Rapid real-time quantitative colorimetric LAMP methodology for field detection of Verticillium dahliae in crude olive-plant samples.

BACKGROUND: Verticilium dahliae is the most important wilt pathogen of olive trees with a broad host range causing devastating diseases currently without any effective chemical control. Traditional detection methodologies are based on symptoms-observation or lab-detection using time consuming culturing or molecular techniques. Therefore, there is an increasing need for portable tools that can detect rapidly V. dahliae in the field. RESULTS: In this work, we report the development of a novel method for the rapid, reliable and on-site detection of V. dahliae using a newly designed isothermal LAMP assay and crude extracts of olive wood. For the detection of the fungus, LAMP primers were designed targeting the internal transcribed spacer (ITS) region of the rRNA gene. The above assay was combined with a purpose-built prototype portable device which allowed real time quantitative colorimetric detection of V. dahliae in 35 min. The limit of detection of our assay was found to be 0.8 fg/µl reaction and the specificity 100% as indicated by zero cross-reactivity to common pathogens found in olive trees. Moreover, detection of V. dahliae in purified DNA gave a sensitivity of 100% (Ct < 30) and 80% (Ct > 30) while the detection of the fungus in unpurified crude wood extracts showed a sensitivity of 80% when multisampling was implemented. The superiority of the LAMP methodology regarding robustness and sensitivity was demonstrated when only LAMP was able to detect V. dahliae in crude samples from naturally infected trees with very low infection levels, while nested PCR and SYBR qPCR failed to detect the pathogen in an unpurified form. CONCLUSIONS: This study describes the development of a new real time LAMP assay, targeting the ITS region of the rRNA gene of V. dahliae in olive trees combined with a 3D-printed portable device for field testing using a tablet. The assay is characterized by high sensitivity and specificity as well as ability to operate using directly crude samples such as woody tissue or petioles. The reported methodology is setting the basis for the development of an on-site detection methodology for V. dahliae in olive trees, but also for other plant pathogens.

Nature heals: An informational entropy account of self-organization and change in field psychotherapy.

This paper reviews biophysical models of psychotherapeutic change based on synergetics and the free energy principle. These models suggest that introducing sensory surprise into the patient-therapist system can lead to self-organization and the formation of new attractor states, disrupting entrenched patterns of thoughts, emotions, and behaviours. We propose that the therapist can facilitate this process by cultivating epistemic trust and modulating embodied attention to allow surprising affective states to enter shared awareness. Transient increases in free energy enable the update of generative models, expanding the range of experiences available within the patient-therapist phenomenal field. We hypothesize that patterns of disorganization at behavioural and physiological levels, indexed by increased entropy, complexity, and lower determinism, are key markers and predictors of psychotherapeutic gains. Future research should investigate how the therapist's openness to novelty shapes therapeutic outcomes.

Remote sensing of temperature-dependent mosquito and viral traits predicts field surveillance-based disease risk.

Mosquito-borne diseases contribute substantially to the global burden of disease, and are strongly influenced by environmental conditions. Ongoing and rapid environmental change necessitates improved understanding of the response of mosquito-borne diseases to environmental factors like temperature, and novel approaches to mapping and monitoring risk. Recent development of trait-based mechanistic models has improved understanding of the temperature dependence of transmission, but model predictions remain challenging to validate in the field. Using West Nile virus (WNV) as a case study, we illustrate the use of a novel remote sensing-based approach to mapping temperature-dependent mosquito and viral traits at high spatial resolution and across the diurnal cycle. We validate the approach using mosquito and WNV surveillance data controlling for other key factors in the ecology of WNV, finding strong agreement between temperature-dependent traits and field-based metrics of risk. Moreover, we find that WNV infection rate in mosquitos exhibits a unimodal relationship with temperature, peaking at ~24.6-25.2°C, in the middle of the 95% credible interval of optimal temperature for transmission of WNV predicted by trait-based mechanistic models. This study represents one of the highest resolution validations of trait-based model predictions, and illustrates the utility of a novel remote sensing approach to predicting mosquito-borne disease risk.

