Miracle-dz/UniFAR-FTUs huggingface dataset:
Sex‐related differences in response to zinc pyrithione shampoo vs. non‐anti‐dandruff shampoo

Sex‐related differences in skin properties may be expected to impact dandruff formation and treatment. A meta‐analysis approach was undertaken to investigate potential differences between males and females in response to zinc pyrithione (ZnPT) treatment vs. non‐anti‐dandruff (AD) shampoo. A separate pooled statistical analysis of ceramide and total protein loss endpoints was also undertaken to assess potential sex‐related differences in stratum corneum properties that might influence response to ZnPT vs. non‐AD shampoo in subjects with dandruff.
The SUPERFAMILY 2.0 database: a significant proteome update and a new webserver

Abstract Here, we present a major update to the SUPERFAMILY database and the webserver. We describe the addition of new SUPERFAMILY 2.0 profile HMM library containing a total of 27 623 HMMs. The database now includes Superfamily domain annotations for millions of protein sequences taken from the Universal Protein Recourse Knowledgebase (UniProtKB) and the National Center for Biotechnology Information (NCBI). This addition constitutes about 51 and 45 million distinct protein sequences obtained from UniProtKB and NCBI respectively. Currently, the database contains annotations for 63 244 and 102 151 complete genomes taken from UniProtKB and NCBI respectively. The current sequence collection and genome update is the biggest so far in the history of SUPERFAMILY updates. In order to the deal with the massive wealth of information, here we introduce a new SUPERFAMILY 2.0 webserver (http://supfam.org). Currently, the webserver mainly focuses on the search, retrieval and display of Superfamily annotation for the entire sequence and genome collection in the database.
OMIM.org: leveraging knowledge across phenotype–gene relationships

Abstract For over 50 years Mendelian Inheritance in Man has chronicled the collective knowledge of the field of medical genetics. It initially cataloged the known X-linked, autosomal recessive and autosomal dominant inherited disorders, but grew to be the primary repository of curated information on both genes and genetic phenotypes and the relationships between them. Each phenotype and gene is given a separate entry assigned a stable, unique identifier. The entries contain structured summaries of new and important information based on expert review of the biomedical literature. OMIM.org provides interactive access to the knowledge repository, including genomic coordinate searches of the gene map, views of genetic heterogeneity of phenotypes in Phenotypic Series, and side-by-side comparisons of clinical synopses. OMIM.org also supports computational queries via a robust API. All entries have extensive targeted links to other genomic resources and additional references. Updates to OMIM can be found on the update list or followed through the MIMmatch service. Updated user guides and tutorials are available on the website. As of September 2018, OMIM had over 24,600 entries, and the OMIM Morbid Map Scorecard had 6,259 molecularized phenotypes connected to 3,961 genes.
A Cheating Detectable Privacy-Preserving Data Sharing Scheme for Cloud Computing

Cloud computing provides a new, attractive paradigm for the effective sharing of storage and computing resources among global consumers. More and more enterprises have begun to enter the field of cloud computing and storing data in the cloud to facilitate the sharing data among users. However, in many cases, users may be concerned about data privacy, trust, and integrity. It is challenging to provide data sharing services without sacrificing these security requirements. In this paper, a data sharing scheme of reliable, secure, and privacy protection based on general access structure is introduced. The proposed scheme is not only effective and flexible, but also is capable of protecting privacy for the cloud owner, supporting data sharing under supervision, enabling accountability of users’ decryption keys, and identifying cheaters if some users behave dishonestly. Security analysis and efficiency analysis demonstrate that our proposed scheme has better performance in computational costs compared with most related works. The scheme is versatile to be used in various environments. For example, it is particularly suitable to be employed to protect personal health data and medical diagnostic data in information medical environment.
SETDB1 is essential for mouse primordial germ cell fate determination by ensuring BMP signaling

