bluuebunny/crossref_metadata_2025 huggingface dataset:
Personalization of Restorative and Compensatory Treatments for People With Aphasia
Authors: Thiessen Amber , Brown Jessica
Published: August 2021

Speech–language pathologists serving individuals with aphasia must make many decisions regarding assessment and intervention practices to support comprehension and expression of language. Each of these decisions can influence the effectiveness of therapy and long-term functional outcomes for individuals with aphasia. One factor that must be considered is the impact of personalizing therapy techniques to match the unique strengths and challenges of a client as well as incorporating personally relevant stimuli and methodologies into therapy. Research indicates that treatment customization can have a positive impact on service provision quality and can potentially lead to positive outcomes in therapy. The purpose of this article is to provide a broad overview of how personalization can be achieved across a variety of interventions. Furthermore, we explore factors (e.g., client motivation, cognitive resources) that influence therapeutic outcomes and discuss the benefits, challenges, and rationale for therapy customization.
Personalization of Patient–Provider Communication Across the Life Span
Authors: Gormley Jessica , Koch Fager Susan
Published: August 2021

People with disabilities are more likely to be hospitalized and use health care services than people without disabilities. They also report negative experiences interacting with health care providers during these encounters, placing them at risk for preventable adverse medical events, poor quality of life, and dependence on others. Fortunately, providers and people with communication disabilities can take steps to improve these interactions by personalizing and implementing communication supports to empower people with communication disabilities to actively participate in these interactions and improve outcomes. The purpose of this article is to describe strategies that health care providers can use to develop and implement personalized communication supports for children and adults with communication disorders during health care interactions. Additional strategies are provided to guide people with disabilities as well as their community/school providers and families to prepare for health care interactions. Case examples are provided to illustrate use of these strategies in acute care, inpatient rehabilitation, and outpatient settings. The use of emerging training tools (e.g., video visual scene displays) and augmentative or alternative communication partner training formats (e.g., just-in-time training) are also presented as future directions to expedite learning and implementation of communication supports in fast-paced and time-limited health care interactions.
Personalization of Visual Scene Displays
Authors: Beukelman David R. , Thiessen Amber , Fager Susan Koch
Published: August 2021

Visual scene displays (VSDs) are becoming an increasingly popular method of message representation within augmentative and alternative communication (AAC) supports; however, design factors can influence the effectiveness of these images as communication supports. One issue that has come to light in recent years is the fact that selecting personalized VSDs, which depict the person with complex communication needs or an individual with whom they are familiar, is preferred over generic VSDs, which depict unfamiliar individuals. Although personalization is likely an important factor in the usability of VSDs, these images may be difficult for clinicians to obtain. As such, compromises must be identified. The purpose of this study was to explore the effects of controlling personal relevance factors (i.e., age and gender of the people depicted in generic VSDs) on the image preference patterns of adults with and without aphasia. Results from three very preliminary study summaries indicate that gender and age are both mitigating factors in image preference, as males tended to indicate preference for VSDs containing males over those containing females. In addition, females tended to indicate preference for females of a similar age depicted in VSDs.
Lip Laceration and Vermilion Border Repair
Authors: Campo Theresa M.
Published: August 2021

Lacerations to the face and lips are commonly seen in the emergency setting from dog bites, falls, and blunt trauma (motor vehicle crash, strike with an object, etc.). Lip lacerations, especially involving the vermilion border, can be most challenging and deforming, especially when greater than 25% of the lip is involved. These lacerations require preciseness for a good cosmetic outcome. Lips are a highly visible facial structure and consist of 3 layers: skin, muscle, and oral mucosa. They are used for speech, food consumption, and tactile sensation (Lammers & Scrimshaw, 2019
;
Lent, 2020).
The Undertriage of Older Adults in the Emergency Department
Authors: Davis Philip , Evans Dian Dowling
Published: August 2021

The Research to Practice column is intended to improve the research critique skills of the advanced practice registered nurse and the emergency nurse and to assist with the translation of research into practice. A topic and a research study are selected for each column. A patient scenario is presented as a vehicle, in which to review and critique, the findings of the selected research study. In this column, we review the conclusions of A. Malinovska, L. Pitasch, N. Geigy, C. H. Nickel, and R. Bingisser (2019) from their article, titled “Modification of the Emergency Severity Index Improves Mortality Prediction in Older Patients.”
Therapeutic strategies for C9orf72 amyotrophic lateral sclerosis and frontotemporal dementia
Authors: Hautbergue Guillaume M. , Cleary John D. , Guo Shu , Ranum Laura P.W.
Published: August 2021

Purpose of review

An intronic G4C2 expansion mutation in C9orf72 is the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia (C9-ALS/FTD). Although there are currently no treatments for this insidious, fatal disease, intense research has led to promising therapeutic strategies, which will be discussed here.

