Miracle-dz/UniFAR-FTUs huggingface dataset:
In‐field genetic stock identification of overwintering coho salmon in the Gulf of Alaska: Evaluation of Nanopore sequencing for remote real‐time deployment

Genetic stock identification (GSI) by single nucleotide polymorphism (SNP) sequencing has become the gold standard for stock identification in Pacific salmon, which are found in mixed-stocks during the oceanic phase of their lifecycle. Sequencing platforms currently applied require large batch sizes and multi-day processing in specialized facilities to perform genotyping by the thousands. However, recent advances in third-generation single-molecule sequencing platforms, like the Oxford Nanopore minION, provide base calling on portable, pocket-sized sequencers and hold promise for the application of real-time, in-field stock identification on variable batch sizes. Here we report and evaluate utility and comparability of at-sea stock identification of coho salmon Oncorhynchus kisutch based on targeted SNP amplicon sequencing on the minION platform during the International Year of the Salmon Signature Expedition to the Gulf of Alaska in the winter of 2019. Long read sequencers are not optimized for short amplicons, therefore we concatenate amplicons to increase coverage and throughput. Nanopore sequencing at-sea yielded stock assignment for 50 of the 80 assessed individuals. Nanopore-based SNP calls agreed with Ion Torrent based genotypes in 83.25%, but assignment of individuals to stock of origin only agreed in 61.5% of individuals highlighting inherent challenges of Nanopore sequencing, such as resolution of homopolymer tracts and indels. However, poor representation of assayed coho salmon in the queried baseline dataset contributed to poor assignment confidence on both platforms. Future improvements will focus on lowering turnaround time, accuracy, throughput, and cost, as well as augmentation of the existing baselines, specifically in stocks from coastal northern BC and Alaska. If successfully implemented, Nanopore sequencing will provide an alternative method to the large-scale laboratory approach. Genotyping by amplicon sequencing in the hands of diverse stakeholders could inform management decisions over a broad expanse of the coast by allowing the analysis of small batches in remote areas in near real-time.
Refining conformational ensembles of flexible proteins against small-angle X-ray scattering data

Intrinsically disordered proteins and flexible regions in multi-domain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modelling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model, i.e. an algorithm to calculate experimental observables from individual conformations or ensembles. In many cases, this involve one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle X-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data, but across the entire ensemble. Here, we present a protocol to dissect the effect of free-parameters on the calculated SAXS intensities, and to identify a reliable set of values. We have implemented this procedure in our Bayesian/Maximum Entropy framework for ensemble refinement, and demonstrate the results on four intrinsically disordered proteins and a three-domain protein connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects, and suggests that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins. SIGNIFICANCE The flexibility of a protein is often key to its biological function, yet understanding and characterizing its conformational heterogeneity is difficult. We here describe a robust protocol for combining small-angle X-ray scattering experiments with computational modelling to obtain a conformational ensemble. In particular, we focus on the contribution of protein hydration to the experiments and how this is included in modelling the data. Our resulting algorithm and software should make modelling intrinsically disordered proteins and multi-domain proteins more robust, thus aiding in understanding the relationship between protein dynamics and biological function.
Seasonal variations of 137Cs concentration in freshwater charr through uptake and metabolism in 1–2 years after the Fukushima accident

Understanding the factors influencing 137Cs concentrations in freshwater salmonids is crucial for reviving inland fisheries in polluted regions. We studied seasonal variations of 137Cs concentration in charr (Salvelinus leucomaenis) through uptake and metabolism in forested headwaters at Fukushima and Gunma sites. Charr consumed both terrestrial and aquatic animals, and terrestrial prey was predated more in summer at both sites. The 137Cs concentrations in litter, which is a dominant basal food resource of both forest and stream ecosystems, differed between forest and stream due to 137Cs leaching effect on litter submerged in streams. The concentration difference in both litter and prey was greater at Fukushima site than at Gunma site. The estimated prey 137Cs concentration at Fukushima site peaked in summer when terrestrial preys are most available, whereas it remained relatively constant at Gunma site because of the small difference of 137Cs concentrations in between terrestrial and aquatic preys. The specific metabolic rate of charr was commonly changed with stream water temperature, greatest in summer and lowest in winter at both sites. Because both prey 137Cs concentrations and specific metabolic rates peaked in summer, the combination of uptake and metabolism at Fukushima site largely negated seasonal 137Cs fluctuations in charr, whereas specific metabolic rate fluctuations could be the major determinant of charr 137Cs concentrations at Gunma site. Our results suggested that 137Cs concentrations in prey items, whose seasonality are varied due to initial 137Cs fallout volume, were expected to be an important determinant for 137Cs concentrations in charr.
Sorghum Pan-Genome Explores the Functional Utility for Genomic-Assisted Breeding to Accelerate the Genetic Gain

Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart crop to overcome the food and nutritional insecurity in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought adaptation traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.
The Impact of Age Stereotypes and Age Norms on Employees’ Retirement Choices: A Neglected Aspect of Research on Extended Working Lives

This article examines how older workers employ internalized age norms and perceptions when thinking about extending their working lives or retirement timing. It draws on semi-structured interviews with employees (n = 104) and line managers, human resource managers and occupational health specialists (n = 52) from four organisations in the United Kingdom. Previous research has demonstrated discrimination against older workers but this is a limiting view of the impact that ageism may have in the work setting. Individuals are likely to internalize age norms as older people have lived in social contexts in which negative images of what it means to be “old” are prevalent. These age perceptions are frequently normalized (taken for granted) in organisations and condition how people are managed and crucially how they manage themselves. How older workers and managers think and talk about age is another dynamic feature of decision making about retirement with implications for extending working lives. Amongst our respondents it was widely assumed that older age would come with worse health—what is more generally called the decline narrative - which served both as a motivation for individuals to leave employment to maximize enjoyment of their remaining years in good health as well as a motivation for some other individuals to stay employed in order to prevent health problems that might occur from an inactive retirement. Age norms also told some employees they were now “too old” for their job, to change job, for training and/or promotion and that they should leave that “to the younger ones”—what we call a sense of intergenerational disentitlement. The implications of these processes for the extending working lives agenda are discussed.
The Stand-Alone PilZ-Domain Protein MotL Specifically Regulates the Activity of the Secondary Lateral Flagellar System in Shewanella putrefaciens

A number of bacterial species control the function of the flagellar motor in response to the levels of the secondary messenger c-di-GMP, which is often mediated by c-di-GMP-binding proteins that act as molecular brakes or clutches to slow the motor rotation. The gammaproteobacterium Shewanella putrefaciens possesses two distinct flagellar systems, the primary single polar flagellum and a secondary system with one to five lateral flagellar filaments. Here, we identified a protein, MotL, which specifically regulates the activity of the lateral, but not the polar, flagellar motors in response to the c-di-GMP levels. MotL only consists of a single PilZ domain binding c-di-GMP, which is crucial for its function. Deletion and overproduction analyses revealed that MotL slows down the lateral flagella at elevated levels of c-di-GMP, and may speed up the lateral flagellar-mediated movement at low c-di-GMP concentrations. In vitro interaction studies hint at an interaction of MotL with the C-ring of the lateral flagellar motors. This study shows a differential c-di-GMP-dependent regulation of the two flagellar systems in a single species, and implicates that PilZ domain-only proteins can also act as molecular regulators to control the flagella-mediated motility in bacteria.
Assessing Vocal Chanting as an Online Psychosocial Intervention

The ancient practice of chanting typically takes place within a community as a part of a live ceremony or ritual. Research suggests that chanting leads to improved mood, reduced stress, and increased wellbeing. During the global pandemic, many chanting practices were moved online in order to adhere to social distancing recommendations. However, it is unclear whether the benefits of live chanting occur when practiced in an online format. The present study assessed the effects of a 10-min online chanting session on stress, mood, and connectedness, carried out either in a group or individually. The study employed a 2 (chanting vs. control) × 2 (group vs. individual) between-subjects design. Participants (N = 117) were pseudo-randomly allocated across the four conditions. Before and after participation, individuals completed the Spielberg’s State Trait Anxiety Inventory, the Positive and Negative Affect Schedule, the Social Connectedness Scale and Aron’s Inclusion of Self in Other Scale. Online chanting led to a significant reduction in stress and an increase in positive affect when compared to the online control task. Participants who took part in group chanting also felt more connected to members of their chanting group than participants in the control group. However, feelings of general connectedness to all people remained similar across conditions. The investigation provides evidence that online chanting may be a useful psychosocial intervention, whether practiced individually or in a group.
The Use of Heptamethine Cyanine Dyes as Drug-Conjugate Systems in the Treatment of Primary and Metastatic Brain Tumors

