bluuebunny/crossref_metadata_2025_split huggingface dataset:
Whole genome analysis of extensively drug resistant Mycobacterium tuberculosis strains in Peru
Authors: Santos-Lazaro David , Gavilan Ronnie G. , Solari Lely , Vigo Aiko N. , Puyen Zully M. 
Published: May 2021

AbstractPeru has the highest burden of multidrug-resistant tuberculosis in the Americas region. Since 1999, the annual number of extensively drug-resistant tuberculosis (XDR-TB) Peruvian cases has been increasing, becoming a public health challenge. The objective of this study was to perform genomic characterization of Mycobacterium tuberculosis strains obtained from Peruvian patients with XDR-TB diagnosed from 2011 to 2015 in Peru. Whole genome sequencing (WGS) was performed on 68 XDR-TB strains from different regions of Peru. 58 (85.3%) strains came from the most populated districts of Lima and Callao. Concerning the lineages, 62 (91.2%) strains belonged to the Euro-American Lineage, while the remaining 6 (8.8%) strains belonged to the East-Asian Lineage. Most strains (90%) had high-confidence resistance mutations according to pre-established WHO-confident grading system. Discordant results between microbiological and molecular methodologies were caused by mutations outside the hotspot regions analysed by commercial molecular assays (rpoB I491F and inhA S94A). Cluster analysis using a cut-off ≤ 10 SNPs revealed that only 23 (34%) strains evidenced recent transmission links. This study highlights the relevance and utility of WGS as a high-resolution approach to predict drug resistance, analyse transmission of strains between groups, and determine evolutionary patterns of circulating XDR-TB strains in the country.
Structural characterization of a Type B chloramphenicol acetyltransferase from the emerging pathogen Elizabethkingia anophelis NUHP1
Authors: Ghafoori Seyed Mohammad , Robles Alyssa M. , Arada Angelika M. , Shirmast Paniz , Dranow David M. , Mayclin Stephen J. , Lorimer Donald D. , Myler Peter J. , Edwards Thomas E. , Kuhn Misty L. , Forwood Jade K. 
Published: May 2021

AbstractElizabethkingia anophelisis an emerging multidrug resistant pathogen that has caused several global outbreaks.E. anophelisbelongs to the large family ofFlavobacteriaceae,which contains many bacteria that are plant, bird, fish, and human pathogens. Several antibiotic resistance genes are found within theE. anophelisgenome,including a chloramphenicol acetyltransferase (CAT). CATs play important roles in antibiotic resistance and can be transferred in genetic mobile elements. They catalyse the acetylation of the antibiotic chloramphenicol, thereby reducing its effectiveness as a viable drug for therapy. Here, we determined the high-resolution crystal structure of a CAT protein from theE. anophelisNUHP1 strain that caused a Singaporean outbreak. Its structure does not resemble that of the classical Type A CATs but rather exhibits significant similarity to other previously characterized Type B (CatB) proteins fromPseudomonas aeruginosa, Vibrio choleraeandVibrio vulnificus,which adopt a hexapeptide repeat fold.Moreover, the CAT protein fromE. anophelisdisplayed high sequence similarity to other clinically validated chloramphenicol resistance genes, indicating it may also play a role in resistance to this antibiotic. Our work expands the very limited structural and functional coverage of proteins fromFlavobacteriaceaepathogens which are becoming increasingly more problematic.
atpD gene sequencing, multidrug resistance traits, virulence-determinants, and antimicrobial resistance genes of emerging XDR and MDR-Proteus mirabilis
Authors: Algammal Abdelazeem M. , Hashem Hany R. , Alfifi Khyreyah J. , Hetta Helal F. , Sheraba Norhan S. , Ramadan Hazem , El-Tarabili Reham M. 
Published: May 2021