Recent findings

Therapeutic strategies for C9-ALS/FTD have primarily focused on reducing the toxic effects of mutant expansion RNAs or the dipeptide repeat proteins (DPRs). The pathogenic effects of G4C2 expansion transcripts have been targeted using approaches aimed at promoting their degradation, inhibiting nuclear export or silencing transcription. Other promising strategies include immunotherapy to reduce the DPRs themselves, reducing RAN translation, removing the repeats using DNA or RNA editing and manipulation of downstream disease-altered stress granule pathways. Finally, understanding the molecular triggers that lead to pheno-conversion may lead to opportunities that can delay symptomatic disease onset.

A large body of evidence implicates RAN-translated DPRs as a main driver of C9-ALS/FTD. Promising therapeutic strategies for these devastating diseases are being rapidly developed with several approaches already in or approaching clinical trials.
On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems
Authors: Wang Yingxu , Karray Fakhri , Kwong Sam , Plataniotis Konstantinos N. , Leung Henry , Hou Ming  , Tunstel Edward , Rudas Imre J. , Trajkovic Ljiljana  , Kaynak Okyay , Kacprzyk Janusz  , Zhou Mengchu , Smith Michael H. , Chen Philip , Patel Shushma
Published: August 2021

Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human–machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention or synergize humans and intelligent machines in coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviours. This paper explores the cognitive and mathematical foundations of SAS. The challenges to seamless human–machine interactions in a hybrid environment are addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, cognitive computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via autonomous knowledge learning systems that symbiotically work between humans and cognitive robots.

This article is part of the theme issue ‘Towards symbiotic autonomous systems'.
A model of symbiomemesis: machine education and communication as pillars for human-autonomy symbiosis
Authors: Abbass Hussein , Petraki Eleni , Hussein Aya , McCall Finlay , Elsawah Sondoss
Published: August 2021

Symbiosis is a physiological phenomenon where organisms of different species develop social interdependencies through partnerships. Artificial agents need mechanisms to build their capacity to develop symbiotic relationships. In this paper, we discuss two pillars for these mechanisms: machine education (ME) and bi-directional communication. ME is a new revolution in artificial intelligence (AI) which aims at structuring the learning journey of AI-enabled autonomous systems. In addition to the design of a systematic curriculum, ME embeds the body of knowledge necessary for the social integration of AI, such as ethics, moral values and trust, into the evolutionary design and learning of the AI. ME promises to equip AI with skills to be ready to develop logic-based symbiosis with humans and in a manner that leads to a trustworthy and effective steady-state through the mental interaction between humans and autonomy; a state we name
symbiomemesis
to differentiate it from ecological symbiosis. The second pillar, bi-directional communication as a discourse enables information to flow between the AI systems and humans. We combine machine education and communication theory as the two prerequisites for symbiosis of AI agents and present a formal computational model of symbiomemesis to enable symbiotic human-autonomy teaming.

This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
Engineering human-focused Industrial Cyber-Physical Systems in Industry 4.0 context
Authors: Walter Colombo Armando , Karnouskos Stamatis , Hanisch Christoph
Published: August 2021

The world is increasingly interconnected, and this can also be seen in industry, where an ecosystem of digitalized assets, and humans with appropriate digital interfaces, constantly interact with each other. Digital transformation efforts in the industry rely on Industrial Cyber-Physical Systems that are driven by service-based cooperation among humans and digitalized industrial assets. This implies a radical paradigm change in their engineering and operation, which is focused on the symbiosis of digitalized assets and humans that cohabit a collaboration-driven industrial ecosystem. This work discusses how a digital transformation can effectively be achieved in an industrial ecosystem via a digitalization process performed along the three dimensions of the Reference Architecture Model for Industry 4.0, facilitated by the specification, development and implementation of an Asset Administration Shell. The discussion focus is put on humans and how the digitally transformed industrial environments empower her/his capabilities and interactions. It is also critically pointed out how one should go beyond technology and consider additional aspects. Therefore, it is argued that human-centred efforts in Industry 4.0 (I4.0) should be seen in the larger context of sustainability and circular economy in order to properly consider the interplay of the involved socio-technical dimensions.

This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
Complete genome sequence and probiotic properties of Lactococcus petauri LZys1 isolated from healthy human gut
Authors: Li Ouyang , Zhang Huijian , Wang Wenjing , Liang Yuxin , Chen Wenbi , Din Ahmad Ud , Li Li , Zhou Yingshun
Published: August 2021

Introduction.

Lactococcus petauri

LZys1 (

L. petauri

LZys1) is a type of lactic acid bacteria (LAB), which was initially isolated from healthy human gut.

Hypothesis/Gap Statement. It was previously anticipated that

L. petauri

LZys1 has potential characteristics of probiotic properties. The genetic structure and the regulation functions of

L. petauri

LZys1 need to be better revealed.

Aim. The aim of this study was to detect the probiotic properties

L. petauri

LZys1 and to reveal the genome information related to its genetic adaptation and probiotic profiles.

