Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

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.

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 study the pharmacokinetic characteristics of the test formulation of compound lidocaine cream and reference formulation of lidocaine and prilocaine cream in Chinese healthy subjects and to evaluate whether there is bioequivalence between the two formulations.Methods A single-center,single-dose,randomized,open-label,two-period,two-sequence,crossover design was used.This study included 40 healthy subjects,and in each period,test formulation or reference formulation 60 g was applied to the skin in front of both thighs(200 cm2 each side,a total of 400 cm2)under fasting conditions,and the drug was left on for at least 5 h after application.The concentrations of lidocaine and prilocaine in plasma were determined using liquid chromatography-tandem mass spectrometry(LC-MS/MS)method.Pharmacokinetic parameters were calculated using WinNonlin 8.0 software to evaluate the bioequivalence of the two formulations.Results After the application of the test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream on both thighs of the subjects,the pharmacokinetic parameters of lidocaine in plasma were as follows:Cmax were(167.27±91.33)and(156.13±66.86)ng·mL-1,AUC0-t were(1 651.78±685.09)and(1 636.69±617.23)ng·mL-1·h,AUC0-∞ were(1 669.85±684.65)and(1 654.37±618.30)ng·mL-1·h,the adjusted geometric mean ratios were 104.49％,101.88％and 101.89％,respectively,with 90％confidence intervals of 98.18％-111.20％,97.80％-106.13％and 97.87％-106.07％,all within the range of 80.00％-125.00％.The pharmacokinetic parameters of prilocaine in plasma were as follows:Cmax were(95.66±48.84)and(87.52±39.16)ng·mL-1,AUC0-t were(790.86±263.99)and(774.14±256.42)ng·mL-1·h,AUC0_m were(807.27±264.67)and(792.84±254.06)ng·mL-1 h,the adjusted geometric mean ratios were 107.34％,103.55％and 102.98％,respectively with 90％confidence intervals of 101.69％-113.31％,99.94％-107.30％and 99.65％-106.43％,all within the range of 80.00％-125.00％.Conclusion The test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream are bioequivalent.

Objective To construct machine learning models that can be used to predict AUC fold change(FC)using a database of existing pharmacokinetic(PK)and drug-drug interaction(DDI)information,which can be used to explore the possibility of predicting existing drug interactions and to provide certain rational recommendations for clinical drug use.Methods PK data of DDIs and AUC fold change data were extracted from FDA-approved drug labels.Peptide and pharmacodynamic(PD)information related to drug interactions were retrieved through DrugBank,and PPDT identification of relevant peptide IDs was performed using Protein Resource(UniProt),and a matrix normalization code was used to generate multidimensional vector data that were easy to analysis.The effect of PPDT on the AUC,and the resulting multiplicity change was used as the dependent variable for machine learning model construction.The model with the smallest root mean square error(RMES)value was used for model construction to train a bagged decision tree(Bagged)prediction model.The models were tested using the trained models for some of the drug tests.The models were evaluated by reviewing the available literature findings on detection of drug interaction pairs and analyzing and comparing the predicted values.Results A total of 16 pairs of model drug pairs were tested for the effects of 16 drugs on tacrolimus,and it was found that the accuracy of the prediction of the presence or absence of drug interactions was 81.25％;the prediction results were classified according to the FDA standard classification of the strong and weak for the strength of drug interactions,and the results showed that the prediction of the strength of drug interactions,with a large deviation from the larger prediction was less.Conclusion The evaluation of the model to predict the presence or absence of drug interactions was general;however,after classifying the strengths and weaknesses of drug interactions,the prediction of drug interactions was better,and the prediction results indicated that the model prediction performance has a certain reference value for potential DDI assessment before clinical trials.

【Objective】 To investigate the association between genetic variations in the glucagon-like peptide-1 receptor (GLP-1R) gene and BP responses to sodium and potassium intake. 【Methods】 A total of 514 subjects from 124 families were recruited in Meixian County, Shaanxi Province, in 2004, resulting in the establishment of a "salt-sensitive hypertension study cohort" . The subjects followed a dietary regimen which involved a normal diet for 3 days, a low-salt diet for 7 days, a high-salt diet for 7 days, and a high-salt potassium-supplemented diet for 7 days. BP measurement was conducted at different intervention periods, and peripheral blood samples were collected. Additionally, eight single nucleotide polymorphisms (SNPs) of the GLP-1R gene were genotyped using the MassARRAY detection platform. 【Results】 The GLP-1R gene SNP rs9462472 exhibited a significant association with systolic BP, diastolic BP, and mean arterial pressure response to high-salt intervention. Similarly, SNP rs2268637 showed a significant association with systolic BP response to high-salt intervention. Furthermore, SNP rs2268637 was significantly associated with systolic BP and mean arterial pressure responses to high-salt plus potassium supplementation intervention. 【Conclusion】 Our findings indicate a significant association of genetic variations in the GLP-1R gene with BP responses to sodium and potassium intake. This suggests that the GLP-1R gene plays a role in the regulation of BP salt sensitivity and potassium sensitivity.

