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A specialized installation has been developed for microscopic study of the Reactive Oxygen Species (ROS) formation during microwave irradiation of biological samples with automated control / mechanized tube and real-time data acquisition. The above installation can be used in biomedical practice for: standardization or certification of the microwave sources; testing of the potential antioxidants that protect tissues from ROS-induced effects; testing fluorescent sensors for ROS; analysis of ROS localization and distribution in various tissues in order to establish specific pharmaco-physiotherapeutic and toxicological localizations of ROS in different topographic-anatomical zones. The paper pays special attention to the singlet oxygen produced by the samples upon microwave treatment, as a physiologically active and highly reactive agent.

Background: Endometrial Thickness (EMT) is considered an important prognostic factor in assisted reproductive technology (ART), particularly in frozen embryo transfer (FET) cycles. Thin endometrium (< 7 mm) is often associated with implantation failure and reduced pregnancy rates, although its precise impact remains controversial.Objective: This thesis summary evaluates the role of thin endometrium in FET cycles, discusses etiologies, diagnostic modalities, treatment approaches, and reviews available patient data.Methods: We retrospectively analyzed 69 patients who underwent FET at Saveetha Medical College. Endometrial thickness was assessed via transvaginal ultrasound. Various treatment strategies including hormonal therapies (estradiol, progesterone), vasoactive agents, granulocyte colony-stimulating factor (G-CSF), platelet-rich plasma (PRP), L-arginine, sildenafil citrate, vitamin E, pentoxifylline, and stem cell therapy were reviewed for their efficacy in improving endometrial receptivity.Results: Endometrial thickness < 7 mm correlated with lower pregnancy rates compared to patients with thickness ≥ 7 mm. Hormonal and adjuvant therapies reported varying degrees of success in improving EMT and subsequent pregnancy outcomes. Vascularity, angiogenesis, and Doppler studies also demonstrated a significant association with endometrial receptivity.Conclusion: Thin endometrium remains a critical challenge in ART cycles. Multimodal therapeutic approaches may improve outcomes; however, larger prospective studies are required to establish standardized protocols. Our patient data support that even minimal increases in EMT can enhance implantation success.

Phyllanthus amarus Schum. and Thonn., a plant of substantial medicinal significance, is known for its usage in the ‘Ayurvedic’ system of medicine for over 2000 years. This herb grows throughout the world including India. P. amarus along with other species of its genus has been a vital part of several herbal formulations available in the Indian market under the trade name Bhuiamlaki. Several pharmacognostic evaluations over the years established the genus Phyllanthus of great commercial value. Ethnopharmacological studies conducted with P. amarus to date have shown its diverse therapeutic usage globally. This owes to the vast array of secondary metabolites present in the herb, substantially in the leaf tissue. Different analytical and phytochemistry studies performed across the globe revealed that P. amarus is a hub of various classes of secondary metabolites viz. lignans like phyllanthin, hypophyllanthin, flavonoids, alkaloids, triterpenes, sterols, volatile oil, ellagitannins including simple and complex tannins, etc. Different analytical techniques have been employed over the past years for isolating and studying these varied secondary metabolites. Further, bioactivities and pharmacological properties of P. amarus that were mainly due to the presence of these wide arrays of secondary metabolites have also been explored extensively across the globe by several research groups. This plant has also been explored at molecular and transcriptome level, although relatively lesser but its extensive molecular and transcriptome analysis have only been performed from our lab. Thus, P. amarus has considerable potential to be explored in the future as a significant therapeutic source not only in the traditional medicinal system but also in the modern pharmaceutical industry.

