Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brain's functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC.

Gas chromatography/mass spectrometry (GC/MS) has long been considered one of the premiere analytical tools for small molecule analysis. Recently, a number of GC/MS systems equipped with high-resolution mass analyzers have been introduced. These systems provide analysts with a new dimension of information, accurate mass measurement to the third or fourth decimal place; however, existing data processing tools do not capitalize on this information. Beyond that, GC/MS spectral reference libraries, which have been curated over the last several decades, contain almost exclusively unit resolution MS spectra making integration of accurate mass data dubious. Here we present an informatic approach, called high-resolution filtering (HRF), which bridges this gap. During HRF, high-resolution mass spectra are assigned putative identifications through traditional spectral matching at unit resolution. Once candidate identities have been assigned, all unique combinations of atoms from these candidate precursors are generated and matched to m/z peaks using narrow mass tolerances. The total amount of measured signal that is annotated is used as a metric of plausibility for the presumed identification. Here we demonstrate that the HRF approach is both feasible and highly specific toward correct identifications.

This study compared the efficacy of neoadjuvant chemotherapy (NACT) followed by radical surgery (RS) vs primary surgical treatment (PST) in patients diagnosed with International Federation of Gynecology and Obstetrics (FIGO) stage IB2/IIA2 cervical cancer.Data of 303 cervical cancer patients who received primary therapy for stage IB2/IIA2 cervical cancer at 7 medical centers in Beijing, China between January 1, 2009 and December 31, 2016 and followed through December 31, 2017 were collected retrospectively. The response rates, surgical characteristics, and overall survival (OS) durations of patients who received NACT followed by RS were compared to those of patients who received PST.An improved short-term complete response rate was observed among patients who received intra-arterial chemotherapy compared with patients who had intravenous chemotherapy (18.3% vs 4.1%, Pdifference = .020). Patients who received NACT were more likely to undergo laparoscopic surgery and to have a lower blood loss volume (555.4 ± 520.2 ml vs PST, 682.5 ± 509.8 ml; P = .036) and increased estimated operative time (249.9 ± 101.9 vs PST, 225.1 ± 76.5 min; P = .022). No differences in high-risk factors (HRFs), the effects of supplemental treatment, or 5-year OS were observed between patients who received NACT and PST.Our findings indicate that patients who received NACT for FIGO stage IB2/IIA2 cervical cancer were more likely to undergo laparoscopic surgery. These findings have important implications regarding treatment with curative intent for stage IB2/IIA2 cervical cancer and warrant a further analysis of treatment strategies to ensure adequate treatment and patient-centered care.

In recent years mass spectrometry-based covalent labeling techniques such as hydroxyl radical footprinting (HRF) have emerged as valuable structural biology techniques, yielding information on protein tertiary structure. These data, however, are not sufficient to predict protein structure unambiguously, as they provide information only on the relative solvent exposure of certain residues. Despite some recent advances, no software currently exists that can utilize covalent labeling mass spectrometry data to predict protein tertiary structure. We have developed the first such tool, which incorporates mass spectrometry derived protection factors from HRF labeling as a new centroid score term for the Rosetta scoring function to improve the prediction of protein tertiary structures. We tested our method on a set of four soluble benchmark proteins with known crystal structures and either published HRF experimental results or internally acquired data. Using the HRF labeling data, we rescored large decoy sets of structures predicted with Rosetta for each of the four benchmark proteins. As a result, the model quality improved for all benchmark proteins as compared to when scored with Rosetta alone. For two of the four proteins we were even able to identify atomic resolution models with the addition of HRF data.

The purpose of this study was to investigate the relationship between organized sport (OS) participation and health-related fitness (HRF) in adolescents. A total of 320 adolescents (176 boys) aged between 10 and 16 years reported their engagement in OS and were assessed on 5 components of HRF (cardiovascular endurance, push-ups, curl-ups, flexibility, and body mass index). Data on OS participation frequency and duration were collected through a self-reported questionnaire. Adolescents were stratified by OS participation (engaged, n = 113; nonengaged, n = 220; 55% boys). Nonparametric quantile regression models were used to estimate the differences in HRF by participation group. Less than 30% of the participants reported they were regularly engaged in OS. Frequency of participation ranged from 2 to 5 days per week (median = 2; SD = 3), and duration of participation ranged from 45 to 180 minutes per week (median = 81.7; SD = 32.4). Adolescents who participated in OS displayed better cardiovascular endurance (+4.1 laps completed), with no statistically significant difference detected on any other HRF component. Our results highlight engagement in OS as a promising strategy for achieving cardiovascular endurance. Engagement in OS alone does not seem to be sufficient to enhance fitness components other than cardiovascular endurance.

