A study on the configuration of factors influencing overweight and obesity in adolescents based on fuzzy set qualitative comparative analysis.

OBJECTIVE: Overweight and obesity among adolescents are grave public health issues around the world. Although the conditions that contribute to obesity have been extensively researched, little is known about how multiple conditions interact to cause overweight and obesity. The current study intends to investigate the histomorphic configuration pathways of several conditions of adolescent overweight and obesity by gender. METHOD: The data came from a social survey conducted in June 2021 in Changchun, Jilin Province, China. The sample collected was 14-year-old adolescents, including 167 boys and 137 girls. The school physicians examined the participants' weight and height, and questionnaires were used to collect risk indicators from adolescents, such as sleep duration, electronic screens times, consumption of sugary drinks and fried foods, and physical activity. Simultaneously, a Fuzzy Qualitative Comparative Analysis will be performed to investigate the combinations of diverse conditions. RESULT: We found that there is no determining necessary condition that, once present, directly determines that an individual is in a state of overweight and obesity. Simultaneously, this study revealed nine alternative configurational paths of overweight and obesity in teenagers of different genders, with a concordance of 0.805 for six male groupings and 0.916 for three female groupings. The outcomes of overweight obesity in adolescents under different genders are similar but not identical. CONCLUSION: This study examined the interactions of a number of conditions from the individual, behavioral, learning and living environment that led to the same overweight obese outcome among adolescents of different genders. Our research will be useful to policymakers in that interventions should take into account the combined effects of a number of different aspects rather than focusing on a single factor that causes overweight and obesity.

Bone alteration and esthetics associated with implant-supported prostheses in the anterior maxilla under different implant placement timing: A retrospective clinical study of 1 to 3 years.

STATEMENT OF PROBLEM: Different factors influence alterations in facial bone thickness and esthetic outcomes after implant placement. Whether the timing of implant placement influences alterations in the bone dimensional and esthetic outcomes is unclear. PURPOSE: The purpose of this retrospective clinical study was to assess the influence of the timing of implant placement on alveolar bone alterations and esthetic outcome. MATERIAL AND METHODS: Data were collected from 40 patients who had received guided bone regeneration (GBR) performed simultaneously with immediate, early, or delayed single-tooth implant placement in the anterior maxilla. Facial and palatal horizontal bone thicknesses (FHBT, PHBT) and vertical bone level (FVBL, PVBL) immediately after surgery (T0), at 6 months after implant placement (T1), and at 1 to 3 years follow-up (T2) were measured, and the changes calculated. The pink esthetic score (PES) and white esthetic score (WES) were evaluated at the 1- to 3-year follow-up. The Kruskal-Wallis followed by the Dunn t test was applied to evaluate bone alteration among groups, and the Bonferroni method was used for adjusting multiple comparisons. The 1-way ANOVA test was used to determine any significance in the esthetic outcome in the 3 groups (α=.05). RESULTS: The reduction in the FHBT0 of the immediate, early, and delayed implant placement group (T2-T0) was -1.17 (-1.70, -0.61) mm, -1.53 (-1.69, -0.49) mm, and -1.47 (-2.30, -0.20) mm, respectively. The FHBT around the implant apices remained basically stable. No obvious changes in the PHBT around the implants of the immediate and delayed implant placement group were noted. The FVBL significantly decreased in each group during the follow-up period (-1.34 (01.88, -0.56) mm, immediate; -2.88 (-3.79, -1.07) mm, early; -1.26 (-2.52, -0.48) mm, delayed). The PVBL change in the early implant placement group (-2.18 (-3.26, -0.86) mm) was more significant than that in the immediate (-0.55 (-2.10, -0.17) mm) and delayed (-0.51 (-1.29, 0.02) mm) implantation groups (P =.013). The mean ±standard deviation PES/WES score of the immediate (15.6 ±1.84) and early (15.00 ±1.13) implant placement groups was higher than that of the delayed implant placement group (13.92 ±2.10) without significant difference. CONCLUSIONS: Similar bone changes and esthetic outcomes were found around implants of the immediate, early, and delayed implant placement groups.

