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.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

A high-performance liquid chromatography method using pre-column derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate was developed to determine the content of 15 amino acids in the medicinal snakes Bungarus Parvus, Agkistrodon, and Zaocys. The results showed that the total amino acid(TAA) content ranged from 277.13 to 515.05 mg·g~(-1), with the top four amino acids in all three species being glutamic acid(Glu), glycine(Gly), aspartic acid(Asp), and lysine(Lys). The essential amino acid(EAA) content ranged from 74.56 to 203.94 mg·g~(-1), with Agkistrodon exhibiting the highest content. The non-essential amino acid(NEAA), semi-essential amino acid(semi-EAA), and medicinal amino acid(MAA) content ranged from 189.06 to 318.23, 12.89 to 33.53, and 179.83 to 342.33 mg·g~(-1), respectively, with Zaocys having the highest content in these categories. Amino acid nutritional value was evaluated using the amino acid ratio(RAA), amino acid ratio coefficient(RCAA), and amino acid ratio coefficient score(SRCAA), and the results indicated that all three medicinal snakes possessed good nutritional value. The amino acid composition was similar across the species, though significant differences in content were observed. Based on these differences, an orthogonal partial least squares-discriminant analysis(OPLS-DA) model was established, which could clearly distinguish between the three medicinal snake species. The key differences in amino acid content included Gly, tyrosine(Tyr), Glu, and serine(Ser), which may be related to the observed clinical application differences among the species. Further research into the mechanisms of these differential amino acids is expected to provide more insights into the clinical application disparities of these three medicinal snake species.
Amino Acids/chemistry* ; Animals ; Nutritive Value ; Chromatography, High Pressure Liquid ; Snakes/classification* ; Bungarus

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Objective To explore the application effect of nursing intervention based on empow-erment theory in treatment of facial photoaging with fractional ablative fractional laser.Methods A total of 90 patients with facial photoaging who underwent fractional ablative fractional laser treatment were selected and divided into control group and observation group according to random number table method,with 45 cases in each group.The control group received routine nursing intervention,while the observation group received nursing intervention based on empowerment theory.The skin condi-tion,the incidence of adverse reactions,psychological state[Self-Rating Anxiety Scale(SAS),Self-Rating Depression Scale(SDS)]scores,and quality of life[Dermatology Life Quality Index(DLQI)]scores were compared between the two groups.Results After intervention,the percentages of skin characteristics such as enlarged facial pores,wrinkles,and spots in the observation group were higher than those in the control group;the incidence of adverse reactions in the observation group was lower than that in the control group(8.89％ versus 24.44％);the SAS scores,SDS scores,and total DLQI scores in the observation group were lower than those in the control group,with statistically sig-nificant differences(P＜0.05).Conclusion Nursing intervention based on empowerment theory can effectively improve the facial skin condition of patients with facial photoaging treated with fraction-al ablative fractional laser,reduce the incidence of adverse reactions,alleviate negative emotions,and enhance quality of life.

Objective To develop a diagnostic model combining the CT angiography(CCTA)-derived myocardial radiomics signatures with the CT-derived fractional flow reserve(CT-FFR)based on coronary CCTA and investigate the diagnostic accuracy of the hybrid model for hemodynamically significant coronary artery disease(CAD).Methods The patients presenting stable angina pectoris,diagnosed with CAD,and clinically referred for CCTA examination and invasive coronary angiography were prospectively recruited.Radiomics features of the left ventricular myocardium were extracted from the three main perfusion territories demarcated according to the coronary blood supply.The extracted features were first selected by the minimum redundancy maximum relevance feature ranking method.A least absolute shrinkage and selection operator Logistic regression algorithm with leave-one-out cross-validation was then employed to construct a radiomics model.The CT-FFR value was generated for each blood vessel.The area under the receiver operating characteristics curve(AUC_ROC),sensitivity,and specificity were adopted to evaluate the performance of each model against the reference standard invasive coronary angiography/FFR.Results A total of 70 patients[42 men and 28 women;(61±10) years old] were included in this study and complemented CCTA examination,with 175 vessels and the corresponding myocardial territories undergoing invasive coronary angiography/FFR.A total of 1 656 specific radiomics parameters were extracted,from which 14 features were selected to establish the radiomics model.The AUC_ROC,sensitivity,and specificity were 0.797(95%CI=0.732-0.861),77.1%,and 73.7%for the radiomics model,0.892(95%CI=0.841-0.943),81.4%,and 88.8%for the CT-FFR model,and 0.928(95%CI=0.890-0.965),83.3%,and 88.4%for the hybrid model,respectively.The hybrid model outperformed the radiomics model and CT-FFR alone(P=0.040).Conclusions The radiomics signatures of the vessel-related myocardium from CCTA could provide incremental value to the diagnostic performance of CT-FFR and improve vessel-specific ischemia detection.The hybrid model combining CT-FFR with radiomics signatures is potentially feasible for improving the diagnostic accuracy for hemodynamically significant CAD.
Coronary Angiography/methods* ; Tomography, X-Ray Computed ; Humans ; Hemodynamics ; Coronary Artery Disease/diagnostic imaging* ; Male ; Female ; Middle Aged ; Aged ; Radiomics ; Angina Pectoris/diagnostic imaging* ; China ; Image Processing, Computer-Assisted ; Coronary Vessels/diagnostic imaging*

OBJECTIVE To standardize the strategies for prevention and control of Chikungunya(CHIK)in healthcare in-stitutions so as to reduce the risk of transmission in the institutions.METHODS A working group comprising the ex-perts in hospital infection control,infectious diseases,and microbiology systematically reviewed domestic and international evidence and current guidelines,integrated China's vector ecology and healthcare realities,conducted two rounds of Delphi to achieve expert consensus,and graded the evidence and recommendation strength using the Oxford Centre for Evidence Based Medicine system.RESULTS The consensus issues 18 actionable recommendations on triage,patient mosquito-proof isolation,integrated vector control,protection of susceptible populations,environmental cleaning and disinfection,specimen management,medical textile handling,and outbreak emergency response,with each statement assigned an evi-dence level and recommendation strength.CONCLUSION This consensus is for the first time in China to provide evidence-graded strategies for control of CHIK in healthcare institutions,offering work flow-oriented,implementable guidance for clinicians,laboratorians,and infection-control personnel under different risk scenarios and enhancing the comprehensive coping capacity of the healthcare institutions.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.