Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.

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.

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

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.

Objective To evaluate the clinical efficacy of buccal acupuncture combined with tuina in treating frozen shoulder and explore its potential mechanism of action.Methods Sixty-four patients diagnosed with frozen shoulder were enrolled from the Rehabilitation Department of Qingyuan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Chinese Medicine between May 2024 and December 2024.Patients were randomly divided into an observation group and a control group using a random number table,with 32 cases in each group.The control group received traditional Chinese tuina therapy,while the observation group received additional buccal acupuncture treatment.Three treatment sessions constituted one course,with a total of two courses administered.Clinical efficacy was evaluated after treatment,and the Visual Analogue Scale(VAS)scores for shoulder pain,Constant-Murley Shoulder Score(CMS),and Hamilton Anxiety Scale(HAMA)scores were observed before and after intervention.Serum levels of interleukin 6(IL-6)and C-reactive protein(CRP)were also compared.Results(1)After treatment,the total effective rate of the observation group was 93.75%(30/32),and that of the control group was 75.00%(24/32),and the efficacy of the observation group was superior to that of the control group,and the difference was statistically significant(P＜0.05).(2)After treatment,the VAS scores of patients in the two groups were significantly reduced(P＜0.05),and the observation group was significantly superior to the control group in improving the patients'VAS scores,with a statistically significant difference(P＜0.05).(3)After treatment,the CMS scores of patients in the two groups were significantly increased(P＜0.05),and the observation group was significantly superior to the control group in improving patients'CMS scores,with statistically significant differences(P＜0.05).(4)After treatment,the HAMA scores of patients in the two groups were significantly increased(P＜0.05),and the observation group was significantly superior to the control group in improving patients'HAMA scores,with statistically significant differences(P＜0.05).(5)After treatment,the IL-6 and CRP levels of patients in the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the IL-6 and CRP levels,and the difference was statistically significant(P＜0.05).Conclusion The combination of buccal acupuncture and traditional Chinese tuina therapy significantly alleviates shoulder pain,improves shoulder joint function,reduces anxiety,and decreases inflammatory markers IL-6 and CRP in patients with frozen shoulder,demonstrating notable clinical efficacy.

Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.

Objective:To investigate the mechanism of immunomodulatory effects of umbilical cord mesenchymal stem cells(UC-MSCs)modified by miR-125b-5p on systemic lupus erythematosus(SLE).Methods:The expression level of miR-125b-5p was detected by real-time fluorescence quantitative PCR in UC-MSCs and peripheral blood mononuclear cells(PBMCs)from SLE patients and health checkers.Annexin V-FITC/PI apoptosis detection kit was used to detect the effect of miR-125b-5p on apoptosis of UC-MSCs.MRL/lpr mice in each group were injected with UC-MSCs via tail vein,and T-lymphocyte subsets in the spleen of the MRL/lpr mice were detected by flow cytometry after 5 weeks.The expression levels of interleukin(IL)-4 and IL-17A in serum of MRL/lpr mice were detected by ELISA.Hematoxylin-eosin staining was used to observe the pathological manifestations of the lungs and kidneys of the MRL/lpr mice.Results:miR-125b-5p was significantly down-regulated in PBMCs of SLE patients compared with healthy controls(P＜0.01).Compared with the UC-MSCs group,the expression of miR-125b-5p in UC-MSCs modified by miR-125b-5p group was increased(P＜0.01).The survival rate of UC-MSCs was significantly increased by miR-125b-5p(P＜0.01).Compared with the untreated group of MRL/lpr mice,the expression level of IL-4 in serum was increased(P＜0.05);the expression level of IL-17A was decreased(P＜0.05);the proportion of Th17 cells in the spleen of MRL/lpr mice was decreased(P＜0.05);the inflammatory cells infiltration and micro-thrombosis of lungs and kidneys of MRL/lpr mice were significantly reduced in the UC-MSCs modified by miR-125b-5p treatment group.Conclusion:UC-MSCs modified by miR-125b-5p have immunomodulatory effects on systemic lupus erythematosus.

