Toxoplasma gondii Causes Adverse Pregnancy Outcomes by Damaging Uterine Tissue-Resident NK Cells That Secrete Growth-Promoting Factors.

Vertical transmission of the intracellular parasite, Toxoplasma gondii can lead to adverse pregnancy outcomes especially when infection occurs in early pregnancy. Decidual natural killer (dNK) cells accumulate at the maternal-fetal interface in large numbers during early pregnancy. Their nutritional roles during infection with T. gondii remain poorly defined. In the present study, we demonstrated that a functional deficiency of the uterine tissue-resident NK (trNK) cells, a subset of dNK cells, contributes to the adverse pregnancy outcomes induced by T. gondii in early pregnancy. Adverse pregnancy outcomes could be ameliorated by adoptive transfer of trNK cells. Moreover, fetal growth restriction could be improved after supplementation of growth-promoting factors. In addition to the widely recognized disturbance of the immune balance at the interface between the mother and the fetus, our study reveals a novel mechanism in T. gondii that contributes to the adverse pregnancy outcomes.

Data-Driven Safe Policy Optimization for Black-Box Dynamical Systems With Temporal Logic Specifications.

Learning-based policy optimization methods have shown great potential for building general-purpose control systems. However, existing methods still struggle to achieve complex task objectives while ensuring policy safety during learning and execution phases for black-box systems. To address these challenges, we develop data-driven safe policy optimization (D 2 SPO), a novel reinforcement learning (RL)-based policy improvement method that jointly learns a control barrier function (CBF) for system safety and a linear temporal logic (LTL) guided RL algorithm for complex task objectives. Unlike many existing works that assume known system dynamics, by carefully constructing the data sets and redesigning the loss functions of D 2 SPO, a provably safe CBF is learned for black-box dynamical systems, which continuously evolves for improved system safety as RL interacts with the environment. To deal with complex task objectives, we take advantage of the capability of LTL in representing the task progress and develop LTL-guided RL policy for efficient completion of various tasks with LTL objectives. Extensive numerical and experimental studies demonstrate that D 2 SPO outperforms most state-of-the-art (SOTA) baselines and can achieve over 95% safety rate and nearly 100% task completion rates. The experiment video is available at https://youtu.be/2RgaH-zcmkY.

An Overview of Systematic Reviews and Meta-Analyses of Clinical Studies of Acupuncture for Cancer Pain.

BACKGROUND: Systematic reviews (SRs) and meta-analyses (MAs) for the use of acupuncture for cancer pain have been increasing, but the evidence has not been systematically and comprehensively assessed. We aimed to perform an overview of the evidence quality of SRs/MAs of acupuncture for improving cancer pain. METHODS: 8 databases were systematically searched to identify SRs/MAs of acupuncture for improving cancer pain. The A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2), Risk of Bias in Systematic Reviews (ROBIS), Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and Grades of Recommendations, Assessment, Development, and Evaluation (GRADE), respectively, were applied by 2 independent reviewers to evaluate the methodological quality, risk of bias, reporting quality, and evidence quality. RESULTS: A total of 14 SRs/MAs were included in the present study. By AMSTAR-2, two reviews were rated as having high methodological quality, while 12 were given a critically low rating. All SRs/MAs in Phase 1, Domain 1, and Domain 4, according to ROBIS, were at low risk. Furthermore, 4 reviews in Domain 2, twelve reviews in Domain 3, and ten SRs/MAs in Phase 3, were rated as having low risk of bias. With reporting quality, some reporting flaws were identified in the topic of protocol and registration, additional analyses, and search strategy. According to GRADE, the level of evidence quality was "critically low" to "moderate," and risk of bias was the most common downgraded factor. CONCLUSION: Acupuncture may be beneficial in improving cancer pain. However, due to the identified limitations and inconsistent findings, we recommend further rigorous, and more standardized SRs/MAs to provide strong evidence for definitive conclusions.

Salvage of Supervision in Weakly Supervised Object Detection and Segmentation.

