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Abstract Lasing in the bad-cavity regime has promising applications in quantum precision measurement and frequency metrology due to the reduced sensitivity of the laser frequency to cavity-length fluctuations. Thus far, relevant studies have been mainly focused on conventional cavities whose finesse is high enough that the resonance linewidth is sufficiently narrow compared to the cavity’s free spectral range, though still in the bad-cavity regime. However, lasing output from the cavity whose finesse is close to the limit of 2 has never been experimentally accessed. Here, we demonstrate an extremely bad-cavity laser, analyze the physical mechanisms limiting cavity finesse, and report on the worst-ever laser cavity with finesse reaching 2.01. The optical cavity has a reflectance close to zero and only provides weak optical feedback. The laser power can be as high as tens of μW and the spectral linewidth reaches a few kHz, over one thousand times narrower than the gain bandwidth. In addition, the measurement of cavity pulling reveals a pulling coefficient of 0.0148, the lowest value ever achieved for a continuous-wave laser. Our findings open up an unprecedentedly innovative perspective for future new ultra-stable lasers, which could possibly trigger future discoveries in optical clocks, cavity QED, continuous-wave superradiant laser, and explorations of quantum many-body physics.

Abstract Chemodynamic therapy represents a novel tumor therapeutic modality via triggering catalytic reactions in tumors to yield highly toxic reactive oxygen species (ROS). Nevertheless, low efficiency catalytic ability, potential systemic toxicity and inefficient tumor targeting, have hindered the efficacy of chemodynamic therapy. Herein, a rationally designed catalytic nanoplatform, composed of folate acid conjugated liposomes loaded with copper peroxide (CP) and chloroquine (CQ; a clinical drug) (denoted as CC@LPF), could power maximal tumor cytotoxicity, mechanistically via maneuvering endogenous and exogenous copper for a highly efficient catalytic reaction. Despite a massive autophagosome accumulation elicited by CP-powered autophagic initiation and CQ-induced autolysosomal blockage, the robust ROS, but not aberrant autophagy, underlies the synergistic tumor inhibition. Otherwise, this combined mode also elicits an early onset, above all, long-term high-level existence of immunogenic cell death markers, associated with ROS and aberrant autophagy -triggered endoplasmic reticulum stress. Besides, CC@LPF, with tumor targeting capability and selective tumor cytotoxicity, could elicit intratumor dendritic cells (mainly attributed to CQ) and tumor infiltrating CD8+ T cells, upon combining with PD-L1 therapeutic antibody, further induce significant anti-tumor effect. Collectively, the rationally designed nanoplatform, CC@LPF, could enhance tumor chemoimmunotherapy via deploying endogenous plus exogenous copper and remodeling tumor microenvironment. Graphical abstract

Abstract Converting solar energy into fuels is pursued as an attractive route to reduce dependence on fossil fuel. In this context, photothermal catalysis is a very promising approach through converting photons into heat to drive catalytic reactions. There are mainly three key factors that govern the photothermal catalysis performance: maximized solar absorption, minimized thermal emission and excellent catalytic property of catalyst. However, the previous research has focused on improving solar absorption and catalytic performance of catalyst, largely neglected the optimization of thermal emission. Here, we demonstrate an optically selective catalyst based Ti3C2Tx Janus design, that enables minimized thermal emission, maximized solar absorption and good catalytic activity simultaneously, thereby achieving excellent photothermal catalytic performance. When applied to Sabatier reaction and reverse water-gas shift (RWGS) as demonstrations, we obtain an approximately 300% increase in catalytic yield through reducing the thermal emission of catalyst by ~70% under the same irradiation intensity. It is worth noting that the CO2 methanation yield reaches 3317.2 mmol gRu −1 h−1 at light power of 2 W cm−2, setting a performance record among catalysts without active supports. We expect that this design opens up a new pathway for the development of high-performance photothermal catalysts.

Abstract Mechanochemistry studies the effect of mechanical force on chemical bonds, bringing opportunities for synthesizing alloys, ceramics, organics, polymers, and biomaterials. A vital issue of applying macro-scale mechanical force to manipulate crystal structures is finding ways to precisely adjust the force directions to break micro-scale target chemical bonds. Inspired by a common technique of driving a wedge into the wood to make wood chopping much easier, a wedging strategy of splitting three-dimensional structured crystalline frameworks and then converting them to nanosheets was proposed, where specific molecules were wedged into crystalline frameworks to drive the directional transmission of mechanical force to break chemical bonds. As a result, various crystalline framework nanosheets including metal−organic framework nanosheets, covalent organic framework nanosheets, and coordination polymer nanosheets were fabricated. This wedging crystal strategy exhibits advantages of operability, flexibility and designability, and furthermore, it is expected to expand mechanochemistry applications in material preparation.

Abstract Whenever the elastic energy of a solid depends on magnetic field, there is a magnetostrictive response. Field-linear magnetostriction implies piezomagnetism and vice versa. Here, we show that Mn3Sn, a non-collinear antiferromanget with Weyl nodes, hosts a large and almost perfectly linear magnetostriction even at room temperature. The longitudinal and transverse magnetostriction, with opposite signs and similar amplitude are restricted to the kagome planes and the out-of-plane response is negligibly small. By studying four different samples with different Mn:Sn ratios, we find a clear correlation between the linear magnetostriction, the spontaneous magnetization and the concentration of Sn vacancies. The recently reported piezomagnetic data fits in our picture. We show that linear magnetostriction and piezomagnetism are both driven by the field-induced in-plane twist of spins. A quantitative account of the experimental data requires the distortion of the spin texture by Sn vacancies. We find that the field-induced domain nucleation within the hysteresis loop corresponds to a phase transition. Within the hysteresis loop, a concomitant mesoscopic modulation of local strain and spin twist angles, leading to twisto-magnetic stripes, arises as a result of the competition between elastic and magnetic energies.

Abstract Transportation systems primarily depend on vehicular flow on roads. Developed countries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

Abstract Anthocidaris crassispina is a very popular edible sea urchin distributed along the coast of the South China Sea. In this study, we performed whole-genome sequencing and generated a chromosome-level assembly of this species. The total length of the genomic contig sequence was 891.02 Mb, and contig N50 was 808.15 kb when Hifiasm was used for assembly. The Hi-C library was constructed and sequenced, yielding approximately 68.61 Gb of data. After Hi-C assembly, approximately 886.72 Mb of sequence was able to be mapped onto 21 chromosomes, accounting for 99.52% of the total genome length. Among the sequences located on the chromosomes, those for which the order and direction could be determined accounted for approximately 826.82 Mb, or 93.24% of the total length. These results provide valuable resources for further study of A. crassispina at the genetic level.

Water pollution has emerged as a significant worldwide issue, with organic pollutants being a key contributor. Titanium dioxide (TiO2) has demonstrated promising photocatalytic performance in removing organic pollutants under ultraviolet (UV) irradiation. However, the wide band gap (3.2 eV) of TiO2 results in low absorption capacity of visible light, hindering its overall efficiency in degrading organic pollutants. To address the limitation, this research aimed to synthesize visible light-driven TiO2 photocatalyst with different polymorphs (anatase and rutile) and investigate the effect of various doping combination (Nb, B and Nb,B) and concentrations (0.25, 0.50, 0.75 and 1.00 mol%) on the photodegradation efficiency towards methylene blue (MB) dye solution. Anatase phase was obtained when TiO2-based nanopowders were calcined at 400 °C, while the rutile phase was formed at 900 °C based on XRD analyses. Additionally, the morphology analyses revealed that the particle size of anatase is much smaller than that of rutile. The presence of dopants further reduced the particle size of both anatase and rutile phases. Based on UV-Vis absorbance spectra analyses, the anatase Nb,B-TiO2 with 0.50 mol% of dopant concentration exhibited the best photocatalytic performance towards MB. Moreover, the anatse phase of 0.50 mol% Nb,B-TiO2 showed the narrowest band gap of 2.74 eV compared to the TiO2 (3.4 eV), representing a reduction of 19.41 %, according to UV-Vis analyses. These outcomes suggest the potential application of anatase phase of 0.50 mol% Nb,B-TiO2 in treating organic pollutants in wastewater under visible light conditions in future. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Abstract Electrocatalysis holds the key to enhancing the efficiency and cost-effectiveness of water splitting devices, thereby contributing to the advancement of hydrogen as a clean, sustainable energy carrier. This study focuses on the rational design of Ru nanoparticle catalysts supported on TiN (Ru NPs/TiN) for the hydrogen evolution reaction in alkaline conditions. The as designed catalysts exhibit a high mass activity of 20 A mg−1 Ru at an overpotential of 63 mV and long-term stability, surpassing the present benchmarks for commercial electrolyzers. Structural analysis highlights the effective modification of the Ru nanoparticle properties by the TiN substrate, while density functional theory calculations indicate strong adhesion of Ru particles to TiN substrates and advantageous modulation of hydrogen adsorption energies via particle-support interactions. Finally, we assemble an anion exchange membrane electrolyzer using the Ru NPs/TiN as the hydrogen evolution reaction catalyst, which operates at 5 A cm−2 for more than 1000 h with negligible degradation, exceeding the performance requirements for commercial electrolyzers. Our findings contribute to the design of efficient catalysts for water splitting by exploiting particle-support interactions.

