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Abstract Processing spatiotemporal data sources with both high spatial dimension and rich temporal information is a ubiquitous need in machine intelligence. Recurrent neural networks in the machine learning domain and bio-inspired spiking neural networks in the neuromorphic computing domain are two promising candidate models for dealing with spatiotemporal data via extrinsic dynamics and intrinsic dynamics, respectively. Nevertheless, these networks have disparate modeling paradigms, which leads to different performance results, making it hard for them to cover diverse data sources and performance requirements in practice. Constructing a unified modeling framework that can effectively and adaptively process variable spatiotemporal data in different situations remains quite challenging. In this work, we propose hybrid spatiotemporal neural networks created by combining the recurrent neural networks and spiking neural networks under a unified surrogate gradient learning framework and a Hessian-aware neuron selection method. By flexibly tuning the ratio between two types of neurons, the hybrid model demonstrates better adaptive ability in balancing different performance metrics, including accuracy, robustness, and efficiency on several typical benchmarks, and generally outperforms conventional single-paradigm recurrent neural networks and spiking neural networks. Furthermore, we evidence the great potential of the proposed network with a robotic task in varying environments. With our proof of concept, the proposed hybrid model provides a generic modeling route to process spatiotemporal data sources in the open world.

Abstract Adipose tissue plays critical roles in an individual’s aging process. In this research, we use single-nucleus RNA sequencing to create highly detailed transcriptional maps of subcutaneous adipose tissue and visceral adipose tissue in young and aged mice. We comprehensively identify the various cell types within the white adipose tissue of mice, our study has elucidated seven distinct cell types within this tissue. Further analyses focus on adipocytes, fibro-adipogenic progenitors, and immune cells, revealing age-related declines in the synthetic metabolic activity of adipocytes, diminished immune regulation, and reduced maturation or proliferation of fibroblasts in undifferentiated adipocytes. We confirm the presence of distinct subpopulations of adipocytes, highlighting decreases in adipogenesis subgroups due to aging. Additionally, we uncover a reduction in immune cell subpopulations, driven by age-associated immune system dysregulation. Furthermore, pseudo-time analyses indicate that Adipocyte1 represents the 'nascent' phase of adipocyte development, while Adipocyte2 represents the 'mature' phase. We use cell–cell interaction to explore the age-dependent complexities of the interactions between FAPs and adipocytes, and observed increased expression of the inflammation-related Retn-Tlr4 interaction in older mice, while the anti-inflammatory Angpt1-Tek interaction was only detected in young mice. These transcriptional profiles serve as a valuable resource for understanding the functional genomics underlying metabolic disorders associated with aging in human adipose tissue.

Abstract The neocortex comprises six cortical layers that play a crucial role in information processing; however, it remains unclear whether laminar processing is consistent across all regions within a single cortex. In this study, we demonstrate diverse laminar response patterns in the primary visual cortex (V1) of three male macaque monkeys when exposed to visual stimuli at different spatial frequencies (SFs). These response patterns can be categorized into two groups. One group exhibit suppressed responses in the output layers for all SFs, while the other type shows amplified responses specifically at high SFs. Further analysis suggests that both magnocellular (M) and parvocellular (P) pathways contribute to the suppressive effect through feedforward mechanisms, whereas amplification is specific to local recurrent mechanisms within the parvocellular pathway. These findings highlight the non-uniform distribution of neural mechanisms involved in laminar processing and emphasize how pathway-specific amplification selectively enhances representations of high-SF information in primate V1.

Abstract Background Exposure to extreme cold or heat temperature is one leading cause of weather-associated mortality and morbidity in animals. Emerging studies demonstrate that the microbiota residing in guts act as an integral factor required to modulate host tolerance to cold or heat exposure, but common and unique patterns of animal-temperature associations between cold and heat have not been simultaneously examined. Therefore, we attempted to investigate the roles of gut microbiota in modulating tolerance to cold or heat exposure in mice. Results The results showed that both cold and heat acutely change the body temperature of mice, but mice efficiently maintain their body temperature at conditions of chronic extreme temperatures. Mice adapt to extreme temperatures by adjusting body weight gain, food intake and energy harvest. Fascinatingly, 16 S rRNA sequencing shows that extreme temperatures result in a differential shift in the gut microbiota. Moreover, transplantation of the extreme-temperature microbiota is sufficient to enhance host tolerance to cold and heat, respectively. Metagenomic sequencing shows that the microbiota assists their hosts in resisting extreme temperatures through regulating the host insulin pathway. Conclusions Our findings highlight that the microbiota is a key factor orchestrating the overall energy homeostasis under extreme temperatures, providing an insight into the interaction and coevolution of hosts and gut microbiota.

Natural plant fibers are hierarchical structures with multi-level microstructures. With advances in composite material science, these fibers have been widely used in various polymer products. Therefore, it is crucial to quantitatively understand the relationship between their microstructures and mechanical behavior. This paper utilizes the Mori-Tanaka micromechanics model, viscoelasticity theory, and Zakian’s inversion method to study the impact of plant fiber microstructure on the viscoelastic behavior of multiscale structures. At the microscopic scale, the macromolecular polymer (matrix) and cellulose (fiber) are first homogenized. The second homogenization involves the cell wall microstructure, and the third homogenization considers the porosity of the cell wall and lumen to predict the effective modulus of fiber bundles. By applying the principle of elastic-viscoelastic correspondence, the viscoelastic mechanical parameters of plant fibers are calculated. The study examines the effects of cellulose crystallinity and lumen porosity on the structural stiffness and viscoelastic properties of fibers, identifying these factors as key influences on the mechanical behavior of plant fibers. Given their significant economic potential, the feasibility of using tobacco plant fibers as bio-based materials is also explored.

Host-microbe interactions are virtually bidirectional, but how the host affects their microbiome is poorly understood. Here, we report that the host is a critical modulator to regulate the lifestyle switch and pathogenicity heterogeneity of the opportunistic pathogens Serratia marcescens utilizing the Drosophila and bacterium model system. First, we find that Drosophila larvae efficiently outcompete S. marcescens and typically drive a bacterial switch from pathogenicity to commensalism toward the fly. Furthermore, Drosophila larvae reshape the transcriptomic and metabolic profiles of S. marcescens characterized by a lifestyle switch. More importantly, the host alters pathogenicity and heterogeneity of S. marcescens in the single-cell resolution. Finally, we find that larvae-derived AMPs are required to recapitulate the response of S. marcescens to larvae. Altogether, our findings provide an insight into the pivotal roles of the host in harnessing the life history and heterogeneity of symbiotic bacterial cells, advancing knowledge of the reciprocal relationships between the host and pathogen.

