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Abstract DNBSEQ employs a patterned array to facilitate massively parallel sequencing of DNA nanoballs (DNBs), leading to a considerable boost in throughput. By employing the ultra-high-density (UHD) array with an increased density of DNB binding sites, the throughput of DNBSEQ can be further expanded. However, the typical imaging system of the DNBSEQ sequencer is unable to resolve adjacent DNBs spaced smaller than the resolution limit, resulting in poor base-calling performance of the UHD array and hindering its practical application. In this study, we propose a deep-learning-based DNB image super-resolution network named DNBSRN to address this problem. DNBSRN has a specifically designed structure for DNB images and employs a histogram-matching-based preprocessing approach. For the eight DNB image datasets generated from the DNBSEQ sequencer using UHD arrays with 360 nm pitch, the base-calling performances are significantly improved after super-resolution reconstruction by DNBSRN and reached a comparable level to those of the regular density array. In terms of reconstruction speed, DNBSRN takes only 7.61 ms for an input image with 500 × 500 pixels, which minimizes its influence on throughput. Furthermore, compared with state-of-the-art super-resolution networks, DNBSRN demonstrates superior performance in terms of both the quality and speed of DNB image reconstruction. DNBSRN successfully addresses the DNB image super-resolution task. Integrating DNBSRN into the image analysis workflow of DNBSEQ will allow for the application of UHD array, hence enabling a considerable improvement in throughput as well as tremendous savings in unit reagent cost.

Abstract The relationship between the platelet to albumin ratio (PAR) and the disease activity of early rheumatoid arthritis (ERA) remains to be elucidated. This cross-sectional study included 372 patients with ERA who were hospitalized at Xingtai People’s Hospital between January 2022 and January 2024. Multiple linear regression analysis was employed to assess the correlation of PAR with Disease Activity Score 28 (DAS28) using erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), and then generalized additive models were used to explore their relationship. After accounting for confounding variables, a positive correlation was observed between the PAR and DAS28-ESR and DAS28-CRP in ERA patients (β (95% CI): 0.20 (0.08, 0.32) and 0.20 (0.08, 0.33), respectively), and the general trends were consistent from the lowest tertile group (T1) to the highest tertile group (T3). Furthermore, a nonlinear relationship was identified between PAR and both DAS28-ESR and DAS28-CRP. Threshold effect analysis indicated that a value of 13.73 was a significant inflection point. In brief, PAR has a threshold effect on the disease activity of ERA. Increased PAR levels were independently positive associated with DAS28-ESR and DAS28-CRP among ERA patients with PAR

Abstract Background Sepsis-associated acute kidney injury (AKI) is a serious complication of systemic infection with high morbidity and mortality in patients. However, no effective drugs are available for AKI treatment. Dexmedetomidine (DEX) is an alpha 2 adrenal receptor agonist with antioxidant and anti-apoptotic effects. This study aimed to investigate the therapeutic effects of DEX on sepsis-associated AKI and to elucidate the role of mitochondrial dynamics during this process. Methods A lipopolysaccharide (LPS)-induced AKI rat model and an NRK-52E cell model were used in the study. This study investigated the effects of DEX on sepsis-associated AKI and the molecular mechanisms using histologic assessment, biochemical analyses, ultrastructural observation, western blotting, immunofluorescence, immunohistochemistry, qRT-PCR, flow cytometry, and si-mRNA transfection. Results In rats, the results showed that administration of DEX protected kidney structure and function from LPS-induced septic AKI. In addition, we found that DEX upregulated the α2-AR/SIRT1/PGC-1α pathway, protected mitochondrial structure and function, and decreased oxidative stress and apoptosis compared to the LPS group. In NRK-52E cells, DEX regulated the mitochondrial dynamic balance by preventing intracellular Ca2+ overloading and activating CaMKII. Conclusions DEX ameliorated septic AKI by reducing oxidative stress and apoptosis in addition to modulating mitochondrial dynamics via upregulation of the α2-AR/SIRT1/PGC-1α pathway. This is a confirmatory study about DEX pre-treatment to ameliorate septic AKI. Our research reveals a novel mechanistic molecular pathway by which DEX provides nephroprotection.

Abstract This study aims to investigate the interplay between tumor-associated endothelial cells (TECs) and immune cells within the tumor microenvironment (TME) and its impact on tumor prognosis. We conducted single-cell RNA sequencing (scRNA-seq) of tumor, normal, and lymph node tissues obtained from intrahepatic cholangiocarcinoma (ICC) patients to reveal the role of TECs in tumor angiogenesis and their significant heterogeneity. Meanwhile, we identified genes highly expressed in TECs and constructed TEC signatures (TEC.Sig). Next, we calculated TEC scores of samples based on TEC.Sig. Patients with higher TEC scores exhibited a higher frequency of KRAS mutations, which was associated with increased infiltration of neutrophils and immature dendritic cells (iDCs), and decreased numbers of natural killer (NK), CD4 + T, and CD8 + T effector memory (Tem) cells, indicating an inflammation-dominated immunosuppressive phenotype. In contrast, BAP1 mutations and CXCL12 overexpression showed a contrasting trend. Spatial transcriptomics analysis and histological experiments further confirmed that TECs interacted with various tumor-killing immune cells through the CXCL12/CXCR4 axis. Multiple tumor immunotherapy datasets confirmed that the TEC.Sig could predict patient responses to immunotherapy. The TEC score is a promising and reliable biomarker for predicting genetic mutations and prognosis in ICC patients. Enhancing the regulation of the CXCL12/CXCR4 signaling pathway may represent a potential novel therapeutic target for ICC treatment.

Abstract This work explores the extraction of the spatial distribution and chemical composition information of pigments in colored relics through visible spectral images. An adaptive superpixel segmentation method is proposed to extract the spatial distribution information of pigments. Quadtree decomposition is applied to generate nonuniform initial seed points based on the image homogeneity. These seed points are used as the initial cluster centers in an extended simple linear iterative clustering (SLIC) algorithm for visible spectral images to create superpixels of varying sizes that reflect the homogeneity. Each superpixel is subsequently treated as an individual area in the colored relics, and a pigment identification method based on the visible spectral reflectance is proposed to identify the pigments in these areas. A standard reference database is constructed using samples that simulate the painting process of ancient wall paintings in the Mogao Grottoes. Geometric features, which are characterized by the linear combination of the normalized visible spectral reflectance, its slope and its curvature, are designed to represent the chemical composition of pigments. The geometric features of the superpixels are compared with those of the pigments in the database using the Euclidean distance to determine the pigments in each area of the colored relics. This work is expected to provide scientific guidance for pigment selection in the color restoration of colored relics.

Abstract Identifying pigments from colored relics is essential for their color restoration and for facsimile creation. A workflow for identifying pigment information is constructed based on visible spectral imaging technology, aligned with the drawing process of colored relics. This workflow includes three steps: boundary extraction, material identification and prediction of mixture proportions. The methods for segmenting visible spectral images, identifying chemical compositions, and predicting mixture proportions of pigments are extensively reviewed. Future research trends of these methods are also analyzed. The influence of the pigment particle size is currently underexplored but can be accomplished by multidisciplinary research.

The Rainfall thresholds are among the most commonly used criteria for predicting rainfall-induced landslides. However, existing empirical rainfall thresholds mainly focused on regional landslide warnings, lacking consideration for the spatial variability of rainfall thresholds for individual landslides within the region. This study uses historical rainfall-induced landslide data and hourly rainfall data from Bazhong City (2014 – 2021) to employ Kriging interpolation methods. It extracts four types of short-term rainfall (1 hour, 12 hours, 24 hours, 72 hours) and their corresponding long-term rainfall (7 days before the landslide occurrence). In these four threshold models, the distribution of long-term and short-term rainfall thresholds in each group is calculated and then validated using landslide disaster data from 2021. The research results indicate that the prediction accuracy of the four threshold models ranges from 40% to 65%, suggesting good potential for practical application. Additionally, the prediction accuracy improves with the increase in the duration of short-term rainfall. The prediction accuracy for rainfall thresholds calculated from the 72-hour-7-day model is highest, reaching 62%, while the 1-hour-7-day model achieves 46%. Based on the highest prediction accuracy of these models, the study calculates the optimal ratios for short-term and long-term disaster-causing rainfall for four types of models. This leads to a quantitative division between short-term rainfall-induced landslides and long-term rainfall-induced landslides. By calculating the spatial distribution of disaster-causing rainfall, the study extracts rainfall thresholds at potential landslide locations, achieving the goal of one threshold per site in the region and enhancing existing models for calculating rainfall thresholds.

