bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diagnostic Utility of Bedside Lung Ultrasonography in Neonates with Respiratory Distress
Authors: Gupta Ravi 
Published: December 2022

Background: Lung Ultrasound (LUS) has recently become an important method for diagnostic examination and monitoring of lung disease. Many lung diseases, such as respiratory distress syndrome (RDS), transient tachypnea of the newborn (TTNB), pneumonia were diagnosed by chest X-ray, but can now easily be diagnosed with LUS. LUS has many advantages over X-ray including accuracy, reliability, low cost, radiation free, simple investigation, do multiple times, results are obtained immediately.
Objective: The aim of this study was to evaluate role of LUS in neonates with respiratory distress (RD) within 4 hours of life and to calculate the sensitivity, specificity, and negative and positive predictive value of LUS for RDS and TTNB, using an external reader blinded to the clinical condition.
Design and Methods: Neonates born at a gestation from 28 weeks to 40 weeks born in the hospital and developing RD on first 4 hours of life were enrolled. The diagnosis based on clinico-radiological features as ascertained by the treating neonatologist was considered gold standard. Just before LUS, the RD was objectively scored using Modified Silverman Andersen score. X-ray and LUS were performed bed side within 4 hours of life. Images were captured and stored and interpreted by the Radiologist who was blinded to the neonate’s clinical condition. LUS were interpreted according to observational index included pleural A lines, B lines, Air bronchogram and Lung consolidation. Based on LUS findings, differentiation between RDS, TTNB, MAS and Pneumonia were made.
Results: 100 neonates were studied. 22 infants had a final diagnosis of RDS and 64 of TTNB. LUS showed a Sn of 100% and Sp of 89.7%, with a PPV of 73.3% and a NPV of 100 % for RDS, and a Sn of 82.8% and Sp of 100% with a PPV of 100% and a NPV of 76.6% for TTNB.
Conclusion: LUS is a reliable method to diagnose RDS and TTNB in newborns with RD with high sn and sp.
Hirschsprung’s Disease: A Review of Its Management Options
Authors: Ragab Sami N. , Almetaher Hisham A. , Eisa Ahmed A. , Hassan Hussam S. , Elhalaby Essam A. 
Published: December 2022

Objectives: This article evaluates current data in literature on the definition, outcomes, and current management strategies for patients with Hirschsprung's disease (HD).
Methods: Different questions about the definition, management, and outcomes of patients with Hirschsprung's disease (HD) had been created. English-language articles published until 2022 had been gathered by searching Scopus, PubMed, Google Scholar and Web of Science.
Results: 61 manuscripts had been included in this review article. The Three well known operations which had been and still available for management of HD are: Soave, Swenson, and Duhamel operations. Transanal endorectal pull-through and laparoscopically assisted Swenson pull-through procedures for Hirschsprung’s disease offer a minimally invasive alternatives to traditional open abdominal operations.
Conclusion: The outcomes of laparoscopic assisted trans-anal or complete transanal are slightly superior to other procedures.
Advances and Development in Hybrid Polymer Composite: The Way Forward
Authors: Olowokere J. A. , Akpan U. G. , Okafor J. O. , Auta S. M. 
Published: December 2022

This paper presents the unique and outstanding properties of hybrid polymer composite (HPC). The various classification of HPC based on the combination of matrices, fibres and fillers in use are brought to bear. The different techniques/methods employed in the production of hybrid polymer composites, ranging from hot press to cold press are being discussed. It is paramount to note that the production process of HPC from start to finish is not without some inherent and external challenges, such as agglomeration of fibre, fillers and weak interfacial adhesion between fillers and matrices. Chemical modification of fibre was identified as one of the ways of proffering solution to this drawback. This study also presents a wide range of the application of HPC as enumerated in this work. The degradation of HPC as a result of natural and accelerated weathering conditions such as ultra violet (UV) rays, heat caused by high temperature, rain and humidity was also discussed. The durability and lifespan of these HPC can be strengthened and prolonged through the use of intumescents and other additives. All of these can help in improving the resistance of HPC to adverse weathering conditions.
Microbiological Control of Thirty Traditional Herbal Formulations Marketed in Divo City in the Center Western of Côte d’ivoire
Authors: Elisée Kporou Kouassi , Ehoulé Kroa , Emmanuel Diboh , Jean-Jacques Kouakou K. , Mathieu Kra A. K. , Joseph Djaman A. 
Published: December 2022

