Miracle-dz/UniFAR-FTUs huggingface dataset:
Harnessing Metabolic Regulation to Increase Hfq-Dependent Antibiotic Susceptibility in Pseudomonas aeruginosa

The opportunistic human pathogen Pseudomonas aeruginosa is responsible for ~ 10% of hospital-acquired infections worldwide. It is notorious for its high level resistance toward many antibiotics, and the number of multi-drug resistant clinical isolates is steadily increasing. A better understanding of the molecular mechanisms underlying drug resistance is crucial for the development of novel antimicrobials and alternative strategies such as enhanced sensitization of bacteria to antibiotics in use. In P. aeruginosa several uptake channels for amino-acids and carbon sources can serve simultaneously as entry ports for antibiotics. The respective genes are often controlled by carbon catabolite repression (CCR). We have recently shown that Hfq in concert with Crc acts as a translational repressor during CCR. This function is counteracted by the regulatory RNA CrcZ, which functions as a decoy to abrogate Hfq-mediated translational repression of catabolic genes. Here, we report an increased susceptibility of P. aeruginosa hfq deletion strains to different classes of antibiotics. Transcriptome analyses indicated that Hfq impacts on different mechanisms known to be involved in antibiotic susceptibility, viz import and efflux, energy metabolism, cell wall and LPS composition as well as on the c-di-GMP levels. Furthermore, we show that sequestration of Hfq by CrcZ, which was over-produced or induced by non-preferred carbon-sources, enhances the sensitivity toward antibiotics. Thus, controlled synthesis of CrcZ could provide a means to (re)sensitize P. aeruginosa to different classes of antibiotics.
Serum Interleukin‐8, Osteopontin, and Monocyte Chemoattractant Protein 1 Are Associated With Hepatic Fibrosis in Patients With Nonalcoholic Fatty Liver Disease

The severity of hepatic fibrosis is the primary predictor of liver‐related morbidity and mortality in patients with nonalcoholic fatty liver disease (NAFLD). Unfortunately, noninvasive serum biomarkers for NAFLD‐associated fibrosis are limited. We analyzed baseline serum samples for 24 cytokines of 97 patients with biopsy‐proven NAFLD. These patients were prospectively enrolled in a clinical study (ClinicalTrials.gov NCT00794716) to identify cytokines associated with liver fibrosis in patients with nonalcoholic steatohepatitis. Patients were stratified according to severity of hepatic fibrosis (mild, stage 0‐1, n = 37; moderate, stage 2, n = 40; and advanced, stage 3‐4, n = 20) while controlling for age, race, sex, body mass index, and diabetes mellitus. Interleukin‐8 (IL‐8), osteopontin (OPN), and monocyte chemoattractant protein 1 (MCP1) were associated with liver fibrosis (P < 0.001, P = 0.005, P = 0.016, respectively). After controlling for steatosis, lobular inflammation, hepatocyte ballooning, age, sex, body mass index, diabetes mellitus, hypertension, and metabolic syndrome status, IL‐8 remained strongly associated with fibrosis (P = 0.001). Furthermore, IL‐8 was also a strong predictor of increased fibrotic liver injury compared to established markers of hepatic fibrosis. Hepatic gene expression from 72 patients with NAFLD (n = 40 mild fibrosis; n = 32 advanced fibrosis) from the Duke University Health System NAFLD Clinical Database and Biorepository revealed IL‐8, MCP1, and OPN gene expression to be increased and differentially expressed in patients with advanced hepatic fibrosis. Thus, serum IL‐8, MCP1, and OPN may reflect up‐regulated gene expression during liver fibrosis in NAFLD. Conclusion: Serum IL‐8, MCP1, and OPN may serve as a test for advanced hepatic fibrosis in NAFLD and thus reveal novel targets for antifibrotic therapies. The increased serum IL‐8, MCP1, and OPN that correspond with associated hepatic gene expression lend strength to such analytes as ideal surrogate serum biomarkers for severity of hepatic fibrosis.
Phantom Device Attack: Uncovering the Security Implications of the Interactions among Devices, IoT Cloud, and Mobile Apps

