Search

Algeria primarily relies on fossil fuels to meet its growing electricity demand, significantly contributing to climate change and the depletion of non-renewable resources. In response, the Algerian government has initiated ambitious plans to integrate renewable energy into the national grid. While photovoltaic solar energy has received substantial attention over the past decade, the potential for Concentrated Solar Power (CSP) remains largely untapped, despite its advantages for thermal energy storage and sustainable electricity production. This study assesses the feasibility of establishing CSP plants in Ghardaïa, a city in southern Algeria, using high-resolution $30\times 30$ -meter Geographic Information Systems (GIS) data. By integrating GIS with Fuzzy Logic and Multi-Criteria Decision-Making (MCDM) techniques, and utilizing a variety of spatial maps, this study identifies areas suitable for high- and medium-scale CSP plants. The analysis reveals that 10% of the region’s land is suitable for CSP installations, with 1% categorized as extremely suitable for large-scale projects. Furthermore, 33% of the land is suitable for small-scale CSP plants, of which 3% is deemed extremely suitable. These findings underscore the significant potential for expanding CSP infrastructure in Ghardaïa, aligning with Algeria’s renewable energy objectives.

Abstract CNS tumours encompass a diverse group of neoplasms with significant morbidity and mortality. The SHH signalling pathway plays a critical role in the pathogenesis of several CNS tumours, including gliomas, medulloblastomas and others. By influencing cellular proliferation, differentiation and migration in CNS tumours, the SHH pathway has emerged as a promising target for therapeutic intervention. Current strategies such as vismodegib and sonidegib have shown efficacy in targeting SHH pathway activation. However, challenges such as resistance mechanisms and paradoxical effects observed in clinical settings underscore the complexity of effectively targeting this pathway. Advances in gene editing technologies, particularly CRISPR/Cas9, have provided valuable tools for studying SHH pathway biology, validating therapeutic targets and exploring novel treatment modalities. These innovations have paved the way for a better understanding of pathway dynamics and the development of more precise therapeutic interventions. In addition, the identification and validation of biomarkers of SHH pathway activation are critical to guide clinical decision making and improve patient outcomes. Molecular profiling and biomarker discovery efforts are critical steps towards personalised medicine approaches in the treatment of SHH pathway-associated CNS tumours. While significant progress has been made in understanding the role of the SHH pathway in CNS tumorigenesis, ongoing research is essential to overcome current therapeutic challenges and refine treatment strategies. The integration of molecular insights with advanced technologies and clinical expertise holds great promise for developing more effective and personalised therapies for patients with SHH pathway-driven CNS tumours. Graphical Abstract

Abstract Whole-exome sequencing (WES), a ground-breaking technology, has emerged as a linchpin in neurology and neurosurgery, offering a comprehensive elucidation of the genetic landscape of various neurological disorders. This transformative methodology concentrates on the exonic portions of DNA, which constitute approximately 1% of the human genome, thus facilitating an expedited and efficient sequencing process. WES has been instrumental in advancing our understanding of neurodegenerative diseases, neuro-oncology, cerebrovascular disorders, and epilepsy by revealing rare variants and novel mutations and providing intricate insights into their genetic complexities. This has been achieved while maintaining a substantial diagnostic yield, thereby offering novel perspectives on the pathophysiology and personalized management of these conditions. The utilization of WES boasts several advantages over alternative genetic sequencing methodologies, including cost-effectiveness, reduced incidental findings, simplified analysis and interpretation process, and reduced computational demands. However, despite its benefits, there are challenges, such as the interpretation of variants of unknown significance, cost considerations, and limited accessibility in resource-constrained settings. Additionally, ethical, legal, and social concerns are raised, particularly in the context of incidental findings and patient consent. As we look to the future, the integration of WES with other omics-based approaches could help revolutionize the field of personalized medicine through its implications in predictive models and the development of targeted therapeutic strategies, marking a significant stride toward more effective and clinically oriented solutions. Graphical Abstract

Abstract Complications are plausible events during surgical operations. Surgical complications profoundly impact surgeons, often called “second victims” of adverse events. These complications trigger a range of emotional and psychological responses, including guilt, anxiety, heightened empathy, and the looming threat of burnout. Moreover, the toll extends to physical health, with chronic stress and sleep disturbances taking their toll. Surgeons’ social lives are not immune to the fallout, and their career satisfaction may wane, pushing some towards defensive medicine practices. While mentorship, counselling, and peer support are crucial support mechanisms, they encounter barriers such as time constraints and the fear of negative perceptions. This paper suggests practical recommendations, including comprehensive wellness programmes, a streamlined badge card system for easy access to resources, and mindfulness training to mitigate stress and burnout. Recognising and proactively addressing these multifaceted impacts is imperative for cultivating a resilient medical community capable of providing optimal patient care.

Abstract Chromosomal instability (CIN) is a pivotal factor in gliomas, contributing to their complexity, progression, and therapeutic challenges. CIN, characterized by frequent genomic alterations during mitosis, leads to genetic abnormalities and impacts cellular functions. This instability results from various factors, including replication errors and toxic compounds. While CIN’s role is well documented in cancers like ovarian cancer, its implications for gliomas are increasingly recognized. CIN influences glioma progression by affecting key oncological pathways, such as tumor suppressor genes (e.g., TP53), oncogenes (e.g., EGFR), and DNA repair mechanisms. It drives tumor evolution, promotes inflammatory signaling, and affects immune interactions, potentially leading to poor clinical outcomes and treatment resistance. This review examines CIN’s impact on gliomas through a narrative approach, analyzing data from PubMed/Medline, EMBASE, the Cochrane Library, and Scopus. It highlights CIN’s role across glioma subtypes, from adult glioblastomas and astrocytomas to pediatric oligodendrogliomas and astrocytomas. Key findings include CIN’s effect on tumor heterogeneity and its potential as a biomarker for early detection and monitoring. Emerging therapies targeting CIN, such as those modulating tumor mutation burden and DNA damage response pathways, show promise but face challenges. The review underscores the need for integrated therapeutic strategies and improved bioinformatics tools like CINdex to advance understanding and treatment of gliomas. Future research should focus on combining CIN-targeted therapies with immune modulation and personalized medicine to enhance patient outcomes.

