Search

As highlighted in Dawid (2000) and Pearl & Mackenzie (2018) , deducing the causes of given effects is a more challenging problem than evaluating the effects of causes in causal inference. Lu et al. (2023) proposed an approach for deducing causes of a single effect variable based on posterior causal effects. In many applications, there are multiple effect variables, and they can be used simultaneously to more accurately deduce the causes. To retrospectively deduce causes from multiple effects, we propose multivariate posterior total, intervention and direct causal effects conditional on the observed evidence. We describe the assumptions of no confounding and monotonicity, under which we prove identifiability of the multivariate posterior causal effects and provide their identification equations. The proposed approach can be applied for causal attributions, medical diagnosis, blame and responsibility in various studies with multiple effect or outcome variables. Two examples are used to illustrate the proposed approach. [ABSTRACT FROM AUTHOR]

The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform 'data' for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ , and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for. [ABSTRACT FROM AUTHOR]

In this paper, we design a decoupled scheme for solving a fluid–fluid interaction problem, which includes two Navier–Stokes equations coupled by some nonlinear interface conditions. Compared with two decoupled schemes proposed by Connors et al. (2012, Decoupled time stepping methods for fluid–fluid interaction. SIAM J. Numer. Anal. , 50 , 1297–1319) for the fluid–fluid interaction problem, we deal with these nonlinear interface conditions by applying explicit scheme. The presented fully discrete scheme is a combination of a mixed finite element approximation for spatial discretization, the first-order backward Euler scheme for temporal discretization and explicit treatment for the interface conditions and the nonlinear terms. Moreover, the unconditional energy stability is established and error estimate for the fully discrete scheme is also showed. Finally, some numerical experiments are provided to verify the theoretical results, which illustrate the accuracy and efficiency of the presented scheme. [ABSTRACT FROM AUTHOR]

Studies have shown that the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome is detrimental to the functional recovery of the sciatic nerve, but the regulatory mechanisms of the NLRP3 inflammasome in peripheral nerves are unclear. C-X-C motif chemokine 12 (CXCL12) can bind to C-X-C chemokine receptor type 4 (CXCR4) and participate in a wide range of nerve inflammation by regulating the NLRP3 inflammasome. Based on these, we explore whether CXCL12-CXCR4 axis regulates the NLRP3 inflammasome in the peripheral nerve. We found that CXCR4/CXCL12, NLRP3 inflammasome-related components, pyroptosis-related proteins and inflammatory factors in the sciatic nerve injured rats were markedly increased compared with the sham-operated group. AMD3100, a CXCR4 antagonist, reverses the activation of NLRP3 inflammasome, Schwann cell pyroptosis and sciatic nerve demyelination. We further treated rat Schwann cells with LPS (lipopolysaccharide) and adenosine triphosphate (ATP) to mimic the cellular inflammation model of sciatic nerve injury, and the results were consistent with those in vivo. In addition, both in vivo and in vitro experiments demonstrated that AMD3100 treatment reduced the phosphorylation of nuclear factor κB (NF-κB) and the expression of thioredoxin interacting protein (TXNIP), which contributes to activating NLRP3 inflammasome. Therefore, our findings suggest that, after sciatic nerve injury, CXCL12-CXCR4 axis may promote Schwann cell pyroptosis and sciatic nerve demyelination through activating NLRP3 inflammasome and slow the recovery process of the sciatic nerve. Studies have shown that the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome is detrimental to the functional recovery of the sciatic nerve, and C-X-C motif chemokine 12 (CXCL12) can bind to C-X-C chemokine receptor type 4 (CXCR4) and participate in a wide range of nerve inflammation by regulating the NLRP3 inflammasome. However, the regulatory mechanisms of the NLRP3 inflammasome in peripheral nerves are unclear. Our findings suggest that, after sciatic nerve injury, CXCL12-CXCR4 axis may promote Schwann cell pyroptosis and sciatic nerve demyelination through activating NLRP3 inflammasome. [ABSTRACT FROM AUTHOR]

Technological advances have now made it possible to simultaneously profile the changes of epigenomic, transcriptomic and proteomic at the single cell level, allowing a more unified view of cellular phenotypes and heterogeneities. However, current computational tools for single-cell multi-omics data integration are mainly tailored for bi-modality data, so new tools are urgently needed to integrate tri-modality data with complex associations. To this end, we develop scMHNN to integrate single-cell multi-omics data based on hypergraph neural network. After modeling the complex data associations among various modalities, scMHNN performs message passing process on the multi-omics hypergraph, which can capture the high-order data relationships and integrate the multiple heterogeneous features. Followingly, scMHNN learns discriminative cell representation via a dual-contrastive loss in self-supervised manner. Based on the pretrained hypergraph encoder, we further introduce the pre-training and fine-tuning paradigm, which allows more accurate cell-type annotation with only a small number of labeled cells as reference. Benchmarking results on real and simulated single-cell tri-modality datasets indicate that scMHNN outperforms other competing methods on both cell clustering and cell-type annotation tasks. In addition, we also demonstrate scMHNN facilitates various downstream tasks, such as cell marker detection and enrichment analysis. [ABSTRACT FROM AUTHOR]

This article, published in Current Zoology, discusses infanticide in golden snub-nosed monkeys. The study reports two cases of infanticide by a dominant male who had taken over a one-male unit (OMU) of monkeys in China. The researchers used behavior and genetic analyses to test the sexual selection hypotheses. The study found that the infanticide events occurred after the infants had become independent and that the females in the OMU showed agonistic behavior towards the male. The findings provide evidence for understanding the sexual selection hypothesis associated with animal infanticide. [Extracted from the article]

Moho determination is an important issue in studying the Earth's interior structure. In accordance with the isostasy-compensation hypothesis in geodesy, it is possible to recover regional or global Moho by employing gravimetric data. The nonlinear property is one of the main difficulties in solving the inverse problem of isostasy. To effectively address this issue, we propose an improved iterative inversion method that combines 3-D integration and linear regularization to achieve an approximate nonlinear solution. To estimate the contributions of different components in the gravity-gradient tensor from the Gravity field and steady-state Ocean Circulation Explorer (GOCE), other than the vertical component, we additionally develop two joint inversion scenarios that utilize diagonal horizontal components and all five non-vertical components. The validating experiments are implemented in Qinghai–Tibet Plateau and its near zone. Simulations and applications illustrate that horizontal responses of Moho undulation are also significant. Yet the off-diagonal components provide minimal contributions, adding only 0.25 km of bias to the joint inversion results. Truncation effects serve as the primary source of systematic errors, resulting in ∼1 km error in vertical inversion results and ∼2.3 km error in joint inversion results. Then, the gravimetric Moho results are compared with CRUST1.0, and they show a generally strong correlation. Differences are obvious at the northern and eastern margins of the plateau. It is maybe due to the local changes in crust–mantle density contrasts. Upwelling of asthenospheric materials and fluid flow in the middle-lower crust are the two main factors. Based on high-precision satellite gravimetry, our study could provide new insights into the tectonic structure of Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

