Ultrasensitive CCL2 Detection in Urine for Diabetic Nephropathy Diagnosis Using a WS2-Based Plasmonic Biosensor.

The accurate diagnosis of diabetic nephropathy relies on achieving ultrasensitive biosensing for biomarker detection. However, existing biosensors face challenges such as poor sensitivity, complexity, time-consuming procedures, and high assay costs. To address these limitations, we report a WS2-based plasmonic biosensor for the ultrasensitive detection of biomarker candidates in clinical human urine samples associated with diabetic nephropathy. Leveraging plasmonic-based electrochemical impedance microscopy (P-EIM) imaging, we observed a remarkable charge sensitivity in monolayer WS2 single crystals. Our biosensor exhibits an exceptionally low detection limit (0.201 ag/mL) and remarkable selectivity in detecting CC chemokine ligand 2 (CCL2) protein biomarkers, outperforming conventional techniques such as ELISA. This work represents a breakthrough in traditional protein sensors, providing a direction and materials foundation for developing ultrasensitive sensors tailored to clinical applications for biomarker sensing.

2-D Heterometallic Pb-Iodoargentate Framework [PbAg2I6]n with a Diskoid [Pb(18-crown-6)]2+ Linker and Cocatalyst for Synergistically Enhanced Photocatalytic Properties via g-C3N4 Doping.

The heterometallic Pb-iodoargentate hybrid [Pb(18-crown-6)(PbAg2I6)]n (1; 18-crown-6 = 1,4,7,10,13,16-hexaoxacyclooctadecane) was prepared via self-assembly of the tetrahedal AgI4 and octahedral PbI6 primary units using crown ether 18-crown-6 as an organic ligand in DMF solvent. The hybrid heterocomposite cocatalyst based on 1 and graphitic carbon nitride (g-C3N4) was prepared by a facile solvothermal method. In 1, the dimeric units Ag2I6 and Pb2I10 are joined via face sharing, leading to a ternary heterometallic 1-D [PbAg2I62-]n chain containing novel Ag2Pb2I4 cubes. The 1-D chains are joined by the discoid [Pb(18-crown-6)]2+ complex cations, forming the 2-D [Pb(18-crown-6)(PbAg2I6)]n hybrid with the skeleton of [Pb2Ag2I6]n. Compound 1 shows photocatalytic activity in the degradation of MB at room temperature under visible-light irradiation. The photoelectric response measurement showed that the photocurrent of 1 increased from 1.41 to 2.43 µA/cm-2 when g-C3N4 was loaded, indicating that the introduction of a certain amount of g-C3N4 on the surface of 1 improves the separation and migration rate of photoinduced electrons and holes. The 1/g-C3N4 composite showed much higher photocatalytic efficiency in comparison to pristine 1 and g-C3N4 for MB degradation, which suggests the synergistic effect between 1 and g-C3N4 toward visible-light-driven photocatalytic performance. Meanwhile, the 1/g-C3N4 composite exhibited good reusability and stability in the photocatalytic reaction. Free radical quenching experiments showed that the •O2- radical is the main reactive substance over catalyst 1, while h+, •OH, and •O2- species have synergistic effects over the 1/g-C3N4 composite catalyst in the process of photodegradation.

Impact of the Time-Weighted Average Glucose Concentration and Diabetes on In-Hospital Mortality in Critically Ill Patients Older Than 75 Years: A Retrospective Cohort Study.

OBJECTIVE: To evaluate the effects of diabetes and hyperglycemia on in-hospital mortality in critically ill patients older than 75 years. METHODS: This was a single-center retrospective cohort study of patients older than 75 years in the first intensive care unit stay. The patients were divided into the following 4 groups: time-weighted average glucose (TWAG) <140 mg/dL without diabetes (group 1), TWAG ≥140 mg/dL without diabetes (group 2), TWAG <180 mg/dL with diabetes (group 3), and TWAG ≥180 mg/dL with diabetes (group 4). Clinical and laboratory data were analyzed. RESULTS: A total of 6760 patients over 75 years of age were included, including 2089 patients previously diagnosed with diabetes. The patients in group 2 had the highest in-hospital mortality (27.4%). In the fully adjusted regression model, the risk of in-hospital mortality increased by 76% (odds ratio = 1.76, 95% CI: 1.49-2.08) in group 2 as compared with group 1. Those from groups 3 and 4 exhibited risks equivalent to the risks of those in group 1; similar results were observed in the subgroup analysis. A J-shaped curve relationship and threshold effect were observed in patients without diabetes. For those with diabetes, a flatter curve pattern with a small slope was observed. CONCLUSION: Stress hyperglycemia was more detrimental to short-term prognosis than diabetes status in these patients. Looser glucose control may be suitable for patients older than 75 years with diabetes but unnecessary for those without diabetes. Patients with diabetes may be more resistant to the detrimental effects of glucose variations.

