Evidence mapping was used to systematically analyze the clinical research evidence of oral Chinese patent medicines in the treatment of intracerebral hemorrhage(ICH), thus revealing the distribution and quality of evidence in this field. The relevant articles were retrieved from CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Cochrane Library, and Web of Science from inception to July 5, 2024. The distribution characteristics of evidence were presented numerically and graphically. A total of 35 Chinese patent medicines were identified, involving 261 articles. The basic information of the 35 Chinese patent medicines, publication trend, traditional Chinese medicine(TCM) syndromes, interventions, and outcome indicators were compared and analyzed, and the methodological quality of the articles was evaluated. The results indicated that the clinical scope of Chinese patent medicines in the treatment of ICH was broad. However, the available studies inadequately emphasized the advantages and characteristics of TCM, lacked the safety information and the standards for evaluating outcome indicators, and paid insufficient attention to cognitive ability and neuropsychology. In addition, these articles demonstrated low quality. It is recommended that follow-up clinical research should be standardized and highlight the characteristics of TCM. In the analysis of outcome indicators, TCM syndrome evaluation should be taken as an important outcome indicator, and the evaluation criteria should be unified. Moreover, more attention should be paid to patients' cognitive ability and neuropsychology. The holder of marketing license of Chinese patent medicines should standardize the clinical position and improve the safety information in the medicine instructions according to the relevant requirements of the National Medical Products Administration. Additionally, the proportion of Chinese patent medicines in the category A list of medical insurance should be increased, and the limited medical resources should be rationally allocated.
Cerebral Hemorrhage/drug therapy* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Nonprescription Drugs/administration & dosage* ; Administration, Oral

Colorectal cancer(CRC) is a common malignant tumor worldwide. Due to the treatment intolerance and side effects, CRC rank the top among various cancers regarding the incidence and mortality rates. Therefore, exploring new therapies is of great significance for the treatment of CRC. Aerobic glycolysis(AEG) plays an important role in the microenvironment formation, proliferation, metastasis, and recurrence of CRC and other tumor cells. It has been confirmed that intervening in the AEG pathway can effectively curb CRC. The active ingredients and compound prescriptions of traditional Chinese medicine(TCM) can effectively inhibit the proliferation, metastasis, and drug resistance and regulate the apoptosis of tumor cells by modulating AEG-associated transport proteins [eg, glucose transporters(GLUT)], key enzymes [hexokinase(HK) and phosphofructokinase(PFK)], key genes [hypoxia-inducible factor 1(HIF-1) and oncogene(c-Myc)], and signaling pathways(MET/PI3K/Akt/mTOR). Accordingly, they can treat CRC, reduce the recurrence, and improve the prognosis of CRC. Although AEG plays a key role in the development and progression of CRC, the specific mechanisms are not yet fully understood. Therefore, this article delves into the intrinsic connection of the targets and mechanisms of the AEG pathway with CRC from the perspective of tumor cell glycolysis and explores how active ingredients(oxymatrine, kaempferol, and dioscin) and compound prescriptions(Quxie Capsules, Jiedu Sangen Decoction, and Xianlian Jiedu Prescription) of TCM treat CRC by intervening in the AEG pathway. Additionally, this article explores the shortcomings in the current research, aiming to provide reliable targets and a theoretical basis for treating CRC with TCM.
Humans ; Colorectal Neoplasms/genetics* ; Drugs, Chinese Herbal/therapeutic use* ; Glycolysis/drug effects* ; Animals ; Medicine, Chinese Traditional ; Signal Transduction/drug effects*

OBJECTIVES: To investigate the clinical features and gene mutation characteristics of combined oxidative phosphorylation deficiency type 7 (COXPD7) caused by mutations in the C12orf65 gene, and to enhance the awareness of this disease. METHODS: A child diagnosed with COXPD7 in the Department of Neurology, Children's Hospital Affiliated to Zhengzhou University in 2021 was included, along with 10 patients reported in the literature. All subjects were analyzed for their genotypes and clinical phenotypes. RESULTS: A total of 11 patients with COXPD7 were included, comprising 1 reported in this study and 10 from the literature. Among the 11 patients, 9 had homozygous mutations in the C12orf65 gene, while 2 had compound heterozygous mutations, which were identified as frameshift or nonsense mutations. The age of onset ranged from 1 day to 2 years, and clinical manifestations included optic nerve atrophy and delays in intellectual and motor development. Eight patients exhibited external ophthalmoplegia, and five patients displayed spastic paralysis. Cranial magnetic resonance imaging revealed optic nerve atrophy in all 11 patients, abnormal brainstem signals in 10 patients, and a lactate peak on brainstem magnetic resonance spectroscopy scans in 3 patients. CONCLUSIONS COXPD7 associated with the C12orf65 gene results from homozygous or compound heterozygous mutations, with primary clinical manifestations of optic nerve atrophy and delays in intellectual and motor development. Some patients may also present with spastic paralysis or external ophthalmoplegia. Cranial imaging reveals symmetrical abnormal signals in bilateral basal ganglia and brainstem, and a lactate peak is observed on brainstem magnetic resonance spectroscopy scans.
Child, Preschool ; Female ; Humans ; Infant ; Male ; Mitochondrial Diseases/genetics* ; Mitochondrial Proteins/genetics* ; Mutation ; Oxidative Phosphorylation ; Infant, Newborn