ABSTRACT Background and Aims The diagnosis and management of soft tissue sarcoma (STS) in sub‐Saharan Africa (SSA) present significant challenges. Positive outcomes in STS treatment include achieving negative margins, improved quality of life, and reduced recurrence rates, while negative outcomes involve incomplete resection, local recurrence, and surgical complications. This review aims to examine the current state of STS management in SSA, identify key challenges, and propose potential solutions to improve patient outcomes. Methods A comprehensive review of the literature using PubMed/MEDLINE, Google Scholar, and Scopus, focusing on English‐language studies examining the management of STS in SSA. Inclusion criteria centered on studies reporting on surgical interventions, outcomes, and healthcare challenges in the region. Articles lacking sufficient data, non‐English sources, conference abstracts, and duplicates were excluded. Results Findings highlight several obstacles in the management of STS in SSA, including limited multidisciplinary teams, inadequate healthcare infrastructure, financial constraints, and lack of standardized treatment protocols. Key themes such as diagnostic capacity and resource allocation were identified as significant barriers. Conclusion Improving STS outcomes in SSA requires investment in healthcare infrastructure, professional development, enhanced funding, and collaborative research. Addressing these gaps is crucial to achieving better surgical management and improving survival rates for patients with STS in SSA.

Abstract Multiple Sclerosis (MS) is a complex autoimmune disorder that significantly impacts the central nervous system, leading to a range of complications. While intracranial haemorrhage (ICH) is a rare but highly morbid complication, more common CNS complications include progressive multifocal leukoencephalopathy (PML) and other CNS infections. This severe form of stroke, known for its high morbidity and mortality rates, presents a critical challenge in the management of MS. The use of disease-modifying drugs (DMDs) in treating MS introduces a nuanced aspect to patient care, with certain medications like Dimethyl Fumarate and Fingolimod showing potential in reducing the risk of ICH, while others such as Alemtuzumab and Mitoxantrone are associated with an increased risk. Understanding the intricate relationship between these DMDs, the pathophysiological mechanisms of ICH, and the individualised aspects of each patient's condition is paramount. Factors such as genetic predispositions, existing comorbidities, and lifestyle choices play a crucial role in tailoring treatment approaches, emphasising the importance of a personalised, vigilant therapeutic strategy. The necessity for ongoing and detailed research cannot be overstated. It is crucial to explore the long-term effects of DMDs on ICH occurrence and prognosis in MS patients, aiming to refine clinical practices and promote patient-centric, informed therapeutic decisions. This approach ensures that the management of MS is not only comprehensive but also adaptable to the evolving understanding of the disease and its treatments.

Abstract Breast cancer (BC) continues to be a significant global challenge due to drug resistance and severe side effects. The increasing prevalence is alarming, requiring new therapeutic approaches to address these challenges. At this point, Extracellular vesicles (EVs), specifically small endosome-released nanometer-sized EVs (SEVs) or exosomes, have been explored by literature as potential theranostics. Therefore, this review aims to highlight the therapeutic potential of exosomes in BC, focusing on their advantages in drug delivery and their ability to mitigate metastasis. Following the review, we identified exosomes' potential in combination therapies, serving as miRNA carriers and contributing to improved anti-tumor effects. This is evident in clinical trials investigating exosomes in BC, which have shown their ability to boost chemotherapy efficacy by delivering drugs like paclitaxel (PTX) and doxorubicin (DOX). However, the translation of EVs into BC therapy is hindered by various challenges. These challenges include the heterogeneity of EVs, the selection of the appropriate parent cell, the loading procedures, and determining the optimal administration routes. Despite the promising therapeutic potential of EVs, these obstacles must be addressed to realize their benefits in BC treatment.

Abstract Introduction The prevalence of abdominal injuries in war and conflict zones, particularly in low‐ and middle‐income countries (LMICs), presents a significant healthcare challenge. These injuries, often resulting from explosive devices, firearms, and shrapnel, lead to high morbidity and mortality rates due to delayed diagnoses, inadequate medical infrastructure, and limited access to specialised care. This review aims to summarise the literature on conflict‐related abdominal injuries in LMICs, highlighting the impact of such trauma on healthcare systems and patient outcomes, and suggesting strategies for improvement. Methods A comprehensive narrative review was conducted, focusing on studies from contemporary and historical conflict‐ridden nations. Databases such as PubMed, EMBASE, Google Scholar, the Cochrane Library, and Scopus were searched using specific keywords. Inclusion criteria encompassed various study designs and both paediatric and adult populations, with studies providing raw data prioritised. Exclusions included non‐English articles, non‐peer‐reviewed studies, and those not reporting outcomes or involving high‐income countries. Results The review identified significant challenges in managing war‐related abdominal trauma in LMICs, including a shortage of healthcare personnel and infrastructure, socio‐political barriers, and research gaps. Clinical implications of such injuries include elevated mortality rates, with surgical and nonsurgical management outcomes varying significantly. Positive advancements in diagnostics and surgical techniques have improved survival rates, yet the need for further infrastructural and workforce enhancements remains critical. Conclusion Abdominal trauma in conflict‐affected LMICs necessitates focused efforts to improve healthcare delivery, including targeted funding for infrastructure and equipment, development of training programs for trauma specialists, and increased humanitarian aid. Bridging research gaps and fostering collaborative efforts are essential for advancing the management of abdominal trauma and enhancing patient outcomes in these challenging environments.

The year 2020 was marked by the health crisis caused by COVID-19, and as a result, the sudden switch from a face-to-face learning teaching modality to a totally distance learning one was imposed. This change of modality placed the actors involved in an unprecedented situation, in which they were encouraged to adapt their teaching practices, in particular their professional gestures, to a totally online teaching modality. The aim of this study is first to identify the difficulties encountered by teachers in coping with this change, and then to assess the impact of this teaching mode on their professional gestures, in the light of Jorro’s model (2005). To this end, we opted for qualitative research carried out through semi-directive interviews with forty teachers belonging to the different establishments of Mohammed First University. These teachers expressed difficulties in implementing professional gestures in a distance learning context. This subsequently led to changes in the appearance and suppression of certain gestures.

