The Effect of Phosphatidylcholine and Deoxycholate Compound Injections to the Localized Adipose Tissue: An Experimental Study with a Murine Model

BackgroundPhosphatidylcholine (PPC) and deoxycholate (DCA) compound has been recently used for the purpose of partial lipolysis and is valued for its efficacy and lower invasiveness compared to liposuction and dermolipectomy used previously. In this article, the authors discuss the efficacy of the PPC dissolved in DCA via an experimental rat study model, along with suggesting a useful animal experimental model for the study of adipose tissue and lipolysis.MethodsBilateral inguinal fat pads of an experimental rat were elevated with the deep inferior epigastric vessel as the sole vascular pedicle. Normal saline was injected on one side as a control group and a PPC and DCA compound was injected on the other side. After 4 days, the rats were euthanized for microscopic tissue examination. The pathology was scored by a semiquantitative system in 4 categories: normal fat amount, fat necrosis, inflammatory activity, and stage of fibrosis. A Wilcoxon signed-rank test powered by SPSS packet program was used for statistical analysis and to determine significance.ResultsMicroscopic examination was performed on the obtained samples, and the experimental data of all four categories showed significant histologic differences compared to the control group. All of the data also showed statistical significance by the Wilcoxon signedrank test (P<0.01).ConclusionsIn the inguinal fat pad rat model, the control group and the experimental group had a differed significantly in the amount of normal fat tissue, inflammation, necrosis, and fibrosis. We recommend the rat inguinal fat pad model used in this study, as it is likely to be useful in related research

Convolution channel separation and frequency sub-bands aggregation for music genre classification

In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this research, we propose a novel framework that can extract and aggregate both short- and long-term features hierarchically. Our framework is based on ECAPA-TDNN, where all the layers that extract short-term features are affected by the layers that extract long-term features because of the back-propagation training. To prevent the distortion of short-term features, we devised the convolution channel separation technique that separates short-term features from long-term feature extraction paths. To extract more diverse features from our framework, we incorporated the frequency sub-bands aggregation method, which divides the input spectrogram along frequency bandwidths and processes each segment. We evaluated our framework using the Melon Playlist dataset which is a large-scale dataset containing 600 times more data than GTZAN which is a widely used dataset in MGC studies. As the result, our framework achieved 70.4% accuracy, which was improved by 16.9% compared to a conventional framework

One-Step Knowledge Distillation and Fine-Tuning in Using Large Pre-Trained Self-Supervised Learning Models for Speaker Verification

The application of speech self-supervised learning (SSL) models has achieved remarkable performance in speaker verification (SV). However, there is a computational cost hurdle in employing them, which makes development and deployment difficult. Several studies have simply compressed SSL models through knowledge distillation (KD) without considering the target task. Consequently, these methods could not extract SV-tailored features. This paper suggests One-Step Knowledge Distillation and Fine-Tuning (OS-KDFT), which incorporates KD and fine-tuning (FT). We optimize a student model for SV during KD training to avert the distillation of inappropriate information for the SV. OS-KDFT could downsize Wav2Vec 2.0 based ECAPA-TDNN size by approximately 76.2%, and reduce the SSL model's inference time by 79% while presenting an EER of 0.98%. The proposed OS-KDFT is validated across VoxCeleb1 and VoxCeleb2 datasets and W2V2 and HuBERT SSL models. Experiments are available on our GitHub

Integrated Parameter-Efficient Tuning for General-Purpose Audio Models

The advent of hyper-scale and general-purpose pre-trained models is shifting the paradigm of building task-specific models for target tasks. In the field of audio research, task-agnostic pre-trained models with high transferability and adaptability have achieved state-of-the-art performances through fine-tuning for downstream tasks. Nevertheless, re-training all the parameters of these massive models entails an enormous amount of time and cost, along with a huge carbon footprint. To overcome these limitations, the present study explores and applies efficient transfer learning methods in the audio domain. We also propose an integrated parameter-efficient tuning (IPET) framework by aggregating the embedding prompt (a prompt-based learning approach), and the adapter (an effective transfer learning method). We demonstrate the efficacy of the proposed framework using two backbone pre-trained audio models with different characteristics: the audio spectrogram transformer and wav2vec 2.0. The proposed IPET framework exhibits remarkable performance compared to fine-tuning method with fewer trainable parameters in four downstream tasks: sound event classification, music genre classification, keyword spotting, and speaker verification. Furthermore, the authors identify and analyze the shortcomings of the IPET framework, providing lessons and research directions for parameter efficient tuning in the audio domain.Comment: 5 pages, 3 figures, submit to ICASSP202

PAS: Partial Additive Speech Data Augmentation Method for Noise Robust Speaker Verification

Background noise reduces speech intelligibility and quality, making speaker verification (SV) in noisy environments a challenging task. To improve the noise robustness of SV systems, additive noise data augmentation method has been commonly used. In this paper, we propose a new additive noise method, partial additive speech (PAS), which aims to train SV systems to be less affected by noisy environments. The experimental results demonstrate that PAS outperforms traditional additive noise in terms of equal error rates (EER), with relative improvements of 4.64% and 5.01% observed in SE-ResNet34 and ECAPA-TDNN. We also show the effectiveness of proposed method by analyzing attention modules and visualizing speaker embeddings.Comment: 5 pages, 2 figures, 1 table, accepted to CKAIA2023 as a conference pape