In this work, two kinds of primary batteries, both of which included a Zn anode, C rod cathode, copper wire and electrolyte composed of Cd2+-contaminated water or soil, were constructed in the first attempt to both remove Cd2+ and generate electricity. Unlike traditional technologies such as electrokinetic remediation with high energy consumption, this technology could realize Cd2+ migration to aggregation and solidification and generate energy at the same time through simultaneous galvanic reactions. The passive surface of Zn and C was proven via electrochemical measurements to be porous to maintain the relatively active galvanic reactions for continuous Cd2+ precipitation. Cd2+ RE (removal efficiency) and electricity generation were investigated under different conditions, based on which two empirical models were established to predict them successfully. In soil, KCl was added to desorb Cd2+ from soil colloids to promote Cd2+ removal. These systems were also proven to remove Cd2+ efficiently when their effects on plants, zebrafish, and the soil bacterial community were tested. LEDs could be lit for days by utilizing the electricity produced herein. This work provides a novel, green, and low-cost route to remediate Cd2+ contamination and generate electricity simultaneously, which is of extensive practical significance in the environmental and energy fields.

Nanoscale zero-valent iron(nZVI) has broad application prospect in the field of water treatment due to its high specific surface area, high reactivity, and strong reduction performance. Four commonly used preparation methods of nZVI were described and compared, including liquid phase reduction, carbothermal reduction, green synthesis and mechanical ball milling. As nZVI had the problems of easy agglomeration and oxidation, four modification methods of nZVI such as load modification, bimetallic modification, vulcanization modification and surface modification were introduced. The mechanism of nZVI coupled with several common oxidants (O2, H2O2, O3, PS, etc.) to remove refractory wastewater was analyzed, and the research trend and development direction of nZVI in the field of water treatment were proposed.

Abstract Electrocatalytic nitrate reduction to ammonia holds great promise for developing green technologies for electrochemical ammonia energy conversion and storage. Considering that real nitrate resources often exhibit low concentrations, it is challenging to achieve high activity in low-concentration nitrate solutions due to the competing reaction of the hydrogen evolution reaction, let alone considering the catalyst lifetime. Herein, we present a high nitrate reduction performance electrocatalyst based on a Co nanosheet structure with a gradient dispersion of Ru, which yields a high NH3 Faraday efficiency of over 93% at an industrially relevant NH3 current density of 1.0 A/cm2 in 2000 ppm NO3 - electrolyte, while maintaining good stability for 720 h under −300 mA/cm2. The electrocatalyst maintains high activity even in 62 ppm NO3 - electrolyte. Electrochemical studies, density functional theory, electrochemical in situ Raman, and Fourier-transformed infrared spectroscopy confirm that the gradient concentration design of the catalyst reduces the reaction energy barrier to improve its activity and suppresses the catalyst evolution caused by the expansion of the Co lattice to enhance its stability. The gradient-driven design in this work provides a direction for improving the performance of electrocatalytic nitrate reduction to ammonia.

Abstract The tumor microenvironment (TME) plays a pivotal role in the onset, progression, and treatment response of cancer. Among the various components of the TME, cancer-associated fibroblasts (CAFs) are key regulators of both immune and non-immune cellular functions. Leveraging single-cell RNA sequencing (scRNA) data, we have uncovered previously hidden and promising roles within this specific CAF subgroup, paving the way for its clinical application. However, several critical questions persist, primarily stemming from the heterogeneous nature of CAFs and the use of different fibroblast markers in various sample analyses, causing confusion and hindrance in their clinical implementation. In this groundbreaking study, we have systematically screened multiple databases to identify the most robust marker for distinguishing CAFs in lung cancer, with a particular focus on their potential use in early diagnosis, staging, and treatment response evaluation. Our investigation revealed that COL1A1, COL1A2, FAP, and PDGFRA are effective markers for characterizing CAF subgroups in most lung adenocarcinoma datasets. Through comprehensive analysis of treatment responses, we determined that COL1A1 stands out as the most effective indicator among all CAF markers. COL1A1 not only deciphers the TME signatures related to CAFs but also demonstrates a highly sensitive and specific correlation with treatment responses and multiple survival outcomes. For the first time, we have unveiled the distinct roles played by clusters of CAF markers in differentiating various TME groups. Our findings confirm the sensitive and unique contributions of CAFs to the responses of multiple lung cancer therapies. These insights significantly enhance our understanding of TME functions and drive the translational application of extensive scRNA sequence results. COL1A1 emerges as the most sensitive and specific marker for defining CAF subgroups in scRNA analysis. The CAF ratios represented by COL1A1 can potentially serve as a reliable predictor of treatment responses in clinical practice, thus providing valuable insights into the influential roles of TME components. This research marks a crucial step forward in revolutionizing our approach to cancer diagnosis and treatment.

Abstract Background Somatic mutations have been observed to induce aldosterone-producing adenomas (APAs). These may be accelerated during pregnancy. Somatic PRKACA mutations are common in cortisol-producing adenomas (CPAs). However, their role in APAs, particularly aldosterone- and cortisol-producing adenomas (A/CPAs), is not well understood. This study aims to investigate the association between PRKACA mutations and the accelerated development of A/CPAs during pregnancy. Case presentation A patient with primary aldosteronism (PA) associated with severe Cushing’s syndrome (CS) underwent surgical resection of an adrenal tumor one year after delivery. Pathologic examination revealed an adrenocortical adenoma characterized primarily by zona glomerulosa hyperplasia. Somatic mutation analysis revealed the presence of the somatic PRKACA mutation, which was validated as a deleterious mutation by various computational databases. Immunohistochemical results showed positive staining for cytochrome P450 family 11 subfamily B member 1 (CYP11B1), cytochrome P450 family 11 subfamily B member 2 (CYP11B2), and luteinizing hormone/chorionic gonadotropin receptor (LHCGR). Our study included a review of 20 previously documented cases of aldosterone- and cortisol-producing adenomas (A/CPAs), two of which were concurrently positive for both CYP11B1 and CYP11B2, consistent with our findings. Conclusion Somatic mutations in PRKACA may correlate with the upregulation of LHCGR, which synergistically drives the accelerated growth of co-secretion tumors during pregnancy, thereby exacerbating disease progression.

Abstract Liver fibrosis is an important pathological process in chronic liver disease and cirrhosis. Recent studies have found a close association between intestinal microbiota and the development of liver fibrosis. To determine whether there are differences in the intestinal microbiota between rhesus macaques with liver fibrosis (MG) and normal rhesus macaques (MN), fecal samples were collected from 8 male MG and 12 male MN. The biological composition of the intestinal microbiota was then detected using 16S rRNA gene sequencing. The results revealed statistically significant differences in ASVs and Chao1 in the alpha-diversity and the beta-diversity of intestinal microbiota between MG and MN. Both groups shared Prevotella and Lactobacillus as common dominant microbiota. However, beneficial bacteria such as Lactobacillus were significantly less abundant in MG (P = 0.02). Predictive functional analysis using PICRUSt2 gene prediction revealed that MG exhibited a higher relative abundance of functions related to substance transport and metabolic pathways. This study may provide insight into further exploration of the mechanisms by which intestinal microbiota affect liver fibrosis and its potential future use in treating liver fibrosis.

