Background: Urinalysis is one of the most commonly performed screening tests in the Clinical laboratory to diagnose and monitor various urological and systemic conditions. Newly developed automated urine analyzers are expected to routinely screen urine to reduce TAT and provide clinicians with prompt clinical information with a lower false-negative rate. The study aimed to evaluate the diagnostic performance of the two Automated Urine analyzers and compare them with microscopy. Method: There were 124 randomly selected samples of patients coming to the clinical pathology laboratory were taken for each Automated analyzer and microscopic evaluation. The results of various cells, formed elements and microorganisms were compared between both the automated urine analyzers and microscopy and the degree of concordance was calculated for each parameter. Results: The degree of concordance of RBC, WBC and epithelial cells was good between the two automated analyzers; URiSCAN Super+ YD Diagnostics and Sysmex UC-3500 -UF 5000 Urine Analyzer and microscopy with p <0.001. The concordance between the Sysmex UC-3500 - UF 5000 Urine Analyzer and manual microscopy was better than between manual microscopy and Uriscan Super + YD Diagnostics. There was no concordance between all these methods for either crystals, cast, bacteria and fungi with p >0.05 Conclusion: The results from the automated analyzers for RBCs, WBCs and epithelial cells were similar to the result of manual microscopy and the analyzers can be relied upon. However, bacteria, fungi, dysmorphic red cells, casts and crystals need to be analyzed by microscopic examination before giving a final diagnosis.

The much hyped Artificial Intelligence (AI) model known as chat generative pre-trained transformer ( Chat GPT), developed by Open AI can have far-reaching benefits for pathologists saving time so that they can devote their time to more meaningful work. Generative AI is a special class of AI model, that based on patterns and structures learned from existing data can create new data. However, certain hurdles have to be taken care of like integrating ChatGPT with image analysis which will revolutionize the field of pathology by providing assistance with diagnostic accuracy and precision. Generation of meaningful insights from the textual information provided by ChatGPT can be possible by the platform which should have the capability of processing different types of image data, such as medical images, and pathology slides. Due consideration should be given to ethical and legal issues including bias.

The emergence of COVID-19 as a global pandemic has had far-reaching effects on the health of individuals worldwide. Although there has been a decrease in the severity of the disease, there is a growing concern about the long-term impact of COVID-19 on the health of individuals, particularly cardiovascular complications, known as Long-COVID, which can significantly increase morbidity and mortality rates in people recovering from COVID-19 in the recent past. The severity of COVID-19 has been linked to various factors, including the role of neutrophils and neutrophil extracellular traps (NET). These extracellular webs, composed of chromatin, microbicidal proteins, and oxidant enzymes, are released by neutrophils to fight infections. However, if not properly regulated, NETs can lead to thrombo-inflammatory states and microangiopathy in the body, resulting in complications such as sepsis, thrombosis, and respiratory failure. Understanding the detailed pathophysiology and association of NETs with the prognosis of COVID-19 infection is crucial for future implications and management. The purpose of this review is to analyze the potential contribution of NETosis in the pathophysiology of COVID-19 and its subsequent complications apart from its beneficial effect. This may provide insight into potential therapeutic interventions for COVID-19 patients.

The past few decades have witnessed a major leap in knowledge relating to the role of tumor microenvironment in carcinogenesis and evolving behaviour of the tumor. Multiple factors within the tumor microenvironment modulate the cancer cells and the associated therapies. Stephen Paget first asserted that the microenvironment plays an important role in the growth of tumor metastasis. The most important player in the tumor microenvironment is cancer-associated fibroblast which significantly participates in the proliferation, invasion and metastasis of tumor cells. Cancer-associated fibroblasts show phenotypic and functional heterogeneity. Mostly cancer-associated fibroblasts originate from quiescent resident fibroblast or mesoderm-derived precursor cells (mesenchymal stem cells), although several alternate sources of origin have been noted, however, due to a lack of specific fibroblast-restricted markers, it is very difficult to trace lineage and identify the biological origin of distinct sub-types of CAFs. CAFs are predominantly shown by several studies to mainly act as tumor-promoting agents, however, tumour-inhibiting actions are also being validated by several studies. A more objectified and comprehensive functional and phenotypic classification of CAF is required, which will help in better way for tumor management. Here, in this review, we have tried to review the current status of CAF origin, along with phenotypic and functional heterogeneity, and recent progress in cancer-associated fibroblast (CAF) research.