Search

The adiabatic shear band is a common dynamic failure mechanism in metal materials at high strain rates. In this work, a new approach was proposed to improve mechanical properties and inhibit the formation and propagation of the adiabatic shear band in the pure Mo single crystal. The microstructure evolution of the pure Mo and Mo-Nb single crystals subjected to the dynamic load was investigated by EBSD and TEM. At a strain rate of 2500 s−1, the developed adiabatic shear band was totally distributed in the pure Mo single crystal, and the slip is the main deformation mechanism. A thinner adiabatic shear band was distributed in the Mo-3Nb single crystal accompanied by a few bands of deformation twins and then disappeared in the Mo-6Nb single crystal, replaced by the {112} deformation twinning. At high strain rates, the dynamic deformation mechanism of the Mo single crystal is sensitive to the Nb element, which attributes to the reduction of the generalized stacking fault energy.

This study examines the hot deformation behavior of Mo-14Re alloy at various true strains (15%, 35%, 65%) and strain rates (0.01 s−1, 10 s−1) at a temperature of 1400K. The findings indicate that dynamic recovery (DRV) and dynamic recrystallization (DRX) occur concomitantly as strain increases at a low strain rate of 0.01 s−1, with DRV being the predominant softening mechanism. At a strain of 65%, DRX emerges as the primary softening process. Conversely, under high strain rates of 10 s−1, DRX is inhibited, and the Mo-14Re alloy experiences work hardening due to an increase in dislocation density. Microscopic analysis shows that the high-density dislocations facilitate the continued nucleation and growth of recrystallized grains at low strain rates. At high strain rates, tangled dislocations hinder dislocation motion and recrystallization. Regarding texture evolution, stronger {100}//CD and weaker {111}//CD fiber texture is observed at low strain rates of 0.01 s−1, while stronger {111}//CD and weaker {100}//CD fiber texture forms at high strain rates of 10 s−1, with enhanced texture intensity. Mechanistic analysis confirms the activation of the {110}, {112}, and {123} dislocation slip systems at elevated temperatures, with the {123} system being the most dominant.

Abstract The optimal surgical approach for elderly patients with early-stage non-small cell lung cancer (NSCLC) remains a topic of debate. A retrospective analysis was conducted on patients who underwent pulmonary resection for early-stage NSCLC at our single institution between January 2018 and December 2022. Propensity score matching was used to balance baseline characteristics between the sublobar resection and lobectomy groups. Perioperative outcomes, pulmonary function recovery, postoperative quality of life, and survival were compared between the two groups. A total of 151 patients were included, with 42 undergoing sublobar resection and 109 undergoing lobectomy. After propensity score matching, baseline characteristics were well-balanced between the two groups. Sublobar resection was associated with shorter operative time (125.83 ± 33.56 min vs. 161.14 ± 61.54 min, p = 0.048), less intraoperative blood loss [65 (30, 75) ml vs. 120 (70, 170) ml, p

Flexible bending sensors have emerged as a technology with significant potential for a wide range of applications, including human-machine interaction, healthcare monitoring, and soft robotics. This paper provides a comprehensive review of the working principles, performance evaluation, application areas, and future trends of flexible bending sensors. The challenges faced by these sensors, such as anti-interference, adaptive detection, and multidirectional sensing, are discussed, along with potential solutions and future developmental directions. The paper highlights the importance of materials development, structural design, and manufacturing processes in advancing flexible bending sensor technology. Overall, this review aims to provide valuable insights and guidance for further research and development in the field of flexible bending sensors.

Abstract Stroke is a major cause of death and disability among adults in China, and an efficient rehabilitation strategy has been an urgent demand for post-stroke rehabilitation. The non-invasive brain stimulation (NBS) can modulate the excitability of the cerebral cortex and provide after-effects apart from immediate effects to regain extremity motor functions, whereas robotic therapy provides high-intensity and long-duration repetitive movements to stimulate the cerebral cortex backward. The combined strategy of the two techniques is widely regarded as a promising application for stroke patients with dyskinesia. Transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (TES) are important methods of NBS. Their recovery principles, stimulation parameters, and clinical applications have been summarized. The combined treatments of rTMS/tDCS and robotic therapy are analyzed and discussed to overcome the application barriers of the two techniques. The future development trend and the key technical problems are expounded for the clinical applications.

Abstract The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny .

Abstract Transition metal chalcogenides have been identified as low-cost and efficient electrocatalysts to promote the hydrogen evolution reaction in alkaline media. However, the identification of active sites and the underlying catalytic mechanism remain elusive. In this work, we employ operando X-ray absorption spectroscopy and near-ambient pressure X-ray photoelectron spectroscopy to elucidate that NiS undergoes an in-situ phase transition to an intimately mixed phase of Ni3S2 and NiO, generating highly active synergistic dual sites at the Ni3S2/NiO interface. The interfacial Ni is the active site for water dissociation and OH* adsorption while the interfacial S acts as the active site for H* adsorption and H2 evolution. Accordingly, the in-situ formation of Ni3S2/NiO interfaces enables NiS electrocatalysts to achieve an overpotential of only 95 ± 8 mV at a current density of 10 mA cm−2. Our work highlighted that the chemistry of transition metal chalcogenides is highly dynamic, and a careful control of the working conditions may lead to the in-situ formation of catalytic species that boost their catalytic performance.

