With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective: To explore the incidence and risk factors of cardiovascular events in hematological neoplasms patients treated with anthracyclines in the real world. Methods: A total of 408 patients with lymphoma and leukemia, who were treated with anthracyclines during hospitalization in the First Affiliated Hospital of Dalian Medical University from January 1, 2018 to July 31, 2021, were included in this retrospective study. Patients were divided into cardiovascular event group (n=74) and non-cardiovascular event group (n=334). The primary endpoint was cardiovascular events (arrhythmia, heart failure, acute myocardial infarction etc.) after anthracyclines therapy. The secondary endpoint was all-cause mortality, cardiovascular-cause death, discontinued chemotherapy due to cardiovascular events. Multivariate regression analysis was used to investigate the risk factors of cardiovascular events. Kaplan-Meier was performed to calculate the incidence of all-cause mortality. Results: The mean age was (55.6±14.9) years, and there were 227 male patients (55.6%) in this cohort. The median follow-up time was 45 months. During follow-up, cardiovascular adverse events occurred in 74 patients (18.1%), including 45 heart failure (38 were heart failure with preserved ejection fraction), 30 arrhythmia, 4 acute myocardial infarction and 2 myocarditis/pericarditis. Multivariate regression analysis showed age (OR=1.024, 95%CI 1.003-1.045, P=0.027) and history of hypertension over 10 years (OR=2.328, 95%CI 1.055-5.134, P=0.036) were independent risk factors for the cardiovascular events. Kaplan-Meier survival curve showed mortality was significantly higher in cardiovascular event group than in non-cardiovascular event group (47.3% vs. 26.6%, P=0.001). In the cardiovascular event group, chemotherapy was discontinued in 9 cases (12.2%) due to cardiovascular events and cardiovascular death occurred in 7 cases (9.5%). Conclusions: Although heart failure is the main cardiovascular event in lymphoma and leukemia patients post anthracyclines therapy, other cardiovascular events especially arrhythmias are also common. The presence of cardiovascular events is associated with higher risk of all-cause mortality in these patients. Age and long-term hypertension are independent risk factors for cardiovascular events in lymphoma and leukemia patients after anthracyclines treatment.
Humans ; Male ; Adult ; Middle Aged ; Aged ; Child ; Anthracyclines/adverse effects* ; Retrospective Studies ; Risk Factors ; Heart Failure/drug therapy* ; Myocardial Infarction/complications* ; Hematologic Neoplasms/complications* ; Arrhythmias, Cardiac/complications* ; Leukemia/complications* ; Hypertension/complications*

OBJECTIVE: To evaluate the efficacy of plasma exchange therapy on crescentic IgA nephropathy (IgAN). METHODS: A retrospective analysis was performed in a cohort of patients with crescentic IgAN from January 2012 to September 2020 at 9 sites across China. Clinical and pathological data, as well as therapeutic regimens, were collected. In order to minimize the effect of potential confounders in baseline characteristics, propensity score matching using a 1 ∶1 ratio nearest neighbor algorithm was performed between the adjunctive plasma exchange therapy group and the intensive immunosuppressive therapy group. The primary outcome was end-stage of kidney disease (ESKD). Kaplan-Meier method was used to compare the difference in renal survival between the two groups. RESULTS: A total of 95 crescentic IgAN patients with acute kidney disease were included in this study, including 37 (38.9%) patients receiving adjunctive plasma exchange therapy, and 58 (61.1%) patients receiving intensive immunosuppressive therapy. In the whole cohort, the baseline eGFR was 12.77 (7.28, 21.29) mL/(min·1.73 m²), 24-hour urinary protein quantification was 5.9 (4.0, 8.9) g, and crescent percentage was 64.71% (54.55%, 73.68%). In the study, 23 patients in each group were matched after propensity score matching The median follow-up time was 7 (1, 26) months. As a whole, 29 patients (63.0%) reached ESKD, including 16 patients (69.6%) in the adjunctive plasma exchange therapy group and 13 (56.5%) patients in the intensive immunosuppressive therapy group.. There were no stastical difference between the two groups in terms of baseline eGFR [14.30 (9.31, 17.58) mL/(min·1.73 m²) vs. 11.45 (5.59, 20.79) mL/(min·1.73 m²)], 24-hour urinary protein (7.4±3.4) g vs. (6.6±3.8) g, crescent percentage 64.49%±13.23% vs. 66.41%±12.65% and the proportion of patients received steroid therapy[23 (100.0%) vs. 21 (91.3%)] (All P>0.05). Kaplan-Meier survival analysis demonstrated that there was no significant difference in renal survival rate between the two groups (Log-rank test, P=0.933). CONCLUSION The adjunctive plasma exchange therapy in addition to conventional intense immunosuppressive therapy did not additionally improve the prognosis of crescentic IgA nephropathy.
Cohort Studies ; Glomerulonephritis, IGA/pathology* ; Humans ; Kidney Failure, Chronic/therapy* ; Plasma Exchange ; Prognosis ; Retrospective Studies ; Steroids/therapeutic use*

BACKGROUND: The study aims to correlate osteogenesis with autophagy during the mineralization induction of MC3T3-e1 through exploring the expression of runt-related transcription factor 2 (RUNX2)/lysosomal-associated transmembrane protein 5 (LAMPT5). METHODS: The induction of mineralization in MC3T3-e1 was followed by detecting the expressions of osteogenesisrelated indexes such as RUNX2, alkaline phosphatase (ALP), osteocalcin (OCN), and LAPTM5 using RT-qPCR and Western blot from 0 to 14 days. Transmission electron microscope was utilised in visualizing the alterations of autophagosomes, which was followed by immunofluorescence detecting the subcellular localization of autophagy-related index sequestosome 1 (P62) and microtubule-associated protein 1 light 3 (LC3) protein and scrutinising the expression of P62 mRNA and P62 and LC3 proteins. RESULTS: Induction of MC3T3-e1 mineralization demonstrated an increased expression of osteogenesis-related indicators such as RUNX2, ALP, OCN, and LAPTM5 (p < 0.05), as evident from the results of RT-qPCR and Western blot. Meanwhile, the expression of autophagosomes increased one day after mineralization induction and then experienced a gradual decline, and enhanced expression of LC3 protein was noted on days 1–2 of mineralization induction but was then followed by a corresponding reduce. In contrast, a continuous increase was reported in the expression of P62 mRNA and protein, respectively (p < 0.05). Up- and down-regulating RUNX2/LAPTM5 expression alone confirmed the aforementioned results. CONCLUSION It was therefore proposed that RUNX2 may be responsible for an early increase and then a gradual decrease in LAPTM5-mediated autophagy through the regulation of its high expression. Meanwhile, increased LAPTM5 expression in osteogenic mineralization presumed that RUNX2/LAPTM5 promoted autophagy and osteogenic expression, which may play a bridging role in the regulation of autophagy and osteogenesis.

Objective The pathogenesis of type 2 diabetes mellitus (DM) is complex and its molecular mechanism remains unclear. This study was to explore the effect of metformin on the TLR4/MyD88/NFκB signaling pathway in the skeletal muscle of type 2 DM rats and its anti-inflammation mechanism from the perspective of immune inflammation.Methods Forty SD male rats were equally randomized into four groups, normal diet, type 2 DM model, insulin treatment (DM+INS), and metformin treatment (DM+MET). The DM model was established in the latter three groups by feeding the rats on a diet of high fat and high glucose followed by intraperitoneal injection of STZ at 30 mg/kg at the end of the 8th week. After modeling, the animals of the DM+INS and DM+MET groups were treated by hypodermic injection of insulin at 1 IU/d and intragastrical administration of metformin at 200 mg/（d·kg） respectively for 4 weeks. Then, the Homeostasis Model Assessment-insulin resistance (HOMA-IR) was calculated, the content of serum IL-23 measured by ELISA, the expressions of AMPK, TLR4, MyD88 and NFκB in the skeletal muscle detected by Western blot, and the levels of MyD88 mRNA and TLR4 mRNA determined by RT-PCR.Results HOMA-IR was significantly elevated in the DM model, DM+INS and DM+MET groups as compared with that in the normal diet group (4.55±0.22, 4.32±0.32 and 1.79±0.15 vs 1.56±0.04, P<0.05), lower in the DM+MET than in either the DM model (P<0.05) or the DM+INS group (P<0.05). The content of serum IL-23 was also markedly increased in the DM model, DM+INS and DM+MET groups in comparison with that in the normal diet group (\[2.279±0.472\], \[1.886±0.233\] and \[1.205±0.398\] vs \[0.788±0.193\] μg/L, P<0.05), lower in the DM+MET than in either the DM model (P < 0.05) or the DM+INS group (P<0.05). A positive correlation was found between HOMA-IR and serum IL-23 in both the DM model (r=0.716, P<0.05) and the DM+MET group (r=0.725, P<0.05). The levels of TLR4 mRNA, MyD88 mRNA, TLR4, MyD88, and NFκB were all increased in the DM model, DM+INS and DM+MET groups compared with those in the normal diet group (P<0.05), lower in the DM+INS and DM+MET than in the DM model (P<0.05), and even lower in the DM+MET than in the DM+INS group (P<0.05). The expression of AMPK in the skeletal muscle was remarkably upregulated in the M+MET group as compared with the other three groups (P<0.05).Conclusion Metformin acts against inflammation and improves insulin resistance by activating AMPK, inhibiting the TLR4/MyD88/NFκB signaling pathway in the skeletal muscle and down-regulating the expression of IL-23.

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease (AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.
Alzheimer Disease ; drug therapy ; pathology ; physiopathology ; Autoanalysis ; Biological Availability ; Biomarkers ; Biomarkers, Pharmacological ; Databases, Chemical ; Drug Combinations ; Drug Discovery ; methods ; Drugs, Chinese Herbal ; chemistry ; pharmacology ; therapeutic use ; Humans ; Machine Learning ; Molecular Docking Simulation ; Neural Networks, Computer ; Peptide Fragments ; chemistry ; Permeability