AbstractProteus mirabilis is a common opportunistic pathogen causing severe illness in humans and animals. To determine the prevalence, antibiogram, biofilm-formation, screening of virulence, and antimicrobial resistance genes in P. mirabilis isolates from ducks; 240 samples were obtained from apparently healthy and diseased ducks from private farms in Port-Said Province, Egypt. The collected samples were examined bacteriologically, and then the recovered isolates were tested for atpD gene sequencing, antimicrobial susceptibility, biofilm-formation, PCR detection of virulence, and antimicrobial resistance genes. The prevalence of P. mirabilis in the examined samples was 14.6% (35/240). The identification of the recovered isolates was confirmed by the atpD gene sequencing, where the tested isolates shared a common ancestor. Besides, 94.3% of P. mirabilis isolates were biofilm producers. The recovered isolates were resistant to penicillins, sulfonamides, β-Lactam-β-lactamase-inhibitor-combinations, tetracyclines, cephalosporins, macrolides, and quinolones. Using PCR, the retrieved strains harbored atpD, ureC, rsbA, and zapA virulence genes with a prevalence of 100%, 100%, 94.3%, and 91.4%, respectively. Moreover, 31.4% (11/35) of the recovered strains were XDR to 8 antimicrobial classes that harbored blaTEM, blaOXA-1, blaCTX-M, tetA, and sul1 genes. Besides, 22.8% (8/35) of the tested strains were MDR to 3 antimicrobial classes and possessed blaTEM, tetA, and sul1genes. Furthermore, 17.1% (6/35) of the tested strains were MDR to 7 antimicrobial classes and harbored blaTEM, blaOXA-1, blaCTX-M, tetA, and sul1 genes. Alarmingly, three strains were carbapenem-resistant that exhibited PDR to all the tested 10 antimicrobial classes and shared blaTEM, blaOXA-1, blaCTX-M, tetA, and sul1 genes. Of them, two strains harbored the blaNDM-1 gene, and one strain carried the blaKPC gene. In brief, to the best of our knowledge, this is the first study demonstrating the emergence of XDR and MDR-P.mirabilis in ducks. Norfloxacin exhibited promising antibacterial activity against the recovered XDR and MDR-P. mirabilis. The emergence of PDR, XDR, and MDR-strains constitutes a threat alarm that indicates the complicated treatment of the infections caused by these superbugs.
Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks
Authors: Strenge Benjamin , Schack Thomas 
Published: May 2021

AbstractThe majority of manufacturing tasks are still performed by human workers, and this will probably continue to be the case in many industry 4.0 settings that aim at highly customized products and small lot sizes. Technical systems could assist on-the-job training and execution of these manual assembly processes, using augmented reality and other means, by properly treating and supporting workers’ cognitive resources. Recent algorithmic advancements automatized the assessment of task-related mental representation structures based on SDA-M, which enables technical systems to anticipate mistakes and provide corresponding user-specific assistance. Two studies have empirically investigated the relations between algorithmic assessments of individual memory structures and the occurrences of human errors in different assembly tasks. Hereby theoretical assumptions of the automatized SDA-M assessment approaches were deliberately violated in realistic ways to evaluate the practical applicability of these approaches. Substantial but imperfect correspondences were found between task-related mental representation structures and actual performances with sensitivity and specificity values ranging from 0.63 to 0.72, accompanied by prediction accuracies that were highly significant above chance level.
GPCR_LigandClassify.py; a rigorous machine learning classifier for GPCR targeting compounds
Authors: Ahmed Marawan , Hasani Horia Jalily , Kalyaanamoorthy Subha , Barakat Khaled 
Published: May 2021

AbstractThe current study describes the construction of various ligand-based machine learning models to be used for drug-repurposing against the family of G-Protein Coupled Receptors (GPCRs). In building these models, we collected > 500,000 data points, encompassing experimentally measured molecular association data of > 160,000 unique ligands against > 250 GPCRs. These data points were retrieved from the GPCR-Ligand Association (GLASS) database. We have used diverse molecular featurization methods to describe the input molecules. Multiple supervised ML algorithms were developed, tested and compared for their accuracy, F scores, as well as for their Matthews’ correlation coefficient scores (MCC). Our data suggest that combined with molecular fingerprinting, ensemble decision trees and gradient boosted trees ML algorithms are on the accuracy border of the rather sophisticated deep neural nets (DNNs)-based algorithms. On a test dataset, these models displayed an excellent performance, reaching a ~ 90% classification accuracy. Additionally, we showcase a few examples where our models were able to identify interesting connections between known drugs from the Drug-Bank database and members of the GPCR family of receptors. Our findings are in excellent agreement with previously reported experimental observations in the literature. We hope the models presented in this paper synergize with the currently ongoing interest of applying machine learning modeling in the field of drug repurposing and computational drug discovery in general.
Relaxation capacity of cartilage is a critical factor in rate- and integrity-dependent fracture
Authors: Han G. , Chowdhury U. , Eriten M. , Henak C. R. 
Published: May 2021

