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BACKGROUND: Various studies have been conducted to analyze data via bibliometric analysis in different dentistry, including prosthetic dentistry. However, these studies evaluated the most cited published articles in dentistry. OBJECTIVE: To analyze and evaluate the characteristic development of several mesh keywords in the Journal of Prosthodontics – Implant, Esthetic, and Reconstructive Dentistry between 1992 and 2022. METHODS: The Scopus databases was searched to retrieve the data related to 8 categories, including published articles, most cited documents, authors and organizations, and maximum articles cited during the evaluation period. The data retrieved were exported to a Microsoft Excel sheet and were analyzed using the bibliometrix package. The data were first analyzed for ten years and then for 30 years. The highest of 10 were reported for each category, and co-authorship, reoccurrence, and linked data were also reported. RESULTS: 2603 published documents were recorded from the Scopus databases. Articles comprised 87.9% of the total published work, followed by review articles at 5.46%. The most productive decade was between 2013 and 2022. 3793 terms were used during the evaluation period, with the maximum number in 2003–2012 (2481). A total of 5392 keywords were used during 1992–2022, with the highest number (3232) from 2013 to 2022. A total of 6108 authors were acknowledged, with the maximum number (3964) from 2013 to 2022 and the fewest (767) from 1992 to 2002. Authors from different countries increased from 17 countries in 1992–2002 to 52 countries in 2013–2022 (total = 63 countries). Similarly, the number of organizations increased from 312 organizations in 1992–2002 to 1315 organizations in 2013–2022 (total = 1976 organizations). CONCLUSION: The current bibliometric analysis delivered a comprehensive overview about more spread research topics and its impactful role in contemporary dentistry, especially prosthetic dentistry.

Correction to Lancet Gastroenterol Hepatol 2022; 7: 627-47. Lancet Gastroenterol Hepatol. 2022 Aug;7(8):704. doi: 10.1016/S2468-1253(22)00210-2. PMID: 35809605. Background: Colorectal cancer is the third leading cause of cancer deaths worldwide. Given the recent increasing trends in colorectal cancer incidence globally, up-to-date information on the colorectal cancer burden could guide screening, early detection, and treatment strategies, and help effectively allocate resources. We examined the temporal patterns of the global, regional, and national burden of colorectal cancer and its risk factors in 204 countries and territories across the past three decades. Methods: Estimates of incidence, mortality, and disability-adjusted life years (DALYs) for colorectal cancer were generated as a part of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019 by age, sex, and geographical location for the period 1990-2019. Mortality estimates were produced using the cause of death ensemble model. We also calculated DALYs attributable to risk factors that had evidence of causation with colorectal cancer. Findings: Globally, between 1990 and 2019, colorectal cancer incident cases more than doubled, from 842 098 (95% uncertainty interval [UI] 810 408-868 574) to 2·17 million (2·00-2·34), and deaths increased from 518 126 (493 682-537 877) to 1·09 million (1·02-1·15). The global age-standardised incidence rate increased from 22·2 (95% UI 21·3-23·0) per 100 000 to 26·7 (24·6-28·9) per 100 000, whereas the age-standardised mortality rate decreased from 14·3 (13·5-14·9) per 100 000 to 13·7 (12·6-14·5) per 100 000 and the age-standardised DALY rate decreased from 308·5 (294·7-320·7) per 100 000 to 295·5 (275·2-313·0) per 100 000 from 1990 through 2019. Taiwan (province of China; 62·0 [48·9-80·0] per 100 000), Monaco (60·7 [48·5-73·6] per 100 000), and Andorra (56·6 [42·8-71·9] per 100 000) had the highest age-standardised incidence rates, while Greenland (31·4 [26·0-37·1] per 100 000), Brunei (30·3 [26·6-34·1] per 100 000), and Hungary (28·6 [23·6-34·0] per 100 000) had the highest age-standardised mortality rates. From 1990 through 2019, a substantial rise in incidence rates was observed in younger adults (age

This research paper explores the role of women in the sports industry, with a focus on their experiences in leadership positions. The paper begins by examining the historical context of women's participation in sports, and how this has evolved over time. It then discusses the current state of women's representation in the industry, including the challenges they face in breaking through the glass ceiling. The paper also looks at the strategies and initiatives that have been put in place to promote gender diversity in sports leadership and evaluates their effectiveness. Finally, the paper concludes by offering recommendations for further research and action that can be taken to ensure greater gender equity in the sports industry.

