Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

This study investigates the mechanism by which Xintong Granules improve myocardial ischemia-reperfusion injury(MIRI) through the regulation of gut microbiota and their metabolites, specifically short-chain fatty acids(SCFAs). Rats were randomly divided based on body weight into the sham operation group, model group, low-dose Xintong Granules group(1.43 g·kg~(-1)·d~(-1)), medium-dose Xintong Granules group(2.86 g·kg~(-1)·d~(-1)), high-dose Xintong Granules group(5.72 g·kg~(-1)·d~(-1)), and metoprolol group(10 mg·kg~(-1)·d~(-1)). After 14 days of pre-administration, the MIRI rat model was established by ligating the left anterior descending coronary artery. The myocardial infarction area was assessed using the 2,3,5-triphenyltetrazolium chloride(TTC) staining method. Apoptosis in tissue cells was detected by the terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL) assay. Pathological changes in myocardial cells and colonic tissue were observed using hematoxylin-eosin(HE) staining. The levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6), creatine kinase MB isoenzyme(CK-MB), and cardiac troponin T(cTnT) in rat serum were quantitatively measured using enzyme-linked immunosorbent assay(ELISA) kits. The activities of lactate dehydrogenase(LDH), creatine kinase(CK), and superoxide dismutase(SOD) in myocardial tissue, as well as the level of malondialdehyde(MDA), were determined using colorimetric assays. Gut microbiota composition was analyzed by 16S rDNA sequencing, and fecal SCFAs were quantified using gas chromatography-mass spectrometry(GC-MS). The results show that Xintong Granules significantly reduced the myocardial infarction area, suppressed cardiomyocyte apoptosis, and decreased serum levels of pro-inflammatory cytokines(TNF-α, IL-1β, and IL-6), myocardial injury markers(CK-MB, cTnT, LDH, and CK), and oxidative stress marker MDA. Additionally, Xintong Granules significantly improved intestinal inflammation in MIRI rats, regulated gut microbiota composition and diversity, and increased the levels of SCFAs(acetate, propionate, isobutyrate, etc.). In summary, Xintong Granules effectively alleviate MIRI symptoms. This study preliminarily confirms that Xintong Granules exert their inhibitory effects on MIRI by regulating gut microbiota imbalance and increasing SCFA levels.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Myocardial Reperfusion Injury/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Apoptosis/drug effects* ; Humans ; Tumor Necrosis Factor-alpha/metabolism* ; Interleukin-6/genetics* ; Malondialdehyde/metabolism*

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVES: To investigate the clinical characteristics and drug resistance profile of invasive non-typhoidal Salmonella (NTS) enteritis in children in Chengdu, China, providing a reference for rational drug use and empirical treatment in clinical practice. METHODS: A retrospective analysis was conducted on the clinical data of 130 children with invasive bacterial enteritis due to NTS identified by fecal bacterial culture and the results of drug sensitivity tests for NTS in Chengdu from January 2022 to December 2023. RESULTS: NTS infections were mainly observed from April to September (113 cases, 86.9%), with a peak in August (36 cases, 27.7%). Children aged <36 months accounted for 86.2% (112/130) of all cases, and the main symptoms were diarrhea (130 cases, 100%), fever (123 cases, 94.6%), and hematochezia (112 cases, 86.2%). The 130 NTS isolates exhibited a sensitivity rate of 64.6% to ceftriaxone and 63.8% to cefotaxime, and a sensitivity rate of >90.0% to piperacillin-tazobactam and nitrofurantoin (nitrofurans). The detection rate of multidrug-resistant strains was 48.5% (63/130), and the clinical efficacy of third-generation cephalosporins used in 38 patients (29.2%) was inconsistent with the results of drug sensitivity tests. CONCLUSIONS The peak of invasive NTS enteritis in children aged 0-6 years occurs in August in the Chengdu area, with a relatively high incidence rate in children aged <36 months. The situation of drug resistance is severe for NTS, and piperacillin-tazobactam may be an effective option for treating multidrug-resistant NTS infections in children, while nitrofuran antibiotics might be used to treat such infections.
Humans ; Infant ; Child, Preschool ; Enteritis/microbiology* ; Retrospective Studies ; Male ; Salmonella Infections/microbiology* ; Female ; Child ; Salmonella/drug effects* ; Infant, Newborn ; Microbial Sensitivity Tests ; Anti-Bacterial Agents/therapeutic use*