ABSTRACT In mouse embryos, primordial germ cells (PGCs) are fate-determined from epiblast cells. Signaling pathways involved in PGC formation have been identified, but their epigenetic mechanisms remain poorly understood. Here, we show that the histone methyltransferase SETDB1 is an epigenetic regulator of PGC fate determination. Setdb1-deficient embryos exhibit drastic reduction of nascent PGCs. Dppa2, Otx2 and Utf1 are de-repressed whereas mesoderm development-related genes, including BMP4 signaling-related genes, are downregulated by Setdb1 knockdown during PGC-like cell (PGCLC) induction. In addition, binding of SETDB1 is observed at the flanking regions of Dppa2, Otx2 and Utf1 in cell aggregates containing PGCLCs, and trimethylation of lysine 9 of histone H3 is reduced by Setdb1 knockdown at those regions. Furthermore, DPPA2, OTX2 and UTF1 binding is increased in genes encoding BMP4 signaling-related proteins, including SMAD1. Finally, overexpression of Dppa2, Otx2 and Utf1 in cell aggregates containing PGCLCs results in the repression of BMP4 signaling-related genes and PGC determinant genes. We propose that the localization of SETDB1 to Dppa2, Otx2 and Utf1, and subsequent repression of their expression, are crucial for PGC determination by ensuring BMP4 signaling. Summary: We show that SETDB1 plays a crucial role in mouse PGC specification by repressing the transcription factors DPPA2, OTX2 and UTF1 to ensure the expression of BMP4 signaling-related genes.
FTP: An Approximate Fast Privacy-Preserving Equality Test Protocol for Authentication in Internet of Things

Privacy-preserving string equality test is a fundamental operation of many algorithms, including privacy-preserving authentication in Internet of Things (IoT). Existing secure equality test schemes can theoretically achieve string equality comparison and preserve the private strings. However, they suffer from heavy computation and communication cost, especially while the strings are of hundreds of bits or longer, which is not suitable for IoT applications. In this paper, we propose an approximate Fast privacy-preserving equality Test Protocol (FTP), which can securely complete string equality test and achieve high running efficiency at the cost of little accuracy loss. We strictly analyze the accuracy of our proposed scheme and formally prove its security. Additionally, we leverage extensive simulation experiments to evaluate the running cost, which confirms our high efficiency; for instance, our proposed FTP can securely compare two 256-bit strings within 0.7 seconds on ordinary laptops.
The Effect of Sulforaphane on Glyoxalase I Expression and Activity in Peripheral Blood Mononuclear Cells

Studies demonstrate that the potential health-beneficial effect of sulforaphane (SR), a compound formed in broccoli, is the result of a number of mechanisms including upregulation of phase two detoxification enzymes. Recent studies suggest that SR increases expression/activity of glyoxalase 1 (Glo1), an enzyme involved in the degradation of methylglyoxal, is major precursor of advanced glycation end products. Those compounds are associated with diabetes complications and other age-related diseases. In this study, the effect of SR on the expression/activity of Glo1 in peripheral blood mononuclear cells (PBMCs) from 8 healthy volunteers was investigated. PBMCs were isolated and incubated with SR (2.5 μM-concentration achievable by consuming a broccoli portion) for 24 h and 48 h. Glo1 activity/expression, reduced glutathione (GSH), and glutathione-S-transferase gene expression were measured. Glo1 activity was not affected while after 48 h a slight but significant increase of its gene expression (1.03-fold) was observed. GSTP1 expression slightly increased after 24 h incubation (1.08-fold) while the expressions of isoform GSTT2 and GSTM2 were below the limit of detection. GSH sharply decreased, suggesting the formation of GSH-SR adducts that may have an impact SR availability. Those results suggest that a regular exposure to SR by broccoli consumption or SR supplements may enhance Glo1.
Fine-Grained Control-Flow Integrity Based on Points-to Analysis for CPS

