Effect of Boswellia serrata extract on tissue inflammation and white blood cells responses of spinal cord injury in rat model

Introduction: The severe inflammatory responses that occurs after traumatic spinal cord injury (SCI) is with great strength related to the further tissue damage. As such, developmental strategies have been investigated, aimed at restricting inflammation and encouraging regeneration of injured neural tissue. One of those encouraging strategies is administration of traditional medicinal plants. The current study was conducted to evaluate the neuroprotective effects of Boswellia serrata extract on the neuronal tissue inflammation and white blood cells (WBCs) responses in rats with SCI. Methods: Forty adult female rats were randomly assigned into 2 equal groups as experimental and control groups. Under general inhalation anesthesia, in both groups, SCI was created, at T9-10 level of the column. On the third day after the operation, an oral supplement of B. serrata extract was administered to the experimental group at 100 mg/kg/d. The histology of the site of injury and changes in the WBCs were examined in both groups at different pre-surgical and post-surgical times. Results: The total population of WBCs in the current study was significantly less in the experimental group, compared to the control group at third and fourth weeks of the study which could be related to the anti-inflammatory effects of B. serrata extract. Histopathological evaluation of lesion sites confirmed the reduced inflammatory responses in the experimental group compared to the control group (P < 0.05). Conclusion: The decrease in the number of inflammatory cells after oral consumption of B. serrata extract and the histopathological results confirm the neuroprotective effects of this extract

Heterogeneous Graph Learning for Acoustic Event Classification

Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities. This makes modeling audiovisual data using heterogeneous graphs an attractive option. However, graph structure does not appear naturally in audiovisual data. Graphs for audiovisual data are constructed manually which is both difficult and sub-optimal. In this work, we address this problem by (i) proposing a parametric graph construction strategy for the intra-modal edges, and (ii) learning the crossmodal edges. To this end, we develop a new model, heterogeneous graph crossmodal network (HGCN) that learns the crossmodal edges. Our proposed model can adapt to various spatial and temporal scales owing to its parametric construction, while the learnable crossmodal edges effectively connect the relevant nodes across modalities. Experiments on a large benchmark dataset (AudioSet) show that our model is state-of-the-art (0.53 mean average precision), outperforming transformer-based models and other graph-based models.Comment: arXiv admin note: text overlap with arXiv:2207.0793

Graph neural network for audio representation learning

Learning audio representations is an important task with many potential applications. Whether it takes the shape of speech, music, or ambient sounds, audio is a common form of data that may communicate rich information. Audio representation learning is also a fundamental ingredient of deep learning. However, learning a good representation is a challenging task. Audio representation learning can also enable more accurate downstream tasks both in audio and video, such as emotion recognition. For audio representation learning, such a representation should contain the information needed to understand the input sound and make discriminative patterns. This necessitates a sizable volume of carefully annotated data, which requires a considerable amount of labour. In this thesis, we propose a set of models for audio representation learning. We address the discriminative patterns by proposing graph structure and graph neural network to further process it. Our work is the first to consider the graph structure for audio data. In contrast to existing methods that use approximation, our first model proposes a manual graph structure and uses a graph convolution layer with accurate graph convolution operation. In the second model, By integrating a graph inception network, we expand the manually created graph structure and simultaneously learn it with the primary objective in our model. In the third model, we addressed the dearth of annotated data by including a semi-supervised graph technique that represents audio corpora as nodes in a graph and connects them depending on label information in smaller subgraphs. We brought up the issue of leveraging multimodal data to improve audio representation learning in addition to earlier works. To accommodate multimodal input data, we included heterogeneous graph data to our fourth model. Additionally, we created a new graph architecture to handle multimodal data

Compact graph architecture for speech emotion recognition

We propose a deep graph approach to address the task of speech emotion recognition. A compact, efficient and scalable way to represent data is in the form of graphs. Following the theory of graph signal processing, we propose to model speech signal as a cycle graph or a line graph. Such graph structure enables us to construct a Graph Convolution Network (GCN)-based architecture that can perform an accurate graph convolution in contrast to the approximate convolution used in standard GCNs. We evaluated the performance of our model for speech emotion recognition on the popular IEMOCAP and MSP-IMPROV databases. Our model outperforms standard GCN and other relevant deep graph architectures indicating the effectiveness of our approach. When compared with existing speech emotion recognition methods, our model achieves comparable performance to the state-of-the-art with significantly fewer learnable parameters (~30K) indicating its applicability in resource-constrained devices. Our code is available at /github.com/AmirSh15/Compact_SER

