Site-specific Level Research Articles

MEDOC: A fast, scalable and mathematically exact algorithm for the site-specific prediction of the protonation degree in large disordered proteins.

Intrinsically disordered regions are found in most eukaryotic proteins and are enriched in positively and negatively charged residues. While it is often convenient to assume these residues follow their model-compound pK a values, recent work has shown that local charge effects (charge regulation) can upshift or downshift sidechain pK a values with major consequences for molecular function. Despite this, charge regulation is rarely considered when investigating disordered regions. The number of potential charge microstates that can be populated through acid/base regulation of a given number of ionizable residues in a sequence, N , scales as ∼2 N . This exponential scaling makes the assessment of the full charge landscape of most proteins computationally intractable. To address this problem, we developed MEDOC (Multisite Extent of Deprotonation Originating from Context) to determine the degree of protonation of a protein based on the local sequence context of each ionizable residue. We show that we can drastically reduce the number of parameters necessary to determine the full, analytic, Boltzmann partition function of the charge landscape at both global and site-specific levels. Our algorithm applies the structure of the q -canonical ensemble, combined with novel strategies to rapidly obtain the minimal set of parameters, thereby circumventing the combinatorial explosion of the number of charge microstates even for proteins containing a large number of ionizable amino acids. We apply MEDOC to several sequences, including a global analysis of the distribution of pK a values across the entire DisProt database. Our results show differences in the distribution of predicted pK a values for different amino acids, in agreement with NMR-measured distributions in proteins.

Generic and site-specific social life cycle assessment of municipal wastewater treatment systems in Spain: challenges and limitations of the method when applied to resource recovery systems

Abstract Purpose This work aims to provide insights on the application of social life cycle assessment (S-LCA) in evaluating the social impacts associated with municipal wastewater treatment (WWT). The study assesses the social risks and social performance of two municipal WWT systems in Catalonia, Spain: a conventional wastewater treatment plant (WWTP) (Reference System) and a novel system that recovers water and other valuable resources (Novel System). Methods S-LCA was conducted at Generic and Site-Specific levels using 1 m3 of wastewater treatment as the functional unit (FU). The Generic assessment was conducted via the Product Social Impact Life Cycle Assessment (PSILCA) database, while the Site-Specific assessment employed the Subcategory Assessment Method (SAM) with four-level reference scales to assess the social performance of the WWTP operator and its first-tier suppliers. Furthermore, activity variables were calculated based on organizations’ shares in the total costs per FU, and the Novel System’s multifunctionality was solved through economic allocation. Results were aggregated by (i) assigning equal weights to organizations and (ii) factoring in organizations’ weights and the allocation factor, leading to results per FU. Results and discussion The Generic analysis results indicated that the Novel System entailed fewer social risks than the Reference System. Most social risks in both systems occurred in the subcategories “Access to material resources,” “Fair salary,” “Freedom of association and collective bargaining,” “Contribution to economic development,” and “Corruption.” In the Site-Specific assessment, the Novel System presented better social performance than the Reference System per 1 m3 of wastewater treatment. The latter’s performance per FU did not meet the basic requirement in four out of eleven subcategories, mainly due to the performance and weight of a chemical supplier. Allocation greatly benefitted the Novel System’s results per FU compared to the results obtained when equal weights were applied. Conclusions Activity variables were used to connect organizations’ conduct with particular WWT systems, and multifunctionality was solved. This approach allowed for obtaining results per FU at both assessment levels. However, social performance was also evaluated by calculating the average social performance of each system without considering activity variables and the FU, leading to different results. The social performance of the Novel System per FU was satisfactory across all subcategories but required improvement in four subcategories based on the average results. Given the limitations of using activity variables and allocation in S-LCA, further research is necessary to appropriately evaluate and compare the social effects of novel resource recovery systems.

Tissue resident memory CD4 + T cells are sustained by site-specific levels of self-renewal and replacement from precursors.

