screening myopia and overweight/obesity. Results: The compliance rates were higher for moderate to vigorous physical activity time and screen time (50.8%, 98.7%), while the compliance rate for outdoor activity time was only 42.6%, and that for sufficient sleep duration was merely 10.2%. There was no significant difference between the total scores derived from the questionnaire and accelerometer methods (45.13±5.83, 45.05±6.87, t=0.29, P >0.05), but they showed a strong positive correlation ( r=0.58, P <0.01). Multivariate Logistic regression revealed that adjusting for individual behaviors such as grade, gender and both parents being myopic, among single behavior indicators of 24 hour physical activity index, only insufficient outdoor activity time was significantly associated with screening myopia among school aged children ( OR=1.50, 95%CI =1.01-2.21); the detection risk of screening myopia and obesity in the low index group were higher than those in the high index group ( OR=2.47, 95%CI =1.02-5.96; OR=16.63,95%CI = 5.99- 46.20) (all P <0.05). Conclusion The developed 24 hour physical activity index for school aged children demonstrates good measurement accuracy and shows stronger associations with screening myopia and obesity than single behavior indicator.

ObjectiveTo explore the potential mechanism of Weicanqing Formula （微残清方， WF） combined with chemotherapy in treating acute myeloid leukemia （AML） based on malic enzyme 2 （ME2）-mediated bone marrow immune-metabolic homeostasis and . MethodsSixty-five male C57BL/6N mice were randomly divided into control group， model group， WF group， chemotherapy group， and the combination group （WF plus chemotherapy）， with 13 mice per group. Except for the control group， mice were injected with C1498 cells （appro-ximately 1×10⁶ cells per mouse） via the tail vein on day 1 to establish an AML model. Starting from day 8， mice in the chemotherapy group and the combination group were administered with cytarabine at 30 mg/（kg·d） via subcutaneous injection， once daily for 3 consecutive days； WF group and the combination group received WF at 7.54 g/（kg·d） by gavage， once daily for 21 consecutive days. On days 1， 7， 14， 21 and 28， hemoglobin （Hb） and white blood cell （WBC） levels were determined in each group. On day 28， Giemsa staining was used to observe morphological changes in bone marrow cells. Flow cytometry was employed to detect the expression levels of bone marrow T lympthocyte subsets， including CD8⁺， CD4⁺， and regulatory T lymphocytes （Treg）. The contents of glutamine （Gln）， nicotinamide adenine dinucleotide phosphate （NADP⁺）， and reduced nicotinamide adenine dinucleotide phosphate （NADPH） in bone marrow were determined using visible spectrophotometry. Adenosine triphosphate （ATP） concentration in bone marrow was measured by chemiluminescence assay. The mRNA expression of malic enzyme 2 （ME2） in bone marrow was detected by RT-qPCR， and the protein expression level of ME2 was determined by Western blotting. ResultsCompared to the control group， the model group showed decreased Hb levels on day 14， 21， and 28， and increased WBC levels on day 7， 14， 21， and 28 （P＜0.05）. On day 28， bone marrow CD8⁺ and CD8⁺/CD4⁺ levels decreased， while Treg cells， ATP， Gln， NADP⁺， NADPH， ME2 mRNA， and their corresponding protein levels increased （P＜0.05）. Compared to the model group， the chemotherapy group and the combination group both exhibited reduced Hb level on day 14， 21 and 28， as well as the increased WBC level； the combination group showed increased CD8⁺ level， decreased Treg， ATP， Gln， and NADPH content， as well as reduced ME2 mRNA expression and protein levels （P＜0.05）. Compared to the chemotherapy group， the combination group showed significantly increased Hb level on days 21 and 28， and increased WBC level on day 28 （P＜0.05）. Bone marrow smear pathology revealed that， in the model group， myeloid blast cells exhibited cytoplasmic vacuoles indicative of abnormal metabolic activity. In contrast， both the chemotherapy group and the combination group showed large numbers of metamyelocytes and band neutrophils， with only a few immature granulocytic blast cells observed. ConclusionWF may improve the prognosis of AML when used as an adjunct to chemotherapy by modulating ME2 expression， inhibiting metabolic energy competition within the bone marrow microenvironment， and reshaping the distribution of T lymphocyte subsets in the bone marrow.

Objective To retrospectively analyze multicenter data from domestic sources, aiming to explore the link between intrahepatic cholangiocarcinoma (ICC) tumor size and prognosis, establishing a classification system based on tumor size. Methods Between December 2011 and September 2018, 280 ICC patients from 13 hospitals were included. The tumor size prognosis cutoff was identified by the minimum P-value method, and the classification's overall survival related effectiveness was assessed by Kaplan-Meier analysis. Results All 280 patients were divided into the group of tumor maximum diameter ≤4 cm and >4 cm. Tumor size was confirmed as an independent prognosis factor by multivariate COX regression analysis (HR=2.110, 95% CI: 1.358-3.280). Conclusions The tumor size dichotomy classification system based on the Chinese patient group can expediently predict ICC prognosis and offers an important basis for selecting post-operative individualized adjuvant therapy and follow up plans.

