Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

The polymerase 1 and transcript release factor (PTRF)-cytoplasmic phospholipase A2 (cPLA2) phospholipid remodeling pathway facilitates tumor proliferation in glioma. Nevertheless, blockade of this pathway leads to the excessive activation of oncogenic receptors on the plasma membrane and subsequent drug resistance. Here, CD26/dipeptidyl peptidase 4 (DPP4) was identified through screening of CRISPR/Cas9 libraries. Suppressing PTRF-cPLA2 signaling resulted in the activation of the epidermal growth factor receptor (EGFR) pathway through phosphatidylcholine and lysophosphatidylcholine remodeling, which ultimately increased DPP4 transcription. In turn, DPP4 interacted with EGFR and prevented its ubiquitination. Linagliptin, a DPP4 inhibitor, facilitated the degradation of EGFR by blocking its interaction with DPP4. When combined with the cPLA2 inhibitor AACOCF3, it exhibited synergistic effects and led to a decrease in energy metabolism in glioblastoma cells. Subsequent in vivo investigations provided further evidence of a synergistic impact of linagliptin by augmenting the sensitivity of AACOCF3 and strengthening the efficacy of temozolomide. DPP4 serves as a novel target and establishes a constructive feedback loop with EGFR. Linagliptin is a potent inhibitor that promotes EGFR degradation by blocking the DPP4-EGFR interaction. This study presents innovative approaches for treating glioma by combining linagliptin with AACOCF3 and temozolomide.

An increasing number of studies suggested that the tumor microenvironment exerts a substantial influence on the pathophysiology of pancreatic cancer. As a crucial component of the tumor microenvironment,the tumor stroma plays a pivotal role in the occurrence,development,and chemotherapy resistance of pancreatic cancer. By serving as a proxy for the interaction between tumor cells and the microenvironment,the tumor stroma ratio(TSR) has emerged as a focal point of investigation in recent years. At present,numerous studies show that a low TSR is a protective factor for the prognosis of resectable pancreatic cancer. Additionally, patients with a low TSR are more suitable for the gemcitabine and albumin-bound paclitaxel chemotherapy regimen. But these researches are not conclusive, and there is still a gap between guiding precision treatment. Further research and exploration are required. Integration of artificial intelligence deep learning models into traditional pathological and imaging assessments facilitates precise evaluation of the TSR. It can also enable stratification and precision treatment of pancreatic cancer patients based on this index.

An increasing number of studies suggested that the tumor microenvironment exerts a substantial influence on the pathophysiology of pancreatic cancer. As a crucial component of the tumor microenvironment,the tumor stroma plays a pivotal role in the occurrence,development,and chemotherapy resistance of pancreatic cancer. By serving as a proxy for the interaction between tumor cells and the microenvironment,the tumor stroma ratio(TSR) has emerged as a focal point of investigation in recent years. At present,numerous studies show that a low TSR is a protective factor for the prognosis of resectable pancreatic cancer. Additionally, patients with a low TSR are more suitable for the gemcitabine and albumin-bound paclitaxel chemotherapy regimen. But these researches are not conclusive, and there is still a gap between guiding precision treatment. Further research and exploration are required. Integration of artificial intelligence deep learning models into traditional pathological and imaging assessments facilitates precise evaluation of the TSR. It can also enable stratification and precision treatment of pancreatic cancer patients based on this index.

Clinicians need to focus on various points in the diagnosis and treatment of insomnia.This article prescribed the treatment protocol based on the unique features,such as insomnia in the elderly,women experiencing specific physiologi-cal periods,children insomnia,insomnia in sleep-breathing disorder patients,insomnia in patients with chronic liver and kidney dysfunction.It pro-vides some reference for clinicians while they make decision on diagnosis,differentiation and treat-ment methods.