Abstract The PICALM::MLLT10 fusion gene is a rare but recurrent event in acute leukemia (AL) associated with poor prognosis. It is still confused whether PICALM::MLLT10 can solely correspond to acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) or acute leukemias of ambiguous lineage (ALAL). Here, we reported a series of PICALM::MLLT10 positive AL patients with miscellaneous immunophenotype including T‐ALL, ALAL, AML, and B‐ALL, complex karyotype, half of extramedullary disease (EMD), frequently concomitant PHF6 mutation, and poor initial treatment response to standard chemotherapy aiming to different immunophenotype, but showing sensitivity to combining chemotherapy especially integrated with venetoclax, suggesting this fusion gene may indicate a new subgroup of AL. Eighteen PICALM::MLLT10 positive patients of 533 AL patients (18/533, 3.4%) were identified by RNA sequencing in our center. We found PICALM::MLLT10 positive AL showing miscellaneous immunophenotype, higher expression of leukemic stemness genes and lower expression of biomarkers of venetoclax resistance, more extramedullary involvement, and especially poor response to conventional induction chemotherapy, but may benefit from venetoclax as well as low‐dose Ara‐C, granulocyte colony‐stimulating factor (G‐CSF), and anthracyclines combination chemotherapy. Sequential hematopoietic stem cell transplantation (HSCT) after chemotherapy combined with venetoclax may further improve long‐term survival in AL patients with complete remission (CR) even measurable residual disease (MRD) positive.

Carboxylesterases (CXE, EC 3.1.1.1), a class of hydrolases with an α/β folding domain, play important roles in plant growth and development and stress response. Here, we identified 32, 63, 41, and 45 CXE genes in Oryza sativa Japonica (Nipponbare), Oryza sativa Indica (93-11), Oryza sativa Indica (Xian-1B1 var.IR64), and Oryza sativa Japonica (Geng-sbtrp var.ChaoMeo), respectively. Then, we analyzed the chromosomal location, physical and chemical properties, subcellular localization, collinearity, and selection pressure of CXE genes in four rice varieties. We also analyzed the functional interaction network, cis-regulatory elements, evolutionary relationship, and protein tertiary structure, and performed gene expression profiling and qPCR verification under abiotic stress, as well as diversity analysis of 3010 gene-CDS-haplotype (gcHap) rice samples, aiming to understand the potential function of the 32 OsCXE genes. Our results indicated that fragment replication is the main reason for amplification of the CXE gene family in rice, and the gene family has undergone strong purification selection. OsCXE3.1, OsCXE3.2, OsCXE3.3, OsCXE5.1, and OsCXE7.3 may be used to improve the tolerance of rice to abiotic stress. OsCXE play important roles in rice population differentiation and improvement, and the major gcHaps at most OsCXE locus are significantly associated with yield traits. Therefore, natural variations of most OsCXE locus have great potential value for improvement of rice productivity.

Abstract Textures in molybdenum‐rhenium (Mo‐Re) alloys are inevitable during thermal fabrication. [110] and [100] are common orientations in Mo‐Re alloys and effect mechanical responses. However, orientation dependence of mechanical responses in Mo‐Re alloys is not quite clear yet. To clarity this problem, micro‐pillar compression tests are conducted in grains with orientation [100] and [110] separately. Orientation‐dependent compressive properties are found in Mo‐14Re and Mo‐42Re (wt.%), but are not found in Mo and Mo‐5Re, which may be attributed to activated multi‐slip planes as increased Re. Solid solution effect of Re not only relies on orientations, but also on Re contents. Softening effect occurs in both [100] and [110] Mo‐5Re. while, strong strengthening effect happens in [110] Mo‐14Re and Mo‐42Re. Our research clarifies that Mo‐Re alloys with [110] orientation/texture could be preferred to obtain good strengthening effect.

Sleep’s crucial role in memory consolidation is well-established, with neuroimaging and sleep stage analysis revealing the intricate processes involved. Sleep deprivation significantly impairs memory performance and the ability to form new memories, highlighting the need for effective countermeasures. This article concludes that while sleep deprivation significantly impairs memory, the emerging insights into the gut-brain axis offer a promising frontier for developing novel interventions that can mitigate these effects. The review discusses various interventions, ranging from pharmaceutical compounds like donepezil, memantine, and tolcapone, to innovative physical therapy techniques such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and transcranial direct current stimulation (tDCS). Additionally, the emerging role of the gut-brain axis in sleep deprivation-induced memory impairment is examined, shedding light on the complex interplay between gut microbiota and cognitive functions. This comprehensive review explores the multifaceted relationship between sleep deprivation and memory impairment, delving into the neurobiological mechanisms underlying these processes and examining potential interventions.

The interaction between organic phosphorus (OP) and iron oxide significantly influences the phosphorus cycle in the natural environment. In shallow lakes, intense oxidation-reduction fluctuations constantly alter the existing form of iron oxides, but little is known about their impact on the adsorption and fractionation of OP molecules. In this study, electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR MS) was used to investigate the fractionation of OP from alkali-extracted sediment induced by crystalline goethite and amorphous ferrihydrite adsorption at a molecular scale. The results showed that ferrihydrite and goethite both exhibited high OP adsorption, and the adsorption amount decreased as the pH increased. The adsorption kinetics matched the pseudo-second-order equation. The ESI-FT-ICR MS analysis showed that 91 P-containing formulas were detected in the alkaline-extracted sediment solution. Ferrihydrite and goethite adsorbed 51 and 24 P-containing formulas, respectively, with adsorption rates of 56.0 % and 26.4 %. Ferrihydrite could adsorb more OP compounds than goethite, but no obvious molecular species selectivity was observed during the adsorption. The P-containing compounds, including unsaturated hydrocarbons-, lignin/carboxyl-rich alicyclic molecule (CRAM)-, tannin-, and carbohydrate-like molecular compounds, were more suitable for iron oxide adsorption. The double bond equivalence (DBE) is a valuable parameter that indicates OP fractionation during adsorption, and P-containing compounds with lower DBE values such as lipid- and protein-like molecular were prone to remain in the solution after adsorption. These research results provide insights into the biogeochemical cycling process of P in the natural environment.

