Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

Baihuasheshecao(Hedyotis diffusa) is a commonly used traditional Chinese medicine derived from the whole herb of H. diffusa and has been widely utilized in folk medicine. It possesses anti-tumor, antibacterial, and anti-inflammatory properties, making it one of the frequently used herbs in TCM clinical practice. However, Shuixiancao(H. corymbosa) and Xianhuaercao(H. tenelliflora), species of the same genus, are often used as substitutes for Baihuasheshecao. To substantiate the medicinal basis of Baihuasheshecao, this study systematically reviewed classical herbal texts and modern literature, examining its nomenclature, botanical origin, harvesting, processing, properties, meridian tropism, pharmacological effects, and clinical applications. The results indicate that Baihuasheshecao was initially recorded as "Shuixiancao" in Preface to the Indexes to the Great Chinese Botany(Zhi Wu Ming Shi Tu Kao). Based on its morphological characteristics and habitat description, it was identified as H. diffusa in the Rubiaceae family. Subsequent records predominantly refer to it as Baihuasheshecao as its official name. In most regions, Baihuasheshecao is recognized as the authentic medicinal material, distinct from Shuixiancao and Xianhuaercao. Baihuasheshecao is harvested in late summer and early autumn, and the dried whole plant, including its roots, is used medicinally. The standard processing method involves cutting. It is known for its effects in clearing heat, removing toxins, reducing swelling and pain, and promoting diuresis to resolve abscesses. Initially, it was mainly used for treating appendicitis, intestinal abscesses, and venomous snake bites, and later, it became a treatment for cancer. The excavation of its clinical value followed a process in which overseas Chinese introduced the herb from Chinese folk medicine to other countries. After its unique anti-cancer effects were recognized abroad, it was reintroduced to China and gradually became a crucial TCM for cancer treatment. The findings of this study help clarify the historical and contemporary uses of Baihuasheshecao, providing literature support and a scientific basis for its rational development and precise clinical application.
Humans ; China ; Drugs, Chinese Herbal/chemistry* ; Hedyotis/classification* ; Medicine, Chinese Traditional/history*

Coronavirus disease 2019 (COVID-19) is an acute infectious respiratory disease that has been prevalent since December 2019. Chinese medicine (CM) has demonstrated its unique advantages in the fight against COVID-19 in the areas of disease prevention, improvement of clinical symptoms, and control of disease progression. This review summarized the relevant material components of CM in the treatment of COVID-19 by searching the relevant literature and reports on CM in the treatment of COVID-19 and combining with the physiological and pathological characteristics of the novel coronavirus. On the basis of sorting out experimental methods in vivo and in vitro, the mechanism of herb action was further clarified in terms of inhibiting virus invasion and replication and improving related complications. The aim of the article is to explore the strengths and characteristics of CM in the treatment of COVID-19, and to provide a basis for the research and scientific, standardized treatment of COVID-19 with CM.
Humans ; Drugs, Chinese Herbal/pharmacology* ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/therapy* ; Medicine, Chinese Traditional/methods* ; Antiviral Agents/pharmacology* ; Animals

Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis* ; Animals ; Drug Resistant Epilepsy/drug therapy* ; Electroencephalography/methods* ; Rats ; Anticonvulsants/pharmacology* ; Neural Networks, Computer ; Male ; Humans ; Phenytoin/pharmacology* ; Adult ; Disease Models, Animal ; Female ; Rats, Sprague-Dawley ; Young Adult ; Convolutional Neural Networks

