Flow through free fibula flap for upper limb reconstruction in sarcoma patients.

INTRODUCTION: SOFT TISSUE SARCOMAS (STS) are rare malignant tumors arising from extraskeletal mesenchymal tissues. They are less than 1% of all newly diagnosed malignant tumors in the United States. Of these only 25% occur at the upper extremity. STS of the extremities used to be treated with amputation in as much as half of the patients. Nowadays limb-sparing surgery , without any compromise in local control or survival rates, is performed. Advances in tumour biology understanding, improved chemotherapy and radiotherapy (neoadjuvant or adjuvant in post op treatment), ability of surgical oncologists to excise the tumour with a good margin (principle of excision without seeing the tumour) and advances in plastic surgical expertise where there is a technique available to reconstruct any composite defect of the axial vessels of the hand compromising its vitality, have all paved the way for limb salvage surgery. Oncological resections, especially in the forearm sarcomas have resulted in complex composite defects with loss of variable amount of bone, muscle, vessels, nerves and skin. AIM OF THE STUDY: To evaluate the free fibula as a flow through flap for reconstruction of upper limb defects after sarcoma excision. To assess the functional and aesthetic outcomes after upper limb reconstruction using free fibula flap. Evaluation of outcomes takes into account the following:- • Overall patient satisfaction. • Functional outcome assessed by the MSTS scoring system. • Cosmetic acceptability of the patient by visual analogue score. • Complications after surgery. • Donor site morbidity. MATERIALS AND METHODS: In our department, between March 2012 and March 2014 we have done 6 cases of upper extremity Sarcoma reconstruction, all involving the forearm region. The following criteria were decided upon for patient selection Inclusion criteria: Patients with soft tissue sarcoma (biopsy proven) of the upper limb. Patients with good IQ who understood the treatment explained to them. Patients who are fit for surgery. Patients willing for long term regular follow up. Patients who received previous chemo/ radiation were also included. Exclusion Criteria: High risk individuals who are medically unfit. Patients not willing for follow up. Patients not willing for long duration of surgery and for the postoperative physiotherapy rigors Elderly patients. OBSERVATIONS AND RESULTS: A total of six patients underwent upper limb reconstruction with flow through free fibula osteomyocutaneou flap. There were a 4 male and 2 female patients. The patients aged between 19 and 40 with a mean of 30 years. Among the 6 patients 2 had spindle cell sarcoma the remaining each 1 patient had Fibro Sarcoma, Synovial Sarcoma, Osteosracoma, Endothelial Sarcoma. CONCLUSION: Upper limb reconstruction after sarcoma excision is a complex challenging task to the reconstructive surgeon. This is because the defect is composite, preoperative radiation makes anastomosis difficult and patient must regain acceptable function post surgery. Sarcoma reconstruction has undergone a radical change towards preservation of the limb with the usage of the vascularised free fibula flap. The major advantage is that there is no compromise in the extent of resection. Our study and review of the literature has shown that vascularised fibula flap harvested in a chimeric pattern along with the peroneus longus provides excellent quality of tissue to reconstruct both bone and soft tissue loss. We recommend the use of the peroneus longus muscle tendon unit based on an independant perforator from the peroneal artery. The use of the peroneus muscle has improved the functional outcome in these patients. Although the number of cases in our study was limited, results were satisfactory. Low donor site morbidity, acceptable functional outcome, limb preservation makes the free fibula osteocutaneous flap as an ideal option for upper limb reconstruction

A Novel Technology Stack for Automated Road Quality Assessment Framework using Deep Learning Techniques

