Protective Effect of Triphala against Oxidative Stress-Induced Neurotoxicity

Effect of Acrylamide and Mycotoxins in SH-SY5Y Cells: A Review

Thermal processes induce the formation of undesired toxic components, such as acrylamide (AA), which has been shown to induce brain toxicity in humans and classified as Group 2A by the International Agency of Research in Cancer (IARC), as well as some mycotoxins. AA and mycotoxins' toxicity is studied in several in vitro models, including the neuroblastoma cell line model SH-SY5Y cells. Both AA and mycotoxins occur together in the same food matrix cereal base (bread, pasta, potatoes, coffee roasting, etc.). Therefore, the goal of this review is to deepen the knowledge about the neurological effects that AA and mycotoxins can induce on the in vitro model SH-SY5Y and its mechanism of action (MoA) focusing on the experimental assays reported in publications of the last 10 years. The analysis of the latest publications shows that most of them are focused on cytotoxicity, apoptosis, and alteration in protein expression, while others are interested in oxidative stress, axonopathy, and the disruption of neurite outgrowth. While both AA and mycotoxins have been studied in SH-SY5Y cells separately, the mixture of them is starting to draw the interest of the scientific community. This highlights a new and interesting field to explore due to the findings reported in several publications that can be compared and the implications in human health that both could cause. In relation to the assays used, the most employed were the MTT, axonopathy, and qPCR assays. The concentration dose range studied was 0.1-10 mM for AA and 2 fM to 200 µM depending on the toxicity and time of exposure for mycotoxins. A healthy and varied diet allows the incorporation of a large family of bioactive compounds that can mitigate the toxic effects associated with contaminants present in food. Although this has been reported in some publications for mycotoxins, there is still a big gap for AA which evidences that more investigations are needed to better explore the risks for human health when exposed to AA and mycotoxins.

Acrylamide toxicity in aquatic animals and its mitigation approaches: an updated overview

Acrylamide (ACR) is widely applied in various industrial activities, as well as in the water purification process. Furthermore, ACR is synthesized naturally in some starchy grains exposed to high temperatures for an extended time during the cooking process. Because of its widespread industrial usage, ACR might be released into water stream sources. Also, ACR poses a high risk of contaminated surface and ground-water resources due to its high solubility and mobility in water. Furthermore, animal studies have indicated that ACR exposure may cause cancer (in many organs such as lung, prostate, uterus, and pancreas), genetic damage (in both somatic and germ cells), and severe effects on reproduction and development. Recently, numerous studies have shown that ACR has a mild acute cytotoxic impact on aquatic species, particularly during early life stages. Besides, wide-spectrum usage of ACR in many industrial activities presented higher environmental risks as well as major hazards to consumer health. This literature was designed to include all potential and accessible reports on ACR toxicity related with aquatic species. The Preferred Reporting Items for Systematic Reviews were applied to evaluate the risk effects of ACR on aquatic organisms, the ACR sub-lethal concentration in the ecosystem, and the possible protective benefits of various feed additives against ACR toxicity in fish. The major findings are summarized in Tables 2 and 3. The primary aim of this literature was to specify the hazards of ACR toxicity related with fish welfare and possible suggested strategies to reduce its risks.

Alzheimer's disease: Molecular aspects and treatment opportunities using herbal drugs

Alzheimer's disease (AD), also called senile dementia, is the most common neurological disorder. Around 50 million people, mostly of advanced age, are suffering from dementia worldwide and this is expected to reach 100-130 million between 2040 and 2050. AD is characterized by impaired glutamatergic and cholinergic neurotransmission, which is associated with clinical and pathological symptoms. AD is characterized clinically by loss of cognition and memory impairment and pathologically by senile plaques formed by Amyloid β deposits or neurofibrillary tangles (NFT) consisting of aggregated tau proteins. Amyloid β deposits are responsible for glutamatergic dysfunction that develops NMDA dependent Ca2+ influx into postsynaptic neurons generating slow excitotoxicity process leading to oxidative stress and finally impaired cognition and neuronal loss. Amyloid decreases acetylcholine release, synthesis and neuronal transport. The decreased levels of neurotransmitter acetylcholine, neuronal loss, tau aggregation, amyloid β plaques, increased oxidative stress, neuroinflammation, bio-metal dyshomeostasis, autophagy, cell cycle dysregulation, mitochondrial dysfunction, and endoplasmic reticulum dysfunction are the factors responsible for the pathogenesis of AD. Acetylcholinesterase, NMDA, Glutamate, BACE1, 5HT6, and RAGE (Receptors for Advanced Glycation End products) are receptors targeted in treatment of AD. The FDA approved acetylcholinesterase inhibitors Donepezil, Galantamine and Rivastigmine and N-methyl-D-aspartate antagonist Memantine provide symptomatic relief. Different therapies such as amyloid β therapies, tau-based therapies, neurotransmitter-based therapies, autophagy-based therapies, multi-target therapeutic strategies, and gene therapy modify the natural course of the disease. Herbal and food intake is also important as preventive strategy and recently focus has also been placed on herbal drugs for treatment. This review focuses on the molecular aspects, pathogenesis and recent studies that signifies the potential of medicinal plants and their extracts or chemical constituents for the treatment of degenerative symptoms related to AD.

