Tool For Long-term Monitoring Research Articles

Testing effectiveness in nature reserve management using GIS-based tools: a 25 years monitoring of land use change in a Mediterranean coastal wetland

Land-cover change dynamics were investigated in a Mediterranean coastal wetland to evaluate the long-term effectiveness of nature reserve management. A multitemporal analysis of land cover maps was conducted, utilizing visual interpretation of aerial orthophotos from the summer seasons of 1996, 2008, 2015, and 2021. Landscape changes were evaluated by transition matrices and chord diagrams. Maps were classified in accordance with CORINE land cover types at a fourth level of detail. The multitemporal analyses provided a comprehensive overview of landscape changes within the reserve over the past 25 years. The most notable changes were the increase of wetland areas and the reduction of agricultural and artificial areas. Moreover, seminatural vegetation constantly extended over time. These changes reflected the continuous management activities within the nature reserve, encompassing agreements for water supply, restoration projects, and measures to counteract illegality. These operational actions induced fine-grained ecological changes (outcomes at ecosystem level). This study highlighted the importance of remote sensing and landscape analysis, matched with fine-grained management data, as tool for long-term monitoring. Such an approach provides valuable support in evaluating the effectiveness of strategies promoted in nature reserves hosting wet coastal ecosystems of high conservation concern.

Quantification of Hydrogen Isotopes Utilizing Raman Spectroscopy Paired with Chemometric Analysis for Application across Multiple Systems.

Online and real-time analysis of a chemical process is a major analytical challenge that can drastically change the way the chemical industry or chemical research operates. With in situ analyses, a new and powerful understanding of chemistry can be gained; however, building robust tools for long-term monitoring faces many challenges, including compensating for instrument drift, instrument replacement, and sensor or probe replacement. Accounting for these changes by recollecting calibration data and rebuilding quantification models can be costly and time-consuming. Here, methods to overcome these challenges are demonstrated with an application of Raman spectroscopy to monitoring hydrogen isotopes with varied speciation within dynamic gas streams. Specifically, chemical data science tools such as chemometric modeling are leveraged along with several examples of calibration transfer approaches. Furthermore, the optimization of instrument and sensor cell parameters for targeted gas-phase analyses is discussed. While the particular focus on hydrogen is highly beneficial within the nuclear energy sector, mechanisms built and demonstrated here are widely applicable to optical spectroscopy monitoring in numerous other chemical systems that can be leveraged in other processes.

Monitoring of Fish Migration in Fishways and Rivers—The Infrared Fish Counter “Riverwatcher” as a Suitable Tool for Long-Term Monitoring

With the globally increasing awareness regarding the interconnectivity between freshwater ecosystems, projects for re-establishing connectivity with fishways as well as stock management are increasing. To ensure the quality and impact of such projects and for extending the scientific state of knowledge on this topic, a detailed monitoring of these measures is mandatory. Automatic, passive, and contactless counting devices can play a major role in these long-term monitoring projects, both for animal protection (non-invasive methods) and technical issues (comparatively low-cost systems in terms of time). Infrared fish counters can be used in a variety of fisheries applications and have proven particularly valuable in situations when long-term or continuous monitoring in lotic systems is required. Herein, we describe the function and technical capabilities of the VAKI Riverwatcher fish counter, provide information regarding its installation, and highlight some specific, practical applications of this technology. We discuss how the Riverwatcher can be used to validate the functionality of fish passage structures and to provide abundance estimates of migratory fish populations. Finally, we call attention to the challenges associated with operating monitoring equipment in variable river systems and briefly discuss potential sources of error that can influence the monitoring results and approaches to minimize or alleviate these errors.

A New Urban Built-Up Index and Its Application in National Central Cities of China

Accurately mapping urban built-up areas is critical for monitoring urbanization and development. Previous studies have shown that Night light (NTL) data is effective in characterizing the extent of human activity. But its inherently low spatial resolution and saturation effect limit its application in the construction of urban built-up extraction. In this study, we developed a new index called VNRT (Vegetation, Nighttime Light, Road, and Temperature) to address these challenges and improve the accuracy of built-up area extraction. The VNRT index is the first to fuse the Normalized Difference Vegetation Index (NDVI), NPP-VIIRS Nighttime NTL data, road density data, and land surface temperature (LST) through factor multiplication. To verify the good performance of VNRT in extracting built-up areas, the built-up area ranges of four national central cities in China (Chengdu, Wuhan, Xi’an, and Zhengzhou) in 2019 are extracted by the local optimum thresholding method and compared with the actual validation points. The results show that the spatial distribution of VNRT is highly consistent with the actual built-up area. THE VNRT increases the variability between urban built-up areas and non-built-up areas, and can effectively distinguish some types of land cover that are easily ignored in previous urban indices, such as urban parks and water bodies. The VNRT index had the highest Accuracy (0.97), F1-score (0.94), Kappa coefficient (0.80), and overall accuracy (92%) compared to the two proposed urban indices. Therefore, the VNRT index could improve the identification of urban built-up areas and be an effective tool for long-term monitoring of regional-scale urbanization.

Dual-Planar Monopole Antenna-Based Remote Sensing System for Microwave Medical Applications.

Neurodegenerative diseases (NDs) can be life threatening and have chronic impacts on patients and society. Timely diagnosis and treatment are imperative to prevent deterioration. Conventional imaging modalities, such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET), are expensive and not readily accessible to patients. Microwave sensing and imaging (MSI) systems are promising tools for monitoring pathological changes, namely the lateral ventricle enlargement associated with ND, in a non-invasive and convenient way. This paper presents a dual-planar monopole antenna-based remote sensing system for ND monitoring. First, planar monopole antennas were designed using the simulation software CST Studio Suite. The antenna analysis was carried out regarding the reflection coefficient, gain, radiation pattern, time domain characterization, E-field distribution, and Specific Absorption Rate (SAR). The designed antennas were then integrated with a controlling circuit as a remote sensing system. The system was experimentally validated on brain phantoms using a vector network analyzer and a laptop. The collected reflection coefficient data were processed using a radar-based imaging algorithm to reconstruct images indicating brain abnormality in ND. The results suggest that the system could serve as a low-cost and efficient tool for long-term monitoring of ND, particularly in clinics and care home scenarios.

Target-activated multicolor fluorescent dyes for 3D imaging of plasma membranes and tracking of apoptosis.

Real-time tracking of dynamic changes in the three-dimensional morphology of the cell plasma membrane is of great importance for a deeper understanding of physiological processes related to the cell plasma membrane. However, there is a lack of imaging dyes that can specifically be used for a long term labelling of plasma membranes, especially for plant cells. Here, we have used molecular engineering strategies to develop a series of target-activated multicolour fluorescent dyes that can be used for long-term and three-dimensional imaging of plant cell plasma membranes. By combining different electron acceptors and donors, four molecular backbones with different emission colours from green to NIR have been obtained. In the designed styrene-based dyes, referred to as the SD dyes, several functional groups were introduced into the backbones to achieve the properties of target-activated fluorescence, rapid and wash-free staining, high plasma membrane targeting ability and long-term imaging function. Using onion epidermal cells as a platform, these dye molecules can provide high-quality imaging of the plasma membrane for up to 6 hours, providing a powerful tool for long-term monitoring of plasma membrane-related biological events. Calcium-mediated apoptosis of plant cells has been tracked for the first time by monitoring the morphological changes of the plasma membrane in real time using SD dyes. These dyes also exhibit excellent 3D imaging performance of the plasma membrane and were further used to track in real time the 3D morphological changes of the plasma membrane during plasmolysis of plant cells, providing a powerful imaging tool for three-dimensional (3D) biology. This work provides a set of multi-colour dye tools for long-term and three-dimensional imaging of plant cell plasma membranes, and also provides molecular design principles for guiding the transmembrane transport of small molecules.

