ABSTRACT
Naive pluripotent stem cells have the highest developmental potential but their in vivo existence in the blastocyst is transient. Here we report a blastocyst motif substrate for the in vitro reversion of mouse and human pluripotent stem cells to a naive state. The substrate features randomly varied microstructures, which we call motifs, mimicking the geometry of the blastocyst. Motifs representing mouse-blastocyst-scaled curvature ranging between 15 and 62 mm-1 were the most efficient in promoting reversion to naivety, as determined by time-resolved correlative analysis. In these substrates, apical constriction enhances E-cadherin/RAC1 signalling and activates the mechanosensitive nuclear transducer YAP, promoting the histone modification of pluripotency genes. This results in enhanced levels of pluripotency transcription factor NANOG, which persist even after cells are removed from the substrate. Pluripotent stem cells cultured in blastocyst motif substrates display a higher development potential in generating embryoid bodies and teratomas. These findings shed light on naivety-promoting substrate design and their large-scale implementation.
ABSTRACT
MDM2 is a gene that encodes a protein involved in cell survival, growth, and DNA repair. It has been implicated in the development and progression of glioblastoma (GBM). Inhibition of the MDM2-p53 interaction has emerged as a promising strategy for treating GBM. In this study, we performed comprehensive transcriptomic expression analysis from diverse datasets and observed MDM2 overexpression in a subset of GBM cases. MDM2 negatively regulates the major onco-suppressor p53. The interaction between MDM2 and p53 is a promising target for cancer therapy, as it can trigger p53-mediated cell death in response to different stress conditions, such as oncogene activation or DNA damage. In this study, we have identified a peptide-based inhibition of MDM2 as a therapeutic strategy for GBM. We have further validated the stability of the MDM2-peptide interaction using a molecular structural dynamics approach. The major trajectories, including root mean square of deviation (RMSD), root mean square of fluctuation (RMSF), and radius of gyration (RoG), indicate that the candidate peptides have a more stable binding compared to the native ligand and control drug. The stability of the binding interaction was further estimated by MMGBSA analysis, which also suggests that MDM2 has a stable binding with both peptide molecules. Based on these results, peptides P-1843 and P-3837 could be tested further for experimental validation to confirm their targeted inhibition of MDM-2. This approach could provide a highly selective and efficient inhibitor with potentially fewer side effects and less toxicity compared to small drug-based molecules.
Subject(s)
Glioblastoma , Peptides , Proto-Oncogene Proteins c-mdm2 , Tumor Suppressor Protein p53 , Proto-Oncogene Proteins c-mdm2/antagonists & inhibitors , Proto-Oncogene Proteins c-mdm2/metabolism , Humans , Glioblastoma/drug therapy , Glioblastoma/metabolism , Glioblastoma/pathology , Tumor Suppressor Protein p53/metabolism , Tumor Suppressor Protein p53/antagonists & inhibitors , Tumor Suppressor Protein p53/genetics , Peptides/chemistry , Peptides/pharmacology , Dose-Response Relationship, Drug , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemistry , Structure-Activity Relationship , Transcriptome/drug effects , Molecular Structure , Gene Expression Profiling , Molecular Dynamics SimulationABSTRACT
PURPOSE: Aluminum fluoride-18-labeled 1,4,7-triazacyclononane-1,4,7-triacetic acid-conjugated mannosylated dextran derivative (Al[18F]F-NOTA-D10CM) is a new tracer for PET imaging. We report here on in vitro and in vivo validation of the tracer's ability to target the macrophage mannose receptor CD206. METHODS: First, the uptake of intravenously (i.v.) administered Al[18F]F-NOTA-D10CM was compared between wild-type (WT) and CD206-/- knockout (KO) mice. C57BL/6N mice were injected with complete Freund's adjuvant (CFA) in the left hind leg and the uptake of Al[18F]F-NOTA-D10CM after i.v. or intradermal (i.d.) injection was studied at 5 and 14 days after CFA induction of inflammation. Healthy C57BL/6N mice were studied as controls. Mice underwent PET/CT on consecutive days with [18F]FDG, i.v. Al[18F]F-NOTA-D10CM, and i.d. Al[18F]F-NOTA-D10CM. After the last imaging, Al[18F]F-NOTA-D10CM was i.v. injected for an ex vivo biodistribution study and autoradiography of inflamed tissues. Blood plasma samples were analyzed using high-performance liquid chromatography. To evaluate the specificity of Al[18F]F-NOTA-D10CM binding, an in vitro competitive displacement study was performed on inflamed tissue sections using autoradiography. CD206 expression was assessed by immunohistochemical staining. RESULTS: Compared with WT mice, the uptake of Al[18F]F-NOTA-D10CM was significantly lower in several CD206-/- KO mice tissues, including liver (SUV 8.21 ± 2.51 vs. 1.06 ± 0.16, P < 0.001) and bone marrow (SUV 1.63 ± 0.37 vs. 0.22 ± 0.05, P < 0.0001). The uptake of i.v. injected Al[18F]F-NOTA-D10CM was significantly higher in inflamed ankle joint (SUV 0.48 ± 0.13 vs. 0.18 ± 0.05, P < 0.0001) and inflamed foot pad skin (SUV 0.41 ± 0.10 vs. 0.04 ± 0.01, P < 0.0001) than in the corresponding tissues in healthy mice. The i.d.