Secretory leukocyte protease inhibitor as a novel predictive biomarker in patients with diabetic kidney disease

BackgroundSecretory leukocyte protease inhibitor (SLPI) is a multifunctional protein involved in the chronic inflammatory process, implicated in the pathogenesis of diabetic kidney disease (DKD). However, its potential as a diagnostic and prognostic biomarker of DKD has yet to be evaluated. This study explored the clinical utility of SLPI in the diagnosis and prognosis of renal endpoint events in patients with DKD.MethodsA multi-center cross-sectional study comprised of 266 patients with DKD and a predictive cohort study comprised of 120 patients with stage IV DKD conducted between December 2016 and January 2022. The clinical parameters were collected for statistical analysis, a multivariate Cox proportional hazards model was used to evaluate the independent risk factors for renal endpoints.ResultsSerum SLPI levels gradually increased with DKD progression (p<0.01). A significant correlation was observed between serum SLPI levels and renal function in patients with DKD. The mean follow-up duration in this cohort study was 2.32 ± 1.30 years. Multivariate Cox regression analysis showed SLPI levels≥51.61ng/mL (HR=2.95, 95% CI[1.55, 5.60], p<0.01), 24h urinary protein levels≥3500 mg/24h (HR=3.02, 95% CI[1.66, 5.52], p<0.01), Alb levels<30g/l (HR=2.19, 95% CI[1.12, 4.28], p<0.05), HGB levels<13g/dl (HR=3.18, 95% CI[1.49, 6.80], p<0.01), and urea levels≥7.1 mmol/L (HR=8.27, 95% CI[1.96, 34.93], p<0.01) were the independent risk factors for renal endpoint events in DKD patients.ConclusionsSerum SLPI levels increased with DKD progression and were associated with clinical parameters of DKD. Moreover, elevated SLPI levels showed potential prognostic value for renal endpoint events in individuals with DKD. These findings validate the results of previous studies on SLPI in patients with DKD and provide new insights into the role of SLPI as a biomarker for the diagnosis and prognosis of DKD that require validation

Challenges in the implementation of the NeoOBS study, a global pragmatic observational cohort study, to investigate the aetiology and management of neonatal sepsis in the hospital setting

Neonatal sepsis is a significant cause of mortality and morbidity in low- and middle-income countries. To deliver high-quality data studies and inform future trials, it is crucial to understand the challenges encountered when managing global multi-centre research studies and to identify solutions that can feasibly be implemented in these settings. This paper provides an overview of the complexities faced by diverse research teams in different countries and regions, together with actions implemented to achieve pragmatic study management of a large multi-centre observational study of neonatal sepsis. We discuss specific considerations for enrolling sites with different approval processes and varied research experience, structures, and training. Implementing a flexible recruitment strategy and providing ongoing training were necessary to overcome these challenges. We emphasize the attention that must be given to designing the database and monitoring plans. Extensive data collection tools, complex databases, tight timelines, and stringent monitoring arrangements can be problematic and might put the study at risk. Finally, we discuss the complexities added when collecting and shipping isolates and the importance of having a robust central management team and interdisciplinary collaborators able to adapt easily and make swift decisions to deliver the study on time and to target. With pragmatic approaches, appropriate training, and good communication, these challenges can be overcome to deliver high-quality data from a complex study in challenging settings through a collaborative research network

Challenges in the Implementation of the NeoOBS Study, a Global Pragmatic Observational Cohort Study, to Investigate the Aetiology and Management of Neonatal Sepsis in the Hospital Setting

Neonatal sepsis is a significant cause of mortality and morbidity in low- and middle-income countries. To deliver high-quality data studies and inform future trials, it is crucial to understand the challenges encountered when managing global multi-centre research studies and to identify solutions that can feasibly be implemented in these settings. This paper provides an overview of the complexities faced by diverse research teams in different countries and regions, together with actions implemented to achieve pragmatic study management of a large multi-centre observational study of neonatal sepsis. We discuss specific considerations for enrolling sites with different approval processes and varied research experience, structures, and training. Implementing a flexible recruitment strategy and providing ongoing training were necessary to overcome these challenges. We emphasize the attention that must be given to designing the database and monitoring plans. Extensive data collection tools, complex databases, tight timelines, and stringent monitoring arrangements can be problematic and might put the study at risk. Finally, we discuss the complexities added when collecting and shipping isolates and the importance of having a robust central management team and interdisciplinary collaborators able to adapt easily and make swift decisions to deliver the study on time and to target. With pragmatic approaches, appropriate training, and good communication, these challenges can be overcome to deliver high-quality data from a complex study in challenging settings through a collaborative research network

Hydrophobic modification of a PVDF hollow fiber membrane by plasma activation and silane grafting for membrane distillation