Smart home connects tens of home devices into the Internet, running a smart algorithm in the cloud that sends remote commands to the devices. While bringing unprecedented convenience, accessibility, and efficiency, it also introduces safety hazards to users. Prior research studied smart home security from various aspects. However, we found that the complexity of the interactions among the participating entities (device, IoT cloud, and mobile app) has not yet been systematically investigated. In this work, we conducted an in-depth analysis to four widely used smart home solutions. Combining firmware reverse-engineering, network traffic interception, and black-box testing, we distill the general state transitions representing the complex interactions among the three entities. Based on the state machine, we reveal several vulnerabilities that lead to unexpected state transitions. While these minor security flaws appear to be irrelevant, we show that combining them in a surprising way poses serious security or privacy hazards to smart home users. To this end, five concrete attacks are constructed and illustrated. We also discuss the implications of the disclosed attacks in the context of business competition. Finally, we propose some general design suggestions for building a more secure smart home solution.
Doctor Robot with Physical Examination for Skin Disease Diagnosis and Telemedicine Application

This paper illustrates various aspects of a doctor robot for physical examination such as for skin disease diagnosis. In modern society, most of the people are too busy to have a physical examination or some people who live in the remote area are difficult to go to the hospital. If everyone has a Doctor Robot at home when they feel uncomfortable, they just go to the front of the doctor robot, and it will start to check your body situation automatically. It will check your body situation and give you the diagnosis result by word and voice. It is, therefore, suitable for a variety of users, including the visually impaired people. Simultaneously, the result is connected to the cloud, so human doctors can see the results from the hospital, if necessary and doctors can help with Telemedicine. User can check data result by using the face. When Doctor Robot sees the user, it will connect it to the recorded data in the system.
Direct Segmentation-Based Full Quantification for Left Ventricle via Deep Multi-Task Regression Learning Network

Quantitative analysis of the heart is extremely necessary and significant for detecting and diagnosing heart disease, yet there are still some challenges. In this study, we propose a new end-to-end segmentation-based deep multi-task regression learning model (Indices-JSQ) to make a holonomic quantitative analysis of the left ventricle (LV), which contains a segmentation network (Img2Contour) and multi-task regression network (Contour2Indices). First, Img2Contour, which contains a deep convolutional encoder-decoder module, is designed to obtain the LV contour. Then, the predicted contour is fed as input to Contour2Indices for full quantification. On the whole, we take into account the relationship between different tasks, which can serve as a complementary advantage. Meanwhile, instead of using images directly from the original dataset, we creatively use the segmented contour of the original image to estimate the cardiac indices to achieve better and more accurate results. We make experiments on MR sequences of 145 subjects and gain the experimental results of 157 mm$^{{\bf 2}}$, 2.43 mm, 1.29 mm, and 0.87 on areas, dimensions, regional wall thicknesses, and Dice Metric, respectively. It intuitively shows that the proposed method outperforms the other state-of-the-art methods and demonstrates that our method has a great potential in cardiac MR images segmentation, comprehensive clinical assessment, and diagnosis.
Application of VMD Algorithm in UGW-based Rail Breakage Detection System

As a solid medium of sound propagation, rails provide perfect acoustic features. In this way, rail breakage detection systems based on ultrasonic guided waves (UGW) have been recently developed. In outdoor applications of these systems, different types of interference are usually added to the received signal, which makes UGW signals difficult to distinguish and analyze, even leading to false alarms and affecting the system efficiency. In order to recover UGW signals in these systems, the application of a variational mode decomposition (VMD) algorithm to denoise and reconstruct UGW signals is proposed in this work. This algorithm can decompose the received signal into different intrinsic mode functions (IMF), which some are useful signals and the others are interference. Removing the interference part and the UGW signals can be reconstructed. By comparing the amplitude of reconstructed UGW signal with a predefined threshold, the rail status can be determined easier than before. Furthermore, by calculating the deviation between the reconstructed signal after the VMD algorithm and the original one, the effectiveness and suitability of the proposal is verified through some simulation results.
Pectin or chitosan coating fortified with eugenol reduces Campylobacter jejuni on chicken wingettes and modulates expression of critical survival genes

