Inflammation-Responsive Hydrogel Accelerates Diabetic Wound Healing Through Immunoregulation and Enhanced Angiogenesis.

Angiogenesis is a prominent component during the highly regulated process of wound healing. The application of exogenous vascular endothelial growth factor (VEGF) has shown considerable potential in facilitating angiogenesis. However, its effectiveness is often curtailed due to chronic inflammation and severe oxidative stress in diabetic wounds. Herein, an inflammation-responsive hydrogel incorporating Prussian blue nanoparticles (PBNPs) is designed to augment the angiogenic efficacy of VEGF. Specifically, the rapid release of PBNPs from the hydrogel under inflammatory conditions effectively alleviates the oxidative stress of the wound, therefore reprogramming the immune microenvironment to preserve the bioactivity of VEGF for enhanced angiogenesis. In vitro and in vivo studies reveal that the PBNPs and VEGF co-loaded hydrogel is biocompatible and possesses effective anti-inflammatory properties, thereby facilitating angiogenesis to accelerate the wound healing process in a type 2 diabetic mouse model. This article is protected by copyright. All rights reserved.

GMOIT: a tool for effective screening of genetically modified crops.

BACKGROUND: Advancement in agricultural biotechnology has resulted in increasing numbers of commercial varieties of genetically modified (GM) crops worldwide. Though several databases on GM crops are available, these databases generally focus on collecting and providing information on transgenic crops rather than on screening strategies. To overcome this, we constructed a novel tool named, Genetically Modified Organisms Identification Tool (GMOIT), designed to integrate basic and genetic information on genetic modification events and detection methods. RESULTS: At present, data for each element from 118 independent genetic modification events in soybean, maize, canola, and rice were included in the database. Particularly, GMOIT allows users to customize assay ranges and thus obtain the corresponding optimized screening strategies using common elements or specific locations as the detection targets with high flexibility. Using the 118 genetic modification events currently included in GMOIT as the range and algorithm selection results, a "6 + 4" protocol (six exogenous elements and four endogenous reference genes as the detection targets) covering 108 events for the four crops was established. Plasmids pGMOIT-1 and pGMOIT-2 were constructed as positive controls or calibrators in qualitative and quantitative transgene detection. CONCLUSIONS: Our study provides a simple, practical tool for selecting, detecting, and screening strategies for a sustainable and efficient application of genetic modification.

Multi-Label Action Anticipation for Real-World Videos with Scene Understanding.

With human action anticipation becoming an essential tool for many practical applications, there has been an increasing trend in developing more accurate anticipation models in recent years. Most of the existing methods target standard action anticipation datasets, in which they could produce promising results by learning action-level contextual patterns. However, the over-simplified scenarios of standard datasets often do not hold in reality, which hinders them from being applied to real-world applications. To address this, we propose a scene-graph-based novel model SEAD that learns the action anticipation at the high semantic level rather than focusing on the action level. The proposed model is composed of two main modules, 1) the scene prediction module, which predicts future scene graphs using a grammar dictionary, and 2) the action anticipation module, which is responsible for predicting future actions with an LSTM network by taking as input the observed and predicted scene graphs. We evaluate our model on two real-world video datasets (Charades and Home Action Genome) as well as a standard action anticipation dataset (CAD-120) to verify its efficacy. The experimental results show that SEAD is able to outperform existing methods by large margins on the two real-world datasets and can also yield stable predictions on the standard dataset at the same time. In particular, our proposed model surpasses the state-of-the-art methods with mean average precision improvements consistently higher than 65% on the Charades dataset and an average improvement of 40.6% on the Home Action Genome dataset.

Machine-learning-based models to predict cardiovascular risk using oculomics and clinic variables in KNHANES.

