5,755 research outputs found

    Implant strategies for femur fractures in osteopetrosis: Insights from a case series and literature review

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    Background: A rare category of hereditary illnesses known as osteopetrosis (OP) causes increased bone radiodensity on radiographs. Due to brittle bone and frequent fractures, symptomatic management is the mainstay of treatment. The underlying pathology of osteopetrosis in a patient presenting with long bone fractures may be missed due to the rarity of the condition and lack of awareness on the part of the treating surgeon. There is no consensus on fracture management in osteopetrosis. When opting for surgical fixation of fractures, there is often a conflict about what implants to use to ensure stable fixation and early functional redemption. Iatrogenic fractures during implant placement, overheating, and drill/saw breakage are some of the difficulties that may arise during surgery. Methods: Our study is a retrospective observational analysis of eight patients with osteopetrosis who underwent surgery for a femur fracture with various types of implants at our facility between January 2010 and March 2022. Following surgery, clinico-radiological follow-ups were done at one, two, six months, 12 months, and then yearly thereafter. Clinically, the patients were assessed based on the Lower Extremity Functional Score (LEFS). Results: The patients who underwent combined extra and intramedullary fixation showed a faster return of LEFS and union time of the fracture. Conclusion: When addressing the fractures in osteopetrosis, it is crucial to consider the risks of fixation in these individuals. Although plate fixation is considered easier, the risk of peri-implant fractures is high. In our experience, intramedullary nailing with plate augmentation and bone grafting provides a much more stable construct which can reduce the risk of further fractures

    Histopathological spectrum of lung findings in autopsy cases

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    Background: The incidence of lung pathology is the most common autopsy finding and is responsible for a great deal of mortality and morbidity. It is affected by a wide variety of respiratory pathogens and is involved in many systemic diseases. It is secondarily involved in almost all forms of terminal disease. Radiological findings are usually nonspecific in lung diseases and need prompt histopathological examination to find out the exact cause of death. Aims and Objectives: The aim is to study the spectrum of histopathological findings in lung in autopsy cases. Materials and Methods: This is a retrospective study done in the Department of Pathology at Government Kilpauk Medical College and Hospital during the year 2022. Lung specimens were received from the Forensic medicine department. Gross findings were noted. Following adequate formalin fixation, the tissue specimens were processed and paraffin sectioning was done followed by hematoxylin and eosin staining. The findings were documented and the results were analyzed. Results: Among 100 cases studied during year maximum cases were seen in the age group of 31–40 years (32%). Males (72%) were more commonly affected than females (28%). The most common findings are Pulmonary edema (34%) followed by congestion (32%) and other findings include emphysematous change (13%), pneumonia (10%), tuberculosis (6%), metastatic adenocarcinomatous deposits (1%), primary well-differentiated adenocarcinoma (1%), pulmonary chondroma (1%), and bronchiectasis (1%). Conclusion: The most common finding observed was pulmonary edema. In our study, male preponderance was noted. This study emphasizes to scrutinize the histopathological findings in the lung, especially following a sudden death

    Building Intelligent Systems by Combining Machine Learning and Automated Commonsense Reasoning

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    We present an approach to building systems that emulate human-like intelligence. Our approach uses machine learning technology (including generative AI systems) to extract knowledge from pictures, text, etc., and represents it as (pre-defined) predicates. Next, we use the s(CASP) automated commonsense reasoning system to check the consistency of this extracted knowledge and reason over it in a manner very similar to how a human would do it. We have used our approach for building systems for visual question answering, task-specific chatbots that can ``understand" human dialogs and interactively talk to them, and autonomous driving systems that rely on commonsense reasoning. Essentially, our approach emulates how humans process knowledge where they use sensing and pattern recognition to gain knowledge (Kahneman's System 1 thinking, akin to using a machine learning model), and then use reasoning to draw conclusions, generate response, or take actions (Kahneman's System 2 thinking, akin to automated reasoning)

