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BACKGROUND: Gene-environment interactions contribute to metabolic disorders such as diabetes and dyslipidemia. In addition to affecting metabolic homeostasis directly, drugs and environmental chemicals can cause persistent alterations in metabolic portfolios across generations in a sex-specific manner. Here, we use inorganic arsenic (iAs) as a prototype drug and chemical to dissect such sex differences. METHODS: After weaning, C57BL/6 WT male mice were treated with 250 ppb iAs in drinking water (iAsF0) or normal water (conF0) for 6 weeks and then bred with 15-week-old, non-exposed females for 3 days in cages with only normal water (without iAs), to generate iAsF1 or conF1 mice, respectively. F0 females and all F1 mice drank normal water without iAs all the time. RESULTS: We find that exposure of male mice to 250 ppb iAs leads to glucose intolerance and insulin resistance in F1 female offspring (iAsF1-F), with almost no change in blood lipid profiles. In contrast, F1 males (iAsF1-M) show lower liver and blood triglyceride levels than non-exposed control, with improved glucose tolerance and insulin sensitivity. The liver of F1 offspring shows sex-specific transcriptomic changes, with hepatocyte-autonomous alternations of metabolic fluxes in line with the sex-specific phenotypes. The iAsF1-F mice show altered levels of circulating estrogen and follicle-stimulating hormone. Ovariectomy or liver-specific knockout of estrogen receptor α/β made F1 females resemble F1 males in their metabolic responses to paternal iAs exposure. CONCLUSIONS: These results demonstrate that disrupted reproductive hormone secretion in alliance with hepatic estrogen signaling accounts for the sex-specific intergenerational effects of paternal iAs exposure, which shed light on the sex disparities in long-term gene-environment interactions.

Immune checkpoint inhibitors (ICIs) have been increasingly used in combination for cancer treatment but are associated with myocarditis. Here, we report that tumor-bearing mice exhibited response to treatment with combinatorial anti-programmed cell death 1 and anti-cytotoxic T lymphocyte antigen-4 antibodies but also presented with cardiovascular toxicities observed clinically with ICI therapy, including myocarditis and arrhythmia. Female mice were preferentially affected with myocarditis compared to male mice, consistent with a previously described genetic model of ICI myocarditis and emerging clinical data. Mechanistically, myocardial tissue from ICI-treated mice, the genetic mouse model, and human heart tissue from affected patients with ICI myocarditis all exhibited down-regulation of MANF (mesencephalic astrocyte-derived neurotrophic factor) and HSPA5 (heat shock 70-kDa protein 5) in the heart; this down-regulation was particularly notable in female mice. ICI myocarditis was amplified by heart-specific genetic deletion of mouse Manf and was attenuated by administration of recombinant MANF protein, suggesting a causal role. Ironically, both MANF and HSPA5 were transcriptionally induced by liganded estrogen receptor β and inhibited by androgen receptor. However, ICI treatment reduced serum estradiol concentration to a greater extent in female compared to male mice. Treatment with an estrogen receptor β-specific agonist and androgen depletion therapy attenuated ICI-associated cardiac effects. Together, our data suggest that ICI treatment inhibits estradiol-dependent expression of MANF/HSPA5 in the heart, curtailing the cardiomyocyte response to immune injury. This endocrine-cardiac-immune pathway offers new insights into the mechanisms of sex differences in cardiac disease and may offer treatment strategies for ICI myocarditis.

Lysosomes are key cellular organelles that metabolize extra- and intracellular substrates. Alterations in lysosomal metabolism are implicated in ageing-associated metabolic and neurodegenerative diseases. However, how lysosomal metabolism actively coordinates the metabolic and nervous systems to regulate ageing remains unclear. Here we report a fat-to-neuron lipid signalling pathway induced by lysosomal metabolism and its longevity-promoting role in Caenorhabditis elegans. We discovered that induced lysosomal lipolysis in peripheral fat storage tissue upregulates the neuropeptide signalling pathway in the nervous system to promote longevity. This cell-non-autonomous regulation is mediated by a specific polyunsaturated fatty acid, dihomo-γ-linolenic acid, and LBP-3 lipid chaperone protein transported from the fat storage tissue to neurons. LBP-3 binds to dihomo-γ-linolenic acid, and acts through NHR-49 nuclear receptor and NLP-11 neuropeptide in neurons to extend lifespan. These results reveal lysosomes as a signalling hub to coordinate metabolism and ageing, and lysosomal signalling mediated inter-tissue communication in promoting longevity.

