bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrolyte Beverage Intake to Promote Hydration and Maintain Kidney Function in Guatemalan Sugarcane Workers Laboring in Hot Conditions
Authors: Krisher Lyndsay , Butler-Dawson Jaime , Yoder Hillary , Pilloni Daniel , Dally Miranda , Johnson Evan C. , Jaramillo Diana , Cruz Alex , Asensio Claudia , Newman Lee S.
Published: September 2020

Objectives:

To evaluate impact of electrolyte supplementation on hydration status and health outcomes in Guatemalan agricultural workers performing heavy work under hot climatic conditions.

Methods:

A 3-week pragmatic trial was conducted with a group of 50 workers during the 2017 to 2018 sugarcane harvest. Workers received an electrolyte hydration intervention during 2 of the 3 weeks. Blood and urine samples were collected each week.

Results:

Increased electrolyte intake resulted in less muscle injury. Kidney function was maintained across the intervention period. Workers were adequately hydrated and average electrolyte levels remained in normal ranges. Mild indications of hyponatremia occurred at higher levels of fluid intake.

Conclusions:

This trial demonstrates the feasibility of maintaining workers’ electrolyte levels under extremely hot and humid conditions while mitigating muscle injury. Electrolyte supplementation should be added to standard workplace water, rest, and shade interventions to protect workers.
Mediation and Moderation of an Educational Intervention for Improving Intention to Practise Pneumoconiosis Prevention Among South Asian Construction Workers
Authors: Wong Cho Lee , Chen Jieling , So Winnie Kowk Wei , Leung Doris Yin Ping
Published: September 2020

Objective:

To examine components of the Health Belief Model (HBM) as mediators and socio-demographic characteristics as moderators of the effects of an educational intervention on intention to practise pneumoconiosis prevention among South Asian construction workers.

Methods:

The study used a one-group pretest and posttest design. Analytic data was from 1001 South Asian construction workers in Hong Kong.

Results:

Changes in the perceived susceptibility, perceived severity, perceived benefits, cues to action, and self-efficacy mediated the intervention's efficacy in improving intention to practise pneumoconiosis prevention. The intervention was more effective in reducing perceived barriers in younger workers, enhancing self-efficacy in older workers and relatively new employees, and improving the intention in unmarried workers.

Conclusions:

It provided preliminary support for the efficacy of the intervention based on the HBM in improving intention to practise pneumoconiosis prevention among South Asian construction workers.
Imaging of renal fibrosis
Authors: Hysi Eno , Yuen Darren A.
Published: September 2020

Purpose of review

Fibrosis is an important biomarker of chronic kidney injury, and a powerful predictor of renal outcome. Currently, the only method for measuring fibrotic burden is histologic analysis, which requires a kidney biopsy in humans, or kidney removal in animal models. These requirements have not only hindered our ability to manage patients effectively, but have also prevented a full understanding of renal fibrosis pathogenesis, and slowed the translation of new antifibrotic agents. The development of noninvasive fibrosis imaging tools could thus transform both clinical care and renal fibrosis research.

Recent findings

Conventional imaging modalities have historically failed to image fibrosis successfully. However, recent exciting technological advances have greatly enhanced their capabilities. New techniques, for example, may allow imaging of the physical consequences of scarring, as surrogate measures of renal fibrosis. Similarly, other groups have developed ways to directly image extracellular matrix, either with the use of contrast-enhanced probes, or using matrix components as endogenous contrast agents.

New developments in imaging technology have the potential to transform our ability to visualize renal fibrosis and to monitor its progression. In doing so, these advances could have major implications for kidney disease care, the development of new antiscarring agents, and our understanding of renal fibrosis in general.
Immunometabolism in haematopoietic stem cell transplantation and adoptive cellular therapies
Authors: Braverman Erica L. , Waltz Gail , Byersdorfer Craig A.
Published: September 2020

Purpose of review

Controlling T cell activity through metabolic manipulation has become a prominent feature in immunology and practitioners of both adoptive cellular therapy (ACT) and haematopoietic stem cell transplantation (HSCT) have utilized metabolic interventions to control T cell function. This review will survey recent metabolic research efforts in HSCT and ACT to paint a broad picture of immunometabolism and highlight advances in each area.

Recent findings

In HSCT, recent publications have focused on modifying reactive oxygen species, sirtuin signalling or the NAD salvage pathway within alloreactive T cells and regulatory T cells. In ACT, metabolic interventions that bolster memory T cell development, increase mitochondrial density and function, or block regulatory signals in the tumour microenvironment (TME) have recently been published.