Background: Microvascular invasion (MVI) is associated with an unfavorable prognosis and early recurrence of hepatocellular carcinoma (HCC), which is the crucial pathological hallmark of immunotherapy. While microvascular invasion (MVI) in hepatocellular carcinoma (HCC) currently lacks a detailed single-cell analysis of the tumor microenvironment (TME), it holds significant promise for immunotherapy using immune checkpoint inhibitors (ICI). Methods: We performed single-cell RNA sequencing (scRNA-seq) on 3 MVI positive (MVIP) and 14 MVI-negative (MVIN) tumor tissues, as well as their paired adjacent non-tumoral tissues. Results: We identified SPP1+ macrophages and CD4+ proliferative T cells as intertumoral populations critical for the formation of cold tumors and immunosuppressive environments in MVI-positive patients and verified their prognostic value in correlation with MVIP HCC patients. Additionally, we identified SPP1+ dominated interactions between SPP1+ macrophages and the immunosuppressive T population as contributors to MVI destruction and tumorigenesis. Conclusions: We provide a comprehensive single-cell atlas of HCC patients with MVI, shedding light on the immunosuppressive ecosystem and upregulated signaling associated with MVI. These findings demonstrate that intercellular mechanisms drive MVI and provide a potential immunotherapeutic target for HCC patients with HCC and underlying MVI.

Immunotherapy has profoundly changed the treatment of gastric cancer, but only a minority of patients benefit from immunotherapy. Therefore, numerous studies have been devoted to clarifying the mechanisms underlying resistance to immunotherapy or developing biomarkers for patient stratification. However, previous studies have focused mainly on the tumor microenvironment. Systemic immune perturbations have long been observed in patients with gastric cancer, and the involvement of the peripheral immune system in effective anticancer responses has attracted much attention in recent years. Therefore, understanding the distinct types of systemic immune organization in gastric cancer will aid personalized treatment designed to pair with traditional therapies to alleviate their detrimental effects on systemic immunity or to directly activate the anticancer response of systemic immunity. Herein, this review aims to comprehensively summarize systemic immunity in gastric cancer, including perturbations in systemic immunity induced by cancer and traditional therapies, and the potential clinical applications of systemic immunity in the detection, prediction, prognosis and therapy of gastric cancer.

Abstract Background Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several challenges. The large variation of anisotropic spatial resolution limits the ability of 3D convolutional neural networks (CNNs) to learn features from different views. The background texture of gastric tumor is complex, and its size, shape and intensity distribution are highly variable, which makes it more difficult for deep learning methods to capture the boundary. In particular, while multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. Methods In this study, we propose a new cross-center 3D tumor segmentation method named Hierarchical Class-Aware Domain Adaptive Network (HCA-DAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale context features from the CT images with anisotropic resolution, and a hierarchical class-aware domain alignment (HCADA) module for adaptively aligning multi-scale context features across two domains by integrating a class attention map with class-specific information. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers and validate its segmentation performance in both in-center and cross-center test scenarios. Results Our baseline segmentation network (i.e., AsTr) achieves best results compared to other 3D segmentation models, with a mean dice similarity coefficient (DSC) of 59.26%, 55.97%, 48.83% and 67.28% in four in-center test tasks, and with a DSC of 56.42%, 55.94%, 46.54% and 60.62% in four cross-center test tasks. In addition, the proposed cross-center segmentation network (i.e., HCA-DAN) obtains excellent results compared to other unsupervised domain adaptation methods, with a DSC of 58.36%, 56.72%, 49.25%, and 62.20% in four cross-center test tasks. Conclusions Comprehensive experimental results demonstrate that the proposed method outperforms compared methods on this multi-center database and is promising for routine clinical workflows.

Abstract Background Deciphering the assembly rules of microbial communities is vital for a mechanistic understanding of the general principles driving microbiome structures and functions. In this study, a null modeling-based framework was implemented to infer the assembly rules of bacterial community in oat silages harvested in southern China starting from the grain-filling stage through to full ripening. Results Most silages displayed “inferior” or “very inferior” fermentation quality. The fermentation qualities of silages tended to further decrease with the delay of harvest. Lactobacillus, Pediococcus, unclassified_f_Enterobacteriaceae, and Hafnia–Obesumbacterium constituted the predominated genera in silages. Delaying harvest increased the proportions of Hafnia–Obesumbacterium. Null model analysis revealed that stochastic processes were the primary contributor to the assembly of rare subcommunity during silage fermentation. The succession of abundant subcommunity was controlled both by stochastic and deterministic processes. Deterministic processes, more specifically, heterogeneous selection, were more prominent in the assembly of abundant bacteria in silages with the delay of harvest. Linear regression analysis indicated the important roles of DM, WSC and pH in the assembly of abundant subcommunity. Conclusion This study, from the ecological perspectives, revealed the ecological processes controlling the bacterial community assembly in silage, providing new insights into the mechanisms underlying the construction of silage bacterial community. Graphical Abstract

The advent of immune checkpoint inhibitors (ICIs) has greatly improved the prognosis of advanced lung cancer patients, but can lead to pseudoprogression (PsP), which complicates clinical evaluation and management. PsP is manifested as temporary enlargement of the tumour or the appearance of new lesions, etc., and improvement in imaging occurs with continued treatment, mostly without worsening of clinical symptoms. Currently, there are still difficulties in the early diagnosis of PsP, and its occurrence mechanism is not yet clear, lacking good predictive factors and related biomarkers. This article reviews the current research status of PsP of ICIs in non-small cell lung cancer in order to provide helpful clinical strategies for oncologists using these drugs.

Abstract This study combined applied PICRUSt2 and BugBase tools to evaluate the effects of these two strains on the fermentation characteristics, microbial community, potential microbial risk and hygienic quality of whole-crop corn (WCC) silage. Fresh WCC harvested at the dough stage was ensiled with distilled water (CON), Leuconostoc lactis (LS) and Weissella confusa (WA) for 2, 4, 8, 15 and 30 days. After ensiling, all WCC silages presented desirable fermentation with high lactic acid and Lactobacillus proportions, low pH and ammonia nitrogen levels and absent butyric acid. Ensiling decreased the complexity of bacterial co-occurrence networks, and the Lc. lactis and W. confusa inoculation further decreased the complexity. The inoculation of W. confusa suppressed the most pathogenic pathways and related modules associated with zoonosis. In bacterial phenotype predicted analysis, although CON had lower proportions of ‘Potentially pathogenic’ than fresh material, this undesirable phenotype declined to negligible levels via LS and WA inoculation. Even for well-fermented WCC silages, the risk of pathogens remained after 30 days of ensiling. Therefore, WA could be developed as a promising fast start-up inoculant for reducing pathogenic contamination and improving hygienic quality of silage. Graphical Abstract

[Objective] When tunnel boring machine advancing in the water-rich sand layer, problems such as high cutter torque, serious wear and spout of the screw conveyer can be easily generated. In order to ensure the safety of construction, it is necessary to improve the muck. [Method] Based on a shield tunnel section project of Xi’an Metro Line 16, the muck modifier is selected according to the characteristics of poor self-stability, high friction and high permeability of sandy soil stratum. By combining slump test, permeability test and on-site test, two schemes of foam alone conditioning and mixed foam-bentonite slurry conditioning are used to carry out the experimental research on muck conditioning in water-rich sand layer. [Result & Conclusion] In the actual shield tunneling construction, on the premise of safety, efficiency and economy and based on the data obtained in laboratory tests, the conditioning scheme of mixed foam-bentonite slurry is adopted. The performance of the modifier meets the requirements of shield tunneling construction when the ratio of bentonite to water is 1/8 and the foam mass fraction is 3%. The muck conditioning by foam alone is greatly affected by water content. The higher the water content is, the smaller the optimal foam injection rate (FIR) becomes. The best muck conditioning option for medium sand is 10% of the bentonite slurry injection ratio (BIR) and 20%~25% of FIR. The best muck conditioning option for gravel sand is 10% of BIR and 35%~40% of FIR. Engineering practice shows that the muck conditioning has good effect and the parameters of shield tunneling are stable.

