A systematic review on deep learning-based automated cancer diagnosis models.

Deep learning is gaining importance due to its wide range of applications. Many researchers have utilized deep learning (DL) models for the automated diagnosis of cancer patients. This paper provides a systematic review of DL models for automated diagnosis of cancer patients. Initially, various DL models for cancer diagnosis are presented. Five major categories of cancers such as breast, lung, liver, brain and cervical cancer are considered. As these categories of cancers have a very high percentage of occurrences with high mortality rate. The comparative analysis of different types of DL models is drawn for the diagnosis of cancer at early stages by considering the latest research articles from 2016 to 2022. After comprehensive comparative analysis, it is found that most of the researchers achieved appreciable accuracy with implementation of the convolutional neural network model. These utilized the pretrained models for automated diagnosis of cancer patients. Various shortcomings with the existing DL-based automated cancer diagnosis models are also been presented. Finally, future directions are discussed to facilitate further research for automated diagnosis of cancer patients.

Determining the effects of targeted high-definition transcranial direct current stimulation on reducing post-stroke upper limb motor impairments-a randomized cross-over study.

BACKGROUND: Stroke is one of the leading causes of death in the USA and is a major cause of serious disability for adults. This randomized crossover study examines the effect of targeted high-definition transcranial direct current transcranial brain stimulation (tDCS) on upper extremity motor recovery in patients in the post-acute phase of stroke recovery. METHODS: This randomized double-blinded cross-over study includes four intervention arms: anodal, cathodal, and bilateral brain stimulation, as well as a placebo stimulation. Participants receive each intervention in a randomized order, with a 2-week washout period between each intervention. The primary outcome measure is change in Motor Evoked Potential. Secondary outcome measures include the Fugl-Meyer Upper Extremity (FM-UE) score, a subset of FM-UE (A), related to the muscle synergies, and the Modified Ashworth Scale. DISCUSSION: We hypothesize that anodal stimulation to the ipsilesional primary motor cortex will increase the excitability of the damaged cortico-spinal tract, reducing the UE flexion synergy and enhancing UE motor function. We further hypothesize that targeted cathodal stimulation to the contralesional premotor cortex will decrease activation of the cortico-reticulospinal tract (CRST) and the expression of the upper extremity (UE) flexion synergy and spasticity. Finally, we hypothesize bilateral stimulation will achieve both results simultaneously. Results from this study could improve understanding of the mechanism behind motor impairment and recovery in stroke and perfect the targeting of tDCS as a potential stroke intervention. With the use of appropriate screening, we anticipate no ethical or safety concerns. We plan to disseminate these research results to journals related to stroke recovery, engineering, and medicine. TRIAL REGISTRATION: ClinicalTrials.gov NCT05479006 . Registered on 26 July 2022.

Characteristics of the phenotype of mixed cardiomyopathy in patients with implantable cardioverter-defibrillators.

BACKGROUND OR PURPOSE: The prognosis of m ixed cardiomyopathy (CMP) in patients with implanted cardioverter-defibrillators (ICDs) has not been investigated. We aim to study the demographic, clinical, device therapies and survival characteristics of mixed CMP in a cohort of patients implanted with a defibrillator. METHODS: The term mixed CMP was used to categorise patients with impaired left ventricular ejection fraction attributed to documented non-ischemic triggers with concomitant moderate coronary artery disease. This is a single center observational cohort of 526 patients with a mean follow-up of 8.7 ± 3.5 years. RESULTS: There were 42.5% patients with ischemic cardiomyopathy (ICM), 26.9% with non-ischemic cardiomyopathy (NICM) and 30.6% with mixed CMP. Mixed CMP, compared to NICM, was associated with higher mean age (69.1 ± 9.6 years), atrial fibrillation (55.3%) and greater incidence of comorbidities. The proportion of patients with mixed CMP receiving device shocks was 23.6%, compared to 18.4% in NICM and 27% in ICM. The VT cycle length recorded in mixed CMP (281.6 ± 43.1 ms) was comparable with ICM (282.5 ± 44 ms; p = 0.9) and lesser than NICM (297.7 ± 48.7 ms; p = 0.1). All-cause mortality in mixed CMP (21.1%) was similar to ICM (20.1%; p = 0.8) and higher than NICM (15.6%; p = 0.2). The Kaplan-Meier curves revealed hazards of 1.57 (95% CI: 0.91, 2.68) for mixed CMP compared to NICM. CONCLUSION: In a cohort of patients with ICD, the group with mixed CMP represents a phenotype predominantly comprised of the elderly with a higher incidence of comorbidities. Mixed CMP resembles ICM in terms of number of device shocks and VT cycle length. Trends of long-term prognosis of patients with mixed CMP are worse than NICM and similar to ICM.

