Targeted Analysis of Veterinary Drugs in Food Samples by Developing a High-Resolution Tandem Mass Spectral Library.

Veterinary drug residues present in foods can pose severe health threats to the population. The present study aims to develop a high-resolution mass spectral library of 158 veterinary drugs of 16 different classes for their rapid identification in food samples through liquid chromatography-high-resolution electrospray ionization-tandem mass spectrometry (LC-HR-ESI-MS/MS). Standard drugs were pooled according to their log P values and exact masses before analysis. Spectra were collected at system automated collision energy, i.e., of 25-60 eV and four predetermined collision energies (10, 20, 30, and 40 eV) for each compound using a schedule precursor list of [M + H]+, [M + Na]+, and [M + NH4]+ ions. The utility of the developed database was checked by analyzing food samples. A total of 17 veterinary drugs based on the reference standard retention times (RTs), HR-MS spectra, and MS/MS spectra were identified in the analyzed samples. Moreover, five veterinary drugs were selected for quantitative analysis, including doxycycline hyclate, lincomycin, sulfasalazine, moxifloxacin, and diphenoxylate, using liquid chromatography-ion trap mass-spectrometry (LC-IT-MS). Concentrations of the drug were obtained to vary from 0.0805 to 0.9731 mg/kg in food samples and were found to be exceeded in most of the cases as per the maximum residue levels described by Food and Agriculture Organization (FAO)/World Health Organization (WHO). The MS data were submitted to the MetaboLights online database (MTBLS2914). This study will help in the high-throughput screening of multiclass veterinary drugs in foodstuffs.

Improving the efficiency of dye-sensitized solar cells based on rare-earth metal modified bismuth ferrites.

This study reports light energy harvesting characteristics of bismuth ferrite (BiFeO3) and BiFO3 doped with rare-earth metals such as neodymium (Nd), praseodymium (Pr), and gadolinium (Gd) dye solutions that were prepared by using the co-precipitation method. The structural, morphological, and optical properties of synthesized materials were studied, confirming that 5-50 nm sized synthesized particles have a well-developed and non-uniform grain size due to their amorphous nature. Moreover, the peaks of photoelectron emission for bare and doped BiFeO3 were observed in the visible region at around 490 nm, while the emission intensity of bare BiFeO3 was noticed to be lower than that of doped materials. Photoanodes were prepared with the paste of the synthesized sample and then assembled to make a solar cell. The natural and synthetic dye solutions of Mentha, Actinidia deliciosa, and green malachite, respectively, were prepared in which the photoanodes were immersed to analyze the photoconversion efficiency of the assembled dye-synthesized solar cells. The power conversion efficiency of fabricated DSSCs, which was confirmed from the I-V curve, is in the range from 0.84 to 2.15%. This study confirms that mint (Mentha) dye and Nd-doped BiFeO3 materials were found to be the most efficient sensitizer and photoanode materials among all the sensitizers and photoanodes tested.

Synthesis and Characterization of Polyvinyl Chloride Matrix Composites with Modified Scrap Iron for Advanced Electronic, Photonic, and Optical Systems.

In this study, Fe2O3 powder was synthesized using the co-precipitation method from scrap iron, which was then treated with varying concentrations of copper. Afterwards, the modified Fe2O3 was reinforced in the PVC matrix by using the solution-casting method to synthesize PVC composite films, which were subjected to a UV-visible spectrophotometer, a Fourier transform infrared spectrophotometer, an X-ray diffractometer, and a thermal gravimetric analyzer to evaluate the optical, chemical, structural, and thermal properties. FTIR analysis reveals the formation of the composite through vibrational bands pertaining to both components present, whereas no significant changes in the XRD patterns of PVC were observed after the doping of modified iron oxide, which reveals the compatibility of fillers with the PVC matrix. The optical properties of the copper-doped iron oxide-PVC composites, including absorbance, refractive index, urbach energy, and optical as well as electrical conductivity are measured, and show an increase in optical activity when compared to the pure PVC compound. Moreover, the increased thermal stability of the synthesized composite was also observed and compared with conventional compounds, which, in accordance with all the other mentioned properties, makes the copper-dopped iron oxide-PVC composite an effective material for electronic, photonic, and optical device applications.

Retraction: Association Between Ureteral Double J Stent Colonization and Lower Urinary Tract Symptom Severity: A Cross-Sectional Study.

[This retracts the article DOI: 10.7759/cureus.19354.].

Mechanistic Impact of Zinc Deficiency in Human Development.

