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Diagnostic and decision-making processes in the 2019 Coronavirus treatment have combined new standards using patient chest images, clinical and laboratory data. This work presents a systematic review aimed at studying the Artificial Intelligence (AI) approaches to the patients’ diagnosis or evolution with Coronavirus 2019. Five electronic databases were searched, from December 2019 to October 2020, considering the beginning of the pandemic when there was no vaccine influencing the exploration of Artificial Intelligence-based techniques. The first search collected 839 papers. Next, the abstracts were reviewed, and 138 remained after the inclusion/exclusion criteria was performed. After thorough reading and review by a second group of reviewers, 64 met the study objectives. These papers were carefully analyzed to identify the AI techniques used to interpret the images, clinical and laboratory data, considering a distribution regarding two variables: (i) diagnosis or outcome and (ii) the type of data: clinical, laboratory, or imaging (chest computed tomography, chest X-ray, or ultrasound). The data type most used was chest CT scans, followed by chest X-ray. The chest CT scan was the only data type that was used for diagnosis, outcome, or both. A few works combine Clinical and Laboratory data, and the most used laboratory tests were C-reactive protein. AI techniques have been increasingly explored in medical image annotation to overcome the need for specialized manual work. In this context, 25 machine learning (ML) techniques with a highest frequency of usage were identified, ranging from the most classic ones, such as Logistic Regression, to the most current ones, such as those that explore Deep Learning. Most imaging works explored convolutional neural networks (CNN), such as VGG and Resnet. Then transfer learning which stands out among the techniques related to deep learning has the second highest frequency of use. In general, classification tasks adopted two or three datasets. COVID-19 related data is present in all papers, while pneumonia is the most common non-COVID-19 class among them.

Structural diversity drives multiple biological activities and mechanisms of action in linear peptides. Here we describe an unusual N-capping asparagine-lysine-proline (NKP) motif that confers a hybrid multifunctional scaffold to a computationally designed peptide (PaDBS1R7). PaDBS1R7 has a shorter α-helix segment than other computationally designed peptides of similar sequence but with key residue substitutions. Although this motif acts as an α-helix breaker in PaDBS1R7, the Asn5 presents exclusive N-capping effects, forming a belt to establish hydrogen bonds for an amphipathic α-helix stabilization. The combination of these different structural profiles was described as a coil/N-cap/α-helix scaffold, which was also observed in diverse computational peptide mutants. Biological studies revealed that all peptides displayed antibacterial activities. However, only PaDBS1R7 displayed anticancer properties, eradicated

This work is aimed at demonstrating the advantages that AI can bring to dam management and which parameters and calculations are important to make the simulations more realistic. To this end, a computational approach that combines a Multilayer Perceptron Artificial Neural Network (MLP-ANN) and Monte Carlo Simulation (MCS) method was developed and tested in simulations of floodgate operation using data collected from one of the biggest sanitation companies in the world. The conducted systematic review and simulations allowed to demonstrate the contributions of this study to the scientific literature and organizational practice, mainly because it shows that the application of the proposed approach can eliminates the need for manual operations in dams, including those aimed at preventing disasters and water wastage.

Since the COVID-19 pandemic emerged, vaccination has been the core strategy to mitigate the spread of SARS-CoV-2 in humans. This paper analyzes the impact of COVID-19 vaccination on hospitalizations and deaths in the state of Rio Grande do Norte, Brazil. We analyzed data from 23,516 hospitalized COVID-19 patients diagnosed between April 2020 and August 2021. We excluded the data from patients hospitalized through direct occupancy, unknown outcomes, and unconfirmed COVID-19 cases, resulting in data from 12,635 patients cross-referenced with the immunization status during hospitalization. Our results indicated that administering at least one dose of the immunizers was sufficient to significantly reduce the occurrence of moderate and severe COVID-19 cases among patients under 59 years. Considering the partially or fully immunized patients, the mean age is similar between the analyzed groups, despite the occurrence of comorbidities and higher than that observed among not immunized patients. Thus, immunized patients present lower Unified Score for Prioritization (USP) levels when diagnosed with COVID-19. Our data suggest that COVID-19 vaccination significantly reduced the hospitalization and death of elderly patients (60+ years) after administration of at least one dose. Comorbidities do not change the mean age of moderate/severe COVID-19 cases and the days required for the hospitalization of these patients.

