Pattersonrosenkilde5302
As the technology moves towards more human-like bionic limbs it is necessary to develop a feedback system that provides active touch feedback to a user of a prosthetic hand. Most of the contemporary sensory substitution methods comprise simple position and force sensors combined with few discrete stimulation units,and hence they are characterized with a limited information bandwidth. The present study describes a novel system for tactile feedback integrating advanced distributed sensing (electronic skin) and stimulation (matrix electrodes). The system comprises a flexible sensing array (16 sensors) integrated on the index finger of a Michelangelo prosthetic hand mockup,embedded interface electronics and multichannel stimulator connected to a flexible matrix electrode (24 pads). To demonstrate the feasibility,the system was tested in six able-bodied subjects who were asked to recognize static patterns (contact position) with two different spatial resolutions and dynamic movement patterns (i.e.,sliding along and/or across the finger) presented on the electronic skin. The experiments demonstrated that the system successfully translated the mechanical interaction into electrotactile profiles,which the subjects could recognize with good performance (Static patterns 91 4% and 5810% for low and high spatial resolution,respectively,and 943% for sliding touch). These results demonstrate that the developed system is an important step towards a new generation of tactile feedback interfaces that can provide high-bandwidth interfacing between the user and his/her bionic limb. Such systems would allow mimicking spatially distributed natural feedback,thereby facilitating the control and embodiment of the artificial device into the user body scheme.Non-coding RNAs (ncRNAs) are a type of RNA which are not used to encode protein sequences. Emerging evidence shows that lots of ncRNAs may participate in many biological processes and must be widely involved in many types of cancers. Therefore,understanding their functionality is of great importance. Similar to proteins,various functions of ncRNAs relies on their subcellular localizations. Traditional high-throughput methods in wet-lab to identify subcellular localization is time-consuming and costly. In this paper,we propose a novel computational method based on multi-kernel learning to identify multi-label ncRNA subcellular localizations,via graph regularized k-local hyperplane distance nearest neighbor algorithm. First,we construct six types of sequence-based feature descriptors and select important feature vectors. Then,we build a multi-kernel learning model with Hilbert-Schmidt independence criterion (HSIC) to obtain optimal weights for vairous features. Furthermore,we propose the graph regularized k -local hyperplane distance nearest neighbor algorithm (GHKNN) as a binary classification model for detecting one kind of non-coding RNA subcellular localization. Finally,we apply One-vs-Rest strategy to decompose multi-label problem of non-coding RNA subcellular localizations. Our method achieves excellent performance on three ncRNA datasets and three human ncRNA datasets. We evaluate our predictor on a novel multi-label benchmark set,and out-performs other outstanding machine learning methods.Functional MRI (fMRI) is widely used to study the functional organization of normal and pathological brains. However, the fMRI signal may be contaminated by subject motion artifacts that are only partially mitigated by motion correction strategies. These artifacts lead to distance-dependent biases in the inferred signal correlations. To mitigate these spurious effects, motion-corrupted volumes are censored from fMRI time series. Censoring can result in discontinuities in the fMRI signal, which may lead to substantial alterations in functional connectivity analysis. We propose a new approach to recover the missing entries from censoring based on structured low rank matrix completion. We formulated the artifact-reduction problem as the recovery of a super-resolved matrix from unprocessed fMRI measurements. We enforced a low rank prior on a large structured matrix, formed from the samples of the time series, to recover the missing entries. The recovered time series, in addition to being motion compensated, are also slice-time corrected at a fine temporal resolution. To achieve a fast and memory-efficient solution for our proposed optimization problem, we employed a variable splitting strategy. We validated the algorithm with simulations, data acquired under different motion conditions, and datasets from the ABCD study. Functional connectivity analysis showed that the proposed reconstruction resulted in connectivity matrices with lower errors in pair-wise correlation than non-censored and censored time series based on a standard processing pipeline. In addition, seed-based correlation analyses showed improved delineation of the default mode network. These demonstrate that the method can effectively reduce the adverse effects of motion in fMRI analysis.
We assess the yearly seasonal, environmental effects on birth pattern in Chinese patients later diagnosed with narcolepsy and cataplexy, and explored if this effect persisted in patients with symptoms onset date before, following and after 2009 H1N1 pandemic.
A total of 1942 patients with birth data information and diagnosed narcolepsy with cataplexy were included in this study. The birth month and seasonal effect of 1064 patients born from 1970 to 2000 were compared to controls (n=2,028,714) from the general population. Furthermore, birth season effect in 1373 patients with definite disease onset month were compared among patients with onset date before (n=595), following (n=325), and after (n=453) H1N1 pandemic.
Patients with narcolepsy and cataplexy had a significantly different seasonality from the general population (p = 0.027). The monthly distribution of birth month yielded a peak in November (odds ratio = 1.23 [95%CI, 1.01-1.49], p=0.042) and a trough in April (odds ratio = 0.68 [95%CI,0.52-0.88], p=0.004). No significant difference was observed in the birth month across patients with symptoms onset dates before, following and after the 2009 H1N1 pandemic (p=0.603).
This reveal across many years of seasonal effect in Chinese narcolepsy cataplexy supports a role for early-life environmental influences on disease development.
