A novel coronavirus (SCoV) is the etiological agent of severe acute respiratory syndrome (SARS). SCoV-like viruses were isolated from Himalayan palm civets found in a live-animal market in Guangdong, ...China. Evidence of virus infection was also detected in other animals (including a raccoon dog, Nyctereutes procyonoides) and in humans working at the same market. All the animal isolates retain a 29-nucleotide sequence that is not found in most human isolates. The detection of SCoV-like viruses in small, live wild mammals in a retail market indicates a route of interspecies transmission, although the natural reservoir is not known.
Deep neural networks currently provide the best quantitative models of the response patterns of neurons throughout the primate ventral visual stream. However, such networks have remained implausible ...as a model of the development of the ventral stream, in part because they are trained with supervised methods requiring many more labels than are accessible to infants during development. Here, we report that recent rapid progress in unsupervised learning has largely closed this gap. We find that neural network models learned with deep unsupervised contrastive embedding methods achieve neural prediction accuracy in multiple ventral visual cortical areas that equals or exceeds that of models derived using today's best supervised methods and that the mapping of these neural network models' hidden layers is neuroanatomically consistent across the ventral stream. Strikingly, we find that these methods produce brain-like representations even when trained solely with real human child developmental data collected from head-mounted cameras, despite the fact that these datasets are noisy and limited. We also find that semisupervised deep contrastive embeddings can leverage small numbers of labeled examples to produce representations with substantially improved error-pattern consistency to human behavior. Taken together, these results illustrate a use of unsupervised learning to provide a quantitative model of a multiarea cortical brain system and present a strong candidate for a biologically plausible computational theory of primate sensory learning.
MicroRNA (miRNA) and long non-coding RNA (lncRNA) have been demonstrated to participate in the progression of many cancers. Hepatocellular carcinoma (HCC) is one of the most common and aggressive ...malignant tumors worldwide, while the molecular mechanisms underlying HCC tumorigenesis are not completely clear. In this study, we showed that miR-92b was significantly upregulated in tumor tissue and plasma of HCC patients, and its expression level was highly correlated with gender and microvascular invasion. Functionally, miR-92b could promote cell proliferation and metastasis of HCC in vitro and in vivo. Mechanistic investigations suggested that Smad7, which exhibited an inverse relationship with miR-92b expression in HCC, was a direct target of miR-92b and could reverse its effects on HCC tumorigenesis. Furthermore, long non-coding RNA (lncRNA) X-inactive specific transcript (XIST) and miR-92b could directly interact with and repress each other, and XIST could inhibit HCC cell proliferation and metastasis by targeting miR-92b. Taken together, our study not only revealed for the first time the importance of XIST/miR-92b/Smad7 signaling axis in HCC progression but also suggested the potential value of miR-92b as a biomarker in the clinical diagnosis and treatment of HCC.
Studies of the mouse visual system have revealed a variety of visual brain areas that are thought to support a multitude of behavioral capacities, ranging from stimulus-reward associations, to ...goal-directed navigation, and object-centric discriminations. However, an overall understanding of the mouse’s visual cortex, and how it supports a range of behaviors, remains unknown. Here, we take a computational approach to help address these questions, providing a high-fidelity quantitative model of mouse visual cortex and identifying key structural and functional principles underlying that model’s success. Structurally, we find that a comparatively shallow network structure with a low-resolution input is optimal for modeling mouse visual cortex. Our main finding is functional—that models trained with task-agnostic, self-supervised objective functions based on the concept of contrastive embeddings are much better matches to mouse cortex, than models trained on supervised objectives or alternative self-supervised methods. This result is very much unlike in primates where prior work showed that the two were roughly equivalent, naturally leading us to ask the question of why these self-supervised objectives are better matches than supervised ones in mouse. To this end, we show that the self-supervised, contrastive objective builds a general-purpose visual representation that enables the system to achieve better transfer on out-of-distribution visual scene understanding and reward-based navigation tasks. Our results suggest that mouse visual cortex is a low-resolution, shallow network that makes best use of the mouse’s limited resources to create a light-weight, general-purpose visual system—in contrast to the deep, high-resolution, and more categorization-dominated visual system of primates.
