Investigation of silicon doped carbon dots/Carboxymethyl cellulose gel platform with tunable afterglow and dynamic multistage anticounterfeiting.

The remarkable optical properties of carbon dots, particularly their tunable room-temperature phosphorescence, have garnered significant interest. However, challenges such as aggregation propensity and complex phosphorescence control via energy level manipulation during synthesis persist. Addressing these issues, we present a facile gel platform for tunable afterglow materials. This involves chemically cross-linking biomass-derived silicon-doped carbon dots with carboxymethylcellulose and incorporating non-precious metal salts (BaCl2, CaCl2, MgCl2, ZnCl2, ZnBr2, ZnSO4) to enhance phosphorescence. Metal salts boost intersystem crossing via spin-orbit coupling, elevating triplet state transitions and activating phosphorescence. Chemical bonding and salt-induced coordination/electrostatic interactions establish confinement effects, suppressing non-radiative transitions. Diverse salt-gel interactions yield gels with tunable phosphorescence lifetimes (9.48 ms to 32.13-492.39 ms), corresponding to afterglow durations ranging from 3.20 to 11.86 s. With its broad tunability and high recognition, this gel material exhibits promising potential for dynamic multilevel anti-counterfeiting applications.

Identification of the body fluid donor in mixtures through target mRNA cSNP sequencing.

In forensic practice, mixture stains containing various body fluids are common, presenting challenges for interpretation, particularly in multi-contributor mixtures. Traditional STR profiles face difficulties in such scenarios. Over recent years, RNA has emerged as a promising biomarker for body fluid identification, and mRNA polymorphism has shown excellent performance in identifying body fluid donors in previous studies. In this study, a massively parallel sequencing assay was developed, encompassing 202 coding region SNPs (cSNPs) from 45 body fluid/tissue-specific genes to identify both body fluid/tissue origin and the respective donors, including blood, saliva, semen, vaginal secretion, menstrual blood, and skin. The specificity was evaluated by examining the single-source body fluids/tissue and revealed that the same body fluid exhibited similar expression profiles and the tissue origin could be identified. For laboratory-generated mixtures containing 2-6 different components and mock case mixtures, the donor of each component could be successfully identified, except for the skin donor. The discriminatory power for all body fluids ranged from 0.997176329 (menstrual blood) to 0.99999999827 (blood). The concordance of DNA typing and mRNA typing for the cSNPs in this system was also validated. This cSNP typing system exhibits excellent performance in mixture deconvolution.

A Study on the Microstructure Regulation Effect of Niobium Doping on LiNi0.88Co0.05Mn0.07O2 and the Electrochemical Performance of the Composite Material under High Voltage.

High-nickel ternary materials are currently the most promising lithium battery cathode materials due to their development and application potential. Nevertheless, these materials encounter challenges like cation mixing, lattice oxygen loss, interfacial reactions, and microcracks. These issues are exacerbated at high voltages, compromising their cyclic stability and safety. In this study, we successfully prepared Nb5+-doped high-nickel ternary cathode materials via a high-temperature solid-phase method. We investigated the impact of Nb5+ doping on the microstructure and electrochemical properties of LiNi0.88Co0.05Mn0.07O2 ternary cathode materials by varying the amount of Nb2O5 added. The experimental results suggest that Nb5+ doping does not alter the crystal structure but modifies the particle morphology, yielding radially distributed, elongated, rod-like structures. This morphology effectively mitigates the anisotropic volume changes during cycling, thereby bolstering the material's cyclic stability. The material exhibits a discharge capacity of 224.4 mAh g-1 at 0.1C and 200.3 mAh g-1 at 1C, within a voltage range of 2.7 V-4.5 V. Following 100 cycles at 1C, the capacity retention rate maintains a high level of 92.9%, highlighting the material's remarkable capacity retention and cyclic stability under high-voltage conditions. The enhancement of cyclic stability is primarily due to the synergistic effects caused by Nb5+ doping. Nb5+ modifies the particle morphology, thereby mitigating the formation of microcracks. The formation of high-energy Nb-O bonds prevents oxygen precipitation at high voltages, minimizes the irreversibility of the H2-H3 phase transition, and thereby enhances the stability of the composite material at high voltages.

