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Credit card fraud identification is an important issue in risk prevention and control for banks and financial institutions. In order to establish an efficient credit card fraud identification model, this article studied the relevant factors that affect fraud identification. A credit card fraud identification model based on neural networks was constructed, and in-depth discussions and research were conducted. First, the layers of neural networks were deepened to improve the prediction accuracy of the model; second, this paper increase the hidden layer width of the neural network to improve the prediction accuracy of the model. This article proposes a new fusion neural network model by combining deep neural networks and wide neural networks, and applies the model to credit card fraud identification. The characteristic of this model is that the accuracy of prediction and F1 score are relatively high. Finally, use the random gradient descent method to train the model. On the test set, the proposed method has an accuracy of 96.44% and an F1 value of 96.17%, demonstrating good fraud recognition performance. After comparison, the method proposed in this paper is superior to machine learning models, ensemble learning models, and deep learning models., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Although recent advances in laparoscopic technology have popularized laparoscopic pancreatoduodenectomy (LPD), laparoscopic pancreaticojejunostomy anastomosis (PJA) still presents a major technical challenge. From February 2021 to January 2023, 42 patients underwent LPD with modified double U-suture PJA. Data on the demographic characteristics and clinical results of these patients were investigated. The median operation time was 316 min (249-596 min). The median PJA time was 32 min (25-40 min). The median intraoperative blood loss was 150 mL (50-500 mL). The median postoperative stay was 12 days (7-30 days). Complications occurred in 10 (23.8%) patients, including two cases (4.8%) of delayed gastric emptying and nine cases (21.4%) of postoperative pancreatic fistula (POPF). One patient presented delayed gastric emptying and POPF. Eight patients (19.0%) experienced biochemical leakage, and one patient (2.4%) had grade B POPF. Laparoscopic double U-suture PJA is a feasible and safe technique for performing LPD., (© 2024. Italian Society of Surgery (SIC).)

Background: Owing to the lack of evidence-based medical studies with large sample sizes, the surgical approach for the radical resection of rectal neuroendocrine tumors remains controversial., Methods: We retrospectively collected the medical records of patients with rectal neuroendocrine tumors who underwent radical resection at 17 large tertiary care hospitals in China between January 1, 2010, and April 30, 2022. All patients were divided into laparoscopic and open surgery groups. After propensity score matching to reduce confounders, the postoperative and oncologic outcomes were compared between the groups., Results: We enrolled 174 patients with rectal neuroendocrine tumors who underwent radical surgery. After random matching, 124 patients were included in the comparison (62, laparoscopic surgery group; 62, open surgery group). The laparoscopic surgery group had fewer complications (14.5% vs. 35.5%, P = 0.007) and superior relapse-free survival (P = 0.048). Subgroup analysis revealed that the laparoscopic surgery group had fewer complications (10.9% vs. 34.7%, P = 0.004), shorter postoperative hospital stays (9.56 ± 5.21 days vs. 12.31 ± 8.61 days, P = 0.049) and superior relapse-free survival (P = 0.025) in the rectal neuroendocrine tumors ≤ 4 cm subgroup., Conclusions: Laparoscopic surgery was associated with improved postoperative outcomes and oncologic prognosis for patients with rectal neuroendocrine tumors ≤ 4 cm; it can serve as a safe and feasible option for radical surgery of rectal neuroendocrine tumors., (© 2024. The Author(s).)

Background: Studies on grade 2 rectal neuroendocrine tumors are limited, and the optimal treatment for these tumors is not well established., Objective: We aimed to compare the oncologic results of local excision versus radical resection for the treatment of grade 2 rectal neuroendocrine tumors., Design: Retrospective multicenter propensity score-matched study to minimize heterogeneity between groups and focus on the differences between surgery strategies., Settings: Seventeen large-scale Chinese medical centers participated in this study., Patients: A total of 144 patients with pathologically confirmed grade 2 rectal neuroendocrine tumors were retrospectively analyzed., Main Outcome Measures: Cancer-specific survival and relapse-free survival were assessed to compare surgery strategies., Results: A total of 144 patients with grade 2 rectal neuroendocrine tumors were enrolled in this study. Twenty-seven patients underwent endoscopic resection, 55 underwent transanal excision, 50 underwent radical resection, and 12 underwent palliative surgery or biopsy for distant metastasis. Of the 50 patients who underwent radical resection, 30 (60.0%) had clinically positive lymph nodes on the basis of the histopathology results. The optimal cutoff value for tumor size to predict cancer-specific survival was 1.5 cm. In patients with grade 2 rectal neuroendocrine tumors of ≤1.5-cm size, there were no significant differences in cancer-specific survival and relapse-free survival between local excision and radical resection groups ( p > 0.05). In patients with grade 2 rectal neuroendocrine tumors of >1.5-cm size, relapse-free survival was significantly lower in the local excision group than in the radical resection group ( p = 0.04)., Limitations: The nature of retrospective reviews and a relatively short follow-up period are limitations of this study., Conclusions: Grade 2 rectal neuroendocrine tumors have a nonnegligible rate of lymph node metastasis. Local excision is a feasible choice for tumors of ≤1.5 cm size without metastasis, whereas radical resection is more beneficial in those of >1.5 cm size. See Video Abstract ., Escisin Local Versus Reseccin Radical Para Tumores Neuroendocrinos Rectales Grado Anlisis Multicntrico Con Puntuacin De Propensin Coincidente: ANTECEDENTES:Los estudios sobre los tumores neuroendocrinos rectales de grado 2 son limitados y el tratamiento óptimo para estos tumores no está bien establecido.OBJETIVO:Comparar los resultados oncológicos de la escisión local versus la resección radical para el tratamiento de tumores neuroendocrinos rectales grado 2.DISEÑO:Estudio multicéntrico retrospectivo emparejado por puntuación de propensión para minimizar la heterogeneidad entre grupos y centrarse en la diferencia entre estrategias quirúrgicas.ESCENARIO:Diecisiete centros médicos chinos de gran tamaño participaron en este estudio.PACIENTES:Se analizaron retrospectivamente un total de 144 pacientes con tumores neuroendocrinos rectales grado 2 patológicamente confirmados.PRINCIPALES MEDIDAS DE RESULTADO:Se evaluaron la supervivencia específica del cáncer y la supervivencia libre de recaída para comparar las estrategias quirúrgicas.RESULTADOS:En este estudio se inscribieron un total de 144 pacientes con tumores neuroendocrinos rectales grado 2. Veintisiete pacientes se sometieron a resección endoscópica, 55 a escisión transanal, 50 a resección radical y 12 a cirugía paliativa o biopsia por metástasis a distancia. De los 50 pacientes que se sometieron a resección radical, 30 (60,0%) tenían ganglios linfáticos clínicamente positivos según los resultados histopatológicos. El valor de corte óptimo para el tamaño del tumor para predecir la supervivencia específica del cáncer fue de 1,5 cm. En pacientes con tumores neuroendocrinos rectales grado 2 ≤ 1,5 cm, no hubo diferencias significativas en la supervivencia específica del cáncer y la supervivencia libre de recaída entre los grupos de escisión local y resección radical ( p >0,05). En pacientes con tumores neuroendocrinos rectales grado 2 > 1,5 cm, la supervivencia libre de recaída fue significativamente menor en el grupo de escisión local que en el grupo de resección radical ( p = 0,04).LIMITACIONES:La naturaleza de la revisión retrospectiva y el período de seguimiento relativamente corto son limitaciones de este estudio.CONCLUSIONES:Los tumores neuroendocrinos rectales grado 2 tienen una tasa no despreciable de metástasis en los ganglios linfáticos. La escisión local es una opción factible para tumores ≤ 1,5 cm sin metástasis, mientras que la resección radical es más beneficiosa en aquellos > 1,5 cm. (Traducción-Dr. Felipe Bellolio )., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Colon and Rectal Surgeons.)

