Application of the speed-duration relationship to normalize the intensity of high-intensity interval training

The tolerable duration of continuous high-intensity exercise is determined by the hyperbolic Speed-tolerable duration (S-tLIM) relationship. However, application of the S-tLIM relationship to normalize the intensity of High-Intensity Interval Training (HIIT) has yet to be considered, with this the aim of present study. Subjects completed a ramp-incremental test, and series of 4 constant-speed tests to determine the S-tLIM relationship. A sub-group of subjects (n = 8) then repeated 4 min bouts of exercise at the speeds predicted to induce intolerance at 4 min (WR4), 6 min (WR6) and 8 min (WR8), interspersed with bouts of 4 min recovery, to the point of exercise intolerance (fixed WR HIIT) on different days, with the aim of establishing the work rate that could be sustained for 960 s (i.e. 4×4 min). A sub-group of subjects (n = 6) also completed 4 bouts of exercise interspersed with 4 min recovery, with each bout continued to the point of exercise intolerance (maximal HIIT) to determine the appropriate protocol for maximizing the amount of high-intensity work that can be completed during 4×4 min HIIT. For fixed WR HIIT tLIM of HIIT sessions was 399±81 s for WR4, 892±181 s for WR6 and 1517±346 s for WR8, with total exercise durations all significantly different from each other (P<0.050). For maximal HIIT, there was no difference in tLIM of each of the 4 bouts (Bout 1: 229±27 s; Bout 2: 262±37 s; Bout 3: 235±49 s; Bout 4: 235±53 s; P>0.050). However, there was significantly less high-intensity work completed during bouts 2 (153.5±40. 9 m), 3 (136.9±38.9 m), and 4 (136.7±39.3 m), compared with bout 1 (264.9±58.7 m; P>0.050). These data establish that WR6 provides the appropriate work rate to normalize the intensity of HIIT between subjects. Maximal HIIT provides a protocol which allows the relative contribution of the work rate profile to physiological adaptations to be considered during alternative intensity-matched HIIT protocols

Photocatalytic proton reduction by a computationally identified, molecular hydrogen-bonded framework

We show that a hydrogen-bonded framework, TBAP-α, with extended π-stacked pyrene columns has a sacrificial photocatalytic hydrogen production rate of up to 3108 μmol g^{−1} h^{−1}. This is the highest activity reported for a molecular organic crystal. By comparison, a chemically-identical but amorphous sample of TBAP was 20–200 times less active, depending on the reaction conditions, showing unambiguously that crystal packing in molecular crystals can dictate photocatalytic activity. Crystal structure prediction (CSP) was used to predict the solid-state structure of TBAP and other functionalised, conformationally-flexible pyrene derivatives. Specifically, we show that energy–structure–function (ESF) maps can be used to identify molecules such as TBAP that are likely to form extended π-stacked columns in the solid state. This opens up a methodology for the a priori computational design of molecular organic photocatalysts and other energy-relevant materials, such as organic electronics

Integrated multiple mediation analysis: A robustness–specificity trade-off in causal structure

Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and interpretations of causal effects, making it unclear which method ought to be selected when investigating a given causal effect. Thus, in this study, we construct an integrated framework, which unifies all existing methodologies, as a standard for mediation analysis with multiple mediators. To clarify the relationship between existing methods, we propose four strategies for effect decomposition: two-way, partially forward, partially backward, and complete decompositions. This study reveals how the direct and indirect effects of each strategy are explicitly and correctly interpreted as path-specific effects under different causal mediation structures. In the integrated framework, we further verify the utility of the interventional analogues of direct and indirect effects, especially when natural direct and indirect effects cannot be identified or when cross-world exchangeability is invalid. Consequently, this study yields a robustness–specificity trade-off in the choice of strategies. Inverse probability weighting is considered for estimation. The four strategies are further applied to a simulation study for performance evaluation and for analyzing the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer data set from Taiwan to investigate the causal effect of hepatitis C virus infection on mortality

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Penetrating spinal injury with wooden fragments causing cauda equina syndrome: case report and literature review