Zinc (Zn) deficiency in humans is an emerging global health issue affecting approximately two billion people across the globe. The situation prevails due to the intake of Zn deficient grains and vegetables worldwide. Clinical identification of Zn deficiency in humans remains problematic because the symptoms do not appear until impair the vital organs, such as the gastrointestinal track, central nervous system, immune system, skeletal, and nervous system. Lower Zn body levels are also responsible for multiple physiological disorders, such as apoptosis, organs destruction, DNA injuries, and oxidative damage to the cellular components through reactive oxygen species (ROS). The oxidative damage causes chronic inflammation lead toward several chronic diseases, such as heart diseases, cancers, alcohol-related malady, muscular contraction, and neuro-pathogenesis. The present review focused on the physiological and growth-related changes in humans under Zn deficient conditions, mechanisms adopted by the human body under Zn deficiency for the proper functioning of the body systems, and the importance of nutritional and nutraceutical approaches to overcome Zn deficiency in humans and concluded that the biofortified food is the best source of Zn as compared to the chemical supplementation to avoid their negative impacts on human.

Association Between Ureteral Double J Stent Colonization and Lower Urinary Tract Symptom Severity: A Cross-Sectional Study.

Introduction Double J stents (DJS) are commonly used in urological practice, but they do have a risk of complications, such as infection and hematuria. This study explored the association between ureteral double J stent colonization and lower urinary tract symptom (LUTS) severity. Methodology This cross-sectional study was conducted from January 2021 to June 2021 in patients admitted to a tertiary care hospital in Karachi, Pakistan, who required double J stent (DJS) insertion. Patients who came to the site for stent removal were invited to participate in the study and enrolled using a consecutive sampling technique between January 15, 2021, and March 15, 2021. Results The study enrolled 176 patients, of whom 73.33% had colonization and the remaining had no colonization. The factors significantly associated with symptom severity included colonization of the DJS (P-value = 0.001) and the patients' ages (P-value = 0.046). The two groups have significantly different symptoms, which included incontinence (P-value = 0.001), polyuria (P-value = 0.001), and nocturia (P-value = 0.001). Conclusion Our study found more severe symptoms in DJS patients with colonization than in those without colonization. Irritative voiding symptoms, including nocturia and dysuria, are more common in DJS patients with colonization.

Structure Dependent Differential Modulation of Aß Fibrillization by Selenadiazole-Based Inhibitors.

Misfolding and fibrillar aggregation of Aß is a characteristic hallmark of Alzheimer's disease and primarily participates in neurodegenerative pathologies. There has been no breakthrough made in the therapeutic regime of Alzheimer's disease while the pharmacological interventions against Aß are designed to sequester and clear Aß burden from the neurological tissues. Based on the physiological relevance of Aß, therapeutic approaches are required to inhibit and stabilize Aß fibrillization, instead of cleaning it from the neurological system. In this context, we have designed a selenadiazole-based library of compounds against the fibrillization paradigm of Aß. Compounds that completely inhibited the Aß fibrillization appeared to stabilize Aß at the monomeric stage as indicated by ThT assay, CD spectrophotometry, and TEM imaging. Partial inhibitors elongated the nucleation phase and allowed limited fibrillization of Aß into smaller fragments with slightly higher ß-sheets contents, while noninhibitors did not interfere in Aß aggregation and resulted in mature fibrils with fibrillization kinetics similar to Aß control. Molecular docking revealed the different binding positions of the compounds for three classes. Complete inhibitors alleviated Aß toxicity to SH-SY5Y neuroblastoma cells and permeated across the blood-brain barrier in zebrafish larvae. The amino acid residues from Aß peptide that interacted with the compounds from all three classes were overlapping and majorly lying in the amyloidogenic regions. However, compounds that stabilize Aß monomers displayed higher association constants (Ka) and lower dissociation constants (Kd) in comparison to partial and noninhibitors, as corroborated by ITC. These results support further structure activity-based preclinical development of these selenadiazole compounds for potential anti-Alzheimer's therapy.

High-Throughput Detection of an Alkaloidal Plant Metabolome in Plant Extracts Using LC-ESI-QTOF-MS.