Weakly supervised vision tasks, including detection and segmentation, have attracted much attention in the vision community recently. However, the lack of detailed and precise annotations in the weakly supervised case leads to a large accuracy gap between weakly- and fully-supervised methods. In this article, we propose a new framework, Salvage of Supervision (SoS), with the key idea being to effectively harness every potentially useful supervisory signal in weakly supervised vision tasks. Starting with weakly supervised object detection (WSOD), we propose SoS-WSOD to shrink the technology gap between WSOD and FSOD, which utilizes the weak image-level labels, the pseudo-labels, and the power of semi-supervised object detection for WSOD. Moreover, SoS-WSOD removes restrictions in traditional WSOD methods, including the reliance on ImageNet pretraining and inability to use modern backbones. The SoS framework also extends to weakly supervised semantic segmentation and instance segmentation. On several weakly supervised vision benchmarks, SoS achieves significant performance boost and generalization ability.

Identification of the Hub Genes Involved in Stem Cell Treatment for Intervertebral Disc Degeneration: A Conjoint Analysis of Single-Cell and Machine Learning.

Intervertebral disc degeneration (IDD), which is distinguished by a variety of pathologic alterations, is the major cause of low back pain (LBP). Nonetheless, preventative measures or therapies that may delay IDD are scarcely available. In this study, we sought to identify new diagnostic biological markers for IDD. In this first-of-a-kind study combining machine learning, stem cell treatment samples and single-cell sequencing data were collected. Differentially expressed genes (DEGs) were detected from the treatment group and clusters. To filter potential markers, support vector machine analysis and LASSO were performed. LAPTM5 was found to be the hub gene for IDD. In addition, the results of single-cell sequencing demonstrated the critical function of stem cells in IDD. Finally, we found that aging is significantly associated with the rate of stem cells. In general, our results may offer fresh insights that may be used in the investigation of innovative markers for diagnosing IDD. The critical genes identified by the machine learning algorithm could provide new perspectives on IDD.

Functional data analysis with covariate-dependent mean and covariance structures.

Functional data analysis has emerged as a powerful tool in response to the ever-increasing resources and efforts devoted to collecting information about response curves or anything that varies over a continuum. However, limited progress has been made with regard to linking the covariance structures of response curves to external covariates, as most functional models assume a common covariance structure. We propose a new functional regression model with covariate-dependent mean and covariance structures. Particularly, by allowing variances of random scores to be covariate-dependent, we identify eigenfunctions for each individual from the set of eigenfunctions that govern the variation patterns across all individuals, resulting in high interpretability and prediction power. We further propose a new penalized quasi-likelihood procedure that combines regularization and B-spline smoothing for model selection and estimation and establish the convergence rate and asymptotic normality of the proposed estimators. The utility of the developed method is demonstrated via simulations, as well as an analysis of the Avon Longitudinal Study of Parents and Children concerning parental effects on the growth curves of their offspring, which yields biologically interesting results.

Fuzzy Logic System Assisted Sensing Resource Allocation for Optical Fiber Sensing and Communication Integrated Network.

With the development of information transmission, there is an increasing demand for state monitoring of fiber-optic communication networks to improve the security and self-healing ability of the network. Distributed optical fiber sensing is one of the most attractive methods because it can achieve real-time detection of the whole network without additional sensing heads. However, when the sensing network is introduced into the communication network, the failure probability should be efficiently suppressed with limited sensing resources. In this paper, the fuzzy logic system is used to evaluate the impact of different sensing resource allocation on optical cable network quality. The link failure probability and path failure probability under the condition of uniform and non-uniform sensing resource allocation are simulated and analyzed, respectively. As shown in the analysis results, the failure probability under non-uniform allocation is significantly lower than under uniform allocation. In this paper, we discussed and addressed the allocation of the optical fiber sensing and communication integrated (OFSCI) network with the limited sensing resource for the first time. The results are helpful to develop an allocation strategy for optical fiber sensing and a communication integrated network with a higher robustness.

Knowledge-Aware Multispace Embedding Learning for Personalized Recommendation.