Background Laboratory tests to diagnose neurosyphilis using cerebrospinal fluid (CSF) are currently disadvantageous as a lumbar puncture is required, which may result in patients with neurosyphilis missing an opportunity for early diagnosis. Thus, blood biomarker candidates that are more convenient and minimally invasive to collect for diagnosing neurosyphilis is urgently needed. Methods This observational study aimed to analyze serum ubiquitin C-terminal hydrolase-L1 (UCH-L1), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NF-L) levels in 153 patients without human immunodeficiency virus (HIV) and to evaluate their diagnostic performance in neurosyphilis compared with CSF. Results Serum UCH-L1, GFAP, and NF-L levels were significantly higher in patients with neurosyphilis compared with patients with uncomplicated syphilis or non-syphilis. For the diagnosis of neurosyphilis, serum UCH-L1, GFAP, and NF-L revealed sensitivities of 90.20%, 80.40%, and 88.24%, and specificities of 92.16%, 78.43%, and 80.39%, respectively, at cutoff levels of 814.50 pg/mL, 442.70 pg/mL, and 45.19 pg/mL, respectively. In patients with syphilis, serum UCH-L1, GFAP, and NF-L levels correlated strongly or moderately with those in the CSF, with similar or better diagnostic performance than those in the CSF. The testing algorithms' sensitivity and specificity increased to 98.04% and 96.08%, respectively, when subjected to parallel and combination testing, respectively. Conclusions To avoid lumbar puncture, each serum UCH-L1, GFAP, and NF-L is a good entry point and biomarker candidate for the diagnosis of neurosyphilis among patients without HIV. These proteins used in concerto can further improve the diagnostic sensitivity and specificity. [ABSTRACT FROM AUTHOR]

This article discusses the use of deep learning (DL) in complex chemical systems. DL models, such as convolutional neural networks and recurrent neural networks, are increasingly popular in the chemistry community because they automatically learn underlying representations. These models utilize nonlinear activation functions to capture the relationship between input descriptors and outputs. DL is used to predict properties, model reactions, and optimize synthetic processes. It can also be combined with simulations and machine learning to create intelligent laboratories for rapid discovery of reactions and functional materials. The article emphasizes the need for a user-friendly platform and the sharing of code and datasets to further advance DL in chemistry. [Extracted from the article]

It is challenging to evaluate causal effects when the outcomes of interest suffer from truncation‐by‐death in many clinical studies; that is, outcomes cannot be observed if patients die before the time of measurement. To address this problem, it is common to consider average treatment effects by principal stratification, for which, the identifiability results and estimation methods with a binary treatment have been established in previous literature. However, in multiarm studies with more than two treatment options, estimation of causal effects becomes more complicated and requires additional techniques. In this article, we consider identification, estimation, and bounds of causal effects with multivalued ordinal treatments and the outcomes subject to truncation‐by‐death. We define causal parameters of interest in this setting and show that they are identifiable either using some auxiliary variable or based on linear model assumption. We then propose a semiparametric method for estimating the causal parameters and derive their asymptotic results. When the identification conditions are invalid, we derive sharp bounds of the causal effects by use of covariates adjustment. Simulation studies show good performance of the proposed estimator. We use the estimator to analyze the effects of a four‐level chronic toxin on fetal developmental outcomes such as birth weight in rats and mice, with data from a developmental toxicity trial conducted by the National Toxicology Program. Data analyses demonstrate that a high dose of the toxin significantly reduces the weights of pups. [ABSTRACT FROM AUTHOR]

Objective Our aim was to investigate the association between gene polymorphisms in catalase (CAT), a well-known oxidative stress regulator, and susceptibility to idiopathic nephrotic syndrome (INS) or responses to steroid therapy in a Chinese pediatric population. Methods We analyzed 3 CAT single-nucleotide polymorphisms (SNVs; rs7943316, rs769217, and rs12270780) using multi-polymerase chain reaction combined with next-generation sequencing in 183 INS patients and 100 healthy controls. Results For the allele and genotype frequencies of the CAT SNVs, no significant differences were observed between INS patients and controls. Patients with C allele of CAT rs769217 had a higher risk of developing steroid-dependent nephrotic syndrome than the steroid-sensitive nephrotic syndrome patients (P = 0.018; odds ratio = 1.76). Conclusion Our data suggests that genetic variations in CAT were unlikely to confer susceptibility to INS in Chinese children, whereas the C allele of the CAT rs769217 polymorphism showed a strong association with steroid-dependent responses in Chinese INS children. [ABSTRACT FROM AUTHOR]

Aim: To obtain promising immunosuppressants from endophytic fungus. Methods and Results: The endophytic fungus Mycosphaerella nawae (ZJLQ129) was isolated from the plant Smilax china L. and its secondary metabolites extracted and fractionated through column chromatography. The metabolites were further modified by a derivatization reaction with ammonium hydroxide. After isolation and derivatization, a new dibenzofuran named as (+)isomycousnine enamine (iME) was obtained. The structures of the derivatives were determined based on chemical evidences and extensive spectroscopic methods including 2D‐NMR, DEPT and HRESI‐MS spectra. The immune activities of iME were first evaluated on the proliferation and cytokines (IL‐2 and IFN‐γ) production of T and B cells by using MTT and ELISA methods respectively. Then, its effects on the proliferation of T‐cell subsets (CD4+ and CD8+ T cells), as well as CD25 and CD69 expressions were also determined by flow cytometry. Finally, by using Cytometric Bead Array (CBA), the impacts of iME on the secretion of Th1/Th2/Th17 cytokines from purified CD4+ T cells were assayed. The results showed that iME not only selectively suppressed the immune responses of T cells, but also preferentially inhibited the activation and proliferation of CD4+ T cells. Conclusion: A novel dibenzofuran derived from endophytic fungus Mycosphaerella nawae preferentially inhibits CD4+ T‐cell activation and proliferation. Significance and Impact of the Study: This work obtained iME, a new dibenzofuran derived from endophytic fungus. iME has the capacity to inhibit CD4+ T‐cell activation and therefore is a novel potential immunosuppressant for development in the future. [ABSTRACT FROM AUTHOR]

In recent years, a number of computational approaches have been proposed to effectively integrate multiple heterogeneous biological networks, and have shown impressive performance for inferring gene function. However, the previous methods do not fully represent the critical neighborhood relationship between genes during the feature learning process. Furthermore, it is difficult to accurately estimate the contributions of different views for multi-view integration. In this paper, we propose MGEGFP, a multi-view graph embedding method based on adaptive estimation with Graph Convolutional Network (GCN), to learn high-quality gene representations among multiple interaction networks for function prediction. First, we design a dual-channel GCN encoder to disentangle the view-specific information and the consensus pattern across diverse networks. By the aid of disentangled representations, we develop a multi-gate module to adaptively estimate the contributions of different views during each reconstruction process and make full use of the multiplexity advantages, where a diversity preservation constraint is designed to prevent the over-fitting problem. To validate the effectiveness of our model, we conduct experiments on networks from the STRING database for both yeast and human datasets, and compare the performance with seven state-of-the-art methods in five evaluation metrics. Moreover, the ablation study manifests the important contribution of the designed dual-channel encoder, multi-gate module and the diversity preservation constraint in MGEGFP. The experimental results confirm the superiority of our proposed method and suggest that MGEGFP can be a useful tool for gene function prediction. [ABSTRACT FROM AUTHOR]