BackgroundCoronary artery disease (CAD) has a high incidence and poor prognosis worldwide. It has been confirmed that smartphone addiction (SA) habit can increase the incidence of hypertension and obesity in adolescents. However, the association of SA with CAD and its severity in Chinese adults remains largely unknown.MethodsA total of 700 Chinese adults (aged 18–70 years) including 350 CAD patients and 350 control subjects were enrolled. The Smartphone Addiction Scale Short Version (SAS-SV) was used to measure SA habit, and the Pittsburgh sleep quality index (PSQI) was used to assess sleep quality. Multiple logistic regression was employed to analyze the relationship between SA habit and CAD.ResultsAfter adjusting for age, smoking, hypertension, type 2 diabetes mellitus, and other risk factors, there was a significant association between SA habit and CAD in adults (p 34) and low Gensini score group (≤34), respectively. Compared with low Gensini score group, patients in high Gensini score group were more likely to have SA habit (p = 0.049).ConclusionsThere is a positive association of SA habit with CAD and its severity in Chinese adults.

The gut microbiota influences host metabolism and health, impacting diseases. Research into how diet affects gut microbiome dynamics in model organisms is crucial but underexplored. Herein, we examined how dietary adenine affects uric acid levels and the gut microbiota over five generations of Drosophila melanogaster. Wild-type W1118 flies consumed diets with various adenine concentrations (GC: 0%, GL: 0.05%, and GH: 0.10%), and their gut microbiota were assessed via Illumina MiSeq sequencing. Adenine intake significantly increased uric acid levels in the GH group > the GC group. Despite no significant differences in the alpha diversity indices, there were significant disparities in the gut microbiota health index (GMHI) and dysbiosis index (MDI) among the groups. Adenine concentrations significantly altered the diversity and composition of the gut microbiota. High adenine intake correlated with increased uric acid levels and microbial population shifts, notably affecting the abundances of Proteobacteria and Firmicutes. The gut microbiota phenotypes included mobile elements, gram-positive bacteria, biofilm-forming bacteria, and gram-negative bacteria. The significantly enriched KEGG pathways included ageing, carbohydrate metabolism, and the immune system. In conclusion, adenine intake increases uric acid levels, alters gut microbiota, and affects KEGG pathways in Drosophila across generations. This study highlights the impact of dietary adenine on uric acid levels and the gut microbiota, providing insights into intergenerational nutritional effects.

Abstract Background Universities have widely switched from traditional face-to-face classes to online instruction as a result of the epidemic. Self-directed learning is becoming the new norm for university students’ learning styles. The ability of health professions students to learn independently during online study directly impacts the effectiveness of online medical education. The ability to learn on their own initiative may be affected by health professions students’ professional identities, defined as their positive perceptions, evaluations, emotional experiences, and identity as professionals related to medicine. This study aimed to look into the current status and the factors that influence health professions students’ self-directed learning ability (SDLA) during online study and its relationship with professional identity. Methods This study was conducted from September to November 2022 at a medical school in East China. An online questionnaire was used to collect participants’ status of online learning, self-directed learning ability (SDLA), and professional identity. Results One thousand two hundred ninety-eight health professions students demonstrated intermediate self-directed learning ability during online study. In terms of teacher-student interaction (F = 14.778, P

Abstract It is widely believed the brain-inspired spiking neural networks have the capability of processing temporal information owing to their dynamic attributes. However, how to understand what kind of mechanisms contributing to the learning ability and exploit the rich dynamic properties of spiking neural networks to satisfactorily solve complex temporal computing tasks in practice still remains to be explored. In this article, we identify the importance of capturing the multi-timescale components, based on which a multi-compartment spiking neural model with temporal dendritic heterogeneity, is proposed. The model enables multi-timescale dynamics by automatically learning heterogeneous timing factors on different dendritic branches. Two breakthroughs are made through extensive experiments: the working mechanism of the proposed model is revealed via an elaborated temporal spiking XOR problem to analyze the temporal feature integration at different levels; comprehensive performance benefits of the model over ordinary spiking neural networks are achieved on several temporal computing benchmarks for speech recognition, visual recognition, electroencephalogram signal recognition, and robot place recognition, which shows the best-reported accuracy and model compactness, promising robustness and generalization, and high execution efficiency on neuromorphic hardware. This work moves neuromorphic computing a significant step toward real-world applications by appropriately exploiting biological observations.

Abstract The coding privilege of end-spectral hues (red and blue) in the early visual cortex has been reported in primates. However, the origin of such bias remains unclear. Here, we provide a complete picture of the end-spectral bias in visual system by measuring fMRI signals and spiking activities in macaques. The correlated end-spectral biases between the LGN and V1 suggest a subcortical source for asymmetric coding. Along the ventral pathway from V1 to V4, red bias against green peaked in V1 and then declined, whereas blue bias against yellow showed an increasing trend. The feedforward and recurrent modifications of end-spectral bias were further revealed by dynamic causal modeling analysis. Moreover, we found that the strongest end-spectral bias in V1 was in layer 4C $$\beta$$ β . Our results suggest that end-spectral bias already exists in the LGN and is transmitted to V1 mainly through the parvocellular pathway, then embellished by cortical processing.

Abstract Background Childbearing in women with advanced maternal age (AMA) has increased the need for artificial reproductive technology (ART). ART and oxidative stress are associated with many pregnancy complications. Paraoxonase (PON) 1 is one of the key components responsible for antioxidative activity in high-density lipoprotein (HDL). This study aimed to investigate the longitudinal changes of oxidative stress and PON1 lactonase activity and status in older women undergoing ART. Methods This prospective nested case-control study included 129 control and 64 ART women. Blood samples were obtained respectively at different stages of pregnancy. PON1 level and lactonase activity were assessed using 7-O-diethylphosphoryl-3-cyano-4-methyl-7-hydroxycoumarin (DEPCyMC) and 5-thiobutyl butyrolactone (TBBL) as a substrate, respectively. A normalized lactonase activity (NLA) was estimated based on the ratio of TBBLase to DEPCyMCase activity. Serum total oxidant status (TOS), total antioxidant capacity (TAC), malondialdehyde (MDA), homocysteine (HCY), PON1 C-108T and Q192R genetic polymorphisms, and metabolic parameters were analyzed. Results Lactonase activity and level of PON1 gradually decreased with pregnancy progression, while glycolipid metabolism parameters and TAC levels increased with pregnancy progression or significantly raised during the 2nd and 3rd trimesters, and NLA of PON1, TOS, OSI, MDA, and HCY significantly increased before delivery in the ART and control groups. Compared with the control women, the ART women had substantially higher or relatively high lactonase activity and NLA of PON1 and TAC during pregnancy; higher triglyceride (TG), total cholesterol, low-density lipoprotein cholesterol, atherogenic index, apolipoprotein (apo) B, and apoB/apoA1 ratio in the 1st trimester; and higher fasting glucose, fasting insulin, homeostatic model assessment of insulin resistance, and TG levels before delivery. No significant differences were found in the frequencies of PON1 C-108T and Q192R genotypes and alleles between the ART and control groups. Conclusions Women with AMA undergoing ART had higher TAC, PON1 lactonase activity, and PON1 NLA than control women, suggesting increased compensatory antioxidant capacity in ART women, thus showing higher sensitivity to oxidative stress-related injury and diseases.

