Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving the Role of Actoymyosin Contractility in Cell Microrheology

Einstein's original description of Brownian motion established a direct relationship between thermally-excited random forces and the transport properties of a submicron particle in a viscous liquid. Recent work based on reconstituted actin filament networks suggests that nonthermal forces driven by the motor protein myosin II can induce large non-equilibrium fluctuations that dominate the motion of particles in cytoskeletal networks. Here, using high-resolution particle tracking, we find that thermal forces, not myosin-induced fluctuating forces, drive the motion of submicron particles embedded in the cytoskeleton of living cells. These results resolve the roles of myosin II and contractile actomyosin structures in the motion of nanoparticles lodged in the cytoplasm, reveal the biphasic mechanical architecture of adherent cells—stiff contractile stress fibers interdigitating in a network at the cell cortex and a soft actin meshwork in the body of the cell, validate the method of particle tracking-microrheology, and reconcile seemingly disparate atomic force microscopy (AFM) and particle-tracking microrheology measurements of living cells.
Pluripotent Stem Cell-Derived Human Tissue: Platforms to Evaluate Drug Metabolism and Safety

Despite the improvements in drug screening, high levels of drug attrition persist. Although high-throughput screening platforms permit the testing of compound libraries, poor compound efficacy or unexpected organ toxicity are major causes of attrition. Part of the reason for drug failure resides in the models employed, most of which are not representative of normal organ biology. This same problem affects all the major organs during drug development. Hepatotoxicity and cardiotoxicity are two interesting examples of organ disease and can present in the late stages of drug development, resulting in major cost and increased risk to the patient. Currently, cell-based systems used within industry rely on immortalized or primary cell lines from donated tissue. These models possess significant advantages and disadvantages, but in general display limited relevance to the organ of interest. Recently, stem cell technology has shown promise in drug development and has been proposed as an alternative to current industrial systems. These offerings will provide the field with exciting new models to study human organ biology at scale and in detail. We believe that the recent advances in production of stem cell-derived hepatocytes and cardiomyocytes combined with cutting-edge engineering technologies make them an attractive alternative to current screening models for drug discovery. This will lead to fast failing of poor drugs earlier in the process, delivering safer and more efficacious medicines for the patient.
Design considerations and experimental results for direct-detection spatial tracking systems

The effect of signal and background shot noise, as well as device noise, on the performance of a direct-detection spatial tracking system is investigated for arbitrary detector arrays, assuming linear loop operation. The performance of quadrant detectors as a function of background radiation and detector radius is then analyzed and compared to some performance bounds. Tracking systems based on avalanche photodetectors (APD) and PIN detectors also are compared. The effects of non-focal-plane processing, focus error, and pupil walk on tracking performance are investigated. Experimental results of a 2.4 kHz two-axis tracking loop operating at low signal power using an APD quadrant detector are presented.
Contextualizing object detection and classification

In this paper, we investigate how to iteratively and mutually boost object classification and detection by taking the outputs from one task as the context of the other one. First, instead of intuitive feature and context concatenation or postprocessing with context, the so-called Contextualized Support Vector Machine (Context-SVM) is proposed, where the context takes the responsibility of dynamically adjusting the classification hyperplane, and thus the context-adaptive classifier is achieved. Then, an iterative training procedure is presented. In each step, Context-SVM, associated with the output context from one task (object classification or detection), is instantiated to boost the performance for the other task, whose augmented outputs are then further used to improve the former task by Context-SVM. The proposed solution is evaluated on the object classification and detection tasks of PASCAL Visual Object Challenge (VOC) 2007 and 2010, and achieves the state-of-the-art performance.
Food pantry selection solutions: a randomized controlled trial in client-choice food pantries to nudge clients to targeted foods

Background Food pantries and food banks are interested in cost-effective methods to encourage the selection of targeted foods without restricting choices. Thus, this study evaluates the effectiveness of nudges toward targeted foods. Methods In October/November 2014, we manipulated the display of a targeted product in a New York State food pantry. We evaluated the binary choice of the targeted good when we placed it in the front or the back of the category line (placement order) and when we presented the product in its original box or unboxed (packaging). Results The average uptake proportion for the back treatment was 0.231, 95% CI = 0.179, 0.29, n = 205, and for the front treatment, the proportion was 0.337, 95% CI = 0.272, 0.406, n = 238 with an odds ratio of 1.688, 95% CI = 1.088, 2.523. The average uptake for the unboxed treatment was 0.224, 95% CI = 0.174, 0.280, n = 255, and for the boxed intervention, the proportion was 0.356, 95% CI = 0.288, 0.429, n = 188 with an odds ratio of 1.923, 95% CI = 1.237, 2.991. Conclusions Nudges increased uptake of the targeted food. The findings also hold when we control for a potential confounder. Low cost and unobtrusive nudges can be effective tools for food pantry organizers to encourage the selection of targeted foods. Trial Registration Number NCT02403882.
Ongoing or previous mental disorders predispose to adverse mood reporting during combined oral contraceptive use