Abstract Remarkable advances in protocol development have been achieved to manufacture insulin-secreting islets from human pluripotent stem cells (hPSCs). Distinct from current approaches, we devised a tunable strategy to generate islet spheroids enriched for major islet cell types by incorporating PDX1+ cell budding morphogenesis into staged differentiation. In this process that appears to mimic normal islet morphogenesis, the differentiating islet spheroids organize with endocrine cells that are intermingled or arranged in a core-mantle architecture, accompanied with functional heterogeneity. Through in vitro modelling of human pancreas development, we illustrate the importance of PDX1 and the requirement for EphB3/4 signaling in eliciting cell budding morphogenesis. Using this new approach, we model Mitchell-Riley syndrome with RFX6 knockout hPSCs illustrating unexpected morphogenesis defects in the differentiation towards islet cells. The tunable differentiation system and stem cell-derived islet models described in this work may facilitate addressing fundamental questions in islet biology and probing human pancreas diseases.

Abstract Purpose Diet plays a fundamental role in promoting resilience against stress-related disorders. We aimed to examine the overall and sex-specific association between food groups and perceived stress in adults. Methods We analyzed the prospective data of 7,434 adults who completed both the 2011 and 2015 surveys of the China Health and Nutrition Survey (CHNS). The Diet Quality Questionnaire (DQQ) was used to code all the food items of 2011 dietary intake into 29 food groups, and perceived stress in 2015 was measured using a 14-item perceived stress scale (PSS-14). Univariate analysis and logistic regression models were used to examine the relationship between food groups and perceived stress. Results People who perceived a higher level of stress (PSS-14 total score > 25) made up 41.5% and 45.1% of the male and female groups, respectively (χ2 = 9.605, p = 0.002). Individuals with increased intake of food groups such as legumes, other vegetables, other fruits, yogurt, poultry, fish & seafood, fluid milk, and fruit juice were less likely to experience a higher level of psychological stress (OR range: 0.544–0.892, p

Abstract Data sources The Global Burden of Diseases, Injuries, and Risk Factors study (GBD) 2019. Background To describe burden, and to explore cross-country inequalities according to socio-demographic index (SDI) for stroke and subtypes attributable to diet. Methods Death and years lived with disability (YLDs) data and corresponding estimated annual percentage changes (EAPCs) were estimated by year, age, gender, location and SDI. Pearson correlation analysis was performed to evaluate the connections between age-standardized rates (ASRs) of death, YLDs, their EAPCs and SDI. We used ARIMA model to predict the trend. Slope index of inequality (SII) and relative concentration index (RCI) were utilized to quantify the distributive inequalities in the burden of stroke. Results A total of 1.74 million deaths (56.17% male) and 5.52 million YLDs (55.27% female) attributable to diet were included in the analysis in 2019.Between 1990 and 2019, the number of global stroke deaths and YLDs related to poor diet increased by 25.96% and 74.76% while ASRs for death and YLDs decreased by 42.29% and 11.34% respectively. The disease burden generally increased with age. The trends varied among stroke subtypes, with ischemic stroke (IS) being the primary cause of YLDs and intracerebral hemorrhage (ICH) being the leading cause of death. Mortality is inversely proportional to SDI (R = -0.45, p

Abstract Macrophages play a pivotal role in orchestrating the immune response against pathogens. While the intricate interplay between macrophage activation and metabolism remains a subject of intense investigation, the role of glutamate oxaloacetate transaminase 1 (Got1) in this context has not been extensively assessed. Here, we investigate the impact of Got1 on macrophage polarization and function, shedding light on its role in reactive oxygen species (ROS) production, pathogen defense, and immune paralysis. Using genetically modified mouse models, including both myeloid specific knockout and overexpression, we comprehensively demonstrate that Got1 depletion leads to reduced ROS production in macrophages. Intriguingly, this impairment in ROS generation does not affect the resistance of Got1 KO mice to pathogenic challenges. Furthermore, Got1 is dispensable for M2 macrophage differentiation and does not influence the onset of LPS-induced immune paralysis. Our findings underscore the intricate facets of macrophage responses, suggesting that Got1 is dispensable in discrete immunological processes.

Regulated cell death (RCD) is a controlled form of cell death orchestrated by one or more cascading signaling pathways, making it amenable to pharmacological intervention. RCD subroutines can be categorized as apoptotic or non-apoptotic and play essential roles in maintaining homeostasis, facilitating development, and modulating immunity. Accumulating evidence has recently revealed that RCD evasion is frequently the primary cause of tumor survival. Several non-apoptotic RCD subroutines have garnered attention as promising cancer therapies due to their ability to induce tumor regression and prevent relapse, comparable to apoptosis. Moreover, they offer potential solutions for overcoming the acquired resistance of tumors toward apoptotic drugs. With an increasing understanding of the underlying mechanisms governing these non-apoptotic RCD subroutines, a growing number of small-molecule compounds targeting single or multiple pathways have been discovered, providing novel strategies for current cancer therapy. In this review, we comprehensively summarized the current regulatory mechanisms of the emerging non-apoptotic RCD subroutines, mainly including autophagy-dependent cell death, ferroptosis, cuproptosis, disulfidptosis, necroptosis, pyroptosis, alkaliptosis, oxeiptosis, parthanatos, mitochondrial permeability transition (MPT)-driven necrosis, entotic cell death, NETotic cell death, lysosome-dependent cell death, and immunogenic cell death (ICD). Furthermore, we focused on discussing the pharmacological regulatory mechanisms of related small-molecule compounds. In brief, these insightful findings may provide valuable guidance for investigating individual or collaborative targeting approaches towards different RCD subroutines, ultimately driving the discovery of novel small-molecule compounds that target RCD and significantly enhance future cancer therapeutics.

Background: The effect of transcranial alternating current stimulation (tACS) on major depressive disorder (MDD) was not confirmed. Objective: To evaluate the feasibility, safety, and efficacy of tACS as an add-on treatment for the symptoms of depression and to understand how tACS affects brain activity. Methods: The 4-week, double-blind, randomized, sham-controlled trial was performed from January 29, 2023 to December 22, 2023. Sixty-six participants were recruited and randomly assigned to receive 20 40-min sessions of either active (77.5Hz, 15 mA) or sham stimulation, with one electrode on the forehead and two on the mastoid, each day (n = 33 for each group) for four weeks (till Week 4). The participants were followed for 4 more weeks (till Week 8) without stimulation for efficacy/safety assessment. During the 4-week trial, all participants were required to take 10–20 mg of escitalopram daily. The primary efficacy endpoint was the change in HAMD-17 scores from baseline to Week 4 (with 20 treatment sessions completed). Resting-state electroencephalography (EEG) was collected with a 64-channel EEG system (Brain Products, Germany) at baseline and the Week 4 follow-up. The chi-square test, Fisher's exact test, independent-sample t-test, or Wilcoxon rank-sum test were used, as appropriate, to compare the differences in variables between groups. The effect of the intervention on the HAMD-17 score was also evaluated with linear mixed modeling (LMM) as sensitivity analysis. The correlation between the mean reduction in EEG and the mean reduction in the HAMD-17 total score was evaluated using Spearman correlation analysis. Results: A total of 66 patients (mean [SD] age, 28.4 [8.18] years; 52 [78.8 %] female) were randomized, and 57 patients completed the study. Significant differences were found in the reductions in the HAMD-17 scores at Week 4 (t = 3.44, P = 0.001). Response rates at Week 4 were significantly higher in the active tACS group than in the sham tACS group (22 out of 33 patients [66.7 %] versus 11 out of 33 [33.3 %], P = 0.007). In the active tACS group, a correlation between the mean change in alpha power and HAMD-17 scores at Week 4 was found (r = 2.38, P = 0.024), and the mean change in alpha power was significantly bigger for responders (Z = 2.46, P = 0.014). No serious adverse events were observed in this trial. Conclusion: The additional antidepressant effect of tACS is significant, and the combination of tACS with antidepressants is a feasible and effective approach for the treatment of MDD. The antidepressant mechanism of tACS may be the reduction in alpha power in the left frontal lobe. Future research directions may include exploring more appropriate treatment parameters of tACS.