AbstractArticular cartilage heals poorly but experiences mechanically induced damage across a broad range of loading rates and matrix integrity. Because loading rates and matrix integrity affect cartilage mechanical responses due to poroviscoelastic relaxation mechanisms, their effects on cartilage failure are important for assessing and preventing failure. This paper investigated rate- and integrity-dependent crack nucleation in cartilage from pre- to post-relaxation timescales. Rate-dependent crack nucleation and relaxation responses were obtained as a function of matrix integrity through microindentation. Total work for crack nucleation increased with decreased matrix integrity, and with decreased loading rates. Critical energy release rate of intact cartilage was estimated as 2.39 ± 1.39 to 2.48 ± 1.26 kJ m−2 in a pre-relaxation timescale. These findings showed that crack nucleation is delayed when cartilage can accommodate localized loading through poroviscoelastic relaxation mechanisms before fracture at a given loading rate and integrity state.
Controlling the corrosion and hydrogen gas liberation inside lead-acid battery via PANI/Cu-Pp/CNTs nanocomposite coating
Authors: Deyab M. A. , Mohsen Q. 
Published: May 2021

AbstractThe liberation of hydrogen gas and corrosion of negative plate (Pb) inside lead-acid batteries are the most serious threats on the battery performance. The present study focuses on the development of a new nanocomposite coating that preserves the Pb plate properties in an acidic battery electrolyte. This composite composed of polyaniline conductive polymer, Cu-Porphyrin and carbon nanotubes (PANI/Cu-Pp/CNTs). The structure and morphology of PANI/Cu-Pp/CNTs composite are detected using transmission electron microscopy (TEM), scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Based on the H2 gas evolution measurements and Tafels curves, the coated Pb (PANI/Cu-Pp/CNTs) has a high resistance against the liberation of hydrogen gas and corrosion. Electrochemical impedance spectroscopy (EIS) results confirm the suppression of the H2 gas evolution by using coated Pb (PANI/Cu-Pp/CNTs). The coated Pb (PANI/Cu-Pp/CNTs) increases the cycle performance of lead-acid battery compared to the Pb electrode with no composite.
Dominant egg surface bacteria of Holotrichia oblita (Coleoptera: Scarabaeidae) inhibit the multiplication of Bacillus thuringiensis and Beauveria bassiana
Authors: Wang Kui , Liu Qi , Liu Chunqin , Geng Lili , Wang Guirong , Zhang Jie , Shu Changlong 
Published: May 2021

AbstractHolotrichia oblita (Coleoptera: Scarabaeidae) and some other scarab beetles are the main soil-dwelling pests in China. Bacillus thuringiensis (Bt) and Beauveria bassiana (Bb) are entomopathogens that have been used as biocontrol agents of various pests. However, scarab larvae especially H. oblita exhibited strong adaptability to these pathogens. Compared to other scarabs, H. oblita could form a specific soil egg case (SEC) structure surrounding its eggs, and young larvae complete the initial development process inside this structure. In this study, we investigated the role of SEC structure and microorganisms from SEC and egg surface in pathogen adaptability. 16S rRNA gene analysis revealed low bacterial richness and high community unevenness in egg surface, with Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria dominating. In terms of OTUs composition analysis, the data show that the egg surface contains a large number of unique bacteria, indicating that the egg bacterial community may be derived from maternal transmission. Furthermore, we found that all culturable bacteria isolated from egg surface possessed antimicrobial activity against both Bt and Bb. The Pseudomonas bacteria with a significantly higher abundance in egg surface showed strong Bt- and Bb antagonistic ability. In conclusion, this study demonstrated a unique and antimicrobial bacterial community of H. oblita egg surface, which may contribute to its adaptability. Furthermore, the specific SEC structure surrounding the H. oblita eggs will provide a stable microenvironment for the eggs and egg surface bacteria, which probably provides more advantages for H. oblita adaptation ability.
Atypical electrophysiological and behavioral responses to diazepam in a leading mouse model of Down syndrome
Authors: Victorino Daniella B. , Pinheiro Daniel J. L. L. , Scott-McKean Jonah J. , Barker Sarah , Stasko Melissa R. , Faber Jean , Scorza Carla A. , Costa Alberto C. S. 
Published: May 2021

