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Purpose: Salivary gland malignancies may have overlapping architectural patterns, tumor morphology, and immunohistochemical phenotypes, presenting challenges in precise classification. Molecular phenotyping has become quite useful for providing an additional diagnostic modality, and potential drug targets. Here we reported a young female patient with salivary gland tumor of the tongue base harboring genetic alterations by next generation sequencing (NGS). Methods: The morphological, immunohistochemical and molecular features of this case were described, and related literature was reviewed. Results: The tumor showed an epithelial myoepithelial architecture arranged in cords and tubules interwoven with a chondromyxoid stroma, along with perineural invasion and adjacent striated muscle infiltration. Myoepithelial cells were positive for CK5/6, partially positive for P63 and CK7, and sporadically positive for S100. Immunoprofiling revealed a low density of infiltrating lymphocytes and macrophages and the absence of programmed death ligand 1 (PD-L1). Notably, RNA-based NGS showed EWSR1::BEND2 gene fusion in this tumor, and EWSR1 break-apart was confirmed by fluorescence in situ hybridization. This led to a final diagnosis of a minor salivary gland malignancy with EWSR1::BEND2 fusion. Only two other cases of salivary gland tumors with EWSR1::BEND2 fusion had been previously reported, which were also detected via RNA-based NGS. Conclusion: This study emphasized that EWSR1::BEND2 fusion may drive the carcinogenesis in salivary glands neoplasia. In clinic RNA-based NGS could be essential for precise genotyping of EWSR1 fusion in this rare disease. [ABSTRACT FROM AUTHOR]

The first-order optimality condition of convexly constrained nonconvex nonconcave min-max optimization problems with box constraints formulates a nonmonotone variational inequality (VI), which is equivalent to a system of nonsmooth equations. In this paper, we propose a quasi-Newton subspace trust region (QNSTR) algorithm for the least squares problems defined by the smoothing approximation of nonsmooth equations. Based on the structure of the nonmonotone VI, we use an adaptive quasi-Newton formula to approximate the Hessian matrix and solve a low-dimensional strongly convex quadratic program with ellipse constraints in a subspace at each step of the QNSTR algorithm efficiently. We prove the global convergence of the QNSTR algorithm to an ϵ -first-order stationary point of the min-max optimization problem. Moreover, we present numerical results based on the QNSTR algorithm with different subspaces for a mixed generative adversarial networks in eye image segmentation using real data to show the efficiency and effectiveness of the QNSTR algorithm for solving large-scale min-max optimization problems. [ABSTRACT FROM AUTHOR]

Stochastic approximation (SA) type methods have been well studied for solving single-stage stochastic variational inequalities (SVIs). This paper proposes a dynamic stochastic projection method (DSPM) for solving multistage SVIs. In particular, we investigate an inexact single-stage SVI and present an inexact stochastic projection method (ISPM) for solving it. Then we give the DSPM to a three-stage SVI by applying the ISPM to each stage. We show that the DSPM can achieve an O (1 ϵ 2) convergence rate regarding to the total number of required scenarios for the three-stage SVI. We also extend the DSPM to the multistage SVI when the number of stages is larger than three. The numerical experiments illustrate the effectiveness and efficiency of the DSPM. [ABSTRACT FROM AUTHOR]

In this paper, we use the distributionally robust approach to study stochastic variational inequalities under the ambiguity of the true probability distribution, which is referred to as distributionally robust variational inequalities (DRVIs). First of all, we adopt a relaxed value function approach to relax the DRVI and obtain its relaxation counterpart. This is mainly motivated by the robust requirement in the modeling process as well as the possible calculation error in the numerical process. After that, we investigate qualitative convergence properties as the relaxation parameter tends to zero. Considering the perturbation of ambiguity sets, we further study the quantitative stability of the relaxation DRVI. Finally, when the ambiguity set is given by the general moment information, the discrete approximation of the relaxation DRVI is discussed. [ABSTRACT FROM AUTHOR]

Refinement of the governing equations for homogeneous isotropy in variable saturated porous media based on the basic equations for the seepage and temperature fields. Combined with the water exchange in the lateral hyporheic zone, a mathematical model of water and heat transport in the saturated-unsaturated zone of the lateral hyporheic zone of river-groundwater is established. The model was solved using COMSOL software and then validated by the measured data obtained from the test site. The simulation and validation results show that the model is effective in simulating the dynamics of hydrodynamic and temperature field changes in the river-groundwater lateral hyporheic zone under the conditions of water exchange, and that the mathematical model of hydrothermal transport can provide technical support for the in-depth study of hydrothermal exchange and pollutant migration processes in the riparian zone. [ABSTRACT FROM AUTHOR]

Objectives: No head-to-head trials had been performed to estimate the relative effectiveness of poly ADP-ribose polymerase inhibitor (PARPi) and androgen receptor signaling inhibitor (ARSi) in the first-line treatment for metastatic castration-resistant prostate cancer (mCRPC). We aimed to perform a systematic review and network meta-analysis to evaluate the comparative effectiveness of various systemic treatment agents for patients with mCRPC. Methods: A comprehensive literature search was conducted for abstracts and full-text articles from the database's inception through April 27, 2023. The study concentrated on assessing radiographic progression-free survival (rPFS) for both overall and homologous recombination repair mutation (HRRm) population, with overall survival (OS) as the secondary measure. Under the Bayesian framework, the overall effect was pooled using the fixed-effects model in base case analysis. Scenario analysis using restricted mean survival time (RMST) methods was performed to test the robustness of the results. Results: Nine studies with 6,830 patients and 8 unique treatment options were included. Network meta-analysis demonstrated that talazoparib in combination with enzalutamide (TALA + ENZA; overall population, hazard ratio [HR], 0.20; 95% credible interval [CrI]: 0.16–0.26; RMST, 3.51; 95% confidence interval [CI] 2.46–4.60; HRRm population, HR, 0.15; 95% CrI: 0.09–0.23; RMST, 4.14; 95% CI 2.84–5.39) was superior to other treatments in the first-line setting in terms of rPFS. The results of Bayesian framework and RMST models showed consistent efficacy ranks. When extrapolated to overall survival benefit, within the Bayesian framework, olaparib plus abiraterone acetate and prednisone (OLAP + AAP) achieved the highest OS benefit for the overall population, which was not statistically significant when compared to TALA + ENZA. However, TALA + ENZA achieved the highest OS benefit at 3 years by applying RMST. Conclusions: We suggest that talazoparib in combination with enzalutamide is probably a preferred treatment agent for the overall population and HRRm patients with mCRPC. Given the limitations of network framework and the modeling assumptions undertaken to finalize the analyses, results should be cautiously interpreted. [ABSTRACT FROM AUTHOR]

