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Chemoautotrophic denitrification plays an important role in nitrogen removal and the formation of a greenhouse gas (N2O) in aquatic environments. Natural stable isotopes support the tracing of nitrogen sources and the identification of biogeochemical processes in field research. However, the isotopic characteristics of N2O produced during chemoautotrophic denitrification have not been investigated so far. In this study, we analyzed isotopic signatures of nitrate and N2O in sulfur‐ and thiosulfate‐dependent denitrifying enrichments obtained from freshwater lakes. Chemoautotrophic denitrification exhibited a nitrate isotope pattern similar to heterotrophic denitrification: the 18ε/15ε‐nitrate followed a ratio close to 1. However, chemoautotrophic denitrification produced N2O with lower δ15N, δ18O, and higher site preference (SP = δ15Nα‐δ15Nβ) values, compared to heterotrophic denitrification. The SP value, approximately 5.1‰, was characteristic in detecting chemoautotrophic denitrification driven by different sulfur forms. δ18O varied with specific electron donors, around 20‰ and 40‰ during sulfur‐ and thiosulfate‐dependent denitrification, respectively. The unique N2O isotope characteristics were likely regulated by nitric oxide reductases of Burkholderiaceae populations during sulfur‐dependent denitrification and Sulfurovum during thiosulfate‐dependent denitrification. These findings improve our understanding of N2O production processes and have important implications for predicting N2O emissions at a greater spatial and temporal resolution. [ABSTRACT FROM AUTHOR]

This article discusses a case study of a Chinese family with hypotrichosis simplex, a rare hair loss disorder. The researchers identified two novel mutations in the LSS gene through whole-exome sequencing and confirmed them through Sanger sequencing. Protein modeling and enzyme-linked immunosorbent assay (ELISA) were used to assess the mutations' impact on the LSS protein structure and expression. The study provides valuable insights into the genetic basis of hypotrichosis simplex and its association with the LSS gene. [Extracted from the article]

Background: Retinal detachment (RD) is a vision-threatening disorder of significant severity. Individuals with high myopia (HM) face a 2 to 6 times higher risk of developing RD compared to non-myopes. The timely identification of high myopia-related retinal detachment (HMRD) is crucial for effective treatment and prevention of additional vision impairment. Consequently, our objective was to streamline and validate a machine-learning model based on clinical laboratory omics (clinlabomics) for the early detection of RD in HM patients. Methods: We extracted clinlabomics data from the electronic health records for 24,440 HM and 5607 HMRD between 2015 and 2022. Lasso regression analysis assessed fifty-nine variables, excluding collinear variables (variance inflation factor > 10). Four models based on random forest, gradient boosting machine (GBM), generalized linear model, and Deep Learning Model were trained for HMRD diagnosis and employed for internal validation. An external test of the models was done. Three random data sets were further processed to validate the performance of the diagnostic model. The primary outcomes were the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUCPR) to diagnose HMRD. Results: Nine variables were selected by all models. Given the AUC and AUCPR values across the different sets, the GBM model was chosen as the final diagnostic model. The GBM model had an AUC of 0.8550 (95%CI = 0.8322–0.8967) and an AUCPR of 0.5584 (95%CI = 0.5250–0.5879) in the training set. The AUC and AUCPR in the internal validation were 0.8405 (95%CI = 0.8060–0.8966) and 0.5355 (95%CI = 0.4988–0.5732). During the external test evaluation, it reached an AUC of 0.7579 (95%CI = 0.7340–0.7840) and an AUCPR of 0.5587 (95%CI = 0.5345–0.5880). A similar discriminative capacity was observed in the three random data sets. The GBM model was well-calibrated across all the sets. The GBM-RD model was implemented into a web application that provides risk prediction for HM individuals. Conclusion: GBM algorithms based on nine features successfully predicted the diagnosis of RD in patients with HM, which will help ophthalmologists to establish a preliminary diagnosis and to improve diagnostic accuracy in the clinic. [ABSTRACT FROM AUTHOR]

• Realizing a high removal efficiency of Al impurity from cathode powder collected in a peeling and recycling production line of spent Li-ion batteries. • Proposing a novel discovery that fluorine was also leached along with the process of Al removal. • Evaluation of kinetics analysis to the leaching of Al and F. • Realizing a low leaching efficiency of valuable metals including Ni, Co, and Mn. • Investigation and analysis of leaching conditions. The high content of aluminum (Al) impurity in the recycled cathode powder seriously affects the extraction efficiency of Nickel, Cobalt, Manganese, and Lithium resources and the actual commercial value of recycled materials, so Al removal is crucially important to conform to the industrial standard of spent Li-ion battery cathode materials. In this work, we systematically investigated the leaching process and optimum conditions associated with Al removal from the cathode powder materials collected in a wet cathode-powder peeling and recycling production line of spent Li-ion batteries (LIBs). Moreover, we specifically studied the leaching of fluorine (F) synergistically happened along with the removal process of Al, which was not concerned about in other studies, but one of the key factors affecting pollution prevention in the recovery process. The mechanism of the whole process including the leaching of Al and F from the cathode powder was indicated by using NMR, FTIR, and XPS, and a defluoridation process was preliminarily investigated in this study. The leaching kinetics of Al could be successfully described by the shrinking core model, controlled by the diffusion process and the activation energy was 11.14 kJ/mol. While, the leaching of F was attributed to the dissolution of LiPF 6 and decomposition of PVDF, and the kinetics associated was described by Avrami model. The interaction of Al and F is advantageous to realize the defluoridation to some degree. It is expected that our investigation will provide theoretical support for the large-scale recycling of spent LIBs. [ABSTRACT FROM AUTHOR]

Quantitative phase imaging (QPI) provides 3D structural and morphological information for label free living cells. Unfortunately, this quantitative phase information cannot meet doctors' diagnostic requirements of the clinical "gold standard," which displays stained cells' pathological states based on 2D color features. To make QPI results satisfy the clinical "gold standard," the virtual staining method by QPI for label free lymphocytes based on self-supervised iteration Cycle-Consistent Adversarial Networks (CycleGANs) is proposed herein. The 3D phase information of QPI is, therefore, trained and transferred to a kind of 2D "virtual staining" image that is well in agreement with "gold standard" results. To solve the problem that unstained QPI and stained "gold standard" results cannot be obtained for the same label free living cell, the self-supervised iteration for the CycleGAN deep learning algorithm is designed to obtain a trained stained result as the ground truth for error evaluation. The structural similarity index of our virtual staining experimental results for 8756 lymphocytes is 0.86. Lymphocytes' area errors after converting to 2D virtual stained results from 3D phase information are less than 3.59%. The mean error of the nuclear to cytoplasmic ratio is 2.69%, and the color deviation from the "gold standard" is less than 6.67%. [ABSTRACT FROM AUTHOR]

With the transformation and upgrading of the manufacturing industry and the advent of the industrial revolution, the complexity of part structures and the variety of materials have increased. The demand for cutting tool performance is becoming increasingly diverse, posing numerous challenges to the design and development of tools. By studying natural cutting phenomena, scholars have discovered that biological structures such as teeth and claws possess unique characteristics. The design and development of tools based on the imitation of these biological structures have become a new research direction. To address the high energy consumption and reduce cutting resistance in the cutting process, limpet teeth were prepared, and their geometric features were extracted. The structural features of limpet teeth were applied to the design of tool structures, and five bionic tools were designed and fabricated. Taking cutting force as the performance indicator, the cutting performance of the bionic tools was investigated by comparing them with conventional tools. The analysis of cutting forces found that effortless tool exhibited a significant force-saving effect, with a reduction in cutting force by 16.2%. Through a single-factor experiment, the influence of cutting parameters on the effortless tool was explored. The results showed that limpet bionic cutting tools with appropriate size parameters exhibited a significant force-saving effect, improving tool cutting performance. [ABSTRACT FROM AUTHOR]