The clinical evaluation of Basti along with Rasayana on symptoms of post-COVID-19 syndrome: an open-labeled proof of concept pragmatic study-a study protocol

BACKGROUND

Post-COVID-19 syndrome is a result of triggering various immune pathways and metabolic disturbances. Basti is an important per rectal Ayurveda-based treatment having multi-targeted actions. Basti and Rasayana treatment modulate immune responses by regulating pro-inflammatory cytokines, immune globulins, and functional properties of T cell. We propose to study the clinical evaluation of Basti along with Rasayana (rejuvenation therapy) on symptoms of post-COVID 19 syndrome.

METHODS AND ANALYSIS

We designed a prospective, open-labeled proof of concept pragmatic study. The study duration is 18 months, and the intervention period are 35 days from the day of enrollment of the patients. The patients will be treated on the basis of Ayurvedic classification of Santarpanottha (over nutrition) symptoms and Apatarpanottha (lack of nutrition) symptoms. The Santarpanottha group will be treated within 3-5 days of oral Guggulu Tiktak Kashayam followed by 8 days of Yog Basti treatment and then 21 days of Rasayana therapy with Brahma Rasayan. The Apatarpanottha group will be treated within 3-5 days of oral Laghumalini Vasant, followed by 8 days of Yog Basti treatment and then 21 days of Kalyanak Ghrit. The outcome measures of this study will be to evaluate the changes in fatigue severity scale, MMRC dyspnea chest pain scale, pain score assessed by VAS scale, smell and taste scale, WOMAC scale, Hamilton depression scale, Hamilton anxiety scale, Insomnia Severity Index, change in Cough Severity Index, facial aging scale, dizziness scale, Pittsburgh Sleep Severity Quality Index, functional status scale, and heart palpitation scale. All adverse events will be monitored at each time throughout the study visit time. A total of 24 participants will be recruited to demonstrate with 95% confidence interval and 80% power.

DISCUSSION

Ayurveda treats Santarpanottha (originated from over nutrition) symptoms and Apatarpanottha (symptoms originated from undernutrition) symptoms differently; hence, inspite of the same disease or symptom management, changes depend upon the type of the origin. This pragmatic clinical study is developed on the fundamental grounds of Ayurveda.

ETHICS AND DISSEMINATION

Ethics approval was obtained through the Institutional Ethics Committees of Government Ayurved College and Hospital on 23 July 2021.

TRIAL REGISTRATION

The trial is prospectively registered with the Clinical Trial Registry of India on 17 August 2021 [CTRI/2021/08/035732] after the Institutional Ethics Committee approval [GACN/PGS/Synopsis/800/2021 Date 23/7/2021].

Chemical fingerprint analysis and quality assessment of Tibetan medicine Triphala from different origins by high-performance liquid chromatography

INTRODUCTION

Although the Tibetan medicine Triphala (THL) is widely used in many countries, insufficient progress has been made in quality control.

OBJECTIVES

The present study aimed to propose a methodology for quality control of THL based on HPLC fingerprinting combined with an orthogonal array design.

METHODS

Seven identified peaks were used as indicators to examine the effects of temperature, extraction time, and solid-liquid ratio on the dissolution of active ingredients in THL. Fingerprint analysis was performed on 20 batches of THL from four geographical areas (China, Laos, Thailand, and Vietnam). For further chemometric assessment, analysis techniques including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discrimination analysis (OPLS-DA) were used to classify the 20 batches of samples.

RESULTS

Fingerprints were established and 19 common peaks were identified. The similarity of 20 batches of THL was more than 0.9 and the batches were divided into two clusters. Four differential components of THL were identified based on OPLS-DA, including chebulinic acid, chebulagic acid, and corilagin. The optimal extraction conditions were an extraction time of 30 min, a temperature of 90°C, and a solid-liquid ratio of 30 mL/g.

CONCLUSION

HPLC fingerprinting combined with an orthogonal array design could be used for comprehensive evaluation and quality assessment of THL, providing a theoretical basis for further development and utilization of THL.

A gene signature driven by abnormally methylated DEGs was developed for TP53 wild-type ovarian cancer samples by integrative omics analysis of DNA methylation and gene expression data

Background

Integrated omics analysis based on transcriptome and DNA methylation data combined with machine learning methods is very promising for the diagnosis, prognosis, and classification of cancer. In this study, the DNA methylation and gene expression data of ovarian cancer (OC) were analyzed to identify abnormally methylated differentially expressed genes (DEGs), screen potential therapeutic agents for OC, and construct a risk model based on the abnormally methylated DEGs to predict patient prognosis.