Improved Ballistic Impact Resistance of Nanofibrillar Cellulose Films with Discontinuous Fibrous Bouligand Architecture.

Natural protective materials offer unparalleled solutions for impact-resistant material designs that are simultaneously lightweight, strong, and tough. Particularly, the Bouligand structure found in the dactyl club of mantis shrimp and the staggered structure in nacre achieve excellent mechanical strength, toughness, and impact resistance. Previous studies have shown that hybrid designs by combining different bioinspired microstructures can lead to enhanced mechanical strength and energy dissipation. Nevertheless, it remains unknown whether combining Bouligand and staggered structures in nanofibrillar cellulose (NFC) films, forming a discontinuous fibrous Bouligand (DFB) architecture, can achieve enhanced impact resistance against projectile penetration. Additionally, the failure mechanisms under such dynamic loading conditions have been minimally understood. In our study, we systematically investigate the dynamic failure mechanisms and quantify the impact resistance of NFC thin films with DFB architecture by leveraging previously developed coarse-grained models and ballistic impact molecular dynamics simulations. We find that when nanofibrils achieve a critical length and form DFB architecture, the impact resistance of NFC films outperforms the counterpart films with continuous fibrils by comparing their specific ballistic limit velocities and penetration energies. We also find that the underlying mechanisms contributing to this improvement include enhanced fibril sliding, intralayer and interlayer crack bridging, and crack twisting in the thickness direction enabled by the DFB architecture. Our results show that by combining Bouligand and staggered structures in NFC films, their potential for protective applications can be further improved. Our findings can provide practical guidelines for the design of protective films made of nanofibrils.

Evolution and health risk of indicator microorganisms in landscape water replenished by reclaimed water.

As an important means to solve water shortage, reclaimed water has been widely used for landscape water supply. However, with the emergence of large-scale epidemic diseases such as SARS, avian influenza and COVID-19 in recent years, people are increasingly concerned about the public health safety of reclaimed water discharged into landscape water, especially the pathogenic microorganisms in it. In this study, the water quality and microorganisms of the Old Summer Palace, a landscape water body with reclaimed water as the only replenishment water source, were tracked through long-term dynamic monitoring. And the health risks of indicator microorganisms were analyzed using Quantitative Microbial Risk Assessment (QMRA). It was found that the concentration of indicator microorganisms Enterococcus (ENT), Escherichia coli (EC) and Fecal coliform (FC) generally showed an upward trend along the direction of water flow and increased by more than 0.6 log at the end of the flow. The concentrations of indicator microorganisms were higher in summer and autumn than those in spring. And there was a positive correlation between the concentration of indicator microorganisms and COD. Further research suggested that increased concentration of indicator microorganisms also led to increased health risks, which were more than 30% higher in other areas of the park than the water inlet area and required special attention. In addition, (water) surface operation exposure pathway had much higher health risks than other pathways and people in related occupations were advised to take precautions to reduce the risks.

Fluorescence-Recovered Wearable Hydrogel Patch for In Vitro Detection of Glucose Based on Rare-Earth Nanoparticles.

