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The rise of Enterobacteriaceae strains that produce an extended spectrum b-lactamase (ESBL) has become a global concern for epidemiological surveillance and the prevention of nosocomial acquired infections in the modern era. The choice of appropriate antibiotics to be employed in the treatment of infections brought on by ESBL-producing bacteria relies greatly on the detection and identification of these ESBLs in the laboratory. Limitations in ESBL detection have aided in the unbridled emergence of bacterial resistance and constitute a major health concern. Isolation and identification of ESBL among Enterobacteriaceae by phenotypic methodswith their Antibiogram.Phenotypic techniques were used to identify ESBL-producing Enterobacteriaceae (ESBLs-E) isolates from diverse clinical samples. Kirby Baur disc diffusion technique was performed to determine antimicrobial's susceptibility.Among 212 Enterobacteriaceae isolates 124(58.3%) were positive for ESBL production. E.coli(74.5%) & K.pneumoniae (52.2%) two main isolates that produce ESBLs. Maximum ESBL producing Enterobacteriaceae isolates were obtained from blood samples 82% (41/50) followed by urine 59 % (62/105). Meropenem (96.7%), Amikacin (82.1%), and Cefoxitin were most susceptible antibiotics for ESBL-producing isolates while high resistance was observed in ceftazidime (62%), followed by Ciprofloxacin (60%). The majority of ESBLs-E was mostly found in urine and blood samples.It was observed that E.coli produced the most ESBLs. There was a high prevalence of ESBLs-E in tertiary care hospital of central India. Therefore, strong infection control strategies must be implemented in hospital settings

Infant feeding practices have a vital role to play in shaping the eating behaviour and overall health of individuals in both childhood as well as adulthood. A lesser-known advantage of breastfeeding in the global obesogenic environment, is its role in self-regulation of an infant’s appetite. Research demonstrates that children fed exclusively from the breast (that is, they are never bottle fed) develop the capacity for self-regulation of breastmilk intake – after all, mothers cannot possibly observe the quantity of milk the infant ingests. This encourages the infant to gain control, thus avoiding any overconsumption. On the other hand, bottle fed infants (whether mother’s milk or formula milk) are subjected to mother’s or other caregivers encouragement of bottle emptying. Since the regulation largely lies externally with the parent/caregiver on scheduled or timed feeding versus a cue feeding, this állows the possibility of such children being prevented from developing their own appetite responsiveness independently. Studies do find differences in satiety responses of children fed human milk with a bottle and those who were directly breastfed. Research has shown that directly breast-fed infants do not consume extra milk once their appetite stimulation phase ends. However, the teaching of bottle emptying during early infancy is positively associated with the weight gain. Such distinctions clearly emphasize the importance of breast feeding, but whether it is the milk composition (human or formula) or the mode of feeding (directly from breast or using bottle) that plays a bigger role in signalling appetite control warrants further examination. Considering that an infant’s weight gain or growth has a multifactorial causation, this review will highlight the association of direct breastfeeding with appetite signalling in infancy.

Background: Screening for congenital hypothyroidism (CH) is a routine practice in most developed countries of the world. This can be done by measuring cord blood thyroid stimulating hormone (CBTSH). Apart from foetal thyroid status and iodine nutrition status of the population, many perinatal factors may also affect CBTSH. The influence of these perinatal factors may affect the sensitivity of CBTSH as a screening tool for CH. The present study was carried out to study the influence of various perinatal factors on CBTSH level. Methods: It was a cross sectional study conducted in tertiary care centre in North Maharashtra. 793 new-borns were included in study. Effects of perinatal factors like maternal age, parity, gender of the baby, birth weight, mode of delivery, gestational age, birth asphyxia on CBTSH was analysed with appropriate scientific method. Results: The mean TSH level in the study group was 7.56±3.9 mIU/l. Among the associated factors vaginal delivery, low gestational age, low birth weight and birth asphyxia were significantly associated with elevated CBTSH values. Hence, any rise in cord blood TSH should be seen in the light of these factors. Conclusions: Among all the associated factors, primi-parity, vaginal delivery, low gestational age, low birth weight and birth asphyxia were significantly associated with elevated CBTSH values. However, no association was observed between CBTSH values and gender of the baby and maternal age.

