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Adrenoleukodystrophy (ALD) is an X linked recessive genetic disorder caused by an abnormality in the ABCD1 gene on the X chromosome, that affects 1 in 20 000 people. In X linked adrenoleukodystrophy (X-ALD), a defect in lignoceroyl-coenzyme A ligase causes pathognomonic tissue accumulation of very long chain fatty acids (VLCFA) in the adrenal cortex and nervous system. The phenotypic variability ranges from cerebral inflammatory demyelination of childhood onset, leading to death within 5 years, to adults remaining presymptomatic through more than five decades. Our case is that of a man who was previously diagnosed with bipolar affective disorder presented with dystonic posturing. During transit, he had an episode of generalised convulsive status epilepticus. He presented with spasticity and exaggerated reflexes. Three important signs of adrenal insufficiency were observed: hypotension, hyperpigmentation and comatose state. The diagnosis of X-ALD should be considered in young men presenting with gradually progressive unexplained cognitive and behavioural problems, a strong family history, adrenal insufficiency, bilateral upper motor signs with absent ankle reflexes.

Content Based Image Retrieval is ever growing technology for many applications such as medical, remote sensing, social media search engines and surveillance monitoring, etc,. Representing image content with appropriate features is tedious task using traditional low level feature extraction methods. Deep learning models achieved high precision in classification and object detection algorithms by extracting automated high level feature extraction process. This paper proposed a hybrid feature extraction technique by combining the high level features and low level features to improve the robustness of the feature vector. The proposed model used pre-trained Googlenet model as feature extractor and combined with Gabor multiscale texture features. The final feature vector will be used for retrieving the relevant image data from the large scale image dataset. It has achieved the precision of 91 percent which shows better than state of art methods.

Maxillomandibular or dental arcade arteriovenous malformations (AVMs) are uncommon lesions with potential for life-threatening bleeding. We report three cases of vascular malformations and a case of pyogenic granuloma and propose a contrast-enhanced computed tomography (CT)-based workup of these lesions for definitive treatment. Four cases of orodental bleeding were diagnosed based on CT angiography (CTA) and treated using endovascular means. Three of them were subsequently operated and confirmed by histopathology. Two were low-flow AVMs, the third one a case of pyogenic granuloma, and one high-flow AVM. The first three lesions were embolized with polyvinyl alcohol particles and subsequently operated and the fourth high-flow one embolized using liquid embolic agent n-butyl cyanoacrylate (Glue). CTA can be used to show separate lesions of arterial vascularity and those of delayed/ venous enhancing lesions. Arterial phase-enhancing lesions are again subdivided in digital subtraction angiography into those of low-to-moderate vascularity and those with high flow, which are treated using particle embolization and liquid glue/onyx (± coil) embolization, respectively. The delayed venous phase enhancing lesions may mimic neoplasms and after tissue biopsy may be managed by sclerotherapy.

Lean six sigma (LSS) is a well-structured process improvement methodology aimed at removing wastes and defects to increase the operational efficiency of a process. In this article, the authors were tasked to identify the root causes of the reworks and rejections occurring in the polycrystalline diamond (PCD) reamer line of a tool manufacturing industry and provide solutions and implement methods to overcome the rejections. Therefore, the author constructed a hybrid approach comprising the select, define, measure, map, analyse, improve, control, sustain (SDMMAICS) model to enhance the define, measure, analyse, improve, control (DMAIC) approach. Further, decision-making trial and evaluation laboratory (DEMATEL) was incorporated in the improve phase of the LSS model to ensure effective decision making. The model is backed by a KAIZEN framework to ensure the sustenance of the improvements implemented. This hybrid LSS framework was successfully applied and resulted in an increased sigma level from 3.3 to 4.3, improving the cycle time of PCD reamer production by 12%. The hybrid SDMMAICS-DEMATEL approach used is easy to follow and can be adopted in any LSS project. Moreover, the relevance of the model in a part manufacturing setup has been effectively tested and will serve as a reference for researchers in process improvement studies.

Dorsal arachnoidal webs are condensations of arachnoidal tissue densely adherent to the pial surface of the posterior aspect of the dorsal spinal cord. Infrequently described in literature they disrupt the flow of CSF in the spinal subarachnoid space leading to syringomyelia and myelopathy. While there are several theories on their origin, the “scalpel sign” on magnetic resonance imaging is considered to be pathognomonic of this condition. An illustrative case of a 58 year old man with syringomyelia and dorsal cord indentation who presented with spastic paraparesis, gait instability, parasthesias and bilateral non radicular upper limb pain that resolved following excision of the web is described to highlight the importance of considering this diagnosis when cases of so called “idiopathic” syringomyelia are encountered.