Aims: In recent years, the incidence rate of hypertensive intracerebral haemorrhage (HICH) has been increasing, accompanied by high mortality and morbidity, which has brought a heavy burden to the social economy. However, the pathogenesis of HICH is still unclear. This study intends to explore the mechanism of gut microbiota metabolism and inflammation in the process of HICH to provide a theoretical basis for the diagnosis and treatment of HICH. Methods and Results: HE staining showed that the brain tissues of model group had obvious oedema injury, which indicated that the HICH model was successfully constructed. ELISA analysis showed that IL‐1β and TNF‐α levels in blood and brain tissues were significantly increased, and IL‐10 level was significantly decreased in blood. IHC analysis showed that microglia and macrophages were activated in the model group. 16S rRNA sequence showed that the diversity of gut microbiota in HICH patients decreased. Also, the microbiota belonging to Firmicutes, Proteobacteria and Verrucomicrobia changed significantly. LC–MS/MS analysis showed that the metabolic phenotype of HICH patients changed. Also, the 3,7‐dimethyluric acid‐ and 7‐methylxanthine‐related metabolic pathways of caffeine metabolism pathways were downregulated in patients with HICH. Bacteroides was negatively correlated with the IL‐1β and TNF‐α levels. Blautia was negatively correlated with the IL‐1β and TNF‐α levels, and positively correlated with the IL‐10 level. Akkermansia was negatively correlated with the 3,7‐dimethyluric acid and 7‐methylxanthine. Conclusion: Our study suggested that HICH was accompanied by the increased inflammation marker levels in peripheral blood and brain, decreased gut microbiota diversity, altered gut metabolic phenotype and downregulation of caffeine metabolism pathway. Significance and Impact of the Study: Our study reported that HICH accompanied by the increased inflammation, decreased gut microbiota diversity and altered gut metabolic phenotype. Due to the number of patients, this work was a pilot study. [ABSTRACT FROM AUTHOR]

Unlike that of other crops, the growth of tea plants can be promoted by aluminum, but its regulation mechanism remains unclear. Some endophytes can also promote growth of plant hosts. In this paper, tea roots treated with aluminum were used to study the growth-promoting traits and aluminum tolerance of endophytes. Meta-16S rDNA analysis revealed that Burkholderia was enriched in tea roots after aluminum treatment, and it was the dominant strain for hydroponic tea roots and field tea roots. Actinomycetes constituted the dominant strains in hydroponic tea seedlings treated with aluminum. Sixteen endophytic bacteria, including 12 strains of Firmicutes , 2 strains of Proteobacteria and 2 strains of Actinomycetes , were isolated and identified from hydroponic tea roots treated with different aluminum concentrations. Growth-promoting activity analysis showed that the isolated endophytic bacteria all had more than one plant growth-promoting trait. Among them, B4 (Bacillus nealsonii), B8 (Brevibacterium frigoritolerans) and A2 (Nocardia nova) bacteria each had three growth-promoting traits. Aluminum tolerance ability analysis indicated that endophyte A1 (Leifsonia shinshuensis) had the strongest aluminum tolerance ability, up to 200 mg l−1 aluminum. Plant–bacteria interactions showed that endophytes A1, A2 and B4 and their synthetic community all had a growth-promoting effect on the growth of wheat lateral roots. Moreover, endophytes A1 and B4 alleviated aluminum stress in wheat. Endophyte A1 also promoted the growth of tea cuttings, especially lateral roots, with/without aluminum. Taken together, aluminum enhanced the distribution of aluminum-tolerant and growth-promoting bacteria, thereby promoting the growth of tea roots. This study provides a new aspect for research on the mechanism by which aluminum promotes tea plant growth. [ABSTRACT FROM AUTHOR]

Objective This study aimed to determine the predictive values of informant-reported memory decline (IMD) among subjective cognitive decline (SCD) older adults from a 7-year community-based cohort study. Method Ninety SCD participants were included. Demographic data and neuropsychological test scores at both baseline and 7-year follow-up were collected. Differences between SCD with IMD (+IMD) and SCD without IMD (−IMD) were compared. Logistic regression models were used to determine whether baseline IMD could predict diagnostic outcomes at 7-year follow-up. Results Forty-one percent of SCD adults had IMD. At baseline, the +IMD group showed more depressive symptoms (p  = 0.016) than the −IMD group. Furthermore, the Beijing-version Montreal Cognitive Assessment (MoCA), Digit Span Test-Forward, Visual Matching and Reasoning, and Wechsler Adult Intelligence Scale-RC Picture Completion (WAIS-PC) scores in the +IMD group were significantly lower than those in the −IMD group. Fifty-four percent of +IMD participants converted to mild cognitive impairment (MCI) or dementia at follow-up, and 22.6% of the −IMD participants converted to MCI. Follow-up Mini-Mental State Examination, MoCA, and Verbal Fluency Test scores of the +IMD group were significantly lower than those in the −IMD group. The +IMD group was more likely to progress to cognitive impairment at 7-year follow-up (OR = 3.361, p  = 0.028). Conclusions SCD participants with +IMD may have poorer cognition and are more likely to convert to cognitive impairment over time. Our long-term follow-up study confirmed the importance of informants' perceptions of SCD, which can help clinicians identify individuals at risk of cognitive decline. [ABSTRACT FROM AUTHOR]

Studying light pollution is an interest to researchers in a wide range of fields including astronomy, biology, civil engineering, ecology, and social science. Consequently, numerous sky brightness metrics have been developed over the years. However, what metrics are truly representative of the night sky quality and unique to the measured feature? The US National Park Service Night Skies Program has collected more than 1500 sets of night skies data throughout the United States. For each data set, a maximum of 56 metrics were measured through the combination of the captured images, Sky Quality Meter readings, and visual observations. This paper analyses these measurements and identifies a distinctive set of night sky brightness metrics based on the principal component analysis. Three major findings emerge. First, the commonly used metrics, such as the zenith brightness, horizontal illuminance, maximum vertical illuminance, all-sky light pollution ratio, Bortle class, and limiting magnitude, are highly correlated. Secondly, the observed sky brightness often offers a good estimate of the artificial light level despite the natural varying night sky background. Thirdly, a set of six metrics that consists of the zenith brightness and sky brightness percentiles are more distinctive when used to concisely describe night sky characteristics. These findings suggest that long-term night sky monitoring can be efficiently carried out by measuring the sky brightness percentiles on the observed all-sky images. [ABSTRACT FROM AUTHOR]