Tissue-resident memory T cells (T RM ) protect from repeated infections within organs and barrier sites. The breadth and duration of such protection is defined at minimum by three quantities; the rate at which new T RM are generated from precursors, their rate of self-renewal, and their loss rate through death, egress, or differentiation. Quantifying these processes in isolation is challenging. Here we combine genetic fate mapping tools and mathematical models to untangle these basic homeostatic properties of CD4 + T RM in skin and lamina propria (LP) of healthy adult mice. We show that CD69 + CD4 + T RM in skin reside for ∼ 24 days and self-renew more slowly, such that clones halve in size approximately every 5 weeks; and approximately 2% of cells are replaced daily from precursors. CD69 + CD4 + T RM in LP have shorter residencies ( ∼ 14 days) and are maintained largely by immigration (4-6% per day). We also find evidence that the constitutive replacement of CD69 + CD4 + T RM at both sites derives from circulating effectormemory CD4 + T cells, in skin possibly via a CD69 - intermediate. Our integrated approach maps the ontogeny of CD4 + T RM in skin and LP and exposes their dynamic and distinct behaviours, with continual seeding and erosion potentially impacting the duration of immunity at these sites.

Site-specific N-glycan alterations on haptoglobin as potential biomarkers for distinguishing intrahepatic cholangiocarcinoma from hepatocellular carcinoma

Intrahepatic cholangiocellular carcinoma (ICC) is a challenging malignancy marked by subtle early symptoms and a high mortality rate, making effective diagnostic markers crucial for early detection and improved patient outcomes. Currently, the conventional diagnosis of ICC is not easily distinguishable from Hepatocellular Carcinoma (HCC) and lacks highly specific and sensitive diagnostic markers. Protein glycosylation, pivotal in biological processes, shows promise for cancer biomarkers due to its association with disease progression. This study aims to develop a novel biomarker discovery framework for ICC utilizing site-specific quantitative N-glycoproteomics to overcome the limitations of existing diagnostic approaches. Employing a tandem mass tag (TMT)-based quantitative analysis, we profiled serum glycoproteins from ICC, HCC, and control cohorts at site-specific glycosylation level. The identified markers underwent further validation in an independent cohort using label-free quantitative methods. Ultimately, we identified five site-specific N-glycans on haptoglobin (HP) as potential biomarkers (AUC > 0.9) for distinguishing ICC from HCC. This finding represents a considerable advance over traditional biomarkers, highlighting the significance of protein glycosylation alterations in ICC pathogenesis. This research, therefore, sets a new precedent for biomarker discovery in ICC, with potential applications in other cancers characterized by glycosylation abnormalities.

Characterization of a typical urban soil in terms of natural radionuclide content. The case study of a university campus

A first comprehensive survey was carried out in a university campus in Italy in order to investigate in terms of natural elements an area where medium-high values of natural radiation are expected because of its peculiar geological features. The content of terrestrial radionuclides in 20 topsoil samples from the campus was determined with the aim to provide an important database of the soil characteristics.226Ra, 232Th, and 40K concentrations were analysed by High Purity Germanium (HPGe) gamma-ray spectrometer in order to determine the background levels of natural radionuclides characteristics of the original area. The mean concentrations of radionuclides in the investigated soil samples ranged from 58.95 ± 4.20 to 158.05 ± 19.95 Bq kg−1 for 226Ra, from 72.28 ± 7.61 to 146.00 ± 22.27 Bq kg−1 for 232Th and, for 40K, from 550.76 ± 33.24 to 1367.50 ± 18.73 Bq kg−1. The radiological hazard indices, including radium equivalent activity, external hazard index, annual effective dose, absorbed dose rate, lifetime excess cancer risk, were also evaluated and compared with global averages, revealing values above the worldwide ones. Finally, a spatial modelling methodology of the site-specific radionuclides levels as graphical tool for the monitoring of the potential land redevelopment of urban soils was proposed.

Mitochondria Transplantation: Rescuing Innate Muscle Bioenergetic Impairment in a Model of Aging and Exercise Intolerance.