-injected Al[18F]F-NOTA-D10CM revealed differences between CFA-induced lymph node activation and lymph nodes in healthy mice. Ex vivo γ-counting, autoradiography, and immunohistochemistry supported the results, and a decrease of ~ 80% in the binding of Al[18F]F-NOTA-D10CM in the displacement study with excess NOTA-D10CM confirmed that tracer binding was specific. At 60 min after i.v. injection, an average 96.70% of plasma radioactivity was derived from intact Al[18F]F-NOTA-D10CM, indicating good in vivo stability. The uptake of Al[18F]F-NOTA-D10CM into inflamed tissues was positively associated with the area percentage of CD206-positive staining. CONCLUSION: The uptake of mannosylated dextran derivative Al[18F]F-NOTA-D10CM correlated with CD206 expression and the tracer appears promising for inflammation imaging.
Subject(s)
Dextrans , Fluorine Radioisotopes , Lectins, C-Type , Mannose Receptor , Mannose-Binding Lectins , Receptors, Cell Surface , Animals , Mice , Lectins, C-Type/metabolism , Receptors, Cell Surface/metabolism , Mannose-Binding Lectins/metabolism , Tissue Distribution , Dextrans/chemistry , Mannose/chemistry , Positron Emission Tomography Computed Tomography , Mice, Inbred C57BL , Macrophages/metabolism , Isotope Labeling , Heterocyclic Compounds, 1-RingABSTRACT
Cardiovascular diseases (CVDs) are known as life-threatening illnessescaused by severe abnormalities in the cardiovascular system. They are a leading cause of mortality and morbidity worldwide.Nanotechnology integrated substantialinnovations in cardiovascular diagnostic and therapeutic at the nanoscale. This in-depth analysis explores cutting-edge methods for diagnosing CVDs, including nanotechnological interventions and crucial components for identifying risk factors, developing treatment plans, and monitoring patients' progress with chronic CVDs.Intensive research has gone into making nano-carriers that can image and treat patients. To improve the efficiency of treating CVDs, the presentreview sheds light on a decision-tree-based solution by investigating recent and innovative approaches in CVD diagnosis by utilizing nanoparticles (NPs). Treatment choices for chronic diseases like CVD, whose etiology might take decades to manifest, are very condition-specific and disease-stage-based. Moreover, thisreview alsobenchmarks the changing landscape of employing NPs for targeted and better drug administration while examining the limitations of various NPs in CVD diagnosis, including cost, space, time, and complexity. To better understand and treatment of cardiovascular diseases, the conversation moves on to the nano-cardiovascular possibilities for medical research.We also focus on recent developments in nanoparticle applications, the ways they might be helpful, and the medical fields where they may find future use. Finally, this reviewadds to the continuing conversation on improved diagnosis and treatment approaches for cardiovascular disorders by discussing the obstacles and highlighting the revolutionary effects of nanotechnology.
Subject(s)
Cardiovascular Diseases , Cardiovascular System , Nanoparticles , Humans , Cardiovascular Diseases/therapy , Cardiovascular Diseases/drug therapy , Nanoparticles/therapeutic useABSTRACT
18F-Labeled [60]fullerene-based molecular spherical nucleic acids (MSNAs), consisting of a human epidermal growth factor receptor 2 (HER2) mRNA antisense oligonucleotide sequence with a native phosphodiester and phosphorothioate backbone, were synthesized, site-specifically labeled with a positron emitting fluorine-18 and intravenously administrated via tail vein to HER2 expressing HCC1954 tumor-bearing mice. The biodistribution of the MSNAs was monitored in vivo by positron emission tomography/computed tomography (PET/CT) imaging. MSNA with a native phosphodiester backbone (MSNA-PO) was prone to rapid nuclease-mediated degradation, whereas the corresponding phosphorothioate analogue (MSNA-PS) with improved enzymatic stability showed an interesting biodistribution profile in vivo. One hour after the injection, majority of the radioactivity was observed in spleen and liver but also in blood with an average tumor-to-muscle ratio of 2. The prolonged radioactivity in blood circulation may open possibilities to the targeted delivery of the MSNAs.
