Shrinking to bird size with dinosaur-level cancer defences: Evolution of cancer suppression over macroevolutionary time.

Ubiquity of cancer across the tree of life yields opportunities to understand variation in cancer defences across species. Peto's paradox, the finding that large-bodied species do not suffer from more cancer despite having more cells at risk of oncogenic mutations compared to small species, can be explained if large size selects for better cancer defences. Since birds live longer than non-flying mammals of equivalent size, and are descendants of moderate-sized dinosaurs, we ask whether ancestral cancer defences are retained if body size shrinks in a lineage.

Contrasting age-dependent leaf acclimation strategies drive vegetation greening across deciduous broadleaf forests in mid- to high latitudes.

Increasing leaf area and extending vegetation growing seasons are two primary drivers of global greening, which has emerged as one of the most significant responses to climate change. However, it remains unclear how these two leaf acclimation strategies would vary across forests at a large spatial scale. Here, using multiple satellite-based datasets and field measurements, we analysed the temporal changes (Δ) in maximal leaf area index (LAI) and length of the growing season (LOS) from 2002 to 2021 across deciduous broadleaf forests (DBFs) in the middle to high latitudes.

Cooling outweighs warming across phenological transitions in the Northern Hemisphere.

Vegetation phenology, i.e., seasonal biological events such as leaf-out and leaf-fall, regulates local climate through biophysical processes like evapotranspiration (ET) and albedo.

Early sensory evidence shapes multichoice confidence bias: A registered report.

Everyday decision making often involves choosing between multiple alternatives, and developing unified theories for this process would benefit broad disciplines of behavioral science. A key challenge lies in explaining behavioral irrationalities that arise specifically in multialternative decisions. This study, based on preregistered procedures, investigated such nonnormative behaviors in a three-choice dot numerosity discrimination task.

Pyrrole-Fused Aza-Nanographene with Two Gulf-Edge Regions as Flexible Sites.

A fused octapyrrolylanthracene, representing a nonplanar pyrrole-fused aza-nanographene with two deep gulf-edge regions, was readily synthesized and found to exhibit a ladder-shaped bent structure. Electrochemical studies revealed reversible multielectron oxidation up to four electrons. Stepwise oxidation with AgPF or I afforded a singlet diradical dication and a closed-shell aromatic tetracation.

One pathogen does not an epidemic make: a review of interacting contagions, diseases, beliefs, and stories.

From pathogens and computer viruses to genes and memes, contagion models have found widespread utility across the natural and social sciences. Despite their success and breadth of adoption, the approach and structure of these models remain surprisingly siloed by field. Given the siloed nature of their development and widespread use, one persistent assumption is that a given contagion can be studied in isolation, independently from what else might be spreading in the population.

Endozoochory by Black Rhinoceroses Enhances Germination of a Key Arid Savanna Tree Species.

Megaherbivores are typically regarded as agents of top-down control, limiting woody encroachment through destructive foraging. Yet they also possess traits and engage in behaviours that facilitate plant success. For example, megaherbivores can act as effective endozoochorous seed dispersers.

A novel decoding strategy for ProteinMPNN to design with less visibility to cytotoxic T-lymphocytes.

Due to their versatility and diverse production methods, proteins have attracted a lot of interest for industrial as well as therapeutic applications. Designing new therapeutics requires careful consideration of immune responses, particularly the cytotoxic T-lymphocyte (CTL) reaction to intra-cellular proteins. In this study, we introduce CAPE-Beam, a novel decoding strategy for the established ProteinMPNN protein design model.

Constructing and Using Cell Type Populations of the Human Reference Atlas.

The human body contains ~27-36 trillion cells of up to 10,000 cell types (CTs) within a volume of ~62-120 liters (males) and 52-89 liters (females). The Human Reference Atlas (HRA) v2.3 provides a quantitative 3D framework of CTs across 73 reference organs and 1,283 3D anatomical structures (ASs).

Stain-free artificial intelligence-assisted light microscopy for the identification of blood cells in microfluidic flow.