Background: The high incidence of acute kidney injury (AKI) requiring dialysis associated with COVID-19 led to the use of peritoneal dialysis (PD) for the treatment of AKI. This study aims to compare in-hospital all-cause mortality and kidney recovery between patients with AKI who received acute PD versus extracorporeal dialysis (intermittent haemodialysis and continuous kidney replacement therapy). Methods: In a retrospective observational study of 259 patients with AKI requiring dialysis during the COVID-19 surge during Spring 2020 in New York City, we compared 30-day all-cause mortality and kidney recovery between 93 patients who received acute PD at any time point and 166 patients who only received extracorporeal dialysis. Kaplan–Meier curves, log-rank test and Cox regression were used to compare survival and logistic regression was used to compare kidney recovery. Results: The mean age was 61 ± 11 years; 31% were women; 96% had confirmed COVID-19 with median follow-up of 21 days. After adjusting for demographics, comorbidities, oxygenation and laboratory values prior to starting dialysis, the use of PD was associated with a lower mortality rate compared to extracorporeal dialysis with a hazard ratio of 0.48 (95% confidence interval: 0.27–0.82, p = 0.008). At discharge or on day 30 of hospitalisation, there was no association between dialysis modality and kidney recovery ( p = 0.48). Conclusions: The use of PD for the treatment of AKI was not associated with worse clinical outcomes when compared to extracorporeal dialysis during the height of the COVID-19 pandemic in New York City. Given the inherent selection biases and residual confounding in our observational study, research with a larger cohort of patients in a more controlled setting is needed to confirm our findings.

Purpose Along with their immense benefit, online channels of communication and information-sharing also present a myriad set of challenges. The unauthorized downloading and sharing of copyrighted content such as music and movies is one such issue. This study aims to examine the factors related to the unauthorized downloading of content amongst young internet users in an emerging market. Design/methodology/approach An online structured questionnaire was used to collect primary data from 219 internet users between 17 and 24 years of age. The partial least squares structural equation modelling was used to analyse the primary data. Findings The study findings report that monetary savings and social influence are the main drivers underlying the propensity to engage in unauthorized downloading amongst young adults. Perceptions of harm caused to artists and producers appear to be a deterrent. Though the respondents perceive the quality of content downloaded from unauthorized sites to be less than desirable, and there is also a higher perceived threat from viruses, this does not appear to deter unauthorized downloading behaviour amongst this segment of consumers. Research limitations/implications Combating unauthorized downloading and other forms of questionable online behaviours is a challenge for multiple stakeholders. Consumption of unauthorized digital content is examined in the context of online consumers whose demographic profile is often associated with this category of questionable behaviour. The study adds to the extant understanding of the aetiology of what are often considered online unethical and illegal behaviours and makes both practical and theoretical contributions to the subject field. Originality/value The study examines an important aspect of rapidly evolving internet technologies. The internet provides a veil to individuals engaging in unethical online activities. Despite the existence of laws declaring these activities to be illegal, instances of copyright violations of music and movies abound. The insights regarding the drivers and deterrents of a form of online unauthorized activity are used to present a set of strategies aimed at addressing such behaviours.

Maternal choline supplementation (MCS) improves cognition in Alzheimer’s disease (AD) models. However, effects of MCS on neuronal hyperexcitability in AD are unknown. We investigated effects of MCS in a well-established mouse model of AD with hyperexcitability, the Tg2576 mouse. The most common type of hyperexcitability in Tg2576 mice, and many other mouse models and AD patients, are generalized EEG spikes (interictal spikes; IIS). Hyperexcitability is also reflected by elevated expression of the transcription factor ΔFosB in the principal cells of the dentate gyrus (DG), granule cells (GCs). We also studied the hilus of the DG because hilar neurons regulate GC excitability. We found reduced expression of the neuronal marker NeuN within hilar neurons in Tg2576 mice, which other studies have shown is a sign of oxidative stress or other pathology.Tg2576 breeding pairs received a diet with a relatively low, intermediate or high concentration of choline. After weaning, all mice received the intermediate diet. In offspring of mice fed the high choline diet, IIS frequency declined, GC ΔFosB expression was reduced, and NeuN expression restored. Spatial memory improved. In contrast, offspring exposed to the relatively low choline diet had several adverse effects, such as increased mortality. The results provide new evidence that a diet high in choline in early life can improve outcomes in a mouse model of AD, and relatively low choline can have negative consequences. This is the first study showing that dietary choline can regulate hyperexcitability, hilar neurons, and spatial memory in an animal model of AD.