Marine macrophyte strandings in the Yucatán peninsula: Citizen science as a potential tool for long-term monitoring

Massive strandings of seaweeds on the eastern coasts of the Yucatán peninsula, Mexico have become a major socioecological problem, creating the need for establishing a baseline monitoring program in the region. A citizen science initiative, Big Seaweed Search Mexico (BSS-Mx), was developed to monitor temporal changes in the biomass stranded (abundance and species composition) in the Yucatán peninsula. The initiative was tested in two regions; Puerto Morelos, Quintana Roo, where massive strandings of Sargassum have caused severe socioecological impacts, and Sisal, Yucatán, where there is scarce information about the species composition of the strandings and their seasonal dynamics. Even the different socioeconomic and ecological context of these regions, the public participation in close collaboration with research scientists allowed detection of the temporal changes in the abundance and species composition of the strandings in both locations over a period of ten months. A total of 45 taxa were identified in Puerto Morelos, from which pelagic Sargassum and a seagrass were dominant for most time of the year; whereas 58 taxa were identified in Sisal, observing a higher diversity dominated by red seaweeds, with dominant taxa changing seasonally. The results represent baseline information that should be considered to develop management strategies and marine conservation actions according to each region. The findings highlight the role of citizen science as a potential tool to conduct large-scale and long-term monitoring and stimulate public participation to address environmental issues.

Detection and prediction of freezing of gait with wearable sensors in Parkinson's disease.

Freezing of gait (FoG) is one of the most distressing symptoms of Parkinson's Disease (PD), commonly occurring in patients at middle and late stages of the disease. Automatic and accurate FoG detection and prediction have emerged as a promising tool for long-term monitoring of PD and implementation of gait assistance systems. This paper reviews the recent development of FoG detection and prediction using wearable sensors, with attention on identifying knowledge gaps that need to be filled in future research. This review searched the PubMed and Web of Science databases to collect studies that detect or predict FoG with wearable sensors. After screening, 89 of 270 articles were included. The data description, extracted features, detection/prediction methods, and classification performance were extracted from the articles. As the number of papers of this area is increasing, the performance has been steadily improved. However, small datasets and inconsistent evaluation processes still hinder the application of FoG detection and prediction with wearable sensors in clinical practice.

Otolith microchemistry of freshwater indigenous minor carp (Bangana dero) as a biomonitoring tool to trace heavy metals in River Sutlej, Ropar Wetland (Ramsar site), Punjab, India.

The elemental composition of the fish otolith may represent a permanent record of the environmental condition the fish inhabited. Fish otolith grows incrementally from the core to a marginal region that acts as a repository of trace metal signatures. The present study explores the potential application of otolith microchemistry of the benthopelagic indigenous minor carp Bangana dero sampled from the Ropar wetland on River Sutlej, Punjab. The concentration of sixteen metals was evaluated in the otolith (n = 42) and water (n = 48) for the post-monsoon and pre-monsoon season from 2020 to 2022 using inductively coupled plasma mass spectrometry (ICP-MS) followed by element detection in the core and marginal region of whole otolith, using energy-dispersive mass spectroscopy (EDS). All the heavy metals exhibited an increase in metal concentrations in fish otolith than water during the post-monsoon season. By indices approach, the otolith was found to have a high bioaccumulation factor for Se in the post-monsoon and Hg in the pre-monsoon. Certain trace metals like As and Hg exhibited fluctuations in their core and marginal region. Thus, trace metal patterns in the otolith could act as a potential tool for monitoring the seasonal changes of metals in water bodies. The EFHg, EFSe and EFAs in the fish otolith predicted its anthropogenic source, while the remaining studied elements showed ambient water origin. Thus, using the otoliths of Bangana dero as a long-term monitoring tool in the future may be helpful for environmental assessments and the reconstruction of historical exposure for safeguarding of water bodies.