Abstract Objectives The main objective of this study was to establish a mouse model of spinal ligament ossification to simulate the chronic spinal cord compression observed in patients with ossification of the posterior longitudinal ligament (OPLL). The study also aimed to examine the mice's neurobiological, radiological, and pathological changes. Methods In the previous study, a genetically modified mouse strain was created using Crispr‐Cas9 technology, namely, Enpp1flox/flox/EIIa‐Cre (C57/B6 background), to establish the OPLL model. Wild‐type (WT) mice without compression were used as controls. Functional deficits were evaluated through motor score assessment, inclined plate testing, and gait analysis. The extent of compression was determined using CT imaging. Hematoxylin and eosin staining, luxol fast blue staining, TUNEL assay, immunofluorescence staining, qPCR, and Western blotting were performed to evaluate levels of apoptosis, inflammation, vascularization, and demyelination in the study. Results The results demonstrated a gradual deterioration of compression in the Enpp1flox/flox/EIIa‐Cre mice group as they aged. The progression rate was more rapid between 12 and 20 weeks, followed by a gradual stabilization between 20 and 28 weeks. The scores for spinal cord function and strength, assessed using the Basso Mouse Scale and inclined plate test, showed a significant decline. Gait analysis revealed a noticeable reduction in fore and hind stride lengths, stride width, and toe spread. Chronic spinal cord compression resulted in neuronal damage and activated astrocytes and microglia in the gray matter and anterior horn. Progressive posterior cervical compression impeded blood supply, leading to inflammation and Fas‐mediated neuronal apoptosis. The activation of Bcl2 and Caspase 3 was associated with the development of progressive neurological deficits (p

This paper introduces a novel carbon emission prediction method based on tracking control, leveraging historical CO2 emission prediction errors and feed-forward integration of electricity consumption data to enhance forecasting accuracy and minimize lag. Comparative analysis with pre-trained models such as LSTM and ARDL using Python showcases the proposed method's substantial reduction in prediction errors compared to singular reliance on electricity data, while also significantly reducing computational time in contrast to LSTM models. The findings establish a valuable reference for policymakers and researchers in refining carbon emission prediction methodologies and formulating effective carbon reduction policies.

Global CO2 emissions have been an essential topic of the environmental discussion. Still, empirical data is needed to support arguments that high-quality government actions could reduce these emissions. By analyzing data from 137 nations from 2000 to 2020, we offer strong evidence that state policies focused on promoting healthy ecosystems, sustainable economic growth, and transcendent legislative changes are capable of decreasing CO2 emissions. Based on our findings, there are essentially three critical institutional factors that need to be improved for environmental policies to be efficient: the concept of law, which protects citizens' intellectual property rights; citizens' speech, which allows them to participate in elections and represent themselves freely, and the management of corruption. Policies aimed at promoting economic growth, lowering oil and gas use, enhancing the usage of green energy by the public and private sectors, and enhancing such institutional factors are all necessary components of a climate-friendly financial strategy.

BackgroundInflammation is associated with the pathophysiology of schizophrenia. The blood markers for systemic inflammation include neutrophil-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), lymphocyte-monocyte ratio (LMR), system inflammation response index (SIRI), and platelet-lymphocyte ratio (PLR). However, these inflammation markers and their relationships with clinical phenotypes among Han Chinese patients with first-episode adolescent-onset schizophrenia (AOS) is unclear. This investigation aimed to elucidate the impact of inflammation on Han Chinese AOS patients as well as the association of blood-based inflammation markers with clinical symptoms.MethodsAltogether, 203 Han Chinese individuals participated in this study, 102 first-episode AOS patients and 101 healthy controls. The assessment of inflammatory indices was based on complete blood cell count. Furthermore, schizophrenia-related clinical symptoms were evaluated using the five-factor model of the Positive and Negative Syndrome Scale (PANSS).ResultsIn Han Chinese first-episode AOS patients, levels of SIRI, PLR, SII, and NLR were significantly increased (p < 0.001), while LMR decreased (p < 0.001) compared to healthy controls. Furthermore, multivariate logistic regression showed that LMR, NLR, SII, and SIRI (all p < 0.05) were independently associated with AOS. Moreover, Receiver operating characteristics assessment indicated that NLR, SIRI, LMR, and SII could effectively distinguish AOS patients from healthy controls. Their areas under the curves were 0.734, 0.701, 0.715, and 0.730 (all p < 0.001). In addition, Correlation analysis revealed that LMR was negatively correlated with the PANSS total, negative, and cognitive factor scores (all p < 0.05); NLR was positively correlated with the cognitive factor score (p < 0.01); SII was negatively correlated with the positive factor score and positively with the negative and cognitive factor scores (all p < 0.05); SIRI was positively correlated with the PANSS total and cognitive factor scores (all p < 0.01).ConclusionsThis research established the involvement of peripheral blood inflammatory markers (LMR, NLR, SII, and SIRI) with the clinical manifestations and pathophysiology of schizophrenia, and these can serve as screening tools or potential indices of the inflammatory state and AOS symptoms severity.

Abstract The post-landfall decay of tropical cyclones (TC) is often closely linked to the magnitude of damage to the environment, properties, and the loss of human lives. Despite growing interest in how climate change affects TC decay, data uncertainties still prevent a consensus on changes in TC decay rates and related precipitation. Here, after strict data-quality control, we show that the rate of decay of TCs after making landfall in China has significantly slowed down by 45% from 1967 to 2018. We find that, except the warmer sea surface temperature, the eastward shift of TC landfall locations also contributes to the slowdown of TC decay over China. That is TCs making landfall in eastern mainland China (EC) decay slower than that in southern mainland China (SC), and the eastward shift of TCs landfall locations causes more TCs landfalling in EC with slower decay rate. TCs making landfall in EC last longer at sea, carry more moisture upon landfall, and have more favorable dynamic and thermodynamic conditions sustaining them after landfall. Observational evidence shows that the decay of TC-induced precipitation amount and intensity within 48 h of landfall is positively related to the decay rate of landfalling TCs. The significant increase in TC-induced precipitation over the long term, due to the slower decay of landfalling TCs, increases flood risks in China’s coastal areas. Our results highlight evidence of a slowdown in TC decay rates at the regional scale. These findings provide scientific support for the need for better flood management and adaptation strategies in coastal areas under the threat of greater TC-induced precipitation.

