Trend analysis of variations in carbon stock using stock big data

Changes in land use affect the terrestrial carbon stock through changes in the land cover. Research on land use and analysis of variations in carbon stock have practical applications in the optimization of land use and the mitigation of climate change effects. This study was conducted in Baixiang and Julu counties in the Taihang Piedmont by employing the trend analysis method to characterize the variation in county land use and carbon stock. The findings show that in both counties, agricultural and unused land areas decreased while built-up land area increased, and the reduction in cropland was the main reason behind the agricultural land reduction. An inflection point appeared on the cropland curves of Julu, because the cropland area decreased by 1576.97 hm\(^{2}\) from 2004 to 2006. Cropland area in Baixiang decreased from 1996 to 1998 by a total of 129.89 hm\(^{2}\) and then remained relatively stable after 1998. The total carbon storage and variation in land use in the two counties displayed similar trends. Total carbon reserves in Julu increased by 2.76 \(\times \) 10\(^{4}\) tC (carbon equivalent), while those in Baixiang decreased by 0.63 \(\times \) 10\(^{4}\) tC. Carbon stock of built-up land in Julu and Baixiang increased by 2.44 \(\times \) 10\(^{4}\) and 1.22 \(\times \) 10\(^{4}\) tC, respectively.     

LPC$$_\mathrm{}$$: A local power controller using the frequency scheduling approach for virtualized servers

For more than a decade, the power consumption of data centers has been addressed from different perspectives. Many solutions have been proposed to reduce (or optimize) this power consumption, such as controlling the operation of the servers in data centers. However, these approaches have not yet reached their optimum goals. Existing power control solutions using CPU frequency with an ad hoc or frequency modulator approach are not sufficient. In this paper, we review the power consumption effects of different configuration settings applied to the server’s CPU. We propose our local power controller using frequency scheduling (LPC\(_\mathrm{FreqSchd}\)), which is a server-level power controller that depends on an extended gain scheduling technique. Our proposed LPC\(_\mathrm{FreqSchd}\) considers the impact of different CPU configuration settings that are typically not considered simultaneously, such as the allocated CPU credits and CPU frequency level. Through a real experimental test bed, our LPC\(_\mathrm{FreqSchd}\) exhibits effective power management of different types of machines and outperforms other existing approaches, such as ad hoc and frequency modulation, when the power budget is low. Moreover, our proposed LPC\(_\mathrm{FreqSchd}\) has a very lightweight control actuation overhead compared with other approaches: approximately \(1/10 \mathrm{th}\) of the ad hoc approach’s overhead and \(1/100 \mathrm{th}\) of the frequency modulator approach’s overhead. This lightweight control actuation overhead reduces the power consumption overhead caused by the controller, and it could be used by other controllers, such as performance or thermal controllers running on the same server.     

Cellular mechanosensitivity to substrate stiffness decreases with increasing dissimilarity to cell stiffness

