" Lijie and yellowish sweating" originates from the chapter on stroke and arthralgia diseases in Synopsis of Golden Chamber. Later generations typically interpret it as yellow fluid oozing from painful joints, a characteristic manifestation of arthralgia. In Western medicine, Lijie corresponds to diseases such as gouty arthritis, with its primary clinical manifestations being redness, swelling, heat, and painful joints, most often without yellow fluid discharge. Therefore, the interpretation of " Lijie and yellowish sweating" contradicts the clinical manifestations often observed in this disease. Thus, this article reinterprets the meaning of " Lijie and yellowish sweating" from the pathogenesis of " sweat exposure to water, as if water harms the heart" , combined with the viewpoints of other medical practitioners. Determining the meaning of " yellowish sweating" is crucial for understanding the pathogenesis of arthralgia and clarifying the relationship between arthralgia and yellowish sweating. ZHANG Zhongjing mentioned arthralgia and " yellowish sweating" together, not to differentiate between the two diseases but to emphasize the common pathogenesis of the two, namely, the cold and dampness injuring the heart, blood, and vessels. This paper proposes a new explanation of " Lijie and yellowish sweating" , which suggests that " yellowish sweating" is not confined to the joints but can be found all over the body. The pathogenesis of " Lijie and yellowish sweating" lies in the insufficiency of the liver and kidney and exogenous water dampness, leading to disharmony between nutrient qi and defensive qi and between yin and yang. Primary treatment should harmonize yingfen and weifen, as well as tonify and replenish the liver and kidney. The clinical selection of medicines can be considered Guizhi Decotion, a type of formula. The pathogenesis of " Lijie and yellowish sweating" is complex, and clinical treatment should be comprehensively considered to achieve the best therapeutic effect.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

AIM: To evaluate the performance of three distinct large language models(LLM), including GPT-3.5, GPT-4, and PaLM2, in responding to queries within the field of ophthalmology, and to compare their performance with three different levels of medical professionals: medical undergraduates, master of medicine, and attending physicians.METHODS: A total of 100 ophthalmic multiple-choice tests, which covered ophthalmic basic knowledge, clinical knowledge, ophthalmic examination and diagnostic methods, and treatment for ocular disease, were conducted on three different kinds of LLM and three different levels of medical professionals(9 undergraduates, 6 postgraduates and 3 attending physicians), respectively. The performance of LLM was comprehensively evaluated from the aspects of mean scores, consistency and confidence of response, and it was compared with human.RESULTS: Notably, each LLM surpassed the average performance of undergraduate medical students(GPT-4:56, GPT-3.5:42, PaLM2:47, undergraduate students:40). Specifically, performance of GPT-3.5 and PaLM2 was slightly lower than those of master's students(51), while GPT-4 exhibited a performance comparable to attending physicians(62). Furthermore, GPT-4 showed significantly higher response consistency and self-confidence compared with GPT-3.5 and PaLM2.CONCLUSION: LLM represented by GPT-4 performs well in the field of ophthalmology, and the LLM model can provide clinical decision-making and teaching aids for clinicians and medical education.

Objective:To investigate the rates of low disease activity and clinical remission in patients with systemic lupus erythematosus(SLE)in a real-world setting,and to analyze the related factors of low disease activity and clinical remission.Methods:One thousand patients with SLE were enrolled from 11 teaching hospitals.Demographic,clinical and laboratory data,as well as treatment regimes were collec-ted by self-completed questionnaire.The rates of low disease activity and remission were calculated based on the lupus low disease activity state(LLDAS)and definitions of remission in SLE(DORIS).Charac-teristics of patients with LLDAS and DORIS were analyzed.Multivariate Logistic regression analysis was used to evaluate the related factors of LLDAS and DORIS remission.Results:20.7％of patients met the criteria of LLDAS,while 10.4％of patients achieved remission defined by DORIS.Patients who met LLDAS or DORIS remission had significantly higher proportion of patients with high income and longer disease duration,compared with non-remission group.Moreover,the rates of anemia,creatinine eleva-tion,increased erythrocyte sedimentation rate(ESR)and hypoalbuminemia was significantly lower in the LLDAS or DORIS group than in the non-remission group.Patients who received hydroxychloroquine for more than 12 months or immunosuppressant therapy for no less than 6 months earned higher rates of LLDAS and DORIS remission.The results of Logistic regression analysis showed that increased ESR,positive anti-dsDNA antibodies,low level of complement(C3 and C4),proteinuria,low household in-come were negatively related with LLDAS and DORIS remission.However,hydroxychloroquine usage for longer than 12 months were positively related with LLDAS and DORIS remission.Conclusion:LLDAS and DORIS remission of SLE patients remain to be improved.Treatment-to-target strategy and standar-dized application of hydroxychloroquine and immunosuppressants in SLE are recommended.

