Computer-assisted System Research Articles

A Cross-Sectional Survey Exploring the Willingness of Hong Kong People to Use Teleconsultation in Primary Care During the COVID-19 Pandemic.

Objectives: To investigate the willingness of the general Hong Kong population to use teleconsultation in primary care and the factors affecting their decisions and to ascertain the medical problems for which people will consider using teleconsultation in primary care. The study was a cross-sectional territory-wide random population survey on adults recruited through a computer-assisted telephone interview system. Outcome Measures: Outcomes were the proportion of the general Hong Kong population indicating their willingness to use teleconsultation in primary care; the drivers and barriers affecting their willingness; and the medical problems in primary care for which people would consider using teleconsultation. Results: After applying population weighting, 51.6% of the study respondents were found to be willing to use teleconsultation in primary care. The main drivers were possessing the perception that teleconsultation would serve the majority of their health problems (odds ratio [OR] = 3.693, p < 0.001), provision of government subsidy (OR = 3.567, p < 0.001), and ownership of a computer/tablet (OR = 2.116, p < 0.001). A major barrier for people's reluctance to use teleconsultation in primary care was having an education level of primary or below (OR = 0.388, p = 0.002). The majority of people had reasonable expectations on which medical conditions teleconsultation could be helpful but misunderstandings did exist. Conclusion: Our survey estimated that more than half of the general Hong Kong population was willing to use teleconsultation in primary care. Health care service providers and the government should address the drivers and barriers and clarify any misconceptions if teleconsultation is to be further developed in the Hong Kong primary care system.

Employing Xception convolutional neural network through high-precision MRI analysis for brain tumor diagnosis

The classification of brain tumors from medical imaging is pivotal for accurate medical diagnosis but remains challenging due to the intricate morphologies of tumors and the precision required. Existing methodologies, including manual MRI evaluations and computer-assisted systems, primarily utilize conventional machine learning and pre-trained deep learning models. These systems often suffer from overfitting due to modest medical imaging datasets and exhibit limited generalizability on unseen data, alongside substantial computational demands that hinder real-time application. To enhance diagnostic accuracy and reliability, this research introduces an advanced model utilizing the Xception architecture, enriched with additional batch normalization and dropout layers to mitigate overfitting. This model is further refined by leveraging large-scale data through transfer learning and employing a customized dense layer setup tailored to effectively distinguish between meningioma, glioma, and pituitary tumor categories. This hybrid method not only capitalizes on the strengths of pre-trained network features but also adapts specific training to a targeted dataset, thereby improving the generalization capacity of the model across different imaging conditions. Demonstrating an important improvement in diagnostic performance, the proposed model achieves a classification accuracy of 98.039% on the test dataset, with precision and recall rates above 96% for all categories. These results underscore the possibility of the model as a reliable diagnostic tool in clinical settings, significantly surpassing existing diagnostic protocols for brain tumors.

Evaluating Alternative Registration Planes in Imageless, Computer-Assisted Navigation Systems for Direct Anterior Total Hip Arthroplasty.

(1) Background: Imageless computer navigation systems have the potential to improve the accuracy of acetabular cup position in total hip arthroplasty (THA). Popular imageless navigation methods include locating the patient in a three-dimensional space (registration method) while using a baseline to angle the acetabular cup (reference plane). This study aims to compare the accuracy of different methods for determining postoperative acetabular cup positioning in THA via the direct anterior approach. (2) Methods: Fifty-one participants were recruited. Optical and inertial sensor imageless navigation systems were used simultaneously with three combinations of registration methods and reference planes: the anterior pelvic plane (APP), the anterior superior iliac spine (ASIS) and the table tilt (TT) method. Postoperative acetabular cup position, inclination, and anteversion were assessed using CT scans. (3) Results: For inclination, the mean absolute error (MAE) was lower using the TT method (2.4° ± 1.7°) compared to the ASIS (2.8° ± 1.7°, p = 0.17) and APP method (3.7° ± 2.1°, p < 0.001). For anteversion, the MAE was significantly lower for the TT method (2.4° ± 1.8°) in contrast to the ASIS (3.9° ± 3.2°, p = 0.005) and APP method (9.1° ± 6.2°, p < 0.001). (4) Conclusion: A functional reference plane is superior to an anatomic reference plane to accurately measure intraoperative acetabular cup inclination and anteversion in THA using inertial imageless navigation systems.

