priyanka singh

Despite advancements in antimicrobial and anti-inflammatory treatments, inflammation and its repercussions continue to pose a considerable challenge in medicine. Acute inflammation may cause life-threatening conditions like septic shock, while chronic inflammation leads to tissue degeneration and impaired function. Lipopolysaccharides (LPS), a well-known pathogenic trigger contributing to several dysfunctions, is a crucial part of the outer membrane of gr-negative bacteria. LPS are well-known for eliciting acute inflammatory responses by activating a pathogen-associated molecular pattern (PAMP), which stimulates the innate immune system and triggers local or systemic inflammatory responses. LPS also activate numerous intracellular molecules that modulate the expression of a wide range of inflammatory mediators. These mediators subsequently initiate or exacerbate various inflammatory processes. Beyond immune cells, LPS can also activate non-immune cells, leading to inflammatory reactions. These excessive inflammatory responses are often detrimental and typically result in chronic and progressive inflammatory diseases, including neurodegenerative, cardiovascular diseases, and cancer. This review delves into the mechanisms by which the bacterial endotoxin LPS contribute to multiple inflammatory diseases. These insights into LPS signaling pathways could inform the design of new treatment strategies such as TLR4, NLRP3, HMGA1, MAPK, and NF-kB inhibitors. This enables precise targeting of inflammation-related processes in disease management.

Atherosclerosis is a primary cause of illness and death globally and its mechanism is still unclear. Different animal models have been created to evaluate the progression of atherosclerosis, allowing researchers to carefully control the circumstances of the experiment as well as the nutrition and environmental risk factors. To investigate the negative effects of various interventions, pathophysiological alterations might be generated utilizing genetic or pharmacological methods. These models’ molecular and pathophysiological mechanisms have been clarified through experiments, and they have served as platforms for the creation of new drugs. Different models can be employed to address various research problems, each with its own benefits and drawbacks. In the current review study, various species of atherosclerosis models are discussed, along with the viability of using them in experiments.

The multifaceted pathophysiology of diabetic wounds coupled with impaired diabetic woundhealing remains a significant challenge for the medical community in the 21st century. Possibilityof bacterial infections, insufficient vascular supply, increment in levels of oxidative stress, andabnormalities in defenses mechanism of antioxidant causes diabetic foot ulcers (DFU) that leads tosignificant morbidity. An effective treatment for diabetic wounds is still lacking. Chronic woundsare taking epidemic proportions, leading to an increased interest in exploring novel therapiesto meet the challenges. Evaluating the progression in diabetic ulcers poses a major threat forthe patients and clinician owing to logistics as irregular visits to the clinics. Unique propertiesof nanoparticles contain ultra-small size, increased surface-to-volume ratio, low cytotoxicity,enhanced cellular uptake, improved antibacterial activity, biocompatibility and biodegradabilitymaking their applications attractive against DFUs. Their potential for healing can be due to theirsuperior antioxidant and anti-inflammatory activities. Further, nanoparticles are effective deliveryvehicles for various small molecules, exosomes, metallic molecules, or conjugated with numerousbiomaterials- chitosan (CS), hyaluronic acid (HA) and smart hydrogels (HG) to enhance theirhealing efficacy against diabetic wounds. This review focuses on the futuristic and potentialviewpoints of nanoparticles for the therapeutics of diabetic wounds/DFUs. Artificial intelligence(AI) tools and optical sensors can further contribute effectively for the monitoring procedures.Software based on AI technology plays crucial role in assessment and provide continuous carethroughout the treatment. AI also helps to connect healthcare experts with larger number ofpatients at the same time. Nanotherapeutics represents a promising innovative strategy for targetedtreatment that can change the landscape of wound healing, by providing a physiologically stablemicro-environment for the thorough wound-healing process.

