As a non-invasive physiological indicator,electroencephalography signal provides an objective assessment of psychological stress levels among nursing staff in major public health emergencies,offering a scientific basis for targeted psychological interventions while overcoming the limitations of subjective bias inherent in traditional questionnaire-based methods.A psychological stress classification model based on bidirectional long short-term memory and attention mechanism is proposed to classify the psychological stress of clinical nurses more effectively by analyzing their electroencephalography signals.Experimental results show that the proposed model exhibits better classification performance than the traditional long short-term memory model on the DREAMER dataset,the Feeling Emotions dataset and the self-built dataset.This study provides a novel approach for assessing psychological stress,which is helpful to improve the pertinence and effectiveness of clinical nursing work.

With the continuous development of genomics and precision medicine,targeted therapy and immunotherapy targeting biomarkers have ush-ered in a new era of anti-tumor therapy.However,due to the heterogeneity of tumor cells and the variability of tumor microenvironment,there are still significant differences in response to the same drug even in patient populations with the same bio-marker enrichment.By combining omics data with drug sensitivity algorithms,the response of anti-tu-mor drugs can be predicted and transformed into personalized diagnosis and treatment strategies re-quired for precision medicine,which is expected to improve the effectiveness of anti-tumor drugs in clinical treatment.Currently,machine learning is one of the commonly used modeling algorithms for predicting the response of anti-tumor drugs.How-ever,due to differences in input data and algorithm construction methods,there is currently a lack of comprehensive literature review in this field.There-fore,this article provides a review of machine learning algorithms for predicting anti-tumor drug responses,summarizing publicly available cell ge-nome characterization datasets,machine learning algorithms,and evaluation indicators in drug re-sponse prediction,as well as the current situation and challenges faced in clinical applications,in or-der to provide methodological references for the main research problems and potential solutions of machine learning algorithms in the field of drug re-sponse prediction.

Purpose To explore the clinicopathological features of EBV-positive nodal T-and NK-cell lymphoma.Methods Clinical and pathological data of 5 cases were collected.The expression of CD3,CD56,TIA-1,Granzyme B and other markers were detected by immunohistochemistry.The expression of EBER was detected by in situ hybrid-ization.The gene rearrangement and clonality were analyzed by PCR and polyacrylamide gel electrophoresis.The litera-tures were reviewed.Results The primary lesions of the 5 patients were all located in lymph nodes.All patients pres-ented with multiple lymphadenopathy,B symptoms,elevated lactate dehydrogenase(LDH)and C-reactive protein(CRP),and were in stage Ⅲ/Ⅳ.Histopathologically,the lesions show a diffuse infiltration of large to medium monot-onous tumor lymphocytes.Cell apoptosis,necrosis,and vascular invasion were not significant.Tumor cells of all cases were positive for CD3 but negative for CD56.All cases were positive for the cytotoxic markers.In situ hybridization de-tection showed that the majority of tumor cells were diffusely positive for EBER.Nevertheless,only 4 cases were posi-tive for TCR gene clonal rearrangement.Three patients received chemotherapy,2 patient declined the treatments.The median overall survival was only 3 months.Conclusions EBV-positive nodal T-and NK-cell lymphoma is an EBV-positive lymphoma of cytotoxic T-or NK-cell lineage presenting primarily with nodal disease,which is more common in elderly males.The patient has obvious symptoms and signs,rapid disease progression,and poor prognosis.Under-standing the clinicopathological features of EBV-positive nodal T-and NK-cell lymphoma can help differentiate it from other EBV-positive T-and NK-cell lymphoid proliferations and lymphomas.

Chemotherapy-induced nausea and vomiting (CINV) is one of the common adverse reactions in cancer patients undergoing chemotherapy, with a relatively high incidence. This article reviews the research progress on risk prediction models for CINV, introduces the basic information of related risk prediction models, and compares differences in research methods and risk factors, aiming to provide reference for the establishment of a prevention and assessment system for CINV in cancer patients.