Metabolic interventions control immune responses. In ACT, efforts seek to improve the in-vivo metabolic fitness of T cells, while in HSCT energies have focused on blocking alloreactive T cell expansion or promoting regulatory T cells. Methods to identify new, metabolically targetable pathways, as well as the ability of metabolic biomarkers to predict disease onset and therapeutic response, will continue to advance the field towards clinically applicable interventions.
Differential Diagnosis of Diarrhea in Patients With Neuroendocrine Tumors
Authors: Eads Jennifer R. , Reidy-Lagunes Diane , Soares Heloisa P. , Chan Jennifer A. , Anthony Lowell B. , Halfdanarson Thorvardur R. , Naraev Boris G. , Wolin Edward M. , Halperin Daniel M. , Li Daneng , Pommier Rodney F. , Zacks Jerome S. , Morse Michael A. , Metz David C. ,   from the Carcinoid Syndrome Control Collaborative
Published: September 2020

Patients with neuroendocrine tumors (NETs) and carcinoid syndrome experience diarrhea that can have a debilitating effect on quality of life. Diarrhea also may develop in response to other hormonal syndromes associated with NETs, surgical complications, medical comorbidities, medications, or food sensitivities. Limited guidance on the practical approach to the differential diagnosis of diarrhea in these patients can lead to delays in appropriate treatment. This clinical review and commentary underscore the complexity in identifying the etiology of diarrhea in patients with NETs. Based on our collective experience and expertise, we offer a practical algorithm to guide medical oncologists and other care providers to expedite effective management of diarrhea and related symptoms in patients with NETs.
Reviews on Current Liquid Biopsy for Detection and Management of Pancreatic Cancers
Authors: Kaczor-Urbanowicz Karolina Elżbieta , Cheng Jordan , King Jonathan C. , Sedarat Alireza , Pandol Stephen J. , Farrell James J. , Wong David T.W. , Kim Yong
Published: September 2020

Pancreatic cancer is the fourth leading cause of cancer death in the United States. Pancreatic cancer presents dismal clinical outcomes in patients, and the incidence of pancreatic cancer has continuously increased to likely become the second most common cause of cancer-related deaths by as early as 2030. One of main reasons for the high mortality rate of pancreatic cancer is the lack of tools for early-stage detection. Current practice in detecting and monitoring therapeutic response in pancreatic cancer relies on imaging analysis and invasive endoscopic examination. Liquid biopsy–based analysis of genetic alterations in biofluids has become a fundamental component in the diagnosis and management of cancers. There is an urgent need for scientific and technological advancement to detect pancreatic cancer early and to develop effective therapies. The development of a highly sensitive and specific liquid biopsy tool will require extensive understanding on the characteristics of circulating tumor DNA in biofluids. Here, we have reviewed the current status of liquid biopsy in detecting and monitoring pancreatic cancers and our understanding of circulating tumor DNA that should be considered for the development of a liquid biopsy tool, which will greatly aid in the diagnosis and healthcare of people at risk.
Direct and Indirect Associations Between Loneliness and Thoughts of Self-Harm Among a Clinical Sample of Older Adults With Serious Mental Illness
Authors: Dell Nathaniel A. , Huang Jin , Buttafuoco Kayla A. , Vidovic Kristina R. , Murphy Allison M. , Farrar Leon A.
Published: September 2020

This cross-sectional study examines the relationships of loneliness and depressive symptoms to thoughts of self-harm among a clinical sample (n= 150) of older adults (M = 58.42 years, SD = 5.86 years; male, 55.3%; African American, 61.3%) with serious mental illness (SMI) receiving publicly funded, community-based psychiatric rehabilitation services. Participants completed the De Jong Gierveld Loneliness Scale, Multidimensional Scale of Perceived Social Support, Patient Health Questionnaire 9, and Geriatric Depression Scale–Short Form. Mediation analyses tested the association of loneliness with thoughts of self-harm through depressive symptoms and were adjusted for social support and demographic variables. The direct association of loneliness with thoughts of self-harm was mediated by depressive symptoms; indirect associations of overall and emotional loneliness to thoughts of self-harm were significant. Findings suggest the need for clinicians to reduce feelings of loneliness among older adults with SMI as a means of partially ameliorating depressive symptoms and thoughts of self-harm.
Voicing Jordanian Adolescents’ Suicide
Authors: Dardas Latefa Ali , Price Malena M. , Arscott Joyell , Shahrour Ghada , Convoy Sean
Published: September 2020

Background

Studies focusing on adolescent suicide in Arab countries are particularly scarce, with the few available undertaken from within an epidemiological paradigm.

Objective

This study aimed to understand Jordanian adolescents’ perceptions, beliefs, and attitudes toward suicide.

Methods

A qualitative design using 12 dual-moderator focus group discussions was conducted in public schools. Participants were selected from the three main regions of the country (rural southern, urban central, and suburban northern). Participants included Jordanian adolescent boys and girls, aged 14–17 years, who reported experiencing mild to moderate depressive symptoms. A relational content analysis approach was used for coding data, and a content analysis was used to identify salient thematic categories. Data were analyzed using NVivo software.

Results

Four themes emerged, including perceived risk factors, perceived protective factors, active and passive suicidal ideations, and e-games and Internet influences. Main risk factors were depression; anxiety; stigma, shame, and isolation; family issues; life pressures; and guilt. Conversely, religiosity, perceived positive family functioning, and availability of long-term goals seemed to confer resilience to adolescents’ suicidal ideation and behavior. Passive suicidality (having death wishes without any plans to complete suicide) was noticed most among participants who feared jeopardizing the family’s reputation if they committed suicide. Several boys with active suicidal ideations used the Blue Whale Challenge e-game to learn how to complete suicide and relinquish their problems.