Correlation of myocardial strain by CMR-feature tracking with substrate abnormalities detected by electro-anatomical mapping in patients with nonischemic cardiomyopathy.

BACKGROUND: Late gadolinium enhancement (LGE) detected by cardiac MRI (CMR) has low correlation with low voltage zones (LVZs) detected by electroanatomical mapping (EAM). We aim to study correlation of myocardial strain by CMR- Feature Tracking (FT) alongside LGE with LVZs detected by EAM. METHODS: Nineteen consecutive CMRs of patients with EAM were analyzed offline by CMR-FT. Peak value of circumferential strain (CS), longitudinal strain (LS), and LGE was measured in each segment of the left ventricle (17-segment model). The percentage of myocardial segments with CS and LS > -17% was determined. Percentage area of LGE-scar was calculated. Global and segment-wise bipolar and unipolar voltage was collected. Percentage area of bipolar LVZ (<1.5 mV) and unipolar LVZ (<8.3 mV) was calculated. RESULTS: Mean age was 62±11 years. Mean LVEF was 37±13%. Mean global CS was -11.8±5%. Mean global LS was -11.2±4%. LGE-scar was noted in 74% of the patients. Mean percentage area of LGE-scar was 5%. There was significant correlation between percentage abnormality detected by LS with percentage bipolar LVZ (r = +0.5, p = 0.03) and combined percentage CS+LS abnormality with percentage unipolar LVZ (r = +0.5, p = 0.02). Per-unit increase in CS increased the percentage area of unipolar LVZ by 2.09 (p = 0.07) and per-unit increase in LS increased the percentage area of unipolar LVZ by 2.49 (p = 0.06). The concordance rates between CS and LS to localize segments with bipolar/unipolar LVZ were 79% and 95% compared to 63% with LGE. CONCLUSIONS: Myocardial strain detected by CMR-FT has a better correlation with electrical low voltage zones than the conventional LGE.

Intelligent predictions of Covid disease based on lung CT images using machine learning strategy.

Covid or Corona Virus, a term ruling the world from past two years and causes a huge destruction in all countries. One of the most important Covid disease identification method is Lung based Computed Tomography (CT) image scanning, in which it provides an effective disease identification means in clear manner. However, this Lung CT image based disease detection principles are complex to health care representatives and doctors to predict the Covid disease accurately. Several manual errors and medical flaws are raised day-by-day, so that a new systematic methodology is required to identify the Covid disease effectively with respect to machine learning principles. The machine learning principles are most popular to identify the respective disease efficiently as well as classify the disease in accurate manner without any time consumption. The infected portions of the chest are identified accurately and report to the respective person without any delay. In this paper, a new machine learning strategy is introduced called Hybrid Disease Detection Principle (HDDP), in which it is derived from the two classical machine learning algorithms called Convolutional Neural Network (CNN) and the AdaBoost Classifier. Both these algorithms are integrated together to produce a new strategy called HDDP, in which it process the lung CT image based on the machine learning factors such as pre-processing, feature extraction and classification. Based on these effective image processing strategies the proposed algorithm handles the CT images to predict the Covid disease and report to the respective user with proper accuracy ratio. This paper intends to provide effcient disease predictions as well as provide a sufficient support to medical people and patients in fine manner to assist them with modern classification algorithms.

Diffuse large B-cell lymphoma and red cell autoimmunity: clinical role and pathogenesis.