Emerging Role of Atopic Dermatitis Control Tool in Long-Term Monitoring of Patients With Moderate-to-Severe Atopic Dermatitis Treated With Dupilumab.

Emerging Role of Atopic Dermatitis Control Tool in Long-Term Monitoring of Patients With Moderate-to-Severe Atopic Dermatitis Treated With Dupilumab.

Numeric Prediction of the Detail Visibility in Industrial X-Ray Computed Tomography by Human Observers

Industrial Computed Tomography (iCT) is applied in industry for flaw detection, flaw evaluation and dimensional measurement. This requires the correct experimental system settings for sufficient visibility and detectability of details and structure elements. This is an essential tool for long term monitoring of the detail sensitivity of CT scanners. The visibility of indications by human observers on a monitor in cross sectional 2D CT-images can be estimated from the square root of the visible flaw area, the Contrast to Noise Ratio (CNR) and the Modulation Transfer Function (MTF). The ASTM guide E 1441 describes a more detailed procedure for the determination of the minimum contrast for the visibility of flaws based on three essential functions for the prediction of the visibility of small circular indications in iCT slice images. This is the Contrast Discrimination Function (CDF), the Modulation Transfer Function (MTF) as described in the latest revision of ASTM E 1695, and the Contrast Detail Diagram (CDD). All these functions analyse the contrast as function of the spatial frequency in digital 2D slice images. The functions do not describe, how to calculate the visibility limit for human observers. The concept for the automated calculation of the visibility limit of circular indications in reconstructed slice images is discussed in this paper. It is finally determined from the intersection point of the MTF with the Contrast Detail Diagram, which is the combination of CDF and MTF, and a physiological factor c. The new measurement procedures for the prediction of the detail visibility by MTF and CDD was tested with test phantoms and be verified by modelling and measurements. A Round Robin test was conducted with more than 10 parties to verify the visibility formula and the procedure for determination of the visibility limit from the combination of these functions. A form factor is considered to compare cylinder holes with pore indications. Conclusions will be reported and recommendations will be given for the determination of the correct physiological factor c.

Convolutional Neural Network for Estimating Spatiotemporal and Kinematic Gait Parameters using a Single Inertial Sensor.

Lower limb disability severely impacts gait, thus requiring clinical interventions. Inertial sensor systems offer the potential for objective monitoring and assessment of gait in and out of the clinic. However, it is imperative such systems are capable of measuring important gait parameters while being minimally obtrusive (requiring few sensors). This work used convolutional neural networks to estimate a set of six spatiotemporal and kinematic gait parameters based on raw inertial sensor data. This differs from previous work which either was limited to spatiotemporal parameters or required conventional strap-down integration techniques to estimate kinematic parameters. Additionally, we investigated a data segmentation method which does not rely on gait event detection, further supporting its applicability in real-world settings.Preliminary results demonstrate our model achieved high accuracy on a mix of spatiotemporal and kinematic gait parameters, either meeting or exceeding benchmarks based on literature. We achieved 0.04 ± 0.03 mean absolute error for stance-time symmetry ratio and an absolute error of 4.78 ± 4.78, 4.50 ± 4.33, and 6.47 ± 7.37cm for right and left step length and stride length, respectively. Lastly, errors for knee and hip ranges of motion were 2.31 ± 4.20 and 1.73 ± 1.93°, respectively. The results suggest that machine learning can be a useful tool for long-term monitoring of gait using a single inertial sensor to estimate measures of gait quality.