Neuropathic pain, a debilitating condition caused by dysfunction of the somatosensory nervous system, remains difficult to treat due to limited understanding of its molecular mechanisms. Bioinformatics analysis identified cerebellin 2 (CBLN2) as highly enriched in human and murine proprioceptive and nociceptive neurons. We found that CBLN2 expression is persistently upregulated in dorsal root ganglia (DRG) following spinal nerve ligation (SNL) in mice. In addition, transcription factor SOX11 binds to 12 cis-regulatory elements within the Cbln2 promoter to enhance its transcription. SNL also induced SOX11 upregulation, with SOX11 and CBLN2 co-localized in nociceptive neurons. The siRNA-mediated knockdown of Sox11 or Cbln2 attenuated SNL-induced mechanical allodynia and thermal hyperalgesia. High-throughput sequencing of DRG following intrathecal injection of CBLN2 revealed widespread gene expression changes, including upregulation of numerous NF-κB downstream targets. Consistently, CBLN2 activated NF-κB signaling, and inhibition with pyrrolidine dithiocarbamate reduced CBLN2-induced pain hypersensitivity, proinflammatory cytokines and chemokines production, and neuronal hyperexcitability. Together, these findings identified the SOX11/CBLN2/NF-κB axis as a critical mediator of neuropathic pain and a promising target for therapeutic intervention.
Animals ; Neuralgia/metabolism* ; Ganglia, Spinal/metabolism* ; Up-Regulation ; Mice ; NF-kappa B/metabolism* ; SOXC Transcription Factors/genetics* ; Male ; Neuroinflammatory Diseases/metabolism* ; Mice, Inbred C57BL ; Nerve Tissue Proteins/genetics* ; Hyperalgesia/metabolism* ; Signal Transduction ; Spinal Nerves

OBJECTIVE: miR-34c-3p is down-regulated in nasopharyngeal carcinoma (NPC). The biological role of miR-34c-3p in NPC and its underlying mechanisms are unknown and were explored in this study. METHODS: Flow cytometry and immunohistochemical staining were employed to detect cluster of differentiation 86 (CD86) and cluster of differentiation 206 (CD206) expression; quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were employed to examine mRNA expression and protein levels; cell counting kit-8 (CCK8) and transwell assays were employed to assess cell proliferation, migration, and invasion; and hematoxylin-eosin (HE) staining was employed to assess pathological changes in tumor tissues. RESULTS: Our results revealed that the miR-34c-3p mimic markedly inhibited M2 polarization of macrophages by targeting SLC7A11, and M2 macrophages transfected with the miR-34c-3p mimic inhibited the proliferation, migration, and invasion of NPC cells. The in vivo experiments further confirmed that miR-34c-3p mimics blocked tumor growth and reduced inflammatory infiltration in tumor tissues. CONCLUSION This study provides novel insights into the pathogenesis of NPC and a new treatment strategy.
MicroRNAs/metabolism* ; Nasopharyngeal Carcinoma/genetics* ; Humans ; Animals ; Nasopharyngeal Neoplasms/genetics* ; Macrophages/physiology* ; Cell Line, Tumor ; Mice ; Cell Proliferation ; Mice, Inbred BALB C ; Cell Movement ; Male ; Gene Expression Regulation, Neoplastic ; Mice, Nude ; Female