Diffuse large B-cell lymphoma (DLBCL) is the most common form of B-cell non-Hodgkin lymphoma (B-NHL) with significant morbidity and mortality despite advancements in treatment. Lymphoma and autoimmune disease both result from breakdowns in normal cell regulatory pathways, and epidemiological studies have confirmed both that B-NHL is more likely to develop in the setting of autoimmune diseases and vice versa. Red cell immunity, as evidenced by direct antiglobulin test (DAT) positivity, has been linked to DLBCL and more recently the pathogenic causes of this association have begun to be better understood using molecular techniques. This project aimed to explore the relationship between red cell autoimmunity and DLBCL. DAT positivity was more common in DLBCL as compared to healthy controls (20.4% vs 3.7%, p=0.0005). Univariate analysis found a non-significant trend towards poorer overall survival in the DAT positive (DAT+) compared to the DAT negative (DAT-) groups (p=0.087). High throughput sequencing was used to compare mutations in DLBCL from DAT+ and DAT- patients. The most frequently mutated genes in 15 patient samples were KMT2D (n=13), MYOM2 (n=9), EP300 (n=8), SPEN (n=7), and ADAMTSL3 (n=7), which were mutated in both DAT+ and DAT- groups. BIRC3 (n=3), FOXO1 (n=3) and CARD11 (n=2) were found to be mutated only in samples from the DAT+ group. These gene mutations may be involved in disease development and progression, and potentially represent targets for future therapy. The immunoglobulin genotype IGHV4-34 is seen more frequently in DLBCL clones than in normal B cells and has intrinsic autoreactivity to self-antigens on red cells, which is largely mediated by two motifs within the first framework region (FR1); Q6W7 and A24V25Y.26 These motifs form a hydrophobic patch which determines red cell antigen binding and are frequently mutated away from self-reactivity in normal B cells. If this does not occur this may provide constant B cell receptor signalling which encourages lymphoma development, a theory known as antigen driven lymphomagenesis. As with previous studies, IGHV4-34 was over-represented (15.6%) in our DLBCL cohort. Furthermore, of 6 IGHV4-34-expressing DLBCL samples five had unmutated hydrophobic patch mutations providing further evidence for antigen-driven lymphomagenesis. Mutation analysis of these five samples demonstrated high frequency of mutations in several genes, including CREBBP and NCOR2. Further research could explore if mutations in CREBBP and NCOR2 work in conjunction with the preserved QW and AVY motifs to promote lymphomagenesis in IGHV4-34-expressing B cells, and if so, could guide future targeted therapy.

Effect of durations and pressures of cupping therapy on muscle stiffness of triceps.

Cupping therapy has been used for the alleviation of muscle soreness in athletes. However, clinical studies of cupping therapy show conflicting results. Lack of standardized guidelines of the dose-response relationship of cupping therapy, such as appropriate cupping duration and negative pressure, limits the adoption of cupping therapy in clinical practice. The objectives of this study were to investigate the effect of various pressures and durations of cupping therapy on reducing muscle stiffness. The 2 × 2 factorial design with the repeated measures and counterbalanced design was used to test four cupping protocols, including two negative pressures at -225 and -300 mmHg and two durations at 5 and 10 min, in 12 healthy young people. B-mode and elastographic ultrasound was used to assess muscle stiffness of the triceps before and after cupping therapy. The region of interest of elastographic image was divided into the superficial and deep layers for assessing the effect of cupping therapy on stiffness of various depths of the triceps. Normalized stiffness was calculated as a ratio of pre-cupping stiffness divided by post-cupping stiffness of each participant. The two-way analysis of variance (ANOVA) was used to examine the main effects of the pressure and duration factors and the interaction effect between the pressure and duration factors. The results showed that there were no interactions between the pressure and duration factors (overall layer p = 0.149, superficial layer p = 0.632, and deep layer p = 0.491). The main effects of duration of the overall, superficial and deep layers were p = 0.538, p = 0.097 and p = 0.018, respectively. The results showed that 10-min cupping at -300 mmHg is more effective on reducing stiffness of the deep layer of the triceps compared to 5-min cupping (p = 0.031). This study provides the first evidence that the dose of cupping therapy could significantly affect changes of triceps stiffness and the deep layer of the muscle is more sensitive to cupping therapy compared to the superficial and overall layers.

Effects of Walking Speeds and Durations on Peak Plantar Pressures.