The contamination of arsenic (As) in aqueous environments has drawn widespread attention, and iron compounds may largely alter the migration ability of As. However, the stability of As(III) in Fe-As system with the intervention of organic matter (OM) remains unclear. Herein, we had explored the co-precipitation and co-oxidation processes of As-Fe system by using batch experiments combined with Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Photoelectron Spectroscopy (XPS) in this research. The precipitation quantity of As(III) increased (28.85–92.41 %) when the As/Fe ratio decreased, and increased (24.20–64.20 %) with pH increased. The main active substance for oxidizing As(III) was H2O2, which was produced in the As-Fe system. FTIR and XPS revealed that As(III) was first oxidized in neutral, and then absorbed and enteredthe interior of Fe(OH)3 colloids. But under alkaline conditions, As(III) was adsorbed by Fe (Oxyhydr) oxides firstly, and then oxidized. The intervention of OM would inhibit the redistribution process of As(III) in aqueous environments. Functional groups and unsaturation of the carbon chain were the dominant factors that affected the precipitation and oxidation processes of As(III), respectively. Co-existing ions (especially PO43-) also signally affected the precipitation quantity of As(Ⅲ) in the system and, when coexisting with OM, could exacerbate this process. The influence of co-existing ions on the redistributive process of As(III) in the As-Fe system with/without OM were as follows: PO43- > SO42- > mixed ions > SiO32-. Moreover, high concentration of OM and PO43- might lead to morphological alterations of As, acting as a threat to aqueous environments. In summary, the present findings were to further understand and appreciate the changes of As toxicity in the aqueous environments. Particularly, the coexistence of OM and As can potentially increase the risk to drinking water safety.

Depression is a prevalent psychiatric disorder with accumulating evidence implicating dysregulation of extracellular adenosine triphosphate (ATP) levels in the medial prefrontal cortex (mPFC). It remains unclear whether facilitating endogenous ATP production and subsequently increasing extracellular ATP level in the mPFC can exert a prophylactic effect against chronic social defeat stress (CSDS)-induced depressive-like behaviors and enhance stress resilience. Here, we found that nicotinamide mononucleotide (NMN) treatment effectively elevated nicotinamide adenine dinucleotide (NAD+) biosynthesis and extracellular ATP levels in the mPFC. Moreover, both the 2-week intraperitoneal (i.p.) injection and 3-week oral gavage of NMN prior to exposure to CSDS effectively prevented the development of depressive-like behavior in mice. These protective effects were accompanied with the preservation of both NAD+ biosynthesis and extracellular ATP level in the mPFC. Furthermore, catalyzing ATP hydrolysis by mPFC injection of the ATPase apyrase negated the prophylactic effects of NMN on CSDS-induced depressive-like behaviors. Prophylactic NMN treatment also prevented the reduction in GABAergic inhibition and the increase in excitability in mPFC neurons projecting to the lateral habenula (LHb). Collectively, these findings demonstrate that the prophylactic effects of NMN on depressive-like behaviors are mediated by preventing extracellular ATP loss in the mPFC, which highlights the potential of NMN supplementation as a novel approach for protecting and preventing stress-induced depression in susceptible individuals.

Rare diseases have various types, low incidence rates, complex conditions, and are often difficult to diagnose. Due to China’s large population, there is a significant number of rare disease patients, but there is a shortage of orphan drugs. Consequently, these patients often find themselves in a situation where necessary medications are either unavailable or unaffordable. To address this urgent clinical need, China has implemented a series of orphan drug policies aimed at improving drug accessibility and affordability. In terms of drug accessibility, companies are encouraged to expedite drug development through the implementation of tax incentives, guidance for clinical research on rare diseases, and the provision of data protection periods of 6 years, along with market exclusivity periods limited to a maximum of 7 years. Moreover, exemptions for clinical trials, acceptance of overseas clinical trial data, and the creation of a list prioritizing clinically urgent new drugs from overseas have been introduced to expedite the drug registration application, review, inspection, and approval processes. In terms of drug affordability, the import value-added tax on rare disease drugs has been reduced by 3%, and various provinces and cities have established a representative rare disease protection model, which includes special funds, medical assistance programs, and serious disease insurance. The national medical insurance catalog has been adjusted to reduce the financial burden on rare disease patients, resulting in an increase in the number of orphan drugs covered by the catalog to 95 as of March 2024. By comparing orphan drug policies in the United States, the European Union, Japan, Australia, and other countries (or regions), we will provide relevant suggestions to further improve orphan drug policies in China, thus bringing more treatment options and hope to patients with rare diseases.

ObjectiveAerobic exercise (AE) interventions are beginning to be used as an emerging adjunctive treatment modality in the treatment of children with Attention Deficit Hyperactivity Disorder (ADHD). However, to date, there is no substantial evidence to support the improved effects of aerobic exercise intervention in children with ADHD aged 6–12 years. This study aims to investigate the effect of aerobic exercise therapy on executive function in children with attention deficit hyperactivity disorder aged 6–12 years.MethodWe conducted a systematic review and meta-analysis using PubMed and Web of Science. The cut-off date was June 1, 2023. The aim was to assess the impact of aerobic exercise interventions on children with ADHD and all randomized controlled trials eligible for aerobic exercise interventions for children with ADHD were included. Nine randomized controlled trials were screened for eligibility for systematic evaluation, and the nine studies were assessed for risk of bias using the PEDro score and the GRADE Quality of Evidence Evaluation System for quality grading of outcome indicators. After testing for heterogeneity, a random-effects model was selected for analysis. Finally, meta-analyses and regression analyses were performed on the core functions (inhibitory control, cognitive flexibility, and working memory) and subgroups of the nine studies on executive function using Revman 5.4 and Stata 16.0.ResultsThe risk of bias evaluation showed a mean PEDro score of 7.78, and of the nine studies, two were rated as having excellent methodological quality, while the remaining seven had a good level of evidence, and the GRADE evidence evaluation showed that the outcome indicators were all of moderate quality. Inhibitory control [SMD = 0.83,95% CI (0.37–1.29), Z = 3.51, p = 0.0005], cognitive flexibility [SMD = 0.65,95% CI (0.37–0.93), Z = 4.58, p

Spaceborne bistatic synthetic aperture radar (BiSAR) employs single-pass cross-track interferometry (XTI) to invert digital elevation models (DEMs) of target areas. However, the accuracy of the inverted DEM is affected by various factors, especially interferometric baseline estimation. To this end, this article proposes an advanced interferometric baseline estimation method (IBEM) for spaceborne BiSAR. First, the IBEM compensates for the time synchronization deviation of BiSAR systems using the pulse exchange phase synchronization method. Subsequently, the time, position, and velocity vectors of satellites are input into a high-precision orbit propagator to derive the state vectors at the imaging time. Leveraging these state vectors, the interferometric baseline is calculated with the main satellite that transmits radar signals as the origin of the coordinate system. Eventually, interferometric baseline estimation and DEM generation are performed based on two sets of data from the LuTan-1 (LT-1) BiSAR system, and the generated DEMs are compared with the external reference DEM to evaluate the performance of the IBEM and the LT-1 system. Results indicate that the proposed IBEM can accurately estimate the interferometric baseline and has extensive application prospects in future spaceborne multibaseline Interferometric SAR missions.

Abstract The scale of propagation of hydraulic fractures in deep shale is closely related to the effect of stimulation. In general, the most common means of revealing hydraulic fracture propagation rules are laboratory hydraulic fracture physical simulation experiments and numerical simulation. However, the former is difficult to meet the real shale reservoir environment, and the latter research focuses mostly on fracturing technology and the interaction mechanism between hydraulic fractures and natural fractures, both of which do not consider the influence of temperature effect on hydraulic fracture propagation. In this paper, the hydraulic fracturing process is divided into two stages (thermal shock and hydraulic fracture propagation). Based on the cohesive zone method, a coupled simulation method for sequential fracturing of deep shale is proposed. The effects of different temperatures, thermal shock rates, and times on the scale of thermal fractures are analyzed. As well as the effects of horizontal stress difference and pumping displacement on the propagation rule of hydraulic fractures. The results show that the temperature difference and the thermal shock times determine the size and density of thermal fractures in the surrounding rock of the borehole, and the number of thermal fractures increases by 96.5% with the increase of temperature difference. Thermal fractures dominate the initiation direction and propagation path of hydraulic fractures. The main hydraulic fracture width can be increased by 150% and the length can be increased by 46.3% by increasing the displacement; the secondary fracture length can be increased by 148.7% by increasing the thermal shock times. This study can provide some inspiration for the development of deep shale by improving the complexity of hydraulic fractures.

