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Abstract Background Oseltamivir (OSM) was the first active oral therapeutic inhibitor approved by the Food and Drug Administration in 1999 for the clinical management of the influenza virus. It is an ester-type prodrug of OSM carboxylate in the market under the trade name Tamiflu™ capsules, i.e., oseltamivir phosphate. Because of the ubiquitous application to alleviate influenza virus (flu virus) symptoms, it is imperative to develop systematic analytical protocols for quality control laboratories, bioequivalence, and pharmacokinetic analysis. Main body of the abstract This review provides complete state-of-the-art analytical protocols for quantifying OSM, as published in scientific journals and official compendia. Several studies use LC–MS/MS and HPLC/UV. Additionally, there are reports on UPLC, HPTLC, capillary electrophoresis, FTIR, voltammetry, potentiometry, spectrophotometric, and spectrofluorometry protocols for the drug. Many analytical protocols have also been documented to analyze OSM from environmental water, surface water, sewage discharge, the Neya River and treated sewage effluent and surface water. Conclusion The present review concludes with significant remarks on the methodology used to analyze OSM. Despite the therapeutic applicability of the drug, there are a limited number of comprehensive documents on analytical protocols for determining its concentration in various matrices. This lack of information is elusive, as the applicability and effectiveness of these protocols are crucial for ensuring the quality, efficacy, and safety of OSM.

Introduction: Fine-needle aspiration cytology (FNAC) is often used as a screening tool. Cytopathologist should be aware of various mimickers of the malignancy. One of these is infarction of benign breast lesions. Careful examination of cytomorphological features will avoid the misdiagnosis of malignancy in such cases. Material and Methods: Six cases were diagnosed as benign breast lesion for 4 years and 5 months in our newly established tertiary referral center. Histopathology follow-up was available in one case. Results: Of six cases, three cases (50%) were reported as fibroadenoma with infarction, two cases (33%) as benign breast lesion with infarction favor fibroadenoma, and one as breast lesion with infarction favor phyllodes tumor in view of recurrence. Most were in the second or third decade of their life. All cases showed dyscohesive cells with pyknotic nuclei. Monolayered sheets of necrotic cells were seen in the four cases (66%). Viable cells were seen in four cases. Conclusions: FNAC provides a rapid and accurate diagnosis of benign breast lesions with infarction in the hands of experienced pathologists who can help in better patient care. Small-sized uniform pyknotic nuclei of dyscohesive cells and regular nuclear membranes help to differentiate them from inflammatory and malignant lesions.