Effective cancer therapeutics for brain tumors must be able to cross the blood-brain barrier (BBB) to reach the tumor in adequate quantities and overcome the resistance conferred by the local tumor microenvironment. Clinically approved chemotherapeutic agents have been investigated for brain neoplasms, but despite their effectiveness in peripheral cancers, failed to show therapeutic success in brain tumors. This is largely due to their poor bioavailability and specificity towards brain tumors. A targeted delivery system might improve the efficacy of the candidate compounds by increasing the retention time in the tumor tissue, and minimizing the numerous side effects associated with the non-specific distribution of the chemotherapy agent. Heptamethine cyanine dyes (HMCDs) are a class of near-infrared fluorescence (NIRF) compounds that have recently emerged as promising agents for drug delivery. Initially explored for their use in imaging and monitoring neoplasms, their tumor-targeting properties have recently been investigated for their use as drug carrier systems. This review will explore the recent developments in the tumour-targeting properties of a specific group of NIRF cyanine dyes and the preclinical evidence for their potential as drug-delivery systems in the treatment of primary and metastatic brain tumors.
Assessing the Response of Ruminal Bacterial and Fungal Microbiota to Whole-Rumen Contents Exchange in Dairy Cows

A major goal for the dairy industry is to improve overall milk production efficiency (MPE). With the advent of next-generation sequencing and advanced methods for characterizing microbial communities, efforts are underway to improve MPE by manipulating the rumen microbiome. Our previous work demonstrated that a near-total exchange of whole rumen contents between pairs of lactating Holstein dairy cows of disparate MPE resulted in a reversal of MPE status for ∼10 days: historically high-efficiency cows decreased in MPE, and historically low-efficiency cows increased in MPE. Importantly, this switch in MPE status was concomitant with a reversal in the ruminal bacterial microbiota, with the newly exchanged bacterial communities reverting to their pre-exchange state. However, this work did not include an in-depth analysis of the microbial community response or an interrogation of specific taxa correlating to production metrics. Here, we sought to better understand the response of rumen communities to this exchange protocol, including consideration of the rumen fungi. Rumen samples were collected from 8 days prior to, and 56 days following the exchange and were subjected to 16S rRNA and ITS amplicon sequencing to assess bacterial and fungal community composition, respectively. Our results show that the ruminal fungal community did not differ significantly between hosts of disparate efficiency prior to the exchange, and no change in community structure was observed over the time course. Correlation of microbial taxa to production metrics identified one fungal operational taxonomic unit (OTU) in the genus Neocallimastix that correlated positively to MPE, and several bacterial OTUs classified to the genus Prevotella. Within the Prevotella, Prevotella_1 was found to be more abundant in high-efficiency cows whereas Prevotella_7 was more abundant in low-efficiency cows. Overall, our results suggest that the rumen bacterial community is a primary microbial driver of host efficiency, that the ruminal fungi may not have as significant a role in MPE as previously thought, and that more work is needed to better understand the functional roles of specific ruminal microbial community members in modulating MPE.
Indifferent or Enthusiastic? Virtual Audiences Animation and Perception in Virtual Reality

In this paper, we present a virtual audience simulation system for Virtual Reality (VR). The system implements an audience perception model controlling the nonverbal behaviors of virtual spectators, such as facial expressions or postures. Groups of virtual spectators are animated by a set of nonverbal behavior rules representing a particular audience attitude (e.g., indifferent or enthusiastic). Each rule specifies a nonverbal behavior category: posture, head movement, facial expression and gaze direction as well as three parameters: type, frequency and proportion. In a first user-study, we asked participants to pretend to be a speaker in VR and then create sets of nonverbal behaviour parameters to simulate different attitudes. Participants manipulated the nonverbal behaviours of single virtual spectator to match a specific levels of engagement and opinion toward them. In a second user-study, we used these parameters to design different types of virtual audiences with our nonverbal behavior rules and evaluated their perceptions. Our results demonstrate our system’s ability to create virtual audiences with three types of different perceived attitudes: indifferent, critical, enthusiastic. The analysis of the results also lead to a set of recommendations and guidelines regarding attitudes and expressions for future design of audiences for VR therapy and training applications.
Specialty Grand Challenge: Sensor Networks