Polyvinylidene fluoride (PVDF) hollow fibers were hydrophobically modified using a simple and scalable method of plasma activation and silane grafting. The effects of plasma gas, applied voltage, activation time, silane type, and concentration were investigated according to the membrane hydrophobicity and direct contact membrane distillation (DCMD) performance. Two kinds of silane were used, including methyl trichloroalkyl silane (MTCS) and 1H,1H,2H,2H-perfluorooctane trichlorosilane silanes (PTCS). The membranes were characterized by techniques such as Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and contact angle. The contact angle of the pristine membrane was 88°, which increased to 112°–116° after modification. Meanwhile, the pore size and porosity decreased. In DCMD, the maximum rejection reached 99.95% by the MTCS-grafted membrane, while the flux decreased by 35% and 65% for the MTCS- and PTCS-grafted membranes, respectively. Treating humic acid-contained solution, the modified membrane showed steadier water flux and higher salt rejection than the pristine membrane, and 100% flux recovery was achieved by simple water flushing. This two-step method of plasma activation and silane grafting is very simple and effective to improve the hydrophobicity and DCMD performance of PVDF hollow fibers. However, further study on improving the water flux should be carried out. HIGHLIGHTS Hydrophobic modification of PVDF fibers were carried out by plasma activation and silane grafting.; The operation conditions were optimized according to hydrophobicity and MD performance.; The contact angles increased from 88° to 112°–116° after modification.; The salt rejection increased to 99.95%, while the flux reduced for the modified membranes.; The modified membrane showed higher resistance to humic acid fouling.

The existence of cautious pedestrians might facilitate evacuation dynamics

How to accurately simulate the real collective behavior of pedestrian evacuation remains an important issue in research of complex systems. The existing crowd simulation models in general assumed that pedestrians move directly towards the exit. In real life, however, there exist “cautious” pedestrians who fear trampling and crowding during evacuation, so we use an improved social force model to investigate how their presence influences evacuation dynamics. Simulation results reveal that the total evacuation time does not increase monotonically with the increment of the number of cautious pedestrians. Specifically, the presence of a moderate number of cautious pedestrians with rational psychological tolerance might substantially facilitate evacuation efficiency, compared with a conventional evacuation scenario. In addition, lower psychological tolerance promotes emergency evacuation, while increasing the tolerance threshold is conducive to slow evacuation. We hope that our research will provide some insights into the reasonable optimal strategies for emergency evacuation

Physical and 3D Printing Properties of Arrowroot Starch Gels

This paper aims to investigate the physical and 3D printing properties of arrowroot starch (AS), a natural biopolymer with many potential health benefits. Scanning electron microscopy images showed that AS granules had mixed spherical and elongated geometries, with average sizes of 10.5 ± 2.5 μm. The molecular weight of AS measured by gel permeation chromatography (GPC) was 3.24 × 107 g/mol, and the amylose/amylopectin ratio of AS was approximately 4:11. AS has an A-type crystal structure, with a gelatinization temperature of 71.8 ± 0.2 °C. The overlap concentration (C*) of AS in aqueous solutions was 0.42% (w/v). Temperature-dependent dynamic rheological analyses of 10% to 30% (w/v) AS fluids showed that the storage modulus (G’) reached the maximum values around the gelatinization temperatures, while the yield stress (τy) and flow stress (τf) values all increased with the increase in AS concentration. The printing accuracy of AS gels was found to be associated with the interplay between the G’ values and the restorability after extrusion, determined by the three-interval thixotropy tests (3ITT). The optimum 3D printing condition occurred at 20% (w/v) AS, the nozzle diameter of 0.60 mm, the printing speed of 100 mm/s and the extrusion speed of 100 mm/s. Our research provides a promising biopolymer to be used in the design of novel personalized functional foods

Using Twitter-Based Data for Sexual Violence Research: Scoping Review

BackgroundScholars have used data from in-person interviews, administrative systems, and surveys for sexual violence research. Using Twitter as a data source for examining the nature of sexual violence is a relatively new and underexplored area of study. ObjectiveWe aimed to perform a scoping review of the current literature on using Twitter data for researching sexual violence, elaborate on the validity of the methods, and discuss the implications and limitations of existing studies. MethodsWe performed a literature search in the following 6 databases: APA PsycInfo (Ovid), Scopus, PubMed, International Bibliography of Social Sciences (ProQuest), Criminal Justice Abstracts (EBSCO), and Communications Abstracts (EBSCO), in April 2022. The initial search identified 3759 articles that were imported into Covidence. Seven independent reviewers screened these articles following 2 steps: (1) title and abstract screening, and (2) full-text screening. The inclusion criteria were as follows: (1) empirical research, (2) focus on sexual violence, (3) analysis of Twitter data (ie, tweets or Twitter metadata), and (4) text in English. Finally, we selected 121 articles that met the inclusion criteria and coded these articles. ResultsWe coded and presented the 121 articles using Twitter-based data for sexual violence research. About 70% (89/121, 73.6%) of the articles were published in peer-reviewed journals after 2018. The reviewed articles collectively analyzed about 79.6 million tweets. The primary approaches to using Twitter as a data source were content text analysis (112/121, 92.5%) and sentiment analysis (31/121, 25.6%). Hashtags (103/121, 85.1%) were the most prominent metadata feature, followed by tweet time and date, retweets, replies, URLs, and geotags. More than a third of the articles (51/121, 42.1%) used the application programming interface to collect Twitter data. Data analyses included qualitative thematic analysis, machine learning (eg, sentiment analysis, supervised machine learning, unsupervised machine learning, and social network analysis), and quantitative analysis. Only 10.7% (13/121) of the studies discussed ethical considerations. ConclusionsWe described the current state of using Twitter data for sexual violence research, developed a new taxonomy describing Twitter as a data source, and evaluated the methodologies. Research recommendations include the following: development of methods for data collection and analysis, in-depth discussions about ethical norms, exploration of specific aspects of sexual violence on Twitter, examination of tweets in multiple languages, and decontextualization of Twitter data. This review demonstrates the potential of using Twitter data in sexual violence research