Free Flap Coverage of Extensive Soft Tissue Defect in Cutaneous Aspergillosis: A Case Report

Isolated fungal soft-tissue infections are uncommon, but may cause severe morbidity or mortality. Aspergillosis infection is rare, but the frequency in increasing over the last two decades. Here, we present a patient with cutaneous aspergillosis of his right elbow with unusual clinical and radiological features suggestive of a malignant disease, which remained undiagnosed for an extended period of time. The patient presented with necrotic, black-colored skin ulcerations. We completely removed the skin ulcer with the surrounding erythematous skin lesion, and then we reconstructed the area with thoracodorsal perforator free flap. The biopsy specimen contained septate hyphae with dichotomous branching, which is morphologically consistent with a finding of Aspergillus. After surgery, we initiated antifungal medication therapy with amphotericin B and itraconazole. At the time of follow-up, the elbow with the reconstructed flap had fully healed, and no recurrent disease was found

Application and evaluation of the MLVA typing assay for the Brucella abortus strains isolated in Korea

<p>Abstract</p> <p>Background</p> <p>A Brucella eradication program has been executed in Korea. To effectively prevent and control brucellosis, a molecular method for genetic identification and epidemiological trace-back must be established. As part of that, the MLVA typing assay was evaluated and applied to <it>B. abortus </it>isolates for analyzing the characteristics of the regional distribution and relationships of foreign isolates.</p> <p>Results</p> <p>A total of 177 isolates originating from 105 cattle farms for the period 1996 to 2008 were selected as representatives for the nine provinces of South Korea. A dendrogram of strain relatedness was constructed in accordance with the number of tandem repeat units for 17 loci so that it was possible to trace back in the restricted areas. Even in a farm contaminated by one source, however, the <it>Brucella </it>isolates showed an increase or decrease in one TRs copy number at some loci with high DI values. Moreover, those 17 loci was confirmed in stability via <it>in-vitro </it>and <it>in-vivo </it>passage, and found to be sufficiently stable markers that can readily identify the inoculated strain even if minor changes were detected. In the parsimony analysis with foreign <it>Brucella </it>isolates, domestic isolates were clustered distinctively, and located near the Central and Southern American isolates.</p> <p>Conclusion</p> <p>The MLVA assay has enough discrimination power in the <it>Brucella </it>species level and can be utilized as a tool for the epidemiological trace-back of the <it>B. abortus </it>isolates. But it is important to consider that <it>Brucella </it>isolates may be capable of undergoing minor changes at some loci in the course of infection or in accordance with the changes of the host.</p

Numb Chin Syndrome with Concomitant Painful Ophthalmoplegia Leading to a Diagnosis of Diffuse Large B Cell Lymphoma

Painful ophthalmoplegia (PO) and concomitant numb chin syndrome (NCS) is a very rare event. There are a few reports in the literature about PO and concomitant NCS that have preceded the diagnosis of a malignancy. In this report, we describe a patient with diffuse large B cell lymphoma who presented with PO and concomitant NCS as the initial symptom of the disease

The impact of the new ESTRO-ACROP target volume delineation guidelines for postmastectomy radiotherapy after implant-based breast reconstruction on breast complications

The European Society for Radiotherapy and Oncology–Advisory Committee in Radiation Oncology Practice (ESTRO-ACROP) updated a new target volume delineation guideline for postmastectomy radiotherapy (PMRT) after implant-based reconstruction. This study aimed to evaluate the impact on breast complications with the new guideline compared to the conventional guidelines. In total, 308 patients who underwent PMRT after tissue expander or permanent implant insertion from 2016 to 2021 were included; 184 received PMRT by the new ESTRO-ACROP target delineation (ESTRO-T), and 124 by conventional target delineation (CONV-T). The endpoints were major breast complications (infection, necrosis, dehiscence, capsular contracture, animation deformity, and rupture) requiring re-operation or re-hospitalization and any grade ≥2 breast complications. With a median follow-up of 36.4 months, the cumulative incidence rates of major breast complications at 1, 2, and 3 years were 6.6%, 10.3%, and 12.6% in the ESTRO-T group, and 9.7%, 15.4%, and 16.3% in the CONV-T group; it did not show a significant difference between the groups (p = 0.56). In multivariable analyses, target delineation is not associated with the major complications (sHR = 0.87; p = 0.77). There was no significant difference in any breast complications (3-year incidence, 18.9% vs. 23.3%, respectively; p = 0.56). Symptomatic RT-induced pneumonitis was developed in six (3.2%) and three (2.4%) patients, respectively. One local recurrence occurred in the ESTRO-T group, which was within the ESTRO-target volume. The new ESTRO-ACROP target volume guideline did not demonstrate significant differences in major or any breast complications, although it showed a tendency of reduced complication risks. As the dosimetric benefits of normal organs and comparable oncologic outcomes have been reported, further analyses with long-term follow-up are necessary to evaluate whether it could be connected to better clinical outcomes