Computational modelling has received increasing attention to investigate multi-scale coupled problems in micro-heterogeneous biological structures such as cells. In the current study, we investigated for a single cell the effects of (1) different cell-substrate attachment (2) and different substrate modulus \(\textit{E}_\mathrm{s}\) on intracellular deformations. A fibroblast was geometrically reconstructed from confocal micrographs. Finite element models of the cell on a planar substrate were developed. Intracellular deformations due to substrate stretch of \(\lambda =1.1\), were assessed for: (1) cell-substrate attachment implemented as full basal contact (FC) and 124 focal adhesions (FA), respectively, and \(\textit{E}_\mathrm{s}\,=\,\)140 KPa and (2) \(\textit{E}_\mathrm{s}\,=\,10\), 140, 1000, and 10,000 KPa, respectively, and FA attachment. The largest strains in cytosol, nucleus and cell membrane were higher for FC (1.35\(\text {e}^{-2}\), 0.235\(\text {e}^{-2}\) and 0.6\(\text {e}^{-2}\)) than for FA attachment (0.0952\(\text {e}^{-2}\), 0.0472\(\text {e}^{-2}\) and 0.05\(\text {e}^{-2}\)). For increasing \(\textit{E}_\mathrm{s}\), the largest maximum principal strain was 4.4\(\text {e}^{-4}\), 5\(\text {e}^{-4}\), 5.3\(\text {e}^{-4}\) and 5.3\(\text {e}^{-4}\) in the membrane, 9.5\(\text {e}^{-4}\), 1.1\(\text {e}^{-4}\), 1.2\(\text {e}^{-3}\) and 1.2\(\text {e}^{-3}\) in the cytosol, and 4.5\(\text {e}^{-4}\), 5.3\(\text {e}^{-4}\), 5.7\(\text {e}^{-4}\) and 5.7\(\text {e}^{-4}\) in the nucleus. The results show (1) the importance of representing FA in cell models and (2) higher cellular mechanical sensitivity for substrate stiffness changes in the range of cell stiffness. The latter indicates that matching substrate stiffness to cell stiffness, and moderate variation of the former is very effective for controlled variation of cell deformation. The developed methodology is useful for parametric studies on cellular mechanics to obtain quantitative data of subcellular strains and stresses that cannot easily be measured experimentally.     

The effective elastic properties of human trabecular bone may be approximated using micro-finite element analyses of embedded volume elements

Boundary conditions (BCs) and sample size affect the measured elastic properties of cancellous bone. Samples too small to be representative appear stiffer under kinematic uniform BCs (KUBCs) than under periodicity-compatible mixed uniform BCs (PMUBCs). To avoid those effects, we propose to determine the effective properties of trabecular bone using an embedded configuration. Cubic samples of various sizes (2.63, 5.29, 7.96, 10.58 and 15.87 mm) were cropped from \(\mu \hbox {CT}\) scans of femoral heads and vertebral bodies. They were converted into \(\mu \hbox {FE}\) models and their stiffness tensor was established via six uniaxial and shear load cases. PMUBCs- and KUBCs-based tensors were determined for each sample. “In situ” stiffness tensors were also evaluated for the embedded configuration, i.e. when the loads were transmitted to the samples via a layer of trabecular bone. The Zysset–Curnier model accounting for bone volume fraction and fabric anisotropy was fitted to those stiffness tensors, and model parameters \(\nu _{0}\) (Poisson’s ratio) \(E_{0}\) and \(\mu _{0}\) (elastic and shear moduli) were compared between sizes. BCs and sample size had little impact on \(\nu _{0}\). However, KUBCs- and PMUBCs-based \(E_{0}\) and \(\mu _{0}\), respectively, decreased and increased with growing size, though convergence was not reached even for our largest samples. Both BCs produced upper and lower bounds for the in situ values that were almost constant across samples dimensions, thus appearing as an approximation of the effective properties. PMUBCs seem also appropriate for mimicking the trabecular core, but they still underestimate its elastic properties (especially in shear) even for nearly orthotropic samples.     

Glutathione <Emphasis Type="BoldItalic">S</Emphasis>-transferase P1 gene polymorphisms and susceptibility to coronary artery disease in a subgroup of north Indian population