Objective:To investigate the occurrence and characteristics of adverse reactions of Xuesaitong preparations, mine its coagulation disorders/bleeding risk signals, and provide references for its safe and rational use in clinic. Methods:The reports of adverse drug reactions (ADR) caused by Xuesaitong preparations from August 2003 to August 2023 in the database of Shandong Provincial Center of Adverse Drug Reaction Monitoring were collected. ADR were counted and classified using the system organ class (SOC) and preferred term (PT) of Medical Dictionary for Regulatory Activities 26.1. Three methods, namely the reporting odds ratio (ROR), the proportional reporting ratio (PRR), and the comprehensive standard method of the Medicines and Healthcare Products Regulatory Agency (MHRA) of the United Kingdom, were used to detect the risk signals of coagulation disorders/bleeding in using Xuesaitong preparations. Results:A total of 17 015 reports of ADR related to Xuesaitong preparations were collected, involving 9 dosage forms, in which injection dosage form accounted for 95.50% (16 250/17 015). The median age of the patients was 62 years, 44.87% of the cases were 45-64 years and 42.90% of them were 65 years and above. There were 2 217 cases of severe ADR reports, accounting for 13.03% (2 217/17 015). A total of 18 SOCs were involved, the top 3 were skin and subcutaneous tissue diseases, systemic diseases and drug administration site reactions, and neurological diseases. A total of 54 PTs were not recorded in the instructions, among which 34 were severe. Ninety-three cases about coagulation disorders/bleeding (98 times) were reported, the top 3 PTs were hematuria [24.49% (24/98)], purpura [11.22% (11/98)], and epistaxis [10.20% (10/98)]. Seven dosage forms of Xuesaitong preparations were involved, the top 3 were Xuesaitong for injection (freeze-dried) (48 cases, accounting for 51.61%), Xuesaitong injection (29 cases, accounting for 31.18%), and Xuesaitong tablets (8 cases, accounting for 8.60%). Among 93 reports of coagulation disorders/bleeding, there were 23 severe cases, accounting for 24.73%, which was significantly higher than that in other reports (12.97%), and the difference was statistically significant ( P<0.001). Sixteen PTs about coagulation disorders/bleeding were not recorded in the instructions, among which 9 were severe. The proportion of cases with onset time longer than 7 days in ADRs about coagulation disorders/bleeding was higher than that in other ADRs [22.58%(21/93) vs. 7.43%(1 258/16 922), P<0.001]. The risk signals of coagulation disorders/bleeding were mined for Xuesaitong for injection (freeze-dried), Xuesaitong injection, Xuesaitong tablets, and Xuesaitong capsules, and the risk signal density of Xuesaitong tablets was the strongest. Conclusions:The ADRs of Xuesaitong preparations involve multiple systems and organs. Among them, Xuesaitong for injection (freeze-dried), Xuesaitong injection, Xuesaitong tablets, and Xuesaitong capsules have a strong association with coagulation disorders/bleeding risks, and the proportion of severe cases is relatively high. However, the relevant risk warning information is not included in the drug instructions of some manufacturers. Medication monitoring needs to be strengthened and timely intervention should be carried out in clinic.

With the technological innovation and the advances in information technology, acupuncture-moxibustion is on the path of modernization and high-quality development. The research on ancient acupuncture-moxibustion literature has been gradually transformed from traditional sorting and digital research to intelligent knowledge services, so as to realize the deep integration of ancient acupuncture-moxibustion knowledge with the needs of modern clinical practice and scientific research. Guided by the characteristics of acupuncture-moxibustion knowledge and based on the knowledge meta-theory, the in-depth analytical indexing and knowledge organization are conducted on more than 400 kinds of ancient acupuncture-moxibustion literature. Taking ancient literature of meridian symptoms/manifestations as an example, thematic literature research and database construction are carried out. Integrated with database, cloud platform, knowledge domain mapping and other technologies, the sharing service platform of ancient acupuncture-moxibustion knowledge is constructed. As a result, the research and development achievements can be adopted by the researchers in the field of basic theory, clinical practice and research of acupuncture-moxibustion. Finally, through the way of "digital reconstruction + intelligent application", the path and paradigm of digital research of ancient acupuncture-moxibustion literature are explored to provide the references for the innovative utilization of ancient acupuncture-moxibustion literature.
Moxibustion/history* ; Humans ; Acupuncture Therapy/history* ; History, Ancient ; Knowledge

OBJECTIVE: To organize and display systematically the ancient medical records of stroke treated with acupuncture and moxibustion based on the knowledge element theory of information technology, so as to provide the path and paradigm for the construction of ancient acupuncture and moxibustion knowledge model. METHODS: The medical records of stroke treated with acupuncture and moxibustion were collected from the monographs of acupuncture and moxibustion and tuina, medical reports, the ancient works of traditional Chinese medicine of comprehensive collection and clinical disorders of each medical department, from the pre-Qin period to the late Qing Dynasty, collected in Zhonghua Yidian (Canon of Chinese Medicine), the fifth edition. Using "knowledge processing platform of ancient Chinese medicine books", the medical records of stroke treated with acupuncture and moxibustion in ancient time were deeply analyzed and indexed. With the MS SQL Server database adopted, the indexing results were exported into logical data; and Neo4j database was employed to build the knowledge graph of stroke treatment with acupuncture and moxibustion in ancient time. RESULTS: There were 43 medical records in 18 ancient books that met the inclusion criteria, and a logical structure was organized and composed of 65 knowledge bodies, 462 knowledge elements, 1,413 semantic types and 315 semantic associations. CONCLUSION Based on the knowledge element theory, the medical records of stroke treated with acupuncture and moxibustion in ancient time have been explored, and the logical data formed can accurately reflect the knowledge of the different attributes inside these medical records. It displays the knowledge organization category from the overall to the local. The knowledge graph generated according to the logical data is conducive to presenting the ancient acupuncture knowledge in view of the "vertical and horizontal" dimensions.
Moxibustion/history* ; Humans ; Acupuncture Therapy/history* ; Stroke/history* ; History, Ancient ; Medical Records ; China