Recommender systems help users filter items they may be interested in from massive multimedia content to alleviate information overload. Collaborative filtering-based models perform recommendation relying on users' historical interactions, which meets great difficulty in modeling users' interests with extremely sparse interactions. Fortunately, the rich semantics hidden in items may be promising in helping to describing users' interests. In this work, we explore the semantic correlations between items on modeling users' interests and propose knowledge-aware multispace embedding learning (KMEL) for personalized recommendation. KMEL attempts to model users' interests across semantic structures to leverage valuable knowledge. High-order semantic collaborative signals are extracted in multiple independent semantic spaces and aggregated to describe users' interests in each specific semantic. The semantic embeddings are adaptively integrated with a target-aware attention mechanism to learn cross-space multisemantic embeddings for users and items, which are fed to the subsequent pairwise interaction layer for personalized recommendation. Experiments on real-world datasets demonstrate the effectiveness of the proposed KMEL model.

A novel circRNA-miRNA-mRNA network reveals hsa-circ-0040039 as a biomarker for intervertebral disc degeneration.

OBJECTIVE: Alterations in the structure and function of intervertebral discs by multifaceted chronic processes can result in intervertebral disc degeneration (IDD). The mechanisms involved in IDD are still unknown. METHODS: We investigated the possible mechanisms underlying IDD using a bioinformatics analysis of publicly available microarray expression datasets and built a circular RNA-microRNA-mRNA (circRNA-miRNA-mRNA) network based on the results. Datasets GSE67566 and GSE116726 were downloaded from the Gene Expression Omnibus (GEO) and analyzed using the limma package in R. The CircInteractome database was used to detect miRNAs related to circRNA, and TargetScan, miRDB, and miRTarBase were used to predict target mRNAs. Key target genes were annotated using Gene Ontology terms. RESULTS: The circRNA hsa-circ-0040039 was found to have the top log fold-change score. Analysis using Metascape showed that the associated genes were enriched mainly in the cell cycle. The Cytoscape plugin MCODE predicted that two members of the RAS oncogene family-RAB1A and RAB1B-and multiple coagulation factor deficiency (MCFD2) may play key roles in IDD. CONCLUSION: Our results suggested that hsa-circ-0040039 and the related network may be potential biomarkers for IDD.

Metal- and halide-free, solid-state polymeric water vapor sorbents for efficient water-sorption-driven cooling and atmospheric water harvesting.

Metal- and halide-free, solid-state water vapor sorbents are highly desirable for water-sorption-based applications, because most of the solid sorbents suffer from low water sorption capacity caused by their rigid porosity, while the liquid sorbents are limited by their fluidity and strong corrosivity, which is caused by the halide ions. Herein, we report a novel type of highly efficient and benign polymeric sorbent, which contains no metal or halide, and has an expandable solid state when wet. A group of sorbents are synthesized by polymerizing and crosslinking the metal-free quaternary ammonium monomers followed by an ion-exchange process to replace chloride anions with benign-anions, including acetate, oxalate, and citrate. They show significantly reduced corrosivity and improved water sorption capacity. Importantly, the water sorption capacity of the acetate paired hydrogel is among the best of the literature reported hygroscopic polymers in their pure form, even though the hydrogel is crosslinked. The hydrogel-based sorbents are further used for water-sorption-driven cooling and atmospheric water harvesting applications, which show improved coefficient of performance (COP) and high freshwater production rate, respectively. The results of this work would inspire more research interest in developing better water sorbents and potentially broaden the application horizon of water-sorption-based processes towards the water-energy nexus.

Solar Seawater Distillation by Flexible and Fully Passive Multistage Membrane Distillation.

Solar-assisted distillation is considered promising to solve the freshwater supply for off-grid communities. In this work, a passive and flexible multistage membrane distillation (F-MSMD) device is devised to produce freshwater via solar distillation with the latent heat of vapor condensation being recycled to enhance its energy efficiency. By designing a siphon effect, source water is continuously wicked into the evaporation layer and the concentrated brine flows out of the device before reaching saturation, which successfully solves the otherwise challenge of salt accumulation inside the device. To achieve such siphon flow, the recycled paper is prepared from spent copy paper and used as the evaporation layer for efficient water delivery owing to its large pore size and high hydrophilicity. An eight-stage F-MSMD device exhibits a stable clean water production rate at 3.61 kg m-2 h-1 in the newly designed siphon-flow mode. This work provides a green route for designing a solar-assisted distillation device.

