Complementary Advantages of ChatGPTs and Human Readers in Reasoning: Evidence from English Text Reading Comprehension

ChatGPT has shown its great power in text processing, including its reasoning ability from text reading. However, there has not been any direct comparison between human readers and ChatGPT in reasoning ability related to text reading. This study was undertaken to investigate how ChatGPTs (i.e., ChatGPT and ChatGPT Plus) and Chinese senior school students as ESL learners exhibited their reasoning ability from English narrative texts. Additionally, we compared the two ChatGPTs in the reasoning performances when commands were updated elaborately. The whole study was composed of three reasoning tests: Test 1 for commonsense inference, Test 2 for emotional inference, and Test 3 for causal inference. The results showed that in Test 1, the students outdid the two ChatGPT versions in local-culture-related inferences but performed worse than the chatbots in daily-life inferences. In Test 2, ChatGPT Plus excelled whereas ChatGPT lagged behind in accuracy. In association with both accuracy and frequency of correct responses, the students were inferior to the two chatbots. Compared with ChatGPTs' better performance in positive emotions, the students showed their superiority in inferring negative emotions. In Test 3, the students demonstrated better logical analysis, outdoing both chatbots. In updating command condition, ChatGPT Plus displayed good causal reasoning ability while ChatGPT kept unchanged. Our study reveals that human readers and ChatGPTs have their respective advantages and disadvantages in drawing inferences from text reading comprehension, unlocking a complementary relationship in text-based reasoning

Prosaposin down-modulation decreases metastatic prostate cancer cell adhesion, migration, and invasion

<p>Abstract</p> <p>Background</p> <p>Factors responsible for invasive and metastatic progression of prostate cancer (PCa) remain largely unknown. Previously, we reported cloning of prosaposin (PSAP) and its genomic amplification and/or overexpression in several androgen-independent metastatic PCa cell lines and lymph node metastases. PSAP is the lysosomal precursor of saposins, which serve as activators for lysosomal hydrolases involved in the degradation of ceramide (Cer) and other sphingolipids.</p> <p>Results</p> <p>Our current data show that, in metastatic PCa cells, stable down-modulation of PSAP by RNA-interference via a lysosomal proteolysis-dependent pathway decreased β_1A-integrin expression, its cell-surface clustering, and adhesion to basement membrane proteins; led to disassembly of focal adhesion complex; and decreased phosphorylative activity of focal adhesion kinase and its downstream adaptor molecule, paxillin. Cathepsin D (CathD) expression and proteolytic activity, migration, and invasion were also significantly decreased in PSAP knock-down cells. Transient-transfection studies with β_1Aintegrin- or CathD-siRNA oligos confirmed the cause and effect relationship between PSAP and CathD or PSAP and Cer-β_1Aintegrin, regulating PCa cell migration and invasion.</p> <p>Conclusion</p> <p>Our findings suggest that by a coordinated regulation of Cer levels, CathD and β_1A-integrin expression, and attenuation of "inside-out" integrin-signaling pathway, PSAP is involved in PCa invasion and therefore might be used as a molecular target for PCa therapy.</p

A new unsupervised pseudo-siamese network with two filling strategies for image denoising and quality enhancement

Digital image noise may be introduced during acquisition, transmission, or processing and affects readability and image processing effectiveness. The accuracy of established image processing techniques, such as segmentation, recognition, and edge detection, is adversely impacted by noise. There exists an extensive body of work which focuses on circumventing such issues through digital image enhancement and noise reduction, but this work is limited by a number of constraints including the application of non-adaptive parameters, potential loss of edge detail information, and (with supervised approaches) a requirement for clean, labeled, training data. This paper, developed on the principle of Noise2Void, presents a new unsupervised learning approach incorporating a pseudo-siamese network. Our method enables image denoising without the need for clean images or paired noise images, instead requiring only noise images. Two independent branches of the network utilize different filling strategies, namely zero filling and adjacent pixel filling. Then, the network employs a loss function to improve the similarity of the results in the two branches. We also modify the Efficient Channel Attention module to extract more diverse features and improve performance on the basis of global average pooling. Experimental results show that compared with traditional methods, the pseudo-siamese network has a greater improvement on the ADNI dataset in terms of quantitative and qualitative evaluation. Our method therefore has practical utility in cases where clean images are difficult to obtain

Electrochemical properties of roots determine antibiotic adsorption on roots

The adsorption behaviors and transfer pathways of antibiotics in plant–soil system are greatly influenced by the electrochemical properties of both soil particles and plant roots. However, the effects of roots electrochemical properties on antibiotic adsorption are largely unknown. Here, the fresh soybean, maize, and wheat roots with different electrochemical properties were obtained from hydroponic cultivation, and the adsorption processes and mechanisms of doxycycline, tetracycline, sulfadiazine, and norfloxacin on roots under various environmental conditions were investigated. Results showed that the adsorption amount of antibiotics on roots increased with the initial concentration of antibiotics. The coexisting low–molecular weight organic acids and anions inhibited the antibiotic adsorption on roots. The soybean roots performed strong adsorption ability compared with the maize and wheat roots driven by the variations in root electrochemical properties. This study demonstrates the significance of electrochemical interactions between antibiotics and roots in plant–soil system and can contribute to the more accurate risk assessment and effective pollution control of antibiotics

