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Abstract Background The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer. Methods A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves. Results In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability. Conclusion The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.

Abstract Background In-home rehabilitation systems are a promising, potential alternative to conventional therapy for stroke survivors. Unfortunately, physiological differences between participants and sensor displacement in wearable sensors pose a significant challenge to classifier performance, particularly for people with stroke who may encounter difficulties repeatedly performing trials. This makes it challenging to create reliable in-home rehabilitation systems that can accurately classify gestures. Methods Twenty individuals who suffered a stroke performed seven different gestures (mass flexion, mass extension, wrist volar flexion, wrist dorsiflexion, forearm pronation, forearm supination, and rest) related to activities of daily living. They performed these gestures while wearing EMG sensors on the forearm, as well as FMG sensors and an IMU on the wrist. We developed a model based on prototypical networks for one-shot transfer learning, K-Best feature selection, and increased window size to improve model accuracy. Our model was evaluated against conventional transfer learning with neural networks, as well as subject-dependent and subject-independent classifiers: neural networks, LGBM, LDA, and SVM. Results Our proposed model achieved 82.2% hand—gesture classification accuracy, which was better (P

Abstract Purpose In VATS surgery, precise preoperative localization is particularly crucial when dealing with small-diameter pulmonary nodules located deep within the lung parenchyma. The purpose of this study was to compare the efficacy and safety of laser guidance and freehand hook-wire for CT-guided preoperative localization of pulmonary nodules. Methods This retrospective study was conducted on 164 patients who received either laser guidance or freehand hook-wire localization prior to Uni-port VATS from September 1st, 2022 to September 30th, 2023 at The First Affiliated Hospital of Soochow University. Patients were divided into laser guidance group and freehand group based on which technology was used. Preoperative localization data from all patients were compiled. The localization success and complication rates associated with the two groups were compared. The risk factors for common complications were analyzed. Results The average time of the localization duration in the laser guidance group was shorter than the freehand group (p

To investigate the bearing capacity of concrete structures strengthened by carbon fiber reinforced composite (CFRP), this study conducted numerical simulation research on seven CFRP-strengthened concrete arch structures with five different strengthening schemes. The finite element model was established by HYPERMESH, the simulation results were compared with the experimental results to verify the accuracy of the model. Based on this, the interfacial bonding performance of concrete and CFRP under different strengthening schemes was analyzed, and the static damage mode of the reinforced concrete arch structure was revealed. The results indicate that the application of CFRP to the surface of a concrete arch will increase the linear segmental stiffness, cracking load, and ultimate load of the structure. The five strengthening schemes in this paper provide enhancements ranging from 2.9 % to 57.6 % for concrete arch cracking loads, from 3.3 % to 14.7 % for ultimate loads, and from 1.1 % to 17.6 % for stiffness. If both the inner and outer sides are strengthened with CFRP, the ultimate bearing capacity of the arch structure can be significantly enhanced. Circumferential wrapping of CFRP can delay the concrete cracking and further enhance the bearing capacity of the arch, and the strengthening effect can be maximized. This study can provide a valuable reference for the strengthening of old concrete arch structures and the construction of newly assembled arch tunnels.

Liver cancer, a common and intractable liver-related disease, is a malignant tumor with a high morbidity, which needs a high treatment cost but still lacks perfect clinical treatment methods. Looking for an effective platform for liver cancer study and drug screening is urgent and important. Traditional analytical methods for liver disease studies mainly rely on the 2D cell culture and animal experiments, which both cannot fully recapitulate physiological and pathological processes of human liver. For example, cell culture can only show basic functions of cells in vitro, while animal models always hold the problem of species divergence. The organoids, a 3D invitro culture system emerged in recent years, is a cell-bound body with different cell types and has partial tissue functions. The organoid technology can reveal the growth state, structure, function and characteristics of the tissue or organ, and plays an important role in reconstructing invitro experimental models that can truly simulate the human liver. In this paper, we will give a brief introduction of liver organoids and review their applications in liver cancer research, especially in liver cancer pathogenesis, drug screening, precision medicine, regenerative medicine, and other fields. We have also discussed advantages and disadvantages of organoids, as well as future directions and perspectives towards liver organoids.

This paper studies a stochastic HIV/AIDS model with nonlinear incidence rate. In the model, the infection rate coefficient and the natural death rates are affected by white noise, and infected people are affected by an intervention strategy. We derive the conditions of extinction and permanence for the stochastic HIV/AIDS model, that is, if $ R_0^s < 1, $ HIV/AIDS will die out with probability one and the distribution of the susceptible converges weakly to a boundary distribution; if $ R_0^s > 1 $, HIV/AIDS will be persistent almost surely and there exists a unique stationary distribution. The conclusions are verified by numerical simulation.

Dendritic fibrous nano silica (DFNS) was functionalized through the utilization of graphene oxide (GO) as a long-lasting anchoring agent. Consequently, the LaFeO3 nanoparticles were evenly spread out without clumping over the DFNS/GO. The supramolecular polymerized GO served the dual purpose of preventing the restacking of graphene sheets and functioned as a supplier of nitrogen to create active sites for the bonding of LaFeO3 nanoparticles. The nitrogen content above the extent of the GO films was modified by LaCl3·7 H2O and Fe(NO3)3·9H2O ions to synthesize LaFeO3 nanoparticles. The catalytic properties of DFNS/GO-LaFeO3 was observed in the reaction between CO2 and oxetane and epoxide, leading to the production of the corresponding polycarbonates. The results indicated that DFNS/GO-LaFeO3 significantly enhanced the efficiency of synthesizing poly(propylene carbonate) and poly(trimethylene carbonate) from carbon dioxide. This approach offers substantial benefits, including high economic efficiency. The union reaction of CO2 and highly substituted epoxides sourced from sustainable sources such as discarded vegetable oils and fatty acids resulted in the production of novel cyclic carbonates of bio-origin. This reaction occurred under gentle and solvent-free conditions using DFNS/GO-LaFeO3 as a catalyst. The DFNS/GO-LaFeO3 exhibited a high capacity for CO2 uptake with exceptionally rapid kinetics. The nanoplate morphology of DFNS/GO-LaFeO3 facilitated the formation of a satisfactory outer layer for carbon dioxide uptake at each metal site. Consequently, the nanoplate morphology of DFNS/GO-LaFeO3 ensured systematic carbon dioxide emission, guaranteeing a complete reaction with the entire sheet and enabling rapid CO2 adsorption kinetics.

The utilization of agro-industrial by-products, such as fruit residues, presents a promising strategy for providing alternative feed to ruminants amidst rising prices and limited availability of traditional roughage. In this study, we investigated the effects of Rosa roxburghii tratt residue, a local fruit residue in Guizhou province of China, on the growth, blood metabolites, rumen fermentation, and slaughter performance of Hu sheep. Ninety-six sheep were randomly divided into four groups, namely control, treatment 1, treatment 2, and treatment 3, and fed diets containing 0, 10, 20, and 30% Rosa roxburghii Tratt residue, respectively. Feeding varying levels of Rosa roxburghii Tratt residue showed no significant differences in dry matter intake, average daily gain, or the ratio of dry matter intake to average daily gain. However, sheep in the group fed with 30% Rosa roxburghii Tratt residue showed the highest gross profit. Plasma albumin content was lower in groups fed with Rosa roxburghii Tratt residue-containing diets compared to the control group (p

Abstract Reactive oxygen species (ROS)‐mediated oxidative stress and apoptosis contribute to the pathogenesis and pathological conditions of various diseases induced by food and environmental pollutants. Myricetin and dihydromyricetin, as natural flavonoids, can counteract oxidative damage, apoptosis, and associated diseases. Molecular docking analysis, ELISA, fluorescence spectroscopy, and Western blot techniques were applied to examine the potential of the two flavonoids as effective therapeutics for ROS‐mediated diseases and the mechanism(s) underlying their protective effects against ethanol/H2O2‐induced damage. In Kunming mice and HepG2 cells, myricetin and dihydromyricetin inhibited ethanol/H2O2‐induced liver damage, ROS accumulation, and oxidative stress and apoptosis. Molecular docking showed that myricetin and dihydromyricetin interacted with JNK1 via hydrophobic interactions and hydrogen bonds, thereby exerting their protective effects. The significant differences in their binding patterns to JNK1 resulted from the different bond types between C2 and C3 on their C ring. Myricetin and dihydromyricetin likely protected liver injury via counteracting ROS/JNK1‐mediated oxidative stress and apoptosis. The finding that the suppression of ROS‐mediated oxidative stress and apoptosis by flavonoids via interacting with functional proteins, such as kinase, may represent an alternative strategy for treating excessive ROS‐induced health problems.