Functional near-infrared spectroscopy (fNIRS) has evolved as a neuro-imaging modality over the course of the past two decades. The removal of superfluous information accompanying the optical signal, however, remains a challenge. A comprehensive analysis of each step is necessary to ensure the extraction of actual information from measured fNIRS waveforms. A slight change in shape could alter the features required for fNIRS-BCI applications. In the present study, the effect of the differential path-length factor (DPF) values on the characteristics of the hemodynamic response function (HRF) was investigated. Results were compiled for both simulated data sets and healthy human subjects over a range of DPF values from three to eight. Different sets of activation durations and stimuli were used to generate the simulated signals for further analysis. These signals were split into optical densities under a constrained environment utilizing known values of DPF. Later, different values of DPF were used to analyze the variations of actual HRF. The results, as summarized into four categories, suggest that the DPF can change the main and post-stimuli responses in addition to other interferences. Six healthy subjects participated in this study. Their observed optical brain time-series were fed into an iterative optimization problem in order to estimate the best possible fit of HRF and physiological noises present in the measured signals with free parameters. A series of solutions was derived for different values of DPF in order to analyze the variations of HRF. It was observed that DPF change is responsible for HRF creep from actual values as well as changes in HRF characteristics.

Background and objective: In modern ophthalmology, automated Computer-aided Screening Tools (CSTs) are crucial non-intrusive diagnosis methods, where an accurate segmentation of Optic Disc (OD) and localization of OD and Fovea centers are substantial integral parts. However, designing such an automated tool remains challenging due to small dataset sizes, inconsistency in spatial, texture, and shape information of the OD and Fovea, and the presence of different artifacts.

Methods: This article proposes an end-to-end encoder-decoder network, named DRNet, for the segmentation and localization of OD and Fovea centers. In our DRNet, we propose a skip connection, named residual skip connection, for compensating the spatial information lost due to pooling in the encoder. Unlike the earlier skip connection in the UNet, the proposed skip connection does not directly concatenate low-level feature maps from the encoder's beginning layers with the corresponding same scale decoder. We validate DRNet using different publicly available datasets, such as IDRiD, RIMONE, DRISHTI-GS, and DRIVE for OD segmentation; IDRiD and HRF for OD center localization; and IDRiD for Fovea center localization.

Results: The proposed DRNet, for OD segmentation, achieves mean Intersection over Union (mIoU) of 0.845, 0.901, 0.933, and 0.920 for IDRiD, RIMONE, DRISHTI-GS, and DRIVE, respectively. Our OD segmentation result, in terms of mIoU, outperforms the state-of-the-art results for IDRiD and DRIVE datasets, whereas it outperforms state-of-the-art results concerning mean sensitivity for RIMONE and DRISHTI-GS datasets. The DRNet localizes the OD center with mean Euclidean Distance (mED) of 20.23 and 13.34 pixels, respectively, for IDRiD and HRF datasets; it outperforms the state-of-the-art by 4.62 pixels for IDRiD dataset. The DRNet also successfully localizes the Fovea center with mED of 41.87 pixels for the IDRiD dataset, outperforming the state-of-the-art by 1.59 pixels for the same dataset.

Conclusion: As the proposed DRNet exhibits excellent performance even with limited training data and without intermediate intervention, it can be employed to design a better-CST system to screen retinal images. Our source codes, trained models, and ground-truth heatmaps for OD and Fovea center localization will be made publicly available upon publication at GitHub.¹.

Keywords: Diabetic retinopathy and glaucoma; Encoder-decoder network; Ophthalmology; Segmentation and localization; Skip connection.

