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The Coronavirus disease (COVID-19) outbreak in 2019, has shocked the entire world. As an effort to control the disease spread, the Indian government declared a nationwide lockdown on March 25th, 2020. As dental treatment was considered high risk in the spread of COVID-19, dentistry became one of the most vulnerable professions during this time. Dental professionals had to face job layoffs, salary cuts in professional colleges, closure of private clinics resulting in huge psychological, moral, and financial crises. Studies during the previous and present pandemics have shown mental issues among health care workers necessitating institutional reforms, along with early care and support. A balance in the work-life amongst professionals is the key to better efficiency and, was majorly affected during the COVID-19 pandemic lockdown due to sudden unexpected changes. Hence this study was conducted to understand the changes they underwent both at home and professional front with a hypothesis that physical and mental health, activities, relationship status, and workplace influence the work-life balance. A pre-validated questionnaire survey was done on dentists across India. Structural Equation Modelling and path analysis were applied to the data collected. The results of the study supported the hypothesis that factors like physical and mental health, activities, relationship status, and workplace influenced the work-life balance directly. A significant imbalance was seen amongst the female dentists. The present study proved the unpreparedness among dental professionals. Hence an evolutionary phase in every field with better working protocols, robust mental health support, and a focus on strategies to face future such emergencies is required.

Background The shipbuilding and ship-repair industries are important contributors to world trade. However, it also generates various types of waste, similar to any other industry, which has a detrimental impact on the environment. This study aims to understand the critical need for effective and appropriate waste management practices in this industry by investigating the factors involved in generating various types of waste. It identifies and ranks the major challenges in waste management in this industry. The study also suggests potential solutions for shipyards and repair yards to address these challenges. Methods The study used the Fuzzy Delphi Method (FDM) to prioritize the challenges identified through a literature review and finalized them based on the feedback of experts. Further, a list of solutions for these challenges was prepared based on interviews with experts in this area. Finally, the Best Worst Method (BWM) was used to rank the solutions for each of the identified challenges. Results The findings indicate that the major challenges for the industry are the generation of hazardous waste and the high costs involved in adopting sustainable practices. The results also showed that strict waste segregation and containment are the top solutions to handle the challenge of hazardous waste generation. Further, the leverage on external funding mechanisms and implementation in a phase-wise manner are the top two solutions to deter the challenge of high costs associated with adopting sustainable practices. Conclusions By prioritizing these challenges and solutions, this study provides a road map for shipyards around the world to effectively allocate resources, improve environmental performance, meet regulations, and improve operational performance. This is important for the adoption of an environmentally friendly and economically sustainable shipbuilding and repair industry.

Background E-waste has rapidly become the fastest growing waste stream in the world, posing serious threats to environmental sustainability and the global agenda for a cleaner, greener, and more prosperous future. Countries that are relatively new to e-waste management as India, face significant challenges in identifying and addressing the barriers to effective mitigation efforts. Methods This study employs the Interpretive Structural Modelling (ISM) technique to decode and structure six levels of barriers leading to the seventh and most critical barrier: lack of sustainable design practices. In addition, a MICMAC analysis is used to classify the identified e-waste challenges as either driving or dependent variables, offering strategic insights for stakeholders. To further validate the findings, the Analytic Hierarchy Process (AHP), a multi-criteria decision-making (MCDM) method, is applied to assign weightage to each challenge based on expert input and to assess the robustness of the data. Results The analysis reveals the absence of autonomous factors in the e-waste challenge ecosystem. Key dependent factors include fluctuating supply chains, underdeveloped R&D practices, lack of safety protocols, and poor integration of sustainable design practices. These are influenced by key driving constraints such as illegal e-waste practices, inconsistent policies and regulations, poor coordination, and limited accessibility. These driving challenges act as precursors to the ultimate barrier: the lack of sustainable design practices. Conclusions The study provides actionable insights and prioritization of challenges that can guide policymakers and business leaders in developing effective e-waste mitigation strategies. The structured model offers a foundational framework for countries—whether newly engaged or planning to implement e-waste management to adopt it as a national agenda for achieving sustainable development goals.

Objectives: The aim of the study was to assess the effect of life course factors on dental fear among adult dental patients attending out-reach clinics in a rural area of South India. The objectives were to measure dental fear and changes in socio-economic status during the life course among the study population and to know whether social mobility reduced/increased dental fear. Methods: Dental fear scale and life course data were collected from 403 respondents. The improvement status of individual life course criteria was categorised into \"less/minimal\", \"stable\", or \"upwardly mobile\". Results: The odds of dental fear in the group showing less or minimal upward social mobility was two times that of the stable group [p = 0.022; 95% confidence interval (C.I): 1.104-3.598], whereas the odds of dental fear in the group showing more or good upward social mobility were 4.5 times that of the stable group [p = 0.001; 95% C.I: 1.928-10.515] when adjusted for covariates, that is, participant age, gender, and education and past history of dental avoidance. Conclusion: Social mobility was found to be a risk indicator for dental fear. Dental services may have been affected even with increased standards of living because of psychological factors such as dental fear.

Therapy-related myeloid neoplasms (T-MN) are poorly characterized secondary hematological malignancies following chemotherapy/radiotherapy exposure. We compared the clinical and mutational characteristics of T-MN ( n  = 129) and primary myelodysplastic syndrome (P-MDS, n  = 108) patients. Although the somatic mutation frequency was similar between T-MN and P-MDS patients (93% in both groups), the pattern was distinct. TP53 mutations were more frequent in T-MN (29.5 vs. 7%), while spliceosomal complex mutations were more common in P-MDS (56.5 vs. 25.6%). In contrast to P-MDS, the ring sideroblasts (RS) phenotype was not associated with better survival in T-MN, most probably due to genetic association with TP53 mutations. SF3B1 was mutated in 96% of P-MDS with ≥15% RS, but in only 32% T-MN. TP53 mutations were detected in 92% T-MN with ≥15% RS and SF3B1 wild-type cases. Interestingly, T-MN and P-MDS patients with “Very low” or “Low” Revised International Prognostic Scoring System (IPSS-R) showed similar biological and clinical characteristics. In a Cox regression analysis, TP53 mutation was a poor prognostic factor in T-MN, independent of IPSS-R cytogenetics, disease-modifying therapy, and NRAS mutation. Our data have direct implications for T-MN management and provide evidence that, in addition to conventional disease parameters, mutational analysis should be incorporated in T-MN risk stratification.

The incorporation of artificial intelligence (AI) into the healthcare system has been revolutionized, promising key advancements in diagnosis, treatment, patient care, administrative tasks, and operational efficiency. Using an in-depth analysis of the extensive amount of research on artificial intelligence and how it could help the medical industry, this study identified eleven barriers and challenges. Interpretive structural modeling (ISM) was used as a methodological approach to determine the relationship between the difficulties extracted and their dependency and driving powers. It resulted in a five-tiered model, with the introduction of innovative and new-generation tools topping the chart as the most dependent challenge. Similarly, Insufficient Data, Data Acquisition, Data Misuse, and Missing Compassion were the key drivers. Therefore, during the implementation of artificial intelligence in medicine, these challenges should be considered. Although artificial intelligence (AI) possesses the groundbreaking power to enhance patient care and operational efficiency in the healthcare sector, there are several key problems that must be addressed for implementation to be fruitful. The order of these challenges was ascertained through interpretive structural modeling, underlining the significance of innovation and data-related issues. Health systems can optimize AI’s benefits and enhance diagnosis, patient care, and overall hospital management by aggressively eliminating its deterrents.

The majority of studies assessing the contribution of pathogenic germline variants (PGVs) to cancer predisposition have focused on patients with single cancers. We analyzed 45 known cancer predisposition genes (CPGs) in germline samples of 202 patients with hematological malignancies (HMs) plus one or more other independent cancer managed at major tertiary medical centers on two different continents. This included 120 patients with therapy-related myeloid neoplasms (t-MNs), where the HM occurred after cytotoxic treatment for a first malignancy, and 82 patients with multiple cancers in which the HM was not preceded by cytotoxic therapy (MC-HM). Using American College of Medical Genetics/Association for Molecular Pathology variant classification guidelines, 13% of patients had PGVs, most frequently identified in CHEK2 (17% of PGVs), BRCA1 (13%), DDX41 (13%), and TP53 (7%). The frequency of PGVs in MC-HM was higher than in t-MN, although not statistically significant (18 vs. 9%; p  = 0.085). The frequency of PGVs in lymphoid and myeloid HM patients was similar (19 vs. 17.5%; p  > 0.9). Critically, patients with PGVs in BRCA1 , BRCA2 or TP53 did not satisfy current clinical phenotypic criteria for germline testing. Our data suggest that a personal history of multiple cancers, one being a HM, should trigger screening for PGVs.

The Greater Palatine Foramen (GPF), is a vital anatomical landmark for palatal nerve blocks. Hence imaging of this structure to understand its anatomy is important. Our study aimed to explore the radiomorphometric parameters of the greater palatine canal and pterygopalatine fossa using CBCT images in different age groups and gender. 100 CBCT images showing both right and left maxillary sinus region were analysed for length of the greater palatine canal, the upper and lower opening diameters, and the intra-canal curvature. The recorded values were statistically analysed. The right greater palatine canal length was significantly shorter in individuals >25 years (Mean = 31.72 mm, SD = 4.30 mm, p-value = 0.021). The left upper opening diameter increased significantly with age (Mean = 5.90 mm, SD = 1.47 mm, p-value = 0.006). Males exhibited longer canals (Avg. length mean = 33.23 mm, SD = 4.19 mm, p-value = 0.095). And larger lower opening diameters (Avg. mean = 5.69 mm, SD = 1.18 mm, p-value = 0.073) than females. Canal curvature was predominantly curved across both the age groups, but age group 18-25 years showed a significantly higher prevalence of curved canals on both sides. The present study showed significant variations in the morphology of the greater palatine foramen and canal curvature with respect to age and sex. Variations in GPC length, diameter, and curvature can influence the success of palatal nerve blocks, that reduce the risk of injury to the greater palatine nerve. Recognizing these differences through preoperative CBCT enables accurate anesthesia delivery, safer flap design, and precise osteotomy planning.

Thyroid hormones have a catabolic effect on bone mineral homeostasis. Hypothyroid patients have shown changes in bone mineral density with increased risk for osteoporosis and bone fractures. Radiomorphometric parameters on panoramic images are good indicators of bone mineral density. The aim of the study was to compare the radiomorphometric parameters in dental panoramic images of patients diagnosed with hypothyroidism with age- and gender-matched control populations. Panoramic radiographs of 47 patients diagnosed with hypothyroidism were measured for radio morphometric indices like mental index (MI), The inferior panoramic mandibular index (PMI), antegonial index (AGI), gonial Index (GI) and mandibular cortical Index (MCI). The measurements were compared with age and gender matched 50 healthy controls. The mean values of MI (3.11), PMI (0.28), and GI (1.38) were lower in hypothyroidism than in 50 healthy controls which was 3.17, 0.30 and 1.33, respectively. However, only AGI (3.14) showed statistically significant differences (p = 0.03). This study showed radiomorphometric parameters like MI, PMI, GI and AGI are valuable indicators of bone changes in mandible of patients with systemic diseases like hypothyroidism. Although statistically significant difference was seen only in AGI compared to healthy controls. Further studies with larger samples can provide substantial data. Applying newer technologies like machine learning can also help us determine whether mandibular morphometric parameters can predict changes in bone mineral density in hypothyroid cases.

The study was designed to characterize the surface, core promoter, precore/core region sequences for the presence of mutations in hepatitis B virus (HBV) associated with different liver diseases. 567 HBV associated patients with different liver diseases were enrolled in this study. All samples were analyzed for HBV surface, core promoter, precore/core region mutations and genotypes using PCR and direct sequencing. HBV genotype D (72.8%) was the predominant type followed by genotype A (27.2%). The serum viral load of HBV was highest in HBsAg carriers group and lowest in patients with hepatocellular carcinoma. 17.9% patients with cirrhosis and 24.6% hepatocellular carcinoma cases were ADV-resistant with rtA181T/V mutations in the S-gene. A1896T was found more frequently in fulminant hepatic failure compared to acute viral hepatitis patients (p = 0.038). T1753V mutation was significantly higher in patients with cirrhosis of liver (34.6%) than in chronic hepatitis (18.9%) and hepatocellular carcinoma patients (21.2%; p = 0.001). T1762/A1764 mutation was observed in all the groups. C1914G core gene mutation was associated with the hepatocellular carcinoma (32.2%) compared to other groups. HBV genotype D predominated in comparison to genotype A. An increased frequency of precore mutation and BCP double mutations amongst the population studied was also observed. Mutations such as T1762/A1764, T1753V and C1914G were usually associated with advanced forms of liver disease and had an increased risk of HCC. The nucleotide variability in the basal core promoter and precore regions possibly plays a role in the progression of HBV disease. Prospective studies on the sequence variations of the preC/C region of the HBV genome and the molecular mechanisms in relation to progression of liver disease would aid in better understanding of the biological significance of HBV strains in India.