The estuarine Crassostrea hongkongensis is the major cultured oyster species in the South China, and mass mortality induced by hyper-salinity has heavily damaged the oyster farming, especially during dry season. To benefit the genetic improvement of hyper-salinity tolerance, three genes related to the intracellular concentration of glycine (Gly) that functions as important osmolyte were identified and investigated in C. hongkongensis. Serine hydroxymethyltransferase 1 in C. hongkongensis (CHSHMT1) was found to be upregulated in gill since 48 h transferred from 18‰ to 30‰ filtered seawater (FSW). While glycine dehydrogenase (CHGLDC) and ALA synthase gene (CHALAS) were significantly upregulated in oyster from 8 to 48 h exposed to 6‰ FSW when compared with that in 18‰ and 30‰ FSW. And the expression of the three genes agreed with that Gly content decreased under hypo-osmotic stress and increased under hyper-osmotic stress. RNA in situ hybridization (ISH) revealed that CHSHMT1 and CHGLDC were mainly expressed in the ciliated columnar cell of gill filament and epithelial cell of water tube wall, where oyster gill directly contacts with seawater when the animal is filtering. But positive signal of CHALAS mRNA showed no significant difference in intensity between various gill cells. Based on these findings, CHSHMT1, CHGLDC and CHALAS were supposed to contribute to the variation of Gly content under osmotic stress. Subsequent RNA interference (RNAi) confirmed the function of CHSHMT1 in the transformation from serine (Ser) to Gly under hyper-osmotic stress. Moreover, CHGLDC and CHALAS were found to be significantly upregulated when CHSHMT1 was silenced under hyper-osmotic stress. This was hypothesized that the expression of CHGLDC and CHALAS might be suppressed by CHSHMT1, but more evidence should be provided. This work enriched the understanding of oyster osmolyte system that prevent cell shrinking or swelling under osmotic stress and provided potential genes for the breeding of Hong Kong oyster strain with hyper-salinity tolerance.

The fishery resource is a kind of important renewable resource and it is closely connected with people's production and life. However, fishery resources are not inexhaustible, so it has become an important research topic to develop fishery resources reasonably and ensure their sustainability. In the current study, considering the environment changes in the system, a fishery model with a variable predator search rate and fuzzy biological parameters was established first and then two modes of capture strategies were introduced to achieve fishery resource exploitation. For the fishery model in a continuous capture mode, the dynamic properties were analyzed and the results show that predator search rate, imprecision indexes and capture efforts have a certain impact on the existence and stability of the coexistence equilibrium. The bionomic equilibrium and optimal capture strategy were also discussed. For the fishery model in a state-dependent feedback capture mode, the complex dynamics including the existence and stability of the periodic solutions were investigated. Besides the theoretical results, numerical simulations were implemented step by step and the effects of predator search rate, fuzzy biological parameters and capture efforts on the system were demonstrated. This study not only enriched the related content of fishery dynamics, but also provided certain reference for the development and utilization of fishery resources under the environment with uncertain parameters.

Abstract Structural variants (SVs), accounting for a larger fraction of the genome than SNPs/InDels, are an important pool of genetic variation, enabling environmental adaptations. Here, we perform long-read sequencing data of 320 Tibetan and Han samples and show that SVs are highly involved in high-altitude adaptation. We expand the landscape of global SVs, apply robust models of selection and population differentiation combining SVs, SNPs and InDels, and use epigenomic analyses to predict enhancers, target genes and biological functions. We reveal diverse Tibetan-specific SVs affecting the regulatory circuitry of biological functions, including the hypoxia response, energy metabolism and pulmonary function. We find a Tibetan-specific deletion disrupts a super-enhancer and downregulates EPAS1 using enhancer reporter, cellular knock-out and DNA pull-down assays. Our study expands the global SV landscape, reveals the role of gene-regulatory circuitry rewiring in human adaptation, and illustrates the diverse functional roles of SVs in human biology.

Abstract Influenza is an acute viral respiratory illness with high morbidity rates worldwide. Excessive pulmonary inflammation is the main characteristic of lethal influenza A virus (IAV) infections. Therapeutic options for managing influenza are limited to vaccines and some antiviral medications. Phillyrin is one of the major bioactive components of the Chinese herbal medicine Forsythia suspensa, which has the functions of sterilization, heat clearing and detoxification. In this work, the effect and mechanism of phillyrin on H1N1 influenza (PR8)-induced pneumonia were investigated. We reported that phillyrin (15 mg/kg) treatment after viral challenge significantly improved the weight loss, ameliorated pulmonary inflammation and inhibited the accumulation of multiple cytokines and chemokines in bronchoalveolar lavage fluid on 7 days post infection (dpi). In vitro, phillyrin suppressed influenza viral replication (Matrixprotein and nucleoprotein messenger RNA level) and reduced influenza virus-induced cytopathic effect (CPE). Furthermore,chemokine receptor CXCR2 was confirmed to be markedly inhibited by phillyrin. Surface plasmon resonance results reveal that phillyrin exhibits binding affinity to CXCR2, having a binding affinity constant (KD) value of 1.858e-5 M, suggesting that CXCR2 is a potential therapeutic target for phillyrin. Moreover, phillyrin inhibited the mRNA and protein expression levels of Caspase1, ASC and NLRP3 in the lungs of mice with H1N1-induced pneumonia.This study reveals that phillyrin ameliorates IAV-induced pulmonary inflammation by antagonizing CXCR2 and inhibiting NLRP3 inflammasome activation partly.

Abstract Background Exposure to air pollution brings the advent effect for various diseases, but study about the relationship between air pollution and ageing is scant. We aimed to determine the associations between household air pollution for cooking and heating with muscle and sarcopenia in Chinese older population by a nationally representative study. Methods This cross‐sectional study included individuals aged 60 and above from the China Health and Retirement Longitudinal Study between 2011 and 2015. The diagnosis of sarcopenia was defined by low muscle mass with low muscle strength and/or reduced physical performance. Generalized additive analyses and dose‐dependent analyses with three models were used to assess the effects of different pattern of cooking and heating on muscle and sarcopenia. Results A total of 8126 Chinese older individuals with predominant male (53.7%) and mean age of 67.3 ± 6.0 years were included in our study. Solid fuel use in cooking showed significant declines in muscle strength (β = −0.424, 95% CI: −0.767, −0.082, P = 0.01 in model 3) and mass (β = −0.034, 95% CI: −0.051, −0.017, P

Climate change is exacerbating the vulnerability of temperate forests to severe disturbances, potentially increasing tree mortality rates. Despite the significance of this issue, there has been a lack of comprehensive research on tree survival across extensive forest areas under the background of global climate change. To fill this gap, we conducted a detailed analysis of tree survival within a canopy nitrogen and water addition experimental platform in central China, utilizing data from two censuses and evaluating contributing factors. Our findings revealed 283 dead trees within the plots, predominantly of very small diameters (1–10 cm). The distribution of these dead trees varied among subplots, influenced by both biotic and abiotic factors. Notably, three dominant tree species were responsible for 64.8% of the deadwood biomass. The study determined that both the breast diameter and the quantity of dead trees, affected by surrounding trees and environmental conditions, played a critical role in deadwood biomass accumulation. This research offers an in-depth examination of deadwood biomass patterns in a temperate forest, highlighting the need to consider both experiment treatments and abiotic elements like topography in studies of forest ecosystem carbon. The insights gained from this study enhance our understanding of warm temperate forests’ role in the global carbon cycle and offer valuable guidance for forest conservation and management strategies.

