Integrating optical and electrical sensing with machine learning for advanced particle characterization.

Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.

Identification of novel scaffolds targeting SIRT3 through molecular modeling techniques for the treatment of Hepatocellular carcinoma.

Hepatocellular carcinoma is one of the top causes of cancer-related death globally. SIRT3 belongs to the Sirtuin family of proteins, a collection of NAD+-dependent enzymes that play a role in controlling several cellular functions, including metabolism, aging, and stress response. SIRT3 expression has been discovered to be often downregulated in HCC tissues relative to normal liver tissues. Hence, SIRT3 may function as a tumor suppressor in HCC. In the present study, pharmacophore-based virtual screening of a small molecule database was performed initially, and then the screened hits were docked to the active site of SIRT3 to choose the best binding modes. One co-crystal ligand (PDB name: 1NQ) was utilized as a template to generate pharmacophore model query. A total of 0.2 million compounds from the VITAS-M Lab database were downloaded and prepared for virtual screening. Following database preparation, ligand-based virtual screening was performed using the pharmacophore query model generated in the previous phase. The compounds with the same pharmacophoric characteristics as the query at the same distance were screened. There were a total of 74 hits that matched the query model. These compounds were then docked to the SIRT3 using the standard precision protocol of the glide tool. To select hits with high binding affinities, a threshold of -8 kcal/mol was used. Based on the glide gscore, two hits were chosen. These two hits were selected to investigate the stability of the protein-ligand complex by molecular dynamics simulation. All of these findings indicate that the selected hit compounds C1 and C2 can serve as lead compounds in inhibiting the biological activity of SIRT3 requiring further detailed investigations.Communicated by Ramaswamy H. Sarma.

NAD- and NADPH-Contributing Enzymes as Therapeutic Targets in Cancer: An Overview.

Actively proliferating cancer cells require sufficient amount of NADH and NADPH for biogenesis and to protect cells from the detrimental effect of reactive oxygen species. As both normal and cancer cells share the same NAD biosynthetic and metabolic pathways, selectively lowering levels of NAD(H) and NADPH would be a promising strategy for cancer treatment. Targeting nicotinamide phosphoribosyltransferase (NAMPT), a rate limiting enzyme of the NAD salvage pathway, affects the NAD and NADPH pool. Similarly, lowering NADPH by mutant isocitrate dehydrogenase 1/2 (IDH1/2) which produces D-2-hydroxyglutarate (D-2HG), an oncometabolite that downregulates nicotinate phosphoribosyltransferase (NAPRT) via hypermethylation on the promoter region, results in epigenetic regulation. NADPH is used to generate D-2HG, and is also needed to protect dihydrofolate reductase, the target for methotrexate, from degradation. NAD and NADPH pools in various cancer types are regulated by several metabolic enzymes, including methylenetetrahydrofolate dehydrogenase, serine hydroxymethyltransferase, and aldehyde dehydrogenase. Thus, targeting NAD and NADPH synthesis under special circumstances is a novel approach to treat some cancers. This article provides the rationale for targeting the key enzymes that maintain the NAD/NADPH pool, and reviews preclinical studies of targeting these enzymes in cancers.

Rapid Assessment of Surface Markers on Cancer Cells Using Immuno-Magnetic Separation and Multi-frequency Impedance Cytometry for Targeted Therapy.

The rapid qualitative assessment of surface markers on cancer cells can allow for point-of-care prediction of patient response to various cancer drugs. Preclinical studies targeting cells with an antibody to "activated" matriptase conjugated to a potent toxin show promise as a selective treatment for a variety of solid tumors. In this paper, we implemented a novel technique for electrical detection of proteins on surfaces of cancer cells using multi-frequency microfluidic impedance cytometry. The biosensor, consists of two gold microelectrodes on a glass substrate embedded in a PDMS microfluidic channel, is used in conjugation with immuno-magnetic separation of cancer cells, and is capable of differentiating between bare magnetic beads, cancer cells and bead-cell aggregates based on their various impedance and frequency responses. We demonstrated proof-of-concept based on detection of "activated" matriptase proteins on the surface of cultured Mantle cells.

Toward point-of-care assessment of patient response: a portable tool for rapidly assessing cancer drug efficacy using multifrequency impedance cytometry and supervised machine learning.