The present study aimed to investigate the association of \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) and \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) polymorphisms of GSTP1 with coronary artery disease (CAD) in a subgroup of north Indian population. In the present case–control study, CAD patients (\(n = 200\)) and age-matched, sex-matched and ethnicity-matched healthy controls (\(n = 200\)) were genotyped for polymorphisms in GSTP1 using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Genotype distribution of \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) and \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) polymorphisms of GSTP1 gene was significantly different between cases and controls (\(P = 0.005\) and 0.024, respectively). Binary logistic regression analysis showed significant association of A/G (odds ratio (OR): 1.6, 95% CI: 1.08–2.49, \(P = 0.020\)) and G/G (OR: 3.1, 95% CI: 1.41–6.71, P \(=\) 0.005) genotypes of GSTP1 \(\hbox {g}.313\hbox {A}{\!>\!}\hbox {G}\), and C/T (OR: 5.8, 95% CI: 1.26–26.34, \(P = 0.024\)) genotype of GSTP1 \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) with CAD. The A/G and G/G genotypes of \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) and C/T genotype of \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) conferred 6.5-fold increased risk for CAD (OR: 6.5, 95% CI: 1.37–31.27, \(P = 0.018\)). Moreover, the recessive model of GSTP1 \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) is the best fit inheritance model to predict the susceptible gene effect (OR: 2.3, 95% CI: 1.11–4.92, \(P = 0.020\)). In conclusion, statistically significant associations of GSTP1 \(\hbox {g}.313\hbox {A}{>}\hbox {G}\) (A/G, G/G) and \(\hbox {g}.341\hbox {C}{>}\hbox {T}\) (C/T) genotypes with CAD were observed.     

Prediction of heterosis in rice based on divergence of morphological and molecular markers

Identifying the best performing hybrid without a field test was essential to save resources and time. In this study, the genetic divergence was estimated using morphological and expressed sequence tag (EST)-derived simple sequence repeats (SSR) markers. Cluster analysis showed that APMS6A and RPHR 1005 belong to groups I and II, respectively, and the hybrid combination recorded the highest mean grain yield of 32.25 g among generated 40 \(\hbox {F}_{1}\hbox {s}\) with standard heterosis of 8.4% over hybrid check, KRH2. The coefficient of marker polymorphism (CMP) value was calculated based on EST-SSR markers; it ranged from 0.40 to 0.80, and a higher CMP value of 0.80 was obtained for the parental combination APMS6A \(\times \) RPHR1005. We predicted heterosis for 40 \(\hbox {F}_{1}\hbox {s}\) based on correlation between CMP and standard heterosis in different traits with standard varietal and hybrid checks indicating positive correlation and significant value for grain yield per plant (\(r=0.58\)**), productivity per day (\(r=0.54\)**), productive tillers (\(r=0.34\)*) and panicle weight (\(r=0.42\)**). This study revealed that the relationship of molecular marker heterozygosity, along with the combining ability, high mean value of different traits, grouping of parental lines based on morphological and molecular characterization is helpful to identify heterotic patterns in rice.     

A new indicator-based many-objective ant colony optimizer for continuous search spaces

In this paper, we propose a novel multi-objective ant colony optimizer (called iMOACO\(_{\mathbb {R}}\)) for continuous search spaces, which is based on ACO\(_{\mathbb {R}}\) and the R2 performance indicator. iMOACO\(_{\mathbb {R}}\) is the first multi-objective ant colony optimizer (MOACO) specifically designed to tackle continuous many-objective optimization problems (i.e., multi-objective optimization problems having four or more objectives). Our proposed iMOACO\(_{\mathbb {R}}\) is compared to three state-of-the-art multi-objective evolutionary algorithms (NSGA-III, MOEA/D and SMS-EMOA) and a MOACO algorithm called MOACO\(_{\mathbb {R}}\) using standard test problems and performance indicators taken from the specialized literature. Our experimental results indicate that iMOACO\(_{\mathbb {R}}\) is very competitive with respect to NSGA-III and MOEA/D and it is able to outperform SMS-EMOA and MOACO\(_{\mathbb {R}}\) in most of the test problems adopted.     

Joint non-uniform sampling of all incremented time delays for quicker acquisition in protein relaxation studies