The physiological state of the human body can be indicated by analyzing the composition of sweat. In this research, a fluorescence-recovered wearable hydrogel patch has been designed and realized which can noninvasively monitor the glucose concentration in human sweat. Rare-earth nanoparticles (RENPs) of NaGdF4 doped with different elements (Yb, Er, and Ce) are synthesized and optimized for better luminescence in the near-infrared second (NIR-II) and visible region. In addition, RENPs are coated with CoOOH of which the absorbance has an extensive peak in the visible and NIR regions. The concentration of H2O2 in the environment can be detected by the fluorescence recovery degree of CoOOH-modified RENPs based on the fluorescence resonance energy transfer effect. For in vivo detection, the physiological state of oxidative stress at tumor sites can be visualized through its fluorescence in NIR-II with low background noise and high penetration depth. For the in vitro detection, CoOOH-modified RENP and glucose oxidase (GOx) were doped into a polyacrylamide hydrogel, and a patch that can emit green upconversion fluorescence under a 980 nm laser was prepared. Compared with the conventional electrochemical detection method, the fluorescence we presented has higher sensitivity and linear detection region to detect the glucose. This improved anti-interference sweat patch that can work in the dark environment was obtained, and the physiological state of the human body is conveniently monitored, which provides a new facile and convenient method to monitor the sweat status.

Unveiling the Nanoconfinement Effect on Crystallization of Semicrystalline Polymers Using Coarse-Grained Molecular Dynamics Simulations.

Semicrystalline polymers under nanoconfinement show distinct structural and thermomechanical properties compared to their bulk counterparts. Despite extensive research on semicrystalline polymers under nanoconfinement, the nanoconfinement effect on the local crystallization process and the unique structural evolution of such polymers have not been fully understood. In this study, we unveil such effects by using coarse-grained molecular dynamics simulations to study the crystallization process of a model semicrystalline polymer-polyvinyl alcohol (PVA)-under different levels of nanoconfinement induced by nanoparticles that are represented implicitly. We quantify in detail the evolution of the degree of crystallinity (XC) of PVA and examine distinct crystalline regions from simulation results. The results show that nanoconfinement can promote the crystallization process, especially at the early stage, and the interfaces between nanoparticles and polymer can function as crystallite nucleation sites. In general, the final XC of PVA increases with the levels of nanoconfinement. Further, nanoconfined cases show region-dependent XC with higher and earlier increase of XC in regions closer to the interfaces. By tracking region-dependent XC evolution, our results indicate that nanoconfinement can lead to a heterogenous crystallization process with a second-stage crystallite nucleation in regions further away from the interfaces. In addition, our results show that even under very high cooling rates, the nanoconfinement still promotes the crystallization of PVA. This study provides important insights into the underlying mechanisms for the intricate interplay between nanoconfinement and the crystallization behaviors of semicrystalline polymer, with the potential to guide the design and characterization of semicrystalline polymer-based nanocomposites.

Sensitive fluorescence detection based on dimeric G-quadruplex combined with enzyme-assisted solid-phase microextraction of streptomycin in honey.

Streptomycin (STR), an aminoglycoside antibiotic with the potential to persist in honey and other food products, may induce allergy, toxicity and antibiotic resistance in humans. In this study, we developed a solid-phase microextraction (SPME) biosensor based on a quartz rod that was modified with double-stranded DNA structures consisting of partially complementary G-rich base DNA strand and STR aptamer. The STR isolated by SPME initially bound to the aptamer. Then the remaining double-stranded DNA structures were cleaved by the Nt.BstNBI enzyme, resulting in release of G-quadruplex dimers. The latter formed a complex with thioflain T fluorescent dye, resulting in an amplified fluorescence response. The method exhibited high sensitivity (a limit of detection of 10.84 pM), wide linear range (0.05 nM âˆ¼ 500 nM (with determination coefficient > 0.99)), and simple operation, making it suitable and convenient for STR detection. Successful STR determination in genuine honey samples was demonstrated.

MPASL: multi-perspective learning knowledge graph attention network for synthetic lethality prediction in human cancer.