Arroum, T, Hish, GA, Burghardt, KJ, Ghamloush, M, Bazzi, B, Mrech, A, Morse, PT, Britton, SL, Koch, LG, McCully, JD, Hüttemann, M, and Malek, MH. Mitochondria transplantation: Rescuing innate muscle bioenergetic impairment in a model of aging and exercise intolerance. J Strength Cond Res 38(7): 1189-1199, 2024-Mitochondria, through oxidative phosphorylation, are crucial for energy production. Disease, genetic impairment, or deconditioning can harm muscle mitochondria, affecting energy production. Endurance training enhances mitochondrial function but assumes mobility. Individuals with limited mobility lack effective treatments for mitochondrial dysfunction because of disease or aging. Mitochondrial transplantation replaces native mitochondria that have been damaged with viable, respiration-competent mitochondria. Here, we used a rodent model selectively bred for low-capacity running (LCR), which exhibits innate mitochondrial dysfunction in the hind limb muscles. Hence, the purpose of this study was to use a distinct breed of rats (i.e., LCR) that display hereditary skeletal muscle mitochondrial dysfunction to evaluate the consequences of mitochondrial transplantation. We hypothesized that the transplantation of mitochondria would effectively alleviate mitochondrial dysfunction in the hind limb muscles of rats when compared with placebo injections. In addition, we hypothesized that rats receiving the mitochondrial transplantation would experience an improvement in their functional capacity, as evaluated through incremental treadmill testing. Twelve aged LCR male rats (18 months old) were randomized into 2 groups (placebo or mitochondrial transplantation). One LCR rat of the same age and sex was used as the donor to isolate mitochondria from the hindlimb muscles. Isolated mitochondria were injected into both hindlimb muscles (quadriceps femoris, tibialis anterior (TA), and gastrocnemius complex) of a subset LCR (n = 6; LCR-M) rats. The remaining LCR (n = 5; LCR-P) subset received a placebo injection containing only the vehicle without the isolated mitochondria. Four weeks after mitochondrial transplantation, rodents were euthanized and hindlimb muscles harvested. The results indicated a significant (p < 0.05) increase in mitochondrial markers for glycolytic (plantaris and TA) and mixed (quadricep femoris) muscles, but not oxidative muscle (soleus). Moreover, we found significant (p < 0.05) epigenetic changes (i.e., hypomethylation) at the global and site-specific levels for a key mitochondrial regulator (transcription factor A mitochondrial) between the placebo and mitochondrial transplantation groups. To our knowledge, this is the first study to examine the efficacy of mitochondrial transplantation in a rodent model of aging with congenital skeletal muscle dysfunction.

Deoxynivalenol induces m6A-mediated upregulation of p21 and growth arrest of mouse hippocampal neuron cells in vitro

Hippocampal neurons maintain the ability of proliferation throughout life to support neurogenesis. Deoxynivalenol (DON) is a mycotoxin that exhibits brain toxicity, yet whether and how DON affects hippocampal neurogenesis remains unknown. Here, we use mouse hippocampal neuron cells (HT-22) as a model to illustrate the effects of DON on neuron proliferation and to explore underlying mechanisms. DON exposure significantly inhibits the proliferation of HT-22 cells, which is associated with an up-regulation of cell cycle inhibitor p21 at both mRNA and protein levels. Global and site-specific m6A methylation levels on the 3’UTR of p21 mRNA are significantly increased in response to DON treatment, whereas inhibition of m6A hypermethylation significantly alleviates DON-induced cell cycle arrest. Further mechanistic studies indicate that the m6A readers YTHDF1 and IGF2BP1 are responsible for m6A-mediated increase in p21 mRNA stability. Meanwhile, 3’UTR of E3 ubiquitin ligase TRIM21 mRNA is also m6A hypermethylated, and another m6A reader YTHDF2 binds to the m6A sites, leading to decreased TRIM21 mRNA stability. Consequently, TRIM21 suppression impairs ubiquitin-mediated p21 protein degradation. Taken together, m6A-mediated upregulation of p21, at both post-transcriptional and post-translational levels, contributes to DON-induced inhibition of hippocampal neuron proliferation. These results may provide new insights for epigenetic therapy of neurodegenerative diseases.Graphical abstractDON inhibits the proliferation of HT-22 cells.RNA m6A hypermethylation on the transcript of p21 enhances the mRNA stability in a YTHDF1- and IGF2BP1-dependent manner, which leads to the upregulation of p21.RNA m6A hypermethylation on the transcript of TRIM21 decreases the mRNA stability in a YTHDF2-dependent manner, which contributes to prevent p21 ubiquitin-mediated degradation.High expression of p21 contributes to inhibit cell proliferation.

