A study about the suitability of the chelation reaction of Ca(2+)with ethylenediaminetetraacetic acid (EDTA) as a validation standard for Isothermal Titration Calorimeter measurements has been ...performed exploring the common experimental variables (buffer, pH, ionic strength and temperature). Results obtained in a variety of experimental conditions have been amended according to the side reactions involved in the main process and to the experimental ionic strength and, finally, validated by contrast with the potentiometric reference values. It is demonstrated that the chelation reaction performed in acetate buffer 0.1M and 25°C shows accurate and precise results and it is robust enough to be adopted as a standard calibration process.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The interaction between cyanidin-3-O-glucoside and four citrus pectic fractions was investigated using a combined molecular approach, including isothermal titration calorimetry (ITC), magnetic ...nuclear resonance (NMR) and UV–Visible spectrophotometry. These pectic fractions differed on their type and degree of esterification (amidated (AHG 30%), low (HG 30%) and high methyl esterified fractions (HG 70%)) and on the pattern of esterification (blockwise (HG-B 70%) vrs random (HG-R 70%)). The binding constant (Ka) and the associated thermodynamic parameters determined showed weak noncovalent interactions, particularly due to electrostatic interactions, hydrogen bonding and hydrophobic effect. The degree and the type of esterification of each pectic fractions had a significant effect on the binding constants determined by ITC and NMR experiments. The binding constants ranged from 102 to 104 M−1, with the highest Ka value observed for the interaction between cy3glc and low methylesterified fraction, followed by the amidated fraction. Pectic fractions with a higher degree of methyl esterification, resulted on lower binding affinities, with these interactions being mostly driven by hydrophobic effect compared to enthalpy. The different binding affinities could be correlated with anthocyanins colour impact, as a higher red colour intensity could be observed for a cy3glc model solution fortified with a low methylated fraction. However, this colour improvement was not observed for amidated fraction, presumably due to charge repulsive forces, lowering the stability of the flavylium cation.
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•Cy3glc bind to pectin fractions with different binding affinities.•Low esterified pectins bind preferentially to cy3glc followed by high esterified.•Cy3glc red colour was shown to be preferentially improved with low esterified pectins.•Amidated pectins did not caused a cy3glc red colour improvement.•Charge interaction, H-bonding, hydrophobic effect and cy3glc stacking contribute to binding.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study focuses on advancing individual tree crown (ITC) segmentation in lidar data, developing a sensor- and platform-agnostic deep learning model transferable across a spectrum of dense laser ...scanning datasets from drone (ULS), to terrestrial (TLS), and mobile (MLS) laser scanning data. In a field where transferability across different data characteristics has been a longstanding challenge, this research marks a step towards versatile, efficient, and comprehensive 3D forest scene analysis.
Central to this study is model performance evaluation based on platform type (ULS vs. MLS) and data density. This involved five distinct scenarios, each integrating different combinations of input training data, including ULS, MLS, and their augmented versions through random subsampling, to assess the model's transferability to varying resolutions and efficacy across different canopy layers. The core of the model, inspired by the PointGroup architecture, is a 3D convolutional neural network (CNN) with dedicated prediction heads for semantic and instance segmentation. The model underwent comprehensive validation on publicly available, machine learning-ready point cloud datasets. Additional analyses assessed model adaptability to different resolutions and performance across canopy layers.
Our results reveal that point cloud random subsampling is an effective augmentation strategy and improves model performance and transferability. The model trained using the most aggressive augmentation, including point clouds as sparse as 10 points m−2, showed best performance and was found to be transferable to sparse lidar data and boosts detection and segmentation of codominant and dominated trees. Notably, the model showed consistent performance for point clouds with densities >50 points m−2 but exhibited a drop in performance at the sparsest level (10 points m−2), mainly due to increased omission rates. Benchmarking against current state-of-the-art methods revealed boosts of up to 20% in the detection rates, indicating the model's superior performance on multiple open benchmark datasets. Further, our experiments also set new performance baselines for the other public datasets. The comparison highlights the model's superior segmentation skill, mainly due to better detection and segmentation of understory trees below the canopy, with reduced computational demands compared to other recent methods.
In conclusion, the present study demonstrates that it is indeed feasible to train a sensor-agnostic model that can handle diverse laser scanning data, going beyond current sensor-specific methodologies. Further, our study sets a new baseline for tree segmentation, especially in complex forest structures. By advancing the state-of-the-art in forest lidar analysis, our work also lays the foundation for future innovations in ecological modeling and forest management.
