Investigating the potent TOPO IIα inhibitors in breast cancer through the study of computational drug discovery research approaches.

Breast cancer (BC) is the second-leading cause of cancer after lung cancer. The disease has affected millions of people and resulted in many deaths. In the metastasis of breast cancer cells, Topoisomerase IIα plays a vital role. Therefore, this investigation aims to identify potential flavonoid compounds against BC by inhibiting this enzyme at an early stage. Based on previous studies, we selected and screened several plant-derived flavonoid compounds with potential anti-breast cancer activity using PyRx 0.8 and Schrodinger applications for preliminary molecular docking: the highest docking scores of Myricetin (-11.6 kcal/mol) and Quercetin (-10.0 kcal/mol). Next, we evaluated the top four compounds on the Way2Drug server to complete the cytotoxicity evaluation, which demonstrated anti-cancer and anti-breast cancer activity in various cell lines. According to pharmacokinetics studies, four compounds exhibited outstanding values and functioned similar to drug-like molecules. Moreover, Myricetin, Quercetin, and Morin displayed the highest number of hydrogen bonds, with the corresponding receptor forming residues asn120, thr147, and lys168. The protein-ligand complexes were validated using the Desmond simulator, and their data were compared to the anti-breast cancer drug Doxorubicin. In the simulation analysis, various parameters were evaluated, including RMSD, RMSF, Rg, SASA, MolSA, PSA, and hydrogen bond interaction. Finally, validated our dynamic simulation result with MM-GBSA operation, and Myricetin and Quercetin had the greatest score of -72.74344651, -66.66771823 kcal/mol, which is outstanding than the control drug. Hence, the computational research approach determined that Myricetin, Quercetin, and Morin could be industrially developed for the alternative treatment of breast cancer following additional confirmation from animal and cell line studies.

Upregulation and functional roles of miR-450b in canine oral melanoma.

Canine oral melanoma (COM) is a common and highly aggressive disease with the potential to model human melanomas. Dysregulated microRNAs represent an interesting line of research for COM because they are implicated in tumor progression. One example is miR-450b, which has been investigated for its molecular mechanisms and biological functions in multiple human cancers, but not human or canine melanoma. Here, we aimed to investigate miR-450b as a potential diagnostic biomarker of COM and its functional roles in metastatic and non-metastatic forms of the disease. We investigated the expression of miR-450b and its target mRNA genes in clinical (tumor tissue and plasma) samples and metastatic and primary-tumor cell lines. Knockdown and overexpression experiments were performed to determine the influence of miR-450b on cell proliferation, migration, colony formation, and apoptosis. miR-450b was significantly upregulated in COM and differentiated between metastatic and non-metastatic tumors, and its potential as a biomarker of metastatic and non-metastatic COM was further confirmed in ROC analysis. miR-450b knockdown promoted cell proliferation, migration, and clonogenicity and inhibited apoptosis, whereas its overexpression yielded the reverse pattern. miR-450b directly binds 3' UTR of PAX9 mRNA and modulates its function leading to BMP4 downregulation and MMP9 upregulation at the transcript level. Furthermore, we surmised that miR-450b activates the Wnt signaling pathway based on gene ontology and enrichment analyses. We concluded that miR-450b has the potential as a diagnostic biomarker and could be a target candidate for COM treatment.

Hypoxia-related Y RNA fragments as a novel potential biomarker for distinguishing metastatic oral melanoma from non-metastatic oral melanoma in dogs.

