Automatic ROI detection and classification of the Achilles tendon ultrasound images

Ultrasound (US) imaging plays an important role in medical imaging technologies. It is widely used because of its ease of use and low cost compared to other imaging techniques. Specifically, ultrasound imaging is used in the detection of the Achilles Tendon (AT) pathologies as it detects important details. For example, US imaging is used for AT rupture that affects about 1 in 5,000 people worldwide. Decision support systems are important in medical imaging, as they assist radiologist in detecting probable diagnoses and lesions. The work presented in this paper concerns the development of a software application to detect changes in the AT ultrasound images and subsequently classify them into normal or abnormal. We propose an approach that fully automates the detection for the Region of Interest (ROI) in ultrasound AT images. The original image is divided into six blocks with 1 cm size in each direction. The blocks lie inside the vulnerable area considered as our ROI. The proposed system achieved an accuracy of 97.21%

Ultrasound-assisted extraction, LC–MS/MS analysis, anticholinesterase, and antioxidant activities of valuable natural netabolites from Astragalus armatus Willd.: In silico molecular docking and In Vitro enzymatic studies

The Astragalus armatus Willd. plant’s phenolic constituent extraction and identification were optimized using the ultrasound-assisted extraction (UAE) method and the LC–MS/MS analysis, respectively. Additionally, cupric reducing antioxidant capacity (CUPRAC), beta carotene, reducing power, DMSO alcalin, silver nanoparticle (SNP)-based method, phenanthroline, and hydroxyl radical tests were utilized to assess the extract’s antioxidant capacity, while the neuroprotective effect was examined in vitro against acetylcholinesterase enzyme. This study accurately estimated the chemical bonding between the identified phenolic molecules derived from LC–MS/MS and the AChE. The extract was found to contain sixteen phenolic substances, and rosmarinic, protocatechuic, and chlorogenic acids, as well as 4-hydroxybenzoic, hyperoside, and hesperidin, were the most abundant substances in the extract. In all antioxidant experiments, the plant extract demonstrated strong antioxidant activity and a significant inhibitory impact against AChE (40.25 ± 1.41 μg/mL). According to molecular docking affinity to the enzyme AChE, the top-five molecules were found to be luteolin, quercetin, naringenin, rosmarinic acid, and kaempferol. Furthermore, these tested polyphenols satisfy the essential requirements for drug-like characteristics and Lipinski’s rule of five. These results highlight the significance of the A. armatus plant in cosmetics, as food additives, and in the pharmaceutical industry due to its rosmarinic and chlorogenic acid content

The Tumor Suppressor Gene, RASSF1A, Is Essential for Protection against Inflammation -Induced Injury

10.1371/journal.pone.0075483PLoS ONE810-POLN

Classification of Types of Stuttering Symptoms Based on Brain Activity

Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type

Molecular networks of human muscle adaptation to exercise and age

Physical activity and molecular ageing presumably interact to precipitate musculoskeletal decline in humans with age. Herein, we have delineated molecular networks for these two major components of sarcopenic risk using multiple independent clinical cohorts. We generated genome-wide transcript profiles from individuals (n = 44) who then undertook 20 weeks of supervised resistance-exercise training (RET). Expectedly, our subjects exhibited a marked range of hypertrophic responses (3% to +28%), and when applying Ingenuity Pathway Analysis (IPA) up-stream analysis to ~580 genes that co-varied with gain in lean mass, we identified rapamycin (mTOR) signaling associating with growth (P = 1.4×10−30). Paradoxically, those displaying most hypertrophy exhibited an inhibited mTOR activation signature, including the striking down-regulation of 70 rRNAs. Differential analysis found networks mimicking developmental processes (activated all-trans-retinoic acid (ATRA, Z-score = 4.5; P = 6×10−13) and inhibited aryl-hydrocarbon receptor signaling (AhR, Z-score = −2.3; P = 3×10−7)) with RET. Intriguingly, as ATRA and AhR gene-sets were also a feature of endurance exercise training (EET), they appear to represent “generic” physical activity responsive gene-networks. For age, we found that differential gene-expression methods do not produce consistent molecular differences between young versus old individuals. Instead, utilizing two independent cohorts (n = 45 and n = 52), with a continuum of subject ages (18–78 y), the first reproducible set of age-related transcripts in human muscle was identified. This analysis identified ~500 genes highly enriched in post-transcriptional processes (P = 1×10−6) and with negligible links to the aforementioned generic exercise regulated gene-sets and some overlap with ribosomal genes. The RNA signatures from multiple compounds all targeting serotonin, DNA topoisomerase antagonism, and RXR activation were significantly related to the muscle age-related genes. Finally, a number of specific chromosomal loci, including 1q12 and 13q21, contributed by more than chance to the age-related gene list (P = 0.01–0.005), implying possible epigenetic events. We conclude that human muscle age-related molecular processes appear distinct from the processes regulated by those of physical activity