A cyber-physical system (CPS) is known as a mix system composed of computational and physical capabilities. The fast development of CPS brings new security and privacy requirements. Code reuse attacks that affect the correct behavior of software by exploiting memory corruption vulnerabilities and reusing existing code may also be threats to CPS. Various defense techniques are proposed in recent years as countermeasures to emerging code reuse attacks. However, they may fail to fulfill the security requirement well because they cannot protect the indirect function calls properly when it comes to dynamic code reuse attacks aiming at forward edges of control-flow graph (CFG). In this paper, we propose P-CFI, a fine-grained control-flow integrity (CFI) method, to protect CPS against memory-related attacks. We use points-to analysis to construct the legitimate target set for every indirect call cite and check whether the target of the indirect call cite is in the legitimate target set at runtime. We implement a prototype of P-CFI on LLVM and evaluate both its functionality and performance. Security analysis proves that P-CFI can mitigate the dynamic code reuse attack based on forward edges of CFG. Performance evaluation shows that P-CFI can protect CPS from dynamic code reuse attacks with trivial time overhead between 0.1% and 3.5% (Copyright © 2018 John Wiley & Sons, Ltd.).
A Cyclic Vernier Two-Step TDC for High Input Range Time-of-Flight Sensor Using Startup Time Correction Technique

Herein, we present a low-power cyclic Vernier two-step time-to-digital converter (TDC) that achieves a wide input range with good linearity. Since traditional approaches require a large area or high power to achieve an input range >300 ns, we solve this problem by proposing a simple yet efficient TDC suitable for time-of-flight (TOF) sensors. In previous studies using the cyclic structure, the effect of startup time on the linearity of the TDC is not described. Thus, the achievable linearity has been limited when the TDC is used for applications requiring a high input range. We solve this problem by using a simple yet effective technique to compensate. The proposed technique is realized using (1) digitally-controlled oscillators (DCOs) that have dual frequency control and matched startup time; (2) an alignment detector that performs startup time correction by proper timing control; and (3) a fully symmetric arbiter that precisely detects the instant of edge alignment. To achieve a fine resolution for the cyclic Vernier TDC, we design two closely-matched DCOs with dual frequency control. The alignment detector performs the critical task of cancelling startup time via timing control. The detector is delay-compensated by using a dummy to provide matched loading for the two DCOs. To enhance the detection speed under low power, a current-reuse approach is employed for the arbiter. The TDC is fabricated using a 0.18 μm complementary metal–oxide–semiconductor (CMOS) process in a compact chip area of 0.028 mm2. Measured results show a dynamic range of 355 ns and a resolution of 377 ps. When the result is applied for TOF sensing, it corresponds to a distance range of 53.2 m and a resolution of 5.65 cm. Over a relatively large input range, good linearity is achieved, which is indicated by a DNL of 0.28 LSBrms and an INL of 0.96 LSBrms. The result corresponds to root mean square (RMS) error distance of 5.42 cm. The result is achieved by consuming a relatively low power of 0.65 mW.
Graph theory for automatic structural recognition in molecular dynamics simulations.

Graph theory algorithms have been proposed in order to identify, follow in time, and statistically analyze the changes in conformations that occur along molecular dynamics (MD) simulations. The atomistic granularity level of the MD simulations is maintained within the graph theoric algorithms proposed here, isomorphism is a key component together with keeping the chemical nature of the atoms. Isomorphism is used to recognize conformations and construct the graphs of transitions, and the reduction in complexity of the isomorphism has been achieved by the introduction of "orbits" and "reference snapshots. " The proposed algorithms are applied to MD trajectories of gas phase molecules and clusters as well as condensed matter. The changes in conformations followed over time are hydrogen bond(s), proton transfer(s), coordination number(s), covalent bond(s), multiple fragmentation(s), and H-bonded membered rings. The algorithms provide an automatic analysis of multiple trajectories in parallel, and can be applied to ab initio and classical MD trajectories alike, and to more coarse grain representations.
Automatic Index Selection for Large-Scale Datalog Computation

