A single-center, randomized, double-blind, dose-controlled trial of modified Sini Powder in treating mild to moderate generalized anxiety disorder(GAD) in the patients with syndrome of liver depression transforming into fire was conducted at Xiyuan Hospital, China Academy of Chinese Medical Sciences. A total of 80 patients with mild to moderate GAD and the syndrome of liver depression transforming into fire were included. Patients were assigned by the central randomization system at a ratio of 3∶1 into an observation group(n=60, receiving a conventional-dose of granules of modified Sini Powder) and a control group(n=20, receiving low-dose granules with the active ingredients being 50% of that in observation group). Assessments were conducted before treatment(baseline), after 2 weeks of introduction, after 2/4/8 weeks of treatment, and after 4 weeks of follow-up. The results were summarized as follows. In terms of primary outcome indicators, the observation group(62.2%) showed higher total response rate than the control group(26.6%)(P<0.05), and greater Hamilton anxiety scale(HAMA) score reduction after 8 weeks of treatment(P<0.05). In terms of secondary outcome indicators, the HAMA score(somatic anxiety score), traditional Chinese medicine(TCM) syndrome scores, Pittsburgh sleep quality index(PSQI) scale, and clinical global impression(CGI) scale score in the observation group showed a significant compared to the control group at each visit points(P<0.05). Adverse events occurred in 10 cases, including 9(16.9%) cases in the observation group and 1(6.6%) case in the control group. No adverse reaction was observed. In conclusion, conventional-dose modified Sini Powder demonstrated superior efficacy and favorable safety for mild and moderate GAD in the patients with the syndrome of liver depression transforming into fire over low-dose treatment.
Humans ; Male ; Female ; Adult ; Middle Aged ; Double-Blind Method ; Drugs, Chinese Herbal/administration & dosage* ; Anxiety Disorders/drug therapy* ; Treatment Outcome ; Young Adult ; Powders ; Aged ; Liver/drug effects* ; Generalized Anxiety Disorder

ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

Isolated male epispadias typically presents with preputial defects and dorsal urethral dehiscence. A less common subtype, known as concealed epispadias, is distinguished by an intact prepuce. Despite its clinical relevance, there is limited literature on this variant. In this study, we retrospectively analyzed the clinical data of 86 pediatric patients with isolated male epispadias treated in Beijing Children's Hospital (Beijing, China) from May 2004 to July 2023, including 19 cases of concealed epispadias and 67 of nonconcealed epispadias. We compared clinical characteristics, preoperative diagnostics, surgical techniques, postoperative outcomes, and sexual function during follow-up between the concealed and nonconcealed groups. No significant differences were observed between the two groups regarding surgical methods, postoperative complications, or rates of urinary incontinence. However, notable distinctions were found in the age at initial diagnosis, timing of surgery, frequency of incontinence, location of the urethral meatus, and postoperative urinary incontinence scores (all P < 0.05). Given the absence of penopubic epispadias in concealed cases, we categorized glans and penile epispadias within nonconcealed epispadias as distal epispadias ( n = 40) and subsequently compared them with concealed epispadias cases. The postoperative urinary incontinence scores did not differ significantly between the concealed and distal epispadias groups. These findings suggest that concealed epispadias represents a relatively milder form of the condition, characterized by the absence of penopubic involvement, lower rates of urinary incontinence, and favorable surgical outcomes. However, the intact prepuce in concealed cases underscores the need for careful identification and early diagnosis.
Humans ; Male ; Retrospective Studies ; Epispadias/classification* ; China ; Tertiary Care Centers ; Child, Preschool ; Child ; Postoperative Complications/epidemiology* ; Urinary Incontinence/epidemiology* ; Urethra/surgery* ; Infant ; Penis/surgery* ; Adolescent ; Urologic Surgical Procedures, Male/methods* ; East Asian People