Synthetic lethality (SL) is widely used to discover the anti-cancer drug targets. However, the identification of SL interactions through wet experiments is costly and inefficient. Hence, the development of efficient and high-accuracy computational methods for SL interactions prediction is of great significance. In this study, we propose MPASL, a multi-perspective learning knowledge graph attention network to enhance synthetic lethality prediction. MPASL utilizes knowledge graph hierarchy propagation to explore multi-source neighbor nodes related to genes. The knowledge graph ripple propagation expands gene representations through existing gene SL preference sets. MPASL can learn the gene representations from both gene-entity perspective and entity-entity perspective. Specifically, based on the aggregation method, we learn to obtain gene-oriented entity embeddings. Then, the gene representations are refined by comparing the various layer-wise neighborhood features of entities using the discrepancy contrastive technique. Finally, the learned gene representation is applied in SL prediction. Experimental results demonstrated that MPASL outperforms several state-of-the-art methods. Additionally, case studies have validated the effectiveness of MPASL in identifying SL interactions between genes.

Genetic associations between circulating immune cells and periodontitis highlight the prospect of systemic immunoregulation in periodontal care.

Periodontitis drives irreversible destruction of periodontal tissue and is prone to exacerbating inflammatory disorders. Systemic immunomodulatory management continues to be an attractive approach in periodontal care, particularly within the context of 'predictive, preventive, and personalized' periodontics. The present study incorporated genetic proxies identified through genome-wide association studies for circulating immune cells and periodontitis into a comprehensive Mendelian randomization (MR) framework. Univariable MR, multivariable MR, subgroup analysis, reverse MR, and Bayesian model averaging (MR-BMA) were utilized to investigate the causal relationships. Furthermore, transcriptome-wide association study and colocalization analysis were deployed to pinpoint the underlying genes. Consequently, the MR study indicated a causal association between circulating neutrophils, natural killer T cells, plasmacytoid dendritic cells, and an elevated risk of periodontitis. MR-BMA analysis revealed that neutrophils were the primary contributors to periodontitis. The high-confidence genes S100A9 and S100A12, located on 1q21.3, could potentially serve as immunomodulatory targets for neutrophil-mediated periodontitis. These findings hold promise for early diagnosis, risk assessment, targeted prevention, and personalized treatment of periodontitis. Considering the marginal association observed in our study, further research is required to comprehend the biological underpinnings and ascertain the clinical relevance thoroughly.

Oral administration of garlic-derived nanoparticles improves cancer immunotherapy by inducing intestinal IFNγ-producing γδ T cells.

Gamma-delta (γδ) T cell-based cancer immunotherapies represent a promising avenue for cancer treatment. However, their development is challenged by the limited expansion and differentiation of the cells ex vivo. Here we induced the endogenous expansion and activation of γδ T cells through oral administration of garlic-derived nanoparticles (GNPs). We found that GNPs could significantly promote the proliferation and activation of endogenous γδ T cells in the intestine, leading to generation of large amount of interferon-γ (IFNγ). Moreover GNP-treated mice showed increased levels of chemokine CXCR3 in intestinal γδ T cells, which can drive their migration from the gut to the tumour environment. The translocation of γδ T cells and IFNγ from the intestine to extraintestinal subcutaneous tumours remodels the tumour immune microenvironment and synergizes with anti-PD-L1, inducing robust antitumour immunity. Our study delineates mechanistic insight into the complex gut-tumour interactome and provides an alternative approach for γδ T cell-based immunotherapy.

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types.

As the most abundant messenger RNA (mRNA) modification in mRNA, N  6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the function and role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A sequencing (m6A-seq) and RNA sequencing samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A-regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin, and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A for cancer precision medicine for patients with different cancer types.

Wearable and Multiplexed Biosensors based on Oxide Field-Effect Transistors.

Wearable sensors designed for continuous, non-invasive monitoring of physicochemical signals are important for portable healthcare. Oxide field-effect transistor (FET)-type biosensors provide high sensitivity and scalability. However, they face challenges in mechanical flexibility, multiplexed sensing of different modules, and the absence of integrated on-site signal processing and wireless transmission functionalities for wearable sensing. In this work, a fully integrated wearable oxide FET-based biosensor array is developed to facilitate the multiplexed and simultaneous measurement of ion concentrations (H+, Na+, K+) and temperature. The FET-sensor array is achieved by utilizing a solution-processed ultrathin (≈6 nm thick) In2O3 active channel layer, exhibiting high compatibility with standard semiconductor technology, good mechanical flexibility, high uniformity, and low operational voltage of 0.005 V. This work provides an effective method to enable oxide FET-based biosensors for the fusion of multiplexed physicochemical information and wearable health monitoring applications.

