Learning from EMG: semi-automated grading of facial nerve function

The current grading of facial nerve function is based on subjective impression with the established assessment scale of House and Brackmann (HB). Especially for research a more objective method is needed to lower the interobserver variability to a minimum. We developed a semi-automated grading system based on (facial) surface EMG-data measuring the facial nerve function of 28 patients with vestibular schwannoma surgery. The sEMG was recorded preoperatively, postoperatively and after 3–12 months. In addition, the HB grade was determined. After manual selection and preprocessing, the data were subjected to machine learning classificators (Logistic regression, SVM and KNN). Lateralization indices were calculated and multivariant machine learning analysis was performed according to three scenarios [differentiation of normal (1) and slight (2) vs. impaired facial nerve function and classification of HB 1-3 (3)]. The calculated AUC for each scenario showed overall good differentiation capability with a median AUC of 0.72 for scenario 1, 0.91 for scenario 2 and multiclass AUC of 0.74 for scenario 3. This study approach using sEMG and machine learning shows feasibility regarding facial nerve grading in perioperative VS-surgery setting. sEMG may be a viable alternative to House Brackmann regarding objective evaluation of facial function especially for research purposes.

A Scoring System for Assessing the Risk of Malignant Partially Cystic Thyroid Nodules Based on Ultrasound Features

ObjectiveTo assess the ultrasound (US) features of partially cystic thyroid nodules (PCTNs) and to establish a scoring system to further improve the diagnostic accuracy.MethodsA total of 262 consecutive nodules from September 2017 to March 2020 were included in a primary cohort to construct a scoring system. Moreover, 83 consecutive nodules were enrolled as an validation cohort from May 2018 to August 2020. All nodules were determined to be benign or malignant according to the pathological results after surgery or ultrasound-guided fine-needle aspiration (US-FNA). The US images and demographic characteristics of the patients were analyzed. The ultrasound features of PCTNs were extracted from primary cohort by two experienced radiologists. The features extracted were used to develop a scoring system using logistic regression analysis. Receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic efficacy of the scoring system in both the primary cohort and validation cohort. In addition, the radiologists evaluated the benign and malignant PCTNs of the validation cohort according to the ACR TI-RADS guidelines and clinical experience, and the accuracy of their diagnosis were compared with that of the scoring system.ResultsBased on the eight features of PCTNs, the scoring system showed good differentiation and reproducibility in both cohorts. The scoring system was based on eight features of PCTNs and showed good performance. The area under the curve (AUC) was 0.876 (95% CI, 0.830 - 0.913) in the primary cohort and 0.829(95% CI, 0.730 - 0.903) in the validation cohort. The optimal cutoff value of the scoring system for the diagnosis of malignant PCTNs was 4 points, with a good sensitivity of 71.05% and specificity of 87.63%. The scoring system (AUC=0.829) was superior to radiologists (AUC= 0.736) in diagnosing PCTNs and is a promising method for clinical application.ConclusionsThe scoring system described herein is a convenient and clinically valuable method that can diagnose PCTNs with relatively high accuracy. The use of this method to diagnose PCTNs, which have been previously underestimated, will allow PCTNs to receive reasonable attention, and assist radiologist to confidently diagnose the benignity or malignancy.

Design of a Generic Virtual Measurement Workflow for Processing Archived Point Cloud of Trees and Its Implementation of Light Condition Measurements on Stems

Virtual measurement workflow (VMW) was a generic data mining method developed in this study. It was used to extract tree information from archived point clouds under limited conditions by applying virtual measurements in virtual reality. As an example of how to use VMW for a specific topic, the VMW implementation of light condition measurement was further developed. This implementation could measure the temporal and spatial distribution of sunlight on virtual trees (stems). The output was expected as a new type of raw measurement data for tree morphology and phycological studies. At a single tree scale, it facilitated the quantitative interpretation of the growth strategy of branches. By measuring a single tree, it was found that only 4.34% of the stem surface could be illuminated throughout the day (8 h). Meanwhile, 35.87% of the stem surfaces were exposed to sunlight for less than one hour a day. A further mathematical processing of the output, i.e., γ (a ratio between relative area of triangles and relative quantities of triangles in each exposure duration group) improved the sensitivity of identifying differences in lighting conditions. Furthermore, we measured virtual trees of four species from an additional data source using a standardized setting. These include the sessile oak, gemu tree, Masson’s pine, and cherry tree. It was found that the shape of the crown was also significant for the distribution of solar energy on stems. For instance, the gemu tree had a cylindrical tree crown with narrow tree skeleton. A percentage of 10.38 of the surface on the gemu tree was illuminated throughout the day (8 h). The Masson’s pine had similar height and DBH with the gemu tree. However, the elliptical tree crown of the Masson’s pines prevented more lights. The area on the stem that was exposed to sunlight (8 h) dropped from 10.38% to 5.71%. This good differentiation of different crown structures might help this VMW implementation to continue to develop as a tool for identifying the effect of various crown shapes on radiosity for different tree species. The successful development of this VMW implementation had several practical applications for tree studies. Meanwhile, it demonstrated the overall feasibility of VMW and provided a paradigm for further development of other VMW implementations.