The identification and classification of blood cells are essential for diagnosing and managing various haematological conditions. Haematology analysers typically perform full blood counts but often require follow-up tests such as blood smears. Traditional methods like stained blood smears are laborious and subjective.

Upcycling human excrement: the gut microbiome to soil microbiome axis.

Human excrement composting (HEC) is a sustainable strategy for human excrement (HE) management that recycles nutrients and mitigates health risks while reducing reliance on freshwater, fossil fuels, and fertilizers. A mixture of HE and bulking material was collected from 15 composting toilets and composted as 15 biological replicates in modified 19-liter buckets under mesophilic conditions with weekly sampling for one year. We hypothesized that (i) the microbiome of 1 year old compost would resemble that of a soil and/or food and landscape waste compost microbiome more closely than the original HE; and (ii) the human fecal indicators, and , would be undetectable after 52 weeks using qPCR and culturing.

Identification and applications of disease-associated differential human and bacterial proteins with metaproteomic evidence.

The gut microbiome plays a fundamental role in human health and disease. Individual variations in the microbiome and the corresponding functional implications are key considerations to enhance precision health and medicine. Metaproteomics has recently revealed protein expression that might be associated with human health and disease.

An intelligent diagnosis method for cardiovascular diseases based on the CNN-CBAM-GRU model.

Early diagnosis of cardiovascular diseases (CVDs) is essential for improving patient outcomes. As a primary diagnostic modality, electrocardiogram (ECG) signals pose challenges for automatic classification due to their complex temporal and morphological characteristics. This study proposes a CNN-CBAM-GRU model that integrates Convolutional Neural Networks (CNN), the Convolutional Block Attention Module (CBAM), and Gated Recurrent Units (GRU) to enhance both spatial feature representation and temporal sequence modeling.

Synthetic data generation with Worley-Perlin diffusion for robust subarachnoid hemorrhage detection in imbalanced CT Datasets.

Purpose: In this paper, we propose a novel generative model to produce high-quality SAH samples, enhancing SAH CT detection performance in imbalanced datasets. Previous methods, such as cost-sensitive learning and previous diffusion models, suffer from overfitting or noise-induced distortion, limiting their effectiveness. Accurate SAH sample generation is crucial for better detection.

MAFNet: A novel adaptive multi-scale model for fine-grained grading of diabetic retinopathy.

Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, and its early detection and accurate grading play a crucial role in clinical intervention. To address the dual limitations of existing methods in multi-scale lesions feature fusion and lesions relation modeling, this study proposes a novel adaptive multi-scale convolutional neural network model for fine-grained grading of DR, called MAFNet (Multi-scale Adaptive Fine-grained Network). The model is constructed through three core modules to establish a multi-scale feature integration framework: the Hierarchical Global Context Module (HGCM) effectively expands the receptive field by employing multi-scale pooling and dynamic feature fusion, capturing lesions features from micro to large-scale areas; the Multi-scale Adaptive Attention Module (MSAM) utilizes an adaptive attention mechanism to dynamically adjust the feature weights at different spatial locations, enhancing the representation of key lesions regions; and the Relational Multi-head Attention Module (RMA) uses a multi-head attention mechanism to model the complex relationships between features in parallel, improving the accuracy of fine-grained lesions identification.

AI-driven WHO 2021 classification of gliomas based only on H&E-stained slides.

Background: The WHO 2021 classification criteria for adult diffuse glioma integrate histology with molecular profiling for conclusive diagnosis. Since molecular profiling can be expensive and time-consuming, often necessitating outsourcing or leading to the 'not otherwise specified (NOS) label', this study develops an AI-driven WHO 2021 classification of gliomas solely from H&E whole-slide images (WSIs).

Methods: Our pipeline is based on a multi-institutional dataset reclassified per WHO 2021 guidelines.

Three-dimensional characterization of caves within the Grand Canyon's deep karst aquifer.

