The c-Jun N-terminal kinase （JNK） signaling pathway， a key member of the mitogen-activated protein kinase （MAPK） family， plays a central role in the pathogenesis and progression of central nervous system （CNS） diseases by regulating core biological processes such as apoptosis， inflammatory responses， synaptic plasticity， and autophagy. This article sorts out and analyzes relevant literature published domestically and internationally in recent years， summarizing the mechanisms of action of the JNK signaling pathway in common CNS diseases and the research progress in traditional Chinese medicine （TCM） interventions in CNS diseases through the regulation of the JNK signaling pathway. Studies have shown that active components of TCM， such as berberine， paeoniflorin， and astragaloside Ⅳ， as well as compound formulations like Heixiaoyao san， Ditan tang， and Buyang huanwu tang， can exert neuroprotective effects in various CNS disorders， including Alzheimer’s disease， Parkinson’s disease， cerebral ischemia-reperfusion injury， and epilepsy， by inhibiting the aberrant activation of the JNK signaling pathway， thereby alleviating neuroinflammation， oxidative stress， and neuronal apoptosis， while improving synaptic function and cognitive behavioral deficits， regulating autophagy， and maintaining blood-brain barrier integrity.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Alzheimer’s disease （AD） is an age-related neurodegenerative disorder. Marrow-sea insufficiency serves as the fundamental basis for the onset of AD. Early syndrome differentiation-based intervention helps to delay disease progression， and improve patients’ cognitive function. Qifu yin is a representative specialized prescription for AD with marrow-sea insufficiency syndrome. Studies demonstrate that Qifu yin exerts neuroprotective effects through multiple pathways， including inhibiting the abnormal deposition of amyloid β -protein and hyperphosphorylation of tau protein， alleviating neuroinflammation， regulating oxidative stress and mitochondrial dysfunction， modulating the cholinergic system， and improving synaptic plasticity. Qifu yin combined with Western medicine such as donepezil， memantine， and butylphthalide， or combined with external therapies such as acupuncture， can effectively improve cognitive function and activities of daily living in AD patients with favorable safety. Future research should focus on the core pathogenesis and key targets of AD with marrow-sea insufficiency syndrome， provide in-depth elucidation of the scientific connotation of Qifu yin’s “tonifying the kidney to produce marrow”， and further conduct high-quality clinical studies to provide scientific evidence for the prevention and treatment of AD with marrow-sea insufficiency syndrome.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba（TPAGH）， and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group， recombinant human epidermal growth factor（rhEGF） group（4 mg·kg^-1）， and low， medium， and high dose groups of TPAGH（3.5， 7， 14 mg·kg^-1）， with 24 mice in each group. A full-thickness skin excision model was constructed， and each administration group was coated with the drug at the wound site， and the model group was treated with an equal volume of normal saline， the treatment was continued for 30 days， during which 8 mice from each group were sacrificed on days 6， 12， and 30. The healing of the wounds in the mice was observed， and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin（HE）， Masson， and Sirius red staining， and enzyme-linked immunosorbent assay（ELISA） was used to dynamically measure the contents of interleukin-6（IL-6）， tumor necrosis factor-α（TNF-α）， vascular endothelial growth factor A（VEGFA）， matrix metalloproteinase（MMP）-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH， and molecular docking of key components and targets was performed. Gene Ontology（GO） biological process analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were carried out for the related targets， so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH， including 28 phenylpropanoids， 31 tannins， 23 triterpenes， 49 flavonoids， and 15 others， and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that， compared with the model group， the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate（P<0.05）， and the number of new capillaries， number of fibroblasts， number of new skin appendages， epidermal regeneration rate， collagen deposition ratio， and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved（P<0.05， 0.01）， the levels of IL-6， TNF-α， MMP-3 and MMP-9 in the skin tissues were reduced to different degrees， while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets， including tumor protein 53（TP53）， sarcoma receptor coactivator（SRC）， protein kinase B（Akt）1， signal transducer and activator of transcription 3（STAT3）， epidermal growth factor receptor（EGFR） and so on， participating in 75 signaling pathways such as advanced glycation end-products（AGE）-receptor for AGE（AGE/RAGE） signaling pathway， phosphatidylinositol 3-kinase（PI3K）/Akt signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway. Molecular docking confirmed that the key components genistein， geraniin， and casuariin had good binding ability to TP53， SRC， Akt1， STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction， thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology， the study explores how key components may bind to targets such as TP53， Akt1 and EGFR， exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.