Plant alkaloids represent a diverse group of nitrogen-containing natural products. These compounds are considered valuable in drug discovery and development. High-throughput identification of such plant secondary metabolites in complex plant extracts is essential for drug discovery, lead optimization, and understanding the biological pathway. The present study aims to rapidly identify different classes of alkaloids in plant extracts through the liquid chromatography with electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) approach using 161 isolated and purified alkaloids. These are biologically important unique alkaloids belonging to different sub-classes such as isoquinoline, quinoline, indole, tropane, pyridine, piperidine, quinolizidine, aporphine, steroidal, and terpenoid. The majority of these are not available commercially and are known to manifest valuable biological activities. Four pools of a maximum of 50 phytostandards each were prepared, based on their log P value to minimize co-elution for rapid and cost-effective analyses. MS/MS spectra were acquired in the positive ionization mode by using their [M + H]+ and/or [M + Na]+ with both the average collisional energy (25.5-62 eV) and individual collisional energies (10, 20, 30, and 40 eV). Accurate mass, high-resolution mass spectrometry (HR-MS) data, MS/MS data, and retention times were curated for each compound. The developed LC-MS/MS method was successfully used to interrogate and fast dereplicate alkaloids in 13 medicinal plant extracts and a herbal formulation. A total of 56 alkaloids were identified based on the reference standard retention times (RTs), HR-MS spectra, and/or MS/MS spectra. The MS data have been submitted to the MetaboLights online database (MTBLS2914). The mass spectrometric and chromatographic data will be useful for the discovery of new congeners and the study of biological pathways of alkaloids in the plant kingdom.

The application of Hybrid deep learning Approach to evaluate chest ray images for the diagnosis of pneumonia in children

BackgroundPneumonia is a leading cause of morbidity and mortality worldwide, particularly among the developing nations. Pneumonia is the most common cause of death in children due to infectious etiology. Early and accurate Pneumonia diagnosis could play a vital role in reducing morbidity and mortality associated with this ailment. In this regard, the application of a new hybrid machine learning vision-based model may be a useful adjunct tool that can predict Pneumonia from chest X-ray (CXR) images. Aim & Objectivewe aimed to assess the diagnostic accuracy of hybrid machine learning vision-based model for the diagnosis of Pneumonia by evaluating chest X-ray (CXR) images Materials & MethodsA total of five thousand eight hundred and fifty-six digital X-ray images of children from ages one to five were obtained from the Chest X-Ray Pneumonia dataset using the Kaggle site. The dataset contains fifteen hundred and eighty-three digital X-ray images categorized as normal, where four thousand two hundred and seventy-three digital X-ray images are categorized as Pneumonia by an expert clinician. In this research project, a new hybrid machine learning vision-based model has been evaluated that can predict Pneumonia from chest X-ray (CXR) images. The proposed model is a hybrid of convolutional neural network and tree base algorithms (random forest and light gradient boosting machine). In this study, a hybrid architecture with four variations and two variations of ResNet architecture are employed, and a comparison is made between them. ResultsIn the present study, the analysis of digital X-ray images by four variations of hybrid architecture RN-18 RF, RN-18 LGBM, RN-34 RF, and RN-34 LGBM, along with two variations of ResNet architecture, ResNet-18 and ResNet-30 have revealed the diagnostic accuracy of 97.78%, 96.42%, 97.1%,96.59%, 95.05%, and 95.05%, respectively. DiscussionThe analysis of the present study results revealed more than 95% diagnostic accuracy for the diagnosis of Pneumonia by evaluating chest x-ray images of children with the help of four variations of hybrid architectures and two variations of ResNet architectures. Our findings are in accordance with the other published study in which the author used the deep learning algorithm Chex-Net with 121 layers. ConclusionThe hybrid machine learning vision-based model is a useful tool for the assessment of chest x rays of children for the diagnosis of Pneumonia.

Smart Pooled sample Testing for COVID-19: A Possible Solution for Sparsity of Test Kits

There is an exponential growth of COVID-19. The adaptation of preventive measures to limit the spread of infection among the people is the best solution to this health issue. The identification of infected cases and their isolation from healthy people is one of the most important preventive measures. In this regard, screening of the samples from a large number of people is needed which requires a lot of reagent kits for the detection of SARS-CoV-2. The use of smart pooled sample testing with the help of algorithms may be a quite useful strategy in the current prevailing scenario of the COVID-19 pandemic. With the help of this strategy, the optimum number of samples to be pooled for a single test may be determined based on the total positivity rate of the particular community.

