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Summary: Cancer cachexia is a prevalent and often fatal wasting condition that cannot be fully reversed with nutritional interventions. Muscle atrophy is a central component of the syndrome, but the mechanisms whereby cancer leads to skeletal muscle atrophy are not well understood. We performed single-nucleus multi-omics on skeletal muscles from a mouse model of cancer cachexia and profiled the molecular changes in cachexic muscle. Our results revealed the activation of a denervation-dependent gene program that upregulates the transcription factor myogenin. Further studies showed that a myogenin-myostatin pathway promotes muscle atrophy in response to cancer cachexia. Short hairpin RNA inhibition of myogenin or inhibition of myostatin through overexpression of its endogenous inhibitor follistatin prevented cancer cachexia-induced muscle atrophy in mice. Our findings uncover a molecular basis of muscle atrophy associated with cancer cachexia and highlight potential therapeutic targets for this disorder.

Objective: Dementia is an important disease burden among the elderly, and its occurrence may be profoundly affected by environmental factors. Evidence of the relationship between air pollution and dementia is emerging, but the extent to which this can be offset by lifestyle factors remains ambiguous. Methods: This study comprised 155,828 elder adults aged 60 years and above in the UK Biobank who were dementia-free at baseline. Cox proportional hazard models were conducted to examine the associations of annual average levels of air pollutants in 2010, including nitrogen dioxide (NO2), nitrogen oxides (NOX), particulate matter (PM2.5, PM10, and PMcoarse) and lifestyle factors recorded at baseline [physical activity (PA), sleep patterns, or smoking status] with incident risk of dementia, and their interactions on both multiplicative and additive scales. Results: During a 12-year period of follow-up, 4,389 incidents of all-cause dementia were identified. For each standard deviation increase in ambient NO2, NOX or PM2.5, all-cause dementia risk increases by 1.07-fold [hazard ratio (HR) and 95 % confidence interval (CI) = 1.07 (1.04, 1.10)], 1.05-fold (95 % CI: 1.02, 1.08) and 1.07-fold (95 % CI: 1.04, 1.10), whereas low levels of PA, poor sleep patterns, and smoking are associated with an elevated risk of dementia [HR (95 % CI) = 1.17 (1.09, 1.26), 1.13 (1.00, 1.27), and 1.14 (1.07, 1.21), respectively]. Furthermore, these air pollutants show joint effects with low PA, poor sleep patterns, and smoking on the onset of dementia. The moderate to high levels of PA could significantly or marginally significantly modify the associations between NO2, NOX or PM2.5 (P-int = 0.067, 0.036, and 0.067, respectively) and Alzheimer’s disease (AD), but no significant modification effects are found for sleep patterns or smoking status. Conclusion: The increased exposures of NO2, NOX, or PM2.5 are associated with elevated risk of dementia among elderly UK Biobank population. These air pollutants take joint effects with low PA, poor sleep patterns, and smoking on the development of dementia. In addition, moderate to high levels of PA could attenuate the incident risk of AD caused by air pollution. Further prospective researches among other cohort populations are warranted to validate these findings.

Summary: Adolescent idiopathic scoliosis (AIS), a sideways curvature of the spine, is sexually dimorphic, with increased incidence in females. A genome-wide association study identified a female-specific AIS susceptibility locus near the PAX1 gene. Here, we use mouse enhancer assays, three mouse enhancer knockouts, and subsequent phenotypic analyses to characterize this region. Using mouse enhancer assays, we characterize a sequence, PEC7, which overlaps the AIS-associated variant, and find it to be active in the tail tip and intervertebral disc. Removal of PEC7 or Xe1, a known sclerotome enhancer nearby, or deletion of both sequences lead to a kinky tail phenotype only in the Xe1 and combined (Xe1+PEC7) knockouts, with only the latter showing a female sex dimorphic phenotype. Extensive phenotypic characterization of these mouse lines implicates several differentially expressed genes and estrogen signaling in the sex dimorphic bias. In summary, our work functionally characterizes an AIS-associated locus and dissects the mechanism for its sexual dimorphism.

Algal toxins produced by microalgae, such as domoic acid (DA)11 (DA) domoic acid, have toxic effects on humans. However, toxicity tests using mice only yield lethal doses of algal toxins without providing insights into the mechanism of action on cells. In this study, a fast segmentation of microfluidic flow cytometry cell images based on the bidirectional background subtraction (BBS)22 (BBS) bidirectional background subtraction method was developed to get the visual evidence of apoptosis in both bright-field and fluorescence images. This approach enables mapping of changes in cell morphology and activity under algal toxins, allowing for fast (within 60 s) and automated biological detection. By combining microfluidics with flow cytometry, the intricate cellular-level reaction process can be observed in micro samples of 293 T cells and mouse spleen cells, offering potential for future in vitro experiments.

