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We present a comprehensive investigation on the mass function (MF) of a snake-like stellar structure in the solar neighbourhood, building on our previous discovery. To ensure the reliability of the data, we reselect the member stars of the Stellar ``Snake'' in the latest {\it Gaia} Data Release 3 using the same approach as the initial series of articles. We also precisely measure the physical parameters of the clusters within the Stellar Snake. In light of the high completeness of the member stars in the cluster regions, we develop a simulated model color-magnitude diagram-based inference method to derive the mass function, binary fraction, and mass-ratio distribution of the clusters in the Stellar Snake. Notably, despite their similar ages and metallicity, we discover systematic variations in the MFs along the elongation direction of the Snake in the mass range of 0.5 to 2.0 M$_\odot$. The ``head'' of the Snake conforms to a canonical initial mass function with a power-law slope of $\alpha\sim-2.3$. Extending towards the ``tail,'' the MF becomes more top-light, indicating a deficiency of massive stars within these clusters. This result provides evidence for the delayed formation of massive stars in the clusters. Such clues give support to the hypothesis that the Stellar Snake constitutes as a hierarchically primordial structure., Comment: 19 pages, 15 figures, Accepted for publication on MNRAS

• AIM: To summarize the application of deep learning in detecting ophthalmic disease with ultrawide-field fundus images and analyze the advantages, limitations, and possible solutions common to all tasks. • METHODS: We searched three academic databases, including PubMed, Web of Science, and Ovid, with the date of August 2022. We matched and screened according to the target keywords and publication year and retrieved a total of 4358 research papers according to the keywords, of which 23 studies were retrieved on applying deep learning in diagnosing ophthalmic disease with ultrawide-field images. • RESULTS: Deep learning in ultrawide-field images can detect various ophthalmic diseases and achieve great performance, including diabetic retinopathy, glaucoma, age-related macular degeneration, retinal vein occlusions, retinal detachment, and other peripheral retinal diseases. Compared to fundus images, the ultrawide-field fundus scanning laser ophthalmoscopy enables the capture of the ocular fundus up to 200° in a single exposure, which can observe more areas of the retina. • CONCLUSION: The combination of ultrawide-field fundus images and artificial intelligence will achieve great performance in diagnosing multiple ophthalmic diseases in the future. © 2023 International Journal of Ophthalmology (c/o Editorial Office). All rights reserved.

Fossil pollen and spore records provide highly creditable proxy data to investigate the past environmental changes such as palaeovegetation and palaeoclimate. Pollen database promotes past environmental studies from local to regional and global scales and from qualitative to quantitative reconstructions. This is of great significance on exploring the interactions among past vegetation, climates and anthropogenic disturbances at large spatial scale and long temporal scale, to better understand the evolution of the earth system. In this paper, a fossil pollen dataset of China is compiled, by synthesizing 372 original or digitized fossil pollen records including 790 pollen taxa in China’s land and ocean during the late-Quaternary (since 50 ka BP). The dataset includes site names, latitude, longitude and altitude, pollen data source, sample type, sediment length or span, sample number of each site, dating method and dating number, age span and reference, as well as the fossil pollen percentage of each sampling site. The pollen data, mostly published from late 1980s to present, are concentrated in vegetation regions of temperate and subtropical forests, temperate grasslands, temperate deserts and alpine vegetation on the Qingzang Plateau. Sample sites are distributed at different altitudes from deep sea to high Qingzang Plateau, but the majority of the sites are located between 0–2 000 m. The dataset comprises of 178 raw pollen records (47.8%) and 194 digitized pollen records (52.2%). Pollen samples are mainly from lake sediment (151 sites), alluvial/fluvial sediment (99 sites), and peat (67 sites), accounting for 85.2% of the total sampling sites. Radiocarbon is the main dating method that accounts for 93.8% of total samples, and most of the sites have 2–10 radiocarbon dating data. Each site has an average number of pollen taxa of 19, with the most sites having 4–30 pollen taxa. The temporal and spatial distribution of representative pollen taxa (Pinus, Quercus, Artemis

Antibiotics have been used in the beef industry to improve animal health. However, this can potentially contribute to developing antimicrobial resistance (AMR) in the bacteria shedding from animal guts in feces. Antimicrobial resistance bacteria (ARB) and their AMR genes (ARGs) may be transmitted to humans via beef contaminated by animal feces during livestock production and slaughtering. However, whether various grass and grain beef feeding systems impact ARB or ARGs in cattle feces is currently unknown. Therefore, the objective of this study was to characterize and compare the fecal resistome of cattle raised in various grass and grain-feeding systems in the Western United States. Fecal samples were collected from individual cattle at 14 months of age as a baseline and collected again from the same animals two days before harvest. Groups included: 1) Conventional grain-fed (CON, n = 10), 2) Grass-fed for 20 months (20GF, n = 10), 3) Grass-fed and then grain-finished for 45 days (GR45, n = 10), 4) Grass-fed for 25 months (25GF, n = 10). Beef cattle raised in grass-fed systems did not receive any antibiotics, while some cattle from CON and GR45 received therapeutic antibiotics, and those finished in the feedlot received monensin in their feedlot rations. Total microbial DNA was extracted from samples and sequenced using the Illumina NovaSeq 6000 platform (250bp paired-end, Illumina, Inc., San Diego, CA, USA) for resistome analysis. In total 598 ARGs were identified, and 448 were kept after the filtration. Regarding the Chao 1 diversity, the 25GF group had the smallest value compared to that of the other three groups (P < 0.05) at the harvest time. Shannon’s diversity suggested that the richness and evenness of ARGs are greater than CON and GR45 compared with 20GF and 25GF (P < 0.05). The beta diversity for GR45 and CON differed concerning the abundance of ARGs and the predominant ARG classes, as compared to the samples collected from cattle within grass-feedin

