Early Detection Research Articles

Detection of Leaf Diseases in Banana Crops Using Deep Learning Techniques

Leaf diseases, such as Black Sigatoka and Cordana, represent a growing threat to banana crops in Ecuador. These diseases spread rapidly, impacting both leaf and fruit quality. Early detection is crucial for effective control measures. Recently, deep learning has proven to be a powerful tool in agriculture, enabling more accurate analysis and identification of crop diseases. This study applied the CRISP-DM methodology, consisting of six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. A dataset of 900 banana leaf images was collected—300 of Black Sigatoka, 300 of Cordana, and 300 of healthy leaves. Three pre-trained models (EfficientNetB0, ResNet50, and VGG19) were trained on this dataset. To improve performance, data augmentation techniques were applied using TensorFlow Keras’s ImageDataGenerator class, expanding the dataset to 9000 images. Due to the high computational demands of ResNet50 and VGG19, training was performed with EfficientNetB0. The models—EfficientNetB0, ResNet50, and VGG19—demonstrated the ability to identify leaf diseases in bananas, with accuracies of 88.33%, 88.90%, and 87.22%, respectively. The data augmentation increased the performance of EfficientNetB0 to 87.83%, but did not significantly improve its accuracy. These findings highlight the value of deep learning techniques for early disease detection in banana crops, enhancing diagnostic accuracy and efficiency.

Human Papillomavirus: A Narrative Review for Dental Providers in Prevention and Care

(1) Introduction: Human papillomavirus (HPV) is a significant public health concern associated with various cancers, including a rising incidence of oropharyngeal cancer (OPC). Despite the availability of effective vaccines targeting high-risk HPV types, vaccination rates remain suboptimal. Dental professionals are uniquely positioned to contribute to HPV prevention through education, vaccination advocacy, and early detection. (2) Methods: This narrative review synthesized the literature from 2006 to 2024 on HPV epidemiology, pathophysiology, vaccine efficacy, and the role of dental providers in HPV prevention. Sources included peer-reviewed articles listed in Pubmed and Google Scholar, including observational studies and review articles, guidelines, clinical trials, and governmental data. Key barriers to HPV-related care in dental practice and strategies for overcoming them were analyzed. (3) Results: The review underscores the critical role of dentists in HPV-related disease prevention, highlighting their ability to detect HPV-related lesions, promote vaccine uptake, and address patient concerns. Barriers such as limited knowledge, discomfort discussing HPV, and misinformation were identified. Strategies like incorporating HPV education into dental training, utilizing emerging diagnostic tools, and adopting effective communication approaches can enhance the role of dental professionals in reducing HPV-associated cancer risks. (4) Conclusion: By integrating HPV education, vaccination advocacy, and early detection into routine dental care, dental professionals can play a transformative role in public health. A dental provider’s endorsement can increase HPV vaccine uptake and help prevent oral cancer. These efforts align with broader health promotion goals, offering a significant opportunity to reduce the burden of HPV-associated cancers and improve long-term patient outcomes.

Does platelet to lymphocyte ratio predict the ultrasound stage in hepatosteatosis?

Background The prevalence of hepatosteatosis, or fatty liver disease, has been increasing globally in recent years largely due to increasing rates of obesity, diabetes, and metabolic syndrome. Purpose To examine the platelet to lymphocyte ratio (PLR) reflection on the hepatosteatosis stage. Material and Methods We evaluated healthy individuals who applied to the check-up department in our hospital. The platelet and lymphocyte counts from blood tests, along with upper abdominal ultrasound results obtained as part of routine diagnostic check-ups, results recorded retrospectively, between November 2022 and April 2024. Results A total 748 participants were included in the study. All participants were divided in three groups according to hepatosteatosis stages.The PLR levels were highest in the stage 1 hepatosteatosis group. There was statistical significance in PLR levels between stage 1 and 3 hepatosteatosis ( P = 0003). In addition, PLR levels were higher in stage 2 than in stage 3, which was also statistically significant ( P = 0037). Conclusion These results could help in early detection and monitoring of disease progression in patients with hepatoteatosis. Lower PLR values (<115.26) in advanced stages might prompt closer monitoring or more aggressive interventions to prevent progression to fibrosis.