Cynanchum belongs to the Apocynaceae family and is a morphologically diverse genus that includes around 200 shrub or perennial herb species. Despite the utilization of CPGs, few molecular phylogenetic studies have endeavored to elucidate infrafamilial relationships within Cynanchum through extensive taxon sampling. In this research, we constructed a phylogeny and estimated divergence time based on the chloroplast genomes (CPGs) of nine Cynanchum species. We sequenced and annotated nine chloroplast (CP) genomes in this study. The comparative analysis of these genomes from these Cynanchum species revealed a typical quadripartite structure, with a total sequence length ranging from 158,283 to 161,241 base pairs (bp). The CP genome (CPG) was highly conserved and moderately differentiated. Through annotation, we identified a total of 129–132 genes. Analysis of the boundaries of inverted repeat (IR) regions showed consistent positioning: the rps19 gene was located in the IRb region, varying from 46 to 50 bp. IRb/SSC junctions were located between the trnN and ndhF genes. We did not detect major expansions or contractions in the IR region or rearrangements or insertions in the CPGs of the nine Cynanchum species. The results of SSR analysis revealed a variation in the number of SSRs, ranging from 112 to 150. In five types of SSRs, the largest number was mononucleotide repeats, and the smallest number was hexanucleotide repeats. The number of long repeats in the cp genomes of nine Cynanchum species was from 35 to 80. In nine species of Cynanchum, the GC3s values ranged from 26.80% to 27.00%, indicating a strong bias towards A/U-ending codons. Comparative analyses revealed four hotspot regions in the CPG, ndhA-ndhH, trnI-GAU-rrn16, psbI-trnS-GCU, and rps7-ndhB, which could potentially serve as molecular markers. In addition, phylogenetic tree construction based on the CPG indicated that the nine Cynanchum species formed a monophyletic group. Molecular dating suggested that Cynanchum diverged from its sister genus approximately 18.87 million years ago (Mya) and species diversification within the Cynanchum species primarily occurred during the recent Miocene epoch. The divergence time estimation presented in this study will facilitate future research on Cynanchum, aid in species differentiation, and facilitate diverse investigations into this economically and ecologically important genus.

Wheat is one of the most important food crops globally, and understanding the regulation of grain size is crucial for wheat breeding to achieve a higher grain yield. MicroRNAs (miRNAs) play vital roles in plant growth and development. However, the miRNA-mediated mechanism underlying grain size regulation remains largely elusive in wheat. Here, we report the characterization and functional validation of a miRNA, TamiR397a, associated with grain size regulation in wheat. The function of three TaMIR397 homoeologs was determined through histochemical β-glucuronidase-dependent assay. MiRNA expression was detected using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and the function of TamiR397a was validated through its transgenic overexpression and repression in wheat. It was found that TaMIR397-6A and TaMIR397-6B encode active TamiR397a. The expression profiling indicated that TamiR397a was differentially expressed in various tissues and gradually up-regulated during grain filling. The inhibition of TamiR397a perturbed grain development, leading to a decrease in grain size and weight. Conversely, the overexpression of TamiR397a resulted in increased grain size and weight by accelerating the grain filling process. Transcriptome analysis revealed that TamiR397a regulates a set of genes involved in hormone response, desiccation tolerance, regulation of cellular senescence, seed dormancy, and seed maturation biological processes, which are important for grain development. Among the down-regulated genes in the grains of the TamiR397a-overexpressing transgenic plants, 11 putative targets of the miRNA were identified. Taken together, our results demonstrate that TamiR397a is a positive regulator of grain size and weight, offering potential targets for breeding wheat with an increased grain yield.

When a ship sails in shallow water, it will show different hydrodynamic performance from that in deep water due to the limitations of water depth. The shallow water effect may lead to hull sinkage and trim, increasing the risk of bottoming or collision. In this study, a new design scheme of a shallow-water seismic survey vessel is proposed to solve the problems of traditional seismic survey vessels in shallow-water marine resources exploration and safety. The RANS (the Reynolds-Averaged Navier–Stokes) method combined with the Overset Mesh and DFBI (Dynamic Fluid Body Interaction) method is used for numerical simulation to analyze the influence of ship type, water depth, and speed on ship sinkage and trim, as well as the influence of the shallow-water ship’s attitude on resistance. The results show that with the decrease in water depth and the increase in speed, the pressure distribution around the hull becomes uneven, which leads to the aggravation of the sinkage and trim of the hull. In response to this problem, the shallow-water seismic survey vessel significantly improved the sinkage and trim of the hull in shallow water to ensure its safe navigation. The research also shows that navigation resistance can be effectively reduced by appropriately adjusting the ship’s attitude. Therefore, this study provides a reference for the development of shallow-water ships in the future.

In the context of the advancing construction engineering field in China, there has been a significant increase in the adoption of building information modeling (BIM) technology within engineering–procurement–construction (EPC) projects. This emerging technology is expected to significantly influence the decision-making practices of professionals in the construction and engineering domain. Consequently, there is an urgent need for comprehensive research focused on construction management specifically pertaining to the effectiveness of construction developer management. This study examines seven representative EPC projects where BIM technology was implemented and it considers various factors that have the potential to influence project decision-making while taking into account time and cost considerations. A comprehensive multidimensional evaluation method that combines the analytic hierarchy process (AHP) and the fuzzy comprehensive evaluation method is introduced in this study. The results of this study emphasize that the efficiency enhancement strategies derived from the judgment indicator method demonstrate favorable practical outcomes. This research highlights the importance of a comprehensive evaluation method combining the AHP and the fuzzy comprehensive evaluation method to enhance decision-making efficiency for construction developer management staff.