Abstract Background and aims In low‐ and middle‐income countries (LMICs), a shortage of skilled surgical practitioners hampers healthcare delivery, impacting well‐being and economic growth. Surgical mentorship programs offer a promising solution but face challenges in implementation. This review aims to comprehensively assess the impact of surgical mentorship programs in LMICs and identify challenges and opportunities for their development and implementation. Methods A thorough literature search was conducted from 2000 to 2023 using multiple databases, focusing on surgical mentorship programs in LMICs. Inclusion criteria encompassed full‐text articles in English that demonstrated characteristics of mentorship. Rigorous exclusion criteria were applied to ensure high‐quality evidence inclusion. Results Surgical mentorship programs in LMICs strengthen local surgical capacity, improve surgical skills and patient outcomes, optimize resources and technology utilization, and positively impact medical students aspiring to be surgeons. However, challenges such as resistance to change, resource limitations, financial constraints, logistical and technological challenges, and time constraints hinder their implementation. Conclusion Despite challenges, surgical mentorship programs hold promise for enhancing surgical capacity and healthcare quality in LMICs. Standardized metrics for accountability, innovative funding mechanisms, collaborative partnerships for scalability, interdisciplinary integration, and leveraging virtual mentorship programs are key strategies to overcome challenges and foster sustainable learning cultures, ultimately contributing to improved healthcare equity and quality in low‐resource settings.

Abstract Tumor progression and eradication have long piqued the scientific community's interest. Recent discoveries about the role of chemokines and cytokines in these processes have fueled renewed interest in related research. These roles are frequently viewed as contentious due to their ability to both suppress and promote cancer progression. As a result, this review critically appraised existing literature to discuss the unique roles of cytokines and chemokines in the tumor microenvironment, as well as the existing challenges and future opportunities for exploiting these roles to develop novel and targeted treatments. While these modulatory molecules play an important role in tumor suppression via enhanced cancer-cell identification by cytotoxic effector cells and directly recruiting immunological effector cells and stromal cells in the TME, we observed that they also promote tumor proliferation. Many cytokines, including GM-CSF, IL-7, IL-12, IL-15, IL-18, and IL-21, have entered clinical trials for people with advanced cancer, while the FDA has approved interferon-alpha and IL-2. Nonetheless, low efficacy and dose-limiting toxicity limit these agents' full potential. Conversely, Chemokines have tremendous potential for increasing cancer immune-cell penetration of the tumor microenvironment and promoting beneficial immunological interactions. When chemokines are combined with cytokines, they activate lymphocytes, producing IL-2, CD80, and IL-12, all of which have a strong anticancer effect. This phenomenon opens the door to the development of effective anticancer combination therapies, such as therapies that can reverse cancer escape, and chemotaxis of immunosuppressive cells like Tregs, MDSCs, and TAMs.

Remote agricultural regions in desert areas, such as Ghardaïa in southern Algeria, face significant challenges in energy supply due to their isolated locations and harsh climatic conditions. Harnessing solar energy through photovoltaic (PV) systems offers a sustainable solution to these energy needs. This study aims to identify suitable areas for PV power installations in Ghardaïa, utilizing a geographic information system (GIS) combined with the fuzzy analytical hierarchy process (AHP). Various environmental, economic, and technical factors, such as solar radiation, land use, and proximity to infrastructure, are incorporated into the analysis to create a multi-criteria decision-making framework. The integration of fuzzy logic into AHP enables a more flexible evaluation of these factors. The results revealed the presence of ideal locations for installing photovoltaic stations, with 346,673.30 hectares identified as highly suitable, 977,606.84 hectares as very suitable, and 937,385.97 hectares as suitable. These areas are characterized by high levels of solar radiation and suitable infrastructure availability, contributing to reduced implementation costs and facilitating logistical operations. Additionally, the proximity of these locations to agricultural areas enhances the efficiency of electricity delivery to farmers. The study emphasizes the need for well-considered strategic planning to achieve sustainable development in remote rural areas.

Neurosurgeons receive extensive technical training, which equips them with the knowledge and skills to specialise in various fields and manage the massive amounts of information and decision-making required throughout the various stages of neurosurgery, including preoperative, intraoperative, and postoperative care and recovery. Over the past few years, artificial intelligence (AI) has become more useful in neurosurgery. AI has the potential to improve patient outcomes by augmenting the capabilities of neurosurgeons and ultimately improving diagnostic and prognostic outcomes as well as decision-making during surgical procedures. By incorporating AI into both interventional and non-interventional therapies, neurosurgeons may provide the best care for their patients. AI, machine learning (ML), and deep learning (DL) have made significant progress in the field of neurosurgery. These cutting-edge methods have enhanced patient outcomes, reduced complications, and improved surgical planning.

Spine surgery is continually evolving, with the application of new technologies often serving as a catalyst for improved clinical outcomes. Exoscope-assisted spinal surgery has recently emerged as a notable technological advancement offering a refined approach to visualisation, thereby potentially contributing to improved surgical precision, reduced complication rates, and optimised patient outcomes. The application of exoscopes have improved spine surgeries such as spinal fusion procedures, decompression surgeries, instrumentation surgeries, minimally invasive and complex surgeries. These improvements include enhanced visualisation, improved ergonomics, improved surgical precision, reduced operation times and postoperative infection rates. The integration of robotics in exoscope-assisted spine surgery enables autofocus function, ensuring the integrity of the sterile field, providing superior image quality, resolution, and three-dimensional perception. However, challenges such as decrease in depth perception and the lack of long-term follow-up data hinder its widespread adoption. Ethical considerations regarding patient safety, technology dependency, and health inequity add another dimension to these challenges. Despite these challenges, exoscope-assisted spine surgery holds significant potential for transforming clinical practice and improving patient outcomes. This review seeks to provide a concise overview of the benefits and limits of exoscope-assisted spine surgeries, while highlighting its challenges and ethical considerations. Addressing these limitations by conducting large-scale clinical trials and exploring the integration of artificial intelligence (AI) could assist in realising the potential of exoscopes in spine surgery.”

Abstract Introduction Artificial intelligence (AI) is transforming oncology and surgery by improving diagnostics, personalizing treatments, and enhancing surgical precision. Patients appreciate AI for its potential to provide accurate prognoses and tailored therapies. However, AI's implementation raises ethical concerns, data privacy issues, and the need for transparent communication between patients and health care providers. This study aims to understand patients' perspectives on AI integration in oncology and surgery to foster a balanced and patient‐centered approach. Methods The study utilized a comprehensive literature review and analysis of existing research on AI applications in oncology and surgery. The focus was on examining patient perceptions, ethical considerations, and the potential benefits and risks associated with AI integration. Data was collected from peer‐reviewed journals, conference proceedings, and expert opinions to provide a broad understanding of the topic. The perspectives of patients was also emphasized to highlight the nuances of their acceptance and concerns regarding AI in their health care. Results Patients generally perceive AI in oncology and surgery as beneficial, appreciating its potential for more accurate diagnoses, personalized treatment plans, and improved surgical outcomes. They particularly value AI's role in providing timely and precise diagnostics, which can lead to better prognoses and reduced anxiety. However, concerns about data privacy, ethical implications, and the reliability of AI systems were prevalent. Consequently, trust in AI and health care providers was deemed as a crucial factor for patient acceptance. Additionally, the need for transparent communication and ethical safeguards was also highlighted to address these concerns effectively. Conclusion The integration of AI in oncology and surgeryholds significant promise for enhancing patient care and outcomes. Patients view AI as a valuable tool that can provide accurate prognoses and personalized treatments. However, addressing ethical concerns, ensuring data privacy, and building trust through transparent communication are essential for successful AI integration. Future initiatives should focus on refining AI algorithms, establishing robust ethical guidelines, and enhancing patient education to harmonize technological advancements with patient‐centered care principles.