Ferroptosis is a promising strategy for cancer therapy, with numerous inhibitors of its braking axes under investigation as potential drugs. However, few studies have explored the potential of activating the driving axes to induce ferroptosis. Herein, phosphatidylcholine peroxide decorating liposomes (LIPPCPO) are synthesized to induce ferroptosis by targeting divalent metal transporter 1 (DMT1). LIPPCPO is found to boost lysosomal Fe2+ efflux by inducing cysteinylation of lysosomal DMT1, resulting in glutathione peroxidase 4 (GPX4) suppression, glutathione depletion and ferroptosis in breast cancer cells and xenografts. Importantly, LIPPCPO induced ferroptotic cell death is independent of acquired resistance to radiation, chemotherapy, or targeted agents in 11 cancer cell lines. Furthermore, a strong synergistic ferroptosis effect is observed between LIPPCPO and an FDA-approved drug, artesunate, as well as X rays. The formula of LIPPCPO encapsulating artesunate significantly inhibits tumor growth and metastasis and improves the survival rate of breast cancer-bearing female mice. These findings provide a distinct strategy for inducing ferroptosis and highlight the potential of LIPPCPO as a vector to synergize the therapeutic effects of conventional ferroptosis inducers. Inducers of ferroptosis hold potential for cancer therapy. Here, the authors identify a peroxide-decorated liposome capable of inducing ferroptosis and enhancing the efficacy of chemotherapeutic agents and radiotherapy. [ABSTRACT FROM AUTHOR]

This study sought to elucidate the mechanisms underlying the impact of the interferon signaling pathway on Ferroptosis in tumor cells and its correlation with CD8 + T cell exhaustion. Using mouse models and single-cell sequencing, the researchers studied the interaction between CD8 + T cells and the interferon signaling pathway. Differential gene analysis revealed key genes involved in CD8 + T cell exhaustion, and their downstream factors were explored using bioinformatics tools. The expression levels of interferon-related genes associated with Ferroptosis were analyzed using data from the TCGA database, and their relevance to tumor tissue Ferroptosis and patients' prognosis was determined. In vitro experiments were conducted to measure the levels of IFN-γ, MDA, and LPO, as well as tumor cell viability and apoptosis. In vivo validation using a mouse tumor model confirmed the results obtained from the in vitro experiments, highlighting the potential of silencing HSPA6 or DNAJB1 in enhancing the efficacy of PD-1 therapy and inhibiting tumor growth and migration. [ABSTRACT FROM AUTHOR]

Purpose: This research aimed to clarify the metastatic patterns of subcarinal, right and left recurrent laryngeal nerve lymph nodes in thoracic esophageal squamous cell carcinoma and to investigate appropriate strategies for lymph node dissection. Methods: Patients with thoracic esophageal squamous cell carcinoma receiving esophagectomy from December 2020 to April 2024 were retrospectively analyzed. Risk factors for subcarinal, right and left recurrent laryngeal nerve lymph nodes metastasis were determined by chi-square test and multivariate logistic regression analysis. We visualized the metastasis rates of these specific lymph nodes based on the different clinicopathological characteristics. Correlation between subcarinal, right and left recurrent laryngeal lymph nodes metastasis and postoperative complications were also analyzed. Results: A total of 503 thoracic esophageal squamous carcinoma patients who underwent esophagectomy were enrolled. The metastasis rates of subcarinal, right and left recurrent laryngeal nerve lymph nodes were 10.3%, 10.3%, and 10.9%, respectively. The lymphovascular invasion status and tumor location were the significant predictors for subcarinal and right recurrent laryngeal nerve lymph nodes metastasis, respectively (P < 0.001 and P = 0.013). For left recurrent laryngeal nerve lymph node metastasis, younger age (P = 0.020) and presence of lymphovascular invasion (P = 0.009) were significant risk factors. Additionally, pulmonary infection is the most frequent postoperative complication in patients with dissection of subcarinal, right and left recurrent laryngeal lymph nodes. There was no significant difference in the incidence of anastomotic leakage (P = 0.872), pulmonary infection (P = 0.139), chylothorax (P = 0.702), and hoarseness (P = 0.179) between the subcarinal lymph node dissection cohort and the reservation cohort. The incidence of hoarseness significantly increased in both right (P = 0.042) and left (P = 0.010) recurrent laryngeal nerve lymph nodes dissection cohorts compared by the reservation cohorts, with incidence rates of 5.9% and 6.7%, respectively. Conclusions: The metastasis rates of subcarinal, right and left recurrent laryngeal nerve lymph nodes in thoracic esophageal squamous cell carcinoma were all over 10%. The dissection of subcarinal lymph nodes does not increase postoperative complications risk, while recurrent laryngeal nerve lymph nodes dissection significantly increases the incidence of hoarseness. Thus, lymph node dissection of subcarinal lymph nodes should be conducted routinely, while recurrent laryngeal nerve lymph nodes dissection may be selectively performed in specific patients. [ABSTRACT FROM AUTHOR]

With the global proliferation of 5G technology, advancing electronic interconnection technologies has become critically important. The development of high-quality electrolytic copper foils, essential for efficient signal transmission, has garnered considerable attention. To mitigate the "skin effect" that could impair signal transmission and to ensure robust adhesion of electrolytic copper foils to the substrate, it's necessary to roughen the copper foils. This roughening process aims to substantially enhance the peel strength of the copper foils without exceeding the bounds of acceptable roughness. An effective strategy to achieve this involves the use of additives to refine the micro-coarsened surface of the copper foils. In this context, we have explored the impact of additives such as carrageenan, guar gum, and SPS on the surface morphology, roughness, and peel strength of electrolytic copper foils. Three types of additives can improve the performance of micro-roughened copper foil. Through electrochemical tests, it was found that all three types of additives have the effect of increasing cathodic polarization. The adsorption behavior of different additives was studied through theoretical calculations. By hybriding the three additives, two micro-coarsening systems were screened to obtain the lowest roughness and the highest peel strength, respectively. At the same time, the relationship between peel strength and surface area was verified, with the larger surface area resulting in greater peel strength. Finally, the synergistic effect of the three additives on increasing cathodic polarization was verified through chronopotentiometry. [ABSTRACT FROM AUTHOR]

Brain tumors are highly lethal, representing 85–90% of all primary central nervous system (CNS) tumors. Magnetic resonance imaging (MRI) images are employed to identify and assess brain tumors. However, this process has historically relied heavily on the expertise of medical professionals and necessitated the involvement of a substantial number of personnel. To optimize the allocation of medical resources and improve diagnostic efficiency, this work proposes a DETR-based RPC–DETR model that utilizes the Transformer. We conducted comparative experiments using RPC–DETR with other traditional detectors on the same equipment to test the performance exhibited by the model with equal computational resources. Tested on the Br35H brain tumor dataset with 701 MRI images (500 training sets and 201 test sets), RPC–DETR surpasses the YOLO models in accuracy while utilizing fewer parameters. This advancement ensures more reliable and faster diagnosis. RPC–DETR achieves a 96% mAP with just 14M parameters, offering high accuracy in brain tumor detection with a lighter model, making it easier to implement in various medical settings. [ABSTRACT FROM AUTHOR]