Discussion

Suicide is a multifactorial problem requiring multimodal strategies. Evidence from this research suggests that those most passionate about the outcome of interest are encouraged to redouble efforts to reduce modifiable risk factors, enrich protective factors, target the underlying psychiatric illness that informs suicidal ideations and behavior, and research the effect of social media and Internet activity more deeply. Parents are advised to monitor the online activities of their children and familiarize themselves with the digital applications they use.
Adherence to a Hypoglycemia Protocol in Hospitalized Patients
Authors: Tracy Mary Fran , Manchester Carol , Mathiason Michelle A. , Wood Jeff , Moore Amy
Published: September 2020

Background

Hypoglycemia can be a common occurrence in hospitalized patients, both those with and without diabetes. Hypoglycemia poses significant risks to hospitalized patients, including increased mortality.

Objectives

This was a retrospective pre–post study of hypoglycemic patients in an academic medical center of an intervention to improve timely staff nurse adherence to a hypoglycemia protocol. The number of mild and severe hypoglycemia events pre- and postintervention, timeliness of adherence to the hypoglycemia protocol, the number of treatment interventions, and time to return patients to euglycemia were analyzed.

Methods

Data from hospitalizations of patients who experienced hypoglycemia (<70 mg/dl) and met inclusion criteria 1 year prior to intervention and 3 years postintervention were extracted, including demographics, glycemic control medications, diagnostic-related group, length of stay, and Charlson comorbidity index. For clarity and to determine if any significant change was sustained, the analysis compared data from 1 year prior to intervention to the second-year postintervention.

Results

A total of 7,895 unique hypoglycemic events in 3,819 patients experiencing 20,094 hypoglycemic measures were included in the analysis. Patients were primarily adult, female, and White. Only 58.7% of the sample had diabetes; the median Charlson comorbidity index was 6. Results demonstrated improvement postintervention to registered nurse hypoglycemia protocol adherence regardless of age category or hypoglycemia severity. There was a significant reduction in median time from the first hypoglycemia measure to the second measure. In addition, there was a significant difference in the number of treatment interventions and reduction in time from the first hypoglycemia measure to return of patient to a blood glucose of ≥70 mg/dl.

Discussion

These study results support that the use of a standardized hypoglycemia protocol and appropriate nurse workflows enables nurses to manage hypoglycemia promptly and effectively in most acute and critically ill hospitalized patients. Results also supported a differentiation in nurse workflow for patients with mild versus severe hypoglycemia. Implementing these interventions may result in avoidance or mitigation of the potential consequences of severe and/or sustained hypoglycemia.
Caring for Critically Ill Children With Suspected or Proven Coronavirus Disease 2019 Infection: Recommendations by the Scientific Sections’ Collaborative of the European Society of Pediatric and Neonatal Intensive Care*
Authors: Rimensberger Peter C. , Kneyber Martin C. J. , Deep Akash , Bansal Mehak , Hoskote Aparna , Javouhey Etienne , Jourdain Gilles , Latten Lynne , MacLaren Graeme , Morin Luc , Pons-Odena Marti , Ricci Zaccaria , Singh Yogen , Schlapbach Luregn J. , Scholefield Barnaby R. , Terheggen Ulrich , Tissières Pierre , Tume Lyvonne N. , Verbruggen Sascha , Brierley Joe
Published: September 2020

Objectives:

In children, coronavirus disease 2019 is usually mild but can develop severe hypoxemic failure or a severe multisystem inflammatory syndrome, the latter considered to be a postinfectious syndrome, with cardiac involvement alone or together with a toxic shock like-presentation. Given the novelty of severe acute respiratory syndrome coronavirus 2, the causative agent of the recent coronavirus disease 2019 pandemic, little is known about the pathophysiology and phenotypic expressions of this new infectious disease nor the optimal treatment approach.

Study Selection:

From inception to July 10, 2020, repeated PubMed and open Web searches have been done by the scientific section collaborative group members of the European Society of Pediatric and Neonatal Intensive Care.

Data Extraction:

There is little in the way of clinical research in children affected by coronavirus disease 2019, apart from descriptive data and epidemiology.

Data Synthesis:

Even though basic treatment and organ support considerations seem not to differ much from other critical illness, such as pediatric septic shock and multiple organ failure, seen in PICUs, some specific issues must be considered when caring for children with severe coronavirus disease 2019 disease.

