bluuebunny/crossref_metadata_2025_split huggingface dataset:
Population distributions of single-cell adhesion parameters during the cell cycle from high-throughput robotic fluidic force microscopy
Authors: Nagy Ágoston G. , Kanyó Nicolett , Vörös Alexandra , Székács Inna , Bonyár Attila , Horvath Robert 
Published: May 2022

AbstractSingle-cell adhesion plays an essential role in biological and biomedical sciences, but its precise measurement for a large number of cells is still a challenging task. At present, typical force measuring techniques usually offer low throughput, a few cells per day, and therefore are unable to uncover phenomena emerging at the population level. In this work, robotic fluidic force microscopy (FluidFM) was utilized to measure the adhesion parameters of cells in a high-throughput manner to study their population distributions in-depth. The investigated cell type was the genetically engineered HeLa Fucci construct with cell cycle-dependent expression of fluorescent proteins. This feature, combined with the high-throughput measurement made it possible for the first time to characterize the single-cell adhesion distributions at various stages of the cell cycle. It was found that parameters such as single-cell adhesion force and energy follow a lognormal population distribution. Therefore, conclusions based on adhesion data of a low number of cells or treating the population as normally distributed can be misleading. Moreover, we found that the cell area was significantly the smallest, and the area normalized maximal adhesion force was significantly the largest for the colorless cells (the mitotic (M) and early G1 phases). Notably, the parameter characterizing the elongation of the cells until the maximum level of force between the cell and its substratum was also dependent on the cell cycle, which quantity was the smallest for the colorless cells. A novel parameter, named the spring coefficient of the cell, was introduced as the fraction of maximal adhesion force and maximal cell elongation during the mechanical detachment, which was found to be significantly the largest for the colorless cells. Cells in the M phase adhere in atypical way, with so-called reticular adhesions, which are different from canonical focal adhesions. We first revealed that reticular adhesion can exert a higher force per unit area than canonical focal adhesions, and cells in this phase are significantly stiffer. The possible biological consequences of these findings were also discussed, together with the practical relevance of the observed population-level adhesion phenomena.
Network topological determinants of pathogen spread
Authors: Pérez-Ortiz María , Manescu Petru , Caccioli Fabio , Fernández-Reyes Delmiro , Nachev Parashkev , Shawe-Taylor John 
Published: May 2022

AbstractHow do we best constrain social interactions to decrease transmission of communicable diseases? Indiscriminate suppression is unsustainable long term and presupposes that all interactions carry equal importance. Instead, transmission within a social network has been shown to be determined by its topology. In this paper, we deploy simulations to understand and quantify the impact on disease transmission of a set of topological network features, building a dataset of 9000 interaction graphs using generators of different types of synthetic social networks. Independently of the topology of the network, we maintain constant the total volume of social interactions in our simulations, to show how even with the same social contact some network structures are more or less resilient to the spread. We find a suitable intervention to be specific suppression of unfamiliar and casual interactions that contribute to the network’s global efficiency. This is, pathogen spread is significantly reduced by limiting specific kinds of contact rather than their global number. Our numerical studies might inspire further investigation in connection to public health, as an integrative framework to craft and evaluate social interventions in communicable diseases with different social graphs or as a highlight of network metrics that should be captured in social studies.
Characterisation of drug-resistant Mycobacterium tuberculosis mutations and transmission in Pakistan
Authors: Napier Gary , Khan Anwar Sheed , Jabbar Abdul , Khan Muhammad Tahir , Ali Sajid , Qasim Muhammad , Mohammad Noor , Hasan Rumina , Hasan Zahra , Campino Susana , Ahmad Sajjad , Khattak Baharullah , Waddell Simon J. , Khan Taj Ali , Phelan Jody E. , Clark Taane G. 
Published: May 2022

