Multifaceted role of TRIM21 in inflammation.

Tripartite motif (TRIM) family members participate in a variety of cellular activities, such as intracellular signaling, development, cellular death, protein quality control, immunological defense, waste degradation, and the emergence of cancer. These proteins usually act as E3 ubiquitin ligase. The final line of resistance against infectious viruses is a cytosolic ubiquitin ligase and antibody receptor called TRIM containing 21. TRIM21, a protein with a tripartite structure, has been linked to autoimmune erythematosus, Sjogren's disorder, and innate immunity. TRIM21 may either promote the formation of specific cancer-activating proteins, resulting in their proteasomal degradation, or it may do neither, depending on the kind of cancer and cancer-causing trigger. The current research has shown that the antiviral action of TRIM mostly depends on their role as E3-ubiquitin ligases and a significant portion of the TRIM family mediates the transmission of innate immune cell signals and the subsequent production of cytokines. We highlighted the function of TRIM family members in various inflammatory diseases.

An idiopathic severe macroglossia in a young adult patient: a rare case.

Macroglossia, an uncommon anatomical anomaly, can manifest as either congenital or acquired. The size of the tongue undergoes variations with age, peaking at 8 years and reaching full maturity at 18 years. Congenital macroglossia stems from diverse conditions, such as muscular hypertrophy, hemangioma, lymphangioma, Down syndrome, and others. Acquired macroglossia can result from malignancies, endocrine and metabolic disorders, chronic infectious diseases, and head and neck infections, among other factors. Additionally, extended-prone surgery can lead to its development. The incidence of macroglossia is likely underreported. This presentation is rare with only six reported cases in the literature.

Novel frameless LINAC radiosurgery solution for uveal melanoma.

Introduction: Radiation treatment has replaced enucleation as an organ-preservation treatment for patients with uveal melanoma (UM). We developed a novel non-invasive, frameless LINAC based solution for fractionated stereotactic radiosurgery (fSRS) treatment. Methods: We designed and constructed the a stereotactic ocular localization box that can be attached and indexed to a stereotactic LINAC tabletop. It contains adjustable LED lights as a gaze focus point and CCD camera for monitoring of the patient's eye position. The device also has 6 infrared spheres compatible with the ExacTRAC IGRT system. Treatment plans were developed using iPLAN Dose version 4.5, with conformal dynamic arcs and 6MV photon beam in flattening filter free mode, dosed to 50Gy in 5 fractions. During treatment, patients were instructed to stare at the light when a radiation beam is prepared and ready for delivery. Eye movement was tracked throughout treatment. Residual setup errors were recorded for evaluation. Results: The stereotactic ocular localization box was 3D-printed with polylactic acid material and attached to the stereotactic LINAC tabletop. 10 patients were treated to evaluate the feasibility, tolerability and setup accuracy. Median treatment time for each arc is 17.3 ± 2.4 seconds (range: 13.8-23.4). After ExacTRAC setup, the residual setup errors are -0.1 ± 0.3 mm laterally, -0.1 ± 0.3 mm longitudinally, and 0 ± 0.2 mm vertically. The residue rotational errors are -0.1 ± 0.3 degree pitch, 0.1 ± 0.2 degree roll, and 0 ± 0.2 degree couch rotation. All patients received treatment successfully. Conclusion: We successfully developed a novel non-invasive frameless mask-based LINAC solution for SRS for uveal melanoma, or other ocular tumors. It is well tolerated with high set up accuracy. Future directions for this localization box would include a multi-center trial to assess the efficacy and reproducibility in the fabrication and execution of such a solution for UM therapy.

Shining insights: Deciphering the biogenic synthesis of Ajuga bracteosa-mediated gold nanoparticles with advanced microscopy techniques.

In this study, gold nanoparticles (AuNPs) were bioreduced from Ajuga bracteosa, a medicinal herb known for its therapeutic properties against various diseases. Different fractions of the plant extract were used, including the methanolic fraction (ABMF), the n-hexane fraction (ABHF), the chloroform fraction (ABCF), and the aqueous extract for AuNPs synthesis. The characterization of AuNPs was performed using UV-Vis spectrophotometry, FT-IR, XRD, EDX, and TEM. UV-Vis spectroscopy confirmed the formation of AuNPs, with peaks observed at 555 nm. FT-IR analysis indicated strong capping of phytochemicals on the surface of AuNPs, which was supported by higher total phenolic contents (TPC) and total flavonoid contents (TFC) in AuNPs. XRD results showed high crystallinity and a smaller size distribution of AuNPs. TEM analysis revealed the spherical shape of AuNPs, with an average size of 29 ± 10 nm. The biologically synthesized AuNPs exhibited superior antibacterial, antioxidant, and cytotoxic activities compared to the plant extract fractions. The presence of active biomolecules in A. bracteosa, such as neoclerodan flavonol glycosides, diterpenoids, phytoecdysone, and iridoid glycosides, contributed to the enhanced biological activities of AuNPs. Overall, this research highlights the potential of A. bracteosa-derived AuNPs for various biomedical applications due to their remarkable therapeutic properties and effective capping by phytochemicals. RESEARCH HIGHLIGHTS: This research underscores the growing significance of herbal medicine in contemporary healthcare by exploring the therapeutic potential of Ajuga bracteosa and gold nanoparticles (AuNPs). The study highlights the notable efficacy of A. bracteosa leaf extracts and AuNPs in treating bacterial infections, demonstrating their bactericidal effects on a range of strains. The anti-inflammatory properties of plant extracts and nanoparticles are evidenced through paw edema method suggesting their applicability in managing inflammatory conditions. These findings position A. bracteosa and AuNPs as potential candidates for alternative and effective approaches to modern medication.

Hypertrophic Pachymeningitis: An Unusual Cause of Headache.

Hypertrophic pachymeningitis (HP) is a rare condition characterized by inflammation and thickening of the dura mater. It can be idiopathic or secondary to various causes, including infections, tumors, or systemic inflammatory diseases. Diagnosis is challenging due to its rarity and the overlap of symptoms with other conditions. We present the case of a 42-year-old Hispanic woman with diabetes mellitus type 2 and end-stage kidney disease who presented with chest pain, dry cough, mild dyspnea, and chronic occipital headaches. Physical examination revealed cranial VI nerve palsy. Imaging showed pulmonary cavitary lesions and mediastinal lymphadenopathy. Elevated inflammatory markers and positive autoimmune tests, including rheumatoid factor and antineutrophil cytoplasmic antibody (ANCA), led to further investigation. Brain imaging revealed dural thickening, confirming HP. The patient's medical history revealed double ANCA positivity and a lung biopsy confirmed granulomatous pneumonitis. A diagnosis of ANCA-associated vasculitis (granulomatosis with polyangiitis (GPA)) was established, and treatment with rituximab and high-dose corticosteroids led to symptom improvement. GPA rarely involves meningeal inflammation, but severe and persistent headaches are common early symptoms. Inflammatory markers are often elevated, and around two-thirds of HP cases related to GPA have positive serum ANCA. MRI is the primary diagnostic tool, with characteristic findings of dural thickening and contrast enhancement. This case highlights HP as a rare cause of chronic headaches and the importance of a comprehensive medical history in diagnosis. Early recognition and treatment are crucial for improving outcomes in GPA-related HP.

Up-scaling of fly ash-based geopolymer concrete to investigate the binary effect of locally available metakaolin with fly ash.

Owing to the increasing threat to environment due to the emission of greenhouse gases from cement industry globally, various promising solutions has been introduced in the past decades. The development of geoplymer concrete (GPC) is one of the contribution by the researches towards ecofriendly and sustainable construction. In this research, geopolymer concrete (GPC) is optimized by adding fixed amount of fly Ash (FA) and alkali activator to fine aggregate ratio as 0.5 with varying Molarity from 12 M to 16 M and Na2SiO3/NaOH ratio from 1.5 to 2.5. Physical and mechanical properties along with effect of heat and ambient curing conditions were investigated at various ages. The optimized mixture of fly ash based geopolymer concrete was then up scaled by blending with locally available Metakaolin (MK) with different dosages (i.e., 10%, 20%, 30%, 40%). The aim of the study is to identify the binary effect of FA and MK on overall performance of geopolymer concrete. Results showed that 30% FA-MK based GPC depicted 21%, 19% and 26% more compressive strength, split tensile strength and flexural strength respectively than Fly Ash based GPC alone at heat cured condition. This can be explained mainly due to two facts namely binary action of metakaolin that enhances compaction of GPC and pozzolanic activity of MK that expedite geopolymeric strength causing phases. The results were further verified by Modified Chapelle test and FTIR. Morphology of the developed GPC is also examined from SEM images. The work is an effort to utilize the fly ash produced by coal power plants to effectively address UN sustainable development goal related to sustainable cities and communities.

Computer vision-based plants phenotyping: A comprehensive survey.

The increasing demand for food production due to the growing population is raising the need for more food-productive environments for plants. The genetic behavior of plant traits remains different in different growing environments. However, it is tedious and impossible to look after the individual plant component traits manually. Plant breeders need computer vision-based plant monitoring systems to analyze different plants' productivity and environmental suitability. It leads to performing feasible quantitative analysis, geometric analysis, and yield rate analysis of the plants. Many of the data collection methods have been used by plant breeders according to their needs. In the presented review, most of them are discussed with their corresponding challenges and limitations. Furthermore, the traditional approaches of segmentation and classification of plant phenotyping are also discussed. The data limitation problems and their currently adapted solutions in the computer vision aspect are highlighted, which somehow solve the problem but are not genuine. The available datasets and current issues are enlightened. The presented study covers the plants phenotyping problems, suggested solutions, and current challenges from data collection to classification steps.

A Holistic Strategy of Mother and Child Health Care to Improve the Coverage of Routine and Polio Immunization in Pakistan: Results from a Demonstration Project.

BACKGROUND: The eradication of poliovirus and improving routine immunization (RI) coverage rates present significant challenges in Pakistan. There is a need for interventions that focus on strengthening community engagement to improve routine immunization coverage. Our primary objective is to assess the impact of an integrated strategy designed to enhance community engagement and maternal and child health immunization campaigns on immunization coverage in Pakistan's high-risk union councils of polio-endemic districts. METHOD: We implemented an integrated approach for routine immunization and maternal and child health in the polio-endemic district of Pakistan. This approach involved setting up health camps and actively engaging and mobilizing the local community. An independent team conducted surveys at three key points: baseline, midline, and endline, to evaluate immunization coverage among children under the age of five. The primary outcome measures for the study were coverage of OPV, IPV, and changes in the proportion of unvaccinated and fully vaccinated children. To select clusters and eligible households in each cluster, we utilized a 30 × 15 cluster sampling technique. Multivariable associations between socio-demographic factors and changes in the proportion of fully vaccinated children at the UC level were assessed using hierarchical linear regression models. RESULTS: A total of 256,946 children under the age of five (122,950 at baseline and 133,996 at endline) were enrolled in the study. By the endline, full immunization coverage had increased to 60% or more in all three study areas compared to the baseline. Additionally, there was a significant increase in the coverage of both OPV and IPV across all three provinces at the endline. The full immunization rates were assessed on three levels of the framework: the distal, intermediate (access and environment), and proximal level (camp attendance and effectiveness). At the distal level, on multivariate analysis, family size was found to be a significant predictor of change in immunity within the families (ß = 0.68; p ≤ 0.0001). At the intermediate level, the likelihood of full immunization decreased with the decrease in knowledge about vaccination (ß = -0.38; p = 0.002), knowledge about polio vaccine (ß = -0.25; p = 0.011), and knowledge about IPV (ß = -0.06; p = 0.546). Perceived obstacles to vaccination were fear of adverse events (ß = -0.4; p ≤ 0.0001) and lack of education (ß = 0.23; p = 0.031), which were found to be significant in bivariate and multivariate analyses. At the proximal level, community mobilization (ß = 0.26; p = 0.008) and attendance at health camp (ß = 0.21; p ≤ 0.0001) were found to enhance full immunization coverage. On the other hand, the most prominent reason for not attending health camp included no need to attend the health camp as the child was not ill (ß = -0.13; p = 0.008). CONCLUSIONS: This study found that community mobilization and attendance at health camps significantly enhanced full immunization coverage. The findings highlight the importance of community engagement and targeted interventions in improving immunization coverage and addressing barriers to healthcare seeking.

Microscopic parasite malaria classification using best feature selection based on generalized normal distribution optimization.

Malaria disease can indeed be fatal if not identified and treated promptly. Due to advancements in the malaria diagnostic process, microscopy techniques are employed for blood cell analysis. Unfortunately, the diagnostic process of malaria via microscopy depends on microscopic skills. To overcome such issues, machine/deep learning algorithms can be proposed for more accurate and efficient detection of malaria. Therefore, a method is proposed for classifying malaria parasites that consist of three phases. The bilateral filter is applied to enhance image quality. After that shape-based and deep features are extracted. In shape-based pyramid histograms of oriented gradients (PHOG) features are derived with the dimension of N × 300. Deep features are derived from the residual network (ResNet)-50, and ResNet-18 at fully connected layers having the dimension of N × 1,000 respectively. The features obtained are fused serially, resulting in a dimensionality of N × 2,300. From this set, N × 498 features are chosen using the generalized normal distribution optimization (GNDO) method. The proposed method is accessed on a microscopic malarial parasite imaging dataset providing 99% classification accuracy which is better than as compared to recently published work.

Correction: Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

[This corrects the article DOI: 10.1371/journal.pone.0292601.].

Clinically acquired new challenging dataset for brain SOL segmentation: AJBDS-2023.

Space-occupying lesions (SOL) brain detected on brain MRI are benign and malignant tumors. Several brain tumor segmentation algorithms have been developed but there is a need for a clinically acquired dataset that is used for real-time images. This research is done to facilitate reporting of MRI done for brain tumor detection by incorporating computer-aided detection. Another objective was to make reporting unbiased by decreasing inter-observer errors and expediting daily reporting sessions to decrease radiologists' workload. This is an experimental study. The proposed dataset contains clinically acquired multiplanar, multi-sequential MRI slices (MPMSI) which are used as input to the segmentation model without any preprocessing. The proposed AJBDS-2023 consists of 10667 images of real patients imaging data with a size of 320*320*3. Acquired images have T1W, TW2, Flair, T1W contrast, ADC, and DWI sequences. Pixel-based ground-truth annotated images of the tumor core and edema of 6334 slices are made manually under the supervision of a radiologist. Quantitative assessment of AJBDS-2023 images is done by a novel U-network on 4333 MRI slices. The diagnostic accuracy of our algorithm U-Net trained on AJBDS-2023 was 77.4 precision, 82.3 DSC, 87.4 specificity, 93.8 sensitivity, and 90.4 confidence interval. An experimental analysis of AJBDS-2023 done by the U-Net segmentation model proves that the proposed AJBDS-2023 dataset has images without preprocessing, which is more challenging and provides a more realistic platform for evaluation and analysis of newly developed algorithms in this domain and helps radiologists in MRI brain reporting more realistically.

Effects of long-term proton pump inhibitor use on sexual hormones and sexual and reproductive health in female patients.

PURPOSE: Proton pump inhibitors (PPIs) are widely used to treat a range of gastrointestinal diseases around the world. Long-term use of PPIs has been associated to a variety of undesirable effects. Although short-term therapy has been shown to have little or no effect on endocrine hormone in women, however, its long-term safety has received little attention. We aimed at evaluating long-term use of PPIs and its effects on female reproductive hormones as well as related clinical consequences. METHODS: A cross-sectional study was conducted in two outpatient gastroenterology clinics in the province of Khyber Pakhtunkhwa. This study included female patients who had been using PPIs on a regular basis for 3 months or more. RESULTS: In total of 101 participants, patients with sexual complaints have significantly altered levels of prolactin (p = 0.05), estrogen (p < 0.001) and progesterone (p = 0.001) than patient without sexual complaints. The frequency of amenorrhea (p < 0.001), cyclic disturbances (p < 0.001), breast augmentation (p = 0.001) and painful breast (p = 0.004) were statistically significant in patients with raised serum prolactin values. Serum values of Sex hormone binding globulin SHBG (p < 0.001), estradiol (p = 0.002) and total testosterone (p < 0.001) were significantly altered between normal prolactin and hyperprolactinemic patients. CONCLUSION: These findings suggest that long-term PPI use may cause endocrine hormone disturbances leading to sexual difficulties in women.

Delayed Presentation of Osmotic Demyelination Syndrome Treated With Plasmapheresis.

We present a unique case of a 42-year-old gentleman with alcohol use disorder who developed osmotic demyelination syndrome (ODS) despite appropriate hyponatremia correction. This patient initially presented with severe hyponatremia (Na 97 mEq/L) due to beer potomania, which was corrected gradually over eight days, resulting in no observed neurological deficits upon discharge. However, he was readmitted with respiratory failure from aspiration pneumonia, leading to endotracheal intubation. Laboratory findings revealed a sodium level of 134 mEq/L and serum osmolality (293 mOsm/kg). The patient had neurological exam findings of spontaneous eye opening with left gaze preference and decreased power ⅕ in all extremities. Following extubation, he experienced a relapse with evolving subacute central pontine myelinolysis and bulbar weakness necessitating reintubation. Subsequently, five sessions of plasmapheresis were conducted, resulting in stable clinical findings. Despite remaining non-verbal, the patient demonstrated gradual neurological motor improvement, progressing from 1/5 power in all extremities to 4/5 on the right side and 3/5 on the left side. He was discharged with ventilator support, tracheostomy, and PEG tube placement to a long-term care facility. This case underscores the importance of vigilant monitoring in high-risk individuals following hyponatremia treatment because ODS presentation can be delayed.

Relative expression levels of growth hormone gene and growth rate in Indian major carp species.

The phenomenon of growth is a leading factor for aquaculture success. The uneven growth of major Indian carps (Labeo rohita, Catla catla, and Cirrhinus mrigala) is a serious issue in fish culture from an economic point of view. The growth hormone (GH) gene is crucial for selection in commercially cultivated fish species for better growth and production. Indian major carp (L. rohita, C. catla, and C. mrigala) are commonly cultured in Pakistan. The GH expression was examined using qPCR to understand growth in fish species better. Muscle tissue samples (n=480) from 160 individuals of the same age were collected from three species (L. rohita, C. catla, and C. mrigala). Individuals were divided into two groups (high-weight and low-weight groups), cultured under normal conditions. The housekeeping gene ß-actin validated GH expression in fast and slow-growing fishes from the same species. Results showed that GH expression varies across species and fish specimens that overweight their counterpart feature have higher GH expression. A selection for overweight fish in the aquaculture breeding systems is preferable as those fish could inherit their genomics to the future cohort, enhancing production, and commercial profit for farmers. Comprehensive research about different growth genes and the environmental aspects that influence fish growth is mandatory. No work has been reported regarding the growth gene analysis of fish from Pakistan. This report was Pakistan's first and baseline study regarding growth analysis of main culturable fish species at the molecular level.

White blood cell image analysis for infection detection based on virtual hexagonal trellis (VHT) by using deep learning.

White blood cells (WBCs) are an indispensable constituent of the immune system. Efficient and accurate categorization of WBC is a critical task for disease diagnosis by medical experts. This categorization helps in the correct identification of medical problems. In this research work, WBC classes are categorized with the help of a transform learning model in combination with our proposed virtual hexagonal trellis (VHT) structure feature extraction method. The VHT feature extractor is a kernel-based filter model designed over a square lattice. In the first step, Graft Net CNN model is used to extract features of augmented data set images. Later, the VHT base feature extractor extracts useful features. The CNN-extracted features are passed to ant colony optimization (ACO) module for optimal features acquisition. Extracted features from the VHT base filter and ACO are serially merged to create a single feature vector. The merged features are passed to the support vector machine (SVM) variants for optimal classification. Our strategy yields 99.9% accuracy, which outperforms other existing methods.

Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

Computer-aided classification of diseases of the gastrointestinal tract (GIT) has become a crucial area of research. Medical science and artificial intelligence have helped medical experts find GIT diseases through endoscopic procedures. Wired endoscopy is a controlled procedure that helps the medical expert in disease diagnosis. Manual screening of the endoscopic frames is a challenging and time taking task for medical experts that also increases the missed rate of the GIT disease. An early diagnosis of GIT disease can save human beings from fatal diseases. An automatic deep feature learning-based system is proposed for GIT disease classification. The adaptive gamma correction and weighting distribution (AGCWD) preprocessing procedure is the first stage of the proposed work that is used for enhancing the intensity of the frames. The deep features are extracted from the frames by deep learning models including InceptionNetV3 and GITNet. Ant Colony Optimization (ACO) procedure is employed for feature optimization. Optimized features are fused serially. The classification operation is performed by variants of support vector machine (SVM) classifiers, including the Cubic SVM (CSVM), Coarse Gaussian SVM (CGSVM), Quadratic SVM (QSVM), and Linear SVM (LSVM) classifiers. The intended model is assessed on two challenging datasets including KVASIR and NERTHUS that consist of eight and four classes respectively. The intended model outperforms as compared with existing methods by achieving an accuracy of 99.32% over the KVASIR dataset and 99.89% accuracy using the NERTHUS dataset.

Phytochemical-Mediated Biosynthesis of Silver Nanoparticles from Strobilanthes glutinosus: Exploring Biological Applications.