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

The aim of this study was to qualitatively and quantitatively detect coronavirus(CoV)in the feces of bats from Qinghua Cave,Yunnan Province,China.CoV was qualitatively tested with reverse transcription polymerase chain reaction(RT-PCR),and homology and genetic evolution were analyzed with bioinformatics software.The established reverse transcription real-time fluores-cence quantitative PCR(qRT-PCR)method was applied to CoV quantification in bat feces.The positivity rate of CoV in 306 fecal samples collected from the fulvous fruit bat(Rousettus leschenaultia)was 7.8%(24/306)according to RT-PCR.All 24 strains of CoV belonged to β-CoV,and showed a similarity of 86.8%-100.0%at the nucleotide level and 95.2%-100.0%at the amino acid level,with respect to other β-CoV sequences in the NCBI database.The positivity rate of CoV was 18.6%(57/306)according to qRT-PCR,a value higher than that according to RT-PCR(χ2=25.3,P<0.05).The mean β-CoV load was 1.3×103 copies/μL.In conclusion,the bats in Qinghua Cave,Yunnan Province,carried CoV belonging to β-CoV.The established qRT-PCR method achieved good sensitiv-ity,accuracy,reproducibility,and a higher detection rate than that of RT-PCR,and can be used for rapid detection of β-CoV in bats.

Ganoderic acid is a class of lanostane-type triterpenoids found in Ganoderma species, and is one of the most important pharmacologically active components in G. lucidum, exhibiting antioxidant, anti-neuropsychiatric, anti-tumor, and immune-enhancing properties. The content of ganoderic acid in G. lucidum is very low, and the traditional extraction process is complex, yielding minimal amounts at high cost. The biosynthetic pathway of G. lucidum triterpenoids(GLTs), including the synthesis of different structural forms of ganoderic acid from lanosterol, as well as the molecular regulatory mechanisms involving key regulatory enzyme genes and their functions, are not yet fully understood. With the continuous development of synthetic biology technologies, there has been a deeper understanding of the biosynthesis and metabolic regulation pathways of ganoderic acid and its derivatives at the molecular level. Research has explored the key regulatory enzyme genes related to ganoderic acid biosynthesis and their functions. Moreover, through the optimization of synthetic biology and culture conditions, large-scale production and preparation of GLTs at the cellular level have been achieved. This paper reviews and analyzes the latest research progress on the biosynthesis pathways and metabolic regulation of GLTs, focusing on the configuration of ganoderic acid and its derivatives, the biosynthetic pathways, key enzyme genes, transcription factors related to ganoderic acid biosynthesis, signal transduction mechanisms, and factors affecting triterpenoid biotransformation. This review is expected to provide a theoretical basis and technical reference for improving the efficient production of triterpenoid pharmacological components and the exploitation and utilization of G. lucidum resources.
Triterpenes/chemistry* ; Reishi/chemistry* ; Biosynthetic Pathways ; Lanosterol

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

The aim of this study was to qualitatively and quantitatively detect coronavirus(CoV)in the feces of bats from Qinghua Cave,Yunnan Province,China.CoV was qualitatively tested with reverse transcription polymerase chain reaction(RT-PCR),and homology and genetic evolution were analyzed with bioinformatics software.The established reverse transcription real-time fluores-cence quantitative PCR(qRT-PCR)method was applied to CoV quantification in bat feces.The positivity rate of CoV in 306 fecal samples collected from the fulvous fruit bat(Rousettus leschenaultia)was 7.8%(24/306)according to RT-PCR.All 24 strains of CoV belonged to β-CoV,and showed a similarity of 86.8%-100.0%at the nucleotide level and 95.2%-100.0%at the amino acid level,with respect to other β-CoV sequences in the NCBI database.The positivity rate of CoV was 18.6%(57/306)according to qRT-PCR,a value higher than that according to RT-PCR(χ2=25.3,P<0.05).The mean β-CoV load was 1.3×103 copies/μL.In conclusion,the bats in Qinghua Cave,Yunnan Province,carried CoV belonging to β-CoV.The established qRT-PCR method achieved good sensitiv-ity,accuracy,reproducibility,and a higher detection rate than that of RT-PCR,and can be used for rapid detection of β-CoV in bats.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.