AbstractMounting evidence implicates dysfunctional GABAAR-mediated neurotransmission as one of the underlying causes of learning and memory deficits observed in the Ts65Dn mouse model of Down syndrome (DS). The specific origin and nature of such dysfunction is still under investigation, which is an issue with practical consequences to preclinical and clinical research, as well as to the care of individuals with DS and anxiety disorder or those experiencing seizures in emergency room settings. Here, we investigated the effects of GABAAR positive allosteric modulation (PAM) by diazepam on brain activity, synaptic plasticity, and behavior in Ts65Dn mice. We found Ts65Dn mice to be less sensitive to diazepam, as assessed by electroencephalography, long-term potentiation, and elevated plus-maze. Still, diazepam pre-treatment displayed typical effectiveness in reducing susceptibility and severity to picrotoxin-induced seizures in Ts65Dn mice. These findings fill an important gap in the understanding of GABAergic function in a key model of DS.
Deep learning for gradability classification of handheld, non-mydriatic retinal images
Authors: Nderitu Paul , do Rio Joan M. Nunez , Rasheed Rajna , Raman Rajiv , Rajalakshmi Ramachandran , Bergeles Christos , Sivaprasad Sobha ,   for the SMART India Study Group, Bhende Pramod , Raman Rajiv , Rajalakshmi Ramachandran , Mohan Viswanathan , Ramasamy Kim , Das Taraprasad , Rani Padmaja K. , Roy Rupak , Das Supita , Mohan Deepa , Narendran V. , Manayath George , Anantharaman Giridhar , Gopalakrishnan Mahesh , Natarajan Sundaram , Krishnan Radhika , Mani Sheena Liz , Agarwal Manisha , Padhi Tapas , Behera Umesh , Bhattacharjee Harsha , Barman Manabjyoti , Chawla Gajendra , Sen Alok , Saxena Moneesh , Sil Asim K. , Chakabarty Subhratanu , Cherian Thomas , Reesha K. R. , Naigaonkar Rushikesh , Desai Abishek , Deshpande Col Madan , Kulkarni Sucheta , Conroy Dolores , Thethi Jitendra Pal , Ramakrishnan Radha , Surya Janani 
Published: May 2021

AbstractScreening effectively identifies patients at risk of sight-threatening diabetic retinopathy (STDR) when retinal images are captured through dilated pupils. Pharmacological mydriasis is not logistically feasible in non-clinical, community DR screening, where acquiring gradable retinal images using handheld devices exhibits high technical failure rates, reducing STDR detection. Deep learning (DL) based gradability predictions at acquisition could prompt device operators to recapture insufficient quality images, increasing gradable image proportions and consequently STDR detection. Non-mydriatic retinal images were captured as part of SMART India, a cross-sectional, multi-site, community-based, house-to-house DR screening study between August 2018 and December 2019 using the Zeiss Visuscout 100 handheld camera. From 18,277 patient eyes (40,126 images), 16,170 patient eyes (35,319 images) were eligible and 3261 retinal images (1490 patient eyes) were sampled then labelled by two ophthalmologists. Compact DL model area under the receiver operator characteristic curve was 0.93 (0.01) following five-fold cross-validation. Compact DL model agreement (Kappa) were 0.58, 0.69 and 0.69 for high specificity, balanced sensitivity/specificity and high sensitivity operating points compared to an inter-grader agreement of 0.59. Compact DL gradability model performance was favourable compared to ophthalmologists. Compact DL models can effectively classify non-mydriatic, handheld retinal image gradability with potential applications within community-based DR screening.
Contribution of sewage to occurrence of phosphodiesterase-5 inhibitors in natural water
Authors: Hong Youngmin , Lee Ingyu , Tae Beomseok , Lee Wonseok , Pan Shu-Yuan , Snyder Seth W. , Kim Hyunook 
Published: May 2021