    A Novel Custom One-Dimensional Time-Series DenseNet for Water Pipeline Leak Detection and Localization Using Acousto-Optic Sensor

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    A crucial component within any structural health monitoring system is a pipeline leak detection mechanism, vital for preventing avoidable water loss. Contemporary literature employs machine learning and deep learning for detecting pipeline leaks and cross-correlation for leak localization. The major drawbacks in the existing methodologies are that machine learning and deep learning methods need two different architectures for leak detection and localization, and the cross-correlation needs two sensors with a denoising technique. The primary objective of this paper is to deploy a unified architecture capable of executing both the detection and localization of a leak without any denoising technique and with a single sensor. The proposed technique utilizes the data collected using an Acousto-optic sensor with two different pressures. This paper proposes a novel custom one-dimensional time-series DenseNet for leak detection and localization. The proposed method gives better accuracies compared with the existing one-dimensional DenseNet-121, three different one-dimensional convolutional neural networks (1DCNN), and cross-correlation for two different pressure datasets. The proposed method’s processing time is thirteen times less than the existing one-dimensional DenseNet-121, with the observed average leak detection and localization accuracy of 99.08%. The results state that the proposed novel custom one-dimensional time-series DenseNet accurately detects and localizes the leak with less time

    Additional file 1 of Stage II oesophageal carcinoma: peril in disguise associated with cellular reprogramming and oncogenesis regulated by pseudogenes

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    Additional file 1: Figure S1. Subset of DaPs exhibit Stage-specific expression pattern across ESCA Box and whisker plots indicating the gene expression profile of DaPs differentially expressed in Stage I (a), Stage II (c), Stage III (e) and Stage IV (g) ESCA as compared to that of normal. Significance of expression between the two groups for each DaP was evaluated using Mann-Whitney tests; indicated by asterisks above the boxplot as *p 1.30103. Additionally, stage-specific downregulation of DaPs is indicated by orange dots, while pale-green dots represent stage-specific upregulation. Genes with adjusted p-value <-log10(0.05) and/or |log2FC| < 1.5 are indicated by grey dots. DaPs; Differentiation-associated pseudogenes, FC; Fold Change and ESCA; Oesophageal Carcinoma

    Arthroscopic fixation of comminuted bony bankart lesion with repair of massive retracted rotator cuff tear-A Technical note

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    Managing concomitant cuff tears with comminuted bony bankart is a challenging scenario. Appropriate management of bony pathology and the rotator cuff ear is necessary in cases associated with both. Bony Bankart with considerable glenoid involvement results in recurrent instability if not treated accordingly. We describe our preferred technique of bony bankart repair with rotator cuff repair in a seventy years old male diagnosed with a large comminuted bony bankart lesion along with a massive cuff tear

    Molecular characterization of the invasive fall armyworm, Spodoptera frugiperda (J.E. Smith) feeding on finger millet, Eleusine coracana (L.) Gaertn

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    Genetically, the maize fall armyworm (FAW, Spodoptera frugiperda J.E. Smith) consists of two strains viz., corn (C) strain mainly feeding on maize, sorghum, cotton, pulses, etc., and rice (R) strain feeding on rice crop and other grasses. The present study was carried out to identify the strains of FAW collected from finger millet crop at three different locations viz., Morappur (Dharmapuri district), Vridhachalam (Cuddalore district) and Salem (Salem district) of Tamil Nadu, India. PCR–RFLP profile of mitochondrial cytochrome oxidase I fragment exhibited the presence of both ‘C’ and ‘R’ strains of FAW feeding on finger millet. Out of ten samples, 6, 8 and 8 samples assumed ‘R’ strain identity, whereas, 4, 2 and 2 samples assumed ‘C’ strain identity in the locations of Morappur, Vridhachalam and Salem, respectively. Sequence analyses of mtCOI region of FAW feeding on finger millet showed nucleotide variations in eight positions. The molecular identity of S. frugiperda was ranged from 98 to 100% with previously deposited sequences in the NCBI GenBank database

    Tailored psychological intervention for anxiety or depression in COPD (TANDEM): a randomised controlled trial.