Objective To study the brain functional connectivity(FC)changes in patients with normal tension glau-coma(NTG)and healthy volunteers using FC technique of resting-state functional magnetic resonance imaging(rs-fMRI)based on V1 region seed point(ROI),so as to explore the pathogenesis and early diagnosis of NTG.Methods Fourteen NTG patients(NTG group)who met the inclusion criteria and 14 healthy controls(HCs group)were enrolled.The clinical data of all subjects were collected,and rs-fMRI was performed in both groups.The magnetic resonance data was pre-pro-cessed by software,and bilateral A1 regions were taken as the ROI to analyze their correction with the whole brain voxel time series and obtain the FC value between the ROI and the whole brain by comparison of FC values in resting state be-tween the groups.Pearson correlation analysis was used to explore the relationship between FC value in the brain regions with significant differences with the ROI and clinical variables in the NTG group.Results Compared with the subjects in the HCs group,there were no statistically significant differences in age,gender,body weight,cup-disc ratio and 24 h mean intraocular pressure of patients in the NTG group(all P＞0.05),and there were statistically significant differences in the best corrected visual acuity(BCVA)of both eyes and peripapillary retinal nerve fiber layer thickness(RNFLT)(all P＜0.05).The Pearson correlation analysis showed that FC value of the brain regions with abnormal FC to V1 region were cor-related with RNFLT in the NTG group(P＜0.05).ROI1-left superior frontal gyrus,ROI1-right superior frontal gyrus,ROI2-left cingulate gyrus and ROI2-right middle frontal gyrus were significantly positively correlated with RNFLT(all P＜0.05).Compared with the HCs group,the brain regions with reduced FC to the right ROI in the NTG group were the left superior frontal gyrus and right superior frontal gyrus;the brain regions with reduced FC to the left ROI were the left cingulate gyrus and right middle frontal gyrus.Conclusion Compared to healthy individuals,NTG patients have significant changes in the functional connections between certain specific brain regions and V1 region,including bilateral superior frontal gyrus,left cingulate gyrus,and middle frontal gyrus.The changes in brain functional activity may be caused by visual dysfunction caused by NTG,leading to functional impairment of the visual and cognitive emotion processing brain regions,which may be one of the potential neuropathological mechanisms in NTG patients.

Background and purpose:For patients with human epidermal growth factor receptor 2(HER2)-positive metastatic breast cancer,trastuzumab treatment can prolong the overall survival and significantly improve the prognosis of patients.However,the reference original research trastuzumab(Herceptin?)is more expensive.Biosimilars have comparable efficacy and safety profiles while increasing patient access to treatment.This clinical trial aimed to evaluate the efficacy,pharmacokinetics,safety and immunogenicity of the trastuzumab biosimilar AK-HER2 compared to trastuzumab(Herceptin?)in patients with HER2-positive metastatic breast cancer.Methods:This multi-center,randomised,double-blind phase Ⅲ clinical trial was conducted in 43 subcenters in China.This study complied with the research protocol,the ethical principles stated in the Declaration of Helsinki and the quality management standards for drug clinical trials.It was approved by the hospital's medical ethics committee.The clinical trial registration agency is the State Food and Drug Administration(clinical trial approval number:2015L04224;clinical trial registration number:CTR20170516).Written informed consent was obtained from subjects before enrollment.Enrolled patients were randomly assigned to the AK-HER2 group and the control group,respectively receiving AK-HER2 or trastuzumab(initial loading dose 8 mg/kg,maintenance dose 6 mg/kg,every 3 weeks as a treatment cycle,total treatment time is 16 cycles)in combination with docetaxel(75 mg/m2,treatment duration is at least 9 cycles).The primary endpoint of this clinical trial was the objective response rate(ORR9)between the AK-HER2 group and the control group in the 9th cycle.Secondary efficacy endpoints included ORR16,disease control rate(DCR),clinical benefit rate(CBR),progression-free survival(PFS)and 1-year survival rate.In this study,100 subjects(AK-HER2 group to control group=1:1)were randomly selected for blood sample collection after the 6th cycle of medication,The collection time points were 45 minutes after infusion(the end of administration),4,8,24,72,120,168,336,and 504 hours after the end of administration.After collection,blood samples were analyzed by PK parameter set(PKPS).Other evaluation parameters included safety and immunogenicity assessment.Results:A total of 550 patients with HER2-positive metastatic breast cancer were enrolled in this clinical trial between Sep.2017 and Mar.2021.In the AK-HER2 group(n=237),129 subjects in the experimental group achieved complete response(CR)or partial response(PR),and the ORR9 was 54.4%.There were 134 subjects in the control group(n=241)who achieved CR or PR,and the ORR9 was 55.6%.The ORR9 ratio between the AK-HER2 group and the control group was 97.9%[90%confidence interval(CI):85.4%-112.2%,P=0.784],which was not statistically significant.In all secondary efficacy endpoints,no statistically significant differences were observed between the two groups.We conducted a mean ratio analysis of pharmacokinetics(PK)parameters between the AK-HER2 group and the control group,and the results suggested that the pharmacokinetic characteristics of the two drugs are similar.The incidence of treatment emergent adverse event(TEAE)leading to drug reduction or suspension during trastuzumab treatment was 3.6%(10 cases)in the AK-HER2 group and 8.1%(22 cases)in the control group.There was statistically significant difference between the two groups(P=0.027).The incidence rate was significantly lower in the AK-HER2 group than in the control group,and there was no statistically significant difference among the other groups.The differences in the positive rates of anti-drug antibodies(ADA)and neutralizing antibodies(NAB)between groups were of no statistical significance(P=0.385 and P=0.752).Conclusion:In patients with HER2-positive metastatic breast cancer,AK-HER2 was comparable to the trastuzumab(Herceptin?)in terms of drug efficacy,pharmacokinetics,safety and immunogenicity.

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.