Suppliers and sellers play a crucial role in the ecommerce ecosystem. Sellers and ecommerce firms use social media to increase user engagement, visibility, and sales. Seller ratings are as important as the product ratings on ecommerce platforms to drive buying decisions. Based on sellers' actions on social media, this study examines seller turnover and disengagement on e-commerce platforms. The study has been supported by the justice theory. Seller reviews and ratings from e-commerce platforms and conversations from social media platforms have been gathered. Using natural language processing, machine learning, partial least squares (PLS) path analysis, and statistical inferences, objectives of the study are met. The study offers recommendations for both practitioners and researchers. The sellers must focus more on interaction and communication than marketing. Through a longitudinal analysis, the study also establishes that ecommerce organizations can use seller social media performance as a predictor of future seller churn and disengagement so they can take the necessary remedial action.

The purpose of this study is to investigate the impact of environmental innovation which is product innovation (PDI) and process innovation (PCI) on firm’s financial performance (FFP). And also, to investigate mediating role of the environment management accounting (EMA) against innovation and FFP. Data were collected from 98 respondents, worked in management positions in Indonesia’s manufacturing sectors. The study uses PLS-SEM (partial least square based structural equation modeling) software for the data analysis. The results showed that PDI has positive and significant impacts on FFP. But PCI has not significant impacts on FFP. Furthermore, PDI and PCI have significant impacts on EMA. This study also indicated that EMA mediate the relationship between innovation and FFP in the manufacturing sector of Indonesia. This study suggests the managers of the manufacturing companies or similar sectors to introduce innovations in their products and processes for developing a better EMA system. The current study also tends to assist policymakers in developing appropriate policies for the manufacturing sector of Indonesia by realizing the importance of environmental innovation, EMA, so that their environmental and economic impacts can be managed and regulated.

Introduction: Determinants of health are divided into four types, such as “Biological-Psychological-Environmental-Social Determinants”. The social determinants of health include gender disparities, economic status, ethnicity, race, geographic isolation, or having a specific health condition. Moreover, the social determinants are interdependent and interrelated with one another. There can also be a primary determinant that affects the other determinants. For example, educational level of the patients is associated with knowledge and awareness of eye care and its conditions. However, education might have a different effect than income in should be access of eye care when needed. Methodology: The study is mainly dependent on secondary data analysis. Results: The primary objective of the study is to illustrate the sociological aspects of visual impairment-related inequities and to identify the social determinants of visual impairments and disparities in India. Another aim of the paper is to present a deeper understanding of how inequities impact the incidence of visual impairment and blindness based on the social determinants of health. The present study adopts the ecological and Commission on Social Determinants of Health (CSDH) framework 2008. We reaffirm the fact that inequities negatively affect the visual impairment and blindness conditions. The national health policies should take into account the social determinants of visual impairment in their policies relating to comprehensive eye care. Social and economic factors are connected with health and welfare; those socio-economic inequalities contribute to health inequalities. For reducing the health inequalities around the world, we need effective policy implementation and proper fund pools. Furthermore, committed action on societal determinants of health, sufficient human resources are also necessary to control the health disabilities, include visual impairment.

Individual elements within a superenhancer can act in a cooperative or temporal manner, but the underlying mechanisms remain obscure. We recently identified anIrf8superenhancer, within which different elements act at distinct stages of type 1 classical dendritic cell (cDC1) development. The +41-kbIrf8enhancer is required for pre-cDC1 specification, while the +32-kbIrf8enhancer acts to support subsequent cDC1 maturation. Here, we found that compound heterozygous Δ32/Δ41 mice, lacking the +32- and +41-kb enhancers on different chromosomes, show normal pre-cDC1 specification but, surprisingly, completely lack mature cDC1 development, suggestingcisdependence of the +32-kb enhancer on the +41-kb enhancer. Transcription of the +32-kbIrf8enhancer-associated long noncoding RNA (lncRNA) Gm39266 is also dependent on the +41-kb enhancer. However, cDC1 development in mice remained intact when Gm39266 transcripts were eliminated by CRISPR/Cas9-mediated deletion of lncRNA promoters and when transcription across the +32-kb enhancer was blocked by premature polyadenylation. We showed that chromatin accessibility and BATF3 binding at the +32-kb enhancer were dependent on a functional +41-kb enhancer located incis. Thus, the +41-kbIrf8enhancer controls the subsequent activation of the +32-kbIrf8enhancer in a manner that is independent of associated lncRNA transcription.

This study aimed to investigate four dental adhesive cements and develop a new method for constructing a bi-layered bone holder for implant testing. HahnTM Tapered Titanium Implants (Glidewell Laboratories) were embedded in mono- and bi-layered holders, and the implant components were assembled. First molar zirconia crowns and crowns for the tensile bond strength test were milled and sintered. Three self-adhesive resin cements (SARC) and one resin-modified glass ionomer (RMGI, Glidewell Laboratories) cement were used to cement the crowns on the abutment. Tensile bond strength, compressive load, and oblique load tests were performed on the implants. The Glidewell Experimental SARC (GES, Glidewell Laboratories) and RMGI cements had the highest tensile bond strength after thermocycling. The implant assemblies with these two cements had the highest mean compressive strength after thermocycling. Under oblique load, the implants with Denali (Glidewell Laboratories) and GES had the highest strength before thermocycling. However, after thermocycling, Dencem (Dentex) and RMGI had the highest strength under an oblique load. The GES cement and RMGI cement had a better overall performance with zirconia crowns and titanium abutments. In addition, a novel technique for constructing an artificial, bi-layered bone holder was successfully developed to mimic the natural structure of the jawbone.

The solid-state reaction technique is used to prepare samples of 0.3BiFeO3–0.7PbZrO3 and 0.5BiFeO3–0.5PbZrO3. Structural parameters, including percent crystallinity, dislocation density, microstrain and average size of crystallites, are calculated using X-ray diffraction data at room temperature. The scanning electron microscopy micrographs reveal the spherical, densely packed nature of the samples with low porosity. The dielectric constant and dielectric loss increase with the rising content of bismuth ferrite (BiFeO3) in the materials. The performance of the materials as a negative-temperature-coefficient (NTC) thermistor in the temperature range 300–450°C is discussed. The values of the thermistor constant (i.e. in the range 3911–6247 K) and the range of the sensitivity index (−1 to −9%) confirm the potential use of the samples as NTC thermistors. The frequency-dependent alternating current (AC) conductivity satisfies the universal Jonscher power law. The high density of states is determined from the frequency- and temperature-dependent AC conductivity of the materials.

The background to the study: Allelopathy can be distinguished from other plant interference strategies because the donor species produces inhibitory compounds into the environment to cause harm. This work aimed to evaluate the allelopathic impact of aqueous leachate of Eucalyptus globulus leaf litter on seed germination, biochemical, and growth parameters of finger millet (Eleusine coracana) seedlings. Methods: This experiment was conducted using aqueous leaf litter leachate at a concentration of 100%, 80%, 60%, 40%, and 20% using water as a control. Results: The experiment showed that all the test concentrations of leachate had a deleterious effect on seed germination, seedling growth-like length, fresh and dry weight, and biochemical parameters such as total chlorophyll and total carbohydrate of the test crop, Eleusine coracana seedlings. Further, it was also observed that the inhibitory effects were gradually increased with a rise in the leaf leachate concentration. Conclusion: It is recommended that crops not be associated with different species of Eucalyptus due to the allelopathic influence on germination and early vegetative developmental stages of crops.

Moringa leaf biochar-based adsorption of fluoride in contaminated drinking water.

An attempt to understand the perception of flood impacts through a gender lens was executed in 2022 in the purposively selected Darbangha district of Bihar as it tops the list of the districts most severely affected by flood in the state. Data from 120 farmers were collected through a focused group discussion and an interview schedule developed specifically for the study. The findings revealed that the maximum percentage of farmers had a medium perception regarding the impact of floods. Variations were seen in the perception of the socio-economic and psychological impact of flood with women perceiving slightly higher than men whereas the opposite was seen for the perception of the environmental impact of the flood where men perceived slightly higher than women. Factors like age, household headship, social participation, decision-making, education, and family size significantly and positively affected the perception women and men had on the impact of the flood. The findings provide an in-depth understanding of the perception of the impact of floods by men and women farmers in the study area which would help the extension agencies and policymakers to plan and design locale-specific preparedness.

Applications hosted in commercial clouds are typically multi-tier and comprise multiple tightly coupled virtual machines (VMs). Service providers (SPs) cater to the users using VM instances with different configurations and pricing depending on the location of the data center (DC) hosting the VMs. However, selecting VMs to host multi-tier applications is challenging due to the trade-off between cost and quality of service (QoS) depending on the placement of VMs. This paper proposes a multi-cloud broker model called CoMCLOUD to select a sub-optimal VM coalition for multi-tier applications from an SP with minimum coalition pricing and maximum QoS. To strike a trade-off between the cost and QoS, we use an ant-colony-based optimization technique. The overall service selection game is modeled as a first-price sealed-bid auction aimed at maximizing the overall revenue of SPs. Further, as the hosted VMs often face demand spikes, we present a parallel migration strategy to migrate VMs with minimum disruption time. Detailed experiments show that our approach can improve the federation profit up to 23% at the expense of increased latency of approximately 15%, compared to the baselines.

Water scarcity is a major issue that arises in current world. So there is an alarming condition trend towards the Asia's drinking water crisis. Thus this issue could quickly be reached to a global crisis. It is therefore extremely important for humans to maintain a specific level of water in worldwide. In many houses unnecessary water wastage is caused by overflow in water tanks. The proposed system utilizes an indicator for water level detection and a controller for solving this particular issue. Different circuits installed in the system for delivering messages as the increment and decrement of water level in the tank. Water shortage is one of the major challenges confronting big cities around the World, and pollution was established by utilizing computational models that build a barrier not only to improve financial benefits and conserve electricity but also to benefit the climate and water cycle as one of the key triggers of this work water scarcity is one of the major problems.

The term “replication” refers to the practice of keeping identical copies of data on multiple systems. Any distributed file system must have replication as one of its design requirements (DRS). For storing and processing data, Hadoop DFS is now used by the majority of academia and industry. The Hadoop distributed file system (HDFS) is a system for storage and processing huge amounts of information. In HDFS, inefficient replication is the main issue that contributes to a file system's performance degradation. Because of the system's robustness and dynamic features, the quantity of applications depending on Hadoop is rapidly growing. The HDFS, which is at the heart of Apache Hadoop, uses a static replication strategy to provide computation with reliability, scalability, and high availability. The admittance rate for each file in HDFS, however, is completely special due to the uniqueness of similar functions on various layers. As a result, using the similar replicating method for each file may have negative performance consequences. This paper proposes a method for dynamically replicating information files depending on predictive analysis after carefully considering the drawbacks of HDFS architecture. To address this issue, we propose an proficient data replication method in the Hadoop framework that increases the availability.

This article aims to evaluate the possible antidepressant effect of the Ghrita prepared from the combination of these plants and to provide probable scientific explanations for using medicated Ghrita (ghee) in Ayurvedic system of medicine. Herbs for Ghrita like Marsilea quadrifolia, Lawsonia inermis, Mimosa pudica, Piper betle were collected freshly during the month of June. One part Kalka (herb bolus), 4 parts pure cow ghee, and 16 parts Dravadravya were used to make Ghrita (Swarasa). Anti-depressant potential of the Ghrita was evaluated by forced swimming, tail suspension, locomotor activity, rota-rod test (motor co-ordination), elevated plus maze (EPM) model, and hole board test were used to assess the Ghrita's anti-depressant potential. According to the Irwin schedule, Gritha medication reduces alertness but has no effect on other parameters, but imipramine treatment reduces responsiveness, alertness, grooming, and writing reflexes to some extent. Following 14 days of therapy with medicinal Ghrita, the immobility time in the forced swim test and the tail suspension test were reduced by 29% and 42%, respectively. In the rotarod test, it had no significant effect on muscle gripping ability when compared to control animals, whereas imipramine produced a significant result. It was observed that the medicinal Gritha significantly (p

