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To adhere to and capitalize on the benefits of the FAIR (findable, accessible, interoperable, and reusable) principles in agricultural genome-to-phenome studies, it is crucial to address privacy and intellectual property issues that prevent sharing and reuse of data in research and industry. Direct sharing of genotype and phenotype data is often prohibited due to intellectual property and privacy concerns. Thus, there is a pressing need for encryption methods that obscure confidential aspects of the data, without affecting the outcomes of certain statistical analyses. A homomorphic encryption method for genotypes and phenotypes (HEGP) has been proposed for single-marker regression in genome-wide association studies (GWAS) using linear mixed models with Gaussian errors. This methodology permits frequentist likelihood-based parameter estimation and inference. In this paper, we extend HEGP to broader applications in genome-to-phenome analyses. We show that HEGP is suited to commonly used linear mixed models for genetic analyses of quantitative traits including genomic best linear unbiased prediction (GBLUP) and ridge-regression best linear unbiased prediction (RR-BLUP), as well as Bayesian variable selection methods (e.g. those in Bayesian Alphabet), for genetic parameter estimation, genomic prediction, and GWAS. By advancing the capabilities of HEGP, we offer researchers and industry professionals a secure and efficient approach for collaborative genomic analyses while preserving data confidentiality.

Cancer-associated cachexia (CAC) is a critical contributor to pancreatic ductal adenocarcinoma (PDAC) mortality. Thus, there is an urgent need for new strategies to mitigate PDAC-associated cachexia; and the exploration of dietary interventions is a critical component. We previously observed that a ketogenic diet (KD) combined with gemcitabine enhances overall survival in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. In this study, we investigated the effect and cellular mechanisms of a KD in combination with gemcitabine on the maintenance of skeletal muscle mass in KPC mice. For this purpose, male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD), a KD, a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. We observed that a KD or a KG-mitigated muscle strength declined over time and presented higher gastrocnemius weights compared CD-fed mice. Mechanistically, we observed sex-dependent effects of KG treatment, including the inhibition of autophagy, and increased phosphorylation levels of eIF2α in KG-treated KPC mice when compared to CG-treated mice. Our data suggest that a KG results in preservation of skeletal muscle mass. Additional research is warranted to explore whether this diet-treatment combination can be clinically effective in combating CAC in PDAC patients.

Pancreatic ductal adenocarcinoma (PDAC) continues to be a major health problem. A ketogenic diet (KD), characterized by a very low carbohydrate and high fat composition, has gained attention for its anti-tumor potential. We evaluated the effect and mechanisms of feeding a strict KD alone or in combination with gemcitabine in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. For this purpose, both male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD; %kcal: 70% carb, 14% protein, 16% fat), a KD (%kcal: 14% protein, 1% carb, 85% fat), a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. Mice fed a KD alone or in combination with gemcitabine showed significantly increased blood β-hydroxybutyrate levels compared to mice fed a CD or CG. KPC mice fed a KG had a significant increase in overall median survival compared to KPC mice fed a CD (increased overall median survival by 42%). Interestingly, when the data was disaggregated by sex, the effect of a KG was significant in female KPC mice (60% increase in median overall survival), but not in male KPC mice (28% increase in median overall survival). Mechanistically, the enhanced survival response to a KD combined with gemcitabine was multifactorial, including inhibition of ERK and AKT pathways, regulation of fatty acid metabolism and the modulation of the gut microbiota. In summary, a KD in combination with gemcitabine appears beneficial as a treatment strategy in PDAC in KPC mice, deserving further clinical evaluation.

Because of the Covid-19 pandemic, urgent surging demand for healthcare products such as personal protective equipment (PPE) has caused significant challenges for multi-tier supply chain management. Although a given firm may predominantly focus on an arms-length solution by targeting the first-tier supplier, the firm can still struggle with extended multi-tier suppliers it cannot choose which use unsustainable practices. One key goal is compliance across various dimensions with production, environmental and labour standards across the multi-tier supply chain, a goal that blockchain technology can be applied to manage. Based on a comprehensive literature review, this research develops a system architecture of blockchain-based multi-tier sustainable supply chain management in the PPE industry designed to identify and coordinate standards in production and social and environmental sustainability in multi-tier PPE supply chains. The architecture was validated by theoretical basis, expert opinions and technical solutions. We conclude with managerial implications for implementing blockchain technology to advance sustainable multi-tier supply chain practices. [ABSTRACT FROM AUTHOR]