Road infrastructure plays a pivotal role in supporting societal, economic, and cultural progress. The capacity of a road refers to its ability to handle vehicular volume. Inadequate road capacity and the presence of defects like potholes and cracks result in suboptimal travel conditions and pose significant safety risks for drivers, cyclists, and pedestrians. The regular evaluation of these road quality aspects is essential for effective maintenance. However, current methods for assessing road capacity are time-consuming, subjective, and heavily reliant on manual labor. Moreover, existing deep learning-based approaches for detecting road defects often lack accuracy. To overcome these challenges, a fully automated and accurate system for evaluating road quality is imperative. Thus, the objective of this research work is to propose a novel technology stack for a comprehensive Automated Road Quality Assessment (ARQA) framework designed to assess road quality. The experimental findings demonstrate that the suggested vehicle detection and pothole detection methods work effectively and exhibit enhancements of 18% and 6%, respectively, in comparison to existing approaches

Use of Genetic Algorithm for Cohesive Summary Extraction to Assist Reading Difficulties

Learners with reading difficulties normally face significant challenges in understanding the text-based learning materials. In this regard, there is a need for an assistive summary to help such learners to approach the learning documents with minimal difficulty. An important issue in extractive summarization is to extract cohesive summary from the text. Existing summarization approaches focus mostly on informative sentences rather than cohesive sentences. We considered several existing features, including sentence location, cardinality, title similarity, and keywords to extract important sentences. Moreover, learner-dependent readability-related features such as average sentence length, percentage of trigger words, percentage of polysyllabic words, and percentage of noun entity occurrences are considered for the summarization purpose. The objective of this work is to extract the optimal combination of sentences that increase readability through sentence cohesion using genetic algorithm. The results show that the summary extraction using our proposed approach performs better in -measure, readability, and cohesion than the baseline approach (lead) and the corpus-based approach. The task-based evaluation shows the effect of summary assistive reading in enhancing readability on reading difficulties

Linguistic Adaptation and Psychometric Properties of Tamil Version of General Oral Health Assessment Index‑Tml

Background: Oral health has an impact on quality of life hence for research purpose validation of a Tamil version of General Oral Health Assessment Index would enable it to be used as a valuable tool among Tamil speaking population.Aim: In this study, we aimed to assess the psychometric properties of translated Tamil version of General Oral Health Assessment Index (GOHAI‑Tml).Subjects and Methods: Linguistic adaptation involved forward and backward blind translation process. Reliability was analyzed using test‑retest, Cronbach alpha, and split half reliability. Inter‑item and item‑total correlation were evaluated using Spearman rank correlation. Convenience sampling was done, and 265 consecutive patients aged 20–70 years attending the outpatient department were recruited. Subjects were requested to fill a self‑reporting questionnaire along with Tamil GOHAI version. Clinical examination was done on the same visit. Concurrent validity was measured by assessing the relationship between GOHAI scores and self‑perceived oral health and general health status, satisfaction with oral health, need for dental treatment and esthetic satisfaction. Discriminant validity was evaluated by comparing the GOHAI scores with the objectively assessed clinical parameters. Exploratory factor analysis was done to examine the factor structure.Results: Mean GOHAI‑Tml was 52.7 (6.8, range 22–60, median 54). The mean number of negative impacts was 2 (2.4, range 0–11, median 1). The Spearman rank correlation for test‑retest ranged from 0.8 to 0.9 (P < 0.001) for all the 12 items between visits. The Cronbach alpha for 265 samples was 0.8 suggesting good internal consistency and homogeneity between items. Item scale correlation ranged from 0.4 to 0.8 (P < 0.001). Concurrent and discriminant validity was established. Principal component analysis resulted in extraction of four factors which together accounted for 66.4% (7.9/12) variance.Conclusion: GOHAI‑Tml has shown acceptable psychometric properties, so that it can be used as an efficient tool in identifying the impact of oral health on quality of life among the Tamil speaking population.Keywords: General oral health assessment index, Linguistic adaptation, Oral health‑related quality of life, Psychometric properties, Reliability, Validit