Subject(s)
Fullerenes , Neoplasms , Nucleic Acids , Mice , Humans , Animals , Positron Emission Tomography Computed Tomography/methods , Tissue Distribution , Positron-Emission Tomography/methods , Neoplasms/diagnostic imaging , Fluorine Radioisotopes , Cell Line, TumorABSTRACT
Nelumbo nucifera (lotus plant) is an important member of the Nelumbonaceae family. This review summarizes the studies conducted on it since the past 15 years to provide an understanding on future areas of focus. Different parts of this plant, that is, leaves, roots, and seeds, have been used as food and for the treatment of various diseases. Polysaccharides have been extracted from different parts using different methods. The manuscript reviews the methods of extraction of polysaccharides used for leaves, roots, and seeds, along with their yield. Some methods can provide better yield while some provide better biological activity with low yield. The composition and structure of extracted polysaccharides have been determined in some studies. Although monosaccharide composition has been determined in various studies, too little information about the structure of polysaccharides from N. nucifera is available in the current literature. Different useful biological activities have been explored using in vivo and in vitro methods, which include antioxidant, antidiabetic, antitumor, anti-osteoporotic, immunomodulatory, and prebiotic activities. Antitumor activity from polysaccharides of lotus leaves is yet to be explored, besides lotus root has been underexplored as compared to other parts (leaves and seeds) according to our literature survey. Studies dedicated to the successful use of combination of extraction methods can be conducted in future. The plant provides a therapeutic as well as nutraceutical potential; however, antimicrobial activity and synergistic relationships of polysaccharides from different parts of the plant need further exploration.
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Introduction: Intellectual disability (ID) is a lifelong disability that affects an individualâ§s learning capacity and adaptive behavior. Such individuals depend on their families for day-to-day survival and pose a significant challenge to the healthcare system, especially in developing countries. ID is a heterogeneous condition, and genetic studies are essential to unravel the underlying cellular pathway for brain development and functioning. Methods: Here we studied a female index patient, born to a consanguineous Pakistani couple, showing clinical symptoms of ID, ataxia, hypotonia, developmental delay, seizures, speech abnormality, and aggressive behavior. Whole exome sequencing (WES) coupled with Sanger sequencing was performed for molecular diagnosis. Further, 3D protein modeling was performed to see the effect of variant on protein structure. Results: WES identified a novel homozygous missense variant (c.178T>C; p.Tyr60His) in the ANK3 gene. In silico analysis and 3-dimensional (3D) protein modeling supports the deleterious impact of this variant on the encoding protein, which compromises the proteinâ§s overall structure and function. Conclusion: Our finding supports the clinical and genetic diversity of the ANK3 gene as a plausible candidate gene for ID syndrome. Intelligence is a complex polygenic human trait, and understanding molecular and biological pathways involved in learning and memory can solve the complex puzzle of how cognition develops. Intellectual disability (ID) is defined as a deficit in an individualâ§s learning and adaptive behavior at an early age of onset [American Psychiatric Association, 2013]. It is one of the major medical, and cognitive disorders with a prevalence of 1-3% in the population worldwide [Leonard and Wen, 2002]. ID often exists with other disabling mental conditions such as autism, attention deficit hyperactivity disorder, epilepsy, schizophrenia, bipolar disorder, or depression. Almost half of the cases appear to have a genetic explanation that ranges from cytogenetically visible abnormalities to monogenic defects [Flint, 2001; Ropers, 2010; Tucker-Drob et al., 2013]. Intellectual disability is a genetically heterogeneous condition, and more than 700 genes have been identified to cause ID alone or as a part of the syndrome. Research in X-linked ID has identified more than 100 disease-causing genes on the X chromosome that play a role in cognition; however, research into autosomal causes of ID is still ongoing [Vissers et al., 2016].