The diagnostic evaluation of Convolutional NeuralNetwork (CNN) for the assessment of chest X-ray ofpatients infected with COVID-19

IntroductionThe main target of COVID-19 is the lungs where it may cause pneumonia in severely ill patients. Chest X-ray is an important diagnostic test to assess the lung for the damaging effects of COVID-19. Many other microbial pathogens can also cause damage to lungs leading to pneumonia but there are certain radiological features which can favor the diagnosis of pneumonia caused by COVID-19. With the rising number of cases of COVID-19, it would be imperative to develop computer programs which may assist the health professionals in the prevailing scenario. Materials & MethodsA total of two hundred and seventy eight (278) images of chest X-rays have been assessed by applying ResNet-50 convolutional neural network architectures in the present study. The digital images were acquired from the public repositories provided by University of Montreal and National Institutes of Health. These digital images of Chest X-rays were divided into three groups labeled as normal, pneumonia and COVID-19. The third group contains digital images of chest X-rays of patients diagnosed with COVID-19 infection while the second group contains images of lung with pneumonia caused by other pathogens. ResultsThe radiological images included in the data set are 89 images of lungs with COVID-19 infection, 93 images of lungs without any radiological abnormality and 96 images of patient with pneumonia caused by other pathogens. In this data set, 80% of the images were employed for training, and 20% for testing. A pre-trained (on ImageNet data set) ResNet-50 architecture was used to diagnose the cases of COVID-19 infections on lung X-ray images. The analysis of the data revealed that computer vision based program achieved diagnostic accuracy of 98.18 %, and F1-score of 98.19. ConclusionThe performance of convolutional neural network regarding the differentiation of pulmonary changes caused by COVID-19 from the other type of pneumonias on digital images of the chest X-rays is excellent and it may be an extremely useful adjunct tool for the health professionals.

Synthesis and identification of novel pyridazinylpyrazolone based diazo compounds as inhibitors of human islet amyloid polypeptide aggregation.

We have carried out a docking inspired synthesis and screening of a library of diazenyl-derivatives of pyridazinylpyrazolone molecules for their ability to modulate the amyloidogenic self-assembly of human islet amyloid polypeptide (hIAPP). hIAPP is a 37-residue peptide which is involved in glycemic control along with insulin. Its extracellular fibrillar assemblies in pancreatic ß-cells are responsible for type 2 diabetes. A three-step synthetic scheme was used to prepare these novel compounds using 2-(6-chloropyridazin-3-yl)-5-methyl-2,4-dihydro-3H-pyrazol-3-one as a key intermediate that was reacted with various diazo electrophiles to generate a library of compounds with yields ranging from 64 to 85%. The effect of the compounds on hIAPP amyloid fibril formation was evaluated with a thioflavin T (ThT) fluorescence-based kinetic assay. Furthermore, TEM imaging was carried out to corroborate the interactions of the compounds with hIAPP and subsequent hIAPP inhibition at the different level of fibrillization. The CD spectroscopy showed that upon incubation with SSE15314 for 12 h, the percentage of α-helices was maintained to a level of hIAPP at 0 h. The current study presents identification and characterization of SSE15314 as the hit, which completely inhibited the fibril formation and can be further optimized into a lead compound.

Outputs and Growth of Primary Care Databases in the United Kingdom: Bibliometric Analysis.

BACKGROUND: Electronic health database (EHD) data is increasingly used by researchers. The major United Kingdom EHDs are the 'Clinical Practice Research Datalink' (CPRD), 'The Health Improvement Network' (THIN) and 'QResearch'. Over time, outputs from these databases have increased, but have not been evaluated. OBJECTIVE: This study compares research outputs from CPRD, THIN and QResearch assessing growth and publication outputs over a 10-year period (2004-2013). CPRD was also reviewed separately over 20 years as a case study. METHODS:  Publications from CPRD and QResearch were extracted using the Science Citation Index (SCI) of the Thomson Scientific Institute for Scientific Information (Web of Science). THIN data was obtained from University College London and validated in Web of Science. All databases were analysed for growth in publications, the speciality areas and the journals in which their data have been published. RESULTS: These databases collectively produced 1,296 publications over a ten-year period, with CPRD representing 63.6% (n=825 papers), THIN 30.4% (n=394) and QResearch 5.9% (n=77). Pharmacoepidemiology and General Medicine were the most common specialities featured. Over the 9-year period (2004-2013), publications for THIN and QResearch have slowly increased over time, whereas CPRD publications have increased substantially in last 4 years with almost 75% of CPRD publications published in the past 9 years. CONCLUSION: These databases are enhancing scientific research and are growing yearly, however display variability in their growth. They could become more powerful research tools if the National Health Service and general practitioners can provide accurate and comprehensive data for inclusion in these databases.

Bedbugs: Helping your patient through an infestation.

Bedbugs--hematophagous parasitic arthropods of the genus Cimex--have been unwelcome bedfellows for humans for thousands of years. With increases in population density, ease of travel, and insecticide resistance, bedbugs have reemerged. As a result, physicians are often at the forefront in the diagnosis and treatment of bedbug infestation. This review summarizes the biology and epidemiology of bedbugs and provides details on the diagnosis and treatment of bedbug infestation.