The stable isotope technique has been used in tracking nitrogen cycling processes, but the isotopic characteristics are influenced by environmental conditions. To better understand the variability of nitrate isotopes in nature, we investigated the influence of organic carbon sources on isotope fractionation characteristics during microbial denitrification. Denitrifying cultures were inoculated with freshwater samples and enriched with five forms of organic compounds, that is, acetate, citrate, glucose, cellobiose, and leucine. Though the isotope enrichment factors of nitrogen and oxygen (15ε and 18ε) changed with carbon sources, 18ε/15ε always followed a proportionality near 1. Genome‐centred metagenomics revealed the enrichment of a few populations, such as Pseudomonas, Enterobacter, and Atlantibacter, most of which contained both NapA‐ and NarG‐type nitrate reductases. Metatranscriptome showed that both NapA and NarG were expressed but to different extents in the enrichments. Furthermore, isotopic data collected from a deep reservoir was analysed. The results showed δ18O‐ and δ15N‐nitrate did not correlate in the surface water where nitrification was active, but 18ε/15ε followed a proportionality of 1.05 ± 011 in deeper waters (≥ 12 m) where denitrification controlled the nitrate isotope. The independence of 18ε/15ε from carbon sources provides an opportunity to determine heterotrophic denitrification and helps the interpretation of nitrate isotopes in freshwaters. [ABSTRACT FROM AUTHOR]

Sulphur‐driven denitrification is a low‐cost process for the treatment of nitrate‐contaminated water. However, a comprehensive understanding of core populations and microbial interactions of a sulphur‐based denitrifying system is lacking. This study presents results from three replicated denitrifying systems amended with thiosulphate and operated under a low C/N ratio. Amplicon sequencing revealed gradual enrichments of a few abundant denitrifiers. Based on genome‐centred metagenomics and metatranscriptomics, a core set of microbes was identified in the systems, with Pseudomonas 1 and Thauera 2 being the most abundant ones. Although the replicates showed different enrichments, generalized observations were summarized. Most core populations conserved energy from denitrification coupled with sulphur. Pseudomonas 1 and Thauera 2 were able to finish complete denitrification. Surprisingly, they were also able to synthesize almost all amino acids and vitamins. In contrast, less abundant members, including Pseudomonas 2, were relatively auxotrophic and required an exogenous supply of amino acids and vitamins. The high expression of enzymes involved in biosynthesis and transport systems indicated their syntrophic relationships. The genomic findings suggested life strategies and interactions of the core thiosulphate‐based denitrifying microbiome, with implications for nitrate‐polluted water remediation. [ABSTRACT FROM AUTHOR]

The cross-linked conjugated polymer poly(tetraphenylethene-co-biphenyl) (PTPEBP) nanoparticles were prepared by Suzuki-miniemulsion polymerization. The structure, morphology, and pore characteristics of PTPEBP nanoparticles were characterized by FTIR, NMR, SEM, and nitrogen adsorption and desorption measurements. PTPEBP presents a spherical nanoparticle morphology with a particle size of 56 nm; the specific surface area is 69.1 m2/g, and the distribution of the pore size is centered at about 2.5 nm. Due to the introduction of the tetraphenylethene unit, the fluorescence quantum yield of the PTPEBP nanoparticles reaches 8.14% in aqueous dispersion. Combining the porosity and nanoparticle morphology, the fluorescence sensing detection toward nitroaromatic explosives in the pure aqueous phase has been realized. The Stern–Volmer quenching constant for 2,4,6-trinitrophenol (TNP) detection is 2.50 × 104 M−1, the limit of detection is 1.07 μM, and the limit of quantification is 3.57 μM. Importantly, the detection effect of PTPEBP nanoparticles toward TNP did not change significantly after adding other nitroaromatic compounds, indicating that the anti-interference and selectivity for TNP detection in aqueous media is remarkable. In addition, the spike recovery test demonstrates the potential of PTPEBP nanoparticles for detecting TNP in natural environmental water samples. [ABSTRACT FROM AUTHOR]

As the interest in "natural" and "safe" products grows, the use of natural products instead of synthetic preservatives to combat food spoilage and poisoning caused by microorganisms during processing and storage has become a prioritized option. The present research evaluated the antibacterial activity of the Mentha longifolia L. essential oil (MLEO) against several pathogenic bacteria, and the mechanism of action against methicillin‐resistant Staphylococcus aureus (MRSA). Gas Chromatography Quadrupole Time‐of‐Flight Mass Spectrometry (GC‐Q‐TOF MS) analysis suggested that main components of MLEO were carvone (47.39%) and limonene (12.48%). The oil showed considerable antibacterial activity with MIC values of 0.394–1.576 mg/mL, and could be a promising bactericide. Non‐targeted metabolomics analysis based on GC‐Q‐TOF MS identified 66 different metabolites, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of these metabolites revealed that MLEO achieves the effects by affecting amino acid metabolism in MRSA. [ABSTRACT FROM AUTHOR]

Simple Summary: The prognosis of patients with primary central nervous system lymphoma (PCNSL) is poor due to the high recurrence rate and lack of consensus on the optimal treatment for refractory or relapsed diseases. Despite having good prognostic scores, such as an MSKCC score or IELSG score, none of them are able to fully explain the clinical outcomes of patients with PCNSL, and they are complicated at the same time. Thus, there is an urgent need to develop simple and readily available parameters that help to stratify the prognosis of patients, especially those at high risk, and provide them with appropriate treatment measures. For the first time, this study identified that pretreatment serum total bilirubin (STB) could predict the prognosis of patients with PCNSL receiving high-dose methotrexate-based combination immunochemotherapy. The results from this study demonstrate that STB is a simple, cost-effective prognostic biomarker that clinicians can apply easily and quickly into routine practice. Primary central nervous system lymphoma (PCNSL) is a predominantly aggressive neoplasm isolated to the central nervous system or vitreoretinal space. Bilirubin is an important biomarker reflecting hepatic function and oxidative stress status that is associated with the occurrence and development of various tumors. However, its prognostic role in PCNSL has yet to be evaluated. Therefore, we conducted a prospective–retrospective study to analyze the predictive value of serum total bilirubin (STB) in PCNSL patients. The association between the pretreatment STB and clinical outcomes in PCNSL was developed in the discovery cohort (retrospective [n = 44] and prospective [n = 45]) and validated in an independent retrospective cohort (n = 69). A generalized additive model, Kaplan–Meier curve, and Cox analysis were applied. In the discovery cohort, the STB showed a linear relationship with overall survival (OS, p = 0.011) and progression-free survival (PFS, p = 0.0476). The median STB level of 12.0 µmol/L was determined as the cutoff value to predict the clinical outcomes with area under the receiver operating characteristic curve (AUROC) values of 0.9205 and 0.8464 for OS and PFS, respectively. The median STB level resulted in similar accuracy for predicting the clinical outcomes in the validation cohort with AUROC values of 0.8857 and 0.8589 for OS and PFS, respectively. In both the discovery and validation cohorts, the Kaplan–Meier survival curve and Cox regression analysis showed that the upper median STB groups showed significantly worse OS than the lower median STB groups. In conclusion, the pretreatment STB could be considered a novel biomarker to predict the clinical outcomes in patients with PCNSL receiving high-dose methotrexate-based combination immunochemotherapy. [ABSTRACT FROM AUTHOR]