Virtual track trains are a new type of rail transportation because the multisection formation structure leads to more degrees of freedom of the vehicle, which may cause unstable phenomena, such as tailing, cross-swing, and folding, affecting the stability and ride comfort of the vehicle driving. To explore the effect of damping coefficient of the articulated systems on vehicle dynamics performance, a vehicle system dynamics model is established based on the actual parameters of a three-module six-axle virtual track train. According to ISO14791: 2000, select typical working conditions such as straight line, lane change, and 1/4 circle curve, and optimize the damping coefficient of the articulated systems through co-simulation. The study shows that under straight-line conditions, increasing the damping coefficient can effectively suppress the yaw angular acceleration and improve the lateral ride comfort of the vehicle but has little effect on the vertical ride comfort. Under lane change conditions, too large or small damping coefficients will deteriorate the train’s lateral stability, and a reasonable damping coefficient will improve the yaw damping ratio of the vehicle and reduce the lateral sway vibration between vehicles. Under the 1/4 circle curve conditions, the additional articulated system damper will reduce the vehicle’s curve passing performance. In this paper, the articulation stability of multimodule fully connected vehicles is analyzed and optimized for the first time, and the damping coefficient control strategy is given based on the geometric tracking control method. The research results are of great significance for the parameter selection of virtual track trains’ articulated system and the design and development of specialized articulated systems for related vehicles.

In order to solve the problems of pesticides abuse, nonuniformity deposition and low operating efficiency, build up the smart mango orchard, sedimentary properties of liquids in mango canopy of two orchard pesticide machinery, i.e., orchard caterpillar mist sprayer and six-rotor unmanned aerial vehicle (UAV) of were compared. Mango canopy was divided into upper, middle and lower canopy, tartrazine wsa selected as the tracer, high-definition printing paper and filter paper were used to collect pesticide droplets, the image processing methods such as deposition distribution uniformity were used to analyze the droplets. The experimental results showed that, for the surface droplets coverage rate of upper canopy leaf, unmanned aerial vehicle (UAV) was significantly higher than the cartipillar mist sprayer, there was no significant difference for the middle and lower canopy leaf. The the average coverage rate of both the front and back of leaves in UAV treatment group were 1.5~2 times for cartipillar mist sprayer, and got more deposition in back of leaves compare with caterpillar mist sprayer. The density of droplets on the front of the leaves of the mist sprayer treatment was significantly higher than that of the UAV treatment, but there was no significant difference on the back of the leaves. Both the front and back of the leaves of the plant protection UAV did not meet the requirements of disease and pest control with a low spray amount of 20/cm2. The liquid deposition of mist sprayer concentrated in the middle and lower canopy (61.1%), and while for the UAVs, it concentrated in the upper canopy (43.0%). The proportion of the deposition in the canopy was higher than that of the UAVs (48.6%), but the deposition capacity of mist sprayer in the upper canopy was insufficient, accounting for only 17%. The research shows that, compared with UAV, caterpillar mist sprayer is more suitable for the pest control of lower and middlein canopy, at the same time, the high density of droplets cover also has obvious advantages when spraying fungicide. UAV is more suitable for the external tidbits pest control of upper mango canopy, such as thrips, anthrax. According to the experimental results, a stereoscopic plant protection system can be built up in which can use the advantages of both caterpillar mist sprayer and UAV to achieve uniform coverage of pesticide in the mango tree canopy.