Research Outputs of England's Hospital Episode Statistics (HES) Database: Bibliometric Analysis.

BACKGROUND: Hospital administrative data, such as those provided by the Hospital Episode Statistics (HES) database in England, are increasingly being used for research and quality improvement. To date, no study has tried to quantify and examine trends in the use of HES for research purposes. OBJECTIVE: To examine trends in the use of HES data for research. METHODS: Publications generated from the use of HES data were extracted from PubMed and analysed. Publications from 1996 to 2014 were then examined further in the Science Citation Index (SCI) of the Thompson Scientific Institute for Science Information (Web of Science) for details of research specialty area. RESULTS: 520 studies, categorised into 44 specialty areas, were extracted from PubMed. The review showed an increase in publications over the 18-year period with an average of 27 publications per year, however with the majority of output observed in the latter part of the study period. The highest number of publications was in the Health Statistics specialty area. CONCLUSION: The use of HES data for research is becoming more common. Increase in publications over time shows that researchers are beginning to take advantage of the potential of HES data. Although HES is a valuable database, concerns exist over the accuracy and completeness of the data entered. Clinicians need to be more engaged with HES for the full potential of this database to be harnessed.

Knowledge of Driving Vehicle Licensing Agency guidelines among NHS doctors: a multicentre observational study.

OBJECTIVES: Over half of the UK population holds a driver's licence. The DVLA have produced guidelines to ensure drivers with medical conditions drive safely. Doctors should ensure that patients are given appropriate information and advice if they have a medical condition affecting their driving. We sought to evaluate doctors' knowledge of DVLA guidelines. DESIGN: A 25-point questionnaire was designed from DVLA guidelines ('The DVLA Questionnaire'). Five questions were included for each of neurology, cardiology, drug and alcohol abuse, visual, and respiratory disorders. SETTING: Ealing Hospital, Northwick Park Hospital, Watford General Hospital, Norfolk and Norwich University Hospital and Leeds Teaching Hospitals Trust. PARTICIPANTS: 140 UK doctors. MAIN OUTCOME MEASURES: Questionnaire scores assessing knowledge of DVLA guidelines in five specialty areas. RESULTS: The median overall questionnaire score was 28%, interquartile range 20-36% and range 0-100% [Watford 28%, Leeds 30%, Norfolk and Norwich 36%, Ealing 30%, Northwick Park 28%]. There were no significant differences between the scores for each centre (p = 0.1332), Mean scores for specialty areas were: neurology 33.1%, standard deviation 22.1; cardiology 35.6%, standard deviation 26.9; drug and alcohol abuse 30.6%, standard deviation 23.8; visual disorders 33.9%, standard deviation 23.5 and respiratory disorders 20.3%, standard deviation 24.8; overall score 30.7%. There was no significant difference between the scores of the specialty areas (p = 0.4060). CONCLUSIONS: Knowledge of DVLA guidelines in our cohort was low. There is a need for increased awareness among hospital doctors through focused education on driving restrictions for common medical conditions. Improving physician knowledge in this area may help optimise patient safety.

The uses of smartphones and tablet devices in surgery: A systematic review of the literature.

BACKGROUND: Smartphones and tablet devices have become ubiquitous, and their adoption in the health care arena is growing. Reviews have looked at their utilities within medical specialties. Despite the many surgical apps available currently, there has not been a comprehensive literature review evaluating uses of these platforms within surgical disciplines. We reviewed the literature systematically in this regard. METHODS: Embase, MEDLINE, Health Management Informatics Consortium, and PsychINFO databases were searched for empiric quantitative studies evaluating interventions based in the use of smartphone or tablet device within surgical disciplines targeted at surgeons, patients, or the wider public. RESULTS: Of the 39 studies included, 24 evaluated smartphone-based interventions and 15 looked at tablet devices, whereas 30 were app-based interventions and 9 were not. A wide range of effective and innovative utilities were identified and categorized into 8 domains; Diagnostics (n = 11), telemedicine (n = 9), operative navigation (n = 6), training (n = 5), data collection (n = 3), patient education (n = 2), behavior change (n = 2), and operative planning (n = 1). CONCLUSION: This comprehensive systematic literature review of smartphone and tablet device use in surgery demonstrates a wide range of innovative utilities in the pre-, intra-, and postoperative contexts. Although results of individual studies generally were favorable, limitations in methodologies existed in many, and although studies clearly highlight the substantial potential of smartphone and tablet devices in the surgical setting, trials of greater quality will be necessary to pave the way for their widespread adoption.