Compelling evidence has shown that geomagnetic disturbances in vertical intensity polarization before great earthquakes are promising precursors across diverse rupture conditions. However, the geomagnetic vertical intensity polarization method uses the spectrum of smooth signals, and the anomalous waveforms of seismic electromagnetic radiation, which are basically nonstationary, have not been adequately considered. By combining pulse amplitude analysis and an experimental study of the cumulative frequency of anomalies, we found that the pulse amplitudes before the 2022 Luding M6.8 earthquake show characteristics of multiple synchronous anomalies, with the highest (or higher) values occurring during the analyzed period. Similar synchronous anomalies were observed before the 2021 Yangbi M6.4 earthquake, the 2022 Lushan M6.1 earthquake and the 2022 Malcolm M6.0 earthquake, and these anomalies indicate migration from the periphery toward the epicenters over time. The synchronous changes are in line with the recognition of previous geomagnetic anomalies with characteristics of high values before an earthquake and gradual recovery after the earthquake. Our study suggests that the pulse amplitude is effective for extracting anomalies in geomagnetic vertical intensity polarization, especially in the presence of nonstationary signals when utilizing observations from multiple station arrays. Our findings highlight the importance of incorporating pulse amplitude analysis into earthquake prediction research on geomagnetic disturbances.

This article investigates a class of constrained distributed fuzzy convex optimization problems, where the objective function is the sum of a set of local fuzzy convex objective functions, and the constraints include partial order relation and closed convex set constraints. In undirected connected node communication network, each node only knows its own objective function and constraints, and the local objective function and partial order relation functions may be nonsmooth. To solve this problem, a recurrent neural network approach based on differential inclusion framework is proposed. The network model is constructed with the help of the idea of penalty function, and the estimation of penalty parameters in advance is eliminated. Through theoretical analysis, it is proven that the state solution of the network enters the feasible region in finite time and does not escape again, and finally reaches consensus at an optimal solution of the distributed fuzzy optimization problem. Furthermore, the stability and global convergence of the network do not depend on the selection of the initial state. A numerical example and an intelligent ship output power optimization problem are given to illustrate the feasibility and effectiveness of the proposed approach.

With the continuous advancement of the economy and technology, the number of cars continues to increase, and the traffic congestion problem on some key roads is becoming increasingly serious. This paper proposes a new vehicle information feature map (VIFM) method and a multi-branch convolutional neural network (MBCNN) model and applies it to the problem of traffic congestion detection based on camera image data. The aim of this study is to build a deep learning model with traffic images as input and congestion detection results as output. It aims to provide a new method for automatic detection of traffic congestion. The deep learning-based method in this article can effectively utilize the existing massive camera network in the transportation system without requiring too much investment in hardware. This study first uses an object detection model to identify vehicles in images. Then, a method for extracting a VIFM is proposed. Finally, a traffic congestion detection model based on MBCNN is constructed. This paper verifies the application effect of this method in the Chinese City Traffic Image Database (CCTRIB). Compared to other convolutional neural networks, other deep learning models, and baseline models, the method proposed in this paper yields superior results. The method in this article obtained an F1 score of 98.61% and an accuracy of 98.62%. Experimental results show that this method effectively solves the problem of traffic congestion detection and provides a powerful tool for traffic management.

Despite the demonstrated importance of DNA G-quadruplexes (G4s) in health and disease, technologies to readily manipulate specific G4 folding for functional analysis and therapeutic purposes are lacking. Here we employ G4-stabilizing protein/ligand in conjunction with CRISPR to selectively facilitate single or multiple targeted G4 folding within specific genomic loci. We demonstrate that fusion of nucleolin with a catalytically inactive Cas9 can specifically stabilize G4s in the promoter of oncogene MYC and muscle-associated gene Itga7 as well as telomere G4s, leading to cell proliferation arrest, inhibition of myoblast differentiation and cell senescence, respectively. Furthermore, CRISPR can confer intra-G4 selectivity to G4-binding compounds pyridodicarboxamide and pyridostatin. Compared with traditional G4 ligands, CRISPR-guided biotin-conjugated pyridodicarboxamide enables a more precise investigation into the biological functionality of de novo G4s. Our study provides insights that will enhance understanding of G4 functions and therapeutic interventions., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Cadmium (Cd) is a nonessential element in plants and has adverse effects on the growth and development of plants. However, the molecular mechanisms of Cd phytotoxicity, tolerance and accumulation in hyperaccumulators Solanum nigrum L. has not been well understood. Here, physiology, transcriptome, and metabolome analyses were conducted to investigate the influence on the S. nigrum under 0, 25, 50, 75 and 100 µM Cd concentrations for 7 days. Pot experiments demonstrated that compared with the control, Cd treatment significantly inhibited the biomass, promoted the Cd accumulation and translocation, and disturbed the balance of mineral nutrient metabolism in S. nigrum, particularly at 100 µM Cd level. Moreover, the photosynthetic pigments contents were severely decreased, while the content of total protein, proline, malondialdehyde (MDA), H 2 O 2 , and antioxidant enzyme activities generally increased first and then slightly declined with increasing Cd concentrations, in both leaves and roots. Furthermore, combined with the previous transcriptomic data, numerous crucial coding-genes related to mineral nutrients and Cd ion transport, and the antioxidant enzymes biosynthesis were identified, and their expression pattern was regulated under different Cd stress. Simultaneously, metabolomic analyses revealed that Cd treatment significantly changed the expression level of many metabolites related to amino acid, lipid, carbohydrate, and nucleotide metabolism. Metabolic pathway analysis also showed that S. nigrum roots activated some differentially expressed metabolites (DEMs) involved in energy metabolism, which may enhance the energy supply for detoxification. Importantly, central common metabolism pathways of DEGs and DEMs, including the "TCA cycle", "glutathione metabolic pathway" and "glyoxylate and dicarboxylate metabolism" were screened using conjoint transcriptomics and metabolomics analysis. Our results provide some novel evidences on the physiological and molecular mechanisms of Cd tolerance in hyperaccumulator S. nigrum plants., (© 2024. The Author(s).)

Objectives: Studies on rectal neuroendocrine tumors (R-NETs) that are 1-2 cm in size are limited, and the optimal treatment for these tumors is not well established., Methods: Data from patients with primary localized R-NETs 1-2 cm in size were retrospectively collected from 17 large-scale referral medical centers in China. Long-term prognosis, quality of life (QOL), and fecal incontinence were evaluated, and the effects of local excision (LE) or radical resection (RR) were elucidated using propensity score matching (PSM)., Results: A total of 272 patients were included in this study; 233 underwent LE, and the remaining 39 underwent RR. Patients in the LE group showed lower tumor location, fewer postoperative Clavien-Dindo III-V complications, more G1 tumors, and lower tumor stage. There were no significant differences in the relapse-free survival or overall survival (OS) between the LE and RR groups after PSM. Patients in the LE group reported superior physical, role, emotional, social, and cognitive functions, global QOL, and Wexner fecal incontinence scores compared with those in the RR group (all P  < 0.050). Eighteen (6.6%) patients had lymph node metastases. Multivariable analysis revealed that tumor location (odds ratio [OR] = 3.19, 95% confidence interval [CI] 1.04-10.07, P  = 0.010), neutrophil-to-lymphocyte ratio (NLR) > 1.80 (OR = 4.50, 1.46-15.89, P  = 0.012), and T3-T4 (OR = 36.31, 95% CI 7.85-208.62, P  < 0.001) were independent risk factor for lymph node metastasis., Conclusions: R-NETs measuring 1-2 cm generally have a favorable prognosis, and there is no difference in postoperative survival between LE and RR. For patients without lymph node metastasis, LE should be the preferred choice; however, for patients with a higher tumor location, preoperative NLR >1.8 or T3/T4 tumors, RR should be considered., Competing Interests: The authors declare that they have no competing interests., (© 2024 The Authors. Published by Elsevier Ltd.)