Struck-by accidents are the leading cause of injuries in highway construction work zones. Despite numerous safety interventions, injury rates remain high. As workers’ exposure to traffic is sometimes unavoidable, providing warnings can be an effective way to prevent imminent threats. Such warnings should consider work zone conditions that can hinder the timely perception of alerts, e.g., poor visibility and high noise level. This study proposes a vibrotactile system integrated into workers’ conventional personal protective equipment (PPE), i.e., safety vests. Three experiments were conducted to assess the feasibility of using vibrotactile signals to warn workers in highway environments, the perception and performance of vibrotactile signals at different body locations, and the usability of various warning strategies. The results revealed vibrotactile signals had a 43.6% faster reaction time than audio signals, and the perceived intensity and urgency levels on the sternum, shoulders, and upper back were significantly higher than the waist. Among different notification strategies used, providing a moving direction imposed significantly lower mental workloads and higher usability scores than providing a hazard direction. Further research should be conducted to reveal factors that affect alerting strategy preference towards a customizable system to elicit higher usability among users.

One major challenge of disentanglement learning with variational autoencoders is the trade-off between disentanglement and reconstruction fidelity. Previous studies, which increase the information bottleneck during training, tend to lose the constraint of disentanglement, leading to the information diffusion problem. In this paper, we present a novel framework for disentangled representation learning, DeVAE, which utilizes hierarchical latent spaces with decreasing information bottlenecks across these spaces. The key innovation of our approach lies in connecting the hierarchical latent spaces through disentanglement-invariant transformations, allowing the sharing of disentanglement properties among spaces while maintaining an acceptable level of reconstruction performance. We demonstrate the effectiveness of DeVAE in achieving a balance between disentanglement and reconstruction through a series of experiments and ablation studies on dSprites and Shapes3D datasets. Code is available at https://github.com/erow/disentanglement_lib/tree/pytorch#devae.

Through their aminoacylation reactions, aminoacyl tRNA-synthetases (aaRS) establish the rules of the genetic code throughout all of nature. During their long evolution in eukaryotes, additional domains and splice variants were added to what is commonly a homodimeric or monomeric structure. These changes confer orthogonal functions in cellular activities that have recently been uncovered. An unusual exception to the familiar architecture of aaRSs is the heterodimeric metazoan mitochondrial SerRS. In contrast to domain additions or alternative splicing, here we show that heterodimeric metazoan mitochondrial SerRS arose from its homodimeric ancestor not by domain additions, but rather by collapse of an entire domain (in one subunit) and an active site ablation (in the other). The collapse/ablation retains aminoacylation activity while creating a new surface, which is necessary for its orthogonal function. The results highlight a new paradigm for repurposing a member of the ancient tRNA synthetase family.

This study focuses on the use of model and data fusion for improving the Spalart-Allmaras (SA) closure model for Reynolds-averaged Navier-Stokes solutions of separated flows. In particular, our goal is to develop of models that not-only assimilate sparse experimental data to improve performance in computational models, but also generalize to unseen cases by recovering classical SA behavior. We achieve our goals using data assimilation, namely the Ensemble Kalman Filtering approach (EnKF), to calibrate the coefficients of the SA model for separated flows. A holistic calibration strategy is implemented via a parameterization of the production, diffusion, and destruction terms. This calibration relies on the assimilation of experimental data collected velocity profiles, skin friction, and pressure coefficients for separated flows. Despite using of observational data from a single flow condition around a backward-facing step (BFS), the recalibrated SA model demonstrates generalization to other separated flows, including cases such as the 2D-bump and modified BFS. Significant improvement is observed in the quantities of interest, i.e., skin friction coefficient ($C_f$) and pressure coefficient ($C_p$) for each flow tested. Finally, it is also demonstrated that the newly proposed model recovers SA proficiency for external, unseparated flows, such as flow around a NACA-0012 airfoil without any danger of extrapolation, and that the individually calibrated terms in the SA model are targeted towards specific flow-physics wherein the calibrated production term improves the re-circulation zone while destruction improves the recovery zone.

Deep Neural Networks (DNNs) have significantly improved the accuracy of intelligent applications on mobile devices. DNN surgery, which partitions DNN processing between mobile devices and multi-access edge computing (MEC) servers, can enable real-time inference despite the computational limitations of mobile devices. However, DNN surgery faces a critical challenge: determining the optimal computing resource demand from the server and the corresponding partition strategy, while considering both inference latency and MEC server usage costs. This problem is compounded by two factors: (1) the finite computing capacity of the MEC server, which is shared among multiple devices, leading to inter-dependent demands, and (2) the shift in modern DNN architecture from chains to directed acyclic graphs (DAGs), which complicates potential solutions. In this paper, we introduce a novel Decentralized DNN Surgery (DDS) framework. We formulate the partition strategy as a min-cut and propose a resource allocation game to adaptively schedule the demands of mobile devices in an MEC environment. We prove the existence of a Nash Equilibrium (NE), and develop an iterative algorithm to efficiently reach the NE for each device. Our extensive experiments demonstrate that DDS can effectively handle varying MEC scenarios, achieving up to 1.25$\times$ acceleration compared to the state-of-the-art algorithm., Comment: Under Review

Offshore wind energy resources are operational in cold regions, while offshore wind turbines will face the threat of icing. Therefore, it is necessary to study icing of offshore wind turbines under different icing conditions. In this study, icing sensitivity of offshore wind turbine blades are performed using a combination of FLUENT and FENSAP-ICE software, and the effects of liquid water content (LWC), medium volume diameter (MVD), wind speed and air temperature on blade icing shape are analyzed by two types of ice, namely rime ice and glaze ice. The results show that the increase of LWC and MVD will increase the amount of ice that forms on the blade surface for either glaze ice or rime ice, and an increase of MVD will expand the adhesion surface between ice and blade. Before reaching the rated wind speed of 11.4 m·s−1, it does not directly affect the icing shape. However, after reaching the rated wind speed, the attack angle of the incoming flow decreases obviously, and the amount of ice increases markedly. When the ambient air temperature meets the icing conditions of glaze ice (i.e., −5ºC to 0ºC), the lower the temperature, the more glaze ice freezes, whereas air temperature has no impact on the icing of rime ice. Compared with onshore wind turbines, offshore wind turbines might face extreme meteorological conditions, and the wind speed has no impact on the amount of ice that forms on the blade surface for most wind speeds.

