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Validity and screening capacity of the FCR-1r for fear of cancer recurrence in long-term colorectal cancer survivors
Get PDFAbstract Purpose
Existing fear of cancer recurrence (FCR) screening measures is being shortened to facilitate clinical use. This study aimed to evaluate the validity and screening capacity of a single-item FCR screening measure (FCR-1r) in long-term colorectal cancer (CRC) survivors with no recurrence and assess whether it performs as well in older as in younger survivors.
Methods
All Danish CRC survivors above 18, diagnosed and treated with curative intent between 2014 and 2018, were located through a national patient registry. A questionnaire including the FCR-1r, which measures FCR on a 0–10 visual analog scale, alongside the validated Fear of Cancer Recurrence Inventory Short Form (FCRI-SF) as a reference standard was distributed between November 2021 and May 2023. Screening capacity and cut-offs were evaluated with a receiver-operating characteristic analysis (ROC) in older (≥ 65 years) compared to younger (< 65 years) CRC survivors. Hypotheses regarding associations with other psychological variables were tested as indicators of convergent and divergent validity.
Results
Of the CRC survivors, 2,128/4,483 (47.5%) responded; 1,654 (36.9%) questionnaires were eligible for analyses (median age 76 (range 38–98), 47% female). Of the responders, 85.2% were aged ≥ 65. Ninety-two participants (5.6%) reported FCRI-SF scores ≥ 22 indicating clinically significant FCR. A FCR-1r cut-off ≥ 5/10 had 93.5% sensitivity and 80.4% specificity for detecting clinically significant FCR (AUC = 0.93, 95% CI 0.91–0.94) in the overall sample. The discrimination ability was significantly better in older (AUC = 0.93, 95% CI 0.91–0.95) compared to younger (0.87, 95% (0.82–0.92), p = 0.04) CRC survivors. The FCR-1r demonstrated concurrent validity against the FCRI-SF ( r = 0.71, p < 0.0001) and convergent validity against the short-versions of the Symptom Checklist-90- R subscales for anxiety ( r = 0.38, p < 0.0001), depression ( r = 0.27, p < 0.0001), and emotional distress ( r = 0.37, p < 0.0001). The FCR-1r correlated weakly with employment status ( r = − 0.09, p < 0.0001) and not with marital status ( r = 0.01, p = 0.66) indicating divergent validity.
Conclusions
The FCR-1r is a valid tool for FCR screening in CRC survivors with excellent ability to discriminate between clinical and non-clinical FCR, particularly in older CRC survivors
Machine learning-based risk of fall estimation on the sit to start of walk sequence of activities in daily living
Get PDFOver the previous years, several methods that combine both the use of biomedical and computational methods have been applied to evaluate risk of fall amongst the elderly using instrumented insoles. The implementation of machine learning techniques in gait analysis have proven itself to be a promising solution. Risk of fall analysis have generally been conducted on the walking phase of different individuals. It can be observed that an important amount of energy is required by individuals preparing to walk out of their beds or bathrooms, with most falls occur during such periods. The aim of this work is to detect two sequences of activities (sit-to-start of walk and walk to sit) and associate different risk fall levels based solely on the analysis of the sit to start of walk sequence. Firstly, based on previously acquired Test Up and Go (TUG) tests on participants with an age range of 67.7 ± 10.07, using an insole comprised of force sensors and accelerometer data, the sit-to-start of walk (STSOW) sequence was identified. Then a recursive clustering approached based on statistical features and Kruskal Wallis test was implemented to accurately define different levels of risk which were classified using machine learning approach. Test results obtained from the classifiers showed the capacity of the proposed risk of fall estimation approach to adequately associate different risk of fall from the previously identified STSOW sequence. The best accuracy was achieved using both the decision tree and ensemble classifiers. The best accuracy for the STSOW sequence of activities identification was achieved using the support vector machine (SVM) model. Furthermore, the decision tree and ensemble classifiers had the best accuracies for the risk of fall estimation Moreover, these results demonstrate the capacity of our approach to permit the analysis of risk related to specific sequences of activities. The implementation of this model will be possible within an instrumented insole device to assist elderly with neurodegenerative diseases and permit clinicians to assess the impact of a new medication and its dose on the temporal evolution of the risk.
