Two Weeks of Ischemic Conditioning Improves Walking Speed and Reduces Neuromuscular Fatigability in Chronic Stroke Survivors

This pilot study examined whether ischemic conditioning (IC), a noninvasive, cost-effective, and easy-to-administer intervention, could improve gait speed and paretic leg muscle function in stroke survivors. We hypothesized that 2 wk of IC training would increase self-selected walking speed, increase paretic muscle strength, and reduce neuromuscular fatigability in chronic stroke survivors. Twenty-two chronic stroke survivors received either IC or IC Sham on their paretic leg every other day for 2 wk (7 total sessions). IC involved 5-min bouts of ischemia, repeated five times, using a cuff inflated to 225 mmHg on the paretic thigh. For IC Sham, the cuff inflation pressure was 10 mmHg. Self-selected walking speed was assessed using the 10-m walk test, and paretic leg knee extensor strength and fatigability were assessed using a Biodex dynamometer. Self-selected walking speed increased in the IC group (0.86 ± 0.21 m/s pretest vs. 1.04 ± 0.22 m/s posttest, means ± SD; P\u3c 0.001) but not in the IC Sham group (0.92 ± 0.47 m/s pretest vs. 0.96 ± 0.46 m/s posttest; P= 0.25). Paretic leg maximum voluntary contractions were unchanged in both groups (103 ± 57 N·m pre-IC vs. 109 ± 65 N·m post-IC; 103 ± 59 N·m pre-IC Sham vs. 108 ± 67 N·m post-IC Sham; P = 0.81); however, participants in the IC group maintained a submaximal isometric contraction longer than participants in the IC Sham group (278 ± 163 s pre-IC vs. 496 ± 313 s post-IC, P = 0.004; 397 ± 203 s pre-IC Sham vs. 355 ± 195 s post-IC Sham; P = 0.46). The results from this pilot study thus indicate that IC training has the potential to improve walking speed and paretic muscle fatigue resistance poststroke

The efficacy and safety of prokinetic agents in critically ill patients receiving enteral nutrition: a systematic review and meta-analysis of randomized trials.

BACKGROUND: Intolerance to enteral nutrition is common in critically ill adults, and may result in significant morbidity including ileus, abdominal distension, vomiting and potential aspiration events. Prokinetic agents are prescribed to improve gastric emptying. However, the efficacy and safety of these agents in critically ill patients is not well-defined. Therefore, we conducted a systematic review and meta-analysis to determine the efficacy and safety of prokinetic agents in critically ill patients. METHODS: We searched MEDLINE, EMBASE, and Cochrane Library from inception up to January 2016. Eligible studies included randomized controlled trials (RCTs) of critically ill adults assigned to receive a prokinetic agent or placebo, and that reported relevant clinical outcomes. Two independent reviewers screened potentially eligible articles, selected eligible studies, and abstracted pertinent data. We calculated pooled relative risk (RR) for dichotomous outcomes and mean difference for continuous outcomes, with the corresponding 95 % confidence interval (CI). We assessed risk of bias using Cochrane risk of bias tool, and the quality of evidence using grading of recommendations assessment, development, and evaluation (GRADE) methodology. RESULTS: Thirteen RCTs (enrolling 1341 patients) met our inclusion criteria. Prokinetic agents significantly reduced feeding intolerance (RR 0.73, 95 % CI 0.55, 0.97; P = 0.03; moderate certainty), which translated to 17.3 % (95 % CI 5, 26.8 %) absolute reduction in feeding intolerance. Prokinetics also reduced the risk of developing high gastric residual volumes (RR 0.69; 95 % CI 0.52, 0.91; P = 0.009; moderate quality) and increased the success of post-pyloric feeding tube placement (RR 1.60, 95 % CI 1.17, 2.21; P = 0.004; moderate quality). There was no significant improvement in the risk of vomiting, diarrhea, intensive care unit (ICU) length of stay or mortality. Prokinetic agents also did not significantly increase the rate of diarrhea. CONCLUSION: There is moderate-quality evidence that prokinetic agents reduce feeding intolerance in critically ill patients compared to placebo or no intervention. However, the impact on other clinical outcomes such as pneumonia, mortality, and ICU length of stay is unclear