Offshore wind energy resources are operational in cold regions, while offshore wind turbines will face the threat of icing. Therefore, it is necessary to study icing of offshore wind turbines under different icing conditions. In this study, icing sensitivity of offshore wind turbine blades are performed using a combination of FLUENT and FENSAP-ICE software, and the effects of liquid water content (LWC), medium volume diameter (MVD), wind speed and air temperature on blade icing shape are analyzed by two types of ice, namely rime ice and glaze ice. The results show that the increase of LWC and MVD will increase the amount of ice that forms on the blade surface for either glaze ice or rime ice, and an increase of MVD will expand the adhesion surface between ice and blade. Before reaching the rated wind speed of 11.4 m·s−1, it does not directly affect the icing shape. However, after reaching the rated wind speed, the attack angle of the incoming flow decreases obviously, and the amount of ice increases markedly. When the ambient air temperature meets the icing conditions of glaze ice (i.e., −5ºC to 0ºC), the lower the temperature, the more glaze ice freezes, whereas air temperature has no impact on the icing of rime ice. Compared with onshore wind turbines, offshore wind turbines might face extreme meteorological conditions, and the wind speed has no impact on the amount of ice that forms on the blade surface for most wind speeds.

Consumer interest in grass-fed beef has been steadily rising due to consumer perception of its potential benefits. This interest has led to a growing demand for niche market beef, particularly in the western United States. Therefore, the objective of this study was to assess the impact of feeding systems on the change in microbial counts, color, and lipid oxidation of steaks during retail display, and on their sensory attributes. The systems included: conventional grain-fed (CON), 20 months-grass-fed (20GF), 25-months-grass-fed (25GF) and 20-months-grass-fed + 45-day-grain-fed (45GR). The results indicate that steaks in the 20GF group displayed a darker lean and fat color, and a lower oxidation state than those in the 25GF group. However, the feeding system did not have an impact on pH or objective tenderness of beef steaks. In addition, consumers and trained panelist did not detect a difference in taste or flavor between the 20GF or 25GF steaks but expressed a preference for the CON and 45GR steaks, indicating that an increased grazing period may improve the color and oxidative stability of beef, while a short supplementation with grain may improve eating quality.

Between increasing public concerns over climate change and heightened interest of niche market beef on social media, the demand for grass-fed beef has increased considerably. However, the demand increase for grass-fed beef has raised many producers' and consumers' concerns regarding product quality, economic viability, and environmental impacts that have thus far gone unanswered. Therefore, using a holistic approach, we investigated the performance, carcass quality, financial outcomes, and environmental impacts of four grass-fed and grain-fed beef systems currently being performed by ranchers in California. The treatments included 1) steers stocked on pasture and feedyard finished for 128 d (CON); 2) steers grass-fed for 20 mo (GF20); 3) steers grass-fed for 20 mo with a 45-d grain finish (GR45); and 4) steers grass-fed for 25 mo (GF25). The data were analyzed using a mixed model procedure in R with differences between treatments determined by Tukey HSD. Using carcass and performance data from these systems, a weaning-to-harvest life cycle assessment was developed in the Scalable, Process-based, Agronomically Responsive Cropping Systems model framework, to determine global warming potential (GWP), consumable water use, energy, smog, and land occupation footprints. Final body weight varied significantly between treatments (P < 0.001) with the CON cattle finishing at 632 kg, followed by GF25 at 570 kg, GR45 at 551 kg, and GF20 478 kg. Dressing percentage differed significantly between all treatments (P < 0.001). The DP was 61.8% for CON followed by GR45 at 57.5%, GF25 at 53.4%, and GF20 had the lowest DP of 50.3%. Marbling scores were significantly greater for CON compared to all other treatments (P < 0.001) with CON marbling score averaging 421 (low-choice ≥ 400). Breakeven costs with harvesting and marketing for the CON, GF20, GR45, and GF25 were $6.01, $8.98, $8.02, and $8.33 per kg hot carcass weight (HCW), respectively. The GWP for th

Offshore wind energy resources are operational in cold regions, while offshore wind turbines will face the threat of icing. Therefore, it is necessary to study icing of offshore wind turbines under different icing conditions. In this study, icing sensitivity of offshore wind turbine blades are performed using a combination of FLUENT and FENSAP-ICE software, and the effects of liquid water content (LWC), medium volume diameter (MVD), wind speed and air temperature on blade icing shape are analyzed by two types of ice, namely rime ice and glaze ice. The results show that the increase of LWC and MVD will increase the amount of ice that forms on the blade surface for either glaze ice or rime ice, and an increase of MVD will expand the adhesion surface between ice and blade. Before reaching the rated wind speed of 11.4 m/s, it does not directly affect the icing shape. However, after reaching the rated wind speed, the attack angle of the incoming flow decreases obviously, and the amount of ice increases markedly. When the ambient air temperature meets the icing conditions of glaze ice (i.e., −5°C to 0°C), the lower the temperature, the more glaze ice freezes, whereas air temperature has no impact on the icing of rime ice.