The role of atmospheric CO2 in controlling sea surface temperature change during the Pliocene

Abstract. We present the role of CO2 forcing in controlling Late Pliocene sea surface temperature (SST) change using six models from Phase 2 of the Pliocene Model Intercomparison Project (PlioMIP2) and palaeoclimate proxy data from the PlioVAR working group. At a global scale, SST change in the Late Pliocene relative to the pre-industrial is predominantly driven by CO2 forcing in the low and mid-latitudes and non-CO2 forcing in the high latitudes. We find that CO2 is the dominant driver of SST change at the vast majority of proxy data sites assessed (17 out of 19), but the relative dominance of this forcing varies between all proxy sites, with CO2 forcing accounting for between 27 % and 82 % of the total change seen. The dearth of proxy data sites in the high latitudes means that only two sites assessed here are predominantly forced by non-CO2 forcing (such as changes to ice sheets and orography), both of which are in the North Atlantic Ocean. We extend the analysis to show the seasonal patterns of SST change and its drivers at a global scale and at a site-specific level for three chosen proxy data sites. We also present a new estimate of Late Pliocene climate sensitivity using site-specific proxy data values. This is the first assessment of site-specific drivers of SST change in the Late Pliocene and highlights the strengths of using palaeoclimate proxy data alongside model outputs to further develop our understanding of the Late Pliocene. We use the best available proxy and model data, but the sample sizes remain limited, and the confidence in our results would be improved with greater data availability.

Potassium adsorption capacity and desorption kinetics in soils of Qenberenaweti sub-watershed, central highlands of Ethiopia

Determining the supply and uptake of K nutrient and the dynamic equilibrium (adsorption-desorption) reactions among the K forms in the soils are not commonly addressed in the highlands of Ethiopia. A study was therefore initiated to determine the adsorption capacity of the exchangeable K and the release kinetics of the non-exchangeable K in the soils of the Qenberenaweti Sub-watershed. Twelve disturbed surface (0–20 cm) soil sub-samples were collected from every farmland which was representative of each pre-identified soil type (Vertic Cambisols, Pellic Vertisols, Pisoplinthic Luvisols, Relictistagnic Cambisols, Pisoplinthic Cambisols, and Plinthofractic Cambisols). A composite sample was made in duplicate for the determination of K adsorption capacity and desorption kinetics per soil type. The mean maximum (69.47 ± 4.31 %) and minimum (56.16 ± 6.04 %) K adsorption rates were obtained from the Plinthofractic Cambisols and Vertic Cambisols, respectively. Among the tested isotherm models, the goodness of the Freundlich was better fit the data of all experimental soils; hence, a modified equation of this model (qe = aCeb/a) could be used to describe the theoretical doses of K fertilizers required to develop K levels in soil solutions. The highest constant K releases from the Plinthofractic Cambisols (47 mg kg−1), Pisiopllintic Cambisols (46 mg kg−1), and Pisoplinthic Luvisols (44 mg kg−1) were attained at the 9th extraction. In comparison, it was noticed at the 7th and 11th extractions of the Relictistagnic Cambisols (45 mg kg−1) and both Pellic Vertisols (48 mg kg−1) and Vertic Cambisols (42 mg kg−1), respectively. The equation of power function was the best to successfully describe the released K+ from all the experimental soils. Eventually, determining the adsorption capacity and release kinetics of K at a site-specific level helps to know the relative potential of the soils to supply K and also plan for an effective K fertilization strategy.

Site-Specific Analysis of Core and Antenna Fucosylation on Serum Glycoproteins.

Fucosylation is an important structural feature of glycans and plays an essential role in the regulation of glycoprotein functions. Fucosylation can be classified into core- (CF) and antenna-fucosylation (AF, also known as (sialyl-) Lewis) based on the location on N-glycans, and they perform distinct biological functions. In this study, core- and antenna-fucosylated N-glycans on human serum glycoproteins that hold great clinical application values were systematically characterized at the site-specific level using StrucGP combined with the recently developed fucosylation assignment method. The results showed that fucosylation was widely distributed on serum glycoproteins, with 50% of fucosylated glycopeptides modified by AF N-glycans, 37% by CF N-glycans, and 13% by dual-fucosylated N-glycans. Interestingly, CF and AF N-glycans preferred to modify different groups of serum glycoproteins with different tissue origins and were involved in distinctive biological processes. Specifically, AF N-glycoproteins are mainly from the liver and participated in complement activation, blood coagulation, and endopeptidase activities, while CF N-glycoproteins originate from diverse tissues and are mainly involved in cell adhesion and signaling transduction. These data further enhanced our understanding of fucosylation on circulation glycoproteins.