AbstractTuberculosis, caused by Mycobacterium tuberculosis, is a high-burden disease in Pakistan, with multi-drug (MDR) and extensive-drug (XDR) resistance, complicating infection control. Whole genome sequencing (WGS) of M. tuberculosis is being used to infer lineages (strain-types), drug resistance mutations, and transmission patterns—all informing infection control and clinical decision making. Here we analyse WGS data on 535 M. tuberculosis isolates sourced across Pakistan between years 2003 and 2020, to understand the circulating strain-types and mutations related to 12 anti-TB drugs, as well as identify transmission clusters. Most isolates belonged to lineage 3 (n = 397; 74.2%) strain-types, and were MDR (n = 328; 61.3%) and (pre-)XDR (n = 113; 21.1%). By inferring close genomic relatedness between isolates (< 10-SNPs difference), there was evidence of M. tuberculosis transmission, with 55 clusters formed consisting of a total of 169 isolates. Three clusters consist of M. tuberculosis that are similar to isolates found outside of Pakistan. A genome-wide association analysis comparing ‘transmitted’ and ‘non-transmitted’ isolate groups, revealed the nusG gene as most significantly associated with a potential transmissible phenotype (P = 5.8 × 10–10). Overall, our study provides important insights into M. tuberculosis genetic diversity and transmission in Pakistan, including providing information on circulating drug resistance mutations for monitoring activities and clinical decision making.
LncMIR181A1HG is a novel chromatin-bound epigenetic suppressor of early stage osteogenic lineage commitment
Authors: Tye Coralee E. , Ghule Prachi N. , Gordon Jonathan A. R. , Kabala Fleur S. , Page Natalie A. , Falcone Michelle M. , Tracy Kirsten M. , van Wijnen Andre J. , Stein Janet L. , Lian Jane B. , Stein Gary S. 
Published: May 2022

AbstractBone formation requires osteogenic differentiation of multipotent mesenchymal stromal cells (MSCs) and lineage progression of committed osteoblast precursors. Osteogenic phenotype commitment is epigenetically controlled by genomic (chromatin) and non-genomic (non-coding RNA) mechanisms. Control of osteogenesis by long non-coding RNAs remains a largely unexplored molecular frontier. Here, we performed comprehensive transcriptome analysis at early stages of osteogenic cell fate determination in human MSCs, focusing on expression of lncRNAs. We identified a chromatin-bound lncRNA (MIR181A1HG) that is highly expressed in self-renewing MSCs. MIR181A1HG is down-regulated when MSCs become osteogenic lineage committed and is retained during adipogenic differentiation, suggesting lineage-related molecular functions. Consistent with a key role in human MSC proliferation and survival, we demonstrate that knockdown of MIR181A1HG in the absence of osteogenic stimuli impedes cell cycle progression. Loss of MIR181A1HG enhances differentiation into osteo-chondroprogenitors that produce multiple extracellular matrix proteins. RNA-seq analysis shows that loss of chromatin-bound MIR181A1HG alters expression and BMP2 responsiveness of skeletal gene networks (e.g., SOX5 and DLX5). We propose that MIR181A1HG is a novel epigenetic regulator of early stages of mesenchymal lineage commitment towards osteo-chondroprogenitors. This discovery permits consideration of MIR181A1HG and its associated regulatory pathways as targets for promoting new bone formation in skeletal disorders.
Electron beam evaporation of superconductor-ferromagnet heterostructures
Authors: Bromley D. , Wright A. J. , Jones L. A. H. , Swallow J. E. N. , Beesley T. , Batty R. , Weatherup R. S. , Dhanak V. R. , O’Brien L. 
Published: May 2022

AbstractWe report on the electronic and magnetic properties of superconductor-ferromagnet heterostructures fabricated by electron beam evaporation on to unheated thermally oxidised Si substrates. Polycrystalline Nb thin films (5 to 50 nm thick) were shown to possess reliably high superconducting critical temperatures ($$T_{c}$$

T
c

), which correlate well with the residual resistivity ratio (RRR) of the film. These properties improved during ex-situ annealing, resulting in $${\Delta }T_{c}$$

Δ

T
c

and $${\Delta }$$
Δ
RRR increases of up 2.2 K ($$\sim$$
∼
40% of the pre-annealed $$T_{c}$$

