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Cholesterol is an essential structural component of membranes that contributes to membrane integrity and fluidity. Cholesterol homeostasis plays a critical role in the maintenance of cellular activities. Recently, increasing evidence has indicated that cholesterol is a major determinant by modulating cell signaling events governing the hallmarks of cancer. Numerous studies have shown the functional significance of cholesterol metabolism in tumorigenesis, cancer progression and metastasis through its regulatory effects on the immune response, ferroptosis, autophagy, cell stemness, and the DNA damage response. Here, we summarize recent literature describing cholesterol metabolism in cancer cells, including the cholesterol metabolism pathways and the mutual regulatory mechanisms involved in cancer progression and cholesterol metabolism. We also discuss various drugs targeting cholesterol metabolism to suggest new strategies for cancer treatment. Cancer: Changes in cholesterol metabolism Emerging evidence suggests that changes in cholesterol metabolism can be involved in the onset and progression of cancer, opening avenues towards better understanding of cancer and new treatment options. Cholesterol is an essential structural component of cell membranes, important for maintaining optimal fluidity of the membrane under varying conditions. Si Shi, Xianjun Yu and colleagues at Fudan University Shanghai Cancer Center, China, review recent research into cholesterol metabolism in cancers, including cellular regulatory pathways involving cholesterol that are also implicated in cancer progression. The influence of cholesterol metabolism on cancer has been linked to effects on several key physiological processes, including the immune response, regulated cell death, recycling of cellular components, DNA repair, and the activities of stem cells. The authors consider the potential of drugs known to influence cholesterol metabolism in anti-cancer therapy.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder seen in age-dependent dementia. There is currently no effective treatment for AD, which may be attributed in part to lack of a clear underlying mechanism. Studies within the last few decades provide growing evidence for a central role of amyloid β (Aβ) and tau, as well as glial contributions to various molecular and cellular pathways in AD pathogenesis. Herein, we review recent progress with respect to Aβ- and tau-associated mechanisms, and discuss glial dysfunction in AD with emphasis on neuronal and glial receptors that mediate Aβ-induced toxicity. We also discuss other critical factors that may affect AD pathogenesis, including genetics, aging, variables related to environment, lifestyle habits, and describe the potential role of apolipoprotein E (APOE), viral and bacterial infection, sleep, and microbiota. Although we have gained much towards understanding various aspects underlying this devastating neurodegenerative disorder, greater commitment towards research in molecular mechanism, diagnostics and treatment will be needed in future AD research.

Sustained activation of glycolytic metabolism would lead to low efficiency of ATP production and compromise of microglial immune functions [9]. Since the energy metabolism is required for Aβ phagocytosis and clearance, the low efficiency of ATP production due to glycolytic metabolism would impair the phagocytic function of microglia and result in Aβ accumulation. In summary, this study highlights a crosstalk between lactate metabolism and histone lactylation in microglia, and reveals how this lactate-derived epigenetic modification exacerbates microglial dysfunction and neuroinflammation in the development and progression of AD. [...]targeting lactate metabolism disorder may represent a novel strategy for AD intervention (Fig. 1). Positive feedback regulation of microglial glucose metabolism by histone H4 lysine 12 lactylation in Alzheimer's disease.

Liquid–liquid phase separation (LLPS) is a novel principle for explaining the precise spatial and temporal regulation in living cells. LLPS compartmentalizes proteins and nucleic acids into micron-scale, liquid-like, membraneless bodies with specific functions, which were recently termed biomolecular condensates. Biomolecular condensates are executors underlying the intracellular spatiotemporal coordination of various biological activities, including chromatin organization, genomic stability, DNA damage response and repair, transcription, and signal transduction. Dysregulation of these cellular processes is a key event in the initiation and/or evolution of cancer, and emerging evidence has linked the formation and regulation of LLPS to malignant transformations in tumor biology. In this review, we comprehensively summarize the detailed mechanisms of biomolecular condensate formation and biophysical function and review the recent major advances toward elucidating the multiple mechanisms involved in cancer cell pathology driven by aberrant LLPS. In addition, we discuss the therapeutic perspectives of LLPS in cancer research and the most recently developed drug candidates targeting LLPS modulation that can be used to combat tumorigenesis.

