bluuebunny/crossref_metadata_2025_split huggingface dataset:
Liquid Transmission Electron Microscopy for Probing Collagen Biomineralization
Authors: DiCecco Liza-Anastasia , Gao Ruixin , Gray Jennifer L. , Kelly Deborah F. , Sone Eli D. , Grandfield Kathryn 
Published: June 2023

ABSTRACTCollagen biomineralization is foundational to hard tissue assembly. While studied extensively, collagen mineralization processes are not fully understood as the majority of theories are derived from electron microscopy (EM) in static, dehydrated, or frozen conditions, unlike the liquid phase environment where mineralization occurs dynamically. Herein, novel liquid transmission EM (TEM) strategies are presented, where collagen mineralization was explored in liquid conditions for the first time. Custom thin-film enclosures were employed to visualize the mineralization of reconstituted collagen fibrils in a calcium-phosphate and polyaspartic acid solution to promote intrafibrillar mineralization. TEM highlighted that at early time points, precursor mineral particles attached to collagen and progressed to crystalline mineral platelets aligned with fibrils at later time points. This aligns with observations from other techniques and validates this liquid TEM approach. This work provides a new liquid imaging approach for exploring collagen biomineralization, advancing toward understanding disease pathogenesis and remineralization strategies for hard tissues.
WAS IT A MATch I SAW? Approximate palindromes lead to overstated false match rates in benchmarks using reversed sequences
Authors: Glidden-Handgis George , Wheeler Travis J. 
Published: June 2023

BackgroundSoftware for labeling biological sequences typically produces a theory-based statistic for each match (the E-value) that indicates the likelihood of seeing that match’s score by chance. E-values accurately predict false match rate for comparisons of random (shuffled) sequences, and thus provide a reasoned mechanism for setting score thresholds that enable high sensitivity with low expected false match rate. This threshold-setting strategy is challenged by real biological sequences, which contain regions of local repetition and low sequence complexity that cause excess matches between non-homologous sequences. Knowing this, tool developers often develop benchmarks that use realistic-seeming decoy sequences to explore empirical tradeoffs between sensitivity and false match rate. A recent trend has been to employ reversed biological sequences as realistic decoys, because these preserve the distribution of letters and the existence of local repeats, while disrupting the original sequence’s functional properties. However, we and others have observed that sequences appear to produce high scoring alignments to their reversals with surprising frequency, leading to overstatement of false match risk that may negatively effect downstream analysis.ResultsWe demonstrate that an alignment between a sequence S and its (possibly mutated) reversal tends to produce higher scores than alignment between truly unrelated sequences, even when S is a shuffled string with no notable repetitive or low-complexity regions. This phenomenon is due to the unintuitive fact that (even randomly shuffled) sequences contain palin-dromes that are on average longer than the longest common substrings shared between permuted variants of the same sequence. Though the expected palindrome length is only slightly larger than the expected longest common substring, the distribution of alignment scores involving reversed sequences is strongly right-shifted, leading to greatly increased frequency of high-scoring alignments to reversed sequences.ImpactOverestimates of false match risk can motivate unnecessarily high score thresholds, leading to potentially reduced true match sensitivity. Also, when tool sensitivity is only reported up to the score of the first matched decoy sequence, a large decoy set consisting of reversed sequences can obscure sensitivity differences between tools. As a result of these observations, we advise that reversed biological sequences be used as decoys only when care is taken to remove positive matches in the original (un-reversed) sequences, or when overstatement of false labeling is not a concern. Though the primary focus of the analysis is on sequence annotation, we also demonstrate that the prevalence of internal palindromes may lead to an overstatement of the rate of false labels in protein identification with mass spectrometry.
Particle size distribution shift and diurnal concentration changes of environmental DNA caused by fish spawning behaviour
Authors: Tsuji Satsuki , Shibata Naoki 
Published: June 2023