Comparison of Inter-Rater and Intra-Rater Reliability of Raters with Different Levels of Experience When Using Landing Error Scoring System (LESS) in Field-Based Screening of Professional Football Players.

It is essential for physical sports therapists to use reliable field-based tests to identify potential injury risk factors in athletes. The purpose of this study was to compare the inter- and intra-rater reliability of experienced and novice raters during use of the Landing Error Scoring System (LESS) in a field-based examination of professional football athletes. Thirty-seven male football athletes underwent pre-season LESS assessment. Two raters independently evaluated the recorded landing techniques at two separate intervals, two months apart, following the LESS standard protocol. Inter-and intra-rater values were calculated for the LESS total scores and individual scoring items. The overall LESS scores had excellent intra-rater reliability values for both the experienced (interclass correlation coefficient (ICC) = 0.95, 95% CI, 0.89-0.97; p < 0.001) and novice rater (ICC = 0.95, 95% CI, 0.90-0.97; p < 0.001), and very good to excellent inter-rater values for the first (ICC = 0.90, 95% CI, 0.77-0.95; p < 0.001) and second (ICC = 0.86, 95% CI, 0.71-0.93; p < 0.001) evaluation. Most of the individual scoring items ranged from moderate to perfect agreement. In conclusion, sports physical therapists, regardless of experience, can reliably use the LESS's total score, through video analysis of the regime. Individual scoring items can inform clinicians about impairments in the landing mechanism but data should be interpreted cautiously.

Assessment of wetland ecosystem health in Rarh Region, India through P-S-R (pressure-state-response) model.

The current study attempted to assess wetland ecosystem health (EH) in the Murshidabad district's Rarh tract using the P-S-R (Pressure-State-Response) model and machine learning (ML) algorithms and validated it with a field-based validation approach as well as conventional validation approaches. To assess the ecosystem's health, 27 metrics were used to monitor the wetlands' pressure, state, and response. All of the models found that 46.1 % of wetlands in strong EH zones have transformed to 11.41 % in relatively fragile EH zones during the previous thirty years, demonstrating a progressive loss of EH quality throughout larger wetland areas. All of the applied models were deemed to be acceptable based on the results of the model validation process, however, the Random Forest (RF) model performed exceptionally well. The deterioration of EH in the wetlands happened due to the rapid expansion of settlement areas and agricultural land. So, the findings of the study deepen our knowledge about EH in the Rarh tract's wetlands, assisting decision-makers in creating sustainable wetland management strategies.

"Male athletes play well to feel good, and female athletes feel good to play well": Attitudes, beliefs, and practices pertaining to perceived sex-related differences in communication and interpersonal approach of strength and conditioning coaches in international women's rugby union.

Effective communication and rapport building with athletes are key tenets of coaching. As the majority of empirical evidence to date has adopted an androcentric view of strength and conditioning, a potential knowledge gap exists regarding sex-related differences in physical preparation and coaching approaches. Therefore, this study explored the attitudes, beliefs and practices of strength and conditioning coaches (n = 8; M/F, 6/2) in elite level (international) women's rugby union using semi-structured interviews (mean ±standard deviation duration 59 ± 15 min). The interviews explored differences in coaching practices for elite female rugby players compared to males, with a specific focus on the interpersonal aspects of the athlete-coach relationship. Reflexive thematic analysis was used to generate a rich qualitative dataset. The analysis resulted in the identification of higher order themes: athlete engagement, and interpersonal approach. The coaches in this study consistently perceived important differences between male and female players in factors related to engagement and interpersonal approach. Coaches adopted differing coaching practices for male and female athletes. This study provides important contextual evidence for the understanding of differences in the interpersonal relationships of female rugby players compared to male athletes from the perspective of elite-level strength coaches.

Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location.

