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.

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.

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.

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.

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data.

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients' prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = -0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.

Solar Evaporator with Controlled Salt Precipitation for Zero Liquid Discharge Desalination.

A sustainable supply of clean water is essential for the development of modern society, which has become increasingly dependent on desalination technology since 96.5% of the water on Earth is salt water. Thousands of desalination plants are producing massive waste brine as byproduct, and the direct discharge of brine raises serious concerns about its ecological impact. The concept of zero liquid discharge (ZLD) desalination is regarded as the solution, but the current ZLD technologies are hampered by their intensive use of energy and high cost. In this work, a 3D cup shaped solar evaporator was fabricated to achieve ZLD desalination with high energy efficiency via solar distillation. It produces solid salt as the only byproduct and uses sunlight as the only energy source. By rationally separating the light absorbing surface from the salt precipitation surface, the light absorption of the 3D solar evaporator is no longer affected by the salt crust layer as in conventional 2D solar evaporators. Therefore, it can be operated at an extremely high salt concentration of 25 wt % without noticeable water evaporation rate decay in at least 120 h. This new solar evaporator design concept offers a promising technology especially for high salinity brine treatment in desalination plants to achieve greener ZLD desalination as well as for hypersaline industrial wastewater treatment.

Qiliqiangxin Attenuates Adverse Cardiac Remodeling after Myocardial Infarction in Ovariectomized Mice via Activation of PPARγ.

BACKGROUND/AIMS: This study was designed to investigate the therapeutic effect of traditional Chinese medication Qiliqiangxin (QLQX) on adverse cardiac remodeling after myocardial infarction (MI) in bilateral ovariectomized (OVX) female mice. METHODS: Eight-week old female C57BL/6 mice were operated to ligate the left anterior descending coronary artery seven days after bilateral ovariectomy and were orally administered either QLQX or vehicle. 21 days after ligation, echocardiography was performed to evaluate the heart function of all mice. Masson's Trichrome staining was applied to evaluate myocardial fibrosis. Collagen deposition was determined by the mRNA level of Collagen I, Collagen III and α-SMA using real-time quantitative polymerase chain reaction (qPCR). Myocardial apoptosis was examined by the protein level of Bax, Bcl2 and the Bcl2/Bax ratio using western blotting. RESULTS: These mice displayed a significant reduction in heart function, increased myocardial fibrosis and apoptosis, and decreased expression of peroxisome proliferator activated receptor γ (PPARγ) in the heart tissue, which could be reversed by QLQX treatment. Inhibition of PPAR reduced QLQX-mediated cardio-protective effects, while PPARγ activation did not further enhance the beneficial effect of QLQX. Furthermore, QLQX upregulated 9 genes (Cd36, Fatp, Pdk4, Acadm, Acadl, Acadvl, Cpt1a, Cpt1b and Cpt2) facilitating energy metabolism in the MI hearts of the OVX mice and 5 (Acadm, Acadl, Cpt1a, Cpt1b, Cpt2) of the 9 genes were the downstream targets of PPARγ. CONCLUSION: The present study indicates that QLQX has a treatment effect on pathological remodeling post MI in bilateral OVX female mice via activation of PPARγ, suggesting that QLQX may be a promising prescription for the treatment of postmenopausal women suffering from MI.

Traditional Chinese Medication Qiliqiangxin Protects Against Cardiac Remodeling and Dysfunction in Spontaneously Hypertensive Rats.

Qiliqiangxin (QLQX), a traditional Chinese herbs medication, exerted protective effect in chronic heart failure patients in a multicenter randomized double-blind study. QLQX has also been found to improve cardiac function and reduce cardiac fibrosis in spontaneously hypertension animal model. However, the effect of longterm treatment with QLQX in such a condition and the related molecular mechanisms remain largely unknown. In the present study, thirteen-week-old spontaneously hypertensive rats (SHRs) were treated by daily intragastric administration of QLQX or saline for one year. Echocardiography, electron microscopy, and Masson's trichrome staining were used to determine cardiac function, mitochondria ultrastructure, and cardiac fibrosis, respectively. Quantitative reverse transcription polymerase chain reactions (qRT-PCRs) and Western blotting were used to determine gene expressions. We found that QLQX significantly improved cardiac function and reduced gene markers of pathological hypertrophy including ANP, BNP, and Myh7. QLQX also attenuated cardiac fibrosis and apoptosis in SHRs as evidenced by downregulation of α-SMA, collagen I, collagen III, and TGF-ß expressions and reduction of Bax to Bcl-2 ratio. Moreover, the damage of mitochondrial ultrastructure was greatly improved and the reduction of PPAR-α, PPAR-γ, and PGC-1α expression levels was significantly restored in SHRs by treatment with QLQX. In conclusion, longterm treatment with QLQX protects against cardiac remodeling and dysfunction in hypertension by increasing PPARs and PGC-1α.

Optofluidic tunable manipulation of microparticles by integrating graded-index fiber taper with a microcavity.

We propose and demonstrate optofluidic tunable manipulation of polystyrene microparticles based on the combination of a graded-index fiber (GIF) taper and a microcavity. The tunability on the manipulation length is experimentally explored by changing the balance between the optical force and the microfluidic flow force, as well as by tuning the focus of light emitting from the GIF taper via adjusting the length of an air microcavity. By optimizing the geometric shape of the GIF taper, as well as the flow rate and laser power, a manipulation length of 177 µm is achieved, more than 4 times longer than the state-of-the-art optical fiber tweezers. This method has advantages of high flexibility, ease of fabrication and use, integration with microfluidics and has the potential for optofluidic sensing applications.

Gut microbiome model predicts response to neoadjuvant immunotherapy plus chemoradiotherapy in rectal cancer.

BACKGROUND: Accurate evaluation of the response to preoperative treatment enables the provision of a more appropriate personalized therapeutic schedule for locally advanced rectal cancer (LARC), which remains an enormous challenge, especially neoadjuvant immunotherapy plus chemoradiotherapy (nICRT). METHODS: This prospective, multicenter cohort study enrolled patients with LARC from 6 centers who received nICRT. The dynamic variation in the gut microbiome during nICRT was evaluated. A species-level gut microbiome prediction (SPEED) model was developed and validated to predict the pathological complete response (pCR) to nICRT. FINDINGS: A total of 50 patients were enrolled, 75 fecal samples were collected from 33 patients at different time points, and the pCR rate reached 42.4% (14/33). Lactobacillus and Eubacterium were observed to increase after nICRT. Additionally, significant differences in the gut microbiome were observed between responders and non-responders at baseline. Significantly higher abundances of Lachnospiraceaebacterium and Blautiawexlerae were found in responders, while Bacteroides, Prevotella, and Porphyromonas were found in non-responders. The SPEED model showcased a superior predictive performance with areas under the curve of 98.80% (95% confidence interval [CI]: 95.67%-100%) in the training cohort and 77.78% (95% CI: 65.42%-88.29%) in the validation cohort. CONCLUSIONS: Programmed death 1 (PD-1) blockade plus concurrent long-course CRT showed a favorable pCR rate and is well tolerated in microsatellite-stable (MSS)/mismatch repair-proficient (pMMR) patients with LARC. The SPEED model can be used to predict the pCR to nICRT based on the baseline gut microbiome with high robustness and accuracy, thereby assisting clinical physicians in providing individualized management for patients with LARC. FUNDING: This research was funded by the China National Natural Science Foundation (82202884).

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.

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.

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.

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.

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.