Study design: Case report Objective: To report an unusual case of cauda equina syndrome following penetrating injury to the lumbar spine by wooden fragments and to stress the importance of early magnetic resonance imaging (MRI) in similar cases. Summary of background data: A 22-year-old girl accidentally landed on wooden bannister and sustained a laceration to her back. She complained of back pain but had fully intact neurological function. The laceration in her back was explored and four large wooden pieces were removed. However 72 h later, she developed cauda equina syndrome. MRI demonstrated the presence of a foreign body between second and third lumbar spinal levels following which she underwent emergency decompressive laminectomy and the removal of the multiple wooden fragments that had penetrated the dura. Results: Post-operatively motor function in her lower limbs returned to normal but she continued to require a catheter for incontinence. At review 6 months later, she was mobilising independently but the incontinence remained unchanged. Conclusion: There are no reported cases in the literature of wooden fragments penetrating the dura from the back with or without the progression to cauda equina syndrome. The need for a high degree of suspicion and an early MRI scan to localise any embedded wooden fragments that may be separate from the site of laceration is emphasized even if initial neurology is intact

Diagnostic dilemmas of squamous differentiation in prostate carcinoma case report and review of the literature

We report a case of pure squamous cell carcinoma involving the prostate and urinary bladder and describe the diagnostic dilemmas that we faced in trying to determine its origin. The patient was diagnosed ten years ago with prostatic adenocarcinoma treated with radioactive seed implantation. During the last year he also underwent a TURP procedure for urinary obstruction complicated by multiple infections. Postsurgery, the patient developed colo-urethral fistula and decision to perform cystprostatectomy was taken. Excision illustrated a tumor mass replacing the entire prostate that microscopically proved to be squamous cell carcinoma. The challenge that we encountered was to determine its origin, the possibilities being divergent differentiation from adenocarcinoma post radiation therapy, de novo neoplasm or urothelial carcinoma with extensive squamous differentiation. Our literature review showed also that the etiology of prostatic squamous carcinoma is still unclear. We present our approach in an attempt to solve this dilemma

West Antarctic ice loss influenced by internal climate variability and anthropogenic forcing

Recent ice loss from the West Antarctic Ice Sheet has been caused by ocean melting of ice shelves in the Amundsen Sea. Eastward wind anomalies at the shelf break enhance the import of warm Circumpolar Deep Water onto the Amundsen Sea continental shelf, which creates transient melting anomalies with an approximately decadal period. No anthropogenic influence on this process has been established. Here, we combine observations and climate model simulations to suggest that increased greenhouse gas forcing caused shelf-break winds to transition from mean easterlies in the 1920s to the near-zero mean zonal winds of the present day. Strong internal climate variability, primarily linked to the tropical Pacific, is superimposed on this forced trend. We infer that the Amundsen Sea experienced decadal ocean ariability throughout the twentieth century, with warm anomalies gradually becoming more prevalent, offering a credible explanation for the ongoing ice loss. Existing climate model projections show that strong future greenhouse gas forcing creates persistent mean westerly shelf-break winds by 2100, suggesting a further enhancement of warm ocean anomalies. These wind changes are weaker under a scenario in which greenhouse gas concentrations are stabilized

ATM haplotypes and breast cancer risk in Jewish high-risk women

While genetic factors clearly play a role in conferring breast cancer risk, the contribution of ATM gene mutations to breast cancer is still unsettled. To shed light on this issue, ATM haplotypes were constructed using eight SNPs spanning the ATM gene region (142 kb) in ethnically diverse non-Ashkenazi Jewish controls (n=118) and high-risk (n=142) women. Of the 28 haplotypes noted, four were encountered in frequencies of 5% or more and accounted for 85% of all haplotypes. Subsequently, ATM haplotyping of high-risk, non-Ashkenazi Jews was performed on 66 women with breast cancer and 76 asymptomatic. One SNP (rs228589) was significantly more prevalent among breast cancer cases compared with controls (P=4 × 10−9), and one discriminative ATM haplotype was significantly more prevalent among breast cancer cases (33.3%) compared with controls (3.8%), (P⩽10−10). There was no significant difference in the SNP and haplotype distribution between asymptomatic high-risk and symptomatic women as a function of disease status. We conclude that a specific ATM SNP and a specific haplotype are associated with increased breast cancer risk in high-risk non-Ashkenazi Jews