Corrigendum: Novel FOXL2 variants in two Chinese families with blepharophimosis, ptosis, and epicanthus inversus syndrome.

[This corrects the article DOI: 10.3389/fgene.2024.1343411.].

A Machine Learning Prediction Model of Adult Obstructive Sleep Apnea Based on Systematically Evaluated Common Clinical Biochemical Indicators.

Objective: Obstructive sleep apnea (OSA) is a common and potentially fatal sleep disorder. The purpose of this study was to construct an objective and easy-to-promote model based on common clinical biochemical indicators and demographic data for OSA screening. Methods: The study collected the clinical data of patients who were referred to the Sleep Medicine Center of the Second Affiliated Hospital of Fujian Medical University from December 1, 2020, to July 31, 2023, including data for demographics, polysomnography (PSG), and 30 biochemical indicators. Univariate and multivariate analyses were performed to compare the differences between groups, and the Boruta method was used to analyze the importance of the predictors. We selected and compared 10 predictors using 4 machine learning algorithms which were "Gaussian Naive Bayes (GNB)", "Support Vector Machine (SVM)", "K Neighbors Classifier (KNN)", and "Logistic Regression (LR)". Finally, the optimal algorithm was selected to construct the final prediction model. Results: Among all the predictors of OSA, body mass index (BMI) showed the best predictive efficacy with an area under the receiver operating characteristic curve (AUC) = 0.699; among the predictors of biochemical indicators, triglyceride-glucose (TyG) index represented the best predictive performance (AUC = 0.656). The LR algorithm outperformed the 4 established machine learning (ML) algorithms, with an AUC (F1 score) of 0.794 (0.841), 0.777 (0.827), and 0.732 (0.788) in the training, validation, and testing cohorts, respectively. Conclusion: We have constructed an efficient OSA screening tool. The introduction of biochemical indicators in ML-based prediction models can provide a reference for clinicians in determining whether patients with suspected OSA need PSG.

Comparative Proteomics Identified EXOSC1 as a Target Protein of Anticancer Peptide LVTX-8 in Nasopharyngeal Carcinoma Cells.

Nasopharyngeal carcinoma (NPC) is a prevalent malignancy that usually occurs among the nose and throat. Due to mild initial symptoms, most patients are diagnosed in the late stage, and the recurrence rate of tumors is high, resulting in many deaths every year. Traditional radiotherapy and chemotherapy are prone to causing drug resistance and significant side effects. Therefore, searching for new bioactive drugs including anticancer peptides is necessary and urgent. LVTX-8 is a peptide toxin synthesized from the cDNA library of the spider Lycosa vittata, which is consisting of 25 amino acids. In this study, a series of in vitro cell experiments such as cell toxicity, colony formation, and cell migration assays were performed to exam the anticancer activity of LVTX-8 in NPC cells (5-8F and CNE-2). The results suggested that LVTX-8 significantly inhibited cell proliferation and migration of NPC cells. To find the potential molecular targets for the anticancer capability of LVTX-8, high-throughput proteomic and bioinformatics analysis were conducted on NPC cells. The results identified EXOSC1 as a potential target protein with significantly differential expression levels under LVTX-8+/LVTX-8- conditions. The results in this research indicate that spider peptide toxin LVTX-8 exhibits significant anticancer activity in NPC, and EXOSC1 may serve as a target protein for its anticancer activity. These findings provide a reference for the development of new therapeutic drugs for NPC and offer new ideas for the discovery of biomarkers related to NPC diagnosis. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository with the data set identifier PXD050542.

Surface Finish Analysis of Gradient Voltage Electrochemical Polishing of 316L Stainless Steel Parts Forming by Laser Powder Bed Fusion.

