Clonal interference, genetic variation and the speed of evolution in structured populations.

When it comes to understanding the role that population structure plays in shaping rates of evolution, it is commonly accepted that interference between evolutionary innovations is more prevalent in structured populations compared to well-mixed, and that population structure reduces the rate of evolution, while simultaneously promoting maintenance of genetic variation. Prior models usually represent population structure using two or more connected demes or lattices with periodic boundary conditions. Fundamentally, the observed spatial evolutionary slow-down is rooted in the fact that these types of structures increase the time it takes for a selective sweep and therefore, increase the probability that multiple beneficial mutations will coexist and interfere.

High-precision phenotyping of breast cancer exosomes based on washable magnetic microarrays and super-resolution tricolor fluorescence co-localization.

Exosome is a kind of membranous vesicles released from cells and carry a number of important signaling molecules, they play an important role in cellular communication, cell migration, angiogenesis as well as tumor cell growth. Exosome-based cancer diagnosis is usually achieved by detecting exosomal nucleic acids, lipids, and surface proteins, as they reflect tumor type and progression. Here, we proposed a method to rapidly prepare an array of washable magnetic nanoparticles (magnetic beads, MBs) by a magnetic field controlled system, which facilitate the analyzing of exosome phenotypes via super-resolution tricolor fluorescence co-localization (SR-TFC) and pixel counting (CFPP).

Fine-grained vehicle recognition under low light conditions using EfficientNet and image enhancement on LiDAR point cloud data.

The detection and recognition of vehicles are crucial components of environmental perception in autonomous driving. Commonly used sensors include cameras and LiDAR. The performance of camera-based data collection is susceptible to environmental interference, whereas LiDAR, while unaffected by lighting conditions, can only achieve coarse-grained vehicle classification.

Immunomodulatory and bone regenerative properties of copper/procyanidins-modified titanium surfaces.

The inflammatory response triggered by the interaction between implants and macrophages is essential for bone regeneration around these implants. This study presents the application of dopamine hydrochloride to develop a copper and procyanidins coating on titanium surfaces to investigate its effects on bacterial inhibition, macrophage polarization, and osteogenic differentiation. The results demonstrated that this copper/procyanidins coating significantly suppressed the growth of Escherichia coli and Staphylococcus aureus.

Weak Antilocalization and Negative Magnetoresistance of the Gate-Tunable PbTe Thin Films.

We have systematically studied the electromagnetic transport properties of PbTe thin films under gate voltage modulation. The system demonstrates pronounced electron-electron interactions exclusively within the gate voltage range where only hole carriers are present. Furthermore, the Berry phase is utilized to qualitatively elucidate the transition between weak antilocalization (WAL) and weak localization (WL) through the regulation of gate voltage and temperature.

Synthesis of Palladium Nanowires on Flagella Template for Electrochemical Biosensor Detection of microRNA-21.

In recent years, the use of bacterial flagella as biomimetic templates has gained increasing attention in nanomaterial synthesis due to their unique structural and functional properties. In this study, we optimized the flagella extraction method and achieved a high concentration of flagella solution. Flagella were isolated from .

DrugRepPT: a deep pretraining and fine-tuning framework for drug repositioning based on drug's expression perturbation and treatment effectiveness.

Motivation: Drug repositioning (DR), identifying novel indications for approved drugs, is a cost-effective strategy in drug discovery. Despite numerous proposed DR models, integrating network-based features, differential gene expression, and chemical structures for high-performance DR remains challenging.

Results: We propose a comprehensive deep pretraining and fine-tuning framework for DR, termed DrugRepPT.

DAPNet: multi-view graph contrastive network incorporating disease clinical and molecular associations for disease progression prediction.

Background: Timely and accurate prediction of disease progress is crucial for facilitating early intervention and treatment for various chronic diseases. However, due to the complicated and longitudinal nature of disease progression, the capacity and completeness of clinical data required for training deep learning models remains a significant challenge. This study aims to explore a new method that reduces data dependency and achieves predictive performance comparable to existing research.

Combining array-assisted SERS microfluidic chips and machine learning algorithms for clinical leukemia phenotyping.

The disease progression and treatment options of leukemia between different subtypes vary considerably, emphasizing the importance of phenotyping. However, early typing of leukemia remains challenging due to the lack of highly sensitive and specific analytical tools. Herein, we propose a SERS-based platform for the classification of acute lymphoblastic T-cell leukemia (T-ALL) and chronic myeloid leukemia (CML) through the combination of machine learning and microfluidic chips.

2D Fe/Co-MOF/SOX cascade reactors for fast noninvasive detection of sarcosine level in prostate cancer urine.

Sarcosine plays a key role in screening for early prostate cancer. However, the several already reported peroxidase mimics immobilized with sarcosine oxidase (SOX) utilized to detect uriary sarcosine still have some limitations such as complex synthesis process, using of expensive heavy metals to mimic enzyme activity and long color development time. Herein, an inexpensive peroxidase-like 2D Fe/Co-MOF nanosheet was prepared by a simple solvent modulation method.

The Influence of Exogenous CdS Nanoparticles on the Growth and Carbon Assimilation Efficiency of .

This study investigated the impact of CdS nanoparticles (NPs) on growth and metabolism under varying conditions. Under illumination, CdS NPs significantly enhanced bacterial growth, glucose assimilation, and biomass accumulation. Key metabolic and stress response genes showed increased expression, indicating improved ATP synthesis and oxidative stress resistance.

One-step detection of nanoplastics in aquatic environments using a portable SERS chessboard substrate.