Conclusions:

In this clinical guidance article, we review the current clinical knowledge of coronavirus disease 2019 disease in critically ill children and discuss some specific treatment concepts based mainly on expert opinion based on limited experience and the lack of any completed controlled trials in children at this time.
Tape lures swell bycatch on a Mediterranean island harbouring illegal bird trapping
Authors: Sebastianelli Matteo , Savva Georgios , Moysi Michaella , Kirschel Alexander N. G.
Published: September 2020

Mediterranean islands provide shelter and sustenance for millions of migrating birds each year. Humans have historically exploited bird migration through hunting. In Cyprus, trapping birds during their migratory peak is considered a tradition, but has long been against the law. Illegal bird trapping is lucrative, however, with trappers using tape lures that broadcast birdsong to increase capture rates. It results in the slaughter of millions of birds each year. Yet, scientific studies quantifying capture rates of target and nontarget species using methods employed by trappers are lacking. Here, we show using playback experiments that tape lures lead to an order of magnitude greater capture rates of target species, but also significantly increase bycatch, which may include species of conservation concern. Conservation efforts focusing on minimizing illegal bird killing should also consider tape lures and their contribution to the overall impact of trapping on avian populations.
Impacted Spike Frequency Adaptation Associated with Reduction of KCNQ2/3 Promotes Seizure Activity in Temporal Lobe Epilepsy
Authors: Li Rongrong , Jiang Shicheng , Tan Shuo , Liu Bei , Liu Yang , Jiang Lei , Ni Hong , Wang Qiyi , Zhao Shidi , Qian Hao , Ge Rongjing
Published: September 2020

Although numerous epilepsy-related genes have been identified by unbiased genome-wide screening based on samples from both animal models and patients, the druggable targets for temporal lobe epilepsy (TLE) are still limited. Meanwhile, a large number of candidate genes that might promote or inhibit seizure activities are waiting for further validation. In this study, we first analyzed two public databases and determined the significant down-regulations of two M-type potassium channel genes (KCNQ2/3) expressions in hippocampus samples from TLE patients. Then we reproduced the similar pathological changes in the pilocarpine mouse model of TLE and further detected the decrease of spike frequency adaptation driven by impacted M-currents on dentate gyrus granule neurons. Finally, we employed a small-scale simulation of dentate gyrus network to investigate potential functional consequences of disrupted neuronal excitability. We demonstrated that the impacted spike frequency adaptation of granule cells facilitated the epileptiform activity among the entire network, including prolonged seizure duration and reduced interictal intervals. Our results identify a new mechanism contributing to ictogenesis in TLE and suggest a novel target for the anti-epileptic drug discovery.
Explaining distortions in metacognition with an attractor network model of decision uncertainty
Authors: Atiya Nadim A. A. , Huys Quentin J. M. , Dolan Raymond J. , Fleming Stephen M.
Published: September 2020

Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the model’s uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. Notably, we are able to account for empirical confidence judgements by fitting the parameters of our biophysical model to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible.

Author Summary

In this work, we use a biologically-plausible model of decision uncertainty to show that shifts in metacognition are associated with disturbances in the interaction between decision-making and higher-order uncertainty-monitoring networks. Specifically, we show that stronger uncertainty modulation is associated with decreased metacognitive bias, sensitivity, and efficiency, with no effect on perceptual sensitivity. Our approach not only enables inferences about uncertainty modulation (and, in turn, these facets of metacognition) from fits to first-order performance data alone – but also provides a first step towards relating dynamical models of decision-making to metacognition. We also relate our model’s uncertainty modulation to psychopathology, and show that it can offer an implicit, low-dimensional marker of metacognitive (dys)function – opening the door to richer analysis of the interaction between metacognitive performance and psychopathology from first-order performance data.
Does estimation methods affect on phosphorus equivalence value of phytase for layers and broiler chickens?
Authors: Yousefi Azam , Zaghari Mojtaba
Published: September 2020

Two experiments were performed for evaluating calibration curve (CC) and comparing negative and positive controls (CNP) as a major method for estimating of phytase phosphorus equivalence for layer and broiler chickens. In the first and second experiments, 360 Hy-line W-36 layer hens and 525 day-old Ross-308 broiler chickens were used in a complete randomized design, respectively. Evaluated methods were setting the two regression equations for NPP-supplemented and phytase supplemented treatments with two sub-methods, include calibration curve (CC) or exclude the amount of phosphorus content of basal diet (CC-BD) in calculation, and exploring enzyme equivalency by comparing phosphorus deficient diet as an negative and supplemented diet by inorganic phosphorus sources as a positive control group (CNP). Experiment one included nine treatments (200, 300, 400 and 500 FTU/kg phytase was added to a phosphorus deficient basal diet contained 0.12% AvP, the rest four treatments were included basal diet supplemented with 0.20, 0.27, 0.35 and 0.43% AvP). Experiment two included seven treatments (a basal P deficient diet contained 0.27% AvP, and two increasing levels of AvP, 0.32 and 0.37%, and four doses of phytase 200, 300, 400 and 500 FTU/kg added to basal diet). Each treatment in the both experiments replicated five times. Results indicated that methods of estimation had a significant effect on phosphorus equivalence estimation (P<0.0001). Fitted regression equations considering P content of basal diet (CC-BD) estimated rational values than those ignore it (CC) (0.161%vs0.365% and 0.432%vs0.564% for 500 FTU/kg phytase for broiler chicken and layer hens, respectively) (P<0.0001). On average, among three methods used, CC method had the highest estimated values both in broiler chickens and layer hens (p<0.0001). Regardless of mathematical method, there were different significant values for different strains (layer, 0.381% and broiler, 0.179%) (P<0.0001), but not for different traits served as response criteria (P>0.05). In conclusion, the phosphorus equivalent value of enzyme varies according to the estimation methods and strain. Hence, using matrix values of enzyme for accurate feed formulation depend on a variety of circumstances and decision making requires comprehensive information.
Ultrafast Sample Placement on Existing Trees (UShER) Empowers Real-Time Phylogenetics for the SARS-CoV-2 Pandemic
Authors: Turakhia Yatish , Thornlow Bryan , Hinrichs Angie S. , De Maio Nicola , Gozashti Landen , Lanfear Robert , Haussler David , Corbett-Detig Russell
Published: September 2020

