Platelet-Rich Plasma Injection With Percutaneous Needling for Recalcitrant Lateral Epicondylitis: Comparison of Tenotomy and Fenestration Techniques.

Background: Recalcitrant lateral epicondylitis (LE) is a common debilitating condition, with numerous treatment options of varying success. An injection of platelet-rich plasma (PRP) has been shown to improve LE, although it is unclear whether the method of needling used in conjunction with a PRP injection is of clinical importance. Purpose: To determine whether percutaneous needle tenotomy is superior to percutaneous needle fenestration when each is combined with a PRP injection for the treatment of recalcitrant LE. Study Design: Cohort study; Level of evidence, 3. Methods: A total of 93 patients with recalcitrant LE were treated with a PRP injection and percutaneous needle fenestration (n = 45) or percutaneous needle tenotomy (n = 48) over a 5-year study interval. Preoperative patient data, including visual analog scale for pain (VAS-P), Quick Disabilities of the Arm, Shoulder and Hand (QuickDASH), and Patient-Rated Tennis Elbow Evaluation (PRTEE) scores and grip strength, were obtained from a chart review and compared with postoperative values obtained prospectively. Secondary outcomes included the incidence of complications, need for additional interventions, return to work, and patient satisfaction. Results: At a mean follow-up of 40 months, significant improvements in VAS-P (mean, -6.1; 95% CI, -6.8 to -5.5; P \u3c .0001), QuickDASH (mean, -46; 95% CI, -52 to -40; P \u3c .0001), and PRTEE (mean, -57; 95% CI, -64 to -50; P \u3c .0001) scores and grip strength (mean, +6.1 kg; 95% CI, 4.9 to 7.3; P \u3c .0001) were observed across the entire study cohort, with no significant differences noted between the fenestration and tenotomy groups. Nine of 45 patients (22%) underwent additional procedures to treat recurrent symptoms in the fenestration group compared with 5 of 48 patients (10%) in the tenotomy group (P = .05). No complications occurred in any patients, and no patients expressed dissatisfaction with their treatment course. Conclusion: A PRP injection with concomitant percutaneous needling is an effective treatment for recalcitrant LE, with sustained improvements in pain, strength, and function demonstrated at a mean follow-up of longer than 3 years. Although the method of concomitant needling does not appear to have a significant effect on treatment outcomes, more aggressive needle tenotomy is less likely to require conversion to open tenotomy than needle fenestration in the short term to midterm

Gene discovery for improvement of kernel quality-related traits in maize

Developing maize plants with improved kernel quality traits involves the ability to use existing genetic variation and to identify and manipulate commercially important genes. This will open avenues for designing novel variation in grain composition and will provide the basis for the development of the next generation of specialty maize. This paper provides an overview of current knowledge on the identification and exploitation of genes affecting the composition, development, and structure of the maize kernel with particular emphasis on pathways relevant to endosperm growth and development, differentiation of starch-filled cells, and biosynthesis of starches, storage proteins, lipids, and carotenoids. The potential that the new technologies of cell and molecular biology will provide for the creation of new variation in the future are also indicated and discussed

A comparative study of Tam3 and Ac transposition in transgenic tobacco and petunia plants

Transposition of the Anthirrinum majus Tam3 element and the Zea mays Ac element has been monitored in petunia and tobacco plants. Plant vectors were constructed with the transposable elements cloned into the leader sequence of a marker gene. Agrobacterium tumefaciens-mediated leaf disc transformation was used to introduce the transposable element constructs into plant cells. In transgenic plants, excision of the transposable element restores gene expression and results in a clearly distinguishable phenotype. Based on restored expression of the hygromycin phosphotransferase II (HPTII) gene, we established that Tam3 excises in 30% of the transformed petunia plants and in 60% of the transformed tobacco plants. Ac excises from the HPTII gene with comparable frequencies (30%) in both plant species. When the β-glucuronidase (GUS) gene was used to detect transposition of Tam3, a significantly lower excision frequency (13%) was found in both plant species. It could be shown that deletion of parts of the transposable elements Tam3 and Ac, removing either one of the terminal inverted repeats (TIR) or part of the presumptive transposase coding region, abolished the excision from the marker genes. This demonstrates that excision of the transposable element Tam3 in heterologous plant species, as documented for the autonomous element Ac, also depends on both properties. Southern blot hybridization shows the expected excision pattern and the reintegration of Tam3 and Ac elements into the genome of tobacco plants.

Exploratory analysis of hyperspectral imaging data

Characterizing sample composition and visualizing the distribution of its chemical compounds is a prominent topic in various research and applied fields. Integrating spatial and spectral information, hyperspectral imaging (HSI) plays a pivotal role in this pursuit. While self-modelling curve resolution techniques, like multivariate curve resolution - alternating least squares (MCR-ALS), and clustering methods, such as K-means, are widely used for HSI data analysis, their effectiveness in complex scenarios, where the structure of the data deviates from the models’ assumptions, deserves further investigation. The choice of a data analysis method is most often driven by research question at hand and prior knowledge of the sample. However, overlooking the structure of the investigated data, i.e. linearity, geometry, homogeneity, might lead to erroneous or biased results. Here, we propose an exploratory data analysis approach, based on the geometry of the data points cloud, to investigate the structure of HSI datasets and extract their main characteristics, providing insight into the results obtained by the above-mentioned methods. We employ the principle of essential information to extract archetype (most linearly dissimilar) spectra and archetype single-wavelength images. These spectra and images are then discussed and contrasted with MCR-ALS and K-means clustering results. Two datasets with varying characteristics and complexities were investigated: a powder mixture analyzed with Raman spectroscopy and a mineral sample analyzed with Laser Induced Breakdown Spectroscopy (LIBS). We show that the proposed approach enables to summarize the main characteristics of hyperspectral imaging data and provides a more accurate understanding of the results obtained by traditional data modelling methods, driving the choice of the most suitable one