The paper mostly summarizes disperse contributions of the authors published during the last fifteen years on the scour depth at single piers. These contributions rely on unique experiments in the sense that they are systematically longer than most of those found in the literature. The characterization of the effects of flow intensity, relative sand size, flow shallowness, time and pier shape and alignment is significantly improved as compared with existing literature. Our contributions consist on refinements of the model suggested by the school of Auckland, initiated by Raudkivi and boosted by Melville and his students. A considerable number of empirical equations and charts expresses those contributions.

Background Crohn’s disease has the potential to involve all segments of the gastrointestinal tract, requiring frequent and judicious clinical and endoscopic surveillance. Capsule endoscopy (CE) has revolutionized the management of these patients, playing a role in diagnosis, classification, and assessment of response to treatment. In 2017, PillCam™ Crohn’s Capsule (PCC) was introduced to provide a panenteric assessment to this panenteric disease. However, reviewing each PCC exam is time-consuming and prone to errors as it implies examining thousands of images while significant lesions may only be represented in a small number of frames. Recently, the development of artificial intelligence (AI) algorithms for automatic interpretation of endoscopic images has generated a large interest. The performance of these tools, particularly convolutional neural networks have shown potential to overcome some of the main drawbacks of CE. This multicentric study aims to assess the performance of a deep learning algorithm for the automatic detection of small intestinal and colonic ulcers and erosions in PCC images. Methods We included a total of 59 PCC exams from two centres (ManopH Gastroenterology Clinic and Centro Hospitalar Universitário de São João) performed between 2017 and 2021. A total of 78415 frames were extracted. This pool of images was constituted by 14124 images depicting ulcers and erosions and 64291 with normal enteric and colonic mucosa. For the automatic identification of these findings, this image pool was split into training and validation datasets in a patient-based manner. Therefore, images from the same patient were restricted to a single dataset. A CNN model with transfer learning was developed using tensorflow and keras tools. Results The neural architecture of our CNN was optimized for the detection of enteric and colonic ulcers and erosions. An example of the output provided by the CNN is shown in Figure 1. The deep learning model had a sensitivity of 86.7%, a specificity of 98.6%, a positive predictive value of 92.3% and a negative predictive value of 97.4%. The overall accuracy of our network was 96.6% (Figure 2). At a threshold value of 50%, our CNN had an area under the curve of 0.98 for the detection of ulcers and erosions (Figure 3). Conclusion In this multicentric study, our group has developed a CNN and assessed its performance in a patient-based design, which provides significant robustness to our results. Patient-split analyses are the first step towards real-life application of AI solutions which, allied to the high-performance results of our model, may significantly improve the diagnostic yield of this panendoscopic tool.

Streptomyces strains are powerhouses for a diverse range of secondary metabolites, including antibiotics, anticancer and immunosuppressive agents, and enzymes. Here, we report the genome sequence of Streptomyces sp. strain PSAA01, which was isolated from a soil sample taken in Manas National Park, Assam, India, in the eastern Himalayan foothills of India.

This work presents a multi-parameter optical fiber monitoring solution applied to an underground power distribution network. The monitoring system demonstrated herein uses Fiber Bragg Grating (FBG) sensors to measure multiple parameters, such as the distributed temperature of the power cable, external temperature and current of the transformers, liquid level, and intrusion in the underground manholes. To monitor partial discharges of cable connections, we used sensors that detect radio frequency signals. The system was characterized in the laboratory and tested in underground distribution networks. We present here the technical details of the laboratory characterization, system installation, and the results of 6 months of network monitoring. The data obtained for temperature sensors in the field tests show a thermal behavior depending on the day/night cycle and the season. The temperature levels measured on the conductors indicated that in high-temperature periods, the maximum current specified for the conductor must be reduced, according to the applied Brazilian standards. The other sensors detected other important events in the distribution network. All the sensors demonstrated their functionality and robustness in the distribution network, and the monitored data will allow the electric power system to have a safe operation, with optimized capacity and operating within tolerated electrical and thermal limits.