Laser powder bed fusion (LPBF) of complex-structure 316L stainless steel (316L ss) parts has a wide application prospects in aerospace, biomedical, and defense industry fields. However, the surface roughness (Ra) of the LPBF sample is unsatisfactory due to the process characteristics of layer-by-layer selective melting and cumulative forming, which limits its applications in the engineering field. Herein, a gradient voltage electrochemical polishing strategy is proposed based on the characteristics of electrochemical polishing technology, which can polish complex structures. The mechanisms of polishing process parameters and polishing strategy on the surface finish of LPBF parts are investigated. The gradient voltage polishing strategy is extended to complex structures, and the Ra of the inner surfaces of square and round tubes are successfully reduced to about 1 µm. The gradient electrochemical polishing process for surface finish post-treatment of LPBF parts can broaden the engineering applications of complex-structure metal parts.

SC-Track: a robust cell-tracking algorithm for generating accurate single-cell lineages from diverse cell segmentations.

Computational analysis of fluorescent timelapse microscopy images at the single-cell level is a powerful approach to study cellular changes that dictate important cell fate decisions. Core to this approach is the need to generate reliable cell segmentations and classifications necessary for accurate quantitative analysis. Deep learning-based convolutional neural networks (CNNs) have emerged as a promising solution to these challenges. However, current CNNs are prone to produce noisy cell segmentations and classifications, which is a significant barrier to constructing accurate single-cell lineages. To address this, we developed a novel algorithm called Single Cell Track (SC-Track), which employs a hierarchical probabilistic cache cascade model based on biological observations of cell division and movement dynamics. Our results show that SC-Track performs better than a panel of publicly available cell trackers on a diverse set of cell segmentation types. This cell-tracking performance was achieved without any parameter adjustments, making SC-Track an excellent generalized algorithm that can maintain robust cell-tracking performance in varying cell segmentation qualities, cell morphological appearances and imaging conditions. Furthermore, SC-Track is equipped with a cell class correction function to improve the accuracy of cell classifications in multiclass cell segmentation time series. These features together make SC-Track a robust cell-tracking algorithm that works well with noisy cell instance segmentation and classification predictions from CNNs to generate accurate single-cell lineages and classifications.

The role of the "gut microbiota-mitochondria" crosstalk in the pathogenesis of multiple sclerosis.

Multiple Sclerosis (MS) is a neurologic autoimmune disease whose exact pathophysiologic mechanisms remain to be elucidated. Recent studies have shown that the onset and progression of MS are associated with dysbiosis of the gut microbiota. Similarly, a large body of evidence suggests that mitochondrial dysfunction may also have a significant impact on the development of MS. Endosymbiotic theory has found that human mitochondria are microbial in origin and share similar biological characteristics with the gut microbiota. Therefore, gut microbiota and mitochondrial function crosstalk are relevant in the development of MS. However, the relationship between gut microbiota and mitochondrial function in the development of MS is not fully understood. Therefore, by synthesizing previous relevant literature, this paper focuses on the changes in gut microbiota and metabolite composition in the development of MS and the possible mechanisms of the crosstalk between gut microbiota and mitochondrial function in the progression of MS, to provide new therapeutic approaches for the prevention or reduction of MS based on this crosstalk.

Metabolomics reveals the implication of acetoacetate and ketogenic diet therapy in radioiodine-refractory differentiated thyroid carcinoma.