Objective:To investigate the accuracy of next-generation sequencing technology(NGS)in detecting the polymorphisms of HLA-DRB1,DQB1,DQA1,DRB3,DRB4,DRB5,DPA1 and DPB1 alleles in randomly-selected unrelated healthy individuals from Shenzhen Han population,investigate the potential reason for HLA-DRB1 allele dropout in routine NGS,and establish an internal quality control system.Methods:NGS-based HLA class Ⅱ genotyping was performed on 1 012 samples using the MiSeqDxTM platform.The suspected missed alleles indicated by the quality control software and HLA-DRB1 homozygotes were confirmed by PCR-SSOP or PCR-SBT methods.Results:A total of 139 alleles were detected,including HLA-DRB1(45),DRB3(7),DRB4(5),DRB5(7),DQA1(17),DQB1(21),DPA1(10)and DPB1(27).HLA-DRB 1*09:01(17.09％),15:01(10.72％);DRB3*02:02(25.99％),03:01(10.18％);DRB4*01:03(36.46％);DRB5*01:01(15.42％);DQA1*01:02(20.01％),03:02(17.19％);DQB1*03:01(19.47％),03:03(17.98％),05:02(11.66％),06:01(10.67％);DPA1*02:02(54.45％),01:03(31.18％)and DPB1*05:01(39.13％),02:01(16.90％)alleles were the most common alleles in Shenzhen Han population(frequencies＞10％).There was no statistical difference between the gene frequencies of HLA-DRB1 and DQB1 loci in our study.The HLA Common and Well-Documented Alleles in China(CWD2.4)(x2=12.68,P＞0.05).94 cases of HLA-DRB1 homozygous samples detected by NGS were retested by PCR-SSOP or SBT method,and one case of allele dropout at HLA-DRB1 locus was found.SBT method confirmed that the allele of DRB1*04:03 was missed.The laboratory internal quality control system was established.Two cases of new alleles were detected and named by WHO Nomenclature Committee for Factors of the HLA System.Conclusion:The HLA genotyping results based on NGS showed a significantly lower ambiguity rate.The HLA class Ⅱ alleles exhibit genetic polymorphism in the Han population of unrelated healthy individuals in Shenzhen.The independent method based on NGS in clinical histocompatibility testing has limitations and requires internal quality control strategies to avoid allele-dropout events.

Objective:To develop the Psychological Monitors'Interpersonal Trust Questionnaire in Colleges(PMITQC)and test its validity and reliability.Methods:A preliminary questionnaire was formulated by construc-ting a model of the psychological monitors'interpersonal trust.Totally 515 psychological monitors were selected for item analysis and exploratory factor analysis.In addition,556 psychological monitors were selected for confirmatory factor analysis and internal consistency reliability tests,of which 114 were retested after 4 weeks.The Trust Scale(TS)and Interpersonal Trust Scale(ITS)were used to test the criterion validity.Results:The PMITQC contained 22 items and was composed of four factors that accounted for 68.634％of the variance.The confirmatory factor a-nalysis showed that the four-factor structure model fitted nicely(x2/df=4.22,NFI=0.92,RFI=0.91,IFI=0.94,TLI=0.93,CFI=0.94,RMSEA=0.076).The criterion validity test showed that the total scores and scores of 4 factor of PMITQC were positively correlated with the total scores of TS and ITS(r=0.28-0.48,Ps＜0.01).The Cronbach's coefficients of the total questionnaire and the 4 factors ranged from 0.87 to 0.97 and the test-retest reli-abilities ranged from 0.73 to 0.89.Conclusion:The Psychological Monitors'Interpersonal Trust Questionnaire in Colleges has good validity and reliability.

Objective To investigate the expression of serum Hsa_circ_0003928 in patients with diabetic foot ulcer(DFU)and its relationship with the severity and prognosis of disease.Methods 113 DFU patients were selected as the study subjects.According to the severity of infection,19 cases were classified into level 1(no infection),40 cases at level 2(mild infection),20 cases at level 3(moderate infection),and 34 cases at level 4(severe infection).According to the prognosis of DFU patients,they were divided into good prognosis group(GP,n=63)and poor prognosis group(PP,n=50).The baseline data and levels of IL-6,C-RP and Hsa_circ_0003928 were compared among the four groups.Logistic regression was used to analyze the risk factors of poor prognosis in patients with DFU.The receiver operating characteristic(ROC)curve was used to analyze the value ofHsa_circ_0003928,C-RP and IL-6 in predicting the poor prognosis in DFU patients.Results The DFU duration,infection grade 3～4,serum creatinine,uric acid,BUN,C-RP,IL-6 and Hsa_circ_0003928 levels in PP group were significantly higher than those in GP group(P＜0.05 or P＜0.01).Grade 3～4 DFU patients had higher Hsa_circ_0003928 expression than grade 1～2(P＜0.01).Logistic regression analysis showed that long duration of DFU,infection grade 3～4,higher levels of BUN,C-RP,IL-6 and Hsa_circ_0003928 were risk factors for poor prognosis in DFU patients.ROC curve showed that Hsa_circ_0003928 had the greatest AUC(0.882,95％CI 0.819～0.942)in predicting poor prognosis in DFU patients,with sensitivity 87.5％and specificity 85.6％,respectively.Conclusion Elevated Hsa_circ_0003928 is associated with DFU severity and poor prognosis,which has certain predictive value for the prognosis of DFU patients.