As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering a new era of “genomic contact tracing” – that is, using viral genome sequences to trace local transmission dynamics. However, because the viral phylogeny is already so large – and will undoubtedly grow many fold – placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient, tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach improves the speed of phylogenetic placement of new samples and data visualization by orders of magnitude, making it possible to complete the placements under real-time constraints. Our method also provides the key ingredient for maintaining a fully-updated reference phylogeny. We make these tools available to the research community through the UCSC SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for laboratories worldwide.

Software Availability

USHER is available to users through the UCSC Genome Browser athttps://genome.ucsc.edu/cgi-bin/hgPhyloPlace. The source code and detailed instructions on how to compile and run UShER are available fromhttps://github.com/yatisht/usher.
Maternal High Fiber Diet Protects Offspring Against Type 2 Diabetes
Authors: Toh Huishi , Thomson James A. , Jiang Peng
Published: September 2020

Previous studies have reported that maternal malnutrition is linked to increased risk of developing type 2 diabetes in adulthood. Although several diabetic risk factors associated with early life environment have been identified, protective factors remain elusive. Here, we modulate the early life environment using a maternal high fiber diet to investigate whether the offspring are protected from type 2 diabetes. We examined the interplay between early life environment (maternal diet) and later life environment (offspring diet) using a longitudinal study with 671 Nile rats. We found that exposure to a high fiber maternal diet prior to weaning significantly lowers the risk of diet-induced diabetes in the offspring. Interestingly, offspring consuming a high fiber diet after weaning do not get diet-induced diabetes, even when exposed to a diabetogenic maternal diet. Here, we provide the first evidence that the protective effect of high fiber can be transmitted to the offspring through a maternal diet, which has important implications in diabetes prevention.
Towards establishing Extracellular Vesicle-associated RNAs as biomarkers for HER2+ breast cancer
Authors: Hisey Colin L. , Tomek Petr , Nursalim Yohanes N.S. , Chamley Lawrence W. , Leung Euphemia
Published: September 2020

Extracellular vesicles (EVs) are emerging as key players in breast cancer progression and hold immense promise as cancer biomarkers. However, difficulties in obtaining sufficient quantities of EVs for the identification of potential biomarkers hampers progress in this area. To circumvent this obstacle, we cultured BT-474 breast cancer cells in a two chambered bioreactor with CDM-HD serum replacement to significantly improve the yield of cancer cell-associated EVs and eliminate bovine EV contamination. Cancer-relevant mRNAsBIRC5(Survivin) andYBX1as well as long-noncoding RNAsHOTAIR, ZFAS1, andAGAP2-AS1were detected in BT-474 EVs by quantitative RT-PCR. Bioinformatics meta-analyses showed thatBIRC5andHOTAIRRNAs were substantially upregulated compared to non-tumour breast tissue, encouraging further studies to explore their usefulness as biomarkers in patient EV samples. We contend that this effective procedure for obtaining large amounts of cancer-specific EVs will accelerate discovery of EV-associated RNA biomarkers for detection of HER2+ breast cancer.
Skeletal muscle tissue secretes more extracellular vesicles than white adipose tissue and myofibers are a major source ex vivo but not in vivo
Authors: Estrada Andrea L. , Valenti Zackary , Hehn Gabriella , Allen Christopher P. , Kruh-Garcia Nicole A. , Lark Daniel S.
Published: September 2020

Circulating extracellular vesicles (EVs) are biomarkers of and contributors to the etiology of disease. Skeletal muscle (SkM) and white adipose tissue (WAT) are the two largest organs by mass in humans and rodents but the relative contribution of EVs from these tissues is unknown. We hypothesized that SkM tissue secretes more EVs than WAT and that a dual fluorescent reporter mouse could be used to detect SkM myofiber-derived EVsin vivo. Human Protein Atlas data and directly measuring EV secretion in mouse SkM and WAT using anex vivotissue explant model confirmed that SkM tissue secretes more EVs than WAT. Differences in EV secretion between SkM and WAT were not due to SkM contraction but may be explained by differences in tissue metabolic capacity. A SkM myofiber-specific dual fluorescent reporter mouse was created. Spectral flow cytometry revealed that SkM myofibers are a major source of SkM tissue-derived EVsex vivobut few reach the circulationin vivo. Our findings demonstrate that SkM secretes more EVs than WAT and many come from SkM myofibers, but ourin vivodata indicate that EVs secreted by SkM myofibers may remain primarily in their local extracellular environment.
CircRNA may not be “circular”
Authors: Sun Handong , Wu Zijuan , Liu Ming , Yu Liang , Li Jianyong , Ding Xiangming , Jin Hui
Published: September 2020

