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.

OBJECTIVE: To analyze the clinical characteristics, microbiological analysis, and drug resistance patterns of intensive care unit (ICU) bloodstream infection. METHODS: A prospective cohort study method was employed to collect clinical data from patients suspected of bloodstream infection (BSI) during their stay in ICUs across 67 hospitals in 16 provinces and cities nationwide, from July 1, 2021, to December 31, 2022. Electronic data collection technology was used to gather general information on ICU patients, including gender, age, length of hospital stay, as well as diagnostic results, laboratory tests, imaging studies, microbiological results (including smear, culture results, and pathogen high-throughput testing), and prognosis. Patients were divided into a BSI group and a non-BSI group based on the presence or absence of BSI; further, patients with BSI were categorized into a drug-resistant group and a non-drug-resistant group based on the presence or absence of drug resistance. Differences in the aforementioned indicators between groups were analyzed and compared; variables with P < 0.10 in the univariate analysis were included in a multivariate Logistic regression analysis to identify risk factors for mortality and drug resistance in ICU patients with BSI. RESULTS: A total of 2 962 ICU patients suspected of BSI participated in the study, including 790 in the BSI group and 2 172 in the non-BSI group. Patients in the BSI group were mainly from East China and Southwest China, with significantly higher age and mortality rates than those in the non-BSI group. Among ICU patients with BSI, Staphylococcus had the highest detection rate (8.10%), followed by Klebsiella pneumoniae (7.47%); there were 169 cases in the drug-resistant group and 621 cases in the non-drug-resistant group; 666 cases survived, and 124 cases died (mortality was 15.70%). There were statistically significant differences between the death group and the survival group in terms of age, regional distribution, and bloodstream infections caused by Gram negative (G^-) bacilli, Enterococcus faecium, Aspergillus, and Klebsiella pneumoniae; multivariate Logistic regression analysis showed that age [odds ratio (OR) = 1.01, 95% confidence interval (95%CI) was 1.00-1.03], regional distribution (OR = 4.07, 95%CI was 1.02-1.34), Enterococcus faecium infection (OR = 3.64, 95%CI was 1.16-11.45), and Klebsiella pneumoniae infection (OR = 2.64,95%CI was 1.45-4.80) were independent risk factors for death in ICU patients with BSI (all P < 0.05). There were statistically significant differences between the drug-resistant group and the non-drug-resistant group in terms of age and bloodstream infections caused by Gram positive (G⁺) cocci and G^- bacilli; multivariate Logistic regression analysis showed that age (OR = 1.01,95%CI was 1.00-1.03), G^- bacilli infection (OR = 2.18, 95%CI was 1.33-3.59), Escherichia coli infection (OR = 0.28,95%CI was 0.09-0.84), and Enterococcus faecium infection (OR = 3.35, 95%CI was 1.06-10.58) were independent risk factors for drug resistance in ICU patients with BSI (all P < 0.05). CONCLUSIONS Bloodstream infections may increase the mortality of ICU patients. Older age, regional distribution, Enterococcus faecium infection and Klebsiella pneumoniae infection can increase the mortality rate of ICU patients with BSI; bloodstream infections caused by G^- bacilli are prone to drug resistance, but have no significant impact on the mortality of ICU patients with BSI.
Adult ; Humans ; Bacteremia/microbiology* ; China/epidemiology* ; Cohort Studies ; Cross Infection/microbiology* ; Drug Resistance, Bacterial ; Intensive Care Units/statistics & numerical data* ; Prospective Studies ; Risk Factors ; Sepsis/microbiology*

