OBJECTIVE To investigate the improvement effects and mechanism of Zhichi suanzaoren decoction （ZSD） on hippocampal oxidative stress injury in hippocampal neurons of mice with perimenopausal insomnia. METHODS The potential targets of active ingredients in ZSD were predicted using TCMSP and TCMIP databases； the targets related to insomnia were searched through GeneCards， OMIM and DisGeNET databases； protein-protein interaction network of intersecting targets of ZSD ingredients and insomnia was constructed； Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted on key targets. Sixty mice were divided into sham operation group， model group， ZSD low-， medium-， and high-dose groups （11， 22， and 33 g/kg）， and eszopiclone group （positive control， 1 mg/kg）. Except for sham operation group， the perimenopausal insomnia model was constructed by ovariectomy （OVX） in the other groups. After successful modeling， mice in each group were gavaged with normal saline or the corresponding drug solution， once a day， for three consecutive weeks. The sleep status of mice was evaluated through the pentobarbital sodium sleep synergy experiment， and the pathological changes of hippocampal neurons and the expressions of related genes and proteins in mice were observed by HE staining， immunohistochemistry staining， immunofluorescence staining， transcriptome sequencing technology and Western blot. RESULTS The results of network pharmacology showed that there were 296 intersection targets between ZSD and perimenopausal insomnia. Protein kinase B1 （Akt1） was a key target for treating insomnia with ZSD. After administration of ZSD， the sleep latency of mice was shortened， the sleep duration was prolonged significantly， and the mean optical density value of neuron-specific nuclear protein in the hippocampal CA1 region was significantly increased （P＜0.01）. Additionally， hippocampal neuron damage in OVX mice was significantly alleviated. The results of transcriptome sequencing showed that ZSD significantly upregulated the transcriptional levels of Nfe2l2 gene in hippocampal tissue of OVX mice （P＜0.05）. After administration of ZSD， protein expressions of nuclear factor E2 related factor 2 （Nrf2） and heme oxygenase-1 （HO-1） in hippocampal tissue of OVX mice， as well as the phosphorylated Akt level， were increased significantly （P＜0.01）. CONCLUSIONS ZSD can ameliorate hippocampal oxidative stress injury of hippocampal neurons in perimenopausal insomnia mice by activating the Akt/Nrf2/HO-1 signaling pathway.

This article systematically described the background of the construction of Professor ZHANG Yonghua's theory of emotion-mind pattern identification， the theoretical basis and the ideas of pattern identification and treatment， and its application. The theory is guided by the concept of the unity of body and spirit， focusing on individual endowment and the characteristics of the seven emotions and five minds of the individual， especially the "vexation， constraint， consideration， frightening and sorrow" emotional symptoms， and adherence to the three core disease mechanism "qi， phlegm， fire"， then prescribed based on the patterns， which is suitable for treatment of emotion-mind diseases and related symptoms. For those with "fire" as the main disease mechanism， identify the manifestation of their emotion and mind： patients with impatience， violent rage mostly belong to excess fire， treated with Zhizi Chi Decoction （栀子豉汤）， Longdan Xiegan Decoction （龙胆泻肝汤）； patients with vexation， easy to anger， mostly belong to deficiency fire， treated with Huanglian Ejiao Decoction （黄连阿胶汤）； patients with vexation， constraint anger， mostly belong to constraint fire， treated with Danzhi Xiaoyao Powder （丹栀逍遥散）， Qinlian Wendan Decoction （芩连温胆汤）； patients with overjoy， usually due to exuberance of heart fire， or phlegm clouding the pericardium， treated with Wendan Decoction （温胆汤）， or Diankuang Mengxing Decoction （癫狂梦醒汤）. For those with "phlegm" as the main disease mechanism， accompanied by excessive consideration and thinking， treated with Wendan Decoction. For those with "qi" as the main disease mechanism， Ganmai Dazao Decoction （甘麦大枣汤） is the main treatment for shorter duration of disease， while Banxia Houpo Decoction （半夏厚朴汤） is the main treatment for longer duration of disease.