Introduction: Paphiopedilum barbigerum is currently the rarest and most endangered species of orchids in China and has significant ornamental value. The mature seeds of P. barbigerum are difficult to germinate owing to the absence of an endosperm and are highly dependent on mycorrhizal fungi for germination and subsequent development. However, little is known about the regulation mechanisms of symbiosis and symbiotic germination of P. barbigerum seeds., Methods: Herein, transcriptomics and proteomics were used to explore the changes in the P. barbigerum seeds after inoculation with (FQXY019 treatment group) or without (control group) Epulorhiza sp. FQXY019 at 90 days after germination., Results: Transcriptome sequencing revealed that a total of 10,961 differentially expressed genes (DEGs; 2,599 upregulated and 8,402 downregulated) were identified in the control and FQXY019 treatment groups. These DEGs were mainly involved in carbohydrate, fatty acid, and amino acid metabolism. Furthermore, the expression levels of candidate DEGs related to nodulin, Ca 2+ signaling, and plant lectins were significantly affected in P. barbigerum in the FQXY019 treatment groups. Subsequently, tandem mass tag-based quantitative proteomics was performed to recognize the differentially expressed proteins (DEPs), and a total of 537 DEPs (220 upregulated and 317 downregulated) were identified that were enriched in processes including photosynthesis, photosynthesis-antenna proteins, and fatty acid biosynthesis and metabolism., Discussion: This study provides novel insight on the mechanisms underlying the in vitro seed germination and protocorm development of P. barbigerum by using a compatible fungal symbiont and will benefit the reintroduction and mycorrhizal symbiotic germination of endangered orchids., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Tian, Wang, Ding, Wang, Yang, Bai, Tan and Liao.)

Autophagosome-tethering compound (ATTEC) technology has recently been emerging as a novel approach for degrading proteins of interest (POIs). However, it still faces great challenges in how to design target-specific ATTEC molecules. Aptamers are single-stranded DNA or RNA oligonucleotides that can recognize their target proteins with high specificity and affinity. Here, ATTEC is combined with aptamers for POIs degradation. As a proof of concept, pathological protein α-synuclein (α-syn) is chosen as the target and an efficient α-syn degrader is generated. Aptamer as a targeting warhead of α-syn is conjugated with LC3B-binding compound 5,7-dihydroxy-4-phenylcoumarin (DP) via bioorthogonal click reaction. It is demonstrated that the aptamer conjugated with DP is capable of clearing α-syn through LC3 and autophagic degradation. These results indicate that aptamer-based ATTECs are a versatile approach to degrade POIs by taking advantage of the well-defined different aptamers for targeting diverse proteins, which provides a new way for the design of ATTECs to degradation of targeted proteins., (© 2023 Wiley-VCH GmbH.)

CD8 + T cells play an important role in anti-tumor immunity. Better understanding of their regulation could advance cancer immunotherapies. Here we identify, via stepwise CRISPR-based screening, that CUL5 is a negative regulator of the core signaling pathways of CD8 + T cells. Knocking out CUL5 in mouse CD8 + T cells significantly improves their tumor growth inhibiting ability, with significant proteomic alterations that broadly enhance TCR and cytokine signaling and their effector functions. Chemical inhibition of neddylation required by CUL5 activation, also enhances CD8 effector activities with CUL5 validated as a major target. Mechanistically, CUL5, which is upregulated by TCR stimulation, interacts with the SOCS-box-containing protein PCMTD2 and inhibits TCR and IL2 signaling. Additionally, CTLA4 is markedly upregulated by CUL5 knockout, and its inactivation further enhances the anti-tumor effect of CUL5 KO. These results together reveal a negative regulatory mechanism for CD8 + T cells and have strong translational implications in cancer immunotherapy., (© 2024. The Author(s).)

Current treatments for T cell malignancies encounter issues of disease relapse and off-target toxicity. Using T cell receptor (TCR)Vβ2 as a model, here we demonstrate the rapid generation of an off-the-shelf allogeneic chimeric antigen receptor (CAR)-T platform targeting the clone-specific TCR Vβ chain for malignant T cell killing while limiting normal cell destruction. Healthy donor T cells undergo CRISPR-induced TRAC, B2M and CIITA knockout to eliminate T cell-dependent graft-versus-host and host-versus-graft reactivity. Second generation 4-1BB/CD3zeta CAR containing high affinity humanized anti-Vβ scFv is expressed efficiently on donor T cells via both lentivirus and adeno-associated virus transduction with limited detectable pre-existing immunoreactivity. Our optimized CAR-T cells demonstrate specific and persistent killing of Vβ2+ Jurkat cells and Vβ2+ patient derived malignant T cells, in vitro and in vivo, without affecting normal T cells. In parallel, we generate humanized anti-Vβ2 antibody with enhanced antibody-dependent cellular cytotoxicity (ADCC) by Fc-engineering for NK cell ADCC therapy., (© 2024. The Author(s).)

Monocytes play important and diverse roles in both homeostatic and inflammatory immune responses. The CRISPR-Cas9 system in lentiviral vectors has been widely used to manipulate specific genes of immortal monocyte cell lines to study monocyte functions. However, human primary monocytes are refractory to this method with low gene knockout (KO) efficiency. In this chapter, we developed an in vitro gene-editing procedure for primary human monocytes with a consistent and high-gene KO efficiency via a ribonucleoprotein (RNP) complex consisting of Cas9 protein and single-guide RNA (sgRNA). This method can be adapted to study the functions of targeted signaling molecules involved in modulating monocyte polarization in primary human monocytes., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In this brief, we investigate the limit cycle of a single-neuron system with smooth continuous and binary-value activation functions and its circuit design. By transforming the system into Liénard-type and using Poincaré-Bendixson theorem as well as the symmetry of these systems, we obtain the existence conditions of limit cycle of the system. Then, by comparing the integral value of the differential of positive definite function along two assumed limit cycles, we prove that the system cannot produce two coexisting limit cycles, which means that the system has at most one limit cycle. In addition, according to the two specific functions, i.e., smooth continuous and binary-value activation functions of the system, we give the numerical simulation and realize the circuit design of the single-neuron system by using Multisim modeling, respectively. The waveform diagram and phase diagram of the numerical simulation and circuit simulation are obtained. By comparing the results of numerical and circuit simulation, the effectiveness of our mathematical analysis and the feasibility of circuit design are better illustrated.

A recommender system (RS) is highly efficient in extracting valuable information from a deluge of big data. The key issue of implementing an RS lies in uncovering users' latent preferences on different items. Latent Feature Analysis (LFA) and deep neural networks (DNNs) are two of the most popular and successful approaches to addressing this issue. However, both the LFA-based and the DNNs-based models have their own distinct advantages and disadvantages. Consequently, relying solely on either the LFA or DNN-based models cannot ensure optimal recommendation performance across diverse real-world application scenarios. To address this issue, this paper proposes a novel hybrid recommendation model that combines Autoencoder and LFA techniques, termed AutoLFA. The main idea of AutoLFA is two-fold: (1) It leverages an Autoencoder and an LFA model separately to construct two distinct recommendation models, each residing in a unique metric representation space with its own set of strengths; and (2) it integrates the Autoencoder and LFA model using a customized self-adaptive weighting strategy, thereby capitalizing on the merits of both approaches. To evaluate the proposed AutoLFA model, extensive experiments on five real recommendation datasets are conducted. The results demonstrate that AutoLFA achieves significantly better recommendation performance than the seven related state-of-the-art models.