Methods

The gene expression and DNA methylation data of primary OC samples with tumor protein 53 (TP53) wild-type and normal samples were obtained from The Cancer Genome Atlas (TCGA) database. DEGs with aberrant methylation were analyzed by screening the intersection between DEGs and differentially methylated genes (DMGs). We attempted to search for potential drugs targeting DEGs with aberrant methylation by employing a network medicine framework. A gene signature based on the DEGs with aberrant methylation was constructed by regularized least absolute shrinkage and selection operator (LASSO) regression analysis.

Results

A total of 440 aberrant methylated DEGs were screened. Based on their gene expression profiles and methylation data from different regions, the results of both discriminative pattern recognition analysis and principal component analysis (PCA) showed a significant separation between tumor tissue and healthy ovarian tissue. In total, 126 potential therapeutic drugs were identified for OC by network-based proximity analysis. Five genes were identified in 440 aberrant methylated DEGs, which formed an aberrant methylated DEGs-driven gene signature. This signature could significantly distinguish the different overall survivals (OS) of OC patients and showed better predictive performance in both the training and validation sets.

Conclusions

In this study, the DNA methylation and gene expression data of OC were analyzed to identify abnormally methylated DEGs and potential therapeutic drugs, and a gene signature based on five aberrant methylation DEGs was constructed, which could better predict the risk of death in patients.

Molecular subtyping and IMScore based on immune-related pathways, oncogenic pathways, and DNA damage repair pathways for guiding immunotherapy in hepatocellular carcinoma patients

Background

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. Although immunotherapy provides hope for advanced HCC patients, the outcomes are not satisfactory and vary by individual case. In this study, we sought to establish novel molecular subtypes and a stable model based on tumor-related pathways for guiding the immunotherapy in HCC patients.

Methods

A total of 15 pathways including immune pathways, stromal pathways, oncogenic pathways, and DNA damage repair pathways were used to construct molecular subtypes through consensus clustering. Immune characteristics, gene mutations, and genomic alterations including copy number variations and homologous recombination deficiency (HRD) were analyzed in different clusters. The Tumor Immune Dysfunction and Exclusion (TIDE) framework was used to predict the response to immunotherapy. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were employed to screen prognostic genes for constructing a risk model.

Results

Three clusters/subtypes were constructed including Immune-E, Immune-D and Stromal-E. Immune-D had the worst prognosis and high enrichment of HRD pathways. Immune-E had higher immune infiltration, higher expression of major histocompatibility complex (MHC)-related genes, and higher expression of PD1, PDL1, CTLA4, and LAG3. TP53 alterations frequently occurred in Immune-D. Immune-E had a relatively high response to immunotherapy and was sensitive to chemotherapeutic drugs. Moreover, we constructed an IMScore model that was effective to classify HCC patients into different risk groups, and the IMScore had a better performance than the TIDE score.

Conclusions

This study revealed the complex interaction among the tumor microenvironment (TME), genomic alterations, and tumor-related pathways by exploring the molecular difference of 3 subtypes. The IMScore model has potential to provide guidance for immunotherapy in HCC patients.

Characterization of osteosarcoma subtypes mediated by macrophage-related genes and creation and validation of a risk score system to quantitatively assess the prognosis of osteosarcoma and reflect the tumor microenvironment

Background

Macrophages are the main immune components in the microenvironment of osteosarcoma. The treatment strategy centered on macrophages has become a hot topic to improve cancer treatment. However, the research on the role of macrophages in the treatment of osteosarcoma is still in its infancy.

Methods

The data of osteosarcoma samples were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and GSE21257 datasets, and the macrophage enrichment fraction of osteosarcoma samples in TARGET was calculated by single-sample gene set enrichment analysis (ssGSEA) method to screen macrophage-related genes for consensus clustering. Differential expression analysis, univariable Cox, and least absolute shrinkage and selection operator (LASSO) regression were conducted to select reliable predictors and create a risk score system. The GSE21257 dataset was used as a verification set to verify the accuracy of risk score system.

Results

We identified 2 osteosarcoma clusters mediated by 22 macrophage score-related genes, namely cluster 1 (C1) and cluster 2 (C2). Compared with C2, C1 had a significant advantage in prognosis, and the degree of immune cell infiltration in tumor microenvironment (TME) was significantly higher, the expression of immune checkpoint molecules was significantly enhanced, and the Tumor Immune Dysfunction and Exclusion (TIDE) score was also significantly down-regulated. A robust risk score system was presented and validated, which demonstrated accuracy and independence in assessing the risk of death of osteosarcoma. The risk score system could also monitor TME infiltration in osteosarcoma samples and showed a close relationship with osteosarcoma biology, including metastasis and immunity.

Conclusions

We identified 2 types of clusters mediated by macrophage-related genes and helped to analyze the cluster suitable for immunotherapy. A new prognostic risk score system was created to quantitatively evaluate the prognosis and TME of osteosarcoma, and to provide a new entry point for the design of personalized treatment.