To study temperature and rate-dependent behaviors of molybdenum-rhenium (Mo–Re) alloys, compressive tests at variable temperatures and strain rates were conducted. After the same machining and thermal annealing processes, fully recrystallization happens in Mo and Mo–Re alloys with low Re content (5 wt %), while recovery occurs in Mo–Re alloys with high Re content (14 wt% and 42 wt %). The strength increases as Re content rises at all temperatures (300 °C, 600 °C and 1200 °C), meaning sufficient strengthening effect of Re. The rate-dependent behaviors, however, show different trends between Mo and Mo–Re alloys. Positive strain rate sensitivity is detected in Mo and low Re Mo–Re alloys in all temperatures, which is consistent to other research. While, near zero strain rate sensitivity is found in high Re Mo–Re alloys at 600 °C. Such an unusual phenomenon may be contributed to high stored dislocation density during mechanical processes. The stored dislocations are activated at a proper temperature to accommodate plastic flow, which weakens the influence of strain rate on strength.

Postbiotics are inanimate microbial cells and/or their components as well as microecological preparations made from their metabolites, which are beneficial to the health of the host. Postbiotics can regulate intestinal microbial balance, enhance immunity, and have anti-inflammatory and antibacterial effects. Compared with probiotics, living bacterial cells, postbiotics are safer, and more stable, effective and convenient. This article summarizes the origin, microbial sources, preparation methods and advantages of postbiotics, and elucidates the mechanisms of action of postbiotics in comparison with those of probiotics. In addition, it introduces readers to the applications of postbiotics as functional food supplements, food quality improvers, food preservatives and detoxifying agents in foods. We believe that as the definition, classification, and functional components of postbiotics become clearer, they will be more widely used in the fields of foods, nutraceuticals, foods for special medical purpose, infant foods, and personal care products. The development of postbiotics will also promote the leapfrog development of basic and applied science.

Abstract The exploration of neural circuitry is paramount for comprehending the computational mechanisms and physiology of the brain. Despite significant advances in materials and fabrication techniques, controlling neuronal connectivity and response in 3D remains a formidable challenge. Here, we introduce a method for engineering the growth of 3D neural circuits with the capability for optical stimulation. We fabricate bioactive interfaces by melt electrospinning writing (MEW) 3D polycaprolactone (PCL) scaffolds followed by coating with titanium carbide (Ti3C2Tx MXene). Beyond enhancing hydrophilicity, cell adhesion, and electrical conductivity, the Ti3C2Tx MXene coating enables optocapacitance-based neuronal stimulation, induced by localized temperature increases upon illumination. This approach offers a pathway for additive manufacturing of neural tissues endowed with optical control, facilitating functional tissue engineering and neural circuit computation.

Abstract The fusion and utilization of multi‐scale deep and shallow features are of great significance in liver tumour segmentation. This study proposes a dual encoding DDS‐UNet liver tumour segmentation method based on multi‐scale deep and shallow feature fusion, aiming to fully achieve the fusion and utilization of deep and shallow features and achieve accurate segmentation. The proposed method mainly consists of residual convolution module fusion residual convolution (FRC), dual encoding end fusion module dual encoding end fusion (DEF), and skip connection fusion module jump connection fusion module (JCF). In the residual convolution module, a layer by layer fused residual convolution is used instead of traditional convolution to achieve better training. In the dual encoding end fusion module, multi‐scale feature fusion at the end provides more comprehensive contextual information, solves the loss of spatial geometric information. The skip connection fusion module reduces the interference of invalid features by changing the weights of spatial attention and channel attention on important features. The Dice coefficient, average intersection to union ratio, accuracy, recall, and accuracy indicators tested on the LiTS dataset were 90.37%, 90.16%, 93.78%, 94.91%, and 98.84%, respectively, which are superior to many advanced liver tumor segmentation methods.

Abstract In this study, we conducted an assembly and analysis of the organelle genomes of Aconitum carmichaelii. Our investigation encompassed the examination of organelle genome structures, gene transfer events, and the environmental selection pressures affecting A. carmichaelii. The results revealed distinct evolutionary patterns in the organelle genomes of A. carmichaelii. Especially, the plastome exhibited a more conserved structure but a higher nucleotide substitution rate (NSR), while the mitogenome displayed a more complex structure with a slower NSR. Through homology analysis, we identified several instances of unidirectional protein-coding genes (PCGs) transferring from the plastome to the mitogenome. However, we did not observe any events which genes moved from the mitogenome to the plastome. Additionally, we observed multiple transposable element (TE) fragments in the organelle genomes, with both organelles showing different preferences for the type of nuclear TE insertion. Divergence time estimation suggested that rapid differentiation occurred in Aconitum species approximately 7.96 million years ago (Mya). This divergence might be associated with the reduction in CO2 levels and the significant uplift of the Qinghai-Tibet Plateau (QTP) during the late Miocene. Selection pressure analysis indicated that the dN/dS values of both organelles were less than 1, suggested that organelle PCGs were subject to purification selection. However, we did not detect any positively selected genes (PSGs) in Subg. Aconitum and Subg. Lycoctonum. This observation further supports the idea that stronger negative selection pressure on organelle genes in Aconitum results in a more conserved amino acid sequence. In conclusion, this study contributes to a deeper understanding of organelle evolution in Aconitum species and provides a foundation for future research on the genetic mechanisms underlying the structure and function of the Aconitum plastome and mitogenome.

