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Probing the chemical profiles and biological activities of medicinal plants is important for the discovery of new potent therapeutic products. Our study deciphers the chemical composition of the essential oils (EOs) obtained from three different flowers of Lantana camara and evaluates their antioxidant and anticancer activities. This work represents the first study of EOs obtained from this plant and is based particularly on the difference in flower color. In addition, no other reports dealing specifically with the antitumor effects of such flower-derived EOs have been described in the literature. The collected flowers, white, pink, and orange, were extracted by hydrodistillation to yield EO1, EO2, and EO3 respectively. Gas chromatography–mass spectroscopy was primarily employed to identify the existing volatile compounds in the samples. Their antioxidant activities were screened through both DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging assays and FRAP (ferric-reducing antioxidant power) assays. The antiproliferative effects were evaluated on two distinct breast cancer cell lines, MCF-7 and MDA-MB-231, and compared to a normal human breast cell line, MCF-10A, using an MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium) assay. All EOs showed notable antioxidant potential attributed to the active phytochemical compounds, with results being supported by a positive correlation between such activity and the total phenolic and flavonoid content. The most eminent, EO1, revealed a selective dose-dependent antiproliferative effect in both breast cancer cell lines, thus reflecting its potent role as an anticancer agent. We suggest that this highly selective activity is associated with the presence of bicyclogermacrene and epi-bicyclosesquiphellandrene in its chemical composition.

Objective: The precision of neuronavigation systems relies on the correct registration of the patient’s position in space and aligning it with radiological 3D imaging data. Registration is usually performed by the acquisition of anatomical landmarks or surface matching based on facial features. Another possibility is automatic image registration using intraoperative imaging. This could provide better accuracy, especially in rotated or prone positions where the other methods may be difficult to perform. The aim of this study was to validate automatic image registration (AIR) using intraoperative cone-beam computed tomography (CBCT) for cranial neurosurgical procedures and compare the registration accuracy to the traditional surface matching (SM) registration method based on preoperative MRI. The preservation of navigation accuracy throughout the surgery was also investigated. Methods: Adult patients undergoing intracranial tumor surgery were enrolled after consent. A standard SM registration was performed, and reference points were acquired. An AIR was then performed, and the same reference points were acquired again. Accuracy was calculated based on the referenced and acquired coordinates of the points for each registration method. The reference points were acquired before and after draping and at the end of the procedure to assess the persistency of accuracy. Results: In total, 22 patients were included. The mean accuracy was 6.6 ± 3.1 mm for SM registration and 1.0 ± 0.3 mm for AIR. The AIR was superior to the SM registration (p < 0.0001), with a mean improvement in accuracy of 5.58 mm (3.71–7.44 mm 99% CI). The mean accuracy for the AIR registration pre-drape was 1.0 ± 0.3 mm. The corresponding accuracies post-drape and post-resection were 2.9 ± 4.6 mm and 4.1 ± 4.9 mm, respectively. Although a loss of accuracy was identified between the preoperative and end-of-procedure measurements, there was no statistically significant decline during surgery. Conclusions: AIR for cranial neuronavigation consistently delivered greater accuracy than SM and should be considered the new gold standard for patient registration in cranial neuronavigation. If intraoperative imaging is a limited resource, AIR should be prioritized in rotated or prone position procedures, where the benefits are the greatest.

The risk–benefit analysis of ERP implementation is worth investigating to optimize the efficiency of ERP deployment in the construction sector. This study investigates the factors affecting the dissipation of ERP through diffusion models in developing countries. Moreover, it suggests a strategy to adopt ERP modules that optimize process integration and project efficiency through the priority factors method. According to the study, the internal model best describes the studied modules, and it suggests that imitative behavior and word of mouth significantly influence ERP adoption in the Africa and Middle East regions. This research concludes with an optimized order for deploying ERP modules based on the importance, urgency, and ease of implementation of each module. It is as follows: work progress (500), budgeting (405), procurement (343), site operations (280), planning and scheduling (270), accounting (252), inventory management (126), document control (90), and tendering (6). Therefore, it can be concluded that this study fills the research gap of ERP module adoption using diffusion models and priority factors within the construction industry, specifically in the specified regions. However, considering dynamic influence factors might provide more precise predictions, while involving a greater number of companies’ owners might highlight a greater importance of external factors.

Understanding the niche interactions between blood and bone through the in vitro co-culture of osteo-competent cells and endothelial cells is a key factor in unraveling therapeutic potentials in bone regeneration. This can be additionally supported by employing numerical simulation techniques to assess local physical factors, such as oxygen concentration, and mechanical stimuli, such as shear stress, that can mediate cellular communication. In this study, we developed a Mesenchymal Stem Cell line (MSC) and a Human Umbilical Vein Endothelial Cell line (HUVEC), which were co-cultured under flow conditions in a three-dimensional, porous, natural pullulan/dextran scaffold that was supplemented with hydroxyapatite crystals that allowed for the spontaneous formation of spheroids. After 2 weeks, their viability was higher under the dynamic conditions (>94%) than the static conditions (

Background The Africa Capacity Building Initiative (ACBI) programme aimed to ‘strengthen the research and training capacity of higher education institutions and support the development of individual scientists in sub-Saharan Africa through UK-Africa research collaborations’ including by funding PhD studentships. We conducted research to understand students’ experiences and to see how consortia-based programmes such as ACBI and their own institutions can enhance PhD students’ research environment and progress. Methods In-depth interviews with 35 ACBI-funded PhD students explored their perspectives about how their research and personal development benefitted from belonging to a research consortium. Questionnaires were used to corroborate interview findings. Results Students recognised that membership of a research consortium provided many benefits compared to less well-resourced peers. By drawing on the programme and consortiums’ resources, they were often able to overcome some limitations in their own institution’s systems and facilities. Through their consortia they could access a wide range of international expertise and support from mentors and colleagues for their technical and psychosocial needs. Multiple consortia opportunities for engaging with the international scientific community and for networking, gave them confidence and motivation and enhanced their career prospects. Conclusion Our study and its recommendations highlight how the breadth and diversity of resources available to PhD students through research consortia can be harnessed to facilitate students’ progress and to create a supportive and conducive research environment. It also underlines how, through a multi-level approach, consortia can contribute to longer-term improvements in institutional research environments for PhD students.

Background The Africa Capacity Building Initiative (ACBI) programme aimed to ‘strengthen the research and training capacity of higher education institutions and support the development of individual scientists in sub-Saharan Africa through UK-Africa research collaborations’ including by funding PhD studentships. We conducted research to understand students’ experiences and to see how consortia-based programmes such as ACBI and their own institutions can enhance PhD students’ research environment and progress. Methods In-depth interviews with 35 ACBI-funded PhD students explored their perspectives about how their research and personal development benefitted from belonging to a research consortium. Questionnaires were used to corroborate interview findings. Results Students recognised that membership of a research consortium provided many benefits compared to less well-resourced peers. By drawing on the programme and consortiums’ resources, they were often able to overcome some limitations in their own institution’s systems and facilities. Through their consortia they could access a wide range of international expertise and support from mentors and colleagues for their technical and psychosocial needs. Multiple consortia opportunities for engaging with the international scientific community and for networking, gave them confidence and motivation and enhanced their career prospects. Conclusion Our study and its recommendations highlight how the breadth and diversity of resources available to PhD students through research consortia can be harnessed to facilitate students’ progress and to create a supportive and conducive research environment. It also underlines how, through a multi-level approach, consortia can contribute to longer-term improvements in institutional research environments for PhD students.