Abstract There are no Food and Drug Administration‐approved drugs for treating noise‐induced hearing loss (NIHL), reflecting the absence of clear specific therapeutic targets and effective delivery strategies. Noise trauma is demonstrated results in nicotinamide adenine dinucleotide (NAD+) downregulation and mitochondrial dysfunction in cochlear hair cells (HCs) and spiral ganglion neurons (SGNs) in mice, and NAD+ boosted by nicotinamide (NAM) supplementation maintains cochlear mitochondrial homeostasis and prevents neuroexcitatory toxic injury in vitro and ex vivo, also significantly ameliorated NIHL in vivo. To tackle the limited drug delivery efficiency due to sophisticated anatomical barriers and unique clearance pathway in ear, personalized NAM‐encapsulated porous gelatin methacryloyl (PGMA@NAM) are developed based on anatomy topography of murine temporal bone by micro‐computed tomography and reconstruction of round window (RW) niche, realizing hydrogel in situ implantation completely, NAM sustained‐release and long‐term auditory preservation in mice. This study strongly supports personalized PGMA@NAM as NIHL protection drug with effective inner ear delivery, providing new inspiration for drug‐based treatment of NIHL.

Hyperuricemia (HUA), a severe metabolic disease derived from purine metabolism disorder, will lead to abnormally increased serum uric acid (SUA) levels in the body. Studies have shown that HUA is highly related to gout, hypertension, diabetes, coronary heart disease, chronic kidney diseases, and so on. Traditional Chinese medicine (TCM) shows excellent results in treating HUA because of its unique advantages of multi-metabolites and multi-targets. This article reports on the use of TCM components for uric acid (UA)-lowering activity with excellent efficacy and low side effects based on established HUA models. This work summarizes the advantages and limitations of various HUA disease models for efficacy evaluation. Applications of TCM in HUA treatment have also been discussed in detail. This paper reveals recent research progress on HUA in constructing evaluation models and systematic TCM interventions. It will provide a scientific reference for establishing the HUA model and suggest future TCM-related HUA studies.

BackgroundThe utility of vocal biomarkers for mental health assessment has gained increasing attention. This study aims to further this line of research by introducing a novel vocal scoring system designed to provide mental fitness tracking insights to users in real-world settings.MethodsA prospective cohort study with 104 outpatient psychiatric participants was conducted to validate the “Mental Fitness Vocal Biomarker” (MFVB) score. The MFVB score was derived from eight vocal features, selected based on literature review. Participants’ mental health symptom severity was assessed using the M3 Checklist, which serves as a transdiagnostic tool for measuring depression, anxiety, post-traumatic stress disorder, and bipolar symptoms.ResultsThe MFVB demonstrated an ability to stratify individuals by their risk of elevated mental health symptom severity. Continuous observation enhanced the MFVB’s efficacy, with risk ratios improving from 1.53 (1.09-2.14, p=0.0138) for single 30-second voice samples to 2.00 (1.21-3.30, p=0.0068) for data aggregated over two weeks. A higher risk ratio of 8.50 (2.31-31.25, p=0.0013) was observed in participants who used the MFVB 5-6 times per week, underscoring the utility of frequent and continuous observation. Participant feedback confirmed the user-friendliness of the application and its perceived benefits.ConclusionsThe MFVB is a promising tool for objective mental health tracking in real-world conditions, with potential to be a cost-effective, scalable, and privacy-preserving adjunct to traditional psychiatric assessments. User feedback suggests that vocal biomarkers can offer personalized insights and support clinical therapy and other beneficial activities that are associated with improved mental health risks and outcomes.

In trees, injuries resulting from subfreezing temperatures can cause damage to the cellular biofilm system, metabolic functions, and fibrous reticulum, and even cell death. Investigating the occurrence of freezing damage and its contributing factors could help understand the mechanisms underlying freezing injury and prevent the subsequent damage in trees. To achieve this, a laboratory experiment was conducted using cut wood samples from Korean pine (Pinus koraiensis Siebold & Zucc) and Simon poplar (Populus simonii Carr.), and the effects of environmental freezing factors, including freezing temperatures, freezing duration, and cooling rate, on the temperature at which freezing injuries occur were examined using the electrical impedance spectroscopy (EIS) method. The semi-lethal temperature (LT50), as an indicator of freezing injury in wood tissue, was theoretically deduced based on the measured extracellular resistance (re) using EIS. The contributory factors to changes in LT50 were determined and their relationship was established. The results revealed that all freezing factors exhibited significant effects on electrical impedance characteristics (re, ri, and τ), significantly influencing the LT50 of the wood. Random forest (RF) and support vector machine (SVM) models were used to assess the contribution of the freezing factors and moisture content (MC). Among the factors examined, freezing duration had the greatest impact on LT50, followed by the MC, whereas the contribution of the cooling rate was minimal. The model accuracies were 0.89 and 0.86 for Korean pine and Simon poplar, respectively. The findings of our study illustrate that the occurrence of freezing injury in trees is primarily influenced by the duration of freezing at specific subzero temperatures. Slow cooling combined with prolonged freezing at low subzero temperatures leads to earlier and more severe freezing damage.

BackgroundTau, a microtubule-associated protein extensively distributed within the central nervous system (CNS), exhibits close associations with various neurodegenerative disorders. Here, we aimed to conduct a qualitative and quantitative bibliometric study of the top 100 most-cited publications on tau protein and reveal the current research hotspots and future perspectives.MethodsThe relevant literature was retrieved from the Web of Science Core Collection. CiteSpace (v6.2.R4) and VOSviewer (1.6.19) were adopted for bibliometric analysis with statistical and visual analysis.ResultsCitations per article ranged from 615 to 3,123, with a median number of 765.5 times. “Neuroscience” emerged as the most extensively researched subject in this field. The USA has emerged as the leading country, with a publication record (n = 65), total citations (n = 66,543), strong centrality (0.29), and extensive international collaborations. Harvard University (n = 11) and the University of California, San Francisco (n = 11) were the top two institutions in terms of publications. Neuron dominated with 13 articles in the 37 high-quality journals. M. Goedert from the MRC Laboratory of Molecular Biology was the most productive (n = 9) and top co-cited (n = 179) author. The most frequently studied keywords were Alzheimer’s disease (n = 38). Future research is anticipated to intensify its focus on the pathogenesis of various tau-related diseases, emphasizing the phosphorylation and structural alterations of tau protein, particularly in Alzheimer’s disease.ConclusionThe pathogenesis of various tau-related diseases, including the phosphorylation and structural alterations of the tau protein, will be the primary focus of future research, with particular emphasis on Alzheimer’s disease as a central area of investigation.

