Research Institute Research Articles

Progress towards universal health coverage and inequalities in infant mortality: an analysis of 4·1 million births from 60 low-income and middle-income countries between 2000 and 2019

Expanding universal health coverage (UHC) might not be inherently beneficial to poorer populations without the explicit targeting and prioritising of low-income populations. This study examines whether the expansion of UHC between 2000 and 2019 is associated with reduced socioeconomic inequalities in infant mortality in low-income and middle-income countries (LMICs). We did a retrospective analysis of birth data compiled from Demographic and Health Surveys (DHSs). We analysed all births between 2000 and 2019 from all DHSs available for this period. The primary outcome was infant mortality, defined as death within 1 year of birth. Logistic regression models with country and year fixed effects assessed associations between country-level progress to UHC (using WHO's UHC service coverage index) and infant mortality (overall and by wealth quintile), adjusting for infant-level, mother-level, and country-level variables. A total of 4 065 868 births to 1 833 011 mothers were analysed from 177 DHSs covering 60 LMICs between 2000 and 2019. A one unit increase in the UHC index was associated with a 1·2% reduction in the risk of infant death (AOR 0·988, 95% CI 0·981-0·995; absolute measure of association, 0·57 deaths per 1000 livebirths). An estimated 15·5 million infant deaths were averted between 2000 and 2019 because of increases in UHC. However, richer wealth quintiles had larger associated reductions in infant mortality from UHC (quintile 5 AOR 0·983, 95% CI 0·973-0·993) than poorer quintiles (quintile 1 0·991, 0·985-0·998). In the early stages of UHC, UHC expansion was generally beneficial to poorer populations (ie, larger reductions in infant mortality for poorer households [infant deaths per 1000 per one unit increase in UHC coverage: quintile 1 0·84 vs quintile 5 0·59]), but became less so as overall coverage increased (quintile 1 0·64 vs quintile 5 0·57). Since UHC expansion in LMICs appears to become less beneficial to poorer populations as coverage increases, UHC policies should be explicitly designed to ensure lower income groups continue to benefit as coverage expands. UK National Institute for Health and Care Research.

Preliminary results of hypofractionated radiotherapy in breast cancer in Chandigarh, India: single-centre, non-inferiority, open-label, randomised, phase 3 trial

Globally, most of the randomised trials with hypofractionation in patients with breast cancer have used 3-dimensional conformal radiotherapy technique (3D-CRT). As facilities for 3D-CRT technique may not be available in low-resource settings, there is a need to see if hypofractionation is feasible and safe with 2-dimensional (2-D) technique. In this study, we compared a 3-week radiation schedule with a 2-week schedule of hypofractionated radiotherapy in patients with breast cancer with 2-D technique. The current study was an open-label, randomised, phase 3 trial. Patients with breast cancer, stage I-III, post mastectomy or after breast conservative surgery who needed adjuvant locoregional radiotherapy were randomised in the Department of Radiotherapy & Oncology, Post Graduate Institute of Medical Education & Research (PGIMER), Chandigarh, India; to 34Gy in 10 fractions over 2 weeks (2-week arm) or 35Gy in 15 fractions over 3 weeks to the chest wall and 40Gy/15#/3wks to breast and supraclavicular fossa (3-week arm). Boost dose when indicated was 8-10Gy/2-4#/2-4 days in both the arms. Patients were planned on a 2-dimensional (2D) simulator with 2 tangential fields to breast/chest wall and incident supraclavicular fossa field. Acute toxicity was assessed using the Radiation Therapy Oncology Group (RTOG) grading scale. Assessments were carried out weekly during radiotherapy and at 4 weeks after treatment by the physician. Cosmetic outcome was assessed using the Harvard/National Surgical Adjuvant Breast and Bowel Project (NSABP)/RTOG scale. The toxicity rates between the two arms were compared using Fisher's exact tests. The trial was approved by institutional ethics committee and registered with ClinicalTrials.gov, number NCT04075058. This study included 1121 eligible patients from June 2015 to December 2020. Median follow-up was 35 months (6-84 months). Mean age was 48 years (24-75 years). The patient characteristics were comparable between the two arms except for more mastectomies in the 3-week arm and more node-positive patients in the 2-week arm. There were more oestrogen receptor-positive tumors in the 3-week arm. Acute skin toxicities were comparable between the two arms. Grade 2 and 3 skin toxicity was 100 (18%) and 82 (15%); and 16 (3%) and 12 (2%) in the 3-week and 2-week arm (p=0.21), respectively. Cosmetic outcome was assessed as Excellent or Good for 89% of patients in the 3-week arm as compared to 94% in the 2-week arm (p=0.004). The two radiation schedules were comparable in terms of acute skin toxicity. The cosmetic outcome was better with the 2-week schedule. The preliminary findings indicate 2-week radiotherapy schedule with 2-D technique was better than the 3-week schedule in patients with breast cancer. However, disease outcomes and late-term toxicities need to be further checked. This study was funded by Science and Engineering Research Board (SERB), India.