Despite the recognized importance of the spinal cord in sensory processing, motor behaviors, and neural diseases, the underlying organization of neuronal clusters and their spatial location remain elusive. Recently, several studies have attempted to define the neuronal types and functional heterogeneity in the spinal cord using single-cell or single-nucleus RNA sequencing in animal models or developing humans. However, molecular evidence of cellular heterogeneity in the adult human spinal cord is limited. Here, we classified spinal cord neurons into 21 subclusters and determined their distribution from nine human donors using single-nucleus RNA sequencing and spatial transcriptomics. Moreover, we compared the human findings with previously published single-nucleus data of the adult mouse spinal cord, which revealed an overall similarity in the neuronal composition of the spinal cord between the two species while simultaneously highlighting some degree of heterogeneity. Additionally, we examined the sex differences in the spinal neuronal subclusters. Several genes, such as SCN10A and HCN1, showed sex differences in motor neurons. Finally, we classified human dorsal root ganglia (DRG) neurons using spatial transcriptomics and explored the putative interactions between DRG and spinal cord neuronal subclusters. In summary, these results illustrate the complexity and diversity of spinal neurons in humans and provide an important resource for future research to explore the molecular mechanisms underlying spinal cord physiology and diseases.

Abstract Background Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimates if those assumptions are violated. Therefore, methods for detecting potential ‘outlier’ evaluators are needed to improve data quality during data collection stage. Methods In this paper, we propose a two-stage algorithm to detect ‘outlier’ evaluators whose evaluation results tend to be higher or lower than their counterparts. In the first stage, evaluators’ effects are obtained by fitting a regression model. In the second stage, hypothesis tests are performed to detect ‘outlier’ evaluators, where we consider both the power of each hypothesis test and the false discovery rate (FDR) among all tests. We conduct an extensive simulation study to evaluate the proposed method, and illustrate the method by detecting potential ‘outlier’ audiologists in the data collection stage for the Audiology Assessment Arm of the Conservation of Hearing Study, an epidemiologic study for examining risk factors of hearing loss in the Nurses’ Health Study II. Results Our simulation study shows that our method not only can detect true ‘outlier’ evaluators, but also is less likely to falsely reject true ‘normal’ evaluators. Conclusions Our two-stage ‘outlier’ detection algorithm is a flexible approach that can effectively detect ‘outlier’ evaluators, and thus data quality can be improved during data collection stage.

Accurate identification of Seriola dumerili (SD) offers crucial technical support for aquaculture practices and behavioral research of this species. However, the task of discerning S. dumerili from complex underwater settings, fluctuating light conditions, and schools of fish presents a challenge. This paper proposes an intelligent recognition model based on the YOLOv8 network called SD-YOLOv8. By adding a small object detection layer and head, our model has a positive impact on the recognition capabilities for both close and distant instances of S. dumerili, significantly improving them. We construct a convenient S. dumerili dataset and introduce the deformable convolution network v2 (DCNv2) to enhance the information extraction process. Additionally, we employ the bottleneck attention module (BAM) and redesign the spatial pyramid pooling fusion (SPPF) for multidimensional feature extraction and fusion. The Inner-MPDIoU bounding box regression function adjusts the scale factor and evaluates geometric ratios to improve box positioning accuracy. The experimental results show that our SD-YOLOv8 model achieves higher accuracy and average precision, increasing from 89.2% to 93.2% and from 92.2% to 95.7%, respectively. Overall, our model enhances detection accuracy, providing a reliable foundation for the accurate detection of fishes.

Perovskite-style materials are cathode systems known for their stability in solid oxide fuel cells (SOFCs). Pr0.5Sr0.5FeO3−δ (PSF) exhibits excellent electrode performance in perovskite cathode systems at high temperatures. Via VB subgroup metals (V, Nb, and Ta) modifying the B-site, the oxidation and spin states of iron elements can be adjusted, thereby ultimately adjusting the cathode’s physicochemical properties. Theoretical predictions indicate that PSF has poor stability, but the relative arrangement of the three elements on the B-site can significantly improve this material’s properties. The modification of Nb has a large effect on the stability of PSF cathode materials, reaching a level of −2.746 eV. The surface structure of PSF becomes slightly more stable with an increase in the percentage of oxygen vacancy structures, but the structural instability persists. Furthermore, the differential charge density distribution and adsorption state density of the three modified cathode materials validate our adsorption energy prediction results. The initial and final states of the VB subgroup metal-doped PSF indicate that PSFN is more likely to complete the cathode surface adsorption reaction. Interestingly, XRD and EDX characterization are performed on the synthesized pure and Nb-doped PSF material, which show the orthorhombic crystal system of the composite theoretical model structure and subsequent experimental components. Although PSF exhibits strong catalytic activity, it is highly prone to decomposition and instability at high temperatures. Furthermore, PSFN, with the introduction of Nb, shows greater stability and can maintain its activity for the ORR. EIS testing clearly indicates that Nb most significantly improves the cathode. The consistency between the theoretical predictions and experimental validations indicates that Nb-doped PSF is a stable and highly active cathode electrode material with excellent catalytic activity.

The potential of bisphenol A (BPA)-binding peptides fused to magnetic beads is demonstrated as novel adsorbents that are reusable and highly selective for BPA removal from aqueous environments, in which various interfering substances coexist. Magnetic beads harboring peptides (peptide beads) showed a higher BPA removal capacity (8.6 mg/g) than that of bare beads without peptides (2.0 mg/g). The BPA adsorption capacity of peptide beads increased with the number of peptides fused onto the beads, where monomeric, dimeric, or trimeric repeats of a BPA-binding peptide were fused to magnetic beads. The BPA-adsorbing beads were regenerated using a methanol–acetic acid mixture, and after six regeneration cycles, the adsorption capacity remained above 87% of its initial capacity. The selective removal of BPA was confirmed in the presence of BPA analogs with high structural similarity (bisphenol F and bisphenol S) or in synthetic wastewater. The present work is a pioneering study that investigates the selective affinity of peptides to remove specific organics with high selectivity from complex environmental matrices.