Research infrastructures play an increasingly essential role in scientific research. They provide rich data sources for scientists, such as services and software packages, via catalog and virtual research environments. However, such research infrastructures are typically domain-specific and often not connected. Accordingly, researchers and practitioners face fundamental challenges introduced by fragmented knowledge from heterogeneous, autonomous sources with complicated and uncertain relations in particular research domains. Additionally, the exponential growth rate of knowledge in a specific domain surpasses human experts' ability to formalize and capture tacit and explicit knowledge efficiently. Thus, a knowledge management system is required to discover knowledge effectively, automate the knowledge acquisition based on artificial intelligence approaches, integrate the captured knowledge, and deliver consistent knowledge to agents, research communities, and end-users. In this study, we present the development process of a knowledge management system for ENVironmental Research Infrastructures, which are crucial pillars for environmental scientists in their quest for understanding and interpreting the complex Earth System. Furthermore, we report the challenges we have faced and discuss the lessons learned during the development process., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 Farshidi S et al.)

Objective: Patients with systemic lupus erythematosus (SLE) often develop multi-organ damages including heart and kidney complications. We sought to better define the underlying mechanisms with a focus on the chemokine receptor CX 3 CR1., Methods: We generated Cx3cr1-deficient MRL/lpr lupus-prone mice through backcrossing. We then employed heterozygous intercross to generate MRL/lpr littermates that were either sufficient or deficient of CX 3 CR1. The mice were also treated with either Lactobacillus spp. or a high-fat diet (HFD) followed by assessments of the kidney and heart, respectively., Results: Cx3cr1 -/- MRL/lpr mice exhibited a distinct phenotype of exacerbated glomerulonephritis compared to Cx3cr1 +/+ littermates, which was associated with a decrease of spleen tolerogenic marginal zone macrophages and an increase of double-negative T cells. Interestingly, upon correction of the gut microbiota with Lactobacillus administration, the phenotype of exacerbated glomerulonephritis was reversed, suggesting that CX 3 CR1 controls glomerulonephritis in MRL/lpr mice through a gut microbiota-dependent mechanism. Upon treatment with HFD, Cx3cr1 -/- MRL/lpr mice developed significantly more atherosclerotic plaques that were promoted by Ly6C + monocytes. Activated monocytes expressed ICOS-L that interacted with ICOS-expressing follicular T-helper cells, which in turn facilitated a germinal center reaction to produce more autoantibodies. Through a positive feedback mechanism, the increased circulatory autoantibodies further promoted the activation of Ly6C + monocytes and their display of ICOS-L., Conclusions: We uncovered novel, Cx3cr1 deficiency-mediated pathogenic mechanisms contributing to SLE-associated glomerulonephritis and cardiovascular disease., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

In this article, a single-layer projection neural network based on penalty function and differential inclusion is proposed to solve nonsmooth pseudoconvex optimization problems with linear equality and convex inequality constraints, and the bound constraints, such as box and sphere types, in inequality constraints are processed by projection operator. By introducing the Tikhonov-like regularization method, the proposed neural network no longer needs to calculate the exact penalty parameters. Under mild assumptions, by nonsmooth analysis, it is proved that the state solution of the proposed neural network is always bounded and globally exists, and enters the constrained feasible region in a finite time, and never escapes from this region again. Finally, the state solution converges to an optimal solution for the considered optimization problem. Compared with some other existing neural networks based on subgradients, this algorithm eliminates the dependence on the selection of the initial point, which is a neural network model with a simple structure and low calculation load. Three numerical experiments and two application examples are used to illustrate the global convergence and effectiveness of the proposed neural network.

This paper investigates a class of power consumption minimization and equalization for intelligent and connected vehicles cooperative system. Accordingly, a distributed optimization problem model related to power consumption and data rate of intelligent and connected vehicles is presented, where the power consumption cost function of each intelligent and connected vehicle may be nonsmooth, and the corresponding control variable is subject to the constraints generated by data acquisition, compression coding, transmission and reception. We propose a distributed subgradient-based neurodynamic approach with projection operator to achieve the optimal power consumption of intelligent and connected vehicles. By differential inclusion and nonsmooth analysis, it is confirmed that the state solution of neurodynamic system converges to the optimal solution of the distributed optimization problem. With the help of the algorithm, all intelligent and connected vehicles asymptotically reach a consensus on an optimal power consumption. Simulation results show that the proposed neurodynamic approach is capable of effectively solving the problem of power consumption optimal control for intelligent and connected vehicles cooperative system., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Drought greatly influences the growth and ecological stoichiometry of plants in arid and semi-arid regions such as karst areas, where Cinnamomum migao ( C. migao ) is an endemic tree species that is used as a bioenergy resource. Arbuscular mycorrhizal fungi (AMF) play a key role in nutrient uptake in the soil-plant continuum, increasing plant tolerance to drought. However, few studies have examined the contribution of AMF in improving the growth of C. migao seedlings and the soil nutrient stoichiometry under drought-stress conditions. A pot experiment was conducted under natural light in a plastic greenhouse to investigate the effects of individual inoculation and Co-inoculation of AMF [ Funneliformis mosseae ( F. mosseae ) and Claroideoglomus etunicatum ( C. etunicatum )] on the growth, water status, and nutrient uptake of C. migao as well as the soil nutrient stoichiometry under well-watered (WW) and drought-stress (DS) conditions. The results showed that compared with non-AMF control (CK), AM symbiosis significantly stimulated plant growth and had higher dry mass. Mycorrhizal plants had better water status than corresponding CK plants. AMF colonization notably increased the total nitrogen and phosphorus content of C. migao seedlings compared with CK. Mycorrhizal plants had higher leaf and stem total carbon concentrations than CK. The results indicated that AM symbiosis protects C. migao seedlings against drought stress by improving growth, water status, and nutrient uptake. In general, the C. migao seedlings that formed with C. etunicatum showed the most beneficial effect on plant growth, water status, and nutrient uptake among all treatments. In the future, we should study more about the biological characteristics of each AMF in the field study to understand more ecological responses of AMF under drought stress, which can better provide meaningful guidance for afforestation projects in karst regions.