Synapse organizers are essential for the development, transmission, and plasticity of synapses. Acting as rare synapse suppressors, the MAM domain containing glycosylphosphatidylinositol anchor (MDGA) proteins contributes to synapse organization by inhibiting the formation of the synaptogenic neuroligin-neurexin complex. A previous analysis of MDGA2 mice lacking a single copy of Mdga2 revealed upregulated glutamatergic synapses and behaviors consistent with autism. However, MDGA2 is expressed in diverse cell types and is localized to both excitatory and inhibitory synapses. Differentiating the network versus cell-specific effects of MDGA2 loss-of-function requires a cell-type and brain region-selective strategy. To address this, we generated mice harboring a conditional knockout of Mdga2 restricted to CA1 pyramidal neurons. Here we report that MDGA2 suppresses the density and function of excitatory synapses selectively on pyramidal neurons in the mature hippocampus. Conditional deletion of Mdga2 in CA1 pyramidal neurons of adult mice upregulated miniature and spontaneous excitatory postsynaptic potentials, vesicular glutamate transporter 1 intensity, and neuronal excitability. These effects were limited to glutamatergic synapses as no changes were detected in miniature and spontaneous inhibitory postsynaptic potential properties or vesicular GABA transporter intensity. Functionally, evoked basal synaptic transmission and AMPAR receptor currents were enhanced at glutamatergic inputs. At a behavioral level, memory appeared to be compromised in Mdga2 cKO mice as both novel object recognition and contextual fear conditioning performance were impaired, consistent with deficits in long-term potentiation in the CA3-CA1 pathway. Social affiliation, a behavioral analog of social deficits in autism, was similarly compromised. These results demonstrate that MDGA2 confines the properties of excitatory synapses to CA1 neurons in mature hippocampal circuits, thereby optimizing this network for plasticity, cognition, and social behaviors. [ABSTRACT FROM AUTHOR]

Inspired by nature, various biomimetic materials have been synthesized for enhanced mechanical properties, among which composites with brick-and-mortar structures attract the most attention. In such bio-inspired composites, the matrix layer mainly functions to transfer load between bricks through shearing, while the shear stress in the matrix is not uniform but highly concentrated on the interface ends, which tends to initiate cracks and evoke interface delamination in composites. To enhance the composites’ resistance to interface delamination, we propose to homogenize the shear stress by adopting a matrix with a gradient modulus. A theoretical solution to the optimal gradient modulus of the matrix layer is obtained, followed by computational validations. Moreover, composites with such functionally graded matrices are further demonstrated to possess higher elastic limits, higher resilience, and flaw tolerance than the uniform controls. The results of this paper should be of great value to the design and synthesis of advanced structural materials for superior mechanical performance. [ABSTRACT FROM AUTHOR]

As a biological material, cellulose with a low carbon footprint is better for preparing emulsions than traditional surfactant emulsions. However, the high hydrophilicity of nanocellulose is not conducive to its adsorption at the oil–water interface, resulting in a low emulsification capacity of Pickering emulsion. This work applied 2,2,6,6-tetramethy1-1-piperidyloxy(TEMPO)-mediated oxidation and sodium periodate oxidation to prepare nanocellulose with carboxyl and aldehyde groups, and studied the effects of bonding forms on the hydrophilicity of bovine serum albumin (BSA)/nanocellulose composites. Compared with pure components, the composite products prepared by adsorbing or grafting had improved effects in the emulsification by increasing viscosity and reducing surface wettability. With adsorbed BSA, the composite showed a higher hydrophobicity, and the corresponding Pickering emulsion had an extended oil fraction of 60%. Due to the strong chemical bonding, the grafted composite can stabilize the Pickering emulsion of a 70% oil fraction with stable droplets of uniform size. This study provides an idea for improving the emulsification performance of nanocellulose through protein bonding. [ABSTRACT FROM AUTHOR]

We explore the generalized covariant entropy bound in the theory where Einstein gravity is perturbed by quadratic curvature terms, which can be viewed as the first-order quantum correction to Einstein gravity. By replacing the Bekenstein-Hawking entropy with the holographic entanglement entropy of this theory and introducing two reasonable physical assumptions, we demonstrate that the corresponding Generalized Covariant Entropy Bound is satisfied under a first-order approximation of the perturbation from the quadratic curvature terms. Our findings suggest that the entropy bound and the Generalized Second Law of black holes are satisfied in the Einstein gravity under the first-order perturbation from the quadratic curvature corrections, and they also imply that the generalized covariant entropy bound may still hold even after considering the quantum correction of gravity, but in this case, we may need to use holographic entanglement entropy as the formula for gravitational entropy. [ABSTRACT FROM AUTHOR]

Takeaway food has become a prominent component of the diet in urban areas of China, especially for young people. Although dietary intake is a major pathway to contaminants for human exposure, studies on emerging organophosphite antioxidants (OPAs) and organophosphate esters (OPEs) in food are scarce. Here, we investigated four OPAs and 19 OPEs in takeaway foods (n = 99) and paired takeaway food packaging (n = 50) in China. AO168=O (mean: 14.9 ng/g ww), TPPO (mean: 1.05 ng/g ww), and TCIPP (mean: 0.579 ng/g ww) were dominant in the takeaway food. Some OPEs had significant correlations in takeaway food. Emerging OPAs and OPEs in takeaway food varied significantly depending on the packaging materials and food types. AO168 and AO168=O were widespread in the paired takeaway food packaging. The migration efficiencies of emerging OPAs and OPEs were low in takeaway food packaged in aluminum foil. Although the actual contamination of emerging OPAs and OPEs in takeaway food significantly differed from those of in food simulants migrated from paired takeaway food packaging, the results imply that food itself and takeaway food packaging are potential contamination sources of emerging OPAs and OPEs in takeaway food. The average estimated dietary intakes of emerging OPAs and OPEs were 465 ng/kg body weight (bw)/day and 91.9 ng/kg bw/day, respectively. The exposure risk of emerging OPAs and OPEs through takeaway food intake is low in China. [ABSTRACT FROM AUTHOR]

In this paper, the discrete approximation of two-stage stochastic variational inequalities has been investigated when the second stage problem has multiple solutions. First, a discrete approximation scheme is given by a series of models with the aid of merit functions. After that, the convergence relationships between these models are analysed, which therefore yields the convergence guarantee of the proposed discrete approximation scheme. Finally, we use the well-known progressive hedging algorithm to report some numerical results and to validate the effectiveness of the discrete approximation approach. [ABSTRACT FROM AUTHOR]

