ObjectiveTo investigate the contamination levels of zearalenone (ZEN) in commercially available edible vegetable oils in Ningbo City and to assess its health risks to local residents. MethodsA total of 330 samples of commercially available edible vegetable oil samples (50 each of peanut oil, corn oil, and olive oil; 40 each of rapeseed oil and blended oil; 30 each of soybean oil, rice oil, and sunflower seed oil; and 10 of camellia oil) were collected in 2024. The samples were tested for ZEN using the first method specified in GB 5009.209‒2016 National Food Safety Standard―Determination of Zearalenone in Food, namely the liquid chromatography method, and the contamination status was analyzed. Additionally, combined with dietary consumption data of residents, the Monte Carlo simulation method was employed to evaluate the health risks of ZEN in edible vegetable oils. ResultsZEN was detected in 267 out of 330 samples, with a detection rate of 80.91%, and the median (P₅₀) and the 25th, 75th percentiles (P₂₅, P₇₅) of ZEN concentrations were 2.02 (0.37, 17.90) μg·kg^-1, with a maximum value of 342.00 μg·kg^-1. The ZEN detection rates in corn oil, peanut oil, and blended oil were all 100.00%. The daily average exposure (P₅₀) and daily high exposure (P₉₅) to ZEN via edible vegetable oils among Ningbo residents were 0.001 μg·kg^-1 (normalized to body weight, same below) and 0.060 μg·kg^-1, respectively. However, 1.22% of Ningbo residents had a daily ZEN exposure exceeding the tolerable daily intake (TDI) of 0.25 μg·kg^-1. The hazard quotients (HQ) for the daily average exposure (P₅₀) and daily high exposure (P₉₅) levels were 0.004 and 0.020, respectively, both substantially below 1. Nevertheless, the probability of health risk for Ningbo residents due to ZEN exposure from vegetable oil consumption remained at 1.02%. ConclusionEdible vegetable oils in Ningbo City were contaminated with ZEN, but the probability of ZEN exposure exceeding the TDI through edible vegetable oils was relatively low, and the associated health risk probability were also minimal, indicating an overall insignificant health risk.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aims to explore the effects of Huangqin Qingre Chubi capsules-containing serum on the expression of CircRNA_0001543/nuclear factor-kappa B （NF-κB） in co-cultured peripheral blood mononuclear cells （PBMCs） and human fibroblast-like synoviocytes （FLSs） from patients with ankylosing spondylitis （AS）. MethodsVenous blood was collected from patients with AS to isolate PBMCs. FLSs were co-cultured with AS patients' PBMCs， and FLSs were harvested after co-culture for subsequent experiments. The normal control group consisted of normal FLSs， while the model group comprised co-cultured AS PBMCs and FLSs to simulate AS pathology. The Huangqin Qingre Chubi capsules group involved adding Huangqin Qingre Chubi capsules-containing serum to the co-cultured cells（6.48 g·kg^-1）. To investigate the effect of HQC-containing serum on the viability of co-cultured cells， and the experiment was divided into the following groups based on the dilution concentration： blank group， 10% HQC group， 20% HQC group， and 30% HQC group.To study the influence of the optimal concentration of HQC-containing serum on cytokine and pathway indicators in each group， the experiment was divided into three groups： normal group， model group， and optimal concentration HQC-containing serum group.For the validation of the transfection efficiency of the CircRNA_0001543 interference plasmid， the experiment was divided into the following groups： blank group， si-NC group （with transfection reagent）， si-circ_0001543-1 group （with transfection reagent and interference plasmid No. 1 targeting circ_0001543）， si-circ_0001543-2 group （with transfection reagent and interference plasmid No. 2 targeting circ_0001543）， and si-circ_0001543-3 group （with transfection reagent and interference plasmid No. 3 targeting circ_0001543）.For the validation of the transfection efficiency of the CircRNA_0001543 overexpression plasmid， the experiment was divided into the following groups： blank group， OE-NC group （with transfection reagent）， and OE-circ_0001543 group （with transfection reagent and overexpression plasmid targeting circ_0001543）.To study the effects of CircRNA_0001543 interference/overexpression on cytokine and pathway indicators in each group， the experiment was divided into the following groups： si-NC group， si-CircRNA_0001543 group， OE-NC group， and OE-CircRNA_0001543 group. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of interleukin-1β （IL-1β）， IL-10， IL-37， and tumor necrosis factor-α （TNF-α）. Real-time quantitative polymerase chain reaction （Real-time PCR） was utilized to measure the expression of CircRNA_0001543， IκBα， and NF-κB p65. ResultsAfter 48 hours， 30% Huangqin Qingre Chubi Capsules-containing serum significantly inhibited the proliferation of co-cultured PBMCs and FLSs， which was determined to be the optimal experimental drug-containing serum concentration. Compared with those in the normal group， the expressions of NF-κB p65 mRNA， IκBα mRNA， IL-1β， and TNF-α in the model group were significantly increased （P<0.01）， while the expressions of CircRNA_0001543 mRNA， IL-10， and IL-37 were significantly decreased （P<0.01）. Compared with those in the model group， the expressions of NF-κB p65 mRNA， IκBα mRNA， IL-1β， and TNF-α in the Huangqin Qingre Chubi Capsules-containing serum group were significantly decreased （P<0.05）， and the expressions of CircRNA_0001543 mRNA， IL-10， and IL-37 were significantly increased （P<0.05）， with the most prominent changes in the 30% drug-containing serum group （P<0.01）. Compared with that in the si-NC group， the expression of CircRNA_0001543 was significantly reduced in the si-CircRNA_0001543 group （P<0.01）. Compared with that in the OE-NC group， the expression of CircRNA_0001543 was significantly increased in the OE-CircRNA_0001543 group （P<0.01）， indicating that the si-CircRNA_0001543 and OE-CircRNA_0001543 plasmids were successfully transfected. Based on the optimal drug-containing serum of Huangqin Qingre Chubi Capsules， si-CircRNA_0001543 transfection led to significantly increased expressions of NF-κB p65 mRNA， IκBα mRNA， IL-1β， and TNF-α and decreased the expressions of IL-10 and IL-37 （P<0.01）. In contrast， OE-CircRNA_0001543 transfection significantly decreased the expressions of NF-κB p65 mRNA， IκBα mRNA， IL-1β， and TNF-α （P<0.01） and increased the expressions of IL-10 and IL-37 （P<0.01）. ConclusionHuangqin Qingre Chubi capsules-containing serum can improve immune inflammation in AS by increasing the expression of CircRNA_0001543， regulating the NF-κB pathway， suppressing pro-inflammatory cytokines， and enhancing anti-inflammatory cytokine expression.