A public workshop, organized by a Steering Committee of scientists from government, industry, universities and research organizations, was held at the National Institute of Environmental Health Sciences (NIEHS) in September, 2010. The workshop explored the dose-response implications of toxicant modes of action (MOA) mediated by nuclear receptors. The dominant paradigm in human health risk assessment has been linear extrapolation without a threshold for cancer, and estimation of sub-threshold doses for non-cancer and (in appropriate cases) cancer endpoints. However, recent publications question the application of dose-response modeling approaches with a threshold. The growing body of molecular toxicology information and computational toxicology tools has allowed for exploration of the presence or absence of sub-threshold doses for a number of receptor-mediated MOAs. The workshop explored the development of dose-response approaches for nuclear receptor-mediated liver cancer, within a MOA Human Relevance Framework (HRF). Case studies addressed activation of the AHR, the CAR and the PPARα. This article describes the workshop process, key issues discussed and conclusions. The value of an interactive workshop approach to apply current MOA/HRF frameworks was demonstrated. The results may help direct research on the MOA and dose-response of receptor-based toxicity, since there are commonalities for many receptors in the basic pathways involved for late steps in the MOA, and similar data gaps in early steps. Three additional papers in this series describe the results and conclusions for each case-study receptor regarding its MOA, relevance of the MOA to humans and the resulting dose-response implications.

Background: China's "13th 5-Year Plan" (2016-2020) for the prevention and control of sudden acute infectious diseases emphasizes that epidemic monitoring and epidemic focus surveys in key areas are crucial for strengthening national epidemic prevention and building control capacity. Establishing an epidemic hot spot areas and prediction model is an effective means of accurate epidemic monitoring and surveying. Objective: This study predicted hemorrhagic fever with renal syndrome (HFRS) epidemic hot spot areas, based on multi-source environmental variable factors. We calculated the contribution weight of each environmental factor to the morbidity risk, obtained the spatial probability distribution of HFRS risk areas within the study region, and detected and extracted epidemic hot spots, to guide accurate epidemic monitoring as well as prevention and control. Methods: We collected spatial HFRS data, as well as data on various types of natural and human social activity environments in Hunan Province from 2010 to 2014. Using the information quantity method and logistic regression modeling, we constructed a risk-area-prediction model reflecting the epidemic intensity and spatial distribution of HFRS. Results: The areas under the receiver operating characteristic curve of training samples and test samples were 0.840 and 0.816. From 2015 to 2019, HRFS case site verification showed that more than 82% of the cases occurred in high-risk areas.

Discussion: This research method could accurately predict HFRS hot spot areas and provided an evaluation model for Hunan Province. Therefore, this method could accurately detect HFRS epidemic high-risk areas, and effectively guide epidemic monitoring and surveyance.

With photoplethysmograph (PPG) sensors showing increasing potential in wearable health monitoring, the challenging problem of motion artifact (MA) removal during intensive exercise has become a popular research topic. In this study, a novel method that combines heart rate frequency (HRF) estimation and notch filtering is proposed. The proposed method applies a cascaded adaptive noise cancellation (ANC) based on the least mean squares (LMS)-Newton algorithm for preliminary motion artifacts reduction, and further adopts special heart rate frequency tracking and correction schemes for accurate HRF estimation. Finally, notch filters are employed to restore the PPG signal with estimated HRF based on its quasi-periodicity. On an open source data set that features intensive running exercise, the proposed method achieves a competitive mean average absolute error (AAE) result of 0.92 bpm for HR estimation. The practical experiments are carried out with the PPG evaluation platform developed by ourselves. Under three different intensive motion patterns, a 0.89 bpm average AAE result is achieved with the average correlation coefficient between recovered PPG signal and reference PPG signal reaching 0.86. The experimental results demonstrate the effectiveness of the proposed method for accurate HR estimation and robust MA removal in PPG during intensive exercise.

Purpose: To investigate a possible correlation between established imaging biomarkers for age-related macular degeneration and local complement system activation, measured in aqueous humor (AH) of patients with early stages of age-related macular degeneration (AMD) and controls.

Methods: This analysis included prospectively acquired AH samples of 106 eyes (35 with early/intermediate AMD, 71 controls). The levels of complement protein 3 (C3), 4 (C4), 5 (C5); activation products of complement factor 3a (C3a) and Ba, C3b/iC3b; complement factors B, D, H, I (CFB, CFD, CFH, CFI); and total protein concentration were analyzed. Quantitative levels of complement factors were correlated to the presence of reticular pseudodrusen (RPD), the presence of hyperreflective foci (HRF), and total drusen volume (DV) graded on imaging by spectral-domain optical coherence tomography and using Spearman's rank correlation test.