BACKGROUND: Recent researches have found a strong correlation between the triglyceride-glucose (TyG) index or the atherogenic index of plasma (AIP) and cardiovascular disease (CVD) risk. However, there is a lack of research on non-invasive and rapid prediction of cardiovascular risk. We aimed to develop and validate a machine-learning model for predicting cardiovascular risk based on variables encompassing clinical questionnaires and oculomics. METHODS: We collected data from the Korean National Health and Nutrition Examination Survey (KNHANES). The training dataset (80% from the year 2008 to 2011 KNHANES) was used for machine learning model development, with internal validation using the remaining 20%. An external validation dataset from the year 2012 assessed the model's predictive capacity for TyG-index or AIP in new cases. We included 32122 participants in the final dataset. Machine learning models used 25 algorithms were trained on oculomics measurements and clinical questionnaires to predict the range of TyG-index and AIP. The area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score were used to evaluate the performance of our machine learning models. RESULTS: Based on large-scale cohort studies, we determined TyG-index cut-off points at 8.0, 8.75 (upper one-third values), 8.93 (upper one-fourth values), and AIP cut-offs at 0.318, 0.34. Values surpassing these thresholds indicated elevated cardiovascular risk. The best-performing algorithm revealed TyG-index cut-offs at 8.0, 8.75, and 8.93 with internal validation AUCs of 0.812, 0.873, and 0.911, respectively. External validation AUCs were 0.809, 0.863, and 0.901. For AIP at 0.34, internal and external validation achieved similar AUCs of 0.849 and 0.842. Slightly lower performance was seen for the 0.318 cut-off, with AUCs of 0.844 and 0.836. Significant gender-based variations were noted for TyG-index at 8 (male AUC=0.832, female AUC=0.790) and 8.75 (male AUC=0.874, female AUC=0.862) and AIP at 0.318 (male AUC=0.853, female AUC=0.825) and 0.34 (male AUC=0.858, female AUC=0.831). Gender similarity in AUC (male AUC=0.907 versus female AUC=0.906) was observed only when the TyG-index cut-off point equals 8.93. CONCLUSION: We have established a simple and effective non-invasive machine learning model that has good clinical value for predicting cardiovascular risk in the general population.

Identification of a novel LFNG variant in a Chinese fetus with spondylocostal dysostosis and a systematic review.

Spondylocostal dysostosis (SCDO) encompasses a group of skeletal disorders characterized by multiple segmentation defects in the vertebrae and ribs. SCDO has a complex genetic etiology. This study aimed to analyze and identify pathogenic variants in a fetus with SCDO. Copy number variant sequencing and whole exome sequencing were performed on a Chinese fetus with SCDO, followed by bioinformatics analyses, in vitro functional assays and a systematic review on the reported SCDO cases with LFNG pathogenic variants. Ultrasound examinations in utero exhibited that the fetus had vertebral malformation, scoliosis and tethered cord, but rib malformation was not evident. We found a novel homozygous variant (c.1078 C > T, p.R360C) within the last exon of LFNG. The variant was predicted to cause loss of function of LFNG by in silico prediction tools, which was confirmed by an in vitro assay of LFNG enzyme activity. The systematic review listed a total of 20 variants of LFNG in SCDO. The mutational spectrum spans across all exons of LFNG except the last one. This study reported the first Chinese case of LFNG-related SCDO, revealing the prenatal phenotypes and expanding the mutational spectrum of the disorder.

Mammalian PIWI-piRNA-target complexes reveal features for broad and efficient target silencing.

The PIWI-interacting RNA (piRNA) pathway is an adaptive defense system wherein piRNAs guide PIWI family Argonaute proteins to recognize and silence ever-evolving selfish genetic elements and ensure genome integrity. Driven by this intensive host-pathogen arms race, the piRNA pathway and its targeted transposons have coevolved rapidly in a species-specific manner, but how the piRNA pathway adapts specifically to target silencing in mammals remains elusive. Here, we show that mouse MILI and human HILI piRNA-induced silencing complexes (piRISCs) bind and cleave targets more efficiently than their invertebrate counterparts from the sponge Ephydatia fluviatilis. The inherent functional differences comport with structural features identified by cryo-EM studies of piRISCs. In the absence of target, MILI and HILI piRISCs adopt a wider nucleic-acid-binding channel and display an extended prearranged piRNA seed as compared with EfPiwi piRISC, consistent with their ability to capture targets more efficiently than EfPiwi piRISC. In the presence of target, the seed gate-which enforces seed-target fidelity in microRNA RISC-adopts a relaxed state in mammalian piRISC, revealing how MILI and HILI tolerate seed-target mismatches to broaden the target spectrum. A vertebrate-specific lysine distorts the piRNA seed, shifting the trajectory of the piRNA-target duplex out of the central cleft and toward the PAZ lobe. Functional analyses reveal that this lysine promotes target binding and cleavage. Our study therefore provides a molecular basis for the piRNA targeting mechanism in mice and humans, and suggests that mammalian piRNA machinery can achieve broad target silencing using a limited supply of piRNA species.

