Resurgence of Chern-Simons Theory at the Trivial Flat Connection.

Some years ago, it was conjectured by the first author that the Chern-Simons perturbation theory of a 3-manifold at the trivial flat connection is a resurgent power series. We describe completely the resurgent structure of the above series (including the location of the singularities and their Stokes constants) in the case of a hyperbolic knot complement in terms of an extended square matrix (, )-series whose rows are indexed by the boundary parabolic -flat connections, including the trivial one. We use our extended matrix to describe the Stokes constants of the above series, to define explicitly their Borel transform and to identify it with state-integrals.

Exploring glioma heterogeneity through omics networks: from gene network discovery to causal insights and patient stratification.

Gliomas are primary malignant brain tumors with a typically poor prognosis, exhibiting significant heterogeneity across different cancer types. Each glioma type possesses distinct molecular characteristics determining patient prognosis and therapeutic options. This study aims to explore the molecular complexity of gliomas at the transcriptome level, employing a comprehensive approach grounded in network discovery.

Buzz pollination: A theoretical analysis via scaling invariance.

Nearly half of the bee species can perform a fascinating stereotyped behavior to collect pollen grains by vibrating flowers, known as buzz pollination. During the floral visit, these bees mechanically transfer the vibrations produced by their thoracic indirect flight muscles to the flower anther, inducing the movement of the pollen grains and leading them to be released through a small pore or slit placed at the tip of the anther in poricidal flowers. In such flowers, pollen release is affected by the vibrational behavior of buzzing bees, primarily their duration and velocity amplitude.

Integrative study of lung cancer adeno-to-squamous transition in EGFR TKI resistance identifies RAPGEF3 as a therapeutic target.

Although adeno-to-squamous transition (AST) has been observed in association with resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) in clinic, its causality, molecular mechanism and overcoming strategies remain largely unclear. We here demonstrate that squamous transition occurs concomitantly with TKI resistance in PC9-derived xenograft tumors. Perturbation of squamous transition via DNp63 overexpression or knockdown leads to significant changes in TKI responses, indicative of a direct causal link between squamous transition and TKI resistance.

Few-shot classification of Cryo-ET subvolumes with deep Brownian distance covariance.

Few-shot learning is a crucial approach for macromolecule classification of the cryo-electron tomography (Cryo-ET) subvolumes, enabling rapid adaptation to novel tasks with a small support set of labeled data. However, existing few-shot classification methods for macromolecules in Cryo-ET consider only marginal distributions and overlook joint distributions, failing to capture feature dependencies fully. To address this issue, we propose a method for macromolecular few-shot classification using deep Brownian Distance Covariance (BDC).

Generating barcodes for nanopore sequencing data with PRO.

DNA barcodes, short and unique DNA sequences, play a crucial role in sample identification when processing many samples simultaneously, which helps reduce experimental costs. Nevertheless, the low quality of long-read sequencing makes it difficult to identify barcodes accurately, which poses significant challenges for the design of barcodes for large numbers of samples in a single sequencing run. Here, we present a comprehensive study of the generation of barcodes and develop a tool, PRO, that can be used for selecting optimal barcode sets and demultiplexing.

UPicker: a semi-supervised particle picking transformer method for cryo-EM micrographs.

Automatic single particle picking is a critical step in the data processing pipeline of cryo-electron microscopy structure reconstruction. In recent years, several deep learning-based algorithms have been developed, demonstrating their potential to solve this challenge. However, current methods highly depend on manually labeled training data, which is labor-intensive and prone to biases especially for high-noise and low-contrast micrographs, resulting in suboptimal precision and recall.

Anomalous Oscillation Modes of Superfluid Pendant Droplets.

Droplets should exhibit various dynamical phenomena when adhered to a surface; not all of them are realized in classical fluids. Visualization of superfluid ^{4}He pendant droplets revealed that the droplets were horizontally translated on a flat surface, bouncing off at the corner, known as the Noether mode that reflects the translation symmetry. The droplets exhibited another mode in vertical oscillations with high amplitude that included oscillation of the droplet edge.