Integrating single-cell and bulk transcriptomic analyses to develop a cancer-associated fibroblast-derived biomarker for predicting prognosis and therapeutic response in breast cancer

BackgroundCancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA.MethodsCAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA.ResultsIntegrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA.ConclusionsA novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA

Patterns of Convergence and Divergence Between Bipolar Disorder Type I and Type II: Evidence From Integrative Genomic Analyses

Aim: Genome-wide association studies (GWAS) analyses have revealed genetic evidence of bipolar disorder (BD), but little is known about the genetic structure of BD subtypes. We aimed to investigate the genetic overlap and distinction of bipolar type I (BD I) & type II (BD II) by conducting integrative post-GWAS analyses. Methods: We utilized single nucleotide polymorphism (SNP)-level approaches to uncover correlated and distinct genetic loci. Transcriptome-wide association analyses (TWAS) were then approached to pinpoint functional genes expressed in specific brain tissues and blood. Next, we performed cross-phenotype analysis, including exploring the potential causal associations between two BD subtypes and lithium responses and comparing the difference in genetic structures among four different psychiatric traits. Results: SNP-level evidence revealed three genomic loci, SLC25A17, ZNF184, and RPL10AP3, shared by BD I and II, and one locus (MAD1L1) and significant gene sets involved in calcium channel activity, neural and synapsed signals that distinguished two subtypes. TWAS data implicated different genes affecting BD I and II through expression in specific brain regions (nucleus accumbens for BD I). Cross-phenotype analyses indicated that BD I and II share continuous genetic structures with schizophrenia and major depressive disorder, which help fill the gaps left by the dichotomy of mental disorders. Conclusion: These combined evidences illustrate genetic convergence and divergence between BD I and II and provide an underlying biological and trans-diagnostic insight into major psychiatric disorders

DC-SIGN as an attachment factor mediates Japanese encephalitis virus infection of human dendritic cells via interaction with a single high-mannose residue of viral E glycoprotein

AbstractThe skin-resident dendritic cells (DCs) are thought to be the first defender to encounter incoming viruses and likely play a role in Japanese encephalitis virus (JEV) early infection. In the current study, following the demonstration of JEV productive infection in DCs, we revealed that the interaction between JEV envelope glycoprotein (E glycoprotein) and DC-SIGN was important for such infection as evidenced by antibody neutralization and siRNA knockdown experiments. Moreover, the high-mannose N-linked glycan at N154 of E glycoprotein was shown to be crucial for JEV binding to DC-SIGN and subsequent internalization, while mutation of DC-SIGN internalization motif did not affect JEV uptake and internalization. These data together suggest that DC-SIGN functions as an attachment factor rather than an entry receptor for JEV. Our findings highlight the potential significance of DC-SIGN in JEV early infection, providing a basis for further understanding how JEV exploits DC-SIGN to gain access to dendritic cells

Crucial Role of miR-433 in Regulating Cardiac Fibrosis

Dysregulation of microRNAs has been implicated in many cardiovascular diseases including fibrosis. Here we report that miR-433 was consistently elevated in three models of heart disease with prominent cardiac fibrosis, and was enriched in fibroblasts compared to cardiomyocytes. Forced expression of miR-433 in neonatal rat cardiac fibroblasts increased proliferation and their differentiation into myofibroblasts as determined by EdU incorporation, α-SMA staining, and expression levels of fibrosis-associated genes. Conversely, inhibition of miR-433 exhibited opposite results. AZIN1 and JNK1 were identified as two target genes of miR-433. Decreased level of AZIN1 activated TGF-β1 while down-regulation of JNK1 resulted in activation of ERK and p38 kinase leading to Smad3 activation and ultimately cardiac fibrosis. Importantly, systemic neutralization of miR-433 or adeno-associated virus 9 (AAV9)-mediated cardiac transfer of a miR-433 sponge attenuated cardiac fibrosis and ventricular dysfunction following myocardial infarction. Thus, our work suggests that miR-433 is a potential target for amelioration of cardiac fibrosis

Detection of early-universe gravitational-wave signatures and fundamental physics

Detection of a gravitational-wave signal of non-astrophysical origin would be a landmark discovery, potentially providing a significant clue to some of our most basic, big-picture scientific questions about the Universe. In this white paper, we survey the leading early-Universe mechanisms that may produce a detectable signal—including inflation, phase transitions, topological defects, as well as primordial black holes—and highlight the connections to fundamental physics. We review the complementarity with collider searches for new physics, and multimessenger probes of the large-scale structure of the Universe.Peer reviewe

Detection of early-universe gravitational-wave signatures and fundamental physics

Detection of a gravitational-wave signal of non-astrophysical origin would be a landmark discovery, potentially providing a significant clue to some of our most basic, big-picture scientific questions about the Universe. In this white paper, we survey the leading early-Universe mechanisms that may produce a detectable signal—including inflation, phase transitions, topological defects, as well as primordial black holes—and highlight the connections to fundamental physics. We review the complementarity with collider searches for new physics, and multimessenger probes of the large-scale structure of the Universe.Peer reviewe