BACKGROUND: This study explores the use of Unmanned Aerial Vehicles (UAVs) for estimating wheat biomass, focusing on the impact of phenotyping and analytical protocols in the context of late-stage variety selection programs. It emphasizes the importance of variable selection, model specificity, and sampling location within the experimental plot in predicting biomass, aiming to refine UAV-based estimation techniques for enhanced selection accuracy and throughput in variety testing programs. RESULTS: The research uncovered that integrating geometric and spectral traits led to an increase in prediction accuracy, whilst a recursive feature elimination (RFE) based variable selection workflowled to slight reductions in accuracy with the benefit of increased interpretability. Models, tailored to specific experiments were more accurate than those modelling all experiments together, while models trained for broad-growth stages did not significantly increase accuracy. The comparison between a permanent and a precise region of interest (ROI) within the plot showed negligible differences in biomass prediction accuracy, indicating the robustness of the approach across different sampling locations within the plot. Significant differences in the within-season repeatability (w2) of biomass predictions across different experiments highlighted the need for further investigation into the optimal timing of measurement for prediction. CONCLUSIONS: The study highlights the promising potential of UAV technology in biomass prediction for wheat at a small plot scale. It suggests that the accuracy of biomass predictions can be significantly improved through optimizing analytical and modelling protocols (i.e., variable selection, algorithm selection, stage-specific model development). Future work should focus on exploring the applicability of these findings under a wider variety of conditions and from a more diverse set of genotypes.

Use of hydroponics-based evaluation for phenotyping tolerance/susceptibility to the aphid, Uroleucon compositae and inheritance analysis of aphid tolerance in a global germplasm collection of Carthamus tinctorius L. (Safflower).

Carthamus tinctorius L. (Safflower) is an important oilseed crop that is cultivated globally. Aphids are a serious pest of safflower and cause significant yield losses of up to 80% due to their ability to multiply rapidly by parthenogenesis. In this study, we report the identification of an aphid-tolerant accession in safflower following screening of a representative global germplasm collection of 327 accessions from 37 countries. Field-based screening methods gave inconsistent and ambiguous results for aphid tolerance between natural and controlled infestation assays and required ~ 3 months for completion. Therefore, we used a rapid, high-throughput hydroponics-based assay system that allows phenotyping of aphid tolerance/susceptibility in a large number of plants in a limited area, significantly reduces the time required to ~ 45 days and avoids inconsistencies observed in field-based studies. We identified one accession out of the 327 tested germplasm lines that demonstrated aphid tolerance in field-based natural and controlled infestation studies and also using the hydroponics approach. Inheritance analysis of the trait was conducted using the hydroponics approach on F1 and F2 progeny generated from a cross between the tolerant and susceptible lines. Aphid-tolerance was observed to be a dominant trait governed by a single locus/gene that can be mobilized after mapping into cultivated varieties of safflower. The hydroponics-based assay described in this study would be very useful for studying the molecular mechanism of aphid-tolerance in safflower and can also be used for bioassays in several other crops that are amenable to hydroponics-based growth. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01467-0.

Bagging Improves the Performance of Deep Learning-Based Semantic Segmentation with Limited Labeled Images: A Case Study of Crop Segmentation for High-Throughput Plant Phenotyping.

Advancements in imaging, computer vision, and automation have revolutionized various fields, including field-based high-throughput plant phenotyping (FHTPP). This integration allows for the rapid and accurate measurement of plant traits. Deep Convolutional Neural Networks (DCNNs) have emerged as a powerful tool in FHTPP, particularly in crop segmentation-identifying crops from the background-crucial for trait analysis. However, the effectiveness of DCNNs often hinges on the availability of large, labeled datasets, which poses a challenge due to the high cost of labeling. In this study, a deep learning with bagging approach is introduced to enhance crop segmentation using high-resolution RGB images, tested on the NU-Spidercam dataset from maize plots. The proposed method outperforms traditional machine learning and deep learning models in prediction accuracy and speed. Remarkably, it achieves up to 40% higher Intersection-over-Union (IoU) than the threshold method and 11% over conventional machine learning, with significantly faster prediction times and manageable training duration. Crucially, it demonstrates that even small labeled datasets can yield high accuracy in semantic segmentation. This approach not only proves effective for FHTPP but also suggests potential for broader application in remote sensing, offering a scalable solution to semantic segmentation challenges. This paper is accompanied by publicly available source code.

Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize.

