Outcomes of distal ulna locking plate in management of unstable distal ulna fractures: a prospective case series.

INTRODUCTION: Given the absence of a satisfying plate system to deal with multifragmentary or subcapital distal ulnar fractures, the Distal Ulna Locking Plate (DUL, I.T.S. GmbH, Graz, Austria) could become a useful treatment option. This study aimed to evaluate the results of this anatomically pre-contoured plate regarding patients with unstable or displaced distal ulnar fractures. METHODS: In a prospective clinical trial, 20 patients (18 female, two male; mean age 70 years (24-91 years)) with unstable or displaced distal ulna fractures between December 2010 and August 2015 were analyzed. All patients were treated with open reduction and internal fixation using the DUL. They were evaluated at three follow-up appointments at 3, 6 and 12 months postoperatively regarding their bone healing, ulnar variance (UV), range of motion (ROM) and grip strength. Patient related outcomes were measured using the Disability of the Arm, Shoulder and Hand (DASH), the Patient Rated Wrist Evaluation (PRWE) questionnaires, and the Visual Analogue Scale (VAS). The results after one year were compared to the outcome of the healthy contralateral side. RESULTS: All fractures treated with open reduction and internal fixation using the Distal Ulna Locking Plate healed within 6 months and showed stable ulnar variances after surgery. ROM (rotational plane 81.1 ± 9.0°, sagittal plane 55.1 ± 14.6°, frontal plane 33.0 ± 9.4°) and grip strength (18.7 ± 7.1 N) at the follow-up after 12 month had similar values compared with the uninjured side. The mean DASH score (36.4 ± 29.0), the PRWE-score (14.5 ± 27.0), and the VAS (at rest 0.5 ± 1.1, during activity 1.2 ± 2.4) after one year had no significant difference to the uninjured side. The surgeon's overall satisfaction rate regarding plate handling reached 81.8%. CONCLUSION: Stabilization of unstable distal ulna fractures using the DUL restores nearly normal anatomy and function. Its pre-countered design, volar placement, and enhanced stability present a satisfying plate system. TRIAL REGISTRATION:  The trial was retrospectively Registered at www. CLINICALTRIALS: gov on 16 December 2021 (Trial Registration Number: NCT05329012).

Three-dimensional localization microscopy using deep learning.

Single molecule localization microscopy (SMLM) is one of the fastest evolving and most broadly used super-resolving imaging techniques in the biosciences. While image recordings could take up to hours only ten years ago, scientists are now reaching for real-time imaging in order to follow the dynamics of biology. To this end, it is crucial to have data processing strategies available that are capable of handling the vast amounts of data produced by the microscope. In this article, we report on the use of a deep convolutional neural network (CNN) for localizing particles in three dimensions on the basis of single images. In test experiments conducted on fluorescent microbeads, we show that the precision obtained with a CNN can be comparable to that of maximum likelihood estimation (MLE), which is the accepted gold standard. Regarding speed, the CNN performs with about 22k localizations per second more than three orders of magnitude faster than the MLE algorithm of ThunderSTORM. If only five parameters are estimated (3D position, signal and background), our CNN implementation is currently slower than the fastest, recently published GPU-based MLE algorithm. However, in this comparison the CNN catches up with every additional parameter, with only a few percent extra time required per additional dimension. Thus it may become feasible to estimate further variables such as molecule orientation, aberration functions or color. We experimentally demonstrate that jointly estimating Zernike mode magnitudes for aberration modeling can significantly improve the accuracy of the estimates.

Visible- and near-infrared hyperspectral imaging for the quantitative analysis of PD-L1+ cells in human lymphomas: Comparison with fluorescent multiplex immunohistochemistry.

INTRODUCTION: We analyzed the expression of PD-L1 in human lymphomas using hyperspectral imaging (HSI) compared to visual assessment (VA) and conventional digital image analysis (DIA) to strengthen further the value of HSI as a tool for the evaluation of brightfield-based immunohistochemistry (IHC). In addition, fluorescent multiplex immunohistochemistry (mIHC) was used as a second detection method to analyze the impact of a different detection method. MATERIAL AND METHODS: 18 cases (6 follicular lymphomas and 12 diffuse large B-cell lymphomas) were stained for PD-L1 by IHC and for PD-L1, CD3, and CD8 by fluorescent mIHC. The percentage of positively stained cells was evaluated with VA, HSI, and DIA for IHC and VA and DIA for mIHC. Results were compared between the different methods of detection and analysis. RESULTS: An overall high concordance was found between VA, HSI, and DIA in IHC (Cohens Kappa = 0.810VA/HSI, 0.710 VA/DIA, and 0.516 HSI/DIA) and for VAmIHCversus DIAmIHC (Cohens Kappa = 0.894). Comparing IHC and mIHC general agreement differed depending on the methods compared but reached at most a moderate agreement (Cohens Kappa between 0.250 and 0.483). This is reflected by the significantly higher percentage of PD-L1+ cells found with mIHC (pFriedman = 0.014). CONCLUSION: Our study shows a good concordance for the different analysis methods. Compared to VA and DIA, HSI proved to be a reliable tool for assessing IHC. Understanding the regulation of PD-L1 expression will further enlighten the role of PD-L1 as a biomarker. Therefore it is necessary to develop an instrument, such as HSI, which can offer a reliable and objective evaluation of PD-L1 expression.

Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep learning approach to analyze MIR hyperspectral data obtained from benign and malignant lymph node pathology results in high accuracy for correct classification, learning the distinct region of 3900 to 850 cm-1 . The accuracy is above 95% for every pair of malignant lymphoid tissue and still above 90% for the distinction between benign and malignant lymphoid tissue for binary classification. These results demonstrate that a preliminary diagnosis and subtyping of human lymphoma could be streamlined by applying a deep learning approach to analyze MIR spectroscopic data.

Visible and Near-Infrared hyperspectral imaging (HSI) can reliably quantify CD3 and CD45 positive inflammatory cells in myocarditis: Pilot study on formalin-fixed paraffin-embedded specimens from myocard obtained during autopsy.

INTRODUCTION: To implement Hyperspectral Imaging (HSI) as a tool for quantifying inflammatory cells in tissue specimens by the example of myocarditis in a collective of forensic patients. MATERIAL AND METHODS: 44 consecutive patients with suspected myocardial inflammation at autopsy, diagnosed between 2013 and 2018 at the Institute of ForensicMedicine, Medical University of Innsbruck, were selected for this study. Using the IMEC SNAPSCAN camera, visible and near infrared hyperspectral images were collected from slides stained with CD3 and CD45 to assess quantity and spatial distribution of positive cells. Results were compared with visual assessment (VA) and conventional digital image analysis (DIA). RESULTS: Finally, specimens of 40 patients were evaluated, of whom 36 patients (90%) suffered from myocarditis, two patients (5%) had suspected healing/healed myocarditis, and two did no have myocarditis (5%). The amount of CD3 and CD45 positive cells did not differ significantly between VA, HSI, and DIA (pVA/HSI/DIA = 0.46 for CD3 and 0.81 for CD45). Cohens Kappa showed a very high correlation between VA versus HSI, VA versus DIA, and HSI versus DIA for CD3 (Cohens Kappa = 0.91, 1.00, and 0.91, respectively). For CD45 an almost as high correlation was seen for VA versus HSI and HSI versus DIA (Cohens Kappa = 0.75 and 0.70) and VA versus DIA (Cohens Kappa = 0.89). CONCLUSION: HSI is a reliable and objective method to count inflammatory cells in tissue slides of suspected myocarditis. Implementation of HSI in digital pathology might further expand the possibility of a sophisticated method.

Raman microscopic spectroscopy as a diagnostic tool to detect Staphylococcus epidermidis in bone grafts.

INTRODUCTION: Raman microscopic spectroscopyis a new approach for further characterization and detection of molecular features in many pathological processes. This technique has been successfully applied to scrutinize the spatial distribution of small molecules and proteins within biological systems by in situ analysis. This study uses Raman microscopic spectroscopyto identify any in-depth benefits and drawbacks in diagnosing Staphylococcus epidermidis in human bone grafts. MATERIAL AND METHODS: 40 non-infected human bone samples and 10 human bone samples infected with Staphylococcus epidermidis were analyzed using Raman microscopic spectroscopy. Reflectance data were collected between 200 cm-1 and 3600 cm-1 with a spectral resolution of 4 cm-1 using a Senterra II microscope (Bruker, Ettlingen, Germany). The acquired spectral information was used for spectral and unsupervised classification, such as principal component analysis. RESULTS: Raman measurements produced distinct diagnostic spectra that were used to distinguish between non-infected human bone samples and Staphylococcus epidermidis infected human bone samples by spectral and principal component analyses. A substantial loss in bone quality and protein conformation was detected by human bone samples co-cultured with Staphylococcus epidermidis. The mineral-to-matrix ratio using the phosphate/Amide I ratio (p = 0.030) and carbonate/phosphate ratio (p = 0.001) indicates that the loss of relative mineral content in bones upon bacterial infection is higher than in non-infected human bones. Also, an increase of alterations in the collagen network (p = 0.048) and a decrease in the structural organization and relative collagen in infected human bone could be detected. Subsequent principal component analyses identified Staphylococcus epidermidis in different spectral regions, respectively, originating mainly from CH2 deformation (wagging) of protein (at 1450 cm-1) and bending and stretching modes of C-H groups (∼2800-3000 cm-1). CONCLUSION: Raman microscopic spectroscopyis presented as a promising diagnostic tool to detect Staphylococcus epidermidis in human bone grafts. Further studies in human tissues are warranted.

Antimicrobial use and susceptibility rates in isolates from intensive care unit and other nosocomial inpatient and outpatient areas.

Our objective was to evaluate the relation between antimicrobial use and susceptibility in the intensive care unit (ICU) and non-ICU inpatient areas in the Bolzano regional hospital. For the isolates of S. aureus, coagulase negative staphylococci, Enterococcus sp., P. aeruginosa and E. coli we found a pattern of significant stepwise decrease in the frequency of antimicrobial susceptibility to penicilloic beta-lactam antibiotics and first generation cephalosporins; the highest senitivity rates occurred among isolates from outpatients, followed in decreasing order by rates among isolates from non-ICU inpatients and from ICU-patients; the rate of use of this group of antimicrobial agents was relatively high in the intensive care unit (13,1%). For P. aeruginosa we observed significantly lower susceptibility-rates to second, third and fourth generation cephalosporins, carbapenems and monobactams for non-ICU inpatient areas than for outpatient or ICU areas; this paralleled with the low use of this group of agents in the ICU area (4,9%). Also, for P. aeruginosa the prevalence of susceptibility to ciprofloxacin and norfloxacin in inpatient areas was lower than in the outpatient or ICU-areas; the rate of quinolone-use was relatively low in the ICU area (4,2%).