Objectives: Household hygiene and food safety are essential parts of food security; better food safety and hygiene will help reduce the chances of illness for young children and family members rarely studied in the selected area of coastal Bangladesh. The study aimed to discover the knowledge, attitude, and practice levels for cleanliness, hygiene, and food safety in the household. Methods: In this study, we employed a cross-sectional survey with simple random sampling to collect data from 384 childbearing mothers. The survey used the pretested, validated, and standardized (knowledge, attitude, and practice) questionnaire-model-based interview guide. Results: According to our study analysis, the knowledge, attitude, and practice scores among mothers were inadequate for household cleanliness and hygiene management. In the area context, knowledge efficiency was related to family type (joint and nuclear). Family economic conditions strongly influenced mothers’ attitudes and behavior toward knowledge, attitude, and practice score. Unemployed and illiterate mothers have lower knowledge, attitude, and practice scores. Educated mothers have better knowledge, attitude, and practice score compared to illiterate mothers ( p

Mechanical stress has been viewed as one of the key risk factors in accelerating the intervertebral disc degeneration process. The goal of the present study was to employ a repeated strike loading bovine caudal disc system to elucidate the pathophysiological impacts of cumulative mechanical stress on the disc. The discs in the model groups were subjected to two different mechanical stresses: one strike loading or repeated strike loading. The following indices were analyzed: histological morphology, glycosaminoglycan release, disc height, cell viability, apoptosis-related protein expression, and catabolism-related gene expression. Both mechanical stress modes induced degenerative changes in the discs by day 11, such as clefts and delamination of the annulus fibrosus; they increased glycosaminoglycan release. Cell viability was significantly decreased and catabolic gene expression was significantly up-regulated in the degenerative loading group and repeated strike loading group by day 9. These alterations remained evident in the annulus fibrosus tissue of the repeated strike loading group on day 11. Our data suggests that the repeated strike loading model adopted in this study could lead to degenerative changes in the disc organ model. Annulus fibrosus cells displayed a more noticeable response to mechanical stress damage and a slower recovery process, suggesting that the annulus fibrosus serves as a pivotal factor in disc degeneration due to mechanical stress injuries. The study also indicates that due to the gradual self-repair of intervertebral disc cells after injury, it is necessary to apply repeated strike loading on the disc at specific intervals when researching the repair of chronic disc injuries.

Constructing infrastructure on soft soils demands the implementation of ground improvement. This study proposed an eco-friendly method of stabilizing marine soil using a calcium carbide residue (CCR)-activated coal gangue (CG) geopolymer derived from industrial waste. Laboratory experiments were conducted to investigate the mechanical properties, durability performance, and stabilization mechanisms of stabilized marine soils under multiple wetting-dry cycles. The results highlighted the effectiveness of CG-CCR geopolymer by a content of 15% to achieve satisfactory strength gain over the engineering requirements. However, the largest decrease in strength (71.89%) was observed when the initial water content was beyond 1.5 times the liquid limit (LL). The optimum solution was proposed to have a geopolymer content of 15% or an initial water content of 1.25·LL to exhibit the highest resistance to strength decay after 12 cycles. Compared with water intrusion, mass loss had a more significant effect on soil strength deterioration. The formation of noncrystalline or amorphous-phase reaction products effectively filled intergranular pores and reduced the void space between soil particles, improving the mechanical properties. The CG-CCR geopolymer was demonstrated to offer a promising solution for soil improvement in geotechnical engineering and waste reduction in industry as a soil stabilizer.

Phosphate-solubilizing bacteria (PSB) enhance plant phosphorus utilization through their ability to dissolve phosphorus. To address the low utilization of nitrogen, phosphorus, potassium, zinc, and selenium by tea plants in acidic, selenium-rich soils, the study aimed to investigate the impact of exogenous PSB on soil nutrients and the absorption of zinc and selenium by tea plants. Following the inoculation of potted Longjing and Huangjinya varieties with exogenous phosphorus-solubilizing bacteria, we determined the concentrations of AN, AP, AK, Zn, and Se in their rhizosphere soil, in addition to the Zn and Se contents in their aboveground and belowground parts. The results show that after respective treatment with the three PSB, the concentration of available P in the tea plant rhizosphere soil significantly increased, with PMS08 having the most pronounced effect.After the same treatment, In the rhizosphere soil of Longjing tea plants, the AN content increased by 26.47%, 18.41%, and 7.51%, respectively, relative to the control, while the AK content decreased in the rhizosphere soil of Huangjinya tea plants. Inoculation with the three PSB resulted in a greater content of available Se in both the aboveground and belowground parts of the two tea plants. After inoculation with PMS20, the available Zn content of the belowground parts of Longjing and Huangjinya tea plants respectively decreased by 13.42% and 15.69% in comparison with the control. Additionally, after inoculating Longjing tea plants with PSt09 and Huangjinya tea plants with PMS08, the content of available Zn in their belowground parts significantly decreased by 9.22% and 35.74%, respectively. Evidently, the inoculation with the three phosphorus-solubilizing bacteria is beneficial for the uptake of available P by tea plants, promoting the utilization and accumulation of available Se. However, the content of AN or AK in rhizosphere soil varies between different tea plant varieties inoculated with the same kind of phosphorus-solubilizing bacteria. Moreover, the content of available Zn in tea plants also differs, highlighting the need to further investigate the differential effects of phosphorus-solubilizing bacteria on different plant varieties.