Methodology. Multiple in vitro experiments were carried out to evaluate its lactic acid-producing ability, resistance to pathogenic bacterial strains, auto-aggregation and co-aggregation ability, and so on. Additionally, complete genome sequencing, gene annotation, and probiotic associated gene analysis were performed.

Results. The complete genome of

L. petauri

LZys1 comprised of 1 985 765 bp, with a DNA G+C content of 38.07 %, containing 50 tRNA, seven rRNA, and four sRNA. A total of 1931 genes were classified into six functional categories by Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The neighbour-joining phylogeny tree based on the whole genome of

L. petauri

LZys1 and other probiotics demonstrated that

L. petauri

LZys1 has a significant similarity to

Lactococcus garvieae

. The functional genes were detected to expound the molecular mechanism and biochemical processes of its potential probiotic properties, such as atpB gene.

Conclusion. All the results described in this study, together with relevant information previously reported, made L. prtauri LZys1 a very interesting potential strain to be considered as a prominent candidate for probiotic use.
Monomorphic Trypanozoon: towards reconciling phylogeny and pathologies
Authors: Oldrieve Guy , Verney Mylène , Jaron Kamil S. , Hébert Laurent , Matthews Keith R.
Published: August 2021

Trypanosoma brucei evansi and T. brucei equiperdum are animal infective trypanosomes conventionally classified by their clinical disease presentation, mode of transmission, host range, kinetoplast DNA (kDNA) composition and geographical distribution. Unlike other members of the subgenus Trypanozoon, they are non-tsetse transmitted and predominantly morphologically uniform (monomorphic) in their mammalian host. Their classification as independent species or subspecies has been long debated and genomic studies have found that isolates within T. brucei evansi and T. brucei equiperdum have polyphyletic origins. Since current taxonomy does not fully acknowledge these polyphyletic relationships, we re-analysed publicly available genomic data to carefully define each clade of monomorphic trypanosome. This allowed us to identify, and account for, lineage-specific variation. We included a recently published isolate, IVM-t1, which was originally isolated from the genital mucosa of a horse with dourine and typed as T. equiperdum. Our analyses corroborate previous studies in identifying at least four distinct monomorphic T. brucei clades. We also found clear lineage-specific variation in the selection efficacy and heterozygosity of the monomorphic lineages, supporting their distinct evolutionary histories. The inferred evolutionary position of IVM-t1 suggests its reassignment to the T. brucei evansi type B clade, challenging the relationship between the Trypanozoon species, the infected host, mode of transmission and the associated pathological phenotype. The analysis of IVM-t1 also provides, to our knowledge, the first evidence of the expansion of T. brucei evansi type B, or a fifth monomorphic lineage represented by IVM-t1, outside of Africa, with important possible implications for disease diagnosis.
Comparison of Wild Type DNA Sequence of Spike Protein from SARS-CoV-2 with Optimized Sequence on The Induction of Protective Responses Against SARS-Cov-2 Challenge in Mouse Model
Authors: Jiang Sheng , Wu Shuting , Zhao Gan , He Yue , Hou Jiawang , Ding Yuan , Bao Linlin , Liu Jiangning , Qin Chuan , Cheng Alex , Jiang Brian , Wu John , Yan Jian , Patel Ami , Weiner David B. , Humeau Laurent , Broderick Kate , Wang Bin
Published: August 2021

COVID-19 caused by SARS-CoV-2 has been spreading worldwide. To date, several vaccine candidates moved into EUA or CA applications. Although DNA vaccine is on phase III clinical trial, it is a promised technology platform with many advantages. Here, we showed that the pGX9501 DNA vaccine encoded the spike full-length protein-induced strong humoral and cellular immune responses in mice with higher neutralizing antibodies, blocking the hACE2-RBD binding against live virus infection in vitro. Importantly, higher levels of IFN-γ expression in CD8+ and CD4+ T cell and specific cytotoxic lymphocyte (CTL) killings effect were also observed in the pGX9501-immunized group. It provided subsequent protection against virus challenges in the hACE2 transgenic mouse model. Overall, pGX9501 was a promising DNA vaccine candidate against COVID-19, inducing strong humoral immunity and cellular immunity that contributed to the vaccine’s protective effects.
Third Generation Cytogenetic Analysis (TGCA): diagnostic application of long-read sequencing
Authors: Magini Pamela , Mingrino Alessandra , Gega Barbara , Mattei Gianluca , Semeraro Roberto , Bolognini Davide , Mongelli Patrizia , Desiderio Laura , Pittalis Maria Carla , Pippucci Tommaso , Magi Alberto
Published: August 2021

Unbalanced Structural Variants (uSVs) play important roles in the pathogenesis of several genetic syndromes. Traditional and molecular karyotyping are considered the first-tier diagnostic tests to detect macroscopic and cryptic deletions/duplications. However, their time-consuming and laborious experimental protocols protract diagnostic times from three to fifteen days. Long read sequencing approaches, such as Oxford Nanopore Technologies (ONT), have the ability to reduce time to results for the detection of uSVs with the same resolution of current state-of-the-art diagnostic tests.