Field-based phenomic prediction employs novel features, like vegetation indices (VIs) from drone images, to predict key agronomic traits in maize, despite challenges in matching biomarker measurement time points across years or environments. This study utilized functional principal component analysis (FPCA) to summarize the variation of temporal VIs, uniquely allowing the integration of this data into phenomic prediction models tested across multiple years (2018-2021) and environments. The models, which included 1 genomic, 2 phenomic, 2 multikernel, and 1 multitrait type, were evaluated in 4 prediction scenarios (CV2, CV1, CV0, and CV00), relevant for plant breeding programs, assessing both tested and untested genotypes in observed and unobserved environments. Two hybrid populations (415 and 220 hybrids) demonstrated the visible atmospherically resistant index's strong temporal correlation with grain yield (up to 0.59) and plant height. The first 2 FPCAs explained 59.3 ± 13.9% and 74.2 ± 9.0% of the temporal variation of temporal data of VIs, respectively, facilitating predictions where flight times varied. Phenomic data, particularly when combined with genomic data, often were comparable to or numerically exceeded the base genomic model in prediction accuracy, particularly for grain yield in untested hybrids, although no significant differences in these models' performance were consistently observed. Overall, this approach underscores the effectiveness of FPCA and combined models in enhancing the prediction of grain yield and plant height across environments and diverse agricultural settings.

Designing of xanthine-based DPP-4 inhibitors: a structure-guided alignment dependent Multifacet 3D-QSAR modeling, and molecular dynamics simulation study.

The DPP-4 enzyme degrades incretin hormones GLP-1 and GIP. DPP-4 inhibitors are found effective in the prevention of the degradation of incretins. Xanthine scaffold-bearing molecules are reported as potential DPP-4 inhibitors for treating type 2 diabetes mellitus, e.g. the marketed drug linagliptin. In this work, structure-guided alignment-dependent atom- and Gaussian field-based 3D-QSAR have been performed on a dataset of 75 molecules. The robustness and predictive ability of the developed multifacet 3D-QSAR models were validated on different statistical parameters and found to be statistically fit. The favorable and unfavorable pharmacophoric features were mapped for each multifacet 3D-QSAR model based on three alignment sets (1-3). A five-point common pharmacophore hypothesis was generated separately for each set of alignments. The molecular dynamics simulations (up to 100 ns) were performed for the potent molecule from each alignment set (Compounds 12, 40 and 57) compared to reference standard linagliptin to study the binding energy and stability of target-ligand complexes. The MM-PBSA calculations revealed that the binding free energy and stability of compounds 12 (-40.324 ± 17.876 kJ/mol), 40 (-80.543 ± 21.782 kJ/mol) and 57 (-50.202 ± 16.055 kJ/mol) were better than the reference drug linagliptin (-20.390 ± 63.200 kJ/mol). The generated contour maps from structure-guided alignment-dependent multifacet 3D-QSAR models offer information about the structure-activity relationship (SAR) and ligand-target binding energy and stability data from MD simulation may be utilized to design and develop target selective xanthine-based novel DPP-4 inhibitors.Communicated by Ramaswamy H. Sarma.

In-Person Versus Remote 6-Minute Walk and Incremental Shuttle Walk Distances in Advanced Lung Disease.

BACKGROUND: Field-based walk tests conducted remotely may provide an alternative method to a facility-based assessment of exercise capacity for people with advanced lung disease. This prospective study evaluated the level of agreement in the distance walked between a 6-min walk test (6MWT) and an incremental shuttle walk test performed by using standard in-person procedures and test variations and settings. METHODS: Adults with advanced lung disease underwent 4 study visits: (i) one in-person standard 6MWT (30-m corridor) and one in-person treadmill 6MWT, (ii) a remote 6MWT in a home setting (10-m corridor), (iii) 2 in-person standard incremental shuttle walk tests (10-m corridor), and (iv) a remote incremental shuttle walk test in a home setting (10-m corridor). A medical-grade oximeter measured heart rate and oxygen saturation before, during, and for 2 min after the tests. RESULTS: Twenty-eight participants were included (23 men [82%]; 64 (57-67) y old; 19 with interstitial lung disease [68%] and 9 with COPD [32%]; and 26 used supplemental oxygen (93%) [exertional [Formula: see text] of 0.46 ± 0.1]). There was no agreement between the tests. Greater walking distances were achieved with standard testing procedures: in-person 6MWT versus treadmill 6MWT (355 ± 68 vs 296 ± 97; P = .001; n = 28), in-person 6MWT versus remote 6MWT (349 ± 68 vs 293 ± 84; P = .001; n = 24), and in-person incremental shuttle walk test versus remote incremental shuttle walk test (216 ± 62 vs 195 ± 63; P = .03; n = 22). CONCLUSIONS: Differences in the distance walked may have resulted from different track lengths, widths, and walking surfaces. This should be considered in test interpretation if tests are repeated under different conditions.

