Objective To explore the application value of physical examination information annotation combined with artificial intelli-gence (AI) in CT diagnosis of rib fractures. Methods The clinical data of 100 patients with chest trauma who underwent rib CT examina-tion with physical examination information annotation were collected. The images were analyzed by two physicians in the department of radiology with different seniorities using four methods[diagnosed by physicians independently (group A),diagnosed by physicians combined with physical examination information annotation (group B),diagnosed by physicians under the assistance of AI (group C),and diagnosed by physicians combined with physical examination information annotation under the assistance of AI (group D)]. The diagnostic efficacy and diagnostic time of two radiologists using different methods for rib fractures were compared. Results The sensitivities of two radiologists with different seniorities in the diagnosis of rib fracture in the group A were lower than those in the groups B,C and D (P<0.05),but there was no significant difference in the sensitivity of rib fracture among groups B,C and D (P>0.05). The diagnostic sensitivity of resident physician in the group A was lower than that of the attending physicians (P<0.05),and there was no significant difference in the diagnostic sensitivity of rib fracture in the other groups between the two physicians (P>0.05). There was no statistically significant difference in the false-positive rate of rib fractures among groups between two physicians (P>0.05). There was statistically significant difference in the diagnostic time among groups between two physicians (P<0.05),among which group A took the longest diagnosis time and group C took the shortest. Conclusion The assistance of AI and conbinatin of physical examination information annotation can increase the sensitivity of the physician in the diagnosis of rib fractures,shorten the diagnostic time and improve the work efficiency.

OBJECTIVE: The present study evaluated the effects of deep acupuncture at Weizhong acupoint (BL40) on bladder function and brain activity in a rat model of overactive bladder (OAB), and investigated the possible mechanisms around the acupuncture area that initiate the effects of acupuncture. METHODS: Adult female Sprague-Dawley rats were randomly divided into six groups, comprising a control group, model group, group treated with deep acupuncture at BL40, group treated with shallow acupuncture at BL40, group treated with acupuncture at non-acupoint next to BL40, and group treated with acupuncture at Xuanzhong (GB39). Urodynamic evaluation was used to observe the urination, and functional magnetic resonance imaging was used to observe the brain activation. The mechanism of acupuncture at BL40 in regulating bladder function was explored by toluidine blue staining and enzyme-linked immunosorbent assay, and the mechanism was verified by stabilizing mast cells (MCs) or blocking tibial nerve. RESULTS: Deep acupuncture at BL40 significantly increased the intercontraction interval in OAB rats and enhanced the mean amplitude of low frequency fluctuation of primary motor cortex (M1), periaquaductal gray matter (PAG), and pontine micturition center (PMC). It also increased the zero-lag functional connectivity between M1 and PAG and between PAG and PMC. Shallow acupuncture at BL40 and acupuncture at non-acupoint or GB39 had no effect on these indexes. Further studies suggested that deep acupuncture at BL40 increased the number and degranulation rate of MCs as well as the contents of 5-hydroxytryptamine, substance P, and histamine in the tissues around BL40. Blocking the tibial nerve by lidocaine injection or inhibiting MC degranulation by sodium cromoglycate injection obstructed the effects of acupuncture on restoring urinary function and modulating brain activation in OAB rats. CONCLUSION Deep acupuncture at BL40 may be more effective for inhibiting OAB by promoting degranulation of MCs around the acupoint and stimulating tibial nerve, thereby regulating the activation of the brain area that controls the lower urinary tract. Please cite this article as: Liu X, Zhang CY, Du XY, Li SS, Wang YQ, Zheng Y, Deng HZ, Fang XQ, Li JY, Wang ZQ, Xu SF, Mi YQ. Acupuncture at Weizhong (BL40) attenuates acetic acid-induced overactive bladder in rats by regulating brain neural activity through the modulation of mast cells and tibial nerves. J Integr Med. 2025; 23(1): 46-55.
Animals ; Urinary Bladder, Overactive/physiopathology* ; Mast Cells/physiology* ; Rats, Sprague-Dawley ; Female ; Acupuncture Therapy ; Acupuncture Points ; Rats ; Brain/physiopathology* ; Tibial Nerve/physiopathology* ; Acetic Acid ; Urinary Bladder/physiopathology*

