PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.
Deep Learning ; Drug Discovery/methods* ; Humans ; Diabetes Mellitus, Type 2/metabolism* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

Objective To investigate the metabolic characteristics of patients with early-onset type 2 diabetes mellitus(T2DM)and to develop a risk prediction model for microvascular complications.Methods A retrospective study was conducted on 980 T2DM patients admitted for treatment between April 2020 and April 2024.Based on age at diagnosis,the patients were divided into two groups,an early-onset T2DM group(age at diagnosis<40 years,n=265)and a late-onset T2DM group(age at diagnosis≥40 years,n=715).Differences in metabolic indicators between the two groups were compared.Patients in the early-onset group were further divided into a complication subgroup(n=142)and a non-complication subgroup(n=123)based on the presence or absence of microvascular complications.Data on baseline characteristics,metabolic parameters,and laboratory indicators were collected and compared between the two groups.Multivariate logistic regression analysis was used to identify independent risk factors for microvascular complications,and a nomogram prediction model was constructed.The model's discriminative performance was assessed using receiver operating characteristic(ROC)curves,and its calibration was evaluated using calibration curves and the Hosmer-Lemeshow test.Decision curve analysis(DCA)was also performed to assess the model's clinical utility.Results Compared with the late-onset group,patients in the early-onset group exhibited more pronounced metabolic abnormalities,including higher body mass index(BMI),proportion of family history of diabetes mellitus,glycated hemoglobin(HbA1c)levels,total cholesterol(TC),triglycerides(TG),low-density lipoprotein cholesterol(LDL-C),triglyceride-glucose index(TyG),and lactate dehydrogenase(LDH)levels(all P<0.05),along with a shorter disease duration and lower levels of high-density lipoprotein cholesterol(HDL-C)(P<0.05).According to a multivariate analysis,systolic blood pressure(SBP),total bilirubin(TBIL),HDL-C,LDL-C,TyG,and LDH were identified as independent risk factors for microvascular complications in patients with early-onset T2DM.A predictive model based on these factors was established as the follows,Log(P)=-19.915+0.017×SBP-0.136×TBIL-1.241×HDL-C+0.684×LDL-C+0.769×TyG+0.050×LDH.The area under the ROC curve(AUC)was 0.864(95%CI,0.820-0.907),and the Hosmer-Lemeshow test indicated good model fit(χ2=10.286,P=0.246).The slope of the DCA curve was also close to 1.Conclusion The nomogram prediction model based on SBP,TBIL,HDL-C,LDL-C,TyG,and LDH demonstrates good predictive performance for microvascular complications and can provide a reference for clinical risk stratification and individualized intervention.

Military training represents one of the most essential activities for troops during peacetime,of which the prevention and treatment of training-induced injuries are a very important part.Recent findings of research suggest that cold atmospheric plasma(CAP)exhibits a distinctive and multifaceted superiority in terms of broad-spectrum sterilization,rapid blood coagulation and healing promotion for wounds.Consequently,CAP has good prospects of applications in diverse fields such as clinical medicine,emergency rescue and military medicine.Based on a review of the research progress in plasma medicine,the applicability of CAP in the prevention and treatment of military training injuries was discussed in this paper by focusing on the urgent issues related to military training injury,including the typical application scenarios and methods for CAP,the safety and effectiveness of plasma trauma prevention and treatment,and the key issues facing the prevention and treatment of military training injuries.

A 11-year old female patient with severe thalassemia, receipt a lentivirus-based cell and gene therapy (CGT) therapy in Shenzhen Children′s Hosptial on July 27th, 2021. At the two follow-up visits after discharge, patient were continuously tested positive for HIV screening through HIV Ag/Ab Combo assay (chemiluminescence Immunoassay), and the viral load results of HIV-1 nucleic acid testing (NAT) were both>5 000 copies/ml. The patient can be diagnosed with HIV infection according to the National Guideline for Detection of HIV/AIDS(2020 Revised Edition). The thorough investigation findings and supplementary experiment results indicated that the false-positive HIV-1 NAT results was caused by cross-reactivity between the target sites detected by conventional HIV-1 NAT reagents and the lentiviral vectors fragments integrated into the genome of patient′s hematopoietic stem/progenitor cells. In conclusion, it is important for laboratories to select appropriate HIV-1 NAT testing platforms which won′t cause cross-reactivity for the testing of samples from patients who have been treated with HIV-derived vectors. It is also recommended to design and develop NAT testing platforms with multiple target regions labeled by different fluorescents for HIV NAT supplementation experiment to reduce the risk of false-positive diagnoses of HIV infection.