Purpose The purpose of this paper is to develop a machine learning model that predicts the component self-alignment offsets along the length and width of the component and in the angular direction. To find the best performing model, various algorithms like random forest regressor (RFR), support vector regressor (SVR), neural networks (NN), gradient boost (GB) and K-nearest neighbors (KNN) were performed and analyzed. The models were implemented using input features, which can be categorized as solder paste volume, paste-pad offset, component-pad offset, angular offset and orientation. Design/methodology/approach Surface-mount technology (SMT) is the technology behind the production of printed circuit boards, which is used in several types of commercial equipment such as communication devices, home appliances, medical imaging systems and sensors. In SMT, components undergo movement known as self-alignment during the reflow process. Although self-alignment is used to decrease the misalignment, it may not work for smaller size chipsets. If the solder paste depositions are not well-aligned, the self-alignment might deteriorate the final alignment of the component. Findings It were trained on their targets. Results obtained by each method for each target variable were compared to find the algorithm that gives the best performance. It was found that RFR gives the best performance in case of predicting offsets along the length and width of the component, whereas SVR does so in case of predicting offsets in the angular direction. The scope of this study can be extended to developing this model further to predict defects that can occur during the reflow process. It could also be developed to be used for optimizing the placement process in SMT. Originality/value This paper proposes a predictive model that predicts the component self-alignment offsets along the length and width of component and in the angular direction. To find the best performing model, various algorithms like RFR, SVR, NN, GB and KNN were performed and analyzed for predicting the component self-alignment offsets. This helps to achieve the following research objectives: best machine learning model for prediction of component self-alignment offsets. This model can be used to optimize the mounting process in SMT, which reduces occurrences of defects and making the process more efficient.

In this era of “infodemic,” online health information has become a prime concern, and therefore, an analysis of studies on online health information, the reasons for which people seek online health information, its strengths and shortcomings, and the concept of E-health literacy has been done in this paper. Various tools to assess online health information and recent papers on assessment using DISCERN tool have been discussed. The concern for immunity boosting and its significance in the COVID era has grown manifold, especially for providers and consumers of health information. Online health information has become a vital part of healthcare in modern times; however, its quality seems to differ across domains. Online information on immunity boosting also seem to be misleading the people. This article provides an insight into the sphere of online health information and throws light over the hurdles that people come across face while retrieving health information online.

The natural terpene limonene is widely found in nature. The (R)-limonene (the most abundant enantiomer) is present in the essential oils of lemon, orange, and other citrus fruits, while the (S)- limonene is found in peppermint and the racemate in turpentine oil. Limonene is a low-cost, low toxicity biodegradable terpene present in agricultural wastes derived from citrus peels. The products obtained from the conversion of limonene are valuable compounds widely used as additives for food, cosmetics, or pharmaceuticals. The conversion of limonene to produce different products has been the subject of intense research, mainly with the objective of improving catalytic systems. This review focused on the application of heterogeneous catalysts in the catalytic conversion of limonene.