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OBJECTIVES: We determined the pulse oximetry benefit in pediatric pneumonia mortality risk stratification and chest-indrawing pneumonia in-hospital mortality risk factors. METHODS: We report the characteristics and in-hospital pneumonia-related mortality of children aged 2-59 months who were included in the Pneumonia Research Partnership to Assess WHO Recommendations dataset. We developed multivariable logistic regression models of chest-indrawing pneumonia to identify mortality risk factors. RESULTS: Among 285,839 children, 164,244 (57.5%) from hospital-based studies were included. Pneumonia case fatality risk (CFR) without pulse oximetry measurement was higher than with measurement (5.8%, 95% confidence interval [CI] 5.6-5.9% vs 2.1%, 95% CI 1.9-2.4%). One in five children with chest-indrawing pneumonia was hypoxemic (19.7%, 95% CI 19.0-20.4%), and the hypoxemic CFR was 10.3% (95% CI 9.1-11.5%). Other mortality risk factors were younger age (either 2-5 months [adjusted odds ratio (aOR) 9.94, 95% CI 6.67-14.84] or 6-11 months [aOR 2.67, 95% CI 1.71-4.16]), moderate malnutrition (aOR 2.41, 95% CI 1.87-3.09), and female sex (aOR 1.82, 95% CI 1.43-2.32). CONCLUSION: Children with a pulse oximetry measurement had a lower CFR. Many children hospitalized with chest-indrawing pneumonia were hypoxemic and one in 10 died. Young age and moderate malnutrition were risk factors for in-hospital chest-indrawing pneumonia-related mortality. Pulse oximetry should be integrated in pneumonia hospital care for children under 5 years.
Subject(s)
Malnutrition , Pneumonia , Child , Humans , Female , Infant , Child, Preschool , Hospital Mortality , Pneumonia/diagnosis , Oximetry , World Health Organization , Risk AssessmentABSTRACT
Background: The existing World Health Organization (WHO) pneumonia case management guidelines rely on clinical symptoms and signs for identifying, classifying, and treating pneumonia in children up to 5 years old. We aimed to collate an individual patient-level data set from large, high-quality pre-existing studies on pneumonia in children to identify a set of signs and symptoms with greater validity in the diagnosis, prognosis, and possible treatment of childhood pneumonia for the improvement of current pneumonia case management guidelines. Methods: Using data from a published systematic review and expert knowledge, we identified studies meeting our eligibility criteria and invited investigators to share individual-level patient data. We collected data on demographic information, general medical history, and current illness episode, including history, clinical presentation, chest radiograph findings when available, treatment, and outcome. Data were gathered separately from hospital-based and community-based cases. We performed a narrative synthesis to describe the final data set. Results: Forty-one separate data sets were included in the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) database, 26 of which were hospital-based and 15 were community-based. The PREPARE database includes 285 839 children with pneumonia (244 323 in the hospital and 41 516 in the community), with detailed descriptions of clinical presentation, clinical progression, and outcome. Of 9185 pneumonia-related deaths, 6836 (74%) occurred in children <1 year of age and 1317 (14%) in children aged 1-2 years. Of the 285 839 episodes, 280 998 occurred in children 0-59 months old, of which 129 584 (46%) were 2-11 months of age and 152 730 (54%) were males. Conclusions: This data set could identify an improved specific, sensitive set of criteria for diagnosing clinical pneumonia and help identify sick children in need of referral to a higher level of care or a change of therapy. Field studies could be designed based on insights from PREPARE analyses to validate a potential revised pneumonia algorithm. The PREPARE methodology can also act as a model for disease database assembly.
