This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

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

OBJECTIVE: To investigate the effect of innovative perioperative pain management on prostate cancer patients with hematuria undergoing prostatic artery embolization (PAE). METHODS: A total of 60 patients undergoing PAE in the Interventional Therapy Department of General Hospital of Eastern Theater Command from May 2024 to January 2025 were selected by convenience sampling method and randomly divided into the intervention group and the control group, with 30 patients in each group. The control group received traditional pain management of nursing. An innovative perioperative pain management was performed in intervention group including preoperative "body-mind-pain" holistic assessment and preparation, intraoperative humanistic care and real-time support, postoperative multimodal analgesia and rehabilitation, dynamic monitoring and closed-loop feedback. The pain degree after 6 hours, 1 day, 3 days and 1 week of the operation, and the quality of life after 1 week of operation, as well as nursing satisfaction at discharge were compared between the two groups. RESULTS: The VAS scores of the intervention group were significantly lower than those of the control group after 6 hours, 1 day, 3 days and 1 week of operation (P<0.05). One week after the operation, the quality of life in the observation group was higher than that of the control group significantly (P<0.05). The nursing satisfaction of the observation group was significantly higher than that of the control group at discharge(P<0.05). CONCLUSION The application of innovative perioperative pain management can alleviate pain of patients with PAE, which improves the quality of life and nursing satisfaction of patients, and is conducive to the rehabilitation of patients.
Humans ; Male ; Embolization, Therapeutic ; Hematuria/therapy* ; Prostatic Neoplasms/surgery* ; Pain Management/methods* ; Quality of Life ; Prostate/blood supply* ; Perioperative Care ; Pain, Postoperative ; Middle Aged ; Aged ; Pain Measurement

Mechanical pain is one of the most common causes of clinical pain, but there remains a lack of effective treatment for debilitating mechanical and chronic forms of neuropathic pain. Recently, neurotoxin GsMTx4, a selective mechanosensitive (MS) channel inhibitor, has been found to be effective, while the underlying mechanism remains elusive. Here, with multiple rodent pain models, we demonstrated that a GsMTx4-based 17-residue peptide, which we call P10581, was able to reduce mechanical hyperalgesia and neuropathic pain. The analgesic effects of P10581 can be as strong as morphine but is not toxic in animal models. The anti-hyperalgesic effect of the peptide was resistant to naloxone (an μ-opioid receptor antagonist) and showed no side effects of morphine, including tolerance, motor impairment, and conditioned place preference. Pharmacological inhibition of TRPV4 by P10581 in a heterogeneous expression system, combined with the use of Trpv4 knockout mice indicates that TRPV4 channels may act as the potential target for the analgesic effect of P10581. Our study identified a potential drug for curing mechanical pain and exposed its mechanism.

Early-life stress (ES) leads to cognitive dysfunction in female adolescents, but the underlying neural mechanisms remain elusive. Recent evidence suggests that the cell adhesion molecules NECTIN1 and NECTIN3 play a role in cognition and ES-related cognitive deficits in male rodents. In this study, we aimed to investigate whether and how nectins contribute to ES-induced cognitive dysfunction in female adolescents. Applying the well-established limited bedding and nesting material paradigm, we found that ES impairs recognition memory, suppresses prefrontal NECTIN1 and hippocampal NECTIN3 expression, and upregulates corticotropin-releasing hormone (Crh) and its receptor 1 (Crhr1) mRNA levels in the hippocampus of adolescent female mice. Genetic experiments revealed that the reduction of dorsal CA1 (dCA1) NECTIN3 mediates ES-induced object recognition memory deficits, as knocking down dCA1 NECTIN3 impaired animals' performance in the novel object recognition task, while overexpression of dCA1 NECTIN3 successfully reversed the ES-induced deficits. Notably, prefrontal NECTIN1 knockdown did not result in significant cognitive impairments. Furthermore, acute systemic administration of antalarmin, a CRHR1 antagonist, upregulated hippocampal NECTIN3 levels and rescued object and spatial memory deficits in stressed mice. Our findings underscore the critical role of dCA1 NECTIN3 in mediating ES-induced object recognition memory deficits in adolescent female mice, highlighting it as a potential therapeutic target for stress-related psychiatric disorders in women.
Animals ; Female ; Mice ; CA1 Region, Hippocampal/metabolism* ; Cell Adhesion Molecules/metabolism* ; CRF Receptor, Type 1/metabolism* ; Memory Disorders/etiology* ; Mice, Inbred C57BL ; Nectins/genetics* ; Receptors, Corticotropin-Releasing Hormone/antagonists & inhibitors* ; Recognition, Psychology/physiology* ; Stress, Psychological/complications*

The current production of Chinese herbal decoction pieces faces several issues including strong subjectivity,unstable quality,low production efficiency,and a lack of intelligent systems.In order to expedite the intelligent transformation and upgrading of Chinese medicine processing,this paper delves deeply into the problems and challenges encountered in establishing a digital and intel-ligent production model for Chinese herbal pieces.Addressing the slow progress in fundamental research on traditional Chinese medi-cine processing mechanisms,the absence of online digital quality characterization techniques,the low level of production equipment in-telligence,and the lack of evaluation standards for high-quality decoction pieces,this paper proposes a"New Quality Productive Forces"formation approach driven by technological innovation.Through interdisciplinary integration methods,the paper explores the mechanisms of Chinese medicine processing in depth,clarifies the correlation between the processing procedures and the"medicinal properties-quality"relationship,and employs bionic sensing and artificial intelligence to achieve a holistic quality characterization of decoction pieces.Additionally,the use of cloud-edge collaborative big data systems is proposed to enhance intelligent upgrades of the production lines.The paper also aims to establish a high-quality decoction piece evaluation system integrating"physical-chemical-bio-logical"multimodal data fusion.This approach aims to steer the Chinese medicine processing towards becoming more efficient,precise,and sustainable,thereby promoting high-quality sustainable development of the Chinese herbal decoction industry and providing both theoretical and practical support for the modernization of traditional Chinese medicine.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.

Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5％in all clinical isolates amd 5.7％in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7％(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)％,followed by secretions/pus(16.4±2.3)％and urine(16.0±0.9)％.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9％),and only(7.1±0.8)％of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)％compared to the inpatients in any other departement.Overall,≤ 7.9％of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6％of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7％vs 3.9％).Overall,≤8.1％of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5％of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0％over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10％of the Proteus and Morganella strains were resistant,while less than 20％of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4％in Proteus isolates,1.9％in Morganella isolates,and 15.6％in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.