Comparison of Implant Placement Accuracy Between Manual, Robot-Assisted, Computer-Navigated, Augmented Reality Navigated, Patient-Specific Instrumentation, and Accelerometer Navigated Total Hip Arthroplasty: A Systematic Review and Network Meta-Analysis.

Malpositioning of the acetabular cup during total hip arthroplasty (THA) can lead to complications. Robotic surgery and navigation techniques aim to address this issue, but there is limited evidence regarding which method can achieve better clinical outcomes. Therefore, this network meta-analysis (NMA) aimed to compare the efficacy of various navigation methods. This NMA of prospective randomized controlled trials compared robot-assisted systems (RAS), computer-assisted navigation systems (CAS), augmented reality-based portable navigation (AR), patient-specific instrumentation (PSI), portable accelerometer-based navigation (PN), and conventional methods (C) for THA procedures. We searched MEDLINE, EMBASE, Cochrane, Central Register of Controlled Trials, International Clinical Trials Platform Search Portal, and ClinicalTrials.gov. databases. The primary outcomes included revision surgery and postoperative clinical scores, and the secondary outcomes encompassed cup placement accuracy, acetabular cup placement outliers from the Lewinnek safe zone, surgical time, and complications. We used a Bayesian random-effects NMA, and confidence of evidence was assessed using confidence in NMA. We identified 45 studies including 2,122 patients. We did not find large differences in revision surgery, clinical outcome scores, cup inclination, or anteversion angle accuracy among the modalities. AR, CAS, and PSI exhibited a lower risk of outliers from safe zones than C. In addition, RAS and CAS had a longer surgical time than C. Robotic and navigation tools did not reduce the revision risk or enhance clinical outcomes. AR, CAS, PSI, and PN may decrease the risk of cup placement outliers in safe zones. However, the cup placement accuracy was equivalent, and the surgical time may be longer in RAS and CAS than in C. Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.

Analysis of stallion spermatozoa metabolism using Agilent Seahorse XFp Technology

Sperm metabolism consists of a sophisticated network of biochemical reactions and varies between species, resulting in different metabolic strategies for ATP production to maintain sperm functionality. ATP can be produced through glycolysis or in the mitochondria by oxidative phosphorylation (OXPHOS). Since OXPHOS is the predominant metabolic pathway in horses spermatozoa, various assessments of mitochondrial activity are used to evaluate fertility, utilizing techniques such as fluorescent probes analysed via microscopy or flow cytometry, and polarographic electrode assays to measure current flow in response to an applied voltage. Though, these methods are limited by low throughput, as they assess mitochondrial activity at a single time point under a specific treatment condition. This study explores, for the first time, the application of the Agilent Seahorse XFp Technology to evaluate metabolism in stallion spermatozoa. This method enables real-time measurement of cellular metabolism across multiple samples or experimental conditions simultaneously. Ejaculates from eight different stallions were collected, and pools were prepared from three of them. Sperm viability and mitochondrial activity were evaluated by fluorescence microscopy, sperm motility by a computer-assisted sperm analysis system, and sperm metabolism was analysed via the Seahorse XFp analyser. Results confirmed a preference for OXPHOS over glycolysis in ATP production in stallion sperm, with mitochondria contributing significantly to total ATP generation. The Seahorse XFp Technology proved effective in evaluating equine sperm bioenergetics, offering insights into metabolic pathways critical for sperm function. In conclusion, this technology grants a new method for high-throughput analysis of sperm metabolism and quality, which could be applied to future reproductive studies in male equine fertility.