Geochemical modeling of CO2 sequestration in ultramafic mine wastes from Australia, Canada, and South Africa: Implications for carbon accounting and monitoring

Passive carbonation in ultramafic mine wastes results from the spontaneous reaction of gangue minerals with carbon dioxide (CO2) to form stable carbonate minerals that store CO2. Mines can benefit from unintentional CO2 sequestration to offset greenhouse gas (GHG) emissions. Quantitative X-ray diffraction (QXRD) analysis of numerous samples of mine wastes has typically been used to quantify passive carbonation rates. This analysis yields valuable information about carbon sinks; however, extensive mineralogical assessments are technically demanding and cost-prohibitive for routine carbon accounting. Alternatively, we explored using inverse geochemical modeling to estimate passive carbonation rates and monitor CO2 sequestration in active mines. Water chemistry data, tailings mineralogy, and operational information routinely collected by mines were used as inputs for models. The predictive capabilities of the models were tested for Mount Keith nickel mine (Australia), Diavik diamond mine (Canada) – for which rates were previously determined using QXRD. A new site — Venetia diamond mine (South Africa) — was used to illustrate the potential of geochemical modeling for carbon accounting and as a long-term monitoring tool for CO2 sequestration. Mount Keith models predicted passive carbonation rates (3900 g CO2/m2/yr) consistent with previous QXRD assessments (2400 g CO2/m2/yr; 172 samples) using only two water samples. CO2 removal rates for Diavik were found to be impacted by seasonality and to range between ∼375 and 510 g CO2/m2/yr, showing similarities with previous QXRD rates estimates (313–350 g CO2/m2/yr). With the long-term water chemistry records (2009–2018) available for Venetia mine, we predicted calcite as the main CO2 sink and that ∼14,875 t CO2 were stored in the kimberlite residues impoundments (3.5 km2) over 9 years at a rate of ∼470 g CO2/m2/yr. Moreover, long-term monitoring shows a decline in CO2 removal rates at Venetia, possibly due to changes in kimberlite reactivity and current mine waste disposal practices. Overall, inverse modeling proved that it can be a viable alternative or complement to QXRD techniques for carbon accounting in active mines, substantially reducing the need for mine waste sampling and permitting long-term monitoring. Moreover, the model shows how passive carbonation rates change dynamically with the mine production and waste management practices. Simultaneously, the model provides insights into potential mineral reactions operating in tailings and that regulate carbon sequestration mechanisms. For that reason, this accounting technique has an enormous potential to assist in decision-making for implementing enhanced CO2 sequestration strategies (e.g., enhanced rock weathering) and to support carbon sequestration monitoring, validation, and reporting in active mines.

In-Situ Fish Heart-Rate Estimation and Feeding Event Detection Using an Implantable Biologger

Monitoring of physiology and behavior of marine animals living undisturbed in their natural habitats can provide valuable information about their well-being and response to environmental stressors. We focus on detecting the feeding behavior in predatory fish using implantable biologgers that record and analyze electrocardiogram (ECG) signals. We propose a novel processing pipeline for resource-constrained embedded systems that can infer higher-level information, such as heart-rate and feeding events, from the ECG signals in situ. Our main contributions are in proposing efficient event detection algorithms that can reliably detect fish feeding events from noisy heart-rate data based on the unique statistical properties of feeding-induced changes in the heart-rate. We evaluate our approaches using an in-house biologger that we surgically implant in twelve coral trout fish and use to collect data during an experiment for a period of ten weeks and show that our signal processing pipeline performs well with noisy ECG signals overall. Specifically, our heart-rate estimation algorithm achieves errors of less than one beat per minute even in scenarios where popular algorithms used by domain specialists perform poorly. Furthermore, our feeding detection algorithms offer improved accuracy compared with the state-of-the-art algorithms while requiring significantly reduced computational and energy resources. We implement the proposed heart-rate estimation and feeding detection algorithms on the biologger and evaluate the associated system overhead. The results show that our proposed heart-rate estimation and feeding detection algorithms can run in-situ on the biologger as they demand rather small computational and energy resources that can conveniently be provisioned. This work is an important first step towards developing effective tools for long-term monitoring of high-level parameters pertaining to the health and behavior of marine animals in the wild.

