Single Institute Experience with Neo-Adjuvant Chemotherapy and Interval Debulking Surgery in Advanced Endometrial Cancer.

Our study aims to review the role of neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) in patients with advanced endometrial cancer. Patients with advanced endometrial cancer treated with NACT followed by IDS at our institute from January 2010 to January 2020 were recruited. Data pertaining to baseline patient characteristics, surgical details, histopathology/imaging reports, treatment and follow up details including the development of recurrence and death were collected from institutional database.

Evaluation of programmed cell death ligand 1 expression in a contemporary cohort of penile squamous cell carcinoma and its correlation with clinicopathologic and survival parameters: A study of 134 patients.

Objectives: Penile squamous cell carcinomas (PCs) are rare malignancies with a dismal prognosis in a metastatic setting; therefore, novel immunotherapeutic modalities are an unmet need. One such modality is the immune checkpoint molecule programmed cell death ligand 1 (PD-L1). We sought to analyze PD-L1 expression and its correlation with various clinicopathologic parameters in a contemporary cohort of 134 patients with PC.

Multifaceted Spindle Cell/Sclerosing Rhabdomyosarcoma With Role of Immunohistochemistry in Avoiding Misdiagnosis: A Multi-Institutional Study of 45 Distinct Tumors.

Spindle cell/sclerosing rhabdomyosarcoma is a rare neoplasm and has an aggressive clinical course. Because of its rarity, we performed a multi-institutional collaboration to comprehend the overarching clinical, histopathological, and immunohistochemical characteristics of a cohort of spindle cell/sclerosing rhabdomyosarcoma. Forty-five patients with spindle cell/sclerosing rhabdomyosarcoma were identified.

An AI Approach to Generating MIDD Assets Across the Drug Development Continuum.

Model-informed drug development involves developing and applying exposure-based, biological, and statistical models derived from preclinical and clinical data sources to inform drug development and decision-making. Discrete models are generated from individual experiments resulting in a single model expression that is utilized to inform a single stage-gate decision. Other model types provide a more holistic view of disease biology and potentially disease progression depending on the appropriateness of the underlying data sources for that purpose.

Integrating AI/ML Models for Patient Stratification Leveraging Omics Dataset and Clinical Biomarkers from COVID-19 Patients: A Promising Approach to Personalized Medicine.

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare system. Identifying the genomics and clinical biomarkers for effective patient stratification and management is critical to controlling the spread of the disease. Omics datasets provide a wealth of information that can aid in understanding the underlying molecular mechanisms of COVID-19 and identifying potential biomarkers for patient stratification.

In Silico Development of Combinatorial Therapeutic Approaches Targeting Key Signaling Pathways in Metabolic Syndrome.

Purpose: Dysregulations of key signaling pathways in metabolic syndrome are multifactorial, eventually leading to cardiovascular events. Hyperglycemia in conjunction with dyslipidemia induces insulin resistance and provokes release of proinflammatory cytokines resulting in chronic inflammation, accelerated lipid peroxidation with further development of atherosclerotic alterations and diabetes. We have proposed a novel combinatorial approach using FDA approved compounds targeting IL-17a and DPP4 to ameliorate a significant portion of the clustered clinical risks in patients with metabolic syndrome.

Nodal Langerhans cell neoplasm: detailing the diagnostic quandaries.

Langerhans cells, found in the supra-basal region of the mucous membranes in the epidermis of the skin, in lymph nodes and thymus, function as antigen-presenting cells within the histiocyte system. Tumors derived from Langerhans cells (LC) can be divided according to the degree of cytological atypia and clinical behavior into Langerhans cell histiocytosis (LCH) and Langerhans cell sarcoma (LCS). LCS is rare, and the nodal presentation is even rarer with challenging histological characteristics.

A hybrid modeling approach for assessing mechanistic models of small molecule partitioning in vivo using a machine learning-integrated modeling platform.