Three-dimensional fluid-structure interaction modelling of the venous valve using immersed boundary/finite element method.

Research on venous hemodynamics is pivotal for unravelling venous diseases, including varicose veins and deep vein thrombosis, essential for clinical management, treatment and artificial valve design. In this study, a three-dimensional (3D) numerical simulation, employing the immersed boundary/finite element method, is constructed to explore the fluid-structure interaction (FSI) between intravenous blood and venous valves. A hyperelastic constitutive model is used to capture the incompressible, nonlinear mechanical response.

Real-world clinical data-driven modelling on the initiation time of antiviral prophylaxis among pregnant women with chronic hepatitis B infection.

Background & Aims: The risk of mother-to-child transmission (MTCT) for pregnant women with chronic hepatitis B (CHB) infection still exists, especially for those with high HBV DNA level. The guidelines for initiating prophylaxis for pregnant women with CHB vary across countries. We aimed to explore the latest prophylaxis initiation time for these women.

Prediction of Disordered Linkers Using APOD.

Intrinsically disordered linkers (DLs) connect protein domains and structural elements within domains and facilitate allosteric regulation. Computational studies suggest that thousands of proteins have DLs. Since there are only about 250 proteins with manually curated DL annotations (DisProt database ver.

General relationship of local topologies, global dynamics, and bifurcation in cellular networks.

Cellular networks realize their functions by integrating intricate information embedded within local structures such as regulatory paths and feedback loops. However, the precise mechanisms of how local topologies determine global network dynamics and induce bifurcations remain unidentified. A critical step in unraveling the integration is to identify the governing principles, which underlie the mechanisms of information flow.

Pseudo-trajectory inference for identifying essential regulations and molecules in cell fate decisions.

Cell fate decision is crucial in biological development and plays fundamental roles in normal development and functional maintenance of organisms. By identifying key regulatory interactions and molecules involved in these fate decisions, we can shed light on the intricate mechanisms underlying the cell fates. This understanding ultimately reveals the fundamental principles driving biological development and the origins of various diseases.

Analysis of six consecutive waves of ICU-admitted COVID-19 patients: key findings and insights from a Portuguese population.

Identifying high-risk patients, particularly in intensive care units (ICUs), enhances treatment and reduces severe outcomes. Since the pandemic, numerous studies have examined COVID-19 patient profiles and factors linked to increased mortality. Despite six pandemic waves, to the best of our knowledge, there is no extensive comparative analysis of patients' characteristics across these waves in Portugal.

An international core outcome set for primary progressive aphasia (COS-PPA): Consensus-based recommendations for communication interventions across research and clinical settings.

Introduction: Interventions to treat speech-language difficulties in primary progressive aphasia (PPA) often use word accuracy as a highly comparable outcome. However, there are more constructs of importance to people with PPA that have received less attention.

Methods: Following Core Outcome Set Standards for Development Recommendations (COSSTAD), this study comprised: Stage 1 - systematic review to identify measures; Stage 2 - consensus groups to identify important outcome constructs for people with PPA (n = 82) and care partners (n = 91); Stage 3 - e-Delphi consensus with 57 researchers.

Neurodegenerative Diseases: Molecular Mechanisms and Therapies 2nd Edition.

Neurodegenerative disorders are multiple chronic neurological diseases that pose a serious public health risk to our society, especially among the aging population [...

Back flux during anaerobic oxidation of butane support archaea-mediated alkanogenesis.

Microbial formation and oxidation of volatile alkanes in anoxic environments significantly impacts biogeochemical cycles on Earth. The discovery of archaea oxidizing volatile alkanes via deeply branching methyl-coenzyme M reductase variants, dubbed alkyl-CoM reductases (ACR), prompted the hypothesis of archaea-catalysed alkane formation in nature (alkanogenesis). A combination of metabolic modelling, anaerobic physiology assays, and isotope labeling of Candidatus Syntrophoarchaeum archaea catalyzing the anaerobic oxidation of butane (AOB) show a back flux of CO to butane, demonstrating reversibility of the entire AOB pathway.