Objective:To investigate the arsenic metabolism pattern and possible influencing factors in the population in drinking-water-borne endemic arsenic poisoning (drinking-water-borne arsenic poisoning for short) areas.Methods:In December 2004, a cluster sampling method was used to select arsenic poisoning population (arsenic poisoning group) and healthy population (control group) in drinking-water-borne arsenic poisoning area of Bayannur City, Inner Mongolia Autonomous Region as the survey subjects. A questionnaire survey was conducted. Arsenic content in drinking water at home of survey subjects, the levels of urinary arsenic and its metabolites, including [trivalent arsenic (As Ⅲ), inorganic arsenic (iAs), monomethylarsenic acid (pentavalent, MMA V), dimethylarsenic acid (pentavalent, DMA V), total arsenic (tAs), percentage of inorganic arsenic (iAs%), percentage of monomethylarsenic acid (MMA%), percentage of dimethylarsenic acid (DMA%), primary methylation index (PMI), secondary methylation index (SMI)] were tested using high performance liquid chromatography-inductively coupled plasma mass spectrometry; nail arsenic and nail selenium levels were tested using atomic fluorescence spectrometer. The influencing factors of arsenic metabolism pattern were analyzed by multiple linear regression. Results:A total of 536 survey subjects were included, including 155 individuals in the arsenic poisoning group and 381 in the control group. The water arsenic level ranged from 0.0 to 825.7 μg/L. Compared with the control group, there was no significant difference in the distribution of gender, education level and dental fluorosis in the arsenic poisoning group ( P > 0.05), but there were significant differences in the distribution of age, marital status, smoking, drinking and water arsenic ( P < 0.05). Compared with the control group, the levels of urinary As Ⅲ, iAs, MMA V, DMA V, tAs, MMA%, MMA/DMA and nail arsenic in the arsenic poisoning group were higher ( P < 0.05), while the levels of urinary DMA%, SMI and nail selenium were lower ( P < 0.05); but there was no statistically significant difference in the levels of urinary iAs% and PMI ( P > 0.05). Gender, education level, depth of wells, water arsenic, total number of wells and nail arsenic were the influencing factors of urinary As Ⅲ (β = - 19.82, - 23.83, 0.61, 0.21, 7.26, 2.98, P < 0.05). Age, depth of wells, water arsenic and nail arsenic were the influencing factors of urinary tAs (β = 3.18, 3.25, 1.31, 15.59, P < 0.05). Gender, education level, depth of wells, water arsenic, total number of wells and nail arsenic were the influencing factors of urinary iAs (β = - 20.47, - 25.90, 0.64, 0.25, 7.87, 3.11, P < 0.05). Age, gender, education level, water arsenic and nail arsenic were the influencing factors of urinary MMA V (β = 0.52, - 17.07, - 21.84, 0.22, 2.77, P < 0.05). Age, depth of wells, water arsenic and nail arsenic were the influencing factors of urinary DMA V (β = 2.35, 2.47, 0.85, 9.22, P < 0.05). Conclusions:Compared with healthy individuals, there are differences in arsenic metabolism pattern among individuals with drinking-water-borne arsenic poisoning. Age, gender, education level, depth of wells, water arsenic, total number of wells and nail arsenic may be influencing factors of different arsenic metabolism patterns.