Can machine learning models provide accurate fertilizer recommendations?

Accurate modeling of site-specific crop yield response is key to providing farmers with accurate site-specific economically optimal input rates (EOIRs) recommendations. Many studies have demonstrated that machine learning models can accurately predict yield. These models have also been used to analyze the effect of fertilizer application rates on yield and derive EOIRs. But models with accurate yield prediction can still provide highly inaccurate input application recommendations. This study quantified the uncertainty generated when using machine learning methods to model the effect of fertilizer application on site-specific crop yield response. The study uses real on-farm precision experimental data to evaluate the influence of the choice of machine learning algorithms and covariate selection on yield and EOIR prediction. The crop is winter wheat, and the inputs considered are a slow-release basal fertilizer NPK 25–6–4 and a top-dressed fertilizer NPK 17–0–17. Random forest, XGBoost, support vector regression, and artificial neural network algorithms were trained with 255 sets of covariates derived from combining eight different soil properties. Results indicate that both the predicted EOIRs and associated gained profits are highly sensitive to the choice of machine learning algorithm and covariate selection. The coefficients of variation of EOIRs derived from all possible combinations of covariate selection ranged from 13.3 to 31.5% for basal fertilization and from 14.2 to 30.5% for top-dressing. These findings indicate that while machine learning can be useful for predicting site-specific crop yield levels, it must be used with caution in making fertilizer application rate recommendations.

Evaluation of crop model-based simplified marginal net return maximising nitrogen application rates on site-specific level in maize

AbstractCrop growth models such as DSSAT-CERES-Maize have proven to be useful for analysing plant growth and yield within homogenous land units. The paper presents results of newly developed model-based site-specific Soil Profile Optimisation (SPO) tools in combination with an updated version of an already published Nitrogen Prescription Model (NPM). Site-specific soil profiles were generated through an inverse modelling approach based on measured site-specific yield (point-based) and tops weight (above-ground biomass time-series) and evaluated. Site-specific soil profiles generated based only on measured yield variability were able to explain 72% (R2 0.72) of yield variability (dependent variable) based on selected soil profile input parameters (independent variable). Site-specific soil profiles generated based on measured yield and tops variability simultaneously (multiple target variable) explained 68% of yield variability (R2 0.68). The NPM uses the SPO generated site-specific soil profiles for economic evaluation of site-specific N application rates. NPM simulated N application rates, aiming at the maximisation of marginal net return (MNR) were 25% lower compared to the uniform N application rates with an assumed grain and N price of 0.17 and 0.3 Euro kg−1 respectively, under rainfed conditions over three years based on soil profiles generated via an inverse modelling approach only from measured yield variability (one target variable). N application rates were 28% lower when based on soil profiles generated from simultaneously included grain and tops variability in the inverse modelling approach. The results highlight the importance of site-specific fertilizer management when maximising MNR.

Drug deconjugation-assisted peptide mapping by LC–MS/MS to identify conjugation sites and quantify site occupancy for antibody-drug conjugates

Antibody-drug conjugates (ADCs) are a heterogeneous mixture of conjugated species with varied drug loadings. Depending on conjugation sites, linkers and drugs can exhibit different stability as influenced by the solvent-accessibility and local charge, resulting in different ADC efficacy, pharmacokinetics, and toxicity. Conjugation site analysis is critical for ADC structural characterization to assure product quality and consistency. It enables early conjugation studies at site-specific levels, confirms the absence of unexpected products to support conjugation process development, and aids in ensuring lot-to-lot consistency for comparability studies. Peptide mapping using liquid chromatography-tandem mass spectrometry is the industry standard method for analyzing conjugation sites. However, some concerns remain for this approach as the large and hydrophobic drug moieties often result in poor MS/MS fragmentation quality and impede the identification of conjugation sites. Additionally, the ionization discrepancy between conjugated and unconjugated peptides can lead to a relatively large bias for site occupancy calculation. In this work, we present a simple drug deconjugation-assisted peptide mapping method to identify and quantify the drug conjugation for ADCs with protease-cleavable linkers. Papain-based drug deconjugation was used to remove the highly hydrophobic drug moiety, which significantly improved the quantitation accuracy of conjugation level and the fragmentation quality. Sample preparation conditions were optimized to avoid introducing artificial modifications, allowing the tracking of initial sample status and subsequent changes of quality attributes during process development and stability assessment. This method was applied to analyze thermally-stressed ADC samples to monitor changes of site-specific conjugation levels, DAR, succinimide hydrolysis of the linker, and various PTMs. We believe this is an effective and straightforward tool for conjugation site analysis while simultaneously monitoring multiple quality attributes for ADCs with protease-cleavable linkers.