Objective:To evaluate the utility of the 9-gene panel as a differential diagnostic method for thyroid nodules within determinate cytological diagnosis and as a parallel diagnostic method for thyroid fine-needle aspiration (FNA) cytology.Methods:579 liquid-based cytology samples from 544 patients were collected after thyroid FNA diagnosis in our hospital from December 2014 to April 2021. Mutations at any site of 9 genes, namely, BRAF, NRAS, HRAS, KRAS, GNAS, RET, TERT, TP53, and PIK3CA as recorded by the Catalogue of Somatic Mutations in Cancer (COSMIC), were analyzed by next-generation sequencing. Taking postoperative histopathology and cytology results with definite benign or malignant diagnosis as the gold standard, the diagnostic efficacy of the 9-gene panel as a reclassified method for thyroid nodules with indeterminate cytological diagnosis and as a parallel diagnostic method for thyroid FNA cytology were evaluated and compared with that of the BRAF V600E single-gene detection method.Results:Of the 579 thyroid nodules, 196 (33.85%) were Bethesda Ⅱ, 11 (1.90%) were Bethesda Ⅲ, 31 (5.35%) were Bethesda Ⅳ, 27 (4.66%) were Bethesda Ⅴ, and 314 (54.23%) were Bethesda Ⅵ, as diagnosed by thyroid FNA cytology. Among these 579 thyroid nodules, 275 were tested positive for 9-gene mutations, with a mutation rate of 47.5%. Of the 329 thyroid nodules surgically removed, 30 (9.12%) were benign, 5 (1.52%) were borderline, and 294 (89.36%) were malignant. Regarding borderline nodules as malignant nodules, the mutation rates of the 9 genes in the 299 malignant thyroid nodules from high to low were BRAF 62.21% (186/299), NRAS 5.02% (15/299), HRAS 1.00% (3/299), PIK3CA 0.67% (2/299), GNAS 0.67% (2/299), KRAS 0.33% (1/299), TP53 0.33% (1/299), TERT 0.33% (1/299) and RET 0.00% (0/299). The malignant risks of the 9 genes from high to low were BRAF 100% (186/186), PIK3CA 100.00% (2/2), GNAS 100.00% (2/2), TERT 100.00% (1/1), TP53 100.00% (1/1), NRAS 78.95% (15/19), HRAS 75.00% (3/4), and KRAS 50.00% (1/2). For thyroid nodules of Bethesda Ⅲ-Ⅳ (indeterminate diagnosis), the sensitivity (SN) of the 9-gene panel in diagnosing thyroid cancer is 34.48% (10/29), the specificity (SP) is 61.54% (8/13), and the accuracy is 42.86% (18/42); whereas the SN of the BRAF V600E detection method is 0%. Therefore, the diagnostic efficiency of the 9-gene panel is significantly better than that of BRAF V600E single gene detection. For thyroid nodules of Bethesda Ⅱ-Ⅵ, the SN of the 9-gene panel in diagnosing thyroid cancer was 68.83% (254/369), the SP was 90.00% (189/210), the accuracy was 76.51% (443/579), and the area under the curve (AUC) was 0.79; whereas the SN of BRAF V600E single-gene detection in diagnosing thyroid cancer was 63.69% (235/369), the SP was 99.52% (209/210), the accuracy was 76.68% (444/579), and the AUC was 0.82. The SP of BRAF V600E detection is higher than that of the 9-gene panel ( P＜0.01), but there is no significant difference in SN, accuracy (both P＞0.05), and AUC ( Z=0.85, P=0.396) between them. Gene mutations indicating poor prognosis were detected in 4 nodules of papillary thyroid carcinoma and 1 nodules of follicular thyroid carcinoma, including 2 nodules with TERT and BRAF V600E co-mutations, 1 nodule with TP53 mutation, and 2 nodules with PIK3CA mutation. Conclusions:As a reclassified method for thyroid lesions with indeterminate cytological diagnosis, the 9-gene panel is better than BRAF V600E single gene detection. As a parallel diagnostic method of thyroid FNA cytology, the 9-gene panel has similar diagnostic efficacy as BRAF V600E single-gene detection. The 9-gene panel can detect individual cases with gene mutations indicating poor prognosis. The identification of patients with these special gene mutations has certain implications for the clinical management of them.