Patients with respiratory viral infections are more likely to develop co-infections leading to increased fatality. Mucormycosis is an epidemic amidst the COVID-19 pandemic that conveys a ‘double threat’ to the global health fraternity. Mucormycosis is caused by the Mucorales group of fungi and exhibits acute angioinvasion generally in immunocompromised patients. The most familiar foci of infections are sinuses (39%), lungs (24%), and skin tissues (19%) where the overall dissemination occurs in 23% of cases. The mortality rate in the case of disseminated mucormycosis is found to be 96%. Symptoms are mostly nonspecific and often resemble other common bacterial or fungal infections. Currently, COVID-19-associated mucormycosis (CAM) is being reported from a number of countries such as the USA, Turkey, France, Mexico, Iran, Austria, UK, Brazil, and Italy, while India is the hotspot for this deadly co-infection, accounting for approximately 28,252 cases up to June 8, 2021. It strikes patients within 12–18 days after COVID-19 recovery, and nearly 80% require surgery. Nevertheless, the mortality rate can reach 94% if the diagnosis is delayed or remains untreated. Sometimes COVID-19 is the sole predisposing factor for CAM. Therefore, this study may provide a comprehensive resource for clinicians and researchers dealing with fungal infections, intending to link the potential translational knowledge and prospective therapeutic challenges to counter this opportunistic pathogen.

Aminoglycosides and β-lactams are the most commonly used antimicrobial agents in clinical practice. This occurs because they are capable of acting in the treatment of acute bacterial infections. However, the effectiveness of antibiotics has been constantly threatened due to bacterial pathogens producing resistance enzymes. Among them, the aminoglycoside-modifying enzymes (AMEs) and β-lactamase enzymes are the most frequently reported resistance mechanisms. AMEs can inactivate aminoglycosides by adding specific chemical molecules in the compound, whereas β-lactamases hydrolyze the β-lactams ring, preventing drug-target interaction. Thus, these enzymes provide a scenario of multidrug-resistance and a significant threat to public health at a global level. In response to this challenge, in recent decades, several studies have focused on the development of inhibitors that can restore aminoglycosides and β-lactams activity. In this context, peptides appear as a promising approach in the field of inhibitors for future antibacterial therapies, as multiresistant bacteria may be susceptible to these molecules. Therefore, this review focused on the most recent findings related to peptide-based inhibitors that act on AMEs and β-lactamases, and how these molecules could be used for future treatment strategies.

Macrophage intracellular infections are difficult to treat because conventional antibiotics tend to have poor penetration of mammalian cells. As a consequence, the immune response is affected and bacteria remain protected inside macrophages. The use of antimicrobial peptides (AMPs) is one of the alternatives developed as new treatments because of their broad spectrum of action. To improve drug delivery into the intracellular space, extracellular vesicles (EVs) have emerged as an innovative strategy for drug delivery. In particular, apoptotic bodies (ApoBDs) are EVs that exhibit attraction to macrophages, which makes them a promising means of improving AMP delivery to treat macrophage intracellular infections. Here, we review important aspects that should be taken into account when developing ApoBD-AMP conjugates.

Few studies have assessed the impact of COVID-19 on surgical training in low- and middle-income countries. The aim of this study was to survey the effect of the COVID-19 pandemic on postgraduate surgical training, research and registrar wellbeing in South Africa.A cross-sectional study was conducted as an online survey from 5 October 2020 to 1 December 2020. The study population was registrars from all surgical disciplines at the Faculty of Medicine and Health Sciences of Stellenbosch University. The survey consisted of 26 multiple-choice and five open-ended qualitative questions on the impact of COVID-19 on physical and mental wellbeing, skills acquisition and postgraduate research.Of 98 surgical registrars, 35 (36%) responded. Twenty-three (65.7%) reported missed planned surgical rotations, 30 (85.7%) decreased surgical training time, and 22 (62.9%) reported a perceived decrease in training quality. Simulated skills training was only available to eight (22.9%) participants. Twenty-four (68.6%) experienced burnout and/or depression symptoms during the pandemic. Twenty-seven (77.1%) reported that postgraduate research was unaffected by the pandemic.During the COVID-19 pandemic, surgical trainees at this institution reported a decrease in the quality of surgical training and skills acquisition and a negative impact on their mental wellbeing.

