Unravelling reference bias in ancient DNA datasets.

MOTIVATION: The alignment of sequencing reads is a critical step in the characterization of ancient genomes. However, reference bias and spurious mappings pose a significant challenge, particularly as cutting-edge wet lab methods generate datasets that push the boundaries of alignment tools. Reference bias occurs when reference alleles are favoured over alternative alleles during mapping, whereas spurious mappings stem from either contamination or when endogenous reads fail to align to their correct position. Previous work has shown that these phenomena are correlated with read length but a more thorough investigation of reference bias and spurious mappings for ancient DNA has been lacking. Here, we use a range of empirical and simulated palaeogenomic datasets to investigate the impacts of mapping tools, quality thresholds, and reference genome on mismatch rates across read lengths. RESULTS: For these analyses, we introduce AMBER, a new bioinformatics tool for assessing the quality of ancient DNA mapping directly from BAM-files and informing on reference bias, read length cut-offs and reference selection. AMBER rapidly and simultaneously computes the sequence read mapping bias in the form of the mismatch rates per read length, cytosine deamination profiles at both CpG and non-CpG sites, fragment length distributions, and genomic breadth and depth of coverage. Using AMBER, we find that mapping algorithms and quality threshold choices dictate reference bias and rates of spurious alignment at different read lengths in a predictable manner, suggesting that optimized mapping parameters for each read length will be a key step in alleviating reference bias and spurious mappings. AVAILABILITY AND IMPLEMENTATION: AMBER is available for noncommercial use on GitHub (https://github.com/tvandervalk/AMBER.git). Scripts used to generate and analyse simulated datasets are available on Github (https://github.com/sdolenz/refbias_scripts).

Long-Term Proton Pump Inhibitor Therapy and its Effect on Endocrine Hormones in Selected Patient Population.

Proton pump inhibitors (PPI) are commonly prescribed medications for a variety of gastrointestinal disorders around the globe. Long-term utilization of proton pump inhibitors is linked with different adverse events. Although, short-term therapy has been demonstrated to have little or no impact on endocrine hormones in men, yet its safety with long-term use has poorly been studied. We aimed to evaluate the impacts of long-term utilization of proton pump inhibitors on male reproductive hormones and its clinical outcomes. A cross-sectional study was performed in two out-patients gastroenterology clinics in Khyber Pakhtunkhwa province. Male patients who were using PPIs regularly for≥3 months were enrolled in this study. Among 65 enrolled participants, patients with sexual complaints have significant variations in mean serum levels of prolactin (p<0.001), sex hormone binding globulins (p=0.043), total testosterone (p<0.001) and progesterone (p=0.001) as compared to patients without sexual complaints. Significantly high values of prolactin mean ranks were observed in patient with sexual complaints (p<0.001). There were statistically significant correlations of serum levels of sex hormone binding globulins (p=0.003), total testosterone (p=0.008) and progesterone (p<0.001) with serum prolactin levels. Similarly, statistically significant variation was observed for decreased libido (p=0.001), erectile dysfunction (p=0.001) and decreased semen mass ((p<0.001) between normal and hyperprolactinemic PPI users. Highly significant differences were observed in serum sex hormone binding globulins (p<0.001), total testosterone (p<0.001) and progesterone (p<0.001) values in normal and hyperprolactinemic groups. In conclusion, long-term utilization of PPI may induce endocrine hormone disruption with subsequent sexual complications.

A hierarchical three-step superpixels and deep learning framework for skin lesion classification.

Skin cancer is one of the most common and dangerous cancer that exists worldwide. Malignant melanoma is one of the most dangerous skin cancer types has a high mortality rate. An estimated 196,060 melanoma cases will be diagnosed in 2020 in the USA. Many computerized techniques are presented in the past to diagnose skin lesions, but they are still failing to achieve significant accuracy. To improve the existing accuracy, we proposed a hierarchical framework based on two-dimensional superpixels and deep learning. First, we enhance the contrast of original dermoscopy images by fusing local and global enhanced images. The entire enhanced images are utilized in the next step to segmentation skin lesions using three-step superpixel lesion segmentation. The segmented lesions are mapped over the whole enhanced dermoscopy images and obtained only segmented color images. Then, a deep learning model (ResNet-50) is applied to these mapped images and learned features through transfer learning. The extracted features are further optimized using an improved grasshopper optimization algorithm, which is later classified through the Naïve Bayes classifier. The proposed hierarchical method has been evaluated on three datasets (Ph2, ISBI2016, and HAM1000), consisting of three, two, and seven skin cancer classes. On these datasets, our method achieved an accuracy of 95.40%, 91.1%, and 85.50%, respectively. The results show that this method can be helpful for the classification of skin cancer with improved accuracy.