Results: DV correlated with C3b/iC3b (r = 0.285; P = 0.034), C3a (r = 0.200; P = 0.047), Ba (r = 0.262; P = 0.009), and C5 (r = 430; P = 0.005), and showed a tendency towards correlation with C3a (r = 0.198; P = 0.057). HRF correlated significantly with C5 (r = 0.388; P = 0.011) and RPD showed a tendency towards correlation with CFB (r = 0.196; P = 0.050).

Conclusion: In patients with early AMD, HRF and drusen parameters but not RPD show low to fair levels of correlation with local complement activation in patients' AH. Better understanding of complement activation could provide some insights into the pathogenesis of AMD. Imaging biomarkers could be useful to identify suitable patients for future clinical trials with complement-modulating therapies.

Keywords: Age-related macular degeneration; Aqueous humor; Complement; Imaging biomarkers.

Purpose: To investigate the hyperreflective foci (HRF) as an inflammatory biomarker using optical coherence tomography angiography (OCTA) in neovascular age-related macular degeneration (AMD) patients after antivascular endothelial growth factor (anti-VEGF) treatment and its association with the retinal microcapillary density.

Methods: Twenty-five eyes from 25 patients with neovascular AMD were included in the study. All eyes were imaged with OCTA at baseline (M0) and after 3 consecutive injections (M3; injection performed each month) of anti-VEGF. The number of HRF in the superficial capillary plexus (SCP), deep capillary plexus (DCP), and outer retina was counted. The vascular density of the fovea, parafovea, and the whole macula, as well as the area of the foveal avascular zone (FAZ), was measured.

Results: The mean interval between baseline and follow-up with OCTA was 93.08 ± 5.00 (range, 85-101) days. Compared with the baseline, the number of HRF significantly decreased in DCP (7.52 ± 3.06 vs. 3.76 ± 1.48, P < 0.01) and outer retina (12.04 ± 4.91 vs. 5.88 ± 3.32, P < 0.01) after treatment. There was no significant difference for HRF number in the SCP, the vascular density (containing foveal, parafoveal, and whole macular), and FAZ area before and after treatments.

Conclusion: The number of HRF in DCP and outer retina might serve as an inflammatory biomarker in patients with neovascular AMD. The reduced HRF possibly represents the alleviation of inflammation after anti-VEGF treatment in patients with AMD.

To our knowledge, the Alberta Moving Beyond Breast Cancer (AMBER) Study is the first and only prospective cohort study of breast cancer survivors that includes objectively-measured physical activity (PA), sedentary behavior, health-related fitness (HRF), and biologic mechanisms focused on understanding breast cancer outcomes. The purpose of the present study was to report on the feasibility of recruitment, baseline measurement completion, and the representativeness of the first 500 participants.

AMBER is enrolling newly diagnosed stage I (≥T1c) to IIIc breast cancer survivors in Alberta, Canada. Baseline assessments are completed soon after diagnosis and include cardiorespiratory fitness, musculoskeletal fitness, body composition, objective and self-reported PA and sedentary behavior, lymphedema, and blood collection.

Between July 2012 and November 2014, AMBER recruited its first 500 participants from a pool of 1,447 (35 %) eligible breast cancer survivors. Baseline HRF assessments were completed on ≥85 % of participants with the exception of upper body strength. Collection of ≥4 days/week of monitoring for the Actigraph GT3X® and ActivPAL® were obtained from 90 % of participants. Completion rates were also high for blood (99 %), lymphedema (98 %), and questionnaires (95 %) including patient-reported outcomes and correlates of exercise. The first 500 participants in AMBER are an average age of 56 years, 60 % are overweight or obese, and 58 % have disease stage II or III.

Despite the modest recruitment rate and younger age, AMBER has demonstrated that many newly diagnosed breast cancer survivors are willing and able to complete a wide array of sophisticated and physically demanding HRF and PA assessments soon after diagnosis. AMBER is a unique breast cancer survivor cohort that may inform future randomized controlled trials on lifestyle and breast cancer outcomes as well as PA behavior change in breast cancer survivors. Moreover, AMBER may also inform guidelines on PA, sedentary behavior, and HRF for improving breast cancer outcomes and survivorship.