Here we compared ONT to molecular karyotyping for the detection of pathogenic uSVs of 7 patients with previously diagnosed causative CNVs of different sizes and allelic fractions. Larger chromosomal anomalies included trisomy 21 and mosaic tetrasomy 12p. Among smaller CNVs we tested two reciprocal genomic imbalances in 7q11.23 (1.367 Mb), a 170 kb deletion encompassing NRXN1 and mosaic 6q27 (1.231 Mb) and 2q23.1 (408 kb) deletions. DNA libraries were prepared following ONT standard protocols and sequenced on the GridION device for 48 h. Data generated during runs were analysed in online mode, using NanoGLADIATOR.

We were capable to identify all pathogenic CNVs with detection time inversely proportional to size and allelic fraction. Aneuploidies were called after only 30 minutes of sequencing, while 30 hours were needed to call CNVs < 500 kb also in mosaic state (44%). These results demonstrate the clinical utility of our approach that allows the molecular diagnosis of genomic disorders within a 30 minutes to 30 hours time-frame.
Estimation of effective concentrations enforced by complex linker architectures from conformational ensembles
Authors: Kjaergaard Magnus
Published: August 2021

Proteins and protein assemblies often tether interaction partners to strengthen interactions, to regulate activity through auto-inhibition or -activation, or to boost enzyme catalysis. Tethered reactions are regulated by the architecture of the tether, which defines an effective concentration of the interactor. Effective concentrations can be estimated theoretically for simple linkers via polymer models, but there is currently no general method for estimating effective concentrations for complex linker architectures consisting of both flexible and folded domains. We describe how effective concentrations can be estimated computationally for any protein linker architecture by defining a realistic conformational ensemble. We benchmark against prediction from a worm-like chain and values measured by competition experiments and find minor differences likely due to excluded volume effects. Systematic variation of the properties of flexible and folded segments show that the effective concentration is mainly determined by the combination of the total length of flexible segments and the distance between the termini of the folded domains. We show that a folded domain in a disordered linker can increase the effective concentration beyond what can be achieved by a fully disordered linker by focusing the end-to-end distance at the appropriate spacing. This suggests that complex linker architecture may have advantages over simple flexible linkers and emphasizes that annotation as a linker should depend on the molecular context.
Antiviral face mask functionalized with solidified hand soap: low-cost infection prevention clothing against enveloped viruses such as SARS-CoV-2
Authors: Cano-Vicent Alba , Tuñón-Molina Alberto , Martí Miguel , Muramoto Yukiko , Noda Takeshi , Takayama Kazuo , Serrano-Aroca Ángel
Published: August 2021

Infection prevention clothing is becoming an essential protective tool in the current pandemic, especially because now we know that SARS-CoV-2 can easily infect humans in poorly ventilated indoor spaces. However, commercial infection prevention clothing is made of fabrics that are not capable of inactivating the virus. Therefore, viral infections of symptomatic and asymptomatic individuals wearing protective clothing such as masks can occur through aerosol transmission or by contact with the contaminated surfaces of the masks, which are suspected as an increasing source of highly infectious biological waste. Herein, we report an easy fabrication method of a novel antiviral non-woven fabric containing polymer filaments that were coated with solidified hand soap. This extra protective fabric is capable of inactivating enveloped viruses such as SARS-CoV-2 and phi 6 in one minute of contact. In this study, this antiviral fabric was used to fabricate an antiviral face mask and did not show any cytotoxic effect in human keratinocyte HaCaT cells. Furthermore, this antiviral non-woven fabric could be used for the fabrication of other infection prevention clothing such as caps, scrubs, shirts, trousers, disposable gowns, overalls, hoods, aprons, and shoe covers. Therefore, this low-cost technology could provide a wide range of infection protective tools to combat COVID-19 and future pandemics in developed and underdeveloped countries.
ALGAEFUN with MARACAS, microALGAE FUNctional enrichment tool for MicroAlgae RnA-seq and Chip-seq AnalysiS
Authors: Romero-Losada Ana B. , Arvanitidou Christina , de los Reyes Pedro , García-González Mercedes , Romero-Campero Francisco J.
Published: August 2021

Background

Microalgae are emerging as promising sustainable sources for biofuels, biostimulants in agriculture, soil bioremediation, feed and human nutrients. Nonetheless, the molecular mechanisms underpinning microalgae physiology and the biosynthesis of compounds of biotechnological interest are largely uncharacterized. This hinders the development of microalgae full potential as cell-factories. The recent application of omics technologies into microalgae research aims at unraveling these systems. Nevertheless, the lack of specific tools for analysing omics raw data generated from microalgae to provide biological meaningful information are hampering the impact of these technologies. The purpose of ALGAEFUN with MARACAS consists in providing researchers in microalgae with an enabling tool that will allow them to exploit transcriptomic and cistromic high-throughput sequencing data.