IntroductionAcute myeloid leukemia (AML) is an aggressive blood cancer with high heterogeneity and poor prognosis. Although the metabolic reprogramming of nicotinamide adenine dinucleotide (NAD) has been reported to play a pivotal role in the pathogenesis of acute myeloid leukemia (AML), the prognostic value of NAD metabolism and its correlation with the immune microenvironment in AML remains unclear.MethodsWe utilized our large-scale RNA-seq data on 655 patients with AML and the NAD metabolism-related genes to establish a prognostic NAD metabolism score based on the sparse regression analysis. The signature was validated across three independent datasets including a total of 1,215 AML patients. ssGSEA and ESTIMATE algorithms were employed to dissect the tumor immune microenvironment. Ex vivo drug screening and in vitro experimental validation were performed to identify potential therapeutic approaches for the high-risk patients. In vitro knockdown and functional experiments were employed to investigate the role of SLC25A51, a mitochondrial NAD+ transporter gene implicated in the signature.ResultsAn 8-gene NAD metabolism signature (NADM8) was generated and demonstrated a robust prognostic value in more than 1,800 patients with AML. High NADM8 score could efficiently discriminate AML patients with adverse clinical characteristics and genetic lesions and serve as an independent factor predicting a poor prognosis. Immune microenvironment analysis revealed significant enrichment of distinct tumor-infiltrating immune cells and activation of immune checkpoints in patients with high NADM8 scores, acting as a potential biomarker for immune response evaluation in AML. Furthermore, ex vivo drug screening and in vitro experimental validation in a panel of 9 AML cell lines demonstrated that the patients with high NADM8 scores were more sensitive to the PI3K inhibitor, GDC-0914. Finally, functional experiments also substantiated the critical pathogenic role of the SLC25A51 in AML, which could be a promising therapeutic target.ConclusionOur study demonstrated that NAD metabolism-related signature can facilitate risk stratification and prognosis prediction in AML and guide therapeutic decisions including both immunotherapy and targeted therapies.

Abstract Anthropogenic climate change (ACC) strengthens the global terrestrial water cycle (TWC) through increases in annual total precipitation (PRCPTOT) over global land. While the increase in the average global terrestrial PRCPTOT has been attributed to ACC, it is unclear whether this is equally true in dry and wet regions, given the difference in PRCPTOT changes between the two climatic regions. Here, we show the increase in PRCPTOT in dry regions is twice as fast as in wet regions of the globe during 1961–2018 in both observations and simulations. This faster increase is projected to grow with future warming, with an intensified human-induced TWC in the driest regions of the globe. We show this phenomenon can be explained by the faster warming and precipitation response rates as well as the stronger moisture transport in dry regions under ACC. Quantitative detection and attribution results show that the global increase in PRCPTOT can no longer be attributed to ACC if dry regions are excluded. From 1961–2018, the observed PRCPTOT increased by 5.63%~7.39% (2.44%~2.80%) over dry (wet) regions, and as much as 89% (as little as 5%) can be attributed to ACC. The faster ACC-induced TWC in dry regions is likely to have both beneficial and detrimental effects on dry regions of the globe, simultaneously alleviating water scarcity while increasing the risk of major flooding.

Abstract Early and accurate diagnosis of focal liver lesions is crucial for effective treatment and prognosis. We developed and validated a fully automated diagnostic system named Liver Artificial Intelligence Diagnosis System (LiAIDS) based on a diverse sample of 12,610 patients from 18 hospitals, both retrospectively and prospectively. In this study, LiAIDS achieved an F1-score of 0.940 for benign and 0.692 for malignant lesions, outperforming junior radiologists (benign: 0.830-0.890, malignant: 0.230-0.360) and being on par with senior radiologists (benign: 0.920-0.950, malignant: 0.550-0.650). Furthermore, with the assistance of LiAIDS, the diagnostic accuracy of all radiologists improved. For benign and malignant lesions, junior radiologists’ F1-scores improved to 0.936-0.946 and 0.667-0.680 respectively, while seniors improved to 0.950-0.961 and 0.679-0.753. Additionally, in a triage study of 13,192 consecutive patients, LiAIDS automatically classified 76.46% of patients as low risk with a high NPV of 99.0%. The evidence suggests that LiAIDS can serve as a routine diagnostic tool and enhance the diagnostic capabilities of radiologists for liver lesions.

Abstract In engineering fields, time‐varying matrix inversion (TVMI) issue is often encountered. Zeroing neural network (ZNN) has been extensively employed to resolve the TVMI problem. Nevertheless, the original ZNN (OZNN) and the integral‐enhanced ZNN (IEZNN) usually fail to deal with the TVMI problem under unbounded noises, such as linear noises. Therefore, a neural network model that can handle the TVMI under linear noise interference is urgently needed. This paper develops a double integral‐enhanced ZNN (DIEZNN) model based on a novel integral‐type design formula with inherent linear‐noise tolerance. Moreover, its convergence and robustness are verified by derivation strictly. For comparison and verification, the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise environments. The experiments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear noises. In general, the DIEZNN model is an innovative work and is proposed for the first time. Satisfyingly, the errors of DIEZNN are always less than 1 × 10−3 under linear noises, whereas the error norms of OZNN and IEZNN models are not convergent to zero. In addition, these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN.

Unmanned Aerial Vehicles (UAVs) are indispensable in promoting the development of remote sensing technology. Nevertheless, the tasks of object recognition in remote sensing images based on UAV platforms face major difficulties and challenges due to the complex and variable background environments and the high-density distribution of objects. This paper proposes an object detection algorithm for UAV remote sensing images—YOLO-Remote, which aims to improve detection accuracy by enhancing YOLOv8. This algorithm innovatively integrates the SaElayer module to enhance the focus on remote sensing targets and improve network efficiency. Additionally, it introduces the Efficient-SPPF structure, which effectively expands the network’s receptive field and promotes deep learning capabilities. To address sample imbalance and improve bounding box localization and classification performance, the study also designs the Focaler-MDPIOU strategy. With these comprehensive optimizations, YOLO-Remote achieves significant progress in network architecture. Experiments were conducted on the NWPU VHR10 and RSOD datasets, and the experimental results show that compared to the base model YOLOv8n, the improved model’s average precision increased by 2.7% and 3.2% respectively, demonstrating its superiority in the field of object detection for UAV remote sensing images.The code is available at https://github.com/QuincyQAQ/Yolo-Remotehttps://github.com/QuincyQAQ/Yolo-Remote.