AIM: To investigate the influence of relevant inflammatory markers in peripheral blood on the progression of neovascular glaucoma(NVG)secondary to diabetic retinopathy(DR)patients.METHODS: Retrospective case-control study. Patients were categorized into two groups based on the presence or absence of NVG: those with proliferative diabetic retinopathy(PDR)alone(PDR group, n=148)and those with NVG secondary to PDR(NVG secondary to PDR group, n=142). Peripheral blood inflammatory markers were evaluated, including white blood cell-related indices, neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), monocyte-to-lymphocyte ratio(MLR), and systemic immune-inflammation index(SII). The distinctions in peripheral blood inflammatory markers between the two groups of patients and their relationships with NVG secondary to PDR were analyzed.RESULTS:No statistically significant differences were observed in basic characteristics between the two groups, confirming their comparability. However, significant differences were found in eosinophil percentage and MLR between the PDR group and the NVG secondary to PDR group(all P<0.05), with both values being significantly higher in the NVG secondary to PDR group. Multivariate Logistic regression analysis revealed that the eosinophil percentage and the MLR were factors influencing the development of patients with NVG secondary to PDR.CONCLUSION: Eosinophil percentage and MLR may be associated with the progression of PDR to NVG, and could serve as potential predictive markers for NVG development in PDR patients.

With the continuous development of genomics and precision medicine,targeted therapy and immunotherapy targeting biomarkers have ush-ered in a new era of anti-tumor therapy.However,due to the heterogeneity of tumor cells and the variability of tumor microenvironment,there are still significant differences in response to the same drug even in patient populations with the same bio-marker enrichment.By combining omics data with drug sensitivity algorithms,the response of anti-tu-mor drugs can be predicted and transformed into personalized diagnosis and treatment strategies re-quired for precision medicine,which is expected to improve the effectiveness of anti-tumor drugs in clinical treatment.Currently,machine learning is one of the commonly used modeling algorithms for predicting the response of anti-tumor drugs.How-ever,due to differences in input data and algorithm construction methods,there is currently a lack of comprehensive literature review in this field.There-fore,this article provides a review of machine learning algorithms for predicting anti-tumor drug responses,summarizing publicly available cell ge-nome characterization datasets,machine learning algorithms,and evaluation indicators in drug re-sponse prediction,as well as the current situation and challenges faced in clinical applications,in or-der to provide methodological references for the main research problems and potential solutions of machine learning algorithms in the field of drug re-sponse prediction.

Purpose To explore the clinicopathological features of EBV-positive nodal T-and NK-cell lymphoma.Methods Clinical and pathological data of 5 cases were collected.The expression of CD3,CD56,TIA-1,Granzyme B and other markers were detected by immunohistochemistry.The expression of EBER was detected by in situ hybrid-ization.The gene rearrangement and clonality were analyzed by PCR and polyacrylamide gel electrophoresis.The litera-tures were reviewed.Results The primary lesions of the 5 patients were all located in lymph nodes.All patients pres-ented with multiple lymphadenopathy,B symptoms,elevated lactate dehydrogenase(LDH)and C-reactive protein(CRP),and were in stage Ⅲ/Ⅳ.Histopathologically,the lesions show a diffuse infiltration of large to medium monot-onous tumor lymphocytes.Cell apoptosis,necrosis,and vascular invasion were not significant.Tumor cells of all cases were positive for CD3 but negative for CD56.All cases were positive for the cytotoxic markers.In situ hybridization de-tection showed that the majority of tumor cells were diffusely positive for EBER.Nevertheless,only 4 cases were posi-tive for TCR gene clonal rearrangement.Three patients received chemotherapy,2 patient declined the treatments.The median overall survival was only 3 months.Conclusions EBV-positive nodal T-and NK-cell lymphoma is an EBV-positive lymphoma of cytotoxic T-or NK-cell lineage presenting primarily with nodal disease,which is more common in elderly males.The patient has obvious symptoms and signs,rapid disease progression,and poor prognosis.Under-standing the clinicopathological features of EBV-positive nodal T-and NK-cell lymphoma can help differentiate it from other EBV-positive T-and NK-cell lymphoid proliferations and lymphomas.