In this paper, a subgradient-based neurodynamic algorithm is presented to solve the nonsmooth nonconvex interval-valued optimization problem with both partial order and linear equality constraints, where the interval-valued objective function is nonconvex, and interval-valued partial order constraint functions are convex. The designed neurodynamic system is constructed by a differential inclusion with upper semicontinuous right-hand side, whose calculation load is reduced by relieving penalty parameters estimation and complex matrix inversion. Based on nonsmooth analysis and the extension theorem of the solution of differential inclusion, it is obtained that the global existence and boundedness of state solution of neurodynamic system, as well as the asymptotic convergence of state solution to the feasible region and the set of LU-critical points of interval-valued nonconvex optimization problem. Several numerical experiments and the applications to emergency supplies distribution and nondeterministic fractional continuous static games are solved to illustrate the applicability of the proposed neurodynamic algorithm., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The incidence of cutaneous T-cell lymphoma (CTCL) increases with age, and blood involvement portends a worse prognosis. To advance our understanding of the development of CTCL and identify potential therapeutic targets, we performed integrative analyses of paired single-cell RNA and T-cell receptor (TCR) sequencing of peripheral blood CD4+ T cells from patients with CTCL to reveal disease-unifying features. The malignant CD4+ T cells of CTCL showed highly diverse transcriptomic profiles across patients, with most displaying a mature Th2 differentiation and T-cell exhaustion phenotype. TCR-CDR3 peptide prediction analysis suggested limited diversity between CTCL samples, consistent with a role for a common antigenic stimulus. Potential of heat diffusion for affinity-based trajectory embedding transition analysis identified putative precancerous circulating populations characterized by an intermediate stage of gene expression and mutation level between the normal CD4+ T cells and malignant CTCL cells. We further revealed the therapeutic potential of targeting CD82 and JAK that endow the malignant CTCL cells with survival and proliferation advantages., (© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Electroencephalogram (EEG) based seizure prediction plays an important role in the closed-loop neuromodulation system. However, most existing seizure prediction methods based on graph convolution network only focused on constructing the static graph, ignoring multi-domain dynamic changes in deep graph structure. Moreover, the existing feature fusion strategies generally concatenated coarse-grained epileptic EEG features directly, leading to the suboptimal seizure prediction performance. To address these issues, we propose a novel multi-branch dynamic multi-graph convolution based channel-weighted transformer feature fusion network (MB-dMGC-CWTFFNet) for the patient-specific seizure prediction with the superior performance. Specifically, a multi-branch (MB) feature extractor is first applied to capture the temporal, spatial and spectral representations fromthe epileptic EEG jointly. Then, we design a point-wise dynamic multi-graph convolution network (dMGCN) to dynamically learn deep graph structures, which can effectively extract high-level features from the multi-domain graph. Finally, by integrating the local and global channel-weighted strategies with the multi-head self-attention mechanism, a channel-weighted transformer feature fusion network (CWTFFNet) is adopted to efficiently fuse the multi-domain graph features. The proposed MB-dMGC-CWTFFNet is evaluated on the public CHB-MIT EEG and a private intracranial sEEG datasets, and the experimental results demonstrate that our proposed method achieves outstanding prediction performance compared with the state-of-the-art methods, indicating an effective tool for patient-specific seizure warning. Our code will be available at: https://github.com/Rockingsnow/MB-dMGC-CWTFFNet.

Seizure prediction of epileptic preictal period through electroencephalogram (EEG) signals is important for clinical epilepsy diagnosis. However, recent deep learning-based methods commonly employ intra-subject training strategy and need sufficient data, which are laborious and time-consuming for a practical system and pose a great challenge for seizure predicting. Besides, multi-domain characterizations, including spatio-temporal-spectral dependencies in an epileptic brain are generally neglected or not considered simultaneously in current approaches, and this insufficiency commonly leads to suboptimal seizure prediction performance. To tackle the above issues, in this paper, we propose Contrastive Learning for Epileptic seizure Prediction (CLEP) using a Spatio-Temporal-Spectral Network (STS-Net). Specifically, the CLEP learns intrinsic epileptic EEG patterns across subjects by contrastive learning. The STS-Net extracts multi-scale temporal and spectral representations under different rhythms from raw EEG signals. Then, a novel triple attention layer (TAL) is employed to construct inter-dimensional interaction among multi-domain features. Moreover, a spatio dynamic graph convolution network (sdGCN) is proposed to dynamically model the spatial relationships between electrodes and aggregate spatial information. The proposed CLEP-STS-Net achieves a sensitivity of 96.7% and a false prediction rate of 0.072/h on the CHB-MIT scalp EEG database. We also validate the proposed method on clinical intracranial EEG (iEEG) database from our Xuanwu Hospital of Capital Medical University, and the predicting system yielded a sensitivity of 95%, a false prediction rate of 0.087/h. The experimental results outperform the state-of-the-art studies which validate the efficacy of our method. Our code is available at https://github.com/LianghuiGuo/CLEP-STS-Net.

This article develops several centralized and collective neurodynamic approaches for sparse signal reconstruction by solving the L 1 -minimization problem. First, two centralized neurodynamic approaches are designed based on the augmented Lagrange method and the Lagrange method with derivative feedback and projection operator. Then, the optimality and global convergence of them are derived. In addition, considering that the collective neurodynamic approaches have the function of information protection and distributed information processing, first, under mild conditions, we transform the L 1 -minimization problem into two network optimization problems. Later, two collective neurodynamic approaches based on the above centralized neurodynamic approaches and multiagent consensus theory are proposed to address the obtained network optimization problems. As far as we know, this is the first attempt to use the collective neurodynamic approaches to deal with the L 1 -minimization problem in a distributed manner. Finally, several comparative experiments on sparse signal and image reconstruction demonstrate that our proposed centralized and collective neurodynamic approaches are efficient and effective.

This letter develops a novel fixed-time stable neurodynamic flow (FTSNF) implemented in a dynamical system for solving the nonconvex, nonsmooth model L1-β2, β∈[0,1] to recover a sparse signal. FTSNF is composed of many neuron-like elements running in parallel. It is very efficient and has provable fixed-time convergence. First, a closed-form solution of the proximal operator to model L1-β2, β∈[0,1] is presented based on the classic soft thresholding of the L1-norm. Next, the proposed FTSNF is proven to have a fixed-time convergence property without additional assumptions on the convexity and strong monotonicity of the objective functions. In addition, we show that FTSNF can be transformed into other proximal neurodynamic flows that have exponential and finite-time convergence properties. The simulation results of sparse signal recovery verify the effectiveness and superiority of the proposed FTSNF., (© 2022 Massachusetts Institute of Technology.)

Analyzing the coupling relationship between biodiversity and environmental geology and exploring the factors affecting the coupling degree are of vital significance for the protection and restoration of the ecological environment. In this study, we selected five typical areas (i.e., Caohai, Chishui, Fanjingshan, Maolan, and Guanshanhu) to represent the whole Guizhou Province, China. Based on the coupling coordination degree model, we analyzed their coupling coordination trend. The results showed that the coordinated development stages of the Chishui and Fanjingshan areas both could be categorized as the synchronous development type of primary coordination because of their excellent nature conditions; the Maolan area was categorized as having restrained environmental geology because of its weak environmental geology condition; and the Guanshanhu and Weining areas were strongly affected by human activities, and both could be categorized as having restrained biodiversity. In combination with practical situation, Guizhou province can be categorized into the following three zones: an original ecological zone, a zone with fragile ecological environment, and a zone affected by human activities. Biodiversity conservation measures should be proposed according to the specific ecological situation of these different zones. In this way, the harmonious coexistence of economic development and the ecological environment can be realized., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

These days, the increasing incremental cost consensus-based algorithms are designed to tackle the economic dispatch (ED) problem in smart grids (SGs). However, one principal obstruction lies in privacy disclosure for generators and consumers in electricity activities between supply and demand sides, which may bring great losses to them. Hence, it is extraordinarily essential to design effective privacy-preserving approaches for ED problems. In this article, we propose a two-phase distributed and effective heterogeneous privacy-preserving consensus-based (DisEHPPC) ED scheme, where a demand response (DR)-based framework is constructed, including a DR server, data manager, and a set of local controllers. The first phase is that Kullback-Leibler (KL) privacy is guaranteed for the privacy of consumers' demand by the differential privacy method. The second phase is that (ε,δ) -privacy is, respectively, achieved for the generation energy of generators and the sensitivity of electricity consumption to electricity price by designing the privacy-preserving incremental cost consensus-based (PPICC) algorithm. Meanwhile, the proposed PPICC algorithm tackles the formulated ED problem. Subsequently, we further carry out the detailed theoretical analysis on its convergence, optimality of final solution, and privacy degree. It is found that the optimal solution for the ED problem and the privacy preservation of both supply and demand sides can be guaranteed simultaneously. By evaluation of a numerical experiment, the correctness and effectiveness of the DisEHPPC scheme are confirmed.