The low expression of NUP62CL indicates good prognosis and high level of immune infiltration in lung adenocarcinoma.

A primary factor in tumor morbidity and mortality, lung adenocarcinoma (LUAD) is known to be a major subtype of lung cancer, having the lowest survival rate among all other cancers. Using The Cancer Genome Atlas (TCGA) database the relationship between the immune infiltrate and the NUP62CL was explored and the value of the NUP62CL expression in the prognosis and diagnosis LUAD was examined. Using the logistic regression and the Wilcoxon signed-rank test the relationship between the NUP62CL and the clinico-pathological features was analyzed. There was a significant correlation between the clinical stage (p = 0.005), the N (p = 0.004), and the decreased expression of NUP62CL. The prognosis of LUAD with high NUP62CL expression was revealed to be worse than that with low NUP62CL expression (p < 0.001) by the Kaplan-Meier survival analysis. The potentiality of NUP62CL to be a significant factor of prognosis for LUAD was indicated by the analyses of the multivariate and the univariate Cox regression models. In LUAD, the crucial role of recombination and maintenance of telomere as a significant pathway for NUP62CL was suggested by the Gene Set Enrichment Analysis (GSEA). To analyze the correlation between the genes and the tumor infiltrating immune cells the CIBERSORT was used. Moreover the positive correlation with the NUP62CL expression in LUAD of the infiltration level of the tumor infiltrating B lymphocytes and memory CD4+ T cells was exhibited by CIBERSORT. Therefore, NUP62CL may be a new valuable prognostic indicator for LUAD.

Designing a next generation solar crystallizer for real seawater brine treatment with zero liquid discharge.

Proper disposal of industrial brine has been a critical environmental challenge. Zero liquid discharge (ZLD) brine treatment holds great promise to the brine disposal, but its application is limited by the intensive energy consumption of its crystallization process. Here we propose a new strategy that employs an advanced solar crystallizer coupled with a salt crystallization inhibitor to eliminate highly concentrated waste brine. The rationally designed solar crystallizer exhibited a high water evaporation rate of 2.42 kg m-2 h-1 under one sun illumination when treating real concentrated seawater reverse osmosis (SWRO) brine (21.6 wt%). The solar crystallizer array showed an even higher water evaporation rate of 48.0 kg m-2 per day in the outdoor field test, suggesting a great potential for practical application. The solar crystallizer design and the salt crystallization inhibition strategy proposed and confirmed in this work provide a low-cost and sustainable solution for industrial brine disposal with ZLD.

High-speed Gaussian-modulated continuous-variable quantum key distribution with a local local oscillator based on pilot-tone-assisted phase compensation.

A high-speed Gaussian-modulated continuous-variable quantum key distribution (CVQKD) with a local local oscillator (LLO) is experimentally demonstrated based on pilot-tone-assisted phase compensation. In the proposed scheme, the frequency-multiplexing and polarization-multiplexing techniques are used for the separate transmission and heterodyne detection between quantum signal and pilot tone, guaranteeing no crosstalk from strong pilot tone to weak quantum signal and different detection requirements of low-noise for quantum signal and high-saturation limitation for pilot tone. Moreover, compared with the conventional CVQKD based on homodyne detection, the proposed LLO-CVQKD scheme can measure X and P quadrature simultaneously using heterodyne detection without need of extra random basis selection. Besides, the phase noise, which contains the fast-drift phase noise due to the relative phase of two independent lasers and the slow-drift phase noise introduced by quantum channel disturbance, has been compensated experimentally in real time, so that a low level of excess noise with a 25 km optical fiber channel (with 5 dB loss) is obtained for the achievable secure key rate of 7.04 Mbps in the asymptotic regime and 1.85 Mbps under the finite-size block of 107.