Assessing the feasibility of augmenting fall detection systems by relying on UWB-based position tracking and a home robot

Falls in the home environment are a primary cause of injury in older adults. According to the U.S. Centers for Disease Control and Prevention, every year, one in four adults 65 years of age and older reports experiencing a fall. A variety of different technologies have been proposed to detect fall events. However, the need to detect all fall instances (i.e., to avoid false negatives) has led to the development of systems marked by high sensitivity and hence a significant number of false alarms. The occurrence of false alarms causes frequent and unnecessary calls to emergency response centers, which are critical resources that should be utilized only when necessary. Besides, false alarms decrease the level of confidence of end-users in the fall detection system with a negative impact on their compliance with using the system (e.g., wearing the sensor enabling the detection of fall events). Herein, we present a novel approach aimed to augment traditional fall detection systems that rely on wearable sensors and fall detection algorithms. The proposed approach utilizes a UWB-based tracking system and a home robot. When the fall detection system generates an alarm, the alarm is relayed to a base station that utilizes a UWB-based tracking system to identify where the older adult and the robot are so as to enable navigating the environment using the robot and reaching the older adult to check if he/she experienced a fall. This approach prevents unnecessary calls to emergency response centers while enabling a tele-presence using the robot when appropriate. In this paper, we report the results of a novel fall detection algorithm, the characteristics of the alarm notification system, and the accuracy of the UWB-based tracking system that we implemented. The fall detection algorithm displayed a sensitivity of 99.0% and a specificity of 97.8%. The alarm notification system relayed all simulated alarm notification instances with a maximum delay of 106 ms. The UWB-based tracking system was found to be suitable to locate radio tags both in line-of-sight and in no-line-of-sight conditions. This result was obtained by using a machine learning-based algorithm that we developed to detect and compensate for the multipath effect in no-line-of-sight conditions. When using this algorithm, the error affecting the estimated position of the radio tags was smaller than 0.2 m, which is satisfactory for the application at hand

Evaluation of Fermi Read-out of the ATLAS Tilecal Prototype

Prototypes of the \fermi{} system have been used to read out a prototype of the \atlas{} hadron calorimeter in a beam test at the CERN SPS. The \fermi{} read-out system, using a compressor and a 40 MHz sampling ADC, is compared to a standard charge integrating read-out by measuring the energy resolution of the calorimeter separately with the two systems on the same events. Signal processing techniques have been designed to optimize the treatment of \fermi{} data. The resulting energy resolution is better than the one obtained with the standard read-out

Clinical pregenetic screening for stroke monogenic diseases: Results from lombardia GENS registry

BACKGROUND AND PURPOSE: Lombardia GENS is a multicentre prospective study aimed at diagnosing 5 single-gene disorders associated with stroke (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, Fabry disease, MELAS [mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes], hereditary cerebral amyloid angiopathy, and Marfan syndrome) by applying diagnostic algorithms specific for each clinically suspected disease METHODS: We enrolled a consecutive series of patients with ischemic or hemorrhagic stroke or transient ischemic attack admitted in stroke units in the Lombardia region participating in the project. Patients were defined as probable when presenting with stroke or transient ischemic attack of unknown etiopathogenic causes, or in the presence of <3 conventional vascular risk factors or young age at onset, or positive familial history or of specific clinical features. Patients fulfilling diagnostic algorithms specific for each monogenic disease (suspected) were referred for genetic analysis. RESULTS: In 209 patients (57.4\ub114.7 years), the application of the disease-specific algorithm identified 227 patients with possible monogenic disease. Genetic testing identified pathogenic mutations in 7% of these cases. Familial history of stroke was the only significant specific feature that distinguished mutated patients from nonmutated ones. The presence of cerebrovascular risk factors did not exclude a genetic disease. CONCLUSIONS: In patients prescreened using a clinical algorithm for monogenic disorders, we identified monogenic causes of events in 7% of patients in comparison to the 1% to 5% prevalence reported in previous series

Grain quality-related traits in maize : gene identification and exploitation

Maize grain is a relevant source of food, feed, and industrial row materials. Developing plants with improved grain structure and quality traits involves the ability to use existing genetic variation and to identify and manipulate economically important genes. This will open new avenues for designing novel variation in kernel size, structures, and composition and will provide the basis for the development of the next generation of specialty maize. This paper provides an overview of current knowledge on the identification and exploitation of genes affecting the development, structure, and composition of the maize kernel with particular emphasis on pathways relevant to endosperm growth and development, and biosynthesis of storage proteins, starch, lipids, and carotenoids. The potential that the new technologies of cell and molecular biology will provide for the creation of new variation or novel compounds in the future are indicated and discussed