This study explored the drying kinetics of Salviae Miltiorrhizae Radix et Rhizoma(SM), established the suitable models simulating the drying kinetics, and then analyzed the dynamic changes of active components during the drying processes with different methods, aiming to provide a basis for the establishment of suitable drying methods and the quality control of SM. The drying kinetics were studied based on the drying curve, drying rate, moisture effective diffusion coefficient, and drying activation energy, and the appropriate drying kinetics model of SM was established. The drying performance of different methods, such as hot air drying, infrared drying, and microwave drying of SM was evaluated, and the changes in the content of 10 salvianolic acids and 6 tanshinones during drying were analyzed by UPLC-TQ-MS. The Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) was employed to evaluate the quality of SM dried with different methods. The results showed that the drying rate and moisture effective diffusion coefficient of SM increased with the rise in drying temperature, and the maximum drying rates of different methods were in the order of microwave drying > infrared drying > hot air drying, slice > whole root. The drying rate decreased with the rise in temperature and the extension of drying time. The activation energy of hot air drying was higher than that of infrared drying in SM. The most suitable model for simulating the drying process of SM was the Page model. The TOPSIS results suggested infrared drying at 50 ℃ was the optimal drying method for SM. During the drying process, the content of salvianolic acids increased in different degrees with the loss of moisture, among which salvianolic acid B showed the largest increase of 44 times compared with that in the fresh medicinal material. Tanshinones also existed in the fresh herb of SM, and the content of tanshinone Ⅱ_A increased by 3 times after drying. The results provided a basis for the establishment of suitable drying methods and the quality control of SM.
Salvia miltiorrhiza/chemistry* ; Desiccation/methods* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Kinetics ; Quality Control ; Abietanes

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

OBJECTIVES: To investigate the correlation between bone mineral density (BMD) and bone metabolic markers in preschool children and the influencing factors for BMD, and to provide a clinical basis for promoting bone health in children. METHODS: A retrospective analysis was performed for the data of 127 preschool children who underwent physical examination in the Department of Child Health Care of the First Affiliated Hospital of Xinjiang Medical University, from June to December 2024. BMD and bone metabolic markers were measured, and physical examination was performed. A multiple linear regression analysis was used to investigate the effect of general information on BMD Z-score in preschool children. Spearman's rank correlation test was used to investigate the correlation of BMD Z-score with 25-hydroxyvitamin D (25-OHD), serum bone Gla protein (BGP), and parathyroid hormone (PTH). RESULTS: BMD Z-score significantly differed by ethnicity, weight category, and height category (all P<0.05). The multiple linear regression analysis indicated that weight and height significantly influenced BMD Z-score (P<0.05), whereas sex, age, ethnicity, and parental education level did not (P>0.05). In children, BMD Z-score was positively correlated with 25-OHD level (r_s=0.260, P<0.001) and BGP level (r_s=0.075, P=0.025) and was negatively correlated with PTH level (r_s=-0.043, P=0.032). CONCLUSIONS Weight, height, 25-OHD, BGP, and PTH are influencing factors for BMD in preschool children. In clinical practice, combined measurement of bone metabolic markers may provide a scientific basis for early identification of children with abnormal BMD and prevention of osteoporosis and osteomalacia.
Humans ; Bone Density ; Child, Preschool ; Female ; Male ; Retrospective Studies ; Vitamin D/blood* ; Parathyroid Hormone/blood* ; Biomarkers/blood* ; Osteocalcin/blood* ; Bone and Bones/metabolism* ; Calcium-Binding Proteins/blood* ; Linear Models ; Matrix Gla Protein ; Extracellular Matrix Proteins/blood* ; Body Weight ; Infant

OBJECTIVE: To investigate the relationship between serum levels of fibroblast growth factor-23 (FGF-23), heparanase (HPSE) and early renal impairment (RI) in patients with multiple myeloma (MM). METHODS: A retrospective analysis was conducted on the clinical data of 125 MM patients who were initially diagnosed in the Department of Hematology of the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology from June 2020 to June 2023. The patients were divided into RI group (>176.80 μmol/L) and non-RI group (≤176.80 μmol/L) based on their serum creatinine levels when diagnosed. The baseline data and laboratory indexes of the two groups were compared. The relationship between serum FGF-23, HPSE and early RI in MM patients was analyzed. RESULTS: Among 125 newly diagnosed MM patients, 33 cases developed early RI, accounting for 26.40%. The proportion of light chain type, blood urea nitrogen (BUN), blood uric acid, lactate dehydrogenase, FGF-23, and HPSE levels in RI group were higher than those in non-RI group (all P <0.05). There was no statistical significant difference in other data between the two groups (P >0.05). Multivariate logistic regression analysis showed that BUN, FGF-23 and HPSE were associated with early RI in MM patients (all P <0.05). The serum FGF-23 level was divided into Q1-Q4 groups by quartile, and the serum HPSE level was divided into q1-q4 groups. The correlation analysis showed that with the increase of serum FGF-23 and HPSE levels, the incidence of early RI increased (r =0.668, 0.592). Furthermore, logistic regression analysis showed that after controlling for confounding factors, elevated levels of serum FGF-23 and HPSE were still influencing factors for early RI in MM patients (OR>1, P <0.05). According to Pearson's linear correlation test, there was a positive correlation between serum FGF-23 level and HPSE level (r =0.373). CONCLUSION There is a certain correlation between serum levels of FGF-23, HPSE and early RI in MM patients, and the incidence of early RI is higher in patients with abnormally high levels of both.
Humans ; Multiple Myeloma/complications* ; Fibroblast Growth Factor-23 ; Retrospective Studies ; Fibroblast Growth Factors/blood* ; Glucuronidase/blood* ; Male ; Female ; Middle Aged ; Renal Insufficiency/blood* ; Aged

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.

In recent years,more and more researches has focused on the correlation between cognitive activity and physiological variables.The change of pupil is regarded as an important target in the cognitive process,and has become a hot research field.This review focuses on the three key brain regions that regulate pupil change,and reflects the neurophysiological mechanism behind pupil change by elaborating the neural pathways related to pupil change and cognitive performance.Based on recent studies on pupil change in cognitive diseases,it aims to promote the application of pupil change in the field of cognitive science in the future.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.