The discrete element method (DEM) is used widely to study the crushing behaviour of granular materials from a microscale perspective. However, a crushing criterion that can be suitable for triggering particle crushing for different coordination numbers (CNs) is still lacking. To develop a crushing criterion, particle crushing tests are conducted for different CNs via the DEM. Crushable spherical agglomerates are made by bonding smaller sub-spheres. Based on the results of simulations, a new crushing criterion invariant to the coordination number effect is proposed. The crushing criterion is simply expressed in terms of the three principal stresses of the particles. Furthermore, the applicability of the criterion is verified under various conditions, such as different numbers of sub-sphere, shapes of particles, microscale parameters and loading patterns. By using the new criterion, the particle strengths obtained from the single particle crushing tests can be used as the crushing strengths for the particles under multiple contact loading conditions in DEM simulations. [ABSTRACT FROM AUTHOR]

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Development of effective non-noble metals catalysts in removing oxygen from propylene remains a substantial challenge. Herein, the designed catalyst of 0.5%Na–Fe/Al2O3 exhibited up to 100% O2 conversion and inhibited the greenhouse gas CO2 formation under hydrogen existence. Multiple characterization results confirmed that Na promoter enhances the dispersion of Fe species and the formation of oxygen vacancies, contributing to enriching the reactivity of the O2. Significantly, the TPD results further demonstrated that the Na promoter facilitates the desorption of C3H6, decreasing the reaction probability of O2 and C3H6, which plays an important role in suppressing the formation of CO2. This finding not only provides a novel approach to understand the role of Na promoter, but also opens an avenue for providing scientific guidance to design and synthesis of high-efficiency catalysts. The effective Na-promoted iron-based catalysts achieved 100% O2 conversion with almost no formation of by-product CO2. Several characterization results confirmed that the presence of Na promoter affected the electronic state of Fe atoms, promoted the formation of oxygen vacancies and improved the O2 reactivity. Significantly, the Na promoter plays an important role in the adsorption of H2 and desorption of C3H6, facilitating to improve the O2 reactivity and inhibit the formation of the by-product CO2. [ABSTRACT FROM AUTHOR]

The principal aim of this investigation is to identify pivotal biomarkers linked to the prognosis of osteosarcoma (OS) through the application of artificial intelligence (AI), with an ultimate goal to enhance prognostic prediction. Expression profiles from 88 OS cases and 396 normal samples were procured from accessible public databases. Prognostic models were established using univariate COX regression analysis and an array of AI methodologies including the XGB method, RF method, GLM method, SVM method, and LASSO regression analysis. Multivariate COX regression analysis was also employed. Immune cell variations in OS were examined using the CIBERSORT software, and a differential analysis was conducted. Routine blood data from 20,679 normal samples and 437 OS cases were analyzed to validate lymphocyte disparity. Histological assessments of the study's postulates were performed through immunohistochemistry and hematoxylin and eosin (HE) staining. AI facilitated the identification of differentially expressed genes, which were utilized to construct a prognostic model. This model discerned that the survival rate in the high-risk category was significantly inferior compared to the low-risk cohort (p < 0.05). SERPINE2 was found to be positively associated with memory B cells, while CPT1B correlated positively with CD8 T cells. Immunohistochemical assessments indicated that SERPINE2 was more prominently expressed in OS tissues relative to adjacent non-tumorous tissues. Conversely, CPT1B expression was elevated in the adjacent non-tumorous tissues compared to OS tissues. Lymphocyte counts from routine blood evaluations exhibited marked differences between normal and OS groups (p < 0.001). The study highlights SERPINE2 and CPT1B as crucial biomarkers for OS prognosis and suggests that dysregulation of lymphocytes plays a significant role in OS pathogenesis. Both SERPINE2 and CPT1B have potential utility as prognostic biomarkers for OS. [ABSTRACT FROM AUTHOR]

The breathtaking economic development put a heavy toll on ecology, especially on water pollution. Efficient water resource management has a long-term influence on the sustainable development of the economy and society. Economic development and ecology preservation are tangled together, and the growth of one is not possible without the other. Deep learning (DL) is ubiquitous in autonomous driving, medical imaging, speech recognition, etc. The spectacular success of deep learning comes from its power of richer representation of data. In view of the bright prospects of DL, this review comprehensively focuses on the development of DL applications in water resources management, water environment protection, and water ecology. First, the concept and modeling steps of DL are briefly introduced, including data preparation, algorithm selection, and model evaluation. Finally, the advantages and disadvantages of commonly used algorithms are analyzed according to their structures and mechanisms, and recommendations on the selection of DL algorithms for different studies, as well as prospects for the application and development of DL in water science are proposed. This review provides references for solving a wider range of water-related problems and brings further insights into the intelligent development of water science. [ABSTRACT FROM AUTHOR]

Plant endophytes produce a variety of secondary metabolites that have a wide range of biological effects. Curcuma wenyujin Y.H. Chen et C. Ling is a medicinal plant of the genus Curcuma in Zingiberaceae possessing anti-tumor effects. However, Bacillus siamensis isolated from C. wenyujin highly remains limited understanding. In this study, a novel B. siamensis named as WYJ-E14 strain from C. wenyujin was isolated. The CCK8 assay showed that the metabolites produced by WYJ-E14 strain significantly inhibited the growth of melanoma and glioma cells. Metabolomic analysis showed that the eight metabolites of the WYJ-E14 metabolites had anti-tumor cell growth activity, including desferrioxamine G1, surfactin, menaquinone-4, tracheloside, proscillaridin, microcolin J, stevioside, and demethoxycurcumin. Genomic sequencing displayed that the whole genome of WYJ-E14 contained a circular chromosome with a total length of 4,020,075 bp, and had no plasmid. Genome annotation identified 4008 putative protein-coding genes, 1 tRNA, and 27 rRNAs. The CDSs number assigned to the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Clusters of Orthologous Genes databases were 2145, 2764 and 3403, respectively. Biosynthetic gene clusters (BGCs) related to the synthesis of surfactin, difficidin, fengycin, bacillaene, macrolactin, butirosin A/butirosin B, bacillibactin and bacilysin were identified in the genome of WYJ-E14 by antiSMASH analysis. Most importantly, the genes involved in the biosynthesis of surfactin and menaquinone-4 metabolism were identified. In addition, WYJ-E14 genome also contained sequences that shared similarity with the genes encoding enzymes involved in the plant curcumin anabolism. The predicted ORFs encoded 120 secretory proteins. Comparative genome analysis showed that WYJ-E14 possessed collinear region among B. siamensis YB-1631 and B. velezensis W1. Taken together, this work offered a foundation for function study of target genes, and facilitated a genetic engineering of B. siamensis WYJ-E14 to improve agricultural and biomedical applications.Key Message: The metabolites produced by endophytic Bacillus siamensis WYJ-E14 significantly inhibited tumor cells, which might facilitate a genetic engineering of B. siamensis WYJ-E14 to improve agricultural and biomedical applications. [ABSTRACT FROM AUTHOR]