Abstract Background L-type Ca2+ channel CaV1.2 is essential for cardiomyocyte excitation, contraction and gene transcription in the heart, and abnormal functions of cardiac CaV1.2 channels are presented in diabetic cardiomyopathy. However, the underlying mechanisms are largely unclear. The functions of CaV1.2 channels are subtly modulated by splicing factor-mediated alternative splicing (AS), but whether and how CaV1.2 channels are alternatively spliced in diabetic heart remains unknown. Methods Diabetic rat models were established by using high-fat diet in combination with low dose streptozotocin. Cardiac function and morphology were assessed by echocardiography and HE staining, respectively. Isolated neonatal rat ventricular myocytes (NRVMs) were used as a cell-based model. Cardiac CaV1.2 channel functions were measured by whole-cell patch clamp, and intracellular Ca2+ concentration was monitored by using Fluo-4 AM. Results We find that diabetic rats develop diastolic dysfunction and cardiac hypertrophy accompanied by an increased CaV1.2 channel with alternative exon 9* (CaV1.2E9*), but unchanged that with alternative exon 8/8a or exon 33. The splicing factor Rbfox2 expression is also increased in diabetic heart, presumably because of dominate-negative (DN) isoform. Unexpectedly, high glucose cannot induce the aberrant expressions of CaV1.2 exon 9* and Rbfox2. But glycated serum (GS), the mimic of advanced glycation end-products (AGEs), upregulates CaV1.2E9* channels proportion and downregulates Rbfox2 expression in NRVMs. By whole-cell patch clamp, we find GS application hyperpolarizes the current-voltage curve and window currents of cardiac CaV1.2 channels. Moreover, GS treatment raises K+-triggered intracellular Ca2+ concentration ([Ca2+]i), enlarges cell surface area of NRVMs and induces hypertrophic genes transcription. Consistently, siRNA-mediated knockdown of Rbfox2 in NRVMs upregulates CaV1.2E9* channel, shifts CaV1.2 window currents to hyperpolarization, increases [Ca2+]i and induces cardiomyocyte hypertrophy. Conclusions AGEs, not glucose, dysregulates Rbfox2 which thereby increases CaV1.2E9* channels and hyperpolarizes channel window currents. These make the channels open at greater negative potentials and lead to increased [Ca2+]i in cardiomyocytes, and finally induce cardiomyocyte hypertrophy in diabetes. Our work elucidates the underlying mechanisms for CaV1.2 channel regulation in diabetic heart, and targeting Rbfox2 to reset the aberrantly spliced CaV1.2 channel might be a promising therapeutic approach in diabetes-induced cardiac hypertrophy.

Cancer is a highly heterogeneous disease, and different individuals of the same cancer type can display different therapeutic effects and prognosis. Genetic variation of long non-coding RNA is the key factor driving tumor development, and plays an important role in genetic and biological heterogeneity. Therefore, it is of great significance to identify lncRNA as a driving factor in the non-coding region and explain its function in tumors for revealing the pathogenesis of cancer. In this study, we developed an integrated method to identify Personalized Functional Driver lncRNAs (PFD-lncRNAs) by integrating the DNA copy number data, gene expression data, and the biological subpathways information. Then, we applied the method to identify 2695 PFD-lncRNAs in 5334 samples across 19 cancer types. We performed an analysis of the association between PFD-lncRNAs and drug sensitivity, which provides medication guidance in disease therapy and drug discovery in the individual. Our research is of great significance for elucidating the biological roles of lncRNA genetic variation in cancer, revealing the related mechanism of cancer, and providing novel insights for individualized medicine.

Bacterial resistance poses a major hazard to human health, and is caused by the misuse and overuse of antibiotics. Thus, it is imperative to investigate the optimal dosing strategy to improve the treatment effect. In this study, a mathematical model of antibiotic-induced resistance is presented to improve the antibiotic effectiveness. First, conditions for the global asymptotical stability of the equilibrium without pulsed effect are given according to the Poincaré-Bendixson Theorem. Second, a mathematical model of the dosing strategy with impulsive state feedback control is also formulated to reduce drug resistance to an acceptable level. The existence and stability of the order-1 periodic solution of the system are discussed to obtain the optimal control of antibiotics. Finally, our conclusions are confirmed by means of numerical simulations.

By considering the fact that the growth of microorganisms in a chemostat is subject to white noise, we construct a stochastic chemostat model with degenerate diffusion by using a discrete Markov chain. By solving the corresponding Fokker-Planck equation, we derive the explicit expression of the stationary joint probability density, which peaks near the deterministic equilibrium. Next, we simulate the the marginal probability density functions for different noise intensities and further discuss the relationship of the marginal probability density function and noise intensities. For the statistical properties of the stochastic model, we mainly investigate the effect of white noise on the variance and skewness of the concentration of microorganisms.

The innate immunity of marine bivalves is challenged upon exposure to heat stress, especially with increases in the frequency and intensity of heat waves. TLR4 serves a classical pattern recognition receptor in recognizing pathogenic microorganisms and activating immune responses. In this study, three genes, HMTLR4, HMMyD88 and HMTRAF6, were characterized as homologs of genes in the TLR4-MyD88 signaling pathway in the selected scallop strain “Hongmo No. 1”. According to RT-PCR, acute heat stress (32 °C) inhibited genes in the TLR4-MyD88 signaling pathway, and LPS stimulation-induced activation of TLR4-MyD88 signal transduction was also negatively affected at 32 °C. ELISA showed LPS-induced tumor necrosis factor alpha (TNF-α) or lysozyme (LZM) activity, but this was independent of temperature. RNA interference (RNAi) confirmed that HMTLR4 silencing suppressed the expression of its downstream gene, whether at 24 °C or at 32 °C. The level of TNF-α and the activity of LZM also decreased after injection with dsRNA, indicating a negative effect on the innate immunity of scallops. Additionally, acute heat stress affected the suppression of downstream gene expression when compared with that at 24 °C, which led us to the hypothesis that heat stress directly influences the downstream targets of HMTLR4. These results enrich the knowledge of scallop immunity under heat stress and can be beneficial for the genetic improvement of new scallop strains with higher thermotolerance.

To achieve a micro-destructive and rapid measurement of the wood density of standing trees, this study investigated the possibility of the unified modeling of multiple tree species, the reliability of the micro drilling resistance method for measuring wood density, the relationship between drilling needle resistance and wood density, and whether moisture content has a significant impact on the model. First, 231 tree cores and drill resistance data were sampled from Pinus massoniana, Cunninghamia lanceolate, and Cryptomeria fortunei. The basic density and moisture content of each core were measured, and the average value of each resistance data record was calculated. Second, the average drill resistance, the natural logarithm of average drill resistance, and absolute moisture content were used as independent variables, while the basic wood density was used as the dependent variable. Third, the total model of the three tree species and sub-model for each tree species were established through a stepwise regression method. Finally, the accuracy of each model was compared and analyzed with that of using the average basic density of each tree species as an estimated density. The estimated accuracy of the total model, sub model, and average wood density modeling data were 90.070%, 93.865%, and 92.195%, respectively. The results revealed that the estimation accuracy of the sub-model was 1.670 percentage points higher than that of the average wood density modeling data, while the estimation accuracy of the total model was 2.125 percentage points lower than that of the average wood density modeling data. Additionally, except for Cryptomeria fortunei, the natural logarithm of drill resistance significantly influenced the wood density model at a significance level of 0.05. Moreover, moisture content significantly affected the total model and sub-models of Pinus massoniana at a significance level of 0.05. The results indicated the feasibility of using the micro-drilling resistance method to measure the wood density of standing trees. Moreover, the relationship between wood density and drill resistance did not follow a linear pattern, and moisture content slightly influenced the drill needle resistance. Furthermore, the establishment of a mathematical model for each tree species was deemed essential. This study provides valuable guidance for measuring the wood density of standing trees through the micro-drilling resistance method.

This article aims to test a causal nexus between bitcoin market and economic policy uncertainty. We use the continuous wavelet analysis to investigate lead-lag relationship between bitcoin market and economic policy uncertainty in different time-frequency domains. Our findings show the negative relationship between bitcoin returns and economic policy uncertainty around the period of bitcoin’s currency recognition and COVIC-19 pandemic crisis both daily and monthly time series test. Furthermore, we find that the causality relationship between bitcoin and economic policy uncertainty is relatively indistinct around the period of bitcoin’s currency recognition, while bitcoin returns are leading economic policy uncertainty changes during COVID-19 pandemic crisis, indicating the economic policy uncertainty fluctuation trend can refer to the fluctuation of bitcoin, bitcoin can be viewed as a leading indicator, but it could not be employed as a safe-haven asset hedge against uncertainty during the period of COVID-19 pandemic.