Objective To explore the application value of physical examination information annotation combined with artificial intelli-gence (AI) in CT diagnosis of rib fractures. Methods The clinical data of 100 patients with chest trauma who underwent rib CT examina-tion with physical examination information annotation were collected. The images were analyzed by two physicians in the department of radiology with different seniorities using four methods[diagnosed by physicians independently (group A),diagnosed by physicians combined with physical examination information annotation (group B),diagnosed by physicians under the assistance of AI (group C),and diagnosed by physicians combined with physical examination information annotation under the assistance of AI (group D)]. The diagnostic efficacy and diagnostic time of two radiologists using different methods for rib fractures were compared. Results The sensitivities of two radiologists with different seniorities in the diagnosis of rib fracture in the group A were lower than those in the groups B,C and D (P<0.05),but there was no significant difference in the sensitivity of rib fracture among groups B,C and D (P>0.05). The diagnostic sensitivity of resident physician in the group A was lower than that of the attending physicians (P<0.05),and there was no significant difference in the diagnostic sensitivity of rib fracture in the other groups between the two physicians (P>0.05). There was no statistically significant difference in the false-positive rate of rib fractures among groups between two physicians (P>0.05). There was statistically significant difference in the diagnostic time among groups between two physicians (P<0.05),among which group A took the longest diagnosis time and group C took the shortest. Conclusion The assistance of AI and conbinatin of physical examination information annotation can increase the sensitivity of the physician in the diagnosis of rib fractures,shorten the diagnostic time and improve the work efficiency.

Objective To investigate the association of insulin resistance(IR)and its related indices,including triacylglycerol-glucose(TyG)index and metabolic score of insulin resistance(Mets-IR),with the occurrence of early neurological deterioration(END)in patients with branch atheromatous disease(BAD),and develop a risk prediction model based on these factors.Methods A total of 189 BAD patients were consecutively recruited from the Department of Neurology of the Second Affiliated Hospital of Zhengzhou University between March 2020 and August 2024.Based on the occurrence of END within 7 d after admission,the participants were stratified into END(75 cases)and non-END(114 cases)groups.Demographic characteristics,clinical parameters,TyG index and Mets-IR values were systematically collected and analyzed.Multivariate logistic regression analysis was performed to identify independent risk factors for END in BAD-related stroke.Receiver operating characteristic curve(ROC)analysis was subsequently conducted to evaluate the predictive performance of significant variables,followed by construction of a nomogram prediction model.Results The END group exhibited significantly elevated fasting blood glucose[6.47(5.74,7.86)mmol/L vs 5.83(5.14,6.70)mmol/L]and triacylglycerol[1.65(1.21,2.04)mmol/L vs 1.27(0.99,1.57)mmol/L]levels,higher body mass index[25.02(23.88,26.67)kg/m2 vs 23.71(22.66,25.27)kg/m2]and TyG index(9.03±0.41 vs 8.71±0.45),and increased Mets-IR(39.98±4.23 vs 36.85±4.38)and NIHSS score[5.00(3.00,7.00)vs 3.00(2.00,5.00)]at admission when compared with the non-END group(P＜0.05).Multivariate logistic regression analysis showed that high TyG index(OR=3.751,95％CI:1.592-9.202,P＜0.01),Mets-IR(OR=1.146,95％CI:1.049-1.252,P＜0.01),and NIHSS score at admission(OR=1.279,95％CI:1.128-1.451,P＜0.01)were risk factors for the occurrence of END in BAD patients(P＜0.05).ROC curve indicated that the AUC value of TyG index,Mets-IR,and NIHSS score at admission in predicting END occurrence was 0.698(95％CI:0.623-0.774,P＜0.01),0.698(95％CI:0.620-0.775,P＜0.01),and 0.666(95％CI:0.586-0.745,P＜0.01),respectively.The nomogram prediction model based on these factors demonstrated significant clinical benefits by decision curve analysis and goodness of fit in internal calibration analysis.Conclusion IR shows significant association with END in BAD patients.The IR related indices,TyG index and Mets-IR,have certain predictive efficiency for occurrence and progression of END.