Subject(s)
Pneumonia , Male , Child , Humans , Infant , Infant, Newborn , Child, Preschool , Female , Pneumonia/drug therapy , Case Management , World Health Organization , Algorithms , ResearchABSTRACT
Clinical evidence suggests that some patients diagnosed with coronavirus disease 2019 (COVID-19) experience a variety of complications associated with significant morbidity, especially in severe cases during the initial spread of the pandemic. To support early interventions, we propose a machine learning system that predicts the risk of developing multiple complications. We processed data collected from 3,352 patient encounters admitted to 18 facilities between April 1 and April 30, 2020, in Abu Dhabi (AD), United Arab Emirates. Using data collected during the first 24 h of admission, we trained machine learning models to predict the risk of developing any of three complications after 24 h of admission. The complications include Secondary Bacterial Infection (SBI), Acute Kidney Injury (AKI), and Acute Respiratory Distress Syndrome (ARDS). The hospitals were grouped based on geographical proximity to assess the proposed system's learning generalizability, AD Middle region and AD Western & Eastern regions, A and B, respectively. The overall system includes a data filtering criterion, hyperparameter tuning, and model selection. In test set A, consisting of 587 patient encounters (mean age: 45.5), the system achieved a good area under the receiver operating curve (AUROC) for the prediction of SBI (0.902 AUROC), AKI (0.906 AUROC), and ARDS (0.854 AUROC). Similarly, in test set B, consisting of 225 patient encounters (mean age: 42.7), the system performed well for the prediction of SBI (0.859 AUROC), AKI (0.891 AUROC), and ARDS (0.827 AUROC). The performance results and feature importance analysis highlight the system's generalizability and interpretability. The findings illustrate how machine learning models can achieve a strong performance even when using a limited set of routine input variables. Since our proposed system is data-driven, we believe it can be easily repurposed for different outcomes considering the changes in COVID-19 variants over time.
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INTRODUCTION: Existing risk assessment tools to identify children at risk of hospitalised pneumonia-related mortality have shown suboptimal discriminatory value during external validation. Our objective was to derive and validate a novel risk assessment tool to identify children aged 2-59 months at risk of hospitalised pneumonia-related mortality across various settings. METHODS: We used primary, baseline, patient-level data from 11 studies, including children evaluated for pneumonia in 20 low-income and middle-income countries. Patients with complete data were included in a logistic regression model to assess the association of candidate variables with the outcome hospitalised pneumonia-related mortality. Adjusted log coefficients were calculated for each candidate variable and assigned weighted points to derive the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) risk assessment tool. We used bootstrapped selection with 200 repetitions to internally validate the PREPARE risk assessment tool. RESULTS: A total of 27 388 children were included in the analysis (mean age 14.0 months, pneumonia-related case fatality ratio 3.1%). The PREPARE risk assessment tool included patient age, sex, weight-for-age z-score, body temperature, respiratory rate, unconsciousness or decreased level of consciousness, convulsions, cyanosis and hypoxaemia at baseline. The PREPARE risk assessment tool had good discriminatory value when internally validated (area under the curve 0.83, 95% CI 0.81 to 0.84). CONCLUSIONS: The PREPARE risk assessment tool had good discriminatory ability for identifying children at risk of hospitalised pneumonia-related mortality in a large, geographically diverse dataset. After external validation, this tool may be implemented in various settings to identify children at risk of hospitalised pneumonia-related mortality.
Subject(s)
Pneumonia , Child , Humans , Income , Infant , Pneumonia/diagnosis , Risk AssessmentABSTRACT
BACKGROUND: Existing scores to identify children at risk of hospitalized pneumonia-related mortality lack broad external validation. Our objective was to externally validate three such risk scores. METHODS: We applied the Respiratory Index of Severity in Children (RISC) for HIV-negative children, the RISC-Malawi, and the Pneumonia Etiology Research for Child Health (PERCH) scores to hospitalized children in the Pneumonia REsearch Partnerships to Assess WHO REcommendations (PREPARE) data set. The PREPARE data set includes pooled data from 41 studies on pediatric pneumonia from across the world. We calculated test characteristics and the area under the curve (AUC) for each of these clinical prediction rules. RESULTS: The RISC score for HIV-negative children was applied to 3574 children 0-24 months and demonstrated poor discriminatory ability (AUC = 0.66, 95% confidence interval (CI) = 0.58-0.73) in the identification of children at risk of hospitalized pneumonia-related mortality. The RISC-Malawi score had fair discriminatory value (AUC = 0.75, 95% CI = 0.74-0.77) among 17 864 children 2-59 months. The PERCH score was applied to 732 children 1-59 months and also demonstrated poor discriminatory value (AUC = 0.55, 95% CI = 0.37-0.73). CONCLUSIONS: In a large external application of the RISC, RISC-Malawi, and PERCH scores, a substantial number of children were misclassified for their risk of hospitalized pneumonia-related mortality. Although pneumonia risk scores have performed well among the cohorts in which they were derived, their performance diminished when externally applied. A generalizable risk assessment tool with higher sensitivity and specificity to identify children at risk of hospitalized pneumonia-related mortality may be needed. Such a generalizable risk assessment tool would need context-specific validation prior to implementation in that setting.