In their recent article, Ogburn et al. (Am J Epidemiol. 2021;190(6):1142–1147) raised a cautionary tale for epidemiologic data fusion: Bias may occur if a variable that is completely missing in the primary data set is imputed according to a regression model estimated from an auxiliary data set. However, in some specific settings, a solution may exist. Focusing on a linear outcome regression model with a missing covariate, we show that the bias can be eliminated if the underlying imputation model for the missing covariate is nonlinear in the common variables measured in both data sets. Otherwise, we describe 2 alternative approaches existing in the data fusion literature that could partially resolve this issue: One fits the outcome model by leveraging an additional validation data set containing joint observations of the outcome and the missing covariate, and the other offers informative bounds for the outcome regression coefficients without using validation data. We justify these 3 methods in a linear outcome model and briefly discuss their extension to general settings. [ABSTRACT FROM AUTHOR]

To evaluate the effects of combat sports on cerebellar function in adolescents based on resting-state functional MRI (rs-fMRI). Rs-fMRI data were acquired from the combat sports (CS) group (n = 32, aged 14.2 ± 1.1 years) and non-athlete healthy control (HC) group (n = 29, aged 14.8 ± 0.9 years). The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) within the cerebellum was calculated and then compared between the two groups. None of these participants displayed intracranial lesions on conventional MRI and microhemorrhages on SWI. Compared with the HC group, the CS group showed decreased ALFF and ReHo in the bilateral cerebellum, mainly located in the inferior regions of the cerebellum (Cerebellum_8, Cerebellum_9, Cerebellum_7b, and Cerebellum_Crus2). While increased FC was found within the cerebellar network, mainly located in the superior regions near the midline (bilateral Cerebellum_6, Cerebellum_Crus1_R, and Vermis_6). There is no internetwork FC change between the CEN and other networks. This study confirmed extensive effects of combat sports on cerebellar rs-fMRI in adolescents, which could enhance the understanding of cerebellar regulatory mechanism under combat conditions, and provide additional information about cerebellar protective inhibition and compensatory adaptation. Adolescent combat participants are an ideal model to study training-induced brain plasticity and vulnerability. Relative to task-related fMRI, rs-fMRI can bring more information about cerebellar regulation and explain the Central Governor Model more comprehensively. [ABSTRACT FROM AUTHOR]

The presence of seismic anisotropy at the base of the Earth's mantle is well established, but there is no consensus on the deformation mechanisms in lower mantle minerals that could explain it. Strong anisotropy in magnesium post-perovskite (pPv) has been invoked, but different studies disagree on the dominant slip systems at play. Here, we aim to further constrain this by implementing the most recent results from atomistic models and high-pressure deformation experiments, coupled with a realistic composition and a 3-D geodynamic model, to compare the resulting deformation-induced anisotropy with seismic observations of the lowermost mantle. We account for forward and reverse phase transitions from bridgmanite (Pv) to pPv. We find that pPv with either dominant (001) or (010) slip can both explain the seismically observed anisotropy in colder regions where downwellings turn to horizontal flow, but only a model with dominant (001) slip matches seismic observations at the root of hotter large-scale upwellings. Allowing for partial melt does not change these conclusions, while it significantly increases the strength of anisotropy and reduces shear and compressional velocities at the base of upwellings. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented molecular resolution. In order to evaluate various biological hypotheses using high-dimensional single-cell gene expression data, most computational and statistical methods depend on a gene feature selection step to identify genes with high biological variability and reduce computational complexity. Even though many gene selection methods have been developed for scRNA-seq analysis, there lacks a systematic comparison of the assumptions, statistical models, and selection criteria used by these methods. In this article, we summarize and discuss 17 computational methods for selecting gene features in unsupervised analysis of single-cell gene expression data, with unified notations and statistical frameworks. Our discussion provides a useful summary to help practitioners select appropriate methods based on their assumptions and applicability, and to assist method developers in designing new computational tools for unsupervised learning of scRNA-seq data. [ABSTRACT FROM AUTHOR]

Infants are more likely to develop severe pertussis. We report a malignant pertussis case in a 2-month-old boy with respiratory failure, severe pneumonia, septic shock, and encephalopathy. Bordetella pertussis was detected from nasopharyngeal secretions by polymerase chain reaction, as well as both blood and cerebrospinal fluid samples via metagenomics next-generation sequencing. [ABSTRACT FROM AUTHOR]

Synaptic associativity, a feature of Hebbian plasticity wherein coactivation of two inputs onto the same neuron produces synergistic actions on postsynaptic activity, is a primary cellular correlate of associative learning. However, whether and how synaptic associativity are implemented into context-dependent relapse of extinguished memory (i.e. fear renewal) is unknown. Here, using an auditory fear conditioning paradigm in mice, we show that fear renewal is determined by the associativity between convergent inputs from the auditory cortex (ACx) and ventral hippocampus (vHPC) onto the lateral amygdala (LA) that reactivate ensembles engaged during learning. Fear renewal enhances synaptic strengths of both ACx to LA and the previously unknown vHPC to LA monosynaptic inputs. While inactivating either of the afferents abolishes fear renewal, optogenetic activation of their input associativity in the LA recapitulates fear renewal. Thus, input associativity underlies fear memory renewal. [ABSTRACT FROM AUTHOR]

(e) Histopathology revealed a subcorneal spongiform pustule in the epidermis (haematoxylin and eosin, original magnification × 200). gl Histopathology revealed a subcorneal spongiform pustule. IgA pemphigus is a rare subtype of pemphigus that is effective on amylin sulfone therapy and is characterized by intercellular IgA deposition that clinically presents as pustules more often than as blistering macules.2 Our patient's direct immunofluorescence test for IgA was negative, thus excluding IgA pemphigus. The differential diagnoses for SPD include IgA pemphigus, secondary bacterial infection, generalized pustular psoriasis (GPP), and acute generalized exanthematous pustulosis (AGEP). [Extracted from the article]