BACKGROUND: Walking at various speeds and durations may result in different peak plantar pressure (PPP). However, there is no study comparing the effect of walking speeds and durations on PPP. The purpose of this study was to explore whether different walking speeds and durations significantly change PPP and establish a normal response in healthy people. METHODS: An in-shoe plantar pressure system was used to measure PPP under the first toe, first metatarsal, second metatarsal, and heel regions in 12 healthy, young people. All participants performed six walking trials at three speeds (3, 6, and 9 km/h) and for two durations (10 and 20 min). The 3 × 2 two-way analysis of variance was used to examine the main effects of speeds and durations and their interaction. RESULTS: The results showed that walking speeds significantly affected PPP and that walking duration did not. No interaction between the walking speed and duration was observed. Peak plantar pressure values under the first toe and the first metatarsal head were significantly higher (P < .05) at 9 km/h (509.1 ± 314.2 kPa and 591.4 ± 302.4 kPa, respectively) than at 3 km/h (275.4 ± 168.7 kPa and 369.4 ± 205.4 kPa, respectively) after 10-min walking. CONCLUSIONS: People at risk for foot ulcers may use slow and brisk walking for exercise to reduce PPP, thus reducing risk for foot ulcers. Our study demonstrated that slow running at 9 km/h significantly increases PPP.

Long-term mortality in heart failure with mid-range ejection fraction: systematic review and meta-analysis.

AIMS: Heart failure patients with mid-range ejection fraction (HFmrEF) have overlapping clinical features, compared with patients with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF). We aim to perform a meta-analysis of studies reporting long-term outcomes in HFmrEF compared with HFrEF and HFpEF. METHODS AND RESULTS: Data from 18 eligible large-scale studies including 126 239 patients were pooled. Patients with HFmrEF had a lower risk of all-cause death than those with HFrEF [risk ratio (RR) = 0.92; 95% CI = 0.85-0.98; P < 0.001]. This significant difference was seen in the follow-up at 1, 2, and 3 years. Patients with HFmrEF had significantly lower risk of cardiovascular (CV) deaths than HFrEF (RR = 0.77; 95% CI = 0.65-0.92; P < 0.001). Subgroup analysis showed that studies recruiting >50% of males had higher risk of deaths with HFrEF (RR = 1.15; 95% CI = 1.04-1.26; P = 0.006). When compared with HFpEF, patients with HFmrEF had comparable risk of all-cause death (RR = 1.02; 95% CI = 0.96-1.09; P = 0.53). Similarly, there were no differences in the 1, 2, and 3 year deaths; CV and non-CV deaths were insignificant between HFmrEF and HFpEF. CONCLUSIONS: The results of the study support that HFmrEF has better prognosis than HFrEF but similar prognosis when compared with HFpEF. Gender disparity between studies seems to influence the results between HFmrEF and HFrEF. Transition in left ventricular ejection fraction (LVEF), which could not be addressed in the study, may play a decisive role in determining outcomes. PROSPERO review registration number CRD42021277107.

Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System.

Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a decentralized, immutable, shared, and distributed ledger. Blockchain can store all types of data with better security. It avoids third-party intervention to ensure better security of the data. Deep learning is another booming field that is mostly used in computer applications. This work proposes an integrated environment of a blockchain-deep learning environment for analyzing the Electronic Health Records (EHR). The EHR is the medical documentation of a patient which can be shared among hospitals and other public health organizations. The proposed work enables a deep learning algorithm act as an agent to analyze the EHR data which is stored in the blockchain. This proposed integrated environment can alert the patients by means of a reminder for consultation, diet chart, etc. This work utilizes the deep learning approach to analyze the EHR, after which an alert will be sent to the patient's registered mobile number.

COVID-19 Public Opinion: A Twitter Healthcare Data Processing Using Machine Learning Methodologies.