Abstract Purpose: Previous studies have emphasised that women with pre-existing mood disorders are more inclined to discontinue hormonal contraceptive use. However, few studies have examined the effects of combined oral contraceptives (COC) on mood in women with previous or ongoing mental disorders. Materials and methods: This is a supplementary analysis of an investigator-initiated, double-blinded, randomised clinical trial during which 202 women were treated with either a COC (1.5 mg estradiol and 2.5 mg nomegestrolacetate) or placebo during three treatment cycles. The Mini International Neuropsychiatric Interview was used to collect information on previous or ongoing mental disorders. The primary outcome measure was the total change score in five mood symptoms on the Daily Record of Severity of Problems (DRSP) scale in the intermenstrual phase of the treatment cycle. Results: Women with ongoing or previous mood, anxiety or eating disorders allocated to COC had higher total DRSP Δ-scores during the intermenstrual phase of the treatment cycle in comparison with corresponding women randomised to placebo, mean difference 1.3 (95% CI 0.3–2.3). In contrast, among women without mental health problems, no difference in total DRSP Δ-scores between COC- and placebo users was noted. Women with a risk use of alcohol who were randomised to the COC had higher total DRSP Δ-scores than women randomised to placebo, mean difference 2.1 (CI 95% 1.0–3.2). Conclusions: Women with ongoing or previous mental disorders or risk use of alcohol have greater risk of COC-induced mood symptoms. This may be worth noting during family planning and contraceptive counselling.
Clusternomics: Integrative context-dependent clustering for heterogeneous datasets

Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm. Author Summary Integrative clustering is the task of identifying groups of samples by combining information from several datasets. An example of this task is cancer subtyping, where we cluster tumour samples based on several datasets, such as gene expression, proteomics and others. Most existing algorithms assume that all such datasets share a similar cluster structure, with samples outside these clusters treated as noise. The structure can, however, be much more heterogeneous: some meaningful clusters may appear only in some datasets. In the paper, we introduce the Clusternomics algorithm that identifies groups of samples across heterogeneous datasets. It models both cluster structure of individual datasets, and the global structure that appears as a combination of local structures. The algorithm uses probabilistic modelling to identify the groups and share information across the local and global levels. We evaluated the algorithm on both simulated and real world datasets, where the algorithm found clinically significant clusters with different survival outcomes.
Selected electrical and thermal properties of polylactide/graphite composites

The influence of graphite on volume and surface resistivity as well as on some thermal properties of composites containing a polylactide matrix was studied. The graphite content was up to 50 wt. %. It was found that the volume and surface resistivity decreased with the increasing graphite content and the percolation threshold appeared at the level of the filler content of 30—40 wt. %. No essential influence of graphite on phase transition temperatures was observed. However, the phenomenon of cold crystallization appeared. The sample mass loss upon heating started at ca. 270 °C.
Pregnancy Outcomes from the Branded Glatiramer Acetate Pregnancy Database.

Background Appropriate counseling and treatment for women with multiple sclerosis (MS) who may become pregnant requires an understanding of the effects of exposure to disease-modifying therapies (DMTs) during pregnancy. Current reports and studies are limited in their usefulness, mostly by small sample size. Branded glatiramer acetate (GA) is a DMT approved for the treatment of relapsing forms of MS. For more than 2 decades, it has been shown to be efficacious and to have a favorable safety profile. The Teva Pharmaceutical Industries Ltd global pharmacovigilance database comprises data from more than 7000 pregnancies, during which women with MS were exposed to treatment with branded GA. Methods We analyzed data from Teva's global pharmacovigilance database. Pregnancy outcomes for patients treated with branded GA were compared with reference rates of abnormal pregnancy outcomes reported in two large registries representing the general population. Results Pregnancies exposed to branded GA were not at higher risk for congenital anomalies than what is expected in the general population. Conclusions These data provide evidence that branded GA exposure during pregnancy seems safe, without teratogenic effect.
Improved annotation of the insect vector of citrus greening disease: biocuration by a diverse genomics community