Acetaminophen (APAP) stands as the predominant contributor to drug-induced liver injury (DILI), and limited options are available. β-Arrestin1 (ARRB1) is involved in numerous liver diseases. However, the role of ARRB1 in APAP-induced liver injury remained uncertain. Wild-type (WT) and ARRB1 knockout (KO) mice were injected with APAP and sacrificed at the indicated times. The histological changes, inflammation, endoplasmic reticulum (ER) stress, and apoptosis were then evaluated. Hepatic cell lines AML-12 and primary hepatocytes were used for in vitro analyses. Systemic ARRB1-KO mice were susceptible to APAP-induced hepatotoxicity, as indicated by larger areas of centrilobular necrosis area and higher levels of ALT, AST, and inflammation level. Moreover, ARRB1-KO mice exhibited increased ER stress (indicated by phosphorylated α subunit of eukaryotic initiation factor 2 (p-eIF2α)-activating transcription factor 4 (ATF4)-CCAAT-enhancer-binding protein homologous protein (CHOP)) and apoptosis (indicated by cleaved caspase 3). Further rescue experiments demonstrated that the induction of apoptosis was partially mediated by ER stress. Overexpression of ARRB1 alleviated APAP-induced ER stress and apoptosis. Moreover, co-IP analysis revealed that ARRB1 directly bound to p-eIF2α and eIF2α. ARRB1 protected against APAP-induced hepatoxicity through targeting ER stress and apoptosis. ARRB1 is a prospective target for treating APAP-induced DILI. ARRB1 mitigates APAP-induced hepatotoxicity through regulating ER stress (p-eIF2α-ATF4-CHOP) and apoptosis (p-JNK and cleaved caspase 3) via binding to p-eIF-2α [ABSTRACT FROM AUTHOR]

Objective: To develop a multimodal deep-learning model for classifying Chinese medicine constitution, i.e., the balanced and unbalanced constitutions, based on inspection of tongue and face images, pulse waves from palpation, and health information from a total of 540 subjects. Methods: This study data consisted of tongue and face images, pulse waves obtained by palpation, and health information, including personal information, life habits, medical history, and current symptoms, from 540 subjects (202 males and 338 females). Convolutional neural networks, recurrent neural networks, and fully connected neural networks were used to extract deep features from the data. Feature fusion and decision fusion models were constructed for the multimodal data. Results: The optimal models for tongue and face images, pulse waves and health information were ResNet18, Gate Recurrent Unit, and entity embedding, respectively. Feature fusion was superior to decision fusion. The multimodal analysis revealed that multimodal data compensated for the loss of information from a single mode, resulting in improved classification performance. Conclusions: Multimodal data fusion can supplement single model information and improve classification performance. Our research underscores the effectiveness of multimodal deep learning technology to identify body constitution for modernizing and improving the intelligent application of Chinese medicine. [ABSTRACT FROM AUTHOR]

Air pollution is potentially leading to cancer mortality; however, there is little evidence for a link between nasopharyngeal carcinoma and air pollution. In particular, limited studies have examined the role of traffic and multiple chemical components on the prognosis of this carcinoma. Here, we hypothesized that fine particulate matter (PM2.5) and traffic-related compositions, i.e., black carbon and organic matter, and ozone (O3), might be associated with increased mortality. We collected individual-level data from a 10-year nasopharyngeal cohort in southern China. Time-varying Cox models were developed. Traffic proximity and road density were studied. Results show that The hazard ratios for each interquartile range elevation in O3, black carbon and organic matter were 1.14, 1.21, and 1.22, respectively, whereas hazards for PM2.5 were significant only at above 31.2 μ g / m 3 . Women and patients below 49 years were susceptible to PM2.5, while men and patients above 50 years were vulnerable to high levels of black carbon, organic matter, and O3. The mortality risks were 28–33% or 16–73% greater for those living near traffic or in high-road density areas. There were positive associations between multiple air pollutants and nasopharyngeal carcinoma mortality among various subgroups. [ABSTRACT FROM AUTHOR]

This paper studies the effects of angularity and coarse particle content on the shear behaviour of granular mixtures via the discrete element method. The contributions of different contact types to the shear strength are quantified, which can be used to classify the structure of granular mixtures. After that, a microscopic analysis of the effect of angularity on the thresholds of the granular mixtures is presented. Finally, a method that can predict the critical friction angle of granular mixtures at arbitrary coarse particle contents is proposed. The validity of the prediction method is verified by comparisons with the experimental and numerical data in other studies. [ABSTRACT FROM AUTHOR]

Among today's nonvolatile memories, ferroelectric-based capacitors, tunnel junctions and field-effect transistors (FET) are already industrially integrated and/or intensively investigated to improve their performances. Concurrently, because of the tremendous development of artificial intelligence and big-data issues, there is an urgent need to realize high-density crossbar arrays, a prerequisite for the future of memories and emerging computing algorithms. Here, a two-terminal ferroelectric fin diode (FFD) in which a ferroelectric capacitor and a fin-like semiconductor channel are combined to share both top and bottom electrodes is designed. Such a device not only shows both digital and analog memory functionalities but is also robust and universal as it works using two very different ferroelectric materials. When compared to all current nonvolatile memories, it cumulatively demonstrates an endurance up to 1010 cycles, an ON/OFF ratio of ~102, a feature size of 30 nm, an operating energy of ~20 fJ and an operation speed of 100 ns. Beyond these superior performances, the simple two-terminal structure and their self-rectifying ratio of ~ 104 permit to consider them as new electronic building blocks for designing passive crossbar arrays which are crucial for the future in-memory computing. Designing efficient high-density crossbar arrays are nowadays highly demanded for many artificial intelligence applications. Here, the authors propose a two-terminal ferroelectric fin diode non-volatile memory in which a ferroelectric capacitor and a fin-like semiconductor channel are combined to share both top and bottom electrodes with high performance and easy fabrication process [ABSTRACT FROM AUTHOR]

