With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

To explore the mechanism of spleen- were obtained for the treatment of acute-on-chronic livstrengthening and moisture-nourishing liver prescription er failure, and 244 intersecting target genes and 7 core (JPLSYGF) in the treatment of acute-on-chronic liver target genes were screened. Molecular docking showed failure using network pharmacology and the molecular that the core target genes AKT1, SRC, VEGFA, docking. Methods Relying on TCMSP and Gene- STAT3 , EGFR, MAPK3 , HRAS had good affinity with Cards and other databases, the relevant targets of JPL- quercetin, the main active component in the JPLSYGF in the treatment of acute-on-chronic liver failure SYGF, and had strong binding activity. In addition, in were obtained. String and Cytoscape were used to con- vivo tests verified that the JPLSYGF could reduce the struct PPI networks of targets, core targets were expression of HRAS, EGFR, STAT3 , SRC, and VEGscreened out, and DAVID was used for GO function FA, to delay the progression of acute-on-chronic liver annotation and KEGG pathway enrichment analysis. failure. Conclusions JPLSYGF may act on core tar- The main active ingredients of the traditional Chinese gets such as HRAS, EGFR, STAT3, SRC, VEGFA medicine compound formula for JPLSYGF were select- and so on, to achieve the effect of treating acute-oned with a bioavailability OB value of =Э 30% and a chronic liver failure. drug-like DL^O. 18 as the screening conditions, and.

Objective To investigate the diagnostic efficiency of artificial intelligence(AI)in rib frac-ture under the computed tomography(CT)images with different reconstruction slice thickness.Methods The first CT images of 100 patients with rib fractures were selected,and the interval-free recon-struction was carried out with the thickness of 0.625 mm,1.250 mm,2.500 mm and 5.000 mm,respectively.The rib fracture screening function of AI was used to automatically detect the CT images of four groups,and the diagnostic efficiency of AI for rib fracture under different reconstruction thickness conditions was com-pared.Results The sensitivity of AI in the diagnosis of rib fracture at 0.625 mm,1.250 mm,2.500 mm and 5.000 mm thickness was 99.32%(436/439),98.41%(432/439),89.52%(393/439)and 83.60%(367/439),respectively.The false positive rate was 4.80%(22/458),0.92%(4/436),0.76%(3/396)and 0.27%(1/368).The diagnostic sensitivity of AI in 0.625 mm and 1.250 mm thickness was higher than that in 2.500 mm and 5.000 mm,and the difference was statistically significant(P<0.05),while there was no significant difference in the thickness of 0.625 mm and 1.250 mm.The false positive rate of AI in the diagnosis of 0.625 mm slice thickness was higher than that of 1.250 mm,2.500 mm and 5.000 mm,and the difference was sta-tistically significant(P<0.05),while there was no significant difference in the thickness of 1.250 mm,2.500 mm and 5.000 mm(P>0.05).Conclusion The diagnostic efficiency of AI in 1.250 mm CT images is better than that in 0.625 mm,2.500 mm and 5.000 mm CT images.

In this article,the mechanism of Shanxian Granule in inhibiting liver cancer,lung cancer,sarcoma,melanoma and other tumors was reviewed,with a view to providing a theoretical basis for the clinical research of Shanxian Granules in the treatment of malignant tumors.Shanxian Granule are the pure Chinese medicine preparation for counteracting malignant tumor developed by the Oncology Research Team of Shaanxi University of Chinese Medicine on the basis of the theory of traditional Chinese medicine syndrome differentiation and treatment combined with decades of clinical experience as well as the achievements of modern pharmacological research.Shanxian Granule are mainly composed of Crataegi Fructus,Agrimoniae Herba,Panacis Quinquefolii Radix,Curcumae Rhizoma,Testudinis Carapax et Plastrum,Trionycis Carapax,Corydalis Rhizoma,and Polyporus,and have the actions of benefiting qi and nourishing yin,supporting healthy-qi and cultivating the essence,activating blood and removing stasis,and eliminating swelling and counteracting cancer.The compatibility of Shanxian Granule embodies the principle of supporting healthy-qi but avoiding maintaining pathogens,and eliminating pathogens but avoiding injuring healthy-qi.The granules can effectively inhibit the growth and metastasis of liver cancer,lung cancer,sarcoma,melanoma and other tumors both in vivo and in vitro,alleviate the clinical symptoms of tumor patients,and improve their prognosis.The anti-tumor mechanism of Shanxian Granules is related to the enhancement of body immune function,inhibition of tumor cell proliferation,enhancement of tumor cell apoptosis,inhibition of tumor cell invasion and metastasis as well as the tumor angiogenesis.

Objective To understand the spectrum and changes of pathogens causing healthcare-associated infec-tion(HAI)in neonatal intensive care unit(NICU).Methods Clinical medical records of neonates with HAI in a hospital from January 2018 to December 2022 were collected,spectrum of pathogens causing HAI were and analyzed retrospectively.Results A total of 7 597 hospitalized neonates were investigated,and 240 of whom had 263 cases of HAI,with an HAI incidence of 3.16％and healthcare-associated case infection incidence of 3.46％.96 cases(36.50％)were bloodstream infection,70(26.62％)were respiratory system infection,and 57(21.67％)were in-fection without clear sites.A total of 170 pathogens were detected from specimens,78(45.88％)of which were Gram-positive bacteria,with Staphylococcus spp.accounting for the highest proportion,78(45.88％)were Gram-negative bacteria,mainly Klebsiella pneumoniae,and 14(8.24％)were fungi.The detection rate of Gram-negative bacteria showed an upward trend from 2018 to 2022(P＜0.01).Conclusion The majority of HAI in NICU is bloodstream infection.In recent years,the detection rate of Gram-negative bacteria has been increasing year by year,and it is necessary to streng-then the prevention and control of HAI in clinical practice.

