Objective: To identify and evaluate the main functional assessment tools applied in the postoperative monitoring of patients undergoing total knee arthroplasty (TKA), and to synthesize the functional outcomes reported through these instruments in the current scientific literature. Methodology: A structured review was conducted following PRISMA 2020 guidelines. Thirty-one peer-reviewed studies were selected through a targeted manual search based on predefined eligibility criteria. Included studies evaluated functional recovery following TKA using validated outcome measures such as the WOMAC, KSS, KOOS, IKDC, SF-36, and SANE. Data extraction focused on the instruments used, patient population characteristics, and reported outcomes. A descriptive synthesis was compiled in Table 1. Additionally, 15 studies with quantitative data were analyzed using a forest plot to illustrate risk ratios (RR) and 95% confidence intervals (CI) for functional improvement. Risk of bias was assessed qualitatively based on methodological rigor, clarity of reporting, and validation of the outcome tools. Results: All included studies reported improvements in functional status following TKA. Most risk ratios ranged from 0.66 to 0.85, indicating a consistent reduction in the risk of postoperative functional limitation. High-quality studies demonstrated more precise effect estimates and greater internal validity. The SANE scale emerged as a valid and practical tool with high responsiveness, including in its culturally adapted Brazilian version. Despite heterogeneity in study design, the direction of effect remained consistent across all included studies. Conclusion: Validated functional assessment tools are essential for monitoring recovery after total knee arthroplasty. Instruments such as WOMAC and SANE demonstrate strong clinical utility and psychometric validity. Their systematic use enhances outcome comparability, supports individualized rehabilitation planning, and improves decision-making in orthopedic care.

Background: Type 2 Diabetes Mellitus (T2DM) and Alzheimer’s Disease (AD) are increasingly linked through shared pathophysiological mechanisms, giving rise to the concept of Type 3 Diabetes Mellitus (T3DM). Brain insulin resistance, oxidative stress, and neuroinflammation are central to both conditions, contributing to cognitive decline and AD progression. Aim: This review aims to explore this emerging relationship and its implications for prevention and management. Methods: Using an integrative review, 21 studies were systematically analyzed. The review focused on identifying demographic, genetic, and lifestyle factors contributing to T2DM and AD and examined shared molecular pathways such as insulin dysregulation and amyloid-beta accumulation. Results: The findings reveal that T3DM shares key features with T2DM and AD, including insulin resistance and chronic inflammation. Lifestyle interventions, such as diet and exercise, alongside routine cognitive and metabolic screenings, are critical in mitigating progression. Conclusions: Further research into diagnostic biomarkers and targeted therapies is essential to manage T3DM and its impact on AD. The role of nursing professionals in early detection, education, and holistic management is emphasized as vital in addressing this dual disease burden. This review offers actionable insights into integrated strategies for addressing these interconnected conditions.

Background: Scapulohumeral periarthritis commonly afflicts individuals in their middle age. Its etiology is multifaceted, and treatment presents a challenge with a high risk of recurrence. The main symptoms include shoulder pain and limited joint mobility, seriously affect the quality of life of the patients. Recent research indicate that acupuncture combined with bloodletting cupping can significantly improve the function of activity of shoulder joint and the pain in individuals with scapulohumeral periarthritis. However, these studies have typically been limited in scope, therefore additional research to substantiate the efficacy and safety of these intervention. Methods: To evaluate the efficacy of acupuncture combined with bloodletting cupping for treating patients with scapulohumeral periarthritis. We conducted an online search of databases in both Chinese and English, including PubMed, the Cochrane Library, Embase, Web of Science, CNKI, Wangfang Data, China Science and Technology Journal Database (VIP) and Chinese BioMedical Literature Database (CBM), to collect randomized controlled trials (RCTs) concerning the use of acupuncture combined with bloodletting cupping in scapulohumeral periarthritis patients. We also examined the references within the identified literature. Search utilised subject headings and free-text terms in both languages, without racial restrictions, for records up to April 3, 2024. Two researchers independently screened the literature, extracted data, and evaluated their qualities. RevMan 5.3 software was used for meta-analysis of the included studies. The protocol of this review was recorded in the International Platform of Registered Systematic Review and Meta-analysis Protocols (PROSPERO). Its registration number is CRD42023454614. Results: This review incorporated 22 RCTs involving a total of 1,774 patients. The results of meta-analysis showed that the clinical effective rate (RR=1.25, 95%CI [1.20, 1.30], P＜0.00001) of treating scapulohumeral periarthritis with acupuncture combined with bloodletting cupping was higher in the experimental group than in the control group. The all of Visual Analogue Scale (VAS) score (MD=-1.70, 95% CI [-2.17, -1.22], P＜0.00001). Melle score (SMD=-2.45, 95% CI [-2.55, -2.34], P=0.007]) and recurrence rate (RR=0.23, 95% CI [0.07, 0.77], P=0.02) were lower in the experimental group than in the control group with statistical significance (P<0.05). Conclusion: The acupuncture combined with bloodletting cupping for the treatment of shoulder impingement syndrome demonstrates definite efficacy and safety, with superior clinical effectiveness, pain relief, improvement in shoulder joint mobility, and reduction in recurrence compared to acupuncture alone. Therefore, it is worthy of being promoted and applied clinically.