New technology: Custom made implants, patient-specific alignment, and navigation – How to convince my hospital it's worth it: Current concepts

Unicompartmental knee arthroplasty (UKA) faces significant challenges, including lower survival rates and higher revision rates than total knee arthroplasty (TKA). To address these issues, technological advancements like custom-made implants (CMI), patient-specific alignment (PSA), and computer-assisted systems (CAS) are being explored. These innovations aim to tailor procedures to individual joint morphology, soft tissue balance, and limb alignment, moving away from the traditional “one size fits all” approach. Early studies suggest that CMI may improve survival rates and patient-reported outcomes, though conclusive evidence is lacking. PSA shows potential for restoring pre-surgical alignment; however, its long-term benefits are uncertain. CAS improves implant placement precision and ligament balance; nevertheless, long-term survival data remain inconclusive. Moreover, economic and implementation challenges, such as cost and the need for specialized training, remain underexplored. While promising, further research is needed to fully understand the long-term efficacy and practical application of these technologies in UKA.

A Survey of Medical Visualization Through the Lens of Metaphors.

We provide an overview of metaphors that were used in medical visualization and related user interfaces. Metaphors are employed to translate concepts from a source domain to a target domain. The survey is grounded in a discussion of metaphor-based design involving the identification and reflection of candidate metaphors. We consider metaphors that have a source domain in one branch of medicine, e.g., the virtual mirror that solves problems in orthopedics and laparoscopy with a mirror that resembles the dentist's mirror. Other metaphors employ the physical world as the source domain, such as crepuscular rays that inspire a solution for access planning in tumor therapy. Aviation is another source of inspiration, leading to metaphors, such as surgical cockpits, surgical control towers, and surgery navigation according to an instrument flight. This paper should raise awareness for metaphors and their potential to focus the design of computer-assisted systems on useful features and a positive user experience. Limitations and potential drawbacks of a metaphor-based user interface design for medical applications are also considered.

Deep learning for surgical workflow analysis: a survey of progresses, limitations, and trends

Automatic surgical workflow analysis, which aims to recognize the ongoing surgical events in videos, is fundamental for developing context-aware computer-assisted systems. This paper reviews representative surgical workflow recognition algorithms based on deep learning, outlining their merits, limitations, and future research directions. The literature survey was performed on three large bibliographic databases, covering 67 lary sources, which were comparatively analyzed in terms of spatial feature modeling, spatio-temporal feature modeling, input pre-processing, regularization and post-processing algorithms, as well as learning strategies. Then, common public datasets and evaluation metrics for surgical workflow recognition are also described in detail. Finally, we discuss all literature from different perspectives, and point out the challenges, possible solutions and future trends. The need for more diverse and larger datasets, the potential of unsupervised and semi-supervised learning approaches, comprehensive and equitable metrics, establishing complete regulatory and data standards, and interoperability will be key challenges in translating models to clinical operating rooms. And we propose that surgical activity anticipation and employing large language model as training assistant are interesting research directions in surgical workflow analysis.

Supplementation of Rooster Semen Extender with Aqueous Extract of Urtica dioicafor a Long Time Preservation by Low Temperature.

The peroxidation of spermatozoa membrane phospholipids is a primary cause of irreversible changes in the preservation of avian semen. To address this issue, the objective of the present study was to assess the potential of Urtica dioica extracts in protecting avian spermatozoa during prolonged storage. Gas chromatography-mass spectroscopic techniques were employed to evaluate the bioactive compounds present in the aqueous and ethanolic extracts obtained from the aerial parts and roots of U. dioica. Semen samples were collected from 16 roosters twice a week and were diluted in Lake's extender containing different concentrations (0, 0.5, and 1 mg/100 mL) of the various extracts. Subsequently, the extended semen samples were cooled and stored at 5°C, and the sperm quality parameters were assessed at 0, 12, 24, and 36 hours of storage. The data from this experiment clearly demonstrate that the addition of nettle root aqueous extracts to the semen diluent, especially at a concentration of 0.5 mg/100 mL, resulted in a significant improvement in various sperm quality parameters. Notably, there were enhancements in total and progressive sperm motilities, viability, fertility, membrane integrity, acrosomal membrane integrity, and a reduction in malondialdehyde production in rooster semen stored in vitro for up to 36 hours. Interestingly, the present study reveals that the beneficial effects of the aqueous extracts from different parts of the nettle were supported not only by the conventional manual method but also by the computer-assisted sperm analysis system. This dual confirmation further emphasizes the positive impact of the aqueous extract on various sperm traits during cooled semen preservation. In conclusion, this study highlights the potential of U. dioica extracts, particularly the aqueous extract from nettle roots at a concentration of 0.5 mg/100 mL, in safeguarding avian spermatozoa during prolonged storage. The significant improvements in various sperm quality parameters and the validation of results through both manual and computer-assisted analysis methods provide strong evidence for the application of U. dioica extracts in avian breeding programs and artificial insemination practices.