NMR relaxometry plays crucial role in studies of protein dynamics. The measurement of longitudinal and transverse relaxation rates of \(^{15}\)N is the main source of information on backbone motions. However, even the most basic approach exploiting a series of \(^{15}\)N HSQC spectra can require several hours of measurement time. Standard non-uniform sampling (NUS), i.e. random under-sampling of indirect time domain, typically cannot reduce this by more than 2–4\(\times\) due to relatively low “compressibility” of these spectra. In this paper we propose an extension of NUS to relaxation delays. The two-dimensional space of \(t_1\)/\(t_{relax}\) is sampled in a way similar to NUS of \(t_1\)/\(t_2\) domain in 3D spectra. The signal is also processed in a way similar to that known from 3D NUS spectra i.e. using one of the most popular compressed sensing algorithms, iterative soft thresholding. The 2D Fourier transform matrix is replaced with mixed inverse Laplace-Fourier transform matrix. The peak positions in resulting 3D spectrum are characterized by two frequency coordinates and relaxation rate and thus no additional fitting of exponential curves is required. The method is tested on three globular proteins, providing satisfactory results in a time corresponding to acquisition of two conventional \(^{15}\)N HSQC spectra.     

Towards the prediction of flow-induced shear stress distributions experienced by breast cancer cells in the lymphatics

Tumour metastasis in the lymphatics is a crucial step in the progression of breast cancer. The dynamics by which breast cancer cells (BCCs) travel in the lymphatics remains poorly understood. The goal of this work is to develop a model capable of predicting the shear stresses metastasising BCCs experience using numerical and experimental techniques. This paper models the fluidic transport of large particles (\(\eta =d_{\mathrm{p}}/W=0.1-0.4\) where \(d_{\mathrm{p}}\) is the particle diameter and W is the channel width) subjected to lymphatic flow conditions (\({ Re}=0.04\)), in a \(100\times 100\,\upmu \hbox {m}\) microchannel. The feasibility of using the dynamic fluid body interaction (DFBI) method to predict particle motion was assessed, and particle tracking experiments were performed. The experiments found that particle translational velocity decreased from the undisturbed fluid velocity with increasing particle size (5–14% velocity lag for \(\eta =0.1-0.3\)). DFBI simulations were found to better predict particle behaviour than theoretical predictions; however, mesh restrictions in the near-wall region (\(0.2\,\mathrm{W}>y>0.8\,\mathrm{W}\)) result in computationally expensive models. The simulations were in good agreement with the experiments (\(<12\%\) difference) across the channel (\(0.2\,\mathrm{W}\le y\le 0.8\,\mathrm{W}\)), with differences up to 25% in the near-wall region. Particles experience a range of shear stresses (0.002–0.12 Pa) and spatial shear gradients (\(0.004-0.137\,\hbox {Pa}/\upmu \hbox {m}\)) depending on their size and radial position. The predicted shear gradients are far in excess of values associated with BCC apoptosis (\(0.004-0.023\,\hbox {Pa}/\upmu \hbox {m}\)). Increasing our understanding of the shear stress magnitudes and gradients experienced by BCCs could be leveraged to elucidate whether a particular BCC size or location exists that encourages metastasis within the lymphatics.     

Optimal Therapy Scheduling Based on a Pair of Collaterally Sensitive Drugs

Despite major strides in the treatment of cancer, the development of drug resistance remains a major hurdle. One strategy which has been proposed to address this is the sequential application of drug therapies where resistance to one drug induces sensitivity to another drug, a concept called collateral sensitivity. The optimal timing of drug switching in these situations, however, remains unknown. To study this, we developed a dynamical model of sequential therapy on heterogeneous tumors comprised of resistant and sensitive cells. A pair of drugs (DrugA, DrugB) are utilized and are periodically switched during therapy. Assuming resistant cells to one drug are collaterally sensitive to the opposing drug, we classified cancer cells into two groups, \(A_\mathrm{R}\) and \(B_\mathrm{R}\), each of which is a subpopulation of cells resistant to the indicated drug and concurrently sensitive to the other, and we subsequently explored the resulting population dynamics. Specifically, based on a system of ordinary differential equations for \(A_\mathrm{R}\) and \(B_\mathrm{R}\), we determined that the optimal treatment strategy consists of two stages: an initial stage in which a chosen effective drug is utilized until a specific time point, T, and a second stage in which drugs are switched repeatedly, during which each drug is used for a relative duration (i.e., \(f \Delta t\)-long for DrugA and \((1-f) \Delta t\)-long for DrugB with \(0 \le f \le 1\) and \(\Delta t \ge 0\)). We prove that the optimal duration of the initial stage, in which the first drug is administered, T, is shorter than the period in which it remains effective in decreasing the total population, contrary to current clinical intuition. We further analyzed the relationship between population makeup, \(\mathcal {A/B} = A_\mathrm{R}/B_\mathrm{R}\), and the effect of each drug. We determine a critical ratio, which we term \(\mathcal {(A/B)}^{*}\), at which the two drugs are equally effective. As the first stage of the optimal strategy is applied, \(\mathcal {A/B}\) changes monotonically to \(\mathcal {(A/B)}^{*}\) and then, during the second stage, remains at \(\mathcal {(A/B)}^{*}\) thereafter. Beyond our analytic results, we explored an individual-based stochastic model and presented the distribution of extinction times for the classes of solutions found. Taken together, our results suggest opportunities to improve therapy scheduling in clinical oncology.     

Potential use of sulfite as a supplemental electron donor for wastewater denitrification

Biological denitrification typically requires the addition of a supplemental electron donor, which can add a significant operating expense to wastewater treatment facilities. Most common electron donors are organic, but reduced inorganic sulfur compounds (RISCs), such as sulfide (HS^?) and elemental sulfur (S⁰), may be more cost-effective. S⁰ is an inexpensive and well characterized electron donor, but it provides slow denitrification rates due to its low solubility. A lesser-known RISC is sulfite (\({\text{SO}}_{3}^{2 - }\)), which can be easily produced from S⁰ by a simple combustion process. Unlike S⁰, \({\text{SO}}_{3}^{2 - }\) is highly soluble, and therefore may provide higher denitrification rates. However, very little is known about microbial denitrification with \({\text{SO}}_{3}^{2 - }\). Also, \({\text{SO}}_{3}^{2 - }\) is a strong reductant that reacts abiotically with oxygen and has toxic effects on microorganisms. This paper reviews \({\text{SO}}_{3}^{2 - }\) in the environment, \({\text{SO}}_{3}^{2 - }\) chemistry, microbiology, toxicity, and its potential use for denitrification. Since \({\text{SO}}_{3}^{2 - }\) is an intermediate in the sulfur oxidation pathway of most sulfur-oxidizing microorganisms, it is an energetic electron donor and it should select for a \({\text{SO}}_{3}^{2 - }\)-oxidizing community. Our review of the literature, as well as our own lab experience, suggests that \({\text{SO}}_{3}^{2 - }\) can effectively serve as an electron donor for denitrification. Further research is needed to determine the kinetics of \({\text{SO}}_{3}^{2 - }\)-based denitrification, its toxic threshold for sulfur-oxidizing microorganisms, and its potential inhibition of sensitive species such as nitrifying microorganisms and potential formation of nitrous oxide. Its effect on sludge settling efficiency also should be explored.     

Isolation and characterization of microsatellite markers in the spiny lobster, <Emphasis Type="Italic">Panulirus echinatus</Emphasis> Smith, 1869 (Decapoda: Palinuridae) by Illumina MiSeq sequencing