Feces and intestinal contents of pigs suspected with porcine epidemic diarrhea virus were collected from a farm in Minqin County,Gansu Province,China.After the suspected positive sam-ples were detected by RT-PCR,Vero cells were used to isolate and culture them in vitro.The suc-cessfully isolated virus was identified in the laboratory,and its whole genome sequence was ana-lyzed for genetic evolution.The pathogenicity was evaluated by animal regression test.The results showed that typical syncytial lesions could be observed when the PEDV-positive treatment solu-tion was inoculated with Vero cells in the 4th generation,and the virus titer in the 6th generation reached 10-4 75TCID50/mL.PEDV-like virions with a diameter of about 100 nm and a round shape with obvious capsular membranes and spikes were observed by electron microscopy.Whole genome sequencing analysis showed that the total length of this strain was 28 085 bp,which was far from the G1 subtype represented by the classical strain CV777(96.6％),and had a high homology with the G2b strains BC-2011-1,IA1,USA/Colorado/2013 and WELL(98.6％).This indicated that the strain belonged to the G2b epidemic strain.The animal regression test showed that the 5-day-old piglets developed vomiting,acute watery diarrhea,emaciation and mental depression within 12 h after the attack,and the symptoms worsened and died within 24 h.After autopsy,the infected piglets could be observed with stomach swelling,high intestinal heave,thin and transparent intesti-nal wall,and undigested milk clots inside.In summary,a PEDV G2b epidemic strain was success-fully isolated and identified in this study,and its whole genome sequence and pathogenicity were analyzed,providing research materials for future studies on PEDV gene function,pathogenic mech-anism and vaccine development.

Objective:To explore the role of 17β-estradiol(17β-E2) derived from the hippocampus and gonad in the cognitive memory during the reconsolidation period of fear memory in rats with post-traumatic stress disorder(PTSD).Methods:The 8-week-old clean grade female SD rats were used for this study. Single prolonged stress combined with context fear conditioning was used to prepare the rat PTSD model.(1) Gonad estradiol experiment: 50 female rats were randomly divided into blank control group, model group, sham ovariectomy group, ovariectomy group, and ovariectomy+ estradiol group by random number table method, with 10 rats in each group. The rats in model group, sham ovariectomy group, ovariectomy group, and ovariectomy+ estradiol group were established PTSD model. Rats in ovariectomy group and ovariectomy+ estradiol group underwent ovariectomy, while rats in sham ovariectomy group only were removed adipose tissue of the same mass around the ovaries. And the rats in ovariectomy+ estradiol group were injected with 17β-E2(1 mg/kg, once a day for 14 days) 7 days after ovariectomy.(2) Hippocampal estradiol experiment: 40 female rats were randomly divided into blank control group, model group, hippocampal solvent control group and hippocampal estradiol inhibitor group by random number table method, with 10 rats in each group.The rats in model group, hippocampal solvent control group and hippocampal estradiol inhibitor group were established PTSD model.Rats in hippocampal estradiol inhibitor group were given letrozole once(bilateral, 0.5 μL per side) during the fear memory consolidation period) and rats in the hippocampus solvent control group were injected once with dimethyl sulfoxide in the hippocampus(bilateral, 0.5 μL per side) . The open field test and elevated cross maze test were used to evaluate the anxiety level and autonomous exploration ability, the freeze test was used to evaluate the fear memory, the new object recognition test was used to evaluate the non-spatial memory, and ELISA was used to detect serum 17β-E2 level. SPSS 25.0 software was used for data analysis, and one-way ANOVA was used for inter group comparisons, LSD test was used for further pairwise comparisons.Results:(1)In the gonad estradiol experiment, there were statistical differences in various indicators among the five groups of rats in the open field test, elevated cross maze test, freeze test, and new object recognition test( F=20.200, 12.702, 7.514, 10.094, 7.899, 13.211, all P<0.05). The number of upright times, central area activity time, distance and frequency of entering the open arm, and cognitive index of the model group rats were all lower than those of the blank control group(all P<0.05), and the freezing time was higher than that of the blank control group( P<0.05). The number of upright positions((11.20±1.55) times), central area activity time((11.33±1.80) s), distance((1.49±0.26) m) and times((10.00±1.50) times) entering the open arm, the freezing time((92.20±6.07) s) and cognitive index((60.40±3.71)%) in ovariectomy+ estradiol group were all higher than those of ovariectomy group((4.90±0.65) times, (4.31±1.07) s, (0.49±0.06) m, (3.10±0.62) times, (60.30±5.28) s, (32.60±8.08)%)(all P<0.05). (2) In the hippocampal estradiol experiment, there were statistical differences in various indicators among the four groups in the open field test, elevated cross maze test, freeze test, and new object recognition test( F=40.831, 5.553, 9.087, 5.848, 7.657, 9.191, all P<0.05). The numbers of upright positions, distance and frequency of entering open arms of the model group rats were lower than those of the blank control group(all P<0.05). The number of upright positions((3.00 ± 0.39) times), distance of entering open arm((1.17±0.37) m), freezing time((46.70±3.57)s), and cognition index((29.60±2.70)%) in the hippocampal estradiol inhibitor group were all lower than those in the hippocampal solvent control group((10.10±1.40) times, (4.02±0.79) m, (93.70±9.73) s, (54.20±5.08)%)(all P<0.05). Conclusion:17β-E2 derived from the hippocampus and gonad both had ameliorative effect on cognitive memory and anxiety-like behavior in the reconsolidation period of fear memory in PTSD model rats.