ABSTRACT Campylobacter jejuni infection in humans is strongly associated with the consumption of contaminated poultry products. With increasing consumer demand for minimally processed and natural product, there is a need for novel intervention strategies for controlling C. jejuni. Antimicrobial coatings are increasingly being used for preventing food contamination due to their efficacy and continuous protection of product. This study investigated the efficacy of pectin and chitosan coating fortified with eugenol to reduce C. jejuni on chicken wingettes. Pectin, chitosan, and eugenol are generally recognized as safe status compounds derived from berries, crustaceans, and cloves respectively. Each wingette was inoculated with a mixture of 4 wild‐type strains of C. jejuni (approximately 107 CFU/sample) and randomly assigned to controls, pectin (3%), chitosan (2%), eugenol (0.5, 1, or 2%), or their combinations. Following 1 min of coating, wingettes were air‐dried, vacuum sealed, and sampled on 0, 1, 3, 5, and 7 d of refrigerated storage for C. jejuni and aerobic counts (n = 5 wingettes/treatment/d). In addition, the effect of treatments on wingette color and expression of C. jejuni survival/virulence genes was evaluated. All 3 doses of eugenol or chitosan significantly reduced C. jejuni and aerobic bacteria from 0 d through 7 d. Incorporation of 2% eugenol in chitosan improved coating efficiency and reduced C. jejuni counts by approximately 3 Log CFU/sample at the end of 7 d of storage (P < 0.05). Similarly, the antimicrobial efficacy of pectin was improved by 2% eugenol and the coating reduced C. jejuni by approximately 2 Log CFU/sample at 7 d of storage. Chitosan coating with 2% eugenol also showed greater reductions of total aerobic counts as compared to individual treatments of eugenol and chitosan. No significant difference in the color of chicken wingettes was observed between treatments. Exposure of C. jejuni to eugenol, chitosan, or combination significantly modulated select genes encoding for motility, quorum sensing, and stress response. Results demonstrate the potential of pectin or chitosan coating fortified with eugenol as a postharvest intervention against C. jejuni contamination on poultry products.
Direct Observation of the Interplay of Catechol Binding and Polymer Hydrophobicity in a Mussel-Inspired Elastomeric Adhesive

Marine organisms such as mussels have mastered the challenges in underwater adhesion by incorporating post-translationally modified amino acids like l-3,4-dihydroxyphenylalanine (DOPA) in adhesive proteins. Here we designed a catechol containing elastomer adhesive to identify the role of catechol in interfacial adhesion in both dry and wet conditions. To decouple the adhesive contribution of catechol to the overall adhesion, the elastomer was designed to be cross-linked through [2 + 2] photo-cycloaddition of coumarin. The elastomer with catechol moieties displayed a higher adhesion strength than the catechol-protected elastomer. The contact interface was probed using interface-sensitive sum frequency generation spectroscopy to explore the question of whether catechol can displace water and bond with hydrophilic surfaces. The spectroscopy measurements reveal that the maximum binding energy of the catechol and protected-catechol elastomers to sapphire substrate is 7.0 ± 0.1 kJ/(mole of surface O–H), which is equivalent to 0.10 J/m2. The higher dry and wet adhesion observed in the macroscopic adhesion measurements for the catechol containing elastomer originates from multiple hydrogen bonds of the catechol dihydroxy groups to the surface. In addition, our results show that catechol by itself does not remove the confined interstitial water. In these elastomers, it is the hydrophobic groups that help in partially removing interstitial water. The observation of the synergy between catechol binding and hydrophobicity in enabling the mussel-inspired soft adhesive elastomer to stick underwater provides a framework for designing materials for applications in tissue adhesion and moist-skin wearable electronics.
Multi-omic based molecular profiling of advanced cancer identifies treatable targets and improves survival in individual patients

A proof-of-concept study was conducted to assess whether patients with advanced stage IV cancer for whom predominantly no standard therapy was available could benefit from comprehensive molecular profiling of their tumor tissue to provide targeted therapy. Tumor samples of 83 patients were collected under highly standardized conditions and analyzed using immunohistochemistry, next-generation sequencing and phosphoprotein profiling. Expression and phosphorylation of key oncogenic pathways were measured to identify targets at the (phospho-) proteomic level. At genomic level, 50 oncogenes and tumor suppressor genes were analyzed. Based on molecular profiling, targeted therapies were decided by the attending oncologist. Accordingly, 28 patients who met the defined criteria fell in two equal-sized groups. One group received targeted therapies while the other did not. Following six months of treatment, disease control was achieved by 49% of patients receiving targeted therapy (complete remission, 14%; partial remission, 21%; stable disease, 14%; disease progression, 36%; death, 14%) and 21% of patients receiving non-targeted therapy (stable disease, 21%; disease progression, 64%; death, 14%). Individual patients experienced dramatic responses to a therapy which otherwise would not have been applied. This approach clarifies the value of multi-omic molecular profiling for cancer diagnostics.
An in vivo translation-reporter system for the study of protein synthesis in zebrafish embryos