Prediction of the first-in-human dosing regimens is a critical step in drug development and requires accurate quantitation of drug distribution. Traditional in vivo studies used to characterize clinical candidate's volume of distribution are error-prone, time- and cost-intensive and lack reproducibility in clinical settings. The paper demonstrates how a computational platform integrating machine learning optimization with mechanistic modeling can be used to simulate compound plasma concentration profile and predict tissue-plasma partition coefficients with high accuracy by varying the lipophilicity descriptor logP.

Effects of Magnesium, Calcium, and Aluminum Chelation on Fluoroquinolone Absorption Rate and Bioavailability: A Computational Study.

Fluoroquinolones (FQs) are a widespread class of broad-spectrum antibiotics prescribed as a first line of defense, and, in some cases, as the only treatment against bacterial infection. However, when administered orally, reduced absorption and bioavailability can occur due to chelation in the gastrointestinal tract (GIT) with multivalent metal cations acquired from diet, coadministered compounds (sucralfate, didanosine), or drug formulation. Predicting the extent to which this interaction reduces in vivo antibiotic absorption and systemic exposure remains desirable yet challenging.

Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform.

The COVID-19 pandemic has reached over 100 million worldwide. Due to the multi-targeted nature of the virus, it is clear that drugs providing anti-COVID-19 effects need to be developed at an accelerated rate, and a combinatorial approach may stand to be more successful than a single drug therapy. Among several targets and pathways that are under investigation, the renin-angiotensin system (RAS) and specifically angiotensin-converting enzyme (ACE), and Ca-mediated SARS-CoV-2 cellular entry and replication are noteworthy.

In Silico Simulation of the Systemic Drug Exposure Following the Topical Application of Opioid Analgesics in Patients with Cutaneous Lesions.

The use of opioid analgesics in treating severe pain is frequently associated with putative adverse effects in humans. Topical agents that are shown to have high efficacy with a favorable safety profile in clinical settings are great alternatives for pain management of multimodal analgesia. However, the risk of side effects induced by transdermal absorption and systemic exposure is of great concern as they are challenging to predict.

Driving success in personalized medicine through AI-enabled computational modeling.

The development of successful drugs is expensive and time-consuming because of high clinical attrition rates. This is caused partially by the rupture seen in the translatability of the drug from the bench to the clinic in the context of personalized medicine. Artificial intelligence (AI)-driven platforms integrated with mechanistic modeling have become instrumental in accelerating the drug development process by leveraging data ubiquitously across the various phases.

Molecular Simulation and Statistical Learning Methods toward Predicting Drug-Polymer Amorphous Solid Dispersion Miscibility, Stability, and Formulation Design.

Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API-carrier mixture and the principal API-carrier non-bonding interactions are critical factors for rational drug development and formulation decisions. Experimental determination of these interactions, solubility, and dissolution mechanisms is time-consuming, costly, and reliant on trial and error.

Scalable in silico Simulation of Transdermal Drug Permeability: Application of BIOiSIM Platform.

Introduction: Transdermal drug delivery is gaining popularity as an alternative to traditional routes of administration. It can increase patient compliance because of its painless and noninvasive nature, aid compounds in bypassing presystemic metabolic effects, and reduce the likelihood of adverse effects through decreased systemic exposure. In silico physiological modeling is critical to predicting dermal exposure for a therapeutic and assessing the impact of different formulations on transdermal disposition.

Entering the era of computationally driven drug development.

Historically, failure rates in drug development are high; increased sophistication and investment throughout the process has shifted the reasons for attrition, but the overall success rates have remained stubbornly and consistently low. Only 8% of new entities entering clinical testing gain regulatory approval, indicating that significant obstacles still exist for efficient therapeutic development. The continued high failure rate can be partially attributed to the inability to link drug exposure with the magnitude of observed safety and efficacy-related pharmacodynamic (PD) responses; frequently, this is a result of nonclinical models exhibiting poor prediction of human outcomes across a wide range of disease conditions, resulting in faulty evaluation of drug toxicology and efficacy.

Epizootiological observations on canine microfilaremia in Gujarat state, India.