Abstract Background In the present era, we are facing different health problems mainly concerning with drug resistance in microorganisms as well as in cancer cells. In addition, we are also facing the problems of controlling oxidative stress and insect originated diseases like dengue, malaria, chikungunya, etc. originated from mosquitoes. In this investigation, we unfurled the potential of Achatina fulica mucus in green synthesis of mucus mediated copper oxide bio-nanocomposites (SM-CuONC) and cobalt oxide bio-nanocomposites (SM-Co3O4NC). Herein we carried out the physico-chemical characterization like UV–Vis spectra, X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Transmission electron microscopy (TEM), Energy Dispersive X-ray Analysis (EDAX) and X-ray photoelectron spectroscopy (XPS) of as synthesized bio-nanocomposites. Both the bio-nanocomposites were tested for their potential as antimicrobial activity using well diffusion assay, anticancer activity by MTT assay, antioxidant activity by phosphomolybdenum assay and mosquito larvicidal activity. Results The results of this study revealed that, SM-CuONC and SM-Co3O4NC were synthesized successfully using A. fulica mucus. The FESEM and TEM data reveal the formation of nanoparticles with quasi-spherical morphology and average particle size of ~ 18 nm for both nanocomposites. The EDAX peak confirms the presence of elemental copper and cobalt in the analyzed samples. The X-ray diffraction analysis confirmed the crystalline nature of the CuO and Co3O4. The result of anti microbial study exhibited that, SM-CuONC showed maximum antimicrobial activity against Escherichia coli NCIM 2065 and Aspergillus fumigatus NCIM 902 which were noted as 2.36 ± 0.31 and 2.36 ± 0.59 cm resp. at 60 µg/well concentration. The result of anticancer activity for SM-CuONC was exhibited as, 68.66 ± 3.72, 62.66 ± 3.61 and 71.00 ± 2.36 percent kill, while SM-Co3O4NC exhibited 61.00 ± 3.57, 72.66 ± 4.50 and 71.66 ± 4.22 percent kill against Human colon cancer (HCT-15), Cervical cancer (HeLa), and Breast cancer (MDA-MB-231) cell lines, respectively, at 20 µg/well concentration. Both the nanocomposites also exhibited better antioxidant activity. Total antioxidant activity for SM-CuONC at 50 µg/ml concentration was found to be highest as 55.33 ± 3.72 while that of SM-Co3O4Ns was 52.00 ± 3.22 mM of ascorbic acid/µg respectively. Both bio-nanocomposites also exhibited 100% mosquito larvicidal activity at concentration ranging from 40 to 50 mg/l. During cytotoxicity study it is noted that at 5 µg/well concentration, SM-CuO and SM-Co3O4NCs suspension showed more than 97% viability of normal (L929) cell lines. We also studied phytotoxicity of both bio-nanocomposites on Triticum aestivum. In this study, 100% seed germination was observed when seeds are treated with SM-CuONC and SM-Co3O4NC at 500 mg/l and 250 mg/l concentration respectively. Conclusions This study concludes that in future as synthesized SM-CuONC and SM-Co3O4NC can be used in pharmaceutical, health care system for betterment and welfare of human life as both bio-nanocomposites exhibits better antimicrobial, anticancer, antioxidant and mosquito larvicidal potential.

This paper reports the use of naturally available raw material as sugarcane bagasse (SB) to prepare cost-effective activated carbon. Activated carbon preparation from SB by using ZnCl2 was carried out by chemical activation method. The raw bagasse, its char and activated carbon were characterized on the basis of iodine number, carbon, hydrogen, nitrogen analysis, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Brunauer–Emmett–Teller (BET) surface area to check their effectiveness. During activated carbon synthesis, the impregnation ratio of SB and ZnCl2 was maintained at 1:1–1:3 and activation temperature was in the range of 600–900 °C for 1 h. From the characterization study, the highest iodine adsorption of activated carbon was found to be 1140.69 mg/g with a 1:2 ratio at 900 °C whereas char gives an iodine number of 529.63 mg/g at the same temperature. The BET surface area of raw bagasse, its char and activated carbon (SB-Zn2-900) obtained was 4.30, 514.27 and 1386.58 m2/g, respectively, which shows charrification and chemical activation improves surface area. The optimum ratio of impregnation and activation temperature was found to be 1:2 at 900 °C. In this work, activated carbon was successfully prepared and obtained product has better characteristics than previously reported studies. HIGHLIGHTS Utilization of agricultural waste material for production of value-added material such as activated carbon.; Minimizes the burden of solid waste management.; Prepared activated carbon can be utilized for pollutant removal.; Minimizes water pollution by adsorption.; Can replace expensive commercial activated carbon.;

Abstract Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and mortality. To aid providers’ decision-making, we aimed to analyze the electrocardiogram (ECG) using a deep convolutional neural network (CNN) to predict serum troponin I (TnI) from ECGs. We developed a CNN using 64,728 ECGs from 32,479 patients who underwent ECG within 2 h prior to a serum TnI laboratory result at the University of California, San Francisco (UCSF). In our primary analysis, we classified patients into groups of TnI

