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Soil erosion plays a crucial role in soil organic carbon (SOC) redistribution and mineralization. Meanwhile, the soil extracellular enzymes (EEs) drive C mineralization. However, the response of soil EEs mediated SOC mineralization to soil erosion remains unclear. We investigated the SOC and soil EEs distribution in long gentle sloping farmland (LGSF) under slop-ridge tillage (SRT) and cross-ridge tillage (CRT) in the black soil region (BSR) of northeast China. The results indicated that the SOC mineralization at the upper slope position was higher than that on the toe-slope (133 % ∼ 340 %) under CRT. However, for SRT, SOC mineralization on the back-slope was 126 % and 164 % higher than on the summit- and shoulder-slope. The SOC, dissolved organic carbon (DOC) content, and β-glucosidase (BG) activities underwent spatial migration and deposition in the lower region under both tillage practices. As for CRT, the SOC content of the back-slope was 19.21 % higher than on the summit-slope, while the DOC content at the back-slope was 29.20 % higher than on the toe-slope. The BG activity was the highest at the toe-slope, followed by the foot-and back-slope, which were 41.74 %-74.73 % higher than at the summit-slope. As for SRT, the SOC, DOC, and BG activities on the back-slope were significantly higher than other slope positions (P < 0.05). The SOC on the back-slope were 47.82 % and 31.72 % higher than those on the summit- and shoulder-slope, respectively. The DOC and BG on the back-slope were 10.98 % and 67.78 % higher than on the summit-slope. The soil EES results indicated strong C and P limitation. Spatial differences in soil C distribution resulted in a significant positive correlation between C limitation and mineralization. This indicated that soil C and nutrient distribution under different slope positions driven by soil erosion, leading to soil nutrient limitation, is a key factor influencing spatial differences in C sources or sinks.
Video-sharing sites such as YouTube (Google) and TikTok (ByteDance) have become indispensable resources for learners and educators. The recent growth in generative artificial intelligence (AI) tools, however, has resulted in low-quality, AI-generated material (commonly called "slop") cluttering these platforms and competing with authoritative educational materials. The extent to which slop has polluted science education video content is unknown, as are the specific hazards to learning from purportedly educational videos made by AI without the use of human discretion. This study aimed to advance a formal definition of slop (based on the recent theoretical construct of "careless speech"), to identify its qualitative characteristics that may be problematic for learners, and to gauge its prevalence among preclinical biomedical science (medical biochemistry and cell biology) videos on YouTube and TikTok. We also examined whether any quantitative features of video metadata correlate with the presence of slop. An automated search of publicly available YouTube and TikTok videos related to 10 search terms was conducted in February and March 2025. After exclusion of duplicates, off-topic, and non-English results, videos were screened, and those suggestive of AI were flagged. The flagged videos were subject to a 2-stage qualitative content analysis to identify and code problematic features before an assignment of "slop" was made. Quantitative viewership data on all videos in the study were scraped using automated tools and compared between slop videos and the overall population. We define "slop" according to the degree of human care in production. Of 1082 videos screened (814 YouTube, 268 TikTok), 57 (5.3%) were deemed probably AI-generated and low-quality. From qualitative analysis of these and 6 additional AI-generated videos, we identified 16 codes for problematic aspects of the videos as related to their format or contents. These codes were then mapped to the 7 characteristics of careless speech identified earlier. Analysis of view, like, and comment rates revealed no significant difference between slop videos and the overall population. We find slop to be not especially prevalent on YouTube and TikTok at this time. These videos have comparable viewership statistics to the overall population, although the small dataset suggests this finding should be interpreted with caution. From the slop videos that were identified, several features inconsistent with best practices in multimedia instruction were defined. Our findings should inform learners seeking to avoid low-quality material on video-sharing sites and suggest pitfalls for instructors to avoid when making high-quality educational materials with generative AI.
Previous studies have reported an association between a significant decline in estimated glomerular filtration rate (eGFR) over time and an increased risk of cardiovascular disease (CVD). This study aimed to investigate the association between the eGFR slope and CVD among individuals with and without diabetes. This prospective cohort study was conducted within the Tehran Lipid and Glucose Study (TLGS) framework. We studied 6919 adults aged 20-70 years, including 985 with diabetes and 5934 without diabetes. The eGFR slope was determined based on repeated measurements of eGFR through linear mixed-effects models. A multivariable Cox proportional hazard model was employed to evaluate the association between eGFR slope, both in continuous and categorical form, and the risk of CVD. The slopes of eGFR exhibited a bell-shaped distribution, with a mean (standard deviation (SD)) of -0.63 (0.13) and - 0.70 (0.14) ml/min per 1.73 m2 per year in individuals with and without diabetes, respectively. During a median follow-up of 8.22 years, following the 9-year eGFR slope ascertainment period, a total of 551 CVD events (195 in patients with diabetes) were observed. Among individuals with diabetes, a steeper decline in eGFR slope was significantly associated with a higher risk of CVD events, even after adjusting for baseline eGFR, demographic factors, and traditional risk factors for CVD; slopes of (-1.05 to -0.74) and (-0.60 to -0.52) were associated with 2.12 and %64 higher risks for CVD, respectively, compared with a slope of (-0.51 to 0.16). Among individuals without diabetes, the annual eGFR slope did not show a significant association with the risk of CVD. Monitoring the eGFR slope may serve as a potential predictor of CVD risk in individuals with diabetes.
Slop oil from oil sands operations presents significant environmental and operational challenges due to its complex composition and stability. This study investigates the separation performance of a field-derived oil-in-water (O/W) slop oil sample from northern Alberta, focusing on centrifugal separation, chemical demulsification, and their integration under the effects of reverse emulsion breaker (REB, branched polyethylenimine), temperature, and dilution. Centrifugal separation was significantly improved by REB addition (optimal dosage: 900 ppm), elevated temperature (70 °C), and organic solvent dilution (e.g., naphtha), enhancing water recovery, reducing turbidity and total organic carbon (TOC) content, and lowering water content in the oil phase. REB exhibited the strongest effect, followed by solvent and thermal treatment, while water dilution hindered separation unless mitigated by REB. Chemical demulsification alone was ineffective. However, when combined with mild centrifugation (5000 rpm, 10 min), REB-assisted treatment achieved results comparable to conventional high-speed centrifugation (7000 rpm, 30 min), while reducing energy input by ∼49 % and cutting process time. Two practical strategies are therefore proposed: (1) solvent dilution followed by high-speed centrifugation for fast bitumen recovery, and (2) REB-assisted mild centrifugation for energy-efficient treatment. This work provides mechanistic insights and practical guidance for the sustainable treatment of oily waste streams in oil sands operations.
Analytical chromatography is a cornerstone of modern science, yet a growing proportion of its literature risks contributing little genuine innovation. Here, we offer a provocation: superficial scholarship, work that satisfies the formal expectations of science while adding limited epistemic value, has become increasingly normalised within the chromatographic literature. We identify recurring archetypes of weak practice, including redundant incremental methods, selective neglect of foundational scholarship, inflated claims of performance, superficial validation, and a culture of metric-driven publications that reward quantity over quality. We argue that these behaviours are no longer isolated failings, but are increasingly embedded within the structures that govern publication, reward, and scientific visibility. We further contend that the rapid adoption of artificial intelligence threatens to accelerate this trajectory, transforming weak but human-driven practices into high-throughput scientific slop that boosts individual productivity while contracting the collective space of discovery. To resist this drift, we propose reforms centred on strengthening validation standards, practical data transparency, incentivising replication and post-publication scrutiny, and realigning academic rewards toward quality and curiosity rather than throughput. The aim is not to disparage analytical chemistry, but to catalyse a candid reckoning with how the field preserves rigour, creativity, and relevance in an era of algorithmic acceleration.
It's hard to talk about any topic in science or education today without the subject of artificial intelligence (AI) coming up-whether large language models should be allowed to aid in searching for a scientific paper or even to write or review the paper itself. In some of the wildest speculations, the humans involved in conducting scientific studies and experiments and vetting the results for publication will be steadily eliminated from the process. But when such grandiose rhetoric starts flying, we at Science try to keep calm and carry on in contributing to a robust, human-curated research literature that will stand the test of time.
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The question of how to specify the posterior tilt of the tibia during arthroplasty operations remains unclear. The most current opinion is that a design whereby incisions are made in parallel with the individual pre-arthritic posterior tilt will yield better post-operational results. However, the wide range of inter-individual variations of posterior tilt of the tibia and the difficult task of identifying the shaft axis of the tibia through standard lateral radiographs are the main obstacles to this particular method. Therefore, there is a need for another reference line that can be measured with plain radiography and yields less inter-individual variation. The hypothesis of this study was that the angle formed between the anterior metaphyseal line of the proximal tibia and the tibial plateau would prove to be less variable across individuals. Long-shot radiographs of non-rotating lateral tibias of 85 patients aged between 18 and 38 years were analysed. The angle forming between the anterior metaphyseal line of the proximal tibia and the slope of the tibial plateau, and the posterior slope angle was measured by 2 separate observers using the classical method. From the measurements of the posterior slope angle taken with the classical method, 38% (33/85) of the patients were within the ±2-degree range of the mean, and the anterior metaphyseal angle was within ±2 degrees of the mean in 75% (64/85) of the total patients. 44.23% variation (CoV) in posterior slop degrees, 2.73% (CoV) variation in the anterior metaphyseal angle measured by the same researchers. The difference between the percentages of variation was also found to be statistically significant. (z = 15.36, p = 0.000). The anterior metaphyseal angle can be utilized to predict the individual posterior slope. Nevertheless, further large-scale, multicentre studies are needed to establish a mean value for the population.
The pumped storage power station (PSPS) is an important measure to achieve the strategic goal of "dual carbon". As one of the preferred types for the upper reservoir dams of PSPSs, the concrete-faced rockfill dam (CFRD) often has a dam foundation on a steep transverse slop and is prone to produce slip deformation along the slope, resulting in poor anti-sliding stability of the dam slope. It is dangerous for the operation safety of PSPSs. Therefore, the slip deformation of CFRDs on dam foundations with large dip angles is investigated. The mechanism for the initiation of slip deformation is revealed. The design measures of physical mechanic and geometric structure are proposed to reduce slip deformation. The results show that the larger sliding forces and smaller anti-sliding forces are the fundamental reasons that CFRDs on dam foundations with large dip angles are prone to produce slip deformation. The larger the dip angle of the dam foundation, the larger the slip deformation of the dam body and face slab, and the smaller the safety factor of the dam slope. When the dip angle of the dam foundation is greater than 15°, the safety factor of the dam slope is less than the minimum value of 1.5 required by codes. The addition of pressure slopes can effectively reduce the slip deformation of the dam body or face slab and significantly improve the anti-sliding stability of the dam slope. When the height or width of the pressure slope platform is greater and the cohesion or internal friction angle of the pressure slope is larger, the slip deformations of the dam body and face slab are smaller, and the safety factor of the dam slope is greater. It is recommended that the height and width of the pressure slope platform be 1/2 times the maximum height of the main dam, and the density (cohesion and internal friction angle) of the pressure slope be equivalent to that of the main dam's rockfill material. The research results can provide theoretical and technical support for the design and construction of CFRDs for the upper reservoir of PSPSs.
Background/Objectives: Exercise capacity and patient prognosis are heavily influenced by comorbidities. However, the specific impact of individual comorbid conditions on objective measures of exercise performance remains insufficiently characterized. The study aimed to identify predictors of reduced physical capacity in patients qualified for cardiac rehabilitation. Methods: A single-center retrospective analysis was conducted on 518 patients qualified for cardiac rehabilitation. After excluding 51 post-cardiac surgery patients, cardiopulmonary exercise testing data from 425 patients (316 men, median age 63 years) were analyzed. Comorbidities data, peak oxygen uptake (peak VO2), and the ventilation-to-carbon dioxide output slope (VE/VCO2 slope) were evaluated. Results: A significantly reduced exercise capacity (peak VO2 < 70% of the predicted value) was observed in 29.4% of patients, while an increased VE/VCO2 slope (≥36) was noted in 20.8% of patients. Univariate logistic regression identified sex, heart failure, valvular disease, peripheral artery disease, diabetes mellitus (T2DM), chronic kidney disease (CKD), Charlson Comorbidity Index (CCI), left ventricular ejection fraction <50%, diastolic dysfunction, and anemia as predictors of both reduced peak VO2 and a steeper VE/VCO2 slope. Multivariate regression analysis further identified T2DM and CKD as independent predictors of reduced peak VO2, while sex, CKD, and CCI were independent predictors of a steeper VE/VCO2 slope. Conclusions: Among patients qualified for cardiac rehabilitation, patient's sex, T2DM, CKD, and the CCI emerged as key predictors of reduced exercise capacity. Reduced peak VO2 was more commonly observed in men, while women more frequently exhibited a steeper VE/VCO2 slope, indicating potential sex-related physiological mechanisms influencing exercise performance.
This study aimed to compare exercise capacity (EC) and comorbidity profiles across left ventricular ejection fraction (LVEF) defined heart failure (HF) categories. From a retrospective, single-centre registry, we analysed 196 individuals with established HF who underwent cardiopulmonary exercise testing and a 6 min walk test (6MWT). EC differed significantly across LVEF categories but not in a linear fashion. The percent of predicted peak oxygen uptake (VO₂) was significantly lower in HF with reduced LVEF (HFrEF, n = 89) than in HF with preserved LVEF (HFpEF, n = 36) and HF with mildly reduced LVEF (HFmrEF, n = 71) (65.9% vs. 76.6% and 76.8%, p < 0.001). Ventilatory inefficiency (VE/VCO₂ slope) was more pronounced in HFrEF than in HFpEF (35.3 vs. 31.7; p = 0.002), while the proportion with VE/VCO₂ slope > 36 did not differ across groups. The achieved workload and 6MWT distance were comparable across groups. Comorbidity profiles diverged meaningfully: HFmrEF had the lowest prevalence of chronic kidney disease (p = 0.009) and type 2 diabetes (p = 0.025). Notably, HFpEF exhibited the highest prevalence of anaemia (p = 0.0013). HFmrEF displays an EC profile closer to HFpEF than to HFrEF, while anaemia emerges as a particularly important comorbidity in HFpEF.
Introduction: Artificial intelligence (AI) raises a fundamental question for modern plastic surgery: will it enable personalized, patient-centered, efficient care, or lead to a dystopian, automated care that diminishes human autonomy, which is dominated by generic "AI slop" that eventually deteriorates the doctor-patient relationship? Methods: This study examines current applications of large language models, generative AI, and neural networks in plastic surgery, assessing AI's roles in surgical planning, automation of repetitive tasks, outcome evaluation, education, and patient communication, alongside associated ethical, legal, and practical risks and considerations. Results: AI has demonstrated utility in evaluating postoperative outcomes, predicting potential surgical complications, assisting with patient inquiries, providing preoperative guidance, and delivering patient education. However, significant challenges accompany these advances, including risks of algorithmic paternalism, cognitive debt, biased decision-making, misinformation, and the use of synthetic images that may create unrealistic patient expectations. Additional concerns include data privacy, accountability, environmental impact, equitable access to AI technologies, and potentially negative patient perceptions or interactions. Conclusions: AI can meaningfully enhance plastic surgery if integrated responsibly, with appropriate human oversight, transparency, and preservation of clinical judgment. The future of the field depends on balancing technological innovation with ethical responsibility while maintaining authenticity, empathy, and patient-centered care. Surgeons must develop AI literacy, monitor public perceptions of AI, establish ethical guidelines, and actively guide responsible adoption to harness AI's benefits while safeguarding human values, creativity, and trust. Future strengths for high-end or boutique practices may lie in emphasizing enhanced human presence, personality, and authenticity rather than excessive reliance on AI. Introduction : L’intelligence artificielle (IA) soulève une question fondamentale pour la chirurgie plastique moderne : permettra-t-elle des soins personnalisés, centrés sur le patient et efficaces, ou conduira-t-elle à une médecine automatisée dystopique réduisant l’autonomie humaine, dominée par un contenu générique produit par l’IA et susceptible de détériorer la relation médecin-patient ? Méthodes : Cette étude examine les applications actuelles des grands modèles de langage, de l’IA générative et des réseaux neuronaux en chirurgie plastique, en évaluant le rôle de l’IA dans la planification chirurgicale, l’automatisation de tâches répétitives, l’évaluation des résultats, l’éducation et la communication avec les patients, ainsi que les risques et considérations éthiques, juridiques et pratiques associés. Résultats : L’IA a démontré son utilité dans l’évaluation des résultats postopératoires, la prédiction de complications potentielles, l’assistance aux questions des patients, l’orientation préopératoire et l’éducation. Cependant, ces avancées s’accompagnent de défis importants, notamment les risques de paternalisme algorithmique, de dette cognitive, de décisions biaisées, de désinformation et d’utilisation d’images synthétiques pouvant créer des attentes irréalistes chez les patients. D’autres préoccupations concernent la protection des données, la responsabilité, l’impact environnemental, l’accès équitable aux technologies d’IA et des perceptions ou interactions potentiellement négatives de la part des patients. Conclusions : L’IA peut améliorer de manière significative la chirurgie plastique si elle est intégrée de façon responsable, avec une supervision humaine appropriée, de la transparence et la préservation du jugement clinique. L’avenir du domaine dépend d’un équilibre entre innovation technologique et responsabilité éthique, tout en maintenant authenticité, empathie et soins centrés sur le patient. Les chirurgiens doivent développer une culture de l’IA, surveiller la perception publique de ces technologies, établir des cadres éthiques et guider activement une adoption responsable afin d’en exploiter les bénéfices tout en protégeant les valeurs humaines, la créativité et la confiance. Pour les pratiques haut de gamme ou spécialisées, un avantage futur pourrait résider dans la mise en avant d’une présence humaine renforcée, de la personnalité et de l’authenticité, plutôt que dans une dépendance excessive à l’IA.
Recent technological advances in artificial intelligence and machine learning have led to rapid changes in clinical informatics. With the release of new models, the barrier to creating medical software has markedly decreased. As noted in the now-viral article by Matt Shumer, we have moved from a world where building a clinical application took a team of engineers working over the course of months to years, to one where a single clinician can develop and deploy a working prototype in hours to days. However, the same innovation driving this 'explosion' of tools also carries the risk of flooding health systems with unvalidated 'AI slop.' As prohibiting tools developed through AI runs the risk of stifling innovation and limiting potentially impactful discoveries, we suggest abandoning the slow, fear-based resistance to AI adoption. Further, we propose a 'go fast and fix things' framework-utilising target product profiles, regulatory sandboxes, and continuous audit-to harness the speed of generation and prototyping while rigorously validating clinical utility.
To determine the independent risk factors of cardiopulmonary exercise test (CPET) parameters related to adverse prognostic events within 5 years in patients undergoing percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI), and establish a prediction model for the occurrence of adverse events within 5 years to provide a reference for cardiac rehabilitation training. From August 2015 to December 2021, patients who underwent PCI for AMI and completed CPET within 1-2 weeks after surgery before discharge from the Department of Cardiovascular Medicine of Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan Provincial Hospital of Traditional Chinese Medicine, and Anyang District Hospital were selected as participants. Univariate and multivariate analyses were used to screen for independent risk factors associated with 5-year adverse events. Feature importance was interpreted using SHapley Additive exPlanations (SHAP), and a logistic regression model was established for prediction. A receiver operating characteristic (ROC) curve was constructed to evaluate the performance of the prediction model. Calibration was assessed by the Hosmer-Lemeshow test and the calibration curve. In total, 375 patients met the inclusion criteria. Based on whether adverse events occurred during the 5-year follow-up period, the patients were divided into two groups: the event group (n = 53) and the non-event group (n = 322). Peak oxygen uptake (peakVO2), carbon dioxide ventilation equivalent slope (VE/VCO2slop), and peak end-tidal carbon dioxide partial pressure (PETCO2) were three independent risk factors for re-acute myocardial infarction (re-AMI), heart failure (HF), and even death after PCI for AMI (P < 0.05). The SHAP plots demonstrated that the significant contributors to model performance were related to peakVO2, VE/VCO2slop, and PETCO2. The risk of adverse events was significantly reduced when the peakVO2 was ≥ 20 mL/kg/min and the VE/VCO2slop was < 33. The ROC curves of the three models were drawn, including the no-event and event groups, re-AMI group, and HF group, which performed well, with AUC of 0.894, 0.760, and 0.883, respectively. The Hosmer-Lemeshow test showed that the three models were a good fit (P > 0.05). The calibration curve of the three models was close to the ideal diagonal lines. CPET parameters can predict the prognosis of adverse events within 5 years after PCI in patients with AMI and provide a theoretical basis for cardiac rehabilitation training.
Background and Objectives: Lean body mass loss after bariatric surgery (BS) is remarkable, despite an effective long-term mass reduction and significant declines in comorbidities. A person's functional capacity is adversely affected when their skeletal muscle strength declines by up to 30%. This study aimed to assess the isokinetic trunk muscle strength and fatigue rate in individuals after BS. Materials and Methods: This study included fifty-eight patients, both male and female, ranging in age from 19 to 45. Twenty-seven individuals had BS and twenty-seven healthy people served as the control group. The primary outcomes were the measurement of the concentric and eccentric isokinetic muscle strength of the trunk flexor and extensor muscles. An isokinetic dynamometer (Biodex Rehabilitation and Testing System 3) was used for the assessment of the isokinetic muscle strength. Noraxon EMG was used to determine a secondary outcome, which was the median frequency slop (MF/time) and root mean square slop (RMS/time) of the lumbar erector spinea muscle at 50% of the Maximum Voluntary Isometric Contraction (MVIC). Outcome measures were assessed for both groups. Results: Compared to the control group, the bariatric group showed a lower mean value of both concentric and eccentric isokinetic muscle strength for the flexor and extensor trunk muscles (p < 0.05). In terms of the EMG fatigue rate, the RMS slope increased significantly more than that of the control group, while the MF slope decreased (p > 0.05). Conclusions: The current study found that, in comparison to the healthy subjects, the BS group showed reduced levels of fatigue and isokinetic strength in the trunk muscles. Based on these results, it is recommended that individuals who underwent BS take part in tailored rehabilitation programs to avoid potential musculoskeletal issues in the future.
Objective.To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion radiotherapy (CIRT).Methods.This dual-modeling study analyzed 106 CIRT-treated SC/LRRC patients. Notice that the unit of Gy is the relative biological effectiveness -weighted dose with local effect model version I in this study for the prescription of our CIRT treatments. The hybrid framework integrated the Lyman-Kutcher-Burman model with generalized machine learning. Radiation dosimetry (the equivalent uniform dose (EUD), the uniform dose over the sciatic nerve for a 50% complication probability [TD50], the parameter for the volume effect of the organ [n], the slop steepness of the dose response curve [m]) and biological parameters were analyzed through univariate/multivariate regression. Model performance was validated using the area under the receiver operating characteristic area under the curve, sensitivity, and specificity metrics.Results.16.9% (18/106) over all patients developed grade ⩾1 LSNT with no grade ⩾4 toxicity. Stratified outcome analysis across various subgroups revealed significant variations, especially that pathological subtype of re-irradiated rectal cancer exhibited manifested 15.6% G2 toxicity. We first successfully obtained coefficients for the NTCP models with univariate analysis by utilizing the correlation between significant variations of stratified outcome and TD50. We then establish an NTCP model by machine learning-enhanced multivariate analysis that allow identifying the critical dose-volume thresholds ofV62,V64, andD3ccto correlate dose-dependent progression of G1, G2, ad G3 toxicities, respectively.Significance.EUD > 61.1 Gy significantly elevates G1 LSNT risk. Our center recommends:V62⩽ 6.2%,V64⩽ 4.69%,D3cc⩽ 32.3 Gy to balance tumor control and neuroprotection in CIRT planning. The n/m parameters provide critical insights into individual radiation sensitivity gradients across toxicity grades with machine learning-enhanced NTCP modeling for LSNT prediction in CIRT.
Metal-organic frameworks (MOFs) have been a hot topic as oxygen evolution reaction (OER) electrocatalysis owing to their superior specific surface area, plentiful metal active sites and modifiable morphology and composition. Nonetheless, the low electronic conductivity, restricted active sites and lack of structural robustness in MOFs impede their efficacy as catalysts in water electrolysis processes. Herein, nickel thiophenedicarboxylic framework@Ni3S2 (Ni-TDC@Ni3S2) composites were prepared on a nickel foam substrate via a two-step hydrothermal method. The results indicate that Ni3S2 not only regulates the morphology and local electronic structure of Ni-TDC, but also enhances the structural stability, which leads to the superior OER performance with an overpotential of 220 mV at 10 mA cm-2, and the Tafel slop of 50.76 mV dec-1. Furthermore, the assembled overall water electrolysis device with Ni-TDC@Ni3S2 and RuNi-TDC as anode and cathode electrodes requires the voltage of only 1.50 V at a current density 10 mA cm-2, and it can run stably for more than 70 h. This study provides a new idea for enhancing the electronic conductivity of MOF-based electrocatalysts for efficient water oxidation.