Objectives: To predict the probability of occult lymph node metastasis (OLNM) in the central cervical by analyzing the dual-energy computed tomography (DECT) parameters derived from papillary thyroid carcinoma (PTC). Methods: Data were retrospectively collected from patients with pathologically confirmed PTC who underwent arterial and venous phases of enhanced DECT with concurrent central neck lymph node dissection (CLND). Three clinical features, three shape-related features, and twenty-six DECT-derived parameters were measured. The univariate and multivariate analyses were applied to select the relevant parameters and develop the nomogram. Results: A total 140 cases with negative diagnosis of cervical central lymph node metastases by preoperative evaluation were included, among which 88 patients with metastasis (OLNM +) and 52 patients without metastasis (OLNM −) were finally confirmed by pathology. (1) Anteroposterior/transverse diameter ratio (A/T) derived from the PTC focus had significant difference between the OLNM + and OLNM − groups (p < 0.05). (2) In the arterial phase, iodine concentration (ICarterial), normalized iodine concentration (NICarterial), effective atomic number (Zeff-arterial), electron density (EDarterial), and slope of energy curve (karterial) from PTC focus showed significant difference (all p < 0.05) between the two groups. In the venous phase, only the CT value under the 40 keV (HU40keVvenous) had differences (p < 0.05). (3) The nomogram was produced to predict the probability of OLNM, and the AUC, sensitivity, and specificity in the training and test cohort were 0.830, 75.0%, 76.9%, and 0.829, 65.9%, 84.6%, respectively. Conclusions: DECT parameters combined with shape-related feature derived from PTC might be used as predictors of OLNM in the central neck. Clinical relevance statement: Preoperative imaging evaluation combining shape-related features and dual-energy CT parameters could serve as a reference to discern occult lymph node metastasis in central neck during the surgically planning of papillary thyroid carcinoma. Key Points: • Papillary thyroid carcinoma (PTC) patients may have occult lymph node metastasis (OLNM) in the central neck, which is extremely difficult to find by preoperative imaging examination. • Dual-energy CT quantitative evaluation has higher accuracy than conventional CT and can predicting OLNM in the central neck of PTC. • Dual-energy CT quantitative parameters and morphology of PTC can serve as a useful tool in predicting OLNM in the central neck, and as a guide for personalized treatment. [ABSTRACT FROM AUTHOR]

Purpose: Pulmonary sarcoidosis (PS) and pulmonary lymphangitic carcinomatosis (PLC) can be complications in tumor patients, and both involve the pulmonary interstitium and have similar imaging findings. Our objective was to distinguish PS and PLC on 18F-FDG PET/CT images. Material and methods: The authors reviewed 18F-FDG PET/CT data of PS and PLC, diagnosed based on histopathology and imaging, in patients with tumors from July 2015 to January 2023. Three independent readers performed a blinded comparative analysis of 18F-FDG PET/CT signs in all patients. A multivariate logistic regression model was used to establish a differential diagnosis model. Results: A total of 114 patients were included in the study: 56 patients with PS (mean age, 56 ± 11 [SD] years; 10 men) and 58 patients with PLC caused by extrapulmonary tumors (mean age, 51 ± 11 [SD] years; 21 men). For PS, breast cancer and cervical cancer were the most common primary tumors. For PLC, breast cancer and gastric cancer were the most common extrapulmonary tumors. The model constructed using multivariate logistic regression consisted of five factors: area of lymph node involvement, bronchovascular bundle diffuse thickening, interlobular septal thickening, pleural effusion, and subpleural hypermetabolic activity. The area under the model characteristic curve was 0.973 (95% CI 0.925–0.994), with a sensitivity, specificity, and positive and negative likelihood ratios of 87.50%, 98.28%, 50.75 and 0.13 respectively. Conclusion: There are detailed differences in 18F-FDG PET/CT manifestations of PS in tumor patients and PLC caused by extrapulmonary tumors, and the constructed diagnostic model has high clinical application value in differentiating the two. [ABSTRACT FROM AUTHOR]

We investigate whether the Strong Cosmic Censorship (SCC) Conjecture can be reinstated at the classical level in Reissner–Nordström–de Sitter (RNdS) black holes by introducing non-minimal couplings between the electromagnetic and scalar fields in Einstein–Maxwell-scalar (EMS) theory. By conducting numerical calculations, we find that the SCC can be restored within a specific range of the coupling constant. Notably, for a given value of the cosmological constant, there exists a critical coupling constant above which the EMS theory satisfies the SCC. These findings suggest that the non-minimal couplings between the electromagnetic and scalar fields may play a crucial role in the restoration of the SCC in RNdS spacetime. Additionally, under negative coupling constants, the low-lying modes of nearly extremal black holes exhibit β > 1 , enabling C 2 extensions beyond the Cauchy horizon and intensifying the violation of the SCC. [ABSTRACT FROM AUTHOR]

Tunnel collapse is a serious hazard that poses a substantial threat to worker safety and construction expenses. The results of risk evaluations can provide valuable information for collapse prevention and risk management. For this purpose, an improved unascertained measure function for collapse risk evaluation was proposed. Firstly, a risk evaluation index system was established using major indexes, including geological conditions, design and construction factors. Secondly, a combination method of the analytic hierarchy process (AHP) and the anti-entropy weight (AEW) based on the maximum deviation (MD) concept was proposed. The subjective and objective weights were linearly optimized to assign the index weights. Finally, the conventional linear unascertained measure function was improved by normalizing. By combining the weights, the values of the evaluation indexes were regarded as intervals for calculating the measure values. Confidence recognition analysis was used to determine the collapse risk level. Jinzhupa Tunnel was evaluated to have a high collapse risk and experienced a small-scale collapse during excavation, verifying the feasibility of the improved unascertained measure model. This method considers the uncertainty of the evaluation index and can effectively predict the risk level of tunnel collapse. [ABSTRACT FROM AUTHOR]

Background: Diabetes mellitus is a known risk factor for Parkinson's disease (PD), but does this risk vary with antidiabetic medications is still unclear. This meta-analysis aims to compile evidence from the literature to assess the risk of idiopathic PD with various oral antidiabetic medications. Methods: Databases PubMed, CENTRAL, Scopus, Web of Science, and Embase were searched till 5th April 2023. Adjusted outcomes were pooled to generate a hazard ratio (HR) on the risk of PD with different antidiabetic medications. Results: Fifteen studies with 2,910,405 diabetic patients were eligible. Pooled analysis failed to show any significant difference in the risk of PD among users of metformin (HR: 1.05 95% CI: 0.91, 1.22 I2 = 81%), glitazones (HR: 0.84 95% CI: 0.68, 1.05 I2 = 91%), glucagon-like peptide-1 agonists (HR: 0.63 95% CI: 0.26, 1.55 I2 = 33%), and sulfonylureas (HR: 1.13 95% CI: 0.96, 1.32 I2 = 76%). However, a meta-analysis of four studies showed that dipeptidyl peptidase-4 inhibitor use was associated with reduced risk of PD in diabetics (HR: 0.69 95% CI: 0.56, 0.86 I2 = 46%). Insufficient data was available on sodium-glucose cotransporter-2 inhibitors, α-glucosidase inhibitors, and glinides. Conclusions: Limited retrospective evidence indicates that DPP4i may reduce the risk of idiopathic PD in diabetics. Metformin, sulfonylureas, glucagon-like peptide-1 agonists, and glitazones were not associated with any change in the risk of PD. Further studies taking into confounding factors and using a common comparator group are needed to strengthen present evidence. [ABSTRACT FROM AUTHOR]