Clinical features of patients with rheumatic and musculoskeletal diseases during the coronavirus disease 2019 pandemic and the association of its relapse with infection: Across-sectional study.

AIM: The aim of this study was to investigate the clinical features of patients with rheumatic and musculoskeletal diseases (RMDs) infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the relationship between RMDs relapse and SARS-CoV-2 infection. METHODS: We carried out a cross-sectional observational study among 585 patients with RMDs and 619 individuals without RMDs. Data on demographics, the clinical features of coronavirus disease 2019 (COVID-19), antirheumatic therapy, and RMD relapse were collected. Differences between RMDs and control groups, infected and uninfected groups, relapse and non-relapse RMDs groups were examined. The influence of COVID-19 infection on medications and relapse of RMDs was also assessed. RESULTS: Among 1204 participants finally recruited for analysis, 1030 (85.5%) were infected with COVID-19. Seven hundred and ninety-five (77.2%) of infected individuals were female, and the median age was 40 years (IQR 33, 50). Patients in the RMD group had a relatively lower risk of COVID-19 symptoms whereas were significantly more likely to require hospitalization (6.7% vs. 2.2%). In the RMDs group, younger patients who were under the age of 65 were more likely to report more symptoms. More patients with RMD relapse (27, 34.6%) adjusted their medications during the period of COVID-19 infection than those without relapse (59, 13.2%). CONCLUSION: Patients with RMDs were at lower risk of symptoms of COVID-19. Rheumatic and musculoskeletal disease patients experience a higher risk of relapse especially when they adjust medications during COVID-19 infection. The long-term prognosis of infected RMDs patients need further investigation.

Distribution characteristics of soil carbon density and influencing factors in Qinghai-Tibet Plateau region.

The Qinghai-Tibet Plateau has low anthropogenic carbon emissions and large carbon stock in its ecosystems. As a crucial region in terrestrial ecosystems responding to climate change, an accurate understanding of the distribution characteristics of soil carbon density holds significance in estimating the soil carbon storage capacity in forests and grasslands. It performs a crucial role in achieving carbon neutrality goals in China. The distribution characteristics of carbon and carbon density in the surface, middle, and deep soil layers are calculated, and the main influencing factors of soil carbon density changes are analyzed. The carbon density in the surface soil ranges from a minimum of 1.62 kg/m2 to a maximum of 52.93 kg/m2. The coefficient of variation for carbon is 46%, indicating a considerable variability in carbon distribution across different regions. There are substantial disparities, with geological background, land use types, and soil types significantly influencing soil organic carbon density. Alpine meadow soil has the highest carbon density compared with other soil types. The distribution of soil organic carbon density at three different depths is as follows: grassland > bare land > forestland > water area. The grassland systems in the Qinghai-Tibet Plateau have considerable soil carbon sink and storage potential; however, they are confronted with the risk of grassland degradation. The grassland ecosystems on the Qinghai-Tibet Plateau harbor substantial soil carbon sinks and storage potential. However, they are at risk of grassland degradation. It is imperative to enhance grassland management, implement sustainable grazing practices, and prevent the deterioration of the grassland carbon reservoirs to mitigate the exacerbation of greenhouse gas emissions and global warming. This highlights the urgency of implementing more studies to uncover the potential of existing grassland ecological engineering projects for carbon sequestration.