Changes in atmospheric CO 2 concentration have played a central role in algal and plant adaptation and evolution. The commercially important red algal genus, Pyropia (Bangiales) appears to have responded to inorganic carbon (C i ) availability by evolving alternating heteromorphic generations that occupy distinct habitats. The leafy gametophyte inhabits the intertidal zone that undergoes frequent emersion, whereas the sporophyte conchocelis bores into mollusk shells. Here, we analyze a high-quality genome assembly of Pyropia yezoensis to elucidate the interplay between C i availability and life cycle evolution. We find horizontal gene transfers from bacteria and expansion of gene families (e.g. carbonic anhydrase, anti-oxidative related genes), many of which show gametophyte-specific expression or significant up-regulation in gametophyte in response to dehydration. In conchocelis, the release of HCO 3 - from shell promoted by carbonic anhydrase provides a source of C i . This hypothesis is supported by the incorporation of 13 C isotope by conchocelis when co-cultured with 13 C-labeled CaCO 3 . The nori producing seaweed Pyropia yezoensis has heteromorphic generations that occupy distinct habitats. Here, via genome assembly, transcriptome analysis, and 13 C isotope labeling, the authors show the interplay between inorganic carbon availability and life cycle evolution in the intertidal environment.

As the most basic mechanical components, bearing troubleshooting is essential to ensure the safe and reliable operation of rotating machinery. Bearing fault diagnosis is challenging due to the scarcity of bearing fault diagnosis samples and the susceptibility of fault signals to external noise. To address these issues, a ResNet-CACNN-BiGRU-SDPA bearing fault diagnosis method based on time–frequency bi-domain and feature fusion is proposed. First, the model takes the augmented time-domain signals as inputs and reconstructs them into frequency-domain signals using FFT, which gives the signals a bi-directional time–frequency domain receptive field. Second, the long sequence time-domain signal is processed by a ResNet residual block structure, and a CACNN method is proposed to realize local feature extraction of the frequency-domain signal. Then, the extracted time–frequency domain long sequence features are fed into a two-layer BiGRU for bidirectional deep global feature mining. Finally, the long-range feature dependencies are dynamically captured by SDPA, while the global dual-domain features are spliced and passed into Softmax to obtain the model output. In order to verify the model performance, experiments were carried out on the CWRU and JNU bearing datasets, and the results showed that the method had high accuracy under both small sample size and noise perturbation conditions, which verified the model’s good fault-feature-learning capability and noise immunity performance.

Recurrent chromosomal aberrations have led to the discovery of oncogenes or tumour suppressors involved in carcinogenesis. Here we characterized an oncogenic long intergenic non-coding RNA in the frequent DNA-gain regions in hepatocellular carcinoma (HCC), LINC01138 (long intergenic non-coding RNA located on 1q21.2). The LINC01138 locus is frequently amplified in HCC; the LINC01138 transcript is stabilized by insulin like growth factor-2 mRNA-binding proteins 1/3 (IGF2BP1/IGF2BP3) and is associated with the malignant features and poor outcomes of HCC patients. LINC01138 acts as an oncogenic driver that promotes cell proliferation, tumorigenicity, tumour invasion and metastasis by physically interacting with arginine methyltransferase 5 (PRMT5) and enhancing its protein stability by blocking ubiquitin/proteasome-dependent degradation in HCC. The discovery of LINC01138, a promising prognostic indicator, provides insight into the molecular pathogenesis of HCC, and the LINC01138/PRMT5 axis is an ideal therapeutic target for HCC treatment. Long intergenic non-coding RNAs have been linked to cancer development. Here the authors, using RNA-seq and genomic amplification data, identify lincRNAs deregulated in hepatocellular carcinoma and propose that Linc01138 is stabilized by IGF2BP1/3 in the cytoplasm, and binds and stabilizes the methyltransferase PRMT5 by preventing the association of PRMT5 to the E3 ubiquitin ligase CHIP.