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Objective To compare the impact of NaClO and EDTA pretreatment on the enamel surfaces pore exposure rate,resin in-filtration effectiveness and shear bond strength between the enamel white spot lesions(WSLs)and resin composite.Methods A total of 104 sound premolars were selected for the study.4 mm×4 mm×2 mm enamel blocks from 64 sound premolars were cut in the center of the buccal surfaces of the teeth.All blocks were randomly divided into five groups:group SE(sound enamels as negative control);group DE(enamel blocks demineralised as positive control);group RI(resin infiltration);group N/RI(5.25％NaClO pretreatment and resin infiltration)and group E/RI(17％EDTA pretreatment and resin infiltration).The pore exposure rate of enamel surfaces and resin penetration depths were observed by scanning electron microscopy(SEM)and confocallaser scanning microscopy(CLSM)in each group.The remaining 40 premolars were cut from the cervical roots and the residual crowns were embedded in self-condensing resin ma-terial(buccal surfaces of the enamel exposed only).According to the grouping information,the samples were given the corresponding pretreatments and resin infiltration respectively and were bonded with a cylindrical resin cylinder on the buccal enamel surface for shear bond test.The shear bond strength and fracture modes were recorded and analyzed in each group.Results Compared to group RI,the pore exposure rate of the enamel surface,resin penetration depths,and percentage of resin penetration area in the N/RI and E/RI groups were significantly increased(P＜0.05).The shear bond strength of the samples in group SE was the highest,and the lowest in group DE.Compared to group DE,the shear bond strength in groups RI,N/RI,and E/RI was significantly increased(P＜0.05).Con-clusion Enamel surface pretreatment with 5.25％NaClO or 17％EDTA has been demonstrated to effectively enhance the enamel pore exposure rate,resin penetration depth and the shear bond strength between WSLs and resin composite.

This study analyzed the epidemiological characteristics of imported malaria in Yunnan Province from 2020 to 2023,to provide scientific evidence for formulating measures to decrease imported malaria and prevent re-establishment of malaria transmission.Malaria data reported by the China Disease Prevention and Control Information System were analyzed to determine parasite species;sources of infection;temporal,spatial,and population distributions;and importation routes.A total of 828 malaria cases were reported in the province.Plasmodium vivax and Plasmodium falciparum accounted for 89.98％and 8.33％of cases,respectively.A total of 47.58％of cases were imported from Myanmar,and all P.falciparum malaria ca-ses were from Africa.Thirteen(81.25％)prefectures or municipalities reported malaria,among which Dehong,Baoshan,Kunming,and Lincang reported 94.32％of cases.A total of 52.54％of cases were in young men.The proportion of cross-bor-der personnel flow,land input,and aircraft input were 88.89％and 11.11％respectively.A total of 98.19％of patients sought medical care within 7 days after fever onset,and 82.85％initiated diagnosis for malaria,and 84.90％of diagnoses were con-firmed by health facilities at or below the county level.Imported malaria is a major challenge in preventing re-establishment of transmission in Yunnan.Most imported cases involved cross-border malaria transmission of mainly Plasmodium vivax between China and Myanmar.To achieve malaria elimination,vigilance of health staff in malaria diagnosis and treatment should be pro-moted,and intensive malaria health education should be provided to people traveling to malaria endemic territories,to enable individual protection,and timely diagnosis and treatment after return from endemic countries.

Objective To compare clinical efficacy of different regimens in treatment of pruritus in maintenance hemodialysis(MHD)patients.Methods A total of 50 patients with MHD admitted to the Sixth People's Hospital of Jiujiang City from August 1,2022 to April 30,2024 as subjects and were divided into two groups according to random number table method.Control group(n=25)was treated with sodium thiosulfate.On this basis,gabapentin combination therapy was added in observation group(n=25).Effects of two groups were compared after 8 weeks of treatment.Results Total clinical effective rate of observation group was significantly higher than that of control group(P＜0.05).After 8 weeks of treatment,scores and total scores of all dimensions of quality of life in two groups were higher than before treatment,and observation group was higher than control group(P＜0.05).Conclusion Sodium thiosulfate combined with gabapentin in treatment of MHD patients with pruritus can not only relieve pruritus symptoms,improve sleep quality,but also have good safety.