The impact of different step rate threshold methods on physical activity intensity in older adults

BackgroundOlder adults benefit most from engaging in higher-intensity physical activity, which is often determined using step rate thresholds. Fixed step rate thresholds that correspond to moderate (MPA) and vigorous-intensity physical activity (VPA) have been developed for heuristic activity promotion. The activPAL monitor uses step rate thresholds to determine activity intensity. Stepping thresholds may also vary based on body mass index (BMI) or aerobic fitness level in older adults. Despite the various thresholds used in the literature, it is unclear whether they produce similar outcomes.Research QuestionHow does time spent in physical activity intensities compare between different step rate thresholds in older adults?MethodsThirty-eight participants (24♀; 67 ± 4 years; BMI: 26.6 ± 4.4 kg/m²) wore an activPAL monitor 24-hr/day for up to 7-d (total: 205-d). Aerobic fitness (V̇O₂max: 23 ± 8 ml/kg/min) was determined via indirect calorimetry during a maximal, graded cycling test. Time spent in each intensity category (light-physical-activity [LPA], MPA, VPA) was determined using the fixed (MPA/VPA) 100/130, 110/130, and activPAL step rate thresholds (74/212), as well as BMI-adjusted absolute (108.5 ± 2.5/134.0 ± 4.8) and BMI-adjusted relative (40%/60% V̇O₂max; 111.4 ± 14.7/132.0 ± 19.0) cut-offs. Times spent in each intensity category were compared between methods.ResultsThe activPAL and 100/130 thresholds yielded less LPA and more MPA than all other methods. The activPAL had no time spent in VPA at all. The BMI-adjusted absolute and relative thresholds produced statistically equivalent time in LPA and MPA (via equivalence testing), but not VPA. No two methods yielded similar time spent in LPA, MPA, or VPA.SignificanceThe choice of step rate threshold has a major impact on physical activity intensity outcomes in older adults. Inherently, strategies that adjust for older adults’ body size and/or aerobic fitness level provide a more individualized data processing strategy than fixed thresholds that assume the same threshold for all older adults     

A Proposal for an Alternative Approach to Particle Size Method Development During Early-Stage Small Molecule Pharmaceutical Development

Particle size analysis in the pharmaceutical industry has long been a source of debate regarding how best to define measurement accuracy; the degree to which the result of a measurement or calculation conforms to the true value. Defining a “true” value for the size of a particle can be challenging as the output of its measurement will differ because of variations in measurement approaches, instrumental differences and calculation methods. Consequently, for “real” particles, a universal “true” value does not exist and accuracy is therefore not a definable characteristic. Accordingly, precision is then a measure of the ability to reproducibly achieve a measurement of unknown relevance.This article proposes, in place of accuracy, a means to define the “appropriateness” of a measurement in line with the critical quality attributes (CQA) of the material being characterized. The decision as to whether the measurement is correct should involve a link to the CQA; that is, correlation should be demonstrated, without which the measured particle size cannot be defined as a critical material attribute.Correspondingly, methods should also be able to provide sufficient precision to demonstrate discrimination relating to variation in the CQA. The benefits and challenges of this approach are discussed.     

Evaluation of selective attention in patients with misophonia

IntroductionMisophonia is characterized by the aversion to very selective sounds, which evoke a strong emotional reaction. It has been inferred that misophonia, as well as tinnitus, is associated with hyperconnectivity between auditory and limbic systems. Individuals with bothersome tinnitus may have selective attention impairment, but it has not been demonstrated in case of misophonia yet.ObjectiveTo characterize a sample of misophonic subjects and compare it with two control groups, one with tinnitus individuals (without misophonia) and the other with asymptomatic individuals (without misophonia and without tinnitus), regarding the selective attention.MethodsWe evaluated 40 normal-hearing participants: 10 with misophonia, 10 with tinnitus (without misophonia) and 20 without tinnitus and without misophonia. In order to evaluate the selective attention, the dichotic sentence identification test was applied in three situations: firstly, the Brazilian Portuguese test was applied. Then, the same test was applied, combined with two competitive sounds: chewing sound (representing a sound that commonly triggers misophonia), and white noise (representing a common type of tinnitus which causes discomfort to patients).ResultsThe dichotic sentence identification test with chewing sound, showed that the average of correct responses differed between misophonia and without tinnitus and without misophonia (p = 0.027) and between misophonia and tinnitus (without misophonia) (p = 0.002), in both cases lower in misophonia. Both, the dichotic sentence identification test alone, and with white noise, failed to show differences in the average of correct responses among the three groups (p ≥ 0.452).ConclusionThe misophonia participants presented a lower percentage of correct responses in the dichotic sentence identification test with chewing sound; suggesting that individuals with misophonia may have selective attention impairment when they are exposed to sounds that trigger this condition.     