Red cultural heritage is precious material and spiritual wealth, and is a non renewable cultural heritage with unique characteristics and protection value. In this paper, red cultural heritage in Mentougou District is taken as the research object. Through GIS, the classification and spatial distribution characteristics of the red cultural heritage in Mentougou are analyzed. On this basis, the analytic hierarchy process (AHP) is introduced to conduct quantitative value evaluation, determine evaluation factors and weights, and form a more systematic and scientific evaluation system suitable for Mentougou red cultural heritage. This paper aims to provide technical and methodological references for the evaluation and planning of the protection and utilization of red cultural heritage, and more scientifically protect and inherit red cultural heritage. [ABSTRACT FROM AUTHOR]

Acetaminophen (APAP) overdose is the most common driver of drug-induced liver injury (DILI) worldwide, and the gut microbiome plays a crucial role in this process. In this study, we estimated the effect of Bifidobacterium longum R0175 on APAP-induced liver injury in mice and discovered that B. longum R0175 alleviated liver injury by diminishing inflammation, reducing oxidative stress levels, inhibiting hepatocyte death and improving APAP-induced microbiome dysbiosis. Further studies revealed that the antioxidative effects of B. longum R0175 were primarily due to activation of the Nrf2 pathway, which was supported by the Nrf2 pathway inhibitor ML385 counteracting these ameliorative effects. B. longum R0175 modified intestinal metabolites, especially the key metabolite sedanolide, which could activate the Nrf2 pathway and contribute to the protective effects against APAP-induced liver injury. Moreover, we found that sedanolide exhibited close interrelationships with specific microbial taxa, indicating that this factor may be derived from gut microbes. In conclusion, our work demonstrated that B. longum R0175 could reduce oxidative damage, inflammation and hepatocyte death by activating the Nrf2 pathway. Importantly, we identified the microbiota-derived metabolite sedanolide, which was first discovered in the mouse intestine, as a key agonist of the Nrf2 pathway and primary effector of B. longum R0175 in APAP challenge. These findings provide new perspectives for APAP overdose therapy and demonstrate the enormous potential of B. longum R0175 in alleviating acute liver injury. [Display omitted] • B. longum R0175 alleviated APAP-induced liver injury by diminishing inflammation, oxidative stress levels and hepatocyte death. • B. longum R0175 modified key metabolite sedanolide which could activate the Nrf2 pathway and exert protective effects. • Sedanolide was identified as a microbiota-derived metabolite for its correlation with specific microbes. [ABSTRACT FROM AUTHOR]

In this article, optimality conditions on (weak) efficient solutions in multiobjective optimization problems are investigated by using the image space analysis. A class of strong separation functions is constructed by oriented distance functions. Simultaneously, a generalized Lagrange function is introduced by the class of strong separation functions. Then, generalized Karush-Kuhn-Tucker (KKT for short) necessary optimality conditions are established without constraint qualifications or regularity conditions. Under the suitable assumptions, Lagrangian-type sufficient optimality conditions are also characterized. Moreover, the difference between strong separation and weak separation methods is explained. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the leading cause of dementia in aged population. Oxidative stress and neuroinflammation play important roles in the pathogenesis of AD. Investigation of hub genes for the development of potential therapeutic targets and candidate biomarkers is warranted. The differentially expressed genes (DEGs) in AD were screened in GSE48350 dataset. The differentially expressed oxidative stress genes (DEOSGs) were analyzed by intersection of DEGs and oxidative stress-related genes. The immune-related DEOSGs and hub genes were identified by weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis, respectively. Enrichment analysis was performed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The diagnostic value of hub genes was assessed by receiver operating characteristic analysis and validated in GSE1297. The mRNA expression of diagnostic genes was determined by qRT-PCR analysis. Finally, we constructed the drug, transcription factors (TFs), and microRNA network of the diagnostic genes. A total of 1160 DEGs (259 up-regulated and 901 down-regulated) were screened in GSE48350. Among them 111 DEOSGs were identified in AD. Thereafter, we identified significant difference of infiltrated immune cells (effector memory CD8 T cell, activated B cell, memory B cell, natural killer cell, CD56 bright natural killer cell, natural killer T cell, plasmacytoid dendritic cell, and neutrophil) between AD and control samples. 27 gene modules were obtained through WGCNA and turquoise module was the most relevant module. We obtained 66 immune-related DEOSGs by intersecting turquoise module with the DEOSGs and identified 15 hub genes through PPI analysis. Among them, 9 hub genes (CCK, CNR1, GAD1, GAP43, NEFL, NPY, PENK, SST, and TAC1) were identified with good diagnostic values and verified in GSE1297. qRT-PCR analysis revealed the downregulation of SST, NPY, GAP43, CCK, and PENK and upregulation of NEFL in AD. Finally, we identified 76 therapeutic agents, 152 miRNAs targets, and 91 TFs regulatory networks. Our study identified 9 key genes associated with oxidative stress and immune reaction in AD pathogenesis. The findings may help to provide promising candidate biomarkers and therapeutic targets for AD. [ABSTRACT FROM AUTHOR]

This paper concentrates on necessary conditions for properly efficient solutions in nonsmooth multiobjective optimization problems. We first present a generalization of Tucker's alternative theorem for conic nonlinear systems, provided that a closedness condition holds. Some sufficient conditions for the validity of such a closedness condition are given. As applications, under the weak Abadie regularity condition, we then establish the primal and the strong Karush/Kuhn–Tucker (dual) necessary optimality conditions for an efficient solution to be locally properly efficient in Borwein's sense. The primal and the dual conditions are formulated as an equivalent pair by means of the Tucker-type alternative results. Finally we give an example to illustrate that Borwein's locally properly efficient solution cannot be reduced to the only efficient one in the main results. [ABSTRACT FROM AUTHOR]

This paper is concerned with nonconvex nonsmooth uncertain multiobjective optimization problems, in which the decision variable of both objective and constraint functions is defined on Banach space while uncertain parameters are defined on arbitrary nonempty (may not be compact) sets. We employ the Stone–C̆ech compactification of uncertainty sets and the upper semicontinuous regularization of original functions with respect to uncertain parameters, giving rise to unified robust necessary optimality conditions for the local robust weakly efficient solution of the considered problem. Moreover, we derive weak and strong KKT robust necessary conditions via the constraint qualification and the regularity condition, respectively. Several examples are provided to illustrate the validity of our results. [ABSTRACT FROM AUTHOR]

Microbial nitrate reduction can be driven by organic carbon oxidation, as well as by inorganic electron donors, such as reduced forms of sulfur and iron. An apparent inverse oxygen isotope fractionation effect was observed during nitrate reduction in sediment incubations from five sampling sites of a freshwater lake, Hongze Lake, China. Incubations with organic and inorganic electron donor additions were performed. Especially, the inverse oxygen isotope effect was intensified after glucose addition, whereas the incubations with sulfide and Fe2+ showed normal fractionation factors. Nitrate reductase encoding genes, napA and narG, were analysed with metagenomics. Higher napA/narG ratios were associated with higher oxygen fractionation factors. The most abundant clade (59%) of NapA in the incubation with glucose was affiliated with Rhodocyclales. In contrast, it only accounted for 8%–9% of NapA in the incubations with sulfide and Fe2+. Differences in nitrate reductases might explain different oxygen isotope effects. Our findings also suggested that large variance of O‐nitrate isotope fractionations might have to be considered in the interpretation of natural isotope records. [ABSTRACT FROM AUTHOR]