OBJECTIVE: Patients with radioiodine-refractory (RAIR) differentiated thyroid carcinoma (DTC; RAIR-DTC) have a poor prognosis. The aim of this study was to provide new insights and possibilities for the diagnosis and treatment of RAIR-DTC. METHODS: The metabolomics of 24 RAIR-DTC and 18 non-radioiodine-refractory (NonRAIR) DTC patients samples were analyzed by liquid chromatograph-mass spectrometry. Cellular radioiodine uptake was detected with γ counter. Sodium iodide symporter (NIS) expression and thyroid stimulating hormone receptor (TSHR) were measured by Western blot analysis. CCK8 and colony formation assays were used to measure cellular proliferation. Scratch and transwell assays were performed to assess cell migration and invasion. Annexin V/PI staining was used to detect cell apoptosis. Cell growth in vivo was evaluated by a tumor xenograft model. The acetoacetate (AcAc) level was measured by ELISA. Pathological changes, Ki67, NIS, and TSHR expression were investigated by immunohistochemistry. RESULTS: The metabolite profiles of RAIR could be distinguished from those of NonRAIR, with AcAc significantly lower in RAIR. The significantly different metabolic pathway was ketone body metabolism. AcAc increased NIS and TSHR expression and improved radioiodine uptake. AcAc inhibited cell proliferation, migration, and invasion, and as well promoted cell apoptosis. Ketogenic diet (KD) elevated AcAc levels and significantly suppressed tumor growth, as well as improved NIS and TSHR expression. CONCLUSION: Significant metabolic differences were observed between RAIR and NonRAIR, and ketone body metabolism might play an important role in RAIR-DTC. AcAc improved cellular iodine uptake and had antitumor effects for thyroid carcinoma. KD might be a new therapeutic strategy for RAIR-DTC.

Terahertz communication: Detection and signal processing.

The development of 6G networks has promoted related research based on terahertz communication. As submillimeter radiation, signal transportation via terahertz waves has several superior properties, including non-ionizing and easy penetration of non-metallic materials. This paper provides an overview of different terahertz detectors based on various mechanisms. Additionally, the detailed fabrication process, structural design, and the improvement strategies are summarized. Following that, it is essential and necessary to prevent the practical signal from noise, and methods such as wavelet transform, UM-MIMO and decoding have been introduced. This paper highlights the detection process of the terahertz wave system and signal processing after the collection of signal data. .

Silicon-Doped Carbon Dots Crosslinked Carboxymethyl Cellulose Gel: Detection and Adsorption of Fe3.

The excessive emission of iron will pollute the environment and harm human health, so the fluorescence detection and adsorption of Fe3+ are of great significance. In the field of water treatment, cellulose-based gels have attracted wide attention due to their excellent properties and environmental friendliness. If carbon dots are used as a crosslinking agent to form a gel with cellulose, it can not only improve mechanical properties but also show good biocompatibility, reactivity, and fluorescence properties. In this study, silicon-doped carbon dots/carboxymethyl cellulose gel (DCG) was successfully prepared by chemically crosslinking biomass-derived silicon-doped carbon dots with carboxymethyl cellulose. The abundant crosslinking points endow the gel with excellent mechanical properties, with a compressive strength reaching 294 kPa. In the experiment on adsorbing Fe3+, the theoretical adsorption capacity reached 125.30 mg/g. The introduction of silicon-doped carbon dots confers the gel with excellent fluorescence properties and a good selective response to Fe3+. It exhibits a good linear relationship within the concentration range of 0-100 mg/L, with a detection limit of 0.6595 mg/L. DCG appears to be a good application prospect in the adsorption and detection of Fe3+.

Miracle in "White":Hexagonal Boron Nitride.

The exploration of 2D materials has captured significant attention due to their unique performances, notably focusing on graphene and hexagonal boron nitride (h-BN). Characterized by closely resembling atomic structures arranged in a honeycomb lattice, both graphene and h-BN share comparable traits, including exceptional thermal conductivity, impressive carrier mobility, and robust pi-pi interactions with organic molecules. Notably, h-BN has been extensively examined for its exceptional electrical insulating properties, inert passivation capabilities, and provision of an ideal ultraflat surface devoid of dangling bonds. These distinct attributes, contrasting with those of h-BN, such as its conductive versus insulating behavior, active versus inert nature, and absence of dangling surface bonds versus absorbent tendencies, render it a compelling material with broad application potential. Moreover, the unity of such contradictions endows h-BN with intriguing possibilities for unique applications in specific contexts. This review aims to underscore these key attributes and elucidate the intriguing contradictions inherent in current investigations of h-BN, fostering significant insights into the understanding of material properties.

Association between gut microbiota and anxiety disorders: a bidirectional two-sample mendelian randomization study.