Deep convolution neural networks (DCNNs) in deep learning have been widely used in semantic segmentation. However, the filters of most regular convolutions in DCNNs are spatially invariant to local transformations, which reduces localization accuracy and hinders the improvement of semantic segmentation. Dynamic convolution with pixel-level filters can enhance the localization accuracy through its region-awareness, but these are sensitive to objects with large-scale variations in semantic segmentation. To simultaneously address the low localization accuracy and objects with large-scale variations, we propose a filter-varying atrous convolution (FAC) to efficiently enlarge the per-pixel receptive fields pertaining to various objects. FAC mainly consists of a conditional-filter-generating network (CFGN) and a dynamic local filtering operation (DLFO). In the CFGN, a class probability map is used to generate the corresponding filters, making the FAC genuinely dynamic. In the DLFO, by replacing the sliding convolution operation one by one with a one-time dot product operation, the efficiency of the algorithm is greatly improved. Also, a dense scale module (DSM) is constructed to generate denser scales and larger receptive fields for exploring long-range contextual information. Finally, a dense-scale dynamic network (DsDNet) simultaneously enhances the localization accuracy and reduces the effect of large-scale variations of the object, by assigning FAC to different spatial locations at dense scales. In addition, to accelerate network convergence and improve segmentation accuracy, our network employs two pixel-wise cross-entropy loss functions. One is between the Backbone and DSM, and the other is at the network's end. Extensive experiments on Cityscapes, PASCAL VOC 2012, and ADE20K datasets verify that the performance of our DsDNet is superior to the non-dynamic and multi-scale convolution neural networks. [ABSTRACT FROM AUTHOR]

Background: Different from other malignant gynecologic tumors, gestational trophoblastic neoplasms (GTNs) exhibit an exceptionally high cure rate primarily through chemotherapeutic interventions. However, there exists a small subset of refractory GTNs that do not respond to conventional chemotherapies. In such cases, the emergence of immunotherapies has demonstrated significant benefits in managing various challenging GTNs. Purpose: This article aims to provide a comprehensive and systematic review of the immune microenvironment and immunotherapeutic approaches for GTNs. The purpose is to identify potential biomarkers that could enhance disease management and summarize the available immunotherapies for ease of reference. Methods: We reviewed the relevant literatures toward immunotherapies of GTNs from PubMed. Conclusion: Current immunotherapeutic strategies for GTNs mainly revolve around immune checkpoint inhibitors (ICIs) targeting programmed death receptor 1 (PD-1) and programmed cell death ligand 1 (PD-L1). Prominent examples include avelumab, pembrolizumab, and camrelizumab. However, existing researches into the underlying mechanisms are still limited. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA) has experienced a spatial imbalance in water resources in recent decades, partly because of a dipolar pattern of precipitation changes known as South Drying–North Wetting1. These changes can be influenced by both human activities and internal climate variability2,3. Although climate projections indicate a future widespread wetting trend over HMA1,4, the timing and mechanism of the transition from a dipolar to a monopolar pattern remain unknown. Here we demonstrate that the observed dipolar precipitation change in HMA during summer is primarily driven by westerly- and monsoon-associated precipitation patterns. The weakening of the Asian westerly jet, caused by the uneven emission of anthropogenic aerosols, favoured a dipolar precipitation trend from 1951 to 2020. Moreover, the phase transition of the Interdecadal Pacific Oscillation induces an out-of-phase precipitation change between the core region of the South Asian monsoon and southeastern HMA. Under medium- or high-emission scenarios, corresponding to a global warming of 0.6–1.1 °C compared with the present, the dipolar pattern is projected to shift to a monopolar wetting trend in the 2040s. This shift in precipitation patterns is mainly attributed to the intensified jet stream resulting from reduced emissions of anthropogenic aerosols. These findings underscore the importance of considering the impact of aerosol emission reduction in future social planning by policymakers.Dipolar precipitation change in High Mountain Asia during summer is primarily driven by weakened westerly jet and decadal variations in the South Asian monsoon, and the dipolar pattern is projected to shift to a monopolar wetting trend in the 2040s. [ABSTRACT FROM AUTHOR]

In China, a traditional Chinese medicine formulation called astragalus membranaceus (AM) has been utilised for more than 20 years to treat tumors with extraordinary effectiveness. The fundamental mechanisms, nevertheless, are still not well understood. The aim of this study is identifying its possible therapeutic targets and to evaluate the effects of AM in combination with a PARP inhibitor (olaparib) in the treatment of BRCA wild-type ovarian cancer. Significant genes were collected from Therapeutic Target Database and Database of Gene-Disease Associations. The components of AM were analyzed using the Traditional Chinese Medicine System Pharmacology (TCMSP) database to screen the active ingredients of AM based on their oral bioavailability and drug similarity index. In order to find intersection targets, Venn diagrams and STRING website diagrams were employed. STRING was also used to create a protein-protein interaction network. In order to create the ingredient-target network, Cytoscape 3.8.0 was used. DAVID database was utilized to carry out enrichment and pathway analyses. The binding ability of the active compounds of AM to the core targets of AM-OC was verified with molecular docking using AutoDock software. Experimental validations, including cell scratch, cell transwell, cloning experiment, were conducted to verify the effects of AM on OC cells. A total of 14 active ingredients of AM and 28 AM-OC-related targets were screened by network pharmacology analysis. The ten most significant Gene Ontology (GO) biological function analyses, as well as the 20 foremost Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathways were selected. Moreover, molecular docking results showed that bioactive compound (quercetin) demonstrated a good binding ability with tumor protein p53 (TP53), MYC, vascular endothelial growth factor A (VEGFA), phosphatase and tensin homolog (PTEN), AKT serine/threonine kinase 1 (AKT1) and cyclin D1 (CCND1) oncogenes. According to experimental methods, in vitro OC cell proliferation and migration appeared to be inhibited by quercetin, which also increased apoptosis. In addition, the combination with olaparib further enhanced the effect of quercetin on OC. Based on network pharmacology, molecular docking, and experimental validation, the combination of PARP inhibitor and quercetin enhanced the anti-proliferative activity in BRCA wild-type ovarian cancer cells, which supplies the theoretical groundwork for additional pharmacological investigation. [ABSTRACT FROM AUTHOR]

