Multivariate Principal Component Analysis Research Articles

Liming and micronutrient application improves soil properties and productivity of the groundnut‐rapeseed cropping system in an acidic Inceptisol of India's eastern Himalayas

AbstractAluminum toxicity, nutrient imbalance, and reduced microbial activity are the most limiting factors for optimum agronomic productivity in acid soils. A field study was conducted to investigate the impact of micronutrient and liming on soil properties and productivity of groundnut‐rapeseed system in an acidic Inceptisol. The impact of six micronutrient (control or no micronutrient, Zn at 5 kg ha−1, B at 1 kg ha−1, Mo at 0.5 kg ha−1, Zn + Mo, and Zn + B + Mo) and two soil amendment (furrow liming at 500 kg ha−1 and no lime addition) treatments were first tested in groundnut and theirs residual effects were assessed on soil properties of succeeding rapeseed crop. Results indicated that liming significantly improved soil pH, soil organic carbon (SOC), available N, P and K, and diethylene triamine penta acetate (DTPA)‐extractable micronutrients, soil microbial biomass C and dehydrogenase activity as compared to no‐lime. After harvesting groundnut, Mo + Zn + B treated plots maintained the highest SOC content, whereas sole B and Mo treatment had the highest SOC content after harvesting rapeseed. Further, Mo + Zn + B treated plots showed higher contents of soil DTPA‐extractable micronutrients as compared to others. The highest groundnut equivalent yield (GEY) of the cropping system (pooled data of 2 years) was obtained with Mo + Zn + B (2.12 Mg ha−1) but remained at par with Zn + Mo (2.02 Mg ha−1). Multivariate principal component analysis indicated that available P was the most prominent soil nutrient with a strong effect on GEY. The results indicated that integrated application of Zn + B + Mo along with liming improves soil properties and agronomic productivity of groundnut‐rapeseed cropping system.

Application of Lipidomics in Psychiatry: Plasma-Based Potential Biomarkers in Schizophrenia and Bipolar Disorder

In this study, we obtained a lipidomic profile of plasma samples from drug-naïve patients with schizophrenia (SZ) and bipolar disorder (BD) in comparison to healthy controls. The sample cohort consisted of 30 BD and 30 SZ patients and 30 control individuals. An untargeted lipidomics strategy using liquid chromatography coupled with high-resolution mass spectrometry was employed to obtain the lipid profiles. Data were preprocessed, then univariate (t-test) and multivariate (principal component analysis and orthogonal partial least squares discriminant analysis) statistical tools were applied to select differential lipids, which were putatively identified. Afterward, multivariate receiver operating characteristic tests were performed, and metabolic pathway networks were constructed, considering the differential lipids. Our results demonstrate alterations in distinct lipid pathways, especially in glycerophospholipids, sphingolipids and glycerolipids, between SZ and BD patients. The results obtained in this study may serve as a basis for differential diagnosis, which is crucial for effective treatment and improving the quality of life of patients with psychotic disorders.

Investigating lactation curve characteristics of dairy cows

The main goal of this study was to analysis of the main characteristics (latent variables) of lactation curve in dairy cows using multivariate Principal Component Analysis. This work used primary database from the milk production of Holstein cows (n = 238 heads) in the PJSC “Pedigree farm ‘Stepnoy’ Kamianka-Dniprovska Raion of Zaporizhzhia Oblast over a 4-yr period (2014-2017). Recording is done with an interval of 30 days for 10 test-days (TD1-TD10), i.e., TD1 is milk production recorded on milking day 30th, TD2 is day 60th, TD3 is day 90th, etc., and 305-day milk yield records (Y305) were used also. High significant correlations were found between daily milk yields for certain test-days. The Principal Component Analysis performed on the variance-correlation matrix of TD1-TD10 records are able to explain about 90.33 % of the total variance. The first principal component (PC1) explained 66.32 % of the total variance and was highly-positively correlated with TD2-TD10 records. Thus, PC1 were defined as “total milk production”. The second principal component (PC2) explained 19.06 % of the total variance and was highly-positively correlated with TD1-TD2 records and highly-negatively correlated with TD9-TD10 records. Thus, PC2 were defined as “lactation curve persistency”. Finally, the third principal component (PC3) explained 4.95 % of the total variance and was highly-positively correlated with TD1 and TD10 records and highly-negatively correlated with TD4-TD5 records. Thus, PC3 were defined as “lactation curve type”. The use of a multivariate method (namely, the PCA) for the analysis of lactation curve characteristics based on monthly test-day records gave very close results of the analysis of milk productivity in different groups of domestic animals (cattle, goats and sheep). In all cases, the first principal component (PC1) described the absolute level of milk productivity during lactation, and the second principal component (PC2) described the persistency of the lactation curve. Significant influence on the PC1-PC3 factor scores was revealed to the greatest extent for such non-genetic factors as age of cow (in lactations), year and month of calving. Of the genetic factors, the greatest influence on the shape of the lactation curve was not so much the differences between the bull lines (Bell, Valiant, Elevation, Starbuck and Chief), but differences between individual bulls within some lines.