•Developed a versatile deep learning method for tree segmentation with lidar.•Evaluated model performance across various platforms with sparsity impact analysis.•Showed that gradual sparsification as a training strategy is effective for lidar.•Improved understory tree detection with lower computational needs than others.•Set new performance standards in Wytham Woods and TreeLearn datasets.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A study about the suitability of the chelation reaction of Ca2+with ethylenediaminetetraacetic acid (EDTA) as a validation standard for Isothermal Titration Calorimeter measurements has been ...performed exploring the common experimental variables (buffer, pH, ionic strength and temperature). Results obtained in a variety of experimental conditions have been amended according to the side reactions involved in the main process and to the experimental ionic strength and, finally, validated by contrast with the potentiometric reference values. It is demonstrated that the chelation reaction performed in acetate buffer 0.1M and 25°C shows accurate and precise results and it is robust enough to be adopted as a standard calibration process.
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•Ca2+–EDTA chelation as standard reaction for calibration of ITC instruments.l•Experimental conditions of Ca2+–EDTA (buffer, pH, T, I) for easy ITC calibration.•Ca2+–EDTA features (n, Kb, ΔH) as calibration parameters of ITC instruments.•Thermodynamic binding constant for isolated Ca2+–EDTA chelation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•MicroScale Thermophoresis (MST) measures dissociation constants down to 1 picomolar.•MST can dissect different binding mechanism by distinct thermophoresis signals.•MST quantifies dissociation ...constants in 100% cell lysate.•MST can be used to determine thermodynamic parameters for interactions.•MST can be used to monitor enzyme kinetics and protein folding.
MicroScale Thermophoresis (MST) is a powerful technique to quantify biomolecular interactions. It is based on thermophoresis, the directed movement of molecules in a temperature gradient, which strongly depends on a variety of molecular properties such as size, charge, hydration shell or conformation. Thus, this technique is highly sensitive to virtually any change in molecular properties, allowing for a precise quantification of molecular events independent of the size or nature of the investigated specimen.
During a MST experiment, a temperature gradient is induced by an infrared laser. The directed movement of molecules through the temperature gradient is detected and quantified using either covalently attached or intrinsic fluorophores. By combining the precision of fluorescence detection with the variability and sensitivity of thermophoresis, MST provides a flexible, robust and fast way to dissect molecular interactions.
In this review, we present recent progress and developments in MST technology and focus on MST applications beyond standard biomolecular interaction studies. By using different model systems, we introduce alternative MST applications – such as determination of binding stoichiometries and binding modes, analysis of protein unfolding, thermodynamics and enzyme kinetics. In addition, wedemonstrate the capability of MST to quantify high-affinity interactions with dissociation constants (Kds) in the low picomolar (pM) range as well as protein–protein interactions in pure mammalian cell lysates.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The sudden global outbreak of COVID-19 in late 2019 has led to thriving online teaching, including the teaching of languages, across the world. As the online teaching of English-as-a-foreign-language ...(EFL) in Chinese universities is facing new challenges, EFL teachers have been positively exploring new solutions. To understand how EFL teachers were coping with the challenges, we set up this research as part of a larger study to examine EFL teachers’ cognitions about online teaching in response to the disruption of normal teaching plans. We did so by taking a qualitative approach through analyzing in-depth interviews with three EFL teachers from a Chinese university. Through thematic analysis we found that teachers had clear cognitions about features, advantages, and constraints of online EFL teaching and that they acquired information and communication technology (ICT) literacy through understanding students’ learning needs, online teaching practice, and the necessity of integrating traditional classroom teaching methods into online delivery. We conclude this study with a discussion on its pedagogical implications for similar contexts or colleagues facing similar challenges in other parts of the world.