Abstract Background Previous studies observed that sleep disorders potentially increased the risk of asthma and asthmatic exacerbation. We aimed to examine whether excessive daytime sleepiness (EDS), probable insomnia, objective short sleep duration (OSSD), and obstructive sleep apnea (OSA) affect all-cause mortality (ACM) in individuals with or without asthma. Methods We extracted relevant data from the Sleep Heart Health Study established in 1995–1998 with an 11.4-year follow-up. Multivariate Cox regression analysis with a proportional hazards model was used to estimate the associations between ACM and four sleep disorders among asthmatic patients and individuals without asthma. Dose-response analysis and machine learning (random survival forest and CoxBoost) further evaluated the impact of sleep disorders on ACM in asthmatic patients. Results A total of 4538 individuals with 990 deaths were included in our study, including 357 asthmatic patients with 64 deaths. Three multivariate Cox regression analyses suggested that OSSD (adjusted HR = 2.67, 95% CI: 1.23–5.77) but not probable insomnia, EDS or OSA significantly increased the risk of ACM in asthmatic patients. Three dose-response analyses also indicated that the extension of objective sleep duration was associated with a reduction in ACM in asthmatic patients compared to very OSSD patients. Severe EDS potentially augmented the risk of ACM compared with asthmatics without EDS (adjusted HR = 3.08, 95% CI: 1.11–8.56). Machine learning demonstrated that OSSD of four sleep disorders had the largest relative importance for ACM in asthmatics, followed by EDS, OSA and probable insomnia. Conclusions This study observed that OSSD and severe EDS were positively associated with an increase in ACM in asthmatic patients. Periodic screening and effective intervention of sleep disorders are necessary for the management of asthma.

Abstract Background Sarcopenia is listed as a treatment trait in behavioral/risk factors for severe asthma, but studies on asthma and sarcopenia are lacking. This study aimed to determine the associations between sarcopenia with asthmatic prevalence, symptoms, lung function and comorbidities. Methods Fifteen thousand four hundred four individuals from the China Health and Retirement Longitudinal Study(CHARLS) and 10,263 individuals from the Study on global AGEing and adult health(SAGE) in China were included in this study. Four components of this study were used to assess the bidirectional association in the prevalence between sarcopenia with asthma, and estimate the relationships between sarcopenia with asthmatic symptoms, lung function and comorbidities via generalized additive models. The 10-item Center for Epidemiological Studies–Depression Scale ≥ 12 scores was classified as depression. Results In the CHARLS and SAGE, the prevalence of sarcopenia in asthmatics was higher than those without asthma. Asthmatics with sarcopenia had a significantly increased prevalence of severe shortness of breath(sarcopenia yes vs. no, adjusted OR = 3.71, 95%CI: 1.43–9.60) and airway obstruction in the SAGE(sarcopenia yes vs. no, adjusted OR = 6.82, 95%CI: 2.54–18.34) and an obvious reduction of PEF in the CHARLS and SAGE(sarcopenia yes vs. no, adjusted RR = 0.86, 95%CI: 0.82–0.91) compared to asthmatics without sarcopenia. The presence of sarcopenia was positively associated with the prevalence of chronic obstructive pulmonary disease(sarcopenia yes vs no, adjusted OR = 5.76, 95%CI:2.01–16.5) and depression(sarcopenia yes vs no, adjusted OR = 1.87, 95%CI:1.11–3.14) in asthmatics. Conclusions Our findings indicated that sarcopenia partakes in the development of asthma by affecting lung function and comorbidities and maybe considered a treatable trait of asthma management.

Most attempts to co-cultivate the artificial microbial communities fail mostly due to the mismatched rates of consumption and production of nutrients among subpopulations. Here, the authors develop a microbial swarmbot mediated spatial segregation method to assemble stably coexisting consortia with both flexibility and precision.

In order to understand the breakup characteristics of a transverse liquid jet flow in an actual combustion chamber, a numerical study was conducted using the Volume of Fluid (VOF) method combined with grid adaptation technology. The study focused on the primary breakup characteristics of liquid jets under the conditions of a steady and oscillating air crossflow. The simulated mediums were set to water and air. The research findings revealed that fluctuations in the incoming gas velocity can influence the development speed of surface waves and the mode of jet breakup during the initial stage of jet development as compared to the steady condition. In both conditions, the surface waves were initially observed to appear within 1/4 T–2/4 T. The surface wave of the jet develops faster under steady conditions because the average velocity of the steady flow is higher than that of the oscillation flow during this stage. As a result, the fragmentation of the jet is primarily influenced by the surface wave. Under an oscillating flow, the rear of the jet begins to break up earlier due to the slower development of surface waves. The velocity of the oscillating air inflow increases over time, and the speed of surface wave development also increases, gradually leading to the dominance of surface-wave-induced jet breakup. In the second stage of air inflow oscillation, an “up and down slapping” phenomenon occurs at the tail of the jet. Additionally, increasing the air inflow velocity leads to a longer jet breakup length and a higher number of droplets near the jet column. Surface waves are observed on both the windward and leeward sides of the jet. The penetration depth of the jet fluctuates with changes in the crossflow velocity, and the response of the jet penetration depth to the velocity fluctuations in the transverse air is delayed by half a period.

Stem volume is a very important parameter in forestry inventory and carbon storage. The stem volume estimated by most existing methods deviates from its true value because the irregularity of the stem is usually overlooked. In this study, we propose a stem segment volume estimation based on the tetrahedron model using TLS data. First, the initial stem segment surface model, including the lower, upper, and outer triangular surface models, was gradually reconstructed. Next, the outer surface model was subdivided based on the edge subdivision. Then, a closed triangular surface model without self-intersection was obtained. Afterward, a tetrahedron model of the stem segment was generated using TetGen software (Version 1.6.0) for the triangular surface model. Finally, the stem segment volume was calculated by summing the volumes of all the tetrahedrons in the tetrahedron model. An experiment with 76 stem segments from different tree species with different parameters showed that the reconstructed stem segment surface model effectively reflected the geometrical features of the stem segment surface. Compared to the volume based on the simulated sectional measurement, the MAPE of the volume based on the tetrahedron model was 2.12%. The results demonstrated the validity of the presented method for stem surface reconstruction and stem volume estimation, and the volume based on the tetrahedron model was closer to the true value than that based on the sectional measurement.

Abstract Background Light-driven consortia, which consist of sucrose-secreting cyanobacteria and heterotrophic species, have attracted considerable attention due to their capability for the sustainable production of valuable chemicals directly from CO2. In a previous study, we achieved a one-step conversion of sucrose secreted from cyanobacteria to fine chemicals by constructing an artificial coculture system consisting of sucrose-secreting Synechococcus elongateus cscB + and 3-hydroxypropionic acid (3-HP) producing Escherichia coli ABKm. Analyses of the coculture system showed that the cyanobacterial cells grew better than their corresponding axenic cultures. To explore the underlying mechanism and to identify the metabolic nodes with the potential to further improve the coculture system, we conducted integrated transcriptomic, proteomic and metabolomic analyses. Results We first explored how the relieved oxidative stress affected cyanobacterial cell growth in a coculture system by supplementing additional ascorbic acid to CoBG-11 medium. We found that the cell growth of cyanobacteria was clearly improved with an additional 1 mM ascorbic acid under axenic culture; however, its growth was still slower than that in the coculture system, suggesting that the improved growth of Synechococcus cscB + may be caused by multiple factors, including reduced oxidative stress. To further explore the cellular responses of cyanobacteria in the system, quantitative transcriptomics, proteomics and metabolomics were applied to Synechococcus cscB +. Analyses of differentially regulated genes/proteins and the abundance change of metabolites in the photosystems revealed that the photosynthesis of the cocultured Synechococcus cscB + was enhanced. The decreased expression of the CO2 transporter suggested that the heterotrophic partner in the system might supplement additional CO2 to support the cell growth of Synechococcus cscB +. In addition, the differentially regulated genes and proteins involved in the nitrogen and phosphate assimilation pathways suggested that the supply of phosphate and nitrogen in the Co-BG11 medium might be insufficient. Conclusion An artificial coculture system capable of converting CO2 to fine chemicals was established and then analysed by integrated omics analysis, which demonstrated that in the coculture system, the relieved oxidative stress and increased CO2 availability improved the cell growth of cyanobacteria. In addition, the results also showed that the supply of phosphate and nitrogen in the Co-BG11 medium might be insufficient, which paves a new path towards the optimization of the coculture system in the future. Taken together, these results from the multiple omics analyses provide strong evidence that beneficial interactions can be achieved from cross-feeding and competition between phototrophs and prokaryotic heterotrophs and new guidelines for engineering more intelligent artificial consortia in the future.