LEADING-EDGE DEVELOPMENTS IN GUIDED ENDODONTICS: UTILIZING NEXT-GENERATION TOOLS

Guided endodontics has revolutionized root canal therapy by integrating advanced technologies to improve precision, safety, and outcomes. This method combines imaging technologies like cone beam computed tomography (CBCT) with computer-assisted navigation systems to enhance the accuracy of root canal treatments. Key stages include initial diagnostic imaging, 3D virtual treatment planning, and the use of customized guides or templates during procedures. These guides help accurately identify canal orifices, reducing procedural errors and improving access to complex root structures. Benefits include better treatment predictability, reduced procedure time, and lower risk of complications. Recent advancements, such as high-resolution CBCT, advanced 3D printing for custom guides, and improved virtual planning, have enhanced the precision of access cavity preparations. Innovations like low-profile clinical templates address challenges with restricted mouth openings, while improved intraoral scanning and virtual planning streamline preparation processes. Despite higher costs and increased planning time, guided endodontics is increasingly seen as a standard method, offering substantial improvements in clinical practice and patient outcomes. This review consolidates these advancements, emphasizing their impact on precision, efficiency, and future research directions in endodontics.

Evaluating the performance of a non-uniform squash function in Capsule networks for early diabetic retinopathy detection using fundus image analysis

Diabetic retinopathy, known as one of the most crucial neurovascular barriers to diabetes, has affected the retina, leading to a potential risk of blindness. The harm is not isolated to personal health, with negative effects felt at the economic and social level in entire communities. The consequences of vision loss secondary to diabetic retinopathy on quality of life, independent living, and employment can be significant. It is necessary to adopt a comprehensive approach for effective management of underlying diabetes, which includes early detection, timely intervention, supportive care, and management of comorbid conditions. Critical to this is a precise classification of its stages for disease analysis. A manual diagnosis, on the other hand, requires qualified individuals to recognize the subtle nuances of the condition, making it a lengthy process. This study aims to develop a computer-assisted system for analyzing retinal fundus images to identify and classify different stages of diabetic retinopathy. A dataset of eye fundus images was used by the proposed network to classify the presence and severity of blindness and its stages. The proposed model uses a non-uniform squash function in capsule neural networks. The motive behind employing a non-uniform squash function was to encourage the model to allocate greater attention and stability to intricate images throughout the training phase. The proposed model's efficiency is assessed meticulously with pre-trained CNN methods like InceptionV3, VGG16, VGG19, and Xception. The proposed capsule network model has been revamped to address the shortcomings of prior research with care. The method stands out with an impressive 99.84 % training accuracy and 98.68 % validation accuracy. Diabetic retinopathy, though rare in occurrence, poses significant challenges due to the high cost of diagnosis, rendering it inaccessible to rural and remote communities with limited access to tests and check-ups.

Assessment of Human Sperm Kinematic Parameters Using Computer-Assisted Semen Analysis

Infertility affects approximately 15% of couples trying to conceive, as reported by the World Health Organization. It is diagnosed when conception does not occur despite unprotected intercourse over the course of at least one year. The spermiogram test is a fundamental tool for identifying whether infertility originates from the male or female partner. Traditionally, sperm analysis is performed manually in reproductive clinics and laboratories, which may lead to variability in results due to subjective technician eval-uations. Recent advancements have introduced computer-assisted systems with image processing capabilities to enhance sperm quality analysis. This study presents a novel computer-assisted sperm analysis (CASA) system designed to evaluate sperm motility through digital micrographs, utilizing 14 distinct kinematic parameters. The algorithms and parameters developed offer a quantitative approach to characterizing infertility.