We examined the effects of Economic Policy Uncertainty (EPU) on dividend distribution strategy to provide some evidence from developing country prospect. Using a sample of 19 commercial banks for 2009–2020 and the Baker, Bloom, and Davis Index as a proxy of EPU, our key finding demonstrates EPU has no significant direct relationship with the dividend decision of the banking firm. The empirical results reveal that the banking firm in Nepal neither terminate nor initiate dividends during EPU. Further, we found evidence of no precautionary incentive of banking executives as a reaction to policy distress. The dividend payment decision is intuitive for the banking firm in Nepal rather than uncertainty prone by the change in economic policy. If the precautionary motive dominates the firms, banks are supposed to distribute lower cash dividend once there is a more considerable degree of policy uncertainty as a buffer against adversity. Other firm-specific variables, such as corporate earnings, past year dividend, ownership structure, and bank size, affect the dividend decision of banking firms in Nepal. As our results contradict the previous major studies conducted in developed market settings, we suggest that the banking firms should consider, analyze, and adjust their dividend policy based on the opportunities and threats posit by the country's economic policy.

Both spatial and non-spatial data are critical to a country's social and economic development. Land use and land cover (LULC) maps are data that can be used to retrieve land information and detect environmental changes. Several recent studies have used deep learning approaches to generate LULC maps from various remote-sensing image formats. They have correctly recognized several land cover elements such as built-up areas, forests, water, etc. On the other hand, spaceborne radar images must be used to test deep learning methods because radar sensors operate in all weather and lighting circumstances and have diverse image characteristics depending on the wavelength. Although many researchers have applied deep learning techniques to classify the land cover features, most of them need to do more by taking less or more several land cover features and taking proper evaluation metrics to justify the classification techniques. The current research shows segmentation on Sentinel-1 C-band synthetic aperture radar (SAR) images of Gujarat's Ahmedabad, Anand, and Kheda regions using four deep-learning models. U-Net, SegNet, FCN, and DeepLabV3+ have primarily been employed in prior research to classify SAR and other satellite image formats and showed excellent results in identifying different land cover features. Training samples of five primary classes for ground-truth data were obtained using Google Earth and Sentinel-2 images as reference maps. For segmenting the Sentinel-1 image, above mentioned four deep-learning semantic segmentation models were chosen and fine-tuned. All models did exceptionally well, with overall accuracy ranging from 76% to 90%. U-Net fared well, followed by DeepLabV3+ in classifying all five land cover features, with mean intersection over union (IoU) of 0.67 and 0.55, respectively. The results reveal that using a self-generated reference map, the Sentinel-1 dual-pol images can categorize the primary land cover features.

Use of internet for assessing health-related information has been growing exponentially in the past few years. The objective of this study was to assess the quality of information on the websites on Google and DuckDuckGo. A total of 120 URLs were recorded from Google and DuckDuckGo using the search terms “immunity booster,” “immunity boosting foods,” and “immunity boosting drinks.” These were rated by three independent raters using DISCERN tool. The average ratings for the DISCERN questions were in the range of 2.01–3.82. More than 85% of the websites were of moderate quality. There was excellent inter-rater reliability among the raters. About 47% of the websites depicted immunity boosting as beneficial. About 11% of the websites recommended use of supplements for immunity boosting. Diet, exercise, and adequate sleep were the most commonly recommended strategies for immunity boosting. Vitamin C, Vitamin A, and gingerol were the most commonly recommended dietary components for immunity boosting. Overall, there was no statistically significant difference in the quality of websites on Google and DuckDuckGo. Most of the websites suffered from shortcomings in the quality of information based on DISCERN quality criteria.

Background Neuroleptic malignant syndrome is a clinical condition which has been studied and described well. But history of the patient and the medications he is on are very important to make this diagnosis. Case presentation We report the case of a young male who presented with the typical features but lacked the history of medication, hence delaying our diagnosis formation. In-depth history taking is very important in patients who present with unusual symptoms. Conclusions Patients on long-term medications, who may develop some side effects due to medication, should always carry a medical card stating their medical history and medication being taken.

Person Re-identification is aimed to identify a person through multiple camera views. The task has attained a huge research interest due to its apparent importance in surveillance systems from security aspects. This paper introduces a novel methodology based on Siamese architecture with multi-layer similarity constraints. The baseline model embraces two dense blocks to preserve feature maps at each convolutional layer. Besides, the model training is performed by applying distinct similarity constraints on low-level and high-level layers. Two important observations validate the robustness of the proposed model. First, the similarity constraints can synchronize with the model's classification constraints and produce a unified multi-tasking network. Second, the similarity patterns are encoded in the framework in terms of learning parameters during model training. Therefore, a single image is required at the test time instead of the image pair, which makes the method time-efficient and suitable for wide-scale real-time applications. Experimental outcomes on various distinct datasets show that the proposed method surpasses the existing performance benchmarks for person re-identification.