Abstract Background and Aims Diabetic Foot Ulcers (DFUs) are a significant health concern, particularly in Low‐ and Middle‐Income Countries (LMICs). This review explores key strategies for managing DFUs in LMICs, including integrating podiatry, endocrinology, and wound care services, educating patients, promoting self‐care, and preventive measures to reduce amputation rates. Methods A comprehensive literature review was conducted, focusing on studies conducted in Low and Middle Income Countries to facilitate a qualitative analysis. The review examined the aetiology and risk factors to developing DFUs, clinical presentation, multidisciplinary management and evidence based interventions, challenges to the provision of care and future directions, all pertaining to DFUs in low and middle income countries. Results The aetiology and risk factors contributing to the development of DFUs are complex and multifaceted. Factors such as limited access to health care, inadequate diabetes management, and socioeconomic disparities significantly influence the incidence of DFUs. Clinical presentation varies, with patients often presenting at advanced stages of the disease due to delayed or missed diagnoses. Multidisciplinary management, incorporating podiatry, endocrinology, and wound care services, has exhibited substantial promise in enhancing patient outcomes. Evidence‐based interventions, including offloading techniques, wound debridement, and the use of advanced wound dressings, have proven effective in promoting ulcer healing. Conclusion The burden of DFUs in LMICs requires comprehensive strategies. Integrating podiatry, endocrinology, and wound care services, along with patient education and self‐care practices, is essential for reducing amputations and improving patients' quality of life. Regular follow‐up and early detection are vital for effective DFU management, emphasizing the need for ongoing research and investment in LMIC health care infrastructure. Embracing these multidisciplinary, patient‐centered approaches can effectively address the challenge of DFUs in LMICs, leading to better patient outcomes and improved quality of life.

Predicting delays in metro and tram services is a complex task that requires advanced approaches, such as powerful machine learning tools. This study addresses this topic by applying the XGBoost and Bayesian Optimization (BO) algorithms, which offer a prediction horizon of 15 minutes instead of the next-station prediction, which leaves a very short time for the operator to react if we want to use the prediction for the next station. Our research strongly emphasizes methodological validation, with daily evaluations against real-time data. This process is reinforced by collaboration with the Operational Control Center (OCC) to ensure robustness. The 15-minute delay strikes a balance, giving control center operators sufficient notice to orchestrate traffic management, mitigate disruption, and take timely action. With an exemplary real-world accuracy of 95%, the results of our model have been validated by the OCC. Future efforts will include the seamless integration of predictive capabilities into real-time display systems for the OCC, providing innovative information to optimize traffic flows and ensure punctuality in urban rail systems.

Abstract Background The Russia-Ukraine war has undeniably impacted global science and healthcare in Ukraine. Many Ukrainian researchers have had their projects disrupted by this war, either due to loss of life, displacement, or destruction of resources. Despite these challenges, these researchers have sought to make their voices heard. This scoping review highlights the trend of healthcare-related publications on the current Russia-Ukraine war and characterizes the contribution of Ukrainian authors to these publications. Method A comprehensive literature search was performed using two databases (Scopus and Pubmed) for publications related to the ongoing Russia-Ukraine war. We included articles only related to healthcare. We then extracted and analyzed bibliometric data. Result One hundred and eighty-three articles were identified, including 12 (6.6%) original articles, 26 (14.2%) cross-sectional studies, 19 (10.4%) letters to the editor, 10 (5.5%) commentaries, 5 (2.7%) perspectives, 35 (19.1%) editorials, 2 (1.1%) randomized controlled trials, 11(6.0%) correspondences, 13 (7.1%) opinions, 8 (4.4%) reviews and 42 (23.0%) are identified as others. 180 (98.4%) studies were in English, and 3 (1.7%) were in German. 54 (29.5%) papers on the war had at least one author affiliated with a Ukrainian institution, and 29 (15.9%) studies had authors with Ukrainian affiliation as first authors. Conclusion our study shows that there has been a significant number of publications on the Russia-Ukraine war and only a small portion of first authors, co-authors, and last authors of these publications are affiliated to an institution in Ukraine. Therefore, despite the relatively high number of publications, most publications do not arise from the perspective of Ukrainian authors.

Abstract Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a transformative technology in neurological and neurosurgical research, revolutionising our comprehension of complex neurological disorders. In brain tumours, scRNA-seq has provided valuable insights into cancer heterogeneity, the tumour microenvironment, treatment resistance, and invasion patterns. It has also elucidated the brain tri-lineage cancer hierarchy and addressed limitations of current models. Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis have been molecularly subtyped, dysregulated pathways have been identified, and potential therapeutic targets have been revealed using scRNA-seq. In epilepsy, scRNA-seq has explored the cellular and molecular heterogeneity underlying the condition, uncovering unique glial subpopulations and dysregulation of the immune system. ScRNA-seq has characterised distinct cellular constituents and responses to spinal cord injury in spinal cord diseases, as well as provided molecular signatures of various cell types and identified interactions involved in vascular remodelling. Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. This review highlights the potential of scRNA-seq in guiding precision medicine approaches, identifying clinical biomarkers, and facilitating therapeutic discovery. However, challenges related to data analysis, standardisation, sample acquisition, scalability, and cost-effectiveness need to be addressed. Despite these challenges, scRNA-seq has the potential to transform clinical practice in neurological and neurosurgical research by providing personalised insights and improving patient outcomes.