Made available in DSpace on 2020-12-10T20:04:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-07-02 Fundacao de Apoio ao Desenvolvimento do Ensino, Ciencia e Tecnologia do Estado de Mato Grosso do Sul Candidayeast infections are the fourth leading cause of death worldwide. Peptides with antimicrobial activity are a promising alternative treatment for such infections. Here, the antifungal activity of a new antimicrobial peptide-PEP-IA18-was evaluated againstCandidaspecies. PEP-IA18 was designed from the primary sequence of profilin, a protein fromSpodoptera frugiperda,and displayed potent activity againstCandida albicansandCandida tropicalis, showing a minimum inhibitory concentration (MIC) of 2.5 mu M. Furthermore, the mechanism of action of PEP-IA18 involved interaction with the cell membrane (ergosterol complexation). Treatment at MIC and/or 10 x MIC significantly reduced biofilm formation and viability. PEP-IA18 showed low toxicity toward human fibroblasts and only revealed hemolytic activity at high concentrations. Thus, PEP-IA18 exhibited antifungal and anti-biofilm properties with potential applicability in the treatment of infections caused byCandidaspecies. Univ Fed Mato Grosso, Fac Pharmaceut Sci Food & Nutr, Prot Purificat Lab & Biol Funct, Campo Grande, MS, Brazil Fed Univ Grande Dourados, Ctr Biotechnol & Bioprospecting Studies Appl Meta, Dourados, MS, Brazil Sao Paulo State Univ, Inst Chem, Dept Biochem, Araraquara, SP, Brazil Univ Catolica Dom Bosco, Grad Program Biotechnol, S Inova Biotech, Campo Grande, MS, Brazil Univ Catolica Brasilia, Ctr Prote & Biochem Anal, Grad Program Genom Sci & Biotechnol, Brasilia, DF, Brazil Univ Brasilia, Fac Med, Grad Program Mol Pathol, Brasilia, DF, Brazil Sao Paulo State Univ, Inst Chem, Dept Biochem, Araraquara, SP, Brazil Fundacao de Apoio ao Desenvolvimento do Ensino, Ciencia e Tecnologia do Estado de Mato Grosso do Sul: 08/2015

TARUMÃ is a multi-technique station at CARNAÚBA (Coherent X-Ray Nanoprobe Beamline) at the 4th-generation light source Sirius at the Brazilian Synchrotron Light Laboratory (LNLS). With a tender-to-hard energy range from 2.05 to 15 keV and a fully coherent nanoprobe focused via an all-achromatic KB (Kirkpatrick-Baez) optics, it can be used for simultaneous multiple nanoscale X-ray techniques in 2D and 3D. This includes ptychography coherent diffraction imaging (ptycho-CDI), absorption spectroscopy (XAS), diffraction (XRD), fluorescence (XRF) and luminescence (XEOL). In particular, the tender energies can be used to study light elements that are commonly present in soft biological samples, ensuring the unique position of the station in the Life and Environmental Sciences program at LNLS. Still, enabling this range of experiments is sometimes only possible with cryogenically cooled samples as the high beam dose can result in both chemical and structural damage at ambient temperature conditions. At TARUMÃ, to comply with the heavily occupied volume around the sample and the sample positioning architecture, this is enabled by an open-atmosphere cryogenic system based on a commercial cryojet and a custom-designed sample holder. Following a predictive engineering approach, the system is capable of conditioning the sample down to 155K, whilst avoiding icing and condensation in nearby instrumentation and preserving the nanometer-level positioning requirements of the scanning station. Here we present the commissioning results of the referred system along with the first beamline measurements.