This study aimed to evaluate the dosimetric variations and treatment efficacy between intensity-modulated radiotherapy (IMRT) and double-arc RapidArc for irradiation of carcinoma left breast, focusing on adequate target coverage, sparing of organs at risk (OARs), delivered monitor units (MUs) per fraction, and treatment delivery time. This prospective, observational study was conducted on 30 patients with carcinoma left breast. All these patients were treated with adjuvant radiation therapy.  We generated two plans for each of these patients: IMRT and double-arc RapidArc technique. The target volume and OARs were analyzed using dose-volume histograms (DVHs). The average MUs and the treatment time were used as markers to assess the efficacy of treatment delivery. The planning target volume parameters such as homogeneity and conformity index were similar for all the plans with both techniques. With IMRT, statistically significantly better sparing of I/L lung, heart, C/L breast, C/L lung, and esophagus were achieved as compared to RapidArc. We found that RapidArc resulted in significantly lower MUs (535.05 ± 105.42) than IMRT (913.57 ± 129.35). Treatment delivery time was statistically shorter with RapidArc as compared to IMRT (p=0.001).  This study concluded that both IMRT and RapidArc plans have similar target coverage in terms of homogeneity and conformality indexes. Better OARs sparing was noticed with IMRT while RapidArc enabled higher efficacy with lower MUs and shorter treatment delivery time. However, further studies are needed to establish these dosimetric advantages being translated to improvements in the clinical outcomes of these patients.

Tobacco consumption causes altered immune and inflammatory responses which lead to various respiratory diseases such as asthma and chronic obstructive pulmonary disease, as well as cardiovascular and cerebrovascular disorders. Studies have only confirmed the harmful effects of tobacco consumption on the severity of COVID-19. The present study aimed to explore the association between tobacco consumption and the initiation of COVID-19. This retrospective cohort study was conducted to explore the relationship between tobacco consumption and COVID-19. A brief closed-ended, self-structured questionnaire was prepared to record participants’ responses. The Participants included the individuals who visited Rajendra Institute of Medical Sciences (RIMS), Ranchi, India for the COVID-19 diagnostic test. The statistical analysis was performed using SPSS software (version 24). The chi-square test and logistic regression analysis were also used to predict the odds of getting infected with COVID-19.  A total of 521 valid responses were obtained and subjected to analysis. Moreover, 256 participants (49.13%) were COVID-19 positive and 57 participants (10.94%) were tobacco users. The odds ratio of tobacco consumption was higher in COVID-19-positive patients compared to COVID-19-negatives (OR=1.78; 95% CI 1.01, 3.13). The current tobacco users had a higher risk of developing COVID-19 as compared to the former users (OR=4.8; 95% CI 1.39, 16.61). The frequency and duration of tobacco use also affected the COVID-19 infectivity rate but these were statistically insignificant. The COVID-19 positivity rate was significantly higher in tobacco users, especially in current tobacco users as compared to former users. Nevertheless, gender and occupation had no significant effect on COVID-19 incidence in this study.

Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening syndrome of excessive immune activation, which is characterized by fever, hepatosplenomegaly, cytopenias, hyperferritinemia, hypertriglyceridemia, and/or hypofibrinogenemia, and evidence of hemophagocytosis. Secondary HLH is often seen in adults and categorized based on autoimmune, infections-related, and malignancy-associated etiologies such as A-HLH, I-HLH, and M-HLH, respectively. This study presented a rare case of HLH developing concurrently at the time of diagnosis of T-cell Acute Lymphoblastic Leukemia (T- ALL) with a unique presentation of membranous tonsillitis in a 10-year-old boy. In all of the cases of T-ALL reported in the pediatric age group, HLH develops post-therapy or at the relapse. The first presentation of leukemia as membranous tonsillitis and concurrent clinic laboratory findings of HLH is rare and can mislead the diagnosis. Therefore, prompt diagnosis is the mainstay of therapy and can considerably improve the prognosis.

In this paper, an Economic Production Quantity (EPQ) inventory model for deteriorating items with price-stock dependent demand rate under complete and partial backlog is developed, in which the deterioration rate is controlled by investment in preservation technology. To fulfil the demand and to reduce the shortage we have considered the production rate proportional to the selling price of the product. This study is to maximize the total profit for seasonal deteriorating items by simultaneously determining the optimal selling price, the optimal production and the optimal preservation technology cost when the producer invests in the preservation technology to reduce the deterioration rate. We first show that for any given number of the production cycle, optimal selling price and preservation technology cost exists and are unique. Next, we show that the total profit is a jointly concave function of selling price and preservation technology cost. We provide some conditions to determine an optimal solution that maximizes profits for the EPQ model. We then provide a simple algorithm to figure out the optimality of total profit for the proposed model. Mathematical theorems are developed to determine optimal inventory policy. Numerical results demonstrate the advantages of the preservation technology, and further show the effects of different system parameters on the optimal variables and the maximal total profit. Finally, some managerial implications are provided.