Hypoxia may promote tumor progression, and hypoxically altered noncoding RNA (ncRNA) expression may play a role in metastasis. Canine oral melanoma (COM) frequently metastasizes, and ncRNA expression under hypoxia may be clinically significant. We aimed to elucidate ncRNA fragments whose expression is altered by hypoxia in COM-derived primary KMeC and metastatic LMeC cell lines using next-generation sequencing to validate these results in qRT-PCR, and then compare expression between metastatic and non-metastatic COM. The NGS analysis and subsequent qRT-PCR validation were performed using hypoxic and normoxic KMeC and LMeC cells, and clinical samples [tumor tissue, plasma, and plasma-derived extracellular vesicles] obtained from dogs with metastatic or non-metastatic melanoma were analyzed with qRT-PCR. Y RNA was significantly decreased in metastatic LMeC cells versus primary KMeC cells in hypoxic and normoxic conditions. The expression of Y RNA was decreased in dogs with metastatic melanoma versus those with non-metastatic melanoma for all clinical sample types, reflecting the pattern found with hypoxia. Receiver operating characteristic analysis demonstrated that Y RNA level is a promising biomarker for discriminating metastatic from non-metastatic melanoma in plasma [area under the curve (AUC) = 0.993, p < 0.0001] and plasma-derived extracellular vesicles (AUC = 0.981, p = 0.0002). Overall, Y RNA may be more resistant to hypoxic stress in the metastatic than the non-metastatic state for COM. However, further investigation is required to elucidate the biological functions of Y RNA under hypoxic conditions.

YRNA and tRNA fragments can differentiate benign from malignant canine mammary gland tumors.

Mammary gland tumors (MGT) are the most common tumors in sexually intact female dogs. The functional regulation of miRNAs, a type of noncoding RNAs (ncRNAs), in canine MGT has been extensively investigated. However, the expression of other ncRNAs, such as YRNAs and transfer RNA-derived fragments (tRFs) in canine MGT is unknown. We investigated ncRNAs other than miRNAs from our small RNA project (PRJNA716131) in different canine MGT histologic subtypes. This study included benign tumors (benign mixed tumor, complex adenoma) and malignant tumors (carcinoma in benign tumor and carcinoma with metastasis) samples. Aberrantly expressed ncRNAs were examined by comparisons among MGT subtypes. The relative expression trends were validated in canine MGT tissues, plasma, extracellular vesicles, and MGT cell lines using quantitative reverse transcription PCR. Three aberrantly expressed ncRNAs were identified by comparisons among MGT subtypes. YRNA and tRNA-Gly-GCC distinguished benign mixed tumor from other MGT histologic subtypes, while tRNA-Val differentiated complex adenoma, carcinoma in benign tumors, and carcinoma with metastasis. The ROC curve of the three ncRNAs showed they might be potential biomarkers to discriminate malignant from benign MGT. YRNA and tRFs expression levels were decreased in metastatic compared with primary canine MGT cell lines. To the best of our knowledge, this is the first investigation of YRNA and tRFs in canine MGT. The three identified ncRNAs may be biomarkers for differentiating MGT histologic subtypes. Suggested Reviewers: Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporatio.

Elevated expression of miR-301a and its functional roles in canine oral melanoma.

miR-301a is one of numerous dysregulated microRNAs (miRNAs) in canine oral melanoma (COM), one of which is miR-301a (upregulated). Its biological role has been described in various human cancer types, including malignant melanoma, but not in COM. Accordingly, in this study, we investigated miR-301a expression in COM in greater detail to ascertain whether it could serve as a diagnostic biomarker, elucidate its functional roles in this cancer, and predict the possible pathways by which it exerts its effects. Relative expression of miR-301a was investigated in clinical oral tissue and plasma samples and COM cell (KMeC and LMeC) lines using qRT-PCR. Knockdown of miR-301a was also validated for KMeC and LMeC cells using qRT-PCR. We performed CCK-8 assays to assess cell proliferation, monolayer wound-healing, and transwell migration assays to assess cell migration, a colony-formation assay to assess clonogenicity, a TUNEL assay and flow cytometry to assess apoptosis-related effects, and gene enrichment analyses to predict possible related pathways. miR-301a was markedly upregulated in COM oral tissue and plasma clinically, suggesting its potential as a diagnostic biomarker for COM diagnosis. In vitro assays demonstrated that miR-301 significantly inhibited apoptosis in COM cells while promoting cell migration, proliferation, and clonogenicity. We also predicted that miR-301 exerts cancer-promoting effects through the Wnt signalling pathway for COM. Our findings suggest that miR-301a is a COM oncomiR that regulates several oncogenic phenotypes with the potential to be a diagnostic biomarker.

Immunoinformatics-aided rational design of multiepitope-based peptide vaccine (MEBV) targeting human parainfluenza virus 3 (HPIV-3) stable proteins.

BACKGROUND: Human parainfluenza viruses (HPIVs) are common RNA viruses responsible for respiratory tract infections. Human parainfluenza virus 3 (HPIV-3) is particularly pathogenic, causing severe illnesses with no effective vaccine or therapy available. RESULTS: The current study employed a systematic immunoinformatic/reverse vaccinology approach to design a multiple epitope-based peptide vaccine against HPIV-3 by analyzing the virus proteome. On the basis of a number of therapeutic features, all three stable and antigenic proteins with greater immunological relevance, namely matrix protein, hemagglutinin neuraminidase, and RNA-directed RNA polymerase L, were chosen for predicting and screening suitable T-cell and B-cell epitopes. All of our desired epitopes exhibited no homology with human proteins, greater population coverage (99.26%), and high conservancy among reported HPIV-3 isolates worldwide. All of the T- and B-cell epitopes are then joined by putative ligands, yielding a 478-amino acid-long final construct. Upon computational refinement, validation, and thorough screening, several programs rated our peptide vaccine as biophysically stable, antigenic, allergenic, and non-toxic in humans. The vaccine protein demonstrated sufficiently stable interaction as well as binding affinity with innate immune receptors TLR3, TLR4, and TLR8. Furthermore, codon optimization and virtual cloning of the vaccine sequence in a pET32a ( +) vector showed that it can be readily expressed in the bacterial system. CONCLUSION: The in silico designed HPIV-3 vaccine demonstrated potential in evoking an effective immune response. This study paves the way for further preclinical and clinical evaluation of the vaccine, offering hope for a future solution to combat HPIV-3 infections.

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery.

Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where "evaluation of the binding affinity" and "a detailed mechanistic understanding on covalent inhibition" are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in "Computational Covalent Drug Discovery (CCDD)". We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.

Novel Y RNA-Derived Fragments Can Differentiate Canine Hepatocellular Carcinoma from Hepatocellular Adenoma.

Hepatocellular carcinomas (HCC) are common tumors, whereas hepatocellular adenomas (HCA) are rare, benign tumors in dogs. The aberrant expression of noncoding RNAs (ncRNAs) plays a pivotal role in HCC tumorigenesis and progression. Among ncRNAs, micro RNAs have been widely researched in human HCC, but much less widely in canine HCC. However, Y RNA-derived fragments have yet to be investigated in canine HCC and HCA. This study targeted canine HCC and HCA patients. We used qRT-PCR to determine Y RNA expression in clinical tissues, plasma, and plasma extracellular vesicles, and two HCC cell lines (95-1044 and AZACH). Y RNA was significantly decreased in tissue, plasma, and plasma extracellular vesicles for canine HCC versus canine HCA and healthy controls. Y RNA was decreased in 95-1044 and AZACH cells versus normal liver tissue and in AZACH versus 95-1044 cells. In plasma samples, Y RNA levels were decreased in HCC versus HCA and Healthy controls and increased in HCA versus Healthy controls. Receiver operating characteristic analysis showed that Y RNA could be a promising biomarker for distinguishing HCC from HCA and healthy controls. Overall, the dysregulated expression of Y RNA can distinguish canine HCC from HCA. However, further research is necessary to elucidate the underlying Y RNA-related molecular mechanisms in hepatocellular neoplastic diseases. To the best of our knowledge, this is the first report on the relative expression of Y RNA in canine HCC and HCA.

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach.