Objective: Current standard nonsurgical management of endometrial intraepithelial neoplasia (EIN) and grade 1 endometrioid endometrial cancer (g1EEC) is the Mirena levonorgestrel intrauterine device (M−IUD). This retrospective study was designed primarily to determine noninferiority of the Liletta IUD (L-IUD) for pathologic regression of EIN and g1EEC compared to the M−IUD at 6 months of continuous use. Secondary objectives include to determine noninferiority as above at 3, 9, and 12 months of continuous use and to identify factors including DNA mismatch repair (MMR) status associated with pathologic regression after LNG-IUD use. Methods: A retrospective observational study was performed with patients treated for EIN or g1EEC and managed continuously with M- or L-IUD. Patients with recent (within 6 months) or concurrent progesterone use were excluded. For the EIN group, the noninferiority margin of odds ratio was predetermined to be 0.58, and for the g1EEC group it was 0.64. Results: 62 patients from an academic center and a safety-net hospital were identified with continuous M−IUD (n = 44) or L-IUD (n = 18) use for EIN or g1EEC. 85% of patients treated with L-IUD were from a safety-net hospital, which had 63% with public insurance. At 3/6/9 months, 54/71/73% of patients with M−IUD and 80/83/100% with L-IUD had pathologic regression of EIN (95% confidence interval of estimated odds ratio 1.00–2.07/0.84–2.03/0.69–2.10). Lifetime smoking status, not MMR status, was significantly associated with pathologic regression. Conclusions: L-IUD is an effective fertility-sparing treatment for EIN. L-IUD is noninferior to M−IUD for pathologic regression of EIN after 3,6, and 9 months. Further larger studies are warranted to validate findings in EIN and g1EEC.

Wheat (Triticum aestivum L.) is inherently low in protein content, Zn and Fe. Boost yield gains have unwittingly reduced grain Zn and Fe, which has had negative impacts on human health. The aim of this study was to understand the inheritance of grain yield per plant and grain Fe, Zn, and protein concentrations in bread wheat (Triticum aestivum L.) under normal and late sown conditions. Half diallel crosses were performed using 10 parents. The crosses and parents were evaluated in replicated trials for the two conditions, to assess the possibility of exploiting heterosis to improve micronutrient contents. The per se performance, heterosis, combining ability, and genetic components were estimated for different characters in both environments. The results revealed that hybrid GW 451 × GW 173 exhibited better parent heterosis (BPH) and standard heterotic effects (SH) in all environments. In both sowing conditions, the general combining ability (GCA) effects of poor × poor parents also showed high specific combining ability (SCA) effects of hybrids for both the micronutrients and protein contents. However, σ2A/σ2D greater than unity confirmed the preponderance of additive gene action for protein content, and GW 173 was identified as a good general combiner for these characteristics under both environments. SCA had positive significant (P < 0.001) correlations with BPH, SH1, SH2, and the phenotype for yield component traits and grain protein, Fe, and Zn concentrations in both conditions. A supplementary approach for biofortifying wheat grainis required to prevent malnutrition.

Abstract Background The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropriateness Criteria (AC) makes it a unique resource for evidence-based clinical imaging decision support, but it is underutilized by clinicians. To facilitate the use of imaging recommendations, we develop a natural language processing (NLP) search algorithm that automatically matches clinical indications that physicians write into imaging orders to appropriate AC imaging recommendations. Methods We apply a hybrid model of semantic similarity from a sent2vec model trained on 223 million scientific sentences, combined with term frequency inverse document frequency features. AC documents are ranked based on their embeddings’ cosine distance to query. For model testing, we compiled a dataset of simulated simple and complex indications for each AC document (n = 410) and another with clinical indications from randomly sampled radiology reports (n = 100). We compare our algorithm to a custom google search engine. Results On the simulated indications, our algorithm ranked ground truth documents as top 3 for 98% of simple queries and 85% of complex queries. Similarly, on the randomly sampled radiology report dataset, the algorithm ranked 86% of indications with a single match as top 3. Vague and distracting phrases present in the free-text indications were main sources of errors. Our algorithm provides more relevant results than a custom Google search engine, especially for complex queries. Conclusions We have developed and evaluated an NLP algorithm that matches clinical indications to appropriate AC guidelines. This approach can be integrated into imaging ordering systems for automated access to guidelines.