To ensure the proper functioning and performance of Industrial grade IoT devices (IIoT) in Industry 4.0 networks, it is critical to identify the capabilities and malfunctions of their component devices (e.g., sensors, actuators, and controllers) and detect potential misbehavior arising due to cyber-attacks, and misconfiguration. We envision future IoT devices embed behavioral profiles through Security-by-Contract (SxC) that are easy to validate and verify against network security policies; manufacturers to provide Manufacturer Usage Description (MUD) profiles as a manifest for the devices to signal to the network what sort of access and network functionality they require to properly function. We design authentication in the IoT onboarding process, employ blockchains to a verifiable and immutable repository to store this network manifests, that are signed and verifiable with SxC based smart contracts by the device manufacturer, or industry authority. The integrated framework combines Blockchains and SxC security contracts, MUD-based behavioral fingerprinting, and Software-Defined-Networking (SDN) for managing the security of IIoT ecosystems. Finally, the proposed scheme is validated in a simulated IoT environment on various performance parameters.

Mirror therapy is increasingly used in stroke rehabilitation to improve functional movements of the affected limb. However, the extent of mirroring in conventional mirror therapy is typically fixed (1:1) and cannot be tailored based on the patient’s impairment level. Further, the movements of the affected limb are not actively incorporated in the therapeutic process. To address these issues, we developed an immersive VR system using HTC Vive and Leap Motion, which communicates with our free and open-source software environment programmed using SteamVR and the Unity 3D gaming engine. The mirror therapy VR environment was incorporated with two novel features: (1) scalable mirroring and (2) shared control. In the scalable mirroring, mirror movements were programmed to be scalable between 0 and 1, where 0 represents no movements, 0.5 represents 50% mirroring, and 1 represents 100% mirroring. In shared control, the contribution of the mirroring limb to the movements was programmed to be scalable between 0 to 1, where 0 represents 100% contribution from the mirroring limb (i.e., no mirroring), 0.5 represents 50% of movements from the mirrored limb and 50% of movements from the mirroring limb, and 1 represents full mirroring (i.e., no shared movements). Validation experiments showed that these features worked appropriately. The proposed VR-based mirror therapy is the first fully developed system that is freely available to the rehabilitation science community. The scalable and shared control features can diversify mirror therapy and potentially augment the outcomes of rehabilitation, although this needs to be verified through future experiments.

Heart rate variability (HRV) is the rate of variability between each heartbeat with respect to time. It is used to analyse the Autonomic Nervous System (ANS), a control system used to modulate the body's unconscious action such as cardiac function, respiration, digestion, blood pressure, urination, and dilation/constriction of the pupil. This review article presents a summary and analysis of various research works that analyzed HRV associated with morbidity, pain, drowsiness, stress and exercise through signal processing and machine learning methods. The points of emphasis with regards to HRV research as well as the gaps associated with processes which can be improved to enhance the quality of the research have been discussed meticulously. Restricting the physiological signals to Electrocardiogram (ECG), Electrodermal activity (EDA), photoplethysmography (PPG), and respiration (RESP) analysis resulted in 25 articles which examined the cause and effect of increased/reduced HRV. Reduced HRV was generally associated with increased morbidity and stress. High HRV normally indicated good health, and in some instances, it could signify clinical events of interest such as drowsiness. Effective analysis of HRV during ambulatory and motion situations such as exercise, video gaming, and driving could have a significant impact toward improving social well-being. Detection of HRV in motion is far from perfect, situations involving exercise or driving reported accuracy as high as 85% and as low as 59%. HRV detection in motion can be improved further by harnessing the advancements in machine learning techniques.

Refereed/Peer-reviewed Cancer treatment is constantly evolving from a one-size-fits-all towards bespoke approaches for each patient. In certain solid cancers, including breast and lung, tumor genome profiling has been incorporated into therapeutic decision-making. For chronic phase chronic myeloid leukemia (CML), while tyrosine kinase inhibitor therapy is the standard treatment, current clinical scoring systems cannot accurately predict the heterogeneous treatment outcomes observed in patients. Biomarkers capable of segregating patients according to outcome at diagnosis are needed to improve management, and facilitate enrollment in clinical trials seeking to prevent blast crisis transformation and improve the depth of molecular responses. To this end, gene expression (GE) profiling studies have evaluated whether GE signatures at diagnosis are clinically informative. Patient material from a variety of sources has been profiled using microarrays, RNA sequencing and, more recently, single-cell RNA sequencing. However, differences in the cell types profiled, the technologies used, and the inherent complexities associated with the interpretation of genomic data pose challenges in distilling GE datasets into biomarkers with clinical utility. The goal of this paper is to review previous studies evaluating GE profiling in CML, and explore their potential as risk assessment tools for individualized CML treatment. We also review the contribution that acquired mutations, including those seen in clonal hematopoiesis, make to GE profiles, and how a model integrating contributions of genetic and epigenetic factors in resistance to tyrosine kinase inhibitors and blast crisis transformation can define a route to GE-based biomarkers. Finally, we outline a four-stage approach for the development of GE-based biomarkers in CML.