Development and Validation of a Clinical Prognostic Model Based on Immune-Related Genes Expressed in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequent and terminal subtype of RCC. Reliable markers associated with the immune response are not available to predict the prognosis of patients with ccRCC. We exploited the extensive number of ccRCC samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository to perform a comprehensive analysis of immune-related genes (IRGs). Methods: Based on TCGA data, we incorporated IRGs and their expression profiles of 72 normal and 539 ccRCC samples. Univariate Cox analysis was used to evaluate the relationship between overall survival (OS) and IRGs expression. The Lasso Cox regression model identified prognostic genes used to establish a clinical immune prognostic model. The TF-IRG network was used to study the potential molecular mechanisms of action and properties of ccRCC-specific IRGs. Multivariate Cox analysis established a clinical prognostic model of IRGs. Results: We found a significant correlation among 15 differentially expressed IRGs with the OS of patients with ccRCC. Gene function enrichment analysis showed that these IRGs are significantly associated with response to receptor ligand activity. Lasso Cox regression analysis identified 10 genes with the greatest prognostic value. A clinical prognostic model based on six IRGs, which performed well for predicting prognosis, revealed significant associations of patients' survival with age, sex, stage, tumor, node, and metastasis. Moreover, these findings reflect the infiltration of tumors by various immune cells. Conclusion: We identified six clinically significant IRGs and incorporated them into a clinical prognostic model with great significance for monitoring and predicting prognosis of ccRCC.

SYT16 is a prognostic biomarker and correlated with immune infiltrates in glioma: A study based on TCGA data.

BACKGROUND: Glioma is the most lethal primary brain tumor. Lower-grade glioma (LGG) is the crucial pathological type of Glioma. Immune-infiltration of the tumor microenvironment positively associated with overall survival in LGG. SYT16 is a gene has not been reported in cancer. We assess the role of SYT16 in LGG, via the publicly available TCGA database. METHODS: Gene Expression Profiling Interactive Analysis (GEPIA) was used to analyze the expression of SYT16 in LGG. We evaluated the influence of SYT16 on survival of LGG patients by survival module. Then, datasets of LGG were downloaded from TCGA. The correlations between the clinical information and SYT16 expression were analyzed using logistic regression. Univariable survival and Multivariate Cox analysis was used to compare several clinical characteristics with survival. we also explore the correlation between SYT16 and cancer immune infiltrates using CIBERSORT and correlation module of GEPIA. Gene set enrichment analysis (GSEA) was performed using the TCGA dataset. In addition, we use TIMER to explore the collection of SYT16 Expression and Immune Infiltration Level in LGG and to explore cumulative survival in LGG. RESULTS: The univariate analysis using logistic regression, indicated that increased SYT16 expression significantly correlated with the tumor grade. Moreover, multivariate analysis revealed that the up-regulated SYT16 expression is an independent prognostic factor for good prognosis. Specifically, SYT16 expression level has significant negative correlations with infiltrating levels of B cell, CD4+ T cells, Macrophages, Neutrophils and DCs in LGG. In addition, GSEA identified ingle organism behavior, gated channel activity, cognition, transporter complex and ligand gated channel activity  in Gene Ontology (GO) were differentially enriched in the high SYT16 expression phenotype pathway. Neuroactive ligand receptor interaction, calcium signaling pathway, long term potentiation, type II diabetes mellitus and long term depression were identified as differentially enriched  pathway in Kyoto Encyclopedia of Genes and Genomes (KEGG). CONCLUSION: SYT16 is a Prognostic Biomarker and Correlated with Immune Infiltrates in LGG.

Prognostic biomarker MITD1 and its correlation with immune infiltrates in hepatocellular carcinoma (HCC).

BACKGROUND: Hepatocellular carcinoma (HCC) is globally recognized as one of the most frequently occurring primary malignant liver tumors, making the identification of HCC biomarkers critically important. The protein MITD1 (Microtubule Interacting and Trafficking Domain containing 1) has been shown to interact with ESCRT-III and participates in cytokinesis, the last step in cell division. This is the first investigation into the expression of MITD1 and its prognostic value, potential biological functions and effects on the immune system in HCC patients. METHODS: The gene expression and clinicopathology analysis, enrichment analysis and immune infiltration analysis are based on data obtained from The Cancer Genome Atlas (TCGA), with additional bioinformatics analyses performed. The statistical analysis was conducted in R and immune responses of MITD1 expression in HCC were analyzed using TIMER and CIBERSORT. In addition, GEPIA, K-M survival analysis and data from the HPA were used to validate the outcomes. RESULTS: Our results highlighted that MITD1 plays a key role as an independent prognostic factor in patients with HCC. MITD1 expression was associated with age, grade, stage and tumor status. GSEA revealed that MITD1 is closely correlated with cell cycle control via the NOTCH signaling pathway. CIBERSORT analysis revealed that the amount of NK cells decreased when MITD1 expression was high. CONCLUSIONS: The identification of MITD1 as a new biomarker for HCC could help elucidate how changes in cytokinesis and the immune environment promote liver cancer development. With further analysis, MITD1 may be able to serve as a predictor for human HCC prognosis.