The Asian citrus psyllid (Diaphorina citri Kuwayama) is the insect vector of the bacterium Candidatus Liberibacter asiaticus (CLas), the pathogen associated with citrus Huanglongbing (HLB, citrus greening). HLB threatens citrus production worldwide. Suppression or reduction of the insect vector using chemical insecticides has been the primary method to inhibit the spread of citrus greening disease. Accurate structural and functional annotation of the Asian citrus psyllid genome, as well as a clear understanding of the interactions between the insect and CLas, are required for development of new molecular-based HLB control methods. A draft assembly of the D. citri genome has been generated and annotated with automated pipelines. However, knowledge transfer from well-curated reference genomes such as that of Drosophila melanogaster to newly sequenced ones is challenging due to the complexity and diversity of insect genomes. To identify and improve gene models as potential targets for pest control, we manually curated several gene families with a focus on genes that have key functional roles in D. citri biology and CLas interactions. This community effort produced 530 manually curated gene models across developmental, physiological, RNAi regulatory, and immunity-related pathways. As previously shown in the pea aphid, RNAi machinery genes putatively involved in the microRNA pathway have been specifically duplicated. A comprehensive transcriptome enabled us to identify a number of gene families that are either missing or misassembled in the draft genome. In order to develop biocuration as a training experience, we included undergraduate and graduate students from multiple institutions, as well as experienced annotators from the insect genomics research community. The resulting gene set (OGS v1.0) combines both automatically predicted and manually curated gene models. All data are available on https://citrusgreening.org/.
Study on Bond-slip Between Recycled Concrete and Rebars

According to "Standard Methods for Testing of Concrete Structures"(GB50152—92),a pull-out test was designed,and the load vs. slip curves between recycled concrete with different recycled coarse aggregate replacement percentages and different types of rebars were recorded.Based on the analysis of the test results,the bond strength between recycled concrete and rebars was investigated.Regression analysis on the test results was performed and the bond stress vs.slip relationship was proposed.Moreover,the anchorage length of rebars in recycled concrete was preliminarily suggested.
Burden of hypertension in The Gambia: evidence from a national World Health Organization (WHO) STEP survey.

Background Non-communicable diseases are increasing in sub-Saharan Africa and are estimated to account for 32% of adult deaths in The Gambia. Worldwide, prevalence of hypertension is highest in the African region (46%) and a very high proportion is undiagnosed. This study examined diagnosed and undiagnosed hypertension in The Gambian adult population. Methods Data were collected in 2010 from a nationally representative random sample of 4111 adults aged 25-64 years, using the World Health Organization STEPwise cross-sectional survey methods. Analyses were restricted to non-pregnant participants with three valid blood pressure measurements (n = 3573). We conducted gender-stratified univariate and multivariate regression analyses to identify the strongest sociodemographic, behavioural and biological risk factors associated with hypertension. Results Almost one-third of adults were hypertensive; a high proportion were undiagnosed, particularly among men (86% of men vs 71% of women with hypertension, P < 0.001). Rural and semi-urban residents and overweight/obese persons had increased odds of hypertension. Compared with urban residents, participants from one of the most rural regions had higher odds of hypertension among both men [adjusted odds ratio (AOR) 3.2; 95% CI: 1.6-6.4] and women (AOR 2.5; 95% CI: 1.3-4.6). Other factors strongly associated with hypertension in multivariate analyses were age, smoking, physical inactivity and ethnicity. Conclusions Rural and semi-urban residence were strongly associated with hypertension, contrary to what has been found in similar studies in sub-Saharan Africa. Intervention to reduce the burden of hypertension in The Gambia could be further targeted towards rural areas.
Forest Plant and Bird Communities in the Lau Group, Fiji