Influence of pre‐gelatinization in conjunction with guar gum addition on texture functionality, bioactive profile, in vitro nutrient digestibility, morphology and secondary structure of protein of quality protein maize pasta

SummaryThe current investigation aimed to develop quality protein maize (QPM) specialty pasta (partial: 50% QPM and full replacement of semolina: 100% QPM) and study the influence of pre‐gelatinization in conjunction with guar gum addition (1.5% or 3%) on bio‐techno‐functional properties of pasta. Scanning electron microscopy depicted the encapsulation of swollen starch within a protective sheet developed as a result of gum addition and starch gelatinisation. The Fourier transform infrared spectra denoted a shift from crystalline towards amorphous state in starch as a consequence of partial gelatinisation. The secondary structure of protein signified a drop in the alpha‐helix structure and thereby enhanced the in vitro protein digestibility of the pregelatinised samples. Multivariate principal component analysis was utilised to validate the differences between the parameters. The overall study inferred that the QPM owned an excellent potentiality for the development of nutrient‐dense pasta by employing the functionality of gums and pre‐gelatinisation treatment.

The Effect of Drying Methods on Chemical Profiling of Zingiberaceae Herbs Production

Background: Drying method is one of the important steps in post-harvesting in herbal production in order to prolong the shelf-life of herbal medicine and to ensure the good quality. Objective: This research aimed to profile and quantify the metabolites changing using metabolomic based on 1H-NMR Spectroscopy on Curcuma and Zingiber genus due to the drying process. Material and Methods: Five species of the Curcuma and Zingiber genus were Curcuma longa L., Curcuma aeruginosa Roxb., Curcuma xanthorrhiza Roxb., Zingiber officinale Roscoe. and Zingiber amaricans BI. The drying method applied were freeze drying and oven drying method at -1080C and 500C, respectively. Samples were extracted using buffer phosphate and deuterated methanol (3:7). The analysis was performed using 1H-NMR spectroscopy 400 MHz with TSP as an internal standard. The 1H-NMR spectra were analysed with multivariate (Principal Component Analysis). Results: The relative concentrations of sucrose and fructose at 5 samples in freeze drying method showed significant higher content than those in oven drying. On the other hands, glucose was mostly significant higher concentration in oven drying at 5 samples. Fructose and sucrose were significantly higher in freeze drying method than those in oven drying in Curcuma and Zingiber genera. Relative glucose content was higher in oven drying at Curcuma genus Conclusion: Therefore, oven drying method which applied heating at 500C is an appropriate method for herbal medicine production, especially in Curcuma and Zingiber genus, for maintaining the major secondary metabolites.

Does the initial C/N ratio interfere with the performance of sewage sludge composting and cotton waste?

ABSTRACT The effects of the initial C/N ratio on the composting of sewage sludge and cotton residues are not reported in the literature. Understanding the main composting control parameters is essential for the good stabilization of these wastes. Therefore, this study sought to evaluate different initial C/N ratios for the composting of sewage sludge and cotton waste, aiming to find the ranges with the best performance for the process and quality of the final organic compost. In this sense, five mixtures of sewage sludge (S) and cotton residues (C) were prepared and composted with three replications for each treatment in a completely randomized design. Physicochemical parameters were evaluated during composting and in the final organic compounds. A Multivariate Principal Component Analysis (PCA) was applied to evaluate the agronomic quality of organic compounds. The thermal behaviour of the mixtures presented differences. The treatments 90C10S, 80C20S and 67C33S showed the highest EXI² index (3566.64, 3448.39 and 2738.89), longer duration of thermophilic phase (12 and 13 days) and better potential for maximum degradation (A) of organic matter (67.5, 61.2 and 65.6%C). The final compounds of 90C10S and 80C20S showed higher pH values (7.9 and 7.5) and higher CEC (123.6 and 114.0 meq/100 g OM). PCA showed similarity in the agronomic quality of organic compounds for 90C10S, 80C20S and 67C33S. The treatment 28C72S (initial C/N ratio of 16.6) presented final pH of 5.3 and did not meet the minimum limit required by Brazilian regulations. Initial C/N relations between 24.9 and 35.2 showed better stabilization of waste and final organic compound with better agronomic quality.