On the relevance of query definition in the performance of 3D ligand-based virtual screening.

Ligand-based virtual screening (LBVS) methods are widely used to explore the vast chemical space in the search of novel compounds resorting to a variety of properties encoded in 1D, 2D or 3D descriptors. The success of 3D-LBVS is affected by the overlay of molecular pairs, thus making selection of the template compound, search of accessible conformational space and choice of the query conformation to be potential factors that modulate the successful retrieval of actives. This study examines the impact of adopting different choices for the query conformation of the template, paying also attention to the influence exerted by the structural similarity between templates and actives. The analysis is performed using PharmScreen, a 3D LBVS tool that relies on similarity measurements of the hydrophobic/philic pattern of molecules, and Phase Shape, which is based on the alignment of atom triplets followed by refinement of the volume overlap. The study is performed for the original DUD-E+ database and a Morgan Fingerprint filtered version (denoted DUD-E+-Diverse; available in https://github.com/Pharmacelera/Query-models-to-3DLBVS ), which was prepared to minimize the 2D resemblance between template and actives. Although in most cases the query conformation exhibits a mild influence on the overall performance, a critical analysis is made to disclose factors, such as the content of structural features between template and actives and the induction of conformational strain in the template, that underlie the drastic impact of the query definition in the recovery of actives for certain targets. The findings of this research also provide valuable guidance for assisting the selection of the query definition in 3D LBVS campaigns.

Accelerating targeted mosquito control efforts through mobile West Nile virus detection.

BACKGROUND: Different mosquito control strategies have been implemented to mitigate or prevent mosquito-related public health situations. Modern mosquito control largely relies on multiple approaches, including targeted, specific treatments. Given this, it is becoming increasingly important to supplement these activities with rapid and mobile diagnostic capacities for mosquito-borne diseases. We aimed to create and test the applicability of a rapid diagnostic system for West Nile virus that can be used under field conditions. METHODS: In this pilot study, various types of adult mosquito traps were applied within the regular mosquito monitoring activity framework for mosquito control. Then, the captured specimens were used for the detection of West Nile virus RNA under field conditions with a portable qRT-PCR approach within 3-4 h. Then, positive samples were subjected to confirmatory RT-PCR or NGS sequencing in the laboratory to obtain genome information of the virus. We implemented phylogenetic analysis to characterize circulating strains. RESULTS: A total of 356 mosquito individuals representing 7 species were processed in 54 pools, each containing up to 20 individuals. These pools were tested for the presence of West Nile virus, and two pools tested positive, containing specimens from the Culex pipiens and Anopheles atroparvus mosquito species. As a result of subsequent sequencing, we present the complete genome of West Nile virus and Bagaza virus. CONCLUSIONS: The rapid identification of infected mosquitoes is the most important component of quick response adulticide or larvicide treatments to prevent human cases. The conceptual framework of real-time surveillance can be optimized for other pathogens and situations not only in relation to West Nile virus. We present an early warning system for mosquito-borne diseases and demonstrate its application to aid rapid-response mosquito control actions.

Fine-Grained Boundary Conditions in Field-Based Routing.