Although gastrointestinal stromal tumors (GISTs) has been reported in patients of all ages, its diagnosis is more common in elders. The two most common types of mutation, receptor tyrosine kinase (KIT) and platelet-derived growth factor receptor a (PDGFRA) mutations, hold about 75 and 15% of GISTs cases, respectively. Tumors without KIT or PDGFRA mutations are known as wild type (WT)-GISTs, which takes up for 15% of all cases. WT-GISTs have other genetic alterations, including mutations of the succinate dehydrogenase and serine–threonine protein kinase BRAF and neurofibromatosis type 1. Other GISTs without any of the above genetic mutations are named “quadruple WT” GISTs. More types of rare mutations are being reported. These mutations or gene fusions were initially thought to be mutually exclusive in primary GISTs, but recently it has been reported that some of these rare mutations coexist with KIT or PDGFRA mutations. The treatment and management differ according to molecular subtypes of GISTs. Especially for patients with late-stage tumors, developing a personalized chemotherapy regimen based on mutation status is of great help to improve patient survival and quality of life. At present, imatinib mesylate is an effective first-line drug for the treatment of unresectable or metastatic recurrent GISTs, but how to overcome drug resistance is still an important clinical problem. The effectiveness of other drugs is being further evaluated. The progress in the study of relevant mechanisms also provides the possibility to develop new targets or new drugs.

AbstractThis study prepared and evaluated polymeric polybutylcyanoacrylate (PBCA) nanoparticles (NPs) that can be used as a new agent for contrast-enhanced intravascular ultrasound (IVUS) imaging with drug delivery capacity. The nanoformulation was successfully developed using suspension polymerisation and characterised in terms of size, size distribution, zeta potential, morphology, stability, toxicity effects, imaging effects and drug release study. The results showed that the nanoparticles were round and hollow, with a particle diameter of 215.8 ± 25.3 nm and a zeta potential of −22.2 ± 4.1 mV. In vitro experiments, the nanoparticles were safe, non-toxic, and stable in nature with the capacity to carry and release drug (ant-miR-126). Moreover, the nanoparticles can match the high-frequency probe of commercially IVUS as a contrast agent to improve the resolution of imaging (the mean echo intensity ratio in the vascular wall increased significantly from 10.89 ± 1.10 at baseline, to 24.51 ± 1.91 during injection and 43.70 ± 0.88 after injection, respectively p

Periodontitis is a chronic inflammatory disease caused by plaque that destroys the alveolar bone tissues, resulting in tooth loss. Poor eradication of pathogenic microorganisms, persistent malignant inflammation and impaired osteo-/angiogenesis are currently the primary challenges to control disease progression and rebuild damaged alveolar bone. However, existing treatments for periodontitis fail to comprehensively address these issues. Herein, an injectable composite hydrogel (SFD/CS/ZIF-8@QCT) encapsulating quercetin-modified zeolitic imidazolate framework-8 (ZIF-8@QCT) is developed. This hydrogel possesses thermo-sensitive and adhesive properties, which can provide excellent flowability and post-injection stability, resist oral fluid washout as well as achieve effective tissue adhesion. Inspirationally, it is observed that SFD/CS/ZIF-8@QCT exhibits a rapid localized hemostatic effect following implantation, and then by virtue of the sustained release of zinc ions and quercetin exerts excellent collective functions including antibacterial, immunomodulation, pro-osteo-/angiogenesis and pro-recruitment, ultimately facilitating excellent alveolar bone regeneration. Notably, our study also demonstrates that the inhibition of osteo-/angiogenesis of PDLSCs under the periodontitis is due to the strong inhibition of energy metabolism as well as the powerful activation of oxidative stress and autophagy, whereas the synergistic effects of quercetin and zinc ions released by SFD/CS/ZIF-8@QCT are effective in reversing these biological processes. Overall, our study presents innovative insights into the advancement of biomaterials to regenerate alveolar bone in periodontitis.

Precisely pinpointing the positions of emitters within the diffraction limit is crucial for quantitative analysis or molecular mechanism investigation in biomedical research but has remained challenging unless exploiting single molecule localization microscopy (SMLM). Via integrating experimental spot dataset with deep learning, we develop a new approach, Digital-SMLM, to accurately predict emitter numbers and positions for sub-diffraction-limit spots with an accuracy of up to 98 % and a root mean square error as low as 14 nm. Digital-SMLM can accurately resolve two emitters at a close distance, e.g. 30 nm. Digital-SMLM outperforms Deep-STORM in predicting emitter numbers and positions for sub-diffraction-limited spots and recovering the ground truth distribution of molecules of interest. We have validated the generalization capability of Digital-SMLM using independent experimental data. Furthermore, Digital-SMLM complements SMLM by providing more accurate event number and precise emitter positions, enabling SMLM to closely approximate the natural state of high-density cellular structures.

Abstract Background Guillain‒Barre syndrome (GBS) is an acute inflammatory peripheral neuropathy caused by autoimmunity. Gangliosides and sulfatides are important components of peripheral nerves. Anti-sulfatide antibody-mediated complement is associated with acute sensorimotor peripheral neuropathy in GBS, which is characterized by pain and paresthesias. Case presentation The child was a 7-year-old girl with headache and abdominal pain, followed by limb numbness and pain. Cranial imaging showed ventricular dilatation, peripheral nerve function conduction examination showed polyradiculopathy, and cerebrospinal fluid tests showed normal cell counts but elevated protein levels, all of which led to the diagnosis of GBS. After treatment with intravenous immunoglobulin (400 mg/kg × 5 days), the symptoms did not improve, and muscle strength progressively worsened, accompanied by paroxysmal complexion flushing, heart rate fluctuation, hyperhidrosis, and a progressive increase in cerebrospinal fluid protein (up to 3780.1 mg/L). On the basis of these findings combined with serum anti-sulfatide IgM positivity, anti-sulfatide antibody-related GBS was considered, and treatment with low-dose prednisolone (1 mg/kg/d) led to symptom improvement. Conclusions Anti-sulfatide antibody-associated GBS is associated with small fiber peripheral neuropathy. The main manifestations are pain, paresthesias and autonomic dysfunction. In addition to the dysfunction of spinal nerve root absorption caused by increased cerebrospinal fluid protein, autonomic dysfunction may be involved in pain. When the therapeutic effect of immunoglobulin is not satisfactory, a low dose and short course of corticosteroids can be considered, and the prognosis is good.

Abstract Objective To compare the effect of different indicators on stress‐induced hyperglycemia for predicting in‐hospital outcomes of acute intracerebral hemorrhage. Methods Using data from the Chinese Stroke Center Alliance database, which is a national, multicenter, prospective, and consecutive program. Stress‐induced hyperglycemia was described as glycemic gap (GG, defined as fasting blood glucose [FBG] minus estimated average blood glucose) and stress hyperglycemia ratio (SHR, defined as FBG‐to‐estimated average blood glucose ratio [SHR 1] or FBG‐to‐HbA1c ratio [SHR 2]). The primary outcome was in‐hospital mortality, and the second outcome was hematoma expansion. Results A total of 71,333 patients with acute intracerebral hemorrhage were included. In multivariate analyses, the highest levels of GG (OR 1.68, 95% CI 1.12–2.51), SHR 1 (OR 1.73, 95% CI 1.15–2.60), and SHR 2 (OR 2.07, 95% CI 1.33–3.23) were associated with in‐hospital death (all the p trends 0.05) was related to hematoma expansion. No association between GG or SHR 1 and hematoma expansion was observed. The areas under the ROC curve of GG, SHR 1, and SHR 2 for in‐hospital mortality were 0.8808 (95% CI 0.8603–0.9014), 0.8796 (95% CI 0.8589–0.9002), and 0.8806 (95% CI 0.8600–0.9012). The areas under the ROC curve of SHR 2 for hematoma expansion were 0.7133 (95% CI 0.6964–0.7302). Interpretation SHR (FBG‐to‐HbA1c ratio) was associated with both in‐hospital death and hematoma expansion in intracerebral hemorrhage, and might serve as an accessory indicator for the in‐hospital prognosis of intracerebral hemorrhage.