T
c

) and 0.8 ($$\sim$$
∼
60% of the pre-annealed RRR) respectively. Nb/Pt/Co/Pt heterostructures showed substantial perpendicular anisotropy in the ultrathin limit (≤ 2.5 nm), even in the extreme limit of Pt(0.8 nm)/Co(1 nm)/Pt(0.6 nm). These results point to the use of electron beam evaporation as route to line-of-sight deposited, low-thickness, high quality Nb-based superspintronic multilayers.
On Methods for the Measurement of the Apelin Receptor Ligand Apelin
Authors: Janssens Peter , de Loor Henriette , Decuypere Jean-Paul , Vennekens Rudi , Llorens-Cortes Catherine , Mekahli Djalila , Bammens Bert 
Published: May 2022

AbstractApelin exists in many isoforms, both in the circulation and in specific tissues. Apelin peptides have a short half-life but preservation before measurement is scarcely studied. Reproducible mass spectrometry methods to specifically measure a broad range of apelinergic peptide isoforms are currently lacking. A sample protocol to conserve apelinergic peptides in the preanalytical phase and a high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) method to measure apelinergic isoforms was developed. Apelin was measured in plasma. For validation, human embryonic kidney (HEK) cells transfected with cDNA for preproapelin were used. Results were compared with a validated radioimmunoassay (RIA) method. Acidifying plasma to pH 2.5 improves post-sampling stability of apelin. HPLC–MS/MS was unable to detect apelin isoforms in plasma of healthy volunteers (n = 16) and chronic kidney disease patients (n = 4). RIA could detect apelin in concentrations between 71 and 263 fmol/l in 10 healthy volunteers. An optimized preanalytical protocol was developed. A sensitive and specific HPLC–MS/MS method failed to detect apelin in human plasma. Apelin-36 was detected in HEK cells transfected with cDNA for preproapelin. Currently, RIA with relatively selective antibodies is the best alternative for the measurement of apelin but novel sensitive and specific methods are needed.
Postural behavior recognition of captive nocturnal animals based on deep learning: a case study of Bengal slow loris
Authors: Lei Yujie , Dong Pengmei , Guan Yan , Xiang Ying , Xie Meng , Mu Jiong , Wang Yongzhao , Ni Qingyong 
Published: May 2022

AbstractThe precise identification of postural behavior plays a crucial role in evaluation of animal welfare and captive management. Deep learning technology has been widely used in automatic behavior recognition of wild and domestic fauna species. The Asian slow loris is a group of small, nocturnal primates with a distinctive locomotion mode, and a large number of individuals were confiscated into captive settings due to illegal trade, making the species an ideal as a model for postural behavior monitoring. Captive animals may suffer from being housed in an inappropriate environment and may display abnormal behavior patterns. Traditional data collection methods are time-consuming and laborious, impeding efforts to improve lorises’ captive welfare and to develop effective reintroduction strategies. This study established the first human-labeled postural behavior dataset of slow lorises and used deep learning technology to recognize postural behavior based on object detection and semantic segmentation. The precision of the classification based on YOLOv5 reached 95.1%. The Dilated Residual Networks (DRN) feature extraction network showed the best performance in semantic segmentation, and the classification accuracy reached 95.2%. The results imply that computer automatic identification of postural behavior may offer advantages in assessing animal activity and can be applied to other nocturnal taxa.
Diagnostic accuracy of keystroke dynamics as digital biomarkers for fine motor decline in neuropsychiatric disorders: a systematic review and meta-analysis
Authors: Alfalahi Hessa , Khandoker Ahsan H. , Chowdhury Nayeefa , Iakovakis Dimitrios , Dias Sofia B. , Chaudhuri K. Ray , Hadjileontiadis Leontios J. 
Published: May 2022