Undifferentiated embryonal sarcoma of the liver in children: our experience in four difficult cases and three-dimensional practical exploration

AimsTo explore rare and difficult cases of undifferentiated embryonal sarcoma of the liver (UESL) in children in a single centre, summarize the diagnosis and treatment experience and analyse the role of a computer-assisted surgery system (Hisense CAS), thus providing a new global vision and three-dimensional perspective.MethodsWe retrospectively collected the clinical data including the diagnoses and treatment processes, of children with UESL confirmed by histopathological examination in our hospital from January 2009 to December 2020. The relationship between the tumour volume and important blood vessels and between the liver volume and tumour volume, as well as other three-dimensional characteristics in the reconstructed three-dimensional model were analysed using Hisense CAS. The findings from this analysis can be used to aid in surgical decision-making and preoperative planning.ResultsFour children—3 girls and 1 boy—with UESL were included in the study. The age at onset ranged from 6 to 8 years. All four children presented with symptoms of abdominal discomfort, and abdominal masses were detected during physical examination. Owing to the wishes of their parents and the possibility that the disease was benign, all four children underwent one-stage radical surgery. For patient 1, a three-dimensional reconstruction was created during the initial diagnosis, which made accurate evaluation and planning of the preoperative procedure challenging. In patient 2, the tumour was located in the middle lobe of the liver and involved the first and second hepatic hilum. For patient 3, the pathological diagnosis of the tumour after surgery was challenging, but eventually, the diagnosis was confirmed through histochemistry and consultation with higher-level hospitals. Patient 4 had a giant tumour, which had a preoperative simulated future liver remnant volume (FLV) that was 21.0% of the total volume of the liver and tumour (TLTV). According to the standard liver volume (SLV) for children, the FLV was 77.0% of the SLV, making surgery feasible. All four children underwent complete resection, and only patient 4 experienced recurrence below the diaphragm 19 months after surgery. Currently, the 3-year overall survival rate is 100%, and the 3-year event-free survival rate is 75%.ConclusionUESL in children is rare, and the key to diagnosis and treatment is complete surgical resection. Through individualized three-dimensional surgical planning, accurate and complete resection of difficult and complex UESL in children can be achieved, leading to a favourable prognosis.

A New Approach for Effective Retrieval of Medical Images: A Step towards Computer-Assisted Diagnosis.

The biomedical imaging field has grown enormously in the past decade. In the era of digitization, the demand for computer-assisted diagnosis is increasing day by day. The COVID-19 pandemic further emphasized how retrieving meaningful information from medical repositories can aid in improving the quality of patient's diagnosis. Therefore, content-based retrieval of medical images has a very prominent role in fulfilling our ultimate goal of developing automated computer-assisted diagnosis systems. Therefore, this paper presents a content-based medical image retrieval system that extracts multi-resolution, noise-resistant, rotation-invariant texture features in the form of a novel pattern descriptor, i.e., MsNrRiTxP, from medical images. In the proposed approach, the input medical image is initially decomposed into three neutrosophic images on its transformation into the neutrosophic domain. Afterwards, three distinct pattern descriptors, i.e., MsTrP, NrTxP, and RiTxP, are derived at multiple scales from the three neutrosophic images. The proposed MsNrRiTxP pattern descriptor is obtained by scale-wise concatenation of the joint histograms of MsTrP×RiTxP and NrTxP×RiTxP. To demonstrate the efficacy of the proposed system, medical images of different modalities, i.e., CT and MRI, from four test datasets are considered in our experimental setup. The retrieval performance of the proposed approach is exhaustively compared with several existing, recent, and state-of-the-art local binary pattern-based variants. The retrieval rates obtained by the proposed approach for the noise-free and noisy variants of the test datasets are observed to be substantially higher than the compared ones.