AbstractSpawning is one of the most significant aspects of fish life history, so understanding spawning is critical for the conservation and management of species. Recently, an efficient and non-invasive spawning detection method for spawning behaviour has been proposed, utilising the increased environmental DNA (eDNA) concentration and nuclear/mitochondrial eDNA ratio associated with fish spawning. However, little is known about the characteristics and dynamics of sperm-derived eDNA, which is key to detection. This study focused on changes in eDNA particle size distribution (PSD) and concentrations pre-, post-, and during spawning of Ayu,Plecoglossus altivelis. Firstly, PSD changes between pre- and post-spawning were investigated by comparing concentrations and proportions of eDNA obtained from filters with different pore sizes. Secondly, the diurnal changes in eDNA concentration were monitored at the peak of the spawning season by collecting river water every one or three hours. Results showed that eDNA related to sperm-head size increased at post-spawning, and eDNA concentrations had significant diurnal changes with a peak during the spawning time window. These findings suggest that semi-selective recovery of sperm-derived eDNA based on particle size and/or sampling during the spawning time window with increased concentrations can improve the detection sensitivity of eDNA-based spawning surveys. This study provides essential basic information for advancing eDNA-based spawning surveys and contributes to their further development.
Determinants of Sense of Coherence among older adults attending a Geriatric Centre in Nigeria A study Protocol
Authors: Adebusoye Lawrence Adekunle , Oyinlola Oluwagbemiga , Cadmus Eniola Olubukola 
Published: June 2023

AbstractBackgroundOld age is a stage of life in which people face changes in their physical and psycho-emotional aspects. Thus, having an adequate sense of coherence (SOC) is required to face these situations successfully. The SOC (comprehensibility, manageability, and meaningfulness of life) is defined as a global orientation expressing a person’s pervasive and enduring feeling of confidence modified by stimuli derived from one’s internal and external environments while living, the resources available to meet the demands posed by these stimuli, and the fact that these demands are challenges worthy of investment and engagement. Empirical evidence on the SOC available to older persons is lacking in countries like Nigeria. This study aims to investigate the Sense of Coherence (SOC) available to older patients attending the Chief Tony Anenih Geriatric Centre (CTAGC), University College Hospital (UCH), Ibadan, Nigeria and its association with socio-demographic, family relationships, spirituality, cognition, depression, functional disability, quality of life, and level of frailty among them.MethodsThis will be a cross-sectional descriptive study of 385 older persons (≥60 years) attending the CTAGC, UCH, Ibadan, Nigeria. A semi-structured, interviewer-administered questionnaire will obtain information on the respondents’ demographic, social, economic, family relationships, health profiles, and healthcare utilization patterns. The Sense of Coherence (SOC) status will be measured with Antonovsky’s SOC scale (SOC-13). The information on the respondent’s spirituality, cognition, depression, functional disability, quality of life, family relationship, and level of frailty will be assessed using the spirituality index of well-being, six-item screener, Geriatric depression scale, Barthel’s independence Activities of Daily Living, World Health Organization-Quality of Life brief scale, Sense of Coherence-Family Relations Scale (SCO-FRS), and self-assessment of frailty syndrome, respectively.Data analysisData will be entered and analyzed using the Statistical Package for Social Sciences (SPSS) Version 27.0. Tables and charts will be summarised using frequency, proportion, and means. Inferential statistics will test for associations between variables using the Student’s t-test and Analysis of Variance (ANOVA) as appropriate. Linear regression analysis will explore the relationship between significant variables in bivariate analysis with SOC. The level of significance will be set at 5%.ImplicationThis investigation holds several promises for enhancing psychological well-being, improving physical health outcomes, informing holistic geriatric care, strengthening social support networks, and guiding policy and program development. By prioritizing research and intervention in these areas, we can foster a society that values and supports the well-being of older adults, ensuring they enjoy a fulfilling and dignified life during their golden years.
Multicenter analysis of COVID-19 hospitalizations and stacking machine learning algorithms for prediction of high-risk patients
Authors: Shaw Reid , Bassily David , Patel Love , O’Connor Timothy , Rafidi Robert , Formanek Perry 
Published: June 2023