Zimmermann-Laband syndrome : clinical and cytogenetic study in two related patients

Zimmermann?Laband Syndrome (ZLS) is an extremely rare autosomal dominant congenital disorder. It is a craniofacial malformation syndrome with predominant intraoral involvement consisting of gingival fibromatosis diffusion in early development. The molecular basis of ZLS is still unknown. Although familial aggregation with different inheritance patterns is detected in ZLS patients, most of the cases are sporadic. We report on two sibling patients with clinical manifestations of ZLS. Blood samples of both patients were obtained in EDTA-tubes followed by performing cytogenetic study using Cyto2.7M array. Analysis of the copy number was performed using the Chromosome Analysis Suite Software (version 1.0.1, annotation file na 30, Affymetrix) and interpreted with recourse to the UCSC genome browser (http://genome.ucsc.edu/; Human Mar. 2006NCBI Build 36.1/hg18 assembly). The array analysis revealed overlapping regions of chromosomal aberrations in both patients. We detected a 258-kb deletion at 3q13.13, a 89-kb duplication at 1q25.2 as well as two 67-kb duplications at 1p12 and 19q12. These altered regions do not contain any known genes and protein-coding sequences. In conclusion, the findings of this report revealed new chromosomal aberrations, including a deletion at 3q13.13 and duplications at 1q25.2, 1p12 and 19q12, in the two patients with ZLS. Such findings indicate that whole genome screening for genomic rearrangements is fruitful in typical and atypical patients with ZLS

RHETORICAL STRUCTURE OF INTEGRATED RESULTS AND DISCUSSION CHAPTER IN MASTER’S DISSERTATIONS ACROSS DISCIPLINES

Writing a dissertation is the most challenging task for students, especially the IntegratedResults and Discussion chapter. One solution would be to offer them a template of therhetorical flow of this chapter. However, to date, a limited number of studies have beenconducted on the rhetorical movement of this chapter. Therefore, the rhetorical units ofIntegrated Results and Discussion chapters of 40 Master’s dissertations in the hard and softscience disciplines obtained from a Malaysian local public university were investigated.The findings indicated that this chapter focused predominantly on presenting the resultsfollowed by commenting on them. Disciplinary variation was observed in the use of‘referring to previous research’ and ‘making overt claims or generalizations’ which wereobserved more in the dissertations in the soft sciences. Besides, ‘invalidating results’ wasfound more in the dissertations in the hard sciences. To conclude, knowing the prevalentmoves may heighten the awareness of novice postgraduate students to align their writing tothe academic writing conventions. Furthermore, awareness on the disciplinary variationsof the use of certain rhetorical moves would sensitize novice writers to the preferreddisciplinary style of writing Integrated Results and Discussion chapter

Effect of biomass fuel combustion on increasing the risk of chronic Bronchitis in women, Shahrekord, 2001

به نظر می رسد که میزان برونشیت در زنان این استان زیاد باشد که احتمالا ناشی از استنشاق هوای آلوده ناشی از سوخت های آلی و چوب است. لذا در یک مطالعه مورد-شاهدی در زنان بالای 40 سال به بررسی احتمال دخالت سوخت مواد آلی و سیگار در ایجاد برونشیت مزمن پرداخته شد. از مراجعه کنندگان به درمانگاه ریه یکصد نفر مبتلا به برونشیت مزمن به عنوان مورد و از بین بیماران بستری 100 نفر به عنوان گروه کنترل انتخاب شدند. افراد این دو گروه به سوالات پرسشنامه در مورد سابقه پخت نان در منزل، نوع سوخت مصرفی برای گرمایش منزل، سوخت آشپزخانه و سوخت تنور پاسخ دادند. عوامل زیر با ایجاد برونشیت مزمن در زنان شهرکرد رابطه آماری معنی داری داشت. سیگار (P=0.009)، قلیان (P=0.014)، پخت نان با تنور در منزل (P=0.002)، وجود بخاری چوب سوز (P=0.009)، مصرف چوب برای آشپزی (P=0.000)، مصرف نفت برای آشپزی (P=0.000) و مصرف چوب برای تنور نان پزی (P=0.000). سوخت چوب برای آشپزی، پخت نان و گرم کردن منزل علل مهم ایجاد برونشیت مزمن در زنان منطقه چهارمحال و بختیاری می باشد و جایگزینی چوب و نفت با سوخت های بهداشتی تر (مثل گاز) باعث کاهش بیماری برونشیت مزمن خواهد شد