Most of siamese network and correlation filter (CF) based trackers usually employ the context regression scheme to achieve appealing performance in both accuracy and efficiency. However, they are prone to drifting in challenging situations exhibiting occlusion, out-of-view and large-scale variations due to the lack of failure correction ability in these regressors. Particle filter based trackers can help to recover from tracking failures since several particles of high confidence about the target can be remained for the probability estimation of next frames, but need the large numbers of particles for each frame. In this paper, we propose a generic dynamic particle filter framework, which can reasonably control the number of particles in different scenarios, to improve the robustness of siamese and CF trackers by jointing the target classifier to relieve drifting. Our fundamental insight is that general scenarios are processed efficiently by the context regressor with few particles, while special scenarios are handled effectively by the target classifier with many particles. We propose a novel measure to determine whether to adopt the regressor and few particles to estimate target states with high measure scores, or increase the number of particles to prevent drifting with the proposed multi-template matching strategy in the classifier. In extensive experiments on eight large-scale benchmarks including OTB, UAV, TC128, VOT2017, VOT2019, LaSOT, TrackingNet and Got-10k, the proposed framework enables many basic siamese and CF trackers to operate at least over 24 frames per second and achieve superior tracking performance than themself, as well as the comparable accuracy with the state-of-the-art trackers. Furthermore, our framework is flexible and still has great potential for improvement and generalization. [ABSTRACT FROM AUTHOR]

This paper focus on the quantitative stability of a class of two-stage stochastic linear variational inequality problems whose second stage problems are stochastic linear complementarity problems with fixed recourse matrix. Firstly, we discuss the existence of solutions to this two-stage stochastic problems and its perturbed problems. Then, by using the corresponding residual function, we derive the quantitative stability of this two-stage stochastic problem under Fortet-Mourier metric. Finally, we study the sample average approximation problem, and obtain the convergence of optimal solution sets under moderate assumptions. [ABSTRACT FROM AUTHOR]

Robot comprehensive performance optimization is a high dimensional non-convex problem, which is of great significance in the practice of robotic intelligent manufacturing. Existing methods still face many challenges in performance evaluation, local optima, and planning efficiency. In this paper, a novel method based on accelerated gradient descent and directed-mutagenesis genetic algorithm (AGD-DGA) is proposed for efficient robotic motion planning and comprehensive performance optimization. Firstly, the time, energy consumption, and impact (T-E-I) are taken as the optimization objectives. In particular, the power loss sub-model is constructed, which is rarely considered in the previous research on motion optimization, and it is combined with the driving power sub-model to improve the evaluation accuracy. Next, a novel directed-mutagenesis genetic algorithm (DGA) is proposed to address the local optima problem. Compared with existing methods based on random sampling, the DGA further improves the success rate and efficiency by updating the probability model based on the adaptive Gaussian process. Moreover, a hierarchical weight updating mechanism is established to overcome the impact of additional performance indicators on the success rate of collision-free path planning. To improve planning efficiency, an incremental optimization mechanism and an adaptive fine-tuning strategy for population size are proposed to reduce unnecessary sampling, evaluation, and sorting. The simulation and experimental results in different scenarios demonstrate that the proposed AGD-DGA achieves better results than most of the mainstream algorithms in terms of optimization efficiency, success rate, and motion performance. In addition, it is also verified that the modified energy consumption model can achieve an average evaluation accuracy of more than 90% while maintaining the calculation efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the recession cone and recession function in the nonconvex case. By virtue of the recession function, we investigate the monotonicity of a function. Then, we obtain a characterization of the Lipschitz continuity for a function by using the recession function. As applications, we study the monotonicity and Lipschitz continuity properties of the optimal value function for a parametric constrained optimization problem. Moreover, we present a characterization of the nonemptiness and boundedness of the solution set for a constrained optimization problem without convexity assumption. [ABSTRACT FROM AUTHOR]

Synthetic hydrogels are unique tissue mimics but rarely reproduce the strain‐stiffening properties of native tissues. This mechanical mismatch impairs the performance of hydrogels in practical applications. Inspired by the crimped structure of collagenous tissues, a series of strain‐stiffening hydrogels composed of curved parallel fibers are developed. These fibers are constructed from a bundle of intertwisted nanofibrils composed of short alkyl side chain‐modified polymer chains. This hierarchical organization enables exquisitely cascaded deformation that facilitates soft‐to‐firm and resilience‐to‐viscoelasticity transitions, thus synergically mimicking the strain‐adaptive stiffening and damping behaviors of natural tissues. Together with structural evolution and a constitutive model, rationally tuning the tortuosity and flexibility of the curved fibers produces a diverse combination of strain‐stiffening properties and unprecedented penetration into the regions of several tissues. The crimped structure and the resultant stiffening properties constitute major improvements to nanofiber‐based scaffolds for use in collagenous tissue repair. [ABSTRACT FROM AUTHOR]

Summary: Impaired wound closure is an increasingly crucial clinical challenge. Recently, wound healing has shifted towards innovative treatments that exploit nanotechnology, biomaterials, biologics and phototherapy. Here, we constructed an engineered MG1363‐pMG36e‐mCXCL12 strain with pMG36e plasmid encoding stromal cell‐derived factor 1α (named CXCL12) and evaluated the synergistic effects of light‐emitting diode (LED) yellow light and MG1363‐pMG36e‐mCXCL12 on scald wounds in mice. The results indicated that the combined treatment with LED yellow light with mCXCL12 delivering strain accelerated wound closure, tissue remodelling, re‐epithelialization and hair follicle regeneration and inhibited over‐inflammation oppositely in the central and surrounding wounds by macroscopic, histopathologic and immunohistochemistry parameters. Furthermore, combination therapy increased the epidermal growth factor and Ki67‐positive cells and upregulated beta‐catenin (β‐catenin), cellular‐myelocytomatosis (c‐Myc), wingless‐type MMTV integration site family member 1 (Wnt1), Jagged 1, neurogenic locus notch homolog protein 1 (Notch 1) and hairy and enhancer of split 1 (Hes 1) protein levels of the Wnt and Notch signalling pathways. It also facilitated collagen fibrogenesis and deposition and improved the activities of hydroxyproline, superoxide dismutase and glutathione peroxidase in scalded granulation tissue, in addition to reducing the inflammatory factors interleukin 1 beta (IL‐1β) and tumour necrosis factor alpha (TNF‐α). The combined treatment effectively reduced skin pathogens Ralstonia and Acinetobacter to further reduce the risk of infection. Overall, combination of LED yellow light and MG1363‐pMG36e‐mCXCL12 represents a potential strategy for the treatment of cutaneous wounds. [ABSTRACT FROM AUTHOR]

Sample average approximation (SAA) approach for two-stage stochastic variational inequalities (SVIs) with continuous probability distributions, where the second-stage problems have multiple solutions, may not promise convergence assertions as the sample size tends to infinity. In this paper, a regularized SAA approach is proposed to numerically solve a class of two-stage SVIs with continuous probability distributions, where the second-stage problems are monotone and allowed to have multiple solutions. We first give some structural properties. After that, the convergence analysis of the regularized SAA approach for two-stage SVIs is investigated as the regularization parameter tends to zero and the sample size tends to infinity. Finally, we employ the progressive hedging algorithm to report some numerical results. [ABSTRACT FROM AUTHOR]