Drug testing has many test elements. It aims to prevent unqualified drugs from entering the market and ensure drug safety. The existing artificial intelligence (AI) online monitoring system identifies active ingredients in the process of use. Owing to their openness, data are easy to be lost, failing to meet user needs and inducing a specific impact on the use of the monitoring system. With the continuous development of computer and measurement technologies, various biochemical data are increasing at an unprecedented speed, and numerous databases are emerging. Extracting patterns from considerable known data and experimental facts is an essential task for a wide range of biological and chemical workers. Pattern recognition is one of the essential technologies for data mining. It is widely used in industry, agriculture, national defense, biomedicine, meteorology, astronomy, and other fields. To improve the effect of the online drug ingredient recognition system, this study used AI to design an online drug ingredient recognition-embedded monitoring system and applied AI to the teaching field to improve teaching efficiency. First, this study constructed the framework of the AI online drug ingredient recognition-embedded monitoring system and introduced the process of online drug ingredient recognition. Then, it introduced the pattern recognition method, constructed the pattern recognition system, and presented the pattern recognition algorithm and the algorithm evaluation index. Afterward, it used pattern recognition to conduct a qualitative analysis of the infrared spectrum of drug components and introduced the overall process of the qualitative analysis. In addition, this study employed AI to implement changes to the embedded system instruction in colleges and universities, summarizing the current issues. The impact of drug component recognition and the educational impact of embedded systems were investigated in the experimental portion. The experimental findings demonstrated the excellent accuracy, sensitivity, specificity, and Matthew correlation coefficient of the online drug component recognition-integrated monitoring system in this work. Compared with that of other systems, its average drug component recognition accuracy was above 0.85. Students in five majors reported high levels of satisfaction with the embedded system teaching, which is better for delivering college instruction.

Abstract To address the current problems of low accuracy and poor reliability of the discrete element model of cotton stalks, as well as the difficulty of guiding the design and optimization of the equipment through simulations, the discrete element modeling and physical-mechanical tests of cotton stalks in machine harvested film-stalk mixtures are carried out. The peak tensile force $$F_{\rm j}^{\max }$$ F j max , the peak pressure $$F_{\rm y}^{\max }$$ F y max , the peak bending force $$F_{\rm w}^{\max }$$ F w max , the peak shear force $$F_{\rm j}^{\max }$$ F j max , and the force-displacement (F–x) curves of cotton stalks are obtained from the physical tests. The discrete element model of double-layer cotton stalks based on the flat-joint model is established with the PFC $$^{\rm 3D}$$ 3 D software. The $$F_{\rm y}^{\max }$$ F y max is taken as the response value, and the microscopic parameters of the cotton stalk model are used as the test factors, then the Plackett–Burman test, the steepest climb test, and the Box–Behnken test are sequentially designed using Design-Expert software. The second-order regression model describing the relationship between the $$F_{\rm y}^{\max }$$ F y max and the microscopic parameters is established. The optimal parameter combinations of the microscopic parameters are obtained, and then they are utilized to construct the compression, bending, and shear models of cotton stalks and to carry out the validation tests. The results confirm that the established discrete element model could accurately characterize the biomechanical properties of cotton stalks and that the parameter calibration method is reasonable, which could provide a reference for the discrete element modeling of cotton stalks and other stalks, and also offer a theoretical basis for the research of the crushing and separation mechanism of the film-stalk mixtures and the development of the equipment.

Abstract Metals have been proved to be one of risk factors for chronic kidney disease (CKD) and diabetes, but the effect of mixed metal co-exposure and potential interaction between metals are still unclear. We assessed the urine and whole blood levels of cadmium (Cd), manganese (Mn), lead (Pb), mercury (Hg), and renal function in 3080 adults from National Health and Nutrition Survey (NHANES) (2011–2018) to explore the effect of mixed metal exposure on CKD especially in people with type 2 diabetes mellitus (T2DM). Weighted quantile sum regression model and Bayesian Kernel Machine Regression model were used to evaluate the overall exposure impact of metal mixture and potential interaction between metals. The results showed that the exposure to mixed metals was significantly associated with an increased risk of CKD in blood glucose stratification, with the risk of CKD being 1.58 (1.26,1.99) times in urine and 1.67 (1.19,2.34) times in whole blood higher in individuals exposed to high concentrations of the metal mixture compared to those exposed to low concentrations. The effect of urine metal mixture was elevated magnitude in stratified analysis. There were interactions between urine Pb and Cd, Pb and Mn, Pb and Hg, Cd and Mn, Cd and Hg, and blood Pb and Hg, Mn and Cd, Mn and Pb, Mn and Hg on the risk of CKD in patients with T2DM and no significant interaction between metals was observed in non-diabetics. In summary, mixed metal exposure increased the risk of CKD in patients with T2DM, and there were complex interactions between metals. More in-depth studies are needed to explore the mechanism and demonstrate the causal relationship.

Objective: A coupled model for predicting tomato quality during short-term storage and transportation under extreme temperatures, utilizing the Arrhenius equation in conjunction with meteorological temperature data, to forecast the quality changes in tomatoes during the short-term storage and transportation processes under extreme weather conditions. Methods: Analyzing the meteorological temperature data for the year 2020 in Weifang, Baoding, and Daxing, 7 temperature points were selected to simulate the range of temperature variations for short-term storage and transportation of tomatoes. By utilizing the Arrhenius equation and integrating temperature with weight loss rate, hardness, color difference (ΔE), and sensory evaluation scores (SE), a coupled model was developed for predicting tomato quality. The model was validated by using temperatures of -10 ℃ and 12 ℃. Results: Within 48 hours of storage and transportation, Loss rate and ΔE of tomatoes gradually increased, while evaluation scores (SE) and hardness decreased gradually. The quality prediction coupling model based on the Arrhenius equation combined with meteorological temperature data was constructed. Under storage conditions from 0 to 36 ℃, changes in loss rate and SE were fitted with zero-order reactions, while changes in hardness and ΔE were fitted with first-order and half-order reactions, respectively. For storage conditions from -15 to 0 ℃, zero-order reaction fits were applied to model the changes in SE, ΔE, weight loss rate, and hardness. Validation of the predictive model revealed that, under 12 ℃ storage conditions, the relative errors for tomato weight loss rate, hardness, and SE were within 15%, except for the 48 hour prediction. Under -10 ℃ storage conditions, the relative errors for tomato hardness and SE were within 15%, excluding the 48 hour prediction. Conclusion: The coupled model for tomato quality prediction, constructed by integrating the Arrhenius equation with extreme meteorological temperature data, proves to be effective in forecasting the quality of tomatoes under extreme temperature conditions.

Abstract Deploying static wireless sensor nodes is prone to network coverage gaps, resulting in poor network coverage. In this paper, an attempt is made to improve the network coverage by moving the locations of the nodes. A surrogate-assisted sine Phasmatodea population evolution algorithm (SASPPE) is used to evaluate the network coverage. A $$50 \times 50$$ 50 × 50 hill simulation environment was tested for the number of nodes of 30 and 40 and radii of 3, 5 and 7, respectively. The results show that the SASPPE algorithm has the highest coverage, which can be up to 23.624% higher than the PPE algorithm, and up to 5.196% higher than the PPE algorithm, ceteris paribus. The SASPPE algorithm mixes the GSAM with LSAMs, which balances the computational cost of the algorithm and the algorithm’s ability to find optimal results. The use of hierarchical clustering enhances the stable type of the LSAMs. In addition, LSAMs are easy to fall into local optimality when they are modeled with local data, and the use of sine Phasmatodea population evolution algorithm (Sine-PPE) for searching in LSAMs alleviates the time for the algorithm to fall into local optimality. On 30D, 50D, and 100D, the proposed algorithm was tested by 7 test functions. The results show that the algorithm has significant advantages on most functions.