Abstract Background Cytochrome P450 2E1 (CYP2E1) plays a key role in the metabolism of xenobiotic and endogenous low-molecular-weight compounds. This study aimed to determine if the genetic variations of 96-bp insertion/deletion (I/D) and C-1054T (rs2031920) in CYP2E1 were associated with the risk of gestational diabetes mellitus (GDM). Methods CYP2E1 polymorphisms were genotyped in a case-control study of 1,134 women with uncomplicated pregnancies and 723 women with GDM. The effects of genotype on the clinical, metabolic, and oxidative stress indices were assessed. Results The CYP2E1 C-1054T variant was associated with an increased risk of GDM based on the genotype, recessive, dominant, and allele genetic models (P

Objective There is no effective standard method to evaluate whether the nerve root tension is restored during lumbar decompression surgery, which is an important indicator for the recovery of nerve function. This study aimed to investigate the feasibility of intraoperative nerve root tension measurement and to confirm the correlation between nerve root tension and intervertebral space height. Methods A total of 54 consecutive patients (mean age, 54.3 years; range, 25–68 years) received posterior lumbar interbody fusion (PLIF) for lumbar disc herniation (LDH) with lumbar spinal stenosis and instability. The 110%, 120%, 130%, 140% height values of each lesion were calculated based on preoperative measurements of the intervertebral space height. The heights were intraoperatively expanded after the intervertebral disc was removed using the interbody fusion cage model. The tension value of nerve root was measured by pulling the nerve root for 5 mm with a self‐made measuring device. The nerve root tension value was measured before decompression, after discectomy at 100%, 110%, 120%, 130%, and 140% of the height of each intervertebral space, and after placement of the cage during intraoperative nerve root tension monitoring. Results The nerve root tension values at 100%, 110%, 120%, and 130% heights were significantly lower than those before decompression, and there was no statistical significance among the four groups. The nerve root tension value was significantly higher at 140% height and was statistically significant compared with that of 130% height. The nerve root tension value after cage placement was significantly lower than that before decompression (1.32 ± 0.22 N vs. 0.61 ± 0.17 N, p

AbstractBackground T-cell large granular lymphocyte leukaemia (T-LGLL) generally has a favourable prognosis, but a small proportion of patients are facing a relatively short survival time. This study aimed to identify clinical factors associated with survival in patients with T-LGLL and develop a predictive model for guiding therapeutic decision-making.Materials and Methods We conducted a retrospective study on 120 patients with T-LGLL. Lasso regression was performed for feature selection followed by univariate and multivariate Cox regression analysis. A decision tree algorithm was employed to construct a model for predicting overall survival (OS) in T-LGLL.Results The median age of diagnosis for the entire cohort was 59 years, and 76.7% of patients reported disease-related symptoms. After a median follow-up of 75 months, the median OS was not reached. The 5-year OS rate was 82.2% and the 10-year OS rate was 63.8%. Multivariate analysis revealed that an Eastern Cooperative Oncology Group performance status over two and a platelet count below 100 × 109/L were independently associated with worse OS, leading to the development of a simplified decision tree model. The model’s performance was adequate when internally validated. The median OS of the high- and intermediate-risk- risk groups was 43 and 100 months respectively, whereas the median OS of the low-risk group was not reached. Furthermore, we found that immunosuppressive agent-based conventional treatment was unsatisfactory for our high-risk patients.Conclusions Our model is an easily applicable clinical scoring system for predicting OS in patients with T-LGLL. However, external validation is essential before implementing it widely.

Oxidative stress plays an important role in the pathophysiology of gestational diabetes mellitus (GDM). We investigated the relationship between NADPH oxidase p22phox subunit (CYBA) C242T (rs4673) and myeloperoxidase (MPO) G-463A (rs2333227) genetic variants and GDM in 719 patients with GDM and 1205 control women. Clinical, metabolic, and oxidative stress parameters were analyzed. We found that frequencies of the A allele (15.6% vs 12.3%) and GA + AA genotype (28.5% vs 23.2%) of the MPO G-463A variation were significantly higher in patients with GDM than in the control women (OR = 1.318, 95% CI: 1.068–1.625, P = 0.010 for the dominant model; OR = 1.999, 95% CI: 1.040–3.843, P = 0.034 for the recessive model; OR = 1.320, 95% CI: 1.095–1.591, P = 0.004 for the allele model). Genotype GA + AA remained a significant predictor of GDM in a logistic regression model including age and BMI at delivery (OR = 1.282, 95% CI: 1.037‒1.583, P = 0.021). Furthermore, the ‒463A allele was associated with higher TG and the 242T allele was related to higher pre-pregnancy BMI and oxidative stress index in all subjects (P < 0.05). The 242T allele was also associated with higher homeostatic model assessment of insulin resistance but lower serum total antioxidant capacity in patients with GDM (P < 0.05). We conclude that the MPO G-463A, but not the CYBA C242T, genetic variation is associated with an increased risk of GDM in Chinese women. These two genetic polymorphisms may be linked to obesity, dyslipidemia, insulin resistance, and oxidative stress.

With the advent of the internet of things and artificial intelligence, flexible and portable pressure sensors have shown great application potential in human-computer interaction, personalized medicine and other fields. By comparison with traditional inorganic materials, flexible polymeric materials conformable to the human body are more suitable for the fabrication of wearable pressure sensors. Given the consumption of a huge amount of flexible wearable electronics in near future, it is necessary to turn their attention to biodegradable polymers for the fabrication of flexible pressure sensors toward the development requirement of green and sustainable electronics. In this paper, the structure and properties of silk fibroin (SF) are introduced, and the source and research progress of the piezoelectric properties of SF are systematically discussed. In addition, this paper summarizes the advance in the studies on SF-based capacitive, resistive, triboelectric, and piezoelectric sensors reported in recent years, and focuses on their fabrication methods and applications. Finally, this paper also puts forward the future development trend of high-efficiency fabrication and corresponding application of SF-based piezoelectric sensors. It offers new insights into the design and fabrication of green and biodegradable bioelectronics for in vitro and in vivo sensing applications.

Traditional spraying of pesticides causes significant drift losses, and the residues of pesticides can also affect non-targeted organisms in the environment. Tree injection technology is a precise and targeted pesticide delivery method used in the prevention and treatment of tree and fruit tree pest infestations. It uses the tree’s xylem to transport the injected pesticides throughout the entire plant, reducing pesticide exposure in an open environment. This review summarizes the basic principles and development process of tree injection technology, compares its advantages with other application techniques, describes the development of injection equipment and key information to be aware of, and proposes suggestions for future research directions in injection application techniques.