Au cours des dernières années, plusieurs méthodes combinant à la fois l'utilisation de méthodes biomédicales et informatiques ont été appliquées pour évaluer le risque de chute chez les personnes âgées à l'aide de semelles instrumentées. La mise en oeuvre de techniques d'apprentissage automatique dans l'analyse de la marche s'est avérée être une solution prometteuse. L'analyse du risque de chute a généralement été menée sur la phase de marche de différents individus. Cependant, on peut observer qu'une quantité importante d'énergie est requise par les personnes qui se préparent à sortir de leur lit ou de leur salle de bain, tandis que la plupart des chutes se produisent au cours de ces périodes. L'objectif de ce travail est de détecter deux séquences d'activités (de la position assise au début de la marche et de la marche à la position assise) et d'y associer différents niveaux de risque de chute en se basant uniquement sur l'analyse de la séquence entre la position assise et le début de la marche. Tout d'abord, sur la base des tests de la chaise chronométrée (TUG) précédemment effectués sur des participants âgés de 67,7 ± 10,07 ans, à l'aide d'une semelle composée de capteurs de force et d'accéléromètre, la séquence de la position assise au début de la marche a été identifiée. Une approche de regroupement récursif basée sur des caractéristiques statistiques et le test de Kruskal Wallis ont ensuite été mise en oeuvre pour définir différents niveaux de risque qui ont été classifiés à l'aide d'une approche d'apprentissage automatique. Les résultats des tests obtenus avec les classificateurs ont montré la capacité de l'approche proposée pour l'estimation du risque de chute à associer de manière adéquate les différents risques de chute entre la position assise et le début de la séquence de marche. La meilleure précision pour l'identification de la séquence d'activités position assise au début de la marche a été obtenue en utilisant le modèle de machine à vecteur de support (SVM). En outre, l'arbre de décision et le classificateur d'ensemble ont obtenu les meilleures précisions pour l'estimation du risque de chute. De plus, ces résultats démontrent la capacité de notre approche à permettre l'analyse du risque lié à des séquences d'activités spécifiques. La mise en oeuvre de ce modèle sera possible au sein d'une semelle instrumentée pour assister les personnes âgées atteintes de maladies neurodégénératives et permettre aux professionnels de la santé d'évaluer l'impact d'un nouveau médicament et de sa dose sur l'évolution temporelle du risque
Impacts et coûts indirects des stresseurs secondaires sur la santé biopsychosociale des sinistrés des inondations de 2019
Get PDFDans diverses régions du Québec, il arrive fréquemment, voire annuellement, que des rivières débordent. Par exemple, en avril 2019, des inondations ont frappé diverses municipalités situées aux abords des lacs Saint-Pierre et des Deux Montagnes ainsi que le long de la rivière Chaudière. Les inondations de 2019 ont touché les régions de l’Abitibi-Témiscamingue, de la Beauce, de l’Outaouais, de Montréal et ses environs, des Laurentides, de la Montérégie, de Lanaudière, de la Mauricie et du Centre-du-Québec. Ce n’est qu’au début juin que les niveaux d’eau se résorbèrent suffisamment pour que le ministère de la Sécurité publique du Québec (MSP) n’ait plus que des inondations mineures sous surveillances dans la région de Montréal (Labbé, 2019).
Lors de ces inondations de 2019, la municipalité de Sainte-Marthe-sur-le-Lac a, pour sa part, été confrontée à une situation particulière. En effet, une rupture de digue a provoqué de graves inondations dans plusieurs secteurs de cette ville. En quelques minutes, 2 500 résidences ont été envahies par des eaux souillées forçant 6 000 personnes à être évacuées de leur domicile (Marceau, 2017).