Subject(s)
Clinical Decision Rules , Pneumonia , Child , Child Health , Humans , Malawi , Severity of Illness IndexABSTRACT
OBJECTIVES: To identify factors influencing the mortality risk in critically ill patients with COVID-19, and to develop a risk prediction score to be used at admission to intensive care unit (ICU). DESIGN: A multicentre cohort study. SETTING AND PARTICIPANTS: 1542 patients with COVID-19 admitted to ICUs in public hospitals of Abu Dhabi, United Arab Emirates between 1 March 2020 and 22 July 2020. MAIN OUTCOMES AND MEASURES: The primary outcome was time from ICU admission until death. We used competing risk regression models and Least Absolute Shrinkage and Selection Operator to identify the factors, and to construct a risk score. Predictive ability of the score was assessed by the area under the receiver operating characteristic curve (AUC), and the Brier score using 500 bootstraps replications. RESULTS: Among patients admitted to ICU, 196 (12.7%) died, 1215 (78.8%) were discharged and 131 (8.5%) were right-censored. The cumulative mortality incidence was 14% (95% CI 12.17% to 15.82%). From 36 potential predictors, we identified seven factors associated with mortality, and included in the risk score: age (adjusted HR (AHR) 1.98; 95% CI 1.71 to 2.31), neutrophil percentage (AHR 1.71; 95% CI 1.27 to 2.31), lactate dehydrogenase (AHR 1.31; 95% CI 1.15 to 1.49), respiratory rate (AHR 1.31; 95% CI 1.15 to 1.49), creatinine (AHR 1.19; 95% CI 1.11 to 1.28), Glasgow Coma Scale (AHR 0.70; 95% CI 0.63 to 0.78) and oxygen saturation (SpO2) (AHR 0.82; 95% CI 0.74 to 0.91). The mean AUC was 88.1 (95% CI 85.6 to 91.6), and the Brier score was 8.11 (95% CI 6.74 to 9.60). We developed a freely available web-based risk calculator (https://icumortalityrisk.shinyapps.io/ICUrisk/). CONCLUSION: In critically ill patients with COVID-19, we identified factors associated with mortality, and developed a risk prediction tool that showed high predictive ability. This tool may have utility in clinical settings to guide decision-making, and may facilitate the identification of supportive therapies to improve outcomes.
Subject(s)
COVID-19 , Critical Illness , Cohort Studies , Hospital Mortality , Humans , Intensive Care Units , Retrospective Studies , Risk Factors , SARS-CoV-2ABSTRACT
This study was designed to preparecarboxyl-functionalized poly (N-isopropylacrylamide) PNIPAM microgels having excellent catalytic properties.Recently, researchers are trying to fabricate cost effective and efficient hybrid catalytic materials for the synthesis of nitrogenous compounds along with enhanced optical properties. For the same motive, synthesis of carboxyl-functionalized PNIPAM microgels was performed by using polymerization of soap-free emulsion of N-isopropyl acrylamide, which is NIPAM along with acrylic acid (AA). The thiol group was introduced through the imide bond mediated by carbodiimide, between carboxyl-functionalized microgels through carboxyl group and aminoethanethiol (AET). Copper, Palladium and Cu/Pd nanoparticles were incorporated successfully into thiol-functionalized PNIPAM microgels through metals thiol linkage. The synthesized microgels and hybrid encompassing metallic nanoparticles were characterized in detail by using Transmission electron microscopy (TEM), Scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron (XPS) and Fourier transformed infrared spectroscopy for structural interpretation. The thermal properties of the pure and hybrid microgels were inspected by TG analysis. The prepared nanocomposites PNIPAM-Cu, PNIPAM-Pd and PNIPAM-Cu/Pd exhibited decent catalytic properties for the degradation of 4-Nitrophenol and methylene blue, but the bimetallic Cu/Pd have remarkable catalytic properties. The catalytic reaction followed pseudo-first-order reaction with rate constants 0.223 min-1, 0.173 min-1 for 4-Nitrophenol and methylene blue in that order. In this study,we were able to establish that Cu/Pd hybrid is an efficient catalyst for 4-Nitrophenol and methylene blue as compared to its atomic analogue.