Group Decision Making-Based Fusion for Human Activity Recognition in Body Sensor Networks.

Ensemble learning systems (ELS) have been widely utilized for human activity recognition (HAR) with multiple homogeneous or heterogeneous sensors. However, traditional ensemble approaches for HAR cannot always work well due to insufficient accuracy and diversity of base classifiers, the absence of ensemble pruning, as well as the inefficiency of the fusion strategy. To overcome these problems, this paper proposes a novel selective ensemble approach with group decision-making (GDM) for decision-level fusion in HAR. As a result, the fusion process in the ELS is transformed into an abstract process that includes individual experts (base classifiers) making decisions with the GDM fusion strategy. Firstly, a set of diverse local base classifiers are constructed through the corresponding mechanism of the base classifier and the sensor. Secondly, the pruning methods and the number of selected base classifiers for the fusion phase are determined by considering the diversity among base classifiers and the accuracy of candidate classifiers. Two ensemble pruning methods are utilized: mixed diversity measure and complementarity measure. Thirdly, component decision information from the selected base classifiers is combined by using the GDM fusion strategy and the recognition results of the HAR approach can be obtained. Experimental results on two public activity recognition datasets (The OPPORTUNITY dataset; Daily and Sports Activity Dataset (DSAD)) suggest that the proposed GDM-based approach outperforms the well-known fusion techniques and other state-of-the-art approaches in the literature.

Application of 3-Alkyl-2-vinylindoles in Catalytic Asymmetric Dearomative (2+3) Cycloadditions.

The first application of 3-alkyl-2-vinylindoles in catalytic asymmetric dearomative cycloadditions was established by chiral phosphoric acid (CPA)-catalyzed (2+3) cycloaddition with azoalkenes, leading to the generation of chiral pyrroloindolines bearing two tetrasubstituted stereogenic centers in good yields (61-96%) and excellent stereoselectivities (all >95:5 dr, 86-99% ee). This reaction has realized the first enantioselective dearomative cycloaddition of 3-alkyl-2-vinylindoles, which brings a new reactivity to this class of vinylindoles and will enrich the chemistry of 3-alkyl-2-vinylindoles. In addition, this approach has provided a useful strategy for the construction of enantioenriched pyrroloindoline skeletons bearing two tetrasubstituted stereogenic centers. More importantly, the bioassay of these chiral pyrroloindolines has revealed that some compounds exhibit strong anti-cancer activity against Hela and MCF-7 cell lines, which will be helpful for discovering anti-cancer drug candidates.

Polymeric Iodoargentate Hybrids Incorporating Octakis- or Heptakis-Solvated Lanthanide Complexes: Syntheses, Crystal Structures, and Photocatalysis.

New iodoargentate hybrids containing lanthanide complexes, [La(DMA)8]Ag9I12·2H2O (1) and [Ln(DMA)7]2Ag16I22 (Ln = Pr (2), Sm(3); DMA = N,N-dimethylacetamide), were prepared by diffusion methods using DMA-solvated lanthanide complexes as structure-directing agents. The octakis-solvated La3+ cation leads to formation of the 1-D nonanuclear [Ag9I12]n3n- polymeric anion constructed by AgI4 tetrahedral units through edge sharing, while the heptakis-solvated Ln3+ (Ln = Pr, Sm) cation affords the new 1-D hexadecanuclear [Ag16I22]n6n- polymeric anion built up from AgI4 units by both corner and edge sharing. Compounds 1-3 possess band gaps of 2.58, 2.77, and 2.74 eV, respectively, and show steady photocurrents in the range 14.2-18.0 µA under Xe light irradiation. They are photocatalytic active in the degradation of organic pollutants of crystal violet (CV) and rhodamine B (RhB) in water at room temperature. 2 and 3 perform higher photocatalytic activities than 1 in the CV degradation, which is attributed to the different photocurrent intensities. Photocatalytic mechanism investigations on compounds 2 and 3 show that h+ hole and ·O2- radical play major roles in the CV degradation, respectively.

Gga-miR-30d regulates infectious bronchitis virus infection by targeting USP47 in HD11 cells.

Avian infectious bronchitis virus (IBV) is a coronavirus which infects chickens and causes severe economic losses to the poultry industry worldwide. MicroRNAs (miRNAs) are important intracellular regulators and play a pivotal role in viral infections. In previous studies, we have revealed that IBV infection caused a significant down-regulation of gga-miR-30d expression in chicken kidneys. In present study, we investigated the role of gga-miR-30d in the process of IBV infection of HD11 cell line in vitro. By transfecting the mimics and inhibitor of gga-miR-30d, it was found that overexpressed gga-miR-30d inhibited IBV replication. Contrarily, low-expressed gga-miR-30d promoted IBV replication. In addition, dual-luciferase reporter assays revealed that ubiquitin-specific protease 47 (USP47), a deubiquitinase-encoding gene, was a target for gga-miR-30d. This is the first study demonstrating that miRNAs regulate IBV replication by regulating the deubiquitinating enzyme (DUBs).