Motivation Single-cell RNA sequencing technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues and cell types with unprecedented molecular resolution. In order to better understand animal development, physiology, and pathology, unsupervised clustering analysis is often used to identify relevant cell populations. Although considerable progress has been made in terms of clustering algorithms in recent years, it remains challenging to evaluate the quality of the inferred single-cell clusters, which can greatly impact downstream analysis and interpretation. Results We propose a bioinformatics tool named Phitest to analyze the homogeneity of single-cell populations. Phitest is able to distinguish between homogeneous and heterogeneous cell populations, providing an objective and automatic method to optimize the performance of single-cell clustering analysis. Availability and implementation The PhitestR package is freely available on both Github (https://github.com/Vivianstats/PhitestR) and the Comprehensive R Archive Network (CRAN). There is no new genomic data associated with this article. Published data used in the analysis are described in detail in the Supplementary Data. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Background Since December 2019, coronavirus disease (COVID-19) has affected over 50 000 people in Wuhan, China. However, the number of daily infection cases, hospitalization rate, lag time from onset to diagnosis date and their associations with measures introduced to slow down the spread of COVID-19 have not been fully explored. Methods This study recruited 6872 COVID-19 patients in the Wuchang district, Wuhan. All of the patients had an onset date from 21 December 2019 to 23 February 2020. The overall and weekly hospitalization rate and lag time from onset to diagnosis date were calculated. The number of daily infections was estimated by the back-projection method based on the number of daily onset cases. Their association with major government reactions and measures was analyzed narratively. Results The overall hospitalization rate was 45.9% (95% CI 44.7 to 47.1%) and the mean lag time from onset to diagnosis was 11.1±7.4 d. The estimated infection curve was constructed for the period from 14 December 2019 to 23 February 2020. Raising public awareness regarding self-protecting and social distancing, as well as the provision of timely testing and inpatient services, were coincident with the decline in the daily number of infections. Conclusion Early public awareness, early identification and early quarantine, supported by appropriate infrastructure, are important elements for containing the spread of COVID-19 in the community. [ABSTRACT FROM AUTHOR]

Background: Systemic vascular injury occurs in coronavirus disease 2019 (COVID-19) patients; however, the underlying mechanisms remain unknown.Methods: To clarify the role of inflammatory factors in COVID-19 vascular injury, we used a multiplex immunoassay to profile 65 inflammatory cytokines/chemokines/growth factors in plasma samples from 24 hospitalized (severe/critical) COVID-19 patients, 14 mild/moderate cases, and 13 healthy controls (HCs).Results: COVID-19 patients had significantly higher plasma levels of 20 analytes than HCs. Surprisingly, only 1 cytokine, macrophage migration inhibitory factor (MIF), was among these altered analytes, while the rest were chemokines/growth factors. Additionally, only matrix metalloproteinase-1 (MMP-1) and vascular endothelial growth factor A (VEGF-A) were significantly elevated in hospitalized COVID-19 patients when compared to mild/moderate cases. We further studied MMP-1 enzymatic activity and multiple endothelial cell (EC) activation markers (soluble forms of CD146, intercellular adhesion molecule 1 [ICAM-1], and vascular cell adhesion molecule 1 [VCAM-1]) and found that they were highly dysregulated in COVID-19 patients.Conclusions: COVID-19 patients have a unique inflammatory profile, and excessive MMP-1 and hyperactivation of ECs are associated with the severity of COVID-19. [ABSTRACT FROM AUTHOR]

Determining cell types by single-cell transcriptomics data is fundamental for downstream analysis. However, cell clustering and data imputation still face the computation challenges, due to the high dropout rate, sparsity and dimensionality of single-cell data. Although some deep learning based solutions have been proposed to handle these challenges, they still can not leverage gene attribute information and cell topology in a sensible way to explore the consistent clustering. In this paper, we present scDeepFC, a deep information fusion-based single-cell data clustering method for cell clustering and data imputation. Specifically, scDeepFC uses a deep auto-encoder (DAE) network and a deep graph convolution network to embed high-dimensional gene attribute information and high-order cell–cell topological information into different low-dimensional representations, and then fuses them to generate a more comprehensive and accurate consensus representation via a deep information fusion network. In addition, scDeepFC integrates the zero-inflated negative binomial (ZINB) into DAE to model the dropout events. By jointly optimizing the ZINB loss and cell graph reconstruction loss, scDeepFC generates a salient embedding representation for clustering cells and imputing missing data. Extensive experiments on real single-cell datasets prove that scDeepFC outperforms other popular single-cell analysis methods. Both the gene attribute and cell topology information can improve the cell clustering. [ABSTRACT FROM AUTHOR]

Graph products have been extensively applied to model complex networks with striking properties observed in real-world complex systems. In this paper, we study the hitting times for random walks on a class of graphs generated iteratively by edge corona product. We first derive recursive solutions to the eigenvalues and eigenvectors of the normalized adjacency matrix associated with the graphs. Based on these results, we further obtain interesting quantities about hitting times of random walks, providing iterative formulas for two-node hitting time, as well as closed-form expressions for the Kemeny's constant defined as a weighted average of hitting times over all node pairs, as well as the arithmetic mean of hitting times of all pairs of nodes. [ABSTRACT FROM AUTHOR]

Summary MitoFlex is a linux-based mitochondrial genome analysis toolkit, which provides a complete workflow of raw data filtering, de novo assembly, mitochondrial genome identification and annotation for animal High Throughput Sequencing data. The overall performance was compared between MitoFlex and its analogue MitoZ, in terms of protein-coding gene recovery, memory consumption and processing speed. Availabilityand implementation MitoFlex is available at https://github.com/Prunoideae/MitoFlex under GPLv3 license. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The advent of single-cell RNA sequencing (scRNA-seq) technologies has enabled gene expression profiling at the single-cell resolution, thereby enabling the quantification and comparison of transcriptional variability among individual cells. Although alterations in transcriptional variability have been observed in various biological states, statistical methods for quantifying and testing differential variability between groups of cells are still lacking. To identify the best practices in differential variability analysis of single-cell gene expression data, we propose and compare 12 statistical pipelines using different combinations of methods for normalization, feature selection, dimensionality reduction and variability calculation. Using high-quality synthetic scRNA-seq datasets, we benchmarked the proposed pipelines and found that the most powerful and accurate pipeline performs simple library size normalization, retains all genes in analysis and uses denSNE-based distances to cluster medoids as the variability measure. By applying this pipeline to scRNA-seq datasets of COVID-19 and autism patients, we have identified cellular variability changes between patients with different severity status or between patients and healthy controls. [ABSTRACT FROM AUTHOR]

SUMMARY: The accuracy and sampling rate of a coseismic displacement and velocity waveform can be improved by fusing Global Navigation Satellite System (GNSS) and strong motion (SM) sensor data with a multirate Kalman filter. However, many studies have shown that the noise in GNSS coseismic waveforms includes coloured noise, and it is challenging to obtain proper GNSS and SM fusion results if the GNSS coloured noise is not accurately represented. In this paper, we propose a coloured noise multirate Kalman filter, which uses a stochastic model for modelling the GNSS coloured noise to achieve an accurate fusion of data from GNSS and SM for different sampling rates. In addition, we also propose an estimation method for the multirate Kalman filter stochastic model under coloured noise to achieve the optimal adaptive fusion of GNSS and SM data. After the reliability of the proposed method was confirmed using Monte Carlo simulations and earthquake engineering data tests, the proposed method was applied to data collected from the 2019 Mw 7.1 Ridgecrest earthquake and 2016 Mw 7.8 Kaikoura earthquake. The test results show that the proposed method can effectively fuse GNSS and SM data and accurately obtain broadband coseismic displacement and velocity waveforms. [ABSTRACT FROM AUTHOR]