Tripedal DNA Walker as a Signal Amplifier Combined with a Potential-Resolved Multicolor Electrochemiluminescence Strategy for Ultrasensitive Detection of Prostate Cancer Staging Indicators.

A multicolor electrochemiluminescence (ECL) biosensor based on a closed bipolar electrode (BPE) array was proposed for the rapid and intuitive analysis of three prostate cancer staging indicators. First, [Irpic-OMe], [Ir(ppy)2(acac)], and [Ru(bpy)3]2+ were applied as blue, green, and red ECL emitters, respectively, whose mixed ECL emission colors covered the whole visible region by varying the applied voltages. Afterward, we designed a simple Mg2+-dependent DNAzyme (MNAzyme)-driven tripedal DNA walker (TD walker) to release three output DNAs. Immediately after, three output DNAs were added to the cathodic reservoirs of the BPE for incubation. After that, we found that the emission colors from the anode of the BPE changed as a driving voltage of 8.0 V was applied, mainly due to changes in the interfacial potential and faradaic currents at the two poles of the BPE. Via optimization of the experimental parameters, cutoff values of such three indicators at different clinical stages could be identified instantly with the naked eye, and standard precision swatches with multiple indicators could be prepared. Finally, in order to precisely determine the prostate cancer stage, the multicolor ECL device was used for clinical analysis, and the resulting images were then compared with standard swatches, laying the way for accurate prostate cancer therapy.

Dynamic characteristics of scraper conveyor chain drive system under the impact condition of lump coal.

Scraper conveyor is the most important transportation equipment in the comprehensive mining equipment, and the chain drive system is its core subsystem, its dynamic characteristics will significantly affect the efficiency of coal transportation in the comprehensive mining face. In this paper, the dynamic characteristics of chain drive system when impacted by falling coal are investigated by means of test. The impact test bench of scraper conveyor was set up to analyze the effects of chain speed, impact height and impact load mass on the dynamic characteristics of the chain drive system of scraper conveyor under the working conditions of unloaded and loaded. The results show that the longitudinal vibration of the scraper conveyor is most obvious when it is impacted by the falling coal, and the chain speed, impact height and impact load mass of the scraper conveyor all play an excitation role on the vibration of the chain drive system, and the vibration of the chain ring is the most intense in the chain drive system, and the loaded coal pile conveyed on the scraper conveyor plays an inhibiting role on the vibration of the chain drive system. This study can help to identify the location where the scraper conveyor fails first in the impact condition, so as to provide a basis for its structural design and improvement, which is of great significance for the stable operation and structural optimization of the scraper conveyor.

Short-term salt stress reduces photosynthetic oscillations under triose phosphate utilization limitation in tomato.

Triose phosphate utilization (TPU) limitation is one of the three biochemical limitations of photosynthetic CO2 assimilation rate in C3 plants. Under TPU limitation, abrupt and large transitions in light intensity cause damped oscillations in photosynthesis. When plants are salt-stressed, photosynthesis is often down-regulated particularly under dynamic light intensity, but how salt stress affects TPU-related dynamic photosynthesis is still unknown. To elucidate this, tomato (Solanum lycopersicum) was grown with and without sodium chloride (NaCl, 100 mM) stress for 13 days. Under high CO2 partial pressure, rapid increases in light intensity caused profound photosynthetic oscillations. Salt stress reduced photosynthetic oscillations in leaves initially under both low- or high-light conditions and reduced the duration of oscillations by about two minutes. Besides, salt stress increased the threshold for CO2 partial pressure at which oscillations occurred. Salt stress increased TPU capacity without affecting Rubisco carboxylation and electron transport capacity, indicating the upregulation in end-product synthesis capacity in photosynthesis. Thus salt stress may reduce photosynthetic oscillations by either decreasing leaf internal CO2 partial pressure and/or increasing TPU capacity. Our results thus provide new insights in how salt stress modulates dynamic photosynthesis as controlled by CO2 availability and end-product synthesis.