AbstractThe unmet timely diagnosis requirements, that take place years after substantial neural loss and neuroperturbations in neuropsychiatric disorders, affirm the dire need for biomarkers with proven efficacy. In Parkinson’s disease (PD), Mild Cognitive impairment (MCI), Alzheimers disease (AD) and psychiatric disorders, it is difficult to detect early symptoms given their mild nature. We hypothesize that employing fine motor patterns, derived from natural interactions with keyboards, also knwon as keystroke dynamics, could translate classic finger dexterity tests from clinics to populations in-the-wild for timely diagnosis, yet, further evidence is required to prove this efficiency. We have searched PubMED, Medline, IEEEXplore, EBSCO and Web of Science for eligible diagnostic accuracy studies employing keystroke dynamics as an index test for the detection of neuropsychiatric disorders as the main target condition. We evaluated the diagnostic performance of keystroke dynamics across 41 studies published between 2014 and March 2022, comprising 3791 PD patients, 254 MCI patients, and 374 psychiatric disease patients. Of these, 25 studies were included in univariate random-effect meta-analysis models for diagnostic performance assessment. Pooled sensitivity and specificity are 0.86 (95% Confidence Interval (CI) 0.82–0.90, I2 = 79.49%) and 0.83 (CI 0.79–0.87, I2 = 83.45%) for PD, 0.83 (95% CI 0.65–1.00, I2 = 79.10%) and 0.87 (95% CI 0.80–0.93, I2 = 0%) for psychomotor impairment, and 0.85 (95% CI 0.74–0.96, I2 = 50.39%) and 0.82 (95% CI 0.70–0.94, I2 = 87.73%) for MCI and early AD, respectively. Our subgroup analyses conveyed the diagnosis efficiency of keystroke dynamics for naturalistic self-reported data, and the promising performance of multimodal analysis of naturalistic behavioral data and deep learning methods in detecting disease-induced phenotypes. The meta-regression models showed the increase in diagnostic accuracy and fine motor impairment severity index with age and disease duration for PD and MCI. The risk of bias, based on the QUADAS-2 tool, is deemed low to moderate and overall, we rated the quality of evidence to be moderate. We conveyed the feasibility of keystroke dynamics as digital biomarkers for fine motor decline in naturalistic environments. Future work to evaluate their performance for longitudinal disease monitoring and therapeutic implications is yet to be performed. We eventually propose a partnership strategy based on a “co-creation” approach that stems from mechanistic explanations of patients’ characteristics derived from data obtained in-clinics and under ecologically valid settings. The protocol of this systematic review and meta-analysis is registered in PROSPERO; identifier CRD42021278707. The presented work is supported by the KU-KAIST joint research center.
Weak representation of awake/sleep states by local field potentials in aged mice
Authors: Konno Daichi , Ikegaya Yuji , Sasaki Takuya 
Published: May 2022

AbstractSenescence affects various aspects of sleep, and it remains unclear how sleep-related neuronal network activity is altered by senescence. Here, we recorded local field potential signals from multiple brain regions covering the forebrain in young (10-week-old) and aged (2-year-old) mice. Interregional LFP correlations across these brain regions could not detect pronounced differences between awake and sleep states in both young and aged mice. Multivariate analyses with machine learning algorithms with uniform manifold approximation and projection and robust continuous clustering demonstrated that LFP correlational patterns at multiple frequency bands, ranging from delta to high gamma bands, in aged mice less represented awake/sleep states than those in young mice. By housing aged mice in an enriched environment, the LFP patterns were changed to more precisely represent awake/sleep states. Our results demonstrate senescence-induced changes in neuronal activity at the network level and provide insight into the prevention of pathological symptoms associated with sleep disturbance in senescence.
A mucin protein predominantly expressed in the female-specific symbiotic organ of the stinkbug Plautia stali
Authors: Moriyama Minoru , Hayashi Toshinari , Fukatsu Takema 
Published: May 2022

AbstractDiverse insects are obligatorily associated with microbial symbionts, wherein the host often develops special symbiotic organs and vertically transmits the symbiont to the next generation. What molecular factors underpin the host-symbiont relationship is of great interest but poorly understood. Here we report a novel protein preferentially produced in a female-specific symbiotic organ of the stinkbug Plautia stali, whose posterior midgut develops numerous crypts to host a Pantoea-allied bacterial mutualist. In adult females, several posteriormost crypts are conspicuously enlarged, presumably specialized for vertical symbiont transmission. We detected conspicuous protein bands specific to the female’s swollen crypts by gel electrophoresis, and identified them as representing a novel mucin-like glycoprotein. Histological inspections confirmed that the mucin protein is localized to the female’s swollen crypts, coexisting with a substantial population of the symbiotic bacteria, and excreted from the swollen crypts to the midgut main tract together with the symbiotic bacteria. Using RNA interference, we successfully suppressed production of the mucin protein in adult females of P. stali. However, although the mucin protein was depleted, the symbiont population persisted in the swollen crypts, and vertical symbiont transmission to the next generation occurred. Possible biological roles and evolutionary trajectory of the symbiosis-related mucin protein are discussed.
Optimization of hydropower energy generation by 14 robust evolutionary algorithms
Authors: Sharifi Mohammad Reza , Akbarifard Saeid , Madadi Mohamad Reza , Qaderi Kourosh , Akbarifard Hossein 
Published: May 2022

