In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.

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 analyze the significance of total vitamin D (tVD), total procollagen type I amino-terminal propeptide (tPINP) and β-CrossLaps (β-CTx) in the staging and prognosis of patients with multiple myeloma (MM). METHODS: A total of 54 patients with newly diagnosed MM admitted to the Second Affiliated Hospital of Fujian Medical University from 2020 to 2022 were selected as the observation group (MM group), and 50 healthy persons who underwent physical examinations in our hospital were selected as the control group. The expression levels of tVD, tPINP and β-CTx in the two groups were detected by chemiluminescence method. The differences in the expression levels of tVD, tPINP and β-CTx among MM patients at different ISS stages were analyzed. The expression levels of tVD, tPINP and β-CTx in MM patients with different levels of hemoglobin (Hb), serum calcium (Ca), creatinine (Crea), albumin (ALB), β₂-microglobulin (β₂-MG) and lactate dehydrogenase (LDH) were compared. The correlations between the expression levels of tVD, tPINP, β-CTx and the aforementioned clinical parameters were analyzed, respectively. The relationship between the expression levels of tVD, tPINP, β-CTx and the progression-free survival (PFS) of MM patients was analyzed. RESULTS: The expression level of tVD in the MM group was significantly lower than that in the control group (21.73±14.45 ng/ml vs 30.78±9.94 ng/ml, P =0.022). The expression level of β-CTx in the MM group was significantly higher than that in the control group (1.43±0.99 ng/ml vs 0.53±0.29 ng/ml, P =0.013). The tVD level in MM patients with ISS stage I-II was significantly higher than that of MM patients with ISS stage III (29.50±14.59 ng/ml vs 12.62±7.73 ng/ml, P =0.028), indicating that the higher the ISS stage, the lower the tVD level. The tPINP and β-CTx levels in MM patients with high Ca levels (>2.65 mmol/L) were significantly higher than those in patients with low Ca levels (≤2.65 mmol/L) (P =0.016, P =0.021). The tVD level of MM patients was positively correlated with the ALB level (r =0.570), tPINP was positively correlated with Ca and β₂-MG levels (r =0.791,r =0.673), and β-CTx was positively correlated with tPINP level (r =0.616). The PFS of the low tVD expression group was significantly lower than that of the high tVD expression group (P =0.041). CONCLUSION The expression level of tVD is decreased in MM patients, which can be used as an indicator to evaluate the disease stage and prognosis of the patients. The β-CTx expression level is increased in MM patients. tPINP and β-CTx may be correlated with clinical symptoms such as osteolytic lesions and renal function changes in MM patients.
Humans ; Multiple Myeloma/pathology* ; Procollagen/blood* ; Vitamin D/blood* ; Prognosis ; Peptide Fragments/blood* ; Collagen Type I/blood* ; Female ; Male ; Middle Aged ; Aged ; Neoplasm Staging

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Sepsis-induced coagulopathy(SIC),a critical and potentially lethal condition arising from sepsis,results in endothelial damage and significant coagulation dysregulation,making it a major factor contributing to mortality among sepsis patients.Early diagnosis and treatment of SIC are expected to improve the prognosis of sepsis patients.In 2019,the International Society on Thrombosis and Hemostasis(ISTH)issued the first guidelines for the diagnosis and treatment of SIC,but there are no corresponding protocols in China.Therefore,Chinese Society of Thrombosis,Hemostasis and Critical Care,Chinese Medicine Education Association,and Chinese People's Liberation Army Professional Committee of Critical Care Medicine jointly formulated the"Chinese Expert Consensus on the Diagnosis and Treatment of Sepsis-induced Coagulopathy(2024 edition)."This consensus includes 5 parts:pathogenesis,classification,laboratory approaches,diagnosis and treatment,with a total of 14 evidence-based recommendations to guide clinical practice.

Objective As primary Sj?gren's syndrome(pSS)primarily affects the salivary glands,saliva can serve as an indicator of the glands'pathophysiology and the disease's status.This study aims to illustrate the salivary proteomic profiles of pSS patients and identify potential candidate biomarkers for diagnosis. Methods The discovery set contained 49 samples(24 from pSS and 25 from age-and gender-matched healthy controls[HCs])and the validation set included 25 samples(12 from pSS and 13 from HCs).Totally 36 pSS patients and 38 HCs were centrally randomized into the discovery set or to the validation set at a 2:1 ratio.Unstimulated whole saliva samples from pSS patients and HCs were analyzed using a data-independent acquisition(DIA)strategy on a 2D LC-HRMS/MS platform to reveal differential proteins.The crucial proteins were verified using DIA analysis and annotated using gene ontology(GO)and International Pharmaceutical Abstracts(IPA)analysis.A prediction model for SS was established using random forests. Results A total of 1,963 proteins were discovered,and 136 proteins exhibited differential representation in pSS patients.The bioinformatic research indicated that these proteins were primarily linked to immunological functions,metabolism,and inflammation.A panel of 19 protein biomarkers was identified by ranking order based on P-value and random forest algorichm,and was validated as the predictive biomarkers exhibiting good performance with area under the curve(AUC)of 0.817 for discovery set and 0.882 for validation set. Conclusions The candidate protein panel discovered may aid in pSS diagnosis.Salivary proteomic analysis is a promising non-invasive method for prognostic evaluation and early and precise treatments for pSS patients.DIA offers the best time efficiency and data dependability and may be a suitable option for future research on the salivary proteome.

Objective:To investigate the clinical phenotype and molecular pathogenic mechanism of a hereditary coagulation factor Ⅴ deficiency (FⅤD)family.Methods:A phase I assay was used to measure coagulation factors Ⅱ,Ⅴ,Ⅶ,Ⅷ,Ⅸ,Ⅹ,Ⅺ,Ⅻ(FⅡ:C,FⅤ:C,FⅦ:C,FⅧ:C,FⅨ:C,FⅩ:C,FⅪ:C,FⅫ:C),activated partial thromboplastin time (APTT)and prothrombin time (PT)to determine the clinical phenotype and molecular pathogenesis of F VD.Prothrombin time (PT)were used for phenotypic identification;high-throughput exome sequencing was applied to screen the whole gene variants,and Sanger sequencing was used to verify the suspected variants in F5 gene;MutationTaster,PolyPhen-2 bioinformatics software was used to predict the pathogenicity of the variants,ClustalX software was used to analyze the amino acid conservatism,and PyMol software was used to simulate the model of the mutant protein.Results:The pre-documented patient had significantly prolonged PT and APTT,FⅤ:C was only 5. 45％,and there was no significant abnormality in TT,FIB and the rest of the coagulation factors.The mother,father and sister of the proband had prolonged PT and APTT,and FⅤ:C was reduced to different degrees.Genetic testing revealed the presence of a c.286G>C (p.Asp96His)pure missense variant in exon 3 of F5 in the prior witness,and a c.286G>C (p.Asp96His)heterozygous missense variant in father,mother,and sister of the proband.Bioinformatics analysis suggested that p.Asp96His was a pathogenic variant,and the associated amino acid site was highly conserved among 10 species.Protein simulation showed that the mutation of Asp96 to His96 could lead to the disappearance of the original hydrogen bond and the change of the distance,destroying the original hydrogen bond interaction force and affecting the stability of the protein structure.Conclusion:The F5 exon 3 c.286G>C (p.Asp96His)missense variant may have contributed to the reduction of FⅤ:C in the preexisting individual and family members,as well as being the genetic etiology of coagulation factor Ⅴ deficiency.

Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

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.