Shortage of personal protective equipment (PPE) is often projected in response to public health emergencies such as infection outbreaks and pandemics. Respiratory protective devices (RPDs), namely medical face masks and respirators, are considered the last defense for the front-line healthcare workers. Cleaning, decontamination and reuse of the disposable RPDs have been accepted by local health authorities during the pandemic period. To contribute to the mitigation of RPD shortage and ensure the safe adoption of decontamination protocols, this review discusses the regulated testing standards and the most commonly studied decontamination methods in the literature. The reuse of RPDs must fulfill three criteria: remove the microbial thread, maintain original function and structural integrity (including fitting tests) and leave no harmful residuals. Decontamination methods such as ultraviolet germicidal irradiation, moist heat and vaporized hydrogen peroxide appeared to be the most promising methods in balancing the above-mentioned criteria. However, the effectiveness of decontamination methods varies depending on the RPDs’ models, materials and design. Therefore, the adoption of protocols needs to be evidence-based with full validation in the local institutes. Additionally, new technology such as antimicrobial treated PPE that can reduce the risks of fomite during donning and doffing process with an extended lifespan should be encouraged. Overall, good training and guidance for appropriate reuse of RPDs are fundamental to ensure their efficiency in protecting front-line healthcare workers.

Potential acute mountain sickness diagnostic, predictive, protective biomarkers are established using plasma proteomic, clinical and symptom phenotype data with machine learning approaches in a longitudinal cohort of 53 individuals.

Background Immunotherapy for malignant tumors has made great progress, but many patients do not benefit from it. The complex intratumoral heterogeneity (ITH) hindered the in-depth exploration of immunotherapy. Conventional bulk sequencing has masked intratumor complexity, preventing a more detailed discovery of the impact of ITH on treatment efficacy. Hence, we initiated this study to explore ITH at the multi-omics spatial level and to seek prognostic biomarkers of immunotherapy efficacy considering the presence of ITH.Methods Using the segmentation strategy of digital spatial profiling (DSP), we obtained differential information on tumor and stromal regions at the proteomic and transcriptomic levels. Based on the consideration of ITH, signatures constructed by candidate proteins in different regions were used to predict the efficacy of immunotherapy.Results Eighteen patients treated with a bispecific antibody (bsAb)-KN046 were enrolled in this study. The tumor and stromal areas of the same samples exhibited distinct features. Signatures consisting of 11 and 18 differentially expressed DSP markers from the tumor and stromal areas, respectively, were associated with treatment response. Furthermore, the spatially resolved signature identified from the stromal areas showed greater predictive power for bsAb immunotherapy response (area under the curve=0.838). Subsequently, our stromal signature was validated in an independent cohort of patients with non-small cell lung cancer undergoing immunotherapy.Conclusion We deciphered ITH at the spatial level and demonstrated for the first time that genetic information in the stromal region can better predict the efficacy of bsAb treatment.Trial registration number NCT03838848.

Purpose: Obesity is considered a risk factor for asthma exacerbation. However, limited studies have focused on the association of different levels of weight clusters with asthma. As such, we study the associations between different weight clusters with FeNO, blood eosinophils, and lung function among adult asthmatics.Methods: Data from 789 participants aged 20 years or older in the National Health and Nutrition Examination Survey 2007–2012 were analyzed. Body mass index (BMI) and waist circumference (WC) were used to determine the weight status. The study population was divided into five groups, including normal weight and low WC (153), normal weight and high WC (43), overweight and high WC (67), overweight and abdominal obesity (128), and general and abdominal obesity (398). A Multivariate linear regression model was used to evaluate the abovementioned associations after adjusting for potential confounding factors.Results: The adjusted models showed that general and abdominal obesity cluster (adjusted β = −0.63, 95% confidence interval (CI): −1.08, −0.17 p < 0.01), and the normal weight with high WC cluster (adjusted β = −0.96, 95% CI: −1.74, −0.19 p < 0.05) were associated with lower levels of blood eosinophils percentage than normal weight and low WC cluster. A similar tendency was shown in the levels of FeNO, but the differences were not significant (p > 0.05). Furthermore, abdominal obesity clusters were significantly associated with lower FVC, FVC% predicted, and FEV1 measures than normal weight and low WC cluster, especially those individuals with general and abdominal obesity cluster. No association was found between different weight clusters and FEV1/FVCF ratio. The two other weight clusters did not show the association with any of the lung function measures.Conclusion: General and abdominal obesity were associated with lung function impairment and a significant reduction of FeNO and blood eosinophil percentage. This study emphasized the importance of concurrent determination of BMI and WC in asthma clinical practice.

Crassostrea hongkongensis (Hong Kong oyster), a commercially valuable bivalve thriving in the estuaries along the northern coast of the South China Sea, is threatened by the increase of salinity during the dry season. It is essential to improve its hyper-salinity tolerance, which requires a clear understanding of the mechanism to regulate its osmotic balance. For this purpose, 25 free amino acids (FAA), the most critical intracellular osmolyte in bivalves, were quantified in gill, adductor muscle, and hemolymph of C. hongkongensis during abrupt salinity changes (18–6, 12, 24 and 30‰) by high-performance liquid chromatography-tandem mass spectrometry. Taurine, alanine and glycine were dominant FAA, contributing to total FAA contents that varied with salinities, no matter in gill, muscle or hemolymph. Under hypo-osmotic stress, total FAA contents decreased in gill and adductor muscle but increased in hemolymph, probably resulting from the extrusion of some FAA from tissues to prevent swelling of cells. And taurine contributed most significantly to the hypo-salinity response, which was mainly reflected by the remarkable increase in hemolymph at 8 h after the exposure to 6‰. By contrast, total FAA contents increased in gill, muscle, and hemolymph when transferred to hyper-salinity, suggesting the assumption that it increases the osmolality and subsequently prevents the cell shrinking. Alanine and glycine contributed most significantly to hyper-salinity response. Of the two, the former was more sensitive to hyper-osmotic stress for its rapid increase in gill within 8 h after the exposure to 24 and 30‰. An inverse pattern with most FAA was presented by ornithine, the intermediate of the urea cycle, which was probably associated with the FAA metabolism. This study identified the major FAA as intracellular osmolytes in C. hongkongensis and would benefit the further understanding of the regulatory mechanisms of oyster salinity acclimation.