Remote sensing has been used for assisting the precision nitrogen (N) management in wheat (Triticum aestivum) production. This study aimed to develop an efficient and energy saving N management strategy based on multi-source data for winter wheat at the farm scale. Five field experiments involving different cultivars and N treatments were conducted to establish and validate the N management strategy in 2017–2021. UAV multi-spectral images, plant sampling, weather and field management data collection were carried out synchronously at Feekes 6.0. Four machine learning methods were used to integrate multi-variate information to determine the optimal parameters in N regulation algorithm. The results showed random forest (RF) algorithm performed best for plant dry matter (R2 = 0.78) and plant N accumulation (R2 = 0.83) estimation, a N nutrition index optimized algorithm (NNIOA), driven by multi-source data, was developed and used for guiding in-season N application. The NNIOA efficiently regulated the deficient, optimal and excessive N status through up- (54.17%), fine- (0.67%) and downward- (18.18%) adjustment of N fertilizers, respectively, while the optimal N treatment achieved highest net profit, energy use efficiency (EUE) and energy productivity (EP). Compared with farmer's practices, the NNIOA increased partial factor productivity (PFP), net profit, EUE and EP by 19.60–27.94%, 22.47–45.13 $ ha−1, 6.94–13.07% and 8.36–12.29%, respectively, while reduced N input (16.77–21.67%), energy input (8.13–10.74%) and CO2 emission (7.60–10.11%) without any yield reduction at study farms. In conclusion, this study supplied a precision N management strategy to implement variable N application for sustainable wheat production at farm scale. [ABSTRACT FROM AUTHOR]

We investigate the collisional Penrose process of extended test particles near an extremal Kerr black hole using the pole-dipole-quadrupole approximation. We analyze the motion of the test particles and examine the dynamics and maximal efficiency of energy extraction in this process. Our results demonstrate that the maximal extracted energy in the collisional Penrose process is influenced by the spin s and quadrupolar parameter C of the test particles. Specifically, we observe that, at a fixed collisional position, the energy extraction efficiency decreases as the spin increases for either the pole-dipole or the pole-dipole-quadrupole approximation case. Furthermore, for a fixed spin, the energy extraction efficiency is higher in the pole-dipole-quadrupole approximation compared to the pole-dipole approximation. These findings provide insight into the role of the internal structures of the test particles in the collisional Penrose process. [ABSTRACT FROM AUTHOR]

JPEG images are widely used by individual users, data centers, cloud storages, and network file systems. The huge transmission and storage bandwidth of existing JPEG images is becoming a big challenge due to its low compression efficiency. Some methods such as Google’s Brunsli can further compress these JPEG images adequately and restore them back to JPEG format losslessly when needed, but its decoding speed is not fast enough especially for real-time mobile applications. To further reduce its decoding complexity, we proposed three optimizations based on Brunsli, which include using asymmetric numeral systems coding to replace the existing arithmetic coding, designing the joint encoding of multiple symbols and cache-friendly optimizing the data structures. Experimental results demonstrate that compared with Brunsli, the proposed method achieves average 1.86–2.25 times decoding faster on mobile platform with comparable compression efficiency which is really valuable for power sensitive real-time mobile applications. [ABSTRACT FROM AUTHOR]

In preclinical Alzheimer's disease, neuro-functional changes due to amyloid-β (Aβ) deposition are not synchronized in different brain lobes and subcortical nuclei. This study aimed to explore the correlation between brain Aβ burden, connectivity changes in an ultra-large structural scale, and cognitive function in mild cognitive impairment. Participants with mild cognitive impairment were recruited and underwent florbetapir (F18-AV45) PET, resting-state functional MRI, and multidomain neuropsychological tests. AV-45 standardized uptake value ratio (SUVR) and functional connectivity of all participants were calculated. Of the total 144 participants, 72 were put in the low Aβ burden group and 72 in the high Aβ burden group. In the low Aβ burden group, all connectivities between lobes and nuclei had no correlation with SUVR. In the high Aβ burden group, SUVR showed negative correlations with the Subcortical-Occipital connectivity (r=-0.36, P = 0.02) and Subcortical-Parietal connectivity (r=-0.26, P = 0.026). Meanwhile, in the high Aβ burden group, SUVR showed positive correlations with the Temporal-Prefrontal connectivity (r = 0.27, P = 0.023), Temporal-Occipital connectivity (r = 0.24, P = 0.038), and Temporal-Parietal connectivity (r = 0.32, P = 0.006). Subcortical to Occipital and Parietal connectivities had positive correlations with general cognition, language, memory, and executive function. Temporal to Prefrontal, Occipital, and Parietal connectivities had negative correlations with memory function, executive function, and visuospatial function, and a positive correlation with language function. In conclusion, Individuals with mild cognitive impairment with high Aβ burden have Aβ-related bidirectional functional connectivity changes between lobes and subcortical nuclei that are associated with cognitive decline in multiple domains. These connectivity changes reflect neurological impairment and failed compensation. [ABSTRACT FROM AUTHOR]

Dependency stochastic Boolean satisfiability (DSSAT), which generalizes stochastic Boolean satisfiability (SSAT) and dependency quantified Boolean formula (DQBF), is a new logical formalism that allows compact encoding of NEXPTIME decision problems under uncertainty. Despite potentially broad applications, a decision procedure for DSSAT remains lacking. In this work, we present the first sound and complete resolution calculus for DSSAT. The resolution system deduces the maximum satisfying probability of a DSSAT formula and provides a witnessing certificate. We also show that when the special case of SSAT formulas is considered, the DSSAT resolution calculus p-simulates a known SSAT resolution scheme. Our result may pave a theoretical foundation for further development and certification of DSSAT solvers. [ABSTRACT FROM AUTHOR]

The dynamic activity of stars such as the Sun influences (exo)planetary space environments through modulation of stellar radiation, plasma wind, particle and magnetic fluxes. Energetic solar-stellar phenomena such as flares and coronal mass ejections act as transient perturbations giving rise to hazardous space weather. Magnetic fields – the primary driver of solar-stellar activity – are created via a magnetohydrodynamic dynamo mechanism within stellar convection zones. The dynamo mechanism in our host star – the Sun – is manifest in the cyclic appearance of magnetized sunspots on the solar surface. While sunspots have been directly observed for over four centuries, and theories of the origin of solar-stellar magnetism have been explored for over half a century, the inability to converge on the exact mechanism(s) governing cycle to cycle fluctuations and inconsistent predictions for the strength of future sunspot cycles have been challenging for models of the solar cycles. This review discusses observational constraints on the solar magnetic cycle with a focus on those relevant for cycle forecasting, elucidates recent physical insights which aid in understanding solar cycle variability, and presents advances in solar cycle predictions achieved via data-driven, physics-based models. The most successful prediction approaches support the Babcock-Leighton solar dynamo mechanism as the primary driver of solar cycle variability and reinforce the flux transport paradigm as a useful tool for modelling solar-stellar magnetism. [ABSTRACT FROM AUTHOR]