Ethnopharmacological relevance: Viticis Fructus (called Manjingzi in China) is the dried ripe fruits of the plant species Vitex trifolia subsp. litoralis Steenis and Vitex trifolia L. in the family Lamiaceae. Viticis Fructus has been used as a traditional Chinese medicine for thousands of years to treat illness such as colds, headache, vertigo, anesthesia, and hyperkinesias. More chemical constituents and medicinal effects have been discovered in Viticis Fructus with the development of modern technology.The aim of the review: This review aims to analyze the research progress of Viticis Fructus from the aspects of botany, ethnopharmacology, phytochemistry, and pharmacological activity, as well as to provide an outlook on the research and use prospects of Viticis Fructus. Material and methods: A comprehensive literature search using online databases such Science Direct, CNKI, Wiley online library, Spring Link, Web of Science, PubMed, Wanfang Data and SCI-Finder. In addition, information was obtained from local and foreign books on ethnobotany and ethnomedicine. Results: The application of Viticis Fructus as a medicine can be traced back to around 480 AD. So far, more than 190 compounds have been isolated from Viticis Fructus, including flavonoids, sterols, cyclic enol ether terpenoids, and diterpenoids. Modern pharmacological studies have shown that the extracts of Viticis Fructus have various pharmacological effects, such as anti-allergic, antioxidant, anti-inflammatory, anti-cancer, and anti-bacterial effects. Conclusion: As a widely used traditional medicine, Viticis Fructus is rich in chemical compositions and has an obvious biological activity. However, the application and pharmacological activity of Viticis Fructus have not been scientifically evaluated or convincing due to poor methodology, unclear results and lack of clinical data. Systematic and comprehensive research evaluations are needed to verify its pharmaceutical activity, clinical therapeutic efficacy and safety. As an important herbal medicine, it should be further explored to facilitate the development of new medicines and treatments for a variety of diseases.

The perception of facial emotion is not only determined by the physical features of the face itself but also be influenced by the emotional information of the background or surrounding information. However, the details of such effect are not fully understood. Here, the authors tested the perceived emotion of a target face surrounded by stimuli with different levels of emotional valence. In Experiment 1, four types of objects were divided into three groups (negative, unpleasant flowers and unpleasant animals; mildly negative (neutral), houses; positive, pleasant flowers). In Experiment 2, three groups of surrounding faces with different social–emotional valence (negative, neutral, and positive) were formed with the memory of affective personal knowledge. The data from two experiments showed that the perception of facial emotion can be influenced and modulated by the emotional valence of the surrounding stimuli, which can be explained by assimilation: the positive stimuli increased the valence of a target face, while the negative stimuli comparatively decreased it. Furthermore, the neutral stimuli also increased the valence of the target, which could be explained by the social positive effect. Therefore, the process of assimilation is likely to be a high-level emotional cognition rather than a low-level visual perception. The results of this study may help us better understand face perception in realistic scenarios.

Developing brain-protective hypothermia is a medical challenge. Here, the authors show that deep brain stimulation of a particular brain area is a new way to trigger the body into a hibernation-like state with reduced body temperature and brain protection in a mouse model of stroke.

Contrapose the high inertness of para-aramid fiber (AF) with high strength modulus, surface modification in a green and effective way is one of the main challenges currently faced by fiber reinforced composites engineers. In this study, AF was treated by a two-step process combining hot air treatment (250 °C, 1 h) and graft reaction of polyamide acid (PAA) assisted with supercritical carbon dioxide (scCO2). The ester group displayed on the fiber surface suggested the successful graft reaction between AF and PAA. Additionally, the auxiliary effect of scCO2 increases the surface roughness, resulting in a more uniform grafted layer on the modified fiber surface. Specifically, in the process of graft modification of AF with 5% PAA assisted by scCO2, the thickness of the grafted layer was about 100 nm. Meanwhile, a 50.15% increment of the interfacial shear strength indicated an obvious enhancements of surface adhesion. This study provides a feasible method for interfacial modification of AF, and further widens the application of scCO2 as an auxiliary process in the surface modification of AF.

How microsaccades modulate visual coding and perception remains incompletely understood. Here, the authors identify an emerging suppression specific to microsaccade directions that alters responses in macaque V2 and impacts perceptual decisions.

Elasmobranchs are crucial for comparative studies of evolution, as they belong to the most ancient vertebrate lineages that survived numerous extinction events and persist until today. The immunoglobulin new antigen receptor (IgNAR) found in sharks and heavy-chain-only antibody (HCAb) found in camelidae are products of convergent evolution. Although it was previously believed that IgNAR emerged 220 million years ago, before the divergence of sharks and skates, there is limited evidence to support this. In this study, we provide data supporting the existence of IgNAR in the ocellate spot skate (Okamejei kenojei) mononuclear cell transcriptome and peripheral blood serum. Additionally, we characterize the germline gene configuration of the ocellate spot skate IgNAR V domain. The ocellate spot skate IgNAR structure prediction and VNAR crystal structure exhibit high similarity to their shark counterparts. These data strongly suggest that IgNAR in both sharks and skates share a common ancestor. Sequencing of the ocellate spot skate VNAR repertoire provided crucial data for further understanding of the IgNAR generation. Notably, we discovered that approximately 99% of the ocellate spot skate VNARs belonged to type IV. This represents an exceptionally high proportion of type IV within the VNAR repertoire, which has not been documented in previously studied elasmobranchs. This unique characteristic of the ocellate spot skate VNAR adds essential structural diversity to the naïve VNAR library from elasmobranchs and could potentially benefit the development of pharmaceutical drugs.

BackgroundRecent studies have shown that major depressive disorder (MDD) is associated with altered intrinsic functional connectivity (FC) of the thalamus; however, investigations of these alterations at a finer time scale and the level of thalamic subregions are still lacking.MethodsWe collected resting-state functional MRI data from 100 treatment-naïve, first-episode MDD patients and 99 age-, gender- and education-matched healthy controls (HCs). Seed-based whole-brain sliding window-based dFC analyses were performed for 16 thalamic subregions. Between-group differences in the mean and variance of dFC were determined using threshold-free cluster enhancement algorithm. For significant alterations, there relationships with clinical and neuropsychological variables were further examined via bivariate and multivariate correlation analyses.ResultsOf all thalamic subregions, only the left sensory thalamus (Stha) showed altered variance of dFC in the patients characterized by increases with the left inferior parietal lobule, left superior frontal gyrus, left inferior temporal gyrus, and left precuneus, and decreases with multiple frontal, temporal, parietal, and subcortical regions. These alterations accounted for, to a great extent, clinical, and neuropsychological characteristics of the patients as revealed by the multivariate correlation analysis. In addition, the bivariate correlation analysis revealed a positive correlation between the variance of dFC between the left Stha and right inferior temporal gurus/fusiform and childhood trauma questionnaires scores (r = 0.562, P < 0.001).ConclusionThese findings suggest that the left Stha is the most vulnerable thalamic subregion to MDD, whose dFC alterations may serve as potential biomarkers for the diagnosis of the disease.