Rice double-haploid (DH) lines of an indica and japonica cross were grown at nine different locations across four countries in Asia. Genotype-by-environment (G x E) interaction analysis for 11 ...growth- and grain yield-related traits in nine locations was estimated by AMMI analysis. Maximum G x E interaction was exhibited for fertility percentage number of spikelets and grain yield. Plant height was least affected by environment, and the AMMI model explained a total of 76.2% of the interaction effect. Mean environment was computed by averaging the nine environments and subsequently analyzed with other environments to map quantitative trait loci (QTL). QTL controlling the 11 traits were detected by interval analysis using mapmaker/qtl. A threshold LOD of >/=3.20 was used to identify significant QTL. A total of 126 QTL were identified for the 11 traits across nine locations. Thirty-four QTL common in more than one environment were identified on ten chromosomes. A maximum of 44 QTL were detected for panicle length, and the maximum number of common QTL were detected for days to heading detected. A single locus for plant height (RZ730-RG810) had QTL common in all ten environments, confirming AMMI results that QTL for plant height were affected the least by environment, indicating the stability of the trait. Two QTL were detected for grain yield and 19 for thousand-grain weight in all DH lines. The number of QTL per trait per location ranged from zero to four. Clustering of the QTL for different traits at the same marker intervals was observed for plant height, panicle number, panicle length and spikelet number suggesting that pleiotropism and or tight linkage of different traits could be the possible reason for the congruence of several QTL. The many QTL detected by the same marker interval across environments indicate that QTL for most traits are stable and not essentially affected by environmental factors.
To further our understanding of the genetic control of blast resistance in rice cultivar Gumei 2 and, consequently, to facilitate the utilization of this durably blast-resistant cultivar, we studied ...304 recombinant inbred lines of indica rice cross Zhong 156/Gumei 2 and a linkage map comprising 181 markers. An analysis of segregation for resistance against five isolates of rice blast suggested that one gene cluster and three additional major genes that are independently inherited are responsible for the complete resistance of Gumei 2. The gene cluster was located to chromosome 6 and includes two genes mapped previously, Pi25(t), against Chinese rice blast isolate 92-183 (race ZC15) and Pi26(t) against Philippine rice blast isolate Ca89 (lineage 4), and a gene for resistance against Philippine rice blast isolate 92330-5 (lineage 17). Of the two genes conferring resistance against the Philippine isolates V86013 (lineage 15) and C923-39 (lineage 46), we identified one as Pi26(t) and mapped the other onto the distal end of chromosome 2 where Pib is located. We used three components of partial blast resistance, percentage diseased leaf area (DLA), lesion number and lesion size, all measured in the greenhouse, to measure the degree of susceptibility to isolates Ca89 and C923-39 and subsequently identified nine and eight quantitative trait loci (QTLs), respectively. Epistasis was determined to play an important role in partial resistance against Ca89. Using DLA measured on lines susceptible in a blast nursery, we detected six QTLs. While different QTLs were detected for partial resistance to Ca89 and C923-39, respectively, most were involved in the partial resistance in the field. Our results suggest that the blast resistance in Gumei 2 is controlled by multiple major genes and minor genes with epistatic effects.
Using an ab initio method based on non-equilibrium Green's functions (NEGF) combined with density functional theory (DFT), a calculation of the transport properties of a single molecular junction ...based on 1,3-diphenylpropynylidene (PhC
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Ph) 'radical-π-radical' is performed. The obvious negative differential resistance (NDR), spin current polarisation (SCP) and dual-spin current rectification (SCR) effects in this device are obtained. The total current for magnetic parallel configuration (PC) is larger at first and then less than that for magnetic antiparallel configuration (APC) as the bias increases, which suggests the abnormal magnetoresistance (MR) effect and can be used as a molecular switch with two working voltages. The evolution of the spin-polarised transmission spectrums and the frontier molecular orbitals (MOs) with applied bias is used to explain the above interesting results. Our calculations may be helpful for designing multifunctional molecular spintronics devices in the future.