Traditional orchard production is facing problems of labor shortage due to the aging, difficulties in the management of agricultural equipment and production materials, and low production efficiency which can be expected to be solved by building a smart orchard that integrates technologies of Internet of Things(IoT), big data, equipment intelligence, et al. In this study, based on the objectives of full mechanization and intelligent management, a smart orchard was built in Pinggu district, an important peaches and pears fruit producing area of Beijing. The orchard covers an aera of more than 30 hm2 in Xiying village, Yukou town. In the orchard, more than 10 kinds of information acquisition sensors for pests, diseases, water, fertilizers and medicines are applied, 28 kinds of agricultural machineries with intelligent technical support are equipped. The key technologies used include: intelligent information acquisition system, integrated water and fertilizer management system and intelligent pest management system. The intelligent operation equipment system includes: unmanned lawn mower, intelligent anti-freeze machine, trenching and fertilizer machine, automatic driving crawler, intelligent profiling variable sprayer, six-rotor branch-to-target drone, multi-functional picking platform and finishing and pruning machine, etc. At the same time, an intelligent management platform has been built in the smart orchard. The comparison results showed that, smart orchard production can reduce labor costs by more than 50%, save pesticide dosage by 30% ~ 40%, fertilizer dosage by 25% ~ 35%, irrigation water consumption by 60% ~ 70%, and comprehensive economic benefits increased by 32.5%. The popularization and application of smart orchards will further promote China's fruit production level and facilitate the development of smart agriculture in China.

Seawater temperature and salinity are basic marine environmental parameters, which can be used to calculate other marine environmental parameters. However, most of the on-site observation data have the problems of uneven spatial distribution and time discontinuity, and it is difficult for remote sensing observation methods to obtain subsurface information. In this study, we proposed a deep learning model with combining remote sensing temperature and salinity as well as in-situ measured data by Argo profiles, and the nonlinear relationship was revealed. An effective and direct inversion method was realized for underwater three-dimensional thermohaline structure based on remote sensing temperature and salinity at accurate points on global scale. The SST data were obtained from the FY3C-VIRR daily sea surface temperature product, the SSS data were acquired from the SMAP Level 3 8-day running averages sea surface salinity product, and the Argo scatter data were got from the 'Global Ocean Argo Scatter Data Set'. Based on the temporal and spatial location information of the data, this paper matched the remote sensing data from 2016 to 2019 with the Argo data, 64751 valid pairing points were obtained. The deep learning model was constructed as a multilayer perceptron model with 5 hidden layers. The RMSE of temperature had a maximum value of 2.106°C in 130 m depth and a minimum value of 0.367°C in 1000 m with an average of 1.174°C for validation dataset. And the RMSE of salinity had a maximum value of 0.356 psu in 0 m and a minimum value of 0.045 psu in 1000 m with an average of 0.202 psu. Compared with other methods based on fixed mesh products, this study realized a direct inversion method at any location in the global ocean and improved the inversion accuracy, which provides a reliable data support for refined marine monitoring. [ABSTRACT FROM AUTHOR]

Ocean mesoscale eddy is a special mesoscale phenomenon in the ocean, which widely exists in all oceans and marginal seas around the world. Compared with ordinary ocean circulation, mesoscale eddy has high rotating speed, strong current velocity, and average vertical depths of several kilometres, which play an important role in ocean circulation and material transport. The traditional mesoscale eddy identification and recognition have great subjectivity and usually depends on the parameters predefined or adjusted by experts, which cannot guarantee the accuracy. With the development of artificial intelligence, deep learning method has also been widely used in the detection and recognition of ocean eddies. Based on the sea-level anomaly (SLA) data provided by Copernicus Marine Environment Detection Service, this study compares the results of the 'you only look once level feature' (YOLOF) model and Detectron2 model in deep learning on marine mesoscale eddy detection. The mesoscale eddies in the South China Sea from 2011 to 2013 are detected and identified. The accuracy of Detectron2 model is about 57%, while the accuracy of YOLOF model can reach 90%. Comparing the performance of the two models on the same data set, it can be found that YOLOF model improves the accuracy and speed of recognition to a certain extent. The deep learning network model provides an effective technical method for the study of mesoscale eddy detection by sea surface height. [ABSTRACT FROM AUTHOR]