Cosmetic obsolescence? User perceptions of new and artificially aged materials

This paper presents the findings of a user study which explored tactile and aesthetic responses to new and artificially aged mobile phone cases made from bamboo, walnut, cork, leather, brushed titanium, plastic and rubber. The paper outlines test methods for accelerated ageing of the external enclosures of consumer electronics based on the types of wear experienced in use, and the use of semantic differential scales (SDS) to probe user attitudes to these materials. The results indicate that preferences for the materials tested were extremely subjective, and even a single participant can have conflicting requirements for the characteristics of the materials (for example, sleek and shiny yet easy to grip). Whilst in general participants preferred the new materials and saw the ageing process as negative, there were examples where the aged samples either scored more highly due to durability (titanium) or received positive comments about the aesthetic changes caused by severe ageing (bamboo and leather). This study captured the participants' immediate, visceral response to the materials, which may be very different to their feelings towards materials and objects that they have owned and interacted with for a period of time

R-CNN and YOLOV4 based Deep Learning Model for intelligent detection of weaponries in real time video

The security of civilians and high-profile officials is of the utmost importance and is often challenging during continuous surveillance carried out by security professionals. Humans have limitations like attention span, distraction, and memory of events which are vulnerabilities of any security system. An automated model that can perform intelligent real-time weapon detection is essential to ensure that such vulnerabilities are prevented from creeping into the system. This will continuously monitor the specified area and alert the security personnel in case of security breaches like the presence of unauthorized armed people. The objective of the proposed system is to detect the presence of a weapon, identify the type of weapon, and capture the image of the attackers which will be useful for further investigation. A custom weapons dataset has been constructed, consisting of five different weapons, such as an axe, knife, pistol, rifle, and sword. Using this dataset, the proposed system is employed and compared with the faster Region Based Convolution Neural Network (R-CNN) and YOLOv4. The YOLOv4 model provided a 96.04% mAP score and frames per second (FPS) of 19 on GPU (GEFORCE MX250) with an average accuracy of 73%. The R-CNN model provided an average accuracy of 71%. The result of the proposed system shows that the YOLOv4 model achieves a higher mAP score on GPU (GEFORCE MX250) for weapon detection in surveillance video cameras

A generic algorithm for layout of biological networks

BackgroundBiological networks are widely used to represent processes in biological systems and to capture interactions and dependencies between biological entities. Their size and complexity is steadily increasing due to the ongoing growth of knowledge in the life sciences. To aid understanding of biological networks several algorithms for laying out and graphically representing networks and network analysis results have been developed. However, current algorithms are specialized to particular layout styles and therefore different algorithms are required for each kind of network and/or style of layout. This increases implementation effort and means that new algorithms must be developed for new layout styles. Furthermore, additional effort is necessary to compose different layout conventions in the same diagram. Also the user cannot usually customize the placement of nodes to tailor the layout to their particular need or task and there is little support for interactive network exploration.ResultsWe present a novel algorithm to visualize different biological networks and network analysis results in meaningful ways depending on network types and analysis outcome. Our method is based on constrained graph layout and we demonstrate how it can handle the drawing conventions used in biological networks.ConclusionThe presented algorithm offers the ability to produce many of the fundamental popular drawing styles while allowing the exibility of constraints to further tailor these layouts.publishe

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Protein Tpr is required for establishing nuclear pore-associated zones of heterochromatin exclusion

Amassments of heterochromatin in somatic cells occur in close contact with the nuclear envelope (NE) but are gapped by channel- and cone-like zones that appear largely free of heterochromatin and associated with the nuclear pore complexes (NPCs). To identify proteins involved in forming such heterochromatin exclusion zones (HEZs), we used a cell culture model in which chromatin condensation induced by poliovirus (PV) infection revealed HEZs resembling those in normal tissue cells. HEZ occurrence depended on the NPC-associated protein Tpr and its large coiled coil-forming domain. RNAi-mediated loss of Tpr allowed condensing chromatin to occur all along the NE's nuclear surface, resulting in HEZs no longer being established and NPCs covered by heterochromatin. These results assign a central function to Tpr as a determinant of perinuclear organization, with a direct role in forming a morphologically distinct nuclear sub-compartment and delimiting heterochromatin distribution