Women’s Awareness and Attitude toward Epidural Analgesia

Introduction: Women’s awareness and attitudes toward Epidural Analgesia (EA) are not clearly identified.  The benefits of EA in relieving labor pain are well recognized.  However, women’s preferences in using EA to relieve labor pain differ between cultures. The objective of this study was to assess women’s awareness and attitudes toward EA. Methods: A descriptive correlational cross-sectional design was used to collect data from a convenience sample of 550 women in childbearing age.   Women were interviewed face-to-face after they agreed to participate in the study.  Data were collected from shopping malls, women’s cafeterias, beauty salons and outpatient clinics in Riyadh, KSA. Demographic profiles, knowledge and attitudes of EA questionnaires were used to collect data for the study. Results:  The majority of women were young, married, multigravids, lived in Riyadh, were well educated, unemployed, and had a significant monthly income.  Women reported a good level of knowledge regarding most of the items on the EA questionnaire.  42% reported that they know about EA from family members/relatives and friends, 18% from the media or readings, 13% from previous delivery experience and 8% from brochures at antenatal clinics.  Women’s attitudes toward using EA in future labor were varied since similar percentages agreed, did not agree and weren’t sure about using EA in their future labor.  The reasons for the unclear attitudes were advice from relatives not to use EA, and a desire to experience natural labor pain.  There was a significance moderate correlation between knowledge and parity (r = .40**, p = .000), income (r = .39**, p = .001), education (r = .31**, p = .000), and attitude (r = .31**, .000). Conclusion and recommendations: Although women’s awareness regarding EA was relatively high, their attitude toward using EA in future labor was not clear.  Culturally sensitive educational programs are needed to improve women’s perception and attitude toward using EA in their future labor and to have a satisfactory labor. Keywords: Awareness, attitude, epidural, labor pain, wome

Are semi-automated software program designed for adults accurate for the identification of vertebral fractures in children?

Objectives To assess whether diagnostic accuracy of morphometric vertebral fracture (VF) diagnosis in children can be improved using AVERT™ (a 33-point semi-automated program developed for VF diagnosis in adults) compared with SpineAnalyzer™ (a 6-point program), which has previously been shown to be of insufficient accuracy. Materials and methods Lateral spine radiographs (XR) and dual-energy X-ray absorptiometry (DXA) scans of 50 children and young people were analysed by two observers using two different programs (AVERT™ and SpineAnalyzer™). Diagnostic accuracy (sensitivity, specificity, false-negative (FN) and false-positive rates (FP)) was calculated by comparing with a previously established consensus arrived at by three experienced paediatric musculoskeletal radiologists, using a simplified algorithm-based qualitative scoring system. Observer agreement was calculated using Cohen’s kappa. Results For XR, overall sensitivity, specificity, FP and FN rates using AVERT™ were 36%, 95%, 5% and 64% respectively and 26%, 98%, 2% and 75% respectively, using SpineAnalyzer™. For DXA, overall sensitivity, specificity, FP and FN rates using AVERT™ were 41%, 91%, 9% and 59% respectively and 31%, 96%, 4% and 69% respectively, using SpineAnalyzer. Reliability (kappa) ranged from 0.34 to 0.37 (95%CI, 0.26–0.46) for AVERT™ and from 0.26 to 0.31 (95%CI, 0.16–0.44) for SpineAnalyzer™. Inter- and intra-observer agreement ranged from 0.41 to 0.47 for AVERT™ and from 0.50 to 0.79 for SpineAnalyzer™. Conclusion AVERT™ has slightly higher accuracy but lower observer reliability for the representation of vertebral morphometry in children when compared with SpineAnalyzer™. However, neither software program is satisfactorily reliable for VF diagnosis in children