Background: Transurethral resection of the prostate (TURP) has been the undisputed gold standard treatment for benign prostatic enlargement (BPE). However, morbidity after TURP remains significant with increased risk of bleeding and TUR syndrome. In recent years, the role of laser technology in endoscopic prostatic surgery has gradually increased. In our study, we evaluate the efficacy and safety of a novel technique of Thulium laser enucleation of prostate (THULEP) in the treatment of BPE. Materials and Methods: Five hundred and thirty-six patients with symptomatic benign prostatic hyperplasia (BPH) were treated with THULEP. The inclusion criteria were acute retention of urine with the failure of trial without catheter, dissatisfaction with medical treatment, maximum urinary flow rate (Qmax) 15. Patients were evaluated by Digital rectal examination (DRE), uroflowmetry, IPSS, prostate-specific antigen (PSA), blood and urine routine tests, abdominal ultrasonography, and trans-rectal ultrasonography (TRUS). Results: The efficacy of THULEP was assessed by comparing preoperative variables with postoperative data. IPSS score got reduced from 24 to 3.5, quality of life score improved to 0–1 from 4–5. Qmax improved from mean 7 to 20 ml/s, Postvoid residue reduced from a mean of 110 to 12 ml. Hospital stay was < 36 h in the majority of patients. The average operative time was 45 min. No postoperative blood transfusion was required. Conclusion: THULEP is a safe procedure and has a lesser number of complications. THULEP can replace monopolar TURP as a gold standard for the treatment of BPH.

Curcuma longa L., usually referred to as turmeric, is an extensively used spice throughout the world. The curcuminoids (a mixture of three components) present in turmeric, as well as their profile, determine its quality. Consequence quantification and profiling of curcuminoids are important. Total quantification and profiling of curcuminoids are commonly done using UV spectroscopy and HPLC, respectively. Today, NMR is a relatively developed area for studying food quality because of its various notable elements. However, its benefits have never been investigated in turmeric quality analysis. The current study explored the possibility of a 1H- NMR-based method for measuring curcuminoids and their profiling. This method has been cross-validated with HPLC and UV analysis. In addition, the application of the proposed method has been demonstrated in turmeric samples from various Indian states. The importance of these studies depends on the evolution of methodologies related to accessible resources.

Abstract Background A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to develop, evaluate, and deploy an NLP model that automates protocol assignment, given the clinician indication text. Methods We collected 7139 spine MRI protocols (routine or contrast) and 990 head MRI protocols (routine brain, contrast brain, or other) from a single institution. Protocols were split into training (n = 4997 for spine MRI; n = 839 for head MRI), validation (n = 1071 for spine MRI, fivefold cross-validation used for head MRI), and test (n = 1071 for spine MRI; n = 151 for head MRI) sets. fastText and XGBoost were used to develop 2 NLP models to classify spine and head MRI protocols, respectively. A Flask-based web app was developed to be deployed via Heroku. Results The spine MRI model had an accuracy of 83.38% and a receiver operator characteristic area under the curve (ROC-AUC) of 0.8873. The head MRI model had an accuracy of 85.43% with a routine brain protocol ROC-AUC of 0.9463 and contrast brain protocol ROC-AUC of 0.9284. Cancer, infectious, and inflammatory related keywords were associated with contrast administration. Structural anatomic abnormalities and stroke/altered mental status were indicative of routine spine and brain MRI, respectively. Error analysis revealed increasing the sample size may improve performance for head MRI protocols. A web version of the model is provided for demonstration and deployment. Conclusion We developed and web-deployed two NLP models that accurately predict spine and head MRI protocol assignment, which could improve radiology workflow efficiency.

Abstract Background Human immunodeficiency virus (HIV) causes severe life-threatening condition, i.e., AIDS. HIV destabilises an individual’s ability to prevent infection. Therefore, the combine medication lamivudine (LVD) and tenofovir disoproxil fumarate (TDF) are prescribed to suppress the amount of HIV infection in individual’s body; thus, the individual’s immune system could function properly. Consequently, the objective of present research work was to investigate robust and sensitive liquid chromatography avenue for simultaneous determination of lamivudine and tenofovir disoproxil fumarate in pure material and combined dosage form. Results The reversed-phase chromatographic separation has been performed through Hypersil BDS C18 column using solvent system composed of 10 mM potassium dihydrogen phosphate (pH 4.0): acetonitrile (60:40% v/v). The determination was executed at 30 oC at 1 mL/min rate for flow of solvent system through column. The eluents of column were monitored at 265 nm using Photodiode Array detector has revealed admirable retention times, i.e., 4.67 and 8.78 min for both drugs, respectively. The calibration curve demonstrated excellent linearity in the range of 10–50 μg/mL for lamivudine and tenofovir disoproxil fumarate with better determination coefficients was more than (r 2 0.999). Conclusion The estimable method was effectively validated with respect to accuracy, precision, sensitive (limit of detection and limit of quantitation), robustness, ruggedness, and for selectivity and specificity. The value less than 2 for percentage relative standard deviation for accuracy, precision, robustness, and ruggedness satisfying the acceptance criteria as per procedure of International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use.