Objective:To evaluate the utility of the 9-gene panel as a differential diagnostic method for thyroid nodules within determinate cytological diagnosis and as a parallel diagnostic method for thyroid fine-needle aspiration (FNA) cytology.Methods:579 liquid-based cytology samples from 544 patients were collected after thyroid FNA diagnosis in our hospital from December 2014 to April 2021. Mutations at any site of 9 genes, namely, BRAF, NRAS, HRAS, KRAS, GNAS, RET, TERT, TP53, and PIK3CA as recorded by the Catalogue of Somatic Mutations in Cancer (COSMIC), were analyzed by next-generation sequencing. Taking postoperative histopathology and cytology results with definite benign or malignant diagnosis as the gold standard, the diagnostic efficacy of the 9-gene panel as a reclassified method for thyroid nodules with indeterminate cytological diagnosis and as a parallel diagnostic method for thyroid FNA cytology were evaluated and compared with that of the BRAF V600E single-gene detection method.Results:Of the 579 thyroid nodules, 196 (33.85%) were Bethesda Ⅱ, 11 (1.90%) were Bethesda Ⅲ, 31 (5.35%) were Bethesda Ⅳ, 27 (4.66%) were Bethesda Ⅴ, and 314 (54.23%) were Bethesda Ⅵ, as diagnosed by thyroid FNA cytology. Among these 579 thyroid nodules, 275 were tested positive for 9-gene mutations, with a mutation rate of 47.5%. Of the 329 thyroid nodules surgically removed, 30 (9.12%) were benign, 5 (1.52%) were borderline, and 294 (89.36%) were malignant. Regarding borderline nodules as malignant nodules, the mutation rates of the 9 genes in the 299 malignant thyroid nodules from high to low were BRAF 62.21% (186/299), NRAS 5.02% (15/299), HRAS 1.00% (3/299), PIK3CA 0.67% (2/299), GNAS 0.67% (2/299), KRAS 0.33% (1/299), TP53 0.33% (1/299), TERT 0.33% (1/299) and RET 0.00% (0/299). The malignant risks of the 9 genes from high to low were BRAF 100% (186/186), PIK3CA 100.00% (2/2), GNAS 100.00% (2/2), TERT 100.00% (1/1), TP53 100.00% (1/1), NRAS 78.95% (15/19), HRAS 75.00% (3/4), and KRAS 50.00% (1/2). For thyroid nodules of Bethesda Ⅲ-Ⅳ (indeterminate diagnosis), the sensitivity (SN) of the 9-gene panel in diagnosing thyroid cancer is 34.48% (10/29), the specificity (SP) is 61.54% (8/13), and the accuracy is 42.86% (18/42); whereas the SN of the BRAF V600E detection method is 0%. Therefore, the diagnostic efficiency of the 9-gene panel is significantly better than that of BRAF V600E single gene detection. For thyroid nodules of Bethesda Ⅱ-Ⅵ, the SN of the 9-gene panel in diagnosing thyroid cancer was 68.83% (254/369), the SP was 90.00% (189/210), the accuracy was 76.51% (443/579), and the area under the curve (AUC) was 0.79; whereas the SN of BRAF V600E single-gene detection in diagnosing thyroid cancer was 63.69% (235/369), the SP was 99.52% (209/210), the accuracy was 76.68% (444/579), and the AUC was 0.82. The SP of BRAF V600E detection is higher than that of the 9-gene panel ( P＜0.01), but there is no significant difference in SN, accuracy (both P＞0.05), and AUC ( Z=0.85, P=0.396) between them. Gene mutations indicating poor prognosis were detected in 4 nodules of papillary thyroid carcinoma and 1 nodules of follicular thyroid carcinoma, including 2 nodules with TERT and BRAF V600E co-mutations, 1 nodule with TP53 mutation, and 2 nodules with PIK3CA mutation. Conclusions:As a reclassified method for thyroid lesions with indeterminate cytological diagnosis, the 9-gene panel is better than BRAF V600E single gene detection. As a parallel diagnostic method of thyroid FNA cytology, the 9-gene panel has similar diagnostic efficacy as BRAF V600E single-gene detection. The 9-gene panel can detect individual cases with gene mutations indicating poor prognosis. The identification of patients with these special gene mutations has certain implications for the clinical management of them.