The global impact of the SARS-CoV-2 pandemic has been unprecedented, posing a significant public health challenge. Chronological age has been identified as a key determinant for severe outcomes associated with SARS-CoV-2 infection. Epigenetic age acceleration has previously been observed in various diseases including human immunodeficiency virus (HIV), Cytomegalovirus (CMV), cardiovascular diseases, and cancer. However, a comprehensive review of this topic is still missing in the field. In this review, we explore and summarize the research work focusing on biological aging markers, i.e., epigenetic age and telomere attrition in COVID-19 patients. From the reviewed articles, we identified a consistent pattern of epigenetic age dysregulation and shortened telomere length, revealing the impact of COVID-19 on epigenetic aging and telomere attrition.

Objective: Limited data on the treatment and outcomes of patients with intracranial aneurysms (ICAs) in the (coronavirus disease 2019) COVID-19 era is available. Our objective was hence to investigate the impact of the pandemic on the overall complication rate and postprocedural ischemic strokes specifically, in patients treated for ICAs. Methods: The National Inpatient sample database was used. The main outcomes were the occurrence of postprocedural ischemic strokes, as well as death, non-routine discharge, total charges (US dollars), and length of stay (days). Propensity score matching was applied to compare the pre- and COVID-19 periods. Trends were assessed using piecewise joinpoint regression with the Mann-Kendall test. Results: A total of 57,715 patients were included in the study. The mean age was 65 years, with most of the patients (69.9 %) being females. After matching, no differences in length of stay (p = 0.266), non-home discharge (p = 0.475), and in-hospital mortality rates (p = 0.305) between the two periods were found. However, the overall complication rate was significantly higher during the pandemic (31.1 % vs. 28.3 %; p

Background and objectives Spontaneous spinal cord infarction (SCInf) is a rare condition resulting in acute neurological impairment. Consensus on diagnostic criteria is lacking, which may present a challenge for the physician. This review aims to analyse the current literature on spontaneous SCInf, focusing on epidemiology, the diagnostic process, treatment strategies and neurological outcomes.Methods The study was performed in accordance with a previously published protocol. PubMed, Web of Science and Embase were searched using the keywords ‘spontaneous’, ‘spinal cord’, ‘infarction’ and ‘ischaemic’. The eligibility of studies was evaluated in two steps by multiple reviewers. Data from eligible studies were extracted and systematically analysed.Results 440 patients from 33 studies were included in this systematic review. Analysis of vascular risk factors showed that hypertension was present in 40%, followed by smoking in 30%, dyslipidaemia in 29% and diabetes in 16%. The severity of symptoms at admission according to the American Spinal Injury Association (ASIA) Impairment Scale was score A 19%, score B14%, score C36% and score D32%. The mean follow-up period was 34.8 (±12.2) months. ASIA score at follow-up showed score A 11%, score B 3%, score C 16%, score D 67% and score E 2%. The overall mortality during the follow-up period was 5%. When used, MRI with diffusion-weighted imaging (DWI) supported the diagnosis in 81% of cases. At follow-up, 71% of the patients were able to walk with or without walking aids.Conclusion The findings suggest a significant role for vascular risk factors in the pathophysiology of spontaneous SCInf. In the diagnostic workup, the use of DWI along with an MRI may help in confirming the diagnosis. The findings at follow-up suggest that neurological recovery is to be expected, with the majority of patients regaining ambulation. This systematic review highlights gaps in the literature and underscores the necessity for further research to establish diagnostic criteria and treatment guidelines.

Abstract Background Aging has been reported as a major risk factor for severe symptoms and higher mortality rates in COVID-19 patients. Molecular hallmarks such as epigenetic alterations and telomere attenuation reflect the biological process of aging. Epigenetic clocks have been shown to be valuable tools for measuring biological age in various tissues and samples. As such, these epigenetic clocks can determine accelerated biological aging and time-to-mortality across various tissues. Previous reports have shown accelerated biological aging and telomere attrition acceleration following SARS-CoV-2 infection. However, the effect of accelerated epigenetic aging on outcome (death/recovery) in COVID-19 patients with acute respiratory distress syndrome (ARDS) has not been well investigated. Results In this study, we measured DNA methylation age and telomere attrition in 87 severe COVID-19 cases with ARDS under mechanical ventilation. Furthermore, we compared dynamic changes in epigenetic aging across multiple time points until recovery or death. Epigenetic age was measured using the Horvath, Hannum, DNAm skin and blood, GrimAge, and PhenoAge clocks, whereas telomere length was calculated using the surrogate marker DNAmTL. Our analysis revealed significant accelerated epigenetic aging but no telomere attrition acceleration in severe COVID-19 cases. In addition, we observed epigenetic age deceleration at inclusion versus end of follow-up in recovered but not in deceased COVID-19 cases using certain clocks. When comparing dynamic changes in epigenetic age acceleration (EAA), we detected higher EAA using both the Horvath and PhenoAge clocks in deceased versus recovered patients. The DNAmTL measurements revealed telomere attrition acceleration in deceased COVID-19 patients between inclusion and end of follow-up and a significant change in dynamic telomere attrition acceleration when comparing patients who recovered versus those who died. Conclusions EAA and telomere attrition acceleration were associated with treatment outcomes in hospitalized COVID-19 patients with ARDS. A better understanding of the long-term effects of EAA in COVID-19 patients and how they might contribute to long COVID symptoms in recovered individuals is urgently needed.

Abstract The increasing prevalence of type 2 diabetes mellitus (T2DM) and its associated health complications highlight the need to develop predictive models for early diagnosis and intervention. While many artificial intelligence (AI) models for T2DM risk prediction have emerged, a comprehensive review of their advancements and challenges is currently lacking. This scoping review maps out the existing literature on AI-based models for T2DM prediction, adhering to the PRISMA extension for Scoping Reviews guidelines. A systematic search of longitudinal studies was conducted across four databases, including PubMed, Scopus, IEEE-Xplore, and Google Scholar. Forty studies that met our inclusion criteria were reviewed. Classical machine learning (ML) models dominated these studies, with electronic health records (EHR) being the predominant data modality, followed by multi-omics, while medical imaging was the least utilized. Most studies employed unimodal AI models, with only ten adopting multimodal approaches. Both unimodal and multimodal models showed promising results, with the latter being superior. Almost all studies performed internal validation, but only five conducted external validation. Most studies utilized the area under the curve (AUC) for discrimination measures. Notably, only five studies provided insights into the calibration of their models. Half of the studies used interpretability methods to identify key risk predictors revealed by their models. Although a minority highlighted novel risk predictors, the majority reported commonly known ones. Our review provides valuable insights into the current state and limitations of AI-based models for T2DM prediction and highlights the challenges associated with their development and clinical integration.

Background The Africa Capacity Building Initiative (ACBI) programme aimed to ‘strengthen the research and training capacity of higher education institutions and support the development of individual scientists in sub-Saharan Africa through UK-Africa research collaborations’ including by funding PhD studentships. We conducted research to understand students’ experiences and to see how consortia-based programmes such as ACBI and their own institutions can enhance PhD students’ research environment and progress. Methods In-depth interviews with 35 ACBI-funded PhD students explored their perspectives about how their research and personal development benefitted from belonging to a research consortium. Questionnaires were used to corroborate interview findings. Results Students recognised that membership of a research consortium provided many benefits compared to less well-resourced peers. By drawing on the programme and consortiums’ resources, they were often able to overcome some limitations in their own institution’s systems and facilities. Through their consortia they could access a wide range of international expertise and support from mentors and colleagues for their technical and psychosocial needs. Multiple consortia opportunities for engaging with the international scientific community and for networking, gave them confidence and motivation and enhanced their career prospects. Conclusion Our study and its recommendations highlight how the breadth and diversity of resources available to PhD students through research consortia can be harnessed to facilitate students’ progress and to create a supportive and conducive research environment. It also underlines how, through a multi-level approach, consortia can contribute to longer-term improvements in institutional research environments for PhD students.

