❌

Normal view

Received β€” 10 September 2026 ⏭

Gastrointestinal motility in microgravity: a critical review of multi-level mechanisms and model-dependent effects

βœ‡Omics in Gastric
By: Qian Niu Β· Tong Mu Β· Junhai Zhang Β· Yue Chen Β· Zhikun Guo Β· Yuanmin Zhu Β· Lin Li
4 September 2026 at 18:00

Front Physiol. 2026 Aug 20;17:1930628. doi: 10.3389/fphys.2026.1930628. eCollection 2026.

ABSTRACT

BACKGROUND: Gastrointestinal motility disturbances rank among the most frequently reported medical complications of spaceflight. Astronauts experience delayed gastric emptying, erratic small intestinal transit and reduced colonic propulsion. The underlying mechanisms are multifactorial. Microgravity alters intra-abdominal physical mechanics, disrupts autonomic and enteric neural circuits, shifts gastrointestinal hormone secretion profiles, inflicts oxidative stress upon effector cells, and perturbs gut microbial communities. Cross-model comparisons reveal substantial disagreement, suggesting that no single ground-based analog fully captures the pathophysiology of orbital flight.

AIM: To critically review how weightlessness affects gastric emptying, small intestinal transit and colonic motility; to critically evaluate contradictory findings across simulation platforms; and to delineate the neural, humoral, cellular and microbiological mechanisms involved.

METHODS: We searched PubMed, Web of Science and the NASA Technical Reports Server for articles published between January 1990 and June 2026 (last search 30 June 2026). Search terms included: "microgravity", "weightlessness", "spaceflight", "gastrointestinal motility", "gastric emptying", "intestinal transit", "gut microbiome", "interstitial cells of Cajal" and "oxidative stress". Studies using head-down bed rest, hindlimb unloading, clinorotation, parabolic flight and actual spaceflight were included. The review follows a critical narrative design; the full search strategy and the framework used to appraise the evidence are described in Section 1.1.

RESULTS: Altered-gravity studies suggest that gastrointestinal dysmotility may involve neurohumoral dysregulation, oxidative injury to interstitial cells of Cajal and smooth muscle, barrier dysfunction and altered enteric signaling; however, most mechanistic evidence derives from simulated models and has not been directly validated during human spaceflight. Direct human motility measurements remain sparse, and the evidence comprises a mixture of direct observations, model-dependent inferences and testable hypotheses. Cross-study agreement is poor: some head-down bed rest trials report accelerated small-bowel transit, whereas tail-suspension models and limited flight observations suggest motor suppression. These divergences may reflect model-specific confounding rather than a uniform effect of microgravity.

CONCLUSION: Current ground-based models each capture only partial aspects of orbital GI pathophysiology. Future work should combine multi-omics profiling with next-generation simulation platforms to develop evidence-based countermeasures for long-duration missions.

PMID:42694486 | PMC:PMC13539599 | DOI:10.3389/fphys.2026.1930628

Received β€” 27 May 2026 ⏭

DynaPURLS: Dynamic Refinement of Part-Aware Representations for Skeleton-Based Zero-Shot Action Recognition

βœ‡cs.AI, q-bio.NC updates on arXiv.org
By: Jingmin Zhu Β· Anqi Zhu Β· James Bailey Β· Jun Liu Β· Hossein Rahmani Β· Mohammed Bennamoun Β· Farid Boussaid Β· Qiuhong Ke
26 May 2026 at 12:00
arXiv:2512.11941v2 Announce Type: replace-cross Abstract: Zero-shot skeleton-based action recognition (ZS-SAR) is fundamentally constrained by prevailing approaches that rely on aligning skeleton features with static, class-level semantics. This coarse-grained alignment fails to bridge the domain shift between seen and unseen classes, thereby impeding the effective transfer of fine-grained visual knowledge. To address these limitations, we introduce \textbf{DynaPURLS}, a unified framework that establishes robust, multi-scale visual-semantic correspondences and dynamically refines them at inference time to enhance generalization. Our framework leverages a large language model to generate hierarchical textual descriptions that encompass both global movements and local body-part dynamics. Concurrently, an adaptive partitioning module produces fine-grained visual representations by semantically grouping skeleton joints. To fortify this fine-grained alignment against the train-test domain shift, DynaPURLS incorporates a dynamic refinement module. During inference, this module adapts textual features to the incoming visual stream via a lightweight learnable projection. This refinement process is stabilized by a confidence-aware, class-balanced memory bank, which mitigates error propagation from noisy pseudo-labels. Extensive experiments on three large-scale benchmark datasets, including NTU RGB+D 60/120 and PKU-MMD, demonstrate that DynaPURLS significantly outperforms prior art, setting new state-of-the-art records. The source code is made publicly available at https://github.com/Alchemist0754/DynaPURLS

ANP32E drives lung adenocarcinoma progression via GSK3beta-mediated glycolytic reprogramming

βœ‡Omics In Lung
By: Zhongliang Wang Β· Qianxia Li Β· Zeguang Ye Β· Xi Wu Β· Can Fang Β· Wenyang Jiang Β· Min Zhu
14 April 2026 at 18:00

Cell Death Dis. 2026 Apr 14. doi: 10.1038/s41419-026-08712-2. Online ahead of print.