TDFPS-Designer: an efficient toolkit for barcode design and selection in nanopore sequencing.

Oxford Nanopore Technologies (ONT) offers ultrahigh-throughput multi-sample sequencing but only provides barcode kits that enable up to 96-sample multiplexing. We present TDFPS-Designer, a new toolkit for nanopore sequencing barcode design, which creates significantly more barcodes: 137 with a length of 20 base pairs, 410 at 24 bp, and 1779 at 30 bp, far surpassing ONT's offerings. It includes GPU-based acceleration for ultra-fast demultiplexing and designs robust barcodes suitable for high-error ONT data.

On the study of solitary wave dynamics and interaction phenomena in the ultrasound imaging modelled by the fractional nonlinear system.

This research work focuses on investigating the propagation of ultrasonic waves, which propagate mechanical vibrations of molecules or particles inside materials. Ultrasound imaging is extensively used and deeply rooted in the medical field. The key technologies that form the basis for many different uses in the area include transducers, contrast agents, pulse compression, beam shaping, tissue harmonic imaging, techniques for measuring blood flow and tissue motion, and three-dimensional imaging.

Priority-Elastic net for binary disease outcome prediction based on multi-omics data.

Background: High-dimensional omics data integration has emerged as a prominent avenue within the healthcare industry, presenting substantial potential to improve predictive models. However, the data integration process faces several challenges, including data heterogeneity, priority sequence in which data blocks are prioritized for rendering predictive information contained in multiple blocks, assessing the flow of information from one omics level to the other and multicollinearity.

Methods: We propose the Priority-Elastic net algorithm, a hierarchical regression method extending Priority-Lasso for the binary logistic regression model by incorporating a priority order for blocks of variables while fitting Elastic-net models sequentially for each block.

vEMstitch: an algorithm for fully automatic image stitching of volume electron microscopy.

Background: As software and hardware have developed, so has the scale of research into volume electron microscopy (vEM), leading to ever-increasing resolution. Usually, data collection is followed by image stitching: the same area is subjected to high-resolution imaging with a certain overlap, and then the images are stitched together to achieve ultrastructure with large scale and high resolution simultaneously. However, there is currently no perfect method for image stitching, especially when the global feature distribution of the sample is uneven and the feature points of the overlap area cannot be matched accurately, which results in ghosting of the fusion area.

GABA Signaling in Health and Disease in the Nervous System.

Throughout development, gamma-aminobutyric acid, or GABA, plays a role in the proliferation, migration, and differentiation of neural progenitor cells [...

tDCS and local scalp cooling do not change corticomotor and intracortical excitability in healthy humans.

Objective: Scalp cooling might increase the long-term potentiation (LTP)-like effect of transcranial direct current stimulation (tDCS) by reducing the threshold for after-effects according to metaplasticity and increasing electrical current density reaching the cortical neurons. We aimed to investigate whether priming scalp cooling potentiates the tDCS after-effect on motor cortex excitability.

Methods: This study had a randomized, parallel-arms, sham-controlled, double-blinded design with an adequately powered sample of 105 healthy subjects.

Robust prediction of colorectal cancer via gut microbiome 16S rRNA sequencing data.

The study addresses the challenge of utilizing human gut microbiome data for the early detection of colorectal cancer (CRC). The research emphasizes the potential of using machine learning techniques to analyze complex microbiome datasets, providing a non-invasive approach to identifying CRC-related microbial markers. The primary hypothesis is that a robust machine learning-based analysis of 16S rRNA microbiome data can identify specific microbial features that serve as effective biomarkers for CRC detection, overcoming the limitations of classical statistical models in high-dimensional settings.