BACKGROUND: There are many articles reporting that the component of intestinal microbiota implies a link to anxiety disorders (AD), and the brain-gut axis is also a hot topic in current research. However, the specific relevance between gut microbiota and AD is uncertain. We aimed to investigate causal relationship between gut microbiota and AD by using bidirectional Mendelian randomization (MR). METHODS: Genetic instrumental variable (IV) for the gut microbiota were obtained from a genome-wide association study (GWAS) involving 18,340 participants. Summary data for AD were derived from the GWAS and included 158,565 cases and 300,995 controls. We applied the inverse variance weighted (IVW) method as the main analysis. Cochran's Q values was computed to evaluate the heterogeneity among IVs. Sensitivity analyses including intercept of MR-Egger method and MR-PRESSO analysis were used to test the horizontal pleiotropy. RESULT: We discovered 9 potential connections between bacterial traits on genus level and AD. Utilizing the IVW method, we identified 5 bacterial genera that exhibited a direct correlation with the risk of AD: genus Eubacteriumbrachygroup, genus Coprococcus3, genus Enterorhabdus, genus Oxalobacter, genus Ruminiclostridium6. Additionally, we found 4 bacterial genera that exhibited a negative association with AD: genus Blautia, genus Butyricicoccus, genus Erysipelotrichaceae-UCG003 and genus Parasutterella. The associations were confirmed by the sensitivity analyses. CONCLUSION: Our study found a causal relation between parts of the gut microbiota and AD. Further randomized controlled trials are crucial to elucidate the positive effects of probiotics on AD and their particular protection systems.

Memristor-based adaptive neuromorphic perception in unstructured environments.

Efficient operation of control systems in robotics or autonomous driving targeting real-world navigation scenarios requires perception methods that allow them to understand and adapt to unstructured environments with good accuracy, adaptation, and generality, similar to humans. To address this need, we present a memristor-based differential neuromorphic computing, perceptual signal processing, and online adaptation method providing neuromorphic style adaptation to external sensory stimuli. The adaptation ability and generality of this method are confirmed in two application scenarios: object grasping and autonomous driving. In the former, a robot hand realizes safe and stable grasping through fast ( ~ 1 ms) adaptation based on the tactile object features with a single memristor. In the latter, decision-making information of 10 unstructured environments in autonomous driving is extracted with an accuracy of 94% with a 40×25 memristor array. By mimicking human low-level perception mechanisms, the electronic neuromorphic circuit-based method achieves real-time adaptation and high-level reactions to unstructured environments.

Effect of social participation on the trajectories of activities of daily living disability among community-dwelling older adults: a 7-year community-based cohort.

INTRODUCTION: Studies examining the effects of social participation on activities of daily living (ADL) disability are still scarce. AIM: To assess the reciprocal relationship between ADL disability trajectories and social participation among older Chinese people aged ≥ 60 years. METHODS: This study included 2976 participants aged ≥ 60 years in six waves of a community-based survey from 2015 to 2022. Basic activities of daily living (BADL) and instrumental activities of daily living (IADL) were used to assess the ADL disability in each survey. Social participation was assessed by involvement in four social activities and an extensive social participation score. Group-based trajectory modeling was used to identify potential heterogeneity in longitudinal changes over 7 years and explore associations between baseline predictors of group membership and these trajectories. RESULTS: Two BADL disability trajectories were identified: stable (94.8%) and increase (5.2%). Additionally, three IADL disability trajectories were distinguished: stable (73.2%), moderate (20.2%), and increase (6.6%). After controlling for the potential covariates, each point increase in the extensive social participation score correlated with a 17% decrease in the odds of older individuals belonging to the increase BADL trajectory group (OR = 0.83, 95% CI = 0.68-1.00). For IADL, it decreased the odds of being assigned to the moderate trajectory group by 16% (OR = 0.84, 95% CI = 0.75-0.95) and to the increase trajectory group by 23% (OR = 0.77, 95% CI = 0.64-0.93). CONCLUSIONS: Higher levels of social participation among older individuals were more likely to be classified as stable trajectories in both BADL and IADL. Increased participation in social activities by community-dwelling elderly adults may promote healthy aging.