Distributing the inference of convolutional neural network (CNN) to multiple mobile devices has been studied in recent years to achieve real-time inference without losing accuracy. However, how to map CNN to devices remains a challenge. On the one hand, scheduling the workload of state-of-the-art CNNs with multiple devices is NP-Hard because the structures of CNNs are directed acyclic graphs (DAG) rather than simple chains. On the other hand, distributing the inference workload suffers from expensive communication and unbalanced computation due to the wireless environment and heterogeneous devices. This paper presents PICO, a pipeline cooperation framework to accelerate the inference of versatile CNNs on diverse mobile devices. At its core, PICO features: (1) a generic graph partition algorithm that considers the characteristics of any given CNN and orchestrates it into a list of model pieces with suitable granularity, and (2) a many-to-many mapping algorithm that produces the best pipeline configuration for heterogeneous devices. In our experiment with 2 ~ 8 Raspberry-Pi devices, the throughput can be improved by 1.8 ~ 6.8x under different CPU frequencies., Comment: Accepted by IEEE Transactions on Mobile Computing

PurposeTo investigate the potential genetic etiology of premature ovarian insufficiency (POI).MethodsWhole-exome sequencing (WES) was done on DNA samples from women diagnosed with POI. Mutations identified were analyzed by in silico tools and were annotated according to the guidelines of the American College of Medical Genetics and Genomics. Plausible variants were confirmed by Sanger sequencing.ResultsFour of the 33 individuals (12%) carried pathogenic or likely pathogenic variants, and 6 individuals carried variants of unknown significance. The genes identified with pathogenic or likely pathogenic variants included PMM2, MCM9, and PSMC3IP.ConclusionsWES is an efficient tool for identifying gene variants in POI women; however, interpretation of variants is hampered by few exome studies involving ovarian disorders and the need for trio sequencing to determine inheritance and to detect de novo variants.

Although high-throughput RNA sequencing (RNA-seq) has greatly advanced small non-coding RNA (sncRNA) discovery, the currently widely used complementary DNA library construction protocol generates biased sequencing results. This is partially due to RNA modifications that interfere with adapter ligation and reverse transcription processes, which prevent the detection of sncRNAs bearing these modifications. Here, we present PANDORA-seq (panoramic RNA display by overcoming RNA modification aborted sequencing), employing a combinatorial enzymatic treatment to remove key RNA modifications that block adapter ligation and reverse transcription. PANDORA-seq identified abundant modified sncRNAs-mostly transfer RNA-derived small RNAs (tsRNAs) and ribosomal RNA-derived small RNAs (rsRNAs)-that were previously undetected, exhibiting tissue-specific expression across mouse brain, liver, spleen and sperm, as well as cell-specific expression across embryonic stem cells (ESCs) and HeLa cells. Using PANDORA-seq, we revealed unprecedented landscapes of microRNA, tsRNA and rsRNA dynamics during the generation of induced pluripotent stem cells. Importantly, tsRNAs and rsRNAs that are downregulated during somatic cell reprogramming impact cellular translation in ESCs, suggesting a role in lineage differentiation.

The United States' large-scale poultry meat industry is energy and water intensive, and opportunities may exist to improve sustainability during the broiler chilling process. By USDA regulation, after harvest the internal temperature of the chicken must be reduced to 40°F or less within 16 h to inhibit bacterial growth that would otherwise compromise the safety of the product. This step is accomplished most commonly by water immersion chilling in the United States, while air chilling methods dominate other global markets. A comprehensive understanding of the differences between these chilling methods is lacking. Therefore, we assessed the meat quality, shelf-life, microbial ecology, and techno-economic impacts of chilling methods on chicken broilers in a university meat laboratory setting. We discovered that air chilling methods resulted in superior chicken odor and shelf-life, especially prior to 14 days of dark storage. Moreover, we demonstrated that air chilling resulted in a more diverse microbiome that we hypothesize may delay the dominance of the spoilage organism Pseudomonas Finally, a techno-economic analysis highlighted potential economic advantages to air chilling compared to water chilling in facility locations where water costs are a more significant factor than energy costs.IMPORTANCE As the poultry industry works to become more sustainable and to reduce the volume of food waste, it is critical to consider points in the processing system that can be altered to make the process more efficient. In this study, we demonstrate that the method used during chilling (air versus water chilling) influences the final product microbial community, quality, and physiochemistry. Notably, the use of air chilling appears to delay the bloom of Pseudomonas spp. that are the primary spoilers in packaged meat products. By using air chilling to reduce carcass temperatures instead of water chilling, producers may extend the time until spoilage of the products and, depending o

His-tRNA synthetase (HARS) is targeted by autoantibodies in chronic and acute inflammatory anti-Jo-1-positive antisynthetase syndrome. The extensive activation and migration of immune cells into lung and muscle are associated with interstitial lung disease, myositis, and morbidity. It is unknown whether the sequestration of HARS is an epiphenomenon or plays a causal role in the disease. Here, we show that HARS circulates in healthy individuals, but it is largely undetectable in the serum of anti-Jo-1-positive antisynthetase syndrome patients. In cultured primary human skeletal muscle myoblasts (HSkMC), HARS is released in increasing amounts during their differentiation into myotubes. We further show that HARS regulates immune cell engagement and inhibits CD4+ and CD8+ T-cell activation. In mouse and rodent models of acute inflammatory diseases, HARS administration downregulates immune activation. In contrast, neutralization of extracellular HARS by high-titer antibody responses during tissue injury increases susceptibility to immune attack, similar to what is seen in humans with anti-Jo-1-positive disease. Collectively, these data suggest that extracellular HARS is homeostatic in normal subjects, and its sequestration contributes to the morbidity of the anti-Jo-1-positive antisynthetase syndrome. © 2019, The Author(s).