Combination of irrigation systems in several soil types using principal component analysis

This study aims to determine the effectiveness of Principal Component Analysis in evaluating irrigation systems in different soil types and to obtain information on the best method and combination of factors for rice cultivation. The study was carried out in Soppeng Regency in April-September 2019. A nested design was used with different replication of soil texture levels (S), namely sandy (S1), loam (S2), and clay (S3). The second factor was water management (W), which consists of farmers' watering practice (W1), as well as intermittent (W2), dry-wet application (W3), and semi-puddled (W4) irrigation systems. Each combination treatment was replicated three times to obtain 36 experimental units. Subsequently, observations were carried out on seven yield component parameters, analyzed with multivariate evaluation, correlation, and principal component analysis. The principal component analysis effectively assessed irrigation methods and soil types with an eigenvalue of 0.9286. The intermittent irrigation system was the best method for rice cultivation, specifically in loam and clay soils, where the latter had the best combination. These results are expected to be a basis for future studies or practical activities on the crop's cultivation

Virulence Phenotyping and Molecular Genotyping Reveal High Diversity Within and Strong Gene Flow Between the Puccinia striiformis f. sp. tritici Populations Collected from Barberry and Wheat in Shaanxi Province of China.

Emergence of new Puccinia striiformis f. sp. tritici races that overcome resistance of wheat cultivars is a challenging issue for wheat production. Although sexual reproduction of the fungus on barberry plants under field conditions in the spring in China has been reported, the diversity of the pathogen on barberry plants and the relationship to the population in wheat fields have not been determined. In the present study, two P. striiformis f. sp. tritici populations collected in western Shaanxi Province in May 2016, one from barberry plants (103 isolates) and the other from nearby wheat crops (107 isolates), were phenotyped for virulence and genotyped with simple sequence repeat (SSR) markers. The phenotypic and genotypic data of the two populations were compared to determine their relationships. A total of 120 races, including 29 previously known races (seven were shared by the two populations) and 91 new races (35 from barberry and 56 from wheat), were identified. Similarly, a total of 132 multilocus genotypes, including 51 only from barberry, 77 only from wheat, and four from both, were detected using the SSR markers. Analyses of molecular variance identified high (93%) genetic variance within populations and low but still significant variance (7%) between the populations. Nonparametric multivariate discriminant analysis of principal components and STRUCTURE analysis showed that the two populations had a close relationship with little genetic differentiation (FST = 0.038) and strong gene flow (Nm = 6.34, P = 0.001) between them. Although the analysis of linkage disequilibrium indicated clonal populations, the isolation of P. striiformis f. sp. tritici from barberry plants and the high genetic diversities in the barberry and wheat populations suggest that barberry plants provide aeciospores to infect wheat crops in the area. The information is useful for understanding stripe rust epidemiology and management of the disease.

Comparative Morphometric Analysis of the Azov Anchovy (<i>Engraulis encrasicolus maeoticus</i> Pusanov, 1926) and the Black Sea Anchovy (<i>E. encrasicolus ponticus</i> Alexandrov, 1927) Based on the Body Shape