Pancreatic duct stones (PDS) are a common complication of chronic pancreatitis (CP). PDS can lead to duct obstruction and cause chronic abdominal pain. Ductal stone clearance, as well as short and long-term pain relief, is the cornerstone of endoscopic or surgical treatment. A step-up approach seems reasonable in pancreatic duct stone clearance. Extracorporeal shock wave lithotripsy (ESWL) combined with standard endoscopic retrograde cholangiopancreatography (ERCP) is as effective as a surgical approach for treating painful CP with less morbidity and medical costs. Therefore, endotherapy is considered a first-line therapy in selected patients. In case of insufficient pancreatic ductal clearance or strictures, advanced endoscopic techniques, per-oral pancreatoscopy (POP) with intraductal lithotripsy and/or endoscopic ultrasound-guided ductal drainage (EUS-PDD), will expand the role of the endoscopic approach. Because these new techniques are challenging, technically complex, and with high adverse events (AEs), they should be reserved for advanced tertiary care centers. Although there is increasing data that early surgical intervention may lead to better pain control and pancreatic duct stone clearance, surgery is reserved for patients failing endotherapy or patients with suspected malignancy.

Background: Acute Respiratory Distress Syndrome (ARDS) is a clinically, radiologically, and biologically heterogeneous condition. This variability contributes to diagnostic challenges and inconsistent responses to therapy. Identifying homogeneous subgroups or phenotypes within ARDS may enhance precision medicine and therapeutic targeting.Objective: This review evaluates the utility of decision tree–based supervised machine learning (ML) algorithms—specifically CART, Random Forest, and AdaBoost—in phenotyping ARDS using clinical, radiological, and biological data.Methods: A comprehensive literature search was conducted between December 2023 and March 2024 using PubMed and Google Scholar. Search terms included ‘decision tree in ARDS’, ‘phenotype in ARDS’, and ‘ML in hypo- and hyperinflammatory ARDS’. Twenty-six relevant articles were included, comprising original studies and reviews.Results: Decision tree–based models have demonstrated significant potential in classifying ARDS subtypes using routine clinical variables, radiographic features, and biomarker profiles. These algorithms have shown strong predictive performance in differentiating inflammatory phenotypes, forecasting mortality, and enabling early ARDS prediction.Conclusion: Decision tree algorithms offer a promising approach to ARDS phenotyping by leveraging routinely available data. Their interpretability and predictive accuracy may aid in translating complex biological insights into bedside clinical decision-making, advancing personalized care in critical illness.

Whiteflies (Bemisia tabaci Genn.) are aggressive hemipteran species that depend primarily on leaf tissue for their nourishment, causing substantial damages and yield losses in their hosts. This study was carried out to assess the effect of whitefly infestation on the growth parameters of one of the commercial eggplant cultivars (round green  Solanum melongena L) under filed conditions. The trial consists of four treatments (T1= 15, T2= 30, T3= 45 and control (T4) = 0 whiteflies/plot) replicated four times. The result revealed that all the parameters assessed are negatively affected by whitefly infestation with plants in treatment (T3) being most affected while those in T1 are least affected. The dry weight recorded least value (1.1 g/leaf) having the highest percentage reduction (69.11%) followed by leaf area with 152.5cm2 (48.83% reduction) while the number of leaves was least affected recording 50.3 leaves/plant (18.09% reduction) at 90 days after infestation in 2022 experiment. In 2023 experiment, similar results were recorded with plants in T3 being most affected. Dry weight of the leaves had the lowest value  (1.3g/leaf) representing the highest reduction (68.30%) followed by the  leaf area with 167.3cm2 (44.8% reduction) with the number of leaves also being least affected, recording 52.1 leaves/plant representing 9.40% reduction with plants in treatment T1,  at 90 days after infestation. The highest reduction in yield was also recorded with plants in T3 (92.10, 90.10%) while the least was observed in T1 (86.8 and 85.70%) for the respective trials (2022 and 2023). The result shows the level of susceptibility of the variety examined to whitefly infestation, demonstrating the urgent needs for the development of eco-friendly and sustainable whitefly management regimes for improved eggplant production in the area.

Lichen Planopilaris is known as the form of Lichen Planus typical of the scalp. It is classified as a lymphatic disease and is characterized by chronic inflammation which leads to cicatricial alopecia. Its causes are not yet well characterized but its etiology seems to strongly correlates with infection, sensitization and pollution. A clear and objective diagnosis of Lichen Planopilaris is not simple but the evolution and strongly negative outcomes on scalp of people affected by, pose the need of an early diagnosis. In this work we report the case of a 27-year-old male and a 54-year-old female, respectively, in which a correct diagnosis of Lichen Planopilaris, followed the incorrect previous ones, was made by means of dermatoscopy and histopathological analysis, decisive tools for the diagnosis of this kind of pathology.

