OBJECTIVE To investigate the relationship between 23-site chip genetic screening failures and the results of newborns hearing screening,and to provide clinical reference for the diagnosis and treatment of genetic screening failures.METHODS There were 1 916 newborns born in the Beijing area from November 2022 to May 2024,who did not pass the 23-site chip genetic screening tests and underwent newborn hearing screening with definite initial screening results.Chi-square test was used to analyze the relationship between different mutation types and genotypes and the initial hearing screening results.RESULTS The overall neonatal hearing screening failure rate was 5.27%(101/1 916),with a higher failure rate of 61.54%(56/91)for homozygous and compound heterozygous mutations than the failure rate of 2.54%(45/1 772)for heterozygous mutations,0%(0/34)for digenic gene heterozygous mutations,and 0(0/19)for mtDNA 12S rRNA mutations,with a statistically significant difference(P<0.001).Among the homozygous and compound heterozygous mutations,the failure rates of homozygous and compound heterozygous for GJB2 gene and SLC26A4 gene were 59.76%(49/82)and 77.78%(7/9),respectively,with no statistically significant difference between the two groups(P=0.488).The homozygous and compound heterozygous for GJB2 gene were divided into three groups based on genotype:c.109G>A homozygous mutations,c.109G>A compound heterozygous mutations,and other homozygous and compound heterozygous mutations.The hearing screening failure rates of the three groups,from highest to lowest,were as follow:other homozygous and compound heterozygous mutations(88.89%,8/9),c.109G>A homozygous mutations(65.12%,28/43),and c.109G>A compound heterozygous mutations(43.33%,13/30),with a statistically significant difference(P=0.029).The failure rates of heterozygous for GJB2 gene,SLC26A4 gene and GJB3 gene were 2.86%(40/1 398),1.25%(4/321)and 1.89%(1/53),respectively,with no statistically significant difference among the three groups(P=0.241).The failure rate of hearing screening for individuals with GJB2 heterozygotes of different genotypes and individuals with SLC26A4 heterozygotes of different genotypes did not show statistically significant differences.CONCLUSION The failure rate of newborn hearing screening for homozygous and compound heterozygous mutation of 23-site chip genetic screening is higher than that of other mutation types,verifying the effectiveness of the newborn hearing screening program.Some newborns of homozygous and compound heterozygous mutation can pass the hearing screening,especially those with the c.109G>A homozygous and compound heterozygous mutation,who need clinical follow-up.

This study aims to explore the effects and mechanisms of the traditional Chinese medicine Cordyceps sinensis(CS) in ameliorating heart aging and injury in mice based on animal experiments and network pharmacology. A mouse model of heart aging was established by continuously subcutaneous injection of D-galactose(D-gal). Thirty mice were randomly assigned into a normal group, a model group, a low-dose CS(CS-L) group, a high-dose CS(CS-H) group, and a vitamin E(VE) group. Mice in these groups were administrated with normal saline, different doses of CS suspension, or VE suspension via gavage daily. After 60 days of treatment with D-gal and various drugs, all mice were euthanized, and blood and heart tissue samples were collected for determination of the indicators related to heart aging and injury in mice. Experimental results showed that both high and low doses of CS and VE ameliorated the aging phenotype, improved the heart index and myocardial enzyme spectrum, restored the expression levels of proteins associated with cell cycle arrest and senescence-associated secretory phenotypes(SASP), and alleviated the fibrosis and histopathological changes of the heart tissue in model mice. From the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),259 active ingredients of CS were retrieved. From Gene Cards and OMIM, 2 568 targets related to heart aging were identified, and 133common targets shared by CS and heart aging were obtained. The Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes( KEGG) pathway enrichment revealed that the pathways related to heart aging involved oxidative stress,apoptosis, inflammation-related signaling pathways, etc. The animal experiment results showed that both high and low doses of CS and VE ameliorated oxidative stress and apoptosis in the heart tissue to varying degrees in model mice. Additionally, CS-H and VE activated the nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1) pathway and inhibited the expression of key proteins in the nuclear factor-κB(NF-κB) pathway in the heart tissue of model mice. In conclusion, this study demonstrated based on network pharmacology and animal experiments that CS may alleviate heart aging and injury in aging mice by reducing oxidative stress,apoptosis, and inflammation in the heart via the Nrf2/HO-1/NF-κB pathway.
Animals ; Cordyceps/chemistry* ; Mice ; NF-E2-Related Factor 2/genetics* ; NF-kappa B/genetics* ; Aging/genetics* ; Male ; Signal Transduction/drug effects* ; Network Pharmacology ; Drugs, Chinese Herbal/pharmacology* ; Heme Oxygenase-1/genetics* ; Heart/drug effects* ; Humans ; Myocardium/metabolism* ; Membrane Proteins/genetics*