The terrestrial water storage anomaly (TWSA) is an important parameter for assessing the land water budget, and it interacts well with terrestrial ecosystems via complex hydrological processes. Recently, the decline in central Asian terrestrial water storage (TWS) has threatened the health of local ecosystems. Therefore, it is of great significance to adopt an efficient approach to explore and identify the nonlinear relationship between two important indicators, i.e., the TWSA and normalized difference vegetation index (NDVI) in the arid central Asian endorheic basins. In this study, we analysed the long-term trends of the TWSA and NDVI, and identified the lag month (1 month) as the optimal moving window of the nonlinear Granger causality test embedded in random forest to detect the nonlinear NDVI change response of NDVI changes in vegetation to the TWSA from 2003 to 2015. There are decreasing trends in TWSAs over approximately 81.7% of the study area and the NDVI generally decreased resulting in approximately 36% vegetation browning in the study area. The nonlinear Granger unidirectional causes of the TWSA were responsible for 97.9% of the NDVI variation in the study area considering the optimal response time for moving windows. The causes of vegetation browning in the central Asian Aral Sea basin and vegetation greening in the basins of Northwest China could be mostly explained by the changes in TWS. Our findings contribute to understanding the nonlinear causal linkages between vegetation and the TWSA in endorheic basins, and these findings provide insights for obtaining terrestrial water consumption patterns and water resource management under the joint influence of climate change and human activities.

Background: The role of cystathionine γ-lyase (CTH) in the prognosis and immune invasion of hepatocellular carcinoma (HCC) remains poorly understood. Methods: In this study, the clinical data of patients with HCC were analyzed, and the expression level of CTH was compared between HCC and normal tissues using the R package and various databases. Results: We found that CTH expression was significantly decreased in HCC compared with normal tissues, and its expression was associated with various clinicopathological factors, including tumor stage, gender, tumor status, residual tumor, histologic stage, race, alpha-fetoprotein (AFP), albumin, drinking, and smoking. Our results suggest that CTH might be a protective factor for the survival of patients with HCC. Further functional analysis revealed that high CTH expression was enriched in the Reactome signaling by interleukins and the Reactome neutrophil degranulation. Moreover, CTH expression was closely correlated with a variety of immune cells, including a negative correlation with the CD56 (bright) NK cells and follicular helper T cell (TFH), while a positive correlation with Th17 cells and central memory T cell (Tcm). High expression of CTH in immune cells predicted a better prognosis of HCC. Our findings further indicated Pyridoxal phosphate, l-cysteine, Carboxymethylthio-3-(3-chlorophenyl)-1,2,4-oxadiazol, 2-[(3-Hydroxy-2-Methyl-5-Phosphonooxymethyl-Pyridin-4-Ylmethyl)-Imino]-5-phosphono-pent-3-enoic acid and L-2-amino-3-butynoic acid as potential target candidate medications for HCC treatment based on CTH. Conclusion: Our study suggests that CTH can serve as a biomarker to predict the prognosis and immune infiltration of HCC.

It is difficult to temporally and spatially track and characterize the slurry viscosity in flowing water during grouting simulation. In this study, a sequential flow and solidification (SFS) method considering the spatial-temporal evolution of slurry viscosity in flowing water in karst conduit is proposed. First, a time-dependent model for the threshold function of slurry viscosity is established. During the grouting process, the spatial-temporal evolution of slurry viscosity is revealed by tracking the diffusion behavior of the slurry injected at different times. This method is capable of describing the gradual solidification process of the slurry during grouting. Furthermore, a physical model of grouting in a karst conduit is developed. Second, the effectiveness of the SFS method in grouting simulation is verified by the experiment of grouting conduit in flowing water. The SFS method enables real-time monitoring of fluid velocity and pressure during grouting in flowing water and provides a feasible calculation method for revealing the grouting plugging mechanism in complex karst conduits at different engineering scales. In addition, it can be used to guide the design of grouting tests in flowing water, improve cost efficiency, and provide theoretical basis for optimizing grouting design and slurry selection.