Antimicrobial peptides (AMPs) are pinpointed as promising molecules against antibiotic-resistant bacterial infections. Nevertheless, there is a discrepancy between the AMP sequences generated and the tangible outcomes in clinical trials. AMPs' limitations include enzymatic degradation, chemical/physical instability and toxicity toward healthy human cells. These factors compromise AMPs' bioavailability, resulting in limited therapeutic potential. To overcome such obstacles, peptidomimetic approaches, including glycosylation, PEGylation, lipidation, cyclization, grafting, D-amino acid insertion, stapling and dendrimers are promising strategies to fine-tune AMPs. Here we focused on chemical modifications applied for AMP optimization and how they have helped these peptide-based antibiotic candidates' design and translational potential.

İki veya daha fazla akarsuyun birleşerek kavşak noktası oluşturmaları, açık kanal hidroliği alanında sık karşılaşılan bir durumdur. Kavşaklar, hidrolik açıdan önemli kontrol noktalarıdır. Kavşak içinde memba ve mansap derinliklerinin bilinmesi oluşacak yük kaybının hesaplanabilmesi açısından önem arz etmektedir. İzmir Kâtip Çelebi Üniversitesi Hidrolik Laboratuvarı’nda bulunan deney düzeneği üzerinde gerçekleştirilmiş bu çalışmada, yan kollardan gelen debi sabit tutularak mansap derinliği değiştirilerek yan kollar ve ana kanal boyunca akım derinlikleri ölçülmüştür. Simetrik 90° açıyla birleşen yan kolların genişliği 1 m, ana kanalın genişliği ise 2 m olup yan kollar ile ana kanalın taban kotları eşit olacak şekilde düzenlenmiştir. Akım derinlikleri, limnimetre vasıtasıyla ölçülmüş olup önce taban kotları ölçülmüş, daha sonra su yüzey kotları ölçülmüştür. Ölçümler, ana kanalda, her 50 cm’de bir, yan kollarda ise her 25 cm’de bir yapılmıştır. Çalışmada, ana kanalda Froude sayıları 1’den küçük olup akım, nehir rejiminde olmuştur. Bu çalışmada sağ kolun debisi 29,61 l/s, sol kolun debisi 20 l/s olup ana kanaldaki toplam debi 49,61 l/s’dir. Mansap kısmında bulunan kapak vasıtasıyla mansap akım derinliği ayarlanmıştır. Gerçekleştirilen deneylerde mansap akım derinliği sırasıyla 9,3 cm 12,60 cm ve 15,35 cm olacak şekilde ayarlanmıştır. Bu koşullarda kavşak birleşim noktasında derinlik sırasıyla, 9,8 cm, 12,8 cm ve 15,75 cm olmuştur. Her 3 deneyde de ana kanalda H2 profili gözlenmiş ve kavşak birleşim noktasındaki derinlik mansap derinliğinden daha fazla olmuştur. Yan kol ve ana kanal debileri arasındaki oran ile akım derinlikleri arasındaki ilişki literatür ışığında incelenmiştir. Deneylerde taban eğimi 0 ve y>ycr olup çalışmalar nehir rejiminde yapıldığından H2 profili gözlemlenmiştir. Su yüzey profillerinde eğimler birbirine paralellik göstermiştir. Mansaptaki derinliğinin artması, su seviyesi ortalamasını artırmıştır.

İki ya da daha fazla akarsuyun birleşmesiyle oluşan akarsu kavşakları, akış ağlarında sıklıkla karşılaşılan bir oluşum olup, kollardaki su seviyesinin yükselmesi gibi akış koşullarının değişmesi ve buna bağlı olarak taşkın hasarlarına ve ekonomik kayıplara neden olabileceğinden incelenmesi gereken bir konudur. Bu kapsamda, İzmir Kâtip Çelebi Üniversitesi’nde mevcut dikdörtgen kesitli birbirine 90° açıyla bağlanan 1 m genişliğinde simetrik iki yan kola sahip ve 2 m genişliğinde ve 18 m uzunluğunda açık kanaldan oluşan simetrik akarsu kavşağı üzerinde deneyler gerçekleştirilmiştir. Yan kollardan birinde taban eşitsizliği 12 cm’lik bir yükselti ile sağlanmıştır. Deneylerde sağ kol debisi 15 l/s, taban eşitsizliğine sahip sol kol debisi 20 l/s’dir. Mansap derinlikleri 15 cm ve 25 cm olacak şekilde mansap kapağı ayarlanmış ve akım derinlikleri ölçümü kanal eksenlerinde, akım yönünde ana kanalda kavşaktan mansaba kadar 50 cm, yan kollarda membadan kavşağa kadar 25 cm arayla yapılmıştır. Çalışmada, yan kollardaki ve ana kanaldaki su seviyeleri mevcut raylı sistem üzerine monte edilmiş limnimetre yardımıyla elde edilmiştir. Her iki deney için su yüzeyi profili elde edilmiştir. Elde edilen deneysel sonuçlar uniform olmayan akım tiplerinden H2 tipi için su yüzeyi profili sayısal olarak çözülmüş ve karşılaştırılmıştır. Sayısal ve deneysel sonuçların akarsu kavşağı mansabında uyum içinde olduğu görülmüştür.