Background We examined species composition of forest and bird communities in relation to environmental and human disturbance gradients on Lakeba (55.9 km2), Nayau (18.4 km2), and Aiwa Levu (1.2 km2), islands in the Lau Group of Fiji, West Polynesia. The unique avifauna of West Polynesia (Fiji, Tonga, Samoa) has been subjected to prehistoric human-caused extinctions but little was previously known about this topic in the Lau Group. We expected that the degree of human disturbance would be a strong determinant of tree species composition and habitat quality for surviving landbirds, while island area would be unrelated to bird diversity. Methodology/Principal Findings All trees >5 cm diameter were measured and identified in 23 forest plots of 500 m2 each. We recognized four forest species assemblages differentiated by composition and structure: coastal forest, dominated by widely distributed species, and three forest types with differences related more to disturbance history (stages of secondary succession following clearing or selective logging) than to environmental gradients (elevation, slope, rockiness). Our point counts (73 locations in 1 or 2 seasons) recorded 18 of the 24 species of landbirds that exist on the three islands. The relative abundance and species richness of birds were greatest in the forested habitats least disturbed by people. These differences were due mostly to increased numbers of columbid frugivores and passerine insectivores in forests on Lakeba and Aiwa Levu. Considering only forested habitats, the relative abundance and species richness of birds were greater on the small but completely forested (and uninhabited) island of Aiwa Levu than on the much larger island of Lakeba. Conclusions/Significance Forest disturbance history is more important than island area in structuring both tree and landbird communities on remote Pacific islands. Even very small islands may be suitable for conservation reserves if they are protected from human disturbance.
Mapping and ablation of anteroseptal atrial tachycardia in patients with congenitally corrected transposition of the great arteries: implication of pulmonary sinus cusps

Aims We sought to investigate focal atrial tachycardias (ATs) in patients with congenitally corrected transposition of the great arteries (ccTGA). Methods and results We identified three cases of focal ATs with ccTGA from 2007 to 2015. The clinical findings, electrocardiography, electrophysiological features, and ablation were reported. All three cases had {S,L,L}-type ccTGA. The AT P waves shared the following features: narrow in width, positive in leads I and aVL, and negative/positive in lead V1. All ATs had focal activation pattern with early activation at the anteroseptal area, and further mapping demonstrated earliest atrial activation (EAA) inside the pulmonary sinus cusps (PSCs), especially the right PSC. In Cases 1 and 2, double potentials were recorded at the EAA sites. Conduction delay between the two potentials during atrial extrastimulus was observed. After successful ablation, the second potential during sinus rhythm was further delayed in Case 1 and was eliminated in Case 2. However, only one potential was recorded in Case 3. All three cases were successfully managed by ablating the sites with EAA, which preceded the P-wave onset by 60, 80, and 42 ms, respectively. During ablation, no junctional rhythm was observed. Incomplete left bundle branch block was induced during mapping in Case 1, but no other complications occurred. All patients were free from tachycardia during follow-up periods of 36, 7, and 5 months, respectively. Conclusion Anteroseptal AT in patients with ccTGA could be eliminated by ablation inside the PSC.
An efficient deep learning hashing neural network for mobile visual search

Mobile visual search applications are emerging that enable users to sense their surroundings with smart phones. However, because of the particular challenges of mobile visual search, achieving a high recognition bitrate has becomes a consistent target of previous related works. In this paper, we propose a few-parameter, low-latency, and high-accuracy deep hashing approach for constructing binary hash codes for mobile visual search. First, we exploit the architecture of the MobileNet model, which significantly decreases the latency of deep feature extraction by reducing the number of model parameters while maintaining accuracy. Second, we add a hash-like layer into MobileNet to train the model on labeled mobile visual data. Evaluations show that the proposed system can exceed state-of-the-art accuracy performance in terms of the MAP. More importantly, the memory consumption is much less than that of other deep learning models. The proposed method requires only 13 MB of memory for the neural network and achieves a MAP of 97.80% on the mobile location recognition dataset used for testing.
Towards Privacy-Preserving Content-Based Image Retrieval in Cloud Computing

Content-based image retrieval (CBIR) applications have been rapidly developed along with the increase in the quantity, availability and importance of images in our daily life. However, the wide deployment of CBIR scheme has been limited by its the severe computation and storage requirement. In this paper, we propose a privacy-preserving content-based image retrieval scheme, which allows the data owner to outsource the image database and CBIR service to the cloud, without revealing the actual content of the database to the cloud server. Local features are utilized to represent the images, and earth mover's distance (EMD) is employed to evaluate the similarity of images. The EMD computation is essentially a linear programming (LP) problem. The proposed scheme transforms the EMD problem in such a way that the cloud server can solve it without learning the sensitive information. In addition, local sensitive hash (LSH) is utilized to improve the search efficiency. The security analysis and experiments show the security and efficiency of the proposed scheme.