Objective To explore the association between serum uric acid levels and the cumulative incidence risk of atrial fibrillation, and to evaluate the predictive value of different uric acid levels for the onset of atrial fibrillation. Methods A retrospective selection of 451 879 participants from the large-scale prospective epidemiological cohort UK Biobank, aged 40-69 years, all completed a median follow-up of 13.6 years. Participants were divided into groups based on the interquartile range of serum uric acid levels (Q1–Q4) related to gender and whether they were diagnosed with hyperuricemia. Cox proportional hazards model, sensitivity analysis, and other methods were used to compare baseline data and atrial fibrillation incidence during follow-up among each group of participants. Results Individuals with higher baseline uric acid levels tended to be older, more obese, and had lower education levels and a history of cancer, along with significantly higher levels of triglyceride, low-density lipoprotein cholesterol, and C-reactive protein, but lower high-density lipoprotein cholesterol levels (P<0.001); the highest uric acid group showed the highest diabetes prevalence (6.49%). Participants with higher serum uric acid levels (log-rank P<0.05) or diagnosed with hyperuricemia had significantly higher incidence of atrial fibrillation (P<0.001). After adjusting for potential confounders, compared to Q1 uric acid level group, the Q4 level was associated with a 20% increased risk of atrial fibrillation (HR=1.20, 95%CI 1.16–1.25). Each 74.7 μmol/L increase in uric acid level was associated with a 9% increased incidence risk of atrial fibrillation (HR=1.09, 95%CI 1.08–1.11). Individuals with hyperuricemia had a 20% increased incidence risk of atrial fibrillation (HR=1.20, 95%CI 1.17–1.24). A nonlinear association was observed between uric acid levels and the incidence risk of atrial fibrillation (P for nonlinearity <0.01). Subgroup analysis indicated significant heterogeneity of the risk effect across subgroups, with a higher risk associated with hyperuricemia in females. Conclusions Elevated blood uric acid levels may increase the cumulative risk of atrial fibrillation, and this pathogenic effect is significantly correlated with age, race, cancer history, body mass index, and sex.

OBJECTIVE To screen characteristic peaks of hypervirulent Klebsiella pneumoniae(hvKP)using ma-trix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF MS)combined with EX-Smartspec software and establish a rapid detection model for hvKP.METHODS Based on identification criteria of any positive peg-344,iroB,iucA,rmpA,prmpA2 genes or siderophore production＞30 μg/ml,89 hvKP and 72 classical Klebsiella pneumoniae(cKP)strains were initially collected and validated for virulence via Galleria mellonella assays.A diagnostic model distinguishing hvKP from cKP was constructed using EX-Smartspec soft-ware and a convolutional neural network algorithm,integrating characteristic peaks and cluster analysis to provide a rapid and accurate clinical diagnostic tool.RESULTS MALDI-TOF MS analysis identified a characteristic hvKP peak at(3 835±100)ppm.Receiver operating characteristic(ROC)curve analysis revealed optimal performance in distinguishing hvKP with an area under the curve(AUC)=0.741.When AUC ≥0.089,the model demonstra-ted high sensitivity(86.41％),specificity(69.90％),accuracy(78.16％),positive predictive value(74.17％),and negative predictive value(83.72％)in differentiating hvKP from cKP.Cluster analysis further validated the model's classification accuracy.Additionally,the typing classification model exhibited high accuracy(approxi-mately 0.95 and 0.90 in training and validation phases,respectively)and low loss values(-0.18 and 0.30).Val-idation of 6 randomly selected hvKP and 5 cKP strains showed a 100.00％pass rate.CONCLUSION The estab-lished diagnostic model for hvKP and cKP provides a rapid and accurate clinical tool for timely treatment of hvKP-related infections.