Bu çalışmada, akarsu kavşaklarında taban kotlarının eşitsizliği durumunda akım derinlikleri deneysel olarak araştırılmıştır. Deneyler, İzmir Kâtip Çelebi Üniversitesi İnşaat Mühendisliği Bölümü Hidrolik Laboratuvarı’nda, mevcut dikdörtgen kesitli 2 m genişliğindeki ana kanal ve birbiri ile 90°’lik açı ile bağlanan, her birinin genişliği 1 m olan 2 yan koldan oluşan akarsu kavşağı deney düzeneği üzerinde gerçekleştirilmiştir. Yan kolların taban kotları ana kanal taban kotundan 12 cm yüksekte bulunmaktadır. Deneylerde genişlikler ve kavşak açısı sabit tutulup, mansap derinliği ve yan kollardan gelen debiler değiştirilerek, farklı koşullar altında, akım derinlikleri kanal ekseninde akım yönünde 50 cm aralıklar ile, yan kollarda ise 25 cm aralıklar ile ölçülmüş ve buna bağlı olarak su yüzeyi profilleri oluşturulmuştur. Yapılan tüm çalışmalarda akım nehir rejimindedir. Yapılan deneylerde her iki yan koldaki debi 20 l/s, toplam debi 40 l/s ve buna bağlı olarak belirlenen mansap derinlikleri 8,15- 15, 35- 18,30 cm’dir. Bu mansap yüksekliklerine bağlı olarak kavşak birleşiminde okunan yükseklik değerleri sırasıyla 8,90 – 15,90 – 18,50 cm’dir. Bu veriler ışığında simetrik akarsu kavşaklarının rehabilitasyonu, bu kavşakların etrafına inşa edilecek olan su yapılarının tasarım parametrelerinin belirlenmesi adına tasarım esaslarının belirlenmesi amaçlanmıştır. Ayrıca bu çalışma ile ana kanal ve yan kol debileri arasındaki oranın akım derinliklerine etkisi mevcut literatür ışığında incelenmiştir.

Cyclotides are cyclic peptides, present in several plant families, that show diverse biological properties. Structurally, cyclotides share a distinctive head-to-tail circular knotted topology of three disulfide bonds. This framework provides cyclotides with extraordinary resistance to thermal and chemical denaturation. There is increasing interest in the therapeutic potential of cyclotides, which combine several promising pharmaceutical properties, including binding affinity, target selectivity, and low toxicity towards healthy mammalian cells. Recently, cyclotides have been reported to be orally bioavailable and have proved to be amenable to modifications. Here, we provide an overview of the structure, properties, and pharmaceutical applications of cyclotides.

The performance of a rake for large wood retention has been analysed in clean water and for the case of a slit check dam. An experimental investigation was conducted in a steep rectangular flume, by employing regular cylinders at different rates and rake geometry. The effects of the inclination and distance of the rake from the check dam have been analysed in terms of the trapping efficiency and backwater effect. By intercepting the incoming wood material, the rake avoids the direct occlusion of the slit check dam, preventing large backwater rises and allowing the dam to work properly even in the presence of intense woody flow. The trapping efficiency slightly increases with the inclination of the rake when it remains very close to the check dam, but it tends to decrease when the structure is out of the calm water region upstream of the dam. Additionally, a comparison between the rake performance and the check dam without retaining devices is presented.