Pathomics and Deep Learning Classification of a Heterogeneous Fluorescence Histology Image Dataset

Automated pathology image classification through modern machine learning (ML) techniques in quantitative microscopy is an emerging AI application area aiming to alleviate the increased workload of pathologists and improve diagnostic accuracy and consistency. However, there are very few efforts focusing on fluorescence histology image data, which is a challenging task, not least due to the variable imaging acquisition parameters in pooled data, which can diminish the performance of ML-based decision support tools. To this end, this study introduces a harmonization preprocessing protocol for image classification within a heterogeneous fluorescence dataset in terms of image acquisition parameters and presents two state-of-the-art feature-based approaches for differentiating three classes of nuclei labelled by an expert based on (a) pathomics analysis scoring an accuracy (ACC) up to 0.957 ± 0.105, and, (b) transfer learning model exhibiting ACC up-to 0.951 ± 0.05. The proposed analysis pipelines offer good differentiation performance in the examined fluorescence histology image dataset despite the heterogeneity due to the lack of a standardized image acquisition protocol.

A tufA metabarcoding approach for Ulva and related seaweeds

Ulva-like green algae are notoriously difficult to distinguish due to their morphological variability and/or similarity. DNA barcoding approaches are therefore currently essential for their reliable identification. However, such approaches often fail when rare or inconspicuous species are to be detected in large mixed populations of Ulva species, for example, at early stages following the introduction of species into new habitats. We therefore developed a detection method based on next-generation DNA sequencing. The approach is suitable for the analysis of DNA traces in preserved water samples or in particles enriched by filtration from such samples. A new pair of primers was designed to amplify a 475 bp segment within the tufA marker gene. The primers were relatively group specific. 68.5% of all reads obtained after quality filtering represented the genus Ulva, 11.1% other Ulvophyceae, and only 20% other Chlorophyta, despite their relatively higher abundance in phytoplankton. The relatively short target amplicon still allows good differentiation of Ulvales and Ulothrichales at the species level. Using a database containing tufA sequences of 879 species - 281 of which were Ulvophyceae and 35 Ulva - we were able to detect mostly Ulvophyceae that had been previously detected in our study area in northern Germany using Sanger sequencing. However, the number of species detected at individual sites was generally higher than in previous studies, which could be due to drifting DNA: Analysis of samples collected at different distances from shore suggests that a sample collected at a given site may be influenced by Ulvophyceae within a radius of up to about 1 km in winter. In summer, this radius is reduced to less than 100 m, possibly due to the less frequent occurrence of strong wind events. Nonetheless, rare species may be detected with this new approach: At one site, an undescribed Blidingia species that was not previously known from our study area was repeatedly detected. Based on these findings, the species was searched for and found, and its identity confirmed by traditional tufA barcoding.

Establishment and verification of an osteoporosis risk model in patients with rheumatoid arthritis: a valuable new model