Spatial resolution is an important aspect of many optical instruments. It is defined as the ability of surface-topography measuring instruments to distinguish closely spaced surface features. Following convention, spatial resolution can be defined as the spatial frequency response of the instrument, known as the instrument transfer function (ITF). In this paper, we describe the step-artifact approach for estimating the ITF for 3D scanners, discuss step artifact characterization and validation approaches, and present a method to estimate the combined uncertainty of the ITF measurement. The approach is demonstrated using the EinScan-Pro 3D scanner. A step artifact is used for the measurement that takes advantage of the cleaving properties of a single-side polished silicon wafer. The uncertainty analysis includes simulations to estimate the contribution due to influencing factors such as the alignment of the step artifact to the measurement axis, the diffuse versus specular scattering properties of the step edge, and various processing parameter choices.

Cannabidiol (CBD), a non-euphoric component of cannabis, reduces seizures in multiple forms of pediatric epilepsy, but the mechanism(s) of anti-seizure action remain unclear. In one leading model, CBD acts at glutamatergic axon terminals, blocking pro-excitatory actions of an endogenous membrane phospholipid, lysophosphatidylinositol (LPI), at the G protein-coupled receptor GPR55. However, the impact of LPI-GPR55 signaling at inhibitory synapses and in epileptogenesis remains underexplored. We found that LPI transiently increased hippocampal CA3→CA1 excitatory presynaptic release probability and evoked synaptic strength in WT mice, while attenuating inhibitory postsynaptic strength by decreasing GABAARγ2 and gephyrin puncta. Effects of LPI at both excitatory and inhibitory synapses were eliminated by CBD pretreatment and absent after GPR55 deletion. Acute pentylenetrazole-induced seizures elevated levels of GPR55 and LPI, and chronic lithium pilocarpine-induced epileptogenesis potentiated the pro-excitatory effects of LPI. We propose that CBD exerts potential therapeutic effect both by blocking synaptic effects of LPI and dampening hyperexcitability.

SUMMARYThe authorized mRNA- and adenovirus-based SARS-CoV-2 vaccines are intramuscularly injected and effective in preventing COVID-19, but do not induce efficient mucosal immunity, or prevent viral transmission. We developed a bacteriophage T4-based, multicomponent, needle and adjuvant-free, mucosal vaccine by engineering spike trimers on capsid exterior and nucleocapsid protein in the interior. Intranasal administration of T4-COVID vaccine induced higher virus neutralization antibody titers against multiple variants, balanced Th1/Th2 antibody and cytokine responses, stronger CD4+and CD8+T cell immunity, and higher secretory IgA titers in sera and bronchoalveolar lavage with no effect on the gut microbiota, compared to vaccination of mice intramuscularly. The vaccine is stable at ambient temperature, induces apparent sterilizing immunity, and provides complete protection against original SARS-CoV-2 strain and its Delta variant with minimal lung histopathology. This mucosal vaccine is an excellent candidate for boosting immunity of immunized and/or as a second-generation vaccine for the unimmunized population.