Hybrid neural networks combine advantages of spiking and artificial neural networks in the context of computing and biological motivation. The authors propose a design framework with hybrid units for improved flexibility and efficiency of hybrid neural networks, and modulation of hybrid information flows.

Abstract This study evaluates the uncertainties of turbulent flux calculation using eddy covariance (EC) and wavelet analysis (WA) methods. First, a non‐stationary data set is concocted by adding periodic waves and random perturbations which mimic the large eddies, turbulent intermittency, and asymmetry into an observational stationary data set, and the theoretical “true” fluxes are used to quantitatively evaluate the accuracy of these methods. Results show that EC and Morlet‐wavelet generate biases ranging 50%–100% of the “true” values at different non‐stationarity grades, whereas the Mexican hat (Mexhat) wavelet has a bias of about half of them. Furthermore, there is a high correlation of the Mexhat‐derived fluxes to the benchmark values, the regression slopes of the values of these two can be improved to almost 1 by adding a correction coefficient. The results suggest the potential of using the Mexhat‐wavelet method to calculate turbulent fluxes with high accuracy under non‐stationary conditions.

Vegetation restoration has always been the focus of ecological research, but the synergistic effect of the soil carbon cycle and vegetation restoration succession process in karst area is still unclear. In this study, the complete succession zones of non-karst, karst, and karst vegetation restoration landforms in a National Nature Reserve, Caohai (Guizhou Province, China), were compared. The content distribution characteristics of SOC, ROC and DOC were investigated, as well as the geomorphology, spatial location and interaction were studied by using GLMM. The results show that the soil types and vegetation coverage of different landforms lead to a decrease in SOC in karst area with an increase in depth. The soil content in karst area was low, and in order to maintain the normal growth of vegetation, the proportion of soil ROC and DOC in SOC must be high, which leads to the order of soil ROC content in unrepaired area > vegetation restoration area > non-karst area. In addition, the content of SOC in the surface layer of the vegetation restoration area was lower than that of the unrepaired area and the non-karst area. The soil microbial activity in the vegetation restoration area is stronger, and more organic carbon was fixed in the plant. The vegetation coverage and diversity increased obviously and markedly as a result of dominant plants changing (from Gramineae to Gramineae + Compositae) in the karst vegetation restoration area, but the soil in the karst area could not provide sufficient nutrition for plants, ultimately resulting in an inverse ratio between surface SOC and vegetation diversity. This study aims to enhance understandings of ecological functions and vegetation restoration in karst areas, as well as responses to regional carbon cycling.

IntroductionCirculating plasma cells (CPC) have been reported to be one of the indicators of high-risk multiple myeloma (MM), yet the prognostic significance of CPC in Chinese population and the genetic mechanisms underlying CPC formation have not been fully elucidated.MethodsPatients with newly diagnosed MM were included in this study. We used multi-parameter flow cytometry (MFC) for CPC quantification and next-generation sequencing (NGS) technology for mutational landscape mapping to identify the correlation of CPC level with clinical characteristics and the mutations.ResultsA total of 301 patients were enrolled in this investigation. We demonstrated that CPC quantification could effectively mirror the tumor load, and CPC ≥ 0.105% at diagnosis or detectable CPC after therapy indicates poor treatment response and adverse outcome, and the introduction of CPC into the R-ISS enables a more accurate risk stratification. Interestingly, we noticed an elevated percentage of light-chain MM in patients with higher CPC. Mutational landscape revealed that patients harboring mutations in TP53, BRAF, DNMT3A, TENT5C, and IL-6/JAK/STAT3 pathway-related genes tended to have higher CPC levels. Gene enrichment analysis demonstrated that pathways involving chromosome regulation and adhesion may be potential mechanisms accounting for CPC formation.DiscussionAccordingly, quantification of CPC may provide a less-invasive and reliable approach for identifying high-risk MM in Chinese population.

Abstract Efficient ethanol oxidation reaction (EOR) is challenging due to the multiple reaction steps required to accomplish full oxidation to CO2 in fuel cells. High‐entropy materials with the adjustable composition and unique chemical structure provide a large configurational space for designing high‐performance electrocatalysts. Herein, a new class of structurally ordered PtRhFeNiCu high‐entropy intermetallics (HEIs) is developed as electrocatalyst, which exhibits excellent electrocatalytic activity and CO tolerance for EOR compared to high‐entropy alloys (HEAs) comprising of same elements. When the HEIs are used as anode catalysts to be assembled into a high‐temperature polybenzimidazole‐based direct ethanol fuel cell, the HEIs achieve a high power density of 47.50 mW/cm2, which is 2.97 times of Pt/C (16.0 mW/cm2). Online gas chromatography measurements show that the developed HEIs have a stronger C–C bond‐breaking ability than corresponding HEAs and Pt/C catalysts, which is further verified by density functional theory (DFT) calculations. Moreover, DFT results indicate that HEIs possess higher stability and electrochemical activity for EOR than HEAs. These results demonstrate that the HEIs could provide a new platform to develop high‐performance electrocatalysts for broader applications.

This paper presents an improved loss calculation method that takes into account the effects of harmonics and skinning effects, thus extending the loss prediction of soft magnetic materials to a larger frequency and induction range. First, the first-order and second-order slew curves are concurrently fitted into a nonlinear Preisach model to determine the hysteresis loss. Then, integrating the effects of high frequency harmonics and high induction, the fixed-point technique based on the H–B magnetic intrinsic relationship is introduced into the finite element calculation in order to calculate the flux density distribution of the silicon steel sheet more accurately. Then, the classical loss at high flux density is further calculated more accurately. Finally, losses for soft magnetic materials in the 1 kHz range are computed under various harmonic excitations. This method is compared to the traditional method and the experimental results, and this method is closer to the experimental results.

Hyaluronic acid is a naturally occurring biopolymer possessing numerous functions within the body including wound repair, cell migration, and cell signaling. Due to its unique physical and chemical properties, it is widely used in health care products, cosmetics, and medicine.In 2021, hyaluronic acid is approved as a new resource food raw material in China, which has attracted widespread attention. Understanding its preparation, separation and purification methods is necessary to promote its industrial development.This article summarizes the physiological functions, preparation methods and preparation trends of HA from different sources, the effect of separation and purification method on HA purity, the application fields of hyaluronic acid, aiming to provide ideas for the development and comprehensive utilization of hyaluronic acid.

