Browse Articles

Synergistic effect of defocus incorporated multiple segment glasses and repeated low level red light therapy against myopia progression

Abstract Defocus incorporated multiple segment (DIMS) lenses and repeated low-level red-light (RLRL) are used to retard myopia progression. However, it is currently unknown if there is a synergistic effect of the two interventions. In the current study, 190 school-aged children with myopia (380 eyes) were studied for the change in axial length (AL) over nearly one year of follow-up. Of 380 eyes, 170 eyes wore DIMS lenses, 80 eyes had RLRL therapy, and 130 eyes had both interventions (DIMS_RLRL) for myopia control. AL changes were calculated at each follow-up visit by subtracting the baseline measurements and normalized to yearly changes in mm. AL changes as a primary outcome were analyzed in a generalized linear mixed model to compare effect sizes of myopia control among three interventions while adjusting for age, sex, baseline axial length, and follow-up length. Participants had a mean age of 9.84 ± 2.63 years old, mean AL of 24.49 ± 1.20 mm, mean SER of -2.90 ± 2.08 diopters, and mean follow-up time of 301 ± 91 days. By the end of the study, the adjusted mean yearly axial change with combination therapy was − 0.13 mm, -0.04 mm for the eyes with RLRL alone, and 0.16 mm for the eyes with DIMS lenses alone (p < 0.0001). Combination therapy of DIMS and RLRL has significantly greater effect size in controlling myopia progression than either RLRL alone (p = 0.0009) or DIMS alone (p < 0.0001).

Toxin protein LukS-PV targeting complement receptor C5aR1 inhibits cell proliferation in hepatocellular carcinoma via the HDAC7–Wnt/β-catenin axis

Pairing up with GLP-1 to combat obesity

Me vs. the machine? Subjective evaluations of human- and AI-generated advice

Abstract Artificial intelligence (“AI”) has the potential to vastly improve human decision-making. In line with this, researchers have increasingly sought to understand how people view AI, often documenting skepticism and even outright aversion to these tools. In the present research, we complement these findings by documenting the performance of LLMs in the personal advice domain. In addition, we shift the focus in a new direction—exploring how interacting with AI tools, specifically large language models, impacts the user’s view of themselves. In five preregistered experiments (N = 1,722), we explore evaluations of human- and ChatGPT-generated advice along three dimensions: quality, effectiveness, and authenticity. We find that ChatGPT produces superior advice relative to the average online participant even in a domain in which people strongly prefer human-generated advice (dating and relationships). We also document a bias against ChatGPT-generated advice which is present only when participants are aware the advice was generated by ChatGPT. Novel to the present investigation, we then explore how interacting with these tools impacts self-evaluations. We manipulate the order in which people interact with these tools relative to self-generation and find that generating advice before interacting with ChatGPT advice boosts the quality ratings of the ChatGPT advice. At the same time, interacting with ChatGPT-generated advice before self-generating advice decreases self-ratings of authenticity. Taken together, we document a bias towards AI in the context of personal advice. Further, we identify an important externality in the use of these tools—they can invoke social comparisons of me vs. the machine.

Metabolic dysfunction in mice with adipocyte-specific ablation of the adenosine A2A receptor

FDA approves first HER2 × HER3 bispecific antibody

Bone health in newly diagnosed female breast cancer patients in China: a cross-sectional study

Acidic pH of early endosomes governs SARS-CoV-2 transport in host cells

A spatiotemporal distribution prediction model for electric vehicles charging load in transportation power coupled network

Human calpain-3 and its structural plasticity: Dissociation of a homohexamer into dimers on binding titin

Tracking metal pollution from illegal gold mining: a health risk assessment in Edfu, Egypt

Abstract Over the past decade, there has been an increase in small-scale gold mining in the arid southern region of Egypt. Miners extract ore from the Eastern Desert and transport it to Nile Valley farms, where ample water facilitates the processing. In Edfu, Egypt, the lack of economic opportunities prompted resource-constrained farmers to transform their agricultural lands into gold mines. The study utilized a multifaceted approach that integrated various methodologies, including remote sensing technologies, field surveys, chemical analyses, and statistical methods. The study aimed to assess the concentrations of carcinogenic agents and determine the potential human health risks associated with these agents in soil and fish samples collected within the city boundaries. The study examined correlations between various heavy metals (HMs), such as Ni, Pb, Cd, Cr, Cu, and Hg, in Soilsamples collected in 2020 and 2022. The results revealed direct proportional relationships among specific HMs. The Index of Geoaccumulation (Igeo) and Pollution Load Index (PLI) revealed significantly elevated values in both years, indicating potential environmental degradation. Although no carcinogenic hazards were identified, non-carcinogenic risks related to ingestion were observed for both adults and children exposed to mercury (Hg), copper (Cu), and arsenic (As). Contamination Factor (CF) values were also significantly high. Ecological risks were observed in both Soiland water, as well as in Nile Tilapia samples. Hazard Quotients (HQ) calculated for Nile Tilapia indicated potential risks for both adults and children, particularly associated with elevated arsenic (As) levels. This transformation elicited concerns regarding environmental and health implications, leading us to undertake a thorough investigation.

Regulation of sod1 mRNA and protein abundance by zinc in fission yeast is dependent on the CCR4-NOT complex

The effectiveness of orthodontic treatment with clear aligners in different thicknesses

Bending stiffness of Toxoplasma gondii actin filaments

Harnessing the biology of regulatory T cells to treat disease

Insights into neuromyelitis optica spectrum disorder and pregnancy from a single-center study in Thailand

CBX2 promotes cervical cancer cell proliferation and resistance to DNA-damaging treatment via maintaining cancer stemness

Migratory behaviour of humpback whales in the southeastern Pacific under climate change

Replisomal coupling between the α-pol III core and the τ-subunit of the clamp loader complex (CLC) are essential for genomic integrity in Escherichia coli

Alpha synuclein overexpression can drive microbiome dysbiosis in mice

Abstract Growing evidence indicates that persons with Parkinson disease (PD), have a unique composition of indigenous gut microbes. Given the long prodromal or pre-diagnosed period, longitudinal studies of the human and rodent gut microbiome before symptomatic onset and for the duration of the disease are currently lacking. PD is partially characterized by the accumulation of the protein α-synuclein (α-syn) into insoluble aggregates, in both the central and enteric nervous systems. As such, several experimental rodent and non-human primate models of α-syn overexpression recapitulate some of the hallmark pathophysiologies of PD. These animal models provide an opportunity to assess how the gut microbiome changes with age under disease-relevant conditions. Here, we used a transgenic mouse strain, which overexpress wild-type human α-syn to test how the gut microbiome composition responds in this model of PD pathology during aging. Using shotgun metagenomics, we find significant, age and genotype-dependent bacterial taxa whose abundance becomes altered with age. We reveal that α-syn overexpression can drive alterations to the gut microbiome composition and suggest that it limits diversity through age. Taxa that were most affected by genotype-age interaction were Lactobacillus and Bifidobacteria . In a mouse model, we showed direct link between alpha synuclein geneotype (hallmark of PD), a dysbiotic and low-diversity gut microbiome, and dysbiotic levels of Bifidobacteria and Lactobacillus (most robust features of PD microbiome). Given emerging data on the potential contributions of the gut microbiome to PD pathologies, our data provide an experimental foundation to understand how the PD-associated microbiome may arise as a trigger or co-pathology to disease.