With the rapid rate of COVID-19 infections and deaths, treatments and cures besides hand washing, social distancing, masks, isolation, and quarantines are urgently needed. The treatments and vaccines rely on the basic biophysics of the complex viral apparatus. Although proteins are serving as main drug and vaccine targets, therapeutic approaches targeting the 30,000 nucleotide RNA viral genome form important complementary approaches. Indeed, the high conservation of the viral genome, its close evolutionary relationship to other viruses, and the rise of gene editing and RNA-based vaccines all argue for a focus on the RNA agent itself. One of the key steps in the viral replication cycle inside host cells is the ribosomal frameshifting required for translation of overlapping open reading frames. The RNA frameshifting element (FSE), one of three highly conserved regions of coronaviruses, is believed to include a pseudoknot considered essential for this ribosomal switching. In this work, we apply our graph-theory-based framework for representing RNA secondary structures, "RAG (or RNA-As-Graphs)," to alter key structural features of the FSE of the SARS-CoV-2 virus. Specifically, using RAG machinery of genetic algorithms for inverse folding adapted for RNA structures with pseudoknots, we computationally predict minimal mutations that destroy a structurally important stem and/or the pseudoknot of the FSE, potentially dismantling the virus against translation of the polyproteins. Our microsecond molecular dynamics simulations of mutant structures indicate relatively stable secondary structures. These findings not only advance our computational design of RNAs containing pseudoknots, they pinpoint key residues of the SARS-CoV-2 virus as targets for antiviral drugs and gene editing approaches.

The continuous rising abstraction resolution of distant police work sensors sets new interest for applications victimization this information. For mining valuable information from far flung police work data, various classifiers hooked in to the supernatural examination of individual pixels are projected and big advancement has been accomplished. Even so, these methodologies have their restrictions, for the foremost half they manufacture "salt and pepper" boisterous outcomes. to beat such problems, object-arranged image examination strategy hooked in to multi-resolution division methodology was advanced and it's been used for various application functions effectively. During this examination, a productive remotely detected image smart understanding technique hooked in to image division and geographical information framework (GIS) was projected, within the 1st place, division hooked in to mean shift was utilized to amass the underlying parts from distant police work footage. At that time, apply vectorization (Raster to Vector Convertor) strategy to supply polygons from the divided image and highlight attributions, as an example, ghostly, shape, surface then on square measure removed by zonal investigation hooked in to distinctive formation and polygons. At last, creating getting ready take a look at and administered characterization square measure dispensed. just about all means that square measure accomplished in geo-data framework with the exception of image division. supported the investigation, we have a tendency to engineered up a product arrangement of remotely detected image examination. Contrasted and also the understanding methodology of a business programming eCognition, the projected one was gettable and practiced once applied to the Quick bird remotely detected footage.

The present study was conducted to assess the usefulness of MUAC as a screening tool to assess nutritional status during pregnancy (>20 weeks). Pregnant women (>20 weeks of gestation, n=100) were enrolled from tertiary care ANC clinics in urban areas of Delhi. Data on socio-demographic profile was collected using pre-tested questionnaires. The blood pressure and anthropometric parameters (weight, height and MUAC) were recorded. The mean height, weight and MUAC of pregnant women were 152.15 ± 4.93cm, 56.7 ± 6.7Kgs and 25.5 ± 2.60cm respectively. Weight gain between trimesters and overall weight gain showed no correlation with blood pressure. Maternal weight was positively correlated with MUAC (p=0.00), SBP (p=0.006) and DBP (p=0.02). Maternal height was negatively correlated with MUAC (p=0.012). BMI and MUAC showed a significantly positive correlation (p=0.00), which indicates the versatility of this tool. However, no association was observed between MUAC and blood pressure during pregnancy in the present study.

Background: United States Food and Drug Administration (FDA) is the fastest drug review agency in the world. FDA is responsible for the protection of public health by assuring that foods are safe, wholesome, sanitary and, properly labeled. Novel drug Approvals are usually innovative products to serve unmet medical needs or otherwise help to advance patient care. Methods: FDA novel drug approvals were analyzed from calendar year (CY) 2012 to 2018 based on not only their numbers but also BASED ON their impact, innovation, access, and predictability. Results: The total number of novel drugs approved from CY 2012 to 2018 was 279 (average 40 novel drugs/ year). Impact of novel drug approvals: 50% were first in class and 43% were for rare diseases. Overall expedited development and review methods were used in 63% of the novel drug approvals. Access of novel drug approvals: 84% were first-cycle approval, 74% were approved in the US before other countries, 58% priority reviews among novel drug approvals. Predictability of novel drug approvals: 98% approvals able to meet PDUFA goal dates for application review. Conclusions: Novel drug approvals during CY 2012-2018 had a high quality which is very much evident by their high impact, good access, and high predictability.