Impact of maternal risk factors on ethnic disparities in maternal mortality: a national population-based cohort study

Ethnic disparities in maternal mortality are consistently reported. This study aimed to investigate the contribution of known risk factors including age, socioeconomic status, and medical comorbidities to observed ethnic disparities in the United Kingdom (UK). A cohort of all women who died during or up to six weeks after pregnancy in the UK 2009-2019 were identified through national surveillance. No single denominator population included data on all risk factors, therefore we used logistic regression modelling to compare to 1) routine population birth and demographic data (2015-19) (routine data comparator) and 2) combined control groups of four UK Obstetric Surveillance System studies (UKOSS) control comparator)). There were 801 maternal deaths in the UK between 2009 and 2019 (White: 70%, Asian: 13%, Black: 12%, Chinese/Other: 3%, Mixed: 2%). Using the routine data comparator (n=3,519,931 maternities) to adjust for demographics, including social deprivation, women of Black ethnicity remained at significantly increased risk of maternal death compared with women of white ethnicity (adjusted OR 2.43 (95% Confidence Interval 1.92-3.08)). The risk was greatest in women of Caribbean ethnicity (aOR 3.55 (2.30-5.48)). Among women of White ethnicity, risk of mortality increased as deprivation increased, but women of Black ethnicity had greater risk irrespective of deprivation. Using the UKOSS control comparator (n=2210), after multiple adjustments including smoking, body mass index, and comorbidities, women of Black and Asian ethnicity remained at increased risk (aOR 3.13 (2.21-4.43) and 1.57 (1.16-2.12) respectively). Known risk factors do not fully explain ethnic disparities in maternal mortality. The impact of socioeconomic deprivation appears to differ between ethnic groups. This research is funded by the National Institute for Health and Care Research (NIHR) Policy Research Programme, conducted through the Policy Research Unit in Maternal and Neonatal Health and Care, PR-PRU-127-21202.

The association between disability and all-cause mortality in low-income and middle-income countries: a systematic review and meta-analysis

There are 1·3 billion people with disabilities globally. On average, they have poorer health than their non-disabled peers, but the extent of increased risk of premature mortality is unknown. We aimed to systematically review the association between disability and mortality in low-income and middle-income countries (LMICs). We searched MEDLINE, Global Health, PsycINFO, and EMBASE from Jan 1, 1990 to Nov 14, 2022. Longitudinal epidemiological studies in any language with a comparator group that measured the association between disability and all-cause mortality in people of any age were eligible for inclusion. Two reviewers independently assessed study eligibility, extracted data, and assessed risk of bias. We used a random-effects meta-analysis to calculate the pooled hazard ratio (HR) for all-cause mortality by disability status. We then conducted meta-analyses separately for different impairment and age groups. We identified 6146 unique articles, of which 70 studies (81 cohorts) were included in the systematic review, from 22 countries. There was variability in the methods used to assess and report disability and mortality. The meta-analysis included 54 studies, representing 62 cohorts (comprising 270 571 people with disabilities). Pooled HRs for all-cause mortality were 2·02 (95% CI 1·77-2·30) for people with disabilities versus those without disabilities, with high heterogeneity between studies (τ2=0·23, I2=98%). This association varied by impairment type: from 1·36 (1·17-1·57) for visual impairment to 3·95 (1·60-9·74) for multiple impairments. The association was highest for children younger than 18 years (4·46, [3·01-6·59]) and lower in people aged 15-49 years (2·45 [1·21-4·97]) and people older than 60 years (1·97 [1·65-2·36]). People with disabilities had a two-fold higher mortality rate than people without disabilities in LMICs. Interventions are needed to improve the health of people with disabilities and reduce their higher mortality rate. UK National Institute for Health and Care Research; and UK Foreign, Commonwealth and Development Office.