Okra’s (Abelmoschus esculentus (L.) Moench) commercial cultivation is threatened in the tropics due to high incidence of yellow vein mosaic virus (YVMV) disease. Okra geneticists across the world tried to understand the inheritance pattern of YVMV disease tolerance without much success. Therefore, the inheritance pattern of YVMV disease in okra was revisited by employing six generations (\(\hbox {P}_{1}\), \(\hbox {P}_{2}\), \(\hbox {F}_{1}\), \(\hbox {F}_{2}\), \(\hbox {BC}_{1}\) and \(\hbox {BC}_{2}\)) of four selected crosses (one tolerant \(\times \) tolerant, two tolerant \(\times \) susceptible and one susceptible \(\times \) susceptible) using two tolerant (BCO-1 and Lal Bhendi) and two susceptible (Japanese Jhar Bhendi and PAN 2127) genotypes. Qualitative genetic analysis was done on the basis of segregation pattern of tolerant and susceptible plants in \(\hbox {F}_{2}\) and backcross generations of all the four crosses. It revealed that a single dominant gene along with some minor factors governed the disease tolerant trait in both the tolerant parents used. However, it was observed that genes governing disease tolerance identified in both the tolerant variety used was different. It could be concluded that the gene governing YVMV disease tolerance in okra was genotype specific. Further, duplicate gene action as evident from an approximate ratio of 15 : 1 (tolerant : susceptible) in the \(\hbox {F}_{2}\) population in the cross of two tolerant varieties gave a scope of increasing the tolerance level of the hybrid plants when both the tolerant genes are brought together. However, generation mean analysis revealed involvement of both additive and nonadditive effects in the inheritance of disease tolerance. Thus, the present study confirms that a complicated genetic inheritance pattern is involved in the disease tolerance against YVMV trait. The major tolerance genes could be transferred to other okra varieties, but the tolerance breaking virus strains might not allow them to achieve tolerance in stable condition. Therefore, accumulation of additional genes may be needed for a sustainable tolerance phenotype in okra.     

Improved identifiability of myocardial material parameters by an energy-based cost function

Myocardial stiffness is a valuable clinical biomarker for the monitoring and stratification of heart failure (HF). Cardiac finite element models provide a biomechanical framework for the assessment of stiffness through the determination of the myocardial constitutive model parameters. The reported parameter intercorrelations in popular constitutive relations, however, obstruct the unique estimation of material parameters and limit the reliable translation of this stiffness metric to clinical practice. Focusing on the role of the cost function (CF) in parameter identifiability, we investigate the performance of a set of geometric indices (based on displacements, strains, cavity volume, wall thickness and apicobasal dimension of the ventricle) and a novel CF derived from energy conservation. Our results, with a commonly used transversely isotropic material model (proposed by Guccione et al.), demonstrate that a single geometry-based CF is unable to uniquely constrain the parameter space. The energy-based CF, conversely, isolates one of the parameters and in conjunction with one of the geometric metrics provides a unique estimation of the parameter set. This gives rise to a new methodology for estimating myocardial material parameters based on the combination of deformation and energetics analysis. The accuracy of the pipeline is demonstrated in silico, and its robustness in vivo, in a total of 8 clinical data sets (7 HF and one control). The mean identified parameters of the Guccione material law were \(C_1=3000\pm 1700\,\hbox {Pa}\) and \(\alpha =45\pm 25\) (\(b_f=25\pm 14\), \(b_{ft}=11\pm 6\), \(b_{t}=9\pm 5\)) for the HF cases and \(C_1=1700\,\hbox {Pa}\) and \(\alpha =15\) (\(b_f=8\), \(b_{ft}=4\), \(b_{t}=3\)) for the healthy case.     

Backbone resonance assignments for the SET domain of the human methyltransferase NSD2

Aberrant NSD2 methyltransferase activity is implicated as the oncogenic driver in multiple myeloma, suggesting opportunities for novel therapeutic intervention. The methyltransferase activity of NSD2 resides in its catalytic SET domain, which is conserved among most lysine methyltransferases. Here we report the backbone \(\hbox {H}^{\mathrm{N}}\), N, C\(^{\prime }\), \(\hbox {C}^\alpha\) and side-chain \(\hbox {C}^\beta\) assignments of a 25 kDa NSD2 SET domain construct, spanning residues 991–1203. A chemical shift analysis of C\(^{\prime }\), \(\hbox {C}^\alpha\) and \(\hbox {C}^\beta\) resonances predicts a secondary structural pattern that is in agreement with homology models.     