Ferritin is a 24-mer protein nanocage that stores iron and regulates intracellular iron homeostasis. The nuclear receptor coactivator-4 (NCOA4) binds specifically to ferritin H subunits and ...facilitates the autophagic trafficking of ferritin to the lysosome for degradation and iron release. Using isothermal titration calorimetry (ITC), we studied the thermodynamics of the interactions between ferritin and the soluble fragment of NCOA4 (residues 383–522), focusing on the effects of the recently identified FeS cluster bound to NCOA4, ferritin subunit composition, and ferritin‑iron loading. Our findings show that in the presence of the FeS cluster, the binding is driven by a more favorable enthalpy change and a decrease in entropy change, indicating a key role for the FeS cluster in the structural organization and stability of the complex. The ferritin iron core further enhances this association, increasing binding enthalpy and stabilizing the NCOA4-ferritin complex. The ferritin subunit composition primarily affects binding stoichiometry of the reaction based on the number of H subunits in the ferritin H/L oligomer. Our results demonstrate that both the FeS cluster and the ferritin iron core significantly affect the binding thermodynamics of the NCOA4-ferritin interactions, suggesting regulatory roles for the FeS cluster and ferritin iron content in ferritinophagy.
•The FeS cluster and the ferritin iron core influence NCOA4-ferritin interactions.•The FeS cluster may play a role in the structural organization of the complex.•The ferritin iron core enhances the interaction and further stabilization of the complex.•The binding thermodynamics indicate enthalpically and entropically favored reaction.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•SARS-2 FP is more hydrophobic than SARS-1 FP.•SARS-2 FP induces greater membrane ordering than SARS-1 FP.•SARS-CoV-2 FP induces membrane ordering in a specific Ca2+-dependent ...fashion.•SARS-2 FP binds two Ca2+ and the binding sites are positively cooperative.•SARS-1 PP is even more effective in inducing membrane ordering than separate FPs.
Coronaviruses are a major infectious disease threat, and include the zoonotic-origin human pathogens SARS-CoV-2, SARS-CoV, and MERS-CoV (SARS-2, SARS-1, and MERS). Entry of coronaviruses into host cells is mediated by the spike (S) protein. In our previous ESR studies, the local membrane ordering effect of the fusion peptide (FP) of various viral glycoproteins including the S of SARS-1 and MERS has been consistently observed. We previously determined that the sequence immediately downstream from the S2′ cleavage site is the bona fide SARS-1 FP. In this study, we used sequence alignment to identify the SARS-2 FP, and studied its membrane ordering effect. Although there are only three residue differences, SARS-2 FP induces even greater membrane ordering than SARS-1 FP, possibly due to its greater hydrophobicity. This may be a reason that SARS-2 is better able to infect host cells. In addition, the membrane binding enthalpy for SARS-2 is greater. Both the membrane ordering of SARS-2 and SARS-1 FPs are dependent on Ca2+, but that of SARS-2 shows a greater response to the presence of Ca2+. Both FPs bind two Ca2+ ions as does SARS-1 FP, but the two Ca2+ binding sites of SARS-2 exhibit greater cooperativity. This Ca2+ dependence by the SARS-2 FP is very ion-specific. These results show that Ca2+ is an important regulator that interacts with the SARS-2 FP and thus plays a significant role in SARS-2 viral entry. This could lead to therapeutic solutions that either target the FP-calcium interaction or block the Ca2+ channel.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•The AOP was activated during social buffering.•AOP activation was not biased toward GABAergic neurons.•The lateral ITC was simultaneously activated during social buffering.•The lateral ITC can be an ...intervening area between the AOP and lateral amygdala.
The presence of an affiliative conspecific reduces stress responses to a wide variety of stimuli. This phenomenon is termed “social buffering”. We previously found that the presence of another Wistar rat (associate) suppressed activation of the lateral amygdala (LA) and ameliorated stress responses to an auditory conditioned stimulus (CS) in a fear-conditioned Wistar subject rat. Subsequent analyses suggested that activation of the posterior complex of the anterior olfactory nucleus (AOP) is responsible for the suppression of the LA. However, it remains unclear how the AOP suppresses the LA. To clarify this issue, a fear-conditioned Wistar subject was exposed to the CS either alone or with a Wistar associate. We also prepared a fear-conditioned Wistar subject that was tested with a Fischer344 (F344) associate as an additional control because F344 associates do not induce social buffering. We found that the presence of a Wistar associate induced a reduction of behavioral responses and Fos expression in the paraventricular nucleus of the hypothalamus (PVN) of the subject. Although Fos expression in the AOP was increased, the expression was not biased towards the GABAergic cells. In addition, Fos expression in the lateral intercalated cell mass of the amygdala (lITC) was increased. In contrast, the presence of a F344 associate did not affect Fos expression in subjects’ PVN or lITC, whereas behavioral responses were slightly reduced. These results suggest that the lITC was activated during social buffering. Based on these findings, we propose that the AOP indirectly suppresses the LA by activating the lITC.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP