Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays.

Disease associated pathological aggregates of alpha-synuclein (αSynD) exhibit prion-like spreading in synucleinopathies such as Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Seed amplification assays (SAAs) such as real-time quaking-induced conversion (RT-QuIC) have shown high diagnostic sensitivity and specificity for detecting proteopathic αSynD seeds in a variety of biospecimens from PD and DLB patients. However, the extent to which relative proteopathic seed concentrations are useful as indices of a patient's disease stage or prognosis remains unresolved. One feature of current SAAs that complicates attempts to correlate SAA results with patients' clinical and other laboratory findings is their quantitative imprecision, which has typically been limited to discriminating large differences (e.g. 5-10 fold) in seed concentration. We used end-point dilution (ED) RT-QuIC assays to determine αSynD seed concentrations in patient biospecimens and tested the influence of various assay variables such as serial dilution factor, replicate number and data processing methods. The use of 2-fold versus 10-fold dilution factors and 12 versus 4 replicate reactions per dilution reduced ED-RT-QuIC assay error by as much as 70%. This enhanced assay format discriminated as little as 2-fold differences in αSynD seed concentration besides detecting ~2-16-fold seed reductions caused by inactivation treatments. In some scenarios, analysis of the data using Poisson and midSIN algorithms provided more consistent and statistically significant discrimination of different seed concentrations. We applied our improved assay strategies to multiple diagnostically relevant PD and DLB antemortem patient biospecimens, including cerebrospinal fluid, skin, and brushings of the olfactory mucosa. Using ED αSyn RT-QuIC as a model SAA, we show how to markedly improve the inter-assay reproducibility and quantitative accuracy. Enhanced quantitative SAA accuracy should facilitate assessments of pathological seeding activities as biomarkers in proteinopathy diagnostics and prognostics, as well as in patient cohort selection and assessments of pharmacodynamics and target engagement in drug trials.

Phosphorus recovery potential from sewage sludge by struvite precipitation: remodelling policy framework in Rajasthan, India.

The manufacturing of fossil-based fertilizers by extraction of rock phosphate has contributed to carbon emissions and depleted the non-renewable phosphorus reserves. Sewage sludge, which is a waste product from Sewage Treatment Plants (STPs), is rich in phosphorus. The existing techniques for sludge management contribute to carbon emissions and ecological footprint. Struvite (raw fertilizer) and biochar recovery from sludge has emerged as viable methods to reduce carbon emission and ensure economic sustainability of STPs. In this work, the potential for phosphorus recovery and revenue generation is discussed for Rajasthan state in India. The fate of phosphorus and heavy metals in STPs is evaluated which indicates that about 70% of the phosphorus and trace amounts of metals end up in sewage sludge. Further, the power consumption is high in STPs due to industrial wastewater ingress. There is a need to bridge the gap between sewage treatment and generation in Rajasthan, improve STP performance before resource recovery inclusion at policy-level and scale-up. Mixing struvite with biochar can lead to safe application of struvite as raw fertilizer as heavy metals are sequestered by biochar. A business framework is developed to serve as a blueprint and potential model for linking technical and market viability.

Performance assessment of VSC-based HVDC system in asynchronous grid interconnection: Offline and real-time validation of control design with symmetric optimum PI tuning.

Asynchronous interconnection is essential for integrating AC networks operating at different frequencies, typically 50 Hz and 60 Hz. This need arises from distributed power generation methods, including offshore renewable sources and diverse regional grid configurations. Advanced strategies are required to overcome these frequency differences and ensure uninterrupted power transfer. High-Voltage Direct Current (HVDC) transmission systems facilitate efficient power exchange, enhancing grid reliability and stability. This study focuses on optimizing the Proportional-plus-Integral (PI) controller parameters within a 20 MVA Voltage Source Converters (VSC)-based HVDC system to enable asynchronous interconnection between offshore and onshore AC networks. The offshore VSC regulates active and reactive power, while the onshore VSC controls DC voltage and reactive power. A vector control approach with symmetric optimum PI tuning is proposed for a comprehensive performance assessment of the VSC-based HVDC transmission system. The effectiveness of the tuned PI controller parameters is evaluated through four test cases using MATLAB/Simulink for offline simulation and Typhoon HIL604 for real-time validation. These cases involve abrupt changes in reference active and reactive power for the offshore VSC; and in reference reactive power and DC voltage for the onshore VSC. Results demonstrate rapid and satisfactory dynamic performance across all test cases, as evidenced by offline simulations and real-time validation. The validation highlights the effectiveness of the proposed control design with symmetric optimum PI tuning, confirming its ability to enhance the overall performance of the HVDC transmission system for efficient asynchronous interconnection.

Systematic computational strategies for identifying protein targets and lead discovery.

Computational algorithms and tools have retrenched the drug discovery and development timeline. The applicability of computational approaches has gained immense relevance owing to the dramatic surge in the structural information of biomacromolecules and their heteromolecular complexes. Computational methods are now extensively used in identifying new protein targets, druggability assessment, pharmacophore mapping, molecular docking, the virtual screening of lead molecules, bioactivity prediction, molecular dynamics of protein-ligand complexes, affinity prediction, and for designing better ligands. Herein, we provide an overview of salient components of recently reported computational drug-discovery workflows that includes algorithms, tools, and databases for protein target identification and optimized ligand selection.

Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.

Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. To address this problem, we describe here a machine learning approach to identify small molecule inhibitors of α-synuclein aggregation, a process implicated in Parkinson's disease and other synucleinopathies. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation, we aim to identify compounds that bind the catalytic sites on the surface of the aggregates. To achieve this goal, we use structure-based machine learning in an iterative manner to first identify and then progressively optimize secondary nucleation inhibitors. Our results demonstrate that this approach leads to the facile identification of compounds two orders of magnitude more potent than previously reported ones.

Moringin, an isothiocyanate modulates multiple cellular signalling molecules in breast cancer cells.

Prohibitin (PHB) is a pleiotropic molecule with a variety of known functions and subcellular locations. PHB's function in breast cancer is poorly understood. Herein, we report that PHB is expressed in cancer types of diverse origin including breast cancer. The cancer patients with changes in PHB were reported to have significantly reduced 'overall survival' in comparison to the cases without alterations in PHB. The expression of PHB was increased by H2O2 and also by Moringin (MG), which is an isothiocyanate derived from the seeds of Moringa oleifera. MG interacted with PHB, DRP1, and SLP2 and inhibited the growth of MCF-7 and MDAMB-231 cells. The isothiocyanate triggered apoptosis in breast cancer cells as revealed by AO/PI assay, phosphatidylserine externalization, cell cycle analysis and DAPI staining. MG induced proapoptotic proteins expression such as cytochrome c, p53, and cleaved caspase-7. Further, cell survival proteins such as survivin, Bcl-2, and Bcl-xL were suppressed. A depolarization of membrane potential suggested that the apoptosis was triggered through mitochondria. The isothiocyanate suppressed the cancer cell migration and interacted with NF-κB subunits. MG suppressed p65 nuclear translocation induced by TNF-α. The reactive oxygen species generation was also induced by the isothiocyanate in breast cancer cells. MG also modulated the expression of lncRNAs. Collectively, the functions of PHB in breast cancer growth is evident from this study. The activities of MG against breast cancer might result from its ability to modulate multiple cancer-related targets.

Evaluation of Efficacy of Curcumin and Caffeic Acid Phenethyl Ester in Breast Cancer by Preclinical Studies.

ims: The aim of this study was to evaluate the combined and comparative efficacy of Caffeic acid phenethyl ester (CAPE) and curcumin in breast cancer. BACKGROUND: CAPE and curcumin are a class of phenolics. While curcumin is obtained from turmeric, CAPE is found in Baccharis sarothroides and Populus deltoides. Both agents are reported to produce activities in some cancer types. The combined and comparative effects of the two agents in breast cancer have not yet reported. OBJECTIVE: We evaluated the potential of CAPE and curcumin in both in vitro and in vivo breast cancer models. METHODS: Human breast cancer cell lines, MDA-MB-231 and MCF-7, were exposed to CAPE and curcumin, followed by functional assays such as cell cytotoxicity, cell proliferation and colony formation, cell cycle, mitochondrial membrane potential, apoptosis, and monodansylcadaverine (MDC) staining for autophagy. Computational analyses and mouse models were also used. RESULTS: Employing computational analyses, both agents were found to exhibit drug-like properties. Both molecules interacted with the key molecules of the NF-κB pathway. CAPE and curcumin inhibited cell proliferation, colony formation, and invasion, triggering apoptosis in breast cancer cells. CAPE was found to be more effective than curcumin. Two agents working together were more effective than each agent working alone. Both agents suppressed the expression of survivin, Bcl-xL and GLUT-1. The level of cleaved PARP was increased by both agents. Both phenolics observed an induction in ROS generation. Further, both molecules triggered a dissipation in mitochondrial membrane potential. In mice models implanted with Ehrlich-Lettre ascites carcinoma (EAC) cells, both drugs inhibited the growth of the tumour. The phenolics also modulated the metabolic parameters in tumour-bearing mice. CONCLUSION: The observations suggest that the combination of curcumin plus CAPE may be better in comparison to individual molecules. Other: The study opens a window for analysing the efficacy of the combination of CAPE and curcumin in animal studies. This will provide a basis for examining the combined efficacy of two agents in a clinical trial.

Multiomics data identifies RSPO2 as a prognostic biomarker in human tumors associated with pan-cancer.

RSPO2 protein may provide valuable insights into the mechanism underlying various types of tumorigenesis. The role of RSPO2 in pan-cancer has not been reported so far. Therefore, this study aimed to provide a comprehensive analysis of RSPO2 from a pan-cancer perspective employing multiomics data. The expression profile and function of RSPO2 across different tumors were investigated using various web-based tools UALCAN, GEPIA, TIMER, Human Protein Atlas, cBioPortal, TISIDB, STRING, and Metascape to interpret the expression profile, promoter methylation status, genomic alterations, survival analysis, protein-protein interaction, correlation with immune cell subtypes, tumor immune microenvironment and enrichment analysis. Comprehensive pan-cancer analysis indicated that RSPO2 was significantly downregulated in eleven and upregulated in five tumor types compared to normal tissues, validation results further suggest RSPO2 was downregulated in most of the tumors. The protein level expression of RSPO2 was mostly low in malignant tissues. We found that RSPO2 was significantly related to individual pathological stages in BLCA, COAD, LUAD and LUSC. Prognostic analysis indicates that the high RSPO2 expression was significantly correlated with the poor prognosis in BRCA, KICH, KIRP, READ, and UCES. Furthermore, RSPO2 is frequently amplified, exhibits hypermethylated promoter in most cancers, and is associated with immune subtypes, molecular subtypes and immune cell infiltration. Finally, enrichment analysis showed that RSPO2 is involved in the regulation of the canonical Wnt pathway and neuronal development. The overall comprehensive pan-cancer analysis affirms that RSPO2 could be a promising diagnostic and prognostic biomarker and latent therapy target in the future.

Unravelling a novel CTNND1-RAB6A fusion transcript: Implications in colon cancer cell migration.

The interchange of DNA sequences between genes may occur because of chromosomal rearrangements leading to the formation of chimeric genes. These chimeric genes have been linked to various cancers, accumulated significant interest in recent times. We used paired-end RNA-seq. data of four CRC and one normal sample generated from our previous study. The STAR-Fusion pipeline was utilized to identify the fusion genes unique to CRC. The in-silico identified fusion gene(s) were explored for their diagnostic, prognostic and therapeutic biomarker potential using TCGA-datasets, then validated through PCR and DNA sequencing. Further, cell line-based studies were performed to gain functional insights of the novel fusion transcript CTNND1-RAB6A, which was amplified in one sample. Sequencing revealed that there was a total loss of the CTNND1 gene, whereas RAB6A retained its coding sequence. Further, RAB6A was functionally characterized for its oncogenic potential in HCT116 cell line. RAB6A under-expression was found to be significantly associated with increased cell migration and is proposed to be regulated via the RAB6A-ECR1-Liprin-α axis. We conclude that RAB6A gene may play significant role in CRC oncogenesis, and could be used as a potential biomarker and therapeutic target in future for better management of a subset of CRCs harbouring this fusion.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response.

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Angle-dependent phononic dynamics for data-driven source localization.

The source angle localization problem is studied based on scattering of elastic waves in two dimensions by a phononic array and the exceptional points of its band structure. Exceptional points are complex singularities of a parameterized eigen-spectrum, where two modes coalesce with identical mode shapes. These special points mark the qualitative transitions in the system behavior and have been proposed for sensing applications. The equi-frequency band structures are analyzed with focus on the angle-dependent modal behaviors. At the exceptional points and critical angles, the eigen-modes switch their energy characteristics and symmetry, leading to enhanced sensitivity as the scattering response of the medium is inherently angle-dependent. An artificial neural network is trained with randomly weighted and superposed eigen-modes to achieve deep learning of the angle-dependent dynamics. The trained algorithm can accurately classify the incident angle of an unknown scattering signal, with minimal sidelobe levels and suppressed main lobewidth. The neural network approach shows superior localization performance compared with standard delay-and-sum technique. The proposed application of the phononic array highlights the physical relevance of band topology and eigen-modes to a technological application, adds extra strength to the existing localization methods, and can be easily enhanced with the fast-growing data-driven techniques.

Insight into the Epigenetics of Kaposi's Sarcoma-Associated Herpesvirus.

Epigenetic reprogramming represents a series of essential events during many cellular processes including oncogenesis. The genome of Kaposi's sarcoma-associated herpesvirus (KSHV), an oncogenic herpesvirus, is predetermined for a well-orchestrated epigenetic reprogramming once it enters into the host cell. The initial epigenetic reprogramming of the KSHV genome allows restricted expression of encoded genes and helps to hide from host immune recognition. Infection with KSHV is associated with Kaposi's sarcoma, multicentric Castleman's disease, KSHV inflammatory cytokine syndrome, and primary effusion lymphoma. The major epigenetic modifications associated with KSHV can be labeled under three broad categories: DNA methylation, histone modifications, and the role of noncoding RNAs. These epigenetic modifications significantly contribute toward the latent-lytic switch of the KSHV lifecycle. This review gives a brief account of the major epigenetic modifications affiliated with the KSHV genome in infected cells and their impact on pathogenesis.

HIF-1α regulates the expression of the non-conventional isoform of the cd5 gene in T cells under the hypoxic condition: A potential mechanism for CD5neg/low phenotype of infiltrating cells in solid tumors.

CD5, a T-cell receptor (TCR) negative regulator, is reduced on the surface of CD8+ lymphocytes in the tumor microenvironment (TME). Reduced surface CD5 expression (sCD5) occurs due to the preferential transcription of HERV-E derived exon E1B, i.e., anon-conventional formofthe cd5gene instead of its conventional exon E1A. A tumor employs several mechanisms to evade anti-tumor response, and hypoxia is one such mechanism that prevails in the TME and modulates the infiltrated T lymphocytes. We identified hypoxia response elements (HREs) upstream of E1B. We showed binding of HIF-1α onto these HREs and increased E1B mRNA expression in hypoxic T cells. This results in decreased sCD5 expression and increased cytoplasmic accumulation in T cells. We also validated our study in a solid tumor, i.e., colorectal cancer (CRC) patient samples. This hypoxia-driven mechanism reduces the surface CD5 expression on infiltrated T-cells in solid tumors.

Autonomous healing of fatigue cracks via cold welding.

Fatigue in metals involves gradual failure through incremental propagation of cracks under repetitive mechanical load. In structural applications, fatigue accounts for up to 90% of in-service failure1,2. Prevention of fatigue relies on implementation of large safety factors and inefficient overdesign3. In traditional metallurgical design for fatigue resistance, microstructures are developed to either arrest or slow the progression of cracks. Crack growth is assumed to be irreversible. By contrast, in other material classes, there is a compelling alternative based on latent healing mechanisms and damage reversal4-9. Here, we report that fatigue cracks in pure metals can undergo intrinsic self-healing. We directly observe the early progression of nanoscale fatigue cracks, and as expected, the cracks advance, deflect and arrest at local microstructural barriers. However, unexpectedly, cracks were also observed to heal by a process that can be described as crack flank cold welding induced by a combination of local stress state and grain boundary migration. The premise that fatigue cracks can autonomously heal in metals through local interaction with microstructural features challenges the most fundamental theories on how engineers design and evaluate fatigue life in structural materials. We discuss the implications for fatigue in a variety of service environments.

Neurovascular Structures at Risk During Surgical Access to Trigeminal Ganglion and Meckel's Cave - An Anatomical Study.

Background: It is difficult to approach the Trigeminal Ganglion (TG) and Meckel's cave (MC) during surgeries. Therefore, the exact knowledge of the relationship of surgical landmarks to related anatomical structures is vital to reduce the associated postoperative morbidity. The aim of the present study was to enhance the knowledge of the surgical anatomy of structures that are present in the conduit of all surgical approaches to TG and MC, their distances from surrounding neurovascular structures, and their variations. Material and Methods: The study was carried out on 40 embalmed cadavers (Eight Female) of the anatomy department of a teaching hospital in Central India. Meticulous dissection of cranial fossae was done to locate TG, MC, and related anatomical structures. All distances from TG and MC were measured using an electronic digital calliper. Results: Length, width, and thickness of TG were 15.39 mm, 4.39 mm, and 2.54 mm, respectively. The distance from zygomatic arch, the lateral end of the petrous ridge, arcuate eminence, foramen ovale, and foramen spinosum to MC was 26.10 mm and 37.94 mm, 16.46 mm, 4.54 mm, and 11.23 mm, respectively. The sixth, fourth, and third cranial nerves were 6.26 mm, 4.94 mm, and 2.53 mm from MC, respectively. The MC was 42.72 mm and 33.87 mm anteromedial from posterior and anterior limits of the sigmoid sinus. Conclusion: Findings of the present study will aid surgical planning and decide the approach to TG and MC and avoid surgical complications.

Paddy-Straw-Derived Graphene Quantum Dots Reinforced Vertical Aligned Zinc Oxide Nanosheet-Based Flexible Triboelectric Nanogenerator for Self-Powered UV Sensors and Tribotronics Application.

Herein, we report the paddy-straw-derived graphene quantum dots (GQDs)-reinforced vertical-aligned two-dimensional (2D) ZnO nanosheet-based flexible triboelectric nanogenerator (FTNG) for scavenging mechanical energy for the first time. The GQDs (diameter ∼5-7 nm) and ZnO nanosheets were grown using a hydrothermal method and seed-assisted chemical route, respectively. The X-ray diffraction and electron microscopy results confirmed the formation of a hexagonal wurtzite crystal structure and vertical-aligned morphology of 2D ZnO nanosheets. The GQD-reinforced ZnO-nanosheet-based FTNG device generated an output voltage of 40 V and current density of 2 µA/cm2, respectively, whereas pristine vertical-aligned ZnO-nanosheet-based device produced an output voltage of only 16 V and a current density of 0.36 µA/cm2, respectively. The performance of the GQD-ZnO nanosheet FTNG device was also measured under illumination of the UV light, and a drastic increase in the output voltage is observed as compared to a pristine ZnO-nanosheet-based device. The GQD-reinforced ZnO nanosheets exhibited very high dielectric constant of 40 at low frequency side. The current finding suggested a novel approach to efficiently harvest mechanical energy and a novel method to fabricate the self-powered UV sensors and tribotronics devices using agrowaste-derived GQDs and ZnO nanosheets.

The long-term impact of coronavirus disease 2019 on environmental health: a review study of the bi-directional effect.

Background: When health systems worldwide grapple with the coronavirus disease 2019 (COVID-19) pandemic, its effect on the global environment is also a significant consideration factor. It is a two-way process where the pre-COVID climate factors influenced the landscape in which the disease proliferates globally and the consequences of the pandemic on our surroundings. The environmental health disparities will also have a long-lasting effect on public health response. Main body: The ongoing research on the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 must also include the role of environmental factors in the process of infection and the differential severity of the disease. Studies have shown that the virus has created positive and negative ramifications on the world environment, especially in countries most critically affected by the pandemic. Contingency measures to slow down the virus, such as self-distancing and lockdowns have shown improvements in air, water, and noise quality with a concomitant decrease in greenhouse gas emissions. On the other hand, biohazard waste management is a cause for concern that can result in negative effects on planetary health. At the peak of the infection, most attention has been diverted to the medical aspects of the pandemic. Gradually, policymakers must shift their focus to social and economic avenues, environmental development, and sustainability. Conclusion: The COVID-19 pandemic has profoundly impacted the environment, both directly and indirectly. On the one hand, the sudden halt in economic and industrial activities led to a decrease in air and water pollution, as well as a reduction in greenhouse gas emissions. On the other hand, the increased use of single-use plastics and a surge in e-commerce activities have had negative effects on the environment. As we move forward, we must consider the pandemic's long-term impacts on the environment and work toward a more sustainable future that balances economic growth and environmental protection. The study shall update the readers on the various facets of the interaction between this pandemic and environmental health with model development for long-term sustainability.

The Long Noncoding RNA LINC00958 Is Induced in Psoriasis Epidermis and Modulates Epidermal Proliferation.

Psoriasis is a common, immune-mediated skin disease characterized by epidermal hyperproliferation and chronic skin inflammation. Long noncoding RNAs are >200 nucleotide-long transcripts that possess important regulatory functions. To date, little is known about the contribution of long noncoding RNAs to psoriasis. In this study, we identify LINC00958 as a long noncoding RNA overexpressed in keratinocytes (KCs) from psoriasis skin lesions, in a transcriptomic screen performed on KCs sorted from psoriasis and healthy skin. Increased levels of LINC00958 in psoriasis KCs were confirmed by RT-qPCR and single-molecule in situ hybridization. Confocal microscopy and analysis of subcellular fractions showed that LINC00958 is mainly localized in the cytoplasm of KCs. IL-17A, a key psoriasis cytokine, induced LINC00958 in KCs through C/EBP-ß and the p38 pathway. The inhibition of LINC00958 led to decreased proliferation as measured by Ki-67 expression, live cell analysis imaging, and 5-ethynyl-2-deoxyuridine assays. Transcriptomic analysis of LINC00958-depleted KCs revealed enrichment of proliferation- and cell cycle‒related genes among differentially expressed transcripts. Moreover, LINC00958 depletion led to decreased basal and IL-17A‒induced phosphorylation of p38. Furthermore, IL-17A‒induced KC proliferation was counteracted by the inhibition of LINC00958. In summary, our data support a role for the IL-17A‒induced long noncoding RNA, LINC00958, in the pathological circuits of psoriasis by reinforcing IL-17A‒induced epidermal hyperproliferation.

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers.

BACKGROUND: The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation. METHODS: We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values. RESULTS: A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response. CONCLUSIONS: The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

Thuja occidentalis: An Unexplored Phytomedicine with Therapeutic Applications.

BACKGROUND: The recent outbreak of SARS-CoV-2 has received global attention. Due to a lack of recommended treatment regimens, the world faced various limitations resulting in improper management of the disease. Phytomedicines have played a prominent role in the prevention of various epidemics and pandemics in the past. OBJECTIVE: Here, we attempt to focus on safe and feasible use of Thuja occidentalis to manage and alleviate the panic of viral respiratory infections, including COVID-19, by strengthening an individual's immunity. The relevant information was collected from the web-based databases PubMed, Google Scholar, and MEDLINE, as well as other internet sources to review the applicability of T. occidentalis as a phytomedicine in managing respiratory infections and strengthening immunity. CONCLUSION: As important phytomedicine, and antipsychotic, T. occidentalis possesses a plethora of immunological properties that can be used effectively in the management of viral respiratory infections and has the potential to prevent further progression of the disease. Importantly, this could be only a part of the approach for treatment during the current outbreak that should be considered along with other measures.