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Fragile X syndrome (FXS) is the most common form of inherited intellectual disability and is closely linked with autism. The genetic basis of FXS is an expansion of CGG repeats in the 5'-untranslated region of the FMR1 gene on the X chromosome leading to the loss of expression of the fragile X mental retardation protein (FMRP). The cause of FXS has been known for over 20 years, yet the full molecular and cellular consequences of this mutation remain unclear. Although mouse and fly models have provided significant understanding of this disorder and its effects on the central nervous system, insight from human studies is limited. We have created human induced pluripotent stem cell (iPSC) lines from fibroblasts obtained from individuals with FXS to enable in vitro modeling of the human disease. Three young boys with FXS who came from a well-characterized cohort representative of the range of affectedness typical for the syndrome were recruited to aid in linking cellular and behavioral phenotypes. The FMR1 mutation is preserved during the reprogramming of patient fibroblasts to iPSCs. Mosaicism of the CGG repeat length in one of the patient's fibroblasts allowed for the generation of isogenic lines with differing CGG repeat lengths from the same patient. FXS forebrain neurons were differentiated from these iPSCs and display defective neurite initiation and extension. These cells provide a well-characterized resource to examine potential neuronal deficits caused by FXS as well as the function of FMRP in human neurons.

AbstractFood festivals play a significant role in driving economic growth and facilitating cultural exploration. However, they also present challenges to sustainability, particularly concerning food waste, which is further exacerbated by the pervasive "Camera Eats First" (CEF) phenomenon. Despite its importance, academic literature has given limited attention to this issue. This study bridges this gap by applying an extended value-attitude-behavior theory to explore food waste behaviors at food festivals, focusing on the moderating role of CEF. Employing partial least squares structural equation modeling and fuzzy-set qualitative comparative analysis, it develops the Food Festival Consumption Values (FFCVs) model, incorporating factors like food taste, healthiness, appearance, peer influence, and festival atmosphere, tested with data from 452 consumers at the 22nd Macau Food Festival. Findings reveal direct influences of factors such as food taste, healthiness, and festival atmosphere on food waste behavior. However, the mediating and moderating effects of attitudes toward food waste and CEF exhibit mixed results. These results underscore the need for targeted waste reduction strategies, contributing to sustainable food festival management and aligning with United Nations Sustainable Development Goal 12.3, enhancing policy and stakeholder efforts toward sustainability. [ABSTRACT FROM AUTHOR]

• Compare with the lower SI group, the higher SI are, the higher cognitive scores they will gain. • SI reveal a pronounced linear relationship with cognitive scores. • In older women with normal kidney function, enhance SI may help them to improve cognitive performance. The Sarcopenia Index (SI) has the potential as a biomarker for sarcopenia, which is characterized by muscle loss. There is a clear association between sarcopenia and cognitive impairment. However, the relationship between SI and cognitive impairment is yet to be fully understood. We employed data extracted from the U.S. National Health and Nutrition Examination Survey (NHANES) spanning the years 1999 to 2002. Our study encompassed individuals aged 65 to 80 who possessed accessible information regarding both SI and cognitive evaluations with a GFR ≥ 90. Cognitive function was assessed using the digit symbol substitution test (DSST). SI was calculated by serum creatinine (mg/dL)/cystatin C (mg/L)*100. Employing multivariate modeling, we estimated the connection between SI and cognitive performance. Furthermore, to enhance the reliability of our data analysis, we categorized SI using tertiles and subsequently calculated the P-value for trend. After adjustment for potential confounders, we found SI was significantly and positively correlated with cognitive function scores both in older female in the American population [β = 0.160, 95 % confidence interval (CI) 0.050 to 0.271, P = 0.00461]. Similarly, when the total cognitive function score was treated as a categorical variable according to tertiles, higher SI was related to better total cognitive function scores in females [odds ratio (OR) = 3.968, 95 % CI 1.863 to 6.073, P = 0.00025] following adjustment for confounders. Higher SI was correlated with a lower prevalence of cognitive impairment among older adult women with normal kidney function. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is currently the most harmful greenhouse gas in the atmosphere. Obtaining long-term, high-resolution atmospheric column CO2 concentration (XCO2) datasets is of great practical significance for mitigating the greenhouse effect, identifying and controlling carbon emission sources, and achieving carbon cycle management. However, mainstream satellite observations provide XCO2 datasets with coarse spatial resolution, which is insufficient to support the needs of higher-precision research. To address this gap, in this study, we integrate spatial information with the extreme random trees model and develop a new machine learning model called spatial extreme random trees (SExtraTrees) to reconstruct a 1 km spatial resolution XCO2 dataset for China from 2016 to 2020. The results indicate that the predictive ability of spatial extreme random trees is more stable and has higher fitting accuracy compared to other methods. Overall, XCO2 in China shows an increasing trend year by year, with the spatial distribution revealing significantly higher XCO2 levels in eastern coastal regions compared to western inland areas. The contributions of this study are primarily in the following areas: (1) Considering the spatial heterogeneity of XCO2 and combining spatial features with the advantages of machine learning, we construct the spatial extreme random trees model, which is verified to have high predictive accuracy. (2) Using the spatial extreme random trees model, we reconstruct high-resolution XCO2 datasets for China from 2016 to 2020, providing data support for carbon emission reduction and related decision making. (3) Based on the generated dataset, we analyze the spatiotemporal distribution patterns of XCO2 in China, thereby improving emission reduction policies and sustainable development measures. [ABSTRACT FROM AUTHOR]