Objective:To establish a set of artificial intelligence (AI) verification rules for blood routine analysis.Methods:Blood routine analysis data of 18 474 hospitalized patients from the First Hospital of Jilin University during August 1st to 31st, 2019, were collected as training group for establishment of the AI verification rules,and the corresponding patient age, microscopic examination results, and clinical diagnosis information were collected. 92 laboratory parameters, including blood analysis report parameters, research parameters and alarm information, were used as candidate conditions for AI audit rules; manual verification combining microscopy was considered as standard, marked whether it was passed or blocked. Using decision tree algorithm, AI audit rules are initially established through high-intensity, multi-round and five-fold cross-validation and AI verification rules were optimized by setting important mandatory cases. The performance of AI verification rules was evaluated by comparing the false negative rate, precision rate, recall rate, F1 score, and pass rate with that of the current autoverification rules using Chi-square test. Another cohort of blood routine analysis data of 12 475 hospitalized patients in the First Hospital of Jilin University during November 1sr to 31st, 2023, were collected as validation group for validation of AI verification rules, which underwent simulated verification via the preliminary AI rules, thus performance of AI rules were analyzed by the above indicators. Results:AI verification rules consist of 15 rules and 17 parameters and do distinguish numeric and morphological abnormalities. Compared with auto-verification rules, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score of AI rules in training group were 22.7%, 1.6%, 74.5%, 1.3%, 75.7%, 97.2%, 93.5%, 94.7%, 94.1, respectively.All of them were better than auto-verification rules, and the difference was statistically significant ( P<0.001), and with no important case missed. In validation group, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score were 19.2%, 8.2%, 70.1%, 2.5%, 72.6%, 89.2%, 70.0%, 88.3%, 78.1, respectively, Compared with the auto-verification rules, The false negative rate was lower, the false positive rate and the recall rate were slightly higher, and the difference was statistically significant ( P<0.001). Conclusion:A set of the AI verification rules are established and verified by using decision tree algorithm of machine learning, which can identify, intercept and prompt abnormal results stably, and is moresimple, highly efficient and more accurate in the report of blood analysis test results compared with auto-vefication.

Objective:To evaluate the clinical application of urine sediment score (USS) in early diagnosis, etiological differentiation, staging and prognosis of acute kidney injury (AKI), and to investigate the diagnostic efficacy of independent USS and its combination with blood urea nitrogen(Bun) serum creatinine(sCr) and uric acid(UA) in AKI.Methods:From August 23 to September 28, 2023, 9 020 morning urine samples of hospitalized patients in the First Hospital of Jilin University were detected by Sysmex UF5000.A total of 3 226 ssamples with small and round cell (SRC) > 1/μl and/or CAST>1/μl were screened for microscopic examination, and 404 cases with positive renal tubular epithelial cells and/or cast were enrolled in this study. There were 218 males and 186 females, aged 59.5 (49.0, 71.0) years. The 404 cases were divided into the USS AKI group (345 cases) and the USS non-AKI group (59 cases) according to the USS results based on the microscopic findings. According to Kidney Disease: Improving Global Outcomes (KDIGO) criteria, they were divided into KDIGO criteria AKI group (63 cases) and KDIGO criteria non-AKI group (341 cases), and the AKI group was divided into renal AKI group (33 cases) and non-renal AKI group (30 cases). According to the clinical diagnosis recorded in the medical records, they were divided into clinically diagnosed AKI group (29 cases) and clinically diagnosed non-AKI group (375 cases).The χ 2 test or Fisher exact test was used to compare USS in different AKI causes and stages. Logistic regression was used to calculate the odds ratio of renal AKI and stage 3 AKI. The area under the receiver operating characteristic curve was used to evaluate the sensitivity and specificity of USS, sCr, UA and Bun alone and in combination in the diagnosis of AKI, and the best cut-off value, sensitivity and specificity in the diagnosis of AKI were calculated. P < 0.05 was considered statistically significant. Results:The USS was used to identify the etiology of KDIGO standard AKI group,and there were significant differences in USS between renal AKI group and non-renal AKI group (χ 2=11.070, P<0.001). Compared to USS=1, the odds ratio of renal AKI was 8.125 when USS≥2 (95% CI 2.208—29.901). There was a statistically significant difference in the comparison of USS between groups in each stage of the AKI staging study based on USS (χ 2=15.724, P<0.05). Compared to USS=1, the odds ratio of stage 3 AKI was 9.714 when USS≥2 (95% CI 1.145-82.390). The AUC of independent USS in the diagnosis of AKI was 0.687 (95% CI 0.618-0.757, P<0.001), the specificity was 65.7% and the sensitivity was 61.9%. The AUC of USS combined with Bun, sCr, UA in the diagnosis of AKI was 0.794 (95% CI 0.608-0.980, P<0.05), the specificity was 82.4%, and the sensitivity was 88.9%. Conclusions:There wasan increased likelihood of renal AKI or stage 3 AKI while USS≥2,and whose combination with Bun, sCr and UA will improve the diagnostic efficiency of AKI.

