Objective: To quantitatively assess the health risk of preservatives from beverages around primary schools in Anshun City, and to provide scientific basis for precise food safety supervision. Methods: From December 2023 to July 2024, 602 beverage samples were randomly collected from within 100 meters of 19 primary schools in Anshun City. The content of benzoic acid, sorbic acid, and dehydroacetic acid was detected according to GB 5009 series standards. Combined with children s physiological parameters (body weight 30 kg, daily intake 0.15 L), the Hazard Quotient (HQ) and Hazard Index (HI) models were used to evaluate health risks. Results: The total detection rate of preservatives from beverages around primary schools was 63.0%, and the total over limit rate was 9.0%. The detection rate of preservatives in flavored beverages was the highest (72.6%), and the highest over limit rate of preservatives in special purpose beverages was the highest (17.2%). The single preservative HQ (benzoic acid up to 0.47 ) and mixed HI (up to 0.55) of all samples were below 1(safety threshold). However, the HQ value of benzoic acid in flavored beverages (0.47) was 2.9 times that of sorbic acid (0.16), contributing significantly to health risk. Sensitivity analysis showed that if the daily consumption increased to 0.3 L, the HI value of flavored beverages would rise to 1.11, exceeding the safety threshold. Enterprise scale analysis showed that the exceedance rate of special purpose beverages in large enterprises reached 30.0%, while micro enterprises, accounting for a dominant market share (52.2%), constituted the main source of children s daily exposure to their products. Conclusions The overall health risk of perservatives in beverages sold near primary schools in Anshun City is controllable, but there is a noticeable risk of gradient. The risk of children’s exposure to preservatives through beverage consumption should not be ignored.

Objective:To evaluate the clinical efficacy of Buyang Huanwu Decoction combined with medium-frequency pulsed electrical stimulation in the treatment of diabetic peripheral neuropathic pain (DPNP).Methods:A randomized controlled trial study was conducted. A total of 86 patients with DPNP in the endocrinology department of Xi'an Hospital of Traditional Chinese Medicine from September 2020 to September 2023 were selected as the observation objects and divided into 2 groups through the random number table method, with 43 cases in each group. The control group was combined with medium-frequency pulsed electrical stimulation on the basis of conventional Western medical treatment, while the observation group was supplemented with Buyang Huanwu Decoction on the basis of the control group. Both groups were treated for 12 weeks. TCM syndrome scores were conducted before and after the treatment respectively. The Toronto Clinical Scoring System (TCSS) was used to grade the severity of neuropathy. The motor nerve conduction velocity (MCV) and sensory nerve conduction velocity (SCV) of the median nerve and common peroneal nerve were detected by electromyography evoked potential tester. Adverse reactions during the treatment were recorded to evaluate the clinical efficacy.Results:The total effective rate was 93.02% (40/43) in the observation group and 74.42% (32/43) in the control group, with statistical significance between the two groups ( χ2=5.46, P=0.019). After treatment, the scores of shortness of breath and fatigue, end-limb pain, listlessness, dull tongue and the total score in the observation group were lower than those in the control group ( t values were 3.06, 3.42, 3.09, 3.57 and 3.98 respectively, P<0.05); the scores of neurological symptoms, neural reflexes and sensory function examinations were lower than those in the control group ( t values were 4.54, 6.28 and 5.16 respectively, P<0.01). After treatment in the observation group, MCV of the median nerve [(47.96±5.98) m/s vs. (42.02±5.74) m/s, t=4.70] and SCV [(54.90±6.29) m/s vs. (48.04±6.16) m/s, t=5.11] were higher than those in the control group. The MCV of the common perbular nerve [(41.76±6.27) m/s vs. (37.04±6.18) m/s, t=3.52] and SCV [(50.35±6.41) m/s vs. (46.14±6.13) m/s, t=3.12] were higher than those in the control group ( P<0.01 or P<0.05). During the treatment period, the incidence of adverse reactions was 11.63% (5/43) in the observation group and 9.30% (4/43) in the control group, without statistical significance between the two groups ( χ2=0.12, P=0.725). Conclusion:Buyang Huanwu Decoction combined with medium-frequency pulsed electrical stimulation can effectively improve the degree of neuropathy in patients with DPNP, increase nerve conduction velocity, alleviate TCM syndromes, enhance clinical efficacy and has good safety.

Objective To screen and analyze key genes in rabbit corneal alkali burns based on transcriptomics se-quencing technology and bioinformatics techniques.Methods Thirty healthy male New Zealand rabbits were randomly di-vided into 2 groups(n=15 per group):The control group received no intervention,while the alkali burn group underwent corneal alkali burn modeling.Histological evaluation of corneal tissues was performed via hematoxylin-eosin(HE)stai-ning.Transcriptome sequencing was conducted for library construction and sequencing.Differentially expressed genes(DEGs)were identified using DESeq2,followed by Gene Ontology(GO)functional enrichment analysis and Kyoto Ency-clopedia of Genes and Genomes(KEGG)pathway analysis.A protein-protein interaction(PPI)network was constructed to screen hub genes,and RT-PCR was employed to validate mRNA expression levels of key genes.Results HE staining revealed orderly arranged corneal stromal layers and scattered stromal cells in the control group,whereas the alkali burn group exhibited stromal edema,thickened collagen fibers with loose/disorganized alignment,and increased fibroblast and inflammatory cell infiltration.Compared to the control group,1 827 significant DEGs were identified in the alkali burn group,including 1 495 upregulated and 332 downregulated genes.GO analysis showed biological processes such as immune response,plasma membrane,and identical protein binding.KEGG analysis indicated that DEGs were enriched in pathways related to cancer,lipid and atherosclerosis,and neuroactive ligand-receptor interaction.The PPI network screened 11 key genes:neutrophil cytosolic factor 1(NCF1),neutrophil cytosolic factor 2(NCF2),matrix metallopeptidase 2(MMP2),ma-trix metallopeptidase 9(MMP9),interleukin-1α(IL-1α),interleukin-1β(IL-1β),interleukin-6(IL-6),interleukin-8(CXCL8),cluster of differentiation 4(CD4),C-C motif ligand 2(CCL2)and tumor necrosis factor(TNF).RT-PCR valida-tion revealed that the mRNA expression levels of key genes in the corneal tissues of the alkali burn group were significantly higher than those in the control group(all P＜0.05),consistent with the transcriptomic sequencing results.Conclusion Based on the rabbit corneal alkali burn model,this study identified 11 key genes(NCF1,NCF2,MMP2,MMP9,IL-1α,IL-1β,IL-6,CXCL8,CD4,CCL2 and TNF)through transcriptomics and bioinformatics analysis.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective:To analyze the interference of an exogenous glucose test on urinary creatinine-related renal injury biomarkers in patients with chronic kidney disease (CKD).Methods:This cross-sectional study enrolled CKD patients who visited Peking University First Hospital between October 2023 and March 2024. The patients (age: 50±18 years) included 90 males and 70 females. Fresh morning urine samples were collected, totaling 160 samples. Each urine sample was divided into 5 aliquots,each containing 225 μl. One aliquot received 75 μl of deionized water as the control. The other aliquots received 75 μl of glucose solutions at concentrations of 120, 480, 960, and 1200 mmol/L, resulting in final glucose concentrations of 30, 120, 240, and 300 mmol/L in the urine samples, respectively. Urinary creatinine in each sample was measured using both the enzymatic method and the picric acid (Jaffe) method. The following ratios were calculated: urinary albumin-to-creatinine ratio (uACR), urinary protein-to-creatinine ratio (uPCR), urinary transferrin-to-creatinine ratio (uTRF/uCr), urinary α1-microglobulin-to-creatinine ratio (uA1M/uCr), urinary immunoglobulin G-to-creatinine ratio (uIgG/uCr), and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/uCr).Results:Under high glucose concentrations, significant differences ( P<0.05) were observed between the enzymatic method and the picric acid method in measuring urinary creatinine-related renal injury biomarkers. At glucose concentrations of 30, 120, 240, and 300 mmol/L, the mean percentage biases for creatinine measured by the enzymatic method were -0.19%, -0.27%, -0.20%, and -0.21%, respectively. The mean percentage biases for creatinine measured by the picric acid method were 0.78%, 1.26%, 1.35%, and 1.38%, respectively, showing an increasing deviation between the results before and after glucose addition as the glucose concentration rose. For uACR measurement, the mean absolute biases using the enzymatic method were -0.01, 1.27, 0.95, and 1.10 mg/g at the respective glucose concentrations. Using the picric acid method, the mean absolute biases for uACR were -11.69, -14.98, -16.91, and-18.51 mg/g. The biases of the picric acid method were significantly higher than the those of the enzymatic method, and the absolute value of the mean biases increased with rising glucose concentration. For uPCR, uTRF/uCr, uA1M/uCr, uNAG/uCr, and uIgG/uCr, the deviations measured by the enzymatic method were consistently smaller than those measured by the picric acid method. Conclusions:The measurement of creatinine and related renal injury biomarkers by the enzymatic method is less affected by glucose concentration. In contrast, the measurement results obtained using the picric acid method are significantly affected by glucose concentration.