Breast and lung cancer are two of the most lethal forms of cancer, responsible for a disproportionately high number of deaths worldwide. Both doctors and cancer patients express alarm about the rising incidence of the disease globally. Although targeted treatment has achieved enormous advancements, it is not without its drawbacks. Numerous medicines and chemotherapeutic drugs have been authorized by the FDA; nevertheless, they can be quite costly and often fall short of completely curing the condition. Therefore, this investigation has been conducted to identify a potential medication against breast and lung cancer through structural modification of genistein. Genistein is the active compound in Glycyrrhiza glabra (licorice), and it exhibits solid anticancer efficiency against various cancers, including breast cancer, lung cancer, and brain cancer. Hence, the design of its analogs with the interchange of five functional groups-COOH, NH2 and OCH3, Benzene, and NH-CH2-CH2-OH-have been employed to enhance affinities compared to primary genistein. Additionally, advanced computational studies such as PASS prediction, molecular docking, ADMET, and molecular dynamics simulation were conducted. Firstly, the PASS prediction spectrum was analyzed, revealing that the designed genistein analogs exhibit improved antineoplastic activity. In the prediction data, breast and lung cancer were selected as primary targets. Subsequently, other computational investigations were gradually conducted. The mentioned compounds have shown acceptable results for in silico ADME, AMES toxicity, and hepatotoxicity estimations, which are fundamental for their oral medication. It is noteworthy that the initial binding affinity was only -8.7 kcal/mol against the breast cancer targeted protein (PDB ID: 3HB5). However, after the modification of the functional group, when calculating the binding affinities, it becomes apparent that the binding affinities increase gradually, reaching a maximum of -11.0 and -10.0 kcal/mol. Similarly, the initial binding affinity was only -8.0 kcal/mol against lung cancer (PDB ID: 2P85), but after the addition of binding affinity, it reached -9.5 kcal/mol. Finally, a molecular dynamics simulation was conducted to study the molecular models over 100 ns and examine the stability of the docked complexes. The results indicate that the selected complexes remain highly stable throughout the 100-ns molecular dynamics simulation runs, displaying strong correlations with the binding of targeted ligands within the active site of the selected protein. It is important to further investigate and proceed to clinical or wet lab experiments to determine the practical value of the proposed compounds.

Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach.

Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.

Mixed-Input Deep Learning Approach to Sleep/Wake State Classification by Using EEG Signals.

Sleep stage classification plays a pivotal role in predicting and diagnosing numerous health issues from human sleep data. Manual sleep staging requires human expertise, which is occasionally prone to error and variation. In recent times, availability of polysomnography data has aided progress in automatic sleep-stage classification. In this paper, a hybrid deep learning model is proposed for classifying sleep and wake states based on a single-channel electroencephalogram (EEG) signal. The model combines an artificial neural network (ANN) and a convolutional neural network (CNN) trained using mixed-input features. The ANN makes use of statistical features calculated from EEG epochs, and the CNN operates on Hilbert spectrum images generated during each epoch. The proposed method is assessed using single-channel Pz-Oz EEG signals from the Sleep-EDF database Expanded. The classification performance on four randomly selected individuals shows that the proposed model can achieve accuracy of around 96% in classifying between sleep and wake states from EEG recordings.

Multidrug Resistance Urinary Tract Infection in Chronic Kidney Disease Patients: An Observational Study.