OBJECTIVE To screen characteristic peaks of hypervirulent Klebsiella pneumoniae(hvKP)using ma-trix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF MS)combined with EX-Smartspec software and establish a rapid detection model for hvKP.METHODS Based on identification criteria of any positive peg-344,iroB,iucA,rmpA,prmpA2 genes or siderophore production＞30 μg/ml,89 hvKP and 72 classical Klebsiella pneumoniae(cKP)strains were initially collected and validated for virulence via Galleria mellonella assays.A diagnostic model distinguishing hvKP from cKP was constructed using EX-Smartspec soft-ware and a convolutional neural network algorithm,integrating characteristic peaks and cluster analysis to provide a rapid and accurate clinical diagnostic tool.RESULTS MALDI-TOF MS analysis identified a characteristic hvKP peak at(3 835±100)ppm.Receiver operating characteristic(ROC)curve analysis revealed optimal performance in distinguishing hvKP with an area under the curve(AUC)=0.741.When AUC ≥0.089,the model demonstra-ted high sensitivity(86.41％),specificity(69.90％),accuracy(78.16％),positive predictive value(74.17％),and negative predictive value(83.72％)in differentiating hvKP from cKP.Cluster analysis further validated the model's classification accuracy.Additionally,the typing classification model exhibited high accuracy(approxi-mately 0.95 and 0.90 in training and validation phases,respectively)and low loss values(-0.18 and 0.30).Val-idation of 6 randomly selected hvKP and 5 cKP strains showed a 100.00％pass rate.CONCLUSION The estab-lished diagnostic model for hvKP and cKP provides a rapid and accurate clinical tool for timely treatment of hvKP-related infections.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

ObjectiveTo investigate the possible mechanism by which Zhiqiao Gancao Decoction （枳壳甘草汤， ZGD） delays intervertebral disc degeneration （IDD） based on the Hippo-yes-associated protein （YAP）/transcriptional co-activator with PDZ-binding motif （TAZ） signaling pathway. MethodsA total of 50 SD rats were randomly divided into sham surgery group， model group， low-dose ZGD group， high-dose ZGD group， and high-dose ZGD + inhibitor group， with 10 rats in each group. In the sham surgery group， the rats were pierced in the skin and muscle at the Co6/7/8 segments of the tail with a 21G needle （depth approximately 2 mm） without damaging the intervertebral disc. In the other groups， rats were injected with a 21G needle at the Co6/7/8 segments of the tail to establish an IDD model by piercing the tail intervertebral disc 5 mm. One week after modeling， rats in the low-dose and high-dose ZGD groups were given 6.24 and 12.24 g/（kg·d） of the decoction via gastric gavage， respectively. The high-dose ZGD + inhibitor group was given 12.24 g/（kg·d） of the decoction and an intraperitoneal injection of YAP/TAZ inhibitor Verteporfin 10 mg/kg. The sham surgery and model groups were given 5 ml/（kg·d） of normal saline via gavage. The gavage was given once a day， and the intraperitoneal injection was given every other day. After 4 weeks of continuous intervention， the pathological changes of the tail intervertebral discs were observed using HE staining， Oil Red O-Green staining， and Toluidine Blue staining. Immunohistochemistry was used to detect the expression of aggrecan and MMP3 in the nucleus pulposus. TUNEL fluorescence staining was performed to detect apoptosis in the nucleus pulposus， and the apoptosis rate was calculated. Western blot was used to detect the Hippo-YAP/TAZ signaling pathway， including YAP， phosphorylated YAP （p-YAP）， phosphorylated MST1/2 （p-MST1/2）， phosphorylated TAZ （p-TAZ） and apoptosis-related proteins， such as Cleaved Caspase 3， P53， Bcl-2 and Bax. ResultsCompared with sham surgery group， the rats in the model group showed significant degenerative changes in the intervertebral disc. The levels of aggrecan， Bcl-2， and YAP proteins in the nucleus pulposus decreased， while the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and the apoptosis rate increased （P < 0.01）. Compared with the model group， the drug intervention groups showed partial recovery in intervertebral disc degeneration. The levels of aggrecan， Bcl-2， and YAP proteins increased， while the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and the apoptosis rate decreased （P＜0.05 or P＜0.01）. The high-dose ZGD group showed more significant recovery in intervertebral disc degeneration compared to the low-dose ZGD group， with a decrease in the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and apoptosis rate， and an increase in the levels of aggrecan， Bcl-2， and YAP proteins （P＜0.05 or P＜0.01）. Compared with the high-dose ZGD group， the high-dose ZGD + inhibitor group showed a reduced recovery in intervertebral disc degeneration， with an increase in the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and apoptosis rate， and a decrease in the levels of aggrecan， Bcl-2， and YAP proteins （P＜0.05 or P＜0.01）. ConclusionZGD may delay intervertebral disc degeneration by inhibiting the phosphorylation of YAP in the nucleus pulposus， maintaining the function of the Hippo-YAP/TAZ signaling pathway， and reducing apoptosis of nucleus pulposus cells.

Objective To investigate the changes in the tumor microenvironment of pancreatic cancer(PDAC)complicated with diabetes mellitus(DM)in a mouse model of hyperglycemia and orthotopic pancreatic cancer by analyzing transcriptome and single-cell transcriptome data in order to identify potential therapeutic targets.Method By integrating single-cell transcriptome and bulk transcriptome data,bioinformatics analysis was conducted to compare the characteristics of tumor cells and tumor immune microenvironment between PDAC patients with DM(DM group)and those without DM(non-DM group).Twenty male C57BL/6 mice(6 weeks old,weighing 18～20 g)were randomly divided into a hyperglycemic group[STZ group,continuous intraperitoneal injection of 50 mg/kg streptozocin(STZ)(final concentration of 1％)dissolved in citrate buffer],and a control group(Control group,an equivalent volume of citrate buffer without STZ at the same time points),with 10 mice in each group.Tail-tip blood glucose level was measured to monitor glycemic status.After orthotopic inoculation of pancreatic cancer cells in both Control and STZ groups,tumor-infiltrating immune cells were harvested.Flow cytometry was employed to determine the effects of hyperglycemia on:total CD8+T cell and Treg cell populations;CD8+T cell subsets expressing Ki67,TNF-α,granzyme B(GZMB)and IFN-γ;surface expression of PD-1,lymphocyte activation gene-3(LAG-3)and T cell immunoglobulin and mucin domain-3(Tim-3)on CD8+T cells;programmed death-ligand 1(PD-L1)expression on tumor cells;and tumor-associated macrophage surface expression of major histocompatibility complex classⅠ(MHC-Ⅰ)and cluster of differentiation 206(CD206).Results Bioinformatics analysis revealed that,compared to the non-DM group,the genes significantly up-regulated in the DM group were associated with poor prognosis(P＜0.001).The proportion of type 2 ductal cells was increased in the DM group,exhibiting higher levels of copy number variation(P＜0.001).In the tumor immune microenvironment of the DM group,there was an increase in the proportion of Treg cells(P＜0.05)and an elevated exhaustion score for CD8+T cells(P＜0.001),accompanied by down-regulated expression of effector molecules,up-regulated expression of inhibitory checkpoints,and a significant increase in the M2 score of M2-like macrophages(P＜0.001).Animal experiments and flow cytometry found that,compared to the Control group,the STZ group had a shorter survival time(P＜0.001),with decreased proportions of total CD8+T cells(P＜0.01)and CD8+T cells expressing Ki67,TNF-α,GZMB and IFN-γ(P＜0.01),increased proportion of Treg cells(P＜0.001),up-regulated expression of PD-1,LAG-3 and Tim-3 on the surface of CD8+T cells(P＜0.001),and up-regulation of PD-L1 on tumor cell surface(P＜0.001)and enhanced expression of CD206 on the surface of tumor-associated macrophages,while down-regulated expression of MHC-Ⅰ(P＜0.001).Conclusion High glucose promotes the formation of an immunosuppressive microenvironment in PDAC,and targeting type 2 ductal cells and immunosuppressive cells in the tumor microenvironment,combined with dual immune checkpoint antibody therapy,may improve patient prognosis.