Circular RNA (circRNA) is a novel regulatory non-coding RNA and participates in diverse physiological and pathological processes. However, the structures and molecular mechanisms of circRNAs remain unclear. In this study, we took advantage of circRNA array and bioinformatics analysis and found lots of internal complementary base-pairing sequences (ICBPS) existed in plenty of circRNAs, especially in extremely long circRNAs (el-circRNAs, > 5,000 nt). The result indicated that circRNA may not be a simple circular structure. In addition, we put forward the hypothesis of “open-close effect “ in the transition for specific circRNA from normal state to morbid state. Taken together, our results not only expand the knowledge of circRNAs, but also highlight the potential molecular mechanism of circRNAs.
Residue-by-residue analysis of cotranslational membrane protein integrationin vivo
Authors: Nicolaus Felix , Metola Ane , Mermans Daphne , Liljenström Amanda , Krč Ajda , Abdullahi Salmo Mohammed , Zimmer Matthew , Miller Thomas F. , von Heijne Gunnar
Published: September 2020

We follow the cotranslational biosynthesis of three multi-spanningE. coliinner membrane proteinsin vivousing high-resolution Force Profile Analysis. The force profiles show that the nascent chain is subjected to rapidly varying pulling forces during translation, and reveal unexpected complexities in the membrane integration process. We find that an N-terminal cytoplasmic domains can fold in the ribosome exit tunnel before membrane integration starts, that charged residues and membrane-interacting segments such as re-entrant loops and surface helices flanking a transmembrane helix (TMH) can advance or delay membrane integration, and that point mutations in an upstream TMH can affect the pulling forces generated by downstream TMHs in a highly position-dependent manner, suggestive of residue-specific interactions between TMHs during the integration process.
Inductive Inference of Gene Regulatory Network Using Supervised and Semi-supervised Graph Neural Networks
Authors: Wang Juexin , Ma Anjun , Ma Qin , Xu Dong , Joshi Trupti
Published: September 2020

Discovering gene regulatory relationships and reconstructing gene regulatory networks (GRN) based on gene expression data is a classical, long-standing computational challenge in bioinformatics. Computationally inferring a possible regulatory relationship between two genes can be formulated as a link prediction problem between two nodes in a graph. Graph neural network (GNN) provides an opportunity to construct GRN by integrating topological neighbor propagation through the whole gene network. We propose an end-to-end gene regulatory graph neural network (GRGNN) approach to reconstruct GRNs from scratch utilizing the gene expression data, in both a supervised and a semi-supervised framework. To get better inductive generalization capability, GRN inference is formulated as a graph classification problem, to distinguish whether a subgraph centered at two nodes contains the link between the two nodes. A linked pair between a transcription factor (TF) and a target gene, and their neighbors are labeled as a positive subgraph, while an unlinked TF and target gene pair and their neighbors are labeled as a negative subgraph. A GNN model is constructed with node features from both explicit gene expression and graph embedding. We demonstrate a noisy starting graph structure built from partial information, such as Pearson’s correlation coefficient and mutual information can help guide the GRN inference through an appropriate ensemble technique. Furthermore, a semi-supervised scheme is implemented to increase the quality of the classifier. When compared with established methods, GRGNN achieved state-of-the-art performance on the DREAM5 GRN inference benchmarks. GRGNN is publicly available athttps://github.com/juexinwang/GRGNN.

Highlights

We present a novel formulation of graph classification in inferring gene regulatory relationships from gene expression and graph embedding.

Our method leverages a powerful framework, gene regulatory graph neural network (GRGNN), which is flexible and powerful to ensemble statistical powers from a number of heuristic skeletons.

Our results show GRGRNN outperforms previous supervised and unsupervised methods inductively on benchmarks.

GRGNN can be interpreted and explained following the biological network motif hypothesis in gene regulatory networks.
Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: Effects on signal quality and sensitivity
Authors: Benitez-Andonegui A. , Lührs M. , Nagels-Coune L. , Ivanov D. , Goebel R. , Sorger B.
Published: September 2020

Designing optode layouts is an essential step for functional near-infrared spectroscopy (fNIRS) experiments as the quality of the measured signal and the sensitivity to cortical regions-of-interest depend on how optodes are arranged on the scalp. This becomes particularly relevant for fNIRS-based brain-computer interfaces (BCIs), where developing robust systems with few optodes is crucial for clinical applications. Available resources often dictate the approach researchers use for optode-layout design. Here we compared four approaches that incrementally incorporated subject-specific magnetic resonance imaging (MRI) information while participants performed mental-calculation, mental-rotation and inner-speech tasks. The literature-based approach (LIT) used a literature review to guide the optode layout design. The probabilistic approach (PROB), employed individual anatomical data and probabilistic maps of functional MRI (fMRI)-activation from an independent dataset. The individual fMRI (iFMRI) approach used individual anatomical and fMRI data, and the fourth approach used individual anatomical, functional and vascular information of the same subject (fVASC). The four approaches resulted in different optode layouts and the more informed approaches outperformed the minimally informed approach (LIT) in terms of signal quality and sensitivity. Further, PROB, iFMRI and fVASC approaches resulted in a similar outcome. We conclude that additional individual MRI data leads to a better outcome, but that not all the modalities tested here are required to achieve a robust setup. Finally, we give preliminary advice to efficiently using resources for developing robust optode layouts for BCI and neurofeedback applications.
Acis-regulatory atlas in maize at single-cell resolution
Authors: Marand Alexandre P. , Chen Zongliang , Gallavotti Andrea , Schmitz Robert J.
Published: September 2020