BACKGROUND: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation and joint destruction. Iguratimod (IGU) is a novel conventional synthetic disease-modifying antirheumatic drugs (csDMARD) with good efficacy and safety for the treatment of active RA in China and Japan. However, the long-term effects of IGU on the progression of bone destruction or radiographic progression in patients with active RA remain unknown. We aimed to investigate the efficacy and safety of iguratimod (IGU), a combination of methotrexate (MTX) and IGU, and IGU in patients with active rheumatoid arthritis (RA) who were naïve to MTX. METHODS: This multicenter, double-blind, randomized, non-inferiority clinical trial was conducted at 28 centers for over 52 weeks in China. In total, 911 patients were randomized (1:1:1) to receive MTX monotherapy (10-15 mg weekly, n = 293), IGU monotherapy (25 mg twice daily, n = 297), or IGU + MTX (10-15 mg weekly for MTX and 25 mg twice daily for IGU, n = 305) for 52 weeks. The patients' clinical characteristics, Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI), disease activity score in 28 joints-C-reactive protein (DAS28-CRP) level, and disease activity score in 28 joints-erythrocyte sedimentation rate (DAS28-ESR) were assessed at baseline. The primary endpoints were the proportion of patients with ≥20% improvement according to the American College of Rheumatology (ACR20) response and changes in the van der Heijde-modified total Sharp score (vdH-mTSS) at week 52. RESULTS: The proportions of patients achieving an ACR20 response at week 52 were 77.44%, 77.05 %, and 65.87% for IGU monotherapy, IGU + MTX, and MTX monotherapy, respectively. The non-inferiority of IGU monotherapy to MTX monotherapy was established with the ACR20 (11.57%; 95% confidence interval [CI], 4.35-18.79%; P <0.001) and vdH-mTSS (-0.37; 95% CI, -1.22-0.47; P = 0.022). IGU monotherapy was also superior to MTX monotherapy in terms of ACR20 ( P = 0.002) but not the vdH-mTSS. The superiority of IGU + MTX over MTX monotherapy was confirmed in terms of the ACR20 (11.18%; 95% CI, 3.99-18.37%; P = 0.003), but not in the vdH-mTSS (-0.68; 95% CI, -1.46-0.11; P = 0.091). However, the difference in the incidence rates of adverse events was not statistically significant. CONCLUSIONS: IGU monotherapy/IGU + MTX showed a more favorable clinical response than did MTX monotherapy. IGU may have some clinical benefits over MTX in terms of radiographic progression, implying that IGU may be considered as an initial therapeutic option for patients with active RA. TRIAL REGISTRATION https://classic.clinicaltrials.gov/ , NCT01548001.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Antirheumatic Agents/therapeutic use* ; Arthritis, Rheumatoid/drug therapy* ; Chromones/adverse effects* ; Double-Blind Method ; Drug Therapy, Combination ; Methotrexate/adverse effects* ; Treatment Outcome ; Sulfonamides

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.