Protein liquid-liquid phase separation (LLPS), a pivotal phenomenon intricately linked to cellular processes, is regulated by various other proteins. However, there is still a lack of high-throughput methods for screening protein regulators of LLPS in target proteins. Here, we developed a CRISPR/Cas9-based screening method to identify protein phase separation regulators by integrating bimolecular fluorescence complementation (BiFC) and fluorescence-activated cell sorting (FACS). Using this newly developed method, we screened the RNA-binding proteins that regulate PABPN1 phase separation and identified the tumor suppressor QKI as a promoter of PABPN1 phase separation. Furthermore, QKI exhibits decreased expression levels and diminished nuclear localization in colorectal cancer cells, resulting in reduced PABPN1 phase separation, which, in turn, promotes alternative polyadenylation (APA), cell proliferation, and migration in colorectal cancer.
Humans ; Colorectal Neoplasms/genetics* ; RNA-Binding Proteins/genetics* ; Poly(A)-Binding Protein I/genetics* ; CRISPR-Cas Systems ; Flow Cytometry ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement

Therapeutic resistance in cancer is responsible for numerous cancer deaths in clinical practice. While target mutations are well recognized as the basis of genetic resistance to targeted therapy, nontarget mutation resistance (or nongenetic resistance) remains poorly characterized. Despite its complex and unintegrated mechanisms in the literature, nongenetic resistance is considered from our perspective to be a collective response of innate or acquired resistant subpopulations in heterogeneous tumors to therapy. These subpopulations, e.g., cancer stem-like cells, cancer cells with epithelial-to-mesenchymal transition, and drug-tolerant persisters, are protected by their resistance traits at cellular and molecular levels. This review summarizes recent advances in the research on resistant populations and their resistance traits. NOTCH signaling, as a central regulator of nongenetic resistance, is discussed with a special focus on its canonical maintenance of resistant cancer cells and noncanonical regulation of their resistance traits. This novel view of canonical and noncanonical NOTCH signaling pathways is translated into our proposal of reshaping therapeutic strategies targeting NOTCH signaling in resistant cancer cells. We hope that this review will lead researchers to study the canonical and noncanonical arms of NOTCH signaling as an integrated resistant mechanism, thus promoting the development of innovative therapeutic strategies.
Neoplasms/metabolism* ; Receptors, Notch/metabolism* ; Disease Resistance/physiology* ; Signal Transduction/physiology* ; Humans ; Drug Resistance, Neoplasm/physiology* ; Molecular Targeted Therapy/methods*

Chimeric antigen receptor (CAR) T-cell therapy has shown remarkable efficacy in treating hematological malignancies and is expanding into other indications such as autoimmune diseases, fibrosis, aging and viral infection. However, clinical challenges persist in treating solid tumors, including physical barriers, tumor heterogeneity, poor in vivo persistence, and T-cell exhaustion, all of which hinder therapeutic efficacy. This review focuses on the critical role of tonic signaling in CAR-T therapy. Tonic signaling is a low-level constitutive signaling occurring in both natural and engineered antigen receptors without antigen stimulation. It plays a pivotal role in regulating immune cell homeostasis, exhaustion, persistence, and effector functions. The "Peak Theory" suggests an optimal level of tonic signaling for CAR-T function: while weak tonic signaling may result in poor proliferation and persistence, excessively strong signaling can cause T cell exhaustion. This review also summarizes the recent progress in mechanisms underlying the tonic signaling and strategies to fine-tune the CAR tonic signaling. By understanding and precisely modulating tonic signaling, the efficacy of CAR-T therapies can be further optimized, offering new avenues for treatment across a broader spectrum of diseases. These findings have implications beyond CAR-T cells, potentially impacting other engineered immune cell therapies such as CAR-NK and CAR-M.
Humans ; Immunotherapy, Adoptive/methods* ; Receptors, Chimeric Antigen/immunology* ; Signal Transduction/immunology* ; T-Lymphocytes/immunology* ; Neoplasms/immunology* ; Animals