Survival of adult AML patients treated with chemotherapy in the U.S. population by age, race and ethnicity, sex, calendar-year period, and AML subgroup, 2001–2019

Population-based survival studies of adult acute myeloid leukemia (AML) have not simultaneously evaluated age at diagnosis, race and ethnicity, sex, calendar period or AML subtypes/subgroups among chemotherapy-treated patients. For 28,473 chemotherapy-treated AML patients diagnosed at ages ≥20 years in population-based cancer registry areas of the Surveillance, Epidemiology, and End Results Program (2001-2018, followed through 2019), we evaluated 1-month through 5-year relative survival (RS) and 95% confidence intervals (95% CI) using the actuarial method in the SEER∗Stat Survival Session and overall survival (OS) using multivariable Cox regression to estimate proportional hazard ratios (HR) and 95% CI. RS decreased with increasing age (20-39, 40-59, 60-74, 75-84, ≥85 years) at AML diagnosis. RS declined substantially within the first month and, except for acute promyelocytic leukemia, decreasing patterns continued thereafter for core binding factor AML, AML with antecedent condition/therapy, and all other AML. For all ages, acute promyelocytic leukemia RS stabilized after the first year. For total AML the hazard of death was significantly increased for non-Hispanic (NH)-Black (HR=1.18, 95% CI=1.12-1.24) and NH-Pacific Islander patients (HR=1.31, 95% CI=1.11-1.55) compared with NH-White patients. In contrast, NH-Asian and Hispanic patients had similar OS to NH-White patients across all ages and most AML subgroups. Males had significantly inferior survival to females with some exceptions. Compared to 2001-2006, in 2013-2018 OS improved for all age and AML subgroups. Chemotherapy-treated U.S. adults with AML have notable differences in survival by age, race and ethnicity, sex, calendar-year period, and AML subgroup. Despite survival gains over time, our findings highlight the need for improving early outcomes across all AML subgroups, older ages, and Black and Pacific Islander patients and long-term outcomes among most treated groups. Intramural Research Program of the U.S. National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics, and the U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Office of Surveillance and Epidemiology.

An ecosystem approach to mentoring research faculty in schools of nursing: The pacific northwest interdependence mentoring model

BackgroundMentoring can facilitate faculty career development and retention. Given ongoing challenges in academic nursing (e.g., shrinking number of experienced mentors), it is necessary to revisit and improve upon existing mentoring models and practices to support current and future nurse researchers. PurposeTo describe the development of a new faculty-to-faculty research mentoring model. MethodsConstruction of a model describing mentoring needed by research-focused nurse faculty based on analysis of the literature alongside the authors’ personal experiences. FindingsThe Pacific Northwest Interdependence Mentoring Model (PIMM) describes academic nursing as an ecosystem that fosters caring, trust, solidarity, equity, openness, and interdependent relationships among research faculty, administration, institutions, and funding sources. DiscussionAlthough mentoring environments differ in unique strengths, weaknesses, mission, culture, and values, the PIMM’s approach could be applicable for many schools of nursing and beyond to support the growth of the nursing discipline.

Predicting skin cancer risk from facial images with an explainable artificial intelligence (XAI) based approach: a proof-of-concept study

Efficient identification of individuals at high risk of skin cancer is crucial for implementing personalized screening strategies and subsequent care. While Artificial Intelligence holds promising potential for predictive analysis using image data, its application for skin cancer risk prediction utilizing facial images remains unexplored. We present a neural network-based explainable artificial intelligence (XAI) approach for skin cancer risk prediction based on 2D facial images and compare its efficacy to 18 established skin cancer risk factors using data from the Rotterdam Study. The study employed data from the Rotterdam population-based study in which both skin cancer risk factors and 2D facial images and the occurrence of skin cancer were collected from 2010 to 2018. We conducted a deep-learning survival analysis based on 2D facial images using our developed XAI approach. We subsequently compared these results with survival analysis based on skin cancer risk factors using cox proportional hazard regression. Among the 2810 participants (mean Age=68.5±9.3 years, average Follow-up=5.0 years), 228 participants were diagnosed with skin cancer after photo acquisition. Our XAI approach achieved superior predictive accuracy based on 2D facial images (c-index=0.72, 95% CI: 0.70-0.74), outperforming that of the known risk factors (c-index=0.59, 95% CI 0.57-0.61). This proof-of-concept study underscores the high potential of harnessing facial images and a tailored XAI approach as an easily accessible alternative over known risk factors for identifying individuals at high risk of skin cancer. The Rotterdam Study is funded through unrestricted research grants from Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. G.V. Roshchupkin is supported by the ZonMw Veni grant (Veni, 549 1936320).