This research proposes constructing a network used for person re-identification called MGNACP (Multiple Granularity Network with Attention Mechanisms and Combination Poolings). Based on the MGN (Multiple Granularity Network) that combines global and local features and the characteristics of the MGN branch, the MGNA (Multiple Granularity Network with Attentions) is designed by adding a channel attention mechanism to each global and local branch of the MGN. The MGNA, with attention mechanisms, learns the most identifiable information about global and local features to improve the person re-identification accuracy. Based on the constructed MGNA, a single pooling used in each branch is replaced by combination pooling to form MGNACP. The combination pooling parameters are the proportions of max pooling and average pooling in combination pooling. Through experiments, suitable combination pooling parameters are found, the advantages of max pooling and average pooling are preserved and enhanced, and the disadvantages of both types of pooling are overcome, so that poolings can achieve optimal results in MGNACP and improve the person re-identification accuracy. In experiments on the Market-1501 dataset, MGNACP achieved competitive experimental results; the values of mAP and top-1 are 88.82% and 95.46%. The experimental results demonstrate that MGNACP is a competitive person re-identification network, and that the attention mechanisms and combination poolings can significantly improve the person re-identification accuracy. [ABSTRACT FROM AUTHOR]

Purpose. Red blood cell distribution width (RDW) has been regarded as an emerging biomarker of the general population and cardiovascular disease. In this study, we aimed to evaluate the association between RDW and diabetic retinopathy (DR). Methods. This case-control study included 167 patients with DR, 131 patients with diabetes mellitus (DM), and 170 age- and sex-matched healthy controls from April 2014 to May 2019. Demographic data, laboratory parameters, and ocular examinations were collected. Results. RDW values of the DR group were significantly higher than those of the healthy control (p < 0.001) and DM group (p = 0.002). A similar trend was observed when RDW was compared among the 3 groups with respect to age and gender. Logistic regression analysis has shown the OR of RDW was 3.791 (2.33–6.168; p < 0.001) against the control group and was 1.348 (0.997–1.823; p = 0.047) against the DM group. Conclusion. RDW values were significantly elevated in DR patients, and an elevated RDW was associated with an increased incidence of DR in patients with DM. [ABSTRACT FROM AUTHOR]

We present an unconstrained optimization reformulation for the stochastic nonlinear complementarity problem in this paper, which aims at minimizing an expected residual defined by the D-gap function. We discuss the existence of a solution to the unconstrained expected residual minimization (UERM) problem. By the quasi-Monte Carlo method, we obtain the discrete approximations of the UERM problem and prove that every accumulation point of minimizers or stationary points of discrete approximation problem is La minimum or stationary point of the UERM problem. We finally apply the UERM formulation to the traffic equilibrium problem. [ABSTRACT FROM AUTHOR]

• Aptamers with broad-spectrum recognition abilities were constructed. • SERS imaging analysis platform for high-throughput detection was developed. • This provides prospects for exploring novel SERS sensing and imaging strategies. Surface-enhanced Raman spectroscopy (SERS) often results in detection errors and/or omissions because of insufficient specificity and/or unstable signals, thereby limiting broader sensing applications. We synthesized an aptamer with a targeted recognition of tetracyclines (TCs) via clipping, mutation, and fragment addition. High-throughput and broad-spectrum analysis of trace TCs in complex systems was enabled by combining Raman spectroscopy automated platform with SERS imaging technology, the Au/Ag nanoparticles were used for Raman-enhancing substrates and aptamer recognition. A 0.07-pM TCs detection limit was observed along with selectivity and stability. Detection of TCs in real samples, such as serum and wastewater, was demonstrated. Overall, the TCs detection provides new potential SERS sensing and imaging strategies. [ABSTRACT FROM AUTHOR]

Nitrate pollution in fresh water is becoming increasingly serious. In this study, the effects of temperature and graphene oxide materials on the potential functions of denitrification communities in lake sediments were investigated by metagenome. The addition of graphene oxide significantly affected the abundance of denitrification genes such as Nap , Nos , and enhanced the contribution of Pseudomonas , making low temperature and material addition conducive to the denitrification process. Module network implied that low temperature increased the centrality of denitrification in community functions. At low temperatures, graphene oxide enhanced community anabolism by stimulation organic carbon consumption and regulating the gene abundance in the citric acid cycle and the semi-phosphorylation Entner-Doudoroff, thus possibly stimulating extracellular polymeric substances (EPS) synthesis and secretion. In addition, graphene oxide may also regulate the transfer of reducing electrons from NADH to denitrifying enzymes by affecting the gene abundances of complex I and complex IV. [Display omitted] • Graphene oxide led to an increase in the proportion of denitrification genes at 8 °C. • Graphene oxide enhanced community anabolism at 8 °C. • Graphene oxide stimulated EPS synthesis and secretion at 8 °C. • Graphene oxide regulated the transfer of electrons to denitrifying enzymes. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the inequality constrained optimization problems, where the involved functions belong to the class C 1 , 1 , i.e. functions which have Lipschitz continuous gradient mappings. We propose a second-order mean value inequality for a C 1 , 1 function in terms of its limiting second-order subdifferential. By virtue of this inequality, using the second-order tangent set and the asymptotic second-order tangent cone, we establish the second-order Fritz John type necessary and sufficient optimality conditions for differentiable optimization problems with inequality and set constraints. [ABSTRACT FROM AUTHOR]

Understanding the fluid dependence of the poroelastic stiffness constants of a layered porous package is of great importance in subsurface exploration and development. While the effects of the pore-fluid distribution caused by coarse-scale heterogeneities within an isotropic medium have been studied for several decades, the role of these heterogeneities on the poroelastic constants of a finely layered package is still largely unexplored. In this study, we apply the poroelastic upscaling methods to estimate the fluid-dependent poroelastic stiffness constants of a layered package at the coarse scale. The numerical results show that the refined Gassmann's fluid substitution formulae presented in this paper is applicable if a single fluid phase is uniformly saturated within a layered package. The stiffness constants (⁠|${c_{11}}$| and |${c_{33}}$|⁠) of the layered package with patchy saturations are always higher than or equal to those obtained for the medium with homogeneous saturations, the stiffness constants predicted by the refined fluid substitution formulae for the package simultaneously saturated with different fluids fall between them. Experimental results confirm the relationship between the undrained vertical stiffness constant and the effective pore-fluid bulk modulus for the patch saturated package, indicating that a reasonable result can be achieved by properly choosing an effective poroelastic model that accounts both for the fluid hydraulic communication and the anisotropy of the medium. The results improve the understanding of the coarse-scale fluid dependence of the poroelastic stiffness constants of a layered package, and therefore, it can be used to interpret the seismically inverted elastic parameter for the petrophysical properties in heterogeneous reservoirs. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to evaluate whether the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune inflammation index (SII) were associated with primary open-angle glaucoma (POAG). Materials and Methods: This retrospective case-control study included 240 patients with POAG and 300 age- and sex-matched control subjects. Complete ophthalmological examination and blood count measurements were performed for all subjects. Results: The values of NLR, PLR, and SII in the POAG group were significantly increased compared with the control group (p < 0.001; p = 0.012; p < 0.001). However, the LMR value was lower in the POAG patients than in the control group (p < 0.001). When we divided the subjects into different age and gender subgroups, the NLR and SII values in the POAG patients were always higher than those in the control group. In the comparison of laboratory parameters in POAG subjects stratified according to severity, we also found that NLR and SII increased with the severity. The receiver operating characteristic (ROC) analysis revealed that the areas under the ROC curve of NLR, PLR, LMR, and SII to predict patients with POAG were found to be 0.627, 0.569, 0.382, and 0.986, respectively. The best cutoff point of NLR was 1.998 with a sensitivity of 59.8% and a specificity of 63.0%, and the SII was 947.365 with a sensitivity of 95.4% and a specificity of 95.7%. Multivariable logistic regression analysis showed that NLR was positively associated with mean deviation; moreover, NLR and SII were independent indicators correlated with POAG (OR 1.502; 95% CI 1.227–1.839; p < 0.001; OR 1.02; 95% CI 1.009–1.021; p < 0.001). Conclusion: We speculated that elevated NLR and SII might serve as readily available inflammatory predictors in POAG patients. [ABSTRACT FROM AUTHOR]