Objective To investigate the attributable risk(AR)of Acinetobacter baumannii(AB)infection in criti-cally ill patients.Methods A multicenter retrospective cohort study was conducted among adult patients in inten-sive care unit(ICU).Patients with AB isolated from sterile body fluid and confirmed with AB infection in each cen-ter were selected as the infected group.According to the matching criteria that patients should be from the same pe-riod,in the same ICU,as well as with similar APACHE Ⅱ score(±5 points)and primary diagnosis,patients who did not infect with AB were selected as the non-infected group in a 1:2 ratio.The AR was calculated.Results The in-hospital mortality of patients with AB infection in sterile body fluid was 33.3％,and that of non-infected group was 23.1％,with no statistically significant difference between the two groups(P=0.069).The AR was 10.2％(95％CI:-2.3％-22.8％).There is no statistically significant difference in mortality between non-infected pa-tients and infected patients from whose blood,cerebrospinal fluid and other specimen sources AB were isolated(P＞0.05).After infected with AB,critically ill patients with the major diagnosis of pulmonary infection had the high-est AR.There was no statistically significant difference in mortality between patients in the infected and non-infec-ted groups(P＞0.05),or between other diagnostic classifications.Conclusion The prognosis of AB infection in critically ill patients is highly overestimated,but active healthcare-associated infection control for AB in the ICU should still be carried out.

Objective Studies on the relationship between iodine,vitamin A(VA),and vitamin D(VD)and thyroid function are limited.This study aimed to analyze iodine and thyroid-stimulating hormone(TSH)status and their possible relationships with VA,VD,and other factors in postpartum women. Methods A total of 1,311 mothers(896 lactating and 415 non-lactating)from Hebei,Zhejiang,and Guangxi provinces were included in this study.The urinary iodine concentration(UIC),TSH,VA,and VD were measured. Results The median UIC of total and lactating participants were 142.00 μg/L and 139.95 μg/L,respectively.The median TSH,VA,and VD levels in all the participants were 1.89 mIU/L,0.44 μg/mL,and 24.04 ng/mL,respectively.No differences in the UIC were found between lactating and non-lactating mothers.UIC and TSH levels were significantly different among the three provinces.The rural UIC was higher than the urban UIC.Obese mothers had a higher UIC and a higher prevalence of excessive TSH.Higher UICs and TSHs levels were observed in both the VD deficiency and insufficiency groups than in the VD-sufficient group.After adjustment,no linear correlation was observed between UIC and VA/VD.No interaction was found between vitamins A/D and UIC on TSH levels. Conclusion The mothers in the present study had no iodine deficiency.Region,area type,BMI,and VD may be related to the iodine status or TSH levels.

Objective:To investigate the effects of compound Duzhong Jiangu Granules on joint function and gut microbiota in patients with Kashin-Beck disease.Methods:A single group pre- and post-experimental design was conducted, the patients with Kashin-Beck disease were selected as the subjects in Xunyi County, Xianyang City, Shaanxi Province; and treated with oral administration of compound Duzhong Jiangu Granules (12 g/bag, 1 bag/time, 3 times/day) for a period of 1 month. The improvement of joint function was evaluated using the joint dysfunction index scoring method before and after treatment. Morning stool samples of patients were collected and the changes in gut microbiota were analyzed before and after treatment using 16S rDNA sequencing technology.Results:A total of 87 patients with Kashin-Beck disease were included, including 44 males and 43 females; the age was (60.38 ± 7.12) years old, and the body mass index was (23.67 ± 3.59) kg/m 2. The comprehensive scores of joint dysfunction index for patients with Kashin-Beck disease before and after treatment were (7.27 ± 2.05) and (5.86 ± 2.01) points, respectively, and the difference was statistically significant ( t = 5.88, P < 0.001). The sequencing results of gut microbiota showed that there were statistically significant differences in the alpha diversity (chao1, observed species index) and beta diversity of gut microbiota in patients with Kashin-Beck disease before and after treatment ( Z = - 5.08, - 5.03, R = 0.09, P < 0.001). In the distribution of gut microbiota, Firmicutes was the dominant phylum, with relative abundances of 50.21% and 52.09% before and after treatment, respectively; the Bifidobacterium was the dominant bacterial genus, with relative abundances of 16.83% and 18.81% before and after treatment, respectively. At the genus level, a total of 17 gut microbiota genera were screened out, among which the relative abundances of Hafnia-Obesumbacterium, Gammaproteobacteria_unclassified, Acinetobacter, Pantoea, Leuconostoc, and Akkermanisia were significantly higher than before treatment ( Z = - 2.40, - 2.24, - 2.06, - 3.59, - 2.24, - 2.11, P < 0.05). The relative abundances of Dubosiella, Selenomonas, Anaeroplasma, Lachnospiraceae_ NK4A136_group, Rikenella, Prevotella, Megasphaera, Lactobacillus, Prevotella-9, Phascolarctobacterium, and Desulfovibrio were significantly lower than before treatment ( Z = - 9.38, - 2.61, - 2.18, - 8.43, - 2.45, - 2.46, - 2.49, - 7.29, - 2.29, - 2.55, - 2.08, P < 0.05). Conclusions:Compound Duzhong Jiangu Granules can effectively improve the joint function of patients with Kashin-Beck disease, and alter the diversity and richness of the gut microbiota community. It may reduce clinical symptoms in patients by regulating the structure of gut microbiota.

Highly sensitive multiple detection and accurate identification of gases are of great importance in the fields of public safety,environmental protection,health diagnosis and industrial production.However,the traditional means of gas detection have many shortcomings such as low sensitivity,long time-consuming,bulky equipment,cumbersome processes and expensive costs.In recent years,Raman spectroscopy has become a hotspot in the field of gas detection because of its fast,sensitive and non-destructive characteristics,and has been more and more closely combined with artificial intelligence.This paper reviews the progress of Raman spectroscopy in gas detection in recent years,including conventional Raman spectroscopy and enhanced Raman spectroscopy,and also introduces the integration of artificial intelligence algorithms in gas Raman detection technology,and discusses the future development of gas Raman detection.