Peroxisome proliferator-activated receptors (PPARs) activity has significant implications for the development of novel therapeutic modalities against neurodegenerative diseases. Although PPAR-α, PPAR-β/δ, and PPAR-γ nuclear receptor expressions are significantly reported in the brain, their implications in brain physiology and other neurodegenerative diseases still require extensive studies. PPAR signaling can modulate various cell signaling mechanisms involved in the cells contributing to on- and off-target actions selectively to promote therapeutic effects as well as the adverse effects of PPAR ligands. Both natural and synthetic ligands for the PPARα, PPARγ, and PPARβ/δ have been reported. PPARα (WY 14.643) and PPARγ agonists can confer neuroprotection by modulating mitochondrial dynamics through the redox system. The pharmacological effect of these agonists may deliver effective clinical responses by protecting vulnerable neurons from Aβ toxicity in Alzheimer’s disease (AD) patients. Therefore, the current review delineated the ligands’ interaction with 3D-PPARs to modulate neuroprotection, and also deciphered the efficacy of numerous drugs, viz. Aβ aggregation inhibitors, vaccines, and γ -secretase inhibitors against AD; this review elucidated the role of PPAR and their receptor isoforms in neural systems, and neurodegeneration in human beings. Further, we have substantially discussed the efficacy of PPREs as potent transcription factors in the brain, and the role of PPAR agonists in neurotransmission, PPAR gamma coactivator-1α (PGC-1α) and mitochondrial dynamics in neuroprotection during AD conditions. This review concludes with the statement that the development of novel PPARs agonists may benefit patients with neurodegeneration, mainly AD patients, which may help mitigate the pathophysiology of dementia, subsequently improving overall the patient’s quality of life.

The rapid development and deployment of IoT devices in modern networks and Industry 4.0 have attracted substantial interest from cybersecurity researchers. In this study, we propose a software-defined framework that improves network intrusion detection systems by using manufacturer usage description (MUD) to enhance the behavioral monitoring in IoT networks. We aim to explore whether industrial IoT devices typically serve a common role in cyber-physical systems, and their communications exhibit predictable patterns that can be defined in MUD profile(s) formally and succinctly. We design a framework that utilizes the concept of digital twins and software-defined networking to improve the security of Industrial IoT environments. The MUD data are profiled, and the actions are evaluated on the network digital twin before they are used in the physical network. The behavioral profiling system is updated in real time, thereby improving the overall system security and compliance to policies in the IoT deployment. Evaluation results show that our solution outperforms existing approaches substantially in terms of attack detection accuracy, predicting security incidents, response time, and resource usage.

BACKGROUND: Improved understanding of the pathways associated with airway pathophysiologic features in COPD will identify new predictive biomarkers and novel therapeutic targets. RESEARCH QUESTION: Which physiologic pathways are altered in the airways of patients with COPD and will predict exacerbations? STUDY DESIGN AND METHODS: We applied a mass spectrometric panel of metabolomic biomarkers related to mucus hydration and inflammation to sputa from the multicenter Subpopulations and Intermediate Outcome Measures in COPD Study. Biomarkers elevated in sputa from patients with COPD were evaluated for relationships to measures of COPD disease severity and their ability to predict future exacerbations. RESULTS: Sputum supernatants from 980 patients were analyzed: 77 healthy nonsmokers, 341 smokers with preserved spirometry, and 562 patients with COPD (178 with Global Initiative on Chronic Obstructive Lung Disease [GOLD] stage 1 disease, 303 with GOLD stage 2 disease, and 81 with GOLD stage 3 disease) were analyzed. Biomarkers from multiple pathways were elevated in COPD and correlated with sputum neutrophil counts. Among the most significant analytes (false discovery rate, 0.1) were sialic acid, hypoxanthine, xanthine, methylthioadenosine, adenine, and glutathione. Sialic acid and hypoxanthine were associated strongly with measures of disease severity, and elevation of these biomarkers was associated with shorter time to exacerbation and improved prediction models of future exacerbations. INTERPRETATION: Biomarker evaluation implicated pathways involved in mucus hydration, adenosine metabolism, methionine salvage, and oxidative stress in COPD airway pathophysiologic characteristics. Therapies that target these pathways may be of benefit in COPD, and a simple model adding sputum-soluble phase biomarkers improves prediction of pulmonary exacerbations. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT01969344; URL: www.clinicaltrials.gov