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    This multi-centre, pragmatic, randomised controlled trial evaluated whether a tailored psychological intervention based on a cognitive behavioural approach for people with COPD and symptoms of anxiety and/or depression improved anxiety or depression compared to usual care (UC).People with COPD and moderate to very severe airways obstruction and Hospital Anxiety and Depression Scale subscales scores indicating mild to moderate anxiety (HADS-A) and/or depression (HADS-D), were randomised 1.25:1, intervention (242): UC (181). Respiratory health professionals delivered the intervention face-to-face over 6-8 weeks. Co-primary outcomes were HADS-A and HADS-D measured six months post-randomisation. Secondary outcomes at six and 12 months included: HADS-A and HADS-D (12 months), Beck Depression Inventory II, Beck Anxiety Inventory, St George's Respiratory Questionnaire, social engagement, the EUROQOL instrument 5-level version, smoking status, completion of pulmonary rehabilitation (PR) and health and social care resource use.The intervention did not improve anxiety (HADS-A mean difference, 95% CI, -0.60, -1.40 to 0.21) or depression (HADS-D -0.66, -1.39 to 0.07) at six months. The intervention did not improve any secondary outcomes at either timepoint, nor did it influence completion of PR or healthcare resource use. Deaths in the intervention arm 13/242 (5%) exceeded those in the control arm 3/181 (2%), but none were associated with the intervention. Health economic analysis found the intervention highly unlikely to be cost-effective.This trial has shown, beyond reasonable doubt, that this cognitive behavioural intervention delivered by trained and supervised respiratory health professionals does not improve psychological comorbidity in people with advanced COPD and depression or anxiety

    Geospatial Analysis Of Public Green And Estimation Of Maintenance Cost

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    In accordance with the guidelines set forth by PBSGEO, this study aims to highlight the significance of public greenspaces within cemeteries and to propose cost-saving solutions for graveyard maintenance. This research employs a Design Science approach to examine the impact of various factors, including geospatial data, on cemetery maintenance costs. Through a case study of graveyards in Frankfurt, this thesis explores alternative solutions and presents graphical data analysis to better understand the properties of public greenspaces and graveyards. The main findings of this study indicate that effective cost estimation can significantly decrease maintenance costs and improve long-term profitability for cemetery management. While no specific model has been created, the availability of a comprehensive analysis and management portal will assist managers in making informed decisions in the future. The research concludes with the presentation of an online interactive map that can be utilized by cemetery management to reduce costs and enhance productivity. This thesis provides valuable insights into the importance of public greenspaces in cemeteries and the ways in which they can be maintained more efficiently. In addition to its exploratory analysis, this study offers practical implications for the cemetery management industry. The proposed cost-saving solutions can be easily implemented by cemetery management, leading to a reduction in maintenance costs and an improvement in the overall profitability of cemeteries. Furthermore, the findings of this study can also inform future research on the topic and contribute to the development of more sustainable cemetery management practices

    Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning

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    Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL &gt;20 ppb, and FUM &gt;5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM contamination. Greater calcium carbonate content in soil was negatively correlated with AFL contamination, which was noticeable in Southern IL. Greater soil moisture and available water-holding capacity throughout Southern IL were positively correlated with high FUM contamination. The higher clay percentage in the northeastern areas of IL negatively correlated with FUM contamination. NN models showed high class-specific performance for 1-year predictive validation for AFL (73%) and FUM (85%), highlighting their accuracy for annual mycotoxin prediction. Our models revealed that soil, NDVI, year-specific weekly average precipitation, and temperature were the most important factors that correlated with mycotoxin contamination. These findings serve as reliable guidelines for future modeling efforts to identify novel data inputs for the prediction of AFL and FUM outbreaks and potential farm-level management practices
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