Objective:To investigate the effects of low-frequency and high frequency repetitive transcranial magnetic stimulation (rTMS) combined with levodopa and benserazide hydrochloride on mild cognitive impairment in patients with Parkinson disease (PD).Methods:Totally 90 PD patients with mild cognitive impairment who visited from January 2020 to June 2022 were included , and they were divided into a simple drug group ( n=30), drug+ low-frequency group ( n=30), and drug+ high-frequency group ( n=30) according to the order of admission.The patients in the simple drug group were treated with oral levodopa and benserazide hydrochloride, while the patients in drug+ low-frequency and drug+ high-frequency groups were treated with low-frequency or high-frequency rTMS on the basis of oral levodopa and benserazide hydrochloride.Montreal cognitive assessment(MoCA), digital span (DS), Chinese auditory learning test (CALT), the judgment of line orientation test (JLOT) and verbal fluency test (VFT) were used to evaluate the cognitive function of patients before and after 4 weeks of treatment.SPSS 26.0 was used for statistical analysis.The paired t-test was used for intra-group comparison before and after treatment, while one-way ANOVA was used for inter-group comparison. Results:There were no significant differences in MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT, and VFT scores among patients in the simple drug group before and after 4 weeks of treatment( t=-1.157, -0.648, -0.215, -0.290, -0.154, -0.782, -0.960, all P>0.05). After 4 weeks of treatment, MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT and VFT scores in drug+ low-frequency group and drug+ high-frequency group were higher than before treatment (drug+ low frequency group: t=-16.357, -11.379, -7.999, -11.805, -16.624, -15.996, -17.241, all P<0.05; drug+ high-frequency group: t=-25.198, -13.971, -13.904, -25.831, -26.382, -20.108, -15.643, all P<0.05). There were no statistically significant differences in the scores of MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT and VFT among the three groups before treatment (all P>0.05). After treatment, there were statistically significant differences in the scores of MoCA, DS anterograde, DS backward, CALT immediate recall, CALT delayed recall, JLOT and VFT among the three groups (simple drug group : (20.37±1.96), (4.37±1.19), (2.80±0.55), (6.93±1.70), (5.17±1.09), (15.50±2.69), (10.73±1.55); drug+ low-frequency group: (23.83±2.32), (5.87±0.94), (3.87±0.73), (9.17±1.74), (8.13±1.50), (20.77±2.19), (13.30±1.73); drug+ high-frequency group: (27.17±1.64), (6.73±1.01), (4.80±0.81), (11.20±2.06), (10.03±1.54), (25.17±3.14), (15.87±2.05)) (all P<0.05). Further analysis showed that both the drug+ low-frequency and drug+ high-frequency groups had higher scores than the simple drug group, and the drug+ high-frequency group had higher scores than the drug+ low-frequency group(all P<0.05). Conclusion:The combination of drug+ low-frequency or drug+ high-frequency rTMS and drug therapy can help improve cognitive function in patients with PD, and the efficacy of drug+ high-frequency rTMS may be more significant, which provides a new therapeutic idea for clinical treatment of patients with PD.

Objective To investigate the effect of dapagliflozin-mediated miR-98-5p on high glucose-induced damage in human renal tubular epithelial cells.Methods Blood samples from patients with diabetic nephropathy(DN)and healthy individuals were collected.The expression of serum miR-98-5p was detected by real-time fluorescence quantitative polymerase chain reaction(RT-qPCR),and kidney injury-related indicators were measured using a biochemical immunoassay analyzer.HK-2 cells were cultured in vitro and randomly divided into control group(5 mmol·L-1 glucose),HG group(30 mmol·L-1 glucose),experimental-L group(30 mmol·L-1 glucose+20 μmol·L-1 dapagliflozin),experimental-H group(30 mmol·L-1 glucose+40 μmol·L-1 dapagliflozin),anti-miR-NC group(transfected with anti-miR-NC+30 mmol·L-1 glucose+40 μmol·L-1 dapagliflozin),and anti-miR-98-5p group(transfected with anti-miR-98-5p+30 mmol·L-1 glucose+40 μmol·L-1 dapagliflozin).Cell viability was evaluated using the cell counting kit 8(CCK-8)assay 24 hours after drug treatment;miR-98-5p expression in cells was detected by RT-qPCR;cell apoptosis rate was measured by flow cytometry,apoptosis-related protein expression was detected by Western blot;and inflammatory cytokine expression was measured by enzyme-linked immunosorbent assay.Results The expression levels of miR-98-5p in the serum of DN patients and healthy individuals were 1.00±0.25 and 0.39±0.05,respectively,showing a significant difference between the two groups(P＜0.05).The expression levels of miR-98-5p in the control group,HG group,experimental-H group,anti-miR-NC group,and anti-miR-98-5p group were 1.00±0.09,0.31±0.04,0.72±0.06,0.75±0.07 and 0.22±0.03;the cell survival rates were(100.00±3.36)％,(51.63±5.89)％,(79.46±9.90)％,(82.88±5.71)％and(59.69±7.43)％;apoptosis rates were(3.52±0.20)％,(35.80±3.67)％,(16.43±1.57)％,(15.71±1.42)％and(29.37±2.18)％;tumor necrosis factor-α(TNF-α)levels were(22.46±1.67),(68.37±6.05),(34.45±2.47),(35.11±2.84)and(60.46±3.56)pg·mL-1,respectively.The differences among these indicators were all statistically significant when comparing the HG group to the control group,the experimental-H group to the HG group,and the anti-miR-98-5p group to the anti-miR-NC group(all P＜0.05).Conclusion Dapagliflozin can alleviate high glucose-induced HK-2 cell damage by upregulating the expression of miR-98-5p,inhibiting inflammation,and reducing cell apoptosis.