Differential effects of warming on carbon budget, photosynthetic yield and biochemical composition of cold-temperate and Arctic isolates of Laminaria digitata (Phaeophyceae).

Cold-temperate and Arctic hard bottom coastal ecosystems are dominated by kelp forests, which have a high biomass production and provide important ecosystem services, but are subject to change due to ocean warming. However, the photophysiological response to increasing temperature of ecologically relevant species, such as Laminaria digitata, might depend on the local thermal environment where the population has developed. Therefore, the effects of temperature on growth rate, biochemical composition, maximum quantum yield, photosynthetic quotient and carbon budget of young cultured sporophytes of Laminaria digitata from the Arctic at Spitsbergen (SPT; cultured at 4, 10 and 16 °C) and from the cold-temperate North Sea island of Helgoland (HLG; cultured at 10, 16 and 22 °C) were comparatively analyzed.

Deep learning aided determination of the optimal number of detectors for photoacoustic tomography.

Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.

Cell-Instructive Biomaterials with Native-Like Biochemical Complexity.

Biochemical signals in native tissue microenvironments instruct cell behavior during many biological processes ranging from developmental morphogenesis and tissue regeneration to tumor metastasis and disease progression. The detection and characterization of these signals using spatial and highly resolved quantitative methods have revealed their existence as matricellular proteins in the matrisome, some of which are bound to the extracellular matrix while others are freely diffusing. Including these biochemical signals in engineered biomaterials can impart enhanced functionality and native-like complexity, ultimately benefiting efforts to understand, model, and treat various diseases.

Digital Home-Based Self-Monitoring System for People with Heart Failure: Protocol for Development of SmartHeart and Evaluation of Feasibility and Acceptability.

Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.

User and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study.

Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.

Value Propositions for Digital Shared Medication Plans to Boost Patient-Health Care Professional Partnerships: Co-Design Study.

Background: Health authorities worldwide have invested in digital technologies to establish robust information exchange systems for improving the safety and efficiency of medication management. Nevertheless, inaccurate medication lists and information gaps are common, particularly during care transitions, leading to avoidable harm, inefficiencies, and increased costs. Besides fragmented health care processes, the inconsistent incorporation of patient-driven changes contributes to these problems.

Macrophage activity modulation via synergistic effect of a porous substrate and low-field laser therapy.

: The aim of this study was to investigate the effect of substrate - polycaprolactone (PCL)-based porous membrane modified with rosmarinic acid (RA), (PCL-RA) and to determine the optimal values of low field laser irradiation (LLLT) as stimulators of biological response of RAW 264.7 macrophages. : The porous polymer membrane was obtained by the phase inversion method, the addition of rosmarinic acid was 1%wt.

Investigating Pb2 CAP-binding domain inhibitors from marine bacteria for targeting the influenza A H5N1.

The ongoing increase in the prevalence and mutation rate of the influenza virus remains a critical global health issue. A promising strategy for antiviral drug development involves targeting the RNA-dependent RNA polymerase, specifically the PB2-cap binding domain of Influenza A H5N1. This study employs an in-silico approach to inhibit this domain, crucial for viral replication, using potential inhibitors derived from marine bacterial compounds.

Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. Part III: partitioning into torsional groups.

We present an approach to reduce this computational cost substantially, based on the partitioning of the molecule into geometrically separated torsional groups, with the dependence of the intramolecular energy and atomic point charges and dependent degrees of freedom on molecular conformation being computed as a linear combination of the contributions of these groups. This can lead to large savings in computational cost without a significant impact on accuracy, as demonstrated in the cases of N-acetyl-para-aminophenol (paracetamol) and methyl 4-hydroxybenzoate (methyl paraben). The approach is also applied successfully to two larger molecules, benzyl [4-(4-methyl-5-[(4-methylphenyl)sulfonyl]-1,3-thiazol-2-yl)phenyl]carbamate (molecule XX from the fifth CSP blind test) and (2S)-2-[4-(3-fluorobenzyloxy)benzylamino]propionamide (safinamide), for which we conduct the first reported CSP study.

A Comprehensive Evaluation of the Neuropharmacological Potential of Methanolic Leaf Extract of Acanthus ebracteatus (Vahl.) Using Experimental and In Silico Approaches.

This study was undertaken to assess the antioxidant and neuropharmacological potentials of the methanol leaf extract of Acanthus ebracteatus (MAEL) through experimental and in silico methods. The phytochemical screening (PS) and GC-MS (gas chromatography-mass spectrometry) identified 28 phytochemicals with different classes in nature in MAEL. The MAEL revealed better antioxidant activity through various in vitro antioxidant assays.

Prevalence, aetiology and antimicrobial resistance profile of diabetic individuals suffering from community-acquired urinary tract infection.

The rise in antimicrobial resistance poses a significant threat to global health, particularly among diabetic patients who are prone to urinary tract infections (UTIs). Pathogens that cause UTI among diabetic patients exhibit significant multidrug resistance (MDR) patterns, necessitating more precise empirical treatment strategies..

Description of six novel species sp. nov., sp. nov., sp. nov., sp. nov., sp. nov. and sp. nov., isolated from mangrove ecosystem.