Datalog has been applied to several use cases that require very high performance on large rulesets and factsets. It is common to create indexes for relations to improve search performance. However, the existing indexing schemes either require manual index selection or result in insufficient performance on very large tasks. In this paper, we propose an automatic scheme to select indexes. We automatically create the minimum number of indexes to speed up all the searches in a given Datalog program. We have integrated our indexing scheme into an open-source Datalog engine S OUFFLÉ. We obtain performance on a par with what users have accepted from hand-optimized Datalog programs running on state-of-the-art Datalog engines, while we do not require the effort of manual index selection. Extensive experiments on large real Datalog programs demonstrate that our indexing scheme results in considerable speedups (up to 2x) and significantly less memory usage (up to 6x) compared with other automated index selections.
The Lernaean Hydra of Data Series Similarity Search: An Experimental Evaluation of the State of the Art

Increasingly large data series collections are becoming commonplace across many different domains and applications. A key operation in the analysis of data series collections is similarity search, which has attracted lots of attention and effort over the past two decades. Even though several relevant approaches have been proposed in the literature, none of the existing studies provides a detailed evaluation against the available alternatives. The lack of comparative results is further exacerbated by the non-standard use of terminology, which has led to confusion and misconceptions. In this paper, we provide definitions for the different flavors of similarity search that have been studied in the past, and present the first systematic experimental evaluation of the efficiency of data series similarity search techniques. Based on the experimental results, we describe the strengths and weaknesses of each approach and give recommendations for the best approach to use under typical use cases. Finally, by identifying the shortcomings of each method, our findings lay the ground for solid further developments in the field.
Accessibility Evaluation of High Order Urban Hospitals for the Elderly: A Case Study of First-Level Hospitals in Xi'an, China

With reference to the hospitalizing trips made by the elderly, the impedance of these trips that require the use of public transportation, is introduced. An evaluation model that can accurately detect the accessibility of high order urban hospitals (HOUHs) for the elderly is established with the help of Geographic Information System (GIS) technology. Furthermore, the established model is employed to detect the accessibility of first-level hospitals in Xi’an City. Results showed that the traffic connection between hospitals and their service objects is an important factor for the feasibility and effectiveness of an accessibility evaluation. It is suggested that special evaluations of the accessibility of hospitals for the elderly are needed to achieve the human-oriented goal of urban traffic planning. The well-served spatial pattern of hospitalizing accessibility for the elderly in Xi’an City has been established in recent years because of the strategies for public transit metropolis. The accessibility constraints can be divided into three types: The imprisonment, the antagonism and the running-in, for which the corresponding countermeasures to settle the low accessibility of hospitals will be taken by the planning administration. Attention is paid to specific population groups during their hospitalizing trips in the accessibility research, which is beneficial for enabling the improvement of the current traditional method which is mainly based on travel facilities.
Metabolomic Profiling of Infants With Recurrent Wheezing After Bronchiolitis

Abstract Background Bronchiolitis is associated with a greater risk of developing recurrent wheezing, but with currently available tools, it is impossible to know which infants with bronchiolitis will develop this condition. This preliminary prospective study aimed to assess whether urine metabolomic analysis can be used to identify children with bronchiolitis who are at risk of developing recurrent wheezing. Methods Fifty-two infants <1 year old treated in the emergency department at University Hospital of Padova for acute bronchiolitis were enrolled (77% tested positive for respiratory syncytial virus [RSV]). Follow-up visits were conducted for 2 years after the episode of bronchiolitis. Untargeted metabolomic analyses based on mass spectrometry were performed on urine samples collected from infants with acute bronchiolitis. Data modeling was based on univariate and multivariate data analyses. Results We distinguished children with and those without postbronchiolitis recurrent wheeze, defined as ≥3 episodes of physician-diagnosed wheezing. Pathway overrepresentation analysis pointed to a major involvement of the citric acid cycle (P < .001) and some amino acids (lysine, cysteine, and methionine; P ≤ .015) in differentiating between these 2 groups of children. Conclusion This is the first study showing that metabolomic profiling of urine specimens from infants with bronchiolitis can be used to identify children at increased risk of developing recurrent wheezing.
An Effective Framework for Chaotic Image Encryption Based on 3D Logistic Map