Objective To investigate the characteristics of changes in blood uric acid(UA)and detection rate of hyperuricemia(HUA)among officers and soldiers during long-term maritime missions,as well as their related influencing factors.Methods A total of 100 servicemen were randomly selected from 240 officers and soldiers who will participate in a long-distance voyage mission.Their general information,including age,education level,administrative position,years of service on board,and department,was surveyed.Their annual data of physical examination were retrospectively analyzed and compared with the results of another 335 shore-based servicemen during the same period.On mission day 10(D10)and day 50(D50),the venous blood samples were collected from the participants to synchronously measure blood UA level and body composition indicators(body fat mass,BMI,fat percentage,fat mass,muscle mass,and muscle percentage).Additionally,on D50,Self-Rating Scale of Sleep(SRSS)and Symptom Checklist-90(SCL-90)were employed to survey their conditions.Seventy service members were randomly selected from the 100 participants to engage in aerobic exercise.The changes in UA level and detection rate of HUA among the mission personnel were analyzed,along with their influencing factors.Results The UA level and HUA detection rate in long-term navigation personnel during concurrent annual physical examinations were significantly lower than those in shore-based personnel(P<0.01).Compared to pre-voyage physical examination results,the UA level and HUA detection rate in long-term navigation personnel were significantly increased from mission day D10(P<0.001).Compared to the values at D10,the UA level and HUA detection rate at D50 showed significant decreases(P<0.05),and then essentially returned to pre-mission examination levels(P>0.05).Aged<32 years was an independent risk factor for new-onset HUA at mission D10(P<0.05).<32 years old and aerobic exercise during the voyage were independent influencing factors for HUA outcome(P<0.05).Conclusion Serum UA level and HUA detection rate among officers and soldiers participating in long-term maritime missions are relatively low before departure,but in significant increases during the early stages of the mission,particularly among those aged<32 years.Scientific aerobic exercise during the mission period helps reduce UA level and HUA detection rate,playing a crucial role in guaranteeing physical and mental health.

The genome tagging project (GTP) plays a pivotal role in addressing a critical gap in the understanding of protein functions. Within this framework, we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411 (HA-tagged Ssp411) mouse model. This model is instrumental in probing the expression and function of Ssp411. Our research revealed that Ssp411 is expressed in the round spermatids, elongating spermatids, elongated spermatids, and epididymal spermatozoa. The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis. Nevertheless, rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions. Ssp411 is not detectable in metaphase II (MII) oocytes, zygotes, or 2-cell stage embryos, highlighting its intricate role in early embryonic development. These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP, fostering groundbreaking advancements in the fields of spermiogenesis and reproductive biology.
Animals ; Female ; Humans ; Male ; Mice ; Spermatids/metabolism* ; Spermatogenesis/physiology* ; Spermatozoa/metabolism* ; Thioredoxins/genetics*

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

OBJECTIVES: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy, with disease progression driven by cytogenetic abnormalities and a complex bone marrow microenvironment. This study aims to construct a prognostic model for MM based on transcriptomic data and lipid metabolism related genes (LRGs), and to identify potential drug targets for high-risk patients to support clinical decision-making. METHODS: In this study, 2 transcriptomic datasets covering 985 newly diagnosed MM patients were retrieved from the Gene Expression Omnibus (GEO) database. Univariate Cox regression and 101 machine learning algorithms were used for gene selection. An LRG-based prognostic model was constructed using Stepwise Cox (both directions) and random survival forest (RSF) algorithms. The association between the prognostic score and clinical events was evaluated, and model performance was assessed using time-dependent receiver operating characteristic (ROC) curves and the C-index. The added predictive value of combining prognostic scores with clinical variables and staging systems was also analyzed. Differentially expressed genes between high- and low-risk groups were identified using limma and clusterProfiler and subjected to pathway enrichment analysis. Drug sensitivity analysis was conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database and oncoPredict to identify potential therapeutic targets for high-risk patients. The functional role of key LRGs in the model was validated via in vitro cell experiments. RESULTS: An LRG-based prognostic model (LRG17) was successfully developed using transcriptomic data and machine learning. The model demonstrated robust predictive performance, with area under the curve (AUC) values of 0.962, 0.912, and 0.842 for 3-, 5-, and 7-year survival, respectively. Patients were stratified into high- and low-risk groups, with high-risk patients showing significantly shorter overall survival (OS) and event-free survival (EFS) (both P<0.001) and worse clinical profiles (e.g., lower albumin, higher β2-microglobulin and lactate dehydrogenase levels). Enrichment analysis revealed that high-risk patients were significantly enriched for pathways related to chromosome segregation and mitosis, whereas low-risk patients were enriched for immune response and immune cell activation pathways. Drug screening suggested that AURKA inhibitor BMS-754807 and FGFR3 inhibitor I-BET-762 may be more effective in high-risk patients. Functional assays demonstrated that silencing of key LRG PLA2G4A significantly inhibited cell viability and induced apoptosis. CONCLUSIONS LRGs serve as promising biomarkers for prognosis prediction and risk stratification in MM. The overexpression of chromosomal instability-related and high-risk genetic event-associated genes in high-risk patients may explain their poorer outcomes. Given the observed resistance to bortezomib and lenalidomide in high-risk patients, combination therapies involving BMS-754807 or I-BET-762 may represent effective alternatives.
Humans ; Multiple Myeloma/mortality* ; Prognosis ; Lipid Metabolism/genetics* ; Transcriptome ; Machine Learning ; Male ; Female ; Gene Expression Profiling ; Algorithms

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.