With an increasing diversity of learners in today’s educational set-ups, there is an insurmountable need to cater for individual differences including the cultural variations among learners. It is therefore necessary for educators to develop culturally responsive teaching that enhances intercultural competencies of learners. As educators strive to provide inclusive learning environments in which learners from diverse cultural backgrounds learn equitably, differentiated instruction becomes a practical tool. This paper explores how differentiated instruction can support and enhance culturally responsive teaching by examining how tailored instructional approaches can bridge cultural gaps and enhance educational outcomes. The aim is to provide a comprehensive understanding of how educators can effectively integrate differentiated instructional methodologies to achieve the goals of Culturally Responsive Teaching. The study used a descriptive survey design to determine the use of differentiated instruction by junior school teachers in Kenya and a systematic review of literature, practical examples, and studies on teachers’ practices in culturally responsive teaching. The study outcomes indicated that teachers used various differentiated instructional strategies with flexible grouping being the most commonly used strategy. However, there arises a concern, that teachers were not very familiar with cultural variations of learners in their classrooms even as they developed their differentiated instructional strategies. Literature provided the principles and practices of culturally responsive teaching. The combination of these results were used to formulate a conceptual framework for Culturally Responsive Differentiated Instruction (CRDI) that provides insights for practitioners to develop and implement culturally responsive differentiated instructional strategies. The study recommends that a framework to support teachers in the implementation of inclusive and equitable curriculum through CRDI be developed, CRDI be integrated into the teaching processes and the teachers be trained on providing for learner differences through CRDI.

The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

Opuntia ficus-indica (L.) Mill., commonly known as prickly pear, is a versatile plant widely used for food, medicinal, and cosmetic purposes in various regions of the Mediterranean and North Africa. This study provides a comparative ethnobotanical review of prickly pear uses in Algeria, Morocco, Tunisia, and Italy. In total, 74 articles were selected from ethnobotanical uses in Italy, Algeria, Morocco and Tunisia. In the Maghreb, the plant is used for fruit production and processed products, such as jams, oils, and flours, as well as for traditional medicinal purposes. In Algeria and Morocco, the fruits and cladodes are used to treat digestive disorders, diabetes, and skin diseases. In Tunisia, products derived from O. ficus-indica are also applied in the cosmetic industry and for erosion control. In Italy, particularly in Sicily and Calabria, the prickly pear is a vital resource, used for both food consumption and for medicinal purposes. The cladodes, rich in mucilage, are applied as topical remedies for skin problems, while the fruits are a key ingredient in the preparation of traditional desserts. Furthermore, O. ficus-indica has historically been used as forage and to produce natural dyes. Results indicate that the versatility of this species, combined with its ability to adapt to extreme climates, makes it a valuable resource for the development of new nutraceutical and cosmetic products. However, further scientific research is necessary to explore the bio-functional potential of this plant and to promote its broader and more sustainable use, especially in arid and semi-arid regions.

Background: The COVID-19 pandemic posed significant psychological challenges to frontline healthcare workers (HCWs), including anxiety, stress, and emotional strain. Aim: This study investigates the psychological impact on HCWs during the pandemic and explores coping strategies employed to manage distress. Methods: An integrative review was conducted using 24 studies published between January and December 2020. These studies were analyzed to identify common psychological outcomes and coping mechanisms among HCWs. Results: Healthcare workers experienced significant psychological distress during the COVID-19 pandemic, including anxiety, stress, insomnia, and depression. Anxiety was the most commonly reported issue, particularly among women, younger healthcare workers, and frontline staff. Stress levels were heightened by high workloads, exposure to COVID-19 patients, and inadequate protective measures. Coping strategies and self-care behaviors, such as seeking social support and utilizing institutional resources, varied in effectiveness across populations. Conclusion: The findings highlight the urgent need for targeted mental health support and resilience programs for HCWs, ensuring they are better equipped to face future health crises.

Background: Diabetes is a chronic global health issue that requires effective management to improve patient outcomes and quality of life. Nursing education plays a critical role in empowering diabetic patients with self-management skills. Aim This systematic review evaluates the impact of diabetes-focused nursing education on patient outcomes and quality of life. Methods: This study uses PRISMA guidelines and a systematic approach to identify and evaluate relevant literature. Results and Discussion: Among the 14 studies reviewed, eight emphasized self-management education, while four incorporated multidisciplinary approaches. Findings consistently demonstrated that structured nursing education programs significantly improved self-management behaviors, glycemic control, and patient knowledge. For instance, nurse-led self-management programs resulted in substantial enhancements in self-care skills and diabetes-related knowledge. Moreover, interventions that combined health education with psychological support were particularly effective, leading to better blood glucose control and increased adherence to treatment. Studies that examined quality of life reported reductions in anxiety, improved lifestyle habits, and better overall self-management. These findings highlight the multifaceted benefits of nursing education, suggesting that structured, supportive programs positively impact both clinical and psychological aspects of diabetes care. Conclusion: The review emphasizes the value of comprehensive nursing education that integrates both clinical guidance and psychological support for holistic diabetes management. Implications: Ongoing professional development and culturally sensitive education programs are recommended to address the diverse needs of diabetic patients. Future research should investigate the long-term effects of nursing education and explore innovative strategies to enhance diabetes management outcomes.

Background: Electrical injuries are underreported in literature, but they can affect the peripheral and central nervous system causing permanent disability. Aims and objectives: This case report aims to highlight cervical spinal cord injury secondary to electrocution, a rare cause of spinal cord injury. Case report: We report the case of a 54-year-old housewife who presented with transient loss of consciousness and right sided hemiparesis following electrocution, while at home. Results: The patient met clinical critera for partial Brown- Sequard syndrome, which to our knowledge, has not been previously reported. She showed significant improvement over a month and is currently under monitoring. Conclusions: Electrical injury is a rare cause of normal MRI myelopathy and the potential for immediate, delayed, and long- term neurological disability.