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As an analytic tool in medicine, deep learning has gained great attention and opened new ways for disease diagnosis. Recent studies validate the effectiveness of deep learning algorithms for binary classification of skin lesions (i.e., melanomas and nevi classes) with dermoscopic images. Nonetheless, those binary classification methods cannot be applied to the general clinical situation of skin cancer screening in which multi-class classification must be taken into account. The main objective of this research is to develop, implement, and calibrate an advanced deep learning model in the context of automated multi-class classification of skin lesions. The proposed Deep Convolutional Neural Network (DCNN) model is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficacy and performance. Dermoscopic images are acquired from the International Skin Imaging Collaboration databases (ISIC-17, ISIC-18, and ISIC-19) for experiments. The experimental results of the proposed DCNN approach are presented in terms of precision, sensitivity, specificity, and other metrics. Specifically, it attains 94 % precision, 93 % sensitivity, and 91 % specificity in ISIC-17. It is demonstrated by the experimental results that this proposed DCNN approach outperforms state-of-the-art algorithms, exhibiting 0.964 area under the receiver operating characteristics (AUROC) in ISIC-17 for the classification of skin lesions and can be used to assist dermatologists in classifying skin lesions. As a result, this proposed approach provides a novel and feasible way for automating and expediting the skin lesion classification task as well as saving effort, time, and human life.
Subject(s)
Melanoma , Nevus , Skin Neoplasms , Dermoscopy , Humans , Melanoma/diagnostic imaging , Neural Networks, Computer , Skin Neoplasms/diagnostic imagingABSTRACT
Artemisia sphaerocephala Krasch (ASK) is an important member of Compositae (Asteraceae) family. Its seeds have been widely used as traditional medicine and to improve the quality of food. Water soluble and water insoluble polysaccharides are found in the seeds of this plant. Research has been conducted on the extraction of polysaccharides, their modification and determination of their structure. To date different techniques for extraction purposes have been applied which are reviewed here. Antioxidant, antidiabetic, anti-obesogenic, antitumor, and immunomodulatory activities have been explored using in vivo and in vitro methods. Moreover, these polysaccharides have been used as packaging material and as a sensing component for monitoring the freshness of packaged food. Some experimental results have shown that the quality of foods is also improved by using them as a food additive. We have also indicated some of the potential areas that are needed to be explored.
Subject(s)
Artemisia/chemistry , Food Additives/chemistry , Plant Extracts/chemistry , Polysaccharides , Seeds/chemistry , Antineoplastic Agents/chemistry , Antioxidants/chemistry , Food Packaging , Hypoglycemic Agents/chemistry , Immunologic Factors/chemistry , Molecular Structure , Polysaccharides/chemistry , Polysaccharides/isolation & purificationABSTRACT
Human infertility is considered as a serious disease of the reproductive system that affects more than 10% of couples across the globe and over 30% of the reported cases are related to men. The crucial step in the assessment of male infertility and subfertility is semen analysis that strongly depends on the sperm head morphology, i.e., the shape and size of the head of a spermatozoon. However, in medical diagnosis, the morphology of the sperm head is determined manually, and heavily depends on the expertise of the clinician. Moreover, this assessment as well as the morphological classification of human sperm heads are laborious and non-repeatable, and there is also a high degree of inter and intra-laboratory variability in the results. In order to overcome these problems, we propose a specialized convolutional neural network (CNN) architecture to accurately classify human sperm heads based on sperm images. It is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficiency and effectiveness. It is demonstrated that our proposed architecture outperforms state-of-the-art methods, exhibiting 88% recall on the SCIAN dataset in the total agreement setting and 95% recall on the HuSHeM dataset for the classification of human sperm heads. Our proposed method shows the potential of deep learning to surpass embryologists in terms of reliability, throughput, and accuracy.
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BACKGROUND AND PURPOSE: There is sparsity of quality evidence for the use of drugs after first-line benzodiazepines in convulsive status epilepticus in children. The aim of the study was to compare the clinical efficacy and safety of intravenous levetiracetam versus intravenous phenytoin as second-line drugs in the management of generalized convulsive status epilepticus in children. METHODS: This open-label randomized controlled trial was conducted in the Emergency Department of The Children's Hospital and The Institute of Child Health, Multan, Pakistan over a period of 4 years and 6 months from January 2014 to June 2018. This study included 600 children with generalized convulsive status epilepticus: 300 in the 40 mg/kg levetiracetam group, and 300 in the 20 mg/kg phenytoin group. Cessation of a clinical seizure (seizure cessation rate) within 30 minutes after the end of drug administration was the primary outcome in this study, and the presence or absence of adverse effects was noted as the secondary outcome. Data were analyzed using SPSS (version 20.0). RESULTS: The children in the levetiracetam and phenytoin were aged 3.5±0.2 and 3.4±0.2 years (mean±SD), respectively, their seizure durations before the start of treatment were 25.1±0.6 and 23.8±0.4 minutes, and their treatment efficacies were 278/300 (92.7%) and 259/300 (83.3%). Levetiracetam was significantly more effective than phenytoin (p=0.012), with no significant difference in safety. Adverse events were observed in eight children in the phenytoin group. CONCLUSIONS: Levetiracetam is significantly more effective than phenytoin for the treatment of convulsive status epilepticus in children who have failed to respond to benzodiazepines.