Cis-regulatory elements (CREs) encode the genomic blueprints of spatiotemporal gene expression programs enabling highly specialized cell functions. To identify CREs at cell-type resolution inZea mays, we implemented single-cell sequencing of Assay for Transposase Accessible Chromatin (scATAC-seq) in seedlings, embryonic roots, crown roots, axillary buds, and pistillate and staminate inflorescence. We describe 92 states of chromatin accessibility across 165,913 putative CREs and 52 known cell types. Patterns of transcription factor (TF) motif accessibility predicted cell identity with high accuracy, uncovered putative non-cell autonomous TFs, and revealed TF motifs underlying higher-order chromatin interactions. Comparison of maize andArabidopsis thalianadevelopmental trajectories identified TF motifs with conserved patterns of accessibility. Cell type-specific CREs were enriched with enhancer activity, phenotype-associated genetic variants, and signatures of breeding-era selection. These data, along with companion software,Socrates, afford a comprehensive framework for understanding cellular heterogeneity, evolution, andcis-regulatory grammar of cell-type specification in a major crop.
Metagenomic Noncoding RNA Profiling and Biomarker Discovery
Authors: Liu Ben , Thippabhotla Sirisha , Zhang Jun , Zhong Cuncong
Published: September 2020

Noncoding RNA plays important regulatory and functional roles in microorganisms, such as gene expression regulation, signaling, protein synthesis, and RNA processing. Given its essential role in microbial physiology, it is natural to question whether we can use noncoding RNAs as biomarkers to distinguish among environments under different biological conditions, such as those between healthy versus disease status. The current metagenomic sequencing technology primarily generates short reads, which contain incomplete structural information that may complicate noncoding RNA homology detection. On the other hand, de novo assembly of the metagenomics sequencing data remains fragmentary and has a risk of missing low-abundant noncoding RNAs. To tackle these challenges, we have developed DRAGoM (Detection ofRNA usingAssemblyGraph fromMetagenomics data), a novel noncoding RNA homology search algorithm. DRAGoM operates on a metagenome assembly graph, rather than on unassembled reads or assembled contigs. Our benchmark experiments show DRAGoM’s improved performance and robustness over the traditional approaches. We have further demonstrated DRAGoM’s real-world applications in disease characterization via analyzing a real case-control gut microbiome dataset for Type-2 diabetes (T2D). DRAGoM revealed potential ncRNA biomarkers that can clearly separate the T2D gut microbiome from those of healthy controls. DRAGoM is freely available fromhttps://github.com/benliu5085/DRAGoM.
Improved yellow-green split fluorescent proteins for protein labeling and signal amplification
Authors: Zhou Shuqin , Feng Siyu , Brown David , Huang Bo
Published: September 2020

The flexibility and versatility of self-complementing split fluorescent proteins (FPs) have enabled a wide range of applications. In particular, the FP1-10/11split system contains a small fragment that facilitates efficient generation of endogenous-tagged cell lines and animals as well as signal amplification using tandem FP11tags. To improve the FP1-10/11toolbox we previously developed, here we used a combination of directed evolution and rational design approaches, resulting in two mNeonGreen (mNG)-based split FPs (mNG3A1-10/11and mNG3K1-10/11) and one mClover-based split FP (CloGFP1-10/11). mNG3A1-10/11and mNG3K1-10/11not only enhanced the complementation efficiency at low expression levels, but also allowed us to demonstrate signal amplification using tandem mNG211fragments in mammalian cells.
Quantifying the Brain Predictivity of Artificial Neural Networks with Nonlinear Response Mapping
Authors: Anand Aditi , Sen Sanchari , Roy Kaushik
Published: September 2020

Quantifying the similarity between artificial neural networks (ANNs) and their biological counterparts is an important step towards building more brain-like artificial intelligence systems. Recent efforts in this direction useneural predictivity, or the ability to predict the responses of a biological brain given the information in an ANN (such as its internal activations), when both are presented with the same stimulus. We propose a new approach to quantifying neural predictivity by explicitly mapping the activations of an ANN to brain responses with a nonlinear function, and measuring the error between the predicted and actual brain responses. Further, we propose to use a neural network to approximate this mapping function by training it on a set of neural recordings. The proposed method was implemented within the Tensorflow framework and evaluated on a suite of 8 state-of-the-art image recognition ANNs. Our experiments suggest that the use of a non-linear mapping function leads to higher neural predictivity. Our findings also reaffirm the observation that the latest advances in classification performance of image recognition ANNs are not matched by improvements in their neural predictivity. Finally, we examine the impact of pruning, a widely used ANN optimization, on neural predictivity, and demonstrate that network sparsity leads to higher neural predictivity.
Self-organized pattern formation increases functional diversity
Authors: Hülsemann Janne , Klauschies Toni , Guill Christian
Published: September 2020