Abstract Background Chlorthalidone is a diuretic medicinal agent used to treat hypertension. Lowering hypertension results in the prevention of strokes, heart attacks and kidney-related problems. Results In this work, the spectrophotometric investigation was employed to examine the reaction between chlorthalidone and 1, 2-naphthoquinone-4-sulfonate. A reaction is performed at the alkaline environment (pH 9.2) and heated at a moderate temperature of 60 ± 1 °C using a water bath. The red colour product was produced, and it displayed a maximum absorbance at 440.50 nm. Further, the advancement of response conditions was explored by UV/visible spectrophotometer. The stoichiometric of the reaction was considered by using Job’s plot and the reaction mechanism of the proposed work was drawn. The established approach obeyed the calibration curve in the concentration range of 2–12 μg/mL with a regression coefficient superior to 0.994. The accuracy of the method, assessed by employing the % recovery, was in the range of 99.06–99.60% with the % relative standard deviation being less than 2%. The limit of detection and limit of quantification were 0.58 μg/mL and 1.72 μg/mL, respectively. Conclusion A UV/visible spectrophotometric investigation for the analysis of the chlorthalidone in the tablet matrix was successfully established and validated. The established investigation was found to be simple and accurate, and because of its ease of use, the proposed strategy could be applied for quality control investigation of chlorthalidone in pharmaceutical matrices.

Abstract We report here an analytical method for expeditious estimation of efonidipine hydrochloride in tablet formulation with statistical screening and optimization designs using NP-HPTLC. TLC silica gel 60 F254 aluminum plates and ethyl acetate to dichloromethane to triethylamine (3:2:0.5 v/v) were chosen for chromatographic separation of efonidipine hydrochloride. The R f value for efonidipine hydrochloride turned out to be 0.35 ± 0.25 and quantitative evaluation was done at 251 nm. Plackett-Burman and face-centered central composite design (CCD) were used to obtain the most peak area and well-resolved compact band with an adequate retention factor of efonidipine hydrochloride. Plackett-Burman design at two-level with six independent variables has been employed for screening of prominent factors that affect the responses. The prominent factors have been selected and are optimized through face-centered CCD. The results obtained from face-centered CCD showed that most peak area can be obtained with development distance 8.50 cm and chamber saturation 17 min. Furthermore, the current NP-HPTLC investigation has been validated according to the ICH guidelines for accuracy, precision, sensitivity, robustness, ruggedness, and specificity. The detection and quantification limit was found that 10.41 ng and 31.57 ng, suggesting that the analysis could be accurately and precisely detected the analyte up to nanogram quantity. The current NP-HPTLC investigation is rugged, accurate, and highly sensitive and could be used for routine analysis of efonidipine hydrochloride.

Early adversity is an important risk factor that influences brain aging. Diverse animal models of early adversity, including gestational stress and postnatal paradigms disrupting dam-pup interactions evoke not only persistent neuroendocrine dysfunction and anxio-depressive behaviors, but also perturb the trajectory of healthy brain aging. The process of brain aging is thought to involve hallmark features such as mitochondrial dysfunction and oxidative stress, evoking impairments in neuronal bioenergetics. Furthermore, brain aging is associated with disrupted proteostasis, progressively defective epigenetic and DNA repair mechanisms, the build-up of neuroinflammatory states, thus cumulatively driving cellular senescence, neuronal and cognitive decline. Early adversity is hypothesized to evoke an “allostatic load” via an influence on several of the key physiological processes that define the trajectory of healthy brain aging. In this review we discuss the evidence that animal models of early adversity impinge on fundamental mechanisms of brain aging, setting up a substratum that can accelerate and compromise the time-line and nature of brain aging, and increase risk for aging-associated neuropathologies.