The COVID-19 pandemic has shattered the whole world, and due to this, millions of people have posted their sentiments toward the pandemic on different social media platforms. This resulted in a huge information flow on social media and attracted many research studies aimed at extracting useful information to understand the sentiments. This paper analyses data imported from the Twitter API for the healthcare sector, emphasizing sub-domains, such as vaccines, post-COVID-19 health issues and healthcare service providers. The main objective of this research is to analyze machine learning models for classifying the sentiments of people and analyzing the direction of polarity by considering the views of the majority of people. The inferences drawn from this analysis may be useful for concerned authorities as they work to make appropriate policy decisions and strategic decisions. Various machine learning models were developed to extract the actual emotions, and results show that the support vector machine model outperforms with an average accuracy of 82.67% compared with the logistic regression, random forest, multinomial naïve Bayes and long short-term memory models, which present 78%, 77%, 68.67% and 75% accuracy, respectively.

Intratumoral T cells have a differential impact on FDG-PET parameters in follicular lymphoma.

Data on the prognostic impact of pretherapy 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in follicular lymphoma (FL) is conflicting. The predictive utility of pretherapy total metabolic tumor volume (TMTV) and maximum standardized uptake value (SUVmax) on outcome appears to vary between regimens. Chemoimmunotherapies vary in the extent of T-cell depletion they induce. The role of intratumoral T cells on pretherapy FDG-PET parameters is undefined. We assessed pretherapy FDG-PET parameters and quantified intratumoral T cells by multiple methodologies. Low intratumoral T cells associated with approximately sixfold higher TMTV, and FL nodes from patients with high TMTV showed increased malignant B-cell infiltration and fewer clonally expanded intratumoral CD8+ and CD4+ T-follicular helper cells than those with low TMTV. However, fluorescently labeled glucose uptake was higher in CD4+ and CD8+ T cells than intratumoral B cells. In patients with FDG-PET performed prior to excisional biopsy, SUVmax within the subsequently excised node associated with T cells but not B cells. In summary, TMTV best reflects the malignant B-cell burden in FL, whereas intratumoral T cells influence SUVmax. This may contribute to the contradictory results between the prognostic role of different FDG-PET parameters, particularly between short- and long-term T-cell-depleting chemoimmunotherapeutic regimens. The impact of glucose uptake in intratumoral T cells should be considered when interpreting pretherapy FDG-PET in FL.

Using Elastographic Ultrasound to Assess the Effect of Cupping Size of Cupping Therapy on Stiffness of Triceps Muscle.

OBJECTIVE: Cupping therapy may reduce muscle stiffness for managing fatigue. However, there is no scientific evidence showing changes of muscle stiffness after cupping therapy. Furthermore, it is unclear whether the cup size of cupping therapy affects the change of muscle stiffness. The objective of this study was to compare the effect of cup size of cupping therapy on muscle stiffness. DESIGN: A repeated measures design with a counterbalanced design was used to test three cup sizes (45, 40, and 35 mm in inner diameter) in 12 healthy participants. Strain elastography was used to measure stiffness of the triceps before and after cupping therapy at 300 mm Hg for 5 mins. Strain elastogram was converted to the grayscale for the quantification of stiffness. RESULTS: The overall stiffness of triceps significantly reduced after cupping therapy with the 45-mm (106.2 ± 7.7, P < 0.05) and 40-mm (109.6 ± 7.1, P < 0.05) cups, but not the 35-mm cup (115.5 ± 10.3, nonsignificant) compared with before cupping (115.8 ± 13.5). The stiffness of superficial layer did not show significantly difference in all three sizes of cup. The stiffness of deep layer significantly reduced after the cupping therapy with the 45- and 40-mm cups. CONCLUSIONS: This is the first study demonstrating that cupping therapy significantly reduced muscle stiffness, especially at the deep layer.

High proportion of anergic B cells in the bone marrow defined phenotypically by CD21(-/low)/CD38- expression predicts poor survival in diffuse large B cell lymphoma.