Background: Image registration is the process of aligning two or more images in a single coordinate. Nowadays, medical image registration plays a significant role in computer-assisted disease diagnosis, treatment, and surgery. The different modalities available in the medical image make medical image registration an essential step in Computer Assisted Diagnosis (CAD), Computer- Aided Therapy (CAT) and Computer-Assisted Surgery (CAS). Problem definition: Recently, many learning-based methods were employed for disease detection and classification, but those methods were not suitable for real-time due to delayed response and the need for pre-alignment and labeling. Method: The proposed research constructed a deep learning model with Rigid transform and B-Spline transform for medical image registration for an automatic brain tumour finding. The proposed research consists of two steps. The first step uses Rigid transformation based Convolutional Neural Network and the second step uses B-Spline transform-based Convolutional Neural Network. The model is trained and tested with 3624 MR (Magnetic Resonance) images to assess the performance. The researchers believe that MR images help in the success of the treatment of patients with brain tumour. Result: The result of the proposed method is compared with the Rigid Convolutional Neural Network (CNN), Rigid CNN + Thin-Plat Spline (TPS), Affine CNN, Voxel morph, ADMIR (Affine and Deformable Medical Image Registration) and ANT(Advanced Normalization Tools) using DICE score, Average Symmetric surface Distance (ASD), and Hausdorff distance. Conclusion: The RBCNN model will help the physician to automatically detect and classify the brain tumor quickly (18 Sec) and efficiently without doing pre-alignment and labeling.

Background/Purpose As survival rates for patients with congenital diaphragmatic hernia (CDH) increase, long-term sequelae become increasingly prevalent. We present the outcomes of patients who underwent CDH repair at our institution and discuss standardization of follow-up care in our long-term multidisciplinary follow-up clinic. Methods A retrospective review of patients followed in multidisciplinary clinic after CDH repair at our institution from January 1, 2005 to December 1, 2020. Results A total of 193 patients met inclusion criteria, 73 females (37.8%) and 120 males (62.2%). Left-sided defects were most common (75.7%), followed by right-sided defects (20.7%). Median age at repair was 4 days (IQR 3–6) and 59.6% of all defects required patch repair. Median length of stay was 29 days (IQR 16.8–50.0). Median length of follow up was 49 months (IQR 17.8–95.3) with 25 patients followed for more than 12 years. Long-term outcomes included gastroesophageal reflux disease (42.0%), diaphragmatic hernia recurrence (10.9%), asthma (23.6%), neurodevelopmental delay (28.6%), attention deficit hyperactivity disorder (7.3%), autism (1.6%), chest wall deformity (15.5%), scoliosis (11.4%), and inguinal hernia (6.7%). Conclusion As survival of patients with CDH improves, long-term care must be continuously studied and fine-tuned to ensure appropriate surveillance and optimization of long-term outcomes.

Chronic obstructive pulmonary disease (COPD) is the end result of a series of dynamic and cumulative gene–environment interactions over a lifetime. The evolving understanding of COPD biology provides novel opportunities for prevention, early diagnosis, and intervention. To advance these concepts, we propose therapeutic trials in two major groups of subjects: “young” individuals with COPD and those with pre-COPD. Given that lungs grow to about 20 years of age and begin to age at approximately 50 years, we consider “young” patients with COPD those patients in the age range of 20–50 years. Pre-COPD relates to individuals of any age who have respiratory symptoms with or without structural and/or functional abnormalities, in the absence of airflow limitation, and who may develop persistent airflow limitation over time. We exclude from the current discussion infants and adolescents because of their unique physiological context and COPD in older adults given their representation in prior randomized controlled trials (RCTs). We highlight the need of RCTs focused on COPD in young patients or pre-COPD to reduce disease progression, providing innovative approaches to identifying and engaging potential study subjects. We detail approaches to RCT design, including potential outcomes such as lung function, patient-reported outcomes, exacerbations, lung imaging, mortality, and composite endpoints. We critically review study design components such as statistical powering and analysis, duration of study treatment, and formats to trial structure, including platform, basket, and umbrella trials. We provide a call to action for treatment RCTs in 1) young adults with COPD and 2) those with pre-COPD at any age.