Increased expression of TTC21A in lung adenocarcinoma infers favorable prognosis and high immune infiltrating level.

BACKGROUND: Lung adenocarcinoma (LUAD) is a crucial pathological type of lung cancer. Immune-infiltration of the tumor microenvironment positively associated with overall survival in LUAD. TTC21A is a gene has not reported in cancer, and the mechanism behind it is still unclear. Our study assesses TTC21A role in LUAD, via TCGA data. METHODS: GEPIA was utilized to analyze the expression of TTC21A in LUAD. We evaluated the influence of TTC21A on survival of LUAD patients by survival module. Then, data sets of LUAD were downloaded from TCGA. The correlations between clinical information and TTC21A expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in TCGA patients using Cox regression. In addition, we explored the correlation between TTC21A and cancer immune infiltrates using CIBERSORT and "Correlation" module of GEPIA. RESULTS: The univariate analysis using logistic regression, wherein TTC21A expression served as a categorical dependent variable (with a median expression value of 2.5), indicated that increased TTC21A expression is significantly correlated with pathological stage, tumor status and lymph nodes. Moreover, multivariate analysis revealed that the up-regulated TTC21A expression, negative results of pathological stage and distant metastasis are independent prognostic factors for good prognosis. Specifically, a positive correlation between increased TTC21A expression and immune infiltrating level of B cells, Neutrophils, Mast cells and T cells was established using CIBERSORT analysis. Furthermore, we confirmed it in "correlation" module of GEPIA. CONCLUSION: Together with all these findings, increased TTC21A expression correlates with favorable prognosis and increased proportion of immune cells, such as B cells, Neutrophils, Mast cells and T cells in LUAD. These conclusions indicate that TTC21A could serve as a potential biomarker to assess prognosis and immune infiltration level in LUAD.

Defeating relapsed and refractory malignancies through a nano-enabled mitochondria-mediated respiratory inhibition and damage pathway.

Hypoxia, which frequently reduces the sensitivity to many therapeutic interventions, including chemotherapy, radiotherapy and phototherapy, has been acknowledged as an important reason for poor prognosis. Burgeoning evidences have proved that the tumor hypoxia microenvironment can reduce the therapeutic effect on tumor through inhibiting the drug efficacy, limiting immune cell infiltration of tumors and accelerating tumor recurrence and metastasis. However, the relationship between oxygen supply and the proliferation of cancer cells is still ambiguous and argued. Different from the current commonly used oxygen supply strategies, this study concentrated on the reduction of endogenous oxygen consumption. Specifically, a novel photosensitizers (IR780) and metformin are packaged in PEG-PCL liposomes. Once such nanoparticles accumulated in tumor tissues, the tumor foci were irradiated through 808 nm laser, generated ROS to further release metformin and IR780. Metformin can directly inhibit the activity of complex Ⅰ in the mitochondrial electron transport chain, thus performed a potent inhibitor of cell respiration. After overcoming tumor hypoxia, the combination of mitochondria-targeted photodynamic therapy (PDT) and photothermic therapy (PTT) via IR780 may achieve superior synergistically therapeutic efficacy. Benefit from excellent characteristics of IR780, such synergistic PDT PTT with the inhibition of mitochondrial respiration can be monitored through near-infrared/photoacoustic dual-modal imaging. Such a conception of reducing endogenous oxygen consumption may offer a novel way to solve the important puzzles of hypoxia-induced tumor resistance to therapeutic interventions, not limited to phototherapy.