A comparative analysis of body shape was performed on 841 specimens of anchovy collected from 21 catches from the Sea of Azov, the Kerch Strait, and the Black Sea off the Crimea and the northeastern coast of the Caucasus in 2006–2007 and 2016–2017. Twenty-three measurements between 12 homologous landmarks of the body of each specimen according to the “Truss Network System” served as characters for analysis. Fifteen characters showed significant differences between the Azov anchovy Engraulis encrasicolus maeoticus Pusa-nov, 1926 and the Black Sea anchovy E. encrasicolus ponticus Alexandrov, 1927. Specimens of the Azov subspecies had larger relative values for all characters of the head region, the height of the trunk region, the re-lative length of the bases of the dorsal and anal fins, and the height of the base of the caudal fin. Specimens of the Black Sea subspecies had a greater postdorsal length and a larger distance from the end of the dorsal fin base to the end of the anal fin base. A multivariate principal component analysis revealed the highest variabi-lity of characters of body height, which depends on the fatness of the fish and demonstrates seasonal dyna-mics. The second group combines characters that do not have a seasonal component (dimensions of the head region, lengths of the bases of the dorsal and anal fins, and postdorsal distance) and can be used for distinguishing the shape of the Azov and Black Sea anchovies. The success rate of classification of Azov and Black Sea anchovies according to the body shape measurement characters using the discriminant analysis was 83.4%.

Identification of the Backsheet Type of Silicon Photovoltaic Modules from Encapsulant Fluorescence Images

Feasibility of the identification of backsheet (BS) composition of field-aged Si photovoltaic (PV) modules based on the analysis of characteristic patterns of UV-excited fluorescence (UVF) of ethylene vinyl acetate copolymer encapsulant is shown. The approach includes BS identification by vibrational spectroscopies and the formation of a database of BS-related characteristic UVF patterns. A multivariate principal component analysis of the UVF images of unknown samples combined with the UVF pattern database allows the BS type to be identified only from UVF images. The geometric place of particular samples in the principal component plots is indicative of the general degradation status of PV modules. The proposed method can be applied for high-throughput noncontact characterization of solar PV plants.

Adaptive Sampling for Monitoring Multi-Profile Data with Within-and-between Profile Correlation

Multi-profile data can provide within-and-between profile information for efficiently modeling and monitoring system status. In practice, however, acquisition of such data requires large number of sensors, which raises various concerns and difficulties, for example, cost, energy, and data transmission bandwidth, in accessing the full data from each sensor. In this article, we propose an adaptive sampling strategy for multi-profile monitoring by using limited portion of data. The proposed sampling and monitoring scheme incorporates the within-and-between profile correlation and features the balance between random search and greedy search in identifying the most informative profiles. More specifically, the multivariate functional principal component analysis (MFPCA) is used to capture the within-and-between profile correlation, and the MFPC scores are augmented for unobservable profiles to feed into a multivariate CUSUM chart. Two properties of the proposed method for allocating sampling resources among sensors are investigated. Numerical and case studies are conducted under various scenarios to demonstrate the effectiveness of the method.

Chemical diversity of wild fennel essential oils (Foeniculum vulgare Mill.): A source of antimicrobial and antioxidant activities

This study aims to provide useful information for the evaluation of wild fennel in terms of their nutritional potential and medicinal values. It is therefore important to bio-prospect the variability of molecules production and the biological properties according to plant georaphical origin. Essential oils (EOs) obtained from leaves of 12 Foeniculum vulgare Mill. populations, growing wild in Tunisia, were analyzed by GC-MS. In addition, their antimicrobial activity was evaluated against eight pathogenic bacteria and fungi. The antioxidant potential of tested oils was evaluated by four different tests: Total antioxidant activity (TAA), DPPH, ABTS and reducing power assay (RPA). In addition, relationships between studied EOs by using Hiearchical Clustering Analysis (HCA) based on Euclidean distance matrix and the multivariate Principal Component Analysis (PCA) were provided. All EOs were found to be rich in monoterpenes hydrocarbons (41.56-63.13%) and phenylpropanoids (35.87-55.29%). Moreover, Limonene (8.40-50.34%) and Methyl Chavicol (35.87%-54.28%) were the main compounds. EOs from Zaghouan displayed the best antioxidant activity (8.5±0.05 mg GAE/g DW). While, EOs from Oued Zarga exhibited the highest DPPH radical scavenging activity (IC50 = 7.7±0.43 mg/mL), and those from Ain Ghlel and Badar regions showed the highest ABTS radical scavenging activity (IC50 = 86.86±0.23 µg/mL and 87.33±0.17 µg/mL, respectively). The most important reducing power assay was found in Ain Ghlel and Charchara EOs (EC50 of 70.46±0.17 and 71.31±0.61µg/mL respectively). Results displayed the sensitivity of the tested strains to fennel EOs especially against Gram-positive strain, and EOs from Zaghouan population exhibited the highest effect against Micrococcus luteus and Staphylococcus aureus. Overall, these results can extend our knowledge of the chemical diversity of wild fennel among geographical origin and pedoclimatic conditions indicating that Tunisian natural populations of F. vulgare had different chemotypes of EOs. In this way, the current study will provide new data and encourage the use of this plant as food. Wild fennel leaf EOs were rich in phenylpropanoids and endowed with significant antibacterial and antioxidant potential, which opens a new prospect for industrial and agronomical exploitation of this species.