Objective:To investigate the application value of optical coherence tomography (OCT) and intravascular ultrasound (IVUS) in evaluating flow diverter (FD) apposition and endothelialization in aneurysm animal models, and analyze the effect of incomplete stent apposition (ISA) on aneurysm lumen healing and stent endothelialization.Methods:Lateral common carotid artery aneurysm models in swines were established by surgical method and then FD was implanted. Immediately after surgery, OCT and IVUS were used to evaluate the locations and degrees of ISA, and difference between these 2 methods in evaluating FD apposition was compared. DSA was performed at 12 weeks after surgery to evaluate the aneurysm occlusion (Kamran grading) and stent patency. OCT and IVUS were used again to observe the stent endothelial situation; by comparing with histopathologic results, effect of ISA on aneurysm healing and stent endothelialization was analyzed.Results:Lateral common carotid artery aneurysm models in 6 swines were established, and 6 Tubridge FDs were successfully implanted. Compared with IVUS (3 stents, 4 locus), OCT could detect more ISA (6 stents, 14 locus); and the vascular diameter change area (7 locus), aneurysm neck area (4 locus) and the head and tail of FD (3 locus) were the main sites of FD malapposition; average distance between stent wire and vessel wall was (560.14±101.48) μm. At 12 weeks after surgery, DSA showed that 1 patient had a little residual contrast agent at the aneurysm neck (Kamran grading 3), and the remaining 5 had complete aneurysm occlusion (Kamran grading 4). One FD had moderate lumen stenosis, and the other 5 FDs had lumen patency. OCT indicated mostly disappeared acute ISA; ISA proportion decreased to 21.4 % (3/14), including 2 in the aneurysm neck and 1 in the partial stent. Histopathological results showed bare stent woven silk, without obvious endothelial coverage; in one FD with luminal stenosis, intimal hyperplasia was mainly composed of vascular smooth muscle cells.Conclusion:In carotid artery aneurysm model with FD implantation, OCT can detect more ISA than IVUS; most acute ISA have good outcome at 12 th week of follow-up, while severe ISA can cause delayed FD endothelialization and delayed aneurysm occlusion.

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Purpose::Traumatic brain injury (TBI), currently a major global public health problem, imposes a significant economic burden on society and families. We aimed to quantify and predict the incidence and severity of TBI by analyzing its incidence, prevalence, and years lived with disability (YLDs). The epidemiological changes in TBI from 1990 to 2019 were described and updated to provide a reference for developing prevention, treatment, and incidence-reducing measures for TBI.Methods::A secondary analysis was performed on the incidence, prevalence, and YLDs of TBI by sex, age group, and region ( n =21,204 countries and territories) between 1990 and 2019 using the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Proportions in the age-standardized incidence rate due to underlying causes of TBI and proportions of minor and moderate or severe TBI were also reported. Results::In 2019, there were 27.16 million (95% uncertainty intervals ( UI): 23.36 -31.42) new cases of TBI worldwide, with age-standardized incidence and prevalence rates of 346 per 100,000 population (95% UI: 298 -401) and 599 per 100,000 population (95% UI: 573 -627), respectively. From 1990 to 2019, there were no significant trends in global age-standardized incidence (estimated annual percentage changes: -0.11%, 95% UI: -0.18% --0.04%) or prevalence (estimated annual percentage changes: 0.01%, 95% UI: -0.04% -0.06%). TBI caused 7.08 million (95% UI: 5.00 -9.59) YLDs in 2019, with age-standardized rates of 86.5 per 100,000 population (95% UI: 61.1 -117.2). In 2019, the countries with higher incidence rates were mainly distributed in Central Europe, Eastern Europe, and Australia. The 2019 global age-standardized incidence rate was higher in males than in females. The 2019 global incidence of moderate and severe TBI was 182.7 per 100,000 population, accounting for 52.8% of all TBI, with falls and road traffic injuries being the main causes in most regions. Conclusions::The incidence of moderate and severe TBI was slightly higher in 2019, and TBI still accounts for a significant portion of the global injury burden. The likelihood of moderate to severe TBI and the trend of major injury under each injury cause from 1990 to 2019 and the characteristics of injury mechanisms in each age group are presented, providing a basis for further research on injury causes in each age group and the future establishment of corresponding policies and protective measures.

Objective To develop a deep learning model for automated age estimation based on 3D CT reconstructed images of Han population in western China,and evaluate its feasibility and reliability.Methods The retrospective pelvic CT imaging data of 1 200 samples(600 males and 600 females)aged 20.0 to 80.0 years in western China were collected and reconstructed into 3D virtual bone models.The images of the ischial tuberosity feature region were extracted to create sex-specific and left/right site-specific sample libraries.Using the ResNet34 model,500 samples of different sexes were randomly selected as training and verification set,the remaining samples were used as testing set.Initialization and transfer learning were used to train images that distinguish sex and left/right site.Mean absolute error(MAE)and root mean square error(RMSE)were used as primary indicators to evaluate the model.Results Prediction results varied between sexes,with bilateral models outperformed left/right unilateral ones,and transfer learning models showed superior performance over initial models.In the prediction results of bilateral transfer learning models,the male MAE was 7.74 years and RMSE was 9.73 years,the female MAE was 6.27 years and RMSE was 7.82 years,and the mixed sexes MAE was 6.64 years and RMSE was 8.43 years.Conclusion The skeletal age estimation model,utilizing is-chial tuberosity images of Han population in western China and employing the ResNet34 combined with transfer learning,can effectively estimate adult ischium age.