OBJECTIVE: To determine the presence of multidrug-resistant (MDR) urinary tract infections (UTI) and the MDR pattern of the bacterial isolates causing MDR UTI in chronic kidney disease (CKD) patients. METHODS: This cross-sectional study was conducted among 326 diagnosed CKD patients in the Department of Nephrology at Bangabandhu Sheikh Mujib Medical University (BSMMU). Purposive sampling technique was used, and data were collected from the respondents using a semi-structured questionnaire. From duly collected urine samples, identification of organisms and antibiotic susceptibility tests were done, maintaining proper procedure in the microbiology laboratory. RESULTS: The study population was predominantly female (60.1%). The outpatient department provided the majority of the respondents (75.2%). A history of UTI within the last six months was present among 74.2% of the respondents, and 59.2% had a history of taking antibiotics. Bacterial isolates were predominantly gram-negative (79.4%). Escherichia coli was the most prevalent bacterial isolate, present in 55.5% of the study population. Among the respondents, 64.7% were found to have MDR UTI, and among them, 81.5% were gram-negative, and 18.5% were gram-positive isolates. Among all the antibiotics tested, Colistin Sulphate, Polymyxin B, Cefoxitin, Vancomycin, and Linezolid had the highest (100%) sensitivity, followed by Meropenem, with 94.9% sensitivity. Among the gram-negative isolates, Acinetobacter and Enterobacter were most resistant to aminoglycoside, at 70% and 91.7%, respectively. E. coli, Klebsiella, Proteus, and Pseudomonas were most resistant to quinolone at 76.8%, 76.9%, 83.3%, and 66.7%, respectively. Among the gram-positive isolates, Enterococci and Staphylococcus aureus were most resistant to aminoglycoside, 81.5% and 88.9%, respectively. Streptococcus was found to be most resistant to cephalosporin (75.0%). There was a statistically significant (p < 0.05) relationship between MDR UTI, history of UTI, and previous antibiotic intake, and diabetic CKD. CONCLUSIONS: The prevalence of MDR UTI among CKD patients is considerably high. When treating UTI, choosing an appropriate antibiotic by urine culture and implementing a guideline on the rational use of antibiotics are essential to managing and preventing the development of MDR UTI.

Identification, characterization of Apyrase (APY) gene family in rice (Oryza sativa) and analysis of the expression pattern under various stress conditions.

Apyrase (APY) is a nucleoside triphosphate (NTP) diphosphohydrolase (NTPDase) which is a member of the superfamily of guanosine diphosphatase 1 (GDA1)-cluster of differentiation 39 (CD39) nucleoside phosphatase. Under various circumstances like stress, cell growth, the extracellular adenosine triphosphate (eATP) level increases, causing a detrimental influence on cells such as cell growth retardation, ROS production, NO burst, and apoptosis. Apyrase hydrolyses eATP accumulated in the extracellular membrane during stress, wounds, into adenosine diphosphate (ADP) and adenosine monophosphate (AMP) and regulates the stress-responsive pathway in plants. This study was designed for the identification, characterization, and for analysis of APY gene expression in Oryza sativa. This investigation discovered nine APYs in rice, including both endo- and ecto-apyrase. According to duplication event analysis, in the evolution of OsAPYs, a significant role is performed by segmental duplication. Their role in stress control, hormonal responsiveness, and the development of cells is supported by the corresponding cis-elements present in their promoter regions. According to expression profiling by RNA-seq data, the genes were expressed in various tissues. Upon exposure to a variety of biotic as well as abiotic stimuli, including anoxia, drought, submergence, alkali, heat, dehydration, salt, and cold, they showed a differential expression pattern. The expression analysis from the RT-qPCR data also showed expression under various abiotic stress conditions, comprising cold, salinity, cadmium, drought, submergence, and especially heat stress. This finding will pave the way for future in-vivo analysis, unveil the molecular mechanisms of APY genes in stress response, and contribute to the development of stress-tolerant rice varieties.

Acidification scenario of Cox's Bazar coast of the Bay of Bengal, Bangladesh and its influence on fish larvae abundance.