Age estimation using canine pulp volumes in adults:A CBCT image analysis

Secondary dentine deposition is responsible for the decrease in the volume of the pulp cavity with age. Therefore, the volume of the pulp cavity can be considered as a predictor for estimating age. The aims of this study were to investigate the relationship strength between canine pulp volumes and chronological age from homogenous (approximately equal numbers of individuals in each age range) age distribution and to assess the effect of sex as predictor in age estimation. This study was performed on 719 subjects of Pakistani origin. Cone beam computed tomography images of 521 left maxillary and 681 left mandibular canines were collected from 368 females and 349 males aged from 15 to 65 years. Planmeca Romexis® software was used to trace the outline of the pulp cavity and to calculate pulp volumes. Regression analysis was performed to assess the correlation between pulp volumes considering with and without sex as a predictor with chronological age. The obtained results showed that mandibular canine pulp volume and sex have the highest predictive power (R 2 = 0.33). The relationship between mandibular canine pulp volume and sex with chronological age demonstrates an odd S-shaped non-linear relationship. A statistically significant difference in volumes of pulp was found (p = 0.000) between males and females. The conclusion was that predictions using the pulp volume of the mandibular canine and sex produced the best estimates of chronological age. </p

Are semi-automated software program designed for adults accurate for the identification of vertebral fractures in children?

Objectives To assess whether diagnostic accuracy of morphometric vertebral fracture (VF) diagnosis in children can be improved using AVERT™ (a 33-point semi-automated program developed for VF diagnosis in adults) compared with SpineAnalyzer™ (a 6-point program), which has previously been shown to be of insufficient accuracy. Materials and methods Lateral spine radiographs (XR) and dual-energy X-ray absorptiometry (DXA) scans of 50 children and young people were analysed by two observers using two different programs (AVERT™ and SpineAnalyzer™). Diagnostic accuracy (sensitivity, specificity, false-negative (FN) and false-positive rates (FP)) was calculated by comparing with a previously established consensus arrived at by three experienced paediatric musculoskeletal radiologists, using a simplified algorithm-based qualitative scoring system. Observer agreement was calculated using Cohen’s kappa. Results For XR, overall sensitivity, specificity, FP and FN rates using AVERT™ were 36%, 95%, 5% and 64% respectively and 26%, 98%, 2% and 75% respectively, using SpineAnalyzer™. For DXA, overall sensitivity, specificity, FP and FN rates using AVERT™ were 41%, 91%, 9% and 59% respectively and 31%, 96%, 4% and 69% respectively, using SpineAnalyzer. Reliability (kappa) ranged from 0.34 to 0.37 (95%CI, 0.26–0.46) for AVERT™ and from 0.26 to 0.31 (95%CI, 0.16–0.44) for SpineAnalyzer™. Inter- and intra-observer agreement ranged from 0.41 to 0.47 for AVERT™ and from 0.50 to 0.79 for SpineAnalyzer™. Conclusion AVERT™ has slightly higher accuracy but lower observer reliability for the representation of vertebral morphometry in children when compared with SpineAnalyzer™. However, neither software program is satisfactorily reliable for VF diagnosis in children

Alpha-amylase and alpha-glucosidase enzyme inhibition and antioxidant potential of 3-oxolupenal and katononic acid isolated from Nuxia oppositifolia