BackgroundThe COVID-19 has caused significant mortality and morbidity across the globe. Patients with cancer are especially vulnerable given their immunocompromised state. We aimed to determine the ...proportion of COVID-19 patients with cancer, their severity and mortality outcomes through a systematic review and meta-analysis (MA).MethodsSystematic review was performed through online databases, PubMed, Medline and Google Scholar, with keywords listed in the Methods section (1 November 2019–31 December 2020). Studies with clinical outcomes of at least 10 COVID-19 patients and at least one with a diagnosis of cancer were included. The studies for MA were assessed with PRISMA guidelines and appraised with Newcastle-Ottawa Scale. The data were pooled using a random-effects model using STATA software. The main outcomes were planned before data collection, including proportion of patients with cancer among COVID-19 populations, relative risk (RR) of severe outcomes and death of patients with cancer compared with general COVID-19 patients.ResultsWe identified 57 case series (63 413 patients), with 230 patients with cancer with individual patient data (IPD). We found that the pooled proportion of cancer among COVID-19 patients was 0.04 (95% CI 0.03 to 0.05, I2=97.69%, p<0.001). The pooled RR of death was 1.44 (95% CI 1.19 to 1.76) between patients with cancer and the general population with COVID-19 infection. The pooled RR of severe outcome was 1.49 (95% CI 1.18 to 1.87) between cancer and general COVID-19 patients. The presence of lung cancer and stage IV cancer did not result in significantly increased RR of severe outcome. Among the available IPD, only age and gender were associated with severe outcomes.ConclusionPatients with cancer were at a higher risk of severe and death outcomes from COVID-19 infection as compared with general COVID-19 populations. Limitations of this study include publication bias. A collaborative effort is required for a more complete database.
Head-mounted cameras have been used in developmental psychology research for more than a decade to provide a rich and comprehensive view of what infants see during their everyday experiences. ...However, variation between these devices has limited the field’s ability to compare results across studies and across labs. Further, the video data captured by these cameras to date has been relatively low-resolution, limiting how well machine learning algorithms can operate over these rich video data. Here, we provide a well-tested and easily constructed design for a head-mounted camera assembly—the BabyView—developed in collaboration with Daylight Design, LLC., a professional product design firm. The BabyView collects high-resolution video, accelerometer, and gyroscope data from children approximately 6–30 months of age via a GoPro camera custom mounted on a soft child-safety helmet. The BabyView also captures a large, portrait-oriented vertical field-of-view that encompasses both children’s interactions with objects and with their social partners. We detail our protocols for video data management and for handling sensitive data from home environments. We also provide customizable materials for onboarding families with the BabyView. We hope that these materials will encourage the wide adoption of the BabyView, allowing the field to collect high-resolution data that can link children’s everyday environments with their learning outcomes.
A linkage map consisting of 158 DNA markers were constructed by using a recombinant inbred line (RIL) population derived from the indica-indica rice cross Zhenshan 97B x Milyang 46. Quantitative ...trait loci (QTLs) conditioning grain yield and five yield component traits were determined at the one-locus and two-locus levels, and genotype-by-environment (GE) interactions were analyzed. Thirty-one QTLs were detected to have significant additive effects for yield traits, of which 12 also exhibited significant epistatic effects. Sixteen significant additive-by-additive (AA) interactions were detected, of which nine occurred between QTLs with own additive effects (M(ep)QTLs), four occurred between QTLs showing epistatic effects only (epQTLs), and three occurred between M(ep)QTLs and epQTLs. Significant GE interactions were found for six QTLs with additive effects and one AA interaction. Generally, the contributions to the phenotypic variation were higher due to QTL main effects than to epistatic effects. The detection of additive effects and AA effects of a QTL interfered with each other, indicating that the detection of QTLs with main effects, as well as the magnitude and directions of the additive effects, might vary depending on their interactions with other loci.
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