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.

Objective To observe the value of machine learning(ML)model based on chest non-contrast CT(NCCT)radiomics for diagnosing metabolic syndrome(MetS)in males.Methods A total of 792 males who would undergo chest NCCT and bone density CT examination for physical check-up were prospectively enrolled and divided into training set(n=554,including 171 cases of MetS)and validation set(n=238,including 70 cases of MetS)at the ratio of 7∶3.Chest NCCT was performed,ROI of liver,intra-abdominal fat and skeletal muscle were delineated,and visceral fat area(VFA)at L2-3 intervertebral disc level was measured.Then radiomic signature(RS)of liver,intra-abdominal fat and skeletal muscle were established,and ML models were constructed using logistic regression(LR),random forests(RF)and extreme gradient boosting(XGBoost)algorithms,respectively,and their diagnostic performance were observed.Results Significant difference of age was found between MetS and non-MetS males in training set(P=0.010),while of RS scores were noticed in both training set and validation set(all P＜0.001).Combined ML models were constructed with age and RS.The area under the curve(AUC)of combined LR,RF and XGBoost models for diagnosing male MetS in training set was 0.899,0.996 and 0.943,while that in validation set was 0.861,0.860 and 0.876,respectively.Combined XGBoost model had the best performance.Conclusion XGBoost model based on chest NCCT radiomics was helpful for diagnosing male MetS.Combining with age could further improve its efficacy.

Aim To evaluate the role of the glucose transporter protein 1(GLUT1)-dependent glycolytic in the attenuation of oxygen-glucose deprivation-reoxygen-ation(OGD/R)injury in HK-2 cells by dexmedetomi-dine(Dex).Methods C57/BL6 mice were random-ly divided into three groups(n=6),namely,sham operation group(Sham group),renal ischemia reper-fusion group(I/R group)and Dex group(I/R+Dex group).Serum creatinine(Cr)and urea nitrogen(BUN)were measured,while the levels of key glyco-lytic enzymes HK2,PFKFB3 and GLUT1 were meas-ured.HK-2 cells were cultured and randomised into seven groups(n=6),which was treated with OGD/R,overexpression or interference with GLUT1,Dex and glycolysis inhibitor 2-DG.CCK-8 and LDH activi-ty were used to detect cellular damage.Glycolysis lev-els were detected by lactate and ECAR.The inflamma-tory level was reflected by qRT-PCR for IL-6 and TNF-α.qRT-PCR and Western blot were performed to de-tect the levels of GLUT1,HK2,and PFKFB3.Results Dex significantly ameliorated kidney injury and HK-2 cell injury(P＜0.05).Dex inhibited the OGD/R-induced rise in lactate and extracellular acidification rate(ECAR),as evidenced by suppression of the ex-pression of GLUT1,HK2 and PFKFB3(P＜0.05).In vitro experiments showed that GLUT1 knockdown sig-nificantly improved OGD/R-induced cellular damage.Lactate,ECAR,glycolysis-related mRNAs and pro-teins were inhibited by GLUT1 knockdown(P＜0.05).Significantly,there were no significant differ-ences in above indexes after Dex treatment based on GLUT1 knockdown.Overexpression of GLUT1 abroga-ted the protective effects of Dex,while reversing the inhibitory effects of Dex on the expression of GLUT1,HK2,and PFKFB3(P＜0.05).Conclusions Dexmedetomidine attenuates OGD/R induced injury in HK-2 cells by inhibiting GLUT1-dependent glycolysis.

Objective:Near-infrared(NIR)spectroscopy technology faces the problem of insufficient model generalization due to individual differences in non-invasive blood glucose testing,in order to solve this problem,to improve data utilization,and to build predictive models with stronger generalization ability,this study introduces a transfer learning method to study the NIR spectroscopy non-invasive glucose testing.Methods:Migration learning is a machine learning technique that aims to improve task performance in the target domain by transferring knowledge from the source domain to the target domain.In this study,we used community population data as the source domain and student population data as the target domain to improve the performance of the noninvasive glucose detection model on the target domain.In order to verify the effectiveness of migration learning,this study compares the performance of the model before and after migration learning.Results:the model's performance on the noninvasive glucose detection task is significantly improved by the migration learning strategy,and the MAPE and MAE of the migrated model decreases by 52.5460％and 6.0805％,respectively,and the RMSE and MSE decreases by 10.7215％and 12.1135％.Conclusions:This study demonstrates the promising application of transfer learning in the field of non-invasive blood glucose detection,which is expected to realize portable and continuous blood glucose monitoring in the future by migrating the features that are difficult to access in the source domain but are related to blood glucose values to the target domain,which will greatly improve the quality of life of diabetic patients.Advances in noninvasive glucose testing technology will not only reduce patients' pain,but also provide a more convenient means of glucose monitoring,which will provide strong support for diabetes management.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