Ocean acidification is caused mainly by atmospheric carbon dioxide stored in the ocean. Ocean acidification is considered a major threat to aquatic life, and how it influences the abundance of marine fish larvae is still unclear. This research was designed to measure the current ocean acidification scenario of the Cox's Bazar coast of the Bay of Bengal, Bangladesh, and its probable influence on the abundance of fish larvae. Three research stations were selected: Bakkhali river estuary, Naf river estuary, and Rezu Khal. Monthly sampling was done, and larvae sample was collected from the surface water column (depth: 0.5 m) using a bongo net. Water parameters such as temperature, salinity, total alkalinity, and pH were determined using laboratory protocol. The seacarb package of the R programming language was used to determine ocean acidification factors. The Bakkhali river estuary showed the highest partial carbon dioxide (143.99 ± 102.27 µatm) and the lowest pH (8.27 ± 0.21). A total of 19 larvae families were identified, and the highest larval count was found in Rezu Khal (390 larvae/1000 m3), while the lowest was found in the Bakkhali river (3 larvae/1000 m3). Clupeidae, Myctophidae, and Engraulidae comprised more than 50% of the identified larvae. Blenniidae, Carangidae, Clupeidae, Engraulidae, and Gobiidae were found in all three seasons. Most of the larvae families showed the highest mean abundance under less pCO2. A negative correlation was observed between larvae and acidification factors such as pCO2, HCO3-, and dissolved inorganic carbon (DIC). The study revealed that acidification parameters of the Cox's Bazar coast were not in an acute state for the aquatic organisms' survival, but fish larvae abundance could be declined with raises in the partial carbon dioxide. The results of this study may aid in developing a management plan for conserving Bangladesh's marine and coastal fish.

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach.

An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein-protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein-ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target's active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

Baicalein as Promising Anticancer Agent: A Comprehensive Analysis on Molecular Mechanisms and Therapeutic Perspectives.

Despite significant therapeutic advancements for cancer, an atrocious global burden (for example, health and economic) and radio- and chemo-resistance limit their effectiveness and result in unfavorable health consequences. Natural compounds are generally considered safer than synthetic drugs, and their use in cancer treatment alone, or in combination with conventional therapies, is increasingly becoming accepted. Interesting outcomes from pre-clinical trials using Baicalein in combination with conventional medicines have been reported, and some of them have also undergone clinical trials in later stages. As a result, we investigated the prospects of Baicalein, a naturally occurring substance extracted from the stems of Scutellaria baicalensis Georgi and Oroxylum indicum Kurz, which targets a wide range of molecular changes that are involved in cancer development. In other words, this review is primarily driven by the findings from studies of Baicalein therapy in several cancer cell populations based on promising pre-clinical research. The modifications of numerous signal transduction mechanisms and transcriptional agents have been highlighted as the major players for Baicalein's anti-malignant properties at the micro level. These include AKT serine/threonine protein kinase B (AKT) as well as PI3K/Akt/mTOR, matrix metalloproteinases-2 & 9 (MMP-2 & 9), Wnt/-catenin, Poly(ADP-ribose) polymerase (PARP), Mitogen-activated protein kinase (MAPK), NF-κB, Caspase-3/8/9, Smad4, Notch 1/Hes, Signal transducer and activator of transcription 3 (STAT3), Nuclear factor erythroid 2-related factor 2 (Nrf2)/Kelch-like ECH-associated protein-1 (Keap 1), Adenosine monophosphate-activated protein kinase (AMPK), Src/Id1, ROS signaling, miR 183/ezrin, and Sonic hedgehog (Shh) signaling cascades. The promise of Baicalein as an anti-inflammatory to anti-apoptotic/anti-angiogenic/anti-metastatic medicinal element for treating various malignancies and its capability to inhibit malignant stem cells, evidence of synergistic effects, and design of nanomedicine-based drugs are altogether well supported by the data presented in this review study.

Understanding how to create healthier places: A qualitative study exploring the complex system of urban development decision-making.

Tackling complex system challenges like creating healthy environments requires understanding priorities and structures affecting multiple actors. This qualitative study, involving 132 multi-sectoral stakeholders spanning the urban development decision-making system, explores how to influence healthier place-making. Using thematic analysis we develop themes around competing stakeholder priorities; structural 'rules' and influential relationships; and justifying a focus on health, requiring greater clarity and consensus around definitions of 'healthy' urban development. Building on the socio-ecological model we highlight how a multi-faceted approach is required for change at multiple levels in the complex system to target individual actor motivations, organisational priorities and structural 'rules'.