The United States' large-scale poultry meat industry is energy and water intensive, and opportunities may exist to improve sustainability during the broiler chilling process. By USDA regulation, after harvest the internal temperature of the chicken must be reduced to 40°F or less within 16 h to inhibit bacterial growth that would otherwise compromise the safety of the product. This step is accomplished most commonly by water immersion chilling in the United States, while air chilling methods dominate other global markets. A comprehensive understanding of the differences between these chilling methods is lacking. Therefore, we assessed the meat quality, shelf-life, microbial ecology, and techno-economic impacts of chilling methods on chicken broilers in a university meat laboratory setting. We discovered that air chilling methods resulted in superior chicken odor and shelf-life, especially prior to 14 days of dark storage. Moreover, we demonstrated that air chilling resulted in a more diverse microbiome that we hypothesize may delay the dominance of the spoilage organism Pseudomonas Finally, a techno-economic analysis highlighted potential economic advantages to air chilling compared to water chilling in facility locations where water costs are a more significant factor than energy costs.IMPORTANCE As the poultry industry works to become more sustainable and to reduce the volume of food waste, it is critical to consider points in the processing system that can be altered to make the process more efficient. In this study, we demonstrate that the method used during chilling (air versus water chilling) influences the final product microbial community, quality, and physiochemistry. Notably, the use of air chilling appears to delay the bloom of Pseudomonas spp. that are the primary spoilers in packaged meat products. By using air chilling to reduce carcass temperatures instead of water chilling, producers may extend the time until spoilage of the products and, depending o

Although high-throughput RNA sequencing (RNA-seq) has greatly advanced small non-coding RNA (sncRNA) discovery, the currently widely used complementary DNA library construction protocol generates biased sequencing results. This is partially due to RNA modifications that interfere with adapter ligation and reverse transcription processes, which prevent the detection of sncRNAs bearing these modifications. Here, we present PANDORA-seq (panoramic RNA display by overcoming RNA modification aborted sequencing), employing a combinatorial enzymatic treatment to remove key RNA modifications that block adapter ligation and reverse transcription. PANDORA-seq identified abundant modified sncRNAs-mostly transfer RNA-derived small RNAs (tsRNAs) and ribosomal RNA-derived small RNAs (rsRNAs)-that were previously undetected, exhibiting tissue-specific expression across mouse brain, liver, spleen and sperm, as well as cell-specific expression across embryonic stem cells (ESCs) and HeLa cells. Using PANDORA-seq, we revealed unprecedented landscapes of microRNA, tsRNA and rsRNA dynamics during the generation of induced pluripotent stem cells. Importantly, tsRNAs and rsRNAs that are downregulated during somatic cell reprogramming impact cellular translation in ESCs, suggesting a role in lineage differentiation.

This study was conducted to evaluate the effect of red macroalgae Asparagopsis taxiformis supplementation for cattle on the shelf life of fresh beef steaks (longissimus dorsi). Three treatment groups (seven steers per treatment) included: 1) Control diet, 2) Control diet + 0.25% of macroalgae inclusion (low dose, LD), and 3) Control + 0.5% of macroalgae inclusion (high dose, HD). After the animals were harvested, the strip loins from all animals were collected and aged for 14 days at the meat lab of the University of California, Davis. Then the strip loins were cut into steaks, packaged, and placed on a retail display case for 6 days. During a retail display, instrumental color (L*, a*, and b*) of lean muscle and external fat surfaces were measured every 12 h. Bacterial counts for total aerobic mesophilic bacteria (AMB), aerobic psychrotrophic bacteria (APB), and lactic acid bacteria (LAB) were assessed on days 0, 3, and 6 of retail display. The thiobarbituric acid reactive substances (TBARS) analysis was conducted to measure the lipid oxidation and the pH was also assessed on days 0, 3, and 6. No interactive effect between treatments and time on the shelf life of steaks was observed. The HD red macroalgae supplement decreased (P < 0.05) the lightness (L*) of the surface muscle of the steaks, while the lightness of the external fat was not affected (P < 0.05) by treatments throughout the retail display. The external fat yellowness of the steaks was lower (P < 0.05) in LD and HD treatment groups compared with the control group. An increase (P < 0.05) in counts of AMB, APB, and LAB was observed on the steaks from the steers in the HD treatment group while steaks in Control and LD group had similar bacterial numbers throughout the retail display. The results indicated that the shelf life of steaks from cattle in LD group remained the same as that of the Control group, but the HD of A. taxiformis caused a darker color of steaks with higher microbial counts

The red macroalgae (seaweed) Asparagopsis spp. has shown to reduce ruminant enteric methane (CH4) production up to 99% in vitro. The objective of this study was to determine the effect of Asparagopsis taxiformis on CH4 production (g/day per animal), yield (g CH4/kg dry matter intake (DMI)), and intensity (g CH4/kg ADG); average daily gain (ADG; kg gain/day), feed conversion efficiency (FCE; kg ADG/kg DMI), and carcass and meat quality in growing beef steers. Twenty-one Angus-Hereford beef steers were randomly allocated to one of three treatment groups: 0% (Control), 0.25% (Low), and 0.5% (High) A. taxiformis inclusion based on organic matter intake. Steers were fed 3 diets: high, medium, and low forage total mixed ration (TMR) representing life-stage diets of growing beef steers. The Low and High treatments over 147 days reduced enteric CH4 yield 45 and 68%, respectively. However, there was an interaction between TMR type and the magnitude of CH4 yield reduction. Supplementing low forage TMR reduced CH4 yield 69.8% (P <0.01) for Low and 80% (P <0.01) for High treatments. Hydrogen (H2) yield (g H2/DMI) increased (P <0.01) 336 and 590% compared to Control for the Low and High treatments, respectively. Carbon dioxide (CO2) yield (g CO2/DMI) increased 13.7% between Control and High treatments (P = 0.03). No differences were found in ADG, carcass quality, strip loin proximate analysis and shear force, or consumer taste preferences. DMI tended to decrease 8% (P = 0.08) in the Low treatment and DMI decreased 14% (P <0.01) in the High treatment. Conversely, FCE tended to increase 7% in Low (P = 0.06) and increased 14% in High (P <0.01) treatment compared to Control. The persistent reduction of CH4 by A. taxiformis supplementation suggests that this is a viable feed additive to significantly decrease the carbon footprint of ruminant livestock and potentially increase production efficiency.