As a critical component of the tumor microenvironment (TME), cancer‐associated fibroblasts (CAFs) play important roles in cancer initiation and progression. Well‐known signaling pathways, including the transforming growth factor‐β (TGF‐β), Hedgehog (Hh), Notch, Wnt, Hippo, nuclear factor kappa‐B (NF‐κB), Janus kinase (JAK)/signal transducer and activator of transcription (STAT), mitogen‐activated protein kinase (MAPK), and phosphoinositide 3‐kinase (PI3K)/AKT pathways, as well as transcription factors, including hypoxia‐inducible factor (HIF), heat shock transcription factor 1 (HSF1), P53, Snail, and Twist, constitute complex regulatory networks in the TME to modulate the formation, activation, heterogeneity, metabolic characteristics and malignant phenotype of CAFs. Activated CAFs remodel the TME and influence the malignant biological processes of cancer cells by altering the transcriptional and secretory characteristics, and this modulation partially depends on the regulation of signaling cascades. The results of preclinical and clinical trials indicated that therapies targeting signaling pathways in CAFs demonstrated promising efficacy but were also accompanied by some failures (e.g., NCT01130142 and NCT01064622). Hence, a comprehensive understanding of the signaling cascades in CAFs might help us better understand the roles of CAFs and the TME in cancer progression and may facilitate the development of more efficient and safer stroma‐targeted cancer therapies. Here, we review recent advances in studies of signaling pathways in CAFs and briefly discuss some future perspectives on CAF research.

Resequencing of 302 soybean accessions and GWAS provide a comprehensive resource for soybean geneticists and breeders. Understanding soybean ( Glycine max ) domestication and improvement at a genetic level is important to inform future efforts to further improve a crop that provides the world's main source of oilseed. We detect 230 selective sweeps and 162 selected copy number variants by analysis of 302 resequenced wild, landrace and improved soybean accessions at >11× depth. A genome-wide association study using these new sequences reveals associations between 10 selected regions and 9 domestication or improvement traits, and identifies 13 previously uncharacterized loci for agronomic traits including oil content, plant height and pubescence form. Combined with previous quantitative trait loci (QTL) information, we find that, of the 230 selected regions, 96 correlate with reported oil QTLs and 21 contain fatty acid biosynthesis genes. Moreover, we observe that some traits and loci are associated with geographical regions, which shows that soybean populations are structured geographically. This study provides resources for genomics-enabled improvements in soybean breeding.

Traditional diagnostic spectroscopy provides a physically interpretable basis for mineral identification. However, how modern classifiers balance spectral and spatial information remains insufficiently understood. This study investigates this issue using CASI airborne hyperspectral data from the Liuyuan area, China. A geologically constrained ground-truth dataset was constructed based on expert knowledge and a semi-automatic Spectral Hourglass workflow. We evaluated representative shallow machine learning methods and deep learning models, including a three-dimensional convolutional neural network (3D-CNN), Vision Transformer (ViT), and SpectralFormer. The Support Vector Machine (SVM) achieved the highest overall accuracy but showed a strong bias toward dominant background classes and failed to reliably detect rare minerals such as jarosite. Deep learning models improved class balance by incorporating broader spectral features. However, excessive spatial aggregation reduced their sensitivity to small and fragmented alteration zones. SpectralFormer models hyperspectral data as ordered spectral sequences and showed more stable performance for spectrally similar and rare minerals. Multi-scale experiments reveal a spectral-dominant discrimination mechanism. Increasing the spectral receptive field improves classification up to an optimal level. In contrast, overly large spatial patches introduce background interference and obscure diagnostic absorption features. These findings highlight the fundamental role of spectral continuity in airborne hyperspectral alteration mineral mapping and clarify the trade-offs involved in integrating spatial context.