The study was aimed at identifying the diversity of tick species in selected areas of Qinghai,to analyze the genetic differentiation characteristics of tick-borne spotted fever group rickettsiae(SFGR),and to provide the theoretical basis for SFGR prevention and control in the region.The 16S rRNA gene was used for molecular biological identification of 446 collected tick samples,and the infection characteristics of SFGR in tick samples were determined according to the SFGR outer membrane protein A(ompA)gene.Haplotype analysis,phylogenetic tree construction,and estimation of differentiation times for SFGR were conducted in DNASP v6,IQ-tree v2.2.0,and BEAST v2.7.4 software.The obtained 446 tick samples belonged to three categories:(1)Haemaphy-salis spp.,including Haemaphysalis qinghaiensis(n=192)and H.danieli(n=37);(2)Dermacentor spp.,including Dermacentor ever-estianus(n=121),D.nuttalli(n=55),and D.silvarum(n=36);and(3)Hyalomma marginatum(n=5).Rickettsia raoultii was de-tected in D.everestianus,D.silvarum,D.nuttalli,H.qinghaiensis,and H.danieli,with infection rates of 95.9%,80.6%,69.1%,4.1%,and 2.7%,respectively.R.sibirica subsp.sibirica BJ-90 was found only in D.silvarum and D.nuttalli,with infection rates of 5.6%and 1.8%,respectively.The Candidatus R.gannanii F107 was found in H.danieli and H.qinghaiensis,with infection rates of 16.2%and 7.8%,respectively.Ca.R.hongyuanensis was detected only in H.qinghaiensis,with a prevalence of 16.3%.The prevalence of R.aeschlimannii was 20%and 2.7%in Hy.marginatum and H.danieli,respectively.Haplotype and nucleotide polymorphism analy-ses revealed 13 haplotypes in R.raoultii,with haplotype H13 as the dominant haplotype(42/192);seven haplotypes in Ca.R.ganna-nii F107,with haplotype H4 as the dominant haplotype(4/18);and three haplotypes in Ca.R.hongyuanensis,with haplotype H1 as the dominant haplotype(11/13).The phylogenetic tree indicated that the sequences of R.raoultii in selected areas of Qinghai and R.rhipicephali clustered into one branch;Ca.R.hongyuanensis and Ca.R.gannanii F107 clustered into one branch;and R.sibirica subsp.sibirica BJ-90 clustered into one branch with R.sibirica.Estimates of differentiation time revealed that the mean differentiation time for the six Rickettsia was approximately 2 000 Mya(95%CI:1 999.08-2 001.02 Mya).The tick species distributed in selected ar-eas of Qinghai are diverse,and this study provides the first report of Hy.marginatum in Qinghai Province.SFGR significantly varied in prevalence among tick species and showed high genetic diversity.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Heart failure(HF)is a cardiovascular disease with a high prevalence and mortality rate worldwide,and despite the widespread use of existing drugs,device intervetions and surgical procedures,the clinical outcomes are still unsatisfactory.The exploration of new methods to treat HF is still an urgent problem.Gene therapy provides a new therapeutic strategy for HF by targeting the regulation of pathogenic genes.This article systematically reviewed the delivery system optimization,key targets and clinical translational challenges of gene therapy for HF,aiming to provide a theoretical basis for the optimization of treatment strategies.

The neurophysiological mechanisms by which exercise improves cognitive function have not been fully elucidated. A comprehensive and systematic review of current domestic and international neurophysiological evidence on exercise improving cognitive function was conducted from multiple perspectives. At the molecular level, exercise promotes nerve cell regeneration and synaptogenesis and maintains cellular development and homeostasis through the modulation of a variety of neurotrophic factors, receptor activity, neuropeptides, and monoamine neurotransmitters, and by decreasing the levels of inflammatory factors and other modulators of neuroplasticity. At the cellular level, exercise enhances neural activation and control and improves brain structure through nerve regeneration, synaptogenesis, improved glial cell function and angiogenesis. At the structural level of the brain, exercise promotes cognitive function by affecting white and gray matter volumes, neural activation and brain region connectivity, as well as increasing cerebral blood flow. This review elucidates how exercise improves the internal environment at the molecular level, promotes cell regeneration and functional differentiation, and enhances the brain structure and neural efficiency. It provides a comprehensive, multi-dimensional explanation of the neurophysiological mechanisms through which exercise promotes cognitive function.
Animals ; Humans ; Brain/physiology* ; Cognition/physiology* ; Exercise/physiology* ; Nerve Regeneration/physiology* ; Neuronal Plasticity/physiology*

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control