Abstract Nowadays a unit quaternion is widely employed to represent the three-dimensional (3D) rotation matrix and then applied to the 3D similarity coordinate transformation. A unit dual quaternion can describe not only the 3D rotation matrix but also the translation vector meanwhile. Thus it is of great potentiality to the 3D coordinate transformation. The paper constructs the 3D similarity coordinate transformation model based on the unit dual quaternion in the sense of errors-in-variables (EIV). By means of linearization by Taylor's formula, Lagrangian extremum principle with constraints, and iterative numerical technique, the Dual Quaternion Algorithm (DQA) of 3D coordinate transformation in weighted total least squares (WTLS) is proposed. The algorithm is capable to not only compute the transformation parameters but also estimate the full precision information of computed parameters. Two numerical experiments involving an actual geodetic datum transformation case and a simulated case from surface fitting are demonstrated. The results indicate that DQA is not sensitive to the initial values of parameters, and obtains the consistent values of transformation parameters with the quaternion algorithm (QA), regardless of the size of the rotation angles and no matter whether the relative errors of coordinates (pseudo-observations) are small or large. Moreover, the DQA is advantageous to the QA. The key advantage is the improvement of estimated precisions of transformation parameters, i.e. the average decrease percent of standard deviations is 18.28%, and biggest decrease percent is 99.36% for the scaled quaternion and translations in the geodetic datum transformation case. Another advantage is the DQA implements the computation and precision estimation of traditional seven transformation parameters (which still are frequent used yet) from dual quaternion, and even could perform the computation and precision estimation of the scaled quaternion. Graphical Abstract

The objective was to evaluate the effectiveness of lactic acid bacteria (LAB) inoculants and chemical additives on the fermentation quality, aerobic stability and in vitro gas production kinetics and digestibility of total mixed ration (TMR) silage. Total mixed ration (568 g/kg dry matter (DM)) was ensiled with six experimental treatments: (1) no additives (control); (2) Lactobacillus buchneri (LB; applied at 1 × 106 cfu/g fresh weight (FW)); (3) Lactobacillus casei (LC; applied at 1 × 106 cfu/g FW); (4) calcium propionate (CAP; applied at 0.5% FW); (5) sodium diacetate (SD; applied at 0.5% FW); (6) potassium sorbate (PS; applied at 0.1% FW). All silos (18 L) were opened for fermentation quality, in vitro gas production kinetics and digestibility analysis after 90 days of ensiling, and then subjected to aerobic stability test for 14 days. All the TMR silage was well-preserved with low pH (4.36 ∼ 4.66) and acceptable levels of butyric acid (1.02 ∼ 2.51 g/kg DM) and ammonia nitrogen (86.3 ∼ 107 g/kg total nitrogen). All the groups were steady during 14 days of aerobic exposure, while SD group was more stable with lower (p

Landslides are the most serious geological disaster in our country, causing economic losses. Because they go undetected, a large number of landslides that have caused disasters are not in the catalogue. At present, Interferometric Synthetic Aperture Radar (InSAR) has been widely used in the identification of landslides. However, it is time-consuming, inefficient, etc., to survey landslides throughout our large country. In the context of massive SAR data, this problem is more obvious. Therefore, based on the current technique of using differential interferogram phase gradient stacking to avoid phase unwrapping errors, a landslide phase gradient dataset has been constructed. To validate the dataset’s effectiveness and applicability, deep learning methods were introduced, applying the dataset to four networks: U-Net, Attention-Unet, Bisenet v2, and Deeplab v3. The results indicate that the phase gradient dataset performs well across different models, with the Attention-Unet network demonstrating the best performance. Specifically, the precision, recall, and accuracy on the test dataset were 0.8771, 0.8712, and 0.9834, respectively, and the accuracy on the validation dataset was 0.8523. Finally, in this paper, the model is applied to landslide identification in Gansu Province, China, during 2022-2023, and a total of 1882 landslides are found. These landslides are mainly concentrated in the south of Gansu Province, where the terrain is relatively undulating. The results show that this method can quickly and accurately realize landslide automatic identification in a wide area and provide technical support for large-scale landslide disaster surveys.

The current work aimed to evaluate the effect of ensiling density on the fermentation quality and aerobic stability of Pennisetum giganteum silages. The silage was ensiled in laboratory silos (1 L), and three treatments were designed according to different ensiling densities: (1) low density (LD, 750 kg/m3); (2) medium density (MD, 900 kg/m3); and (3) high density (HD, 1050 kg/m3). During ensiling, the silage was sampled for a fermentation quality analysis. All silages were well preserved, as indicated by the high lactic acid (LA) content and low pH (3-N) content (68.2 g/kg total nitrogen, TN) among all silages after 45 days of ensiling. The aerobic stability of HD, MD, and LD persisted for 51 h, 54 h, and 48 h, respectively. The NH3-N contents of HD and MD were below 80 g/kg TN during aerobic exposure. These results show that the increase in ensiling density improved the fermentation quality and aerobic stability of Pennisetum giganteum silages.

Objective: Hepatic insulin resistance, which leads to increased hepatic gluconeogenesis, is a major contributor to fasting hyperglycemia in type 2 diabetes mellitus (T2DM). However, the mechanism of impaired insulin-dependent suppression of hepatic gluconeogenesis remains elusive. Delta/Notch-like epidermal growth factor (EGF)-related receptor (DNER), firstly described as a neuron-specific Notch ligand, has been recently identified as a susceptibility gene for T2DM through genome-wide association studies. We herein investigated whether DNER regulates hepatic gluconeogenesis and whether this is mediated by enhanced insulin signaling. Methods: The association between DNER, tribbles homolog 3 (TRB3) and Akt signaling was evaluated in C57BL/6J, ob/ob and db/db mice by western blot analysis. DNER loss-of-function and gain-of-function in hepatic gluconeogenesis were analyzed by western blot analysis, quantitative real-time PCR, glucose uptake and output assay in AML-12 cells and partially validated in primary mouse hepatocytes. Hepatic DNER knockdown mice were generated by tail vein injection of adenovirus to confirm the effects of DNER in vivo. The interaction between DNER and TRB3 was investigated by rescue experiments, cycloheximide chase analysis, co-immunoprecipitation and immunofluorescence. The potential insulin-stimulated phosphorylation sites of DNER were determined by co-immunoprecipitation, LC-MS/MS analysis and site-specific mutagenesis. Results: Here we show that DNER enhanced hepatic insulin signaling in gluconeogenesis by inhibiting TRB3, an endogenous Akt inhibitor, through the ubiquitin-proteasome degradation pathway. In AML-12 hepatocytes, insulin-stimulated activation of Akt and suppression of gluconeogenesis are attenuated by DNER knockdown, but potentiated by DNER over-expression. In C57BL/6J mice, hepatic DNER knockdown is accompanied by impaired glucose and pyruvate tolerance. Furthermore, the in vitro effects of DNER knockdown or over-expression on both Akt activity and hepatic gluconeogenesis can be rescued by TRB3 knockdown or over-expression, respectively. In response to insulin stimulation, DNER interacted directly with insulin receptor and was phosphorylated at Tyr677. This site-specific phosphorylation is essential for DNER to upregulate Akt activity and then downregulate G6Pase and PEPCK expression, by interacting with TRB3 directly and inducing TRB3 proteasome-dependent degradation. Conclusions: Taken together, the crosstalk between insulin-Akt and DNER-TRB3 pathways represents a previously unrecognized mechanism by which insulin regulates hepatic gluconeogenesis.