For the case with a single causal variable, Dawid et al. (2014) defined the probability of causation, and Pearl (2000) defined the probability of necessity to assess the causes of effects. For a case with multiple causes that could affect each other, this paper defines the posterior total and direct causal effects based on the evidence observed for post-treatment variables, which could be viewed as measurements of causes of effects. Posterior causal effects involve the probabilities of counterfactual variables. Thus, as with the probability of causation, the probability of necessity and direct causal effects, the identifiability of posterior total and direct causal effects requires more assumptions than the identifiability of traditional causal effects conditional on pre-treatment variables. We present assumptions required for the identifiability of posterior causal effects and provide identification equations. Further, when the causal relationships between multiple causes and an endpoint can be depicted by causal networks, we can simplify both the required assumptions and the identification equations of the posterior total and direct causal effects. Finally, using numerical examples, we compare the posterior total and direct causal effects with other measures for evaluating the causes of effects and the population attributable risks. [ABSTRACT FROM AUTHOR]

J Am Chem Soc 2018; 140: 12434 - 41. 10.1021/jacs.8b05206 Crossref Search ADS PubMed 10 Kim S, Ju M, Lee J et al. J Am Chem Soc 2019; 141: 2508 - 15. 10.1021/jacs.8b12428 Crossref Search ADS PubMed 4 Wang R, Lan K, Chen Z et al. Graph: Figure 1. class="chapter-para">Schematic illustration of the (A) micelle-guided self-assembly strategy for 2D mesoporous materials and (B) the typical interfaces for 2D self-assembly, including gas-liquid, liquid-liquid and solid-liquid interfaces. [Extracted from the article]

Comment on: 'Eczematous drug eruption in patients with psoriasis under anti-interleukin-17A: does interleukin-22 play a key role? Paradoxical eczema in patients with psoriasis receiving biologics: a case series. Eczematous drug eruption in patients with psoriasis under anti-interleukin-17A: does interleukin-22 play a key role?. [Extracted from the article]

To develop and validate a nomogram incorporating circulating tumour cell counts (CTCs) and the ultrasomics signatures of contrast‐enhancement ultrasound (CEUS) for predicting postoperative early recurrence (ER) of HCC after radical treatment. Methods: Between December 2017 and December 2018, 153 HCC patients (134 males and 19 females; mean age, 56.0 ± 10.2 years; range, 28–78 years) treated with radical therapy were enrolled in our retrospective study and were divided into a training cohort (n = 107) and a validation cohort (n = 46). All patients underwent preoperative CTC tests and CEUS examinations before treatment. The ultrasomics signature was extracted and built from CEUS images. Univariate and multivariate logistic regression analyses were used to identify the significant variables related to ER, which were then combined to build a predictive nomogram. The performance of the nomogram was evaluated by its discrimination, calibration and clinical utility. The predictive model was further evaluated in the internal validation cohort. Results: HBV DNA, serum AFP level, CTC status, tumour size and ultrasomics score were identified as independent predictors associated with ER (all p < 0.05). Multivariable logistic regression analysis showed that the CTC status (OR = 7.02 [95% CI, 2.07 to 28.38], p = 0.003) and ultrasomics score (OR = 148.65 [95% CI, 25.49 to 1741.72], p < 0.001) were independent risk factors for ER. The nomogram based on ultrasomics score, CTC status, serum AFP level and tumour size exhibited C‐indexes of 0.933 (95% CI, 0.878 to 0.988) and 0.910 (95% CI, 0.765 to 1.055) in the training and validation cohorts, respectively, fitting well in calibration curves. Decision curve analysis further confirmed the clinical usefulness of the nomogram. Conclusion: The nomogram incorporating CTC, ultrasomics features and independent clinical risk factors achieved satisfactory preoperative prediction of ER in HCC patients after radical treatment. Advances in knowledge: 1. CTC status and ultrasomics score were identified as independent predictors associated with ER of HCC after radical treatment. 2. The nomogram constructed by ultrasomics score generated by 17 ultrasomics features, combined with CTCs and independent clinical risk factors such as AFP and tumour size. 3. The nomogram exhibited satisfactory discriminative power, and could be clinically useful in the preoperative prediction of ER after radical treatment in HCC patients. [ABSTRACT FROM AUTHOR]

To develop and validate a nomogram incorporating circulating tumour cell counts (CTCs) and the ultrasomics signatures of contrast‐enhancement ultrasound (CEUS) for predicting postoperative early recurrence (ER) of HCC after radical treatment. Methods: Between December 2017 and December 2018, 153 HCC patients (134 males and 19 females; mean age, 56.0 ± 10.2 years; range, 28–78 years) treated with radical therapy were enrolled in our retrospective study and were divided into a training cohort (n = 107) and a validation cohort (n = 46). All patients underwent preoperative CTC tests and CEUS examinations before treatment. The ultrasomics signature was extracted and built from CEUS images. Univariate and multivariate logistic regression analyses were used to identify the significant variables related to ER, which were then combined to build a predictive nomogram. The performance of the nomogram was evaluated by its discrimination, calibration and clinical utility. The predictive model was further evaluated in the internal validation cohort. Results: HBV DNA, serum AFP level, CTC status, tumour size and ultrasomics score were identified as independent predictors associated with ER (all p < 0.05). Multivariable logistic regression analysis showed that the CTC status (OR = 7.02 [95% CI, 2.07 to 28.38], p = 0.003) and ultrasomics score (OR = 148.65 [95% CI, 25.49 to 1741.72], p < 0.001) were independent risk factors for ER. The nomogram based on ultrasomics score, CTC status, serum AFP level and tumour size exhibited C‐indexes of 0.933 (95% CI, 0.878 to 0.988) and 0.910 (95% CI, 0.765 to 1.055) in the training and validation cohorts, respectively, fitting well in calibration curves. Decision curve analysis further confirmed the clinical usefulness of the nomogram. Conclusion: The nomogram incorporating CTC, ultrasomics features and independent clinical risk factors achieved satisfactory preoperative prediction of ER in HCC patients after radical treatment. Advances in knowledge: 1. CTC status and ultrasomics score were identified as independent predictors associated with ER of HCC after radical treatment. 2. The nomogram constructed by ultrasomics score generated by 17 ultrasomics features, combined with CTCs and independent clinical risk factors such as AFP and tumour size. 3. The nomogram exhibited satisfactory discriminative power, and could be clinically useful in the preoperative prediction of ER after radical treatment in HCC patients. [ABSTRACT FROM AUTHOR]