The application of green synthesis for silver nanoparticles in nanomedicine has experienced significant growth. Strobilanthes glutinosus, a plant primarily located in the Himalayas, remains largely unexplored. Considering the biomedical value of S. glutinosus, phytochemicals from this plant were used for the biosynthesis of silver nanoparticles. Silver nanoparticles were synthesized from aqueous extract of root and leaves of Strobilanthes glutinosus. The synthesized silver nanoparticles were characterized using UV-Vis spectrophotometry, Fourier-transform infrared spectroscopy, transmission electron microscopy, and X-ray diffraction. Total phenolic and flavonoid contents of plants were determined and compared with nanoparticles. The biomedical efficacy of plant extracts and silver nanoparticles was assessed using antioxidant and antibacterial assays. The UV-Vis spectra of leaf- and root-extract-mediated AgNPs showed characteristic peaks at 428 nm and 429 nm, respectively. TEM images revealed the polycrystalline and spherical shapes of leaf- and root-extract-mediated AgNPs with size ranges of 15-60 nm and 20-52 nm, respectively. FTIR findings shown the involvement of phytochemicals of root and leaf extracts in the reduction of silver ions into silver nanoparticles. The crystalline face-centered cubic structure of nanoparticles is depicted by the XRD spectra of leaf and root AgNPs. The plant has an ample amount of total phenolic content (TPC) and total flavonoid content (TFC), which enhance the scavenging activity of plant samples and their respective AgNPs. Leaf and root AgNPs have also shown good antibacterial activity, which may enhance the medicinal value of AgNPs.

The Biogenic Synthesis of Bimetallic Ag/ZnO Nanoparticles: A Multifunctional Approach for Methyl Violet Photocatalytic Degradation and the Assessment of Antibacterial, Antioxidant, and Cytotoxicity Properties.

In this study, bimetallic nanoparticles (NPs) of silver (Ag) and zinc oxide (ZnO) were synthesized using Leptadenia pyrotechnica leaf extract for the first time. Monometallic NPs were also obtained for comparison. The characterization of the prepared NPs was carried out using various techniques, including UV-Visible spectroscopy (UV-Vis), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The latter confirmed the crystalline nature and diameter of the monometallic and bimetallic NPs of Ag and ZnO. The SEM images of the prepared NPs revealed their different shapes. The biological activities of the NPs were evaluated concerning their antibacterial, antioxidant, and cytotoxic properties. The antibacterial activities were measured using the time-killing method. The results demonstrated that both the monometallic and bimetallic NPs inhibited the growth of Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria. The antioxidant activities of the NPs were evaluated using the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay and their cytotoxicity was checked using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. The results indicated that the controlled quantity of the monometallic and bimetallic NPs did not affect the viability of the cells. However, the decreased cell (L-929) viability suggested that the NPs could have anticancer properties. Furthermore, the photocatalytic degradation of methyl violet and 4-nitrophenol was investigated using the prepared Ag/ZnO NPs, examining the factors affecting the degradation process and conducting a kinetic and thermodynamic study. The prepared Ag/ZnO NPs demonstrated good photocatalytic degradation (88.9%) of the methyl violet (rate constant of 0.0183 min-1) in comparison to 4-nitrophenol (NPh), with a degradation rate of 81.37% and 0.0172 min-1, respectively. Overall, the bimetallic NPs showed superior antibacterial, antioxidant, cytotoxic, and photocatalytic properties compared to the monometallic NPs of Ag and ZnO.

Encephalitis as a Clinical Manifestation of COVID-19: A Case Series.

COVID-19 is a novel virus which causes a variety of clinical manifestations in the body, some of which are yet to be discovered. The main aim of our study is to highlight the neurological manifestations of COVID-19 as it is still new to the medical world, and to emphasize the fact that the physicians have to be wary of the possibility that patients affected by COVID-19 can present with encephalitis. Only a few studies are available so far regarding the neurological manifestations of this novel virus which highlights the need for this study. We present a case series of 4 patients who were found to have COVID-19 encephalitis. There is still no disease-defining test for diagnosis so the mainstay of diagnosis is exclusion of all the common causes of encephalitis. Brain magnetic resonance imaging and cerebrospinal fluid analysis performs an ancillary in the diagnostic tools. Our study also supports the use of IV tocilizumab (4-8 mg/kg) and IV methylprednisolone (0.5-2 mg/kg) as possible treatment options with good results, as the patients described in our case series responded well to these medications.