OBJECTIVE: To investigate the whole-genome differential methylation profile of patients with high-altitude polycythemia (HAPC). METHODS: In this study, a total of 20 adult male patients with HAPC were included, including 10 Tibetan and 10 Han patients. The control group consisted of 20 healthy adult males, including 10 Tibetan and 10 Han patients. Peripheral blood was collected from each group for DNA extraction and quality inspection, and DNA libraries were constructed. The differential methylation regions (DMRs) between groups were detected using reduced representation bisulfite sequencing, with enriched regions compared to those of the control group. The differential enrichment regions were selected, and the intersection of the enriched regions was associated with genes. The methylation enrichment regions that differed significantly between groups were filtered based on the number of enriched samples in the enriched regions between the groups. GO, KEGG functional, and pathway analysis were performed on the differentially associated gene sets to reveal significant differences between the patients and control groups at the functional and pathway levels. RESULTS: In comparison with the control group, 17 152 sites with more than 25% difference and 15 558 sites with less than -25% difference were identified in Tibetan patients. The top 5 genes with the largest methylation differences between the two groups were MCCC2, RP3-399L15.3, ZNF621, RP11-394A14.2 and SLC39A10. The top significantly different pathways annotated in the differentially expressed genes pathway was serotonergic synapse. In comparison with the control group, 2 687 CpG sites with a greater than 25% difference and 2 602 CpG sites with a less than -25% difference were identified in Han patients. The top 5 genes with the largest methylation differences between the two groups were NAA25, CORO2B, PDC, ZNF853, and MLLT10. The top significantly different pathways annotated in the differentially expressed genes pathway were glutamatergic synapse, retrograde endocannabinoid signaling, Rap1 signaling pathway and cholinergic synapse. In comparison with the control group, 3 895 CpG sites with a greater than 25% difference and 3 969 CpG sites with a less than -25% difference were identified in HAPC patients. The maximum methylation difference between the two groups could reach 78.1%, while the minimum was -42.6%. The top 5 genes with the largest methylation differences between the two groups were MCCC2, ARSJ, CTNNA3, SLC39A10, and SWAP70. The top significantly different pathways annotated in the differentially expressed genes pathway was signaling pathways regulating pluripotency of stem cells. CONCLUSION The occurrence of HAPC may be related to abnormal changes in DNA methylation, and methylation sites may be helpful for the early diagnosis of HAPC.
Humans ; DNA Methylation ; Altitude ; Polycythemia/genetics* ; Male ; Adult ; CpG Islands

Objective:To assess the relationship between basophil levels and mortality in patients with intra-abdominal infection.Methods:Information on patients with intraperitoneal infection admitted to the intensive care unit were extracted from the MIMIC database.A time-dependent Cox regression model was used to adjust for confounders associated with 28-day mortality.Propensity score matching(PSM)was used to balance the baseline differences be-tween groups with different basophil levels,and a restricted cube chart(RCS)was used to show the relationship between basophil count and 28-day mortality in patients with intra-abdominal infection.Results:A total of 4403 patients with intra-abdominal infection were enrolled in the MIMIC database.Patients with high basophil levels have lower mortality than those with low basophil levels.There was an L-shaped curve between basophil level and 28-day mortality,with a cut-off value of 0.47×109/L.Cox regression analysis showed that basophil levels were an independent protective factor for mortal-ity in patients with intra-abdominal infection after adjusting for potential confounders(HR=0.586,95%CI:0.443-0.769).Protective factors for death at basophil levels remained after PSM adjusted for potential confounders(HR=0.628,95%CI:0.470-0.832).Conclusion:Basophil level is an independent protective factor for mortality in patients with intra-abdominal infection,and basophil levels should be dynamically monitored to better evaluate the prognosis of patients.

Aim To explore the mechanism of the syn-ergistic effect of the ferroptosis inducer erastin com-bined with shikonin in promoting ferroptosis in human hypertrophic scar fibroblasts(HSFBs).Methods Hypertrophic scar tissues provided by the General Hos-pital of Ningxia Medical University were collected,and HSFBs were extracted.HSFBs were identified by HE staining and immunofluorescence.The inhibitory rates of Era and SHK on HSFBs at different concentrations were detected by CCK-8 assay,and the IC50 value was calculated.CompuSyn software was used to calculate the co-use index(CI).Control group,Erastin(Era)group,shikonin(SHK)group and Era+SHK group were set up,and the number and morphological chan-ges of cells were observed after 24 hours of interven-tion.The ability of cell migration and invasion was de-tected by scratch test and Transwell test.The changes of malondialdehyde(MDA),total iron ion and reactive oxygen species(ROS)were detected by corresponding biochemical kits.The expressions of collagen I,α-SMA and GOT1,SLC7A11,GPX4 and FTH1 were detected by Western blot.Results The IC50 value of Era and SHK of primary HSFBs was 2.22 μmol·L-1 and 3.94μmol·L-1 respectively,which was used as the single drug concentration for subsequent experiments.The CompuSyn software was employed to calculate the CI value when the two drugs were used in combination,and the concentrations corresponding to CI=0.39597(Era:1.2 μmol·L-1+SHK:1.5 μmol·L-1)were selected as subsequent combination concentrations(Because when CI was equal to 0.395 97,the concen-tration of each drug was lower than the concentration of single drug,and the inhibition rate of combined drug was greater than 50％).Compared with the monother-apy group,the number of HSFBs in the SHK+Era group was significantly reduced,cell membrane showed breakage and vesiculation,cell wrinkling became smal-ler,and cytoplasm was concentrated.The migration and invasion ability of HSFBs in the SHK+Era group were obviously weakened(P＜0.05),and the expres-sion of fibrosis-related proteins collagen Ⅰ and α-SMA was reduced(P＜0.05);the contents of MDA,total i-ron ions,and ROS in HSFBs of the SHK+Era group increased(P＜0.05),and the protein expression lev-els of SLC7A11,GOT1,GPX4,and FTH1 further de-creased(P＜0.05).Conclusions Erastin in combi-nation with shikonin can synergistically inhibit the pro-liferation,migration and fibrosis levels of HSFBs.The mechanism may be that erastin enhances the inhibition of shikotin on GOT1,increases the levels of cellular i-ron ions,ROS,and lipid peroxides,thereby promoting ferroptosis in HSFBs.

