Low-Dimensional Gradient Helps Out-of-Distribution Detection.

Detecting out-of-distribution (OOD) samples is essential for ensuring the reliability of deep neural networks (DNNs) in real-world scenarios. While previous research has predominantly investigated the disparity between in-distribution (ID) and OOD data through forward information analysis, the discrepancy in parameter gradients during the backward process of DNNs has received insufficient attention. Existing studies on gradient disparities mainly focus on the utilization of gradient norms, neglecting the wealth of information embedded in gradient directions.

Clinicopathological and immune characterization of mismatch repair deficient endocervical adenocarcinoma.

Endocervical adenocarcinoma (ECA) is reported increasingly often in young women, and this aggressive disease lacks effective methods of targeted therapy. Since mismatch repair deficiency (dMMR) is an important biomarker for predicting response to immune checkpoint inhibitors, it is important to investigate the clinicopathological features and immune microenvironment of dMMR ECAs. We assessed 617 ECAs from representative tissue microarray sections, gathered clinicopathologic information, reviewed histological characteristics, and performed immunohistochemical staining for MMR, programmed cell death 1 (PD-L1), and other immune markers.

Establishment of an In Bacterio Assay for the Assessment of Carbon Storage Regulator A (CsrA) Inhibitors.

Polymicrobial infections involving various combinations of microorganisms, such as Escherichia, Pseudomonas, or Yersinia, can lead to acute and chronic diseases in for example the gastrointestinal and respiratory tracts. Our aim is to modulate microbial communities by targeting the posttranscriptional regulator system called carbon storage regulator A (CsrA) (or also repressor of secondary metabolites (RsmA)). In previous studies, we identified easily accessible CsrA binding scaffolds and macrocyclic CsrA binding peptides through biophysical screening and phage display technology.

Phage display-based discovery of cyclic peptides against the broad spectrum bacterial anti-virulence target CsrA.

Small macrocyclic peptides are promising candidates for new anti-infective drugs. To date, such peptides have been poorly studied in the context of anti-virulence targets. Using phage display and a self-designed peptide library, we identified a cyclic heptapeptide that can bind the carbon storage regulator A (CsrA) from Yersinia pseudotuberculosis and displace bound RNA.

First Small-Molecule Inhibitors Targeting the RNA-Binding Protein IGF2BP2/IMP2 for Cancer Therapy.

The RNA-binding protein IGF2BP2/IMP2/VICKZ2/p62 is overexpressed in several tumor entities, promotes tumorigenesis and tumor progression, and has been suggested to worsen the disease outcome. The aim of this study is to (I) validate IMP2 as a potential target for colorectal cancer, (II) set up a screening assay for small-molecule inhibitors of IMP2, and (III) test the biological activity of the obtained hit compounds. Analyses of colorectal and liver cancer gene expression data showed reduced survival in patients with a high IMP2 expression and in patients with a higher IMP2 expression in advanced tumors.

The Role of Conspiracy Theories in the Spread of COVID-19 across the United States.

The outbreak of coronavirus disease 2019 (COVID-19) inspires various conspiracy theories, which could divert public attention, alter human behaviors, and consequently affect the spread of the pandemic. Here we estimate the relation of the online attention on COVID-19-related conspiracy theories to human mobility, as well as to the numbers of confirmed COVID-19 cases, during 14 March 2020 to 28 August 2020. We observe that the online attention to COVID-19 conspiracy theories is significantly and negatively related to human mobility, but its negative impact is noticeably less than those of the attention to official information and personal protection measures.

Collaborative Penalized Least Squares for Background Correction of Multiple Raman Spectra.

Although Raman spectroscopy has been widely used as a noninvasive analytical tool in various applications, backgrounds in Raman spectra impair its performance in quantitative analysis. Many algorithms have been proposed to separately correct the background spectrum by spectrum. However, in real applications, there are commonly multiple spectra collected from the close locations of a sample or from the same analyte with different concentrations.