Herbal medicinal products are widely used by the population. Unfortunately, the majority of these remedies in Côte d’Ivoire were not tested for efficacy, safety and quality. This work aims to investigate the microbial quality of some traditional herbal formulations produced and sold in Divo city. For this study, 30 samples of liquid remedies were collected in 2017 and analyzed in the goal to check potential contaminations by pathogens. Microbial analysis was achieved according to method based on standard procedures for food safety in specific culture media. The results showed that the contamination level of yeasts and molds were evaluated between 1.3x104 to 7x105 CFU/g. The level of contamination of total coliforms, aerobic mesophilic flora and fecal streptococci varied from 1.5x104 to 7.5x105 CFU/g; 1.6x104 to 5x105 CFU/g then 1.6x104 to 4.3x105 CFU/g respectively. Nine (30%) of the samples were contaminated by total coliforms, one (3.33%) was contaminated by mesophilic aerobic mesophilic microorganisms, fourteen (46.66%) were contaminated by fecal streptococci and fourteen (46.66%) were contaminated by yeasts and fungi. Therefore, the use of these herbal remedies could generate risks of toxi-infection for consumers. It is necessary to train practitioners of traditional medicine on Good Manufacturing Practices in order to produce quality and safety herbal remedies for the market.
Antimicrobial Activity and Phytochemical Screening of Methanolic Leaf Extract of Vernonia amygdalina
Authors: Jarmai Adamu Hassan , Sheikh Abdullahi Mohammed , Onyiche ThankGod E. , Yunus Harun , Aji Mustapha Abba , Umar Sadiya Mohammed 
Published: December 2022

Aims: Crude methanolic leaf extract of Vernonia amygdalina was evaluated to determine its bioactive constituents, the antimicrobial properties, measure the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against some selected bacterial organisms.
Place and Duration of Study: The investigation was carried out at University of Maiduguri in Borno State, Nigeria. The herb obtained from Lake Chad Research Institute were identified and validated by the department of Forestry and wild life, Mohammet Lawan College of Agriculture (MOLCA) in Maiduguri, Borno State.
Methodology: Crude methanolic leaf extraction of the plant, qualitative phytochemical screening, antimicrobial sensitivity against some disease-causing organisms, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were carried out.
Results: Phytochemical screening of V. amygdalina leaves extract revealed the presence of tannins, saponins, terpenoids, flavonoid, carbohydrates and cardiac glycosides. The antimicrobial sensitivity shows P. aeruginosa, had the highest sensitivity with effect at all concentrations (26 mm at 1000 mg/ml), the lowest against Salmonella typhi were 9 mm at 1000 mg/ml and 7 mm at 200 mg/ml, while the highest were 17 mm at 400 mg/ml and 14 mm at 200 mg/ml. When tested at all concentrations (200-1000 mg/ml), S. aureus, S. pyogenes, B. subtilis, Corynebacteria species, and K. pneumonia showed greater sensitivity than Salmonella typhi but less sensitivity to P. aeruginosa. Based on the outcomes of the MIC and MBC results, S. aureus was found to be sensitive to the extract at 100 and 200 mg/ml, while P. aeruginosa was found to have the highest sensitivity to the extract at all concentrations (25-200 mg/ml) with the exception of 12.5 mg/ml of the extract.
Conclusion: The study highlighted the antimicrobial effects of V. amygdalina leave extracts on some pathogens thereby verifying the traditional healer’s claim. Also, it was concluded that the extract of V. amygdalina contained pharmacologically active phytochemicals which could be responsible for the numerous medicinal properties exhibited by the plant leaf extract.
Antimicrobial Sensitivity Profile of Mimosa pudica Leaf Extract and its Combination Treatment with Potassium Aluminum Sulphate on Some Bacteria
Authors: Chima Nwekeala , Amadi Lawrence O. , Ugboma C. J. 
Published: December 2022