AbstractObjectiveTo create and validate an ensemble of machine learning algorithms to accurately predict ICU admission or mortality upon initial presentation to the emergency department.MethodsThis is a retrospective cohort study of a multicenter hospital system in the United States. The electronic health record was queried from March 2020 to December 2021 for patients who presented to the emergency department who were subsequently COVID-positive. Associated patient demographics, vitals, and laboratory vitals were obtained. High-risk individuals were defined as those who required ICU admission or died; low-risk individuals did not meet those criteria. The dataset was split into a 3:1 training to testing dataset. A machine learning ensemble stack was built to predict ICU admission and mortality.ResultsOf the 3,142 hospital admissions with a COVID positive test, there were 1,128 (36%) individuals labeled as high-risk, and 2,014 (64%) as low-risk. We obtained 147 unique variables. CRP, LDH, procalcitonin, glucose, anion gap, creatinine, age, oxygen saturation, oxygen device, and obtainment of an ABG were chosen. Six machine learning models were then trained over model-specific hyperparameters, and then assessed on the testing dataset, generating an area under the receiver operator curve of 0.751, with a specificity of 95% in predicting high-risk individuals based on an initial emergency department assessment.ConclusionA novel machine learning model was generated to predict ICU admission and patient mortality from a multicenter hospital system and validated on unseen data.
GATA1-defective immune-megakaryocytes as possible drivers of idiopathic pulmonary fibrosis
Authors: Gobbo Francesca , Zingariello Maria , Verachi Paola , Falchi Mario , Arciprete Francesca , Martelli Fabrizio , Peli Angelo , Mazzarini Maria , Vierstra Jeff , Mead-Harvey Carolyn , Dueck Amylou C. , Sarli Giuseppe , Nava Stefano , Sgalla Giacomo , Richeldi Luca , Migliaccio Anna Rita 
Published: June 2023

SummaryIdiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disorder with limited therapeutic options. Insufficient understanding of driver mutations and poor fidelity of currently available animal models has limited the development of effective therapies. Since GATA1 deficient megakaryocytes sustain myelofibrosis, we hypothesized that they may also induce fibrosis in lungs. We discovered that lungs from IPF patients andGata1lowmice contain numerous GATA1negative immune-poised megakaryocytes that, in mice, have defective RNA-seq profiling and increased TGF-β1, CXCL1 and P-selectin content. With age,Gata1lowmice develop fibrosis in lungs. Development of lung fibrosis in this model is prevented byP-selectindeletion and rescued by P-selectin, TGF-β1 or CXCL1 inhibition. Mechanistically, P-selectin inhibition decreases TGF-β1 and CXCL1 content and increases GATA1positive megakaryocytes while TGF-β1 or CXCL1 inhibition decreased CXCL1 only. In conclusion,Gata1lowmice are a novel genetic-driven model for IPF and provide a link between abnormal immune-megakaryocytes and lung fibrosis.
Sustained polyphasic sleep restriction abolishes human growth hormone release
Authors: Rosenblum Yevgenia , Weber Frederik D. , Rak Michael , Zavecz Zsófia , Kunath Nicolas , Breitenstein Barbara , Rasch Björn , Zeising Marcel , Uhr Manfred , Steiger Axel , Dresler Martin 
Published: June 2023