Morphometric indices of native sheep breeds of the Himalayan region of India using multivariate principal component analysis.

This study was performed to analyze the morphometric traits and indices in 3000 animals of five registered sheep breeds in the Himalayan region under a multivariate approach. Data were recorded under field conditions with equal coverage of the five breeds, viz., Karnah, Gurez, Poonchi, Bakerwal and Changthangi on body length (BL), height at withers (HW), chest girth (CG), ear length (EL), and tail length (TL). Furthermore, four derived traits (indices) were studied, which included an index of body frame (IBF), an index of thorax development (ITD), a Baron-Crevat index (BCI), and an index of body weight (IBW). Multivariate principal component analysis (PCA) was undertaken on nine morphometric traits. Kaiser's criterion was used to reduce the number of principal components for further analysis and interpretation. The adequacy of sampling was evaluated using Kaiser-Meyer-Olkin (KMO) test and Bartlett's test of sphericity. The mean BL ranged from 52.15 (Changthangi) to 71.13 (Gurez). The estimates of HW, CG, EL and TL were highest in Gurez (63.49), Bakerwal (84.82), Bakerwal (7.26), and Karnah (8.18) breeds, respectively. Among the derived traits, the highest IBF was observed in the Gurez breed with an estimate of 112.22. Upon multivariate PCA on the dataset, the first four principal components were able to explain 92.117% of the total variance. The KMO test, Bartlett's test of sphericity and estimated communalities showed the appropriateness of PCA on the evaluated traits. Four eigenvalues were greater than one and were extracted for further analysis. Morphometric traits were highly correlated, except for EL and TL that showed lower correlation estimates with other traits. The Changthangi population showed the lowest estimates of BL, HW, CG and rectangular body frame. The present study ascertained important morphometric traits/indices that can help in developing selection criteria and formulating sustainable breeding and conservation plans vis-à-vis the unique sheep breeds of the temperate Himalayas.

High temperature events shape the broadscale distribution of juvenile Atlantic salmon (Salmo salar)

Abstract Summer water temperatures within many temperate rivers regularly surpass the incipient lethal temperature for juvenile Atlantic salmon (c. 27°C), causing widescale abandonment of territory in favour of areas of cooler water (thermal refuges). This study aims to highlight the influence of thermal refuges on river‐scale abundance patterns. That is, do salmon parr adjust their distribution over time according to proximity to thermal refuges? Twelve reaches (seven reference: five refuge) were chosen along a 17‐km section of the Little Southwest Miramichi River in Canada. Reaches were sampled throughout the 2011 and 2012 summer periods; high temperature events were recorded during summer 2012 but not summer 2011. Multivariate principal component analyses indicated no discernible difference in habitat characteristics between the reach‐types under normal thermal conditions. However, reaches containing a thermal refuge had a significant increase in relative abundance of parr immediately after a series of high temperature events (water temperature >26°C) in 2012 (p = 0.034). This increase in relative abundance in refuge reaches was not present during the summer of 2011 when no temperature events occurred (p = 0.088), prior to the event of 2012 (p = 0.999), or at the late autumn survey following the 2012 event (p = 0.999). Difference in temperature between refuge and mainstem reaches significantly influenced the suitability of a tributary as a thermal refuge habitat (R2 = 0.84), with preference shown for cooler refuges. River‐wide thermal heterogeneity therefore plays a critical role in survival of juvenile salmon throughout summer months and is likely to become necessary under future climate change scenarios.