Lithium-ion batteries are the most widely used as energy storage devices in electric mobility applications. However, due to complex electrochemical processes of battery degradation, it is challenging to predict accurately the battery end-of-life (EOL) to ensure their reliability, safety, and extended usage. In this context, the introduction of machine learning techniques can provide relevant solutions based on data collection and analysis. Indeed, we compared in this study the prediction performance of numerous machine learning approaches that predict if the battery EOL bypasses a predefined threshold. Based on the variation of different indicators during the first several hundred cycles, such as charge and discharge capacity, internal resistance, and energy efficiency, extensive numerical tests have been executed and compared in terms of accuracy score, precision score, recall score, etc. All the studied machine learning approaches are trained and validated using an open-access database of 124 commercial lithium iron phosphate/graphite cells cycled under different fast-charging conditions. As a result, the classification prediction performance score reached up to 98.74% depending on the percentage of data and cycles used for training and validation as well as the predefined EOL threshold. The comparative results can be used to improve the existing health-aware energy management strategy by taking the state-of-health (SOH) of batteries into consideration. Overall, the presented research findings are relevant to battery system reliability and safety engineering.

Introduction: Africa bears the largest burden of communicable and non-communicable diseases globally, yet it contributes only about 1 % of global research output, partly because of inaccessibility and low maintenance of medical data. Data is widely recognized as a crucial tool for improvement of population health. Despite the introduction of electronic health data systems in low-and middle-income countries (LMICs) to improve data quality, some LMICs still lack an efficient system to collect and archive data. This study aims to examine the underlying causes of data archive inaccessibility and poor maintenance in LMICS, and to highlight sustainable mitigation measures. Method: Authors conducted a comprehensive search on PubMed, Google scholar, organization websites using the search string “data archive” or “medical data” or “public health statistics” AND “challenges” AND “maintenance” AND “Low Middle Income Countries” or “LMIC”. to Identify relevant studies and reports to be included in our review. All articles related data archive in low and middle income countries were considered without restrictions due to scarcity of data. Result: Medical data archives in LMICs face challenges impacting data quality. Insufficient training, organizational constraints, and limited infrastructure hinder archive maintenance. To improve, support for public datasets, digital literacy, and technology infrastructure is needed. Standardization, cloud solutions, and advanced technologies can enhance data management, while capacity building and training programs are crucial. Conclusion: The creation and maintenance of data archives to facilitate the storage of retrospective datasets is critical to create reliable and consistent data to better equip the development of resilient health systems and surveillance of diseases in LMICs.

Hereditary spastic paraplegia is a genetically heterogeneous neurodegenerative disorder characterised primarily by muscle stiffness in the lower limbs. Neurodegenerative disorders are conditions that result from cellular and metabolic abnormalities, many of which have strong genetic ties. While ageing is a known contributor to these changes, certain neurodegenerative disorders can manifest early in life, progressively affecting a person’s quality of life. Hereditary spastic paraplegia is one such condition that can appear in individuals of any age. In hereditary spastic paraplegia, a distinctive feature is the degeneration of long nerve fibres in the corticospinal tract of the lower limbs. This degeneration is linked to various cellular and metabolic processes, including mitochondrial dysfunction, remodelling of the endoplasmic reticulum membrane, autophagy, abnormal myelination processes and alterations in lipid metabolism. Additionally, hereditary spastic paraplegia affects processes like endosome membrane trafficking, oxidative stress and mitochondrial DNA polymorphisms. Disease-causing genetic loci and associated genes influence the progression and severity of hereditary spastic paraplegia, potentially affecting various cellular and metabolic functions. Although hereditary spastic paraplegia does not reduce a person’s lifespan, it significantly impairs their quality of life as they age, particularly with more severe symptoms. Regrettably, there are currently no treatments available to halt or reverse the pathological progression of hereditary spastic paraplegia. This review aims to explore the metabolic mechanisms underlying the pathophysiology of hereditary spastic paraplegia, emphasising the interactions of various genes identified in recent network studies. By comprehending these associations, targeted molecular therapies that address these biochemical processes can be developed to enhance treatment strategies for hereditary spastic paraplegia and guide clinical practice effectively.

Craniosynostosis, marked by premature cranial suture fusion, necessitates prompt intervention to avert developmental, neurological, and aesthetic issues. While high-income countries have advanced in managing this condition, low- and middle-income countries grapple with substantial healthcare access disparities. This narrative review explores current craniosynostosis management in low- and middle-income countries. The review focused on studies published between 2008 and 2023. The focus was neurosurgical outcomes, and the search utilised databases like PubMed, EMBASE, Google Scholar, the Cochrane Library and Scopus, incorporating specific keywords and phrases. An in-depth analysis of 21 included studies reveals noteworthy positive outcomes, including low mortality, successful corrections and sustained efficacy. These advancements stem from enhanced pre-operative strategies, surgical techniques and postoperative care. Nonetheless, challenges persist, encompassing complications, mortality, reoperations, and treatment disparities, particularly in low- and middle-income countries constrained by financial and expertise limitations. The enhancement of clinical practice and the formulation of effective policies in the future entail several key strategies. These include the reinforcement of specialised healthcare infrastructure and diagnostic capabilities, the ongoing training and retention of neurosurgeons, the improvement of funding mechanisms, and the promotion of equitable access. Additionally, a crucial focus is placed on fortifying paediatric neurosurgical care in low- and middle-income countries. The recommendations underscore the importance of collaborative initiatives, the development of specialised healthcare infrastructure, and the implementation of strategic policies to not only advance pediatric neurosurgical care but also to address existing gaps in management.

Abstract Background and Aims Intracranial surgeries are pivotal in treating cerebral pathologies, particularly in resource‐limited contexts, utilizing techniques such as craniotomy, transsphenoidal approaches, and endoscopy. However, challenges in low and middle income countries (LMICs), including resource scarcity, diagnostic delays, and a lack of skilled neurosurgeons, lead to elevated perioperative mortality (POM). This review seeks to identify major contributors to these challenges and recommend solutions for improved patient outcomes in neurosurgical care within LMICs. Methods This review examines POM in LMICs using a detailed literature search, focusing on studies from these regions. Databases like PubMed, EMBASE, and Google Scholar were utilized using specific terms related to “intracranial surgery,” “perioperative mortality,” “traumatic brain injuries,” and “LMICs.” Inclusion criteria covered various study designs and both pediatric and adult populations while excluding stand‐alone abstracts and case reports. Results POM rates for intracranial surgeries differ widely across many low and middle‐income regions: Africa sees rates from 2.5% to 39.1%, Asia between 3.6% and 34.8%, and Latin America and the Caribbean have figures ranging from 1.3% to 12%. The POM rates in LMICs were relatively higher compared to most first‐world countries. The high POM rates in LMICs can be attributed to considerable delays and compromises in neurosurgical care delivery, exacerbated by late diagnoses and presentations of neurosurgical pathologies. This, coupled with limited resources, underdeveloped infrastructure, and training gaps, complicates intracranial disease management, leading to elevated POM. Conclusion Intracranial POM is a pronounced disparity within the neurosurgical field in LMICs. To mitigate intracranial POM, it is imperative to bolster healthcare infrastructure, amplify personnel training, foster global partnerships, and harness technologies like telemedicine. Tackling socioeconomic obstacles and prioritizing early detection through sustained funding and policy shifts can substantially enhance patient outcomes.

Neurological disorders during pregnancy are a substantial threat to women’s health, particularly in low- and middle-income countries. Furthermore, a critical shortage of mental health workers and neurologists exacerbates the already pressing issue, where a lack of coordination of respective healthcare among multidisciplinary teams involved in managing these conditions perpetuates the current state of affairs. Financial restrictions and societal stigmas associated with neurological disorders in pregnancy amplify the situation. Addressing these difficulties would necessitate a multifaceted approach comprising investments in healthcare infrastructure, healthcare professional education and training, increased government support for research, and the implementation of innovative care models. Improving access to specialized treatment and coordinated management of antenatal neurological diseases will precipitate improved health outcomes for women and their families in low- and middle-income countries.

Abstract Introduction The introduction of the diphtheria−tetanus−pertussis (DTP) vaccine into childhood immunization programs resulted in its widespread elimination in high‐income countries. However, Nigeria is currently experiencing an outbreak. The primary cause of diphtheria outbreaks and its high mortality rates in Nigeria was waning herd immunity due to low DTP coverage and a lack of diphtheria antitoxin (DAT), respectively. However, the underlying causes of Nigeria's low DTP coverage and DAT supply remain unknown. Method Relevant studies and reports included in our review were obtained by a search through Google Scholar, PubMed, and organization websites using the terms “Diphtheria−Pertussis−Tetanus vaccine OR Diphtheria antitoxin and Nigeria OR Diphtheria Outbreak.” All articles considering diphtheria outbreaks, DTP vaccine, and DAT supply in Nigeria were considered without time restriction due to the paucity of data. We used the narrative synthesis approach to critically appraise, analyze, and draw inferences from the selected articles. Results The main causes of low DTP coverage are insufficient supply, an inefficient cold chain system, and low uptake due to poor health literacy and negative sociocultural and religious beliefs, whereas the key barriers to DAT availability are insufficient production by pharmaceutical industries because of low demand and priority. Conclusion The underlying causes of Nigeria's low DTP coverage and DAT supply are multifactorial. Both short‐term and long‐term measures are needed to control this outbreak and prevent future occurrences.

The increase of world energy demand contributes to the development of renewable energy sources. Fuel cells, which use hydrogen to deliver energy, have seen a promising future. Fuel cells have been investigated since the last 50 years but they are still relatively absent for the commercial use due to the large exploitation cost and poor durability. One of the reasons is that the health state of a running fuel cell is hard to evaluate due to the system complexity and insufficient data. To tackle this problem, this paper proposes a data-driven fuel cell performance prediction method based on transfer learning and dynamic time warping. Historical data is trained in the source domain to build a model that can be transferred to the target domain and can be fine-tuned with only a small volume of online measurement. To improve the model recognition, dynamic time warping technology is applied to quantify the similarity between two different time series so that similar instances can be selected to build the neural network prediction model. Results show that, compared to traditional prediction method, the proposed prediction method has improved the prediction accuracy by almost 50%.

The global refugee community, including those forced to flee due to persecution, conflict, or violence, faces significant challenges in accessing healthcare, resulting in a higher prevalence of surgical disease. These challenges have a profound impact on morbidity and mortality rates, particularly in low- and middle-income countries where many immigrants seek refuge. Limited availability of medical facilities, an inadequate surgical workforce, financial constraints and linguistic and cultural barriers all contribute to reduced access to healthcare. Limited access to competent healthcare leads to poor health outcomes, increased morbidity and mortality rates and suboptimal surgical results for refugees. To address these challenges, a multifaceted approach is necessary. This includes increased funding for healthcare initiatives, workforce recruitment and training and improved coordination between aid organisations and local healthcare systems. Strategies for managing surgical conditions in the global refugee community encompass the development of targeted public health programmes, removing legal barriers, establishing healthcare facilities to enhance surgical access and prioritising disease prevention among refugees.

Intracranial aneurysms, affecting 2%–5% of the population, pose a significant challenge to neurosurgeons due to their potential to cause subarachnoid haemorrhage and high mortality rates. Intraoperative angiography is necessary for effective surgical planning and indocyanine green video angiography (ICG-VA) has emerged as a useful tool for real-time visualization of aneurysmal blood flow, aiding in better planning for potential blood flow and detection of aneurysm remnants. This mini narrative review explores the application of ICG-VA in intracranial aneurysm surgery. Compared with conventional dye-based angiography, ICG-VA is safer, more effective and more cost-effective. It can assess haemodynamic parameters, cerebral flow during temporary artery occlusion, completeness of clipping and patency of branch vessels. However, implementing ICG-VA in low- and middle-income countries presents challenges such as financial constraints, limited access to training and expertise, patient selection and consent issues. Addressing these obstacles requires capacity-building, training programmes for neurosurgeons and multidisciplinary teams, technology transfer, equipment donations, public–private partnerships, continued research and development, reducing conventional dye usage, reducing ICG wastage, exploring mechanisms to reuse ICG dyes and advocating for increased government funding and healthcare budgets.