An integrated analytical modeling framework for determining site-specific soil screening levels for PFAS

Soils at many contaminated sites have accumulated a significant amount of per- and polyfluoroalkyl substances (PFAS) and may require remediation to mitigate leaching to groundwater. USEPA’s current approaches for determining soil screening levels (SSLs) were developed for non-PFAS contaminants. Because many PFAS are interfacially-active with unique leaching behaviors in soils, the current non-PFAS-specific soil screening models may not be applicable. Following USEPA’s general methodology, we develop a new modeling framework representing PFAS-specific transport processes for determining site-specific SSLs for PFAS-contaminated sites. We couple a process-based analytical model for PFAS leaching in the vadose zone and a dilution factor model for groundwater in an integrated framework. We apply the new modeling framework to two typical types of contaminated sites. Comparisons with the standard USEPA SSL approach suggest that accounting for the PFAS-specific transport processes may significantly increase the SSL for some PFAS. For the range of soil properties and groundwater recharge rates examined, while SSLs determined with the new model are less than a factor of 2 different from the standard-model values for less interfacially-active shorter-chain PFAS, they are up to two orders of magnitudes greater for more interfacially-active longer-chain PFAS. The new analytical modeling framework provides an effective tool for deriving more accurate site-specific SSLs and improving site characterization and remedial efforts at PFAS-contaminated sites.

A Decision Support System That Considers Risk and Site Specificity in the Assessment of Irrigation Water Quality (IrrigWQ)

Irrigators are increasingly challenged to maintain or even increase production using less water, sometimes of poorer quality, and often from unconventional sources. This paper describes the main features of a newly developed software-based Decision Support System (DSS), with which the fitness for use (FFU) of water for irrigation (IrrigWQ) can be assessed. The assessment considers site-specific factors, several non-traditional water constituents, and the risk of negative effects. The water balance components of a cropping system and the redistribution of solutes within a soil profile are assessed with a simplified soil water balance and chemistry model. User-friendly, colour-coded output highlights the expected effects of water constituents on soil quality, crop yield and quality, and irrigation infrastructure. Because IrrigWQ uses mainly internationally accepted cause–effect relationships to assess the effect of water quality constituents, it is expected to find universal acceptance and application among users. IrrigWQ also caters for calculating so-called Water Quality Requirements (WQRs). WQRs indicate the threshold levels of water quality constituents for irrigation at specified levels of acceptability or risk. WQRs assist water resource managers in setting site-specific maximum threshold levels of water quality constituents that can be tolerated in a water source before impacting negatively on successful irrigation.

A little on the nose: A mosquito targets the nostrils of tree frogs for a blood meal

AbstractAs the females of most mosquitoes require a blood meal to provision their eggs, they can be a vector of parasites and pathogens that have profound impacts on both animal and human populations. Understanding the interactions between mosquitoes and their hosts, including animal and feeding site preferences, could thus provide valuable insights into disease transmission. In this study, we present a highly specific feeding strategy observed in a mosquito from Australia (Mimomyia elegans). Over 3 years of fieldwork, we found this mosquito feeding exclusively on the nostrils when using several amphibian species as hosts. Mosquitoes were observed initially landing on the backs of hosts before walking towards the nostrils, potentially minimizing detection and mitigating the risk of predation or defensive responses. This remarkable level of feeding site specificity suggests strong selection pressures that are causing the nostril to be the optimal location for blood extraction on amphibians. Possible explanations include the presence of thinner, more accessible skin tissue or enhanced vascular properties in the nostril region. Understanding mosquito host preferences, points of contact and feeding site specificity could provide valuable insights into disease transmission among amphibians, as mosquitoes have been identified as potential vectors of pathogens like the amphibian chytrid fungus.