Microinterfaces in biopolymer-based bicontinuous hydrogels guide rapid 3D cell migration.

Cell migration is critical for tissue development and regeneration but requires extracellular environments that are conducive to motion. Cells may actively generate migratory routes in vivo by degrading or remodeling their environments or instead utilize existing extracellular matrix microstructures or microtracks as innate pathways for migration. While hydrogels in general are valuable tools for probing the extracellular regulators of 3-dimensional migration, few recapitulate these natural migration paths. Here, we develop a biopolymer-based bicontinuous hydrogel system that comprises a covalent hydrogel of enzymatically crosslinked gelatin and a physical hydrogel of guest and host moieties bonded to hyaluronic acid. Bicontinuous hydrogels form through controlled solution immiscibility, and their continuous subdomains and high micro-interfacial surface area enable rapid 3D migration, particularly when compared to homogeneous hydrogels. Migratory behavior is mesenchymal in nature and regulated by biochemical and biophysical signals from the hydrogel, which is shown across various cell types and physiologically relevant contexts (e.g., cell spheroids, ex vivo tissues, in vivo tissues). Our findings introduce a design that leverages important local interfaces to guide rapid cell migration.

Structures and Dynamics of ß-Rich Oligomers of ATTR (105-115) Assembly.

Transthyretin (TTR) is a tetrameric homologous protein that can dissociate into monomers. Misfolding and aggregation of TTR can lead to amyloid transthyretin amyloidosis (ATTR), which can cause many diseases (e.g., senile systemic amyloidosis, familial amyloid cardiomyopathy, and familial amyloid polyneuropathy). Despite growing evidence indicating that small oligomers play a critical role in regulating cytotoxicity, the structures of these oligomeric intermediates and their conformational transformations are still unclear, impeding our understanding of neurodegenerative mechanisms and the development of therapeutics targeting early aggregation species. The TTR monomer protein consists of various fragments prone to self-aggregation, including the residue 105-115 sequence. Therefore, our study investigated the assembly progress of ATTR (105-115) peptides using all-atom molecular dynamics simulations. The findings indicate that the probability of ß-sheet content increases with increasing numbers of peptides. Additionally, interactions between hydrophobic residues L110 and L111 are crucial for the formation of a ß-rich oligomer formation. These ß-rich oligomers may adopt ß-barrel conformations, potentially toxic oligomer species. Free-energy analysis reveals that ß-barrel conformations serve as intermediates for these ß-rich oligomers. Our insights into the structural ensemble dynamics of ATTR (105-115) contribute to understanding the physical mechanisms underlying the ß-barrel oligomers of ATTR. These findings may shed light on the pathological role of ATTR in neurodegenerative diseases and offer potential therapeutic targets.

Chemical modification of Arthrobacter sarcosine oxidase by N-methylisothiazolinone reduces reactivity toward oxygen.

N-methylisothiazolinone (MIT) is a thiol group modifier and antimicrobial agent. Arthrobacter sarcosine oxidase (SoxA), a diagnostic enzyme for assaying creatinine, loses its activity upon the addition of MIT, and its inactivation mechanism remains unclear. In this study, SoxA was chemically modified using MIT (mo-SoxA), and its structural and chemical properties were characterised. Spectral analysis data, oxygen consumption rates, and reactions were compared between intact and mo-SoxA. These demonstrate that the oxidative half-reaction toward oxygen is inhibited by MIT modification. The oxidase activity of mo-SoxA was approximately 2.1% of that of intact SoxA, and its dehydrogenase activity was approximately 4.2 times higher. The C-to-S mutants revealed that cooperative modification of two specific cysteine residues caused a drastic change in the enzyme reaction mode. Based on the modelled tertiary structures, the putative entrance for oxygen uptake is predicted to be blocked by the chemical modification of the two cysteine residues.

Geochemical baseline establishment, pollution level and health risk assessment of soil heavy metals in the upper Xiaowen River Basin, Shandong Province, China.