Improving yield is the main aim of plant breeders. In the case of bread wheat (Triticum aestivum), a major challenge in this regard is genotype–environment interactions, and a knowledge of these is required to successfully select high-yielding genotypes. In this study, graphical and numerical approaches of diallel analysis have been used to reveal such interactions. Ten different wheat genotypes were crossed using a half-diallel approach. The parents, hybrids, and standard checks were evaluated at the Regional Research Station, Anand Agricultural University, Gujarat, Anand, India under both standard and late-sown conditions in two separate years (E1 and E2 (normal-18 November 2018 and late sown-10 December 2018, respectively, Rabi 2018–2019), E3 and E4 (normal-18 November 2019 and late sown-10 December 2019, respectively, Rabi 2019–2020)). For each sowing, ‘t2’ values were calculated for eleven phenotypic characteristics: days to 50% heading, days to maturity, plant height, number of effective tillers per plant, length of main stem, number of spikelets per main spike, number of grains per main spike, grain yield per main spike, grain yield per plant, 1000-grain weight, and harvest index. Components of the gene effect revealed that the number of spikelets per main spike in E2 and E4, and the number of grains per main spike in E2 were governed by both additive and dominance gene action across the environments. Other characteristics were the greater influence of the dominance gene effect, except for days to 50% heading in E1, E2, E3, and E4; days to maturity in E2, E3, and E4; grain yield per main spike in E4. Many characteristics exhibited overdominance, an asymmetrical distribution of positive–negative, dominance–recessive genes, and narrow-sense heritability in all environments. In graphical analysis, regression value ‘b’ was unity for days to 50% heading (E1 and E4) and 1000-grain weight (E3 and E4), which revealed an absence of digenic interactions for these characteristics in the respective environments. Therefore, a given population may be improved to isolate superior recombinants for the development of desired parents in future breeding programs.

Wheat is one of the main cereals. At this time, the crucial difficulty in improving nutritional traits is the influence on genotypes of different environments. Selecting superior genotypes on the basis of a gene effects analysis for varying environments is demanded. In this study, 10 different genotypes of bread wheat (Triticum aestivum L.) were used. Parents, hybrids, and two standard checks were evaluated in a complete randomized block design with three replicates in four environments: E1 and E2 (normal and late sown, Rabi 2018-19) & E3 and E4 (normal and late sown, Rabi 2019-20). The analysis of the components of the gene effect revealed that most of the characters were governed by additive and dominant gene actions in the environments; for gluten, the wet gluten (E2) and starch (E3) content were the only dominant components (H1 and H2) with a significant gene effect. Overdominance, asymmetrical distribution of positive–negative and dominant–recessive genes, and narrow-sense heritability were observed in most of the characters in all environments. In a graphical analysis, the regression value b was observed to be in unity among protein content (E1 and E3), sedimentation value (E1, E2, and E3), and starch content (E1), indicating the absence of digenic interactions. Based on the intercept of the regression line on the Wr axis, the degree of dominance for protein content (E1 and E3), sedimentation value (E1, E2, and E3), and starch content (E1) was depicted as overdominance. Therefore, a given population may be improved to isolate superior recombinants for the development of desired parents in future breeding programs.

Abstract Background UHPLC-MS/MS is connected in various research facilities for the qualitative and quantitative investigation of a pharmaceutical substance, pharmaceutical items, and biological specimen. Main body The commence review article is an endeavor to offer pervasive awareness around assorted aspects and details about the UHPLC-MS/MS and related techniques with the aim on practice to an estimation of medicinal active agents in the last 10 years. The article also focused on isolation, separation, and characterization of present impurity in drug and biological samples. Conclusion Review article compiles a general overview of medicinally important drugs and their analysis with UHPLC-MS/MS. It gives fundamental thought regarding applications of UHPLC-MS/MS for the study on safety limit. The summary of developed UHPLC-MS/MS methods gives a contribution to the future trend and limitations in this area of research.