P694 Long-term monitoring of post-surgical recurrence in Crohn’s disease using a strategy based on the periodic determination of fecal calprotectin in patients without early postoperative recurrence

Abstract Background Current guidelines recommend to perform an ileocolonoscopy 6-12 months after surgery in patients with Crohn’s disease (CD) and ileo-cecal resection with ileocolic anastomosis to assess the occurrence of endoscopic post-operative recurrence (PORe) and escalate therapy if necessary. However, it is not established whether and/or when endoscopic monitoring is advised in patients who do not present early PORe Objective To evaluate the usefulness of a strategy based on the periodic determination of faecal calprotectin (FC) to decide whether to carry out a new endoscopic control in patients without PORe (iR<2) in the last endoscopic assessment performed Methods Pilot, prospective, multicentre and open study. Inclusion criteria: 1) CD with intestinal resection and ileo-colic anastomosis; 2) last ileocolonoscopy after surgery with a Rutgeerts score i0 or i1; 3) No suspicion of clinical POR. Patients with an ostomy or chronic use of NSAIDs or omeprazole were excluded. Centralized FC determinations were performed every 4 months for 2 years and an ileocolonoscopy at the end of follow-up was performed. In the case of FC>250μg/g in 2 consecutive determinations, ileocolonoscopy was advanced and the patient was withdrawn from the study. The main variable of interest was the rate of advanced PORe (as defined by Rutgeerts score >i2) at the final ileocolonoscopy. Results 55 patients were included, 13% perianal disease, 24% smokers and 27% surgery prior to the index surgery. 47% followed prevention with thiopurines and 14% with anti-TNF. During follow-up, 7 patients had FC>250μg/g in two consecutive determinations; advanced PORe was identified in 5 of these patients, PORe i2 in one and intestinal adenocarcinoma in another one. Among the patients who completed the 2-year follow-up, none had advanced PORe at the final ileocolonoscopy although intermediate PORe (i2) was found in 12. The rate of advanced PORe was 71% in those who finished the study before 2 years and 0% in those who were not advanced to endoscopy. The AUC for FC to detect advanced PORe was 0.98 (p=0.002). The cut-off point of FC>250μg/g obtained a sensitivity of 100% and specificity of 60% to detect advanced PORe. Conclusion The serial determination of FC is a suitable long-term monitoring tool to decide whether to perform ileocolonoscopy in patients without early PORe.

Inter-annual variability patterns of reef cryptobiota in the central Red Sea across a shelf gradient

The combination of molecular tools, standard surveying techniques, and long-term monitoring programs are relevant to understanding environmental and ecological changes in coral reef communities. Here we studied temporal variability in cryptobenthic coral reef communities across the continental shelf in the central Red Sea spanning 6 years (three sampling periods: 2013–2019) and including the 2015 mass bleaching event. We used a combination of molecular tools (barcoding and metabarcoding) to assess communities on Autonomous Reef Monitoring Structures (ARMS) as a standardized sampling approach. Community composition associated with ARMS for both methodologies (barcoding and metabarcoding) was statistically different across reefs (shelf position) and time periods. The partition of beta diversity showed a higher turnover and lower nestedness between pre-bleaching and post-bleaching samples than between the two post-bleaching periods, revealing a community shift from the bleaching event. However, a slight return to the pre-bleaching community composition was observed in 2019 suggesting a recovery trajectory. Given the predictions of decreasing time between bleaching events, it is concerning that cryptobenthic communities may not fully recover and communities with new characteristics will emerge. We observed a high turnover among reefs for all time periods, implying a homogenization of the cryptobiome did not occur across the cross shelf following the 2015 bleaching event. It is possible that dispersal limitations and the distinct environmental and benthic structures present across the shelf maintained the heterogeneity in communities among reefs. This study has to the best of our knowledge presented for the first time a temporal aspect into the analysis of ARMS cryptobenthic coral reef communities and encompasses a bleaching event. We show that these structures can detect cryptic changes associated with reef degradation and provides support for these being used as long-term monitoring tools.