In a practical power system, power plants are not equidistant from the distribution center and their fuel cost is different. Under normal operating conditions, the production capacity is even greater than the required total load and losses. Therefore, there are many options for planning the build. In an interconnected network, the objective is to determine the planning of the active and reactive power of each system in order to minimize operating costs. This means that the active and reactive power of the generator can vary within certain limits in order to cover a certain load requirement with minimal fuel costs. This is called the optimal power flow problem. This paper provides an overview of AI-based algorithms, genetic algorithms and their applications with cost-effective charge transport.

With the rapid rate of COVID-19 infections and deaths, treatments and cures besides hand washing, social distancing, masks, isolation, and quarantines are urgently needed. The treatments and vaccines rely on the basic biophysics of the complex viral apparatus. Although proteins are serving as main drug and vaccine targets, therapeutic approaches targeting the 30,000 nucleotide RNA viral genome form important complementary approaches. Indeed, the high conservation of the viral genome, its close evolutionary relationship to other viruses, and the rise of gene editing and RNA-based vaccines all argue for a focus on the RNA agent itself. One of the key steps in the viral replication cycle inside host cells is the ribosomal frameshifting required for translation of overlapping open reading frames. The RNA frameshifting element (FSE), one of three highly conserved regions of coronaviruses, is believed to include a pseudoknot considered essential for this ribosomal switching. In this work, we apply our graph-theory-based framework for representing RNA secondary structures, "RAG (or RNA-As-Graphs)," to alter key structural features of the FSE of the SARS-CoV-2 virus. Specifically, using RAG machinery of genetic algorithms for inverse folding adapted for RNA structures with pseudoknots, we computationally predict minimal mutations that destroy a structurally important stem and/or the pseudoknot of the FSE, potentially dismantling the virus against translation of the polyproteins. Our microsecond molecular dynamics simulations of mutant structures indicate relatively stable secondary structures. These findings not only advance our computational design of RNAs containing pseudoknots, they pinpoint key residues of the SARS-CoV-2 virus as targets for antiviral drugs and gene editing approaches.

Centrosome serves as the primary site of microtubule organization in a majority of animal cells. These microtubules carry out several significant functions in the cell such as cell division, chromosome segregation, mechanical support and cellular transport. Proteins localized at the centrosome play extensive role in orchestrating the process of microtubule organization, growth and stabilization in space and time. Anomalies in centrosome number, structure and functioning disturb microtubule organization and lead to several human diseases. Advancements in proteomics and microscopy methods have been instrumental in identifying molecular mechanisms pertaining to the microtubule organizing function of centrosomes. This review focuses on the involvement of centrosome as a microtubule nucleating center of the cell. We present the major molecular mechanisms at the centrosome which affect microtubule nucleation and activation. Finally, we discuss human diseases associated with defective microtubule organization resulting from centrosome abnormalities.

One of the cornerstone research models used in our laboratories is the induction of ischemic injury through cold ischemia followed by warm ischemia to donor kidneys to mimic the clinical realities of transplantation. The experimental design of the present study included bilateral nephrectomies on the day of syngeneic kidney transplant, with serum creatinine measured 24 hours postoperatively to measure acute function. Cold ischemia time in these experiments was always 30 minutes, and warm ischemia time was not standardized but always recorded. It became apparent that some transplanted kidneys that should have displayed injury were producing close to normal serum creatinine levels on postoperative day 1. In reviewing our data, we found a potential correlation between warm ischemia time and serum creatinine, in particular a significant proportion of low serum creatinine results (0.48 ± 0.26 mg/dL vs 1.99 ± 1.11 mg/dL; P .05) was associated with warm ischemia times that were significantly shorter than our historical average (29.2 ± 2.7 min vs 35.7 ± 2.2 min; P .05). The kidneys with lower serum creatinine also displayed lower apoptosis and brush border injury scores and fewer tubular casts. Therefore, we concluded that establishing a minimum warm ischemia time was just as important as standardized cold ischemia time to ensure consistent injury in this model.

