Cancer prevention is currently envisioned as a molecular-based approach to prevent carcinogenesis in pre-cancerous stages, i.e., dysplasia and carcinoma in situ. Cancer is the second-leading cause of mortality worldwide, and a more than 61% increase is expected by 2040. A detailed exploration of cancer progression pathways, including the NF-kβ signaling pathway, Wnt-B catenin signaling pathway, JAK-STAT pathway, TNF-α-mediated pathway, MAPK/mTOR pathway, and apoptotic and angiogenic pathways and effector molecules involved in cancer development, has been discussed in the manuscript. Critical evaluation of these effector molecules through molecular approaches using phytomolecules can intersect cancer formation and its metastasis. Manipulation of effector molecules like NF-kβ, SOCS, β-catenin, BAX, BAK, VEGF, STAT, Bcl2, p53, caspases, and CDKs has played an important role in inhibiting tumor growth and its spread. Plant-derived secondary metabolites obtained from natural sources have been extensively studied for their cancer-preventing potential in the last few decades. Eugenol, anethole, capsaicin, sanguinarine, EGCG, 6-gingerol, and resveratrol are some examples of such interesting lead molecules and are mentioned in the manuscript. This work is an attempt to put forward a comprehensive approach to understanding cancer progression pathways and their management using effector herbal molecules. The role of different plant metabolites and their chronic toxicity profiling in modulating cancer development pathways has also been highlighted.

Poisoning and its aftermath are globally observed and acknowledged concerns. India has a large burden of \"self-harm/suicides\" with 12.4/per 100,000 population committing suicide. Consumption of poisonous substances is the second most common mode of self-harm in India. Patients present to both public and private institutions in a critically ill state. The Indian Society of Critical Care Medicine (ISCCM) and Indian College of Critical Care Medicine (ICCCM) decided to address common and contentious issues related to poisoning by developing a position statement that is expected to be appropriate in the Indian scenario by the constitution of an \"expert group\" to provide a \"set of statements\" aimed at addressing the common issues faced by intensivists in their practice in managing such patients. The structured approach, framework, and process adopted in developing the position statement on the approach to poisoning have been detailed in this statement. The formation of an expert advisory panel was followed by a literature search, and multiple sessions of consensus-building exercises to reach the current statement presented below. The statement consists of relevant questions with possible answers thereof. Each answer was further weighed against the data and evidence available in the literature. Recommendations were made using a simplified score to make the statement qualitatively meaningful.
UNASSIGNED: Rungta N, Ray B, Bhalla A, DP Samaddar, Paul G, Prasad S, et al. Indian Society of Critical Care Medicine Position Statement: Approach to a Patient with Poisoning in the Emergency Room and Intensive Care Unit. Indian J Crit Care Med 2024;28(S2):S217-S232.

Arylcyclohexylamine (ACH) compounds represent a predominant faction within new psychoactive substances. Due to their powerful dissociative effects, they are used in recreational contexts but also in situations of drug-facilitated sexual assault, and therefore, they are a constant target of analysis by forensic experts. In recent years, their consumption has been notably high, especially the use of ketamine, presenting daily challenges for laboratories in the determination of this and other ACH analogues. This review comprises the recent strategies that forensic specialists use to identify and quantify ACH compounds in the laboratory with more traditional analytical techniques and technology, and on the point-of-care testing via sensor technology. The study focuses on analogues of phencyclidine (PCP), ketamine, and eticyclidine, highlighting the consistent need for higher sensitivity in the analysis of various samples collected from real cases and simulations of possible matrices. The review also emphasises the ongoing research to develop more sensitive, quicker, and more capable sensors.

Danio rerio is a small tropical freshwater fish, also known as Brachydanio rerio and commonly referred to as zebrafish, described for the first time in 1822 by Francis Hamilton in the Ganges River but widespread throughout the entire Great Himalayan region of Southeast Asia [...].