Summary To establish a model for osteoporosis risk in patients with rheumatoid arthritis and validate the model. A newly generated predictive model has been suggested to have good differentiation, calibration, and clinical validity and may be a useful clinical model for predicting osteoporosis in patients with rheumatoid arthritis. Purpose To establish a prediction model for osteoporosis risk in patients with rheumatoid arthritis and validate the model internally and externally. Methods A total of 270 patients with rheumatoid arthritis who underwent bone mineral density measurement at our hospital from June 2019 to June 2020 were enrolled in the study. The patients were divided into two groups according to their entry time: a training set containing the first 2/3 of the patients (n = 180) and a validation set containing the remaining 1/3 of the patients (n = 90). Binary logistic regression analysis was used to establish the regression models, and the concordance index (C-index), calibration plot, and decision curve analysis were used to evaluate the prediction model. Results Five variables, including age (X1), course of disease (X2), the disease activity score using 28 joint counts (DAS28) (X4), anti-cyclic citrullinated peptide antibody (CCP) (X7), and 7-joint ultrasonic bone erosion (X14), were selected to enter the model. The prediction model is Logit Y = − 12.647 + 0.133X1 + 0.011X2 + 0.754X4 + 0.001X7 + 0.605X14. The model had good differentiation; the C-index in the internal verification was 0.947 (95% CI is 0.932–0.977) and the C-index in the external verification was 0.946 (95% CI is 0.940–0.994). The calibration plot of the model showed excellent consistency between the prediction probability and actual probability. When > 0.483 was taken as the cutoff value for the diagnosis of osteoporosis, the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and Jordan index of the model were 90.24%, 87.76%, 7.37, 0.11, and 78.00%, respectively. Conclusion A newly generated predictive model has been suggested to have good differentiation, calibration, and clinical validity and may be a useful clinical model for predicting osteoporosis in patients with rheumatoid arthritis.

Stability of canine and feline cerebrospinal fluid samples regarding total cell count and cell populations stored in “TransFix®/EDTA CSF sample storage tubes”

Background Because of fast leucocyte degeneration in cerebrospinal fluid (CSF) laboratory examinations of CSF samples should be performed approximately within 30 min after withdrawal. This study examines the storage of canine and feline CSF samples in “TransFix®/EDTA CSF Sample Storage Tubes” (Cytomark, Buckingham, UK) for preventing leucocytes from degeneration, so that routine and flow cytometry examinations are feasible up to 3 days after sampling. Results After storage in TransFix® tubes, leukocytes could not be adequately stained with Türk’s solution and differentiating between erythrocytes and leukocytes was cumbersome. In addition, the cell morphology could not be sufficiently assessed on cytospin preparations because of shrunken leukocytes and indistinct cell nuclei. In contrast, by flow cytometry, a significantly higher cell count was measured over the entire study period in the samples stored in TransFix® tubes compared to the untreated samples. The antibodies (AB) against CD3, CD4 and CD21, against CD11b and against CD45 showed a good binding strength and thus enabled a good differentiation of cell populations. However, after storage in the TransFix® tubes, monocytes were no longer detectable using an AB against CD14. Conclusion Based on these results, “TransFix®/EDTA CSF Sample Storage Tubes” can be used for extended storage prior to flow cytometric analysis of lymphocytes and granulocytes in CSF samples but not for detecting monocytes. However, standard examinations, such as microscopic cell counting and morphological cell assessment should be performed on fresh CSF samples.

Development and Validation of a High Sensitivity Assay for Measuring p217 + tau in Cerebrospinal Fluid

Background: Early and accurate detection and staging is critical to managing Alzheimer’s disease (AD) and supporting clinical trials. Cerebrospinal fluid (CSF) biomarkers for amyloid-β peptides, tau species, and various neurodegenerative and inflammatory analytes are leading the way in this regard, yet there is room for improved sensitivity and specificity. In particular tau is known to be present in many different fragments, conformations, and post-translationally modified forms. While the exact tau species that might best reflect AD pathology is unknown, a growing body of evidence suggests that forms with high levels of phosphorylation in the mid-region may be especially enriched in AD. Objective: Develop an assay for measuring p217tau in CSF. Methods: Here we describe the development and validation of a novel sELISA for measuring CSF tau species containing phosphorylation at threonines 212 & 217, aka p217 + tau, using the PT3 antibody. Results: While the analyte is present at extremely low levels the assay is sufficiently sensitive and specific to quantitate p217 + tau with excellent precision, accuracy, and dilution linearity, allowing good differentiation between diagnostic subgroups. The p217 + tau measurements appear to track AD pathology better than the commonly used p181tau epitope, suggesting superior diagnostic and staging performance. Finally, the assay can also be configured to differentiate antibody-bound versus antibody-free tau, and therefore can be used to measure target engagement by p217 + tau-targeting immunotherapeutics. Conclusion: The assay for measuring p217 + tau described here is highly sensitive, accurate, precise, dilution linear, and shows good potential for identifying and staging AD.