Comparative study on three-dimensional versus two-dimensional imaging using a computer-assisted surgery system for preoperative planning in pediatric middle hepatic tumors

BackgroudThe study objective was to compare three-dimensional and two-dimensional imaging using computer-assisted systems (CASs) in clinical guidance for preoperative surgical planning for middle hepatic tumors in children.MethodsA retrospective analysis was performed on 23 children who underwent surgery for middle hepatic tumors in our hospital from January 2016 to June 2022. The surgical resection plan was formulated by the operator team using two-dimensional CT images before the operation. Then, the same qualified surgeons conducted an in-depth analysis and formulated the surgical resection scheme for the same pediatric patient using three-dimensional imaging of the middle hepatic tumor. The feasibility of the two schemes was compared and analyzed.ResultAll the tumors were successfully removed according to the preoperative method developed using three-dimensional imaging. The postoperative short-term follow-up revealed that all patients were doing well. Preoperative plans were revised in 9 cases after evaluating the three-dimensional images due to the disparity between the original plans and the three-dimensional relationship between the tumor and blood vessels, vascular variation, and the volume of remnant liver.ConclusionsThree-dimensional imaging with a computer-assisted surgery system is superior to two-dimensional imaging in the preoperative planning of pediatric hepatoblastoma.

Computer-aided Detection and Diagnosis of Cancer Regions in Mammogram Images Using Resource-Efficient CNN Architecture.

The automatic computer-assisted mammogram classification system is important for women patients to detect and diagnose the cancer regions. In this work, the mammogram images are classified into three cases: healthy, benign and cancer, using the proposed Resource Efficient Convolutional Neural Network (RECNN architecture). The proposed mammogram image classification system consists of Data Augmentation (DA) module and Spatial transformation module and CNN architecture with a segmentation module. The DA methods are used to increase the mammogram image count and Spatial Gabor Transform is used as the spatial transformation module for transforming the spatial pixels into spatial-frequency pixels. Then, the proposed RECNN architecture is used to perform the classification of mammogram images into healthy, benign and cancer cases. Further, the cancer mammogram images are diagnosed as either 'Early' or 'Severe' using the proposed RECNN architecture in this work. The proposed MCDS obtains 98.65% SeDR, 98.93% SpDR and 98.84% ADR for benign case mammogram images on DDSM dataset and also obtains 98.84% SeDR, 98.7% SpDR and 98.92% ADR for benign case mammogram images on DDSM dataset. The proposed MCDS obtains 98.94% SeDR, 98.86% SpDR and 98.96% ADR for benign case mammogram images on DDSM dataset and also obtains 98.89% SeDR, 98.88% SpDR and 99.03% ADR for benign case mammogram images on MIAS dataset. This proposed method is tested on the mammogram images from DDSM and MIAS datasets and the experimental results are compared with other similar mammogram classification works in this paper. Based on several performance evaluation measures, the experimental results show that MCDS outperforms the state-of-the-art methods currently used for the diagnosis and detection of mammography cancer.

Fast and accurate distal locking of interlocked intramedullary nails using computer-vision and a 3D printed device

IntroductionDistal locking is a challenging and time-consuming step in interlocked intramedullary nailing of long bone fractures. Current methods have limitations in terms of simplicity, universality, accuracy, speed, and safety. We propose a novel device and software for distal locking using computer vision.Methods and materialsThe device consists of an universal ancillary clamp, a telescopic arm, a viewfinder clamp, and a radio-opaque cross. The software uses a camera photo from the C-arm intensifier and adjusts for geometric projection deformities. The software employs edge detection, Hough transform, perspective interpolation, and vector calculation algorithms to locate the distal hole center. The device and software were designed, manufactured, and tested using 3D CAD, FEM, DRR, and performance testing on phantom bones.ResultsThe device and software showed high accuracy and precision of 98.7% and 99.2% respectively in locating the distal hole center and calculating the correctional vector. The device and software also showed high success ratio in drilling the hole and inserting the screw. The device and software reduced the radiation exposure for the surgeon and the patient. The success ratio of the device and software was validated by the physical testing, which simulated the real clinical scenario of distal locking. The radiation exposure was as low as 5 s with a radiation dose of 0.2mSv, drastically reducing radiation exposure during distal locking.DiscussionOur device and software have several advantages over other distal locking methods, such as simplicity, universality, accuracy, speed, and safety. Our device and software also have some disadvantages, such as reliability and legislation. Our device and software can be compared with other distal locking methods based on these criteria. Our device and software have some limitations and challenges that need to be addressed in the future, such as clinical validation, and regulatory approval.ConclusionThe device showed promising results in terms of low-cost, reusability, low radiation exposure, high accuracy, fast distal locking, high stiffness, and adaptability. The device has several advantages over other distal locking techniques, such as free-hand technique, mechanical aiming devices, electromagnetic navigation systems, and computer-assisted systems. We believe that our device and software have the potential to revolutionize the distal locking technique and to improve the outcomes and quality of life of the patients with long bone fractures.