Abstract Background Echinacoside (ECH) possesses a wide range of biological activity. This present study analyzes the effect of ECH on cytochrome P450 isozymes (CYPs) activities of human liver microsomes. Methods The effect of ECH on CYPs enzyme activities were studied using the enzyme-selective substrates phenacetin (1A2), chlorzoxazone (2E1), S-mephenytoin (2C19), testosterone (3A4), coumarin (2A6), diclofenac (2C9), paclitaxel (2C8), and dextromethorphan (2D6). The IC50 values for CYP1A2, CYP2E1, CYP2C19, and CYP3A4 isoforms were examined to express the strength of inhibition. Further, the inhibition of CYPs was checked for time-dependent or not, and then fitted with competitive or non-competitive inhibition models. The corresponding parameters were also obtained. Results ECH caused inhibitions on CYP1A2, CYP2E1, CYP2C19 and CYP3A4 enzyme activities in HLMs with IC50 of 21.23, 19.15, 8.70 and 55.42 μM, respectively. The obtained results showed that the inhibition of ECH on CYP3A4 was time-dependent with the KI/K inact value of 6.63/0.066 min− 1·μM− 1. Moreover, ECH inhibited the activity of CYP1A2 and CYP2E1 via non-competitive manners (K i = 10.90 μM and K i = 14.40 μM, respectively), while ECH attenuated the CYP2C19 activity via a competitive manner (K i = 4.41 μM). Conclusions The results of this study indicate that ECH inhibits CYP1A2, CYP2E1, CYP2C19 and CYP3A4 activities in vitro. In vivo and clinical studies are warranted to verify the relevance of these interactions.

Abstract Background Chronic lymphocytic leukemia (CLL) results in increased susceptibility to infections. T cell dysfunction is not associated with CLL in all patients; therefore, it is important to identify CLL patients with T cell defects. The role of B-cell lymphoma-2 (BCL-2) in CLL has been explored; however, few studies have examined its role in T cells in CLL patients. Herein, we have investigated the regulatory role of BCL-2 in T cells in the CLL tumor microenvironment. Methods The expression of BCL-2 in T cells was evaluated using flow cytometry. The regulatory roles of BCL-2 were investigated using single-cell RNA sequencing (scRNA-seq) and verified using multi-parameter flow cytometry on CD4 and CD8 T cells. The clinical features of BCL-2 expression in T cells in CLL were also explored. Results We found a significant increase in BCL-2 expression in the T cells of CLL patients (n = 266). Single cell RNA sequencing (scRNA-seq) indicated that BCL-2+CD4+ T cells had the gene signature of increased regulatory T cells (Treg); BCL-2+CD8+ T cells showed the gene signature of exhausted cytotoxic T lymphocytes (CTL); and increased expression of BCL-2 was associated with T cell activation and cellular adhesion. The results from scRNA-seq were verified in peripheral T cells from 70 patients with CLL, wherein BCL-2+CD4+ T cells were enriched with Tregs and had higher expression of interleukin-10 and transforming growth factor-β than BCL-2−CD4+ T cells. BCL-2 expression in CD8+T cells was associated with exhausted cells (PD-1+Tim-3+) and weak expression of granzyme B and perforin. T cell–associated cytokine profiling revealed a negative association between BCL-2+ T cells and T cell activation. Decreased frequencies and recovery functions of BCL-2+T cells were observed in CLL patients in complete remission after treatment with venetoclax. Conclusion BCL-2 expression in the T cells of CLL patients is associated with immunosuppression via promotion of Treg abundance and CTL exhaustion.

Global and local learning represent two distinct approaches to artificial intelligence. In this manuscript, Wu et al present a hybrid learning strategy, drawing from elements of both approaches, and implement it on a co-designed neuromorphic platform.

How brightness is encoded in the visual cortex remains incompletely understood. By recording from macaque V1, the authors revealed a switch from surface to edge encoding that is mediated by widespread inhibition in the output layers of the cortex.

Abstract Background For the encoding part of U-Net3+,the ability of brain tumor feature extraction is insufficient, as a result, the features can not be fused well during up-sampling, and the accuracy of segmentation will reduce. Methods In this study, we put forward an improved U-Net3+ segmentation network based on stage residual. In the encoder part, the encoder based on the stage residual structure is used to solve the vanishing gradient problem caused by the increasing in network depth, and enhances the feature extraction ability of the encoder which is instrumental in full feature fusion when up-sampling in the network. What’s more, we replaced batch normalization (BN) layer with filter response normalization (FRN) layer to eliminate batch size impact on the network. Based on the improved U-Net3+ two-dimensional (2D) model with stage residual, IResUnet3+ three-dimensional (3D) model is constructed. We propose appropriate methods to deal with 3D data, which achieve accurate segmentation of the 3D network. Results The experimental results showed that: the sensitivity of WT, TC, and ET increased by 1.34%, 4.6%, and 8.44%, respectively. And the Dice coefficients of ET and WT were further increased by 3.43% and 1.03%, respectively. To facilitate further research, source code can be found at: https://github.com/YuOnlyLookOne/IResUnet3Plus . Conclusion The improved network has a significant improvement in the segmentation task of the brain tumor BraTS2018 dataset, compared with the classical networks u-net, v-net, resunet and u-net3+, the proposed network has smaller parameters and significantly improved accuracy.

Ecosystems away from human disturbance provide an ideal paradigm for microbial ecology research. The Burqin glacier No. 18 in the Chinese Altay Mountains is such an ecosystem; however, there are no prior studies on the microbiology in the area. Here, we isolated 902 bacterial strains on the Burqin glacier No. 18 to determine the diversity and distribution characteristics of microorganisms. Isolated strains belonged to six phyla (in the order of dominance: Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Deinococcus-Thermus) and 90 genera. Our results also demonstrated the presence of a high proportion of potential new species (43%) in the Burqin glacier No. 18, and 67% of the potential new species were isolated at 25 °C. Species diversity varied among habitats, with the lowest diversity in surface ice and the highest diversity in the soil farthest from the glacier terminus. The pigmented colonies made up 52.7% of all isolates, with yellow-colored colonies being the most abundant (18.8%). This study indicates that the Burqin glacier No. 18 hosts rich bacterial strain diversity, and may represent a significant potential source of new functional and pigmented bacteria for the development of critical pharmaceuticals.