In this paper, we employ the image space analysis method to investigate a vector optimization problem with non-cone constraints. First, we use the linear and nonlinear separation techniques to establish Lagrange-type sufficient and necessary optimality conditions of the given problem under convexity assumptions and generalized Slater condition. Moreover, we give some characterizations of generalized Lagrange saddle points in image space without any convexity assumptions. Finally, we derive the vectorial penalization for the vector optimization problem with non-cone constraints by a general way. [ABSTRACT FROM AUTHOR]

• Quick automatic extracting the head photo. • Need not given tripmap or scribble. • Creating a new training data set for hair matting. • High performance of a strategy for reducing search space. Image matting is a process of extracting objects from background in an image, which is an important work in digital image processing and video editing. Previous methods have poor performance and most methods need trimap or scribble to compute to get accurate image matting results. In this paper a quick automatic head image matting method for certificate photo production is put forward, which could rapidly extract satisfied head photo from images that are shoot by portable camera. First a new training data set about hair matting is created, and the image is segmented into different regions according to different gray level; then we detect and locate the face and eyes to adjust the correct head position; Finally, the accurate hair pixels are extracted from the edge region around head by multimodal Gaussian process regression. It's the advantage that the regions with clear foreground and background could be quickly extracted by segmented method, and the regions with similar foreground and background colors or complicated textures were labeled (the edge regions with hair around head), thus the hair could be extracted in smaller area. In our method the quick and accurate extracting of head photo needn't the trimap or scribbling or lots of training. Experimental results clearly demonstrate the superiority of our algorithm over previous methods. [ABSTRACT FROM AUTHOR]

Particle filter algorithms are a very important branch for visual object tracking in the past decades, showing strong robustness to challenging scenarios with partial occlusion and large-scale variations. However, since a large number of particles need to be extracted for the accurate target state estimation, their tracking efficiency typically suffers especially when meeting deep convolutional features, which have been developed for handling significant variations of the target appearance in the visual tracking community. In this paper, we propose to elegantly exploit deep convolutional features with few particles in a novel hierarchical particle filter, which formulates correlation filters as observation models and breaks the standard particle filter framework down into two constituent particle layers, namely, particle translation layer and particle scale layer. The particle translation layer focuses on the object location with the deep convolutional features capturing semantics but failing to precisely estimate the object scale, while the particle scale layer pays attention to large-scale variations with the lightweight hand-crafted features handling spatial details of the object size. Moreover, an efficient ensemble method is proposed to help explore deeper convolutional features with more semantics in the particle translation layer. Extensive experiments on four challenging tracking datasets, including OTB-2013, OTB-2015, VOT2014, and VOT2015 demonstrate that the proposed method performs favorably against a number of state-of-the-art trackers. [ABSTRACT FROM AUTHOR]

Simple Summary: Two subspecies of largemouth bass (Micropterus salmoides, LMB) with different thermal tolerance, northern largemouth bass (NLMB) and Florida largemouth bass (FLMB), were subjected to acute and chronic thermal stress at 33 °C. Then, variations of 12 candidate biomarkers between NLMB and FLMB were analyzed. Compared to NLMB, FLMB exhibited a lower plasma cortisol level and a higher expression of hsp90 under acute thermal stress. Additionally, lower expression of hsp70 in FLMB was observed under chronic thermal stress. The differences in plasma cortisol levels and hsp expression represent variations in thermal tolerance between the two subspecies of LMB, providing valuable information for the identification and breeding of LMB varieties with better thermal tolerance in the future. Affected by the continuously rising temperature, thermal stress leads to a delinked growth rate and resistance to stress in cultured largemouth bass (Micropterus salmoides, LMB) in China. Identification of LMB with better thermal resistance will benefit the breeding of new varieties. However, there has been limited reporting on the evaluation to identify LMB with better thermal resistance. LMB consists of the northern LMB (Micropterus salmoides salmoides, NLMB) and the Florida LMB (Micropterus salmoides floridanus, FLMB). Due to their different geographical distributions, it has been suggested that FLMB exhibit better thermal resistance compared to NLMB. In this study, NLMB and FLMB were subjected to thermal stress for 3 h (acute) and 60 d (chronic) at 33 °C, respectively. Subsequently, the variations of 12 candidate biomarkers between NLMB and FLMB were analyzed. Exposure to acute thermal stress significantly increased plasma cortisol, blood glucose, and lactate levels; activities of superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT), glucose kinase (GK), pyruvate kinase (PK), lactate dehydrogenase (LDH), and glucose 6 phosphatase (G6Pase); and the expressions of hsp70 and hsp90 in both NLMB and FLMB (p < 0.05). Compared to NLMB, FLMB exhibited a lower plasma cortisol level and a higher expression of hsp90 under acute thermal stress (p < 0.05). Exposure to chronic thermal stress significantly increased plasma cortisol and blood glucose levels, as well as activities of GK, PK, LDH, and G6Pase, as well as expressions of hsp70 and hsp90 in both NLMB and FLMB (p < 0.05). Additionally, FLMB showed a lower expression of hsp70 compared to NLMB (p < 0.05). In conclusion, our results showed that LMB with lower plasma cortisol level and higher expression of hsp90 under acute thermal stress, as well as lower expression of hsp70 under chronic thermal stress were suggested to have better thermal resistance. Our study provides valuable information for identifying and breeding LMB varieties with better thermal resistance in the future. [ABSTRACT FROM AUTHOR]

This article focuses on a conjugate duality for a constrained vector optimization in the framework of abstract convexity. With the aid of the extension for the notion of infimum to the vector space, a set-valued topical function and the corresponding conjugate map, subdifferentials are presented. Following this, a conjugate dual problem is proposed via this conjugate map. Then, inspired by some ideas in the image space analysis, some equivalent characterizations of the zero duality gap are established by virtue of the subdifferentials. [ABSTRACT FROM AUTHOR]

In this paper, strong Karush/Kuhn–Tucker conditions are studied for smooth multiobjective optimization with inequality constraints. We introduce a new second-order regularity condition of Abadie type in terms of the second-order directional derivatives and then obtain a second-order strong Karush/Kuhn–Tucker necessary condition at a Borwein-properly efficient solution. Simultaneously, we also use an example to show that, if the Abadie type regularity condition is weakened to the Guignard type one, the second-order strong Karush/Kuhn–Tucker necessary condition may not hold. Finally, then we also apply the second-order strong Karush/Kuhn–Tucker conditions to derive a sufficient result for local Geoffrion-proper efficiency. [ABSTRACT FROM AUTHOR]