ABSTRACT

Lung adenocarcinoma (LUAD), a leading cause of cancer mortality, involves incompletely understood epigenetic-metabolic crosstalk. We identified ANP32E as a key regulator through multi-omics (TCGA, scRNA-seq) and clinical analyses, finding its overexpression correlates with poor prognosis. Functionally, ANP32E knockdown suppressed proliferation, migration, and glycolysis in LUAD cells (A549/H1975) and attenuated xenograft growth, while overexpression promoted tumorigenesis. Mechanistically, ANP32E transcriptionally upregulates histone demethylase KDM3B, reducing repressive H3K9me2 marks at the EGFR promoter to enhance EGFR transcription. This activates PI3K/AKT signaling, inducing inhibitory GSK3Ξ² phosphorylation. Combined with ANP32E-mediated GSK3Ξ² suppression, this dual inactivation liberates oncogenic glycolysis. Crucially, KDM3B silencing or EGFR inhibition (Cetuximab) abrogated ANP32E-driven phenotypes. High-throughput screening identified Penta-O-galloyl-Ξ²-D-glucose (PGG) as an ANP32E-targeting compound, with molecular dynamics confirming binding. PGG dose-dependently inhibited the ANP32E/KDM3B/EGFR axis in vitro and suppressed tumor growth in vivo. Thus, ANP32E drives LUAD progression via KDM3B/EGFR-mediated GSK3Ξ² inactivation, representing a prognostic biomarker and therapeutic target validated by PGG.

PMID:41980942 | DOI:10.1038/s41419-026-08712-2

Received β€” 4 April 2026 ⏭

SenseMath: Do LLMs Have Number Sense? Evaluating Shortcut Use, Judgment, and Generation

βœ‡cs.AI, q-bio.NC updates on arXiv.org
By: Haomin Zhuang Β· Xiangqi Wang Β· Yili Shen Β· Ying Cheng Β· Xiangliang Zhang
3 April 2026 at 12:00
arXiv:2604.01988v1 Announce Type: new Abstract: Large language models often default to step-by-step computation even when efficient numerical shortcuts are available. This raises a basic question: do they exhibit number sense in a human-like behavioral sense, i.e., the ability to recognize numerical structure, apply shortcuts when appropriate, and avoid them when they are not? We introduce SenseMath, a controlled benchmark for evaluating structure-sensitive numerical reasoning in LLMs. SenseMath contains 4,800 items spanning eight shortcut categories and four digit scales, with matched strong-shortcut, weak-shortcut, and control variants. It supports three evaluation settings of increasing cognitive demand: Shortcut Use (whether models can apply shortcuts on shortcut-amenable problems); Applicability Judgment (whether they can recognize when a shortcut is appropriate or misleading); and Problem Generation (whether they can generate new problem items that correctly admit a given type of shortcut). Our evaluation across five LLMs, ranging from GPT-4o-mini to Llama-3.1-8B, shows a consistent pattern: when explicitly prompted, models readily adopt shortcut strategies and achieve substantial accuracy gains on shortcut-amenable items (up to 15%), yet under standard chain-of-thought prompting they spontaneously employ such strategies in fewer than 40% of cases, even when they demonstrably possess the requisite capability. Moreover, this competence is confined to the Use level; models systematically over-generalise shortcuts to problems where they do not apply, and fail to generate valid shortcut-bearing problems from scratch. Together, these results suggest that current LLMs exhibit procedural shortcut fluency without the structural understanding of when and why shortcuts work that underlies human number sense.

Dual Optimal: Make Your LLM Peer-like with Dignity

βœ‡cs.AI, q-bio.NC updates on arXiv.org
By: Xiangqi Wang Β· Yue Huang Β· Haomin Zhuang Β· Kehan Guo Β· Xiangliang Zhang
3 April 2026 at 12:00
arXiv:2604.00979v2 Announce Type: replace-cross Abstract: Current aligned language models exhibit a dual failure mode we term the Evasive Servant: they sycophantically validate flawed user beliefs while deflecting responsibility with boilerplate disclaimers. We propose the Dignified Peer framework, which counters servility with anti-sycophancy and trustworthiness, and mitigates evasiveness through empathy and creativity. Realizing this agent requires overcoming significant challenges in data supervision, objective collapse, and evaluation bias. We address these issues by introducing the PersonaKnob dataset which features a compositional partial order structure of multiple persona preference. This data is utilized alongside a tolerant constrained Lagrangian DPO algorithm that dynamically balances all persona dimensions to prevent behavioral collapse. Additionally, we employ a psychometrically calibrated Item Response Theory evaluation protocol to disentangle latent model persona capability from confounders like judge biases. Extensive empirical studies demonstrate that our approach successfully build a LLM agent with both dignity and peer.
There are no more articles
❌