This study analyzed the distribution and content of eight heavy metals (Cu, Pb, Zn, Ni, Cr, As, Cd, and Hg) in 221 surface soil samples from the upper reaches of the Xiaowen River. Environmental geochemical baselines were established for the eight heavy metals, and the pollution status was assessed on the basis of these baselines and the soil background value of Weifang City. The calculation results of Nemerow pollution index and the potential ecological hazard index (PEHI)-Ri showed that the overall pollution degree and ecological hazard in the study area were at a slight level. 49% (calculated by baseline value) and 24% (calculated by background value of Weifang City) samples were at moderate or above pollution level. 9% (calculated by baseline value) and 42% (calculated by background value) samples were at the level of moderate potential ecological hazards or above. According to the calculation results of Igeo and PEHI-Ei, the main pollutant in the study area was Hg, followed by Cd. 3% (calculated by baseline value) and 12% (calculated by background value) of Hg samples were at moderate or above contamination levels. 5% (calculated by baseline value) and 38% (calculated by background value) of Hg samples were at the level of strong potential ecological hazard or above. The western, central, and eastern parts of the study area were mainly the primary areas of pollution and ecological hazards. The non-carcinogenic risk was at an acceptable level, the carcinogenic risk was at a tolerable level, and the main risk pathway was oral intake, with Cr being the main contributor. Source apportionment indicated that soil heavy metals primarily originate from soil parent material, transportation, agricultural fertilization, and industrial emissions (waste gas, waste water and solid waste).

Visualization of Ice Crystal Behavior in Mouse Oocytes During High-Speed Quench Cooling and Ice Inhibition by Antifreezing Hydrogels.

Oocyte vitrification has become a widely adopted method in clinical practice. However, the solidification behavior and its impact on oocytes during the ultrarapid cooling process remain poorly understood. In this study, we established a system and methodology to observe crystallization behavior in oocytes during quench cooling and warming. Subsequently, the threshold concentration of cryoprotective agents (CPAs) required for oocyte vitrification was determined through a visualization method. The results demonstrated that the ice front could not be observed in the image sequence when using 16.5% DMSO +16.5% EG during high-speed quench cooling (2821.58°C/min). Finally, oocytes were encapsulated with an antifreezing hydrogel (7.5% EG +7.5% DMSO +0.5% alginate) and subjected to high-speed quench cooling. No ice crystals appeared in the antifreezing hydrogel-encapsulated oocytes at a low concentration of osmotic CPA (2.4 M). This research opens up new possibilities for oocyte vitrification with a reduced concentration of CPA.

Health risk assessment of soil heavy metals in a typical mining town in north China based on Monte Carlo simulation coupled with Positive matrix factorization model.

The accumulation of heavy metals (HMs) in soil caused by mineral resource exploitation and its ancillary industrial processes poses a threat to ecology and public health. Effective risk control measures require a quantification of the impacts and contributions to health risks from individual sources of soil HMs. Based on high-density sampling, soil contamination risk indexes, positive matrix factorization (PMF) model, Monte Carlo simulation and human health risk analysis model were applied to investigate the risk of HMs in a typical mining town in North China. The results showed that As was the most dominant soil pollutant factor, Cd and Hg were the most dominant soil ecological risk factors, and Cr and Ni were the most dominant health risk factors in the study area. Overall, both pollution and ecological risks were at low levels, while there were still some higher hazard areas located in the central and south-central part of the region. According to the probabilistic health risk assessment (HRA), children suffered greater health risks than adults, with 21.63% of non-carcinogenic risks and 53.24% of carcinogenic risks exceeding the prescribed thresholds (HI > 1 and TCR>1E-4). The PMF model identified five potential sources: fuel combustion (FC), processing of building materials with limestone as raw materials (PBML), industry source (IS), iron ore mining combined with garbage (IOG), and agriculture source (AS). PBML is the primary source of soil HM contamination, as well as the major anthropogenic source of carcinogenic risk for all populations. Agricultural inputs associated with As are the major source of non-carcinogenic risk. This study offers a good example of probabilistic HRA using specific sources, which can provide a valuable reference for strategy establishment of pollution remediation and risk prevention and control.