Burnout in South Asian rheumatologists in the COVID-19 pandemic: an online survey.

Physician burnout is recognized as a global crisis and an epidemic. However, burnout in rheumatology is an understudied phenomenon. We explored the prevalence of physician burnout among rheumatologists from South Asia in the peri-pandemic period (2021-2022). Rheumatologists from Asian countries were invited to participate in an anonymized, validated, and pilot-tested e-survey via social media platforms from December 2021 to April 2022. Demographic information, social aspects (marital status, income, vacation time, daily exercise), substance abuse, EHR (electronic health record) use, and years in practice were obtained. In addition, burnout was estimated using Maslach Burnout Inventory-Human Services Survey for Medical Personnel (MBI-HSS) in three domains: emotional exhaustion (EE), depersonalization (DP), and personal accomplishment (PA), and intergroup comparisons were made using independent t test and one-way ANOVA using SPSS v27. Of 146 respondents who participated in the survey, 134 belonged to Asian nations. The highest number of respondents was from Pakistan (56/134, 38.36%), followed by India (49/134, 33.56%). Slightly more respondents were male, 75 (51.4%), than females, 71 (48.6%). Over two-thirds of our respondents (99/134, 67.8%) reported burnout in at least one domain. Notably, we found statistically significant increased depersonalization scores in males. (P < 0.05). Females scored significantly higher on the following items: #5 (I feel I treat some patients as if they were impersonal objects), item# 10 (I've become more insensitive toward people since I took this job and item#22 (I feel patients blame me for some of their problems) (P < 0.05). We found differences in monthly salaries among South Asian (1484 ± 2717 USD) and non-South Asian respondents (5672 ± 8874 USD) (P < 0.01). A substantial proportion of rheumatologists in our survey report burnout, suggesting a felt need to introduce organizational measures to prevent and mitigate burnout and preserve the rheumatology workforce.

Biofabrication of Fe3O4 Nanoparticles from Spirogyra hyalina and Ajuga bracteosa and Their Antibacterial Applications.

Iron oxide nanoparticles (NPs) have attracted substantial interest due to their superparamagnetic features, biocompatibility, and nontoxicity. The latest progress in the biological production of Fe3O4 NPs by green methods has improved their quality and biological applications significantly. In this study, the fabrication of iron oxide NPs from Spirogyra hyalina and Ajuga bracteosa was conducted via an easy, environmentally friendly, and cost-effective process. The fabricated Fe3O4 NPs were characterized using various analytical methods to study their unique properties. UV-Vis absorption peaks were observed in algal and plant-based Fe3O4 NPs at 289 nm and 306 nm, respectively. Fourier transform infrared (FTIR) spectroscopy analyzed diverse bioactive phytochemicals present in algal and plant extracts that functioned as stabilizing and capping agents in the fabrication of algal and plant-based Fe3O4 NPs. X-ray diffraction of NPs revealed the crystalline nature of both biofabricated Fe3O4 NPs and their small size. Scanning electron microscopy (SEM) revealed that algae and plant-based Fe3O4 NPs are spherical and rod-shaped, averaging 52 nm and 75 nm in size. Energy dispersive X-ray spectroscopy showed that the green-synthesized Fe3O4 NPs require a high mass percentage of iron and oxygen to ensure their synthesis. The fabricated plant-based Fe3O4 NPs exhibited stronger antioxidant properties than algal-based Fe3O4 NPs. The algal-based NPs showed efficient antibacterial potential against E. coli, while the plant-based Fe3O4 NPs displayed a higher zone of inhibition against S. aureus. Moreover, plant-based Fe3O4 NPs exhibited superior scavenging and antibacterial potential compared to the algal-based Fe3O4 NPs. This might be due to the greater number of phytochemicals in plants that surround the NPs during their green fabrication. Hence, the capping of bioactive agents over iron oxide NPs improves antibacterial applications.