[Objective]To summarize Professor ZHANG Youhua's clinical experience in treating multiple-dream disorder based on the emotion syndrome differentiation theory.[Methods]By sorting out,reviewing and analyzing Professor ZHANG's medical cases related to the treatment of multiple dream disorder,this paper summarized Professor ZHANG's academic experience in the treatment of multiple-dream disorder from the aspects of etiology,pathogenesis,treatment principles and methods of traditional Chinese medicine understanding the association between dreams and emotional states,and listed one medical case for vevification.[Results]In the treatment of multiple dream disorder,Professor ZHANG emphasizes the importance of the emotional experience in dreams rather than the content of the dreams themselves.Therefore,the use of emotion syndrome differentiation method is deemed appropriate.According to the emotional experience in dreams,multiple-dream disorder is divided into five basic types:thinking,panic,anger,sad sorrow and joy syndromes.The three core pathogeneses of"Qi,phlegm and fire"are addressed through methods such as eliminating phlegm,regulating Qi and clearing fire.The medical case cited was multiple-dream disorder with panic syndrome,"phlegm stagnation and fire hyperactivity"was the main pathogenesis,the treatment of clearing fire and eliminating phlegm,calming the heart and tranquilizing the mind was adopted,and the prescription was based on Qinlian Wendan Decoction,added and subtracted according to the syndrome,and achieved a significant effect.[Conclusion]Professor ZHANG Yonghua's approach to treating multiple-dream disorder is based on the theory of emotional syndrome differentiation theory.He emphasizes the importance of emotional experiences in dreams,and his unique experience has shown remarkable clinical results.This approach is worth considering,learning from and promoting.

Objective To explore the medication experience of famous traditional Chinese medicine(TCM)Zhang Yonghua in insomnia based on the data mining and analysis,and to provide guidance for the treatment of insomnia with traditional Chinese medicine.Methods A total of 195 medical cases of famous TCM for insomnia disorder were collected.The Ancient and Modern Medical record cloud platform V 2.3.7 was used to analyze the TCM syndromes,the frequency of Chinese medicinals,formulas,four properties,five flavors and the meridian tropism of Chinese medicinals,and hierarchical cluster analysis,community analysis and complex network analysis were also carried out to summarize the medication rules of TCM Zhang Yonghua for insomnia.Results The main TCM syndrome types of insomnia were irritability and irritability and excessive thinking.A total of 115 Chinese medicinals were involved in 195 cases,with the main actions of calming the mind,clearing fire,resolving phlegm and regulating thi.Complex network analysis obtained the core traditional Chinese medicines as bupleurum,Scutellaria baicalensis,Pinellia pinellia,Poria cocos,Shouwu vine,Acacia bark,Coptis chinensis,Yuanzhi,Jujube kernel and Licorice.Conclusion Famous TCM Zhang Yonghua treated insomnia with the emotional syndrome differentiation theory.According to the pathogenesis of,phlegm,and fire,formulas of regulation,phlegm resolving,and fire clearing are prescribed respectively for its root cause,formulas of calming the mind a given for the manifestation,and finally to cure insomnia by regulating abnormal emotions.