Failure properties of vena cava tissue due to deep penetration during filter insertion

In this work, we use an in-vitro mechanical test to explore the resistance of biaxially stretched vena cava tissue against deep perforation and a methodology which integrates experimental and numerical modeling to identify constitutive fracture properties of the vena cava. Six sheep vena cava were harvested just after killing, and cyclic uniaxial tension tests in longitudinal and circumferential directions and biaxial deep penetration tests were performed. After that, we use a nonlinear finite element model to simulate in vitro penetration of the cava tissue in order to fit the fracture properties under penetration of the vena cava by defining a cohesive fracture zone. An iterative process was developed in order to fit the fracture properties of the vena cava using the previously obtained experimental results. The proposed solutions were obtained with fracture energy of 0.22 or 0.33 N/mm. In comparison with the experimental data, the simulation using \(\delta _{0}=0.01\,\hbox {mm}\), \(\delta _{r}=0.35\,\hbox {mm}\), and \(K=220\, \hbox {N}/\hbox {mm}^{3}\) parameters (\(F_{\hbox {max}}=0.92\)) is in good agreement with results from penetration experiments of cava tissue. It is noticeable that the parameter estimation process of the fracture behavior is more accurate than the estimation process of the elastic behavior for the toe region of the curve.     

Cell Volume Regulation in the Proximal Tubule of Rat Kidney

We developed a dynamic model of a rat proximal convoluted tubule cell in order to investigate cell volume regulation mechanisms in this nephron segment. We examined whether regulatory volume decrease (RVD), which follows exposure to a hyposmotic peritubular solution, can be achieved solely via stimulation of basolateral K\(^+\) and \(\hbox {Cl}^-\) channels and \(\hbox {Na}^+\)–\(\hbox {HCO}_3^-\) cotransporters. We also determined whether regulatory volume increase (RVI), which follows exposure to a hyperosmotic peritubular solution under certain conditions, may be accomplished by activating basolateral \(\hbox {Na}^+\)/H\(^+\) exchangers. Model predictions were in good agreement with experimental observations in mouse proximal tubule cells assuming that a 10% increase in cell volume induces a fourfold increase in the expression of basolateral K\(^+\) and \(\hbox {Cl}^-\) channels and \(\hbox {Na}^+\)–\(\hbox {HCO}_3^-\) cotransporters. Our results also suggest that in response to a hyposmotic challenge and subsequent cell swelling, \(\hbox {Na}^+\)–\(\hbox {HCO}^-_3\) cotransporters are more efficient than basolateral K\(^+\) and \(\hbox {Cl}^-\) channels at lowering intracellular osmolality and reducing cell volume. Moreover, both RVD and RVI are predicted to stabilize net transcellular \(\hbox {Na}^+\) reabsorption, that is, to limit the net \(\hbox {Na}^+\) flux decrease during a hyposmotic challenge or the net \(\hbox {Na}^+\) flux increase during a hyperosmotic challenge.     

Effects of tunable excitation in carotenoids explained by the vibrational energy relaxation approach

Carotenoids are fundamental building blocks of natural light harvesters with convoluted and ultrafast energy deactivation networks. In order to disentangle such complex relaxation dynamics, several studies focused on transient absorption measurements and their dependence on the pump wavelength. However, such findings are inconclusive and sometimes contradictory. In this study, we compare internal conversion dynamics in \(\beta\)-carotene, pumped at the first, second, and third vibronic progression peak. Instead of employing data fitting algorithms based on global analysis of the transient absorption spectra, we apply a fully quantum mechanical model to treat the high-frequency symmetric carbon–carbon (C=C and C–C) stretching modes explicitly. This model successfully describes observed population dynamics as well as spectral line shapes in their time-dependence and allows us to reach two conclusions: Firstly, the broadening of the induced absorption upon excess excitation is an effect of vibrational cooling in the first excited state (\(S_{1}\)). Secondly, the internal conversion rate between the second excited state (\(S_{2}\)) and \(S_{1}\) crucially depends on the relative curve displacement. The latter point serves as a new perspective on solvent- and excitation wavelength-dependent experiments and lifts contradictions between several studies found in literature.