We investigated the residual rate and mass loss rate of litter, as well as the carbon release dynamics of litter and soil across seasons, to better understand the effects of seasonal fluctuations on carbon dynamics in mixed coniferous forests. The study was carried out in natural mixed coniferous forests in the Xiaoxinganling region of Heilongjiang Province, China, and the number of temperature cycles in the unfrozen season, freeze-thaw season, frozen season, and thaw season was controlled. The goal of the study was to examine how the carbon release dynamics of litter and soil respond to the freeze-thaw process and whether there are differences in carbon release dynamics under different seasons. Repeated-measures analysis of variance was used to analyze the residual mass rate and mass loss rate of litter, litter organic carbon and soil organic carbon during the unfrozen season, freeze-thaw season, frozen season, and thaw season. Litter decomposition was highest in the unfrozen season (15.9%~20.3%), and litter and soil carbon were sequestered throughout this process. Temperature swings above and below 0°C during the freeze-thaw season cause the litter to physically fragment and hasten its decomposition. Decomposition of litter was still feasible during the frozen season, and it was at its lowest during the thaw season (7.2%~7.8%), when its organic carbon was transported to the soil. Carbon migrates from undecomposed litter to semi-decomposed litter and then to soil. The carbon in the environment is fixed in the litter (11.3%~18.2%) and soil (34.4%~36.7%) in the unfrozen season, the carbon-fixing ability of the undecomposed litter in the freeze-thaw season is better, and the carbon in the semi-decomposed litter is mostly transferred to the soil; the carbon-fixing ability of the litter in the frozen season is worse (-3.9%~ -4.3%), and the organic carbon in the litter is gradually transferred to the soil. The carbon-fixing ability of the undecomposed litter in the thaw season is stronger, and the organic carbon in the semi-decomposed litter is mostly transferred to the soil. Both litter and soil can store carbon; however, from the unfrozen season until the thaw season, carbon is transported from undecomposed litter to semi-decomposed litter and to the soil over time.

Umbilical cord mesenchymal stem cells (UCMSCs) are a reportedly promising choice in the treatment of irreversible pulmonary fibrosis and lethal interstitial lung disease with limited drug treatment options. In this study, we investigated the therapeutic efficacy of UCMSCs overexpressing hepatocyte growth factor (HGF), which is considered one of the main anti-fibrotic factors secreted by MSCs. Adenovirus vector carrying the HGF gene was transfected into UCMSCs to produce HGF-modified UCMSCs (HGF-UCMSCs). Transfection promoted the proliferation of UCMSCs and did not change the morphology, and differentiation ability, or biomarkers. Rats were injected with HGF-UCMSCs on days 7 and 11 after intratracheal administration of bleomycin (10 mg/kg). We performed an analysis of histopathology and lung function to evaluate the anti-fibrotic effect. The results showed that HGF-UCMSCs decreased the Ashcroft scores in hematoxylin and eosin-stained sections, the percentage positive area in Masson trichrome-stained sections, and the hydroxyproline level in lungs. Forced expiratory volume in the first 300 m/forced vital capacity was also improved by HGF-UCMSCs. To explore the possible therapeutic mechanism of HGF-UCMSCs, we detected inflammatory factors in the lungs and performed mRNA sequencing in UCMSCs and HGF-UCMSCs. The data indicated that inhibition of interleukin-17 in the lung may be related to the anti-fibrosis of HGF-UCMSCs, and overexpressed HGF probably played a primary role in the treatment. Collectively, our study findings suggested that the overexpression of HGF may improve the anti-fibrotic effect of UCMSCs through directly or indirectly interacting with interleukin-17-producing cells in fibrotic lungs.

Abstract Irisin protects the cardiovascular system against vascular diseases. However, its role in chronic kidney disease (CKD) -associated vascular calcification (VC) and the underlying mechanisms remain unclear. In the present study, we investigated the potential link among Irisin, pyroptosis, and VC under CKD conditions. During mouse vascular smooth muscle cell (VSMC) calcification induced by β-glycerophosphate (β-GP), the pyroptosis level was increased, as evidenced by the upregulated expression of pyroptosis-related proteins (cleaved CASP1, GSDMD-N, and IL1B) and pyroptotic cell death (increased numbers of PI-positive cells and LDH release). Reducing the pyroptosis levels by a CASP1 inhibitor remarkably decreased calcium deposition in β-GP-treated VSMCs. Further experiments revealed that the pyroptosis pathway was activated by excessive reactive oxygen species (ROS) production and subsequent NLR family pyrin domain containing 3 (NLRP3) inflammasome activation in calcified VSMCs. Importantly, Irisin effectively inhibited β-GP-induced calcium deposition in VSMCs in vitro and in mice aortic rings ex vivo. Overexpression of Nlrp3 attenuated the suppressive effect of Irisin on VSMC calcification. In addition, Irisin could induce autophagy and restore autophagic flux in calcified VSMCs. Adding the autophagy inhibitor 3-methyladenine or chloroquine attenuated the inhibitory effect of Irisin on β-GP-induced ROS production, NLRP3 inflammasome activation, pyroptosis, and calcification in VSMCs. Finally, our in vivo study showed that Irisin treatment promoted autophagy, downregulated ROS level and thereby suppressed pyroptosis and medial calcification in aortic tissues of adenine-induced CKD mice. Together, our findings for the first time demonstrated that Irisin protected against VC via inducing autophagy and inhibiting VSMC pyroptosis in CKD, and Irisin might serve as an effective therapeutic agent for CKD-associated VC.

Most stroke survivors have difficulties completing activities of daily living (ADLs) independently. However, few rehabilitation systems have focused on ADLs-related training for gross and fine motor function together. We propose an ADLs-based serious game rehabilitation system for the training of motor function and coordination of both arm and hand movement where the user performs corresponding ADLs movements to interact with the target in the serious game. A multi-sensor fusion model based on electromyographic (EMG), force myographic (FMG), and inertial sensing was developed to estimate users’ natural upper limb movement. Eight healthy subjects and three stroke patients were recruited in an experiment to validate the system’s effectiveness. The performance of different sensor and classifier configurations on hand gesture classification against the arm position variations were analyzed, and qualitative patient questionnaires were conducted. Results showed that elbow extension/flexion has a more significant negative influence on EMG-based, FMG-based, and EMG+FMG-based hand gesture recognition than shoulder abduction/adduction does. In addition, there was no significant difference in the negative influence of shoulder abduction/adduction and shoulder flexion/extension on hand gesture recognition. However, there was a significant interaction between sensor configurations and algorithm configurations in both offline and real-time recognition accuracy. The EMG+FMG-combined multi-position classifier model had the best performance against arm position change. In addition, all the stroke patients reported their ADLs-related ability could be restored by using the system. These results demonstrate that the multi-sensor fusion model could estimate hand gestures and gross movement accurately, and the proposed training system has the potential to improve patients’ ability to perform ADLs.

Aspect-Based Sentiment Analysis (ABSA) is one of the highly challenging tasks in natural language processing. It extracts fine-grained sentiment information in user-generated reviews, as it aims at predicting the polarities towards predefined aspect categories or relevant entities in free text. Previous deep learning approaches usually rely on large-scale pre-trained language models and the attention mechanism, which applies the complete computed attention weights and does not place any restriction on the attention assignment. We argue that the original attention mechanism is not the ideal configuration for ABSA, as for most of the time only a small portion of terms are strongly related to the sentiment polarity of an aspect or entity. In this paper, we propose a masked attention mechanism customized for ABSA, with two different approaches to generate the mask. The first method sets an attention weight threshold that is determined by the maximum of all weights, and keeps only attention scores above the threshold. The second selects the top words with the highest weights. Both remove the lower score parts that are assumed to be less relevant to the aspect of focus. By ignoring part of input that is claimed irrelevant, a large proportion of input noise is removed, keeping the downstream model more focused and reducing calculation cost. Experiments on the Multi-Aspect Multi-Sentiment (MAMS) and SemEval-2014 datasets show significant improvements over state-of-the-art pre-trained language models with full attention, which displays the value of the masked attention mechanism. Recent work shows that simple self-attention in Transformer quickly degenerates to a rank-1 matrix, and masked attention may be another cure for that trend.