Six Gram-stain-positive and rod-shaped strains, designated FJAT-51614, FJAT-51639, FJAT-52054, FJAT-52991, FJAT-53654 and FJAT-53711, were isolated from a mangrove ecosystem. The condition for growth among the strains varied (pH ranging 5.0-11.

The Added Effect of Artificial Intelligence in CT Assessment of Abdominal Lymphadenopathy.

Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).

Screening of Oncogenic Proteins and Development of a Multiepitope Peptide Vaccine Targeting AKT1 and PARP1 for Breast Cancer by Integrating Reverse Vaccinology and Immune-Informatics Approaches.

Background: Breast cancer remains a significant global health challenge, requiring innovative therapeutic strategies. In silico methods, which leverage computational tools, offer a promising pathway for vaccine development. These methods facilitate antigen identification, epitope prediction, immune response modelling, and vaccine optimization, accelerating the design process.

Staging at Diagnosis and Survival of Hematologic Neoplasms in Children and Adolescents in Mato Grosso, Brazil: A Population-based Study.

Objective: To apply the Toronto Childhood Cancer Staging Guidelines (TG) and Estimate the Observed Survival Probabilities for Pediatric Patients with Leukemia and Lymphoma.

Methods: Staging at diagnosis was conducted according to tier 2 of the TG. The study cohort included patients aged 0 -19 years from the Population-Based Cancer Registry (PBCR) of Mato Grosso, diagnosed with leukemia and lymphoma between 2008 and 2017, with follow-up until December 31, 2022.

Enhanced ZBTB10 expression induced by betulinic acid inhibits gastric cancer progression by inactivating the ARRDC3/ITGB4/PI3K/AKT pathway.

Background: Gastric cancer (GC) ranks as the fourth leading cause of cancer-related deaths worldwide, with most patients diagnosed at advanced stages due to the absence of reliable early detection biomarkers.

Methods: RNA-sequencing was conducted to identify the differentially expressed genes between GC tissues and adjacent normal tissues. CCK8, EdU, colony formation, transwell, flow cytometry and xenograft assays were adopted to explore the biological function of ZBTB10 and betulinic acid (BA) in GC progression.

Center-Based Childcare Access to Health Screenings and Developmental Assessments in U.S. Children from Birth to Five.

Objective: To examine the odds of children aged 0-5 in center-based childcare programs receiving referrals for health screenings and developmental assessments, controlling for children's races/ethnicities and provider and program factors.

Methods: We conducted secondary analyses using the 2019 National Survey for Early Care and Education (NSECE) Center-based Provider survey. We used multivariate logistic regression models to estimate referral odds for health screenings and developmental assessments from centers without these services onsite.

The bioavailability and blood levels of low-dose rapamycin for longevity in real-world cohorts of normative aging individuals.

Rapamycin, also known as sirolimus, has demonstrated great potential for application in longevity medicine. However, the dynamics of low-dose rapamycin bioavailability, and any differences in bioavailability for different formulations (e.g.

Bioinformatics and immunoinformatics approaches in the design of a multi-epitope vaccine targeting CTLA-4 for melanoma treatment.

Melanoma, a highly aggressive skin cancer, remains a significant cause of mortality despite advancements in therapeutic strategies. There is an urgent demand for developing vaccines that can elicit strong and comprehensive immune responses against this malignancy. Achieving this goal is crucial to enhance the efficacy of immunological defense mechanisms in combating this disease.

Carboxy-Amidated AamAP1-Lys has Superior Conformational Flexibility and Accelerated Killing of Gram-Negative Bacteria.

C-terminal amidation of antimicrobial peptides (AMPs) is a frequent minor modification used to improve antibacterial potency, commonly ascribed to increased positive charge, protection from proteases, and a stabilized secondary structure. Although the activity of AMPs is primarily associated with the ability to penetrate bacterial membranes, hitherto the effect of amidation on this interaction has not been understood in detail. Here, we show that amidation of the scorpion-derived membranolytic peptide AamAP1-Lys produces a potent analog with faster bactericidal activity, increased membrane permeabilization, and greater Gram-negative membrane penetration associated with greater conformational flexibility.

Machine Learning Interatomic Potential for Modeling the Mechanical and Thermal Properties of Naphthyl-Based Nanotubes.

Two-dimensional (2D) nanomaterials are at the forefront of potential technological advancements. Carbon-based materials have been extensively studied since synthesizing graphene, which revealed properties of great interest for novel applications across diverse scientific and technological domains. New carbon allotropes continue to be explored theoretically, with several successful synthesis processes for carbon-based materials recently achieved.

Comparison of different microbiome analysis pipelines to validate their reproducibility of gastric mucosal microbiome composition.

Microbiome analysis has become a crucial tool for basic and translational research due to its potential for translation into clinical practice. However, there is ongoing controversy regarding the comparability of different bioinformatic analysis platforms and a lack of recognized standards, which might have an impact on the translational potential of results. This study investigates how the performance of different microbiome analysis platforms impacts the final results of mucosal microbiome signatures.

A point mutation in a like gene in enhances the anticorrosion activity.

The protection of steel based on microbial biomineralization has emerged as a novel and eco-friendly strategy for corrosion control. However, the molecular basis of the biomineralization process in mineralization bacteria remains largely unexplored. We previously reported that EPS+ strain provides protection against steel corrosion by forming a hybrid biomineralization film.