BACKGROUND: Diffuse large B cell lymphoma (DLBCL) is the commonest lymphoma that is highly aggressive where one-third of the patients relapse despite effective treatment. Interaction between the lymphoma cells and the non-clonal immune cells within the bone marrow microenvironment is thought to play a critical role in the pathogenesis of DLBCL. METHODS: We used flow cytometry to characterize the proportion of B cell subpopulations in the bone marrow (N = 47) and peripheral blood (N = 54) of 75 DLBCL patients at diagnosis and study their impact on survival. RESULTS: Anergic B cells in the bone marrow (BM), characterized as having CD21(-/low)/CD38- expression, influenced survival with high numbers (defined as > 13.9%) being associated with significantly shorter overall survival (59.7 months vs 113.6 months, p = 0.0038). Interestingly, low numbers of anergic B cells in the BM (defined as ≤13.9%) was associated with germinal center B cell type of DLBCL (p = 0.0354) that is known to have superior rates of survival when compared to activated B cell type. Finally, Cox regression analysis in our cohort of patients established that the inferior prognosis of having high numbers of anergic B cells in the bone marrow was independent of the established Revised International Prognostic Index (R-IPI) score. CONCLUSIONS: High proportion of anergic B cells in the BM characterized by CD21(-/low)/CD38- expression predicts poor survival outcomes in DLBCL.

Comorbid Conditions Differentiate Rehabilitation Profiles in Traumatic Versus Nontraumatic Brain Injury: A Retrospective Analysis Using a Medical Database.

PURPOSE: We examined the relationship between comorbid medical conditions and changes in cognition over the course of rehabilitation following acquired brain injury. In particular, we compared outcomes between traumatic brain injury (TBI) and non-TBI using a retrospective inpatient rehabilitation dataset. We hypothesized that differences by diagnosis would be minimized among subgroups of patients with common comorbid medical conditions. MATERIALS AND METHODS: We used the Functional Independence Measure (FIM)-cognition subscale to index changes in cognition over rehabilitation. A decision tree classifier determined the top 10 comorbid conditions that maximally differentiated TBI and non-TBI. Ten subsets of patients were identified by matching on these conditions, in rank order. Data from these subsets were submitted to repeated-measures logistic regression to establish the minimum degree of commonality in comorbid conditions that would produce similar cognitive rehabilitation, regardless of etiology. RESULTS: The TBI group demonstrated a greater increase in ordinal scores over time relative to non-TBI, across all subscales of the FIM-cognition. When both groups were matched on the top 3 symptoms, there were no significant group differences in rehabilitation trajectory in problem-solving and memory domains (Cohen's d range: 0.2-0.4). CONCLUSION: Comorbid medical conditions explain differences in cognitive rehabilitation trajectories following acquired brain injury beyond etiology.

LAG3: a novel immune checkpoint expressed by multiple lymphocyte subsets in diffuse large B-cell lymphoma.

Blockade of the PD-1 axis has modest efficacy in diffuse large B-cell lymphoma (DLBCL), but data regarding LAG3 are sparse. The impact of LAG3 digital gene expression was tested in 309 patients with DLBCL treated with standard chemoimmunotherapy. Cellular distribution of LAG3 protein was determined by immunohistochemistry and flow cytometry. In tumor-infiltrating lymphocytes (TILs), LAG3 expression was highest on CD4+ regulatory T cells (Tregs) and was also highly expressed on CD8+ T cells compared with CD4+ non-Tregs (both P = .008). LAG3high TILs were enriched in PD-1 and TIM-3. LAG3 was also expressed on a proportion of malignant B cells, and these patients had significantly higher LAG3 messenger RNA in their biopsies (P = .03). LAG3high gene expression was associated with inferior survival in discovery/validation cohorts, independent of cell of origin and the international prognostic index. Patients who were PD-L1high were fivefold more likely to be LAG3high (P < .0001). Patients who were LAG3high/PD-L1high had an inferior progression-free survival (P = .011) and overall survival (P = .005) compared with patients who were LAG3low/PD-L1high. Digital spatial protein analysis confirms LAG3 expression on T cells and, surprisingly, tumor-associated macrophages (TAMs) at higher levels than found on CD20+ B cells in the tumor microenvironment. LAG3 is frequently expressed on CD4+ Tregs and CD8+ TILs, typically with other immune checkpoints, and is also present in a proportion of malignant B cells in DLBCL and in areas enriched for TAMs. LAG3high expression is associated with poor outcome independent of conventional prognosticators.

Dynamic changes in seating pressure gradient in wheelchair users with spinal cord injury.