Potential drug-drug interactions in patients presenting with osteoarthritis to community orthopaedic clinics of Abbottabad, Khyber Pakhtunkhwa: A cross-sectional study.

OBJECTIVES: Osteoarthritis (OA) causes long-term pain and disorders of lower extremities. Paracetamol is the drug of choice; however, NSAIDs, opioids and steroids are frequently employed in the symptomatic relief of OA. The prescribing of multiple analgesics leads to potential drug-drug interactions (pDDIs). The primary objective of this study was to identify the prevalence and predictors of pDDIs in OA. MATERIALS AND METHODS: A total of three hundred and eighty-six patients, either newly diagnosed or with a history of OA, were enrolled for this cross-sectional study. Data regarding patients' demographics, clinical characteristics and prescribed medications were recorded from the prescriptions and examined for the pDDIs using Medscape multidrug interaction checker. RESULTS: Among 386, most patients were females (53.4%). The most prevalent diagnoses were knee OA (39.7%) and unspecified OA (31.3%). Paracetamol and topical NSAIDs were underprescribed whereas an oral NSAID, Diclofenac, was the most frequently used drug in OA. Total of 109 pDDIs were found in 386 prescriptions, of which 63.3% DDIs were categorised as moderate, followed by minor (34.9%) and major (1.8%). CONCLUSIONS: This study finds a prevalence of DDIs and polypharmacy among the OA patients. Collaborative efforts among healthcare providers, pharmacists, and patients themselves are essential to optimize medication regimens and minimize the polypharmacy including the associated risks as well as DDIs.

Rotavirus exploits SREBP pathway for hyper lipid biogenesis during replication.

Species A rotavirus (RVA) is one of the pathogens causing severe acute gastroenteritis in young children and animals worldwide. RVA replicates and assembles its immature particle within electron dense compartments known as viroplasm. Despite the importance of lipid droplet (LD) formation in the RVA viroplasm, the upstream molecules modulating LD formation have remained elusive. Here, we demonstrate that RVA infection reprogrammes sterol regulatory element binding proteins (SREBPs)-dependent lipogenic pathways in virus-infected cells. Interestingly, silencing of SREBPs significantly reduced RVA protein synthesis, genome replication and progeny virus production. Moreover, knockout of SREBP-1c gene conferred resistance to RVA-induced diarrhoea, reduction of RVA replication, and mitigation of small intestinal pathology in mice. This study identifies SREBPs-mediated lipogenic reprogramming in RVA-infected host cells for facilitating virus replication and SREBPs as a potential target for developing therapeutics against RVA infection.

Porcine Sapovirus-Induced Tight Junction Dissociation via Activation of RhoA/ROCK/MLC Signaling Pathway.

Tight junctions (TJs) are a major barrier and also an important portal of entry for different pathogens. Porcine sapovirus (PSaV) induces early disruption of the TJ integrity of polarized LLC-PK cells, allowing it to bind to the buried occludin co-receptors hidden beneath the TJs on the basolateral surface. However, the signaling pathways involved in the PSaV-induced TJ dissociation are not yet known. Here, we found that the RhoA/ROCK/MLC signaling pathway was activated in polarized LLC-PK cells during the early infection of PSaV Cowden strain in the presence of bile acid. Specific inhibitors of RhoA, ROCK, and MLC restored PSaV-induced reduction of transepithelial resistance, increase of paracellular flux, intracellular translocation of occludin, and lateral membrane lipid diffusion. Moreover, each inhibitor significantly reduced PSaV replication, as evidenced by a reduction in viral protein synthesis, genome copy number, and progeny viruses. The PKC/MLCK and RhoA/ROCK/MYPT signaling pathways, known to dissociate TJs, were not activated during early PSaV infection. Among the above signaling pathways, the RhoA/ROCK/MLC signaling pathway was only activated by PSaV in the absence of bile acid, and specific inhibitors of this signaling pathway restored early TJ dissociation. Our findings demonstrate that PSaV binding to cell surface receptors activates the RhoA/ROCK/MLC signaling pathway, which in turn disrupts TJ integrity via the contraction of the actomyosin ring. Our study contributes to understanding how PSaV enters the cells and will aid in developing efficient and affordable therapies against PSaV and other calicivirus infections.IMPORTANCEPorcine sapovirus (PSaV), one of the most important enteric pathogens, is known to disrupt tight junction (TJ) integrity to expose its buried co-receptor occludin in polarized LLC-PK cells. However, the cellular signaling pathways that facilitate TJ dissociation are not yet completely understood. Here, we demonstrate that early infection of PSaV in polarized LLC-PK cells in either the presence or absence of bile acids activates the RhoA/ROCK/MLC signaling pathway, whose inhibitors reverse the early PSaV infection-induced early dissociation of TJs and reduce PSaV replication. However, early PSaV infection did not activate the PKC/MLCK and RhoA/ROCK/MYPT signaling pathways, which are also known to dissociate TJs. This study provides a better understanding of the mechanism involved in early PSaV infection-induced disruption of TJs, which is important for controlling or preventing PSaV and other calicivirus infections.