This article discusses the couple-group consensus for heterogeneous multiagent systems via event-triggered and pinning control methods. Considering cooperative-competitive interaction among the agents, a novel group consensus protocol is designed. As inducing the time-correlation threshold function, a class of fully distributed event-triggered conditions without depending on any global information is proposed. Utilizing the Lyapunov stability theory, some sufficient conditions are obtained. Under hybrid event triggered and pinning control, pinning control strategies are first introduced. It is shown that under the proposed strategies, all agents can asymptotically achieve pinning couple-group consensus with discontinuous communication in a fully distributed way. Furthermore, the Zeno behavior for each agent is overcome. Finally, the reduction of the systems' controller update frequency and the correctness of our conclusions are illustrated by some simulations.

Consider that the constrained convex optimization problems have emerged in a variety of scientific and engineering applications that often require efficient and fast solutions. Inspired by the Nesterov's accelerated method for solving unconstrained convex and strongly convex optimization problems, in this paper we propose two novel accelerated projection neurodynamic approaches for constrained smooth convex and strongly convex optimization based on the variational approach. First, for smooth, and convex optimization problems, a non-autonomous accelerated projection neurodynamic approach (NAAPNA) is presented and the existence, uniqueness and feasibility of the solution to it are analyzed rigorously. We provide that the NAAPNA has a convergence rate which is inversely proportional to the square of the running time. In addition, we present a novel autonomous accelerated projection neurodynamic approach (AAPNA) for addressing the constrained, smooth, strongly convex optimization problems and prove the existence, uniqueness to the strong global solution of AAPNA based on the Cauchy-Lipschitz-Picard theorem. Furthermore, we also prove the global convergence of AAPNA with different exponential convergence rates for different parameters. Compared with existing projection neurodynamic approaches based on the Brouwer's fixed point theorem, both NAAPNA and AAPNA use the projection operators of the auxiliary variable to map the primal variables to the constrained feasible region, thus our proposed neurodynamic approaches are easier to realize algorithm's acceleration. Finally, the effectiveness of NAAPNA and AAPNA is illustrated with several numerical examples., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The decomposition of litter plays an important role in the return of forest soil nutrients, as well as the growth and productivity of plants. With this study, we aimed to determine the impact of litter mulching on different tissues of Cinnamomum migao , a rare Chinese endemic species. In particular, seeds and pericarp are easily overlooked components of C. migao litter. In this study, we tested control (uncovered litter) and litter (leaf, branch, seed, and pericarp) mulching conditions and conducted a one-year litter decomposition experiment. The enzyme activities of urease enzyme (UE) and invertase enzyme (INV) were significantly improved by litter mulching. Catalase (CAT) enzyme activities in leaf, branch, and seed litter mulching were lower than in the control, whereas CAT activity in pericarp mulching was significantly higher than in the control. Although Mortierella, Cladophialophora , Acidothermus , Sphingomonas , and Burkholderia were the dominant microbes of topsoil in different mulching treatments, there were differences in the number and connectivity of microbial communities, and this change was correlated with soil organic carbon (SOC) and CAT enzyme activity. Compared with leaves and branches, seeds and pericarp as litter are also very important for nutrient return and affect topsoil microbes in C. migao forest, which may be of significance for the growth feedback of C. migao in biennial bearing.

Background: Extraperitoneal colostomy (EPC) after laparoscopic abdominoperineal resection (APR) remains a challenge for surgeons. This study aims to summarize our laparoscopic EPC method and assess its effects versus a transperitoneal colostomy (TPC) for patients with rectal tumors., Methods: A total of 133 patients with rectal cancer treated with laparoscopic APR between May 2009 and May 2020 were retrospectively reviewed. The clinical data, including demographics, comorbidities, tumor stage, colostomy duration, and complications were compared between the EPC group and the TPC group., Results: The EPC group included 83 patients whose extraperitoneal tunnels were created using a cannula through a trocar port, and the TPC group included 50 patients whose stomata were formed traditionally. There were no differences in colostomy time [(23.1 ± 6) min vs. (21.4 ± 4) min, P = 0.078], number of parastomal dermatitis patients (5 vs. 2, P = 0.916), or number of stomal stenoses (1 vs. 1, P = 0.715) between the EPC and TPC groups. No cases of parastomal hernia developed in the EPC group, whereas 4 patients were diagnosed with a parastomal hernia; the difference between the two groups was statistically significant (P = 0.036)., Conclusions: Laparoscopic EPC have a lower incidence of parastomal hernia than TPC. It is easy and inexpensive to create an extraperitoneal tunnel using a cannula through a trocar port., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The genomes of thousands of individuals are profiled within Dutch healthcare and research each year. However, this valuable genomic data, associated clinical data and consent are captured in different ways and stored across many systems and organizations. This makes it difficult to discover rare disease patients, reuse data for personalized medicine and establish research cohorts based on specific parameters. FAIR Genomes aims to enable NGS data reuse by developing metadata standards for the data descriptions needed to FAIRify genomic data while also addressing ELSI issues. We developed a semantic schema of essential data elements harmonized with international FAIR initiatives. The FAIR Genomes schema v1.1 contains 110 elements in 9 modules. It reuses common ontologies such as NCIT, DUO and EDAM, only introducing new terms when necessary. The schema is represented by a YAML file that can be transformed into templates for data entry software (EDC) and programmatic interfaces (JSON, RDF) to ease genomic data sharing in research and healthcare. The schema, documentation and MOLGENIS reference implementation are available at https://fairgenomes.org ., (© 2022. The Author(s).)

Background and Aims: Hepatocellular carcinoma (HCC) is a common malignant disease with high morbidity and mortality throughout the world. While Borealin is a putative oncogene that is dysregulated in multiple tumors, its exact role in HCC remains less investigated., Methods: Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) assays were employed to examine the relative amount of Borealin. Gene set enrichment analysis (GSEA) and other bioinformatic analyses were implemented to probe into the potential functions of Borealin. The biological roles and mechanisms of Borealin in the tumorigenesis and development of HCC were further evaluated using a battery of functional assays in vivo and in vitro., Results: Borealin was enhanced in the HCC tissue samples and hepatoma cells when compared with the nontumor tissues and normal liver cells. Higher Borealin expression was positively linked with advanced pathological phenotypes and inferior overall survival. The overexpression of Borealin promoted the cells' abilities on proliferation, invasion and epithelial-mesenchymal transition (EMT) in vitro, facilitated tumor growth and lung metastasis in vivo, whereas the silencing of Borealin inhibited these capabilities in vitro. Furthermore, Borealin interacted with β-catenin and further activated the Wnt/β-catenin signaling pathway, which endowed HCC cells with highly aggressive and metastatic capabilities., Conclusion: Borealin was identified as an oncogene that could promote HCC growth and metastasis by activating the WNT/β-catenin signaling pathway. These findings extended the understanding of Borealin in HCC tumorigenesis and development and highlighted the significance of Borealin in HCC diagnosis and treatment., Competing Interests: All authors declare no conflicts of interest for this work., (© 2022 Chen et al.)