New applications such as smart homes, autonomous vehicles are leading an increasing research topic of convolutional neural network (CNN) based inference on IoT edge devices. Unfortunately, this scenario meets a huge roadblock caused by the limited computing resources owned by these devices. One popular solution is to execute inference on an edge cluster with parallelization schemes instead of on a single device. However, the heterogeneous edge devices and varied neural layers bring challenges to this process. In this paper, we propose a pipelined cooperation scheme (PICO) to efficiently execute CNN inference for edge devices. Our goal is to maximize throughput by reducing redundant computing meanwhile to keep the inference latency under a certain value. PICO divides the neural layers and edge devices into several stages. The input data is fed into the first stage and the inference result is produced at the last stage. These stages compose an inference pipeline. The execution time of each stage is optimized to approach the maximum throughput as close as possible. We also implement an adaptive framework to choose the best inference scheme under different workloads. In our experiment with 8 RaspberryPi devices, the average inference latency can be reduced by $1.7\sim 6.5\times$ under different workloads, and the throughput can be improved by $1.8\sim 6.2\times$ under various network settings. © 2021 IEEE.

His-tRNA synthetase (HARS) is targeted by autoantibodies in chronic and acute inflammatory anti-Jo-1-positive antisynthetase syndrome. The extensive activation and migration of immune cells into lung and muscle are associated with interstitial lung disease, myositis, and morbidity. It is unknown whether the sequestration of HARS is an epiphenomenon or plays a causal role in the disease. Here, we show that HARS circulates in healthy individuals, but it is largely undetectable in the serum of anti-Jo-1-positive antisynthetase syndrome patients. In cultured primary human skeletal muscle myoblasts (HSkMC), HARS is released in increasing amounts during their differentiation into myotubes. We further show that HARS regulates immune cell engagement and inhibits CD4+ and CD8+ T-cell activation. In mouse and rodent models of acute inflammatory diseases, HARS administration downregulates immune activation. In contrast, neutralization of extracellular HARS by high-titer antibody responses during tissue injury increases susceptibility to immune attack, similar to what is seen in humans with anti-Jo-1-positive disease. Collectively, these data suggest that extracellular HARS is homeostatic in normal subjects, and its sequestration contributes to the morbidity of the anti-Jo-1-positive antisynthetase syndrome. © 2019, The Author(s).

As a crucial scheme to accelerate the deep neural network (DNN) training, distributed stochastic gradient descent (DSGD) is widely adopted in many real-world applications. In most distributed deep learning (DL) frameworks, DSGD is implemented with Ring-AllReduce architecture (Ring-SGD) and uses a computation-communication overlap strategy to address the overhead of the massive communications required by DSGD. However, we observe that although $O(1)$ gradients are needed to be communicated per worker in Ring-SGD, the $O(n)$ handshakes required by Ring-SGD limits its usage when training with many workers or in high latency network. In this paper, we propose Shuffle-Exchange SGD (SESGD) to solve the dilemma of Ring-SGD. In the cluster of 16 workers with 0.1ms Ethernet latency, SESGD can accelerate the DNN training to $1.7 \times$ without losing model accuracy. Moreover, the process can be accelerated up to $5\times$ in high latency networks (5ms)., Comment: NeurIPS 2020 Under Review

Classical principal component analysis (PCA) may suffer from the sensitivity to outliers and noise. Therefore PCA based on $\ell_1$-norm and $\ell_p$-norm ($0 < p < 1$) have been studied. Among them, the ones based on $\ell_p$-norm seem to be most interesting from the robustness point of view. However, their numerical performance is not satisfactory. Note that, although T$\ell_1$-norm is similar to $\ell_p$-norm ($0 < p < 1$) in some sense, it has the stronger suppression effect to outliers and better continuity. So PCA based on T$\ell_1$-norm is proposed in this paper. Our numerical experiments have shown that its performance is superior than PCA-$\ell_p$ and $\ell_p$SPCA as well as PCA, PCA-$\ell_1$ obviously.

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species

Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the β-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, β-lactams in dairies), whereas ARGs in soil were dominated by multidr

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species

A dual-functional photosensitizer that demonstrates exceptional photodynamic therapy (PDT) efficacy while simultaneously self-monitoring the therapeutic response in real time is reported here. Possessing an ultrahigh 1O2 quantum yield of 98.6% in water, the photosensitizer TPCI can efficiently induce cell death in a series of carcinoma cells (IC50 values less than 300 × 10−9 m) upon irradiation with an extremely low fluence (460 nm, 4 mW cm−2 for 10 min). In addition, TPCI can self-monitor cell death in real time. It is weakly fluorescent in living cells before irradiation and lights up the nuclei concomitantly with cell death during PDT treatment by binding with chromatin to activate its aggregation-induced emission, attributed to its strong binding affinity with DNA. In vivo studies using mouse models bearing H22 and B16F10 tumor cells validate the ultraefficient PDT efficacy of TPCI as well as the precise real-time noninvasive readout of the tumor response from the beginning of cancer treatment. The dual-functional TPCI serves as an excellent candidate for single-agent photodynamic theranostics, and this work represents a new paradigm for the development of molecules with multiple intrinsic functions for future self-reporting medical applications.