Although hypoxia is known to be associated with immune resistance, the adaptability to hypoxia by different cell populations in the tumor microenvironment and the underlying mechanisms remain elusive. This knowledge gap has hindered the development of therapeutic strategies to overcome tumor immune resistance induced by hypoxia. Here, bulk, single‐cell, and spatial transcriptomics are integrated to characterize hypoxia associated with immune escape during carcinogenesis and reveal a hypoxia‐based intercellular communication hub consisting of malignant cells, ALCAMhigh macrophages, and exhausted CD8+ T cells around the tumor boundary. A hypoxic microenvironment promotes binding of HIF‐1α complex is demonstrated to the ALCAM promoter therefore increasing its expression in macrophages, and the ALCAMhigh macrophages co‐localize with exhausted CD8+ T cells in the tumor spatial microenvironment and promote T cell exhaustion. Preclinically, HIF‐1ɑ inhibition reduces ALCAM expression in macrophages and exhausted CD8+ T cells and potentiates T cell antitumor function to enhance immunotherapy efficacy. This study reveals the systematic landscape of hypoxia at single‐cell resolution and spatial architecture and highlights the effect of hypoxia on immunotherapy resistance through the ALCAMhigh macrophage‐exhausted T cell axis, providing a novel immunotherapeutic strategy to overcome hypoxia‐induced resistance in cancers. [ABSTRACT FROM AUTHOR]

IntroductionDuring the COVID-19 pandemic, many employees were encouraged to temporarily work from home as an attempt to decrease social contact with others. However, the employees' quality of life (QoL) may have been threatened by this mode of working. This study, therefore, aims to explore the employees' QoL given the new mode of working from home (WFH) as a result of the pandemic vs. working in the office (WIO), the amount of social contact that they were exposed to, and the ratio of face-to-face contact that they had.MethodsA total of 803 WFH employees and 588 WIO employees' QoL was assessed during the same time period using the WHOQOL-BREF, which contains four domains: physical health, psychological health, social relationship, and the environment. We then divided the participants into 16 groups in accordance with the levels of work mode, social contact quantity, and face-to-face contact ratio–forming a case-control study. A differential item functioning (DIF) analysis was used to analyze the responses on the WHOQOL-BREF under the 4-dimensional rating scale model fitting.ResultsThe results indicated that WFH employees' QoL was superior to that of WIO employees. The relationship between the WFH mode and the employees' QoL was specifically moderated by the amount of social contact and the ratio of face-to-face contact that was experienced. The results further demonstrated that the increased amount of non-face-to-face contact was better for WFH employees' QoL than that of WIO employees.DiscussionIn conclusion, the WFH mode was practical during the COVID-19 pandemic, as our findings indicated that WFH employees' QoL was better than WIO employees' QoL. However, maintaining social connections is equally important as this allows employees to perform better at their jobs and maintain such performance. The employees with a higher number of social support had a better QoL. Additionally, the facets detected as DIF items provided implications for the QoL with regard to the research methodology and insight into factors affecting the employees' QoL.

Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional "omic" data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era.

In the originally published version of this Article, the positions of the final two authors in the author list were inadvertently inverted during the production process. This error has now been corrected in both the PDF and HTML versions of the Article.

The transcribed ultraconserved regions (T-UCRs) encode long non-coding RNAs implicated in human carcinogenesis. Their mechanisms of action and the factors regulating their expression in cancers are poorly understood. Here we show that high expression of uc.339 correlates with lower survival in 210 non-small cell lung cancer (NSCLC) patients. We provide evidence from cell lines and primary samples that TP53 directly regulates uc.339. We find that transcribed uc.339 is upregulated in archival NSCLC samples, functioning as a decoy RNA for miR-339-3p, -663b-3p, and -95-5p. As a result, Cyclin E2, a direct target of all these microRNAs is upregulated, promoting cancer growth and migration. Finally, we find that modulation of uc.339 affects microRNA expression. However, overexpression or downregulation of these microRNAs causes no significant variations in uc.339 levels, suggesting a type of interaction for uc.339 that we call "entrapping". Our results support a key role for uc.339 in lung cancer.