Aim: The present investigation was conducted to study the prevalence of microfilaremia in dogs in Gujarat.

Materials And Methods: A total of 418 adult dogs aged between 2 and 14 years with signs of weakness and non-specified complaints, presented at TVCC, Deesa (North Gujarat), Nandini Veterinary Hospital, Surat (South Gujarat), and Private Clinics, Ahmedabad (Central Gujarat), were included in the present investigation for studying the prevalence of microfilaremia from July 2016 to May 2017.

Results: A total of 418 dogs were screened, of which 33 were found positive for circulating microfilariae with the prevalence rate of 7.

CRISPR/Cas9-Based Positive Screens for Cancer-Related Traits.

Since the advent of large-scale, detailed descriptive cancer genomics studies at the beginning of the century, such as The Cancer Genome Atlas (TCGA), labs around the world have been working to make this data useful. Data like these can be made more useful by comparison with complementary functional genomic data. One new example is the application of CRISPR/Cas9-based library screening for cancer-related traits in cell lines.

AlzhaTV: A nonpharmacological intervention to manage behavioral and psychological symptoms in nursing home dementia patients.

Background: Currently, 5 million seniors who reside in the community or assisted living or nursing facilities are affected by Alzheimer's disease and other neurocognitive disorders. They experience various psychiatric symptoms. Also, their family members are stressed from caregiving, and may feel guilty for not doing more.

Comparative Transcriptome Analysis Quantifies Immune Cell Transcript Levels, Metastatic Progression, and Survival in Osteosarcoma.

Overall survival of patients with osteosarcoma (OS) has improved little in the past three decades, and better models for study are needed. OS is common in large dog breeds and is genetically inducible in mice, making the disease ideal for comparative genomic analyses across species. Understanding the level of conservation of intertumor transcriptional variation across species and how it is associated with progression to metastasis will enable us to more efficiently develop effective strategies to manage OS and to improve therapy.

Slit-Robo GTPase-Activating Protein 2 as a metastasis suppressor in osteosarcoma.

Osteosarcoma is the most common primary bone tumor, with metastatic disease responsible for most treatment failure and patient death. A forward genetic screen utilizing Sleeping Beauty mutagenesis in mice previously identified potential genetic drivers of osteosarcoma metastasis, including Slit-Robo GTPase-Activating Protein 2 (Srgap2). This study evaluates the potential role of SRGAP2 in metastases-associated properties of osteosarcoma cell lines through Srgap2 knockout via the CRISPR/Cas9 nuclease system and conditional overexpression in the murine osteosarcoma cell lines K12 and K7M2.

Importance of CT Scan of Paranasal Sinuses in the Evaluation of the Anatomical Findings in Patients Suffering from Sinonasal Polyposis.

Sinonasal polyps are benign lesions arising from nose and/or sinuses mucosa. Paranasal sinuses computed tomogram (CT) scan are important for functional endoscopic sinus surgery (FESS) as their information assist the surgeon in pre-operative planning. This study aimed to show importance of CT scan in evaluation of anatomical variations to prove a correlation with disease process and extent of disease in sinonasal polyposis patients.

Imprinting defects at human 14q32 locus alters gene expression and is associated with the pathobiology of osteosarcoma.

Osteosarcoma is the most common primary bone malignancy affecting children and adolescents. Although several genetic predisposing conditions have been associated with osteosarcoma, our understanding of its pathobiology is rather limited. Here we show that, first, an imprinting defect at human 14q32-locus is highly prevalent (87%) and specifically associated with osteosarcoma patients < 30 years of age.

Polycyclic aromatic hydrocarbons' formation and occurrence in processed food.

Polycyclic aromatic hydrocarbons (PAHs) emerged as an important contaminant group in a gamut of processed food groups like dairy, nuts, herbs, beverages, meat products etc. Different cooking processes and processing techniques like roasting, barbecuing, grilling, smoking, heating, drying, baking, ohmic-infrared cooking etc. contribute towards its formation.