Proposing the n+-AlGaN tunnel junction for an efficient deep-ultraviolet light-emitting diode at 254 nm emission.

Toxic and low-pressure deep-ultraviolet (DUV) mercury lamps have been used widely for applications of surface disinfection and water sterilization. The exposure of pathogens to 254 nm DUV radiations has been proven to be an effective and environmentally safe way to inactivate germs as well as viruses in short time. To replace toxic mercury DUV lamps, an n +-A l G a N tunnel junction (TJ)-based DUV light-emitting diode (LED) at 254 nm emission has been investigated. The studied conventional LED device has maximum internal quantum efficiency (IQE) of 50% with an efficiency droop of 18% at 200A/c m 2. In contrast, the calculated results show that a maximum IQE of 82% with a 3% efficiency droop under a relatively higher injection current was estimated by employing a 5 nm thin n +-A l G a N TJ with a 0.70 aluminum molar fraction. In addition, the TJ LED emitted power has been improved significantly by 2.5 times compared with a conventional LED structure. Such an efficient n +-A l G a N TJ-based DUV LED at 254 nm emission might open a new way, to the best of our knowledge, for the development of safe and efficient germicidal irradiation sources.

Multiclass Skin Lesion Classification Using Hybrid Deep Features Selection and Extreme Learning Machine.

The variation in skin textures and injuries, as well as the detection and classification of skin cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a difficult and time-consuming process. Recent advancements in the domains of the internet of things (IoT) and artificial intelligence for medical applications demonstrated improvements in both accuracy and computational time. In this paper, a new method for multiclass skin lesion classification using best deep learning feature fusion and an extreme learning machine is proposed. The proposed method includes five primary steps: image acquisition and contrast enhancement; deep learning feature extraction using transfer learning; best feature selection using hybrid whale optimization and entropy-mutual information (EMI) approach; fusion of selected features using a modified canonical correlation based approach; and, finally, extreme learning machine based classification. The feature selection step improves the system's computational efficiency and accuracy. The experiment is carried out on two publicly available datasets, HAM10000 and ISIC2018. The achieved accuracy on both datasets is 93.40 and 94.36 percent. When compared to state-of-the-art (SOTA) techniques, the proposed method's accuracy is improved. Furthermore, the proposed method is computationally efficient.

Intelligent Tracking of Mechanically Thrown Objects by Industrial Catching Robot for Automated In-Plant Logistics 4.0.

Industry 4.0 smart manufacturing systems are equipped with sensors, smart machines, and intelligent robots. The automated in-plant transportation of manufacturing parts through throwing and catching robots is an attempt to accelerate the transportation process and increase productivity by the optimized utilization of in-plant facilities. Such an approach requires intelligent tracking and prediction of the final 3D catching position of thrown objects, while observing their initial flight trajectory in real-time, by catching robot in order to grasp them accurately. Due to non-deterministic nature of such mechanically thrown objects' flight, accurate prediction of their complete trajectory is only possible if we accurately observe initial trajectory as well as intelligently predict remaining trajectory. The thrown objects in industry can be of any shape but detecting and accurately predicting interception positions of any shape object is an extremely challenging problem that needs to be solved step by step. In this research work, we only considered spherical shape objects as their3D central position can be easily determined. Our work comprised of development of a 3D simulated environment which enabled us to throw object of any mass, diameter, or surface air friction properties in a controlled internal logistics environment. It also enabled us to throw object with any initial velocity and observe its trajectory by placing a simulated pinhole camera at any place within 3D vicinity of internal logistics. We also employed multi-view geometry among simulated cameras in order to observe trajectories more accurately. Hence, it provided us an ample opportunity of precise experimentation in order to create enormous dataset of thrown object trajectories to train an encoder-decoder bidirectional LSTM deep neural network. The trained neural network has given the best results for accurately predicting trajectory of thrown objects in real time.