Informing Management of Atlantic Bluefin Tuna Using Telemetry Data

Sustainable management of exploited marine fish and wildlife populations requires knowledge about their productivity. Survival from natural causes of mortality is a key component of population productivity, but is notoriously difficult to estimate. We evaluate the potential for acoustic telemetry as a long-term monitoring tool to estimate rates of natural mortality. We present a Bayesian multistate mark-recapture model for telemetry data collected over a decade from 188 Atlantic bluefin tuna (Thunnus thynnus) and apply it to estimate the rate of natural mortality using only acoustic tag detections for all animals, or using acoustic tag detections for 96 single-tagged tuna plus acoustic tag detections combined with estimated positions from pop-up satellite archival tags for 92 double-tagged animals. We support the model for bluefin tuna with a simulation study to quantify bias in estimates of population dynamics parameters and investigate the effect of auxiliary information from satellite tagging on mortality rate estimates for different acoustic tag detection probability scenarios.We obtained posterior estimates of the instantaneous annual natural mortality (survival) rate across a decade of tagging for Atlantic bluefin tuna of 0.17 yr-1 (0.84 yr-1) both using only acoustic tagging data, and using a combination of acoustic and satellite tagging data. Use of a prior implying a higher rate of fishing mortality yielded an instantaneous annual natural mortality (survival) estimate of 0.10 yr-1 (0.90 yr-1), with combined acoustic and satellite tag data. Results from the simulation study indicate that the use of satellite tags can improve the precision and accuracy of estimates of detection probabilities, area-specific movement probabilities and mortality rates, where the extent of the improvement depends on true underlying acoustic tag detection probabilities. Our work demonstrates that long-term acoustic tagging data sets have strong potential for monitoring of highly migratory marine fish and wildlife populations, providing information on a number of key parameters, including survival and movement rates. However, improved information on tag reporting rates or fishing mortality is needed to better separate natural and fisheries mortality for Atlantic bluefin tuna.

Evaluation of nocturnal vs. morning measures of heart rate indices in young athletes.

PurposeThe purpose of this study was to compare heart rate (HR) and heart rate variability in young endurance athletes during nocturnal sleep and in the morning; and to assess whether changes in these values are associated with changes in submaximal running (SRT) and counter-movement jump (CMJ) performance.MethodsDuring a three-week period of similar training, eleven athletes (16 ± 1 years) determined daily HR and heart rate variability (RMSSD) during sleep utilizing a ballistocardiographic device (Emfit QS), as well as in the morning with a HR monitor (Polar V800). Aerobic fitness and power production were assessed employing SRT and CMJ test.ResultsComparison of the average values for week 1 and week 3 revealed no significant differences with respect to nocturnal RMSSD (6.8%, P = 0.344), morning RMSSD (13.4%, P = 0.151), morning HR (-3.9 bpm, P = 0.063), SRT HR (-0.7 bpm, P = 0.447), SRT blood lactate (4.9%, P = 0.781), CMJ (-4.2%, P = 0.122) or training volume (16%, P = 0.499). There was a strong correlation between morning and nocturnal HRs during week 1 (r = 0.800, P = 0.003) and week 3 (r = 0.815, P = 0.002), as well as between morning and nocturnal RMSSD values (for week 1, r = 0.895, P<0.001 and week 3, r = 0.878, P = 0.001).ConclusionThis study concluded that HR and RMSSD obtained during nocturnal sleep and in the morning did not differ significantly. In addition, weekly changes in training and performance were small indicating that fitness was similar throughout the 3-week period of observation. Consequently, daily measurement of HR indices during nocturnal sleep provide a potential tool for long-term monitoring of young endurance athletes.

