Principal Component Analysis Analysis Research Articles

Analysis of lipophilic fingerprints of edible wild rhubarb (Rheum ribes L.) using GC-MS combined with chemometrics

Rhubarb (Rheum ribes L.) is used globally as both a food supplement and a vegetable. The lipophilic fingerprints of wild rhubarb of Turkiye origin were investigated by gas chromatography-mass spectrometry (GC-MS) combined with chemometrics, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). GC-MS results identified a total of 72 lipophi6lic compounds, including fatty acids, fatty acid esters, simple hydrocarbons and other organics, in all parts of the plant. PCA and HCA analyses revealed intraspecific lipophilic component variation among six wild rhubarb populations, as well as significant variation among lipophilic fingerprints in leaves, fruits, flowers, and roots. Among the compounds, palmitic acid, α-linolenic acid, ethyl palmitate, ethyl oleate, linoleic acid ethyl ester and n-tetracosane were important for the overall lipophilic fingerprints of all parts of the rhubarb. These findings highlight the potential of using HCA and PCA analysis in combination with GC-MS fingerprints as an effective analytical approach.

Assessment of 'Golden Delicious' Apples Using an Electronic Nose and Machine Learning to Determine Ripening Stages.

Consumers often face a lack of information regarding the quality of apples available in supermarkets. General appearance factors, such as color, mechanical damage, or microbial attack, influence consumer decisions on whether to purchase or reject the apples. Recently, devices known as electronic noses provide an easy-to-use and non-destructive assessment of ripening stages based on Volatile Organic Compounds (VOCs) emitted by the fruit. In this study, the 'Golden Delicious' apples, stored and monitored at the ambient temperature, were analyzed in the years 2022 and 2023 to collect data from four Metal Oxide Semiconductor (MOS) sensors (MQ3, MQ135, MQ136, and MQ138). Three ripening stages (less ripe, ripe, and overripe) were identified using Principal Component Analysis (PCA) and the K-means clustering approach from various datasets based on sensor measurements in four experiments. After applying the K-Nearest Neighbors (KNN) model, the results showed successful classification of apples for specific datasets, achieving an accuracy higher than 75%. For the dataset with measurements from all experiments, an impressive accuracy of 100% was achieved on specific test sets and on the evaluation set from new, completely independent experiments. Additionally, correlation and PCA analysis showed that choosing two or three sensors can provide equally successful results. Overall, the e-nose results highlight the importance of analyzing data from several experiments performed over a longer period after the harvest of apples. There are similarities and differences in investigated VOC parameters (ethylene, esters, alcohols, and aldehydes) for less or more mature apples analyzed during autumn or spring, which can improve the determination of the ripening stage with higher predicting success for apples investigated in the spring.

Differential Chemical Components Analysis of Periplocae Cortex, Lycii Cortex, and Acanthopanacis Cortex Based on Mass Spectrometry Data and Chemometrics.

Background:Periplocae Cortex (PC), Acanthopanacis Cortex (AC), and Lycii Cortex (LC), as traditional Chinese medicines, are all dried root bark, presented in a roll, light and brittle, easy to break, have a fragrant scent, etc. Due to their similar appearances, it is tough to distinguish them, and they are often confused and adulterated in markets and clinical applications. To realize the identification and quality control of three herbs, in this paper, Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry Expression (UHPLC-QTOF-MSE) combined with chemometric analysis was used to explore the different chemical compositions. Methods: LC, AC, and PC were analyzed by UHPLC-QTOF-MSE, and the quantized MS data combined with Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were used to explore the different chemical compositions with Variable Importance Projection (VIP) > 1.0. Further, the different chemical compositions were identified according to the chemical standard substances, related literature, and databases. Results: AC, PC, and LC can be obviously distinguished in PCA and PLS-DA analysis with the VIP of 2661 ions > 1.0. We preliminarily identified 17 differential chemical constituents in AC, PC, and LC with significant differences (p < 0.01) and VIP > 1.0; for example, Lycium B and Periploside H2 are LC and PC's proprietary ingredients, respectively, and 2-Hydroxy-4-methoxybenzaldehyde, Periplocoside C, and 3,5-Di-O-caffeoylquinic acid are the shared components of the three herbs. Conclusions: UHPLC-QTOF-MSE combined with chemometric analysis is conducive to exploring the differential chemical compositions of three herbs. Moreover, the proprietary ingredients, Lycium B (LC) and Periploside H2 (PC), are beneficial in strengthening the quality control of AC, PC, and LC. In addition, limits on the content of shared components can be set to enhance the quality control of LC, PC, and AC.