Staged energy and water quality optimization for large water distribution systems.

Simultaneous optimization of energy and water quality in real-time large-sized water distribution systems is a daunting task for water suppliers. The complexity of energy optimization increases with a large number of pipes, scheduling of several pumps, and adjustments of tanks' water levels. Most of the simultaneous energy and water quality optimization approaches evaluate small (or hypothetical) networks or compromise water quality. In the proposed staged approach, Stage 1 uses a risk-based approach to optimally locate the chlorine boosters in a large distribution system based on residual chlorine failures and the associated consequences in different land uses of the service area. Integrating EPANET and CPLEX software, Stage 2 uses mixed integer goal programming for optimizing the day-ahead pump scheduling. The objective function minimizes the pumping energy cost as well as the undesirable deviations from goal constraints, such as expected water demand. Stage 3 evaluates the combined hydraulics and water quality performances at the network level. The implementation of the proposed approach on a real-time large-sized network of Al-Khobar City in Saudi Arabia, with 44 groundwater wells, 12 reservoirs, 2 storage tanks, 191 mains, 141 junctions, and 17 pumps, illustrated the practicality of the framework. Simulating the network with an optimal pumping schedule and chlorine boosters' locations shows a 40% improvement in water quality performance, desired hydraulics performance with optimal pump scheduling, and an average 20% energy cost reduction compared to the normal (unoptimized) base case scenario.

Individual and organizational barriers faced by physiotherapists in implementing evidence based practice - an analytical study.

OBJECTIVE: To determine the present barriers in the implementation of evidence-based physiotherapy practice. METHODS: The analytical cross-sectional study was conducted in Lahore, Pakistan, from 06 January 2021 to 30th April 2021 and comprised physiotherapists practising either in government facility or in private clinic for a minimum of 2 years and who had either studied or had some idea about evidence-based physiotherapy practice. Data was collected using the Barrier Scale. Data was analysed using SPSS 16. RESULTS: Of the 235 subjects, 104(44.3%) were males and 131(55.7%) were females with an overall mean age of 31.5+9.5 years. Of the total, 151(64.30%) subjects had 2-5 years of experience, and 66(28.10%) had 6-7 years of working experience. There was no significant association of working experience with time on job to implement new ideas and time to read research (p>0.05). CONCLUSIONS: The physiotherapist faced barriers at both organisational and individual levels.

Ceftriaxone-induced hepatotoxicity in patients with common medical infections in Qatar: A retrospective study.

INTRODUCTION: Ceftriaxone, a third-generation cephalosporin, is frequently used for the treatment of various bacterial infections as a broad-spectrum antibiotic for many decades. Although ceftriaxone is a well-tolerated drug in most cases, it can lead to serious liver injury, which can be a real challenge to the treating physician. Given the potentially serious adverse effects that can vary from mild biochemical abnormalities to complete liver failure, we intend to assess the spectrum of liver injury based on biochemical criteria for patients treated with ceftriaxone for common bacterial infections in Qatar. OBJECTIVES: This study aimed to explore the incidence of ceftriaxone-induced liver injury at Hazm Mebaireek General Hospital, Qatar, and to evaluate the relationship of the ceftriaxone dose, if any, with liver dysfunction. METHODS: This retrospective study included hospitalized adult patients treated with ceftriaxone at our hospital from January 2019 to December 2019 and analyzed demographic and clinical data obtained from electronic medical records. This study determined the incidence of liver injury (primary outcome) in patients treated with ceftriaxone (2 g/day) for ≥ 2 consecutive days by reviewing liver function test results until the day of discharge and at the first outpatient follow-up. RESULTS: The final data analysis included a total of 634 patients admitted and treated with ceftriaxone from January 2019 to December 2019.In the multivariate analysis with propensity score adjustment, ceftriaxone was independently associated with liver injury, especially when combined with other agents utilizing hepatic metabolism. CONCLUSIONS: Ceftriaxone was associated with a significantly higher incidence of liver injury (19.7%) when used along with other medications that are metabolized in the liver, as found in the present study compared with other similar studies (approximately 2.9%-13.9%). Furthermore, the incidence was too high to be ignored in clinical practice.

Demographics, clinical characteristics, and recurrence rate of patients with primary spontaneous pneumothorax at a tertiary care center in Qatar.

INTRODUCTION: Primary spontaneous pneumothorax (PSP) is a common medical emergency. Its treatment includes simple observation, needle thoracentesis, pleural catheter, video-assisted thoracoscopy (VATS), and open surgery. We aimed to establish the demographic, clinical characteristics, and 12-month recurrence rate of patients with PSP in four hospitals of the Hamad Medical Corporation, Qatar. MATERIALS AND METHODS: We conducted a retrospective analysis of patients >14 years old who were admitted with PSP from January 1, 2017 to December 31, 2019. The patients were followed up for 12 months for the recurrence of PSP. RESULTS: Out of 246 patients enrolled in this study, 223 (90.7%) were males and 23 (9.3%) were females. Their mean age was 29.1 ± 9.59 years and their mean body mass index (BMI) was 21.7 ± 4.22 kg/m2. Of these, 123 (51.2%) patients were smokers. Chest pain was the most common presenting complaint (82.5%). A total of 59 (23.98%) patients had a small pneumothorax, whereas 187 (76.01%) patients had a large pneumothorax. Among the patients with small pneumothorax, 16 (28.33%) were managed through observation alone, 2 (3.33%) required needle aspiration, 15 (25%) required pleural catheter insertion, and 26 (44.06%) underwent surgical intervention for management. Out of 187 patients with large pneumothorax, 16 (8.6%) were managed through observation, 7 (3.76%) required needle aspiration, 73 (38.1%) required pleural catheter insertion, and 91 (48.6%) underwent surgery. During the 12-month follow-up, 58 patients were lost to follow-up and 5 patients (5/188; 2.66%) presented with a recurrence of PSP. Out of 108 patients who underwent VATS, 2 (1.85%) had a recurrence of PSP. CONCLUSION: PSP is more common in males than in females, with a tendency for younger age onset. The recurrence rate of PSP in our study was 2.66%. Furthermore, the recurrence rate in our patients who underwent VATS was 1.85%. Prospective studies are warranted to compare the success rates of different treatment interventions.

Compositionally graded AlGaN hole source layer for deep-ultraviolet nanowire light-emitting diode without electron blocking layer.

The electron blocking layer (EBL) plays a vital role in blocking the electron overflow from an active region in the AlGaN-based deep-ultraviolet light-emitting diode (DUV-LED). Besides the blocking of electron overflow, EBL reduces hole injection toward the active region. In this work, we proposed a DUV nanowire (NW) LED structure without EBL by replacing it with a compositionally continuous graded hole source layer (HSL). Our proposed graded HSL without EBL provides a better electron blocking effect and enhanced hole injection efficiency. As a result, optical power is improved by 48% and series resistance is reduced by 50% with 4.8 V threshold voltage. Moreover, graded HSL without EBL offer reduced electric field within the active region, which leads to a significant increment in radiative recombination rate and enhancement of spontaneous emission by 34% at 254 nm wavelength, as a result, 52% maximum internal quantum efficiency with 24% efficiency drop is reported.

First case report of acute cholangitis secondary to Cronobacter sakazakii.

INTRODUCTION: Cronobacter sakazakii is an opportunistic Gram-negative, rod-shaped bacterium which may be a causative agent of meningitis in premature infants and enterocolitis and bacteremia in neonates and adults. While there have been multiple cases of C. sakazakii infections, there have been no acute cholangitis cases reported in humans. CASE PRESENTATION: An 81-year-old male with a past medical history of basal cell carcinoma, alcoholic liver cirrhosis, transjugular intrahepatic portosystemic shunt procedure, complicated by staphylococcus bacteremia, pituitary tumor, glaucoma, and hypothyroidism presented to the emergency room with the complaint of diffuse and generalized 10/10 abdominal pain of 1 day's duration. There was a concern for pancreatitis, acute cholangitis, and possible cholecystitis, and the patient underwent a percutaneous cholecystostomy tube placement. Blood cultures from admission and biliary fluid cultures both grew C. sakazakii. The patient was treated with a carbapenem and clinically improved. CONCLUSIONS: The case study described a patient with multiple medical comorbidities that presented with C. sakazakii bacteremia and cholangitis. While this bacterium has been implicated in other infections, we believe this is the first time the bacteria is being documented to have caused acute cholangitis.