Enhancing the Stability of Aerobic Granular Sludge Process Treating Municipal Wastewater by Adjusting Organic Loading Rate and Dissolved Oxygen Concentration

Aerobic granular sludge (AGS) application in treating municipal wastewater has been greatly restricted due to its low stability. It has been found that operation parameters have a great impact on stability. The organic loading rate (OLR) and dissolved oxygen (DO) concentration are two very important parameters that impact stability. In this study, the organic loading rate (OLR) and aeration rate were studied to verify their influence on AGS system stability, which is indicated by determining pollutant removal performance, including chemical oxygen demand (COD), ammonia nitrogen, and total nitrogen (TN). The physical and chemical property changes of AGS and the effects of pollutant removal during the formation of AGS were systematically investigated. The AGS was formed after about 25 days and remained stable for about 45–50 days. The AGS was light-yellow globular sludge with an average particle size of 1.25 mm and a sludge volume index (SVI) of 33.9 mL/g. The optimal condition was obtained at an OLR of 4.2 kg COD/m3·d, aeration rate of 4 L/min, and a hydraulic retention time (HRT) of 4 h. The corresponding removal efficiencies of COD, ammonia nitrogen, and TN were 94.1%, 98.4% and 74.1%, respectively. The study shows that the AGS system has great potential for pollutant removal from wastewater

Innate Immunity, Inflammation, and Intervention in HBV Infection

Hepatitis B virus (HBV) infection is still one of the most dangerous viral illnesses. HBV infects around 257 million individuals worldwide. Hepatitis B in many individuals ultimately develops hepatocellular carcinoma (HCC), which is the sixth most common cancer and the third leading cause of cancer-related deaths worldwide. The innate immunity acts as the first line of defense against HBV infection through activating antiviral genes. Along with the immune responses, pro-inflammatory cytokines are triggered to enhance the antiviral responses, but this may result in acute or chronic liver inflammation, especially when the clearance of virus is unsuccessful. To a degree, the host innate immune and inflammatory responses dominate the HBV infection and liver pathogenesis. Thus, it is crucial to figure out the signaling pathways involved in the activation of antiviral factors and inflammatory cytokines. Here, we review the interplay between HBV and the signal pathways that mediates innate immune responses and inflammation. In addition, we summarize current therapeutic strategies for HBV infection via modulating innate immunity or inflammation. Characterizing the mechanisms that underlie these HBV-host interplays might provide new approaches for the cure of chronic HBV infection

Two novel AP2/EREBP transcription factor genes TaPARG have pleiotropic functions on plant architecture and yield-related traits in common wheat

AP2/EREBPs play significant roles in plant growth and development. The novel, pleiotropic TaPARG (PLANT ARCHITECTURE-RELATED GENE), a member of the AP2/EREBP transcription factor gene family, and its flanking sequences were isolated in wheat (Triticum aestivum L.). Two TaPARG genes were identified and named as TaPARG-2A and TaPARG-2D. Their amino acid sequences were highly similar especially in the functional domains. TaPARG-2A on chromosome 2A was flanked by markers Xwmc63 and Xgwm372. TaPARG-2D was mapped to chromosome 2D. Subcellular localization revealed that TaPARG-2D was localized in the nucleus. The results of tissue expression pattern, overexpression in rice, association analysis and distinct population verification jointly revealed that TaPARG functions during the entire growth cycle of wheat. Its functions include regulation of plant architecture-related and yield-related traits. Association analysis, geographic distribution and allelic frequencies suggested that favored haplotypes Hap-2A-2 and Hap-2A-3 were selected in Chinese wheat breeding programs. Both favored haplotypes might be caused by a single amino acid substitution (His/Tyr). These results suggest that TaPARG is a regulatory factor in plant growth and development, and that the favored alleles might be useful for improving plant architecture and grain yield of wheat