AbstractVoluntary sleep restriction is a common phenomenon in industrialized societies aiming to increase time spent awake and thus productivity. We explored how restricting sleep to a radically polyphasic schedule affects neural, cognitive, and endocrine characteristics. Ten young healthy participants were restricted to one 30-min nap opportunity at the end of every 4 hours (i.e., 6 sleep episodes per 24 hours) without any extended core sleep window, which resulted in a cumulative sleep amount of just 2 hours per day (i.e., ∼20 min per bout). All but one participant terminated this schedule during the first three weeks. The remaining participant (a 25-year-old male) succeeded to adhere to a polyphasic schedule for 5 weeks with no apparent impairments in cognitive and psychiatric measures except for psychomotor vigilance. While in-blood cortisol or melatonin release pattern and amounts were unaltered by the polyphasic as compared to monophasic sleep, growth hormone seemed almost entirely abolished (>95% decrease), with the residual release showing a considerably changed polyphasic secretional pattern. While coarse sleep structure appeared intact during polyphasic sleep, REM sleep showed decreased oscillatory and increased aperiodic EEG activity compared to monophasic sleep. Considering the decreased vigilance, abolished growth hormone release, and neurophysiological changes observed, it is doubtful that radically polyphasic sleep schedules can subserve the different functions of sleep to a sufficient degree.
Inactivation of face selective neurons alters eye movements when free viewing faces
Authors: Azadi Reza , Lopez Emily , Taubert Jessica , Patterson Amanda , Afraz Arash 
Published: June 2023

AbstractDuring free viewing, faces attract gaze and induce specific fixation patterns corresponding to the facial features. This suggests that neurons encoding the facial features are in the causal chain that steers the eyes. However, there is no physiological evidence to support a mechanistic link between face encoding neurons in high-level visual areas and the oculomotor system. In this study, we targeted the middle face patches of inferior temporal (IT) cortex in two macaque monkeys using an fMRI localizer. We then utilized muscimol microinjection to unilaterally suppress IT neural activity inside and outside the face patches and recorded eye movements while the animals free viewing natural scenes. Inactivation of the face selective neurons altered the pattern of eye movements on faces: the monkeys found faces in the scene but neglected the eye contralateral to the inactivation hemisphere. These findings reveal the causal contribution of the high-level visual cortex in eye movements.SignificanceIt has been shown, for more than half a century, that eye movements follow distinctive patterns when free viewing faces. This suggests causal involvement of the face-encoding visual neurons in the eye movements. However, the literature is scant of evidence for this possibility and has focused mostly on the link between low-level image saliency and eye movements. Here, for the first time, we bring causal evidence showing how face-selective neurons in inferior temporal cortex inform and steer eye movements when free viewing faces.
Polyploidy enhances desiccation tolerance in the grassMicrochloa caffra
Authors: Marks Rose A. , Delgado Paula , Makonya Givemore Munashe , Cooper Keren , VanBuren Robert , Farrant Jill M. 
Published: June 2023

ABSTRACTDesiccation tolerance evolved recurrently across diverse plant lineages to enable survival in water limited conditions. Many resurrection plants are polyploid and several groups have hypothesized that polyploidy enabled the evolution of desiccation tolerance. However, due to the vast evolutionary divergence between resurrection plant lineages, the rarity of desiccation tolerance, and the prevalence of polyploidy in plants, this hypothesis has been difficult to test. Here, we surveyed variation in morphological, reproductive, and desiccation tolerance traits across natural populations of a single species that has differing ploidies and tested for links between polyploidy and resilience. We sampled multiple populations of the resurrection grassMicrochloa caffraacross an environmental gradient ranging from mesic to xeric in South Africa. We describe two distinct ecotypes ofM. caffrathat occupy different ends of the environmental gradient and exhibit consistent differences in ploidy, morphological, reproductive, and desiccation tolerance traits in both field and common growth conditions. Interestingly, plants with more polyploid genomes were consistently more desiccation tolerant, less reproductive, and larger than plants with smaller genomes and lower ploidy. These data suggest that polyploidy enhances desiccation tolerance and that stronger selective pressures in increasingly xeric sites may play a role in maintaining and increasing desiccation tolerance.
QuantUMS: uncertainty minimisation enables confident quantification in proteomics
Authors: Kistner Franziska , Grossmann Justus L. , Sinn Ludwig R. , Demichev Vadim 
Published: June 2023