Cervi Cornu Pantotrichum is a precious animal-derived Chinese medicinal material, while there are often adulterants derived from animals not specified in the Chinese Pharmacopeia in the market, which disturbs the safety of medication. This study was conducted with the aim of strengthening the quality control of Cervi Cornu Pantotrichum and standardizing the medication. To achieve digital identification of Cervi Cornu Pantotrichum from different sources, a digital identification model was constructed based on ultra-high performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry(UHPLC-QTOF-MS~E) combined with an adaptive boosting algorithm(Adaboost). The young furred antlers of sika deer, red deer, elk, and reindeer were processed and then subjected to polypeptide analysis by UHPLC-QTOF-MS~E. Then, the mass spectral data reflecting the polypeptide information were obtained by digital quantification. Next, the key data were obtained by feature screening based on Gini index, and the digital identification model was constructed by Adaboost. The model was evaluated based on the recall rate, F_1 composite score, and accuracy. Finally, the results of identification based on the constructed digital identification model were validated. The results showed that when the Gini index was used to screen the data of top 100 characteristic polypeptides, the digital identification model based on Adaboost had the best performance, with the recall rate, F_1 composite score, and accuracy not less than 0.953. The validation analysis showed that the accuracy of the identification of the 10 batches of samples was as high as 100.0%. Therefore, based on UHPLC-QTOF-MS~E and Adaboost algorithm, the digital identification of Cervi Cornu Pantotrichum can be realized efficiently and accurately, which can provide reference for the quality control and original animal identification of Cervi Cornu Pantotrichum.
Animals ; Algorithms ; Antlers/chemistry* ; Boosting Machine Learning Algorithms ; Chromatography, High Pressure Liquid/methods* ; Deer ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Quality Control ; Reindeer ; Tandem Mass Spectrometry/methods* ; Tissue Extracts/analysis*

In this study, the pharmacodynamic components and potential pharmacological functions of Danzhi Xiaoyao Formula in treating nervous system diseases were investigated by hippocampal component characterization and network pharmacology. After rats were administrated with Danzhi Xiaoyao Formula by gavage, high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(HPLC-Q-TOF-MS/MS) was employed to explore the components in the hippocampus of rats. Fifty-seven components were identified in the hippocampus of rats by comparing the extract of Danzhi Xiaoyao Formula, herbal components in the hippocampus after administration, and blank samples. KEGG and GO analyses predicted 74 core targets including GSK3B, MAPK1, AKT, IL6. These targets were involved in PI3K/Akt, NF-κB, MAPK, JAK/STAT, Wnt, and other signaling pathways. The results indicated that Danzhi Xiaoyao Formula may ameliorate other nervous system diseases enriched in DO, such as neurodegenerative diseases, cerebrovascular diseases, and mental and emotional disorders by mediating target pathways, inhibiting inflammation, reducing neuronal damage, and alleviating hippocampal atrophy. The relevant activities exhibited by this formula in nervous system diseases such as Alzheimer's disease, Parkinson's disease, and diabetic neuropathy have extremely high development value and are worthy of further in-depth research. This study provides a theoretical basis and practical guidance for expanding the application of Danzhi Xiaoyao Formula in the treatment of nervous system diseases.
Drugs, Chinese Herbal/administration & dosage* ; Animals ; Rats ; Hippocampus/metabolism* ; Network Pharmacology ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Rats, Sprague-Dawley ; Male ; Nervous System Diseases/genetics* ; Humans ; Signal Transduction/drug effects*