Association between the coexistence of chronic kidney disease and sarcopenia with cardiovascular disease and mortality

Abstract Background Chronic kidney disease (CKD) and sarcopenia are independently associated with adverse cardiovascular and mortality outcomes. However, the combined impact of CKD and sarcopenia remains poorly understood. To evaluate the combined effects of CKD and sarcopenia on cardiovascular disease (CVD) and mortality risks in a large population-based cohort. Methods We analyzed data from 477,380 participants in the UK Biobank, categorized into four groups based on the presence or absence of CKD and sarcopenia: Non-CKD Non-Sarcopenia, Non-CKD Sarcopenia, CKD Non-Sarcopenia, and CKD Sarcopenia. Cox proportional hazards models estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for CVD and mortality outcomes. Kaplan-Meier survival analyses compared event-free survival across the groups. Results Participants with both CKD and sarcopenia exhibited the highest risks across all outcomes compared to those without either condition. For stroke, the adjusted HR was 2.17 (95% CI: 1.65–2.86), significantly higher than CKD alone (HR: 1.69, 95% CI: 1.47–1.94) or sarcopenia alone (HR: 1.28, 95% CI: 1.03–1.59). Similar trends were observed for coronary artery disease (CAD) and heart failure (HF), with HRs of 1.53 (95% CI: 1.38–1.69) and 2.22 (95% CI: 1.99–2.47), respectively, in the CKD-sarcopenia group. The coexistence of CKD and sarcopenia was also associated with significantly elevated all-cause mortality (HR: 2.59, 95% CI: 2.17–3.09) and cardiovascular-specific mortality (HR: 4.08, 95% CI: 2.95–5.66). Conclusion The coexistence of CKD and sarcopenia significantly amplifies the risks of CVD and mortality, highlighting the need for integrated management strategies to address this high-risk population. Early detection and tailored interventions targeting these dual risk factors may mitigate their compounded burden and improve clinical outcomes.

Komparasi Metode SVM dan Adaboost untuk Klasifikasi Kanker Payudara

One of the most prevalent malignancies in women and a major global cause of death is breast cancer. To determine whether a cancer is benign or malignant, early detection is essential. The usefulness of the Support Vector Machine (SVM) and Adaptive Boosting (Adaboost) algorithms for breast cancer classification using mammography data is compared in this study. 569 records make up the dataset, which was sourced from the Kaggle Repository and is split into 75% training data and 25% testing data. Preprocessing steps include feature and target variable creation, categorical-to-numerical conversion, data splitting, and normalization. SVM achieved an accuracy of 97%, with a precision of 98%, recall of 94%, and F1 score of 96%. Adaboost, on the other hand, achieved an accuracy of 96%, precision of 98%, recall of 92%, and F1 score of 95%. The results reveal that both algorithms are highly effective for breast cancer detection, with SVM marginally exceeding Adaboost in total performance. These findings emphasize the promise of machine learning techniques in facilitating early cancer diagnosis, hence boosting survival rates. It is advised that future research employ a wider range of datasets and investigate different classification techniques in order to improve accuracy and dependability even more.

LSTM-MGTO: a novel early breast cancer detection using long short term memory based modified gorilla troops optimization algorithm

LSTM-MGTO: a novel early breast cancer detection using long short term memory based modified gorilla troops optimization algorithm

Pediatric Criteria on Children’s Mental Health. Early Medical Identificationof Anxiety and Depression Disorders In Children In Brazil

Child mental health is recognized as essential for integral development, influencing children’s emotional, academic and social well-being. The increase in the prevalence of disorders such as anxiety and depression in childhood has stimulated research into specific pediatric criteria for early diagnosis, allowing for assertive interventions that can modify the clinical course of these conditions. Thus, standardized and culturally adapted instruments prove fundamental for the detection and management of symptoms, considering the particularities of children’s emotional and behavioural development. Objectives: The purpose of the study was to carry out a systematic literature review to identify, analyze and synthesize the pediatric criteria applied to child mental health in Brazil, with an emphasis on the early identification of anxiety and depression disorders. The specific objectives were: to map the scientific literature; to evaluate the effectiveness of the screening instruments; to identify gaps and challenges in the application of the criteria in the Brazilian context; to propose guidelines for clinical practice and public policies; and to promote the integration of interdisciplinary approaches. Methodology: The systematic review followed the PRISMA guidelines, searching databases such as PubMed, Scopus, Web of Science, SciELO and LILACS. Controlled terms were used (e.g. “infant mental health”, “pediatric criteria”, “anxiety disorders”, “depression”, “Brazil”). The selection included original studies that addressed the early identification of disorders in children using pediatric criteria or instruments. Methodological quality was assessed using standardized tools (QUADAS-2) and the data extracted systematically, with narrative synthesis of the findings. Results: The studies analyzed show that early detection of anxiety and depression disorders can significantly improve prognosis, allowing for personalized interventions and a reduction in long-term complications. However, Brazil’s cultural diversity and socioeconomic disparities pose challenges to the standardization of diagnostic criteria, reflecting a variability in prevalence rates (10-25% for depression and 20-30% for anxiety). The integration of standardized protocols in primary care and school environments, together with the continuous training of professionals, is essential to improve the identification and management of these disorders. Conclusion: In summary, the systematic review confirms that the implementation of specific pediatric criteria and culturally adapted instruments is crucial for the early detection of mental disorders in childhood. The adoption of interdisciplinary approaches and the formulation of robust public policies are indispensable measures to mitigate the impacts of these disorders, promoting more effective interventions and contributing to the improvement of child mental health in Brazil.

Ventriculo-arterial coupling in pulmonary regurgitation following transannular patch repair of pulmonary stenosis

Pulmonary regurgitation is a common consequence following the repair of tetralogy of Fallot and can lead to heart failure. Early detection of right ventricular dysfunction remains challenging, and current clinical markers have limited predictive value to identify which patients are at risk for heart failure and require interventions. This study aimed to investigate the potential of ventriculo-arterial coupling as a marker of early right ventricular dysfunction in a porcine model of chronic pulmonary regurgitation following transannular patch repair of neonatal pulmonary stenosis. Neonatal swine were subjected to pulmonary artery banding for 1 month to induce RV pressure overload, followed by transannular patch repair (rTAP, n=10) to create chronic pulmonary regurgitation, and were compared to Sham animals (n=6). Longitudinal hemodynamic assessments, including pressure-volume analysis and cardiac magnetic resonance imaging, were performed. VAC was defined as the ratio of end-systolic elastance to effective arterial elastance. Over the follow-up period of 4 months, VAC was preserved in the rTAP group. Effective arterial elastance was significantly lower in rTAP animals (P=0.001), while end-systolic elastance remained unchanged. Lower end-diastolic pulmonary artery pressures and increased early systolic ejection were observed in rTAP, correlating with higher VAC. Ventriculo-arterial coupling remains preserved in chronic pulmonary regurgitation due to decreased afterload, making it unsuitable as an early marker for right ventricular dysfunction. Low afterload, a consequence of diastolic emptying of the pulmonary artery into the right ventricle, may pseudo-normalize systolic function. Alternative markers e.g. focusing on diastolic function and atrio-ventricular interactions should be investigated.

Extracted step parameters during the timed up and go test discriminate between groups with different levels of cognitive ability—a cross-sectional study

Abstract Background Identifying cognitive impairment at an early stage is important to enable preventive treatment and lifestyle changes. As gait deviations precede cognitive impairment, the aim of this study was to investigate if step parameters during different Timed Up and Go (TUG) conditions could discriminate between people with different cognitive ability. Methods Participants (N = 304) were divided into the following groups: (1) controls, n = 50, mean age:73, 44% women; (2) Subjective cognitive Impairment (SCI), n = 71, mean age:67, 45% women; (3) Mild Cognitive Impairment (MCI), n = 126, mean age: 73, 42% women; and (4) dementia disorders, n = 57, mean age: 78, 51% women. Participants conducted TUG and two motor-cognitive TUG-conditions: TUG while naming animals (TUGdt-NA) and reciting months in reverse order (TUGdt-MB). Tests were video recorded for data extraction of valid spatiotemporal parameters: step length, step width, step duration, single step duration and double step duration. Step length was investigated with the step length/body height ratio (step length divided by body height). Logistic regression models (adjusted for age, sex and education) investigated associations between step parameters and dichotomous variables of groups adjacent in cognitive ability: dementia disorders vs. MCI, MCI vs. SCI, and SCI vs. controls. Results were presented as standardized odds ratios (sORs), with 95% confidence intervals (CI95) and p-values (significance level: p < 0.05). The areas under the Receiver Operating Characteristic curves were presented for the step parameters/conditions with the highest sORs and, where relevant, optimal cutoff values were calculated. Results Step length showed greatest overall ability to significantly discriminate between adjacent groups (sOR ≤ . 67, CI95: .45-.99, p = ≤ . 047) during all group comparisons/conditions except three. The highest sOR for step-length was obtained when discriminating between SCI vs controls during TUGdt-MB (sOR = .51, CI95:.29- .87, p = .014), whereby the area under the curve was calculated (c-statistics = .700). The optimal cut-off indicated a step length of less than 32.9% (CI95 = 22.1–43.0) of body height to identify SCI compared with controls. Conclusions The results indicate that step length may be important to assess during TUG, for discrimination between groups with different cognitive ability; and that the presented cut-off has potential to aid early detection of cognitive impairment. Trial registration number NCT05893524 (retrospectively registered 08/06/23).

Role of Calcium and Alkaline Phosphatase in Bone Growth and its Impact on Osteoporosis

Aim: The objective of this study is to determine bone mineral density (BMD) and the biochemical markers with variation in healthy, osteopenic and osteoporotic individuals. It reviews the part of total alkaline phosphatase (T-ALP), bone-specific alkaline phosphatase (B-ALP) in assessment of bone metabolism and osteoporosis progression. The research also looks into the interaction of the calcium levels and estrogen deficiency in relation to bone health.  Methods: A total of three groups (healthy individuals, osteopenia and osteoporosis) were studied in a cross-sectional manner. Dual energy X-ray absorptiometry (DEXA) was used to measure BMD; and also, the serum samples analyzed for biochemical markers of calcium levels. The statistical comparison to identify the significant within the groups and correlation between biomarkers and the severity of osteoporosis were performed.  Results: Osteopenic and osteoporotic individuals’ BMD is significantly lower than that in healthy group. With B-ALP and T- ALP levels higher also, osteoporotic participants showed increased bone turnover. Additionally, the vit D deficient group was found to have significantly lower intake. There was only minor variation of calcium level except osteopenic and osteoporotic individuals showed a significant difference. The research further proves that estrogen deficiency greatly contributes to bone loss and the risk of fractures.  Conclusion: The finding of this study supports the importance of early detection and treatment of osteoporosis. BMD and biochemical markers simultaneously are used in combination for diagnosing (and monitoring) of bone health. Calcium and vitamin D supplementation, probiotics, as well as targeted molecular therapies based on a molecular analysis of luminal HC p5S fractions are recommended. With the success of chondroprotective nanotechnology, more work on novel interventions nanotechnology-based supplements and gene targeted treatments for osteoporosis prevention and treatment outcomes needs to happen.

Prostate cancer diagnosis and management: current practices in Africa a consultant-based survey

IntroductionIn Africa, prostate cancer poses significant diagnostic and treatment challenges due to limited access to diagnostic tools and healthcare resources. This survey aimed to assess current prostate biopsy practices, patient classification methods, and available therapeutic means among African urologists to propose strategies for improved screening, diagnosis, and management.MethodsA web-based self-administered questionnaire was distributed to urologists in 58 African centres, focusing on biopsy practices, cancer diagnosis, management, and treatment protocols. After pretesting and validation, data collection spanned six weeks, followed by duplicate elimination and arithmetical analysis, with results expressed in absolute, mean, or percentage values.ResultsFeedback was received from 58 centres across diverse African regions, including Central, Southern, West, East Africa, and Madagascar, comprising general, private, and university hospitals. Prostate cancer emerged as the most frequent urological cancer in all regions studied. The assay for prostate-specific antigen (PSA) was available in nearly all centres. Biopsy techniques varied, with ultrasound-guided biopsies being the most common (30 centres), followed by digital-guided (20 centres) and MRI-guided biopsies (5 centres). One centre lacked the expertise to perform biopsies. Radiological workup availability was high, with CT available in 56 centres, MRI in 54, PET scans in 14, and scintigraphy in 29. Treatment capabilities varied, with 53.4% of centres able to perform radical prostatectomies, 86.2% offering radiotherapy, and 94.8% providing medical castration. Among the centres, 56 performed fewer than 5 radical prostatectomies per month, while only 2 centres performed between 5 and 10 per month.ConclusionIt is important to standardise prostate cancer diagnosis and treatment protocols across Africa while improving access to advanced diagnostic technologies and treatment facilities. Implementing these changes could enhance early detection, improve treatment outcomes, and reduce the burden of prostate cancer in Africa.

Structural basis for the fast maturation of pcStar, a photoconvertible fluorescent protein

Green-to-red photoconvertible fluorescent proteins (PCFPs) serve as key players in single-molecule localization super-resolution imaging. As an early engineered variant, mEos3.2 has limited applications, mostly due to its slow maturation rate. The recent advent of a novel variant, pcStar, obtained by the simple mutation of only three amino acids (D28E/L93M/N166G) in mEos3.2, exhibits significantly accelerated maturation and enhanced fluorescent brightness. This improvement represents an important advance in the field of biofluorescence by enabling early detection with reliable signals, essential for labelling dynamic biological processes. However, the mechanism underlying the significant improvement in fluorescent performance from mEos3.2 to pcStar remains elusive, preventing the rational design of more robust variants through mutagenesis. In this study, we determined the crystal structures of mEos3.2 and pcStar in their green states at atomic resolution and performed molecular-dynamics simulations to reveal significant divergences between the two proteins. Our structural and computational analyses revealed crucial features that are distinctively present in pcStar, including the presence of an extra solvent molecule, high conformational stability and enhanced interactions of the chromophore with its surroundings, tighter tertiary-structure packing and dynamic central-helical deformation. Resulting from the triple mutations, all of these structural features are likely to establish a mechanistic link to the greatly improved fluorescent performance of pcStar. The data described here not only provide a good example illustrating how distant amino-acid substitutions can affect the structure and bioactivity of a protein, but also give rise to strategic considerations for the future engineering of more widely applicable PCFPs.

State-of-the-Art Review on the Treatment of Axial Spondyloarthritis

The term axial spondyloarthritis (axSpA) encompasses patients with both radiographic (r-axSpA) and non-radiographic (nr-axSpA) forms of the disease. These are two entities within the same family that share many genetic and pathogenic factors, but they also have significant differences. For example, the male-to-female ratio is 2:1 in r-axSpA and 1:1 in nr-axSpA. Additionally, the prevalence of the HLA-B27 gene is notably higher in r-axSpA. Early diagnosis remains an unmet need, with magnetic resonance imaging (MRI) being the most important tool for diagnosis and disease monitoring. Early detection is crucial, as it allows for timely treatment, increasing the chances of preventing new bone formation and long-term structural bone damage. Various cytokines, such as tumor necrosis factor (TNF)-α and interleukin-17, play active roles in the disease’s pathogenesis, although the exact mechanisms of interaction are not yet fully understood. Clarifying these mechanisms will be key to developing new classification criteria, screening methods, and more personalized, targeted therapies. Non-steroidal anti-inflammatory drugs (NSAIDs), TNF inhibitors, interleukin-17 blockers, and, more recently, Janus kinase (JAK) inhibitors, are the most effective treatments for both radiographic and non-radiographic axial spondyloarthritis.

RFID sensor development for corrosion monitoring in bridges cables

ABSTRACT This article investigates the RFID technology for corrosion monitoring of prestressed concrete structures. Common corrosion detection methods are time-consuming and expensive, leading to challenges in early detection, especially in inaccessible areas. RFID technology offers advantages such as wireless operation, small size, and easy integration. The present paper aims at applying RFID corrosion sensors to the monitoring of steel strands used in prestressed bridges. As it will be shown, corrosion of both steel strands and sensitive parts of sensors is governed by localized corrosion. When the depth of pits become higher than 150 m on the steel strands, an alert is triggered by sensors. With this alert, maintenance actions can be planned. The paper also validates the radio-frequency communication with sensors embedded within a High-Density Polyethylene (HDPE) sheath through in-situ testing. It is proved that embedded sensors in HDPE sheath can be manually interrogated by operators during inspections with a reading distance of 25 cm or more, depending on the location of the sensors with respect to strands. These findings highlight the interest of the method and contributes to the advancement of corrosion monitoring strategies for prestressed bridges, enabling improved maintenance practices and extended durability.

The Interplay between Anemia and Malaria Treatment Outcomes in East Africa: Implications for Clinical Recovery and Complication Risks

Anemia is a common and often severe complication of malaria, especially in East Africa, where the dual burden of these conditions significantly contributes to morbidity and mortality. The complex interplay between malaria and anemia impedes clinical recovery, increases the risk of complications, and challenges the effectiveness of malaria treatment regimens. This review explores the pathophysiology of malaria-induced anemia, highlighting mechanisms such as hemolysis, impaired erythropoiesis, and nutritional deficiencies. The impact of anemia on malaria treatment outcomes is discussed, including delayed recovery, increased risk of multi-organ dysfunction, and reduced efficacy of antimalarial therapies. Special populations, such as children under five, pregnant women, and individuals with hemoglobinopathies, face heightened risks. The review emphasizes the need for integrated management strategies, including early anemia detection, tailored antimalarial treatments, and targeted nutritional interventions, to improve treatment outcomes in anemic malaria patients. Additionally, the review identifies critical research gaps and outlines future directions for enhancing malaria and anemia management, with a focus on cost-effective interventions and the development of comprehensive treatment protocols. Addressing both malaria and anemia simultaneously offers a promising approach to reducing disease burden and improving recovery rates in East Africa. Keywords: Malaria, Anemia, East Africa, Treatment Outcomes, Plasmodium falciparum.

A Review on Predictive Analytics for Early Disease Detection in Neonatal Healthcare using Artificial Intelligence

The early detection of diseases plays a crucial role in improving patient outcomes, reducing healthcare costs, and enabling timely interventions. In recent years, the integration of Artificial Intelligence (AI) and Predictive Analytics (PA) has emerged as a transformative approach in healthcare, offering significant advancements in detecting diseases at their earliest stages. This paper provides a comprehensive review of the application of AI-driven predictive analytics in early disease detection, focusing on various AI techniques such as machine learning (ML), deep learning (DL), natural language processing (NLP), and neural networks. These techniques have shown exceptional promise in identifying patterns and correlations within medical data—including electronic health records (EHRs), medical imaging, genetic data, and wearable devices—that can signal the onset of diseases before they become clinically evident. The paper discusses the effectiveness of AI-based predictive models in detecting a wide range of diseases, including cancer, cardiovascular diseases, diabetes, neurological disorders, neonatal conditions, and infectious diseases. Special attention is given to AI applications in neonatal healthcare, where early detection of conditions such as neonatal sepsis, respiratory distress syndrome, and congenital anomalies can significantly improve survival rates and long-term health outcomes. By leveraging large datasets and advanced algorithms, AI systems can provide accurate predictions, risk assessments, and personalized treatment plans, leading to improved early diagnosis and targeted interventions. However, the integration of AI in disease detection also presents challenges such as data privacy concerns, model interpretability, ethical issues, and the need for robust regulatory frameworks. Furthermore, the paper highlights key advancements in AI technologies that have contributed to the success of predictive analytics in healthcare, along with real-world applications, case studies, and examples of AI models that have been implemented in clinical settings. The limitations and potential solutions to these challenges are also examined, with an emphasis on the importance of high-quality, representative datasets and continuous collaboration between AI researchers, clinicians, and regulatory bodies. This review aims to provide a thorough understanding of the current landscape of AI-powered predictive analytics for early disease detection and to highlight future directions in the field. As AI technologies continue to evolve, their role in enhancing early disease detection, particularly in neonatal care, improving patient outcomes, and enabling preventive healthcare will become increasingly significant, ultimately leading to a more efficient, effective, and equitable healthcare system.