The U.S. PFAS exposure burden calculator for 2017-2018: Application to the HOME Study, with comparison of epidemiological findings from NHANES.

BACKGROUND: The 2017-2018 U.S. PFAS exposure burden calculator was designed to provide a summary exposure score for per- and polyfluoroalkyl substances (PFAS) mixtures using targeted PFAS analyte data. Its aim was to place PFAS burden score estimates onto a common scale based on nationally representative U.S. reference ranges from 2017 to 2018, enabling comparisons of overall PFAS burden scores across studies even if they did not measure the same set of PFAS analytes. OBJECTIVE: To use the U.S. PFAS exposure burden calculator for comparing the same mixture of PFAS compounds in similarly aged adolescents and their associations with cardiometabolic outcomes in the HOME Study and NHANES between 2015 and 2018. METHODS: We applied the PFAS burden calculator to 8 PFAS analytes measured in the serum of adolescents from the HOME Study (Cincinnati, Ohio; age range 11-14 years; years: 2016-2019; n = 207) and NHANES (US; age range 12-14 years; years 2015-2018; n = 245). We used the non-parametric Mann-Whitney U test and chi-squared test to compare the two study samples. In both studies, we examined associations of PFAS burden scores with the same cardiometabolic outcomes, adjusted for the same core set of covariates using regression analyses. We conducted sensitivity analyses to verify robustness of exposure-outcome associations, by accounting for measurement error of PFAS burden scores. RESULTS: PFAS burden scores were significantly different (p = 0.004) between the HOME Study (median: 0.00, interquartile range - 0.37, 0.34) and the NHANES samples (median: 0.04, IQR -0.11, 0.54), while no significant difference was found for PFAS summed concentrations (p = 0.661). In the HOME Study, an interquartile (IQR) increase in PFAS burden score was associated with higher total cholesterol [7.0 mg/dL, 95% CI: 0.6, 13.4]; HDL [2.8 mg/dL, 95% CI: 0.4, 5.2]; LDL [5.9 mg/dL, 95% CI: 0.5, 11.3], insulin [0.1 log(mIU/L), 95% CI: 0.01, 0.2], and HOMA-IR [0.1, 95% CI: 0.01, 0.2]. In NHANES, an IQR increase in PFAS burden score was associated with higher diastolic blood pressure [2.4 mmHg, 95% CI: 0.4, 4.4] but not with other outcomes. Sensitivity analyses in the HOME Study and NHANES were consistent with the main findings. CONCLUSIONS: Performance of the U.S. PFAS exposure burden calculator was similar in a local versus national sample of adolescents, and may be a useful tool for the assessment of PFAS mixtures across studies.

An artificial visual neuron with multiplexed rate and time-to-first-spike coding.

Human visual neurons rely on event-driven, energy-efficient spikes for communication, while silicon image sensors do not. The energy-budget mismatch between biological systems and machine vision technology has inspired the development of artificial visual neurons for use in spiking neural network (SNN). However, the lack of multiplexed data coding schemes reduces the ability of artificial visual neurons in SNN to emulate the visual perception ability of biological systems. Here, we present an artificial visual spiking neuron that enables rate and temporal fusion (RTF) coding of external visual information. The artificial neuron can code visual information at different spiking frequencies (rate coding) and enables precise and energy-efficient time-to-first-spike (TTFS) coding. This multiplexed sensory coding scheme could improve the computing capability and efficacy of artificial visual neurons. A hardware-based SNN with the RTF coding scheme exhibits good consistency with real-world ground truth data and achieves highly accurate steering and speed predictions for self-driving vehicles in complex conditions. The multiplexed RTF coding scheme demonstrates the feasibility of developing highly efficient spike-based neuromorphic hardware.