Nuxia oppositifolia is traditionally used in diabetes treatment in many Arabian countries; however, scientific evidence is lacking. Hence, the present study explored the antidiabetic and antioxidant activities of the plant extracts and their purified compounds. The methanolic crude extract of N. oppositifolia was partitioned using a two-solvent system. The n-hexane fraction was purified by silica gel column chromatography to yield several compounds including katononic acid and 3-oxolupenal. Antidiabetic activities were assessed by α-amylase and α-glucosidase enzyme inhibition. Antioxidant capacities were examined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) scavenging assays. Further, the interaction between enzymes (α-amylase and α-glucosidase) and ligands (3-oxolupenal and katononic acid) was followed by fluorescence quenching and molecular docking studies. 3-oxolupenal and katononic acid showed IC50 values of 46.2 µg/mL (101.6 µM) and 52.4 µg/mL (119.3 µM), respectively against the amylase inhibition. 3-oxolupenal (62.3 µg/mL or 141.9 µM) exhibited more potent inhibition against α-glucosidases compared to katononic acid (88.6 µg/mL or 194.8 µM). In terms of antioxidant activity, the relatively polar crude extract and n-butanol fraction showed the greatest DPPH and ABTS scavenging activity. However, the antioxidant activities of the purified compounds were in the low to moderate range. Molecular docking studies confirmed that 3-oxolupenal and katononic acid interacted strongly with the active site residues of both α-amylase and α-glucosidase. Fluorescence quenching results also suggest that 3-oxolupenal and katononic acid have a good affinity towards both α-amylase and α-glucosidase enzymes. This study provides preliminary data for the plant’s use in the treatment of type 2 diabetes mellitus

An experimental analysis of attack classification using machine learning in IoT networks

\ua9 2021 by the authors. Licensee MDPI, Basel, Switzerland. In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT networks can be problematic due to their resource-constrained nature, and integrating security on these devices is often overlooked. This has resulted in attackers having an increased incentive to target IoT devices. As the number of attacks possible on a network increases, it becomes more difficult for traditional intrusion detection systems (IDS) to cope with these attacks efficiently. In this paper, we highlight several machine learning (ML) methods such as k-nearest neighbour (KNN), support vector machine (SVM), decision tree (DT), naive Bayes (NB), random forest (RF), artificial neural network (ANN), and logistic regression (LR) that can be used in IDS. In this work, ML algorithms are compared for both binary and multi-class classification on Bot-IoT dataset. Based on several parameters such as accuracy, precision, recall, F1 score, and log loss, we experimentally compared the aforementioned ML algorithms. In the case of HTTP distributed denial-of-service (DDoS) attack, the accuracy of RF is 99%. Furthermore, other simulation results-based precision, recall, F1 score, and log loss metric reveal that RF outperforms on all types of attacks in binary classification. However, in multi-class classification, KNN outperforms other ML algorithms with an accuracy of 99%, which is 4% higher than RF

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Airway pressure release ventilation as a recruitment maneuver in mechanically ventilated children with restrictive lung disease

RationaleRestrictive lung disease is common in pediatric patients, leading to acute-on-chronic respiratory failure and the need for invasive mechanical ventilation. There is no consensus on lung recruitment maneuvers.ObjectivesTo examine the use of airway pressure release ventilation (APRV) in patients with restrictive lung disease as an effective open-lung tool maneuver.MethodsThis single-center retrospective case series included patients with restrictive lung disease in a 28-bed pediatric intensive care unit from 2013 to 2024, who developed acute-on-chronic respiratory failure requiring invasive mechanical ventilation. Inclusion criteria were ventilation for at least 48 h, with at least 24 h in APRV. Descriptive statistics were performed.Measurements and main results18 patient encounters met inclusion criteria. Subjects were divided into two groups: neuromuscular disease (14 encounters) and truncal obesity (4 encounters). Lung surface area improved significantly in the first 12–24 h of APRV use: neuromuscular group by 7,600 mm2 [95% CI, 4,000–11,000 mm2]; p &lt; 0.001, and obesity group by 15,000 mm2 [95% CI, 3,000–27,000]; p = 0.018. Atelectasis improved at 12–24 h and 48 h from starting APRV, with mean differences of 14% [95% CI, 4%–24%]; p = 0.005 and 14% [95% CI, 3%–25%]; p = 0.009, respectively. As expected, oxygenation improved substantially in both groups.ConclusionAPRV is a safe and effective method for improving atelectasis and oxygenation in children with RLD related to neuromuscular conditions and obesity. Further high-quality prospective studies are needed to establish clear guidelines for its use