Results

ALGAEFUN with MARACAS consists of two different tools. First, MARACAS (MicroAlgae RnA-seq and Chip-seq AnalysiS) implements a fully automatic computational pipeline receiving as input RNA-seq (RNA sequencing) or ChIP-seq (chromatin immunoprecipitation sequencing) raw data from microalgae studies. MARACAS generates sets of differentially expressed genes or lists of genomic loci for RNA-seq and ChIP-seq analysis respectively. Second, ALGAEFUN (microALGAE FUNctional enrichment tool) is a web-based application where gene sets generated from RNA-seq analysis as well as lists of genomic loci from ChIP-seq analysis can be used as input. On the one hand, it can be used to perform Gene Ontology and biological pathways enrichment analysis over gene sets. On the other hand, using the results of ChIP-seq data analysis, it identifies a set of potential target genes and analyses the distribution of the loci over gene features. Graphical representation of the results as well as tables with gene annotations are generated and can be downloaded for further analysis.

Conclusions

ALGAEFUN with MARACAS provides an integrated environment for the microalgae research community that facilitates the process of obtaining relevant biological information from raw RNA-seq and ChIP-seq data. These applications are designed to assist researchers in the interpretation of gene lists and genomic loci based on functional enrichment analysis. ALGAEFUN with MARACAS is publicly available on https://greennetwork.us.es/AlgaeFUN/.
Group-level inference of information-based measures for the analyses of cognitive brain networks from neurophysiological data
Authors: Combrisson Etienne , Allegra Michele , Basanisi Ruggero , Ince Robin A. A. , Giordano Bruno , Bastin Julien , Brovelli Andrea
Published: August 2021

The reproducibility crisis in neuroimaging and in particular in the case of underpowered studies has introduced doubts on our ability to reproduce, replicate and generalize findings. As a response, we have seen the emergence of suggested guidelines and principles for neuroscientists known asGood Scientific Practicefor conducting more reliable research. Still, every study remains almost unique in its combination of analytical and statistical approaches. While it is understandable considering the diversity of designs and brain data recording, it also represents a striking point against reproducibility. Here, we propose a non-parametric permutation-based statistical framework, primarily designed for neurophysiological data, in order to perform group-level inferences on non-negative measures of information encompassing metrics from information-theory, machine-learning or measures of distances. The framework supports both fixed- and random-effect models to adapt to inter-individuals and inter-sessions variability. Using numerical simulations, we compared the accuracy in ground-truth retrieving of both group models, such as test- and cluster-wise corrections for multiple comparisons. We then reproduced and extended existing results using both spatially uniform MEG and non-uniform intracranial neurophysiological data. We showed how the framework can be used to extract stereotypical task- and behavior-related effects across the population covering scales from the local level of brain regions, inter-areal functional connectivity to measures summarizing network properties. We also present an open-source Python toolbox called Frites1that includes the proposed statistical pipeline using information-theoretic metrics such as single-trial functional connectivity estimations for the extraction of cognitive brain networks. Taken together, we believe that this framework deserves careful attention as its robustness and flexibility could be the starting point toward the uniformization of statistical approaches.

Graphical abstract

Highlights

Group-level statistics for extracting neurophysiological cognitive brain networks

Combining non-parametric permutations with measures of information

Fixed- and random-effect models, test- and cluster-wise corrections

Multi-level inferences, from local regions to inter-areal functional connectivity

A Python open-source toolbox calledFritesincludes the proposed statistical methods
Anterior thalamic nuclei: A critical substrate for non-spatial paired-associate memory in rats
Authors: Hamilton Jennifer J , Dalrymple-Alford John C
Published: August 2021

Injury or dysfunction in the anterior thalamic nuclei (ATN) may be the key contributory factor in many instances of diencephalic amnesia. Experimental ATN lesions impair spatial memory and temporal discriminations, but there is only limited support for a more general role in non-spatial memory. To extend evidence on the effects of ATN lesions, we examined the acquisition of bi-conditional associations between odour and object pairings presented in a runway, either with or without a temporal gap between these items. Intact adult male rats acquired both the no-trace and 10-second trace versions of this non-spatial task. Intact rats trained in the trace version showed elevated Zif268 activation in the dorsal CA1 of the hippocampus, suggesting that the temporal component recruited additional neural processing. ATN lesions completely blocked acquisition on both versions of this association-memory task. This deficit was not due to poor inhibition to non-rewarded cues or impaired sensory processing, because rats with ATN lesions were unimpaired in the acquisition of simple odour discriminations and simple object discriminations using similar task demands in the same apparatus. This evidence challenges the view that impairments in arbitrary paired-associate learning after ATN lesions require the use of multimodal spatial stimuli. It suggests that diencephalic amnesia associated with the ATN stems from degraded attention to stimulus-stimulus associations and their representation across a distributed memory system.
Angiotensin antagonist inhibits preferential negative memory encoding via decreasing hippocampus activation and its coupling with amygdala
Authors: Xu Ting , Zhou Xinqi , Jiao Guojuan , Zeng Yixu , Zhao Weihua , Li Jialin , Yu Fangwen , Zhou Feng , Yao Shuxia , Becker Benjamin
Published: August 2021