This study established the mouse podocyte clone-5 (MPC5) with Smad3 knockout and studied the effect of transforming growth factor-beta 1 (TGF-β1) on the dedifferentiation of the MPC5 cells with Smad3 knockout, aiming to provide a cell tool for studying the role of Smad3 in mouse podocytes. The single-guide RNA (sgRNA) sequence targeting Smad3 was designed according to the principles of CRISPR/Cas9 design. The pX458-Smad3 vector was constructed and introduced into competent cells, and then the vector was extracted and used to transfect MPC5 cells. The successfully transfected cells were sorted by a flow cytometer. After single-cell clone expansion, PCR amplification of sequences adjacent to the edition site of Smad3 and sequencing were performed to identify potential cells with gene knockout. Western blotting was employed to verify the knockout efficiency of Smad3. Finally, the effect of Smad3 knockout on TGF-β1-induced dedifferentiation of MPC5 cells was analyzed by reverse transcription-polymerase chain reacting (RT-PCR), Western blotting, and the immunofluorescence method. The sgRNA was designed to target the fifth exon of Smad3. EGFP expression was observed 24 h after transfection of the pX458-Smad3 plasmid into MPC5 cells, with the transfection efficiency of 0.1% as determined by flow cytometry. From the transfected cells, 21 cell clones were obtained through flow cytometric sorting and single-cell clone expansion. PCR amplification and sequencing of the region around the sgRNA target site in Smad3 identified two cell clones with biallelic frameshift mutations. Western blotting results confirmed the absence of Smad3 expression in these clones, indicating successful establishment of the MPC5 cell line with Smad3 knockout. In normal MPC5 cells, TGF-β1 stimulation promoted the expression of fibrosis-related genes fibronectin and Col1a1 (collagen I) and inhibited the expression of the podocyte marker proteins synaptopodin and podocin, which suggested epithelial-mesenchymal transition and podocyte injury. However, in the two MPC5 cell lines with Smad3 knockout, TGF-β1-induced expression of epithelial-mesenchymal transition markers was significantly suppressed. The MPC5 cell lines with Smad3 knockout that were constructed by CRISPR/Cas9 provide a valuable cell model for functional studies of Smad3 protein and highlight the critical role of Smad3 in cell dedifferentiation.
Animals ; Smad3 Protein/genetics* ; CRISPR-Cas Systems/genetics* ; Mice ; Podocytes/metabolism* ; Transforming Growth Factor beta1/pharmacology* ; Cell Line ; Gene Knockout Techniques ; RNA, Guide, CRISPR-Cas Systems/genetics*

Objective:To evaluate the analgesic effect of intercostal muscle plane block of external oblique muscle in patients undergoing endoscopic pancreaticoduodenectomy.Methods:A total of 48 patients undergoing endoscopic pancreaticoduodenectomy under elective general anesthesia in Nanjing First Hospital from February to July 2023 were prospectively selected and divided into two groups ( n=24) according to random number table method: abdominal external oblique intercostal muscle plane block combined with general anesthesia group (EG group) and general anesthesia group (G group). The EG group was blocked in the intercostal muscle plane of the external oblique muscle before general anesthesia induction, and 0.375% ropivacaine 20 ml was injected on both sides, respectively. Patient-controlled intravenous analgesia (PCIA) was performed in both groups after operation, and the pain Visual Analogue Scale (VAS) score was less than 4 points. When the VAS score was ≥4, 1 mg oxycodone was injected intravenously for relief and analgesia. VAS scores at 30 min (T 0), 6 h (T 1), 12 h(T 2), 24 h(T 3), 48 h(T 4) after extubation, intraoperative drug and fluid dosage, postoperative sleep quality, analgesic satisfaction score, remedial analgesia and the occurrence of adverse reactions were recorded. Results:The scores of rest and exercise VAS at T 0, T 1, T 2, T 3 and T 4 in the EG group were significantly lower than those in the G group (all P<0.05). The dosage of norepinephrine, propofol, remifentanil and total fluid infusion in the EG group were significantly lower than those in the G group (all P<0.05). The sleep quality and analgesic satisfaction of the EG group were better than those of the G group (all P<0.05), the first time of PCIA compression after surgery was longer than that of the G group ( P<0.05), the number of effective compressions, the amount of oxycodone relief and analgesia, the proportion of nausea and vomiting, and the stay time of anesthesia intensive care unit (AICU) were lower than those of the G group (all P<0.05). There was no significant difference in total hospital stay between the two groups ( P>0.05). Conclusions:Compared with general anesthesia alone, abdominal external oblique intercostal muscle plane block combined with general anesthesia in patients with endoscopic pancreaticoduodenectomy has significant postoperative analgesia effect, which can not only reduce postoperative VAS score and opioid consumption, but also improve sleep quality and increase postoperative analgesia satisfaction. Ultrasound-guided intercostal muscle plane block of external oblique muscle can be used as a better analgesic method in endoscopic pancreaticoduodenectomy.