A unified model for high resolution mapping of global lake (>1 ha) clarity using Landsat imagery data

Lake clarity, usually measured by Secchi disc depth (SDD), is a reliable proxy of lakes trophic status due to its close link with total suspended matter, chlorophyll-a, and nutrients. Trained with in-situ measured SDD and match-up Landsat images, we established various regression models to estimate SDD for global lakes. We selected a unified model which demonstrated good spatiotemporal transferability, and has potential to map SDD in different years with good quality of Landsat top-of-atmosphere (TOA) images embedded in Google Earth Engine (GEE). The unified model was successfully calibrated (n = 3586 data points, R2 = 0.84, MAPE = 29.8%) against SDD measured in 2235 lakes across the world, and the validation (n = 1779, R2 = 0.76, MAPE = 38.8%) also exhibited stable performance. The unified model was tuned to historical SDD measurements coincident with different Landsat sensors (L5-TM, L7-ETM+, L8-OLI) launched over the past four decades (1984–2020), thus confirming its temporal stability. Global SDD was mapped using GEE with OLI TOA products mainly acquired in 2019 to examine the spatial variation of lake water clarity (lake surface area ≥ 1 ha) all over the world. Worldwide, lake water clarity averaged 3.13 ± 1.71 m in 2019, but exhibited remarkable spatial variability due to catchment hydrological and landscape settings, lake morphology, elevation and anthropogenic impact. Inland waters in Europe (4.18 ± 1.82 m) and North America (3.84 ± 1.77 m) had the highest clarity due to greater water depth combined with less human disturbance in the high latitude regions. Lakes in South America (2.50 ± 2.33 m), Asia (2.44 ± 1.63 m) and Africa (2.36 ± 0.72 m) displayed intermediate clarity. Lakes in Oceania (1.97 ± 1.48 m) exhibited the lowest clarity for all continents except Antarctica. Further, we used the mapped SDD to evaluate water trophic status using the Carlson trophic state index. Our results indicate that, in 2019, about 63.6% of the lake areas and 47.8% of total lake numbers (2,219,627/4,646,056) were oligotrophic for global lakes, while about 23.6% areal percent and 37.1% of lake numbers are eutrophic mostly as a result of their being located in agricultural and urban-dominated drainage basins. This study, for the first time, provides water clarity information for lakes with area ≥ 1 ha all over the world with 30-m resolution and facilitates the understanding of the water clarity relevant to TSM (r = 0.95), Chl-a (r = 0.73), total phosphorus (r = 0.75), total nitrogen (r = 0.60), which could further provide water clarity data and technical support for trophic level evaluations as well. This unified model could serve as a powerful research tool for long-term monitoring of aquatic ecosystems and assessing their resilience to anthropogenic disturbance and climate change-related stressors.

Development of reaction-free and mitochondrion-immobilized fluorescent probe for monitoring pH change

Mitochondrial pH is an indispensable parameter of reflecting mitochondrial function, and its abnormity is closely associated with various diseases, such as cardiovascular diseases, Alzheimer’s disease, and Reye's syndrome. For real-time and long-term monitoring of mitochondrial pH changes, we for the first time developed a free-reaction and mitochondrion-immobilized pH-sensitive fluorescent probe (MTpH). This probe consists of a cationic pyridinium for targeting mitochondrion, a long alkyl chain for fixing on the mitochondrion, and a morpholine-linked naphthalimide as a fluorescence turn-on signaling unit to pH change. By linking a long alkyl chain, probe MTpH could successfully immobilize on the mitochondrion in a reaction-free way, which efficiently avoided the irreversible destroy to the original structure and function of the mitochondrion. Importantly, this probe also showed a sensitive response to pH changes with the pKa of 5.77, allowing for monitoring mitochondrial pH changes in impaired mitochondria undergoing mitophagy. Therefore, the strategy in this context provides a new thought for designing mitochondrion-immobilized pH-sensitive probes and our probe MTpH is promising as a useful tool for long-term monitoring of mitochondrial pH changes.