Objective To understand the consumption of hand hygiene(HH)products and HH compliance in in-tensive care units(ICUs)of secondary and higher grade medical institutions(MIs)in Shanghai,and provide basis for further monitoring of HH among health care workers(HCWs).Methods Through healthcare-associated infec-tion surveillance system,the consumption of HH products and HH compliance in ICUs from secondary and higher grade MIs in Shanghai in 2017-2021 were analyzed.Results 105 ICUs from 74 MIs were included in analysis,the average consumption of HH products was 79.24(44.88-258.63)mL/(bed·day),with statistically significant difference among different types of ICUs(P＜0.001).The average consumption of HH products increased from 65.75 mL/(bed·day)in 2017 to 87.55 mL/(bed·day)in 2021,showing an increasing trend year by year(P＜0.001).HCWs'HH compliance rate was 82.13％,with the highest in nurses(86.59％)and the lowest(48.90％)in medical technicians,HH compliance rates of HCWs of different occupations were statistically significant different(P＜0.001).Among the implementation modes of HH,39.86％used running water for hand washing,42.27％used alcohol-based hand rub to wipe hands,13.22％didn't take HH measures,and 4.65％didn't take HH mea-sures when wearing gloves,with statistically significant differences among different HH implementation modes of HCWs(P＜0.001).There was a positive correlation between the average consumption of HH products per bed·day and HCWs'HH compliance rate(r=0.703,P＜0.05).Conclusion The average consumption of HH products per bed·day and HH compliance rate of HCWs in ICUs in Shanghai presents an increasing trend year by year.There are differences in the average consumption of HH products per bed·day and HH compliance rate among different types of ICUs.The implementation of HH can be evaluated by continuously surveillance on the average consumption of HH products per bed·day.

Objective To analyze the basic case data and laboratory test index characteristics of patients with myasthenia gravis(MG),so as to evaluate the application value of common clinical laboratory indicators in the construction of a diagnostic model for MG.Methods A retrospective analysis was performed on the basic data and laboratory indicators of MG patients and gender and age-matched healthy controls diagnosed at Beijing Tiantan Hospital,Capital Medical University from April 2021 to April 2023.A diagnostic model was constructed,and the receiver operating characteristic(ROC)curve was drawn to analyze the area under the curve(AUC).Results The BMI,heart rate,systolic blood pressure,and diastolic blood pressure in the MG group were significantly higher than those in the control group,with statistical significance(P＜0.05).There were significant differences in total protein,albumin,white blood cell count,proportion of large platelets,abso-lute value of monocyte and triiodothyronine between MG group and control group(P＜0.05).Seven indexes of heart rate,diastolic blood pressure,albumin,creatine kinase,cholinesterase,triglyceride and apolipoprotein B were selected to construct the diagnostic model.The area under the curve of the combined application of multiple indexes could reach 0.995,with a sensitivity and specificity of 97.60％and 96.10％,respectively.Conclusion In this study,the laboratory test indexes that can be used for the diagnosis of MG are successfully selected,and the sensitivity and specificity of the combined application of multiple indexes are high,which can be used for the auxiliary diagnosis of MG.

Tranexamic acid is widely used in joint orthopedic surgery.At the same time,it has high safety and few adverse drug reactions.It can effectively improve intraoperative bleeding and promote early functional recovery of patients.This article reviews the mode of administration,safe dose,administration time and adverse drug reactions of tranexamic acid in the perioperative period of joint replacement and arthroscopic surgery,in order to provide reference for the clinical application of tranexamic acid.

Objective To develop a deep learning model for automated age estimation based on 3D CT reconstructed images of Han population in western China,and evaluate its feasibility and reliability.Methods The retrospective pelvic CT imaging data of 1 200 samples(600 males and 600 females)aged 20.0 to 80.0 years in western China were collected and reconstructed into 3D virtual bone models.The images of the ischial tuberosity feature region were extracted to create sex-specific and left/right site-specific sample libraries.Using the ResNet34 model,500 samples of different sexes were randomly selected as training and verification set,the remaining samples were used as testing set.Initialization and transfer learning were used to train images that distinguish sex and left/right site.Mean absolute error(MAE)and root mean square error(RMSE)were used as primary indicators to evaluate the model.Results Prediction results varied between sexes,with bilateral models outperformed left/right unilateral ones,and transfer learning models showed superior performance over initial models.In the prediction results of bilateral transfer learning models,the male MAE was 7.74 years and RMSE was 9.73 years,the female MAE was 6.27 years and RMSE was 7.82 years,and the mixed sexes MAE was 6.64 years and RMSE was 8.43 years.Conclusion The skeletal age estimation model,utilizing is-chial tuberosity images of Han population in western China and employing the ResNet34 combined with transfer learning,can effectively estimate adult ischium age.

Objective To describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification re-search.Methods The data retrieved and extracted from the Web of Science Core Collection (WoSCC),the core database of the Web of Science information service platform (hereinafter referred to as "WoS"),was used to analyze the trends and topic changes in research on forensic identification of human re-mains from 1991 to 2022.Network visualisation of publication trends,countries (regions),institutions,authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10.Results A total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained.The journal with the largest number of publications was Forensic Science International (164 articles).The country (region) with the largest number of published papers was China (90 articles).Katholieke Univ Leuven (Netherlands,21 articles) was the institution with the largest number of publications.Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation,and the most commonly studied remains were teeth.Conclusion The volume of publications in the field of forensic anthropological remains identification research has a distinct phasing.However,the scope of both international and domestic collaborations remains limited.Traditionally,human remains identifica-tion has primarily relied on key areas such as the pelvis,skull,and teeth.Looking ahead,future re-search will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques.