Explore the vast range of titles available.

The contribution of Cutibacterium acnes (C. acnes) infection to intervertebral disc degeneration (IDD) and the antibiotic therapy has evoked several controversies in recent years. While some microbiology studies report bacterial disc infection within IDD patients, others attribute the positive results to contamination during prolonged cultures. In addition to the clinical controversy, little was known about the mechanism of C. acnes-caused Modic changes (MCs) if C. acnes was the pathogenic factor. This study aimed to investigate the inflammatory mechanism of MCs induced by different phylotypes of C. acnes in patients with IDD. Specimens from sixty patients undergoing microdiscectomy for disc herniation were included, C. acnes were identified by anaerobic culture, followed by biochemical and PCR-based methods. The identified species of C. acnes were respectively inoculated into the intervertebral discs of rabbits. MRI and histological change were observed. Additionally, we detected MMP expression in the rabbit model using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Of the 60 cases, 18 (30%) specimens were positive for C. acnes, and we identified 4 of 6 defined phylogroups: IA, IB, II and III. The rabbits that received Type IB or II strains of C. acnes showed significantly decreased T1WI and higher T2WI at eighth weeks, while strain III C. acnes resulted in hypointense signals on both T1WI and T2WI. Histological examination results showed that all of the three types of C. acnes could cause disc degeneration and endplates rupture. Moreover, endplate degeneration induced by type IB or II strains of C. acnes is related with MMP13 expression. Meanwhile, strain III C. acnes might upregulated the level of MMP3. This study suggested that C. acnes is widespread in herniated disc tissues. Different types of C. acnes could induce different MCs by increasing MMP expression.

Eye diseases and injuries impose a significant clinical problem worldwide. Safe and effective ocular drug delivery is, however, challenging due to the presence of ocular barriers. Here we report a strategy using an eye patch equipped with an array of detachable microneedles. These microneedles can penetrate the ocular surface tissue, and serve as implanted micro-reservoirs for controlled drug delivery. The biphasic drug release kinetics enabled by the double-layered micro-reservoirs largely enhances therapeutic efficacy. Using corneal neovascularization as the disease model, we show that delivery of an anti-angiogenic monoclonal antibody (DC101) by such eye patch produces ~90% reduction of neovascular area. Furthermore, quick release of an anti-inflammatory compound (diclofenac) followed by a sustained release of DC101 provides synergistic therapeutic outcome. The eye patch application is easy and minimally invasive to ensure good patient compliance. Such intraocular drug delivery strategy promises effective home-based treatment of many eye diseases. Treatment for eye injuries and diseases is most efficient when delivered directly into the eye. Here, the authors developed a patient-friendly eye patch equipped with an array of detachable microneedles, through which drugs can be delivered through the cornea for an extended period of time.

Background Prediction scoring systems for coronary artery bypass grafting (CABG) patients on venoarterial extracorporeal membrane oxygenation (VA-ECMO) have not yet been reported. This study was designed to develop a predictive score for in-hospital mortality for cardiogenic shock patients who received VA-ECMO after isolated CABG. Methods Retrospective cohort study of consecutive CABG patients supported with VA-ECMO ( n  = 166) at the Beijing Anzhen Hospital between February 2004 and March 2017. Results One hundred and six patients (64%) could be weaned from VA-ECMO, and 74 patients (45%) survived to hospital discharge. On the basis of multivariable logistic regression analyses, the pRedicting mortality in patients undergoing veno-arterial Extracorporeal MEMBrane oxygenation after coronary artEry bypass gRafting (REMEMBER) score was created with six pre-ECMO parameters: older age, left main coronary artery disease, inotropic score > 75, CK-MB > 130 IU/L, serum creatinine > 150 umol/L, and platelet count < 100 × 10 9 /L. Four risk classes, namely class I (REMEMBER score 0–13), class II (14–19), class III (20–25), and class IV (> 25) with their corresponding mortality (13%, 55%, 70%, and 94%, respectively), were identified. The area under the receiver operating characteristic curve 0.85(95% CI 0.79–0.91) for the REMEMBER score was better than those for the SOFA, SAVE, EuroSCORE, and ENCOURAGE scores in this population. Conclusions The REMEMBER score might help clinicians at bedside to predict in-hospital mortality for patients receiving VA-ECMO after isolated CABG for refractory cardiogenic shock. Prospective studies are needed to externally validate this scoring system.

Rapid population and economic growth have led to an increased demand for water and food, thereby exacerbating the water scarcity crisis. Therefore, an objective assessment of water usage in crop production is crucial for ensuring national food security and alleviating water scarcity. However, the city-scale crop production water footprint (CWF) in China remains incomplete, while grid-scale CWF data are plagued by the limitations of coarse crop statistics. To fill this knowledge gap, we propose a novel methodology for developing a high-resolution inventory of CWFs. Based on this methodology, we quantified the city-scale water footprint (WF) of three major crops (rice, wheat, and maize) in China and allocated the CWFs of individual cities to 3 km × 3 km grids through a top-down downscaling approach to create a high-resolution CWF inventory. The results show that the average annual CWF of the three crops from 2000 to 2020 was in the order of rice (2.50 × 10 12 m 3 ), maize (1.55 × 10 12 m 3 ) , and wheat (1.21 × 10 12 m 3 ). During the study period, the dependence on green water resources for crop production in China increased, especially for maize, which showed a relative increase of 106.76% in green water demand, in addition to optimal water use efficiency, with the dual advantages of combining high yield and low irrigation dependence. At a grid scale of 3 km × 3 km, the CWFs of the three crops followed the same order as at the city scale. Furthermore, the green water footprint (GWF) of each of the three crops increased at different rates during the study period, with maize showing a particularly significant increase of 59.26%. Meanwhile, the blue water footprint (BWF) per unit area for rice and wheat increased, while the BWF for maize decreased by 0.94%. This finding implies that maize cultivation is more efficient in utilizing rainwater resources, thereby reducing dependence on blue water. The inventory established in this study can assist in optimizing crop production in various regions of China, thereby mitigating the effects of water scarcity and facilitating sustainable agricultural development.

Preliminary research has found that MENK can upregulate the antiviral state of macrophages to inhibit influenza virus infection. To further study the immunomodulatory mechanism of MENK in macrophages against reovirus, we used RNA-Seq technology to analyze the genomic changes between macrophages infected with Nelson Bay orthoreoviruses (Miyazaki) after MENK pretreatment and those infected with Miyazaki alone. A total of 3,624 genes were screened, with 1,817 genes upregulated and 1,447 genes downregulated. Differentially expressed genes were mainly enriched in the cell cycle (ko04110), FoxO signaling pathway (ko04068), cell adhesion molecules (ko04514), Fc receptor-mediated endocytosis (ko04666), and antigen processing and presentation pathways (ko04612). Key genes such as IL6ST, TNFR2, CCL24, MHC I, MHC II, CD28, FOXO-1, SYK, and CYCD1 were successfully docked with the MENK molecule. Genomic analysis showed that MENK enhanced the immune function of macrophages by upregulating cytokine-related molecules such as CCL24, IL6ST, and TNFR2 to recruit and induce inflammatory responses. Moreover, MENK upregulated the expression of MHC I, MHC II, and CD28 to promote antigen presentation and initiate adaptive immune responses and regulated the FOXO-CYCD1 pathway to inhibit the cell cycle, thereby exerting antiviral effects during reovirus infection.

Virtual water trade (VWT) links local water withdrawal (WW) with distant consumption. Given the significant contradictions between China’s water demand and supply, it is urgent to clarify the responsibilities for WW (RWW) in VWT. Previous studies considering this responsibility have focused solely on the absolute volume of WW; however, the disparities in water availability and economic capacity lead to differing implications of the same WW action across regions. Here, to reassess the RWW, we introduce water scarcity index and value-added to WW and propose the concept of the three-dimensional water footprint (3DWF). We reveal the distribution distinction between WW and 3DWF among China’s regions. In addition, we explore how the 3DWF is transferred within the supply chain and further reveal its inequality and the contributions of regions to the inequality. We find that the distribution of 3DWF has changed dramatically compared to WW, primarily concentrating in China’s economic center. The 3DWF inequality primarily results from the distribution of 3DWF-local, with a Gini coefficient of 0.7556. Xinjiang has only 1.8% of the population but is responsible for 22% of the 3DWF-local in China and has become the largest contributor to the inequality. Notably, this inequality is mitigated when 3DWF-non-local is taken into account. Our findings provide new insights into the establishment of rigid constraints and the sustainable spatial deployment of water resources.

Lane departure crashes were more likely to result in severe traffic crashes. This objective of this study was to explore the effects of drivers’ characteristics on the asymmetric lane departure behaviour in combined curves. A high degree of freedom driving simulator was used to collected vehicle operation data in a mountainous freeway. Totally 948 lane departure events were collected. The lane departure behaviour was classified into two categories based on centrifugal force direction: In the Direction of Centrifugal Force (IDCF) and Against the Direction of Centrifugal Force (ADCF). The average speed, maximum lateral departure and departure duration distance were analyzed. A Multivariate Adaptive Regression Splines (MARS) model was used to analyze nonlinear relationships between driver characteristics and maximum lane departure. It found that: (1) Sag-curves and crest-curves had higher average lane departure frequencies compared to downslope- and upslope-curves. (2) IDCF events showed greater departure (0.83 m > 0.41 m) and longer departure duration distance (70.07 m > 58.60 m) than ADCF events. (3) The years of driving, daily driving distance, driving experience, road expert type and departure duration distance had significantly influence on departure severity. Also, driver characteristics and lane departure duration distance had an interaction effect on departure severity. (4) Speed and road geometry design could jointly influence the degree of lane departure, e.g., speed significantly affects lane departure behaviour on downslope-curves and upslope-curves in the IDCF scenario. (5) The lane departure duration distance threshold (35.00–110.00 m), and speed threshold (86.77–108.63 km/h) were proposed for the lane departure process. The study provided a basis for the optimisation of ADAS systems, the development of targeted driver training for high-risk drivers, and the optimisation of visual guidance design for combined curves.

Objective We aimed to identify independent risk factors for perineural invasion (PNI) in early gastric cancer (EGC) and to construct the first individualized nomogram for predicting PNI risk. Methods We retrospectively analyzed clinicopathological data from 416 EGC patients who underwent radical gastrectomy between December 2019 and August 2025. The optimal set of risk predictors for PNI was selected using the LASSO regression model with ten-fold cross-validation. Independent risk factors were subsequently identified via multivariable logistic regression analysis. For internal validation, we randomly selected 30% of the sample as a validation set using R software (version 4.4.2). The model’s performance was comprehensively evaluated by assessing its discrimination (area under the receiver operating characteristic curve, AUC), calibration (Hosmer-Lemeshow test and calibration curve), and clinical utility (decision curve analysis, DCA). Results A total of 416 patients were included in the final analysis, among whom 30 (7.21%) had PNI. LASSO regression analysis identified eight predictors for PNI: age, CEA level (ng/mL), tumor location, maximum tumor thickness, tumor differentiation, lymphovascular invasion, Lauren classification, and pT stage. These variables were subsequently incorporated into a multivariable logistic regression model. The analysis revealed that age (OR = 1.105, 95% CI: 1.029–1.187, P  = 0.006), CEA level (OR = 59.489, 95% CI: 3.456–1023.871, P  = 0.005), maximum tumor thickness (OR = 38.807, 95% CI: 3.408–441.872, P  = 0.003), and lymphovascular invasion (OR = 4.131, 95% CI: 1.337–12.768, P  = 0.014) were independent risk factors for PNI in EGC (all P  < 0.05). The nomogram demonstrated strong discriminative ability, with AUC values of 0.895 (95% CI: 0.839–0.950) in the training cohort and 0.783 (95% CI: 0.625–0.940) in the validation cohort. The Hosmer–Lemeshow test indicated good model calibration in both the training (χ² = 11.994, P  = 0.152) and validation cohorts (χ² = 3.833, P  = 0.872). DCA showed substantial clinical net benefits across a wide range of threshold probabilities. Conclusion In conclusion, this study identified age, CEA level, maximum tumor thickness, and lymphovascular invasion as independent predictors of PNI in EGC. We developed the first nomogram for individualized PNI risk assessment, which demonstrated strong predictive performance, good calibration, and clinical usefulness. Although this tool offers a reliable approach for personalized risk evaluation, further multicenter validation is necessary to enhance its clinical applicability.