An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study

The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64-73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953-0.998) to 0.992 (0.982-1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908-1.000]) surpassed that of two junior pathologists (0.862 [0.746-0.939], P=0.023; 0.879 [0.767-0.950], P=0.041) by 10-12% and showed no difference to that of two senior pathologists (both 0.983 [0.908-1.000], both P>0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P=0.041) to the level of senior pathologists (both P>0.99), and substantially reduced the four pathologists' slide reviewing time (-31%, P<0.0001;-34%, P<0.0001;-29%, P<0.0001; and-27%, P=0.00031). ProCaLNMD demonstrated high diagnostic capabilities for identifying LNM in prostate cancer, reducing the likelihood of missed diagnoses by pathologists and decreasing the slide reviewing time, highlighting its potential for clinical application. National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, the Guangdong Provincial Clinical Research Centre for Urological Diseases, and the Science and Technology Projects in Guangzhou.

Child, maternal, and adult mortality in rural Ethiopia in 2019: a cross-sectional mortality survey using electronic verbal autopsies

Ethiopia, with about 10% of Africa's population, has little direct information on causes of death, particularly in rural areas where 80% of Ethiopians live. In 2019-2020, we conducted electronic verbal autopsies (e-VA) to examine causes of death and quantify cause-specific mortality rates in rural Ethiopia. We examined deaths under 70 years in the three years prior to the survey dates (November 25, 2019-February 29, 2020) among 2% of East Gojjam Zone (Amhara Region) using registered deaths and adding random sampling in this cross-sectional study. Trained surveyors interviewed relatives of the deceased with central dual-physician assignment of causes as the main outcome. We documented details on age, sex and location of death, and derived overall rural death rates using 2007 Census data and the United Nations national estimates for 2019. To these, we applied our sample-weighted causes to derive cause-specific mortality rates. We calculated death risks for the leading causes for major age groups. We studied 3516 deaths: 55% male, 97% rural, and 68% occurring at home. At ages 5 and older, injuries were notable, accounting for over a third of deaths at 5-14 years, half of the deaths at ages 15-29 years, and a quarter of deaths at ages 30-69 years. Neonatal mortality was high, mostly from prematurity/low birthweight and infections. Among children under 5 (excluding neonates), infections caused nearly two-thirds of deaths. Most maternal deaths (84%) arose from direct causes. After injuries, especially suicide, assaults, and road traffic accidents, vascular disease (15%) and cancer (13%) were the leading causes among adults at 30-69 years. HIV/AIDS and tuberculosis deaths were also important causes among adults. Rural Ethiopia has a high burden of avoidable mortality, particularly injury, including suicide, assaults, and road traffic accidents. International Development Research Centre, and the Canadian Institutes of Health Research.

Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging

Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD. 445 cross-sectional participants (aged≥50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants. We found both tau metrics significantly elevated across increasing disease stages (p<0.0001) and as a function of increasing amyloid burden for participants with preclinical (p<0.0001, p=0.0056) and symptomatic (p=0.010, p=0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p=0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (β=0.59), but then tau burden elevated relative to spread (β=0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R=0.83). Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design. This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund.

Sedentary lifestyle, physical activity, and gastrointestinal diseases: evidence from mendelian randomization analysis

The causal associations of physical activity and sedentary behavior with the risk of gastrointestinal disease are unclear. We performed a Mendelian randomization analysis to examine these associations. Genetic instruments associated with leisure screen time (LST, an indicator of a sedentary lifestyle) and moderate-to-vigorous intensity physical activity (MVPA) at the genome-wide significance (P<5×10-8) level were selected from a genome-wide association study. Summary statistics for gastrointestinal diseases were obtained from the UK Biobank study, the FinnGen study, and large consortia. Multivariable MR analyses were conducted for genetically determined LST with adjustment for MVPA and vice versa. We also performed multivariable MR with adjustment for genetically proxied smoking, body mass index (BMI), waist-to-hip ratio, type 2 diabetes, and fasting insulin for both exposures. Genetically proxied longer LST was associated with an increased risk of gastrointestinal reflux, gastric ulcer, duodenal ulcer, chronic gastritis, irritable bowel syndrome, diverticular disease, Crohn's disease, ulcerative colitis, non-alcoholic fatty liver disease, alcoholic liver disease, cholangitis, cholecystitis, cholelithiasis, acute pancreatitis, chronic pancreatitis, and acute appendicitis. Most associations remained after adjustment for genetic liability to MVPA. Genetic liability to MVPA was associated with decreased risk of gastroesophageal reflux, gastric ulcer, chronic gastritis, irritable bowel syndrome, cholecystitis, cholelithiasis, acute and chronic pancreatitis. The associations attenuated albeit directionally remained after adjusting for genetically predicted LST. Multivariable MR analysis found that BMI and type 2 diabetes mediated the associations of LST and MVPA with several gastrointestinal diseases. The study suggests that a sedentary lifestyle may play a causal role in the development of many gastrointestinal diseases. Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), Natural Science Foundation of Hunan Province (2021JJ30999), Swedish Heart-Lung Foundation (Hjärt-Lungfonden, 20210351), Swedish Research Council (Vetenskapsrådet, 2019-00977), Swedish Cancer Society (Cancerfonden), the Wellcome Trust (225790/7/22/Z), United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7) and National Institute for Health Research Cambridge Biomedical Research Centre (NHIR203312).

International EV policies: A comparative review of strategies in the United States and Nigeria for promoting electric vehicles

This paper provides a comprehensive comparative analysis of the strategies employed by the United States and Nigeria in promoting electric vehicles (EVs) within their respective national contexts. As the world shifts towards sustainable energy solutions, EVs have emerged as a pivotal component in reducing greenhouse gas emissions and mitigating climate change. Drawing upon a range of scholarly literature, governmental reports, and policy documents, this study examines the policy frameworks, incentives, and challenges faced by both countries in fostering the adoption of EVs. In the United States, a diverse array of federal, state, and local initiatives have been implemented to incentivize EV adoption, including tax credits, rebates, infrastructure investments, and regulatory mandates. Moreover, collaborations between the government, industry stakeholders, and research institutions have facilitated technological advancements and market growth in the EV sector. However, challenges such as range anxiety, high upfront costs, and inadequate charging infrastructure continue to impede widespread adoption. Conversely, Nigeria, while grappling with its own set of socio-economic and infrastructural challenges, has exhibited a nascent interest in promoting EVs as part of its broader sustainable development agenda. Despite lacking a comprehensive national policy framework, various initiatives such as tax exemptions, import duty waivers, and pilot projects have been introduced to stimulate EV uptake. Moreover, Nigeria's abundant renewable energy resources offer a promising opportunity for leveraging EVs to enhance energy security and reduce dependence on fossil fuels. Nevertheless, significant barriers such as limited infrastructure, affordability constraints, and institutional capacity gaps pose formidable obstacles to scaling up EV adoption in the country. By juxtaposing the experiences of the United States and Nigeria, this study contributes valuable insights into the diverse approaches and lessons learned in crafting effective international EV policies amidst varying socio-economic contexts. Through a nuanced understanding of the policy landscape, policymakers, industry stakeholders, and researchers can identify strategies for overcoming barriers and accelerating the transition towards a sustainable transportation paradigm.

Biography Leticia Myriam Torres Guerra

Born in Monterrey, Nuevo León, in 1955, Dr. Leticia Torres graduated with a degree in Industrial Chemistry from the Autonomous University of Nuevo León and earned her PhD in Advanced Ceramic Materials from the University of Aberdeen, Scotland, in 1985. She holds a certification in Applied Renewable Energies and Energy Efficiency from Harvard University. Throughout her distinguished professional career, she has held key positions such as Deputy Director of Research at the Faculty of Chemical Sciences (1995-2001), Deputy Director of Scientific Development at CONACYT (2011-2013), Head of the Department of Eco-materials and Energy at the Faculty of Civil Engineering UANL (2005-2019), and leader of the Consolidated Academic Body "Development of Environmental Materials" from 2008 to the present. Since December 6, 2019, she has been serving as the General Director of the Center for Research in Advanced Materials (CIMAV).

Thermophilic lipases in industrial applications: Stutzerimonas stutzeri as a Case Study in Nigeria and the US

Thermophilic lipases derived from Stutzerimonas stutzeri have garnered significant attention in recent years due to their robustness and efficiency in various industrial applications. This review delves into the research, development, and application of these enzymes, with a comparative analysis between Nigeria and the United States. In both nations, researchers have explored the enzymatic properties of thermophilic lipases from Stutzerimonas stutzeri, aiming to optimize their performance for diverse industrial processes. The research encompasses studies on enzyme purification, characterization, and genetic engineering to enhance catalytic activity and stability under extreme conditions. Additionally, efforts have been directed towards understanding the enzyme's structure-function relationship to tailor it for specific applications. In Nigeria, the focus on thermophilic lipases from Stutzerimonas stutzeri has been primarily driven by the need for sustainable biotechnological solutions in various industries, including food, pharmaceuticals, and biofuel production. The enzymes' thermostability makes them particularly suitable for high-temperature processes prevalent in Nigeria's tropical climate, offering potential for cost-effective and eco-friendly alternatives to conventional chemical catalysts. In contrast, the United States has witnessed extensive research and development in thermophilic lipases for industrial applications, with a strong emphasis on biocatalysis in the pharmaceutical, detergent, and biofuel sectors. The advanced infrastructure and investment in biotechnology have facilitated the commercialization of Stutzerimonas stutzeri lipases, leading to their integration into various industrial processes to improve efficiency and sustainability. Despite the similarities in research objectives, disparities exist in the technological advancements and industrial utilization of thermophilic lipases from Stutzerimonas stutzeri between Nigeria and the US. While Nigeria faces challenges related to limited resources and infrastructure, the US benefits from well-established research institutions and industrial networks, enabling accelerated innovation and commercialization. Bridging these gaps through international collaborations and knowledge exchange could facilitate the widespread adoption of thermophilic lipases for sustainable industrial development globally.

Paddy Crop Disease Detection Using Machine Learning

Abstract: India has risen as a significant player in earlier years, the world’s second-largest producer of paddy, yielding approximately 497.7 million metric tons annualy. Sustaining vast paddy fields demand ongoing attention and upkeep. It is critical to recognize the symptoms and understand how this can effectively control the disease. Therefore, inspired by this research paper, a solution is suggested to train machine learning for identify diseases in paddy plants. The system utilizes rea;- time datasets sourced from the Agriculture Research Institute of Lonavala, which are freely accessible. This system can be used for identification purposes four major paddy plant diseases -Leaf Blast, Leaf Scald, Neck Blast and False smut. This Proposed system, first images are pre-processed and then the custom Convolution Neural Network is used to arranging the images. This project work discusses the methodology for disease identifying diseased leaves at an early At this stage, the suggested automated system can assist farmers in mitigating further harm to their crops.

National culture, religiosity, and audited financial statements of small-scale MNCs

Purpose The research objective starts from the argument that small-scale multinational corporations’ (SMNCs’) managerial behavior toward auditing decisions is influenced by their personal value, especially when the auditing process is not mandatory. This study aims to examine how national culture-religiosity affects that decision. The authors further examine how foreign-owned MNCs might behave differently from local MNCs, although the host country’s cultural-religiosity value might influence that decision. Design/methodology/approach This study obtains the data from three sources: Hofstede Framework, Pew Research Center and World Bank Enterprise Survey in cross-sectional mode. The final sample consists of 8,590 SMNCs from 45 countries as the observations. This study uses robust regression analysis to test the effects of culture, religiosity and controlling shareholders on the audited financial statements decision. Findings The regression results support the hypothesis, whereas cultural-religiosity values are associated with the audited financial report. The findings confirm stakeholder theory and institutional theory. Originality/value This study fills a gap in the literature by providing empirical evidence on the cultural and religiosity effects on the accounting decision of SMNCs. The results can be used as the foundation for future research related to MNCs’ managerial behavior toward accounting policies, especially with the psychosocial factors.

Identifying carers in general practice (STATUS QUO): a multicentre, cross-sectional study in England

ObjectivesTo determine General Practice (GP) recording of carer status and the number of patients self-identifying as carers, while self-completing an automated check-in screen prior to a GP consultation.DesignA descriptive cross-sectional...

Prevalence and factors associated with uptake of pre-exposure prophylaxis amongst women vulnerable to HIV who received HIV antibodies in Antibody Mediated Prevention HVTN703/HPTN081 trial in Harare, Zimbabwe: a cross-sectional study

IntroductionThere is limited evidence on pre-exposure prophylaxis (PrEP) uptake post-trial participation for women vulnerable to HIV. This study investigates the prevalence and factors associated with PrEP uptake post-participation in an...

Breeding Programs Against Coffee Leaf Rust in Brazil: A Review

Leaf rust caused by Hemileia vastatrix Berk &amp;amp; Br. is the main disease that attack coffee plants all over the world. The disease causes 35-50% of yield loss in average in Brazil. The disease is present in all the countries that cultivate coffee (Coffea arabica L. and C. canephora L.). Resistance of coffee to leaf rust is the main method of disease control. But the great variability of the pathogen makes it very difficult. In the world and in Brazil there are more than 50 and 16 races of the pathogen, respectively. In Brazil there are seven research institutions that have been working with breeding programs against coffee leaf rust. The main source of resistance to coffee leaf rust used by all the research institutions in Brazil came from &amp;lsquo;Centro de Investiga&amp;ccedil;&amp;atilde;o das Ferrugens do Cafeeiro-CIFC&amp;rsquo; in Oeiras, Portugal. They are: H&amp;iacute;brido de Timor (HdT) CIFC 832-1 and HdT CIFC 832 and HdT CIFC 2570. Crosses were made at CIFC with a variety Caturra and Vila Sarchi and sent to Brazil, Colombia and some countries of Central America and Caribean. The countries that received the germplasm of CIFC back crossed them with varieties Catuai and Mundo Novo. Crossing HdT with Caturra originated the group Catimor and HdT with Vila Sarchi the group Sarchimor. Other source of resistance to leaf rust came from Coffea canephora crossed with C. arabica originating the cultivar Icatu. But the great majority of the resistant cultivar came from Catimor and Sarchimor. More than 50 coffee varieties have been launched with resistance to the leaf rust in the last 40 years in Brazil. But only few of them remain with vertical resistance to all the races of H. vastatrix. Horizontal resistance is more common on C. canephora var. conilon and C. canephora var. robusta than in C. arabica. This revision has the purpose to relate to the scientific comunity the breeding programs against coffee leaf rust in Brazil.

Application of AI in Sepsis: Citation Network Analysis and Evidence Synthesis.

Artificial intelligence (AI) has garnered considerable attention in the context of sepsis research, particularly in personalized diagnosis and treatment. Conducting a bibliometric analysis of existing publications can offer a broad overview of the field and identify current research trends and future research directions. The objective of this study is to leverage bibliometric data to provide a comprehensive overview of the application of AI in sepsis. We conducted a search in the Web of Science Core Collection database to identify relevant articles published in English until August 31, 2023. A predefined search strategy was used, evaluating titles, abstracts, and full texts as needed. We used the Bibliometrix and VOSviewer tools to visualize networks showcasing the co-occurrence of authors, research institutions, countries, citations, and keywords. A total of 259 relevant articles published between 2014 and 2023 (until August) were identified. Over the past decade, the annual publication count has consistently risen. Leading journals in this domain include Critical Care Medicine (17/259, 6.6%), Frontiers in Medicine (17/259, 6.6%), and Scientific Reports (11/259, 4.2%). The United States (103/259, 39.8%), China (83/259, 32%), United Kingdom (14/259, 5.4%), and Taiwan (12/259, 4.6%) emerged as the most prolific countries in terms of publications. Notable institutions in this field include the University of California System, Emory University, and Harvard University. The key researchers working in this area include Ritankar Das, Chris Barton, and Rishikesan Kamaleswaran. Although the initial period witnessed a relatively low number of articles focused on AI applications for sepsis, there has been a significant surge in research within this area in recent years (2014-2023). This comprehensive analysis provides valuable insights into AI-related research conducted in the field of sepsis, aiding health care policy makers and researchers in understanding the potential of AI and formulating effective research plans. Such analysis serves as a valuable resource for determining the advantages, sustainability, scope, and potential impact of AI models in sepsis.