Functional near-infrared spectroscopy (fNIRS) provides an alternative to functional magnetic resonance imaging (fMRI) for assessing changes in cortical hemodynamics. To establish the utility of fNIRS for measuring differential recruitment of the motor network during the production of timing-based actions, we measured cortical hemodynamic responses in 10 healthy adults while they performed two versions of a finger-tapping task. The task, used in an earlier fMRI study (Jantzen et al., 2004), was designed to track the neural basis of different timing behaviors. Participants paced their tapping to a metronomic tone, then continued tapping at the established pace without the tone. Initial tapping was either synchronous or syncopated relative to the tone. This produced a 2 × 2 design: synchronous or syncopated tapping and pacing the tapping with or continuing without a tone. Accuracy of the timing of tapping was tracked while cortical hemodynamics were monitored using fNIRS. Hemodynamic responses were computed by canonical statistical analysis across trials in each of the four conditions. Task-induced brain activation resulted in significant increases in oxygenated hemoglobin concentration (oxy-Hb) in a broad region in and around the motor cortex. Overall, syncopated tapping was harder behaviorally and produced more cortical activation than synchronous tapping. Thus, we observed significant changes in oxy-Hb in direct relation to the complexity of the task.

Keywords: AR-IRLS; Canonical statistical analysis; Continuation paradigm; Finger tapping task; HRF; Simple motor timing task; Temporal motor task; fNIRS.

Objectives: Frailty can be used as a predictor of adverse outcomes in people with COVID-19. The aim of the study was to analyze the prognostic value of two different frailty scores in patients hospitalized for COVID-19.

Material and methods: This retrospective cohort study included adult (≥ 18 years) inpatients with COVID-19 and took place from 3 March to 2 May 2020. Patients were categorized by Clinical Frailty Score (CFS) and Hospital Frailty Risk Score (HFRS). The primary outcome was in-hospital mortality, and secondary outcomes were tocilizumab treatment, length of hospital stay, admission in intensive care unit (ICU), and need for invasive mechanical ventilation. Results were analyzed by multivariable logistic regression and expressed as odds ratios (ORs), adjusting for age, sex, kidney function, and comorbidity.

Results: Of the 290 included patients, 54 were frail according to the CFS (≥5 points; prevalence 18.6%, 95% confidence interval [CI]: 14.4-23.7) versus 65 by HFRS (≥5 points; prevalence: 22.4%, 95% CI 17.8-27.7). Prevalence of frailty increased with age according to both measures: 50-64 years, CFS 1.9% versus HFRS 12.3%; 65-79 years, CFS 31.5% versus HFRS 40.0%; and ≥ 80 years, CFS 66.7% versus HFRS 40.0% (p<0.001). CFS-defined frailty was independently associated with risk of death (OR 3.67, 95% CI 1.49-9.04) and less treatment with tocilizumab (OR 0.28, 95% CI 0.08-0.93). HRFS-defined frailty was independently associated with length of hospital stay over 10 days (OR 2.89, 95% CI 1.53-5.44), ICU admission (OR 4.18, 95% CI 1.84-9.52) and invasive mechanical ventilation (OR 5.93, 95% CI 2.33-15.10).

Conclusion: In the spring 2020 wave of the COVID-19 pandemic in Spain, CFS-defined frailty was an independent predictor for death, while frailty as measured by the HFRS was associated with length of hospital stay over 10 days, ICU admission, and use of invasive mechanical ventilation.

Keywords: COVID-19; Hospital Frailty Risk Score; Intensive Care Unit; Intubation; Length of stay; Spain; clinical frailty score; death; frailty; mortality.

UNASSIGNED

Parenchymal changes after stereotactic body radiation therapy (SBRT) make differential diagnosis between treatment outcomes and disease recurrence often difficult. The purpose of our study was to identify the radiographic features detectable at computed tomography (CT) scan [high-risk features (HRFs)] that allow enough specificity and sensitivity for early detection of recurrence.

UNASSIGNED

We retrospectively evaluated patients who underwent SBRT for inoperable early stage non-small cell lung cancer (NSCLC). The median delivered dose performed was 50 Gy in 5 fractions prescribed to 80% isodose. All patients underwent chest CT scan before SBRT and at 3, 6, 12, 18, 24 months after, and then annually. Each CT scan was evaluated and benign and HRFs were recorded. 18F-fluorodeoxyglucose-CT was not used routinely.