In this paper, an effective framework for chaotic encryption based on a three-dimensional logistic map is presented together with secure hash algorithm-3 (SHA-3) and electrocardiograph (ECG) signal. Following the analysis of the drawbacks, namely, fixed key and low sensitivity, of some current algorithms, this work tries to solve these two problems and includes two contributions: (1) removal of the phenomenon of summation invariance in a plain-image, for which SHA-3 is proposed to calculate the hash value for the plain-image, with the results being employed to influence the initial keys for chaotic map; (2) resolution of the problem of fixed key by using an ECG signal, that can be different for different subjects or different for same subject at different times. The Wolf algorithm is employed to produce all the control parameters and initial keys in the proposed encryption method. It is believed that combining with the classical architecture of permutation-diffusion, the summation invariance in the plain-image and shortcoming of a fixed key will be avoided in our algorithm. Furthermore, the experimental results and security analysis show that the proposed encryption algorithm can achieve confidentiality.
Shuffle methodological deck chairs or abandon theoretical ship? The complexity turn in injury prevention

Injury prevention theory, research, policy and practice have provided a rich basis for the consensus that injuries are not unavoidable ‘accidents’, but rather the result of predictable and preventable events.1–8 Yet unintentional injuries remain a leading cause of morbidity and mortality worldwide.9 Thus, there remains a persistent global burden of injury that appears resistant to the efforts of conventional science, and a growing recognition that injury is a complex problem requiring complex solutions.10–12 In response to the recognition of this complexity, recent authors have noted the advantages of systems thinking approaches to injury prevention research.13–15 This shift holds that intrapersonal, interpersonal, organisational, community and societal determinants combine together into a highly complex ‘web of determinants’ that influences the likelihood of injury occurrence.13–16 Systems thinking thus offers much promise for further improvements in understanding injury and its prevention as a complex problem. The move to systems thinking is a promising one. However, the growing support for systems thinking as a valid way to approach complex, intractable injury problems has an unintended unhelpful consequence. This being an overemphasis on the epistemological question of how multifactorialism is accounted for in research, and a corresponding underemphasis on the ontological considerations and assumptions we make about the world. This dissonance in how complexity is understood and applied has been explored in a recent systematic review of systems thinking approaches in public health, which concluded that (1) close to half the papers identified by the review process are commentaries, (2) systems thinking in public health suffers from methodological weaknesses that need to be addressed, (3) …
An Adversarial and Densely Dilated Network for Connectomes Segmentation

Automatic reconstructing of neural circuits in the brain is one of the most crucial studies in neuroscience. Connectomes segmentation plays an important role in reconstruction from electron microscopy (EM) images; however, it is rather challenging due to highly anisotropic shapes with inferior quality and various thickness. In our paper, we propose a novel connectomes segmentation framework called adversarial and densely dilated network (ADDN) to address these issues. ADDN is based on the conditional Generative Adversarial Network (cGAN) structure which is the latest advance in machine learning with power to generate images similar to the ground truth especially when the training data is limited. Specifically, we design densely dilated network (DDN) as the segmentor to allow a deeper architecture and larger receptive fields for more accurate segmentation. Discriminator is trained to distinguish generated segmentation from manual segmentation. During training, such adversarial loss function is optimized together with dice loss. Extensive experimental results demonstrate that our ADDN is effective for such connectomes segmentation task, helping to retrieve more accurate segmentation and attenuate the blurry effects of generated boundary map. Our method obtains state-of-the-art performance while requiring less computation on ISBI 2012 EM dataset and mouse piriform cortex dataset.