Introduction Effective pain management in the immediate postoperative period is a crucial first step in the treatment of shoulder arthroplasty patients. Previous studies suggested that local infiltrative analgesia (LIA), specifically with Liposomal Bupivacaine (LB), is equivalent to interscalene nerve block (ISNB) for postoperative pain management. This prospective, randomized, double-blinded study seeks to measure the difference in efficacy between the 3 widely-used LIA cocktail formulations: Bupivacaine, LB, and Ropivacaine. Methods Between 2018 and 2019, 179 consecutive patients underwent reverse total shoulder arthroplasty for end-stage shoulder arthropathy. Patients were enrolled and randomized in a prospective, double-blind clinical trial to receive one of 3 LIA injections before skin incision and after skin closure: 0.25% Bupivacaine ±Epinephrine, 1.3% LB, or 0.5% Ropivacaine cocktail with Ketorolac. There were 67 patients excluded due to preoperative comorbidities or consent refusal. The eligible 112 patients were monitored for 24 hours after surgery. Mean age was 67.9 years (range: 40-90 years). The primary outcome measure was the mean preoperative Visual Analog Scale (VAS) pain score, mean postoperative VAS score during the 24-hour postoperative period, and change in mean VAS score. The secondary outcome measure was total Morphine Milligram Equivalents (MMEs) used, antiemetic use, and laxative use during the same period. Pre-hoc power analysis found a total sample size of 219 (73 per group) was estimated to detect a significant difference at 80% power and 0.05 Type I error rate. Results Use of Bupivacaine, LB, and Ropivacaine resulted in 1.2±2.9, 0.6±3.2, and 0.1±2.8 change in VAS scores, respectively (P=.32). Total postoperative MMEs used were 124.1±115.1, 116±84.5, and 105±96.7 milligrams, respectively (P=.71). There were no statistically significant differences amongst the 3 cocktails for postoperative pain relief or rate of antiemetic/laxatives used.There was a nonsignificant trend toward superior analgesic effect of Ropivacaine compared to Bupivacaine. Ad-hoc power analysis found that the estimated sample sizes required to detect a difference between the Ropivacaine and Bupivacaine treatment for change in VAS score and total MMEs use, were 321 and 1593 patients, respectively. Because of the non-clinically significant differences, continued patient enrollment was terminated. The cost of Bupivacaine was comparable to Ropivacaine ($13.43 and $21.95, respectively), whereas LB cost ($434.96) was 20-30 times higher. Conclusion There were no differences in clinical efficacy amongst Bupivacaine, LB, and Ropivacaine cocktails for perioperative pain management in shoulder arthroplasty. LB was not clinically advantageous compared to the other two medications and did not justify the increase in cost. Level of evidence Level I

This review and meta-analysis aims to assess the prognostic value of the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score for detecting necrotizing fasciitis in the extremities. The LRINEC score has been validated in multiple studies as a clinical tool for differentiating necrotizing fasciitis from non-necrotizing infections however many studies do not specify the location of infection. As the prevalence of diabetes and diabetic foot infections continues to rise, the utility of LRINEC scores in these populations becomes of increased importance. Four databases were reviewed for citations between January 2010 and December 2020. English, full text articles reporting the diagnostic effects of LRINEC were utilized in the systematic review portion of this paper. Further inclusion of 2 × 2 tables and discussion specific to the extremities were applied for citations implemented in the meta-analysis. Of the 111 results, 12 citations (n = 932) were included in this review. The diagnostic sensitivity of the LRINEC score ranged from 36% to 77% while specificity ranged from 72% to 93%. Cumulative odds ratio for LRINEC ≥6 among the 4 studies assessing extremity necrotizing fasciitis was 4.3 with p value of