Nanoplastics present a significant hazard to both the environment and human health. However, the development of rapid and sensitive analysis techniques for nanoplastics is limited by their small size, lack of specificity, and low concentrations. In this study, a surface-enhanced Raman scattering (SERS) chessboard substrate was introduced as a multi-channel platform for the pre-concentration and detection of nanoplastics, achieved by polydomain aggregating silver nanoparticles (PASN) on a hydrophilic and a punched hydrophobic PVDF combined filter membrane.

New perspectives on microbiome-dependent gut-brain pathways for the treatment of depression with gastrointestinal symptoms: from bench to bedside.

Patients with depression are more likely to have chronic gastrointestinal (GI) symptoms than the general population, but such symptoms are considered only somatic symptoms of depression and lack special attention. There is a chronic lack of appropriate diagnosis and effective treatment for patients with depression accompanied by GI symptoms, and studying the association between depression and GI disorders (GIDs) is extremely important for clinical management. There is growing evidence that depression is closely related to the microbiota present in the GI tract, and the microbiota-gut-brain axis (MGBA) is creating a new perspective on the association between depression and GIDs.

PrescDRL: deep reinforcement learning for herbal prescription planning in treatment of chronic diseases.

Treatment planning for chronic diseases is a critical task in medical artificial intelligence, particularly in traditional Chinese medicine (TCM). However, generating optimized sequential treatment strategies for patients with chronic diseases in different clinical encounters remains a challenging issue that requires further exploration. In this study, we proposed a TCM herbal prescription planning framework based on deep reinforcement learning for chronic disease treatment (PrescDRL).

PresRecRF: Herbal prescription recommendation via the representation fusion of large TCM semantics and molecular knowledge.

Background: Herbal prescription recommendation (HPR) is a hotspot in the research of clinical intelligent decision support. Recently plentiful HPR models based on deep neural networks have been proposed. Owing to insufficient data, e.

ELAVL1 regulates PD-L1 mRNA stability to disrupt the infiltration of CD4-positive T cells in prostate cancer.

Prostate cancer (PCa) currently ranks second in male tumor mortality. Targeting immune checkpoint in tumor as immunotherapy is a new direction for tumor treatment. However, targeting PD-1/PD-L1 and CTLA4 to treat PCa has poor immunotherapeutic efficacy because PCa is known as a cold tumor.

Silk fibroin-based wearable SERS biosensor for simultaneous sweat monitoring of creatinine and uric acid.

Sweat biomarkers have the potential to offer valuable clinical insights into an individual's health and disease condition. Current sensors predominantly utilize enzymes and antibodies as biometric components to measure biomarkers present in sweat quantitatively. However, enzymes and antibodies are susceptible to interference by environmental factors, which may affect the performance of the sensor.

Telomerase related molecular subtype and risk model reveal immune activity and evaluate prognosis and immunotherapy response in prostate cancer.

Background: Prostate cancer ranks among the six most lethal malignancies worldwide. Telomerase, a reverse transcriptase enzyme, plays a pivotal role in extending cellular telomeres and is intimately associated with cell proliferation and division. However, the interconnection between prostate cancer and telomerase-related genes (TEASEs) remains unclear.

Apoptotic bodies encapsulating TiN nanosheets for synergistic chemo-photothermal therapy.

Extracellular vesicles (EVs) have great potential in oncology drug delivery because of their unique biological origin. Apoptotic bodies (ABs), as a member of the EV family, offer distinct advantages in terms of size, availability and membrane properties, but have been neglected for a long time. Here, using ABs and TiN nanosheets, we propose a novel drug delivery system (TiN-DOX@ABs), which exhibit a homologous targeting ability for dual-strategy tumor therapy with intrinsic biological property.

A theory of evolutionary dynamics on any complex population structure reveals stem cell niche architecture as a spatial suppressor of selection.

How the spatial arrangement of a population shapes its evolutionary dynamics has been of long-standing interest in population genetics. Most previous studies assume a small number of demes or symmetrical structures that, most often, act as well-mixed populations. Other studies use network theory to study more heterogeneous spatial structures, however they usually assume small, regular networks, or strong constraints on the strength of selection considered.

A MXene Hydrogel-Based Versatile Microrobot for Controllable Water Pollution Management.

The urgent demand for addressing dye contaminants in water necessitates the development of microrobots that exhibit remote navigation, rapid removal, and molecular identification capabilities. The progress of microrobot development is currently hindered by the scarcity of multifunctional materials. In this study, a plasmonic MXene hydrogel (PM-Gel) is synthesized by combining bimetallic nanocubes and TiCT MXene through the rapid gelation of degradable alginate.

Inflammatory cytokine profiles in erectile dysfunction: a bidirectional Mendelian randomization.

Objectives: Inflammatory cytokines (ICs) play an important role in erectile dysfunction (ED). Previous studies have demonstrated that most ED patients have high levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-8 (IL-8). The causality between 41 ICs and ED is investigated using the Mendelian randomization (MR) approach.

Evolutionary graph theory beyond single mutation dynamics: on how network-structured populations cross fitness landscapes.

Spatially resolved datasets are revolutionizing knowledge in molecular biology, yet are under-utilized for questions in evolutionary biology. To gain insight from these large-scale datasets of spatial organization, we need mathematical representations and modeling techniques that can both capture their complexity, but also allow for mathematical tractability. Evolutionary graph theory utilizes the mathematical representation of networks as a proxy for heterogeneous population structure and has started to reshape our understanding of how spatial structure can direct evolutionary dynamics.