Since 2019, the Ministry of Natural Resources has comprehensively promoted the research and development of universal equipment and the automatic monitoring and forewarning of geological hazard. As of June 2023, it has been applied to 55 000 potential points of geological hazard in 17 key geological hazard prevention provinces, and the national geological hazard monitoring and forewarning system has entered a rapid development stage. At present, the system receives more than 10 million monitoring data every day, and has made positive progress in massive data storage management, parallel processing of time series data, intelligent analysis of big data and multi-parameter risk early warning. However, there are many challenges in data security of the system, especially in data consistency, data tamper resistance and system reliability. On the basis of systematic research on the characteristics of the blockchain technology and its typical application in related fields, this paper proposes a “trusted data flow” technology based on distributed ledger and consensus mechanism, according to which the overall framework of “blockchain + NRWSL” is formed, and a prototype system is established. The test data show that the improved system can solve the problem of data inconsistency between provinces and Ministry of Natural Resources, identify and prevent illegal data tampering, ensure the stable operation of the system under multi-node failure conditions, and the overall performance loss of the system is less than 20%. The research results provide technical methods for the application of blockchain technology to geological hazard risk early warning systems at all levels in China, and also provide top-level design ideas for improving the security of geological hazard monitoring data and the early warning system.

Abstract Light guide plate (LGP) is a key component of liquid crystal display (LCD) display systems, so its quality directly affects the display effect of LCD. However, LGPs have complex background texture, low contrast, varying defect size and numerous defect types, which makes realizing efficient and accuracy-satisfactory surface defect automatic detection of LGPS still a big challenge. Therefore, combining its optical properties, dot distribution, defect imaging characteristics and detection requirements, a surface defect detection algorithm based on LGP-YOLO for practical industrial applications is proposed in this paper. To enhance the feature extraction ability of the network without dimensionality reduction, expand the effective receptive field and reduce the interference of invalid targets, we built the receptive field module (RFM) by combining the effective channel attention network (ECA-Net) and reviewing large kernel design in CNNs (RepLKNet). For the purpose of optimizing the performance of the network in downstream tasks, enhance the network's expression ability and improve the network’s ability of detecting multi-scale targets, we construct the small detection module (SDM) by combining space-to-depth non-strided convolution (SPDConv) and omini-dimensional dynamic convolution (ODConv). Finally, an LGP defect dataset is constructed using a set of images collected from industrial sites, and a multi-round experiment is carried out to test the proposed method on the LGP detect dataset. The experimental results show that the proposed LGP-YOLO network can achieve high performance, with mAP and F1-score reaching 99.08% and 97.45% respectively, and inference speed reaching 81.15 FPS. This demonstrates that LGP-YOLO can strike a good balance between detection accuracy and inference speed, capable of meeting the requirements of high-precision and high-efficiency LGP defect detection in LGP manufacturing factories.

Abstract Objectives Primary blast lung injury (PBLI) is the main cause of death in blast injury patients, and is often ignored due to the absence of a specific diagnosis. Circular RNAs (circRNAs) are becoming recognized as new regulators of various diseases, but the role of circRNAs in PBLI remain largely unknown. This study aimed to investigate PBLI-related circRNAs and their probable roles as new regulators in PBLI in order to provide new ideas for PBLI diagnosis and treatment. Methods The differentially expressed (DE) circRNA and mRNA profiles were screened by transcriptome high-throughput sequencing and validated by quantitative real-time PCR (qRT-PCR). The GO and KEGG pathway enrichment was used to investigate the potential function of DE mRNAs. The interactions between proteins were analyzed using the STRING database and hub genes were identified using the MCODE plugin. Then, Cytoscape software was used to illustrate the circRNA-miRNA-hub gene network. Results A total of 117 circRNAs and 681 mRNAs were aberrantly expressed in PBLI, including 64 up-regulated and 53 down-regulated circRNAs, and 315 up-regulated and 366 down-regulated mRNAs. GO and KEGG analysis revealed that the DE mRNAs might be involved in the TNF signaling pathway and Fanconi anemia pathway. Hub genes, including Cenpf, Ndc80, Cdk1, Aurkb, Ttk, Aspm, Ccnb1, Kif11, Bub1 and Top2a, were obtained using the MCODE plugin. The network consist of 6 circRNAs (chr18:21008725–21020999 + , chr4:44893533–44895989 + , chr4:56899026–56910247-, chr5:123709382–123719528-, chr9:108528589–108544977 + and chr15:93452117–93465245 +), 7 miRNAs (mmu-miR-3058-5p, mmu-miR-3063-5p, mmu-miR-668-5p, mmu-miR-7038-3p, mmu-miR-761, mmu-miR-7673-5p and mmu-miR-9-5p) and 6 mRNAs (Aspm, Aurkb, Bub1, Cdk1, Cenpf and Top2a). Conclusions This study examined a circRNA-miRNA-hub gene regulatory network associated with PBLI and explored the potential functions of circRNAs in the network for the first time. Six circRNAs in the circRNA-miRNA-hub gene regulatory network, including chr18:21008725–21020999 + , chr4:44893533–44895989 + , chr4:56899026–56910247-, chr5:123709382–123719528-, chr9:108528589–108544977 + and chr15:93452117–93465245 + may play an essential role in PBLI.

Abstract Background The PI3K/AKT pathway transduces the majority of the metabolic actions of insulin. In addition to cytosolic targets, insulin-stimulated phospho-AKT also translocates to mitochondria in the myocardium. Mouse models of diabetes exhibit impaired mitochondrial AKT signaling but the implications of this on cardiac structure and function is unknown. We hypothesized that loss of mitochondrial AKT signaling is a critical step in cardiomyopathy and reduces cardiac oxidative phosphorylation. Methods To focus our investigation on the pathophysiological consequences of this mitochondrial signaling pathway, we generated transgenic mouse models of cardiac-specific, mitochondria-targeting, dominant negative AKT1 (CAMDAKT) and constitutively active AKT1 expression (CAMCAKT). Myocardial structure and function were examined using echocardiography, histology, and biochemical assays. We further investigated the underlying effects of mitochondrial AKT1 on mitochondrial structure and function, its interaction with ATP synthase, and explored in vivo metabolism beyond the heart. Results Upon induction of dominant negative mitochondrial AKT1, CAMDAKT mice developed cardiac fibrosis accompanied by left ventricular hypertrophy and dysfunction. Cardiac mitochondrial oxidative phosphorylation efficiency and ATP content were reduced, mitochondrial cristae structure was lost, and ATP synthase structure was compromised. Conversely, CAMCAKT mice were protected against development of diabetic cardiomyopathy when challenged with a high calorie diet. Activation of mitochondrial AKT1 protected cardiac function and increased fatty acid uptake in myocardium. In addition, total energy expenditure was increased in CAMCAKT mice, accompanied by reduced adiposity and reduced development of fatty liver. Conclusion CAMDAKT mice modeled the effects of impaired mitochondrial signaling which occurs in the diabetic myocardium. Disruption of this pathway is a key step in the development of cardiomyopathy. Activation of mitochondrial AKT1 in CAMCAKT had a protective role against diabetic cardiomyopathy as well as improved metabolism beyond the heart.

An algorithm, named long short-term memory (LSTM)-logistic chaos mapping chicken swarm algorithm (LCCSA), is proposed for initializing the weights and thresholds of LSTM neural networks using the Logistic chaotic mapping chicken swarm algorithm (CSA). This algorithm aims to improve mid- to long-term runoff sequence prediction in river basins. In this model, the logistic chaotic mapping method is used to initialize the chicken swarm, and LCCSA is employed to pre-train the weights and thresholds of each layer of LSTM 50 times, using the training results' initial weights of LSTM to enhance convergence accuracy and speed. Taking the Manas river and Kuitun river, two typical basins in northern Xinjiang, China, as the research objects, LSTM-LCCSA was used to forecast the mean monthly runoff in the mid- to long-term under different lag time series by using the runoff evolution data within a certain period. The example using the basin located in northern Xinjiang demonstrates the effectiveness, stability, and generality of the LSTM-LCCSA method in mid- to long-term prediction of average monthly runoff, and the prediction accuracy and universality of LSTM-LCCSA are better than other data-driven models. HIGHLIGHTS Proposed an LSTM-LCCSA algorithm to address mid- to long-term runoff sequence prediction in river basins.; Initialization of the chicken swarm using a logistic chaotic mapping method improved population diversity and avoided CSA falling into a local extreme value.; The intercomparison of data-driven models (CM-SVM, GA-SAA, MRA, GA-FFNN) with respect to prediction accuracy and stability.;

Macrophages, as important immune cells of the organism, are involved in maintaining intrahepatic microenvironmental homeostasis and can undergo rapid phenotypic changes in the injured or recovering liver. In recent years, the crucial role of macrophage-programmed cell death in the development and regression of liver diseases has become a research hotspot. Moreover, macrophage-targeted therapeutic strategies are emerging in both preclinical and clinical studies. Given the macrophages’ vital role in complex organismal environments, there is tremendous academic interest in developing novel therapeutic strategies that target these cells. This review provides an overview of the characteristics and interactions between macrophage polarization, programmed cell death, related biomarkers, and macrophage-targeted therapies. It aims to deepen the understanding of macrophage immunomodulation and molecular mechanisms and to provide a basis for the treatment of macrophage-associated liver diseases.

