Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases.Accurately predicting microbe-disease interactions(MDIs)offers critical insights for disease intervention and pharmaceutical research.Current advanced AI-based technologies automatically generate robust representations of microbes and diseases,enabling effec-tive MDI predictions.However,these models continue to face significant challenges.A major issue is their reliance on complex feature extractors and classifiers,which substantially diminishes the models' generalizability.To address this,we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer po-tential MDIs.Initially,we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation.Secondly,we employ decoupled representation learning technology,compelling the graph neural network(GNN)to independently learn the weights for each feature subspace,thus enhancing its expressive power.Finally,we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN,reducing information loss due to occlusion.Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models.This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research.Code and data are accessible at:https://github.com/shmildsj/MDI-IFDRL.

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases. Accurately predicting microbe-disease interactions (MDIs) offers critical insights for disease intervention and pharmaceutical research. Current advanced AI-based technologies automatically generate robust representations of microbes and diseases, enabling effective MDI predictions. However, these models continue to face significant challenges. A major issue is their reliance on complex feature extractors and classifiers, which substantially diminishes the models' generalizability. To address this, we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer potential MDIs. Initially, we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation. Secondly, we employ decoupled representation learning technology, compelling the graph neural network (GNN) to independently learn the weights for each feature subspace, thus enhancing its expressive power. Finally, we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN, reducing information loss due to occlusion. Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models. This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research. Code and data are accessible at: https://github.com/shmildsj/MDI-IFDRL.

Background The mental health problems of employees in administrative organs and public institutions are highly valued.However,there is a lack of understanding regarding the mental health status of employees in provincial and municipal administrative organs and public institutions in Qinghai region.Objective To analyze the anxiety and depression of employees in provincial and municipal administrative organs and public institutions in Qinghai region,so as to provide references for promoting their mental health and intervening in psychological problems.Methods From October 23 to 28,2022,a total of 3 096 employees in provincial and municipal administrative organs and public institutions in Qinghai region were enrolled using stratified cluster sampling technique,and were assessed using Self-rating Anxiety Scale(SAS)and Self-rating Depression Scale(SDS).Results A total of 1797(58.04％)employees in municipal and above administrative organs and public institutions in Qinghai region completed a valid questionnaire survey.Depressive symptoms were noted in 579(32.22％).SDS scores yielded statistical difference among the selected employees of different ethnicities,types of job positions and educational levels(F=9.074,101.488,4.477,P<0.01),and the severity of depressive symptoms also demonstrated statistical difference among the selected employees with different ethnicities,educational levels and types of job positions(H=49.196,17.028,160.848,P<0.01).Anxiety symptoms were detected in 711(39.57％)employees.SAS scores exhibited statistical difference among the employees with different genders,ages,ethnicities,educational levels,marital status and types of job positions(t=-4.571,F=6.648,3.950,5.243,12.008,22.253,P<0.01).Statistical differences were also illustrated in the severity of anxiety symptoms among the selected employees with different ages,genders,ethnicities,educational levels,marital status and types of job positions(H=24.361,-3.788,28.365,24.268,25.976,56.204,P<0.01).Conclusion About one-third of employees in municipal and above administrative organs and public institutions in Qinghai region may have symptoms of depression and anxiety.The depression symptoms are more severe among Tibetan people,those with low education levels and ordinary civil servants.The anxiety symptoms are more severe among employees aged 30 and below,those with low education levels,unmarried and those in technical positions.

Objective This study aimed to explore the relationships between residential greenness and cardiometabolic risk factors among rural adults in Xinjiang Uygur Autonomous Region(Xinjiang)and thus provide a theoretical basis and data support for improving the health of residents in this region. Methods We recruited 9,723 adult rural residents from the 51st Regiment of the Third Division of the Xinjiang Production and Construction Corps in September 2016.The normalized difference vegetation index(NDVI)was used to estimate residential greenness.The generalized linear mixed model(GLMM)was used to examine the association between residential greenness and cardiometabolic risk factors. Results Higher residential greenness was associated with lower cardiometabolic risk factor prevalence.After adjustments were made for age,sex,education,and marital status,for each interquartile range(IQR)increase of NDVI500-m,the risk of hypertension was reduced by 10.3%(OR=0.897,95%CI=0.836-0.962),the risk of obesity by 20.5%(OR=0.795,95%CI=0.695-0.910),the risk of type 2 diabetes by 15.1%(OR=0.849,95%CI=0.740-0.974),and the risk of dyslipidemia by 10.5%(OR=0.895,95%CI=0.825-0.971).Risk factor aggregation was reduced by 20.4%(OR=0.796,95%CI=0.716-0.885)for the same.Stratified analysis showed that NDVI500-m was associated more strongly with hypertension,dyslipidemia,and risk factor aggregation among male participants.The association of NDVI500-m with type 2 diabetes was stronger among participants with a higher education level.PM10 and physical activity mediated 1.9%-9.2%of the associations between NDVI500-m and obesity,dyslipidemia,and risk factor aggregation. Conclusion Higher residential greenness has a protective effect against cardiometabolic risk factors among rural residents in Xinjiang.Increasing the area of green space around residences is an effective measure to reduce the burden of cardiometabolic-related diseases among rural residents in Xinjiang.