Badminton is one of the fastest sports in the world. Athletes’ body rotations introduce a lot more complexities for studying badminton. The goal of this work is to develop a series of analysis including designing MATLAB programs and acquire kinematics data of badminton sport to help badminton players improve their skills. To validate these analyses are consistent with what badminton coaches teach athletes, interviews are conducted with coaches at the collegiate level to set commonly agreed “coaching points”. A full body marker setup is applied to this study while the markers are hand-made to reduce the weight and improve accuracy. 6 badminton players in different skill levels are brought in for data collecting. Subjects are asked to perform a smash motion as a return of a high and long badminton serving. Smashing data was captured by an eight-camera Vicon Motion Capture System (Nexus 1.8.5), and one video camera. Analyses were programmed by MATLAB to examine coaching points: speed and acceleration of shuttlecock and racket, contact point on racket net surface, coefficient of momentum transfer, coefficient of restitution, the angle between racket surface direction, racket moving direction, and angular velocity contributions from body parts. The results indicate the experiments and analysis are successful. Most of the ”coaching points” are proved by comparing kinematic quantities from players. These kinematic quantities can be applied as indicators to show the skill level of a player. With further development of this research, the coaching system can provide a series of dynamic analysis and lively visualized feedback to the athlete.

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species

This experiment aimed to evaluate meat quality, fatty acid profile in back-fat, and fecal microbiota of growing-finishing pigs fed with liquid enzymatically digested food waste. Fifty-six crossbred pigs (approximately 32.99 kg body weight) were assigned to one of two treatments with seven replicate pens and four pigs per pen. Pigs were fed with control (corn-soybean meal diets) or food waste from d 0 to 53, while all pigs were fed with the control diet from d 53 to 79. The 16S rRNA sequencing was used to analyze microbiota of feces collected on d 0, 28, 53, and 79. Meat quality and carcass characteristics were measured in one pig per pen at the end of the experiment. Pigs fed with food waste contained more (p < 0.05) eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in back-fat. Feeding food waste increased (p < 0.05) the relative abundances of Lachnospiraceae and Ruminococcaceae, but decreased (p < 0.05) the relative abundances of Streptococcaceae and Clostridiaceae in feces on d 29 or d 53. In conclusion, feeding enzymatically digested food waste did not affect pork quality, but provided more beneficial fatty acids to pork consumers and altered the fecal microbiota in growing-finishing pigs.

A dual-functional photosensitizer that demonstrates exceptional photodynamic therapy (PDT) efficacy while simultaneously self-monitoring the therapeutic response in real time is reported here. Possessing an ultrahigh 1O2 quantum yield of 98.6% in water, the photosensitizer TPCI can efficiently induce cell death in a series of carcinoma cells (IC50 values less than 300 × 10−9 m) upon irradiation with an extremely low fluence (460 nm, 4 mW cm−2 for 10 min). In addition, TPCI can self-monitor cell death in real time. It is weakly fluorescent in living cells before irradiation and lights up the nuclei concomitantly with cell death during PDT treatment by binding with chromatin to activate its aggregation-induced emission, attributed to its strong binding affinity with DNA. In vivo studies using mouse models bearing H22 and B16F10 tumor cells validate the ultraefficient PDT efficacy of TPCI as well as the precise real-time noninvasive readout of the tumor response from the beginning of cancer treatment. The dual-functional TPCI serves as an excellent candidate for single-agent photodynamic theranostics, and this work represents a new paradigm for the development of molecules with multiple intrinsic functions for future self-reporting medical applications.

Badminton is one of the fastest sports in the world. Athletes’ body rotations introduce a lot more complexities for studying badminton. The goal of this work is to develop a series of analysis including designing MATLAB programs and acquire kinematics data of badminton sport to help badminton players improve their skills. To validate these analyses are consistent with what badminton coaches teach athletes, interviews are conducted with coaches at the collegiate level to set commonly agreed “coaching points”. A full body marker setup is applied to this study while the markers are hand-made to reduce the weight and improve accuracy. 6 badminton players in different skill levels are brought in for data collecting. Subjects are asked to perform a smash motion as a return of a high and long badminton serving. Smashing data was captured by an eight-camera Vicon Motion Capture System (Nexus 1.8.5), and one video camera. Analyses were programmed by MATLAB to examine coaching points: speed and acceleration of shuttlecock and racket, contact point on racket net surface, coefficient of momentum transfer, coefficient of restitution, the angle between racket surface direction, racket moving direction, and angular velocity contributions from body parts. The results indicate the experiments and analysis are successful. Most of the ”coaching points” are proved by comparing kinematic quantities from players. These kinematic quantities can be applied as indicators to show the skill level of a player. With further development of this research, the coaching system can provide a series of dynamic analysis and lively visualized feedback to the athlete.

Gene therapy approaches are being deployed to treat recessive genetic disorders by restoring the expression of mutated genes. However, the feasibility of these approaches for dominantly inherited diseases - where treatment may require reduction in the expression of a toxic mutant protein resulting from a gain-of-function allele - is unclear. Here we show the efficacy of allele-specific RNAi as a potential therapy for Charcot-Marie-Tooth disease type 2D (CMT2D), caused by dominant mutations in glycyl-tRNA synthetase (GARS). A de novo mutation in GARS was identified in a patient with a severe peripheral neuropathy, and a mouse model precisely recreating the mutation was produced. These mice developed a neuropathy by 3-4 weeks of age, validating the pathogenicity of the mutation. RNAi sequences targeting mutant GARS mRNA, but not wild-type, were optimized and then packaged into AAV9 for in vivo delivery. This almost completely prevented the neuropathy in mice treated at birth. Delaying treatment until after disease onset showed modest benefit, though this effect decreased the longer treatment was delayed. These outcomes were reproduced in a second mouse model of CMT2D using a vector specifically targeting that allele. The effects were dose dependent, and persisted for at least 1 year. Our findings demonstrate the feasibility of AAV9-mediated allele-specific knockdown and provide proof of concept for gene therapy approaches for dominant neuromuscular diseases.