Reservoir water fluctuation can often trigger deformation and failure of reservoir bank landslides. This study focuses on the Hongyanzi landslide in the Pubugou hydropower Station of the Dadu River to investigate the deformation characteristics and deformation mechanisms of the reservoir bank landslides. Through detailed surface macro deformation surveys, monitoring data analysis, and GeoStudio numerical simulation, the deformation characteristics, seepage field, stability and the influence of reservoir water on landslide were studied in depth. The research revealed significant macro deformation of the Hongyanzi landslide surface, with a cumulative displacement curve exhibiting a “step-like” characteristic. The primary inducing factor of landslide deformation was found to be the decrease in the reservoir water level. When the reservoir water level dropped from 850 m to below 830 m, the displacement step was triggered, and the cumulative deformation of the “step” segment accounted for over 90% of the total annual deformation. Accelerated deformation of the landslide occurred when the rate of the reservoir water level decline was greater than 0.5 m/d. The landslide deformation mode was identified as creep slip-tensile cracking, with the rise and fall of the reservoir water level significantly impacting the internal permeability of the sliding body and causing a large impact on the landslide’s stability, leading to the “step-like” deformation of the landslide.

Abstract Background Soybean is one of the most important oil crops in the world. The domestication of wild soybean has resulted in significant changes in the seed oil content and seed size of cultivated soybeans. To better understand the molecular mechanisms of seed formation and oil content accumulation, WDD01514 (E1), ZYD00463 (E2), and two extreme progenies (E23 and E171) derived from RILs were used for weighted gene coexpression network analysis (WGCNA) combined with transcriptome analysis. Results In this study, both seed weight and oil content in E1 and E171 were significantly higher than those in E2 and E23, and 20 DAF and 30 DAF may be key stages of soybean seed oil content accumulation and weight increase. Pathways such as “Photosynthesis”, “Carbon metabolism”, and “Fatty acid metabolism”, were involved in oil content accumulation and grain formation between wild and cultivated soybeans at 20 and 30 DAF according to RNA-seq analysis. A total of 121 oil content accumulation and 189 seed formation candidate genes were screened from differentially expressed genes. WGCNA identified six modules related to seed oil content and seed weight, and 76 candidate genes were screened from modules and network. Among them, 16 genes were used for qRT-PCR and tissue specific expression pattern analysis, and their expression-levels in 33-wild and 23-cultivated soybean varieties were subjected to correlation analysis; some key genes were verified as likely to be involved in oil content accumulation and grain formation. Conclusions Overall, these results contribute to an understanding of seed lipid metabolism and seed size during seed development, and identify potential functional genes for improving soybean yield and seed oil quantity.

Abstract Background Amputation is a serious complication of acute compartment syndrome (ACS), and predicting the risk factors associated with amputation remains a challenge for surgeons. The aim of this study was to analyze the risk factors for amputation in patients with ACS and develop a nomogram to predict amputation risk more accurately. Methods The study population consisted of 143 patients (32 in the amputation group and 111 in the limb preservation group) diagnosed with ACS. LASSO and multivariate logistic regression were used to screen predictors and create a nomogram. The model’s accuracy was assessed by receiver operating characteristic (ROC) curves, C-index, calibration curves, and decision curve analysis (DCA). Results The predictors included cause of injury, vascular damage, shock, and fibrinogen in the nomogram. The C-index of the model was 0.872 (95% confidence interval: 0.854–0.962), and the C-index calculated by internal validation was 0.838. The nomogram’s area under the curve (AUC) was 0.849, and the calibration curve demonstrated a high degree of agreement between the nomogram’s predictions and actual observations. Additionally, the DCA indicated good clinical utility for the nomogram. Conclusion The risk of amputation in ACS patients is associated with the cause of injury, vascular damage, shock, and fibrinogen. Our nomogram integrating clinical factors and biochemical blood markers enables doctors to more conveniently predict the risk of amputation in patients with ACS.

Abstract Background The purpose of this research is to study the contribution of epiphytic microbiota in fresh oat (OT), Italian ryegrass (IR) and whole-crop maize (MZ) to silage fermentation products and bacterial community structure of MZ. After γ-ray irradiation, the sterile MZ was treated via microbiota transplantation method: (1) sterile deionized water (STMZ); (2) microbiota epiphytic on MZ (MZMZ); (3) microbiota epiphytic on OT (MZOT); (4) microbiota epiphytic on IR (MZIR). Triplicate silos of each treatment were tested after 1, 3, 7, 15, 30 and 60 days of ensiling. Results MZMZ had higher (P

Abstract Background Angiosarcoma of the breast is a rare malignancy. There are little data evaluating the survival and estimating the prognostic factors. The best surgical management and the role of systemic adjuvant therapy remain ill‐defined. This study aimed to investigate the clinicopathological features, survival, and prognostic factors of breast angiosarcoma. Methods The data on patients diagnosed with breast angiosarcoma were extracted from the Surveillance, Epidemiology, and End Results database (1975–2016). Univariate and multivariate Cox regression analyses were used to estimate the influential prognostic factors. The overall survival (OS) and disease‐specific survival (DSS) of patients with breast angiosarcoma were evaluated. Results This study included 656 patients diagnosed with breast angiosarcoma between 1975 and 2016. The 5‐year OS rate of all patients was 44.9% (95% CI 40.8–49.0). In both OS and DSS, Kaplan–Meier survival analyses revealed significant differences for both OS and DSS according to age, year at diagnosis, laterality, grade, and stage (all log‐rank p

Objectives: To summarize current evidence about the influence of body composition on the prognosis of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) treatment. Methods: Public databases were systematically searched to identify relevant studies published from the inception of the database up to May 2023. Studies that evaluated the association between body composition and clinical outcomes in HCC patients who underwent TACE were included. A pre-designed table was applied to summarize relevant information. Meta-analysis was performed to estimate the association of body composition with overall survival. Results: Fourteen studies were included in this review, including 3631 patients (sample size range: 56–908, median 186). All body composition measurements (including skeletal muscle area, visceral and subcutaneous adipose area, and bone mineral density) were based on computer tomography. The commonly used parameter was skeletal muscle index at 3rd lumbar vertebra level (8/14). Three studies evaluated the correlations of body composition changes with the prognosis after TACE. Most studies (12/14) identified body composition parameters as an independent indicator for overall survival, progression-free survival, and treatment response rate. The hazard ratio of different body composition parameters ranged from 1.01 to 2.88, and hazard ratio of body composition changes ranged from 1.88 to 5.93. The pooled hazard ratio of sarcopenia for overall survival was 1.38 (95 %CI: 1.20–1.58). Conclusions: Body composition seems to be an important prognostic factor for a poorer clinical outcome after TACE treatment in patients with hepatocellular carcinoma. Future prospective studies with a larger sample size are required to confirm these findings. Registration study: This study has been prospectively registered at the PROSPERO platform (https://www.crd.york.ac.uk/prospero/) with the registration No. CRD42022345602.