RATIONALE: Whether biomarkers can be used to predict response to inhaled corticosteroids (ICS) or long-acting muscarinic antagonists (LAMA) in mild persistent asthma is unclear. OBJECTIVES: In a prespecified exploratory analysis of a randomized clinical trial of 295 participants 12 years of age or older with uncontrolled mild persistent asthma, we sought to identify biomarkers of treatment response after 12 weeks of ICS (mometasone, 200 μg or 220 μg twice/d), LAMA (tiotropium, 5 μg/d), or placebo in adults (⩾18 yr) and adolescents (12–17 yr) separately. METHODS: The primary outcome was a composite outcome of asthma control (treatment failure, asthma control days, and forced expiratory volume in 1 second [FEV(1)]). Analyses examined type 2 inflammatory biomarkers and physiologic biomarkers. We assessed the area under the receiver operating characteristic curve (AUC) for response to ICS and LAMA (each versus placebo). An AUC of 0.5 suggests no discrimination, 0.7–0.8 is considered acceptable, more than 0.8–0.9 is considered excellent, and more than 0.9 is considered outstanding. RESULTS: In 237 adults, sputum and blood eosinophil levels and fractional exhaled nitric oxide (Fe(NO)) each predicted ICS response (AUCs: 0.61 [95% confidence interval (CI), 0.53–0.69], 0.64 [95% CI, 0.56–0.72], and 0.62 [95% CI, 0.54–0.70], respectively; all P

Liver tumours are uncommon in the paediatric population, constituting 1–2 % of all paediatric tumours and 4% of all paediatric liver tumours. Hepatoblastoma followed by hepatocellular carcinoma is the most common tumours in this age group. Simultaneous development of two discrete liver tumours of distinct histologies (collision tumour) has been occasionally reported in adults but never in children. We hereby present the first reported case of hepatic collision tumours (hepatocellular carcinoma and cholangiocarcinoma) in the explant liver of a child who underwent living donor liver transplantation for end-stage liver disease and severe hepatopulmonary syndrome. The manuscript describes the clinical, radiological and histopathological findings of this case and also highlights the dilemma associated with management of this case had the diagnosis been made in the preoperative setting and also about the proposed management plan for this case in the postoperative period.

OBJECTIVES: The study aimed to explore the in vivo protective potential of rosuvastatin (ROSS), an oral antihyperlipidemic drug against doxorubicin (DOXO) induced cardio toxicity in rats. MATERIALS AND METHODS: Cardiac toxicity was induced by DOXO injection (10 mg/kg, i.p.), once on the 20(th) day of the experiment. Except for the control rats, all were received DOXO and the study was continued for up to 21 days. The influence of ROSS on acute treatment was analyzed by quantification of cardiac marker enzymes such as creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH) and liver marker enzymes like aspartate aminotransferase (AST), alanine aminotransferase (ALT) along with the measurement of in vivo antioxidants like superoxide dismutase and catalase. To observe histological changes of myocardial tissue hematoxylin and eosin staining were used. RESULTS: Acute administration of DOXO resulted in a marked rise of cardiac marker enzymes that confirms the myocardial damage compared to control animals whereas administration of ROSS (10 mg/kg, p.o.) resulted in the significant reduction of CK-MB, LDH levels (p

Summary Objective This systematic review and meta-analysis aimed to define the current evidence and systematically summarize the relevant data regarding the utility and safety of hyperbaric oxygen therapy (HBOT) as an adjunctive treatment in complicated re-operative cases of hypospadias. Method The authors systematically searched the PubMed, EMBASE, Web of Science, and Scopus databases on August 5, 2021. Patients were divided into two groups, i.e. HBOT and non-HBOT. The main outcomes were graft failure rate and the incidence of complications following urethroplasty. The proportion of patients developing adverse events due to HBOT was the secondary outcome. The pooled risk ratio and heterogeneity were calculated using the Mantel-Haenszel method and the I2 statistics respectively. The quality assessment of the included studies was performed using the Downs and Black scale. Result Four studies constituting 176 patients (101 in the HBOT group) were included (Figure). Variations were observed among these studies in terms of the age of participants, the number and types of previous operations performed, and the protocol of administration of HBOT. The graft failure rate (RR 0.19; 95% CI 0.05–0.73, p = 0.02) and the incidence of complications (RR 0.40, 95% CI 0.20–0.77, p = 0.007) were significantly low in the HBOT versus the non-HBOT group. Apart from myringotomy insertion (n = 10; 9.9%) and claustrophobia (n = 1), no other adverse events were associated with HBOT. All studies had a moderate risk of bias. An almost perfect agreement (kappa = 0.956, p Conclusion The present systematic review and meta-analysis significantly favor the administration of HBOT versus no HBOT in terms of graft failure rate and incidence of complications following urethroplasty. The available data also highlights the safety of HBOT in complicated cases of hypospadias. However, well-designed randomized controlled trials need to be conducted for an optimal comparison between the two treatment groups.

Rationale: Individuals with Chronic Obstructive Pulmonary Disease (COPD) have a high prevalence of depression, which is associated with increased COPD hospitalizations and readmissions. Objectives:...