Objective To construct a group psychological training for junior officers based on competency model and explore its intervention effect on competency and mental health of junior officers. Methods Delphi method was used to construct a group psychological training program for junior officers based on competency model. A total of 63 junior officers were subjected with convenience sampling during October and November 2023. According to the principle of randomized controlled experimental design, the participants were divided into experimental group (n=30) and control group (n=33). The experimental group was given our group psychological training program for totally 8 sessions, 90~120 min per session, 2 sessions per week, while the control group received no such training. Competency scale, 12-item general health questionnaire (GHQ-12), Chinese perceived stress scale (CPSS), and Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) were used to assess the 2 groups before and at the end of intervention. Results ① The results of the 2 rounds of expert consultation showed that the total recovery rate was 100%, the expert authority coefficient was 0.87, the Kendall's coordination coefficients (ω) of the 2 rounds of expert consultation were 0.102 (P < 0.001) and 0.410 (P < 0.001), respectively, with a coefficients of variation of < 0.3, indicating reliable expert consultation. ② The results of post-intervention time main effect indicated that the total score of competence (P < 0.001), extroversion score (P < 0.05) and responsibility score (P < 0.01) were significantly higher, but the total score of GHQ-12 was obviously lower in the experimental group than the control group (P < 0.001). ③ The results of post-intervention group main effects revealed that the extraversion score of the experimental group was significantly higher than that of the control group (P < 0.01). ④ The results of the post-intervention time × group interaction displayed that the experimental group had notably higher total competency score (P < 0.01), job performance score (P < 0.05), extraversion score (P < 0.05), agreeableness score (P < 0.001) and responsibility score (P < 0.01), but lower total GHQ-12 score (P < 0.01) than the control group. Conclusion Competency-based modeling group psychological training for junior officers can significantly enhance the competency, strengthen the extroversion, agreeableness and responsibility in personality traits, and thus improve job performance for them. [Key words] competency , job performance , group psychological training , junior officers ,

Abstract Background Changes in economy and dietary guidelines brought a great shock to diet quality and meal behaviors, but if these transformations have extended to minerals intake and their sources was still poorly understood. It is essential to evaluate time trends in minerals intake and their sources to inform policy makers. Objective To investigate trends in minerals intake and their sources among U.S. adults. Methods This analysis used dietary data collected by 24-h recalls from U.S. adults (≥ 20 years) in NHANES (1999-March 2020). Minerals intake, age-adjusted percentage of participants meeting recommendations, and minerals sources were calculated among all participants and by population subgroups in each NHANES survey cycle. Weighted linear or logistic regression models were used to examine the statistical significance of time trends. Results A total of 48223 U.S. adults were included in this analysis. From 1999 to March 2020, intake of calcium (from 0.94 to 1.02 g/day), magnesium (from 308.07 to 321.85 mg/day), phosphorus (from 1.24 to 1.30 g/day), and sodium (from 3.24 to 3.26 mg/day) from food and beverages (FB) and dietary supplements (DSs) significantly increased, and intake of iron (from 19.17 to 16.38 mg/day), zinc (from 16.45 to 14.19 mg/day), copper (from 1.79 to 1.38 mg/day), and potassium (from 2.65 to 2.50 g/day) from FB + DSs decreased (all FDR

Abstract The contrast-enhanced ultrasound (CEUS) has been mainly applied to adults to differentiate benign and malignant renal lesions, however, the characteristics of CEUS in pediatric has not been as well studied as in adults. In the present work, the eligible pediatric patients who underwent renal CEUS between March 2016 and February 2023 were retrospectively analyzed. It included 20 lesions (median diameter, 8.4 cm; range, 1.8–18.0 cm) from 20 patients (median age, 28.0 months; range, 3.0–212.0 months; 9 boys) in malignant group and 5 lesions (median diameter, 3.8 cm; range, 1.3–7.5 cm) from 5 patients (median age, 25.0 months; range, 0.7–216.0 months; 2 boys) in benign group. The diagnostic performance was assessed. Nonparametric and Chi-square tests were performed. With hyperenhancement plus wash-out, CEUS showed a sensitivity of 95.0% [95% confidence interval (CI): 75.1%, 99.9%], a specificity of 80.0% (CI: 28.4%, 99.5%), a positive predictive value of 95.0% (CI: 75.1%, 99.9%) and a negative predictive value of 80.0% (CI: 28.4%, 99.5%). It suggested that CEUS is a valuable technique for identifying between malignant and benign renal lesions in children.

Abstract Background Spatial molecular profiling depends on accurate cell segmentation. Identification and quantitation of individual cells in dense tissues, e.g. highly inflamed tissue caused by viral infection or immune reaction, remains a challenge. Methods We first assess the performance of 18 deep learning-based cell segmentation models, either pre-trained or trained by us using two public image sets, on a set of immunofluorescence images stained with immune cell surface markers in skin tissue obtained during human herpes simplex virus (HSV) infection. We then further train eight of these models using up to 10,000+ training instances from the current image set. Finally, we seek to improve performance by tuning parameters of the most successful method from the previous step. Results The best model before fine-tuning achieves a mean Average Precision (mAP) of 0.516. Prediction performance improves substantially after training. The best model is the cyto model from Cellpose. After training, it achieves an mAP of 0.694; with further parameter tuning, the mAP reaches 0.711. Conclusion Selecting the best model among the existing approaches and further training the model with images of interest produce the most gain in prediction performance. The performance of the resulting model compares favorably to human performance. The imperfection of the final model performance can be attributed to the moderate signal-to-noise ratio in the imageset.

Abstract Background The aim of the present study was to compare the predictive accuracy of PD‐L1 immunohistochemistry (IHC), tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profile (GEP), driver gene mutation, and combined biomarkers for immunotherapy response of advanced non‐small cell lung cancer (NSCLC). Methods In part 1, clinical trials involved with predictive biomarker exploration for immunotherapy in advanced NSCLC were included. The area under the curve (AUC) of the summary receiver operating characteristic (SROC), sensitivity, specificity, likelihood ratio and predictive value of the biomarkers were evaluated. In part 2, public datasets of immune checkpoint inhibitor (ICI)‐treated NSCLC involved with biomarkers were curated (N = 871). Odds ratio (OR) of the positive versus negative biomarker group for objective response rate (ORR) was measured. Results In part 1, the AUC of combined biomarkers (0.75) was higher than PD‐L1 (0.64), tTMB (0.64), bTMB (0.68), GEP (0.67), and driver gene mutation (0.51). Combined biomarkers also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers. In part 2, the OR of combined biomarkers of PD‐L1 plus TMB (PD‐L1 cutoff 1%, 0.14; cutoff 50% 0.13) was lower than that of PD‐L1 (cutoff 1%, 0.33; cutoff 50% 0.24), tTMB (0.28), bTMB (0.48), EGFR mutation (0.17) and KRAS mutation (0.47), for distinguishing ORR of patients after immunotherapy. Furthermore, positive PD‐L1, tTMB‐high, wild‐type EGFR, and positive PD‐L1 plus TMB were associated with prolonged progression‐free survival (PFS). Conclusion Combined biomarkers have superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. Further investigation is warranted to select optimal biomarkers for various clinical settings.