Urban reservoirs contribute significantly to human survival and ecological balance. Machine learning-based remote sensing techniques for monitoring water quality parameters (WQPs) have gained increasing prominence in recent years. However, these techniques still face challenges such as inadequate band selection, weak machine learning model performance, and the limited retrieval of non-optical active parameters (NOAPs). This study focuses on an urban reservoir, utilizing unmanned aerial vehicle (UAV) multispectral remote sensing and ensemble machine learning (EML) methods to monitor optically active parameters (OAPs, including Chla and SD) and non-optically active parameters (including CODMn, TN, and TP), exploring spatial and temporal variations of WQPs. A framework of Feature Combination and Genetic Algorithm (FC-GA) is developed for feature band selection, along with two frameworks of EML models for WQP estimation. Results indicate FC-GA's superiority over popular methods such as the Pearson correlation coefficient and recursive feature elimination, achieving higher performance with no multicollinearity between bands. The EML model demonstrates superior estimation capabilities for WQPs like Chla, SD, CODMn, and TP, with an R2 of 0.72–0.86 and an MRE of 7.57–42.06%. Notably, the EML model exhibits greater accuracy in estimating OAPs (MRE ≤ 19.35%) compared to NOAPs (MRE ≤ 42.06%). Furthermore, spatial and temporal distributions of WQPs reveal nitrogen and phosphorus nutrient pollution in the upstream head and downstream tail of the reservoir due to human activities. TP, TN, and Chla are lower in the dry season than in the rainy season, while clarity and CODMn are higher in the dry season than in the rainy season. This study proposes a novel approach to water quality monitoring, aiding in the identification of potential pollution sources and ecological management. [ABSTRACT FROM AUTHOR]

AbstractThis study explored the influence of genetic and environmental factors on adolescent anxiety. Ninety-eight monozygotic and dizygotic twins from Chongqing, China (aged 15–18 years) were assessed for anxiety with the Self-Rating Anxiety Scale (SAS). The Parenting Styles and Dimensions Questionnaire (PSDQ) and Strengths and Difficulties Questionnaire (SDQ) were applied to assess environmental factors. Venous blood was drawn from the twins for zygosity determination. Structural equation modeling was performed to evaluate the effects of additive genetic factors (A), common environmental factors (C), and individual-specific environmental factors (E) on adolescent anxiety. The estimates of A and E on adolescent anxiety were 0.34 (95% CI = 0.12–0.53) and 0.66 (95% CI:0.47–0.89), respectively. The environment played an important role in adolescent anxiety. Adolescent anxiety was significantly positively correlated with peer relations (r = 0.606, p < 0.05) and negatively correlated with prosocial behavior (r = 0.207, p < 0. 05). No sex differences were observed. Adolescent anxiety was influenced by both genetic and environmental factors. The individual-specific environmental factors played an important role. Consideration of these variables will facilitate the targeted and individualized implementation of specific interventions for adolescent anxiety. [ABSTRACT FROM AUTHOR]

Consistently sleeping 5 hours or less per night will increase the development of various health issues. Dihydromyricetin (DHM) could reduce oxidative stress and promote longevity, but its effectiveness in alleviating sleep deprivation remains unclear. Thus, we established a sleep-deprived Drosophila model by prolonged illumination, named light-prolonged Drosophila (LPD), to explore this problem. Results showed that DHM enhanced the sleep quality of the LPD and expanded their lifespan, by reducing their nocturnal activities, decreasing intestinal epithelial cell mortality, and restoring glucose and glutathione levels. Transcriptome analysis and RT-qPCR results showed that DHM has the potential to modulate Drosophila's gut immunity and mitigate mitochondrial oxidative stress. Furthermore, we found that DHM can inhibit the expression of TIM, Pi3k, and TOR, then decrease Tsc1, while simultaneously promoting FoxO and Thor. In conclusion, DHM could be used as an effective intervention for enhancing sleep quality and counteracting the detrimental of sleep deprivation on lifespan. [ABSTRACT FROM AUTHOR]

Phytolith-occluded Ccarbon (PhytOC) is an important carbon sink in wetland ecosystems and a mechanism for long-term carbon sequestration. In recent years, nitrogen pollution has become increasingly severe and poses a threat to the healthy development of coastal ecological environments and socio-economic development; therefore, studying the impact of nitrogen deposition on the sequestration potential of PhytOC in the soil of coastal wetlands is highly significant. In the present study, two indoor tidal simulation experiments were set up with and without the planting of vegetation. The sequestration capacity and factors that influence soil PhytOC in the Kandelia obovata soil system were compared and analyzed under five nitrogen concentrations. The analysis shows that with the introduction of Kandelia obovata, the occluded carbon content of the soil phytoliths was significantly increased by 31.45% compared with the non-plant group, and the PhytOC content of the soil increased by 7.94%. The exogenous nitrogen input reduced the PhytOC content of the soil, with a rate of decline exceeding 26%. The PhytOC of the soil phytoliths and the PhytOC content of the soil in the planting group increased with increasing nitrogen concentration, while that of the non-plant group decreased as the concentration of nitrogen increased. The non-plant group was more affected by the exogenous nitrogen concentration than the planting group, and the soil microbial biomass carbon and microbial biomass nitrogen were the main factors that influenced changes in the PhytOC. In conclusion, nitrogen input has a significant inhibitory effect on soil PhytOC sequestration potential in coastal wetlands. Planting Kandelia obovata helps to improve the stability of carbon in wetland soil. [ABSTRACT FROM AUTHOR]