Family-Centred Early Hearing Detection and Intervention in the African Context: Relevance and Responsiveness to African Culture

Family-centred early hearing detection and intervention (FC-EHDI) is an established framework globally recognized for its emphasis on family involvement in supporting children who are deaf and hard of hearing (DHH). In the African context, unique sociocultural and systemic challenges necessitate tailored approaches to ensure effective implementation. This narrative review explores the relevance of FC-EHDI in Africa, highlights barriers to its implementation, and offers recommendations for creating sustainable and culturally aligned interventions. A narrative review methodology synthesizing evidence from African countries to examine the intersection of FC-EHDI with cultural practices, systemic barriers, and opportunities for innovation was adopted. Databases including PubMed, Scopus, Web of Science, and Google Scholar were searched for peer-reviewed journal articles, books, and reports published between 2000 and 2024. Keywords included “family-centred care”, “EHDI”, “Africa”, “cultural responsiveness”, and “early hearing detection and intervention”. Studies were included if they addressed EHDI in African contexts, explored family-centred approaches, or provided barriers and recommendations specific to the region. Thematic analysis was employed to synthesize findings into barriers, evidence, and strategies for FC-EHDI implementation. Data were extracted and analysed thematically to identify patterns and gaps in knowledge. Key challenges identified include resource limitations, economic constraints, linguistic and cultural diversity, and fragmented healthcare systems. Evidence highlights the effectiveness of community-based care, linguistic inclusivity, and culturally tailored interventions in enhancing family engagement and programme outcomes. Recommendations focus on leveraging technology, interdisciplinary collaboration, and policy advocacy. FC-EHDI offers a transformative approach to addressing DHH African children by integrating family involvement, cultural responsiveness, and systemic innovations. Future efforts should emphasize technology, scalable models, and family empowerment to create sustainable and equitable services.

Examination of the relationship between D-amino acid profiles and cognitive function in individuals with mild cognitive impairment: A machine learning approach.

The global prevalence of dementia is significantly increasing. Early detection and prevention strategies, particularly for mild cognitive impairment (MCI), are crucial but currently hindered by the lack of established biomarkers. Here, we aimed to develop a high-precision screening method for MCI by combining D-amino acid profiles from peripheral blood samples with non-invasive subject information using nonlinear machine learning algorithms. A cross-sectional study was conducted with 200 participants aged 50-89 years, classified into cognitively normal and MCI-suspected groups based on Mini Mental State Examination scores. High-throughput techniques were used to analyze the D-amino acid profiles, specifically D-alanine (%) and D-proline (%), in peripheral blood. Correlation analysis was performed between D-amino acid levels in venous and fingertip blood. The predictive performance of various machine learning models, including Logistic Regression, Random Forest (RF), kernel Support Vector Machine (SVM), and Artificial Neural Network (ANN), was compared. Nonlinear models (kernel SVM and ANN) that combined D-amino acid profiles with subject information achieved the highest area under the curve values of 0.78 and 0.79, respectively, demonstrating that the combination of D-amino acid profiles and non-invasive subject information is effective in detecting MCI. Combining D-amino acid profiles with non-invasive subject information using nonlinear machine learning models, particularly kernel SVM and ANN, shows promise as a high-precision screening tool for MCI. This approach could serve as a cost-effective preliminary screening method before more invasive and expensive diagnostic tests and significantly contribute to the early detection and development of intervention strategies for dementia.