Assessing communication abilities in patients with disorders of consciousness (DOCs) is challenging due to limitations in the behavioral scale. Electroencephalogram-based brain-computer interfaces (BCIs) and eye-tracking for detecting ocular changes can capture mental activities without requiring physical behaviors and thus may be a solution. This study proposes a hybrid BCI that integrates EEG and eye tracking to facilitate communication in patients with DOC. Specifically, the BCI presented a question and two randomly flashing answers (yes/no). The subjects were instructed to focus on an answer. A multimodal target recognition network (MTRN) is proposed to detect P300 potentials and eye-tracking responses (i.e., pupil constriction and gaze) and identify the target in real time. In the MTRN, the dual-stream feature extraction module with two independent multiscale convolutional neural networks extracts multiscale features from multimodal data. Then, the multimodal attention strategy adaptively extracts the most relevant information about the target from multimodal data. Finally, a prototype network is designed as a classifier to facilitate small-sample data classification. Ten healthy individuals, nine DOC patients and one LIS patient were included in this study. All healthy subjects achieved 100% accuracy. Five patients could communicate with our BCI, with 76.1±7.9% accuracy. Among them, two patients who were noncommunicative on the behavioral scale exhibited communication ability via our BCI. Additionally, we assessed the performance of unimodal BCIs and compared MTRNs with other methods. All the results suggested that our BCI can yield more sensitive outcomes than the CRS-R and can serve as a valuable communication tool.

In most real world rehabilitation training, patients are trained to regain motion capabilities with the aid of functional/epidural electrical stimulation (FES/EES), under the support of gravity-assist systems to prevent falls. However, the lack of motion analysis dataset designed specifically for rehabilitation-related applications largely limits the conduct of pilot research. We provide an open access dataset, consisting of multimodal data collected via 16 electromyography (EMG) sensors, 6 inertial measurement unit (IMU) sensors, and 230 insole pressure sensors (IPS) per foot, together with a 26-sensor motion capture system, under different MOVEments and POstures for Rehabilitation Training (MovePort). Data were collected under diverse experimental paradigms. Twenty four participants first imitated multiple normal and abnormal body postures including (1) normal standing still, (2) leaning forward, (3) leaning back, and (4) half-squat, which in practical applications, can be detected as feedback to tune the parameters of FES/EES and gravity-assist systems to keep patients in a target body posture. Data under imitated abnormal gaits, e.g., (1) with legs raised higher under excessive electrical stimulation, and (2) with dragging legs under insufficient stimulation, were also collected. Data under normal gaits with low, medium and high speeds are also included. Pathological gait data from a subject with spastic paraplegia further increases the clinical value of our dataset. We also provide source codes to perform both intra- and inter-participant motion analyses of our dataset. We expect our dataset can provide a unique platform to promote collaboration among neurorehabilitation engineers.

The quadratic programming (QP) problem constitutes a distinctive class within mathematical optimization, prevalent in scientific computations and engineering applications. In practical scenarios, noise interference has the potential to adversely impact the solution accuracy of time-varying QP (TVQP) problems, thereby compromising the performance of established neural network models, including the original zeroing neural network (OZNN). Consequently, certain variants of the Zeroing Neural Network (ZNN) model exhibit notable tolerance to constant or linear noise; however, it is imperative to acknowledge the prevalence of more intricate forms of noise, particularly nonlinear noise. To ameliorate compromised solution accuracy in the presence of nonlinear noise, this study introduces a novel Zeroing Neural Network (ZNN) model, denoted as Triple Integral Enhancement Zeroing Neural Network (TIEZNN). The model incorporates a novel error processing mechanism strategically enhanced through triple integral augmentation, designed specifically to address TVQP perturbed by nonlinear noise. Theoretical analysis rigorously establishes the convergence properties and commendable noise suppression capabilities intrinsic to the proposed TIEZNN model. Compared with the traditional gradient-based neural network and the previous ZNN model and its variants, the TIEZNN model proposed in this paper is still highly robust and accurate in the face of nonlinear noise. Simulation results unequivocally demonstrate the efficiency and superior performance of the TIEZNN model in addressing TVQP challenges, particularly in scenarios featuring equality and inequality constraints influenced by nonlinear noise.

Abstract Cytokine release syndrome (CRS) is the most common complication of chimeric antigen receptor redirected T cells (CAR-T) therapy. CAR-T toxicity management has been greatly improved, but CRS remains a prime safety concern. Here we follow serum cytokine levels and circulating immune cell transcriptomes longitudinally in 26 relapsed/refractory multiple myeloma patients receiving the CAR-T product, ciltacabtagene autoleucel, to understand the immunological kinetics of CRS. We find that although T lymphocytes and monocytes/macrophages are the major overall cytokine source in manifest CRS, neutrophil activation peaks earlier, before the onset of severe symptoms. Intracellularly, signaling activation dominated by JAK/STAT pathway occurred prior to cytokine cascade and displayed regular kinetic changes. CRS severity is accurately described and potentially predicted by temporal cytokine secretion signatures. Notably, CAR-T re-expansion is found in three patients, including a fatal case characterized by somatic TET2-mutation, clonal expanded cytotoxic CAR-T, broadened cytokine profiles and irreversible hepatic toxicity. Together, our findings show that a latent phase with distinct immunological changes precedes manifest CRS, providing an optimal window and potential targets for CRS therapeutic intervention and that CAR-T re-expansion warrants close clinical attention and laboratory investigation to mitigate the lethal risk.