BackgroundBreast cancer (BC) diagnosis and treatment rely heavily on molecular markers such as HER2, Ki67, PR, and ER. Currently, these markers are identified by invasive methods.ObjectiveThis meta-analysis investigates the diagnostic accuracy of ultrasound-based radiomics as a novel approach to predicting these markers.MethodsA comprehensive search of PubMed, EMBASE, and Web of Science databases was conducted to identify studies evaluating ultrasound-based radiomics in BC. Inclusion criteria encompassed research on HER2, Ki67, PR, and ER as key molecular markers. Quality assessment using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS) was performed. The data extraction step was performed systematically.ResultsOur meta-analysis quantifies the diagnostic accuracy of ultrasound-based radiomics with a sensitivity and specificity of 0.76 and 0.78 for predicting HER2, 0.80, and 0.76 for Ki67 biomarkers. Studies did not provide sufficient data for quantitative PR and ER prediction analysis. The overall quality of studies based on the RQS tool was moderate. The QUADAS-2 evaluation showed that the studies had an unclear risk of bias regarding the flow and timing domain.ConclusionOur analysis indicated that AI models have a promising accuracy for predicting key molecular biomarkers' status in BC patients. We performed the quantitative analysis for HER2 and Ki67 biomarkers which yielded a moderate to high accuracy. However, studies did not provide adequate data for meta-analysis of ER and PR prediction accuracy of developed models. The overall quality of the studies was acceptable. In future research, studies need to report the results thoroughly. Also, we suggest more prospective studies from different centers.

Background With the establishment of the cardiac-gut axis concept, increasing evidence has suggested the involvement and important regulatory role of the gut microbiota (GM) and short chain fatty acid (SCFA) in cardiovascular diseases. However, the relationship between GM and atrial fibrillation (AF) is still poorly understood. Objectives The aim of this study was to investigate whether there were differences in GM and SCFA between AF patients and healthy controls. Methods In this study, we enrolled 30 hospitalized patients with AF and 30 matched patients with sinus rhythm (SR). GM species in fecal samples were evaluated through amplicon sequencing targeting the 16Sribosomal RNA gene. The feces SCFAs were describe step by step the quantitative analysis using gas chromatography-mass spectrometry (GC-MS). GM species richness, diversity, differential abundance of individual taxa between AF and SR were analyzed. Results AF patients showed decreased species richness and α-diversity compared to SR patients, but there was no statistical difference. The phylogenetic diversity was significant decreased in AF group. The β-diversity indexes revealed significant differences in GM community structure between the AF group and the SR group. After investigated the individual taxa, AF group showed altered relative abundance in several taxa compared to the SR group. linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed, a significant decrease in Bifidobacterium and a greater abundance of Lactobacillus, Fusobacterium, Haemophilus in AF group compared with the SR group. The abundance of haemophilus was negative correlated with isovaleric acid and isobutyric acid. Conclusions In AF patients, the GM phylogenetic diversity and β-diversity decreased, the relative abundance altered in several taxa and the bacterial community structure changed as well as the SCFA level. GM and SCFA dysbiosis might play a crucial part in the occurrence and development of AF.

Abstract Background Italian ryegrass is a temperate climate crop, which is widely cultivated in the winter fallow paddy fields of subtropical China. The utilization efficiency of Italian ryegrass depends greatly on its growth stage at harvest. Previous studies have reported the optimum stage for harvesting various forage to balance their quality and quantity. However, when considering the practice condition, such as rainy or unavailability of harvest equipment, the harvest stage of forage cannot always be implemented according to the production schedules. Thus, to characterize the effect of growth stage on the silage fermentation profile, bacterial community construction and metabolisms of carbohydrates and amino acids, Italian ryegrass were naturally ensiled at the filling stage (FSN) and the dough stage (DSN), respectively. After ensiling for 1, 3, 7, 15, 30, and 60 days, triplicate silos were opened for sampling. Results The growth of Italian ryegrass increased the pH, dry matter, neutral, and acid detergent fiber contents, but decreased buffering capacity, crude protein and water-soluble carbohydrates contents, and the epiphytic microbiota of Italian ryegrass harvested at the filling stage was simpler than that harvested at the dough stage. During ensiling, FSN had lower pH and higher organic acid content than DSN. The bacterial succession rate in FSN was also faster than DSN, which showed that Lactobacillus becomes the dominant genus in the early stage of ensiling. The predicted metabolisms revealed that carbohydrate and amino acid metabolisms were the two main metabolisms in silage fermentation. When compared with epiphytic microbiota, ensiling enhanced carbohydrate metabolism and diminished amino acid metabolism. The difference of these two metabolisms between FSN and DSN was obvious at the early stage of ensiling. Conclusions Growth stage affected the chemical and microbial composition of Italian ryegrass, so as to the fermentation profile, bacterial community and its metabolisms intensity. Italian ryegrass harvested at the filling stage was prone to ferment. The complexity of epiphytic microbiota made Italian ryegrass harvested at the dough stage more difficult to ferment. Graphical Abstract

This study aims to accurately determine the distribution of landslides in the complex terrain of Jiangdingya, Nanyu Township, Zhouqu County, Gansu Province. The digital orthophoto map (DOM) and digital elevation model (DEM) are used to accurately identify landslide areas and analyze associated data. Based on image-based supervised classification, the influence factor constraint analysis is used to further identify and delineate the landslide area. Three mathematical morphology operations—erosion, dilation, and opening—are then applied to automatically identify and extract landslides. Experimental results demonstrate that achieving an accuracy, precision, and recall of 98.02%, 85.24%, and 84.78% shows that it is possible to better avoid interference caused by complex terrain with rich features. High-resolution DEM and DOM data contain rich spectral and texture information. These data can accurately depict geomorphic features of complex terrain and aid in identifying landslide-prone areas when combined with mathematical morphology processing. This contribution is important for identifying landslides in complex terrain and emergency disaster management.

Tumushuke, a significant node of “the China–Pakistan Economic Corridor” and “the Silk Road Economic Belt”, is strategically located in the southern region of Xinjiang. Due to the widespread distribution of its salty soils, concrete construction safety is significantly compromised. The construction of this project used sulfate-resistant cement, which was costly to construct. Six groups with varying sulfate immersion concentrations were set up to perform sulfate erosion tests and sulfate freeze–thaw coupling tests, respectively, based on the survey of the distribution of sulfate concentration in the area. The Tumushuke area’s concrete erosion kinds were classified using a microanalysis of the degraded concrete. The findings indicate that the concrete primarily exhibits gypsum-type erosion when the sulfate concentration is greater than 20,000 mg/kg, ettringite–gypsum-type erosion when the sulfate concentration is between 15,000 and 20,000 mg/kg, and ettringite-gypsum-type erosion when the sulfate concentration is less than 15,000 mg/kg. The erosion product, carbon–sulfur silica-calcite, also occurs under sulfate freeze–thaw coupling. In the Tumushuke area, ettringite-type erosion damage is primarily found in low-sulfate areas in the southwest and a small portion of the northeast. In contrast, higher-sulfate areas in the central northward area are primarily affected by ettringite–gypsum and gypsum-type erosion damage. The results of this study can provide a basis for adopting different anti-sulfate erosion measures for engineering construction in different regions.

BackgroundWith the increasing focus on addressing the challenges of aging, researchers have begun to recognize the potential impact of empowering older individuals in addressing retirement issues. However, within different cultural contexts, there still needs to be a more precise analysis regarding the definition of empowering older individuals.ObjectiveTo define and analyze the concept of empowering older individuals within the cultural context of China.MethodUsing Rodgers’ concept analysis approach, a search was conducted in five databases (PubMed, Web of Science, China National Knowledge Infrastructure, Wan fang Data, and VIP Chinese Journal Platform) for studies on empowering older individuals from the time the databases were established until February 2023. The main disciplines involved in the search included nursing, medicine, and public health.ResultsOut of the 7,028 studies, 50 articles met the inclusion criteria. The identified attributes are as follows: support system, belief change, and behavioral autonomy. The antecedents were grouped into four categories: physical obstacles, psychological concerns, personal needs and external challenges. The consequences were determined to be improved quality of life, reduced burden of old-age care, gain respect, and self-actualization.ConclusionEmpowering older individuals is a dynamic and evolving concept that involves aligning personal aspirations with appropriate external resources and expressing a certain degree of belief and behavioral change. This study deepens our understanding of empowering older individuals through comprehensive concept analysis, and the identified attributes, antecedents, and consequences of empowering older individuals can be utilized in practice, education, and research.