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study

IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.     

Influence of COMT genotype and affective distractors on the processing of self-generated thought

The catechol-O-methyltransferase (COMT) enzyme is a major determinant of prefrontal dopamine levels. The Val¹⁵⁸Met polymorphism affects COMT enzymatic activity and has been associated with variation in executive function and affective processing. This study investigated the effect of COMT genotype on the flexible modulation of the balance between processing self-generated and processing stimulus-oriented information, in the presence or absence of affective distractors. Analyses included 124 healthy adult participants, who were also assessed on standard working memory (WM) tasks. Relative to Val carriers, Met homozygotes made fewer errors when selecting and manipulating self-generated thoughts. This effect was partly accounted for by an association between COMT genotype and visuospatial WM performance. We also observed a complex interaction between the influence of affective distractors, COMT genotype and sex on task accuracy: male, but not female, participants showed a sensitivity to the affective distractors that was dependent on COMT genotype. This was not accounted for by WM performance. This study provides novel evidence of the role of dopaminergic genetic variation on the ability to select and manipulate self-generated thoughts. The results also suggest sexually dimorphic effects of COMT genotype on the influence of affective distractors on executive function.     

Effect of Day Optimizing Throughput (Dot) Knee Software Implementation on Magnetic Resonance Imaging Workflow Efficiency

PurposeAttempts by magnetic resonance (MR) manufacturers to help imaging centres improve patient throughput has led to the development of more automated acquisition. This software is capable of customizing individual scan alignment; potentially improving imaging efficiency and standardizing protocols. However, substantial investments are required to introduce such systems, potentially deterring their widespread application. This study assessed the implementation costs and reduction in examination durations for automated knee MR imaging (MRI) software.Materials and MethodsResearch activities were performed at a community-based academic centre on a 3-Tesla (3-T) system using Siemens' Day Optimizing Throughput (Dot) knee software. Examination acquisition times were extracted from the system before and after software implementation. Fiscal year 2012/13 finances were used to determine the average hourly cost of MRI utilization. Costs associated with automated software implementation were also calculated. Finally, the number of knee scans required to achieve a positive return on investment using the software was established.Results and DiscussionThe mean (standard deviation, sample size) pre- and post-Dot software scan times were 23.20 (4.18, n = 266) and 21.94 (4.51, n = 59) minutes, respectively, for a routine knee scan and 11.88 (1.60, n = 74) and 11.24 (1.51, n = 27) minutes, respectively, for a fast knee scan. The overall weighted average resulted in a 64-second time savings per automated knee examination. This negligible time savings would be extremely difficult to make use of clinically. Dot simplified 29 unique knee protocols to two, improving the consistency of knee examinations. Current Dot software is not compatible with all patients and therefore has limitations that are a concern among MR technologists.ConclusionAdoption of automated knee systems could assist in standardizing protocols; however, the cost of implementation and difficulty in modifying patient scheduling to reflect the minimal time savings would make a financial return unlikely to occur at small- and medium-sized institutions.     