Introduction: Diabetes mellitus (DM) is considered as a group of metabolic diseases with a global distribution and severe complications. It is caused by insulin deficiency, which with time leads to development of pathological changes in the cardiovascular, respiratory, and other systems. Several studies have shown some features and the connection of structural changes of the lungs with DM, however very little is known regarding ultrastructural changes of type 2 alveolocytes (AT2). Materials and methods: The study involved 24 white non-linear male laboratory rats which were divided into two groups (experimental and intact). The experimental group was further divided into two subgroups depending on the duration of study: the first group with hyperglycemia for 30 days, and the second with hyperglycemia for 60 days. For the experimental modeling of hyperglycemia, the rats were injected once subcutaneously with solution of alloxan monohydrate hyperglycemia. Results: AT2 of the intact group had a high degree of differentiation with plates of high electron density. In AT2 of rats with hyperglycemia for 30 days, there were signs of vacuolation, mass accumulation of primary and secondary lysosomes, and lamellar bodies were grouped as conglomerates. In AT2 of the rats with 60 days of hyperglycemia, nuclei with scalloped contour, karyoplasmic outgrowths and intussusception, and condensation of heterochromatin were observed. Conclusion: Under conditions of experimental chronic hyperglycemia, proliferation and destruction of AT2 are observed, which is the morphological basis for the violation of surfactant synthesis and immunocompetent properties in lung tissues of young rats.

Abstract Background and Aims Prostate cancer imposes a significant health burden, particularly in South America with its high incidence and mortality rates. This article explores the emergence of robot‐assisted radical prostatectomy (RARP) as a potential solution in the region. Methods This study relies on a comprehensive review of relevant literature. The analysis highlights the advantages of RARP, identifies impediments to its implementation, and proposes strategies to overcome these barriers. Results RARP demonstrates notable benefits, including improved functional outcomes, reduced complications, and minimized incisions. However, the integration of RARP in South America is hindered by challenges such as regional disparities, financial limitations, and data gaps. Limited healthcare infrastructure and a scarcity of skilled professionals further compound the issues. Conclusion Despite its potential, RARP faces obstacles to widespread adoption in South America. Strategic solutions encompassing technology investment, healthcare infrastructure enhancement, and workforce training are imperative. Overcoming these challenges can establish RARP as a crucial tool in managing prostate cancer in the region, ultimately enhancing patient care and treatment outcomes.

This study presents a decision-support methodology to design and optimize modular Boost converters in the context of fuel-cell electric vehicles. It involves the utilization of interleaved techniques to reduce fuel-cell current ripple, enhance system efficiency, tackle issues related to weight and size concerns, and offer better flexibility and modularity within the converter. The methodology incorporates emerging technologies by wide-bandgap semiconductors, providing better efficiency and higher temperature tolerance. It employs a multiphysical approach, considering electrical, thermal, and efficiency constraints to achieve an optimal power architecture for FCHEVs. Results demonstrate the advantages of wide-bandgap semiconductor utilization in terms of volume reduction and efficiency enhancements for different power levels. Results from one of the considered power levels highlight the feasibility of certain architectures through the utilization of WBG devices. These architectures reveal improvements in both efficiency and volume reduction as a result of incorporating WBG devices. Additionally, the analysis presents a comparison of manufacturing cost between standard and wide-bandgap semiconductors to demonstrate the market penetration potential.

Parkinson’s disease is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms, including hallucinations. The use of antipsychotic medications is a common strategy to manage hallucinations associated with Parkinson’s disease psychosis (PDP). However, careful consideration is necessary when selecting the most appropriate drug due to the potential risks associated with the available treatment options. Atypical antipsychotics (AAPs), such as Pimavanserin and Clozapine, have effectively controlled PDP symptoms. On the contrary, the support for utilizing quetiapine is not as substantial as other antipsychotics because research studies specifically investigating its application are still emerging and relatively recent. The broad mechanisms of action of AAPs, involving dopamine and serotonin receptors, provide improved outcomes and fewer side effects than typical antipsychotics. Conversely, other antipsychotics, including risperidone, olanzapine, aripiprazole, ziprasidone, and lurasidone, have been found to worsen motor symptoms and are generally not recommended for PDP. While AAPs offer favorable benefits, they are associated with specific adverse effects. Extrapyramidal symptoms, somnolence, hypotension, constipation, and cognitive impairment are commonly observed with AAP use. Clozapine, in particular, carries a risk of agranulocytosis, necessitating close monitoring of blood counts. Pimavanserin, a selective serotonin inverse agonist, avoids receptor-related side effects but has been linked to corrected QT (QTc) interval prolongation, while quetiapine has been reported to be associated with an increased risk of mortality. This review aims to analyze the benefits, risks, and mechanisms of action of antipsychotic medications to assist clinicians in making informed decisions and enhance patient care.

In this paper, a fuzzy sliding mode controller (FSMC) with adaptive gain is proposed for a class of MIMO nonlinear systems. The coupled system can be divided into two different subsystems, each of which can be separated into two sliding surfaces created by the state variables. The integration of these two sliding surfaces requires the introduction of an intermediary variable. In order to ensure that the control system is stable, the adaptive gain is derived using the Lyapunov method. The synthesized fuzzy sliding mode control with adaptive gain is applied to an inverted pendulum to illustrate the suggested control technique. The performance and robustness of the proposed controller are compared, terms of time, with those of provided by fuzzy sliding mode controller. This comparison reveals the superiority of the proposed method over the fuzzy sliding mode controller, in terms of the system stabilization and tracking of the trajectory.

Understanding the failure modes of damaged or cracked structures and repaired by bonding a composite patch is an essential point to improve its resistance to failure and subsequently extend its service life. In the present study, a 3D finite element analysis using ANSYS software was performed to elucidate the failure modes of the repaired structures by double and single sided bonded composite. The plate is represented by an aluminum plate (Al2024 T3), cracked at the edge and repaired by three types of laminates, with different fiber orientation in order to determine its effect on the repair. The contact interfaces patch-adhesive and aluminum-adhesive were modeled by cohesive zone modeling (CZM) using bilinear interface of delamination (BID) method to determine the failure at the adhesive layer. The obtained results show the importance of the impact of the composite patch fiber orientation on the structure design for suitable repair

Abstract Craniomaxillofacial trauma (CMFT) is a type of injury that affects the face, neck, and scalp, and includes facial bone fractures, dentoalveolar trauma, and soft tissue injuries. Work, traffic accidents, sports, and daily activities commonly cause these injuries. However, they are widespread in war‐torn countries where armed conflict leads to a high incidence of CMFT. The lack of resources, health care infrastructure, and surgical personnel in these areas result in subpar treatment and poor patient outcomes, contributing to the high mortality and morbidity rates among war victims. The importance of a multidisciplinary approach to CMFT management cannot be overstated, but current obstacles, such as a lack of access to proper medical care and rehabilitation services, impede the development of effective treatments. CMFT treatment is complex and prohibitively expensive for war‐torn nations to afford, necessitating international intervention to provide life‐saving surgical procedures for those suffering from CMFT in conflict zones. Despite efforts to improve CMFT treatments in war‐torn countries, more must be done to improve treatment outcomes. Data collection and research must also be improved in order to develop effective evidence‐based treatment methods.