EARLY DETECTION OF RENAL CYST ON ULTRASONOGRAPHY AND THEIR ASSOCIATED RISK FACTORS

Background: Renal cysts are fluid-filled sacs that develop within or on the kidneys, often detected incidentally during routine ultrasonographic examinations. Although usually benign, renal cysts can be associated with systemic conditions and contribute to renal dysfunction in certain cases. Identifying their prevalence and associated risk factors is essential for early diagnosis and management. Hypertension, diabetes mellitus, and age-related changes have been recognized as potential contributors to renal cyst development, yet their exact epidemiological burden varies across different populations. Objective: To determine the prevalence of renal cysts in patients undergoing ultrasound evaluation and to assess their associated risk factors. Methods: A cross-sectional descriptive study was conducted at the Institute of Kidney Diseases, Peshawar, Pakistan, on 344 patients referred for renal ultrasound. Convenience sampling was applied. Patients of all ages and genders were included, while those with congenital anomalies, unilateral nephrectomy, or kidney transplants were excluded. Data were collected through a pre-structured questionnaire, and statistical analysis was performed using SPSS version 20. Descriptive and inferential statistics, including chi-square tests and binary logistic regression, were applied to determine associations. Results: Renal cysts were present in 23.8% of cases. Simple cysts were the most common type (89%), while complex and other cyst types accounted for 9.6%. Females had a higher prevalence (52.3%) than males (30.3%) (P=0.034). The left kidney was more frequently affected (52%) than the right (34%), with bilateral involvement in 14%. Cyst location was predominantly cortical (84%), followed by medullary (4.8%), renal pelvis (8.5%), and polycystic (1.2%). Solitary cysts were most common (64.6%), while double (8.5%) and multiple cysts (25.6%) were less frequent. Hypertension (P=0.000, OR=2.969) and diabetes mellitus (P=0.007, OR=2.519) were significant risk factors. Conclusion: Simple renal cysts were the most frequently detected type, with a higher prevalence in females. Hypertension, diabetes mellitus, and renal stone history were strongly associated with cyst development. Ultrasound plays a crucial role in early detection, guiding appropriate management to prevent complications such as chronic kidney disease.

Localized Excision of Gastrointestinal Stromal Tumor (GIST) After Sleeve Gastrectomy: Highlighting a Sleeve-Preserving Surgical Approach.

Gastrointestinal stromal tumors (GISTs) are relatively rare, accounting for approximately 0.1-3% of all gastrointestinal tumors. Their incidence is higher in individuals aged 50 to 70years, with an equal gender distribution. Due to their diverse clinical presentations, including upper gastrointestinal (GI) bleeding and gastric discomfort, along with an indolent growth pattern, GISTs can remain undetected for extended periods. This delay in diagnosis can lead to complications. Diagnosis involves upper GI endoscopy, computed tomography (CT) scan, biopsy with histologic grading, and immunohistochemical testing for CD-117 and CD34. The higher incidence of GISTs in patients with obesity underscores the need for preoperative upper GI endoscopic screening. A 31-year-old female with a history of sleeve gastrectomy (SG) for obesity (BMI 38kg/m2) presented 13months postoperatively with recurrent hematemesis, epigastric fullness, and pain radiating to the back. Despite medical management, including proton pump inhibitors (PPIs), her symptoms persisted. Upper GI endoscopy revealed a polypoidal mass at the gastroesophageal junction (GEJ). Endoscopic ultrasound (EUS) indicated that the lesion originated from the muscularis propria. A contrast-enhanced CT scan confirmed the presence of a polypoid mass without extra-luminal extension, raising suspicion of GIST. The patient underwent laparoscopic resection of the tumor using a sleeve-preserving approach. The tumor was excised with a 1-cm margin of normal tissue, ensuring complete resection with negative margins confirmed by the frozen section. The gastric defect was closed with interrupted sutures, and a 38-Fr gastric tube was placed to maintain luminal patency. The patient had an uneventful recovery, with minimal drain output, and was discharged on postoperative day 3 with continued PPI therapy. Histopathological examination confirmed a low-risk GIST. At 1-year follow-up, the patient remained asymptomatic with no recurrence. Early detection and sleeve-preserving resection of GISTs in post-sleeve gastrectomy patients ensure effective tumor management while maintaining gastric integrity. This case highlights the importance of preoperative evaluation and long-term follow-up in these patients.