COVID-19 is a viral infectious disease caused by SARS-COV2. Its clinical signs and symptoms are on a broad spectrum ranging from asymptomatic to severe complications like multi-organ failure, thromboembolism, and severe pneumonia with respiratory failure. Worse outcomes and higher mortality rates have been reported in the elderly, people with co-morbidities, and malnourished individuals. Nutrition is fundamental to good health and immune function. It forms an integral component of treatment modalities for various acute and chronic diseases, especially where a causative treatment is not yet recognized. Taking into consideration the magnitude of demands this pandemic has posed on hospital resources, an orderly assessment of nutritional status and body composition may not be possible for critically ill and/or for patients with mild-moderate symptoms who are managing their illness at home. Adequate intake of various macro and micro-nutrients--energy, protein, fat, vitamins--A, B, C, D, E and minerals--iron, selenium, zinc, and copper, along with supportive health practices like hydration, meal consistency, frequency of meal consumption and physical activity, often ameliorate respiratory infections, in part by modulating the immune response. Though at present there is a lack of well-defined nutrition-based guidelines for COVID-19 patient care, this paper brings forward the existing relevant evidence base for caregivers and patients to use as a reference/guide.

Cerebral embolism from a cardiac myxoma is a rare cause of ischaemic stroke. These emboli may later lead to the development of cerebral aneurysms. We report a case of delayed presentation of neurological manifestations in form of multiple intracranial aneurysms many years after treatment of a cardiac myxoma. Our patient, a 55-year-old right-handed female with a background history of hypertension, first presented at the age of 45 years with a sudden onset of right hemiplegia. A CT brain scan detected multiple infarcts in the territory of the left middle cerebral artery. Echocardiography revealed a cardiac myxoma for which she underwent immediate total surgical resection. Nearly 10 years after this diagnosis, she presented again with right-sided weakness and left ptosis. CT scan of the brain revealed bilateral acute superior cerebellar infarcts with interval evolution of previously known left cortical infarcts. MRI/MR angiogram showed multiple aneurysms arising from the bilateral middle, left anterior and left posterior cerebral arteries. She was managed conservatively. The management of multiple aneurysms with cardiac myxomas is highly debatable and dependent on the patient’s presentation. This case highlights the importance to follow up on potential late extra-cardiac manifestations of the myxomas despite adequate resection.

Background Spontaneous intracerebral hemorrhage (ICH) is a devastating cerebrovascular disease with high morbidity and mortality. Branching pattern of the lenticulostriate arteries from the middle cerebral artery makes them susceptible to formation of microaneurysms, which have been implicated in hypertensive ICH. Recurrence of hematoma due to delayed development of pseudoaneurysm after initial surgical evacuation is uncommon. Case Description Our patient is a 61-year-old gentleman who underwent primary evacuation of a spontaneous right-sided ICH. The initial vascular imaging was unremarkable for any underlying vascular malformation. After initial neurologic recovery, the patient developed another rebleeding in the hematoma cavity nearly 10 days after presentation. A formal angiogram showed the presence of a pseudoaneurysm that was treated via endovascular means. Conclusions The rates of rebleeding have ranged from 10%−40% in various studies and have been directly correlated with mortality. Since follow-up with angiograms are not a usual practice in spontaneous ICH management, such as pseudoaneurysmal rebleeds could go undiagnosed. This case report reinforces the need for a thorough angiographic evaluation in the event of a deviation from expected clinical course, rebleeding not in concordance with intraoperative findings and significantly delayed hematoma recurrence.

More often, the user likes to visit the web documents that appear in few top excellent responses to the list of links provided by the search engine and these results are the most likely accurate results to the search query. The Information Retrieval by Search Engine helps in retrieving the most relevant pages for query. In this paper, we propose an ideal technique for link analysis by taking web graph structure and we focus around the ranking of such links. The relevancy of the links is evaluated by using Markov Chain Principle and also query keyword occurrence is given a weight-age to the overall ranking of the links. The term proximity and discounted cumulative gain are used to simulate results and the scores show that the proposed methodology efficiently enhances the ranking of the web pages.