Surgeons are traditionally categorized as working either in academic or private/community practice, but some transition between the two environments. Here, we profile current academic cardiothoracic surgeons who began their attending careers in private or community practice. We hypothesized that research activity may distinguish cardiothoracic surgeons who started in non-academic versus academic practice.Publicly available data regarding professional history and research productivity were collected for 992 academic cardiothoracic surgeons on faculty at the 77 cardiothoracic surgery training programs in the United States in 2018. Data are presented as medians analyzed with the Mann-Whitney test or proportions analyzed with Fisher exact test or the χA total of 80 (8.1%) academic cardiothoracic surgery faculty started their careers in non-academic practice, and 912 (91.9%) started directly in academia. Those who started in non-academic practice spent a median 7.0 y in private/community practice and were more likely to be cardiac surgeons (68.8% vs 51.6%, P = .0132). They were equally likely to pursue a protected research fellowship (56.3% vs 57.0%, P = .9067) and publish research during training (92.5% vs 91.1%, P = .8374), but they published fewer total papers by the end of cardiothoracic surgery fellowship (3.0 vs 7.0, P = .0001) and fewer papers per year as an academic attending (0.8 vs 2.9, P.0001). Nevertheless, the majority of cardiothoracic surgery faculty who started in non-academic practice are currently active in research (68.8%), and 2 such surgeons received National Institutes of Health R01 funding.Transitioning from non-academic to academic practice is an uncommon but feasible pathway for interested cardiothoracic surgeons.

This study quantifies the performance of an international cohort of cornea specialists in image-based differentiation of bacterial and fungal keratitis, identifying significant regional variation and establishing a reference standard for comparison against machine learning models.

Superior mesenteric arteriovenous fistula is an extremely rare vascular malformation with most cases occurring following abdominal trauma or surgery. They are often asymptomatic or present with various abdominal symptoms with or without features of portal hypertension. A 30-year-old man developed fistulising of the superior mesenteric artery into the superior mesenteric vein following bowel resection surgery for an acquired midgut volvulus. Although endovascular management remains the treatment of choice in such cases due to increased morbidity of a repeat abdominal surgery, definite risks remain, such as coil migration, which happened in this case. The open surgical approach remains the only option in such instances.

Pediatric pulmonary hypertension (PH) is a rare disease with historically very high morbidity and mortality. In the past 20 years, there has been a growing recognition that pediatric PH, although having similarities to adult PH, is a unique entity with its own particular pathogeneses, presentation, and management. With better understanding and earlier diagnosis of pediatric PH, and as more medications have become available, survival of children with PH has also significantly improved. This article reviews the various forms of PH in childhood, with a focus on both established and investigational therapies that are available for children with PH.

Background To investigate the cost-effectiveness of training lay first responders (LFRs) to address road traffic injury (RTI) in sub-Saharan Africa (SSA) as the first step toward formal emergency medical services (EMS) development. Materials/Methods Cost data from five LFR programs launched between 2008 and 2019 in SSA was collected for LFR cost estimation, including three prospective collections from our group. We systematically reviewed literature and projected aggregate disability-adjusted life years (DALYs) from RTI in SSA that are addressable by LFRs to inform cost-effectiveness ratios ($USD cost per DALY averted). Cost-effectiveness ratios were then compared against African per capita gross domestic product (GDP) to determine the cost-effectiveness of LFRs addressing RTIs in SSA, following WHO-CHOICE guidelines, which state cost-effectiveness ratios less than GDP per capita are considered “very cost-effective.” Results Average annual cost per LFR trained across five programs was calculated to be 16.32USD (training=4.04USD, supplies=12.28USD). Following WHO and Disease Control Priorities recommendations for adequate emergency catchment, initial training of 750 LFRs per 100,000 people would cost 12,239.47USD with projected total annual DALYs averted equal to 227.7 per 100,000. Cost per DALY averted would therefore be 53.75USD with appropriate LFR availability, less than sub-Saharan African GDP per capita (1,585.40USD) and the lowest sub-Saharan African GDP per capita (Burundi, 261.20USD). Conclusion Following WHO-CHOICE guidelines, training LFRs can be a highly cost-effective means to address RTI morbidity and mortality across sub-Saharan Africa. With EMS unavailable for 91.3% of the African population, training LFRs can be an affordable first step toward formal EMS development.