Prenatal diagnosis of de novo small supernumerary marker chromosome 4q (4q11-q12): A case report

Background: Small supernumerary marker chromosomes (sSMCs) are chromosomal fragments with abnormal structures found in patients with fertility problems and developmental delay. They may be detected in amniotic cell karyotypes. sSMCs are categorized as hereditary or de novo. Here, we describe a case of prenatal de novo 4q11q12 sSMC and its molecular cytogenetic features which had no apparent phenotypic abnormality. Case: The fetus of a 36-yr-old pregnant woman was detected positive for Down’s syndrome (trisomy 21) at the 16th wk of gestation. Quantitative fluorescent polymerase chain reaction technique was applied for the rapid detection of numerical aneuploidy of chromosomes X, Y, 13, 18, and 21 microsatellites. Array comparative genomic hybridization (array CGH) technique was also conducted following the karyotype analysis of amniotic cells. The karyotype analysis was also done for the parents. Quantitative fluorescent polymerase chain reaction result revealed a male fetus with a normal chromosomal pattern, while the amniocentesis karyotype analysis identified a male fetus with a marker chromosome (47, XY, +mar), and the sSMC were existing in 100% of amniocyte metaphase spreads. The parents’ normal karyotypes indicated that the sSMC was de novo. Array CGH analysis revealed a 6.48-Mb duplication at 4q11q12. Eventually, the parents decided to terminate the pregnancy by legal abortion. Conclusion: Our study highlights the importance of the application of array CGH in combination with karyotype analysis for rapid and precise prenatal diagnosis of partial aneuploidy region. &nbsp;Key words: Prenatal diagnosis, Array CGH, Chromosome 4, Chromosome markers

Discrepancy of target sites between clinician and cytopathological reports in head neck fine needle aspiration: Did I miss the target or did the clinician mistake the organ site?

The diagnostic accuracy of fine needle aspiration cytology (FNAC) of head and neck lesions is relatively high, but cytologic interpretation might be confusing if the sample is lacking typical cytologic features according to labeled site by physician. These errors may have an impact on pathology search engines, healthcare costs or even adverse outcomes. The cytology archive database of multiple institutions in southern Iran and Australia covering the period 2001–2011, were searched using keywords: salivary gland, head, neck, FNAC, and cytology. All the extracted reports were reviewed. The reports which showed discordance between the clinician’s impression of the organ involved and subsequent fine needle biopsy request, and the eventual cytological diagnosis were selected. The cytological diagnosis was confirmed by histology or cell block, with assistance from imaging, clinical outcome, physical examination, molecular studies, or microbiological culture. The total number of 10,200 head and neck superficial FNAC were included in the study, from which 48 cases showed discordance between the clinicians request and the actual site of pathology. Apart from the histopathology, the imaging, clinical history, physical examination, immunohistochemical study, microbiologic culture and molecular testing helped to finalize the target organ of pathology in 23, 6, 7, 8, 2, and 1 cases respectively. The commonest discrepancies were for FNAC of “salivary gland” [total: 20 with actual final pathology in: bone (7), soft tissue (5), lymph node (3), odontogenic (3) and skin (2)], “lymph node” [total: 12 with final pathology in: soft tissue (3), skin (3), bone (1) and brain (1)], “soft tissue” [total: 11 with final pathology in: bone (5), skin (2), salivary gland (1), and ocular region (1)] and “skin” [total: 5 with final pathology in: lymph node (2), bone (1), soft tissue (1) and salivary gland (1)]. The primary physician requesting FNAC of head and neck lesions are incorrect in their clinical impression of the actual site in nearly 0.5 percent of cases, due to the overlapping clinical and imaging findings or possibly due to inadequate history taking or physical examination