Optimizing Sensor Deployment for Multi-Sensor-Based HAR System with Improved Glowworm Swarm Optimization Algorithm.

Human activity recognition (HAR) technology that analyzes and fuses the data acquired from various homogeneous or heterogeneous sensor sources has motivated the development of enormous human-centered applications such as healthcare, fitness, ambient assisted living and rehabilitation. The concurrent use of multiple sensor sources for HAR is a good choice because the plethora of user information provided by the various sensor sources may be useful. However, a multi-sensor system with too many sensors will bring large power consumption and some sensor sources may bring little improvements to the performance. Therefore, the multi-sensor deployment research that can gain a tradeoff among computational complexity and performance is imperative. In this paper, we propose a multi-sensor-based HAR system whose sensor deployment can be optimized by selective ensemble approaches. With respect to optimization of the sensor deployment, an improved binary glowworm swarm optimization (IBGSO) algorithm is proposed and the sensor sources that have a significant effect on the performance of HAR are selected. Furthermore, the ensemble learning system based on optimized sensor deployment is constructed for HAR. Experimental results on two datasets show that the proposed IBGSO-based multi-sensor deployment approach can select a smaller number of sensor sources while achieving better performance than the ensemble of all sensors and other optimization-based selective ensemble approaches.

The "hyper-triglyceridemic waist phenotype" is a reliable marker for prediction of accumulation of abdominal visceral fat in Chinese adults.

PURPOSE: The "hyper-triglyceridemic waist (HTW) phenotype" is relatively convenient to identify, acquired readily, and is inexpensive. We explored the relationship between the HTW phenotype and abdominal-fat accumulation in Chinese adults. METHODS: The study cohort comprised 195 adults divided into four groups according to triglyceride (TG) concentration and waist circumference (WC): normal (A), "hyper-TG" (B), "hyper-WC" (C) and the HTW phenotype (D). The abdominal-fat compartment was measured by magnetic resonance imaging. A 75-g oral glucose tolerance test (OGTT) was administered after an overnight fast. Clinical, anthropometric and laboratory data were analyzed. RESULTS: Individuals with the HTW phenotype had the highest WC, Conicity Index, waist:hip ratio and abdominal visceral fat (AVF) area, and the highest TG and uric-acid concentrations among the four groups. People with the HTW phenotype were older, had higher blood pressure than those with normal WC (groups A and B). In the OGTT, participants with the HTW phenotype had the highest insulin resistance and lowest insulin sensitivity. In binary logistic regression analysis, age, sex, Body Mass Index, high concentrations of density lipoprotein-cholesterol and low-density lipoprotein-cholesterol, and the HTW phenotype were independent risk factors for predicting AVF accumulation with a sensitivity of 81.08% and specificity of 90.91%. CONCLUSIONS: Chinese adults with the HTW phenotype had the highest AVF area and insulin resistance, and were associated with higher blood pressure than individuals with normal WC. The HTW phenotype is a reliable marker for prediction of AVF accumulation associated with insulin resistance. LEVEL OF EVIDENCE: IV.

Genetic characterization of a novel G9P[23] rotavirus A strain identified in southwestern China with evidence of a reassortment event between human and porcine strains.

Group A rotaviruses (RVAs) are important zoonotic pathogens that cause intestinal disease in humans and other mammals. In this study, the novel strain RVA/Pig/China/SC11/2017/G9P[23](SC11) was isolated from fecal samples from a pig farm in Sichuan province, southwestern China. The complete genome was found to be 18,347 bp in length with 11 segments. The genotype constellation of strain SC11 was G9-P[23]-I12-R1-C1-M1-A1-N1-T1-E1-H1, according to whole-genome sequencing analysis. The VP1, VP2, VP4, VP6, NSP1-NSP3, and NSP5 genes of RVA strain SC11 were found to be closely related to those of porcine and/or porcine-like human RVAs. Meanwhile, the VP7 and NSP4 genes of strain SC11 were closely related to genes of human RVAs. However, it was difficult to pinpoint the porcine or human origin of the VP3 gene of strain SC11 based on the available data. These results showed that SC11 originated from a natural reassortment event between human and pig RVA strains, and crossover points for recombination were identified at nucleotides (nt) 109-806 of NSP2. This is the first report of such a reassortant and recombinant RVA strain in the southwestern region of China.