Researchers traditionally compute isolated points for an efficient frontier and assume a line which passes through a risk-free asset r f and is tangent to the frontier. The tangency plays pivotal roles for the capital asset pricing model (CAPM). However, the assumption may not hold in the presence of kinks (as non-differentiable points) on efficient frontiers. Kinks are detected by parametric-quadratic programming only and not by ordinary portfolio optimization. Up until now, there has been no research to theoretically scrutinize kink properties (especially implications to CAPM) and systematically quantify the nonexistence of the tangency. In such an area, this paper contributes to the literature. In theorems and corollaries, we prove the nonexistence of the tangency and substantiate that expected-return axis is composed of piecewisely connected intervals for which the tangency does not exist and intervals for which the tangency exists. Computationally, we reveal universal existence of kinks (e.g., 0.2 to 8.0 kinks for 5-stock to 1800-stock portfolio selections) and the tangency-nonexistence ratios as about 0.066. [ABSTRACT FROM AUTHOR]

Understanding the impact of drought on agriculture is critical for reducing drought-related yield losses in the Koshi River Basin, Nepal. This study used the Standardized Potential Evapotranspiration Index (SPEI) to analyze drought during the crop growing season. The Lagrange interpolation method was employed to identify expected crop yields and to quantify crop yield losses in the Koshi River Basin, Nepal. Finally, the correlation method was applied to observe the relationship between yield loss and drought in the basin. Spatially, the growing seasons of maize, rice, and wheat in the hill region exhibited a more pronounced increase in the drought trend compared to the mountain and Terai regions. Similarly, the maize growing season demonstrated a more significant increasing drought trend than rice and wheat across all regions. However, the wheat growing season in the mountain exhibited an increasing drought trend. The correlations between the detrended SPEI and crop yield loss revealed that maize yields in the Terai and mountain regions are sensitive to drought in both the early stages (from sowing to tasseling) and later stages (milking, seed ripening) in the hill. Similarly, rice yields are sensitive to drought from the plant elongation to ripening in both the hill and Terai regions. Wheat yield analysis showed a weak positive relationship in all regions. The findings of our study can enhance understanding of drought conditions and their impact on crop growth stages, thereby assisting local farmers and agricultural institutions in managing crop yield loss. [ABSTRACT FROM AUTHOR]

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Xinjiang has abundant cotton by-products resources, but their utilization rate is relatively low. Cotton by-products include cotton stalks, cottonseed meal, cottonseed hulls, cottonseed residue, and more. Among them, cottonseed meal is an important protein source in livestock and poultry production, while cotton stalks, cottonseed hulls, and cottonseed residue can serve as coarse feed sources for ruminant animals. However, the long-term application of cotton by-products in the livestock and poultry breeding industry is constrained due to the presence of anti-nutritional factors such as free gossypol and the relatively high crude fiber content in cotton stalks, cottonseed hulls, and cottonseed residue. The article reviews the production, types, nutritional value of cotton by-products, and their research and application in the livestock and poultry breeding industry, aiming to provide a reference for further application of cotton by-products in the livestock and poultry breeding industry. [ABSTRACT FROM AUTHOR]

Proprotein convertase subtilisin/kexin type 9 (PCSK9) has attracted lots of attention in preventing the clearance of plasma low‐density lipoprotein cholesterol (LDL‐C). PCSK9 inhibitors are developed to primarily reduce the cardiovascular risk by lowering LDL‐C level. Recently, a number of pleiotropic extrahepatic functions of PCSK9 beyond the regulation of cholesterol metabolism, particularly its effects on central nervous system (CNS) diseases have been increasingly identified. Emerging clinical evidence have revealed that PCSK9 may play a significant role in neurocognition, depression, Alzheimer's disease, and stroke. The focus of this review is to elucidate the functions of PCSK9 and highlight the effects of PCSK9 in CNS diseases, with the aim of identifying the potential risks that may arise from low PCSK9 level (variant or inhibitor) in the clinical practice. [ABSTRACT FROM AUTHOR]

Solid–liquid phase equilibria of the quaternary system (Li+,K+// , –H2O) and its subsystem are very important for the separation of lithium and potassium salts from the salt lake brines. In this paper, the solubilities, densities, refractive indices and pH values of the reciprocal quaternary system (Li+,K+// , –H2O) at 308.15 K were determined experimentally using the isothermal dissolution method. The dry-salt diagram and water-phase diagram were plotted based on the experimental data. The stable phase diagram contains four invariant points, nine univariant curves and six crystallization regions corresponding to Li2CO3, Li2CO3⋅K2CO3, K2CO3⋅1.5H2O, Li2SO4⋅H2O, K2SO4, and Li2SO4⋅K2SO4. Li2CO3 has the largest crystallization field, whereas the Li2CO3⋅K2CO3 crystallization field is the smallest one. [ABSTRACT FROM AUTHOR]