Background: COVID-19 boosted healthcare digitalization and personalization in cardiology. However, understanding patient attitudes and engagement behaviors is essential to achieve successful acceptance and implementation of digital health technologies in personalized care. Objective: This study aims to understand current and future trends in wearable device and telemedicine use in the cardiology clinic patient population, recognize patients’ attitude towards digital health before and after COVID-19, and identify potential socioeconomic and racial/ethnic differences in adoption of digital health tools in a New Orleans patient population. Methods: A cross-sectional survey was distributed to Tulane Cardiology Clinic patients between September 2020 and January 2021. Basic demographic information, medical comorbidities, device usage, and opinions on digital health tools were collected. Results: Survey responses from 299 participants (average age = 54 years, 50.8% female, 24.4% African American) showed that digital health use was more prevalent in younger, healthier, and more educated individuals. Wearable use was also higher among White patients compared to African American patients. Patients cited costs and technology knowledge as primary deterrents for using wearables, despite being more inclined to use wearables for disease monitoring (41%). While wearable use did not increase after COVID-19 (36.6% pre-COVID vs 35.4% post-COVID, P = .77), telemedicine use rose significantly (10.8% pre-COVID vs 24.3% during COVID, P < .0001). Patients mostly noted telemedicine’s effectiveness in overcoming difficult healthcare access barriers. Additionally, most patients are in support of wearables and telemedicine either complementing or replacing routine tests and traditional clinical visits. Conclusion: Demographic and socioeconomic disparities negatively impact wearable health device and telemedicine adoption within cardiovascular clinic patients. Although telemedicine use increased after COVID-19, this effect was not observed for wearables, reflecting significant economic and digital literacy challenges underlying wearable acceptance.

Vegetation, being a core component of ecosystems, is known to be influenced by natural and anthropogenic factors. Studying vegetation cover dynamics variation and its drivers is critical to understanding the interactions between vegetation and ecosystems. The Loess Plateau (LP) is located in a semi-arid and semi-humid region with severe soil erosion and fragile ecology. This paper used the annual maximum Normalized Difference Vegetation Index (NDVIymax) and growing season mean NDVI (NDVIgsmean) as the vegetation cover indicator. The vegetation cover variation of LP from 2000 to 2020 was analyzed using Sen's slope and Mann-Kendall test. Then the influence of natural and anthropogenic factors on the driving mechanisms of spatial vegetation differentiation was explored by the Geodetector model. The results revealed that the growth trends of NDVIymax and NDVIgsmean were 0.075/10 years and 0.038/10 years, respectively, and the areas with improved vegetation cover accounted for 92.67 % and 88.58 % of the total area. The vegetation cover of the southeastern and northern parts of the LP decreased significantly; however, the central, southwestern, and northeastern parts exhibited a remarkable improvement. Precipitation, vegetation type, soil type, temperature, and land use type were the key driving forces, ranked differently on NDVIymax and NDVIgsmean. However, precipitation was the most critical factor both on NDVIymax and NDVIgsmean. The interaction detection showed non-linear and mutual enhancement, with no independent factor. The findings of our study can assist in identifying the vegetation cover status of the LP, as well as the driving forces, which can provide theoretical support for the formulation of environmental conservation policies.

In 2020, China for the first time developed guidelines for indoor fine particulate matter (PM2.5) in the draft document of indoor air standards, while the associated health implication remains unclear. Here, we first estimated the PM2.5 associated premature deaths was 965 thousand in 2019, with the indoor PM2.5 of outdoor origin accounting for 72.9%. Then, we examined the dynamic mortalities under a scenario matrix of 36 conditions, by incorporating various shared socioeconomic pathways in 2035, the draft guidelines and the contributions of ambient PM2.5 to indoor exposure. Although it may be improbable, the averages of premature deaths associated with ambient PM2.5 will be 1018–1361 thousand in 2035 when the worst-case scenario of guidelines mandating a yearly (rather than daily) indoor PM2.5 concentration of 75 µg/m3, compared to the averages of estimation were 816–1304 thousand for better-case scenario of 35 µg/m3. Under these scenarios, the increase in the number of premature deaths was mainly driven by population aging. In 2035, an ambitious target of yearly indoor PM2.5 concentrations of 15 µg/m3 is anticipated to reduce the number of deaths associated with ambient PM2.5 by approximately 25% of the 2019 baseline. Stricter guidelines to restrict the indoor PM2.5 concentrations are recommended to mitigate the mortality risk in the future.