Mimosa pudica is a famous ornamental plant commonly known as sleeping grass, sensitive plant, humble plant, shy plant and touch-me not, among other names. The study was aimed at determining the antibacterial activity of Mimosa pudica extract in combination with alum. The plant was obtained, identified, prepared and extracted using both aqueous and methanolic medium. The extracts were reconstituted to final concentration of 250g/ml, 125g/ml, 62.5g/ml (w/v). The bacterial isolates identified were; Pseudomonas aeruginosa NC002516, Staphylococcus aureus FR821779 and Escherichia coli CP031892.1 obtained from wound source at the University of Port Harcourt Teaching Hospital and maintained in stock culture and were further confirmed using biochemical and molecular methods. In-vitro bioactivity of various concentrations of the extracts and in combination with alum were evaluated by measuring diameter of inhibition zones. From the bioassay, the combinations of the aqueous extract and alum demonstrated the highest inhibitory potential; (26.00±0.00mm) at 250g/ml for Staphylococcus aureus FR821779 and the least antibacterial effect was recorded in the consortium extract for Staphylococcus aureus FR821779; (13.00±0.00mm) at same concentration compared with other bacteria (E. coli and P. aeruginosa). The result obtained showed that all the treatments and combination treatments recorded MIC at 0.50g/ml for all the bacteria studied. The composition in percentage of the various phytochemicals were as follows: Flavanoid, 7.96±1.17%, Alkaloid, 9.85±0.21%, Saponin, 7.34±0.35% and Total-phenol, 1.63±0.00%. Alkaloids (9.85±0.21%) had the highest concentrations in the extracts while Total-phenol (1.63±0.00%) was the least in concentration. This study has been able to ascertain the sensitivity profiles of Mimosa pudica leaf extracts and its combination treatment with potassium aluminium sulphate (Alum) on some microbes specifically S. aureus, E. coli, P. aeruginosa.
Anxiety Disorders
Authors: Szuhany Kristin L. , Simon Naomi M. 
Published: December 2022

ImportanceAnxiety disorders have a lifetime prevalence of approximately 34% in the US, are often chronic, and significantly impair quality of life and functioning.ObservationsAnxiety disorders are characterized by symptoms that include worry, social and performance fears, unexpected and/or triggered panic attacks, anticipatory anxiety, and avoidance behaviors. Generalized anxiety disorder (6.2% lifetime prevalence), social anxiety disorder (13% lifetime prevalence), and panic disorder (5.2% lifetime prevalence) with or without agoraphobia are common anxiety disorders seen in primary care. Anxiety disorders are associated with physical symptoms, such as palpitations, shortness of breath, and dizziness. Brief screening measures applied in primary care, such as the Generalized Anxiety Disorder–7, can aid in diagnosis of anxiety disorders (sensitivity, 57.6% to 93.9%; specificity, 61% to 97%). Providing information about symptoms, diagnosis, and evidence-based treatments is a first step in helping patients with anxiety. First-line treatments include pharmacotherapy and psychotherapy. Selective serotonin reuptake inhibitors (SSRIs, eg, sertraline) and serotonin-norepinephrine reuptake inhibitors (SNRIs, eg, venlafaxine extended release) remain first-line pharmacotherapy for generalized anxiety disorder, social anxiety disorder, and panic disorder. Meta-analyses suggest that SSRIs and SNRIs are associated with small to medium effect sizes compared with placebo (eg, generalized anxiety disorder: standardized mean difference [SMD], −0.55 [95% CI, −0.64 to −0.46]; social anxiety disorder: SMD, −0.67 [95% CI, −0.76 to −0.58]; panic disorder: SMD, −0.30 [95% CI, −0.37 to −0.23]). Cognitive behavioral therapy is the psychotherapy with the most evidence of efficacy for anxiety disorders compared with psychological or pill placebo (eg, generalized anxiety disorder: Hedges g = 1.01 [large effect size] [95% CI, 0.44 to 1.57]; social anxiety disorder: Hedges g = 0.41 [small to medium effect] [95% CI, 0.25 to 0.57]; panic disorder: Hedges g = 0.39 [small to medium effect[ [95% CI, 0.12 to 0.65]), including in primary care. When selecting treatment, clinicians should consider patient preference, current and prior treatments, medical and psychiatric comorbid illnesses, age, sex, and reproductive planning, as well as cost and access to care.Conclusions and RelevanceAnxiety disorders affect approximately 34% of adults during their lifetime in the US and are associated with significant distress and impairment. First-line treatments for anxiety disorders include cognitive behavioral therapy, SSRIs such as sertraline, and SNRIs such as venlafaxine extended release.
Development and Validation of a Machine Learning Model to Estimate Risk of Adverse Outcomes Within 30 Days of Opioid Dispensation
Authors: Sharma Vishal , Kulkarni Vinaykumar , Jess Ed , Gilani Fizza , Eurich Dean , Simpson Scot H. , Voaklander Don , Semenchuk Michael , London Connor , Samanani Salim 
Published: December 2022