Dual "on-off" signal conversion strategy based on surface plasmon coupling and resonance energy transfer for visual electrochemiluminescence ratiometric analysis of MiRNA-141.

An electrochemiluminescence (ECL) biosensor with a pair of new ECL emitters and a novel sensing mechanism was designed for the high-sensitivity detection of microRNA-141 (miRNA-141). Sulfur-doped boron nitrogen quantum dots (S-BN QDs) were initially employed to modify the cathode of the bipolar electrode (BPE), while the anode reservoir was [Ir(dfppy)2(bpy)]PF6/TPrA system. The next step involved attaching H1-bound ultra-small WO3-x nanodots (WO3-x NDs) to the S-BN QDs-modified BPE cathode via DNA hybridization. A strong surface plasmon coupling (SPC) effect was observed between S-BN QDs and WO3-x NDs, which allowed for the enhancement of the red and visible ECL emission from S-BN QDs. After target-induced cyclic amplification to produce abundant Zn2+ and Au NPs-DNA3-Au NPs (Au NPs-S3-Au NPs), Zn2+ could cleave DNA at a nucleotide sequence-specific recognition site to release the WO3-x NDs, resulting in the first diminution of cathode ECL signal and the first enhancement of anode ECL signal. Moreover, the ECL signal at cathode decreased for the second time and the emission of [Ir(dfppy)2(bpy)]PF6 was continuously enhanced after the introduction of Au nanoparticles-S3-Au nanoparticles on the cathode surface. Our sensing mode with a dual "on-off" signal conversion strategy shows a good detection capability for miRNAs ranging from 10-17 to 10-10 M, with a limit of detection (LOD) as low as 10-17 M, which has great application potential in biomedical research and clinical diagnosis.

A Hybrid Redox-Mediated Zinc-Air Fuel Cell for Scalable and Sustained Power Generation.

Zinc-air batteries (ZABs) have attracted considerable attention for their high energy density, safety, low noise, and eco-friendliness. However, the capacity of mechanically rechargeable ZABs was limited by the cumbersome procedure for replacing the zinc anode, while electrically rechargeable ZABs suffer from issues including low depth of discharge, zinc dendrite and dead zinc formation, and sluggish oxygen evolution reaction, etc. To address these issues, we report a hybrid redox-mediated zinc-air fuel cell (HRM-ZAFC) utilizing 7,8-dihydroxyphenazine-2-sulfonic acid (DHPS) as the anolyte redox mediator, which shifts the zinc oxidation reaction from the electrode surface to a separate fuel tank. This approach decouples fuel feeding and electricity generation, providing greater operation flexibility and scalability for large-scale power generation applications. The DHPS-mediated ZAFC exhibited a superior peak power density of 0.51 W/cm2 and a continuous discharge capacity of 48.82 Ah with ZnO as the discharge product in the tank, highlighting its potential for power generation.

AI-based Virtual Screening of Traditional Chinese Medicine and the Discovery of Novel Inhibitors of TCTP.

BACKGROUND: Translationally controlled tumour protein (TCTP) is associated with tumor diseases, such as breast cancer, and its inhibitor can reduce the growth of tumor cells. Unfortunately, there is currently no effective medication available for treating TCTP-related breast cancer. OBJECTIVE: The objective of this study was to explore the inhibitor candidates among natural compounds for the treatment of breast cancer related to TCTP protein. METHODS: To explore the potential inhibitors of TCTP, we first screened out four potential inhibitors in the Traditional Chinese Medicine (TCM) for cancer based on AI virtual screening using the docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCM with molecular docking and molecular dynamics (MD) methods. RESULTS: Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with the AI method using MolAICal software. Our MD simulations have revealed that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, and the VDW and hydrophobic interactions are crucial in the interactions between TCTP and ligands. CONCLUSION: We have proposed the candidate inhibitor of TCTP. Our study has provided a potential new method for exploring inhibitors from Traditional Chinese Medicine (TCM).