Self-organized formation of spatial patterns is known from a variety of different ecosystems, yet little is known how these patterns affect functional diversity of local and regional communities. Here we use a food chain model in which autotroph diversity is described by a continuous distribution of a trait that affects both growth rate and defense against a heterotroph. On a single patch, stabilizing selection always promotes the dominance of a single autotroph species. Two alternative community states, with either defended or undefended species, are possible. In a metacommunity context, dispersal can destabilize these states, and complex spatio-temporal patterns emerge. This creates varying selection pressures on the local autotroph communities, which feed back on the trait dynamics. Local functional diversity increases ten-fold compared to a situation without self-organized pattern formation, thereby maintaining the adaptive potential of communities in an environment threatened by fragmentation and global change.
Endosomal Sorting Drives the Formation of Mutant Prion Endoggresomes
Authors: Chassefeyre Romain , Chaiamarit Tai , Verhelle Adriaan , Novak Sammy Weiser , Andrade Leonardo R. , Manor Uri , Encalada Sandra E.
Published: September 2020

Intra-axonal misfolded protein aggregates are a pathological feature of neurodegenerative diseases. How aggregates are formed and cleared is key to maintaining proteostasis. By systematically analyzing the trafficking itinerary of a misfolded GPI-anchored prion protein (PrP) mutant, we unveil endocytic pathways that drive its immediate degradation in the soma, versus its aggregation in axons inside endosomal structures we termed endoggresomes. Axonal sorting occurs post-Golgi, by association of mutant PrP vesicles with Arl8b/kinesin-1/HOPS, a complex that earmarks them for axonal entry, fusion, and aggregation via a mechanism ofaxonalrapidendosomalsorting andtransport-dependentaggregation (ARESTA). Endoggresomes persist in axons due to transport and lysosomal deficits, impairing calcium dynamics and accelerating neuronal death. Reducing ARESTA inhibits endoggresome formation and circumvents these defects. These data identify the endo-lysosomal system as critical for the sorting of misfolded PrP, and ARESTA as an actionable anti-aggregation target that can ameliorate axonal dysfunction in the prionopathies.
Acute noise causes down-regulation of ECM protein expression in guinea pig cochlea
Authors: Shi Min , Shi Lei , Ding Daxiong , Hu Yiyong , Qi Guowei , Zhan Li , Zhu Yuhua , Lv Ping , Yu Ning
Published: September 2020

Objective

To study the differences in cochlea protein expression before and after noise exposure using proteomics to reveal the pathological mechanism of noise-induced hearing loss (NIHL).

Methods

A guinea pig NIHL model was established to test the ABR thresholds before and after noise exposure. The proteomics technology was used to study the mechanism of differential protein expression in the cochlea by noise stimulation.

Results

The average hearing threshold of guinea pigs on the first day after noise exposure was 57.00±6.78dB SPL, high-frequency hearing loss was more severe than low frequency; the average hearing threshold on the seventh day after noise exposure was 45.83±6.07dB SPL, and the 4k Hz hearing threshold has the best recovery. The proteomics technology identified 3122 different inner ear proteins, of which six proteins related to the hearing were down-regulation: TenascinC, Collagen type XI alpha two chains, Collagen type II alpha one chain, Thrombospondin 2, Collagen type XI alpha one chain and Ribosomal protein L38, and are enriched in protein absorption, focal adhesion, and extracellular matrix receptor pathways.

Conclusion

Impulse noise can affect the expression of differential proteins through focal adhesion pathways. This data can provide an experimental basis for the research on the prevention and treatment of NIHL.
THAP1 Modulates Oligodendrocyte Maturation by Regulating ECM Degradation in Lysosomes
Authors: Yellajoshyula Dhananjay , Pappas Samuel S. , Rogers Abigail , Choudhury Biswa , Reed Xylena , Ding Jinhui , Cookson Mark R. , Shakkottai Vikram , Giger Roman , Dauer William T.
Published: September 2020

Mechanisms controlling myelination during CNS maturation play a pivotal role in the development and refinement of CNS circuits. The transcription factor THAP1 is essential for timing the inception of myelination during CNS maturation through a cell-autonomous role in the oligodendrocyte lineage. Here, we demonstrate that THAP1 modulates ECM composition by regulating glycosaminoglycan (GAG) catabolism within oligodendrocyte progenitor cells (OPCs).Thap1-/-OPCs accumulate and secrete excess GAGs, inhibiting their maturation through an auto-inhibitory mechanism. THAP1 controls GAG metabolism by binding to and regulating theGusBgene encoding β-glucuronidase, a GAG-catabolic lysosomal enzyme. Applying GAG-degrading enzymes or overexpressing β-glucuronidase rescuesThap1-/-OL maturation deficitsin vitroandin vivo.Our studies establish lysosomal GAG catabolism within OPCs as a critical mechanism regulating oligodendrocyte development.