Sludge-based activated carbons (SACs) prepared from sewage sludge and corn straw, were modified by ferric nitrate, and the unmodified SAC and modified SAC were used as the adsorbing agent to treat the landfill leachate, the elimination capacity for chemical oxygen demand (COD) and organic matter in leachate were studied. Based on this, the physicochemical properties of SACs and the components changes in leachate were analyzed and characterized by X-ray photoelectron spectroscopy and three-dimensional fluorescence spectroscopy. The results showed that under optimal experimental conditions, the elimination capacities of SAC372 for COD, biological oxygen demand over 5 days, and NH 4 + -N in the leachate were 81.58%, 54.73%, and 69.08%, respectively; while the adsorption capacities of modified SAC for these three substances were 86.25%, 63.51%, and 79.15%, respectively. The ferric nitrate modification improved the ability of SAC to eliminate COD and organic matter from leachate slightly, and made the adsorption occurred easily. The adsorption process of unmodified SAC was dominated by multi-layer adsorption, while the adsorption process of modified SAC was dominated by monolayer adsorption. The mass fraction of Fe (2p) in modified SAC remarkably increased, from 0.70% to 26.01%, organic functional groups certain phase of Fe oxides with different valence states were generated in SAC, which provided a substrate for iron-carbon micro electrolysis. After adsorbed by unmodified SAC and modified SAC adsorption, the total fluorescence intensity of in the leachate increased by 17.01% and 116.84%, respectively. Both two SACs could decompose the humic acid-like substances into aromatic protein organic compounds, and modified SAC could further decompose the soluble microbial byproduct-like substances.

Drought stress is one of the greatest obstacles affecting field crop productivity in arid and semi-arid regions, and its severity and frequency are expected to increase due to human-induced changes to the environment and climate. Drought has led to rocky desertification in Karst regions. Cinnamomum migao is a unique, fast-growing medicinal plant of Southwest China that only thrives in Karst regions. Arbuscular mycorrhizal fungi (AMF) symbiosis alleviates drought stress in plants; however, establishment and function of the symbiotic interaction between AMF host plant in relation to the inoculation method remain unclear. Therefore, we conducted an experiment to investigate the effects of AMF species ( Glomus etunicatum and Funneliformis mosseae ) and two inoculation methods (seed vs. seedling inoculation) under drought stress on C. migao seedlings, and quantified mycorrhizal colonization, AMF spore density, root vigor, relative water content, C. migao growth, antioxidant enzyme activities, and osmotic adjustment. Inoculation with AMF ( G. etunicatum and F. mosseae ) positively affected the growth and root vigor of Cinnamomum migao under drought stress, regardless of the inoculation method. Additionally, both AMF species markedly upregulated antioxidant enzyme activities and osmotic adjustment substances, regardless of the inoculation method. Our results showed that the collective stimulatory effect of G. etunicatum is more efficient than that of F. mosseae . AMF application could promote afforestation with C. migao to prevent rocky desertification in Karst regions where water is the greatest limiting factor on plant growth and yield.

Background: To evaluate the clinical risk factors that influence the overall survival in patients with duodenal adenocarcinoma (DA) after tumor resection., Methods: This study retrospectively analyzed 188 patients who underwent tumor resection for DA between January 2005 and June 2020 at Xiangyang Central Hospital., Results: The median survival of the patients who underwent resectional operation was 54 months, longer than of those who underwent palliative surgery (20.8 months) (2,916.17; 95% CI, 916.3-9,280.5; p < 0.001). Survival of non-ampullary duodenal carcinoma patients (50.3 months; 95% CI, 39.7-61.8) was similar to that of ampullary duodenal carcinoma patients (59.3 months; 95% CI, 38.6-66.7) but was significantly better than that of papillary adenocarcinoma patients (38.9 months; 95% CI, 29.8-54.8; p = 0.386). Those with intestinal-type ductal adenocarcinomas had a longer median overall survival than those with the gastric type (61.8 vs. 46.7 months; p < 0.01) or pancreatic type (32.2 months; p < 0.001). Clinical DA samples had significantly diverse expressions of ATG12, IRS2, and IGF2. Higher expressions of the ATG12 and IRS2 proteins were significantly correlated with worse survival. Multivariate Cox regression analysis revealed that lymph node metastasis (hazard ratio (HR), 6.44; 95% CI, 3.68-11.27; p < 0.0001), margin status (HR, 4.94; 95% CI, 2.85-8.54; p < 0.0001), and high expression of ATG12 (HR, 1.89; 95% CI, 1.17-3.06; p = 0.0099) were independent prognostic factors negatively associated with survival in patients undergoing curative resection. There was no survival difference between the groups with ampullary, non-ampullary, and papillary adenocarcinomas treated with adjuvant chemotherapy ( p = 0.973)., Conclusion: Gastric/pancreatic type, high expression of ATG12, lymph node metastases, and margin status were negative prognosticators of survival in patients with DAs than in those with tumor anatomical location. Curative resection is the best treatment option for appropriate patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Sun, Liu, Lv, Li, Liao and Gong.)

Artemisia argyi H. Lév. and Vaniot is a traditional medical herb that has been used for a long time in China and other Asian counties. Essential oil is the main active fraction of Artemisia argyi H. Lév. and Vaniot, and its anti-inflammatory potential has been observed in vitro and in vivo . Here, we found that the essential oil of Artemisia argyi H. Lév. and Vaniot (EOAA) inhibited monosodium urate (MSU)- and nigericin-induced NLRP3 inflammasome activation. EOAA suppressed caspase-1 and IL-1β processing and pyroptosis. NF-κB p65 phosphorylation and translocation were also inhibited. In addition, EOAA suppressed nigericin-induced NLRP3 inflammasome activation without blocking ASC oligomerization, suggesting that it may inhibit NLRP3 inflammasome activation by preventing caspase-1 processing. Our study thus indicates that EOAA inhibits NLRP3 inflammasome activation and has therapeutic potential against NLRP3-driven diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Chen, Bai, Wu, Zeng, Song, Guo, Zhou, Wang, Liao, Wang, Ren and Wang.)

Federated learning (FL) is a machine-learning setting, where multiple clients collaboratively train a model under the coordination of a central server. The clients' raw data are locally stored, and each client only uploads the trained weight to the server, which can mitigate the privacy risks from the centralized machine learning. However, most of the existing FL models focus on one-time learning without consideration for continuous learning. Continuous learning supports learning from streaming data continuously, so it can adapt to environmental changes and provide better real-time performance. In this article, we present a federated continuous learning scheme based on broad learning (FCL-BL) to support efficient and accurate federated continuous learning (FCL). In FCL-BL, we propose a weighted processing strategy to solve the catastrophic forgetting problem, so FCL-BL can handle continuous learning. Then, we develop a local-independent training solution to support fast and accurate training in FCL-BL. The proposed solution enables us to avoid using a time-consuming synchronous approach while addressing the inaccurate-training issue rooted in the previous asynchronous approach. Moreover, we introduce a batch-asynchronous approach and broad learning (BL) technique to guarantee the high efficiency of FCL-BL. Specifically, the batch-asynchronous approach reduces the number of client-server interaction rounds, and the BL technique supports incremental learning without retraining when learning newly produced data. Finally, theoretical analysis and experimental results further illustrate that FCL-BL is superior to the existing FL schemes in terms of efficiency and accuracy in FCL.