Background Over 70% of the patients with hepatocellular carcinoma (HCC) are diagnosed at an advanced stage and lose the opportunity for radical surgery. Combination therapy of tyrosine kinase inhibitors (TKIs) and anti-programmed cell death protein-1 (PD-1) antibodies has achieved a high tumor response rate in both the first-line and second-line treatment of advanced HCC. However, few studies have prospectively evaluated whether TKIs plus anti-PD-1 antibodies could convert unresectable intermediate-advanced HCC into resectable disease.Methods This single-arm, phase II study enrolled systemic therapy-naïve adult patients with unresectable Barcelona Clinic Liver Cancer stage B or C HCC. Patients received oral lenvatinib one time per day plus intravenous anti-PD-1 agents every 3 weeks (one cycle). Tumor response and resectability were evaluated before the fourth cycle, then every two cycles. The primary endpoint was conversion success rate by investigator assessment. Secondary endpoints included objective response rate (ORR) by independent imaging review (IIR) assessment per modified RECIST (mRECIST) and Response Evaluation Criteria in Solid Tumors, V.1.1 (RECIST 1.1), progression-free survival (PFS) and 12-month recurrence-free survival (RFS) rate by IIR per mRECIST, R0 resection rate, overall survival (OS), and safety. Biomarkers were assessed as exploratory objectives.Results Of the 56 eligible patients enrolled, 53 (94.6%) had macrovascular invasion, and 16 (28.6%) had extrahepatic metastasis. The median follow-up was 23.5 months. The primary endpoint showed a conversion success rate of 55.4% (31/56). ORR was 53.6% per mRECIST and 44.6% per RECIST 1.1. Median PFS was 8.9 months, and median OS was 23.9 months. Among the 31 successful conversion patients, 21 underwent surgery with an R0 resection rate of 85.7%, a pathological complete response rate of 38.1%, and a 12-month RFS rate of 47.6%. Grade ≥3 treatment-related adverse events were observed in 42.9% of patients. Tumor immune microenvironment analysis of pretreatment samples displayed significant enrichment of CD8+ T cells (p=0.03) in responders versus non-responders.Conclusion Lenvatinib plus anti-PD-1 antibodies demonstrate promising efficacy and tolerable safety as conversion therapy in unresectable HCC. Pre-existing CD8+ cells are identified as a promising biomarker for response to this regimen.Trial registration number Chinese Clinical Trial Registry, ChiCTR1900023914.

Abstract Background and objective The recurrence occurs within 5 years in up to 70% of hepatocellular carcinoma (HCC) patients who received radical liver resection, and most patients are no longer suitable for repeat surgery. There are limited treatment options for unresectable recurrent HCC. This study aimed to explore the potential efficacy of treatment based on TKIs in combination with PD-1 inhibitors for unresectable recurrent HCC. Methods Forty-four patients with unresectable recurrent HCC after radical surgery between January 2017 and November 2022 were retrospectively collected and screened. All patients received the combination therapy of tyrosine kinase inhibitors (TKIs) and programmed cell death protein 1 (PD-1) inhibitors, and 18 of these patients received trans-arterial chemoembolization (TACE) or TACE combined with radiofrequency ablation (RFA). Two patients who received TKIs in combination with PD-1 inhibitors eventually obtained repeat surgery, with one patient undergoing a repeat hepatectomy and one patient receiving a liver transplant. Results The median survival for these patients was 27.0 months (95% confidence interval [CI] 21.2, 32.8), with a 1-year overall survival (OS) rate of 83.6% (95% CI 77.9%, 89.3%). Median progression-free survival (PFS) was 15.0 months (95.0% CI 12.1, 17.9), with a 1-year PFS rate of 77.0% (95% CI 70.6%, 83.4%). The two patients who underwent repeat surgery had a survival time of 34 and 37 months after the combined treatment with no recurrence, respectively, as of November 2022. Conclusion The combination of TKIs and PD-1 inhibitors for unresectable recurrent HCC is effective and can prolong the survival of patients in this group.

In this paper, a high-precision hot-pressed light guide plate defect detection model based on improved YOLOv7 is proposed. The model strengthens the spatial correlation between background and foreground by fusing global context information. A densely connected convolutional network is used to enhance the feature extraction capability and mitigate problems such as gradient vanishing while ensuring the maximum information flow in the network. Further, adaptive spatial feature fusion is used in the feature fusion structure of the model; the adaptive spatial feature fusion structure compensates for the small targets that are difficult to extract in high dimensions from low dimensions, thus solving the problem of detecting small targets that are easy to lose. Finally, a self-constructed dataset is built using images of hot-pressed light guide plates collected from industrial sites, and a large number of experiments are conducted. Experimental results show that the defect detection model has a mean average precision (mAP) of 99.1% and a detection speed of 127 FPS. Compared with the mainstream surface defect target detection algorithms, while ensuring the detection speed, the accuracy rate has been significantly improved, and the accuracy rate and real-time can meet the requirements of the industrial field inspection of hot-pressed light guide plate.

Abstract Background Early diagnosis of lung adenocarcinoma (LUAD), one of the most common types of lung cancer, is very important to improve the prognosis of patients. The current methods can’t meet the requirements of early diagnosis. There is a pressing need to identify novel diagnostic biomarkers. Secretory proteins are the richest source for biomarker research. This study aimed to identify candidate secretory protein biomarkers for early diagnosis of LUAD by integrated bioinformatics analysis and clinical validation. Methods Differentially expressed genes (DEGs) of GSE31210, gene expression data of early stage of LUAD, were analyzed by GEO2R. Upregulated DEGs predicted to encode secreted proteins were obtained by taking the intersection of the DEGs list with the list of genes encoding secreted proteins predicted by the majority decision-based method (MDSEC). The expressions of the identified secreted proteins in the lung tissues of early-stage LUAD patients were further compared with the healthy control group in mRNA and protein levels by using the UALCAN database (TCGA and CPTAC). The selected proteins expressed in plasma were further validated by using Luminex technology. The diagnostic value of the screened proteins was evaluated by receiver operating characteristic (ROC) analysis. Cell counting kit-8 assay was carried out to investigate the proliferative effects of these screened proteins. Results A total of 2183 DEGs, including 1240 downregulated genes and 943 upregulated genes, were identified in the GSE31210. Of the upregulated genes, 199 genes were predicted to encode secreted proteins. After analysis using the UALCAN database, 16 molecules were selected for further clinical validation. Plasma concentrations of three proteins, Midkine (MDK), WAP four-disulfide core domain 2 (WFDC2), and C-X-C motif chemokine ligand 14 (CXCL14), were significantly higher in LUAD patients than in healthy donors. The area under the curve values was 0.944, 0.881, and 0.809 for MDK, WFDC2, and CXCL14, 0.962 when combined them. Overexpression of the three proteins enhanced the proliferation activity of A549 cells. Conclusions MDK, WFDC2, and CXCL14 were identified as candidate diagnostic biomarkers for early-stage LUAD and might also play vital roles in tumorigenesis.

Abstract Background This study evaluated the effects of growth stage and storage time on fermentation characteristics, bacterial communities and their functionality in alfalfa (Medicago sativa L.) silage. Alfalfa was harvested at initial flowering (10–20% bloom, AL1) and full flowering (> 80% bloom, AL2) stages, respectively. The harvested alfalfa was ensiled in 15 L plastic silos. Triplicate silos were sampled after 1, 3, 7, 15, 30 and 60 days of ensiling, respectively. Fermentation products were analyzed on each sampling day. The bacterial communities and their functional potential after 3 and 60 days were analyzed by high-throughput sequencing technique and PICRUSt2 method. Results AL2 had better fermentation quality than AL1 with lower pH, ammonia nitrogen and butyric acid concentrations and higher lactic acid concentrations on day 60. AL2 had higher abundances of Weissella and Lactobacillus after 3 days, and lower abundances of Enterobacter and Enterobacteriaceae on day 60 compared to AL1. In metabolic pathway analysis, ensiling promoted the carbohydrate and amino acid metabolism, and inhibited the signal transduction and membrane transport. In enzyme analysis, AL2 had lower abundances of nitrite reductase (NADH) and ornithine decarboxylase than AL1 on day 60. In phenotype analysis, AL2 had higher proportions of facultatively anaerobic and lower proportions of anaerobic, potentially pathogenic and gram negative than AL1 on day 60. Conclusions High throughput sequencing technique combined with PICRUSt2 can be successfully used to describe the changes of bacterial communities and their functionality in silage. This approach can improve our understanding of the silage microbiology to further regulate the fermentation products. Graphical Abstract