ImportanceMachine learning approaches can assist opioid stewardship by identifying high-risk opioid prescribing for potential interventions.ObjectiveTo develop a machine learning model for deployment that can estimate the risk of adverse outcomes within 30 days of an opioid dispensation as a potential component of prescription drug monitoring programs using access to real-world data.Design, Setting, and ParticipantsThis prognostic study used population-level administrative health data to construct a machine learning model. This study took place in Alberta, Canada (from January 1, 2018, to December 31, 2019), and included all patients 18 years and older who received at least 1 opioid dispensation from a community pharmacy within the province.ExposuresEach opioid dispensation served as the unit of analysis.Main Outcomes and MeasuresOpioid-related adverse outcomes were identified from administrative data sets. An XGBoost model was developed on 2018 data to estimate the risk of hospitalization, an emergency department visit, or mortality within 30 days of an opioid dispensation; validation on 2019 data was done to evaluate model performance. Model discrimination, calibration, and other relevant metrics are reported using daily and weekly predictions on both ranked predictions and predicted probability thresholds using all data from 2019.ResultsA total of 853 324 participants represented 6 181 025 opioid dispensations, with 145 016 outcome events reported (2.3%); 46.4% of the participants were men and 53.6% were women, with a mean (SD) age of 49.1 (15.6) years for men and 51.0 (18.0) years for women. Of the outcome events, 77 326 (2.6% pretest probability) occurred within 30 days of a dispensation in the validation set (XGBoost C statistic, 0.82 [95% CI, 0.81-0.82]). The top 0.1 percentile of estimated risk had a positive likelihood ratio (LR) of 28.7, which translated to a posttest probability of 43.1%. In our simulations, the weekly measured predictions had higher positive LRs in both the highest-risk dispensations and percentiles of estimated risk compared with predictions measured daily. Net benefit analysis showed that using machine learning prediction may not add additional benefit over the entire range of probability thresholds.Conclusions and RelevanceThese findings suggest that prescription drug monitoring programs can use machine learning classifiers to identify patients at risk of opioid-related adverse outcomes and intervene on high-risk ranked predictions. Better access to available administrative and clinical data could improve the prediction performance of machine learning classifiers and thus expand opioid stewardship efforts.
Tough, Bio‐disintegrable and Stretchable Substrate Reinforced with Nanofibers for Transient Wearable Electronics
Authors: Ghosh Gargi , Bag Atanu , Hanif Adeela , Meeseepong Montri , Lee Yu Rim , Lee Nae‐Eung 
Published: December 2022

AbstractResearch on transient wearable electronics with stretchable components is of increasing interest because of their abilities to conform seamlessly to human tissues and, more interestingly, disappear from the environment when disposed. To wear them comfortably, their component materials must be pliable, tough, stretchable, biocompatible, and disintegrable. However, most biodegradable materials are not stretchable or tough, limiting their use in transient wearable electronics. Herein, these challenges are addressed by demonstrating a biodegradable nanofiber (NF)‐reinforced water‐borne polyurethane (NFR‐WPU) with stretchability, toughness, and partial biodegradability by embedding biodegradable composite NFs of poly(glycerol sebacate): poly(vinyl alcohol) (PGS:PVA) into the WPU matrix, thus rendering its properties tunable. An optimal loading amount of NFs into the NFR‐WPU significantly enhanced the toughness by 19 times while maintaining the Young's modulus as low as 3.3 MPa. Furthermore, the NFR‐WPU substrate has very high fracture toughness and shows excellent biocompatibility. Moreover, the NFR‐WPU has a disintegration rate nine times greater than that of pristine WPU. Finally, disintegrable and stretchable triboelectric and capacitive touch sensors on the NFR‐WPU are fabricated and demonstrated for potential use in transient wearable electronics.
Accurate Magneto‐Driven Multi‐Dimensional Droplet Manipulation
Authors: Jing Xueshan , Chen Huawei , Zhang Liwen , Zhao Song , Wang Yan , Wang Zelinlan , Zhou Yu 
Published: December 2022