Intermittent water supply (IWS) is a typical characteristic of cities in developing countries like India. One of the factors responsible for IWS is unaccounted for water (UFW). Factors like increase in population, upward trends in water demand, water scarcity due to climate change, and asymmetric distribution of water resources are also equally important. However, social relations of water are poorly understood and camouflaged under technicalities associated with IWS. Thus, in this paper, we examine IWS in Indian mega cities and secondary cities with an ethno-economic framework by bringing the data together from various administrative sources like government agencies, allude to its parameters from logistical perspectives, e.g. distances, capacities, population strength, etc., and try to position the water issue with challenges associated with caste, class, gender, religion, region, and governance. The ethno-economic perspective is an attempt to not only complement but also supplement the scientific studies from other disciplines by understanding the real nature of demand and supply problems in urban water management. This paper demonstrates IWS as a multi-dimensional problem and stresses the human drivers of intermittency.

Background: This study used an artificial neural network (ANN) and a decision tree to predict maternal outcomes and their major determinants. An artificial neural network (ANN) and a decision tree were used in this study to determine maternal outcomes and their significant determinants. Methods: Data was gathered from 955 pregnant women at a tertiary care hospital in Bhubaneswar, Odisha. A popular machine learning algorithm, artificial neural networks (ANN), was used to predict maternal outcomes and their determinants. Results: in the bivariate analysis, we found gestational age is significantly associated with maternal outcome (p=

Knowledge and awareness about current concept of drug therapy in dentistry is very important for clinicians to deliver a high quality of care to their patients. Most of the patients report to dental setup with the chief complaint of pain and swelling. Efficient utilization of latest regimen of analgesics and antibiotics not only helps in reducing pain and swelling but also build up good trust with the dentist. In the present time numerous newer analgesics like ketorolac and tramadol are available in the market. This review article gives an overview of newer analgesics, antibiotics, local anesthetic agents, and delivery devices which will enable the dentist to provide Painless Dentistry.

This research study describes the text mining adaptation of the business organization. In the present time, text mining helps the business organization to analyze the vast text document and extract valuable data from this text. This study has adopted the secondary qualitative data collection methods and from this secondary data, this study has conducted the thematic analysis to find the authentic result. This text mining process has used several types of tools and technologies that can help to increase the capacity of the organization. The business organization can get several benefits from this text mining process. Keyword : Text mining, Text analytics, automated process

Data visualization is an effective method to enhance the efficiency of the storytelling process through clearly delivering the message to the audience. This research study is based on the role of data visualization in storytelling through curetting data into an easier form. In order to demonstrate the importance of data visualization, the research study has provided a concept about the data visualization and its benefits on the organization. In addition, the research study has critically evaluated the impact of data visualization on the process of storytelling. However, the research has implicated the positivism research philosophy, descriptive research design and deductive research approach to justify the research purpose. On the other hand, the data has been collected through a secondary method of data collection to collect the valuable data regarding the research topic. The research study also provide a sustainable view about the Keyword : Data visualization, Storytelling, information, organization

Odisha is a state in the eastern part of India with a population of 46 million. Annually, a large number of people migrate to financial and industrial centers in other states for their livelihood earning. Bulk of them returned to Odisha during the early stage of national lockdown (March–June 2020) due to the Covid-19 outbreak as their places of work became Covid hotspots while Odisha was much less affected. This triggered the Odisha government to take precautionary measures such as mandatory quarantine of returning migrants, setting up of containment zones, and establishing temporary medical centres (TMC). Moreover, it was necessary for the government to devise a policy that could slow down the spread of Covid-19 in Odisha due to inflow of migrants. Being part of a task-force constituted by government to understand Covid-19 spread dynamics in Odisha, we predicted the number of people who would get infected primarily due to reverse-migration. This helped the government to make timely resource mobilisation. After analyzing reasons behind the rise in infections at various districts with large migrant population, we mapped the prediction problem to Sequential Probability Ratio Test (SPRT) of Abraham Wald. Our predictions were highly accurate when compared with real data that were obtained at a later stage. Two levels of SPRT were carried out over the data provided by the government. Use of SPRT for Covid-19 spread analysis is novel, particularly to predict the number of possible infections much ahead in time due to the sudden inflow of migrants.

Numerous areas of medical services, including as imaging diagnostics, advanced pathology, emergency clinic confirmation prediction, drug plan, grouping of cancer and stromal cells, specialist help, and so forth, have profited from the utilization of deep learning. Cancer prognosis involves predicting the course of the disease, the likelihood that it will spread and recur, and the likelihood that patients will survive. The clinical management of cancer patients will considerably benefit from the precision of cancer prognosis prediction. To better forecast cancer prognosis, modern statistical analysis and Deep learning techniques are being applied, as well as biomedical translational research being improved. In recent years, the processing capacity has significantly increased and the innovation of artificial insight, especially deep learning, has advanced quickly. Cancer is the leading reason for death in people. As a result, cancer detection is essential for early diagnosis and provides the best chance for treating cancer patients in a secure and efficient manner. It is, however, the trickiest way to increase the likelihood of the person surviving. RNA sequencing has significantly advanced in the last few decades and is now a crucial method for transcriptome profiling.

During this pandemic outbreak of COVID-19, the whole world is getting severely affected in respect of population health and economy. This novel virus has brought the whole world including the most developed countries to a standstill in a very short span like never before. The prime reason for this unexpected outburst of COVID-19 is lack of effective medicine and lack of proper understanding of the influencing factors. Here, the authors aim to find the effect of epidemiological factors that influence its spread using a fuzzy approach. For the same, a total of nine factors have been considered which are classified into risk and preventive factors. This fuzzy model supports to understand and evaluate the impact of these factors on the spread of COVID-19. Also, the model establishes a basis for understanding the effect of risk factors on preventive factors and vice versa. It is worth mentioning that this is the first attempt to analyze the effect of clinical and epidemiological factors with respect to COVID-19 using a fuzzy approach.

The theory of Dhatus (Tissues) is a typical element in Ayurvedic medical science. The human body contains eight main substances; known as Dhatus that give support and strength to our body. The human temperament and its behavioural manifestations are proportionally related to these substances and their proper presence is called ‘health’. Charaka, one of the great physicians of Ayurvedic medicine, methodically observed the human behaviours and temperaments. He concluded that besides physiology, human behaviours and temperaments are also motivated by various factors like environment and geography, thus fixing the platform for holistic perspectives.

Background: The management of pediatric forearm fracture has been a dilemma to surgeon. Conservative treatment with cast still is the preferred treatment. Never the less old children and proximal fracture warrants some form of internal fixation. Aims and Objective: The aims of this were to analyze the role of titanium elastic nailing system in fixation of pediatric forearm fractures and its associated complications. Materials and Methods: Over 3 years, 103 patients were enrolled in our institute. After obtaining consent and preanesthetic check-up, patients were scheduled for surgery, where internal fixation was done using titanium elastic nailing system. Patients were followed up every month for 3 months and then every 3 months interval for 8 months. The time to union and functional score were assessed using modified Flynn score. Results: Among the 103 patients, 63 (61.16%) were in the age group of 7–13 years. Mean age was 11.72±3.50 years (range 4–18 years). Seventy-eight (75.72%) patients were male and fall from height was the most common 66 (64%) mode of injury. Radiological union occurred in most 54 (52.42%) of the patients at average 5–7 weeks. As per the modified Flynn criteria, 82 (79.61%) cases had excellent functional outcome, 11 (10.67%) cases good, 4 (4.12%) fair, and 6 (5.82%) had poor outcome. Neuropraxia was seen in 8 (7.76%) cases and rupture of extensor pollicis brevis was seen in 4 (4.12%) patients and treated accordingly. All the patients regained full functional recovery. Conclusion: TENS is an effective, safe, reliable, and easily reproducible technique for the management of pediatric forearm fractures. It has advantage of preserving the fracture hematoma, providing relative stability to ensue early rehabilitation and minimally invasive nature.

Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019.Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively.Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries. Funding: Bill & Melinda Gates Foundation.