A Decision Support System for Face Sketch Synthesis Using Deep Learning and Artificial Intelligence.

The recent development in the area of IoT technologies is likely to be implemented extensively in the next decade. There is a great increase in the crime rate, and the handling officers are responsible for dealing with a broad range of cyber and Internet issues during investigation. IoT technologies are helpful in the identification of suspects, and few technologies are available that use IoT and deep learning together for face sketch synthesis. Convolutional neural networks (CNNs) and other constructs of deep learning have become major tools in recent approaches. A new-found architecture of the neural network is anticipated in this work. It is called Spiral-Net, which is a modified version of U-Net fto perform face sketch synthesis (the phase is known as the compiler network C here). Spiral-Net performs in combination with a pre-trained Vgg-19 network called the feature extractor F. It first identifies the top n matches from viewed sketches to a given photo. F is again used to formulate a feature map based on the cosine distance of a candidate sketch formed by C from the top n matches. A customized CNN configuration (called the discriminator D) then computes loss functions based on differences between the candidate sketch and the feature. Values of these loss functions alternately update C and F. The ensemble of these nets is trained and tested on selected datasets, including CUFS, CUFSF, and a part of the IIT photo-sketch dataset. Results of this modified U-Net are acquired by the legacy NLDA (1998) scheme of face recognition and its newer version, OpenBR (2013), which demonstrate an improvement of 5% compared with the current state of the art in its relevant domain.

Prediction of COVID-19 - Pneumonia based on Selected Deep Features and One Class Kernel Extreme Learning Machine.

In this work, we propose a deep learning framework for the classification of COVID-19 pneumonia infection from normal chest CT scans. In this regard, a 15-layered convolutional neural network architecture is developed which extracts deep features from the selected image samples - collected from the Radiopeadia. Deep features are collected from two different layers, global average pool and fully connected layers, which are later combined using the max-layer detail (MLD) approach. Subsequently, a Correntropy technique is embedded in the main design to select the most discriminant features from the pool of features. One-class kernel extreme learning machine classifier is utilized for the final classification to achieving an average accuracy of 95.1%, and the sensitivity, specificity & precision rate of 95.1%, 95%, & 94% respectively. To further verify our claims, detailed statistical analyses based on standard error mean (SEM) is also provided, which proves the effectiveness of our proposed prediction design.

Isolation and identification of Saccharomyces cerevisiae for fermentation of rice polishing in Livestock feeding.

Biomass of Saccharomyces cerevisiae wasenhancedin rice polishing by fermentation to increase protein contents of feedfor its use in livestock. Broth culture of Saccharomyces cerevisiae (2.6×108CFU/mL) was prepared from culture obtained by continuous streaking. The isolated culture was identified morphologically by Gram staining and confirmed by biochemical characteristics. Rice polishing was sieved to remove larger particles. Then it was distributed to 4 treatments in triplicates. Treatments were represented as rice polishing (RP), rice polishing plus Saccharomyces culture (RPSC), rice polishing plus ammonium sulphate (RPAS), rice polishing plus Saccharomyces culture plus ammonium sulphate (RPSCAS).Fermentation was provided for 144 hours at 320C,while samples were collected after every 24 hours. Samples were dried, ground and subjected to proximate analysis. It was observed that protein content was increased from 11% to 21.51% and maximum increment was obtained after 144 hours of incubation in RPSC treatment. Ether extract and ash were increased from 14% and 10% to 16.96% and 11.11% in RPSCAS respectively. A significant reduction in neutral detergent fiber was observed after fermentation. It is concluded that Saccharomyces cerevisiae has potential to improve mineral and protein contents of rice polishing by fermentation process with or without addition of nitrogen source.