PD-L1 downregulation by carbonic anhydrase IX immunotherapy prompts immune checkpoint blockade in renal cell carcinoma.

The carbonic anhydrase IX (CAIX) expression occurs in most cases of clear cell renal cell carcinoma (ccRCC). This tumor type is characterized by an immunosuppressive microenvironment, where approximately one-fourth of patients overexpress the programmed cell death ligand-1 (PD-L1), significantly increasing their risk of death. Herein, we present a secondary effect of CAIX inhibition using monoclonal antibodies (mAbs) and CAR T cells, leading to PD-L1 downregulation in ccRCC and in vivo immune checkpoint blockade.

Carbonic Anhydrase IX and Cyclooxygenase-2 Regulation in Renal Cell Carcinoma and Impact on Therapeutic Efficiency of Anti-CAIX CAR T cells.

Background: Clear cell renal cell carcinoma (ccRCC) is the most prevalent of renal cancers, with a 5-year survival rate of less than 10% for metastatic cases. The most efficient current strategies to treat ccRCC in advanced settings slightly increase progression-free survival. Chimeric antigen receptor T cells (CAR T cells) targeting carbonic anhydrase IX (CAIX) have reemerged as a promising alternative to ccRCC treatment based on recent preclinical data.

Cytotoxic activity of the crude venom from Odontomachus affinis ants is mediated by thiol oxidation and mitochondrial dysfunction.

Animal toxins, including ant venoms, contain numerous compounds with potential biomedical and therapeutic applications. Ant venoms are mostly composed by peptides and proteins that might elicit inflammatory responses and cytotoxicity. The venom of Odontomachus affinis, a predatory ant species endemic to Brazil, is still poorly studied.

Liquid biopsy as a potential tool for diagnosis and clinical monitoring of cutaneous and uveal melanoma.

Melanoma is the most aggressive type of skin cancer, characterized by high metastatic potential and high mortality rates. Currently, diagnosis and mutational status assessment involves the excisional tissue biopsy followed by anatomopathological and immunohistochemical analyses. However, this technique is invasive and does not assess the molecular heterogeneity of the tumor.

Enhancing and advancements in deep learning for melanoma detection: A comprehensive review.

Melanoma, although not the most common skin cancer, poses a significant global health challenge, particularly in Europe, where incidence rates are high. Traditional melanoma diagnosis through biopsies can be invasive, but advancements in artificial intelligence (AI), particularly deep learning (DL), have shown promising potential for early and accurate melanoma detection through image analysis. In this systematic review, we explore the trends and gaps in the application of DL for melanoma detection, focusing on the replicability and generalization of existing models.

Improving Bonding Protocols: The Effect of Selective Dentin Etching with Two Different Universal Adhesives-An In Vitro Study.

Universal adhesives can be applied in versatile bonding strategies, with selective dentin etching (SDE) emerging as a promising approach for enhancing dentin-adhesive interfaces. This study evaluated the immediate adhesive interface to dentin of two universal adhesives (Optibond Universal and Futurabond M+) with an SDE strategy. Sixty human molars were randomly assigned to six experimental groups ( = 10): control (self-etch strategy), SDE, and SDE3 (SDE with three adhesive layers).

Bioavailability of Tryptophan Biomass for Laying Hens.

Two concurrent assays were conducted with the objective of evaluating the bioequivalence and determining the relative bioavailability value (RBV) of L-tryptophan biomass 60% for laying hens. In both assays, L-tryptophan 98% was used as the reference source. A total of 216 hens were used in the two assays.

Exploiting Paradoxical Activation of Oncogenic MAPK Signaling by Targeting Mitochondria to Sensitize Mutant-Melanoma to Vemurafenib.

Vemurafenib is a BRAF (rapidly accelerated fibrosarcoma B-type)-targeted therapy used to treat patients with advanced, unresectable melanoma. It inhibits the MAPK (mitogen-activated protein kinase)/ERK (extracellular signal-regulated kinase) pathway and tumor proliferation in BRAF-mutated melanoma cells. Resistance to vemurafenib has been reported in melanoma patients due to secondary (neuroblastoma RAS viral oncogene homolog) mutations, which lead to paradoxical MAPK pathway activation and tumor proliferation.

Leveraging Sustainable Household Energy and Environment Resources Management with Time-Series.

This paper presents a novel and extensive dataset featuring comprehensive cross-sectional data from 13 households with nearly three years of electrical load, energy cost, and on-premises solar energy production directly linked to solar irradiation and weather parameters (SHEERM dataset). The dataset is essential for understanding and optimizing energy utilization to achieve Sustainable Development Goals (SDG) 7, 9, 11 and 13. It provides data about solar energy production, weather conditions, residential energy needs, and market prices.

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.

Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive coronary angiography (CAG), possibly outperforming humans, but has seldom been explored, especially for instantaneous wave-free Ratio (iFR). We aimed to develop binary iFR lesion classification AI models and compare them with human performance.

Maternal hyperglycemia and postnatal high-fat diet impair metabolic regulation and autophagy response in the liver of adult female rats.

This study aimed to investigate the mechanisms by which the association between maternal hyperglycemia and postnatal high-fat diet (HFD) exposure compromises metabolic parameters and hepatic autophagy in adult female pups. For this, Sprague Dawley rats, female pups from nondiabetic (control = FC) or diabetic (FD) mothers, were fed a standard diet (SD) or HFD from weaning until adulthood ( minimum = 5 rats/group): FC/SD, FC/HFD, FD/SD, and FD/HFD. In adulthood, these rats were tested with the oral glucose tolerance test, euthanized, and serum biochemistry parameters were analyzed.

Proximity-driven site-specific cyclization of phage-displayed peptides.

Cyclization provides a general strategy for improving the proteolytic stability, cell membrane permeability and target binding affinity of peptides. Insertion of a stable, non-reducible linker into a disulphide bond is a commonly used approach for cyclizing phage-displayed peptides. However, among the vast collection of cysteine reactive linkers available, few provide the selectivity required to target specific cysteine residues within the peptide in the phage display system, whilst sparing those on the phage capsid.

A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a comprehensive database of inorganic NP research is not currently available, it is crucial for developing effective cancer therapies. In this context, machine learning (ML) has emerged as a transformative tool, but its adaptation to nanomedicine is hindered by inexistent or small datasets.

Coronary Intravascular Lithotripsy Effectiveness and Safety in a Real-World Cohort.

: Coronary artery calcification is a predictor of adverse outcomes after percutaneous coronary intervention (PCI). Intravascular lithotripsy (IVL) is a promising tool for the treatment of calcified lesions. The aim of this study was to assess the effectiveness and safety of IVL.

Insulin signaling and mitochondrial phenotype of skeletal muscle are programmed in utero by maternal diabetes.

Maternal diabetes may influence glucose metabolism in adult offspring, an area with limited research on underlying mechanisms. Our study explored the impact of maternal hyperglycemia during pregnancy on insulin resistance development. Adult female Sprague-Dawley rats from control and diabetic mothers were mated, and their female offspring were monitored for 150 days.

Coronary physiology instantaneous wave-free ratio (iFR) derived from x-ray angiography using artificial intelligence deep learning models: a pilot study.

Objectives: Coronary angiography (CAG)-derived physiology methods have been developed in an attempt to simplify and increase the usage of coronary physiology, based mostly on dynamic fluid computational algorithms. We aimed to develop a different approach based on artificial intelligence methods, which has seldom been explored.

Methods: Consecutive patients undergoing invasive instantaneous free-wave ratio (iFR) measurements were included.

Targeting autophagy by antipsychotic phenothiazines: potential drug repurposing for cancer therapy.

Cancer is recognized as the major cause of death worldwide and the most challenging public health issues. Tumor cells exhibit molecular adaptations and metabolic reprograming to sustain their high proliferative rate and autophagy plays a pivotal role to supply the high demand for metabolic substrates and for recycling cellular components, which has attracted the attention of the researchers. The modulation of the autophagic process sensitizes tumor cells to chemotherapy-induced cell death and reverts drug resistance.

Clinical and molecular profiling of human visceral adipose tissue reveals impairment of vascular architecture and remodeling as an early hallmark of dysfunction.

Adipose tissue dysfunction is more related to insulin resistance than body mass index itself and an alteration in adipose tissue function is thought to underlie the shift from metabolically healthy to unhealthy obesity. Herein, we performed a clustering analysis that revealed distinct visceral adipose tissue gene expression patterns in patients with obesity at distinct stages of metabolic dysregulation. We have built a cross-sectional cohort that aims at reflecting the evolution of the metabolic sequelae of obesity with the main objective to map the sequential events that play a role in adipose tissue dysfunction from the metabolically healthy (insulin-sensitive) state to several incremental degrees of metabolic dysregulation, encompassing insulin resistance establishment, pre-diabetes, and type 2 diabetes.

Machine Learning Uncovers Natural Product Modulators of the 5-Lipoxygenase Pathway and Facilitates the Elucidation of Their Biological Mechanisms.

Machine learning (ML) models have made inroads into chemical sciences, with optimization of chemical reactions and prediction of biologically active molecules being prime examples thereof. These models excel where physical experiments are expensive or time-consuming, for example, due to large scales or the need for materials that are difficult to obtain. Studies of natural products suffer from these issues─this class of small molecules is known for its wealth of structural diversity and wide-ranging biological activities, but their investigation is hindered by poor synthetic accessibility and lack of scalability.