Objective:To improve the isolation and culture method of seasonal influenza virus in embryonated chicken eggs (ECEs), and evaluate their isolation efficiency.Methods:We randomly selected 80 positive samples of H1N1 (H1N1pdm09) and seasonal H3N2 (H3N2snl) influenza virus nucleic acid, and inoculated them into the amniotic and urinary sac cavities of 10-day-old (traditional method) and 14-day-old (improved method) ECEs respectively to adapt the virus to the ECEs (E1-E2). Both method were used to inoculate 10-day-old urinary sac amplification virus (E2-E3), and the final virus isolation positive rates of the two method were compared; using fluorescence quantitative PCR method to detect viral nucleic acids in the improved amniotic and urinary sac cultures, and evaluate the viral proliferation at different inoculation sites; we analyzed the correlation between virus content and isolation positivity rate in the original specimen based on the CT value of nucleic acid testing and the final virus isolation positivity rate using the improved method.Results:The improved method obtained 42 strains of H1N1pdm09 strain, with a positive rate of 52.5% ( χ2=38.571, P<0.01); obtained 54 strains of H3N2snl strain, with a positive rate of 67.5% ( χ2=40.921, P<0.01). Significant differences were observed in the isolation efficiency of H1N1pdm09 samples when the improved method was applied to different inoculation sites of chicken embryos ( χ2=30.476, P<0.01), and similar differences were noted for H3N2snl samples ( χ2=4.928, P=0.026). There was no significant difference in the isolation rate of different CT value intervals of the original samples ( χH1N1pdm092=10.226, χH3N2snl2=3.764, P>0.05). Conclusions:The improved method of inoculating 14-day old ECEs adapted the virus, and the final number of strains obtained was significantly higher than the traditional method of inoculating 10 day old ECEs, which can significantly improve the positive isolation rate of H1N1pdm09 and H3N2snl influenza virus in ECEs. The amniotic cavity is more sensitive to H1N1pdm09 and H3N2snl influenza viruses, which helps the virus adapt in ECEs. There was no significant difference in the sample isolation rate and total positive rate of virus isolation among different CT value ranges, and further verification is needed.

A 34-year-old male patient was admitted to the hospital on October 6, 2023 due to fall from a high place. Physical examination showed blood pressure 96/53 mmHg (1 mmHg=0.133 kPa), heart rate of 105 beats/min, slight bulge in the right kidney area, and positive percussion pain in the right kidney area. CT examination showed complete rupture of the lower pole of the right kidney, thrombosis of the right renal vein, and contusion and laceration of the right posterior lobe of the liver. According to the American Association for the Surgery of Trauma renal injury classification, he was diagnosed as grade Ⅳ renal rupture. After blood transfusion and fluid infusion, vital signs were stable. Laparoscopic nephrectomy plus renal vein thrombectomy plus liver rupture repair were performed. The operation took 90 minutes, and about 300 ml of blood clots and fresh blood were aspirated during the operation. The patient's vital signs were stable after the operation, and he could get out of bed 3 days after the operation. CT reexamination 1 month after the operation showed right kidney resected and the liver healed well. This operation is feasible if the patient's vital signs are stable, with the advantages of small surgical incision, short operation time, less bleeding, fast postoperative recovery and good surgical effect.

Objective This study aims to evaluate the safety and efficacy of internal carotid artery(ICA)embolization for the resection of head and neck tumors invading the ICA.Methods A retrospective analysis was conducted on eight patients with ICA-invading head and neck tumors treated between August 2022 and June 2024 in Beijing Tongren Hospital,Capital Medical University.All patients underwent a preoperative balloon occlusion test(BOT),which yielded negative results before undergoing ICA embolization.Parameters from BOT,technical success rates of embolization procedures,perioperative complications,and follow-up outcomes were recorded.Results During BOT assessments,the mean reflux pressure was found to be 75.4％±10.3％of the pre-occlusion pressure.Patency of both anterior and posterior communicating arteries was observed in three cases;four cases exhibited patency solely in the anterior communicating artery,while one case showed patency only in the posterior communicating artery.The technical success rate of embolization was 100％.One patient experienced acute cerebral infarction following embolization treatment,while two patients had migraine attacks post-procedure.All patients achieved complete tumor resection without new-onset neurological deficits.Conclusion For patients with head and neck tumors invading the ICA who are negative on BOT,preoperative ICA embolization is a safe and feasible approach that enhances surgical safety during tumor resection.