An Ion-Mediated Spiking Chemical Neuron based on Mott Memristor.

Artificial spiking neurons capable of interpreting ionic information into electrical spikes are critical to mimic biological signaling systems. Mott memristors are attractive for constructing artificial spiking neurons due to their simple structure, low energy consumption, and rich neural dynamics. However, challenges remain in achieving ion-mediated spiking and biohybrid-interfacing in Mott neurons. Here, a biomimetic spiking chemical neuron (SCN) utilizing an NbOx Mott memristor and oxide field-effect transistor-type chemical sensor is introduced. The SCN exhibits both excitation and inhibition spiking behaviors toward ionic concentrations akin to biological neural systems. It demonstrates spiking responses across physiological and pathological Na+ concentrations (1-200 × 10-3 m). The Na+-mediated SCN enables both frequency encoding and time-to-first-spike coding schemes, illustrating the rich neural dynamics of Mott neuron. In addition, the SCN interfaced with L929 cells facilitates real-time modulation of ion-mediated spiking under both normal and salty cellular microenvironments.

Dual-Specificity Inhibitor Targets Enzymes of the Trehalose Biosynthesis Pathway.

To reduce the risk of resistance development, a novel fungicide with dual specificity is demanded. Trehalose is absent in animals, and its synthases, trehalose-6-phosphate synthase (TPS) and trehalose-6-phosphate phosphatase (TPP), are safe fungicide targets. Here, we report the discovery of a dual-specificity inhibitor of MoTps1 (Magnaporthe oryzae Tps1, TPS) and MoTps2 (M. oryzae Tps2, TPP). The inhibitor, named A1-4, was obtained from a virtual screening and subsequent surface plasmon resonance screening. In in vitro assays, A1-4 interacts with MoTps1 and MoTps2-TPP (MoTps2 TPP domain) and inhibits their enzyme activities. In biological activity assays, A1-4 not only inhibits the virulence of M. oryzae on host but also causes aggregation of conidia cytosol, which is a characteristic phenotype of MoTps2. Furthermore, hydrogen/deuterium exchange mass spectrometry assays support the notion that A1-4 binds to the substrate pockets of TPS and TPP. Collectively, A1-4 is a promising hit compound for the development of safe fungicide with dual-target specificity.

A lightweight segmentation network for endoscopic surgical instruments based on edge refinement and efficient self-attention.

In robot-assisted surgical systems, surgical instrument segmentation is a critical task that provides important information for surgeons to make informed decisions and ensure surgical safety. However, current mainstream models often lack precise segmentation edges and suffer from an excess of parameters, rendering their deployment challenging. To address these issues, this article proposes a lightweight semantic segmentation model based on edge refinement and efficient self-attention. The proposed model utilizes a lightweight densely connected network for feature extraction, which is able to extract high-quality semantic information with fewer parameters. The decoder combines a feature pyramid module with an efficient criss-cross self-attention module. This fusion integrates multi-scale data, strengthens focus on surgical instrument details, and enhances edge segmentation accuracy. To train and evaluate the proposed model, the authors developed a private dataset of endoscopic surgical instruments. It containing 1,406 images for training, 469 images for validation and 469 images for testing. The proposed model performs well on this dataset with only 466 K parameters, achieving a mean Intersection over Union (mIoU) of 97.11%. In addition, the model was trained on public datasets Kvasir-instrument and Endovis2017. Excellent results of 93.24% and 95.83% were achieved on the indicator mIoU, respectively. The superiority and effectiveness of the method are proved. Experimental results show that the proposed model has lower parameters and higher accuracy than other state-of-the-art models. The proposed model thus lays the foundation for further research in the field of surgical instrument segmentation.