UNASSIGNED

Forty-five patients were included (34 males, 11 females; median age: 77 years; stage IA: 77.8%, stage IB: 22.2%; median follow-up: 21.7 months). Two year and actuarial local control was 77%. HRFs were identified in 20 patients. The most significant predictor of relapse was an enlarging opacity at 12 months (P<0.001) with 84.6% sensitivity and 71.8% specificity. The presence of ≥2 HRFs demonstrated a high sensibility (92.3%) and specificity (71.9%) (P<0.0001).

UNASSIGNED

Detection of HRFs is predictive of relapse with a sensibility that increases with the number of HRFs observed. This observation may allow to better define the diagnostic follow algorithm up suggesting to performing further exams only in patients with >2 HRFs.

Wastewater reuse in arid regions is important for the production of a water resource to be utilised for non-potable purposes and to prevent the environmental transmission of disease-causing agents. This study was conducted to evaluate the effect of water quality on the comparative disinfection efficiency of viruses, bacteria and spores by UV irradiation. Furthermore, the microbial quality of effluent produced by coagulation, high rate filtration (HRF) and either UV irradiation or chlorination was determined. Using low pressure collimated beam, a UV dose of 80 mWs/cm2 was needed to achieve a 3-log10 inactivation of either rotavirus SA-11 or coliphage MS2, whereas over 5-log10 inactivation of E. coli was reached with a dose of only 20 mWs/cm2. B. subtilis inactivation was found to be linear up to a dose of 40 mWs/cm2 and then a tailing up to a UV dose of 120 mWs/cm2 was observed. It is worth noting that effluent turbidity of < 5 NTU did not influence the inactivation efficiency of UV irradiation. Operation of a pilot plant to treat secondary effluent by coagulation, HRF and UV disinfection at a UV dose of 80 mWs/cm2 resulted in the production of high quality effluent in compliance with the Israel standards for unrestricted irrigation (< 10 CFU/100 mL faecal coliform and turbidity of < 5 NTU). Sulphite reducing clostridia (SRC) were found to be more resistant than coliphages and F coliform for UV irradiation. The results of this study indicated that UV disinfection is suitable for the production of effluents for unrestricted irrigation of food crops.

The prevalence of food allergies has been increasing at an alarming rate over the last few decades. Despite the dramatic increase in disease prevalence, the development of effective therapies has not kept pace. In this issue of the JCI, Ando et al. provide a causal link between histamine-releasing factor (HRF) interactions with IgE and food allergy in a murine model. Successful oral immunotherapy of both egg-allergic human patients and food-allergic mice was associated with sustained suppression of HRF-reactive IgE levels. These results support a role for HRF-IgE interactions in the amplification of intestinal inflammation and suggest HRF as a therapeutic target in food allergy.

Nonparametric hemodynamic response function (HRF) estimation in functional near-infrared spectroscopy (fNIRS) data plays an important role when investigating the temporal dynamics of a brain region response during activations. Assuming the drift arising from both physical and physiological effects in fNIRS data is Lipschitz continuous; a novel algorithm for joint HRF and drift estimation is derived in this paper. The proposed algorithm estimates the HRF by applying a first-order differencing to the fNIRS time series samples in order to remove the drift effect. An estimate of the drift is then obtained using a wavelet thresholding technique applied to the residuals generated by removing the estimated induced activation response from the fNIRS time-series. It is shown that the proposed HRF estimator is √N consistent whereas the estimator of the drift is asymptotically optimal. The de-drifted fNIRS oxygenated (HbO) and deoxygenated (HbR) hemoglobin responses are then obtained by removing the corresponding estimated drifts from the fNIRS time-series. Its performance is assessed using both simulated and real fNIRS data sets. The application results reveal that the proposed joint HRF and drift estimation method is efficient both computationally and in terms of accuracy. In comparison to traditional model based methods used for HRF estimation, the proposed novel method avoids the selection of a model to remove the drift component. As a result, the proposed method finds an optimal estimate of the fNIRS drift and offers a model-free approach to de-drift the HbO/HbR responses.