Abstract Background To determine the differences in the microbial communities in the Camellia sinensis L. hairy root, lateral root, and main root rhizospheres in Anping Village, Kaiyang County, Guizhou Province, the community structure, diversity, and main dominant species of bacteria and fungi in different parts of the soil were analyzed by ITS and 16S sequencing. Results In the rhizosphere soil of the main root, lateral root, and hairy root of Camellia sinensis L., there were significant differences in the diversity and richness of the bacterial and fungal communities. The bacterial diversity was the highest and the fungal richness was the lowest in the rhizosphere soil of the main root. In the bacterial community, Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, and Gemmatimonadetes were the common dominant bacteria. Rhodospirillaceae, Bradyrhizobiaceae, Hyphomicrobiaceae, Solibacteraceae, and Koribacteraceae were the common dominant bacteria in the rhizosphere soil of different parts of the root system, but the relative abundance of bacteria in different parts of the rhizosphere soil varied greatly. The dominant groups of fungal communities in different parts of the rhizosphere soil were Basidiomycota, Ascomycota, Mortierellomycota, and Sebacinaceae. The structure of the fungal community is similar in different parts. Conclusions Compared with the different parts of the hairy root, lateral root, and main root of rhizosphere soil of Camellia sinensis L. in Anping village, it was found that the abundance of fungal community decreased with the increase of bacterial community abundance, and there were significant differences in bacterial community diversity and structure. However, the fungal community maintained stability among different parts.

Abstract In order to further explore the effects of soil mercury pollution on soil microbial diversity and community structure, soil samples were randomly collected from 2 m, 20 m, 30 m, 500 m and 650 m periphery of Wanshan mining area, as 5 different treatments. Each treatment had 4 replicates. Soil microbial DNA was extracted from 20 soil samples, and then high-throughput sequencing technology was used to analyse the structure and distribution of bacterial and fungal communities. The results showed that the number of bacterial and fungal communities in T0–T30 treatments was significantly larger than that in T500–T650 treatments at order, family and genus level. Whatever, the number of uniquely distributed bacterial and fungal communities among 4 replicates soil samples was quite different at order, family and genus level. The results of the effect on the microbial community structure showed that there were both the same dominant bacterial and fungal communities, and the different dominant bacterial and fungal communities at any classification level, moreover, the number of same dominant bacterial and fungal communities was larger than that of different dominant bacterial and fungal communities. The results of relationship between soil environment factors and bacterial and fungal community structure showed that distance (Hg2+), EC and pH had a high correlation with community structure, especially the distance factor, that is, the content of mercury in soil had the highest effects on community structure. The internal heterogeneity of soil caused significant differences in bacterial and fungal community structure, and the emergence of dominant bacterial and fungal communities was a manifestation of better adaptability to long-term mercury stress and other stresses in soil, which will provide a scientific reference for further exploring the mechanism of mercury enrichment between microorganisms and plants.

Enhancing irrigation and nitrogen fertilizer application has become a vital strategy for ensuring food security in the face of population growth and resource scarcity. A 2-year experiment was conducted to determine to investigate the effects of different irrigation lower limits and nitrogen fertilizer application amounts on millet growth, yield, water use efficiency (WUE), N utilization, and inorganic nitrogen accumulation in the soil in 2021 and 2022. The experiment was designed with four irrigation lower limits, corresponding to 50%, 60%, 70%, and 80% of the field capacity (FC), referred to as I50, I60, I70, and I80. Four nitrogen fertilizer application were also included: 0, 50, 100, and 150 kg·hm−2 (designated as F00, F50, F100, and F150), resulting in a total of 16 treatments. Binary quadratic regression equations were established to optimize the irrigation and nitrogen application. The results demonstrated that the plant height, stem diameter, leaf area index, aboveground biomass, yield, spike diameter, spike length, spike weight, WUE, and nitrogen agronomic efficiency for millet initially increased before subsequently decreasing as the irrigation lower limit and nitrogen fertilizer application increased. Their maximum values were observed in the I70F100. However, the nitrogen partial factor productivity (PFPN) exhibited a gradual decline with increasing nitrogen application, reaching its peak at F50. Additionally, PFPN displayed a pattern of initial increase followed by a decrease with rising irrigation lower limits. The accumulation of NO3−-N and NH4+-N in the 0~60 cm soil layer increased with the increase of nitrogen fertilizer application in both years, while they tended to decrease as the irrigation lower limit increased. An optimal irrigation lower limit of 64% FC to 74% FC and nitrogen fertilizer application of 80 to 100 kg ha−1 was recommended for millet based on the regression equation. The findings of this study offer a theoretical foundation and technical guidance for developing a drip irrigation and fertilizer application for millet cultivation in Northeast China.

Glaucoma represents a significant global contributor to blindness. Accurately segmenting the optic disc (OD) and optic cup (OC) to obtain precise CDR is essential for effective screening. However, existing convolutional neural network (CNN)-based segmentation techniques are often limited by high computational demands and long inference times. This paper proposes an efficient end-to-end method for OD and OC segmentation, utilizing the lightweight MobileNetv3 network as the core feature-extraction module. Our approach combines boundary branches with adversarial learning, to achieve multi-label segmentation of the OD and OC. We validated our proposed approach across three public available datasets: Drishti-GS, RIM-ONE-r3, and REFUGE. The outcomes reveal that the Dice coefficients for the segmentation of OD and OC within these datasets are 0.974/0.900, 0.966/0.875, and 0.962/0.880, respectively. Additionally, our method substantially lowers computational complexity and inference time, thereby enabling efficient and precise segmentation of the optic disc and optic cup.