BACKGROUND: Dysfunction of the gap junction channel protein connexin 43 (Cx43) contributes to myocardial ischemia/reperfusion (I/R)-induced ventricular arrhythmias. Cx43 can be regulated by small ubiquitin-like modifier (SUMO) modification. Protein inhibitor of activated STAT Y (PIASy) is an E3 SUMO ligase for its target proteins. However, whether Cx43 is a target protein of PIASy and whether Cx43 SUMOylation plays a role in I/R-induced arrhythmias are largely unknown. METHODS: Male Sprague-Dawley rats were infected with PIASy short hairpin ribonucleic acid (shRNA) using recombinant adeno-associated virus subtype 9 (rAAV9). Two weeks later, the rats were subjected to 45 min of left coronary artery occlusion followed by 2 h reperfusion. Electrocardiogram was recorded to assess arrhythmias. Rat ventricular tissues were collected for molecular biological measurements. RESULTS: Following 45 min of ischemia, QRS duration and QTc intervals statistically significantly increased, but these values decreased after transfecting PIASy shRNA. PIASy downregulation ameliorated ventricular arrhythmias induced by myocardial I/R, as evidenced by the decreased incidence of ventricular tachycardia and ventricular fibrillation, and reduced arrythmia score. In addition, myocardial I/R statistically significantly induced PIASy expression and Cx43 SUMOylation, accompanied by reduced Cx43 phosphorylation and plakophilin 2 (PKP2) expression. Moreover, PIASy downregulation remarkably reduced Cx43 SUMOylation, accompanied by increased Cx43 phosphorylation and PKP2 expression after I/R. CONCLUSION PIASy downregulation inhibited Cx43 SUMOylation and increased PKP2 expression, thereby improving ventricular arrhythmias in ischemic/reperfused rats heart.
Rats ; Male ; Animals ; Myocardial Reperfusion Injury/metabolism* ; Connexin 43/genetics* ; Sumoylation ; Down-Regulation ; Rats, Sprague-Dawley ; Arrhythmias, Cardiac/drug therapy* ; Myocardial Ischemia/metabolism* ; RNA, Small Interfering/metabolism*

ObjectiveTo investigate the effects of flavanomarein on the transcriptome of small intestinal organoids in insulin-resistant mice. MethodFirstly， small intestinal organoids of C57BL/6J and db/db mice were established. Ki-67 and E-cadherin expression was determined by immunofluorescence. Small intestinal organoids were divided into the following three groups： C57BL/6J mouse small intestinal organoids as the normal control group， db/db mouse small intestinal organoids as the model group （IR group）， and db/db mouse small intestinal organoids treated with flavanomarein as the administration group （FM group）. Western blot was used to detect the expression of glucagon-like peptide-1（GLP-1） protein on the small intestinal organoids of the three groups. Finally， transcriptome sequencing was performed on samples from the three groups. ResultOn the 6^th day of small intestine organoids culture， a cyclic structure was formed around the lumen， and a small intestine organoids culture model was preliminarily established. Immunofluorescence detection showed that ki-67 and E-cadherin were expressed in small intestinal organoids. Western blot results showed that the expression of GLP-1 protein was increased by flavanomarein. In the results of differential expressed gene （DEG） screening， there were 1 862 DEGs in the IR group as compared with the normal control group， and 2 282 DEGs in the FM group as compared with the IR group. Through protein-protein interaction（PPI） network analysis of the DEGs of the two groups， 10 Hub genes， including Nr1i3， Cyp2c44， Ugt2b1， Gsta1， Gstm2， Ptgs1， Gstm4， Cyp2c38， Cyp4a32， and Gpx3， were obtained. These genes were highly expressed in the normal control group， and their expression was reduced in the IR group. After the intervention of flavanomarein， the expression of the above genes was reversed. ConclusionFlavanomarein may play its role in improving insulin resistance by reversing the expression levels of 10 Hub genes， including Nr1i3， Cyp2c44， Ugt2b1， Gsta1， Gstm2， Ptgs1， Gstm4， Cyp2c38， Cyp4a32， and Gpx3.