Background::Despite the adverse effects of ambient fine particulate matter (PM 2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM 2.5 on the relationship between PA and type 2 diabetes remains unclear. Methods::In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long-term PM 2.5 exposure was calculated using 1-km resolution satellite-based PM 2.5 estimates. PM 2.5 exposure and PA's effect on type 2 diabetes were assessed by cohort-stratified Cox proportional hazards models, individually and in combination. Results::In 488,166 person-years of follow-up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM 2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM 2.5 stratification (≤65.02 μg/m 3) other than in high PM 2.5 stratification (>65.02 μg/m 3), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66-0.85) and 1.10 (95% CI: 0.99-1.22), respectively. Similar results were observed for PA intensity. High PM 2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR= 1.79, 95% CI: 1.59-2.01 for PA volume; HR = 1.82, 95% CI: 1.64-2.02 for PA intensity). Conclusion::PA could reduce type 2 diabetes risk in low-pollution areas, but high PM 2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long-term polluted residents.

Background::Despite the adverse effects of ambient fine particulate matter (PM 2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM 2.5 on the relationship between PA and type 2 diabetes remains unclear. Methods::In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long-term PM 2.5 exposure was calculated using 1-km resolution satellite-based PM 2.5 estimates. PM 2.5 exposure and PA's effect on type 2 diabetes were assessed by cohort-stratified Cox proportional hazards models, individually and in combination. Results::In 488,166 person-years of follow-up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM 2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM 2.5 stratification (≤65.02 μg/m 3) other than in high PM 2.5 stratification (>65.02 μg/m 3), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66-0.85) and 1.10 (95% CI: 0.99-1.22), respectively. Similar results were observed for PA intensity. High PM 2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR= 1.79, 95% CI: 1.59-2.01 for PA volume; HR = 1.82, 95% CI: 1.64-2.02 for PA intensity). Conclusion::PA could reduce type 2 diabetes risk in low-pollution areas, but high PM 2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long-term polluted residents.

Objective:To analyze and monitor the genetic stability of Omicron strain inactivated vaccine.Methods:The virus seeds of Omicron strain for inactivated vaccine through different routes, that was with plaque purification or not, were continuously passaged on cells, and then the supernatant of cell culture was harvested to extract virus nucleic acid. The next generation sequencing was used to analyze virus transcriptome, and the differences of mutation sites, mutation frequencies and insertions/deletions in the whole genome of Omicron virus under different conditions were compared.Results:After continuous passage, more than 5% mutation sites in ORF1ab and S gene sequences were significantly less in the plaque-purified seed than those of the virus without plaque purification, and no insertion/deletion mutations were detected in the whole genome of the purified virus.Conclusions:The nucleic acid sequences of virus with different routes were analyzed by next generation sequencing. The result showed that the genetic stability of virus after plaque purification was better than that of unpurified virus strains, which provides a scientific basis for virus seed selection in the development of inactivated vaccine.

The vagina contains at least a billion microbial cells,dominated by lactobacilli.Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age,as well as cervical,fecal,and salivary samples from a second cohort of 632 women.Factors such as pregnancy history,delivery history,cesarean section,and breastfeeding were all more important than menstrual cycle in shaping the microbiome,and such information would be necessary before trying to interpret differences between vagino-cervical micro-biome data.Greater proportion of Bifidobacterium breve was seen with older age at sexual debut.The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history.Potential markers for lack of menstrual regularity,heavy flow,dysmenor-rhea,and contraceptives were also identified.Lactobacilli were rare during breastfeeding or post-menopause.Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome.Gut and salivary microbiomes,plasma vitamins,metals,amino acids,and hormones showed associations with the vagino-cervical microbiome.Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.