Exaggerated arousal and dysregulated emotion-memory interactions are key pathological dysregulations that accompany the development of post-traumatic stress disorder (PTSD). Current treatments for PTSD are of moderate efficacy and preventing the dysregulations already during exposure to threatening events may attenuate the development of PTSD-symptomatology. In a preregistered double-blind, between-subject, placebo-controlled pharmaco-fMRI design, the present proof-of-concept study examined the potential of a single dose of angiotensin II type 1 receptor (AT1R) antagonist losartan (LT) to attenuate the mnemonic advantage of threatening stimuli and the underlying neural mechanism via combining an emotional subsequent memory paradigm with LT (n=29) or placebo treatment (n=30) and a surprise memory test after 24h washout. LT generally improved memory performance and abolished emotional memory enhancement for negative yet not positive material while emotional experience during encoding remained intact. LT further suppressed hippocampus activity during encoding of subsequently remembered negative stimuli. On the network level LT reduced coupling between hippocampus and basolateral amygdala during successful memory formation of negative stimuli. Our findings suggest that LT may have the potential to attenuate memory formation for negative yet not positive information by decreasing hippocampus activity and its functional coupling strength with amygdala. These findings suggest a promising potential of LT to prevent preferential encoding and remembering of negative events, a mechanism that could prevent the emotion-memory dysregulations underlying the development of PTSD-symptomatology.
Scoring Protein Sequence Alignments Using Deep Learning
Authors: Shrestha Bikash , Adhikari Badri
Published: August 2021

Background

A high-quality sequence alignment (SA) is the most important input feature for accurate protein structure prediction. For a protein sequence, there are many methods to generate a SA. However, when given a choice of more than one SA for a protein sequence, there are no methods to predict which SA may lead to more accurate models without actually building the models. In this work, we describe a method to predict the quality of a protein’s SA.

Methods

We created our own dataset by generating a variety of SAs for a set of 1,351 representative proteins and investigated various deep learning architectures to predict the local distance difference test (lDDT) scores of distance maps predicted with SAs as the input. These lDDT scores serve as indicators of the quality of the SAs.

Results

Using two independent test datasets consisting of CASP13 and CASP14 targets, we show that our method is effective for scoring and ranking SAs when a pool of SAs is available for a protein sequence. With an example, we further discuss that SA selection using our method can lead to improved structure prediction.
Nanopore ion sources deliver single amino acid and peptide ions directly into high vacuum
Authors: Drachman Nicholas , LePoitevin Mathilde , Szapary Hannah , Wiener Benjamin , Maulbetsch William , Stein Derek
Published: August 2021

Abstract

We report a nanopore ion source for mass spectrometry that delivers ions directly into high vacuum from aqueous solutions. The ion source comprises a pulled quartz pipette with a sub-100 nm opening. Ions escape an electrified meniscus by ion evaporation and travel along collisionless trajectories to the ion detector. We measure mass spectra of 16 different amino acid ions, post-translationally modified variants of glutathione, and the peptide angiotensin II, showing that these analytes can be emitted as desolvated ions. The emitted current is composed of ions rather than charged droplets, and more than 90% of the current can be recovered in a distant collector. By circumventing the sample loss mechanisms inherent to conventional electrospray ionization (ESI), where charged droplets are sprayed into a background gas that scatters ions and degrades their transmission, the nanopore ion source could enable more sensitive proteomic analyses.
Dynamics of transcription elongation are finely tuned by dozens of regulatory factors
Authors: Couvillion Mary , Harlen Kevin M. , Lachance Kate C. , Trotta Kristine L. , Smith Erin , Brion Christian , Smalec Brendan M. , Stirling Churchman L.
Published: August 2021