Objective: Deep endometriosis (DE) is the most severe form of endometriosis. Bowel and urinary tract are the most common sites of intrapelvic DE. Urinary tract endometriosis (UTE) mainly involves the bladder and the ureters. The two mostly accepted theories explaining the pathophysiology of UTE are the “Retrograde Menstruation Theory” and the “Müllerian Remnants Theory”. The purpose of this paper is to provide a review of literature on the UTE, a rare form, affecting only 1–6% of patients with endometriosis. Mechanism: A literature review was conducted using keywords specific to UTE and DE to identify peer-reviewed, original research articles published between 1996 and 2024. Findings in Brief: When the bladder is involved, the patient presents lower urinary tract symptoms. Ureteral endometriosis is usually asymptomatic, thus delaying early diagnosis and efficient treatment leading to cases of chronic ureteral stricture. Clinical history and examination as well as questionnaires play an important role in guiding the clinician. Diagnostic modalities include conventional imaging such as ultrasonography and magnetic resonance imaging (MRI) as well as invasive techniques such as cystoscopy. As for all endometriotic lesions, definitive diagnosis should be confirmed by histopathology. Treatment modalities include medical hormonal treatments or surgical treatment. There are a multitude of surgical techniques that are more or less invasive depending on the location and the extent of the lesion. Conclusions: UTE, is an underdiagnosed form of endometriosis, and specialists should be aware of this important entity, due to the serious health implications for women.

This study builds on our previous systematic literature review (SLR) that assessed the applications and performance of zk-SNARK, zk-STARK, and Bulletproof non-interactive zero-knowledge proof (NIZKP) protocols. To address the identified research gaps, we designed and implemented a benchmark comparing these three protocols using a dynamic minimized multiplicative complexity (MiMC) hash application. We evaluated performance across four general-purpose programming libraries and two programming languages. Our results show that zk-SNARK produced the smallest proofs, while zk-STARK generated the largest. In terms of proof generation and verification times, zk-STARK was the fastest, and Bulletproof was the slowest. Interestingly, zk-SNARK proofs verified marginally faster than zk-STARK, contrary to other findings. These insights enhance our understanding of the functionality, security, and performance of NIZKP protocols, providing valuable guidance for selecting the most suitable protocol for specific applications.

Software-Defined Networking (SDN) revolutionizes network management by decoupling control plane functionality from data plane devices, enabling the centralized control and programmability of network behavior. This paper uses the ternary system to improve the Central Processing Unit (CPU) inside the SDN controller to enhance network management. The Multiple-Valued Logic (MVL) circuit shows remarkable improvement compared to the binary circuit regarding the chip area, propagation delay, and energy consumption. Moreover, the Carbon Nanotube Field-Effect Transistor (CNTFET) shows improvement compared to other transistor technologies regarding energy efficiency and circuit speed. To the best of our knowledge, this is the first time that a ternary design has been applied inside the CPU of an SDN controller. Earlier studies focused on Ternary Content-Addressable Memory (TCAM) in SDN. This paper proposes a new 1-trit Ternary Full Adder (TFA) to decrease the propagation delay and the Power–Delay Product (PDP). The proposed design is compared to the latest 17 designs, including 15 designs that are 1-trit TFA CNTFET-based, 2-bit binary FA FinFET-based, and 2-bit binary FA CMOS-based, using the HSPICE simulator, to optimize the CPU utilization in SDN environments, thereby enhancing programmability. The results show the success of the proposed design in reducing the propagation delays by over 99% compared to the 2-bit binary FA CMOS-based design, over 78% compared to the 2-bit binary FA FinFET-based design, over 91% compared to the worst-case TFA, and over 49% compared to the best-case TFAs.