Lung cancer poses a serious threat to global public health security.Chemotherapy,as the main strategy for cancer treatment,faces challenges such as high toxicity and drug resistance.Anticancer peptides have the potential of being developed into new anticancer drugs due to their advantages of broad-spectrum anticancer activity,rapid action,and difficulty in generating drug resistance,but they also face shortcomings such as weak activity and strong toxic side effects.The weakly acidic microenvironment of tumors(pH 6.5-6.8)provides a good idea for the design of anticancer peptides of high-efficiency and low-toxicity.Previously,we designed the acid-sensitive antibacterial peptide pHly-1 using the wolf spider(Lycosa singoriensis)toxin Lycosin-Ⅰ as a template.In this study,we found that pHly-1 also had acid-sensitive anticancer activity.Further alanine scanning analysis of pHly-1 was carried out,and we ob-tained a mutant pHTP-2 with better acid sensitivity,whose IC50(half maximal inhibitory concentration)against A549 cells was 15.68 μmol/L at pH 6.6 and was greater than 100 μmol/L at pH 7.4.At pH 6.6,pHTP-2 could act on various lung cancer cell lines and induce the death of A549 cells by rapid ly-sis;at pH 7.4,500 μmol/L pHTP-2 had weak toxicity to red blood cells(the hemolysis rate was ap-proximately 38％)and primary myocardial cells(the inhibition rate was 49.7％,with P＜0.05).Analy-sis of its charge,particle size,morphology,and secondary structure showed that at pH 6.6,the histidine in the sequence of pHTP-2 was protonated,increasing the positive charge(P＜0.01),decreasing the hy-drated particle size(P＜0.05)and forming an α-helical structure to induce membrane lysis of A549 cells.At pH 7.4,it was deprotonated,the positive charge decreases,a β-sheet structure was formed and self-aggregation occurred,limiting its effect on the A549 cell membrane and showing weak activity.In summary,pHTP-2 could respond to the weakly acidic microenvironment of tumors to exert selective cyto-toxic activity,effectively overcoming the shortcomings of anticancer peptides such as low efficiency and high toxicity.Our findings suggest that it is a high-quality lead molecule for anticancer drugs.

Objective:To evaluate the levels and source of cadmium exposure by dietary pathway among middle-aged and elderly people ≥40 in cadmium-contaminated areas of China.Methods:A total of 7 193 people aged 40-89 years from four typical cadmium-contaminated areas in China were selected as the study subjects. Food Frequency Questionnaire (FFQ), Total Diet Study (TDS) and a 3-day-24-hour dietary recall survey were conducted. Dietary cadmium intake and food sources through dietary pathways were assessed based on cadmium content in foods, consumption amounts and intake frequencies.Results:The mean age of the participants was 63.39±12.21 years, with 50.05% being males. The average monthly dietary cadmium intake was 7.39 μg/(kg·BW). Staple foods and vegetables were the primary sources of dietary cadmium intake, accounting for 57.51% and 32.48%, respectively. The monthly dietary cadmium intake in all surveyed regions did not exceed the Provisional Tolerable Monthly Intake (PTMI) recommended by the Joint FAO/WHO Expert Committee on Food Additives (JECFA).Conclusion:The monthly dietary cadmium intake among middle-aged and elderly people in cadmium-contaminated areas of China is relatively low, with the risk remaining at an acceptable level. Staple foods and vegetables are the most significant contributors to dietary cadmium intake.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To investigate the impact of G pro-tein-coupled estrogen receptor 1(GPER1),also known as GPR30 playing a significant role in the nerv-ous system,on neuronal damage and cognitive dysfunc-tion following epileptic seizures.Methods The pro-tein expression levels of GPER1 and the DNA damage marker γ-H2AX in epileptic rats were assessed using Western blot.The hippocampal neuronal damage and apoptosis in pilocarpine-induced epilepsy models were evaluated using Nissl and TUNEL staining techniques,compared with GPER1 knockdown(GPER1-KD)rats with wild-type(WT)controls.The behavioral activi-ties,including memory and spatial learning,were mo-nitored during the chronic phase of epilepsy using the IntelliCage system.Results Compared to the control group,GPER1 protein expression in the cerebral cortex and hippocampus significantly increased 24 hours post-epilepsy onset.In the GPER1-KD+EP group,hipp-ocampal neuronal damage was more severe,with a sig-nificant increase in apoptotic neurons compared to the WT+EP group.The IntelliCage data revealed that during free exploration,nose contact,position learn-ing,and reverse position learning stages in the GPER1-KD+EP group exhibited fewer visits and a higher error rate than in the WT+EP group.Conclu-sions Deficiency in GPER1 impairs memory and spa-tial learning abilities following epilepsy,potentially due to exacerbated neuronal injury,apoptosis,and inflam-mation.GPER1 represents a promising therapeutic tar-get for mitigating post-epileptic nerve damage and cog-nitive impairment.