AbstractDroplet manipulation has gradually drawn worldwide attention through diverse potential applications such as microfluidics, and medical diagnostic test. Whereas, the high‐precision liquid manipulation on an open surface that is under control at will is still a huge challenge, especially in 3D. Herein, the novel magnetic micropillars array (MMA) is developed for multi‐dimensional droplet manipulation, depending on huge symmetric bending deformation under the low magnetic field. In situ observation demonstrated the droplet's behavior and the driving force acted on the droplet is derived from these micropillar's deformation. Two modes, that are, propelling mode and rolling mode are found in horizontal transport that determined by the relative position of crest and droplets and can be transported with excellent accuracy and rapidity. The recombination of the contact liquid between droplets and micropillars occurs in swinging to dynamically adjust the length of the three‐phase contact line, which is the main reason for capture‐release behavior. Theoretical models of multi‐dimensional droplet manipulation are systematically established to demonstrate the underlying mechanism. Finally, several MMA‐based operating platforms are built to validate its feasibility in accurate 3D droplet manipulation and exhibit great potential in chemical micro‐reactions, bioassays, and the medical field.
Recent Advances in MXene‐Based Aerogels: Fabrication, Performance and Application
Authors: Wei Chunxiang , Zhang Quangang , Wang Zhen , Yang Wenjie , Lu Hongdian , Huang Zehuan , Yang Wei , Zhu Jixin 
Published: December 2022

AbstractAs one of the “miracle materials” in the 21st century, aerogels with ultra‐low weight and remarkable mechanical performance have emerged and shown incredible immunity to harsh working environments, attracting substantial research interests across a wide range of areas. Recently, exploitation of MXene nanosheets into aerogels represents a new research focus in the field of materials science, on account of their unique structures and outstanding properties. In this review, the aim is to provide a timely and insightful overview for the recent advances in the fabrication, performance, and application of MXene‐based aerogels. The main strategies for constructing MXene‐based aerogels, directly from MXene‐dispersion or in the presence of other functional components, are summarized. Furthermore, the desirable performance of MXene‐based aerogels and their related applications in the areas including electromagnetic management, sensors, solar steam generators, and energy storage are highlighted. A thorough investigation and comparison of their mechanical, electrical, sensing, and other properties are performed to understand the structure‐property relationships. At last, this study is concluded with summary and outlook section on the future development as well as challenges that remained, thus bringing new research opportunities for the material engineering and functional application of MXene‐based aerogels.
Phase‐Separated Liposomes Hijack Endogenous Lipoprotein Transport and Metabolism Pathways to Target Subsets of Endothelial Cells In Vivo
Authors: Arias‐Alpizar Gabriela , Papadopoulou Panagiota , Rios Xabier , Pulagam Krishna Reddy , Moradi Mohammad‐Amin , Pattipeiluhu Roy , Bussmann Jeroen , Sommerdijk Nico , Llop Jordi , Kros Alexander , Campbell Frederick 
Published: December 2022

AbstractPlasma lipid transport and metabolism are essential to ensure correct cellular function throughout the body. Dynamically regulated in time and space, the well‐characterized mechanisms underpinning plasma lipid transport and metabolism offers an enticing, but as yet underexplored, rationale to design synthetic lipid nanoparticles with inherent cell/tissue selectivity. Herein, a systemically administered liposome formulation, composed of just two lipids, that is capable of hijacking a triglyceride lipase‐mediated lipid transport pathway resulting in liposome recognition and uptake within specific endothelial cell subsets is described. In the absence of targeting ligands, liposome‐lipase interactions are mediated by a unique, phase‐separated (“parachute”) liposome morphology. Within the embryonic zebrafish, selective liposome accumulation is observed at the developing blood‐brain barrier. In mice, extensive liposome accumulation within the liver and spleen – which is reduced, but not eliminated, following small molecule lipase inhibition – supports a role for endothelial lipase but highlights these liposomes are also subject to significant “off‐target” by reticuloendothelial system organs. Overall, these compositionally simplistic liposomes offer new insights into the discovery and design of lipid‐based nanoparticles that can exploit endogenous lipid transport and metabolism pathways to achieve cell selective targeting in vivo.