Abstract Background Apremilast is phosphodiesterase-4 and an immunomodulating agent used for treatment of refractory psoriatic arthritis. Methods The reversed-phase high-performance liquid-chromatography method for analysis of apremilast was developed and validated as per ICH guidelines. The separation of apremilast was performed on PrincetonSPHERE Ultima C18 column (250 mm × 4.6 mm, i.d., 5 μm particle size) with photodiode array detection carried out at 231 nm. A Box–Behnken design with response surface methodology was executed out for optimization of chromatographic conditions of reversed-phase high-performance liquid-chromatography for finished desired chromatographic separation of apremilast from its formulation with less number of experimental trials. Three independent factors, namely methanol composition in the mobile phase, pH of an aqueous phase, and flow rate, were used to construct a mathematical model and study the effects of these independent factors on responses such as retention time, theoretical plates, and tailing factor. Results Optimized experimental conditions for proposed work consists of methanol and water, pH 3.50 adjusted with ortho-phosphoric acid (70:30 % v/v) as a mobile phase at a flow rate 1 ml/min with a retention time was found to be 5.15 min. Accuracy study was completed at three different levels and was found in the range of 99.44–101.49%. Conclusion The 3D response surface graphs revealed that the methanol composition and pH of an aqueous phase were both most stringent factors affecting the responses. Thus, a new, precise, and accurate HPLC method was developed and validated and can be used for regular analysis of apremilast.

From staying quarantined at home, practicing work from home to moving outside wearing masks and carrying sanitizers, every individual has now become so adaptive to so called ‘New Normal’ post series of lockdowns across the countries. The situation triggered by novel Coronavirus has changed the behaviour of every individual towards every other living as well as non-living entity. In the Wuhan city of China, multiple cases were reported of pneumonia caused due to unknown reasons. The concerned medical authorities confirmed the cause to be Coronavirus. The symptoms seen in these cases were not much different than those seen in case of pneumonia. Earlier the research has been carried out in the field of pneumonia identification and classification through X-ray images of chest. The difficulty in identifying Covid19 infection at initial stage is due to high resemblance of its symptoms with the infection caused due to pneumonia. Hence it is trivial to well distinguish cases of coronavirus from pneumonia that may help in saving life of patients. The paper uses chest X-ray images to identify Covid19 infection in lungs using machine learning classifiers and ensembles with Gray-Level Cooccurrence Matrix (GLCM) features. The advocated methodology extracts statistical texture features from X-ray images by computing a GLCM for each image. The matrix is computed by considering various stride combinations. These GLCM features are used to train the machine learning classifiers and ensembles. The paper explores both the multiclass classification (X-ray images are classified into one of the three classes namely Covid19 affected, Pneumonia affected and normal lungs) and binary classification (Covid19 affected and other). The dataset used for evaluating performance of the method is open sourced and can be accessed easily. Proposed method being simple and computationally effective achieves noteworthy performance in terms of Accuracy, F-Measure, MCC, PPV and Sensitivity. In sum, the best stride combination of GLCM and ensemble of machine learning classifiers is suggested as vital outcome of the proposed method for effective Covid19 identification from chest X-ray images

Early adversity is a risk factor for the development of adult psychopathology. Common across multiple rodent models of early adversity is increased signaling via forebrain Gq-coupled neurotransmitter receptors. We addressed whether enhanced Gq-mediated signaling in forebrain excitatory neurons during postnatal life can evoke persistent mood-related behavioral changes. Excitatory hM3Dq DREADD-mediated chemogenetic activation of forebrain excitatory neurons during postnatal life (P2–14), but not in juvenile or adult windows, increased anxiety-, despair-, and schizophrenia-like behavior in adulthood. This was accompanied by an enhanced metabolic rate of cortical and hippocampal glutamatergic and GABAergic neurons. Furthermore, we observed reduced activity and plasticity-associated marker expression, and perturbed excitatory/inhibitory currents in the hippocampus. These results indicate that Gq-signaling-mediated activation of forebrain excitatory neurons during the critical postnatal window is sufficient to program altered mood-related behavior, as well as functional changes in forebrain glutamate and GABA systems, recapitulating aspects of the consequences of early adversity.