Prognostic value of serum IGF-1, Gal-3, and PTX-3 levels in elderly patients with chronic heart failure.

OBJECTIVES: To evaluate the diagnostic and prognostic value of insulin-like growth factor-1 (IGF-1), galactoagglutinin-3 (GAL-3), and pentamerin-3 (PTX-3) levels in elderly patients with chronic heart failure (CHF). METHODS: In this retrospective study, 107 elderly CHF patients treated in Xiangyang Central Hospital were designated as the observation group, and 60 healthy individuals were selected as the control group. The cardiac function indexes and serum IGF-1, Gal-3, and PTX-3 levels were compared between the two groups. Furthermore, the serum IGF-1, Gal-3, and PTX-3 levels in patients across different cardiac function grades were compared, as well as in patients with poor or favorable prognosis. Additionally, receiver operating characteristic (ROC) curve was adopted to explore the diagnostic value of serum IGF-1, Gal-3, and PTX-3 levels for senile CHF; and multivariate logistic regression analysis was used to screen the independent factors affecting patients' prognosis. RESULTS: The serum IGF-1 level was significantly lower, while the levels of Gal-3 and PTX-3 were significantly higher in the observation group than those of the control group (all P<0.05). The serum IGF-1 level in patients with cardiac function grade IV was lower than that of the patients with cardiac function grade II and III, while the levels of Gal-3 and PTX-3 were higher than those with cardiac function grade II and III (all P<0.05). The serum IGF-1 level in the patients with cardiac function grade III was lower than those with cardiac function grade II, while the levels of Gal-3 and PTX-3 were higher in patients with grade III than those with grade II (all P<0.05). The serum IGF-1 level was lower, while the levels of Gal-3 and PTX-3 were higher in the patients with poor prognosis than those with favorable prognosis (all P<0.05). CONCLUSION: In elderly CHF patients, IGF-1 level were decreases, while the levels of Gal-3 and PTX-3 were increase. These biomarkers show high sensitivity in diagnosing CHF and are closely linked to the prognosis, indicating their value for clinical assessment and management of CHF.

Helminth alleviates COVID-19-related cytokine storm in an IL-9-dependent way.

Hyperactivation of pro-inflammatory type 1 cytokines (e.g., tumor necrosis factor alpha [TNF-α] and interferon gamma [IFN-γ]) mirrors the inflammation of coronavirus disease 2019. Helminths could alleviate excessive immune responses. Here, helminth Trichinella spiralis (Ts) infection was shown to protect against TNF-α- and IFN-γ-induced shock. Mechanistically, Ts-induced protection was interleukin-9 (IL-9) dependent but not IL-4Rα. Recombinant IL-9 treatment not only improved the survival of wild-type mice with TNF-α- and IFN-γ-induced shock but also that of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected K18-human angiotensin-converting enzyme 2 (hACE2) mice, emphasizing the significance of IL-9 in alleviating cytokine storm syndromes during SARS-CoV-2 infection. Interestingly, Ts excretory/secretory (TsES)-induced protection was also observed in SARS-CoV-2 infection, indicating that identifying anti-inflammatory molecules from TsES could be a novel way to mitigate adverse pathological inflammation during pathogen infection.IMPORTANCESevere coronavirus disease 2019 (COVID-19) is linked to cytokine storm triggered by type 1 pro-inflammatory immune responses. TNF-α and IFN-γ shock mirrors cytokine storm syndromes, including COVID-19. Helminths (e.g., Trichinella spiralis, Ts) can potently activate anti-inflammatory type 2 immune response. Here, we found that helminth Ts-induced protection against TNF-α and IFN-γ shock was IL-9 dependent. Treatment with recombinant IL-9 could protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in K18-hACE2 mice. Helminth Ts excretory/secretory (TsES) products also ameliorated SARS-CoV-2 infection-related cytokine storm. In conclusion, our study emphasizes the significance of IL-9 in protecting from cytokine storm syndromes associated with SARS-CoV-2 infection. Anti-inflammatory molecules from TsES could be a new source to mitigate adverse pathological inflammation associated with infections, including COVID-19.