We present a novel method to rapidly assess drug efficacy in targeted cancer therapy, where antineoplastic agents are conjugated to antibodies targeting surface markers on tumor cells. We have fabricated and characterized a device capable of rapidly assessing tumor cell sensitivity to drugs using multifrequency impedance spectroscopy in combination with supervised machine learning for enhanced classification accuracy. Currently commercially available devices for the automated analysis of cell viability are based on staining, which fundamentally limits the subsequent characterization of these cells as well as downstream molecular analysis. Our approach requires as little as 20 µL of volume and avoids staining allowing for further downstream molecular analysis. To the best of our knowledge, this manuscript presents the first comprehensive attempt to using high-dimensional data and supervised machine learning, particularly phase change spectra obtained from multi-frequency impedance cytometry as features for the support vector machine classifier, to assess viability of cells without staining or labelling.

A Novel Antibody-Toxin Conjugate to Treat Mantle Cell Lymphoma.

Matriptase is a transmembrane serine protease, synthesized as an inactive single-chain zymogen on the endoplasmic reticulum and transported to the plasma membrane. Matriptase is activated in different epithelial and some B-cell malignancies and changes its conformation and activity is inhibited mainly by its endogenous inhibitor HAI-1. Activated matriptase plays a key role in tumor initiation as well as tumor progression, including invasiveness, and metastasis. To target the anti-mitotic toxin (monomethyl auristatin-E) to activated matriptase, a novel antibody to activated matriptase was conjugated with this toxin via a valine-citrulline-PABA linker. In a previous study, this antibody-toxin conjugate was found to be effective against triple negative breast cancer cell lines and xenografts, alone, or in combination with cisplatin (1). In this study, we examined the anti-tumor effect of the antibody toxin conjugate (ADC) against activated matriptase positive mantle cell lymphoma cell lines (JeKo-1, Maver, Mino, and Z138). This ADC was cytotoxic to these cell lines with IC50s between 5 and 14 µg/mL. The ADC also showed a dose dependent anti-tumor effect on the JeKo-1 xenograft in mice without toxicity.

Modeling and antitumor studies of a modified L-penetratin peptide targeting E2F in lung cancer and prostate cancer.

E2F1-3a overexpression due to amplification or to mutation or loss of the retinoblastoma gene, induces genes involved in DNA synthesis and leads to abnormal cellular proliferation, tumor growth, and invasion. Therefore, inhibiting the overexpression of one or more of these activating E2Fs is a recognized target in cancer therapeutics. In previous studies we identified by phage display, a novel 7-mer peptide (PEP) that bound tightly to an immobilized consensus E2F1 promoter sequence, and when conjugated to penetratin to increase its uptake into cells, was cytotoxic to several malignant cell lines and human prostate and small cell lung cancer xenografts. Based on molecular simulation studies that showed that the D-Arg penetratin peptide (D-Arg PEP) secondary structure is more stable than the L-Arg PEP, the L-Arg in the peptide was substituted with D-Arg. In vitro studies confirmed that it was more stable than the L- form and was more cytotoxic as compared to the L-Arg PEP when tested against the human castrate resistant cell line, DU145 and the human lung cancer H196 cell line. When encapsulated in PEGylated liposomes, the D-Arg-PEP potently inhibited growth of the DU145 xenograft in mice. Our findings validate D- Arg PEP, an inhibitor of E2F1and 3a transcription, as an improved second generation drug candidate for targeted molecular therapy of cancers with elevated levels of activated E2F(s).

Activated matriptase as a target to treat breast cancer with a drug conjugate.

The antitumor effects of a novel antibody drug conjugate (ADC) was tested against human solid tumor cell lines and against human triple negative breast cancer (TNBC) xenografts in immunosuppressed mice. The ADC targeting activated matriptase of tumor cells was synthesized by using the potent anti-tubulin toxin, monomethyl auristatin-E linked to the activated matriptase-specific monoclonal antibody (M69) via a lysosomal protease-cleavable dipeptide linker. This ADC was found to be cytotoxic against multiple activated matriptase-positive epithelial carcinoma cell lines in vitro and markedly inhibited growth of triple negative breast cancer xenografts and a primary human TNBC (PDX) in vivo. Overexpression of activated matriptase may be a biomarker for response to this ADC. The ADC had potent anti-tumor activity, while the unconjugated M69 antibody was ineffective in a mouse model study using MDA-MB-231 xenografts in mice. Treatment of a human TNBC (MDA-MB-231) showed potent anti-tumor effects in combination with cisplatin in mice. This ADC alone or in combination with cisplatin has the potential to improve the treatment outcomes of patients with TNBC as well as other tumors overexpressing activated matriptase.