A common method for identifying an unknown compound involves acquiring its mass spectrum and then comparing that spectrum against a spectral database, or library. Accurate comparison and identification is dependent on the quality of both the library and the test spectrum, but also the search algorithm used. Here, we describe a redesigned probability-based library search algorithm (ProLS) and compare its performance against two predicate algorithms, AMDIS from NIST (NIST) and LibraryView/MasterView (LV/MV), on human urine samples containing drugs of interest that were analyzed by quadrupole-time of flight (QqTOF) mass spectrometry. Each algorithm was used to compare the spectral data collected against an in-house spectral library. ProLS outperformed both NIST and LV/MV in efficiency of drug detection. Additionally, it demonstrated a scoring profile that resulted in an increased likelihood of low match scores for compounds that were absent from a sample. Increased scoring accuracy has the potential to reduce the time that analysts spend manually reviewing match data. Although search algorithms tend to be underappreciated, since they are not typically part of the end-user interface, this work illustrates how a redesigned algorithm can impact the accuracy of identification of small molecules in a biological matrix, and influence the overall utility of a bioanalytical method.

During the reproducibility validation for a time-of-flight (TOF) high-resolution mass spectrometry (HRMS) method set up to detect 61 drugs of abuse commonly encountered in the toxicology laboratory, it was noticed that, a number of compounds were not identified correctly during the between run analysis; the most difficult compounds to identify were norpropoxyphene, morphine, norbuprenorphine, nortriptyline, EDDP and tramadol. In subsequent patient comparison studies, screening a panel of 338 analytes, the TOF-HRMS method correctly identified 211 analytes over two runs, but did not identify 127. A total of 11 false positive results were identified by manual review of the data to be the result of confirmation ion signal-to-noise ratio(s) < 3, although one false positive that was difficult to resolve (i.e., identification of maprotiline as amitriptyline) was due to similar fragment ions and retention times. The TOF-HRMS method showed reasonable agreement with LC-MS/MS results, but there were a number of discrepant results. Additionally, the TOF-HRMS did detect five compounds missed by the LC-MS/MS methods. This extensive validation effort highlights the difficulty of analysis for certain compounds that are likely to require additional follow up prior to reporting a positive result, especially at low and high concentrations, regardless of the type of instrumentation involved.

Methanol, or wood alcohol, is a clear liquid with a weak odor, slightly sweeter than ethanol, which is easily accessible. The last makes it a product of choice for intentional self-harm, severe intoxication, or even suicide. Accidental ingestion and homicidal usage are not exclusions. We present and discuss the case of a man in his 20s who was in continuous alcoholic intoxication until he finally abused with methanol and was admitted to a hospital, where he died six days later. When it comes to intoxication, there are often no apparent findings that could help in determining the cause and manner of death. The last is especially important in cases of delayed death when the toxicology results are negative.

This case report describes a 65-year-old male who presented to the emergency department with significant lactic acidosis after self-poisoning by ingesting bispyribac sodium, a commonly known herbicide. This case highlights the rarity of poisoning with freely available herbicides in the literature, which may be elusive in clinical history and life-threatening in presentation. The patient had attempted to commit suicide with ingestion of an unidentified herbicide and was brought to the emergency department post two hours after the incident. He complained of abdominal pain. The hemodynamics of the patient were within normal limits. However, his initial lactate levels were elevated along with a high anion gap metabolic acidosis. The patient was provided symptomatic care and close monitoring. The ingested substance was later found to be bispyribac sodium. The patient symptomatically improved over time, with lactate levels attaining normal ranges, and was discharged after observation of 24 hours. Human ingestion of bispyribac sodium is mostly asymptomatic and non-fatal. The management in this case mainly consisted of symptomatic care. The initial presentation of herbicide poisoning in an emergency department setting as lactic acidosis and the subsequent evaluation to rule out other possible causes of lactic acidosis in the patient was challenging for the treating physician. The possibility of herbicide-mediated cellular damage and subsequent lactic acidosis is thought to be the reason for this rare presentation.

This study focuses on developing machine learning models to detect subtle alterations in hepatocyte chromatin organization due to Iron (II, III) oxide nanoparticle exposure, hypothesizing that exposure will significantly alter chromatin texture. A total of 2000 hepatocyte nuclear regions of interest (ROIs) from mouse liver tissue were analyzed, and for each ROI, 5 different parameters were calculated: Long Run Emphasis, Short Run Emphasis, Run Length Nonuniformity, and 2 wavelet coefficient energies obtained after the discrete wavelet transform. These parameters served as input for supervised machine learning models, specifically random forest and gradient boosting classifiers. The models demonstrated relatively robust performance in distinguishing hepatocyte chromatin structures belonging to the group exposed to IONPs from the controls. The study\'s findings suggest that iron oxide nanoparticles induce substantial changes in hepatocyte chromatin distribution and underscore the potential of AI techniques in advancing hepatocyte evaluation in physiological and pathological conditions.

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