Artificial intelligence (AI) is revolutionizing various fields, including business, medicine, education, and the arts. In the medical field, AI has made remarkable progress. AI algorithms designed for medical imaging can analyze images to detect abnormalities, leading to more precise and timely diagnose. In dentistry, it is used in diagnostic imaging, dental analytics, treatment planning, virtual and augmented reality training, natural language processing for medical records, patient experience through chatbots, and oral hygiene with smart devices. In periodontics, AI is being explored for tasks such as diagnosing and predicting periodontally compromised teeth, severity prediction of chronic periodontitis, correlation with systemic health outcomes, and detection of periodontal bone loss in radiographic images.While AI holds great potential, it also poses challenges. 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Artificial intelligence (AI) is revolutionizing various fields, including business, medicine, education, and the arts. In the medical field, AI has made remarkable progress. AI algorithms designed for medical imaging can analyze images to detect abnormalities, leading to more precise and timely diagnose. In dentistry, it is used in diagnostic imaging, dental analytics, treatment planning, virtual and augmented reality training, natural language processing for medical records, patient experience through chatbots, and oral hygiene with smart devices. In periodontics, AI is being explored for tasks such as diagnosing and predicting periodontally compromised teeth, severity prediction of chronic periodontitis, correlation with systemic health outcomes, and detection of periodontal bone loss in radiographic images.While AI holds great potential, it also poses challenges. Privacy, security, transparency, accountability, and the impact on economic inequality and job markets are important considerations. &nbsp

Purpose:DNA methylation is a novel biomarker for Human Papilloma Virus (HPV) infection amongst women to identify those progressing to pre-cancer. This study was done to see the HPV genotype distribution among the different population and find out the association between Global DNA Methylation and HPV infection. Method:300 patients participated in the study. Cervical swab was collected and analysed by Real Time Polymerase Chain reaction (RT-PCR) for HPV Genotyping study. DNA was extracted from venous blood to estimate Global DNA methylation levels. Results:Global DNA methylation levels were significantly lower in women with HPV infection than women without the infection. Global DNA hypomethylation was more predominant in unhealthy cervix group and cancer cervix and it was more prevalent in patients infected with HPV 16, HPV 18 and other high-risk strain. Conclusion:In our study we found that other high-risk genotype of HPV had the highest rate of hypomethylation followed by HPV 18 and HPV 16 in cancer Cervix. Hence froma sample of whole blood of women infected with HPV, the Global DNA hypomethylation can be assessed and used as a predictive marker for progression to Cervical Cancer.

Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2–M checkpoint, interferon-gamma signaling, and immune-checkpoint components. Proteogenomic analyses of somatic copy-number aberrations identified a resistance-associated 19q13.31–33 deletion where LIG1, POLD1, and XRCC1 are located. In orthogonal datasets, LIG1 (DNA ligase I) gene deletion and/or low mRNA expression levels were associated with lack of pathologic complete response, higher chromosomal instability index (CIN), and poor prognosis in TNBC, as well as carboplatin-selective resistance in TNBC preclinical models. Hemizygous loss of LIG1 was also associated with higher CIN and poor prognosis in other cancer types, demonstrating broader clinical implications. Significance: Proteogenomic analysis of triple-negative breast tumors revealed a complex landscape of chemotherapy response associations, including a 19q13.31–33 somatic deletion encoding genes serving lagging-strand DNA synthesis (LIG1, POLD1, and XRCC1), that correlate with lack of pathologic response, carboplatin-selective resistance, and, in pan-cancer studies, poor prognosis and CIN. This article is highlighted in the In This Issue feature, p. 2483

To study the prevalence of Non-Alcoholic Fatty Liver Disease in Coronary Artery Disease patient and the correlation of Coronary Artery Disease severity in patients of Non-Alcoholic Fatty Liver Disease Study included 124 patients of Coronary Artery Disease who underwent detailed clinical and anthropometric examination and routine blood investigations. Ultrasonography of abdomen was done and Non-Alcoholic Fatty Liver Disease grading was done. Coronary angiography was done and angiographic severity was calculated by Gensini score. Non-Alcoholic Fatty Liver Disease was found in 71% of patient. There is a significant difference of Gensini score between patients with and without Non-Alcoholic Fatty Liver Disease. All the stage of Non-Alcoholic Fatty Liver Disease had a significant difference of Gensini score among them with but there was no difference of Gensini score between stage 1 and 2. The presence of Non-Alcoholic Fatty Liver Disease Is associated with a higher Gensini score, however a higher grade of Non-Alcoholic Fatty Liver Disease doesn’t mandate a higher Gensini score.