Understanding the fluid dependence of poroelastic constants of a layered porous package is important for various aspects of applied and fundamental geosciences. To decouple the effects of fluid substitutions and anisotropy in a layered package on vertical stiffness constants, a set of approximations to anisotropic fluid substitution theory is introduced in conjunction with Thomsen's anisotropy parameters. Validation of the approximations is performed by physical modelling and theoretical examples. In physical modelling, synthetic porous layers are used and interbedded by Plexiglas sheets to build a layered transversely isotropic symmetry with a vertical symmetry axis package. Seismic acquisitions over the physical model saturated with air, oil and water are carefully conducted, respectively. The reflection amplitudes are properly corrected and inverted by a specific seismic inversion scheme to recover P - and S -wave impedances. Poroelastic constants of the thin package then are deduced from the inverted results. Applying the approximations to the physical modelling results, a good match between the estimated vertical stiffness constant values of the physical model and the theoretical predictions is observed. Results of both physical modelling and theoretical analysis demonstrate that fluid substitutions when going from drained to undrained behaviour will enhance or reduce the degree of anisotropy of the medium, depending on the sign and magnitude of Thomsen's anisotropy parameter δ. Results show that the shear modulus of the individual layer plays a key role in controlling the degree of the initial anisotropy of the thin package, which directly dominates the effect of pore fluids on poroelastic constants of the upscaled medium. [ABSTRACT FROM AUTHOR]

Purpose: It has been hypothesised that uric acid (UA) has a protective effect against oxidative damage in the central nervous system. Therefore, we investigated serum UA concentrations in patients with primary open‐angle glaucoma (POAG) and explored the relationship between serum UA concentration and glaucoma severity. Methods: This prospective, cross‐sectional, case–control study was conducted in 163 POAG patients and 103 normal controls. Clinical and demographic information was obtained from the medical data platform of the Eye & ENT Hospital of Fudan University, Shanghai, China. The POAG patients were categorised into mild [median deviation (MD) ≤ 6.00 dB], moderate (MD > 6 Db–≥12 dB) and severe (MD > 12 dB) subgroups, based on their visual field MD results. Results: The level of serum UA in the POAG group (0.321 ± 0.084 mmol/l) was approximately 12.77% lower (p < 0.001) than that of the control group (0.362 ± 0.053 mmol/l). The UA/creatinine (Cr) ratio was approximately 14.99% lower (p < 0.001) in patients with POAG (4.47 ± 1.15), compared with the control group (5.14 ± 1.05). The mean level of UA was lowest in the severe POAG group, followed by the moderate POAG group, and the mild POAG group (p < 0.001). A similar trend was observed when UA levels were compared between the POAG and control groups in males. Multivariate regression analyses showed a significant negative correlation between UA and vertical cup–disc ratio (B = −0.320, p = 0.034), and UA and MD (B = −0.441, p = 0.031) in males. Conclusion: Primary open‐angle glaucoma patients have lower UA levels; however, a negative association between UA levels and disease severity was evident in male patients. [ABSTRACT FROM AUTHOR]

Abstract The combined effects of aging and low temperature, long time heating (LTLT) on meat toughness were investigated. Pork loins were heated at 53 or 58 °C for up to 20 h, and shear force values, cooking loss, moisture content, collagen solubility, electrophoresis of myofibrillar proteins were determined. Structural changes in perimysium were also observed by light microscopy and scanning electron microscopy (SEM). Results showed that aging and LTLT cooking independently affected meat toughness, and higher temperature or longer time were required to decrease toughness of one-day aged meat to the same level as in 10-day aged meat. Collagen solubilization is suggested as the main reason for the tenderization effect of LTLT. Myofibrillar proteolysis might not occur during LTLT cooking, and will not be contributing to meat tenderness. [ABSTRACT FROM AUTHOR]

Purpose. PLEKHA7 and COL11A1 were genotyped for single-nucleotide polymorphisms (SNPs) to investigate the possible association of these two genes with primary angle-closure glaucoma (PACG) and disease severity. Method. A total of 51 PACG cases and 51 normal controls were recruited. Twelve SNPs in the PLEKHA7 (rs216489, rs1027617, rs366590, rs11024060, rs6486330, rs11024097, and rs11024102) and COL11A1 (rs1676484, rs3753841, rs12138977, rs2126642, and rs2622848) genes were genotyped by direct Sanger sequencing. Distributions of allele frequencies and genotype frequencies in cases and controls, as well as in mild, moderate, and severe subgroups, were compared based on mean defect (MD ≤ 6.00 dB, 6 dB < MD ≤ 12 dB, and MD > 12 dB were considered mild, moderate, and severe, respectively). Independent Student's t-tests and chi-square tests were used to compare characteristics of PACG cases and controls. Chi-square tests were used to compare the distribution of allele frequencies in cases and controls and in MD-based subgroups with various degrees of glaucoma severity. Binary logistic regression was used to compare the distribution of genotype frequencies and calculate odds ratios (OR) with confidence intervals (CI). Result. Three of the 12 SNPs in COL11A1, rs1676486 (P=0.026, OR = 2.089, 95% CI = 1.092–3.996), rs3753841 (P=0.036, OR = 1.886, 95% CI = 1.038–3.426), and rs12138977 (P=0.024, OR = 2.133, 95% CI = 1.104–4.123) were found to have a significant association with PACG. Furthermore, in the subgroup analysis, rs1676486 (P=0.018, OR = 2.416, 95% CI = 1.284–4.544; P=0.011, OR = 2.119, 95% CI = 1.204–3.729), rs12138977 (P=0.009, OR = 2.158, 95% CI = 1.287–3.618; P=0.006, OR = 1.962, 95% CI = 1.239–3.106), and rs3753841 (P=0.007, OR = 2.550, 95% CI = 1.344–4.839) showed statistically significant differences between moderate/severe groups and controls. Conclusion. Our data suggested that COL11A1 rs1676484, rs3753841, and rs12138977 polymorphisms may be of value for further study as potential gene-dependent risk factors for developing PACG. Moreover, COL11A1 rs1676484 and rs12138977 polymorphisms might be associated with PACG disease severity. [ABSTRACT FROM AUTHOR]

Abstract In this study, the spatial and seasonal bacterioplankton community dynamics were investigated in the main channel of the Middle Route of the South-to-North Water Diversion Project (MRP) using Illumina HiSeq sequencing. Water samples were collected in spring and summer from south to north at eight water quality monitoring stations, respectively. The results showed that seasonal changes had a more pronounced effect on the bacterioplankton community compositions (BCCs) than spatial variation. The diversity analysis results indicated that samples of summer have more operational taxonomic units (OTUs), higher richness and diversity than those in spring. The main phyla, Proteobacteria , Actinobacteria , Bacteroidetes , Cyanobacteria and Chloroflexi , displayed significant differences (P < 0.05) between spring and summer in the main channel. The Redundancy analysis (RDA) targeting all samples indicated that specific conductivity (SPC), dissolved oxygen (DO), pH and temperature (T) might be key factors in driving BCCs, while trophic status showed no significant correlation (P > 0.05). The present study provides important insights into the potential ecological roles of specific taxa in the new artificial ecosystem and it offers reference for studies on ecosystem succession of other giant interbasin water diversion project in the world. [ABSTRACT FROM AUTHOR]