Generic optimization approach of soil hydraulic parameters for site-specific model applications

Site-specific crop management is based on the postulate of varying soil and crop requirements in a field. Therefore, a field is separated into homogenous management zones, using available data to adapt management practices environment to maximize productivity and profitability while reducing environmental impacts. Due to advancing sensor technologies, crop growth and yield data on more minor scales are common, but soil data often needs to be more appropriate. Crop growth models have shown promise as a decision support tool for site-specific farming. The Decision Support System for Agrotechnology Transfer (DSSAT) is a widely used point-based model. To overcome the problem of inappropriate soil input data problem, this study introduces an external plug-in program called Soil Profile Optimizer (SPO), which uses the current DSSAT v4.8 to calibrate soil profile parameters on a site-specific level. Developed as an inverse modelling approach, the SPO can calibrate selected soil profile parameters by targeting available in-season plant data. Root Mean Square Error (RMSE) and normalized RMSE as error minimization criteria are used. The SPO was tested and evaluated by comparing different simulation scenarios in a case study of a 3-yr field trial with maize. The scenario with optimized soil profiles, conducted with the SPO, resulted in an R2 of 0.76 between simulated and observed yield and led to significant improvements compared to the scenario conducted with field scale soil profile information (R2 0.03). The SPO showed promise in using spatial plant measurements to estimate management zone scale soil parameters required for the DSSAT model.

Expression of tight junction proteins in smokers and non-smokers with generalized Stage III periodontitis.

This study aims to evaluate the gingival crevicular fluid (GCF) levels of tumor necrosis factor-α (TNF-α), zonula occludens-1 (ZO-1), occludin (Occ), and tricellulin (Tric) in periodontitis, as well as their alterations due to smoking. Tight junctions (TJ), which consist of transmembrane and cytoplasmic scaffolding proteins, connect the epithelial cells of the periodontium. Occ, claudins, junctional adhesion molecules, and Tric are transmembrane TJ proteins found at the cell membrane. The transmembrane TJ proteins and the intracellular cytoskeleton are directly linked by cytoplasmic scaffolding proteins such as ZO-1. Although the functions and locations of these molecules have been defined, their behavior in periodontal inflammation is unknown. The study included four groups: individuals with periodontal health without smoking (C; n = 31), individuals with generalized Stage III periodontitis without smoking (P; n = 28), individuals with periodontal health while smoking (CS; n = 22), and individuals with generalized Stage III periodontitis while smoking (PS; n = 18). Clinical periodontal parameters were recorded, and enzyme-linked immunosorbent assay (ELISA) was used to examine ZO-1, Occ, Tric, and TNF-α levels in GCF. In the periodontitis groups, clinical parameters were significantly higher (p < .001). The site-specific levels of TNF-α, ZO-1, Tric, and Occ in the P group were statistically higher than those in the other groups (p < .05). TNF-α, probing pocket depth (PPD), and bleeding on probing (BOP) exhibited positive correlations with all TJ proteins (p < .005). Smoking could potentially affect the levels of epithelial TJ proteins in the GCF, thereby potentially playing a significant role in the pathogenesis of the periodontal disease.

The DNA methylation landscape of the human oxytocin receptor gene (OXTR): data-driven clusters and their relation to gene expression and childhood adversity

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers reporting childhood maltreatment (CM). OXTR DNA methylation was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated in mothers. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, substantial mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study makes an important contribution to the mapping of the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to facilitate the choice of CpG sites.

Monitoring of Groundwater in a Limestone Island Aquifer Using Ambient Seismic Noise

The limestone islands of Malta face high levels of water stress due to low rainfall over a small land area and a high population density. We investigate an innovative, cost-effective approach to groundwater monitoring in an island environment by computing auto- and cross-correlations of ambient seismic noise recorded on short-period and broadband seismic stations. While borehole readings give accurate site-specific water level data of the groundwater across the islands, this technique provides a more regional approach to quantitative groundwater monitoring. We perform the moving window cross-spectral method to determine temporal changes in seismic velocity (δv/v). Comparison of the δv/v with groundwater levels from boreholes and precipitation shows comparable patterns. We find that the variations of the δv/v from auto-correlations are more pronounced than the cross-correlation, and that short-period seismic stations are also sensitive. The δv/v signal deteriorates at longer interstation distances, presumably because paths traverse complex geology. We conclude that changes in the groundwater level found beneath very small islands, even as small as 3 km2, can be detected seismically. Low-cost, easy-to-deploy seismic stations can thus act as an additional tool for groundwater monitoring, especially in places with limited natural water reservoirs, like rivers and lakes, and infrastructure.