Objective     To analyze the perioperative outcomes of uniportal thoracoscopic lobectomy compared with three-port thoracoscopic lobectomy. Methods     Data were extracted from the Western China Lung Cancer Database, a prospectively maintained database at the Department of Thoracic Surgery, West China Hospital, Sichuan University. Perioperative outcomes of the patients who underwent uniportal or three-port thoracoscopic lobectomy for lung cancer during January 2014 through April 2021 were analyzed by using propensity score matching. Altogether 5 817 lung cancer patients were enrolled who underwent thoracoscopic lobectomy (uniportal: 530 patients; three-port: 5 287 patients). After matching, 529 patients of uniportal and 1 583 patients of three-port were included. There were 529 patients with 320 males and 209 females at median age of 58 (51, 65) years in the uniportal group and 1 583 patients with 915 males and 668 females at median age of 58 (51, 65) years in the three-port group. Results     Uniportal thoracoscopic lobectomy was associated with less intraoperative blood loss (20 mL vs. 30 mL, P<0.001), longer operative time (115 min vs. 105 min, P<0.001) than three-port thoracoscopic lobectomy. No significant difference was found between the two groups regarding the number of lymph node dissected, rate of conversion to thoracotomy, incidence of postoperative complication, postoperative pain score within 3 postoperative days, length of hospital stay, or hospitalization expenses. Conclusion     Uniportal video-assisted thoracoscopic lobectomy is safe and effective, and the overall perioperative outcomes are comparable between uniportal and three-port strategies, although the two groups show differences in intraoperative blood loss.

Objective: To investigate the expression of B7H3 in neuroblastoma (NB) tissues and its relationship between clinical characteristics and prognosis of patients. Methods: The clinical data and pathological wax of 100 cases with neuroblastoma admitted from January 2000 to December 2015 in Sun Yet-Sen University Cancer Center were collected.The expression of B7H3 in tumor tissues was detected by immunohistochemistry (IHC) and then the expression of B7H3 and its relation to pathological parameters and survival rate of patients were analyzed. Results: (1) The positive rates of B7H3 in tumor tissues were 79% (79/100 cases), of which 37 were weak positive, 31 were mode-rate positive, 11 were strong positive, 58%(58/100 cases) showed low expression and 42%(42/100 cases) showed high expression.(2)The positive rate of B7H3 was positively correlated with the risk stratification, age, stage, primary site and N-MYC gene status (r=0.621, 0.350, 0.730, 0.224, 0.335; all P<0.05). (3)The high expression rates of B7H3 were positively correlated with the risk, stage, N-MYC gene status and tumor size (r=0.177, 0.016, 0.175, 0.284; all P<0.05). (4)B7H3 negative and positive 4-year event free survival (EFS) rates of 100 patients were 89.5% and 19.9% (χ²=31.260, P<0.001), 4-year overall survival(OS) rates were 94.7% and 48.3% (χ²=20.212, P<0.001), for 33 non-high-risk patients, B7H3 negative and positive 4-year EFS rates were 100.0% and 47.3% (χ²=8.760, P=0.003), and 4-year OS rates were 100.0% and 93.8% (χ²=1.063, P=0.003), respectively.Sixty-seven high-risk patients with B7H3 negative and positive 4-year EFS were 50.0% and 15.4% (χ²=4.093, P=0.043), 4-year OS were 75.0% and 42.0%, respectively (χ²=1.872, P=0.171). (5)The 4-year EFS rates of 100 patients with B7H3 low expression and high expression were 41.8% and 27.1% (χ²=3.801, P=0.051), and 4-year OS rates were 58.6% and 63.8% (χ²=0.111, P=0.739), respectively.The 4-year EFS and OS rates for 33 non-high-risk patients with B7H3 low expression and high expression were 94.7% and 44.2% (χ²=9.122, P=0.003), 100.0% and 90.9% (χ²=2.000, P=0.157), respectively.The 4-year EFS and OS rates of 67 high-risk patients with high expression and low expression of B7H3 were 13.9% and 22.1% (χ²=0.061, P=0.805), 36.3% and 57.7%(χ²=2.060, P=0.151), respectively.(6)Multivariate analysis showed that OS and EFS in B7H3 positive patients were lower than those in B7H3 negative patients[RR 95%CI: 28.110 (2.430-325.148); P=0.008; RR 95%CI: 12.834 (2.669-61.715), P=0.001]. Conclusions The positive rate of B7H3 in neuroblastoma is high, and the expression level of B7H3 is closely related to the clinical characteristics of the patients.Positive B7H3 in tumor tissues is an independent poor prognostic factor.B7H3 may be one of the new prognostic indicators for NB.