Renewable energy sources (RESs) such as solar photovoltaic (PV) systems are increasingly used as distributed generation for replacing the conventional energy. At the same time, energy storage systems like battery (BAT) must be applied for maintaining the balance between fluctuating energy production and load consumption. BAT’s state of charge (SOC) should be maintained within their design limits unaffected by RES intermittency and/or load power variations. This necessitates advanced power control and management methodologies for overcoming challenging conditions. This paper discusses and evaluates an optimal DC bus voltage regulation approach: an intelligent controller using an adaptive fuzzy logic controller (FLC) and a novel supervisory power management strategy for PV systems with BAT. The objectives are to keep a stable power flow in the system and guarantee the continuity of service by ensuring that the system components do not exceed their limits. In this manner, the DC bus voltage regulation of the PV/BAT system can be improved in comparison with conventional regulation. Therefore, the most important contributions of this work are as follows. (1) Development of comprehensive and modular novel energy management system (EMS): its originality is related to the inclusion of the control system limits with faster SOC balancing and smaller DC bus voltage fluctuation. (2) Providing a simple power flow management implementation that considers the optimal energy flow between PV system, BAT system, and load: a balance between minimal energy flow in the connecting line and the least requirements of BAT capacity is kept, reducing component constraints with a very straightforward structure. (3) Furthermore, FLC offers high robustness and smooth performances. FLC is added to the control strategy design requirements to reduce DC bus voltage deviation. (4) Real-time simulation/experimentation-based complete cases utilizing Matlab/Simulink and DSpace are illustrated to testify the effectiveness of the proposed FLC and EMS.

This article proposes a quantitative method for the identification and assessment of geological and geomorphological sites in the Tagleft syncline. This method proposes new criteria of evaluation relatively in conformity with the characteristics of the Moroccan mountain by making reference to the various methods which were already carried out in the European countries. The objective is thus to reduce the subjectivity of the evaluator, to clarify deeply the criteria composing the assessment values (scientific value, additional values and use value). This method is finally applied on the geological and geomorphological sites of the syncline of Tagleft, Atlas of Beni Mellal, Morocco.

Dans cette article, une étude expérimentale est réalisée afin d'évaluer l'effet de matériau de revêtement sur les performances desoutils de coupe en tournage de l’acier 42 CrMo4. Une étude comparative a été réalisée entre deux outils en carbure de même géométrie ;le premier non revêtu et le second revêtu en CVD1. Le procédé ANOVA a été utilisé pour quantifier les effets des paramètres de coupesur l’état des surfaces obtenues. L’effet des couches de revêtement sur la qualité de surface est également étudié. On observe qu’uneplus faible rugosité de surface est obtenue lors de l’utilisation de plaquettes revêtues.

The approach presented in this paper addresses the machining process optimization problem through realistic modeling of multi-pass operations. It is designed to determine, at the same time, the number of passes and the cutting conditions of each. This is a multi-objective optimization model that simultaneously minimizes the production rate and the used tool life under all technological and organizational constraints based on fundamental cutting laws. The posterior selection of a solution is made from a Pareto front generated by a multi-objective particle swarm algorithm based on the concept of dynamic neighborhood. In an example application which consists in determining the cutting conditions for a turning operation, using this approach has provided a rich set of Pareto optimal solutions that represents all possible compromises. This set offers, normally, all the information needed for the optimal selection of cutting conditions. Despite the complexity of treated problem, the analysis of the obtained results demonstrates the effectiveness of the developed approach. Thus, it presents the possibility of using this approach for other problems from industry.

This paper proposes a modular modeling towards a health system integration of fuel cells by considering not only the dynamics of the gases but also fault models that affect the PEMFC performances. The main goal is to simulate the faulty state in order to overcome data scarcity, since running a fuel cell to generate a database under faulty conditions is a costly process in time and resources. The degradation processes detailed in this paper allow to introduce a classification of faults that can occur, giving a better understanding of the performance losses necessary to simulate them. The faults that are detailed and modeled are the flooding, drying and aging processes. This modeling is based on a system approach, so it runs faster than real-time degradation tests, allowing the training and validation of online supervisors, such as the energy management strategy (EMS) method or diagnosis. The faults are reproduced according to the study requirements to be a very effective support tool to help design engineers to include faulty conditions in early design stages toward a diagnosis process and health-conscious energy management strategies.

This paper proposes a design methodology that is dedicated to improving the concept of a modular hybrid power chain that uses interleaved converters. The approach involves optimising the system under multi-physical constraints, where the number of cells in the interleaved converters is considered as a key modular parameter. The methodology uses analytical models to strike a balance between computation time and result accuracy. This compromise is indispensable to the construction of a smart design approach under multi-physical constraints, such as electric, efficiency, volume, and thermal constraints. The proposed approach has been applied to a hybrid fuel cell and battery power system for automotive applications; the goal is to obtain a global optimal architecture chain by optimising the number of interleaved converter cells and by determining appropriate power electronics components and the optimal sizing of sources. This constitutes the primary step for providing an effective pre-design support tool for considering architecture modularity, facilitating the use of new technologies in the early design stage. The results showed that the interleaving concept allows for better flexibility in respecting the design constraints to improve the design of hybrid power systems. The analysis also highlights the current limitations and performance of the optimisation method and suggests new areas for future work.

Hard turning is a machining process that is widely used in the precision mechanical industry. The characterization of the functional surface texture by the ISO 13565 standard holds a key role in automotive mechanics. Until now, the impact of cutting conditions during hard turning operation on the bearing area curve parameters has not been studied (ISO 13565). The three parameters Rpk , Rk and Rvk illustrate the ability of the surface texture to resist friction. In this work, the main objective is to study the impact of cutting conditions (Vc, f and ap) of the hard turning on three parameters of the bearing area curve. The statistical study based on response surface methodology (RSM), analysis of variance (ANOVA) and quadratic regression were performed to model the three output parameters and optimize the input parameters. The experimental design used in this study is the Taguchi L25 orthogonal array. The results obtained show that the cutting speed has a greater effect on the bearing ratio curve (Rpk , Rk and Rvk ) parameters with a percentage contribution of 37.68%, 37.65% and 36.91%, respectively. The second significant parameter is the feed rate and the other parameter is significant only in relation to Rpk and Rk parameters.