This reveal across many years of seasonal effect in Chinese narcolepsy cataplexy supports a role for early-life environmental influences on disease development.
Geriatric impairments and obstructive sleep apnea (OSA) are prevalent among older patients with atrial fibrillation (AF). Little is known about the association between OSA and geriatric impairments including frailty, cognitive performance, and AF-related quality of life. The objective of this study was to examine the associations of OSA with frailty, cognitive performance, and AF-related quality of life among older adults with AF.
Data from the Systemic Assessment of Geriatrics Elements-AF study were used which included AF participants 65 years and older and with a CHA
DS
-VASc ≥2. The STOP-BANG questionnaire was used to assess the risk of OSA. Multivariable logistic regression models were used to examine the association between risk of OSA and geriatric impairments, adjusting for sociodemographic, geriatric, and clinical characteristics.
A total of 970 participants (mean age 75 years; 51% male) were studied. Of the 680 participants without a medical history of OSA, 26% (n=179) of participants had a low risk of OSA, 53% (n=360) had an intermediate risk, and 21% (n=141) had a high risk for OSA. Compared to those with low risk of OSA, participants with an intermediate or high risk of OSA were more likely to be frail (adjusted odds ratio [aOR]= 1.67, 95% confidence interval [CI] 1.08-2.56; aOR= 3.00, 95% CI 1.69-5.32, respectively) in the fully adjusted models.
Our findings identify a group of patients at high risk who would benefit from early screening for OSA. Future longitudinal studies are needed to assess the effect of OSA treatment on frailty, physical functioning, and QoL among patients with AF.
Our findings identify a group of patients at high risk who would benefit from early screening for OSA. Future longitudinal studies are needed to assess the effect of OSA treatment on frailty, physical functioning, and QoL among patients with AF.
Women with sleep-disordered breathing (SDB) in pregnancy are at a greater risk of developing serious adverse perinatal outcomes. However, the pathogenesis of SDB in pregnancy is poorly understood. As nasal congestion is common in pregnancy, nasal obstruction may contribute to SDB in this population. This study aims to assess the impact of nasal dilator strips (NDS) on measures of SDB and their potential for use as a placebo condition.
Pregnant women ≥18 years old, BMI ≥ 27 kg/m
, and habitual snoring were enrolled. Participants completed 2 consecutive level III home sleep apnea tests, and used NDS during the second test. Objective measures including respiratory event index (REI) and pulse transit time (PTT) drop index, a measure of increased arterial stiffness, were compared across tests. Subjective assessments of participants' perceived impact of NDS use was also obtained.
54 women, 59% White, 60% in the third trimester were enrolled. Median time between the two studies was 1 (IQR 4) days. There was no significant change between the night without NDS use and the night with NDS use in REI (5.30 (IQR 6.20) vs. 4.80 (IQR 6.78), p=0.8) or PTT drop index (6.8 (IQR 13.3) vs. 6.6 (IQR 15.8), p= 0.360). Subjective measures of sleep did not differ between the two nights.
Despite the high prevalence of pregnancy-associated rhinitis, NDS do not have a significant impact on measures of SDB. Results from this study support the use of NDS as an appropriate placebo in prenatal clinical trials.
Despite the high prevalence of pregnancy-associated rhinitis, NDS do not have a significant impact on measures of SDB. Results from this study support the use of NDS as an appropriate placebo in prenatal clinical trials.
At the end of the activity, participant will be able to • Identify patients who could benefit from continuous glucose monitoring (CGM) vs fingerstick blood glucose monitoring. • List the types of information provided by CGM systems. • Interpret CGM data using the ambulatory glucose profile (AGP) to assess if the patient is achieving targets established by the International Consensus on Time in Range. • Modify the treatment plan based on CGM data to improve patient outcomes.
At the end of the activity, participant will be able to • Identify patients who could benefit from continuous glucose monitoring (CGM) vs fingerstick blood glucose monitoring. • List the types of information provided by CGM systems. • Interpret CGM data using the ambulatory glucose profile (AGP) to assess if the patient is achieving targets established by the International Consensus on Time in Range. • Modify the treatment plan based on CGM data to improve patient outcomes.
• Chronic kidney disease (CKD) is common, occurring in 1 of 7 adults in the United States. • 9 out of 10 adults with CKD are unaware of it. • People with CKD have the same risk for cardiovascular (CV) death as people with known atherosclerotic heart disease. Erastin2 mw • The risk for CV events and death increases with worsening albuminuria and estimated glomerular filtration rate (eGFR). • Patients with risk factors for CKD (hypertension, diabetes, family history of CKD, or advancing age) should be screened by measuring both eGFR and urinary albuminto-creatinine ratio. • Sodium-glucose cotransporter-2 inhibitors are first-line agents for treatment of patients with type 2 diabetes mellitus and CKD or a history of atherosclerotic CV disease. • Dapagliflozin has demonstrated equivalent efficacy for reducing kidney events in patients with CKD irrespective of diabetes status, and a similar, ongoing trial with empagliflozin may provide potential confirmation.
• Chronic kidney disease (CKD) is common, occurring in 1 of 7 adults in the United States.