Spatially resolved transcriptomics technologies enable the measurement of transcriptome information while retaining the spatial context at the regional, cellular or sub-cellular level. While previous computational methods have relied on gene expression information alone for clustering single-cell populations, more recent methods have begun to leverage spatial location and histology information to improve cell clustering and cell-type identification. In this study, using seven semi-synthetic datasets with real spatial locations, simulated gene expression and histology images as well as ground truth cell-type labels, we evaluate 15 clustering methods based on clustering accuracy, robustness to data variation and input parameters, computational efficiency, and software usability. Our analysis demonstrates that even though incorporating the additional spatial and histology information leads to increased accuracy in some datasets, it does not consistently improve clustering compared with using only gene expression data. Our results indicate that for the clustering of spatial transcriptomics data, there are still opportunities to enhance the overall accuracy and robustness by improving information extraction and feature selection from spatial and histology data. [ABSTRACT FROM AUTHOR]

Thickness reduction or loss of the calcareous eggshell is one of major phenotypic changes in the transition from oviparity to viviparity. Whether the reduction of eggshells in viviparous squamates is associated with specific gene losses is unknown. Taking advantage of a newly generated high‐quality genome of the viviparous Chinese crocodile lizard (Shinisaurus crocodilurus), we found that ovocleidin‐17 gene (OC‐17), which encodes an eggshell matrix protein that is essential for calcium deposition in eggshells, is not intact in the crocodile lizard genome. Only OC‐17 transcript fragments were found in the oviduct transcriptome, and no OC‐17 peptides were identified in the eggshell proteome of crocodile lizards. In contrast, OC‐17 was present in the eggshells of the oviparous Mongolia racerunner (Eremias argus). Although the loss of OC‐17 is not common in viviparous species, viviparous squamates show fewer intact eggshell‐specific proteins than oviparous squamates. Our study implies that functional loss of eggshell‐matrix protein genes may be involved in the reduction of eggshells during the transition from oviparity to viviparity in the crocodile lizard. [ABSTRACT FROM AUTHOR]

Plant senescence, as a highly integrated developmental stage, involves functional degeneration and nutrient redistribution. NAM/ATAF1/CUC (NAC) transcription factors orchestrate various senescence-related signals and mediate the fine-tuning underlying plant senescence. Previous data revealed that knockout of either NtNAC028 or NtNAC080 leads to delayed leaf senescence in tobacco (Nicotiana tabacum), which implies that NtNAC028 and NtNAC080 play respective roles in the regulation of leaf senescence, although they share 91.87% identity with each other. However, the mechanism underlying NtNAC028- and NtNAC080-regulated leaf senescence remains obscure. Here, we determined that NtNAC028 and NtNAC080 activate a putative jasmonic acid (JA) biosynthetic gene, NtLOX3 , and enhance the JA level in vivo. We found that NtNAC028 and NtNAC080 interact with each other and themselves through their NA-terminal region. Remarkably, only the dimerization between NtNAC028 and NtNAC080 stimulated the transcriptional activation activity, but not the DNA binding activity of this heterodimer on NtLOX3. Metabolome analysis indicated that overexpression of either NtNAC028 or NtNAC080 augments both biosynthesis and degradation of nicotine in the senescent stages. Thus, we conclude that NtNAC028 cooperates with NtNAC080 and forms a heterodimer to enhance NtLOX3 expression and JA biosynthesis to trigger the onset of leaf senescence and impact secondary metabolism in tobacco. [ABSTRACT FROM AUTHOR]

Due to their uncontrollable assembly and crystallization process, the synthesis of mesoporous metal oxide single crystals remains a formidable challenge. Herein, we report the synthesis of single-crystal-like mesoporous Li2TiSiO5 by using soft micelles as templates. The key lies in the atomic-scale self-assembly and step-crystallization processes, which ensure the formation of single-crystal-like mesoporous Li2TiSiO5 microparticles via an oriented attachment growth mechanism under the confinement of an in-situ formed carbon matrix. The mesoporous Li2TiSiO5 anode achieves a superior rate capability (148 mAh g−1 at 5.0 A g−1) and outstanding long-term cycling stability (138 mAh g−1 after 3000 cycles at 2.0 A g−1) for lithium storage as a result of the ultrafast Li+ diffusion caused by penetrating mesochannels and nanosized crystal frameworks (5–10 nm). In comparison, bulk Li2TiSiO5 exhibits poor rate capability and cycle performance due to micron-scale diffusion lengths. This method is very simple and reproducible, heralding a new way of designing and synthesizing mesoporous single crystals with controllable frameworks and chemical functionalities. [ABSTRACT FROM AUTHOR]

Solid solutions are ubiquitous in metals and alloys. Local chemical ordering (LCO) is a fundamental sub-nano/nanoscale process that occurs in many solid solutions and can be used as a microstructure to optimize strength and ductility. However, the formation of LCO has not been fully elucidated, let alone how to provide efficient routes for designing LCO to achieve synergistic effects on both superb strength and ductility. Herein, we propose the formation and control of LCO in negative enthalpy alloys. With engineering negative enthalpy in solid solutions, genetic LCO components are formed in negative enthalpy refractory high-entropy alloys (RHEAs). In contrast to conventional 'trial-and-error' approaches, the control of LCO by using engineering negative enthalpy in RHEAs is instructive and results in superior strength (1160 MPa) and uniform ductility (24.5%) under tension at ambient temperature, which are among the best reported so far. LCO can promote dislocation cross-slip, enhancing the interaction between dislocations and their accumulation at large tensile strains; sustainable strain hardening can thereby be attained to ensure high ductility of the alloy. This work paves the way for new research fields on negative enthalpy solid solutions and alloys for the synergy of strength and ductility as well as new functions. [ABSTRACT FROM AUTHOR]

Background The impact of SARS-CoV-2 variants of concern (VOCs) on disease severity is unclear. In this retrospective study, we compared the outcomes of patients infected with B.1.1.7, B.1.351, and B.1.617.2 with wild-type strains from early 2020. Methods National surveillance data from January to May 2021 were obtained and outcomes in relation to VOCs were explored. Detailed patient-level data from all patients with VOC infection admitted to our center between December 2020 and May 2021 were analyzed. Clinical outcomes were compared with a cohort of 846 patients admitted from January to April 2020. Results A total of 829 patients in Singapore in the study period were infected with these 3 VOCs. After adjusting for age and sex, B.1.617.2 was associated with higher odds of oxygen requirement, intensive care unit admission, or death (adjusted odds ratio [aOR], 4.90; 95% confidence interval [CI]: 1.43-30.78). Of these patients, 157 were admitted to our center. After adjusting for age, sex, comorbidities, and vaccination, the aOR for pneumonia with B.1.617.2 was 1.88 (95% CI:.95-3.76) compared with wild-type. These differences were not seen with B.1.1.7 and B.1.351. Vaccination status was associated with decreased severity. B.1.617.2 was associated with significantly lower polymerase chain reaction cycle threshold (Ct) values and longer duration of Ct value ≤30 (median duration 18 days for B.1.617.2, 13 days for wild-type). Conclusions B.1.617.2 was associated with increased severity of illness, and with lower Ct values and longer viral shedding. These findings provide impetus for the rapid implementation of vaccination programs. [ABSTRACT FROM AUTHOR]