In the realm of industrial wireless mesh networks, an efficient routing protocol is highly demanded to play a crucial role in ensuring that packets are efficiently directed along shorter and congestion-free routes toward gateways. Field-based routing has emerged as a promising solution to tackle these network challenges. This routing approach draws inspiration from physics and employs a differential equation to model its behavior in finding efficient routes. Given the fundamental significance of boundary conditions in physics, where they play an essential role in shaping the solutions to the equation, exploring the impact of boundary conditions on field-based routing behavior within network domains becomes highly significant. However, despite their influence, the impact of boundary conditions has remained unexplored in existing studies on field-based routing. In this context, our work explores the boundary condition problem and introduces new advanced fine-grained boundary conditions for field-based routing. We demonstrate the superior performance of our proposed scheme, highlighting the substantial role of boundary conditions in network behavior. Our work holds significant value in that it explores the boundary condition problem, an aspect largely overlooked in previous research, and provides a viable solution, underscoring its crucial importance in routing enhancement.

Rapid detection of porcine sapelovirus by reverse transcription recombinase polymerase amplification assay.

BACKGROUND: Porcine Sapelovirus (PSV) infection has been confirmed in pigs worldwide, mostly asymptomatic, but in some cases, it can lead to significant issues in the gastrointestinal, respiratory, neurological, or reproductive systems. PSV is considered an emerging pathogen of porcine species. Recombinase polymerase amplification (RPA) is a simple and fast isothermal technique that uses three enzymes for amplification without the use of any sophisticated equipment. METHODS AND RESULTS: The reverse transcription recombinase polymerase amplification (RT-RPA) assay was developed and optimized for field based detection of PSV. The assay was developed by targeting 5´UTR region of PSV genome and optimized for reaction time, temperature, primer and MgOAc concentration. The analytical sensitivity and specificity of assay was determined. The assay was evaluated on 85 porcine faecal samples collected from field. In addition to conventional format, this assay was also optimized for visual dye-based detection format and lateral flow strips based detection (in combination with probe). The developed assay works at constant temperature of 35 °C for 20 min with forward primer concentration 20pm, reverse primer concentration 10pm and MgOAc concentration of 14mM. This assay is highly sensitive and detects up to 28 copies of viral nucleic acid both in the conventional as well as in fluorescent dye based detection format. Using the newly developed assay 21 samples out of 85 samples were found positive, showing positivity rate of 24.7%. The positivity rate of RT-RPA assay corroborated with the gold standard RT-PCR test. CONCLUSIONS: This study presented the development of an RT-RPA isothermal assay for rapid and accurate detection of PSV. The assay is highly sensitive, specific, works at a low and constant temperature, does not require any high-end instrument and can be a potential diagnostics tool for pen-side testing of PSV in the field conditions. The newly developed RT-RPA assay could successfully detect PSV circulating in swine population of Haryana, India. This is a first report of this kind from the region.

Field-work reveals a novel function for MAX2 in a native tobacco's high-light adaptions.

Laboratory studies have revealed that strigolatone (SL) and karrikin (KAR) signalling mediate responses to abiotic and biotic stresses, and reshape branching architecture that could increase reproductive performance and crop yields. To understand the ecological function of SL and KAR signalling, transgenic lines of wild tobacco Nicotiana attenuata, silenced in SL/KAR biosynthesis/signalling were grown in the glasshouse and in two field plots in the Great Basin Desert in Utah over four field seasons. Of the lines silenced in SL and KAR signalling components (irMAX2, irD14, irKAI2 and irD14 × irKAI2 plants), which exhibited the expected increases in shoot branching, only irMAX2 plants showed a strong leaf-bleaching phenotype when grown in the field. In the field, irMAX2 plants had lower sugar and higher leaf amino acid contents, lower lifetime fitness and were more susceptible to herbivore attack compared to wild-type plants. These irMAX2 phenotypes were not observed in glasshouse-grown plants. Transcriptomic analysis revealed dramatic responses to high-light intensity in irMAX2 leaves in the field: lutein contents decreased, and transcriptional responses to high-intensity light, singlet oxygen and hydrogen peroxide increased. PAR and UV-B manipulations in the field revealed that the irMAX2 bleaching phenotype is reversed by decreasing PAR, but not UV-B fluence. We propose that NaMAX2 functions in high-light adaptation and fitness optimisation by regulating high-light responses independently of its roles in the SL and KAR signalling pathways. The work provides another example of the value of studying the function of genes in the complex environments in which plants evolved, namely nature.

Test-retest reliability of four flatwater performance-related tests in canoe slalom athletes.