AbstractPhosphodiesterase-5 inhibitors (PDE-5i, such as Sildenafil, Tadalafil and Vardenafil, mainly prescribed to treat erectile dysfunction) and their generic drug equivalents have been widely marketed and consumed in Korea. From the concentrations detected in wastewater, we could deduce that relatively large amounts of PDE-5i were consumed without a legal prescription. Thus, PDE-5i’s presence in the environment via sewage is unavoidable, and their environmental fate within a sewage treatment plant (STP) should be evaluated. In this study, we investigated the occurrence of three PDE-5i analogs in the influent and effluent of two STPs and the receiving water bodies. The PDE-5i concentration in total reached 62 ± 12 (STP#1) and 88 ± 37 ng L−1 (STP#2) in the sewage influent; about 70% of it was Sildenafil in both STPs. However, they were hardly removed by the STPs as the removal efficiency of the STPs was less than 10% ± 5%. Therefore, the pharmaceuticals were detected in the receiving water (lower than 7 ng L−1as a total amount) and the concentration slightly increased downstream of the STPs. A simple mass balance model applied for the compounds in the STP effluent and receiving water bodies also confirmed that the discharged PDE-5i were quite persistent. Lastly, we identified temporal and regional patterns in the consumption of the drugs from daily variations of PDE-5i in the influent to these two STPs. For instance, the levels of PDE-5i in the sewage significantly increased on weekends (from Friday to Saturday), and especially in the area where adult-entertainment businesses are common. We estimated that the amount of PDE-5i consumption in this area was 31% higher than that in the area with fewer nightlife spots. Considering that they are pharmaceutically active and resistant to treatment processes within an STP, it is advised that a regular monitoring and management program for PDE-5i should be developed to prevent the discharge of the pharmaceuticals into the water environment.
Toxoplasma gondii infection in domestic and wild felids as public health concerns: a systematic review and meta-analysis
Authors: Hatam-Nahavandi Kareem , Calero-Bernal Rafael , Rahimi Mohammad Taghi , Pagheh Abdol Sattar , Zarean Mehdi , Dezhkam Asiyeh , Ahmadpour Ehsan 
Published: May 2021

AbstractFelidae as definitive hosts for Toxoplasma gondii play a major role in transmission to all warm-blooded animals trough oocysts dissemination. Therefore the current comprehensive study was performed to determine the global status of T. gondii infection in domestic and wild felids aiming to provide comprehensive data of interest for further intervention approaching the One Health perspective. Different databases were searched by utilizing particular key words for publications related to T. gondii infecting domestic and wild feline host species, worldwide, from 1970 to 2020. The review of 337 reports showed that the seroprevalence of T. gondii in domestic cats and wild felids was estimated in 37.5% (95% CI 34.7–40.3) (I2 = 98.3%, P < 0.001) and 64% (95% CI 60–67.9) (I2 = 88%, P < 0.0001), respectively. The global pooled prevalence of oocysts in the fecal examined specimens from domestic cats was estimated in 2.6% (95% CI 1.9–3.3) (I2 = 96.1%, P < 0.0001), and that in fecal samples from wild felids was estimated in 2.4% (95% CI 1.1–4.2) (I2 = 86.4%, P < 0.0001). In addition, from 13,252 examined soil samples in 14 reviewed studies, the pooled occurrence of T. gondii oocysts was determined in 16.2% (95% CI 7.66–27.03%). The observed high rates of anti-T. gondii antibodies seroprevalence levels and oocyst excretion frequency in the felids, along with soil (environmental) contamination with oocysts may constitute a potential threat to animal and public health, and data will result of interest in further prophylaxis programs.
Weakly supervised temporal model for prediction of breast cancer distant recurrence
Authors: Sanyal Josh , Tariq Amara , Kurian Allison W. , Rubin Daniel , Banerjee Imon 
Published: May 2021

AbstractEfficient prediction of cancer recurrence in advance may help to recruit high risk breast cancer patients for clinical trial on-time and can guide a proper treatment plan. Several machine learning approaches have been developed for recurrence prediction in previous studies, but most of them use only structured electronic health records and only a small training dataset, with limited success in clinical application. While free-text clinic notes may offer the greatest nuance and detail about a patient’s clinical status, they are largely excluded in previous predictive models due to the increase in processing complexity and need for a complex modeling framework. In this study, we developed a weak-supervision framework for breast cancer recurrence prediction in which we trained a deep learning model on a large sample of free-text clinic notes by utilizing a combination of manually curated labels and NLP-generated non-perfect recurrence labels. The model was trained jointly on manually curated data from 670 patients and NLP-curated data of 8062 patients. It was validated on manually annotated data from 224 patients with recurrence and achieved 0.94 AUROC. This weak supervision approach allowed us to learn from a larger dataset using imperfect labels and ultimately provided greater accuracy compared to a smaller hand-curated dataset, with less manual effort invested in curation.