The Northern Hemisphere is experiencing amplified warming and greening; however, the responses of greening to warming remain unclear in terms of the cumulative and time-lag effects of climate factors. We chose Siberia, a hotspot in the Northern Hemisphere, as a study area and identified the relationships between the enhanced vegetation index (EVI) and climate factors (e.g., surface temperature, precipitation, and solar radiation) during 2000–2016. In the growing season, the average cumulative duration of the vegetation response to climate factors was 3.6 ± 2.0 months, and the time-lag period was 1.5 ± 1.2 months, with the longest duration in forests and the shortest duration in tundra. Solar radiation was the dominant driver of vegetation greening in 56% of the study area, followed by temperature (41%) and precipitation (3%). In addition, the temporal effects of the climate factors were separated through partial correlation analysis; vegetation responded most rapidly to solar radiation variations with a cumulative duration of 2.2 ± 1.2 months and a time-lag period of 1.8 ± 0.8 months, followed by temperature (2.3 ± 1.3 and 1.9 ± 1.0 months, respectively). Precipitation showed the longest cumulative effect (3.7 ± 1.5 months) and the shortest time-lag effect (1.2 ± 1.1 months). Our results suggest that vegetation activity is influenced by both cumulative and time-lag effects. The temporal effects vary among the land cover categories, and complex ecosystems generally correspond to long-term temporal effects, and vice versa. Thus, the conversion of tundra to boreal forest due to warming in Siberia enhances the temporal effects of climate. These temporal effects could be incorporated into Earth system models to improve our understanding and monitoring of terrestrial ecosystems.

Metal alloy additive manufacturing (AM) has gained wide industrial interest in the past decade due to its capability to efficiently deliver complicated mechanical parts with high quality. However, due to a lack of understanding of the fundamental correlation between the operating conditions and build quality, the exploration of the optimal operating policy of the AM process is costly and difficult. In this work, a data-driven process optimization framework has been proposed for the additive manufacturing process, integrating machine learning, finite-element method (FEM) modeling, and cloud-edge data storage/transfer optimization. A three-level hierarchy of local machines, factory clouds, and a research center is introduced with each level responsible for its dedicated tasks. In addition, to ensure the efficiency of data transfer and storage, an edge-cloud data transfer scheme is constructed, which serves as a guideline for the data flow in the AM framework. Moreover, an overview of the connections between the proposed framework and the Industry 4.0 framework is presented.

Large-scale anthropic conversion of natural ecosystems into human-dominated countryside ecosystems has led to biodiversity loss worldwide. However, how countryside landscapes affect biodiversity is still controversial, especially in karst regions lack of relevant studies. To answer this question, we analyzed the impact of countryside landscapes on biodiversity changes in the South China Karst, featured as a World Natural Heritage site of subtropical karst landscape and rich biodiversity. We presented a new framework to examine the impact of countryside landscapes on biodiversity change at a semi centennial-scale using three indicators: biodiversity cluster characteristics, the barrier of villages to biodiversity, and the barrier of arable land to biodiversity. Unmanned aerial vehicle (UAV) images, satellite remote sensing data, and field survey data were combined during the process. Results revealed that plant biodiversity was positively correlated to vegetation restoration, and vegetation took approximately 80 years to recover to a stable state. Plant biodiversity spatial points are densely distributed at karst peaks, with an average distance of only 420 m–480 m. Small villages create no apparent barriers to biodiversity, with an average barrier distance of about 450 m–530 m. Arable land intersecting with forest patches connects biodiversity spatial points. Hence, the expansion of countryside landscapes in karst depressions was restricted by karst peaks, and patches of artificial arable land and forest connect the natural reserved forest at karst peaks, which both promote local spatial heterogeneity and sustain local biodiversity. This study enriches the application of countryside biogeography theory in karst regions and provides evidence for integrating biodiversity conservation into sustainable planning in broader areas. We strongly recommend that a heterogeneous landscape pattern similar to karst peak forests, such as the distance between biodiversity spatial points and the barrier distance to villages both around 450–500 m, would be conducive to biodiversity preservation.

Thrombocytopenia 2 (THC2) is a major type of inherited thrombocytopenia caused by the persistent ANKRD26 expression during the late stage of megakaryocytopoiesis. For the first time, we generated a human induced pluripotent stem cell (hiPSC) line SHAMUi001-A from the bone marrow hematopoietic progenitor cells of a THC2 patient, who has a heterozygous mutation (c.-128G>T) in the 5′-UTR of ANKRD26 gene. SHAMUi001-A cells retain the mutation, display pluripotent stem cell characteristics, and have a normal female karyotype. This disease-specific hiPSC line will be a useful model for THC2 research.