In this paper, we study a vector optimization problem (VOP) with both inequality and equality constraints. We suppose that the functions involved are Fréchet differentiable and their Fréchet derivatives are continuous or stable at the point of study. By virtue of a second-order constraint qualification of Abadie type, we provide second-order Karush-Kuhn-Tucker type necessary optimality conditions for the VOP. Moreover, we also obtain second-order sufficient optimality conditions for a kind of strict local efficiency. Both the necessary conditions and the sufficient conditions are shown in equivalent pairs of primal and dual formulations by using theorems of the alternative for the VOP. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Adding an external source under low C/N can significantly improve nitrogen removal efficiency. • N transformation processes were coupled at the functional genes level. • The vertical distribution of the microbial community in CWs was a remarkable discrepancy. • Adding rice husk as a carbon source could be conducive to the complete nitrification process. Abstract The effect of adding rice husk as an electron donor on the genetic and metabolic diversity of denitrifying communities in a long-term flooded constructed wetland (D1) was compared with the control group without external carbon source addition (D2). The underlying molecular mechanisms responsible for nitrate removal were quantified under different nitrate loading rates. The results showed that D1 achieved higher and more stable removal efficiencies for NO 3 −-N (90–97%) and total nitrogen (73–87%) under different nitrate loading rates, which were approximately 10 times higher than those of D2. This corresponded with much higher absolute abundances of bacterial and nitrogen functional genes in D1 than D2. Additionally, the vertical distribution of microbial communities in D1 and D2 showed significant differences. This pattern suggested that adding rice husk in flooded CWs had beneficial effects on the denitrifying community. Quantitative response relationships and network analysis indicated that denitrification was the dominant nitrogen removal pathway. Moreover, the present study indicated that using rice husk as an external carbon source could be conducive to completing the nitrification process, which was first confirmed at the molecular level. The present study indicated that using rice husk as an external carbon source can significantly enhance denitrification rates and thus improve nitrogen removal in CWs for wastewater treatment process. [ABSTRACT FROM AUTHOR]

This paper aimed to develop a quantitative method based on high-performance liquid chromatography (HPLC) coupled with triple quadrupole tandem mass spectrometry (MS/MS) for the simultaneous determination of two protein carbonylation products derived from lysine residues in meat proteins, namely, α-aminoadipic semialdehyde (AAS) and lysinonorleucine (LNL). Mass spectrometry conditions and derivatization parameters were optimized and the linearity, repeatability, bias, the limit of detection (LOD), the lower limit of quantification (LLOQ), and recovery were validated. The developed method showed satisfactory linearity, repeatability, and sensitivity for both AAS and LNL. This method was applied to analyze the contents of these compounds in different meat products, and the formation of AAS was observed to be closely related to the severity of the manufacturing conditions. Moreover, AAS was demonstrated to be a reliable but more sensitive marker for protein carbonylation compared to the DNPH method, which could also provide information regarding the specific pathway of protein carbonylation. • A method for the simultaneous quantification of AAS and LNL in meat was developed. • The method was with satisfactory linearity, repeatability and sensitivity. • AAS was a more sensitive marker for protein carbonylation compared to DNPH method. [ABSTRACT FROM AUTHOR]

[Display omitted] • Iron-based denitrification improved nitrogen removal at low C/N ratio in freshwaters. • Microbially mediated denitrification dominated rather than chemodenitrification. • Five fast-growing microbes accounted for over 99% of the community. • Amino acids and vitamins needed by an organism could be satisfied by another member. • The two-partner relationships increased community stability without limiting activity. Iron-dependent denitrification is a safe and promising technology for nitrogen removal in freshwaters. However, the understanding of microbial physiology and interactions during the process was limited. Denitrifying systems inoculated with freshwater samples were operated with and without iron(II) at a low C/N ratio for 54 days. Iron addition improved nitrogen removal. Batch experiments confirmed that microbially mediated reaction rather than abiotic reaction dominated during the process. Metagenomics recovered genomes of the five most abundant microorganisms, which accounted for over 99% of the community in every triplicate of the iron-based system. Based on codon usage bias, all of them were fast-growing organisms. The total abundance of fast-growing organisms was 38% higher in the system with iron than in the system without iron. Notably, the most abundant organism Diaphorobacter did not have enzymes for asparagine and aspartate biosynthesis, whereas Rhodanobacter could not produce serine and cobalamin. Algoriphagus and Areminomonas lost synthesis enzymes for more amino acids and vitamins. However, they could always obtain these growth-required substances from another microorganism in the community. The two-partner relationship minimized the limitation on microbial reproduction and increased community stability. Our results indicated that iron addition improved nitrogen removal by supplying electron donors, promoting microbial growth, and building up syntrophic interactions among microorganisms with timely communications. The findings provided new insights into the process, with implications for freshwater remediation. [ABSTRACT FROM AUTHOR]

The dominance of different nitrate-reducing pathways determines nitrogen cycling patterns. Denitrification (DNF) has been widely studied, but assimilatory nitrate reduction (ANR) and dissimilatory nitrate reduction to ammonium (DNRA) have received much less attention. Their ecological patterns and responsible microbes are poorly understood. Here, we studied the structure and function succession of the three functional groups in the middle route of the South-to-North Water Diversion Project, which is a 1230 km canal spanning 8 degrees of latitude. The results reflected a nitrogen-removing pattern dominated by DNF in the summer and a nitrogen-retaining pattern dominated by ANR and DNRA in the winter. Stenotrophomonas , a typical denitrifier, was the keystone species in the summer and contributed to N 2 O production. Clostridium , a genus able to conduct ANR and DNRA, was the keystone species in the winter. Notably, a significant zonation pattern was discovered. According to the community structure, the system could be separated into two biogeographic zones, and the Yellow River (about latitude 35°N) is an important cut-off line. This bacterial biogeography followed different water characteristics and ecological processes. ANR was found to be an important process and seasonally transformed its habitat from the northern zone to the southern zone. DNRA bacteria were acclimated to the northern zone and favored at this region in both seasons. The generation of N 2 O, a strong greenhouse gas, also exhibited this zonation pattern. This is the first study to consider assimilatory and dissimilatory nitrate reducers together at a molecular level, and provides new insights into the underlying patterns of a nitrate-reducing bacterioplankton community. [ABSTRACT FROM AUTHOR]

Influencing factors for recovery of patients with gastrointestinal tumor after laparoscopic surgery were explored to promote recovery of patients. Clinical data from 521 gastrointestinal tumor patients who underwent laparoscopic surgery in Dalian Central Hospital were collected. The recovery of gastrointestinal function was recorded, and the factors that affected the recovery of gastrointestinal function were analyzed. All data were processed using Statistical Product and Service Solutions (SPSS) 21.0 software. t-test and F-test were used for univariate analysis, and multivariate linear regression was adopted for multivariate analysis. Results of univariate analysis displayed that age, starting time of postoperative activity, peritoneal drainage tube indwelling time, blood potassium level, sleep disorder, fasting and fluid deprivation time, duration of the first postoperative defecation/exhaustion, abdominal distention and pain reaction and social support level had significant influences on recovery of patients after operation (P<0.05). Results of multivariate analysis indicated that peritoneal drainage tube indwelling time, blood potassium level, fasting and fluid deprivation time and starting time of postoperative activity were independent factors affecting the recovery of patients after operation (P<0.05). Some methods are conducive to the recovery of gastrointestinal function in patients with gastrointestinal tumor, including the removal of peritoneal drainage tube, timely potassium supplementation, and diet recovery after laparoscopic surgery as soon as possible. [ABSTRACT FROM AUTHOR]