Multivariate analysis applied to the evaluation of genetic variability for the physiological quality trait of common bean seeds

Abstract: Knowledge of the genetic variability and of the variables for evaluating common bean lines for the physiological seed quality trait is important for the selection of promising common bean genotypes for this trait in breeding programs. Through multivariate analysis, the objective of this study was to evaluate the efficiency of physical and physiological tests for studies of genetic variability in seeds of common bean lines. Twenty lines of common bean were evaluated for thousand-seed weight, first count, germination, tetrazolium, electrical conductivity, accelerated aging, field emergence and seedling performance. The experimental data were subjected to analysis of variance, analysis of genetic parameters and multivariate analysis of principal components. Genetic variability was observed among the common bean lines, and two groups of lines with superior physiological performance according to the germination and seed vigor tests were identified. First germination count, germination, seedling length in the field, accelerated aging and emergence speed index tests are the most promising for characterizing the physiological potential of seeds of common bean lines.

Multivariate curve Resolution-Alternating least squares coupled with Raman microspectroscopy: new insights into the kinetic response of primary oral squamous carcinoma cells to cisplatin.

Raman MicroSpectroscopy (RMS) is a powerful label-free tool to probe the effects of drugs at a cellular/subcellular level. It is important, however, to be able to extract relevant biochemical and kinetic spectroscopic signatures of the specific cellular responses. In the present study, a combination of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis (PCA) is used to analyse the RMS data for the example of exposure of primary Oral Squamous Carcinoma Cells (OSCC) to the chemotherapeutic agent cisplatin. Dosing regimens were established by cytotoxicity assays, and the effects of the drug on cellular spectral profiles were monitored from 16 to 72 hours post-exposure using an apoptosis assay, to establish the relative populations of viable (V), early (EA) and late apoptotic/dead (LA/D) cells after the drug treatment. Based on a kinetic model of the progression from V > EA > D, MCR-ALS regression analysis of the RMS responses was able to extract spectral profiles associated with each stage of the cellular responses, enabling a quantitative comparison of the response rates for the respective drug treatments. Moreover, PCA was used to compare the spectral profiles of the viable cells exposed to the drug. Spectral differences were highlighted in the early stages (16 hours exposure), indicative of the initial cellular response to the drug treatment, and also in the late stages (48-72 hours exposure), representing the cell death pathway. The study demonstrates that RMS coupled with multivariate analysis can be used to quantitatively monitor the progression of cellular responses to different drugs, towards future applications for label-free, in vitro, pre-clinical screening.

Initial proposal of a novel voltammetric sensor system for the detection of concrete carbonation by means of PCA model

The monitoring of concrete carbonation takes an important role in the structures maintenance, considering that corrosion induced by this phenomenon is one of the mainly failure causes in the Reinforcement Concrete Structures (RCS) located in industrial zones, roads and cities. Carbonation of concrete is produced by the penetration of the CO2 inside of the porous net, which is mainly combined with the Ca(OH)2 contained in the concrete pore solution producing carbonates with low solubility and eventually causing a pH drop until neutral levels. The pH drop produces the instability and final generalised destruction of the rebars passive layers, which is the step that precedes generalized corrosion. The current existing systems to detect concrete carbonation are based on potentiometric sensors to detect the pH of concrete pore solution. These have some limitations such as the interference of different reactions on the sensor surface. Considering these limitations, in this study a novel system of voltammetric Au sensors embedded in concrete for the detection of concrete carbonation was presented. In the voltammetric sensor, the potential sweep signal applied comprises the potential range where the effect of the pH variations has more influence in the sensor response. Then the response processing by means of the multivariate analysis PCA (principal component analysis) allows to manage a huge quantity of variables and to reduce the effect of the interference with other analytes, increasing the importance of the pH changes effect in the obtained data. Thus, increasing the reliability of the system to detect the concrete carbonation.

Variability in the Chemical Composition of Spring Waters in the Postomia River Catchment (Northwest Poland)