Afin d’identifier les différents stresseurs que peuvent vivre les adultes exposés à des inondations et leurs impacts sur la santé de ces derniers, des chercheurs provenant de différentes universités du Québec (UQAC, Laval, Sherbrooke, UQAM et l’ÉNAP) et de différentes disciplines (ex. travail social, santé publique, administration publique, finances et actuariat) ont mis en commun leur expertise afin de mieux comprendre ce que peuvent vivre les victimes d’inondations dans le cadre d’une étude mixte
Spatiotemporal variability in otolith elemental fingerprint and the potential to determine deepwater redfish (Sebastes mentella) origins and migrations in the Estuary and Gulf of St. Lawrence, Canada
Get PDFConnectivity processes have major implications in defining the resiliency of fish populations to overexploitation. A preliminary estimate of population exchange rates can be done by identifying the natal origin of adult fish. In this study, otolith elemental fingerprints were used as natural marker of origins and movements of Deepwater redfish (Sebastes mentella) in the Gulf of St. Lawrence (GSL). We specifically targeted the strong 2011–2013 cohorts that supported the rapid recovery of the GSL stock after its collapse in the 1990s. Elemental fingerprints were extracted from the core (proxy for larval origin) and edge (proxy for capture location) of otoliths using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). We observed an East to West gradient in the multi-elemental fingerprint of the otolith edge in the GSL, as well as evidence of temporal variation between 2016 and 2018. Cluster analysis of the core fingerprint revealed the existence of two chemically distinct natal sources of variable contribution between the Saguenay Fjord, the western GSL and the eastern GSL. This new insight on the population structure of redfish in the GSL at an ecologically relevant scale constitutes important knowledge for the assessment and sustainable management of a key recovering resource
Local adaptation shapes functional traits and resource allocation in black spruce
Get PDFClimate change is rapidly altering weather patterns, resulting in shifts in climatic zones. The survival of trees in specific locations depends on their functional traits. Local populations exhibit trait adaptations that ensure their survival and accomplishment of growth and reproduction processes during the growing season. Studying these traits offers valuable insights into species responses to present and future environmental conditions, aiding the implementation of measures to ensure forest resilience and productivity. This study investigates the variability in functional traits among five black spruce ( Picea mariana (Mill.) B.S.P.) provenances originating from a latitudinal gradient along the boreal forest, and planted in a common garden in Quebec, Canada. We examined differences in bud phenology, growth performance, lifetime first reproduction, and the impact of a late-frost event on tree growth and phenological adjustments. The findings revealed that trees from northern sites exhibit earlier budbreak, lower growth increments, and reach reproductive maturity earlier than those from southern sites. Late-frost damage affected growth performance, but no phenological adjustment was observed in the successive year. Local adaptation in the functional traits may lead to maladaptation of black spruce under future climate conditions or serve as a potent evolutionary force promoting rapid adaptation under changing environmental conditions
Enhanced Mechanical Strength and Electrical Conductivity of Al–Ni‐Based Conductor Cast Alloys Containing Mg and Si
Get PDFThe electrical conductivity (EC), mechanical strength, hot tearing susceptibility (HTS), and related microstructure of Al– x Ni–0.55Mg–0.55Si conductor alloys ( x = 1–4 wt%) are investigated. Adding Mg and Si into Al–Ni‐based alloys, numerous β″/β′ precipitate after T5 and T6 treatments, thus significantly improving the EC and mechanical strength. The HTS of the alloys reduces significantly as the Ni content increases, mainly because of an increase in the eutectic Al–Al 3 Ni and a reduction in the grain size. Under T5 condition, the tensile strengths increase gradually with the Ni content and reach a medium strength level, with yield strength (YS) of 158–205 MPa and EC of 47.1–50.7% IACS. After applying T6, all alloys achieve a high strength, with YS of 246–287 MPa and EC of 47.7–51.1% IACS. However, the strength decreases with increasing Ni content. In general, the Al3Ni–0.55Mg–0.55Si alloy presents a better trade‐off among HTS, YS, and EC among the four alloys investigated. Due to its excellent properties (EC of 49.4% IACS and YS of 178 MPa in T5, and EC of 49.7% IACS and YS of 250 MPa in T6), the Al3Ni–0.55Mg–0.55Si alloy is a promising material for the fabrication of Al conductor cast alloys
Variability in lake bacterial growth and primary production under lake ice: Evidence from early winter to spring melt