Abstract As an important classification of photodetectors, broad spectral photodiodes are ubiquitous in the fields of industry and scientific research. Here, we reported a type of broad spectral organic–inorganic hybrid photodiodes (OIHPDs) based on planar-bulk heterojunction, which composed of 3,4,9,10-perylenetertracarboxylic dianhydride (PTCDA), copper phthalocyanine (CuPc) and fullerene (C60). In our research, the dark current of the OIHPD with 10 nm C60 film (10 nm-C60 OIHPD) was as low as 25.6 μA, which is about 63 times smaller than the dark current of the OIHPD without C60 film (C60-free OIHPD). It is considered that the significantly enhanced performance of 10 nm-C60 OIHPD is attributed to the introduction of the C60 film, which act as hole-blocking layer to reduce the dark current. And through the schematic energy level model combined with experimental measurements, the reason for the dark current change was well explained. Furthermore, the specific detectivity of 10 nm-C60 OIHPD was almost one order of magnitude larger than it of C60-free OIHPD, and a notable enhancement of over 1011 cm Hz1/2/W was obtained due to the fiercely reduced dark current. These results provide insights on how to improve the performance of organic photodiodes.

Urban fugitive dust is a significant contributor to atmospheric PM2.5 and a potential risk to humans. In 2019, both road dust and construction dust were collected from four cities, including Xi’an, Xianyang, Baoji, and Tongchuan, in Guanzhong Plain, China. Elements, water-soluble ions, and carbonaceous fractions were determined to establish the chemical source profile. High enrichment degrees of Se, Sc, Cl, and Zn in both road dust and construction dust indicated that the industrial system and energy consumption influenced Guanzhong Plain strongly. According to the coefficient of divergence, the two datasets within Xianyang and Tongchuan were similar. Combined with the chemical profile, road dust was affected by more stationary emission sources than construction dust in Xi’an, while biomass burning and vehicle exhaust contributed more to road dust than construction dust in Baoji. Moreover, the health risk of heavy metal was assessed, and corresponding influencing factors were identified. Road dust in all cities showed a non-negligible non-carcinogenic risk for children. Ingestion and inhalation were the main exposure pathways to which As and Co contributed the most, respectively. The land-use regression model revealed that the first-class road in a 100 m radius impacted all high-risk level metals, and the commercial building material and enterprises weakly influenced Co and Pb, respectively.

A tree skeleton reflects the geometric and structural characteristics of a tree. Terrestrial laser scanning (TLS) provides an effective means to construct tree skeletons that can capture the surface and topological features of trees. However, it is difficult to construct a tree skeleton located at the geometric centre of the tree with a detailed hierarchy of branches because of the natural intricate topology of the tree and the defects of the tree point cloud scanned by TLS. In this study, we presented a tree-skeletonization method based on density-based spatial clustering of applications with noise (DBSCAN) using TLS data. First, outliers were removed using DBSCAN, and the point-traversal order of each point was recorded. Next, a tree point cloud was divided into several tree slices using contour planes, and several tree segments were obtained by applying DBSCAN to each tree slice. Tree skeleton points were retrieved from each tree segment after the point-inversion transformation. Then, the adjacent relationship between skeleton points and the flow weight of each skeleton point was calculated based on the point-traversal order. After that, the skeleton points were classified into stems and different levels of branch points using the flow weights of the skeleton points, and the branch hierarchies were identified. Finally, the tree skeleton was optimized using the angle consistency. The positional deviation dp and directivity deviation dd were presented in this study to verify the validity of the constructed tree skeleton. From the visualization results, the constructed tree skeleton effectively reflected the geometrical structure and branch hierarchies of the tree. The averages of dp and dd were 0.418 cm and 8.474 degrees, respectively. The results demonstrated the validity of the presented method. It will help improve the visualization and accurate measurement of trees.

Abstract Caffeic acid phenethyl ester (CAPE) is a bioactive component of honeybee propolis, which has protective effect against heavy metal induced toxicology. Cadmium is a kind of heavy metal pollutant that is hazardous to human health especially liver, and apoptosis is an important mechanism related to cadmium injury. Circular RNAs (CircRNAs) are involved in the regulation of apoptosis. However, the protective effects of CAPE on cadmium‐induced cell apoptosis through CircRNA related mechanisms remains unclear at the current stage. In the present research, cell‐based studies revealed that treating HepG2 cells with CdCl2 (0–30 μM; 24 h) caused a dose‐dependent decrease in cell viability, and CAPE at 10 μM could reverse such a decrease. The circular RNA hsa‐circ‐0010039 may function as a ceRNA for the microRNA miR‐661 to enhance caspase 9 expression and regulate apoptosis. The anti‐apoptotic effects of CAPE against CdCl2‐induced injury may be achieved through inhibiting the expression of hsa‐circ‐0010039 and caspase 9 while up‐regulating miR‐661 expression. This is the first report on the involvement of circRNA in CAPE's alleviating effect on CdCl2‐induced injury and apoptosis. The hsa_circ_0010039/miR‐661/caspase9 axis deserves further research efforts especially in search of dietary interventions for cadmium injury.

Surface acoustic wave (SAW) can be used as passive wireless sensors in high temperature environments. For such applications, protective layers are crucial and important for the SAW sensors. In this paper, ultra-thin Al2O3 layers prepared by atomic layer deposition (ALD) and RF magnetron sputtering were used to protect SAW devices with platinum (Pt) electrodes and their temperature stability was studied systematically. The devices were thermally treated up to 1150 °C in air, the real-time resistance of Pt resistive tracks with a sputtering Al2O3 protective layer showed much better and improved thermal stability than those without or with an ALD Al2O3 protective layer. Microstructure characterizations showed that the superior temperature stability is attributed to its mixture of amorphous and nano-crystalline nature of the Al2O3 layer deposited by sputtering and full recrystallization at high temperatures. SAW devices with a sputtering Al2O3 protective layer after 1150 °C treatment maintained almost unchanged properties, while those with an ALD Al2O3 protective layer failed to work. Investigation also indicated there exists an optimal thickness for the sputtering Al2O3 layer to achieve best performance and thermal-stability for the SAW devices. Besides, the deposition rate of Al2O3 layer by sputtering is 10 times faster than that by ALD. All the results demonstrate that the sputtering Al2O3 protective layer is more suitable for high temperature SAW device applications owing to its lower cost, higher deposition rate and temperature stability.

Objectives: The complexity and specificity of lung tumor motion render it necessary to determine the external and internal correlation individually before applying indirect tumor tracking. However, the correlation cannot be determined from patient respiratory and tumor clinical characteristics before treatment. The purpose of this study is to present a machine learning model for an external/internal correlation prediction that is based on computed tomography (CT) radiomic features. Methods: 4-dimensional computed tomography (4DCT) images of 67 patients were collected retrospectively, and the external/internal correlation of lung tumor was calculated based on Spearman's rank correlation coefficient. Radiomic features were extracted from average intensity projection and the light gradient boosting machine (LightGBM)-based cross-validation (the recursive elimination method) was used for feature selection. The LightGBM framework forecasting models with classification thresholds 0.7, 0.8, and 0.9 are established using stratified 5-fold cross-validation. Model performance was assessed using receiver operating characteristics, sensitivity, and specificity. Results: There were 16, 18, and 13 features selected for models 0.7, 0.8, and 0.9, respectively. Texture features are of great importance in external/internal correlation prediction compared to other features in all models. The sensitivities of the predictions in models 0.7, 0.8, and 0.9 were 0.800 ± 0.126, 0.829 ± 0.140, and 0.864 ± 0.086, respectively. The specificities were 0.771 ± 0.114, 0.936 ± 0.0581, and 0.839 ± 0.101, whereas the area under the curve (AUC) was 0.837, 0.946, and 0.877, respectively. Conclusions: Our findings indicate that radiomics is an effective tool for respiratory motion correlation prediction, which can extract tumor motion characteristics. We proposed a machine learning framework for correlation prediction in the motion management strategy for lung tumor patients.