Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in osteoarthritis by integrating bioinformatics and machine learning.

Objective: Exosomes as important carriers of intercellular communication have frequently appeared in recent studies related to osteoarthritis (OA), while the specific mechanism of exosome action in osteoarthritis remains unclear. The aim of this study was to identify potential exosome-related biomarkers in osteoarthritis, to explore the role and mechanism of exosome-related genes in articular cartilage.

Methods: The data on exosome related genes and normal and OA cartilage genes were obtained through online databases.

A Decomposition Optimization-Based Multiobjective Reinforcement Learning Algorithm for Obtaining Nonconvex Pareto Fronts.

Multiobjective reinforcement learning (MORL) aims to seek a complete Pareto front (PF) with different compromise policies in multiobjective Markov decision processes (MOMDPs). However, most MORL algorithms currently have a limitation in handling the MOMDPs with nonconvex PFs. In this article, we propose a nonlinear MORL algorithm based on decomposition and variance reduction (MORL/D-VR) to overcome this limitation.

Influence of pH and electric field on HgCl adsorption in clay-water systems and its environmental implications.

Mercury and its compounds, particularly mercury chloride (HgCl), are highly toxic and persistent environmental pollutants. Understanding the adsorption behavior of HgCl in clay-water systems is essential for developing effective mercury remediation strategies. This study investigates the effects of pH and background cations on the adsorption kinetics, adsorption energy, and dipole moment of HgCl in montmorillonite clay systems.

Sulfur isotopes from the lunar farside reveal global volatile loss following the giant impact.

The Moon is strongly depleted in volatile elements and exhibits heavier isotopic signatures (e.g., K, Zn) than the Earth.

Distinct Airway Microbiome and Metabolite Profiles in Eosinophilic and Neutrophilic Asthma.

Background: Asthma is a chronic, heterogeneous disease driven by inflammatory phenotypes, primarily eosinophilic asthma (EA) and neutrophilic asthma (NEA). While allergen triggers are well-known, the role of the airway microbiome and metabolites in asthma exacerbations remains poorly understood.

Methods: We recruited 64 participants (24 EA, 20 NEA, 20 healthy controls [HC]) for the discovery cohort, with validation in an external cohort (10 EA, 8 NEA, 8 HC).

Functionalized liposomes induce cascade degradation of extracellular matrix by hyaluronidase and photodynamic therapy for synergistic suppression of breast cancer.

Treatment of breast cancer (BC) remains to face clinical challenges due to poor tumor penetration of therapeutic agents, which is a direct consequence of the high content of hyaluronan (HA) within the extracellular matrix (ECM) of tumor tissues. Herein, we reported the synthesis of phototherapy liposomes which integrated hyaluronidase (HAase) conjugated with a matrix metalloproteinase 2 (MMP-2) responsive peptide in their phospholipid membrane, and preloaded with indocyanine green (ICG), CaO, and L-buthionine sulfoximine (BSO). Under near-infrared (NIR) laser irradiation, the responsive release of HAase and photodynamic therapy (PDT) effect generated by ICG enabled the controlled degradation of HA in the ECM.

Searching in Symmetric Solution Space for Permutation-Related Optimization Problems.

Symmetry is a widespread phenomenon in nature. Recognizing symmetry can minimize redundancy to improve computing efficiency. In this paper, we take permutation-related combinatorial optimization problems as a starting point and explore the symmetric structure of its solution space through group theory.

Prediction and optimization of stretch flangeability of advanced high strength steels utilizing machine learning approaches.

Advanced high strength steels (AHSS) exhibit diverse mechanical properties due to their complex chemical compositions and microstructures. Existing machine learning (ML) studies often focus on specific steel grades, limiting generalizability in predicting and optimizing AHSS properties. Here, an ML framework was presented to predict and optimize the stretch-flangeability of AHSS based on composition-microstructure-property correlations, using datasets from 212 steel conditions.

Factors Influencing Resistivity Inversion for CO Geological Storage Zones: A Quantitative Study.

This study establishes a homogeneous half-space and a horizontally layered two-layer background stratigraphy model using cross-borehole electrical resistivity tomography (ERT) based on an incomplete Gauss-Newton (IGN) method to investigate the resistivity inversion characteristics of CO storage zones. The effects of storage zone volume (VCO2), storage zone resistivity (ρCO2), background formation resistivity (ρf), and CO diffusion on inversion results were systematically analyzed, and the mechanisms underlying the influence of different parameters on inversion imaging were explored. The results indicate that an increase in the VCO2 significantly affects the inverted resistivity.

Association of unsaturated fatty acid intake with risk of all-cause death in patients with osteoarthritis.

Aim: To investigate the relationship between unsaturated fatty acids (UFAs) intake and the risk of all-cause mortality in osteoarthritis (OA) patients.

Methods: This cohort study included the data of 3,271 participants with OA using data from the National Health and Nutrition Examination Survey (NHANES). Univariate and multivariable weighted Cox regression models were applied to analyze the relationship between UFAs intake and the risk of mortality in patients with OA.

Photodynamic Biomimetic Liposomes Targeted to the Endoplasmic Reticulum Enhance Combined Immunotherapy for Triple-Negative Breast Cancer.

Cancer immunotherapies, such as immune checkpoint inhibitors, have advanced rapidly and achieved notable success, yet they face significant challenges due to poor response rates and immune-related adverse effects, particularly in cases of triple-negative breast cancer (TNBC). Photodynamic therapy (PDT) can initiate immunogenic cell death (ICD) by inducing endoplasmic reticulum (ER) stress, thereby enhancing the effectiveness of tumor immunotherapy. Herein, we develop potent PDT biomimetic liposomes (PB Lipo) locating the ER to realize a synergistic immuno-photodynamic treatment.

Optimized fluorine recovery and regulated synthesis of aluminum fluoride hydroxy hydrate from waste cryolite via chemical equilibrium modeling and DFT analysis.

Waste cryolite generated during industrial aluminum smelting is rich in fluorine, posing significant risks to the environment. In this study, we propose a novel two-step method for efficiently synthesizing aluminum fluoride hydroxy hydrate (AFHH) from this waste, guided by chemical equilibrium modeling and density functional theory (DFT) calculations. This process involves the leaching of waste cryolite with Al(NO) and the subsequent alkalization of the leachate with NaOH.

Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach.

Background: Acute kidney injury (AKI) and acute kidney disease (AKD) are prevalent among pediatric patients, both linked to increased mortality and extended hospital stays. Early detection of kidney injury is crucial for improving outcomes. This study presents a machine learning-based risk prediction model for AKI and AKD in pediatric patients, enabling personalized risk predictions.

Genetically predicted metabolite mediates the causal relationship between immune cells and autoimmune diseases.

Background: This study investigates the causal role of metabolites mediating immune cells in rheumatoid arthritis (RA) and ankylosing spondylitis (AS) through a Mendelian randomization (MR) study.

Methods: The two-sample and two-step MR methods were used for the current analysis: (1) causal effects of immune cells on RA and AS; (2) mediation effects of metabolites. Inverse variance weighted (IVW) is the main method to analyze causality, and MR results are verified by several sensitive analyses.

Limitations of the cox proportional hazards model and alternative approaches in metachronous recurrence research.

The article by Shin et al. provides valuable insights into the correlation between the gastric mucosa-associated gastric microbiome (MAM) and metachronous recurrence. However, the use of the Cox proportional hazards model in their analysis presents several limitations.

Formononetin Alleviates Ischemic Acute Kidney Injury by Regulating Macrophage Polarization through KLF6/STAT3 Pathway.

Recent research has indicated that formononetin demonstrates a potent anti-inflammatory effect in various diseases. However, its impact on sterile inflammation kidney injury, specifically acute kidney injury (AKI), remains unclear. In this study, we utilized an ischemia/reperfusion-induced AKI (IRI-AKI) mouse model and bone marrow-derived macrophages (BMDMs) to investigate the effects of formononetin on sterile inflammation of AKI and to explore the underlying mechanism.

Peritoneal fluid indocyanine green test for diagnosis of gut leakage in anastomotic leakage rats and colorectal surgery patients.

Background: Application of indocyanine green (ICG) fluorescence has led to new developments in gastrointestinal surgery. However, little is known about the use of ICG for the diagnosis of postoperative gut leakage (GL). In addition, there is a lack of rapid and intuitive methods to definitively diagnose postoperative GL.

Personalized prediction of mortality in patients with acute ischemic stroke using explainable artificial intelligence.

Background: Research into the acute kidney disease (AKD) after acute ischemic stroke (AIS) is rare, and how clinical features influence its prognosis remain unknown. We aim to employ interpretable machine learning (ML) models to study AIS and clarify its decision-making process in identifying the risk of mortality.

Methods: We conducted a retrospective cohort study involving AIS patients from January 2020 to June 2021.

Facile synthesis of MoS@red phosphorus heterojunction for synergistically photodynamic and photothermal therapy of renal cell carcinoma.

The therapy of the clear cell renal cell carcinoma (ccRCC) is crucial for the human healthcare due to its easy metastasis and recurrence, as well as resistance to radiotherapy and chemotherapy. In this work, we propose the synthesis of MoS@red phosphorus (MoS@RP) heterojunction to induce synergistic photodynamic and photothermal therapy (PDT/PTT) of ccRCC. The MoS@RP heterojunction exhibits enhanced spectra absorption in the NIR range and produce local heat-increasing under the NIR laser irradiation compared with pure MoS and RP.

Development of a novel six DNA damage response-related prognostic signature in osteosarcoma.

DNA damage response (DDR) plays a vital role in the development of cancer. Nevertheless, in osteosarcoma, the potential of DDR-related genes (DDRGs) remains unclear. Thus, the current research is intended to investigate the mechanisms of DDRGs in the development of osteosarcoma and to explore potential DDR-related biomarkers in forecasting the prognosis of osteosarcoma patients.

Vaporization phosphorization-mediated synthesis of phosphorus-doped TiO nanocomposites for combined photodynamic and photothermal therapy of renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is a disease with high incidence and poor prognosis. The conventional treatment involves radiotherapy and chemotherapy, but chemotherapeutic agents are often associated with side effects, , cytotoxicity to nontumor cells. Therefore, there is an urgent need for the development of novel therapeutic strategies for ccRCC.