In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response function (HRF) and its associated statistics (e.g., the magnitude and duration of the activation). Most methods to date are developed in the time domain and they have utilized almost exclusively the temporal information of fMRI data without accounting for the spatial information. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) in the frequency domain by integrating the spatial and temporal information to adaptively and accurately estimate HRFs pertaining to each stimulus sequence across all voxels in a three-dimensional (3D) volume. We use two sets of simulation studies and a real data set to examine the finite sample performance of MASM in estimating HRFs. Our real and simulated data analyses confirm that MASM outperforms several other state-of-art methods, such as the smooth finite impulse response (sFIR) model.

Functional magnetic resonance imaging (fMRI), being an indirect measure of brain activity, is mathematically defined as a convolution of the unmeasured latent neural signal and the hemodynamic response function (HRF). The HRF is known to vary across the brain and across individuals, and it is modulated by neural as well as non-neural factors. Three parameters characterize the shape of the HRF, which is obtained by performing deconvolution on resting-state fMRI data: response height, time-to-peak and full-width at half-max. The data provided here, obtained from 47 healthy adults, contains these three HRF parameters at every voxel in the brain, as well as HRF parameters from the default-mode network (DMN). In addition, we have provided functional connectivity (FC) data from the same DMN regions, obtained for two cases: data with deconvolution (HRF variability minimized) and data with no deconvolution (HRF variability corrupted). This would enable researchers to compare regional changes in HRF with corresponding FC differences, to assess the impact of HRF variability on FC. Importantly, the data was obtained in a 7T MRI scanner. While most fMRI studies are conducted at lower field strengths, like 3T, ours is the first study to report HRF data obtained at 7T. FMRI data at ultra-high fields contains larger contributions from small vessels, consequently HRF variability is lower for small vessels at higher field strengths. This implies that findings made from this data would be more conservative than from data acquired at lower fields, such as 3T. Results obtained with this data and further interpretations are available in our recent research study (Rangaprakash et al., in press) [1]. This is a valuable dataset for studying HRF variability in conjunction with FC, and for developing the HRF profile in healthy individuals, which would have direct implications for fMRI data analysis, especially resting-state connectivity modeling. This is the first public HRF data at 7T.

Public health guidelines for physical activity (PA) behaviors are being updated with 2018 as a proposed release date. Currently, ≥60 minutes of daily PA are recommended for youth. Thus, the purpose of this study was to investigate the association between reported days of aerobic PA and health-related fitness (HRF). Participants included 4448 students in grades 6-8. Self-reported days of ≥60 minutes of aerobic PA was obtained. HRF was assessed with FitnessGram. Discriminant analysis indicated that weekly days of aerobic PA related to HRF. Adolescents who participated in ≥5 days of weekly aerobic PA generally had better fitness results than those with ≤4 days. Chi-square analyses indicated the highest percentages of adolescents in the FitnessGram Healthy Fitness Zone™ (HFZ) for each test item were those with ≥5 days of aerobic PA. These findings provided initial support that the impact of aerobic PA on HRF plateaus at 5 days per week. Thus, adolescents may be able to improve HRF even if they do not meet the currently recommended guidelines for daily PA.

Acute noninvasive ventilation (NIV) is a well-established therapy for acute respiratory failure but the dose-response characteristics of this therapy have not been defined. The aim of this study was to define this dose-response relationship. This study was a retrospective review of patients receiving NIV for acute respiratory failure in a tertiary hospital respiratory high-dependency unit between July 2012 and June 2017. Mask-on time (rather than the period that NIV was in use) as the "dose" was compared with hospital survival as the "response". 654 patients were included, 594 (91%) with hypercapnic respiratory failure (HCRF). NIV was used for a median (interquartile range (IQR)) duration of 2.74 (1.51-4.73) days and median (IQR) mask-on time was 34 (18-60) h (56.1% (41.2-69.5%) of treatment time). There was evidence of a dose-response relationship in the HCRF group up to a ceiling of 24 h mask-on time, but not in the hypoxaemic respiratory failure (HRF) group. There was a difference in survival with as little as 2 h mask-on time (92% compared with 73%; p<0.001). Patients requiring NIV for 80-100% of therapy time had lower survival. We conclude that there is evidence of a dose-response relationship between cumulative NIV usage (mask-on time) and survival from as little as 2 h to a ceiling of ∼24 h in HCRF, but not in HRF.