Get PDFClimate change is causing seasonally ice‐covered lakes of the boreal region to undergo changes in their winter regime by altering patterns of precipitation and temperature, often reflected as reduced snow and ice cover duration. The duration, extent and quality of ice, and snow cover have a pivotal role for production and carbon cycling in lakes in winter, with potentially cascading effects for the following open water period. We investigated under‐ice carbon cycling by assessing bacterial growth (including bacterial production, bacterial respiration, and bacterial growth efficiency) and primary production at five water depths during early winter, midwinter, late winter and melting season in a boreal lake, and report significantly different temporal patterns. Bacterial respiration was dominant in early and midwinter, whereas the late winter and melting season were dominated by bacterial production. Multiple linear regression models indicated that high early winter bacterial respiration was associated with senescing phytoplankton, whereas bacterial production was promoted by the onset of spring processes. Collectively, bacterial growth indices were inherently linked with bacterioplankton community composition and specific biomarker taxa. Primary production under ice increased in late winter when light‐blocking snow cover melted, and primary production measured from the lake ice exceeded that of the water column at the melting season. Ice samples hosted diverse eukaryotic communities including photoautotrophs, suggesting that the habitat potential of the understudied lake ice and the role of ice for ecological processes at ice melt should be further explored
The Thores Lake proglacial system: remnant stability in the rapidly changing Canadian High Arctic
Get PDFWe describe limnological data sets from Thores Lake, a large ice-contact proglacial lake in northern Ellesmere Island, Nunavut (82.65°N), including longitudinal and cross transects (vertical resolution 0.03 m, horizontal resolution 100–200 m). The lake is formed due to damming by Thores Glacier at its northwest margin, has multi-year ice cover and a cold (<1.54 °C) fresh water column with a bottom layer of <0 °C, high-conductivity water in the deepest basin. Thores Lake is ultraoligotrophic, with low nutrient and phytoplankton stocks. Accessory pigment data and metagenomics were used to describe the eukaryotic microbial community. Diversity and taxonomic composition in the water column were homogeneous down to a depth of 40 m, consistent with density profiles. Surface water at the glacier interface was characterized by high turbidity and total phosphorus concentrations, and a distinct phytoplankton community dominated by chlorophytes, whereas the lake water column had higher relative abundances of chrysophytes and photosynthetic dinoflagellates. Thores Lake has a contracted pelagic food web, with the highest trophic level occupied by phytoplankton-feeding rotifers, and no crustacean zooplankton; profiles showed that omega-3 fatty acids (FAs) ranged from <1% (glacier interface) to 3.6% (central lake) of total seston FAs. Given the stability of the Thores Glacier ice dam and the persistence of cold water capped by perennial ice, Thores Lake provides a baseline to assess the impact of climate change on far northern lakes
Editorial Special Section on Liquid Dielectrics
No full textThis Special Section is part of a sequel of IEEE Transactions on Dielectrics and Electrical Insulation (TDEI) dedicated to papers focusing on liquid dielectrics which are normally published every three years. The tradition of having a number of issues on liquid dielectrics was initiated at the end of the last century by the IEEE TDEI Editor-in-Chief Prof. A. van Roggen and kept on by Prof. R. Hackam and Prof. E. Cherney. Starting in 2020, this tradition was maintained and relaunched by the actual IEEE TDEI Editor-in-Chief, Prof. Michael Wubbenhorst. Massimo Pompili (MP) has been involved as a Guest Editor of IEEE TDEI Special Issues on Liquid Dielectrics quite from the beginning (TDEI, vol. 5, 1998), at that time in cooperation with Prof. Ray Bartnikas and Prof. Carlo Mazzetti; this effort went on periodically, and from 2018, MP is sharing this role with Luigi Calcara (LC), a younger colleague at the University of Roma “La Sapienza,” Rome, Italy. The present 2023 Special Section was handled by Massimo Pompili, Luigi Calcara, and Issouf Fofana (IF) from the University of Quebec at Chicoutimi, Saguenay, QC, Canada. Hopefully, MP, LC, and IF will care also about the next Special Issue on Liquid Dielectrics expected for the end of 2026 or the beginning of 2027
Comparing phenocam color indices with phenological observations of black spruce in the boreal forest
Get PDFBud phenology identifies the growing period of trees and determines the pattern of mass and energy exchanges between forest and atmosphere over time and space. Canopy color metrics derived from phenocams have been widely used to investigate tree phenology. However, it remains unclear which color-based index better tracks the seasonal variations of tree phenology in evergreen forest ecosystems. Herein, we compared four color metrics (red chromatic coordinate (RCC), green chromatic coordinate (GCC), vegetation contrast index (VCI) and excess green index (ExG)) derived from phenocam images with bud phenological phases recorded in black spruce [Picea mariana (Mill.) B.S·P] during 2017–2020 at a boreal forest site in Quebec, Canada. Canopy redness (RCC) and greenness (GCC, ExG, and VCI) showed a bimodal and bell-shaped seasonal pattern, respectively. The phases of bud burst and bud set lasted from end-May to end-June and from mid-July to end-September, respectively. The neural network model indicated that GCC had the best predictive ability in capturing the sequential phases of bud phenology. Bud phenological phases predicted by GCC showed the highest correlation with actual bud phenological phases among four indices, with R2 above 0.9 and RMSE lower than 0.5. Overall, color indices performed better when representing bud burst than bud set. Our findings improve the efficiency and confidence of the phenocam greenness index to characterize the growing season of evergreen forests