Pressure ulcer interventions are commonly assessed with measures of seating interface pressure, such as peak pressure gradients (PPGs). Decreases in PPG magnitudes may reduce pressure ulcer risk by decreasing tissue deformation and increasing tissue perfusion of at-risk weight-bearing tissues. Changes in PPG directions, which have previously been overlooked in the seating pressure literature, may provide a transient increase in blood flow to at-risk tissues, even if the PPG magnitude and location remain the same. The purpose of this study was to assess both PPG components in response to combinations of wheelchair tilt and recline angles. Thirteen power wheelchair users were recruited into the study. Six combinations of wheelchair tilt (15°, 25°, and 35°) and recline (10° and 30°) were tested in random order. Each combination was tested with 5-min upright sitting, 5-min tilt and recline, and 5-min maximal pressure relief recovery. Changes in PPG magnitudes and PPG directions under the left ischial tuberosity were computed for the six angle combinations. The findings in this study suggested that when combining wheelchair tilt and recline, the recline function may be particularly useful in reducing PPG magnitudes, while the tilt function may be particularly useful in manipulating PPG directions.

Effects of walking speeds and durations on plantar skin blood flow responses.

BACKGROUND: Various walking speeds and durations in daily life cause different levels of ischemia of plantar tissues. It is unclear what walking speeds and durations significantly affect plantar tissue viability and risks for foot ulcers in non-diabetics and diabetics. OBJECTIVE: The aim of this study was to establish the normal response of plantar skin blood flow to different speeds and durations of walking exercise in non-diabetics that would be needed to quantify impaired responses in diabetics. METHOD: Laser Doppler flowmetry was used to measure plantar skin blood flow of the first metatarsal head in 12 non-diabetics. A 3 × 2 factorial design, including 3 speeds (slow at 3 km/h, moderate at 6 km/h, and fast at 9 km/h) and 2 durations (10 and 20 min), was used in this study. Skin blood flow after walking was expressed as a ratio of skin blood flow before walking. The 3 × 2 two-way analysis of variance (ANOVA) with repeated measures was used to examine the main effects of speeds and durations and their interaction. RESULT: The walking speed significantly affected skin blood flow responses (p < 0.01). Walking at 9 km/h significantly increased plantar skin blood flow (5.71 ±â€¯1.89) compared to walking at 6 km/h (2.1 ±â€¯0.29) and 3 km/h (1.16 ±â€¯0.14), especially at 20-minute walking duration (p < 0.01). The walking duration showed a trend of significance on affecting skin blood flow responses (p = 0.06). There was no significant interaction between walking speeds and durations (p > 0.05). CONCLUSIONS: Our results provide the first evidence that walking speeds affect plantar skin blood flow and a fast walking speed (9 km/h) significantly increases plantar skin blood flow compared to moderate (6 km/h) and slow (3 km/h) walking speeds.

The tumour microenvironment is immuno-tolerogenic and a principal determinant of patient outcome in EBV-positive diffuse large B-cell lymphoma.

OBJECTIVE: Epstein-Barr virus-positive diffuse large B-cell lymphoma (EBV-pos DLBCL) is a recently identified entity. Data regarding outcome to frontline immuno-chemotherapy are conflicting. Although the prognostic impact of the tumour microenvironment (TME) in EBV-neg DLBCL is well-established, it remains untested whether the TME influences survival in EBV-pos DLBCL. There are no data with new digital gene expression technologies that simultaneously interrogate the virus, B cells and the tumour microenvironment (TME). METHODS: We used the NanoString™ platform in a population-based cohort of 433 patients to establish if the technology could detect EBV in the tumour biopsies and to investigate the influence that EBV has on the complex tumour microenvironment of DLBCL. RESULTS: Incidence of EBV-pos DLBCL was 6.9% with 5-year survival of 65% vs 82% in EBV-neg DLBCL (P = 0.018). EBV-pos tissues had similar expression of T-cell genes compared to EBV-neg DLBCL but higher levels of the antigen-presenting molecule B2M. This was countered by elevated PD-L1, PD-L2, LAG3 and TIM3 immune checkpoints and a higher CD163/CD68 "M2" macrophage score. CONCLUSION: In EBV-pos DLBCL, the TME is immuno-tolerogenic and may explain the poor outcomes seen in this subtype of DLBCL.