Nowadays, Sensors have been deployed all over the daily living environment, integrated into smart phones, smart watches, and other wireless terminal devices, and become the necessities in modern daily life. With the progress of IoT (Internet of Things) and AI (artificial intelligence), more wireless sensing devices will be used to extend human senses for providing accurate and comprehensive sensory data of life activities via networking. The International Data Corporation (IDC) reports that both the number of online devices and total generated data will reach unprecedented magnitudes in 2025. Their exponential increase heralds the advent of a new era named “Internet of Everything (IoE)”. Obviously, mass data is an opportunity to develop data-driven technologies, but also a challenge for computational loading capacity. Given the transmission cost, information security, and system scalability, Sensor Network based schemes may be the current optimal solution (Akyildiz et al., 2002). The field of Sensor Networks has gone through three major reforms ranging from version 1.0 (isolated static systems) to 3.0 (invisible adaptive, self-managing systems), each of which has witnessed the revolution of IoT technology. In stage 1.0, i.e., Sensor Networks 1.0, the topics under continuous discussion are about sensor localization, intelligent management, interconnection, etc., on which most of current research products still concentrate. In other words, how to connect our physical world to the Internet through sensor networks is an everlasting hotspot. In moving forward, the fusion of sensors and networks must confront the following challenges:
Regulatory T-Cells as an Emerging Barrier to Immune Checkpoint Inhibition in Lung Cancer

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment paradigm for lung cancer in recent years. These strategies consist of neutralizing antibodies against negative regulators of immune function, most notably cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and PD-1 ligand 1 (PD-L1), thereby impeding the ability of tumor cells to escape immune surveillance. Though ICIs have proven a significant advance in lung cancer therapy, overall survival rates remain low, and lung cancer continues to be the leading cause of cancer-related death in the United States. It is therefore imperative to better understand the barriers to the efficacy of ICIs, particularly additional mechanisms of immunosuppression within the lung cancer microenvironment. Recent evidence suggests that regulatory T-lymphocytes (Tregs) serve as a central mediator of immune function in lung cancer, suppressing sterilizing immunity and contributing to the clinical failure of ICIs. Here, we provide a comprehensive summary of the roles of Tregs in lung cancer pathobiology and therapy, as well as the potential means through which these immunosuppressive mechanisms can be overcome.
Towards a Bio-Inspired Real-Time Neuromorphic Cerebellum

This work presents the first simulation of a large-scale, bio-physically constrained cerebellum model performed on neuromorphic hardware. A model containing 97,000 neurons and 4.2 million synapses is simulated on the SpiNNaker neuromorphic system. Results are validated against a baseline simulation of the same model executed with NEST, a popular spiking neural network simulator using generic computational resources and double precision floating point arithmetic. Individual cell and network-level spiking activity is validated in terms of average spike rates, relative lead or lag of spike times, and membrane potential dynamics of individual neurons, and SpiNNaker is shown to produce results in agreement with NEST. Once validated, the model is used to investigate how to accelerate the simulation speed of the network on the SpiNNaker system, with the future goal of creating a real-time neuromorphic cerebellum. Through detailed communication profiling, peak network activity is identified as one of the main challenges for simulation speed-up. Propagation of spiking activity through the network is measured, and will inform the future development of accelerated execution strategies for cerebellum models on neuromorphic hardware. The large ratio of granule cells to other cell types in the model results in high levels of activity converging onto few cells, with those cells having relatively larger time costs associated with the processing of communication. Organizing cells on SpiNNaker in accordance with their spatial position is shown to reduce the peak communication load by 41%. It is hoped that these insights, together with alternative parallelization strategies, will pave the way for real-time execution of large-scale, bio-physically constrained cerebellum models on SpiNNaker. This in turn will enable exploration of cerebellum-inspired controllers for neurorobotic applications, and execution of extended duration simulations over timescales that would currently be prohibitive using conventional computational platforms.