Understanding the complex network and dynamics that regulate transcription elongation requires the quantitative analysis of RNA polymerase II (Pol II) activity in a wide variety of regulatory environments. We performed native elongating transcript sequencing (NET-seq) in 41 strains ofS. cerevisiaelacking known elongation regulators, including RNA processing factors, transcription elongation factors, chromatin modifiers, and remodelers. We found that the opposing effects of these factors balance transcription elongation dynamics. Different sets of factors tightly regulate Pol II progression across gene bodies so that Pol II density peaks at key points of RNA processing. These regulators control where Pol II pauses with each obscuring large numbers of potential pause sites that are primarily determined by DNA sequence and shape. Genes that are sensitive to disruptions in transcription elongation tend to couple changes in Pol II pausing and antisense transcription to transcription output. Our findings collectively show that the regulation of transcription elongation by a diverse array of factors affects gene expression levels and co-transcriptional processing by precisely balancing Pol II activity.
Deciphering Multi-way Interactions in the Human Genome
Authors: Dotson Gabrielle A. , Lindsly Stephen , Cicalo Anthony , Chen Can , Dilworth Sam , Ryan Charles , Jeyarajan Sivakumar , Meixner Walter , Beckloff Nicholas , Surana Amit , Wicha Max , Muir Lindsey A. , Rajapakse Indika
Published: August 2021

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types.
Soldier neural architecture is temporarily modality-specialized but poorly predicted by repertoire size in the stingless bee Tetragonisca angustula
Authors: Baudier Kaitlin M. , Bennett Meghan M. , Barrett Meghan , Cossio Frank J. , Wu Robert D. , O’Donnell Sean , Pavlic Theodore P. , Fewell Jennifer H.
Published: August 2021

Individual heterogeneity within societies provides opportunities to test hypotheses about adaptive neural investment in the context of group cooperation. Here we explore neural investment in defense specialist soldiers of the eusocial stingless bee (Tetragonisca angustula) which are age sub-specialized on distinct defense tasks, and have an overall higher lifetime task repertoire than other sterile workers within the colony. Consistent with predicted behavioral demands, soldiers had higher relative visual (optic lobe) investment than non-soldiers but only during the period when they were performing the most visually demanding defense task (hovering guarding). As soldiers aged into the less visually demanding task of standing guarding this difference disappeared. Neural investment was otherwise similar across all colony members. Despite having larger task repertoires, soldiers had similar absolute brain size and smaller relative brain size compared to other workers, meaning that lifetime task repertoire size was a poor predictor of brain size. Together, our results are consistent with the specialized but flexible defense strategies of this species, broadening our understanding of how neurobiology mediates age and morphological task specialization in highly cooperative societies.
Characteristic core voxels in normal individuals revealed by hyperbolic disc embedding and k-core percolation on resting state fMRI
Authors: Whi Wonseok , Huh Youngmin , Ha Seunggyun , Lee Hyekyoung , Kang Hyejin , Lee Dong Soo
Published: August 2021

Hyperbolic disc embedding and k-core percolation reveal the core structure of the functional connectivity on resting-state fMRI (rsfMRI). Inter-voxel relations were visualized on embedded hyperbolic discs, and their core composition was traced using k-core percolation. Using 180 normal adults’ rsfMRI data from the Human Connectome Project database, scale- free intervoxel connectivity represented by IC-voxels composition, while visualized on hyperbolic discs using model, showed the expected change of the largest component decreasing its size on k-core percolation eventually yielding the core structures of individuals. This kmax-core voxels-ICs composition revealed such stereotypes of individuals as visual network dominant, default mode network dominant, and distributed patterns. Characteristic core structures of resting-state brain connectivity of normal subjects disclosed the distributed or asymmetric contribution of voxels to the kmax-core, which suggests the hierarchical dominance of certain IC subnetworks characteristic to subgroups of individuals at rest.
Insights into the nutritional properties and microbiome diversity in sweet and sour yogurt manufactured in Bangladesh
Authors: Islam S. M. Rafiqul , Tanzina Afsana Yeasmin , Foysal Md Javed , Hoque M. Nazmul , Siddiki AMAM Zonaed , Tay Alfred , Hossain S. M. Jakir , Bakar Muhammad Abu , Mostafa Mohammad , Rumi Meheadi Hasan , Mannan Adnan
Published: August 2021

Yogurt quality mainly depends on nutritional properties, microbial diversity and purity of starter culture. This study aimed to assess the nutritional composition and microbiome diversity in yogurt. Microbial diversity was analyzed by 16S and 18S rRNA based high-throughput sequencing. Significantly (P<0.05) higher pH, fat, moisture, total solid and solid-non-fat contents (%) were observed in sweet yogurt whereas sour varieties had significantly higher ash and minerals. Metagenomic investigation showed that 44.86% and 55.14% reads were assigned to bacterial and fungal taxa, respectively, with significantly higher taxonomic richness in sour yogurt. A significant difference in bacterial (Ppermanova=0.001) and fungal (Ppermanova=0.013) diversity between sweet and sour yogurt was recorded. We detected 76 bacterial and 70 fungal genera across these samples which were mostly represented by Firmicutes (>92%) and Ascomycota (98%) phyla, respectively. Among the detected genera, 36.84% bacterial and 22.86% fungal genera were found in both yogurt types. Our results suggest that Streptococcus (50.82%), Lactobacillus (39.92%), Enterobacter (4.85%), Lactococcus (2.84%) and Aeromonas (0.65%) are the most abundant bacterial genera, while Kluyveromyces (65.75%), Trichosporon (8.21%), Clavispora (7.19%), Candida (6.71%), Iodophanus (2.22%), Apiotrichum (1.94%), and Issatchenkia (1.35%) are the most abundant fungal genera in yogurt metagenomes. This is the first study on nutritional properties and microbiome diversity of Bangladeshi yogurt that would be a benchmark for safe production of quality yogurt by commercial manufacturers.
Optimal dynamic incentive scheduling for Hawk-Dove evolutionary games
Authors: Stuckey K. , Dua R. , Ma Y. , Parker J. , Newton P.K.
Published: August 2021

