Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records.

Background: Prostate cancer (PCa) screening is not routinely conducted in men aged 55 and younger, although this age group accounts for more than 10% of cases. Polygenic risk scores (PRSs) and patient data applied toward early prediction of PCa may lead to earlier interventions and increased survival. We have developed machine learning (ML) models to predict PCa risk in men 55 and under using PRSs combined with patient data.

Predicting Falls in Long-term Care Facilities: Machine Learning Study.

Background: Short-term fall prediction models that use electronic health records (EHRs) may enable the implementation of dynamic care practices that specifically address changes in individualized fall risk within senior care facilities.

Objective: The aim of this study is to implement machine learning (ML) algorithms that use EHR data to predict a 3-month fall risk in residents from a variety of senior care facilities providing different levels of care.

Methods: This retrospective study obtained EHR data (2007-2021) from Juniper Communities' proprietary database of 2785 individuals primarily residing in skilled nursing facilities, independent living facilities, and assisted living facilities across the United States.

Prediction of diabetic kidney disease with machine learning algorithms, upon the initial diagnosis of type 2 diabetes mellitus.

Introduction: Diabetic kidney disease (DKD) accounts for the majority of increased risk of mortality for patients with diabetes, and eventually manifests in approximately half of those patients diagnosed with type 2 diabetes mellitus (T2DM). Although increased screening frequency can avoid delayed diagnoses, this is not uniformly implemented. The purpose of this study was to develop and retrospectively validate a machine learning algorithm (MLA) that predicts stages of DKD within 5 years upon diagnosis of T2DM.

Next generation sequencing and functional pathway analysis to understand the mechanism of action of copper-tolfenamic acid against pancreatic cancer cells.

Anti-cancer activity of tolfenamic acid (TA) in preclinical models for pancreatic cancer (PaCa) is well established. Since the dosage for anti-cancer actions of TA is rather high, we recently demonstrated that IC values of Copper-TA are 30-80% less than TA in 12 cancer cell lines. This study elucidates the underlying mechanisms of Copper-TA in PaCa cells.

Deletion of indoleamine 2,3 dioxygenase (Ido)1 but not Ido2 exacerbates disease symptoms of MOG-induced experimental autoimmune encephalomyelitis.

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) with pathological features of inflammation, demyelination, and neurodegeneration. Several lines of evidence suggest that the enzymes indoleamine 2,3-dioxygenase (Ido)1 and/or Ido2 influences susceptibility to autoimmune diseases. Deletion of exacerbates experimental autoimmune encephalomyelitis (EAE) an animal model of MS.

Combination of clotam and vincristine enhances anti-proliferative effect in medulloblastoma cells.

Medulloblastoma (MB) is characterized by highly invasive embryonal neuro-epithelial tumors that metastasize via cerebrospinal fluid. MB is difficult to treat and the chemotherapy is associated with significant toxicities and potential long-term disabilities. Previously, we showed that small molecule, clotam (tolfenamic acid: TA) inhibited MB cell proliferation and tumor growth in mice by targeting, survivin.

Novel Survivin Inhibitor for Suppressing Pancreatic Cancer Cells Growth via Downregulating Sp1 and Sp3 Transcription Factors.

Background/aims: Targeting survivin, an anti-apoptotic protein and mitotic regulator, is considered as an effective therapeutic option for pancreatic cancer (PaCa). Tolfenamic acid (TA) showed anti-cancer activity in pre-clinical studies. A recent discovery demonstrated a copper(II) complex of TA (Cu-TA) can result in higher activity.

Copper-tolfenamic acid: evaluation of stability and anti-cancer activity.

The non-steroidal anti-inflammatory drug, Tolfenamic acid (TA) acts as an anti-cancer agent in several adult and pediatric cancer models. Copper (Cu) is an important element with multiple biological functions and has gained interest in medical applications. Recently, [Cu(TA)(bpy)] (Cu-TA) has been synthesized in order to enhance therapeutic activity.

Investigational agents to enhance the efficacy of chemotherapy or radiation in pancreatic cancer.

Pancreatic cancer (PC) continues to be a fatal malignancy. With standard treatments having modest impact, alternative courses of actions are being investigated such as enhancing the efficacy of standard treatment through sensitization of PC cells to chemotherapy or radiation. This review emphasizes investigational agents that increase the responses to chemotherapy or radiation in PC models.

Tolfenamic acid-induced alterations in genes and pathways in pancreatic cancer cells.

Non-steroidal anti-inflammatory drugs (NSAIDs) are being tested extensively for their role in the treatment and prevention of several cancers. Typically NSAIDs exhibit anti-tumor activities via modulation of cyclooxygenase (COX)-dependent mechanisms, however, an anti-cancer NSAID tolfenamic acid (TA) is believed to work through COX-independent pathways. Results from our laboratory and others have demonstrated the anti-cancer activity of TA in various cancer models including pancreatic cancer.

Combination of tolfenamic acid and curcumin induces colon cancer cell growth inhibition through modulating specific transcription factors and reactive oxygen species.

Curcumin (Cur) has been extensively studied in several types of malignancies including colorectal cancer (CRC); however its clinical application is greatly affected by low bioavailability. Several strategies to improve the therapeutic response of Cur are being pursued, including its combination with small molecules and drugs. We investigated the therapeutic efficacy of Cur in combination with the small molecule tolfenamic acid (TA) in CRC cell lines.