ABSTRACT Control of gene expression at the translation level is increasingly regarded as a key feature in many biological processes. Simple, inexpensive and reliable procedures to visualize sites of protein production are required to allow observation of the spatiotemporal patterns of mRNA translation at subcellular resolution. We present a method, named SPoT (for Subcellular Patterns of Translation), developed upon the original TimeStamp technique ( Lin et al., 2008), consisting in the expression of a fluorescent protein fused to a tagged, self-cleavable protease domain. The addition of a cell-permeable protease inhibitor instantly stabilizes newly produced tagged protein allowing us to distinguish recently synthesized proteins from pre-existing ones. After a brief protease inhibitor treatment, the ratio of tagged versus non-tagged forms is highest at sites where proteins are the most recent, i.e. sites of synthesis. Therefore, by comparing tagged and non-tagged proteins it is possible to spotlight sites of translation. By specifically expressing the SPoT cassette in neurons of transgenic zebrafish embryos, we reveal sites of neuronal protein synthesis in diverse cellular compartments during early development. Summary: We describe a transgene-based method, SPoT, that reveals subcellular sites of protein synthesis in neurons of wholemount zebrafish embryos.
Privacy and Security issues in Big Data: Through Indian Prospective

BIG DATA is one of the emerging domain and performing a key role under several applications like, smart city, smart grid and intelligent transportation system, etc. In order to provide the real time services, Big Data has achieved a great success on the other side its counterpart is facing lot of challenges of privacy and security. Keeping in the view of real time access and services, security and privacy issues need to be given the highest priority. Personal and professional information's of an individual or an organization are globally available through cloud storage, which attract the attacker(s) and can be misused. Social media is very active and popular among the young generation, movement of very heavy traffic is involving under social environment, smart attackers capture the personal information from social environment and may create the problems against required information. As per the literature review number of proposals is available for the above mentioned issues but there is no guarantee of data privacy and security, therefore, still lot of scope is there for optimal or sub-optimal solutions. Motive of this study is to investigate the different challenges of big data for privacy and security through Indian prospective. We have collected the existing solutions for data privacy and security, and performed a comprehensive review by including their pros and cons. Impact areas of different cyber attacks have been investigated and covered in details. This study is not only preventing the data from fraud but also interested in knowing the culprit behind this fraud/attack.
Sex differences in HIV-associated cognitive impairment: an observational cohort study.

OBJECTIVE We determined whether there are sex differences in the prevalence and profile of HIV-associated neurocognitive impairment, and whether sex moderates the effect of HIV-serostatus on neurocognitive impairment among HIV+ and HIV- individuals. Secondarily, we assessed whether differences were explained by greater biopsychosocial risk factors in HIV+ women. DESIGN Observational cohort study. METHODS Analyses included 1,361 HIV+ (204 women) and 702 HIV- (214 women) (ages = 18-79) participants from the UCSD HIV Neurobehavioral Research Program. Demographically-corrected standardized T-scores from 15 neuropsychological tests were used to calculate domain-specific and global deficit scores (GDS). GDS≥0.5 defined neurocognitive impairment. Biopsychosocial risk factors included low education, low reading level (education quality), lifetime substance use disorders, depressed mood (clinically-significant depressive symptoms and/or current major depressive disorder), and a cumulative syndemic count (sum of biopsychosocial risk factors, range = 0-4). Race-stratified analyses were conducted. Analyses were adjusted for relevant demographic and clinical factors. RESULTS HIV-associated neurocognitive impairment was more prevalent in women versus men; however, the difference was eliminated after adjustment for reading level. In sex-stratified logistic regressions, the association between HIV-seropositivity and higher likelihood of neurocognitive impairment was stronger in women versus men; however, the association was attenuated in women, but not men, after adjusting for reading level. These results in the overall sample were specific to blacks. Sex differences in the profile of HIV-associated neurocognitive impairment varied by race. CONCLUSIONS Women, particularly black women, were most at-risk for HIV-associated neurocognitive impairment. Higher rates of HIV-associated neurocognitive impairment in women versus men may reflect differences in educational quality.
Enhanced detection of circulating tumor DNA by fragment size analysis

Selective sequencing or in silico analysis for differences in DNA fragment size can improve the detection of circulating tumor DNA. Sizing up circulating tumor DNA Unlike solid tumors, which are often hidden deep within a patient’s body, a patient’s blood is easy to access safely. As a result, liquid biopsy, the analysis of tumor DNA in the blood, is an attractive alternative to conventional biopsy. Unfortunately, tumor DNA molecules are usually vastly outnumbered by the fragments of noncancer DNA in the blood, and detecting them can be a challenge, especially in early stages of cancer. Mouliere et al. identified characteristic differences in the size distribution of tumor-derived and noncancer DNA fragments and then used these observations to design a method of tumor DNA detection with greater sensitivity. Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 patients with cancer using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90 and 150 bp and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90 and 150 bp improved detection of tumor DNA, with more than twofold median enrichment in >95% of cases and more than fourfold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with area under the curve (AUC) >0.99 compared to AUC <0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC > 0.91 compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cfDNA.