AbstractThe use of evolutionary algorithms (EAs) for solving complex engineering problems has been very promising, so the application of EAs for optimal operation of hydropower reservoirs can be of great help. Accordingly, this study investigates the capability of 14 recently-introduced robust EAs in optimization of energy generation from Karun-4 hydropower reservoir. The best algorithm is the one that produces the largest objective function (energy generation) and has the minimum standard deviation (SD), the minimum coefficient of variations (CV), and the shortest time of CPU usage. It was found that the best solution was achieved by the moth swarm algorithm (MSA), with the optimized energy generation of 19,311,535 MW which was 65.088% more than the actual energy generation (11,697,757). The values of objective function, SD and CV for MSA were 0.147, 0.0029 and 0.0192, respectively. The next ranks were devoted to search group algorithm (SGA), water cycle algorithm (WCA), symbiotic organism search algorithm (SOS), and coyote optimization algorithm (COA), respectively, which have increased the energy generation by more than 65%. Some of the utilized EAs, including grasshopper optimization algorithm (GOA), dragonfly algorithm (DA), antlion optimization algorithm (ALO), and whale optimization algorithm (WOA), failed to produce reasonable results. The overall results indicate the promising capability of some EAs for optimal operation of hydropower reservoirs.
Parallel MR image reconstruction based on triple cycle optimization
Authors: Sheng Jinhua , Yin Jie , Wang Luyun , Yang Xiaofan , Huang Pu 
Published: May 2022

AbstractThe self-calibration parallel imaging (SC-SENSE) method reconstructs the image by estimating the coil sensitivity matrix. In order to obtain the sensitivity matrix, it is necessary to take a small amount of automatic calibration signal lines (ACSL) in the center of k-space. This method uses the data of the central region to obtain the sensitivity matrix, and then the reconstructed image is obtained. This paper proposed the triple cycle optimization (TCO) method to continuously optimize reconstructed images. The proposed TCO method takes the sensitivity matrix obtained by ACSL and substituted the reconstructed image as the initial data generation into the loop, and estimates the k-space data repeatedly. A new sensitivity matrix is obtained by using k-space data and the reconstructed image, and a stable triple cycle is obtained. In the cycle, all data are optimized to a certain extent, including the reconstructed image. Experimental results show that under the same sampling density, images reconstructed by using the triple cycle optimization method have lower noise and artifacts than those of the traditional method. When combined with the variable density sampling method, the effect is remarkable with a much low sampling rate.
Experimental study on ultrasonic irradiation for enhancing coalbed methane recovery
Authors: Ding Xin , Hou Jing , Xiao Xiaochun 
Published: May 2022

AbstractThe present study proposes the use of a new ultrasonic irradiation method to enhance permeability and desorption for gas recovery from low-permeability coal reservoirs. A triaxial stress ultrasonic irradiation test apparatus was developed specifically for coal, considering the properties of gas adsorption, migration, and sound intensity, and providing a simultaneous measurement of gas flux, to investigated the deformation and temperature of coal samples obtained from the Fuxin coal field by permeability and desorption experiments. With the ultrasonic irradiation duration, the permeability of coal improved gradually with unequal variation, accompanied by the Klinkenberg effect where it decreased rapidly and then increased slowly with increasing gas pressure. The ability to desorb coal was enhanced by higher sound intensity ultrasound irradiation, and the volume of gas desorption was much greater than that of the sample without mange, the temperature and strain were demonstrated as a “J shaped” curve. An X-ray computer tomography (CT) technique was used to visualise the meso- or macro-cracks in the coal sample at pre- and post- ultrasonic irradiation, consequently, fractures expanded under the irradiation of ultrasonic waves. A permeability and desorption model was developed to describe the improvement of coal seam gas production capacity under ultrasonic irradiation, which introduced effective sound pressure.