The evaluation of computational modelling performance within the context of rationality theory: finding the area between two curves

ABSTRACT This study aimed to investigate the development of computational modelling performances of students during the computer-assisted system (CAS) integrated ACODESA method based on Habermas’ construct of rationality. The participants included 22 university students. In the study, in which the embedded design was utilised, the qualitative phase aimed to examine the computational modelling performances of the students during the stages of CAS integrated ACODESA method. It was determined that the students showed improvement in modelling the Riemann sum accurately with CAS, and in choosing to use for loop to determine the area of the rectangles that represented the Riemann sum, and in comprehensibility and acceptability. In the quantitative phase of the study, pre and post-tests were conducted to determine the effect of the CAS-integrated ACODESA method on computational modelling performances of the students. The computational modelling scores were compared with the paired samples t-test. It was found that CAS-integrated ACODESA method made statistically significant effect on computational modelling performances of the students.

One year "ADAPT system" use for proximal femoral fracture osteosynthesis with intramedullary nail . A case control study.

Proximal femoral fractures (PFF) are a significant health concern among the elderly, often leading to complications and high mortality rates. Intramedullary nailing is widely considered the most effective treatment for lateral proximal femoral fractures (LPFF), with the Tip Apex Distance (TAD) being a crucial predictor of surgical success. This study aimed to compare outcomes between patients treated with and without the ADAPT (ADAptive Positioning Technology) system, which aids in the precise placement of the cephalic screw. A retrospective analysis was conducted on 97 patients with intertrochanteric fractures treated in 2022. Patients were divided into two groups: those treated with the ADAPT system (group I, n=34) and those treated without it (group II, n=63). Fractures were classified according to AO/OTA classification. The primary outcomes measured were operative time, cephalic screw angle, TAD, and incidence of lag screw cut-out. Statistical analyses included chi-square tests and t-tests, with significance set at P < 0.05. The ADAPT system did not significantly reduce TAD (18.21 mm in the ADAPT group vs.19.94 mm in the control group, p=0.149). Operative times were similar between the groups. The incidence of lag screw cut-out was low in both groups, with no significant differences. The study confirmed a strong correlation between higher TAD and increased risk of screw cut-out, underscoring the importance of precise screw placement. Computer-assisted surgery, such as the ADAPT system, aims to enhance the accuracy of cephalic screw placement. In this study, the ADAPT system didn't demonstrate a statistically significant advantage in reducing TAD or preventing screw cut-out. Nevertheless, the critical role of TAD in preventing fixation failure was reaffirmed, emphasising the need for precise surgical techniques. While the ADAPT system did not show a significant advantage in reducing TAD or preventing screw cut-out in this study, the importance of achieving optimal TAD in cephalomedullary nailing was reinforced. Future research should continue to explore the role of computer-assisted systems in enhancing surgical accuracy and improving outcomes for patients with LPFF.

The association between dietary selenium intake and telomere length in hypertension.

Telomere length is closely linked to biological aging, oxidative stress, and the development of cardiovascular diseases. This study aimed to assess the association between dietary selenium intake and telomere length in individuals with hypertension. Data on dietary selenium intake were captured through the National Health and Nutrition Examination Survey (NHANES) computer-assisted dietary interview system (CADI). Telomere length determination entailed selecting blood samples from all participants in the NHANES database. The analysis was performed using Analysis System software, with Empower stats utilized for data analysis. Results showed that there was a significant association between dietary selenium intake and telomere length in hypertension, particularly within the female group. In female hypertension cases, a 1 mcg increase in dietary selenium intake corresponded to a telomere length increase of 1.19bp, even after adjusting for age, race, BMI, marital status, physical activity, energy intake, and stroke history. The relationship between dietary selenium intake and telomere length exhibited a linear pattern in female hypertension patients. This study identified a positive association between dietary selenium intake and telomere length in hypertension, particularly within the female group.