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

Treatment of food-producing animals with antimicrobial drugs (AMD) is controversial because of concerns regarding promotion of antimicrobial resistance (AMR). To investigate this concern, resistance genes in metagenomic bovine fecal samples during a clinical trial were analyzed to assess the impacts of treatment on beef feedlot cattle resistomes. Four groups of cattle were exposed, using a 2-by-2 factorial design, to different regimens of antimicrobial treatment. Injections of ceftiofur crystalline-free acid (a third-generation cephalosporin) were used to treat all cattle in treatment pens or only a single animal, and either chlortetracycline was included in the feed of all cattle in a pen or the feed was untreated. On days 0 and 26, respectively, pre- and posttrial fecal samples were collected, and resistance genes were characterized using shotgun metagenomics. Treatment with ceftiofur was not associated with changes to β-lactam resistance genes. However, cattle fed chlortetracycline had a significant increase in relative abundance of tetracycline resistance genes. There was also an increase of an AMR class not administered during the study, which is a possible indicator of coselection of resistance genes. Samples analyzed in this study had previously been evaluated by culture characterization (Escherichia coli and Salmonella) and quantitative PCR (qPCR) of metagenomic fecal DNA, which allowed comparison of results with this study. In the majority of samples, genes that were selectively enriched through culture and qPCR were not identified through shotgun metagenomic sequencing in this study, suggesting that changes previously documented did not reflect changes affecting the majority of bacterial genetic elements found in the predominant fecal resistome.IMPORTANCE Despite significant concerns about public health implications of AMR in relation to use of AMD in food animals, there are many unknowns about the long- and short-term impact of common uses of AMD for trea

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

This paper develops a new technology for the quality inspection of the transmission line that is important across the tensile clamp. The new technology mainly based on the ultrasonic pulse echo thickness measurement mechanism tests the thickness of the aluminum sleeve after crimping the tensile clamp to reflect the relative position of the aluminum sleeve and the steel anchor after the crimping, thereby judging whether there is a crimping positioning defect. At the same time, it is supplemented by steel anchor model comparison, crimping position length comparison, and crimping to margin detection to determine whether the transmission line crimping quality is qualified.

We report for the first time that the commercial yttrium stabilized zirconia (YSZ) nano composite with a natural CuFe-oxide mineral (CF) exhibits a greatly enhanced ionic conductivity in the low temperature range (500-600 degrees C), e.g. 0.48 S/cm at 550 degrees C. The CF YSZ composite was prepared via a nanocomposite approach. Fuel cells were fabricated by using a CF YSZ electrolyte layer between the symmetric electrodes of the Ni0.8Co0.2Al0.5Li (NCAL) coated Ni foam. The maximum power output of 562 mW/cm(2) has been achieved at 550 degrees C. Even the CF alone to replace the electrolyte the device reached the maximum power of 281 mW/cm(2) at the same temperature. Different ion-conduction mechanisms for YSZ and CF YSZ are proposed. This work provides a new approach to develop natural mineral composites for advanced low temperature solid oxide fuel cells with a great marketability., QC 20170825

Background: Psychological disorders are common in diabetes mellitus (DM) patients, and the aim of this study was to estimate the prevalence of psychological distress and to determine the influence factors associated with psychological distress among DM patients in the Jilin province of China. Methods and Materials: Multistage, stratified cluster sampling was used in this cross-sectional study. The 12-item General Health Questionnaire (GHQ-12) was used to assess psychological status with the total score of ≥4 as the threshold for psychological distress. Results: A total of 1,956 subjects with DM were included in the study. Out of this total diabetic participants, 524 (26.8%) had psychological distress. Multiple logistic regression analysis showed that low educational level, divorce or separation from one's spouse, low family average monthly income, short sleep duration, being aware of DM status, and multiple co-morbidities are positively associated with psychological distress (all P < 0.05). Conclusions: This study revealed a high rate of psychological distress among DM population in Jilin province. Low educational level, divorce or separation from one's spouse, low family average monthly income, short sleep duration, awareness of DM status, and multiple co-morbidities are all associated with psychological distress among our study subjects. Interventions to control these factors are needed to address the psychological problems among diabetics in Jilin Province.

Background: Psychological disorders are common in diabetes mellitus (DM) patients, and the aim of this study was to estimate the prevalence of psychological distress and to determine the influence factors associated with psychological distress among DM patients in the Jilin province of China. Methods and Materials: Multistage, stratified cluster sampling was used in this cross-sectional study. The 12-item General Health Questionnaire (GHQ-12) was used to assess psychological status with the total score of ≥4 as the threshold for psychological distress. Results: A total of 1,956 subjects with DM were included in the study. Out of this total diabetic participants, 524 (26.8%) had psychological distress. Multiple logistic regression analysis showed that low educational level, divorce or separation from one's spouse, low family average monthly income, short sleep duration, being aware of DM status, and multiple co-morbidities are positively associated with psychological distress (all P < 0.05). Conclusions: This study revealed a high rate of psychological distress among DM population in Jilin province. Low educational level, divorce or separation from one's spouse, low family average monthly income, short sleep duration, awareness of DM status, and multiple co-morbidities are all associated with psychological distress among our study subjects. Interventions to control these factors are needed to address the psychological problems among diabetics in Jilin Province.