Advanced implications of nanotechnology in disease control and environmental perspectives.

Nanotechnology encompasses a wide range of devices derived from biology, engineering, chemistry, and physics, and this scientific field is composed of great collaboration among researchers from several fields. It has diverse implications notably smart sensing technologies, effective disease diagnosis, and sometimes used in treatment. In medical science, the implications of nanotechnology include the development of elements and devices that interact with the body at subcellular (i.e., molecular) levels exhibiting high sensitivity and specificity. There is a plethora of new chances for medical science and disease treatment to be discovered and exploited in the rapidly developing field of nanotechnology. In different sectors, nanomaterials are used just because of their special characteristics. Their large surface area of them enables higher reactivity with greater efficiency. Furthermore, special surface chemistry is displayed by nanomaterials which compare to conventional materials and facilitate the nanomaterials to decrease pollutants efficiently. Recently, nanomaterials are used in some countries to reduce the levels of contaminants in water, air, and soil. Moreover, nanomaterials are used in the cosmetics and medical industry, and it develops the drug discovery (DD) system. Among a huge number of nanomaterials, Cu, Ag, TiO2, ZnO, Fe3O4, and carbon nanotubes (CNTs) are extensively used in different industries for various purposes. This extensive review study has introduced the major scientific and technical features of nanotechnology, as well as some possible clinical applications and positive feedback in environmental waste management and drug delivery systems.

microRNAs Are Abundant and Stable in Platelet-Rich Fibrin and Other Autologous Blood Products of Canines.

Various microRNAs (miRNAs) present in autologous blood products of canines have not been studied recently. We aimed to elucidate the existence of miRNAs in platelet-rich fibrin (PRF) and the stability of canine autologous blood products under various storage conditions. Total RNAs were isolated from PRF and other autologous blood products following newly adapted protocols used in commercial kits for plasma and tissue samples. Quantitative real-time polymerase chain reaction analysis (qPCR) was used to detect miRNAs in autologous blood products. The miR-16, miR-21, miR-155, and miR-146a were abundant in PRF and other autologous blood products of canines. Furthermore, we found they could maintain stability under protracted freezing temperatures of -30 °C for at least one month. Our findings revealed that PRF might be a stable resource for various canine miRNAs.

Features and risk factors of post-COVID-19 syndrome: findings from a longitudinal study in Bangladesh.

Background: A comprehensive study of the post-COVID syndrome (PCS) remains scarce in low-and middle-income countries. We assessed the prevalence, incidence rate, evolution over time, and risk factors of PCS among hospitalized (HS) and non-hospitalized (NHS) COVID-19 survivors. Methods: We undertook a prospective longitudinal study of COVID-19 survivors at months 1, 3, and 5 post-discharge or post-isolation period. The study was conducted at two COVID-19-designated hospitals in Dhaka, Bangladesh, between December 2020 and October 2021. Findings: 362 participants were enrolled in the study; the median time from the onset of COVID-19 to enrolment was 57 days (IQR 41, 82). At enrolment, after adjusting for potential confounders, the HS more often had one or more symptoms, peripheral neuropathy (PN), depression and anxiety disorder, poor quality of life, dyspnea, tachycardia, restrictive lung disease on spirometry, anemia, proteinuria, and need for insulin therapy than the non-hospitalized group (95% CI > 1 for all). Although most of these findings decreased significantly over time in HS, PN increased in both groups. The incidence of diabetes was 9.8/1000 person-month, and the new requirement of insulin therapy was higher (aOR, 6.71; 95% CI, 2.87, 15.67) among HS than the NHS. Older age, being female, comorbidity, cigarette smoking, hospitalization, and contact with COVID-19 cases were independently associated with PCS. Interpretation: We observed a high burden of PCS in hospitalized and non-hospitalized survivors despite most findings' decreasing trend over time. Our results underscore the importance of continuing long-term follow-up and subsequent management. Funding: The United States Agency for International Development (USAID).