AbstractMass spectrometry-based proteomics has been rapidly gaining traction as a powerful analytical method both in basic research and translation. While the problem of error control in peptide and protein identification has been addressed extensively, the quality of the resulting quantities remains challenging to evaluate. Here we introduce QuantUMS (Quantification using anUncertaintyMinimisingSolution), a machine learning-based method which minimises errors and eliminates bias in peptide and protein quantification by integrating multiple sources of quantitative information. In combination with data-independent acquisition proteomics, QuantUMS boosts accuracy and precision of quantities, as well as reports an uncertainty metric, enabling effective filtering of data for downstream analysis. The algorithm has linear complexity with respect to the number of mass spectrometry acquisitions in the experiment and is thus scalable to infinitely large proteomic experiments. For an easy implementation in a proteomics laboratory, we integrate QuantUMS in our automated DIA-NN software suite.
The landscape of microRNA interactions annotation: analysis of three rare disorders as case study
Authors: Simona Panni , Panneerselvam Kalpana , Porras Pablo , Duesbury Margaret , Perfetto Livia , Licata Luana , Hermjakob Henning , Orchard Sandra 
Published: June 2023

AbstractIn recent years, a huge amount of data on ncRNA interactions has been described in scientific papers and databases. Although considerable effort has been made to annotate the available knowledge in public repositories, there are still significant discrepancies in how different resources capture and interpret data on ncRNAs functional and physical associations.In the present paper, we have focused on microRNAs which regulate genes associated with rare diseases, as a case study to investigate data availability.The list of protein-coding genes with a known role in specific rare diseases was retrieved from the Genome England PanelApp, and associated microRNA-mRNA interactions were annotated in the IntAct database, and compared with other datasets. The annotation follows recognised standard criteria approved by the IMEX consortium. RNAcentral identifiers were used for unambiguous, stable identification of ncRNAs. The information about the interaction was enhanced by a detailed description of the cell types and experimental conditions, providing a computer-interpretable summary of the published data, integrated with the huge amount of protein interactions already gathered in the database. Furthermore, for each interaction, the binding sites of the microRNA are precisely mapped on a well-defined mRNA transcript of the target gene. This information is crucial to conceive and design optimal microRNA mimics or inhibitors, to interfere in vivo with a deregulated process. As these approaches become more feasible, high-quality, reliable networks of microRNA interactions are needed to help, for instance, in the selection of the best target to be inhibited and to predict potential secondary off-target effects.
Cathepsin B abundance, activity and microglial localisation in Alzheimer’s disease – Down syndrome and early onset Alzheimer’s disease; the role of elevated cystatin B
Authors: Wu Yixing , Mumford Paige , Noy Suzanna , Cleverley Karen , Mrzyglod Alicja , Luo Dinghao , van Dalen Floris , Verdoes Martijn , Fisher Elizabeth M.C. , Wiseman Frances K. 
Published: June 2023

AbstractCathepsin B is a cysteine protease that is implicated in multiple aspects of Alzheimer’s disease pathogenesis. The endogenous inhibitor of this enzyme, cystatin B (CSTB)is encoded on chromosome 21. Thus, individuals who have Down syndrome, a genetic condition caused by having an additional copy of chromosome 21, have an extra copy of an endogenous inhibitor of the enzyme. Individuals who have Down syndrome are also at significantly increased risk of developing early-onset Alzheimer’s disease (EOAD). The impact of the additional copy of cystatin B (CSTB)on Alzheimer’s disease development in people who have Down syndrome is not well understood. Here we compared the biology of cathepsin B and cystatin B (CSTB) in individuals who had Down syndrome and Alzheimer’s disease, with disomic individuals who had Alzheimer’s disease or were ageing healthily. We find that the activity of cathepsin B enzyme is decreased in the brain of people who had Down syndrome and Alzheimer’s disease compared with disomic individuals who had Alzheimer’s disease. This change occurs independently of an alteration in the abundance of the mature enzyme or the number of cathepsin B+cells. We find that the abundance of cystatin B (CSTB) is significantly increased in the brains of individuals who have Down syndrome and Alzheimer’s disease compared to disomic individuals both with and without Alzheimer’s disease and we go on to investigate how this impacts enzyme activity in mouse and human cellular preclinical models of Down syndrome.