Line-of-sight (LOS) is a critical requirement for mmWave wireless communications. In this work, we explore the use of access point (AP) infrastructure mobility to optimize indoor mmWave WiFi network performance based on the discovery of LOS connectivity to stations (STAs). We consider a ceiling-mounted mobile (CMM) AP as the infrastructure mobility framework. Within this framework, we propose two heuristic algorithms (basic and weighted) derived from Hamming distance computation and a machine learning (ML) solution fully exploiting available network state information to address the LOS discovery problem. Based on the ML solution, we then propose a systematic solution WiMove, which can decide if and where the AP should move to for optimizing network performance. Using both ns-3 based simulation and experimental prototype implementation, we show that the throughput and fairness performance of WiMove is up to 119% and 15% better compared with single static AP and brute force search.

RATIONALE: There is currently no data supporting specific dosing and weaning strategies for parental prostanoid therapy in children with pulmonary arterial hypertension (PAH).OBJECTIVES: To describe the clinical practice of intravenous (IV) or subcutaneous (SC) prostanoid therapy in pediatric PAH and identify dosing strategies associated with favorable outcome.METHODS: From an international multicenter cohort of 275 children with PAH, 98 patients that received IV/SC prostanoid therapy were retrospectively analyzed.RESULTS: IV/SC prostanoids were given as monotherapy (20%), or combined with other PAH-targeted drugs as dual (46%) or triple therapy (34%). The median time-averaged dose was 37 ng/kg/min, ranging 2-136 ng/kg/min. During follow up, IV/SC prostanoids were discontinued and transitioned to oral or inhaled PAH-targeted therapies in 29 patients. Time-dependent ROC analyses showed specific hemodynamic criteria at discontinuation of IV/SC prostanoids (mean pulmonary arterial pressure (mPAP)25 ng/kg/min), early start after diagnosis and combination with other PAH-targeted drugs were associated with better transplant-free survival.CONCLUSIONS: Early initiation of IV/SC prostanoids, higher doses of IV/SC prostanoids and combination with additional PAH-targeted therapy were associated with favorable outcome. Transition from IV/SC prostanoid therapy to oral or inhaled therapies is safe on the long-term in selected children, identified by reaching hemodynamic criteria for durable IV/SC prostanoid discontinuation while on IV/SC prostanoid therapy.

Early identification and diagnosis of brain tumor using a supervised approach plays an essential role in the field of medicine. In this paper, an automated computer-aided method using deep learning architecture named CNN Deep net is proposed for the detection, classification and diagnosis of meningioma brain tumor. This proposed method includes preprocessing, classification, and segmentation of the primary occurring brain tumor in adults. The proposed CNN Deep Net architecture extracts the features internally from enhanced image and classifies them into normal and abnormal tumor images. The segmentation of tumor region is performed by the global thresholding with area morphological function method. This proposed method of fully automated classification and segmentation of brain tumor preserves the spatial invariance and inheritance. Furthermore, based on its feature attributes the proposed CNN Deep net classifier, classifies the detected tumor image belongs either to (low grade)benign or (high grade)malignant. This proposed CNN Deep net classification methodology approach with grading system is evaluated both quantitatively and qualitatively. The quantitative measures such as sensitivity, specificity, accuracy, Dice similarity coefficient, precision, F-score of the proposed classification and segmentation methodology states a better segmentation accuracy and classification rate of 99.4% and 99.5% with respect to ground truth images.

The project aims to develop a low-cost horizontal axis wind turbine that will reduce energy costs and reduce reliance on non-renewable resources for power generation. There are many types of commercially available wind turbine designs are present currently but they require sophisticated manufacturing using composite materials that makes it very complex hence they are very costly. Our aim is to suggest a suitable alternate to this that can cater the needs of small-scale wind turbine design having a simple and cost-effective design. For this, PVC was chosen as a material because it is readily available, inexpensive, and lightweight, allowing it to deliver more power. Our main focus was to study the feasibility of this design and have a comparison with the current industrial 3D blade designs. CFD analysis on the proposed design was conducted including parametric studies on PVC, as well as structural and modal analysis for blades with appropriate power coefficients and it is compared with the industrial 3D wind turbine blades. The analysis is carried out in such a way that the pressure distribution obtained from the CFD analysis is imported into structural analysis and used as a load boundary condition. The total deformation and equivalent stress on the blade are calculated for a design which was giving the highest efficiency from the parametric studies.

COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initiate prevention and control action, namely lockdown and qurantine. There are various mathematical and machine-learning models proposed for analyzing the spread and prediction. Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID-19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Furthermore, accurate diagnose of COVID-19 is another essential process to identify the infected person and control further spreading. As the spreading is fast, there is a need for quick auotomated diagnosis mechanism to handle large population. Deep-learning and machine-learning based diagnostic mechanism will be more appropriate for this purpose. In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.