In this paper, we propose a smoothing inertial neurodynamic approach (SINA) which is used to deal with L p -norm minimization problem to reconstruct sparse signals. Note that the considered optimization problem is nonsmooth, nonconvex and non-Lipschitz. First, the problem is transformed into a smooth optimization problem based on smoothing approximation method, and the Lipschitz property of gradient of the smooth objective function is discussed. Then, SINA based on Karush-Kuhn-Tucker (KKT) condition, smoothing approximation and inertial dynamical approach, is designed to handle smooth optimization problem. The existence, uniqueness, global convergence and optimality of the solution of the SINA are discussed by the Cauchy-Lipschitz-Picard theorem, energy function and KKT condition. In addition, for p=1, the SINA has a mean sublinear convergence rate O1∕t under some mild conditions. Finally, some numerical examples on sparse signal reconstruction and image restoration are given to illustrate the theoretical results and the efficiency of SINA., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Cinnamomum migao plants often face different degrees of drought in karst habitats, which can lead to plants' death, especially in the seedling stage. Widespread of arbuscular mycorrhizal (AM) fungi in karst soils have the potential to address this drought, which is a threat to C. migao seedlings. We inoculated C. migao seedlings with spores from Glomus lamellosum and Glomus etunicatum , two AM fungi widely distributed in karst soils, to observe seedling growth response after simulated drought. Our results showed that 40 g of G. lamellosum and G. etunicatum significantly promoted the growth of C. migao seedlings, 120 days after inoculation. Following a 15-day drought treatment, root colonization of the seedlings with G. lamellosum or G. etunicatum had lower the accumulation of malondialdehyde (MDA) and increased the accumulation of enzymes and osmotic substances in the seedlings. The relative water content in different organs (roots, stems, and leaves) of the drought-stressed seedlings was higher in plants with G. lamellosum or G. etunicatum than in plants without AM fungi colonization. Our results showed that inoculation with AM fungi was an effective means to improve the drought resistance of C. migao seedlings., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could influence the work reported in this paper., (© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the Korean Society of Mycology.)

Background: This study examined how rhizosphere fungi influence the accumulation of chemical components in fruits of a small population species of Cinnamomum migao., Results: Ascomycota and Basidiomycota were dominant in the rhizosphere fungal community of C. migao. Pestalotiopsis and Gibellulopsis were associated with α-Terpineol and sabinene content, and Gibellulopsis was associated with crude fat and carbohydrate content. There were significant differences in rhizosphere fungal populations between watersheds, and there was no obvious change between fruiting periods. Gibberella, Ilyonectria, Micropsalliota, and Geminibasidium promoted sabinene accumulation, and Clitocybula promoted α-Terpineol accumulation., Conclusion: The climate-related differentiation of rhizosphere fungal communities in watershed areas is the main driver of the chemical composition of C. migao fruit. The control of the production of biologically active compounds by the rhizosphere fungal community provides new opportunities to increase the industrial and medicinal value of the fruit of C. migao.

This article investigates the problem of distributed online optimization for a group of units communicating on time-varying unbalanced directed networks. The main target of the set of units is to cooperatively minimize the sum of all locally known convex cost functions (global cost function) while pursuing the privacy of their local cost functions being well masked. To address such optimization problems in a collaborative and distributed fashion, a differentially private-distributed stochastic subgradient-push algorithm, called DP-DSSP, is proposed, which ensures that units interact with in-neighbors and collectively optimize the global cost function. Unlike most of the existing distributed algorithms which do not consider privacy issues, DP-DSSP via differential privacy strategy successfully masks the privacy of participating units, which is more practical in applications involving sensitive messages, such as military affairs or medical treatment. An important feature of DP-DSSP is tackling distributed online optimization problems under the circumstance of time-varying unbalanced directed networks. Theoretical analysis indicates that DP-DSSP can effectively mask differential privacy as well as can achieve sublinear regrets. A compromise between the privacy levels and the accuracy of DP-DSSP is also revealed. Furthermore, DP-DSSP is capable of handling arbitrarily large but uniformly bounded delays in the communication links. Finally, simulation experiments confirm the practicability of DP-DSSP and the findings in this article.

As a novel heat shock protein 90 inhibitor, AT-533 exhibits various biological activities in vitro , including anti-viral, anti-tumor and anti-inflammatory activities. Moreover, AT-533 gel, a gel dosage form of AT-533, has been suggested to have anti-keratitis and herpes simplex virus type-1 infection-induced effects on the skin lesions of animals. However, the safety evaluation of AT-533 and AT-533 gel has, to the best of our knowledge, not been examined in in vivo toxicological tests. Therefore, these toxicological tests were carried out in the present study. A 30-day subacute toxicity test for AT-533 was conducted at doses of 1, 2 and 4 mg/kg in Sprague-Dawley rats, while that for AT-533 gel was conducted using a single dose of 5 g/kg. The toxicological tests showed that a high-dose of AT-533 caused lethality and side effects in Sprague-Dawley rats. However, no mortality, loss of appetite and body weight, adverse reactions, or toxicologically relevant alterations in hematology, biochemistry and macroscopic findings (except for skin) occurred in rats exposed to low-dose AT-533 and single-dose AT-533 gel (5 g/kg) during a 30-day subacute dermic toxicity study. The aforementioned results suggested that AT-533 gel is non-toxic for Sprague-Dawley rats, as shown by a dermic subacute toxicity test and that except for slight skin irritation, AT-533 gel had almost no side effects when administered percutaneously for 30 days., Competing Interests: The authors declare that they have no competing interests., (Copyright: © Wu et al.)

Background: To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This model would assist frontline clinicians in optimizing medical treatment with limited resources., Methods: 6415 patients from seven hospitals in Wuhan city were assigned to the training and testing cohorts. A total of 6351 patients from another three hospitals in Wuhan, 2169 patients from outside of Wuhan, and 553 patients from Milan, Italy were assigned to three independent validation cohorts. A total of 64 candidate clinical variables at hospital admission were analyzed by random forest and least absolute shrinkage and selection operator (LASSO) analyses., Results: Eight factors, namely, O xygen saturation, blood U rea nitrogen, R espiratory rate, admission before the date the national M aximum number of daily new cases was reached, A ge, P rocalcitonin, C -reactive protein (CRP), and absolute N eutrophil counts, were identified as having significant associations with mortality in COVID-19 patients. A composite score based on these eight risk factors, termed the OURMAPCN-score, predicted the risk of mortality among the COVID-19 patients, with a C-statistic of 0.92 (95% confidence interval [CI] 0.90-0.93). The hazard ratio for all-cause mortality between patients with OURMAPCN-score >11 compared with those with scores ≤ 11 was 18.18 (95% CI 13.93-23.71; p  < .0001). The predictive performance, specificity, and sensitivity of the score were validated in three independent cohorts., Conclusions: The OURMAPCN score is a risk assessment tool to determine the mortality rate in COVID-19 patients based on a limited number of baseline parameters. This tool can assist physicians in optimizing the clinical management of COVID-19 patients with limited hospital resources.

Corticosteroid therapy is now recommended as a treatment in patients with severe COVID-19. But one key question is how to objectively identify severely ill patients who may benefit from such therapy. Here, we assigned 12,862 COVID-19 cases from 21 hospitals in Hubei Province equally to a training and a validation cohort. We found that a neutrophil-to-lymphocyte ratio (NLR) > 6.11 at admission discriminated a higher risk for mortality. Importantly, however, corticosteroid treatment in such individuals was associated with a lower risk of 60-day all-cause mortality. Conversely, in individuals with an NLR ≤ 6.11 or with type 2 diabetes, corticosteroid treatment was not associated with reduced mortality, but rather increased risks of hyperglycemia and infections. These results show that in the studied cohort corticosteroid treatment is associated with beneficial outcomes in a subset of COVID-19 patients who are non-diabetic and with severe symptoms as defined by NLR., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)