BackgroundHealthcare provider wellness have been reported to correlate with patient care outcomes. It is not understood whether synergistic effects may exist between them.ObjectiveWe aim to investigate three provider wellness markers and determine their associations with provider self-reported medical errors and intent-to-leave outcomes among Emergency Department (ED) providers.DesignThis is a multi-center retrospective study.MethodThree wellness domains include professional fulfillment (PF), burnout (BO), and personal resilience (PR). Two outcomes measured as provider self-reported medical errors and provider intent-to-leave. Correlations between wellness markers and outcomes were analyzed. When adjusted for other confounders (provider demographics, provider experience, and operational environment), a multivariate logistic regression analysis was performed to further determine the interactions among these three domains on provider wellness affecting patient and provider related outcomes.ResultsTotal 242 surveys were collected from providers at 16 different EDs. The median score of PF were 2.83 among physicians and 2.67 among APPs, BO were 1.00 (physicians) and 0.95 (APPs), and PR were 0.88 (physicians) and 0.81 (APPs). The median scores of self-reported medical errors were 1.50 (physicians) and 0.95 (APPs), and intent-to-leave were 1.00 (physicians and APPs). High correlations occurred among PF, BO, and PR. When analyzed together, high PF, low BO, and high PR functioned as a protective effect on provider intent-to-leave (adjusted odds ratios = 0.09, 95% CI 0.03-0.30).ConclusionHigh correlations occurred among three provider wellness markers with no significant difference between physicians and APPs. Providers with high PR, low BO, and high PR tended to be more stable in their jobs.

Cancer research is primarily dependent on rodent models. There has been a huge advancement in anticancer drug discovery in the last two decades, which is mainly due to improved animal models and introduction of non-invasive imaging technologies. Non-invasive imaging technology plays an important role in cancer and other biomedical research areas including neurology, cardiology, nanotechnology and stem cell biology. The intricate pathways in cancer initiation, progression and metastasis can be visualized and the processes can be analyzed quantitatively using these techniques. Robust preclinical data is the backbone of anticancer drug discovery, which can be obtained precisely using imaging technology. This review is focused on the dedicated preclinical imaging modalities such as Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), X-ray Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Optical imaging and Cerenkov imaging. This paper discusses their present roles in basic and translational research towards evaluation of suitability of target molecules for further clinical trials.The unique features of the imaging modalities enable them to provide information necessary for understanding structural, functional and molecular processes involved in various stages of cancer development thus bridging the gap between bench and bedside.

Anxiety disorders are amongst the most prevalent mental health disorders. Several lines of evidence have implicated cortical regions such as the medial prefrontal cortex, orbitofrontal cortex, and insular cortex along with the hippocampus in the top–down modulation of anxiety-like behaviour in animal models. Both rodent models of anxiety, as well as treatment with anxiolytic drugs, result in the concomitant activation of multiple forebrain regions. Here, we sought to examine the effects of chemogenetic activation or inhibition of forebrain principal neurons on anxiety and despair-like behaviour. We acutely activated or inhibited Ca2+/calmodulin-dependent protein kinase II α (CamKIIα)-positive forebrain excitatory neurons using the hM3Dq or the hM4Di Designer Receptor Exclusively Activated by Designer Drug (DREADD) respectively. Circuit activation was confirmed via an increase in expression of the immediate early gene, c-Fos, within both the hippocampus and the neocortex. We then examined the influence of DREADD-mediated activation of forebrain excitatory neurons on behavioural tests for anxiety and despair-like behaviour. Our results indicate that acute hM3Dq DREADD activation of forebrain excitatory neurons resulted in a significant decline in anxiety-like behaviour on the open field, light–dark avoidance, and the elevated plus maze test. In contrast, hM3Dq DREADD activation of forebrain excitatory neurons did not alter despair-like behaviour on either the tail suspension or forced swim tests. Acute hM4Di DREADD inhibition of CamKIIα-positive forebrain excitatory neurons did not modify either anxiety or despair-like behaviour. Taken together, our results demonstrate that chemogenetic activation of excitatory neurons in the forebrain decreases anxiety-like behaviour in mice.