Veterinary and agricultural surfactants are supposed to be inert additives, yet these substances commonly exert biological side-effects, in given cases synergistic with those of the active ingredients of these preparations. This is explicitly seen in altered toxicity of veterinary or pesticide formulations compared to their active ingredients alone. Neither the individual effects of these excipients, nor such combination effects are well-studied in toxicology, and therefore, possible toxicity consequences are occasionally not being considered at sufficient significance in the authorization, use and control of these substances. Risk assessment of these substances should cover all hazards they may represent, and corresponding levels of exposure. Surfactants used in veterinary and pesticide formulation enter the environment either by direct dispersion or by indirect release through excrement, leaching, sewage waters or sludge, and in turn, create potential exposure to a number of non-target organisms. Biochemical and (eco)toxicological hazards recently identified regarding certain agricultural surfactants include cytotoxicity (on cell lines of epithelial, neural and other tissues, as well as stem cells and tumor cells), endocrine disrupting effects, as well as aquatic ecotoxicity. This Mini Review summarizes toxicological effects identified in our studies in aquatic toxicity tests, in cell viability and cytotoxicity tests, in estrogenic activity assays, correlated with biochemical analysis of the surfactants and their decomposition. The conclusions are hoped to facilitate environmentally precautious revision of surfactants widely used in agriculture.

Neurotoxicity is increasingly recognized as a critical factor impacting long-term health, with growing evidence linking it to both neurodevelopmental and neurodegenerative diseases. Pesticides, widely used in agriculture and industry, have emerged as significant contributors to neurotoxic risk, given their capacity to disrupt key neurodevelopmental processes at low exposure levels. As conventional animal models present limitations in interspecies translation, human-derived neuron-based in vitro screening strategies are urgently needed to assess potential toxicants accurately. Human-induced pluripotent stem cells (hiPSCs) offer an innovative and scalable source for human-specific neuronal models that complement traditional animal-based approaches and support the development of predictive assays for neurotoxicity. Recent various stem cell models, including 2D cultures, 3D organoids, and microfluidic systems, are now available, advancing predictive neurotoxicology by simulating key aspects of human neural development and function. With the integration of High-Throughput (HT) and High-Content (HC) screening methodologies, these hiPSC-based systems enable efficient, large-scale evaluation of chemical effects on neural cells, enhancing our ability to detect early biomarkers of neurotoxic effects. Identifying early biomarkers of neurotoxic is essential to developing therapeutic interventions before irreversible damage occurs. This is particularly crucial in the context of developmental neurotoxicity, where early exposure to toxicants can have lifelong consequences. This review specifically presents an in-depth overview of the current progress in hiPSC-derived neural models and their applications in neurotoxicity testing, with a specific focus on their utility in assessing pesticide-induced neurotoxicity. Emphasizing future research priorities, we highlight the potential of these models to transform predictive toxicology, offering more human-relevant assessments and advancing the field toward a more precise evaluation of environmental neurotoxicants.

The global energy transition necessitates a shift to renewables to mitigate climate change and ensure energy security. For developing nations like Ethiopia, this presents a critical opportunity to leverage abundant domestic resources for suitable development. Ethiopia, with over 45% of its population lacking electricity, faces a paradox of energy poverty and immense renewable potential. Its grid is 90% hydropower-dependent, making it vulnerable to climate-induced droughts. Previous studies have individually assessed Ethiopia’s hydropower, geothermal, wind, and solar potential. However, a holistic analysis integrating all sectors with current policy and investment frameworks is needed. This article provides a comprehensive analysis of Ethiopia’s renewable energy landscape. We synthesize the potential of hydropower, geothermal, wind, and solar resources, and propose integrated policy and investment pathways to achieve universal electrification by 2030 and position Ethiopia as a regional renewable energy exporter.