BackgroundIt is unclear if there is any combined effect of air pollutants and non-optimal temperature on metabolic syndrome, or any molecular mechanisms of related signaling pathways in the process, which requires urgent systematic research. ObjectiveTo observe the effects of combined exposure to PM2.5 and non-optimal temperature on metabolic damage at gene and protein levels in mice, and elucidate the role of related signaling pathway in crucial organs. MethodsA total of 60 six-week-old male C57BL/6J mice were randomly divided into six groups: a normal temperature-filter air group (TN-FA), a normal temperature-concentrated PM2.5 group (TN-PM), a heat-filter air group (TH-FA), a heat-concentrated PM2.5 group (TH-PM), a cold-filter air group (TC-FA), and a cold-concentrated PM2.5 group (TC-PM). The Shanghai Meteorological and Environmental Animal Exposure System (Shanghai-METAS) was used to provide combined exposure settings of air types [concentrated PM2.5 and filter air (FA)] and temperatures [normal (22°C), cold (4°C), and heat (30°C)] for 4 weeks. Skeletal muscle and white adipose tissue (WAT) of the mice were sampled at the end of exposure, and transcriptomics and Western blot (WB) assay were adopted to observe selected gene and protein expression levels in the samples respectively. ResultsThe transcriptomics results indicated that the PM2.5 exposure enhanced the number of differentially expressed genes. Specifically, 4820 genes were differentially expressed in the TN-PM mice compared to the TN-FA mice at normal temperature, and 1143 genes were differentially expressed in the Tc-PM mice compared to the Tc-FA mice in the cold environment. The phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway and the endoplasmic reticulum protein processing pathway were identified as the most significant pathways in metabolic injury resulting from combined exposure to PM2.5 and non-optimal temperature exposure. The WB results showed that exposure to PM2.5 in the normal temperature and the cold environments led to a significant increase in the expression of p-AKT in WAT (P

Abstract This paper focuses on radio resource management (RRM) in multi-user dual-function radar communication (DFRC) systems using orthogonal frequency division multiplexing (OFDM) waveforms. We propose two RRM schemes, one from the perspective of sum rate maximization and the other from the perspective of user fairness maximization. These optimization problems are non-convex due to the presence of mixed integer terms, making them difficult to solve. To address these challenges, we have employed a decomposition approach to transform these two complex problems into separate, more readily solvable ones. In addressing the sum rate maximization problem, we initially introduce a heuristic greedy algorithm to obtain a resource allocation scheme that satisfies radar performance requirements. Subsequently, we utilize a cyclic iterative method along with KKT conditions to solve the sum rate maximization problem for communication users. Concerning the fairness maximization problem for communication users, we similarly employ a heuristic greedy algorithm to obtain a resource allocation scheme that meets radar performance constraints. Then utilize the Lagrangian dual method to solve the multi-user fairness maximization problem for communication users. Our experimental results confirm the effectiveness of the proposed algorithms.

Abstract CSF1R is a receptor tyrosine kinase responsible for the growth/survival/polarization of macrophages and overexpressed in some AML patients. We hypothesized that a novel multi-kinase inhibitor (TKi), narazaciclib (HX301/ON123300), with high potency against CSF1R (IC50 ~ 0.285 nM), would have anti-AML effects. We tested this by confirming HX301’s high potency against CSF1R (IC50 ~ 0.285 nM), as well as other kinases, e.g. FLT3 (IC50 of ~ 19.77 nM) and CDK6 (0.53 nM). An in vitro proliferation assay showed that narazaciclib has a high growth inhibitory effect in cell cultures where CSF1R or mutant FLT3-ITD variants that may be proliferation drivers, including primary macrophages (IC50 of 72.5 nM) and a subset of AML lines (IC50

Abstract Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability – the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem. We show that correlations between these traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a protein’s ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

The current research status of refractory high-entropy alloys（RHEAs） is reviewed，the composition design of RHEAs is described，and the effects of metal elements and non-metal elements on the structure and properties of RHEAs are summarized. In addition，the microstructure and mechanical properties of RHEAs under different preparation methods are described，and the strengthening mechanism of RHEAs matrix composites is discussed. The future development of RHEAs is prospected，and the following suggestions are put forward for its future research direction: enhancing of RHEAs by multiphase synergistic effects through the interface design between different phases；designing and optimizing the composition of RHEAs to develop RHEAs that are easy to process at room temperature；quickly screening the composition and microstructure of RHEAs by combining with high-throughput calculation methods；regulating and controlling the microstructure and structure of RHEAs by additive manufacturing technology；carrying out the configuration design of RHEAs matrix composites to balance the strength and plasticity of RHEAs matrix composites.

Abstract The colloidal borescope, using colloidal particle motion, is used to monitor the flow velocities and directions of groundwater. It integrates advanced techniques such as microscopy, high-speed photography, and big data computing and enjoys high sensitivity at the micron level. However, In the same well, the groundwater flow velocity monitored by colloidal hole mirror is varies greatly from that obtained by conventional hydrogeological monitoring, such as pumping test. In order to solve this problem, the stability catcher and stratified packer are designed to control the interference of the vertical flow in drilling, and to monitor the flow velocity and direction of groundwater velocity at the target aquifer and target fracture. Five wells with different aquifers and different groundwater types were selected for monitoring in south-central China. The instantaneous velocity and direction are converted into east–west component and north–south component, the average velocity and direction is calculated according to the time of 10 min, and the particle trajectory diagram is established. Based on these results, it proposed a concept of cumulative flow velocity. Using curve-fitting equations, the limits of cumulative flow velocities as the monitoring time tends to infinity were then calculated as the actual flow velocities of the groundwater. The permeability coefficient of aquifer is calculated by using the fissure ratio of aquifer, hydraulic slope and flow velocity, and compared with the permeability coefficient obtained by pumping test. The results are as follows: (1) The variation coefficient of the instantaneous flow velocity measured at the same depth in the same well at different times is greater than that of the time average flow velocity and greater than that of the cumulative flow velocity. The variation coefficient of the actual velocity is the smallest, indicating that the risk of using the actual flow velocity is lower. (2) The variation coefficient of the flow rate monitored at different depths in the same well is mainly controlled by the properties of the aquifer. The more uniform water storage space in the aquifer, the smaller the variation coefficient. (3) The comparison between the permeability coefficient obtained by monitoring and the permeability coefficient obtained by pumping test shows that the flow of structural fissure water controlled by planar fissure is more surface flow, and the results are consistent. When the groundwater flow is controlled by pores and solution gaps, the flow channel is complicated, which is easy to produce turbulent flow, and the result consistency is poor. (4) According to different research accuracy requirements, different monitoring and calculation methods can be selected for different aquifers and groundwater types. Researches show that, the permeability coefficient calculated for the actual flow velocity in well DR01 is the same as that calculated for the pumping test. The aquifer characteristics reflected by the coefficient of variation of the actual flow velocity in the same aquifer are more realistic. The pumping test method obtains the comprehensive parameters of a certain aquifer, and this method can be used to monitor a certain fissure. In this paper, the new technology developed for monitoring, and the new algorithm established for data processing, can accurately obtain the flow velocity and direction of groundwater, using capsule hole mirror monitoring method. The key parameters of hydrogeology can be obtained by using one well, which can reduce the time and cost input and improve the work efficiency.

Abstract Double-sided microlens arrays (DSMLAs) include combinations of two single-sided MLAs to overcome positioning errors and greatly improve light transmissivity compared to other types of lenses. Precision glass molding (PGM) is used to fabricate DSMLAs, but controlling alignment errors during this process is challenging. In this paper, a mold assembly was manufactured with a novel combination of materials to improve the alignment accuracy of mold cores during PGM by using the nonlinear thermal expansion characteristics of the various materials to improve the DSMLA alignment accuracy. By establishing a mathematical model of the DSMLA alignment error and a thermal expansion model of the mold-sleeve pair, the relationship between the maximum alignment error of the DSMLA and the mold-sleeve gap was determined. This research provides a method to optimize the mold-sleeve gap and minimize the alignment error of the DSMLA. The measured DSMLA alignment error was 10.56 μm, which is similar to the predicted maximum alignment error. Optical measurements showed that the uniformity of the homogenized beam spot was 97.81%, and the effective homogeneous area accounted for 91.66% of the total area. This proposed method provides a novel strategy to improve the performance of DSMLAs.

Aggregate is the basic component of concrete, and its shape and surface properties largely determine the mechanical properties and durability of concrete. In order to further study the mesoscopic influence of aggregate shape on concrete interfacial phase, this study focuses on two aggregate shapes, circular and polygonal, and the elastic modulus and hardness of interfacial phase of specimens with different aggregate shapes were obtained by nano-indentation technology, and the mesoscopic component partition was quantified. Based on Gaussian statistical theory, the distribution model of nanomechanical properties of each phase was established, and the influence of aggregate shape on mechanical properties was studied by SEM test. The results show that (1) The width of the interfacial zone of natural rounded aggregate (∼50 μm) is slightly smaller than that of polygonal aggregate (∼60 μm), and the modulus of elasticity and hardness of the interfacial zone corresponding to the rounded aggregate (e.g., interfacial transition zone (E,H) ∼ (23.65 GPa, 0.9 GPa)) are larger than that of the interfacial zone of polygonal aggregate (interfacial transition zone (E,H) ∼ (21.66 GPa, 0.73 GPa)), indicating that the micromechanical properties of the interfacial zone of the circular aggregate are better than those of the polygonal aggregate; (2) The hydration products in the transition zone of the interface of different shapes of aggregates are almost the same, indicating that the influence of the shape of aggregates on the performance of concrete is mainly due to its own geometric characteristics. Based on the findings of the study, the direction of future research can focus on modeling with further refinement of the influence of aggregate shape parameters, such as shape factor and surface roughness, on the performance of concrete, so as to facilitate more accurate prediction and regulation of the performance of concrete. This study provides theoretical references for the design of aggregate proportioning and the simulation technology of fine data values in actual projects, and also provides theoretical basis and technical support for the standardization and performance evaluation of concrete materials.