Negative Expression of DSG1 and DSG2, as Prognostic Biomarkers, Impacts on the Overall Survival in Patients with Extrahepatic Cholangiocarcinoma

Aims. To evaluate the expression of DSG1 and DSG2 and investigate their clinicopathological significance in EHCC. Method. The protein expression of DSG1 and DSG2 was measured by EnVision immunohistochemistry in 15 normal biliary tract tissues, 10 biliary tract adenoma tissues, 30 peritumoral tissues, and 100 EHCC tumour tissues. Result. The expression of the DSG1 and DSG2 proteins was significantly lower in EHCC tumour tissues than in normal biliary tract tissues, biliary tract adenoma, and peritumoral tissues (P<0.05). Adenoma and peritumoral tissues with negative DSG1 and/or DSG2 protein expression exhibited atypical hyperplasia. DSG1 expression was positively correlated with DSG2 expression in EHCC (P<0.01). In patients with good differentiation, no invasion, no lymph metastasis, TNM I + II stage, and radical surgery, the positive expression of DSG1 and DSG2 proteins was higher (P<0.05). In comparison to patients with negative DSG1 and/or DSG2 expression, the average overall survival time of those with positive expression was significantly longer (P=0.000). Cox multivariate analysis revealed that negative DSG1 and DSG2 expressions were independent of poor prognosis factors in EHCC patients. The AUC calculated for DSG1 was 0.681 (95% confidence interval: 0.594–0.768) and that for DSG2 was 0.645 (95% confidence interval: 0.555–0.734), while that for DSG1 and DSG2 was 0.772 (95% confidence interval: 0.609-0.936). Conclusions. Negative protein expression of DSG1 and DSG2 is closely related to the pathogenesis, severe clinicopathological characteristics, aggressive biological behaviours, and dismal prognosis in EHCC.

Validitas Instrumen Penilaian Kemampuan Berpikir Tingkat Tinggi tentang Materi Tumbuhan untuk Peserta Didik SMA/MA Kelas X

ABSTRACT. Assessment in the 2013 curriculum places more emphasis on cognitive assessment possessed by students. Assessment instruments made by teachers at daily tests are generally still at the C1-C3 cognitive level, instruments that can be used to train students' abilities are at the C4-C6 level. This study aims to produce instruments for assessing higher order thinking skills on Plant material for high, reliable, high school/MA grade X students, difficulty levels, distinguishing features and good quality options. This study uses 4-D models. Which consists of the stages define, design, develop and disseminate. The disseminate stage was not carried out. The subjects of this research were 34 students of SMAN 7 Padang. The validity test results show logically valid questions with an average value of 3.27 with valid criteria. The average practicality value of 98.61% with very practical question criteria, the reliability of the questions is 0.85, and the level of difficulty of the questions between 0.29 to 0.67 with moderate criteria, as well as the questions have a good difference in power and good quality of question options. From the research it can be concluded that an instrument of assessment of high-level thinking ability about Plant material for high-school/MA grade X students has been produced which is valid, reliable, has a moderate level of difficulty, good differentiation and good quality options. ABSTRAK. Penilaian dalam kurikulum 2013 lebih menekankan kepada penilaian kognitif yang dimiliki peserta didik. Instrumen penilaian yang dibuat oleh guru pada ulangan harian umumnya masih berada pada tingkatan kognitif C1-C3, instrumen yang dapat digunakan untuk melatih kemampuan peserta didik berada pada tingkatan C4-C6. Penelitian ini bertujuan untuk menghasilkan instrumen penilaian kemampuan berpikir tingkat tinggi pada materi Tumbuhan untuk peserta didik SMA/MA Kelas X yang valid, reliabel, tingkat kesukaran sedang, daya pembeda dan kualitas option yang baik. Penelitian ini menggunakan model yaitu 4-D models. Yang terdiri dari tahap define, design, develop dan disseminate. Tahap dessiminate itu tidak dilakukan. Subjek penelitian ini yaitu 34 orang siswa SMAN 7 Padang. Hasil uji validitas menunjukkan soal valid secara logis dengan rata-rata nilai yaitu 3,27 dengan kriteria valid. Nilai rata-ra praktikalitas 98,61% dengan kriteria soal sangat praktis, reliabilitas soal yaitu 0,85, serta tingkat kesukaran soal antara 0,29 sampai 0,67 dengan kriteria sedang, serta soal memiliki daya beda yang baik dan kualitas option soal yang baik. Dari penelitian dapat disimpulkan telah dihasilkan instrumen penilaian kemampuan berpikir tingkat tinggi tentang materi Tumbuhan untuk peserta didik SMA/MA kelas X yang valid, reliabel, tingkat kesukaran sedang, daya pembeda yang baik dan kualitas option yang baik.