Objective To analyze the epidemiological distribution,microbiological characteristics,drug-resistance status,and risk factors for mortality in adult intensive care unit(ICU)patients with Klebsiella pneumoniae infection.Methods This multi-center prospective cohort study included ICU patients with suspected infection from 67 hospitals across 16 Chinese provinces/municipalities between July 1,2021 and December 31,2022.Clinical data and microbiological results were collected,and patients were divided into survival and non-survival groups according to their survival status and drug-resistance situation.Risk factors for mortality and drug resistance in ICU patients with Klebsiella pneumonia infection were determined through univariate and multivariate logistic regression analyses.Results A total of 2964 ICU-infected patients were enrolled,with 12 175 microbial specimens submitted for testing.Among these,487 specimens tested positive for Klebsiella pneumoniae.Ultimately,314 patients with Klebsiella pneumoniae infection were identified,primarily from lung infections,with a drug-resistance rate of 78.3%.The in-hospital mortality rate of ICU patients infected with Klebsiella pneumoniae was 19.8%.Univariate and multivariate logistic regression analyses revealed that older age(P=0.027),high drug-resistance rate(P=0.028),and low clinical-effectiveness rate(P<0.001)were independent risk factors for mortality in ICU patients infected with Klebsiella pneumoniae.Drug-resistance analysis showed that,compared with non-resistant cases,ICU patients with drug-resistant Klebsiella pneumoniae infection had lower pathogen-clearance rates(P=0.003),clinical-effectiveness rates(P=0.004),and antibiotic-effectiveness rates(P<0.010),and higher mortality rates(P=0.006).Patients with Klebsiella pneumoniae abdominal infection(P=0.003)and urinary tract infection(P=0.007)had higher drug-resistance incidences.There were no statistically significant differences in clinical-effectiveness rate,Klebsiella pneumoniae clearance,drug-resistance incidence,mortality rate,or hospital-stay length between patients with lung infection and those with non-lung infection of Klebsiella pneumoniae(P>0.05).Compared with patients with non-bloodstream infection,patients with bloodstream infection of Klebsiella pneumoniae had lower clinical-effectiveness rates(P=0.027)and higher mortality rates(P=0.021).Conclusions Older age,high drug-resistance rate,and low clinical-effectiveness rate are independent risk factors for mortality in ICU patients infected with Klebsiella pneumoniae.ICU patients with bloodstream infection of Klebsiella pneumoniae may have lower clinical-effectiveness rates and higher mortality rates.ICU patients with abdominal and urinary tract infections caused by Klebsiella pneumoniae are more likely to develop drug resistance.

Objective To investigate the effects of estrogen signaling on T-cell recruitment and polarization in acutely injured skeletal muscle.Methods One hundred C57BL/6 male mice,one hundred and eighty C57BL/6 female mice were selected.Twenty-five female mice were ovariectomized(OVX)and 10 male mice were taken as the sham-operated(sham).Then,cardiotoxin(CTX)induced tibialis anterior(TA)injury for preparing mice myoinjury model.Subcutaneous injection of 17β-estradiol(E2)or estrogen receptor antagonist 4-hydroxytamoxifen(4-OHT)was performed.A total of 140 mice(70 males and 70 females)were divided into four group including:PBS-male,CTX-male,PBS-female,and CTX-female.Serum estradiol(E2)levels were measured by ELISA,and muscle injury models were validated via HE staining.Subsequently,20 male and 20 female mice were selected for immunofluorescence(IF)and Real-time PCR to assess estrogen receptors(ER)expression in injured muscle tissue.Further,10 male and 40 female mice were allocated into five experimental groups,including CTX,CTX+E2,CTX+4-OHT,CTX+OVX,CTX+sham.HE staining and IF were performed to evaluate inflammatory infiltration in the injured muscle.Additionally,50 female mice were divided into CTX and CTX+OVX groups,and IF combined with flow cytometry were used to analyze T-cell phenotypes and muscle fiber regeneration in the injured muscle.Results In vivo,serum E2 and myofiber ERβ increased post-injury in mice of both sexes,significantly higher in females.Compared to the control group,E2 alleviated inflammation,OVX exacerbated inflammation,increased CD4+T-cell infiltration,elevated T helper 1 cell(Th1)response,decreased regulatory T cells(Tregs),impaired regeneration.In vitro,IFN-γ/LPS significantly upregulated ERβ in myotubes.Conclusion Estrogen signaling critically regulates muscle inflammation.Estrogen deficiency(OVX)delays repair of skeletal muscle by promoting Th1 response and suppressing Tregs function.

Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

Objective To investigate mortality risk factors and characterize pathogen distribution and antimicrobial resistance patterns in intensive care unit(ICU)patients with suspected infection following surgery.Methods A total of 65 hospitals in 16 provinces in China from July 1,2021,to December 31,2022.Clinical data were collected for surgical patients transferred to the ICU with suspected infection.Data included demographics[sex,age,underlying conditions(hypertension,diabetes,cardiovascular/cerebrovascular disease,hematologic disease)],surgical site,infection site,microbiological results with susceptibility testing,drug resistance and acute physiology and chronic health evaluationⅡ(APACHEⅡ)scores and the length of hospital stays.Patients were stratified by prognosis into death group and survial group,by drug resistance status into resistant and non-resistant groups.Univariate and multivariate Logistic regression identified risk factors for mortality and antimicrobial resistance.Draw the receiver operator characteristic curve(ROC curve)to evaluate the predictive value of each risk factor for patient prognosis and drug resistance occurrence.Results A total of 677 patients with suspected postoperative infection in the ICU were enrolled.There were 96 deaths and 591 survivors.① Analysis of risk factors affecting prognosis:univariate analysis showed that compared with the survival group,the patients in the had a higher APACHEⅡscore,the proportion of patients with previous cerebrovascular disease,surgery sites in the abdomen,chest,brain,pelvis,limbs,other areas,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,Gram-positive bacterial infection(Candida),fungal infection,multi-drug resistant bacterial infection was higher,and the length of hospital stay was shorter(all P<0.05).Multivariate Logistic regression analysis identified higher APACHEⅡscore[odds ratio(OR)=1.15,95%confidence interval(95%CI)was 1.11-1.20],pulmonary infection(OR=4.07,95%CI was 2.05-8.11),bloodstream infection(OR=2.61,95%CI was 1.52-4.51),and urinary tract infection(OR=2.20,95%CI was 1.01-4.42)were independent risk factors for prognosis(all P<0.05).The ROC curve analysis showed that the death risk prediction model established based on the above independent risk factors had certain predictive value for the prognosis of ICU postoperative patients with suspected infection,area under the curve(AUC)=0.820,95%CI was 0.770-0.860,P<0.05.②Regarding antimicrobial resistance:250 patients developed resistance and 427 did not.Univariate analysis showed compared with the non-resistant group,the APACHEⅡscore,the proportion of patients with cerebrovascular diseases,hematological diseases,surgeries at chest,brain,limbs,other sites,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,intracranial infection,Gram-negative bacillus infection,and Gram-positive cocci infection(Staphylococcus epidermidis,Staphylococcus aureus,Enterococcus faecalis),and the mortality rate in the resistant group were significantly higher,the proportion of patients with surgeries at abdominal cavity,pelvic cavity and abdominal cavity infection were significantly lower,and the length of hospital stay was significantly longer(all P<0.05).Multivariate Logistic regression analysis bloodstream infection(OR=4.00,95%CI was 2.22-7.19),urinary tract infection(OR=3.25,95%CI was 1.47-7.17),Klebsiella pneumoniae infection(OR=2.23,95%CI was 11.22-44.02),Acinetobacter baumannii infection(OR=48.12,95%CI was 20.10-115.17),Pseudomonas aeruginosa infection(OR=34.06,95%CI was 13.00-89.25),Escherichia coli infection(OR=24.97,95%CI was 10.55-59.13),Stenotrophomonas maltophilia infection(OR=19.04,95%CI was 3.30-109.96),and Staphylococcus aureus infection(OR=13.48,95%CI was 4.57-39.78)were independent risk factors for resistance(all P<0.01).The ROC curve analysis showed that the predictive model for drug resistance established based on the above independent risk factors had certain predictive value for drug resistance in adult patients with suspected infections after surgery in the ICU.The AUC=0.920,95%CI was 0.890-0.940,P<0.05.Conclusion Higher APACHEⅡscores and the presence of pulmonary,bloodstream,or urinary tract infections were associated with increased mortality in ICU patients with suspected postoperative infection.Patients with bloodstream or urinary tract infections,or infections caused by Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,Escherichia coli,Stenotrophomonas maltophilia,or Staphylococcus aureus,had significantly higher odds of developing antimicrobial resistance.