Understanding groundwater movement within karst aquifers remains challenging because flow-defining conduit and fracture networks are both complex and inaccessible. In Grand Canyon National Park, dye tracers have been used to establish flow paths for springs that support ecosystems and park operations. Unfortunately, these point-to-point studies are limited when attempting to extrapolate flow paths over thousands of square kilometers.

Modeling resource consumption in the US air transportation system via minimum-cost percolation.

Percolation theory has been proven useful to study the robustness of supply-and-demand networks (SDNs) such as transportation and communication infrastructures. Here, we show that it can also be leveraged to understand how resources of SDNs are utilized, and eventually depleted. We introduce a model where rational agents consume network's edges along demanded minimum-cost paths.

Association of rs3761548 With Cancer: Systematic Review and Two Approaches of X-chromosome Genotypic Meta-analysis.

Background/aim: Cancer development involves complex interactions between immune mechanisms and the tumor microenvironment, with regulatory T cells (Tregs) being implicated in suppressing anti-tumor immunity. The X-linked gene Forkhead Box P3 (), which regulates Tregs' function, and its promoter variant rs3761548 C>A have been widely studied for their role in tumorigenesis. This meta-analysis aims to re-evaluate the association between rs3761548 and cancer risk using two statistical approaches to account for sex-based genotypic differences and X-chromosome statistical challenges.

Inattentional noise leads to subjective color uniformity across the visual field.

Humans perceive a vividly colored world coherently across the visual field, even though our peripheral vision has limited color sensitivity compared to central vision. How is this sense of color uniformity achieved? This question can be explored through a phenomenon called the pan-field color illusion, in which observers perceive scene images achromatized in the peripheral region (chimera images) as full-color images. Our previous work demonstrated that inattention to the peripheral visual field contributed to this illusion.

LLaVA-Pose: Keypoint-Integrated Instruction Tuning for Human Pose and Action Understanding.

Current vision-language models (VLMs) are well-adapted for general visual understanding tasks. However, they perform inadequately when handling complex visual tasks related to human poses and actions due to the lack of specialized vision-language instruction-following data. We introduce a method for generating such data by integrating human keypoints with traditional visual features such as captions and bounding boxes, enabling more precise understanding of human-centric scenes.

Energy-Efficient Resource Allocation Scheme Based on Reinforcement Learning in Distributed LoRa Networks.

The rapid growth of Long Range (LoRa) devices has led to network congestion, reducing spectrum and energy efficiency. To address this problem, we propose an energy-efficient reinforcement learning method for distributed LoRa networks, enabling each device to independently select appropriate transmission parameters, i.e.

T360Fusion: Temporal 360 Multimodal Fusion for 3D Object Detection via Transformers.

Object detection plays a significant role in various industrial and scientific domains, particularly in autonomous driving. It enables vehicles to detect surrounding objects, construct spatial maps, and facilitate safe navigation. To accomplish these tasks, a variety of sensors have been employed, including LiDAR, radar, RGB cameras, and ultrasonic sensors.

Mindful Movement Programs in Community and University Preschools: Protocol for a Pilot Randomized Controlled Trial.

Background: Chronic stress and emotional and cognitive regulation difficulties during early childhood are associated with risky behaviors and negative outcomes later in life. As preschoolers are at a developmental stage where their emotional and cognitive regulation skills are still emerging, they often rely on external support to manage their emotions and behaviors. Intervening early promotes healthy development and preventing adverse outcomes.

Human Brain Cell-Type-Specific Aging Clocks Based on Single-Nuclei Transcriptomics.

Aging is the primary risk factor for most neurodegenerative diseases, yet the cell-type-specific progression of brain aging remains poorly understood. Here, human cell-type-specific transcriptomic aging clocks are developed using high-quality single-nucleus RNA sequencing data from post mortem human prefrontal cortex tissue of 31 donors aged 18-94 years, encompassing 73,941 high-quality nuclei. Distinct transcriptomic changes are observed across major cell types, including upregulation of inflammatory response genes in microglia from older samples.