This study applied the grading of recommendations assessment, development and evaluation(GRADE) system and the integrated evidence chain-based effectiveness evaluation of traditional Chinese medicine(Eff-iEC) to evaluate the evidence for 12 commonly used Chinese patent medicines for the treatment of osteoporosis, which are frequently recommended in guidelines or expert consensuses. The results showed that Xianling Gubao Capsules/Tablets were rated as C(low-level evidence) according to the GRADE system, and as BA~+B~+(intermediate evidence) according to the Eff-iEC system. Jintiange Capsules were rated as C(low-level evidence) by the GRADE system, and as AA~+B(high-level evidence) by the Eff-iEC system. Gushukang Granules/Capsules were rated as C(low-level evidence) by GRADE system, and as BA~+B~+(intermediate evidence) by Eff-iEC system. Zuogui Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Qianggu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B~+(high-level evidence) by Eff-iEC system. Zhuanggu Zhitong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BA~+B(intermediate evidence) by Eff-iEC system. Jingui Shenqi Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B(high-level evidence) by Eff-iEC system. Quanduzhong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AD~+B~+(low-level evidence) by Eff-iEC system. Epimedium Total Flavones Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AAB~+(high-level evidence) by Eff-iEC system. Yougui Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~(++)B~(+ )(high-level evidence) by Eff-iEC system. Qigu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BB~+B(intermediate evidence) by Eff-iEC system. Liuwei Dihuang Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Overall, the Eff-iEC system provides a more comprehensive assessment of the effectiveness evidence for traditional Chinese medicine(TCM) than the GRADE system. However, it still has certain limitations that hinder its wider promotion and application. In terms of clinical evidence evaluation, both the Eff-iEC and GRADE systems reflect that the current clinical research quality on Chinese patent medicines for the treatment of osteoporosis is generally low. High-quality clinical trials are still needed in the future to further validate clinical efficacy.
Drugs, Chinese Herbal/therapeutic use* ; Osteoporosis/drug therapy* ; Humans ; Nonprescription Drugs/therapeutic use* ; Evidence-Based Medicine ; Medicine, Chinese Traditional

The therapeutic effects of Yueju Pills on depression and cardiovascular diseases have been widely recognized. Previous studies have shown that the drug can significantly improve depressive-like behaviors induced by chronic unpredictable mild stress(CUMS) combined with atherosclerosis(AS). Given the complex pathogenesis of psychocardiac diseases, this study integrated metabolomics and network pharmacology to systematically elucidate the mechanism of Yueju Pills in alleviating depressive symptoms in psychocardiac diseases. The results demonstrate that, after Yueju Pill intervention, the levels of 9 abnormal metabolites in the hippocampus restore to normal ranges, primarily involving key pathways or signaling pathways, including the cyclic adenosine monophosphate(cAMP), mammalian target of rapamycin(mTOR), glycine/serine/threonine metabolism, and aminoacyl-tRNA biosynthesis. In a high-fat diet-induced CUMS ApoE~(-/-) mouse model, Yueju Pills significantly increases adenosine monophosphate(AMP) levels and decreases L-alanine and D-glyceric acid levels in the hippocampus. In conclusion, Yueju Pills exert antidepressant effects by regulating multiple metabolic axes, including glycine/serine/threonine metabolism and the cAMP, mTOR signaling pathways. Network pharmacology predictions reveal that the treatment of CUMS combined with AS by its core active components may be realized through modulating pathways concerning neuroinflammation and synaptic plasticity, including serine/threonine-protein kinase 1(AKT1), mitogen-activated protein kinase 1(MAPK1), and prostaglandin-endoperoxide synthase 2(PTGS2). This study provides a theoretical reference for the clinical application of Yueju Pills in alleviating the depressive symptoms of psychocardiac diseases.
Animals ; Network Pharmacology ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Male ; Depression/genetics* ; Humans ; Hippocampus/drug effects* ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.