Purpose: This study aims to evaluate the test-retest reliability of four flatwater performance-related tests in canoe slalom athletes. Methods: Twenty-two Slovak national team members of junior and U23 age group racing in a category K1 men (K1M), K1 women (K1W) or C1 men (C1M) volunteered to take part in this study. During both test and retest testing sessions athletes performed 4 flatwater tests: SPS-Sprints with a turn to the preferred side (2 × 15 m shuttle sprints), SNPS-Sprints with a turn to the non-preferred side (2 × 15 m shuttle sprints), SBS-Sprints with turns to both sides (2 × 15 m shuttle sprints) as well as 12 × 15 AOT-12 × 15 m all out shuttle test (12 × 15 m shuttle sprints). Each athlete completed two sessions separated by a minimum of days and a maximum of 5 days. Results: The results have shown the excellent test-retest reliability of all four flatwater tests (ICC-SPS: 0.98; SPNPS 0.97; SBS: 0.98 and 12 × 15 m AOT: 0.96). Additionally, results have shown SEM (SPS: 0.14; SPNPS 0.18; SBS: 0.13 and 12 × 15 m AOT: 1.05) and SWC (SPS: 0.21; SPNPS 0.26; SBS: 0.19 and 12 × 15 m AOT: 1.58). Conclusion: Based on our results we suggest that coaches use these valid and reliable tests to assess changes in their athletes' performance-related physical fitness over time, to verify the effectiveness of training programs focused on improvement in specific physical fitness of athletes as well as to identify asymmetries between the preferred and non-preferred side in canoe slalom athletes.

Remote sensing continuity: a comparison of HTP platforms and potential challenges with field applications.

In an era of climate change and increased environmental variability, breeders are looking for tools to maintain and increase genetic gain and overall efficiency. In recent years the field of high throughput phenotyping (HTP) has received increased attention as an option to meet this need. There are many platform options in HTP, but ground-based handheld and remote aerial systems are two popular options. While many HTP setups have similar specifications, it is not always clear if data from different systems can be treated interchangeably. In this research, we evaluated two handheld radiometer platforms, Cropscan MSR16R and Spectra Vista Corp (SVC) HR-1024i, as well as a UAS-based system with a Sentera Quad Multispectral Sensor. Each handheld radiometer was used for two years simultaneously with the unoccupied aircraft systems (UAS) in collecting winter wheat breeding trials between 2018-2021. Spectral reflectance indices (SRI) were calculated for each system. SRI heritability and correlation were analyzed in evaluating the platform and SRI usability for breeding applications. Correlations of SRIs were low against UAS SRI and grain yield while using the Cropscan system in 2018 and 2019. Dissimilarly, the SVC system in 2020 and 2021 produced moderate correlations across UAS SRI and grain yield. UAS SRI were consistently more heritable, with broad-sense heritability ranging from 0.58 to 0.80. Data standardization and collection windows are important to consider in ensuring reliable data. Furthermore, practical aspects and best practices for these HTP platforms, relative to applied breeding applications, are highlighted and discussed. The findings of this study can be a framework to build upon when considering the implementation of HTP technology in an applied breeding program.

A computational investigation of thymidylate synthase inhibitors through a combined approach of 3D-QSAR and pharmacophore modelling.

Thymidylate synthase (TS) is a crucial target of cancer drug discovery and is mainly involved in the De novo synthesis of the DNA precursor thymine. In the present study, to generate reliable models and identify a few promising molecules, we combined QSAR modelling with the pharmacophore hypothesis-generating technique. Input molecules were clustered on their similarity, and a cluster of 74 molecules with a pyrimidine moiety was chosen as the set for 3D-QSAR and pharmacophore modelling. Atom-based and field-based 3D-QSAR models were generated and statistically validated with R2 > 0.90 and Q2 > 0.75. The common pharmacophore hypothesis(CPH) generation identified the best six-point model ADHRRR. Using these best models, a library of FDA-approved drugs was screened for activity and filtered via molecular docking, ADME profiling, and molecular dynamics simulations. The top ten promising TS-inhibiting candidates were identified, and their chemical features profitable for TS inhibitors were explored.Communicated by Ramaswamy H. Sarma.