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

ObjectiveTo analyze the reported cases of infectious diseases across different tiers of public medical and healthcare institutions in Minhang District, Shanghai from 2013 to 2023, to investigate the status and changes in reported infectious diseases in this district from a temporal, etiological, and demographic perspectives, so as to provide a scientific basis for the construction of a hierarchica early-warning surveillance system under the grading diagnosis and treatment model in medical institutions, as well as for optimizing sentinel surveillance at facilities of different levels. MethodsA retrospective analysis was performed using surveillance data from the China Disease Prevention and Control Information System in Minhang District from 2013 to 2023. Reported infectious diseases were categorized into three categories based on transmission routes: respiratory infectious diseases, intestinal infectious diseases, and sexually transmitted and blood borne infectious diseases. According to the implementation phase of the grading diagnosis and treatment policy, the research time was divided into four time periods: 2013‒2016, 2017‒2019, 2020‒2022, and 2023. The distribution and temporal changes of reported cases of infectious diseases were compared across community health service centers (CHCs), secondary hospitals, tertiary grade-A hospitals and tertiary grade-B hospitals. Chi-square test was used for univariate analysis of differences in the number of reported cases. Quantitative data with normal distribution were analyzed using parametric tests, otherwise, Kruskal⁃Wallis H tests were used. ResultsThe proportions of total reported cases of infectious diseases in medical institutions at all levels in Minhang District, Shanghai from 2013 to 2023 were 10.66% in CHCs, 9.10% in secondary hospitals, 64.95% in tertiary grade-B hospitals, and 15.29% in tertiary grade-A hospitals, with an overall decline and then rebound trend in the reported cases. After the implementation of grading diagnosis and treatment policy, the number of reported cases in CHCs and secondary hospitals showed a trend of first decreasing and then increasing, while that in tertiary grade-B hospitals showed a steady decreasing trend and that in tertiary grade-A hospitals showed an increasing trend. In terms of the research periods divided above, a total of 10 392 cases were reported in 2013‒2016 (70.34% from tertiary grade-B hospitals and 12.59% from CHCs), including 2 922 cases of respiratory infectious diseases, 1 241 cases of intestinal infectious diseases, and 6 229 cases of sexually transmitted and blood-borne infectious diseases. Between 2017 and 2019, a total of 6 967 cases were reported (73.49% from tertiary grade-B hospitals and 11.84% from tertiary grade-A hospitals), including 2 983 cases of respiratory infectious diseases, 279 cases of intestinal infectious diseases, and 3 705 cases of sexually transmitted and blood-borne infectious diseases. Between 2020 and 2022, a total of 4 599 cases were reported (69.92% from tertiary grade-B hospitals and 24.57% from tertiary grade-A hospitals), including 1 627 cases of respiratory infectious diseases, 123 cases of intestinal infectious diseases, and 2 849 cases of sexually transmitted and blood-borne infectious diseases. In 2023, a total of 4 648 cases were reported (35.20% from tertiary grade-B hospitals and 27.50% from tertiary grade-A hospitals), including 3 165 cases of respiratory infectious diseases, 69 cases of intestinal infectious diseases, and 1 414 cases of sexually transmitted and blood-borne infectious diseases. The proportion of reported cases from tertiary grade-B hospitals was the highest in all the four research periods, but exhibited an obvious decrease in 2023. The differences in the reported cases of infectious diseases with different transmission routes among medical institutions at all levels were statistically significant (χ²=3 225.628, P<0.05). The differences in the mean age of patients among medical institutions at all levels were statistically significant (H=1 325.927, P<0.05). ConclusionThere are significant differences in the number of reported cases of infectious disease in the medical institutions at different levels. Tertiary grade-B hospitals have historically dominated the number of reported cases, but its share has declined recently. Whereas, CHCs and tertiary grade-A hospitals have played an increasingly important role in the surveillance and early warning of respiratory and intestinal infectious diseases. Therefore, it is recommended to leverage the strengths of grading diagnosis and treatment to establish targeted sentinel sites and deploy specialized teams tailored to the epidemiological characteristics of specific disease categories.

Objective To investigate the effect and mechanism of proteasome inhibitor MG132 on memory impairment induced by chronic hypoxia in mice.Methods(1)A hypoxic model of the mouse midbrain dopaminergic neuron cell line MN9D was established using a hypoxia workstation.To observe the effects of hypoxia on the expression of TH,Ub-K48 and Ub-K63,MN9D cells were divided into normoxia group and hypoxia(12 h,24 h and 48 h)groups.To observe the effects of MG132 on the expression of the above-mentioned proteins,MN9D cells were divided into normoxia group,hypoxia group and hypoxia + MG132(25,50,100,200 μmol/L)group.(2)A mouse model of memory impairment was established using a hypobaric chamber.To observe the effects of hypobaric hypoxia on the expression of TH,Ub-K48 and Ub-K63 in the substantia nigra compacta(SNc)of mice,thirty C57BL/6 mice were randomly and equally divided into normoxia group and hypobaric hypoxia(3 d and 21 d)groups,10 in each group.To observe the effects of MG132 on spatial memory impairment induced by hypobaric hypoxia,twenty-four C57BL/6 mice were randomly and equally divided into normoxia group,hypobaric hypoxia 21 d group and hypobaric hypoxia 21 d+MG132 group,8 in each group.(3)The protein expression levels of TH,Ub-K48,and Ub-K63 in MN9D cells which were either subjected to different durations of hypoxia treatment or pre-treated with MG132 prior to hypoxia treatment were detected using Western blotting(WB).The novel object recognition test was used to detect the memory function of mice.Immunofluorescence was used to detect the proportion of positive immunoreactive area of TH response in the SNc region.The expression levels of TH,Ub-K48,and Ub-K63 in the SNc region were detected by WB.Results(1)Compared with normoxia group,MN9D cells in hypoxia 24 h group showed increasing expression of Ub-K48 and Ub-K63(P<0.05),and decreasing expression of TH(P<0.05),and MN9D cells in all hypoxia groups showed increasing expression of Ub-K48/TH and Ub-K63/TH(P<0.05).Compared with hypoxia group,MN9D cells showed decreasing expression of Ub-K48/TH and Ub-K63/TH in hypoxia + MG132 100 umol/L group and hypoxia + MG132 200 umol/L group(P<0.05).(2)Compared with the mice in normoxia group,mice in 3 d and 21 d hypobaric hypoxia groups showed decreasing expression of TH(P<0.001),and increasing expression of Ub-K48/TH and Ub-K63/TH(P<0.05)in the SNc region.Compared with normoxia group,the mice in 21 d hypobaric hypoxia group showed a lower new object recognition index(P<0.01),and the proportion of positive immunoreactive area of TH response in the SNc region(P<0.05).Compared with 21 d hypobaric hypoxia group,the mice in hypobaric hypoxia 21 d+MG132 group showed a higher new object recognition index(P<0.01).Conclusion The proteasome inhibitor MG132 could alleviate the memory impairment induced by chronic hypoxia in mice,and its mechanism may be related to the inhibition of Ub-K63 and Ub-K48,which in turn upregulates expression of TH in dopaminergic neurons.