The Hawk-Dove mathematical game offers a paradigm of the trade-offs associated with aggressive and passive behaviors. When two (or more) populations of players (animals, insect populations, countries in military conflict, economic competitors, microbial communities, populations of co-evolving tumor cells, or reinforcement learners adopting different strategies) compete, their success or failure can be measured by their frequency in the population (successful behavior is reinforced, unsuccessful behavior is not), and the system is governed by the replicator dynamical system. We develop a time-dependent optimal-adaptive control theory for this nonlinear dynamical system in which the payoffs of the Hawk-Dove payoff matrix are dynamically altered (dynamic incentives) to produce (bang-bang) control schedules that (i) maximize the aggressive population at the end of timeT, and (ii) minimize the aggressive population at the end of timeT. These two distinct time-dependent strategies produce upper and lower bounds on the outcomes from all strategies since they represent two extremizers of the cost function using the Pontryagin maximum (minimum) principle. We extend the results forward to timesnT(n= 1, …, 5) in an adaptive way that uses the optimal value at the end of timenTto produce the new schedule for time (n+ 1)T. Two special schedules and initial conditions are identified that produce absolute maximizers and minimizers over an arbitrary number of cycles for 0 ≤T≤ 3. ForT> 3, our optimum schedules can drive either population to extinction or fixation. The method described can be used to produce optimal dynamic incentive schedules for many different applications in which the 2 × 2 replicator dynamics is used as a governing model.
ColabFold - Making protein folding accessible to all
Authors: Mirdita Milot , Schütze Konstantin , Moriwaki Yoshitaka , Heo Lim , Ovchinnikov Sergey , Steinegger Martin
Published: August 2021

ColabFold offers accelerated protein structure and complex predictions by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold’s 40 - 60× faster search and optimized model use allows predicting close to a thousand structures per day on a server with one GPU. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding. ColabFold is open-source software available at github.com/sokrypton/ColabFold. Its novel environmental databases are available at colabfold.mmseqs.com

Contact

milot.mirdita@mpibpc.mpg.de, so@fas.harvard.edu, martin.steinegger@snu.ac.kr
Diversity and evolution of amphibian pupil shapes
Authors: Thomas Kate N. , Rich Caitlyn , Quock Rachel , Streicher Jeffrey W. , Gower David J. , Schott Ryan K. , Fujita Matthew K. , Bell Rayna C.
Published: August 2021

Pupil constriction has important functional consequences for animal vision, yet the evolutionary mechanisms underlying diverse pupil sizes and shapes, often among animals that occupy optically similar environments, are poorly understood. We aimed to quantify the diversity and evolution of pupil shapes among amphibians and test for potential correlations to ecology based on functional hypotheses. Using photographs, we surveyed pupil shape and the orientation of the constricted pupil across adults of 1293 amphibian species, 72 families, and 3 orders, and additionally for larval life stages for all families of frogs and salamanders with a biphasic ontogeny. Pupil shape is exceptionally diverse in amphibians with evolutionary transitions throughout the amphibian tree of life. For amphibians with a biphasic life history, we found that pupils change in many species that occupy distinct habitats before and after metamorphosis. Finally, we found that non-elongated (round or diamond) constricted pupils were correlated with species inhabiting consistently dim light environments (burrowing and aquatic species) and that elongated pupils (vertical and horizontal) were more common in species with larger absolute eye sizes. We propose that amphibians provide a valuable group within which to explore the anatomical, physiological, optical, and ecological mechanisms underlying the evolution of pupil shape.
On-chip light diffraction imaging of nano structures in the guanine platelet
Authors: Iwasaka Masakazu
Published: August 2021

Light projection over short distances can minimize the size of photonic devices, e.g., head-mounted displays and lens-free microscopes. Small lenses or light condensers without typical lenses are essential for light control in micron-scale spaces. In this work, micro-platelets floating in water are used for light projection near the image sensor. These platelets, which are made from guanine, have nanohole gratings and demonstrate light diffraction toward specific directions. By setting a thin water layer on the image sensor’s cover glass, each platelet in water forms column-or bar-code-shaped images on the screen. The projected image shapes and colors are inferred to contain information about nano-structures present in the guanine platelet. The proposed down-sized imaging technique can realize extremely compact and portable imagers for nanoscale object detection.