The paper presents the results of physicochemical analyses of spring waters in the Postomia River valley (Northwest Poland). Multivariate statistical methods, i.e., cluster analysis (CA) and principal component analysis (PCA) were used to assess the spatial distribution of similarities and differences in the concentrations of individual elements. Concentrations of macro elements (MEs), trace elements (TEs) and rare-earth elements (REEs) were analysed concerning the spring’s typology, land use structure and the distance from roads. The results showed that the springs waters are of the Ca2+-HCO3− and Ca2+-HCO3−-SO42− types, medium hardness and low mineralisation. The study revealed differences between valley springs and scarp-foot springs in terms of electrical conductivity and concentrations of F−, SO42−, NO3−, Mg2+, Ba, Zn, and U. Greater variability was observed between the physical and chemical conditions of the spring waters due to their location in terms of land use. Springs located in agricultural areas had lower pH values than those in other areas, and higher NO3− concentrations. The pH values and concentrations of Fe, Mo, Rb, and Th in urban areas were higher than in agricultural areas. Moreover, the concentrations of F−, Cl−, K+, Na+, Mo, Sb, Se, and Sr were higher in urban areas than in forested areas. The study shows that only HCO3− values and SO42− concentrations were related to the distance from the road network. The concentrations of Cl−, SO42−, and K+ were higher in the waters of springs located more than 50 m from the road network. The Ca and PCA analysis did not permit the identification of a single dominant origin of pollutants, suggesting an interaction of different types of pollution sources.

Identification of a Novel N7-Methylguanosine-Related LncRNA Signature Predicts the Prognosis of Hepatocellular Carcinoma and Experiment Verification.

(1) Background: It is well-known that long non-coding RNAs (lncRNAs) and N7-methylguanosine (m7G) contribute to hepatocellular carcinoma (HCC) progression. However, it remains unclear whether lncRNAs regulating m7G modification could predict HCC prognosis. Thus, we sought to explore the prognostic implications of m7G-related lncRNAs in HCC patients. (2) Methods: Prognostic M7G-related lncRNAs obtained from The Cancer Genome Atlas (TCGA) database were screened by co-expression analysis and univariate Cox regression analysis. Next, the m7G-related lncRNA signature (m7GRLSig) was conducted by Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analysis. Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) assessed the prognostic abilities of our signature. Univariate and multivariate Cox regression, nomogram, and principal component analysis (PCA) were conducted to evaluate our signature. Subsequently, we investigated the role of m7GRLSig on the immune landscape and sensitivity to drugs in HCC patients. The potential function of lncRNAs obtained from the prognostic signature was explored by in vitro experiments. (3) Results: A novel m7GRLSig was identified using seven meaningful lncRNA (ZFPM2-AS1, AC092171.2, PIK3CD-AS2, NRAV, CASC19, HPN-AS1, AC022613.1). The m7GLPSig exhibited worse survival in the high-risk group and served as an independent prognostic factor. The m7GRLSig stratification was sensitive in assessing the immune landscape and sensitivity to drugs between the high-risk and low-risk groups. Finally, in vitro experiments confirmed that the knockdown of NRAV was accompanied by the downregulation of METTL1 during HCC progression. (4) Conclusions: The m7G-related signature is a potential predictor of HCC prognosis and contributes to individualize the effective drug treatment of HCC.

HSP27–HSP40–HSP70–HSP90 pathway participated in molecular mechanism of selenium alleviating lead-caused oxidative damage and proteotoxicity in chicken Bursa of Fabricius

Lead (Pb), a toxic environmental pollutant, is hazardous to the health of humans and birds. Bursa of Fabricius (BF) is a unique organ of birds. Toxic substances can attack BF and induce proteotoxicity. Increased heat shock proteins (HSPs) can induce oxidative damage. Selenium (Se) can alleviate harmful substance-caused oxidative damage. This study aimed to investigate whether Pb can cause oxidative damage and proteotoxicity, as well as Se reverse Pb-caused chicken BF toxicity. A model of chickens treated with Se and Pb alone and in combination was established. BFs were collected on days 30, 60, and 90. H&E and qRT-PCR were performed to observe the microstructure and to detect HSP27, HSP40, HSP60, HSP70, and HSP90 mRNA levels, respectively, in BFs. Multivariate correlation analysis and principal component analysis were conducted to explore the correlation among the five HSPs. In our results, Pb caused BF damage and up-regulated the five HSPs at three time points, causing oxidative damage and proteotoxicity via HSP27–HSP40–HSP70–HSP90 pathway. Furthermore, Pb caused time-dependent stress on HSP27, HSP40, HSP60, and HSP70. In addition, Se relieved Pb-caused damage and up-regulation of HSPs. Taken together, we concluded that Se alleviated Pb-caused oxidative injury and proteotoxicity in chicken BFs via the HSP27–HSP40–HSP70–HSP90 pathway.