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The Finnish-variant late infantile neuronal ceroid lipofuscinosis, also known as CLN5 disease, is caused by mutations in the CLN5 gene. Cln5 is strongly expressed in the developing brain and expression continues into adulthood. CLN5, a protein of unknown function, is implicated in neurodevelopment but detailed investigation is lacking. Using Cln5-/- embryos of various ages and cells harvested from Cln5-/- brains we investigated the hitherto unknown role of Cln5 in the developing brain. Loss of Cln5 results in neuronal differentiation deficits and delays in interneuron development during in utero period. Specifically, the radial thickness of dorsal telencephalon was significantly decreased in Cln5-/- mouse embryos at embryonic day 14.5 (E14.5), and expression of Tuj1, an important neuronal marker during development, was down-regulated. An interneuron marker calbindin and a mitosis marker p-H3 showed down-regulation in ganglionic eminences. Neurite outgrowth was compromised in primary cortical neuronal cultures derived from E16 Cln5-/- embryos compared with WT embryos. We show that the developmental deficits of interneurons may be linked to increased levels of the repressor element 1-silencing transcription factor, which we report to bind to glutamate decarboxylase (Gad1), which encodes GAD67, a rate-limiting enzyme in the production of gamma-aminobutyric acid (GABA). Indeed, adult Cln5-/- mice presented deficits in hippocampal parvalbumin-positive interneurons. Furthermore, adult Cln5-/- mice presented deficits in hippocampal parvalbumin-positive interneurons and showed age-independent cortical hyper excitability as measured by electroencephalogram and auditory-evoked potentials. This study highlights the importance of Cln5 in neurodevelopment and suggests that in contrast to earlier reports, CLN5 disease is likely to develop during embryonic stages.
Subject(s)
Brain/growth & development , Glutamate Decarboxylase/genetics , Interneurons/metabolism , Lysosomal Membrane Proteins/genetics , Neuronal Ceroid-Lipofuscinoses/genetics , Animals , Brain/metabolism , Cell Differentiation , Cell Line , Cells, Cultured , Embryo, Mammalian/metabolism , Female , Gene Expression Regulation, Developmental , Humans , Male , Mice , Neuronal Ceroid-Lipofuscinoses/metabolism , Neurons/cytology , Neurons/metabolism , Parvalbumins/metabolism , Repressor Proteins/genetics , Tubulin/metabolismABSTRACT
BACKGROUND: Persistent pulmonary hypertension is a serious disease among new-borns. Inhaled nitric oxide is first line of therapy along with extracorporeal membrane oxygenation. Pulmonary vasodilators such as sildenafil, bosentan and milrinone are also used to treat persistent pulmonary hypertension especially in resource limited centres where inhaled nitric oxide is not available. The objective of this study was to compare the effect of sildenafil alone and sildenafil with bosentan on severity of tricuspid regurgitation and duration of hospitalization in new-borns with persistent pulmonary hypertension. METHODS: This was single blinded clinical trial conducted at The Children's Hospital & the Institute of Child Health, Multan, Pakistan, from July 2016 to December 2016. New-borns with pulmonary hypertension were admitted and divided into two groups. Group A was treated with sildenafil (2mg per kg per dose three times a day) and group B with both sildenafil (2 mg per kg per dose three times a day) and bosentan (1 mg per kg per dose twice a day). RESULTS: There were 50 new-borns in each group. The mean age, sex distribution and baseline TR measurement (mmHg) at the time of admission was similar in both the groups. Measurement of TR (mmHg) after 72 hours admission was significantly less in Group B as compared to group A (11±4.62 versus 23±4.78), p-value<0.0001. The mean duration of hospital stays (days) was 10.12±5.20 in group A and 7.56±3.77 in group B (p-value <0.0001). There was no mortality in any group and no case of hypotension in both groups. CONCLUSIONS: The combined use of sildenafil and bosentan is more effective than sildenafil alone for control of pulmonary hypertension in resource limited centres.