Recently, an astrocytic aquaporin 4-dependent drainage system, that is, the glymphatic system, has been identified in the live murine and human brain. Growing evidence suggests that glymphatic function is impaired in patients with several neurodegenerative diseases, including Alzheimer's and Parkinson's disease. As the third most common neurodegenerative disease, although animal studies have indicated that early glymphatic dysfunction is likely an important pathological mechanism underpinning amyotrophic lateral sclerosis (ALS), no available study has been conducted to thoroughly assess glymphatic function in vivo in ALS patients to date, particularly in patients with early-stage ALS. Thus, using diffusion tensor imaging analysis along the perivascular space (ALPS) index, an approximate measure of glymphatic function in vivo , we aimed to explore whether glymphatic function is impaired in patients with patients with early-stage ALS, and the diagnostic performance of the ALPS index in distinguishing between patients with early-stage ALS and healthy subjects. We also aimed to identify the relationships between glymphatic dysfunction and clinical disabilities and sleep problems in patients with early-stage ALS. In this retrospective study, King's Stage 1 ALS patients were defined as patients with early-stage ALS. We enrolled 56 patients with early-stage ALS and 32 age- and sex-matched healthy control subjects. All participants completed clinical screening, sleep assessment and ALPS index analysis. For the sleep assessment, the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and polysomnography were used. Compared with healthy control subjects, patients with early-stage ALS had a significantly lower ALPS index after family-wise error correction (P < 0.05). Moreover, receiver operating characteristic analysis showed that the area under the curve for the ALPS index was 0.792 (95% confidence interval 0.700–0.884). Partial correlation analyses showed that the ALPS index was significantly correlated with clinical disability and sleep disturbances in patients with early-stage ALS. Multivariate analysis showed that sleep efficiency (r = 0.419, P = 0.002) and periodic limb movements in sleep index (r = −0.294, P = 0.017) were significant predictive factors of the ALPS index in patients with early-stage ALS. In conclusion, our study continues to support an important role for glymphatic dysfunction in ALS pathology, and we provide additional insights into the early diagnostic value of glymphatic dysfunction and its correlation with sleep disturbances in vivo in patients with early-stage ALS. Moreover, we suggest that early improvement of glymphatic function may be a promising strategy for slowing the neurodegenerative process in ALS. Future studies are needed to explore the diagnostic and therapeutic value of glymphatic dysfunction in individuals with presymptomatic-stage neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Cold acclimation is a crucial biological process that enables conifers to overwinter safely. The late embryogenesis abundant (LEA) protein family plays a pivotal role in enhancing freezing tolerance during this process. Despite its importance, the identification, molecular functions and regulatory networks of the LEA protein family have not been extensively studied in conifers or gymnosperms. Pinus tabuliformis , a conifer with high ecological and economic values and with high-quality genome sequence, is an ideal candidate for such studies. Here, a total of 104 LEA genes were identified from P. tabuliformis , and we renamed them according to their subfamily group: PtLEA1 – PtLEA92 (group LEA1–LEA6), PtSMP1 – PtSMP6 (group seed maturation protein) and PtDHN1 – PtDHN6 (group Dehydrin). While the sequence structure of P. tabuliformis   LEA genes are conserved, their physicochemical properties exhibit unique characteristics within different subfamily groupings. Notably, the abundance of low-temperature responsive elements in PtLEA genes was observed. Using annual rhythm and temperature gradient transcriptome data, PtLEA22 was identified as a key gene that responds to low-temperature induction while conforming to the annual cycle of cold acclimation. Overexpression of PtLEA22 enhanced Arabidopsis freezing tolerance. Furthermore, several transcription factors potentially co-expressed with PtLEA22 were validated using yeast one-hybrid and dual-luciferase assays, revealing that PtDREB1 could directly bind PtLEA22 promoter to positively regulate its expression. These findings reveal the genome-wide characterization of P. tabuliformis   LEA genes and their importance in the cold acclimation, while providing a theoretical basis for studying the molecular mechanisms of cold acclimation in conifers. [ABSTRACT FROM AUTHOR]

Background Previously treated (ie, recurrent) tuberculosis (TB) cases account for approximately 7%–8% of incident TB globally and in Singapore. Molecular fingerprinting has enabled the differentiation of these patients into relapsed or reinfection cases. Methods Patient demographics, disease characteristics, and treatment information were obtained from the national TB notification registry and TB Control Unit. We performed a retrospective, case-control study to evaluate factors associated with recurrent TB disease in Singapore citizens and permanent residents with culture-positive TB from 2006 to 2013 and who developed a second episode of culture-positive TB up to 2016 using multivariable logistic regression analyses. Results Ninety-one cases with culture-positive first and recurrent TB disease episodes were identified. Recurrent TB was associated with age ≥60 years (adjusted odds ratio [aOR], 1.98 [95% confidence interval {CI}, 1.09–3.61), male sex (aOR, 2.29 [95% CI, 1.22–4.51]), having concomitant pulmonary and extrapulmonary TB (aOR, 3.10 [95% CI, 1.59–6.10]) and extrapulmonary TB alone (aOR, 3.82 [95% CI, 1.12–13.31]), and was less likely in non-Malays (aOR, 0.52 [95% CI,.27–.99]). DNA fingerprinting results for both episodes in 49 cases differentiated these into 28 relapsed and 21 reinfection cases. Relapse was associated with having concomitant pulmonary and extrapulmonary TB (aOR, 9.24 [95% CI, 2.50–42.42]) and positive sputum acid-fast bacilli smear (aOR, 3.95 [95% CI, 1.36–13.10]). Conclusions Relapse and reinfection contributed to 57% and 43%, respectively, of recurrent TB in Singapore. Our study highlights the underappreciated association of concomitant pulmonary and extrapulmonary TB as a significant risk factor for disease relapse. [ABSTRACT FROM AUTHOR]

Receptor-like kinases (RLKs) are the most important class of cell surface receptors, and play crucial roles in plant development and stress responses. However, few studies have been reported about the biofunctions of RLKs in leaf senescence. Here, we characterized a novel Arabidopsis RLK-encoding gene, SENESCENCE-RELATED RECEPTOR KINASE 1 (SENRK1), which was significantly down-regulated during leaf senescence. Notably, the loss-of-function senrk1 mutants displayed an early leaf senescence phenotype, while overexpression of SENRK1 significantly delayed leaf senescence, indicating that SENRK1 negatively regulates age-dependent leaf senescence in Arabidopsis. Furthermore, the senescence-promoting transcription factor WRKY53 repressed the expression of SENRK1. While the wrky53 mutant showed a delayed senescence phenotype as previously reported, the wrky53 senrk1-1 double mutant exhibited precocious leaf senescence, suggesting that SENRK1 functions downstream of WRKY53 in regulating age-dependent leaf senescence in Arabidopsis. [ABSTRACT FROM AUTHOR]