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.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

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.

This paper summarizes Professor HAN Mingxiang's clinical experience in treating chronic obstructive pulmonary disease （COPD）. He believes that the key pathomechanism of COPD in the acute exacerbation stage is the invasion of external pathogens triggering latent illness， while lung qi deficiency is the primary mechanism in the stable stage. The core pathological factors throughout disease progression are deficiency， phlegm， and blood stasis. Treatment emphasizes a staged and syndrome-based approach. During the acute exacerbation stage， for wind-cold invading the lung syndrome， the self-formulated Sanzi Wenfei Decoction （三子温肺汤） is used to relieve the exterior， dispel cold， warm the lung， and resolve phlegm. For phlegm-dampness obstructing the lung syndrome， Huatan Jiangqi Fomulation （化痰降气方） is prescribed to warm the lung， transform phlegm， descend qi， and calm wheezing. For phlegm-heat obstructing the lung syndrome， Qingfei Huatan Fomulation （清肺化痰方） is applied to clear heat， resolve phlegm， moisten the lung， and stop coughing. For phlegm and blood stasis interlocking syndrome， Qibai Pingfei Fomulation （芪白平肺方） is used to tonify qi， resolve phlegm， and activate blood circulation to remove stasis. During the stable stage， for lung qi deficiency syndrome， Shenqi Wenfei Decoction （参芪温肺汤） is employed to warm the lung， tonify qi， resolve phlegm， and eliminate turbidity. For lung-spleen qi deficiency syndrome， Shenqi Buzhong Decoction （参芪补中汤） is utilized to strengthen the spleen， tonify qi， and reinforce metal （lung） from earth （spleen）. For lung-kidney deficiency syndrome， Shenqi Tiaoshen Fomulation （参芪调肾方） is prescribed to tonify the lung， warm yang， and regulate kidney function to calm wheezing. These strategies provide insights into the traditional Chinese medicine treatment of COPD.

This paper summarizes Professor HAN Mingxiang's clinical experience in the use of Zeqi （Euphorbia HelioscopiaL.）. It is believed that Zeqi （Euphorbia HelioscopiaL.） has the effects of promoting qi， relieving water retention and swelling， resolving phlegm， stopping cough， dissipating masses， activating blood， removing stasis， and detoxifying. In clinical practice， Zeqi （Euphorbia HelioscopiaL.） is flexibly applied in the treatment of skin diseases， respiratory diseases， tumors， etc. For instance， in treating psoriasis with the pathogenesis of damp-heat toxin， a compound prescription of Zeqi Decoction （泽漆汤） is formulated. For bronchial asthma with kidney deficiency and water retention， Zeqi Decoction is commonly combined with Wuling Powder （五苓散） in adjusted doses. For lung nodules with a combination of deficiency， phlegm， stasis， and toxin， a Lung Nodule Prescription is proposed. For advanced lung cancer with both qi and yin deficiency and toxin accumulation， Qiyu Sanlong Decoction （芪玉三龙汤） is suggested， and for cancer-related ascites with qi deficiency and water retention， Wuling Powder combined with Zeqi （Euphorbia HelioscopiaL.）is chosen.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

Objective To preliminarily design a wide-energy-spectrum CR-39 solid-state nuclear track individual neutron dosimeter with different energy sections. Methods The thickness of the converter was optimized using the Monte Carlo SRIM program to broaden the energy range of the dosimeter. The self-made wide-energy-spectrum CR-39 individual neutron dosimeter was calibrated using ²⁴¹Am-Be, ²⁵²Cf, and thermal neutron sources to evaluate its dosimetric performance, including linearity, energy response, and neutron energy resolution. Results The linear correlation coefficient of the measurement system exceeded 0.98. The relative deviations of the energy response were 35.0% for blank section and 42.0% for polyethylene section, falling within the range of −50% to + 100% and meeting the monitoring requirements. The detection sensitivity for thermal neutron dose was 67 137.2 tr·cm⁻²·mSv⁻¹, and the detection sensitivity for thermal neutron fluence was 0.98 × 10⁻³ tr·n⁻¹, demonstrating good thermal neutron detection capability. Conclusion The self-made wide-energy-spectrum CR-39 individual neutron dosimeter fundamentally meets the requirements for individual neutron dose monitoring and is suitable for individual neutron dose monitoring in the energy range of thermal neutrons (up to approximately 15 MeV).

Ischemic stroke (IS) is a globally life-threatening disease. Presently, few therapeutic medicines are available for treating IS, and rt-PA is the only drug approved by the US Food and Drug Administration (FDA) in the US. In fact, many agents showing excellent neuroprotection but no blood flow-improving activity in animals have not achieved ideal clinical efficacy, while thrombolytic drugs only improving blood flow without neuroprotection have limited their wider application. To address these challenges and meet the huge unmet clinical need, we have designed and identified a novel compound AAPB with dual effects of neuroprotection and cerebral blood flow improvement. AAPB significantly reduced cerebral infarction and neural function deficit in tMCAO rats, pMCAO rats, and IS rhesus monkeys, as well as displayed exceptional safety profiles and excellent pharmacokinetic properties in rats and dogs. AAPB has now entered phase I of clinical trials fighting IS in China.