Building and Exploitation of Learning Curves to Train Radiographer Students in X-Ray CT Image Postprocessing

IntroductionThis study aims to construct learning curves related to the realization of standardized postprocessing by radiographer students and to discuss their exploitation and interest.Materials and MethodsThis study was carried out in 21 French students in their 3rd year of training. Two postprocessing protocols in CT (#1 traumatic shoulder; #2 petrous bone) were repeated 15 times by each student. Each achievement was timed to obtain overall learning curves. The realization accuracy was also assessed for each student at each repetition.ResultsThe learning rates for the two protocols are 63% and 56%, respectively. The number of repetitions to reach the reference time for each protocol is 11 and 12, respectively. In both protocols, the standard deviations are significantly reduced and stabilized during repetitions. The mean accuracy progresses more quickly in protocol #1.DiscussionThe measured learning rates reflect a rapid learning process for each protocol. The analysis of the standard deviations shows that students have reached a homogeneous level. The average times and accuracies measured during the last repetitions show that the group has reached a high level of performance. Building learning curves helps students measure their progress and motivates them.ConclusionObtaining learning curves allows trainers/supervisors to qualify the learning difficulty of a task while motivating students/radiographers. The use of learning curves is inline with the competency-based training paradigm.     

H型高血压患者舌面诊图像颜色特征参数分析＊

目的 分析H型高血压患者的舌面诊图像颜色参数特征，探讨H型高血压患者的舌诊、面诊变化规律。方法 运用上海中医药大学自行研制的Smart TCM-1型中医舌面一体仪，采集高血压患者舌面诊图像，提取特征参数，分析健康对照组、H型高血压组与非H型高血压组患者舌面颜色参数特征。结果 ①在舌色各项参数中，H型高血压组舌尖部R值、B值、V值均显著小于健康对照组（P < 0.01）；非H型高血压组舌尖部B值显著小于健康对照组（P < 0.01），S值较健康对照组显著增大（P < 0.05）；H型高血压组舌尖部R、V值均明显小于非H型高血压组（P < 0.05）。在舌苔各项参数中，H型高血压组舌中H值、V值均明显小于健康对照组（P < 0.05）；非H型高血压组舌中V值、舌右V值均显著小于健康对照组（P < 0.01）；H型高血压组舌中H值明显小于非H型高血压组（P < 0.05），右侧舌苔S值明显大于非H型高血压组（P < 0.05）。②H型高血压组面色参数鼻G值、下颌G值、口唇R值、口唇V值均明显小于健康对照组（P < 0.05）；非H型高血压组前额H值、目眶H值、脸颊H值、鼻H值、下颌H值、整体H值均明显大于健康对照组（P < 0.05）；H型高血压组前额H值、目眶G值、目眶H值、脸颊H值、鼻G值、鼻H值、下颌R值、下颌G值、下颌H值、下颌V值、口唇R值、口唇G值、口唇V值、整体R值、整体G值、整体H值、整体V值均明显小于非H型高血压组（P < 0.05）。结论 H型高血压患者苔色偏黄，以舌中部为主，且舌右侧黄苔积聚较明显；H型高血压患者面色为黄中带红，口唇、下颌部更为晦暗。H型高血压患者的舌、面诊特征参数的变化，与高血压病阳亢湿盛病机相符。     

中药栀子本草考证

栀子临床应用广泛,且历史悠久,为更好地利用栀子资源,通过梳理历代文献与现代研究,对栀子名称、品种、产地、炮制、功效等方面进行考证,发现栀子命名主要以形态、色泽为依据,一定程度上反映了栀子的特征,并且存在与水栀子混用"黄栀"之名的情况。古代文献中记载的栀子产地最早为南阳,但产量不高,受人口迁移以及生产力发展的影响,栀子的产地主要转移到南方,且以南方产者为佳。在历代本草文献中记载入药用的栀子为山栀子,水栀子不堪入药,但在《伤寒论》等古代方书中有"肥栀子""大栀子"入药用的记载,通过后世对相应方剂的记载,确定二者应为水栀子,为水栀子的临床应用提供了有力依据。之所以与本草文献记载有所差异,应与《雷公炮炙论》和《伤寒论》的年代不同,栀子的产量及采收能力有所差距,且本草书重规范,择优入药,方书注重实用等特点有关,并且根据现代实验研究表明山栀子与水栀子化学成分组成、含量相似,具有相同的利胆作用。此外,系统整理了历代本草与方书中栀子的炮制方法和功效,并进行了分析,为栀子属资源的进一步研究与利用提供了参考和借鉴。