Chlorogenic acid (CGA) is one of the effective components of Chinese medicine plant such as honeysuckle and Eucommia ulmoides. CGA can inhibits various cancer types, but its effectivity against tongue cancer remains unknown.In the present study, we utilized patient-derived xenograft (PDX) models in conjunction with hydrogel-embedded drug sensitivity tests (HDST) to demonstrate the inhibitory effects of CGA on tongue cancer tissues in both in vivo and ex vivo experimental paradigms. Immunohistochemical (IHC) analysis and TUNEL staining revealed that CGA downregulated the expression of CD31 and Ki-67, while concurrently promoting apoptosis. Furthermore, the involvement of the EGFR-AKT-MMP9 signaling cascade in the tumor-suppressive effects of CGA was confirmed using network pharmacology analysis and immunofluorescent validation techniques.Overall, our findings indicate that CGA robustly inhibits tongue cancer in cellular and organismal models. The EGFR-AKT-MMP9 axis plays a highly significant role in mediating this bioactivity, thereby positioning CGA as a promising candidate for further investigation in oncology. The multifaceted therapeutic potential of CGA, as evidenced by its ability to disrupt angiogenesis, suppress cell proliferation, and induce apoptosis, underscores its value as a novel therapeutic agent for the treatment of tongue cancer.

Background: Mitochondrial dysfunction and metabolic reprogramming can lead to the development and progression of hepatocellular carcinoma (HCC). Ferredoxin 1 (FDX1) is a small mitochondrial protein and recent studies have shown that FDX1 plays an important role in tumor cuproptosis, but its role in HCC is still elusive. In this study, we aim to investigate the expression and novel functions of FDX1 in HCC. Methods: FDX1 expression was first analyzed in publicly available datasets and verified by immunohistochemistry, qRT-PCR and Western blot. In vitro and in vivo experiments were applied to explore the functions of FDX1. Non-targeted metabolomics and RNA-sequencing were used to determine molecular mechanism. mRFP-GFP-LC3 lentivirus transfection, Mito-Tracker Red and Lyso-Tracker Green staining, transmission electron microscopy, flow cytometry, JC-1 staining, etc. were used to analyze mitophagy or ROS levels. Hydrodynamic tail vein injection (HTVi) and patient-derived organoid (PDO) models were used to analyze effect of FDX1 overexpression. Results: FDX1 expression is significantly downregulated in HCC tissues. FDX1 downregulation promotes HCC cell proliferation, invasion in vitro and growth, metastasis in vivo. In addition, FDX1 affects metabolism of HCC cells and is associated with autophagy. We then confirmed that FDX1 deficiency increases ROS levels, activates mitophagy and the PI3K/AKT signaling pathway in HCC cells. Interestingly, scavenging ROS attenuates the tumor-promoting role and mitophagy of FDX1 downregulation. The results of HTVi and PDO models both find that FDX1 elevation significantly inhibits HCC progression. Moreover, low FDX1 expression is associated with shorter survival and is an independent risk factor for prognosis in HCC patients. Conclusions: Our research had investigated novel functions of FDX1 in HCC. Downregulation of FDX1 contributes to metabolic reprogramming and leads to ROS-mediated activation of mitophagy and the PI3K/AKT signaling pathway. FDX1 is a potential prognostic biomarker and increasing FDX1 expression may be a potential therapeutic approach to inhibit HCC progression.

A long noncoding RNA (lncRNA) is longer than 200 bp. It regulates various biological processes mainly by interacting with DNA, RNA, or protein in multiple kinds of biological processes. Adenosine monophosphate-activated protein kinase (AMPK) is activated during nutrient starvation, especially glucose starvation and oxygen deficiency (hypoxia), and exposure to toxins that inhibit mitochondrial respiratory chain complex function. AMPK is an energy switch in organisms that controls cell growth and multiple cellular processes, including lipid and glucose metabolism, thereby maintaining intracellular energy homeostasis by activating catabolism and inhibiting anabolism. The AMPK signalling pathway consists of AMPK and its upstream and downstream targets. AMPK upstream targets include proteins such as the transforming growth factor β-activated kinase 1 (TAK1), liver kinase B1 (LKB1), and calcium/calmodulin-dependent protein kinase β (CaMKKβ), and its downstream targets include proteins such as the mechanistic/mammalian target of rapamycin (mTOR) complex 1 (mTORC1), hepatocyte nuclear factor 4α (HNF4α), and silencing information regulatory 1 (SIRT1). In general, proteins function relatively independently and cooperate. In this article, a review of the currently known lncRNAs involved in the AMPK signalling pathway is presented and insights into the regulatory mechanisms involved in human ageing and age-related diseases are provided.

BackgroundPerioperative neurocognitive disorder (PND) is a critical concern for older patients undergoing cardiac surgery, impacting cognitive function and quality of life. Electroacupuncture and transcutaneous electrical acupoint stimulation (TEAS) hold promise for mitigating PND. This protocol outlines a systematic review and meta-analysis to thoroughly assess the efficacy of electroacupuncture and TEAS in older patients undergoing cardiac surgery with PND, providing up-to-date evidence for PND prevention and treatment. ObjectiveThis study aimed to thoroughly assess the efficacy of electroacupuncture and TEAS in older patients undergoing cardiac surgery with PND, providing up-to-date evidence for PND prevention and treatment. MethodsA comprehensive and systematic approach will be used to identify eligible studies from a diverse range of electronic databases, including 9 major sources such as PubMed (NLM) and Cochrane (Wiley), as well as 2 clinical trial registration websites. These studies will focus on investigating the effects of electroacupuncture and TEAS on PND in older patients undergoing cardiac surgery. The study selection will adhere to the criteria outlined in the patient, intervention, comparison, outcome, and studies (PICOS) format. Data extraction will be carried out by 2 independent researchers (YP and LS), using established tools to evaluate the risk of bias. The primary outcome will be PND incidence, with secondary outcomes including Mini Mental State Examination scores, neuron-specific enolase, S100β, interleukin-1β, interleukin-6, tumor necrosis factor-α, time to first flatus, first defecation, bowel sound recovery, and hospitalization duration to be selectively reported. Adverse events linked to acupuncture, such as bleeding, needle site pain, and local reactions, rather than serious adverse events, will also be considered. Meta-analysis will be performed using appropriate statistical methods to assess the overall effect of electroacupuncture and TEAS on PND prevention, treatment, or other relevant outcomes. The Cochrane Collaboration Risk of Bias tool will be used for assessment, and data synthesis will be executed using the RevMan 5.4 software (Cochrane). ResultsWe plan to summarize the eligible studies through the use of a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart. The findings will be showcased in the form of a summary table of evidence. Figures and forest plots will be used to illustrate the outcomes of the meta-analysis. ConclusionsThe impacts of electroacupuncture and TEAS interventions on PND in older patients undergoing cardiac surgery have not yet been established. This protocol addresses a critical gap by thoroughly assessing electroacupuncture and TEAS for PND in older patients undergoing cardiac surgery, enhancing understanding of nonpharmacological interventions, and guiding future research and clinical practices in this field. Its strength lies in rigorous methodology, including comprehensive search strategies, independent review processes, and thorough assessments of the risk of bias. Trial RegistrationPROSPERO CRD42023411927; https://tinyurl.com/39xdz6jb International Registered Report Identifier (IRRID)PRR1-10.2196/55996