LC[sbnd]HRMS-based metabolomics on Acalypha indica with different altitude and antioxidant activity

Achalypha indica is a weed that has medicinal properties. This study aims to determine the metabolite profile and evaluate the antioxidant activity of A. indica from areas with different altitudes, Tuban (20 to 50 masl; TBN), Banyuwangi (60 to 90 masl; BB), Magetan (300 to 600 masl; MGT), and Malang (500 to 800 masl; MLG). The ethanol extract of A. indica was analyzed for total phenolics and antioxidant activity. Separation and identification of samples were carried out using liquid chromatography-high-resolution mass spectrometry (LCHRMS), then classified by Principal Component Analysis (PCA). The total phenol value ranged from 6.83 to 10.67 mg GAE /g of dry powder, with an antioxidant IC50 of 86.09 to 118.96 µg/mL. LCHRMS successfully identified 83 metabolites. PCA analysis was able to clearly distinguish each sample based on the altitude of the growing location with a total variance value reaching 82 % (PC-1: 57 %, and PC-2: 25 %). Heat map analysis that observes variations in metabolite composition in each sample shows an increase in the content of flavonoid compounds in the lowlands under certain geographical conditions. Therefore, the height of the growing location has a significant influence on the metabolite profile and antioxidant activity. These findings are very important for assessing the quality, safety, and efficacy of medicinal plant raw materials.

A comparative study of population structure and genetic diversity of commercial and indigenous chickens from different agro-ecological zones in Ghana using SilicoDArT and SNP markers

Chicken production, both in the local and commercial sectors, contributes significantly to human livelihood and food security. Precise use of diverse genetic resources is primary in breeding programs. The study analyzed the genetic diversity and population structure of commercial chickens and indigenous chicken ecotypes from three different agro-ecological zones (Semi-Deciduous Rainforest Zone, Guinea Savannah, and Coastal Savannah) using SilicoDArT and SNP markers, utilizing whole-genome sequencing and phenotypic data. Phenotypic data were collected from 72 indigenous chicken ecotypes across the three AEZs, and 32 commercial birds kept at the Kwame Nkrumah University of Science and Technology (KNUST). DNA samples used for sequencing were obtained from 88 chickens (62 indigenous chicken ecotypes and 26 commercial chickens). A total of 54,995 SilicoDArT and 85,396 SNPs markers were generated from DArTseq genotyping. After filtering, 44,784 SilicoDArT and 58,353 SNP were used for genetic diversity and population structure analysis. Both markers showed high reproducibility and call rate. Polymorphic information content (PIC) values ranged from 0.00 to 0.50, while ≥ 50 % showed PIC values more than the median. Furthermore, we obtained FST values, Nei’s genetic distance, dendrogram analysis, and principal component analysis (PCA) of commercial and indigenous chickens. The FST and Nei’s genetic distance showed that there is high genetic diversity between the commercial chickens and the indigenous chicken ecotypes. However, there was low genetic diversity among the indigenous chicken ecotypes. The PCA analysis indicated a clear separation between the commercial and indigenous chicken ecotypes, while no clear separation was observed between the indigenous chicken ecotypes. The phenotypic data and the dendrogram indicated that naked and frizzle genes do not markedly alter the genetics of indigenous and commercial birds, and their influence on economic traits may be solely determined by the prevailing environmental conditions. The results indicate that there is high genetic differentiation between commercial and indigenous chickens based on SilicoDArT and SNP markers. The indigenous chickens from the agro-ecological zones have low genetic diversity and might have a common origin. Naked neck and frizzle genes do not markedly alter the genetic performance of birds in terms of economic traits. Therefore, the superiority of birds carrying these genes in economic traits may be solely due to environmental variation.

Forensic differentiation of blue pen inks using time-of-flight secondary ion mass spectrometry and multivariate statistical methods

This study investigates the use of time-of-flight secondary ion mass spectrometry (ToF-SIMS) combined with multivariate statistical analysis for the identification of blue pen strokes in document forgery cases. Strokes of six commercially available blue pens were analysed using ToF-SIMS, and the data were interpreted using principal component analysis (PCA) and multivariate curve resolution (MCR). PCA effectively reduced the dimensionality of the complex ToF-SIMS data, enabling clear differentiation of the blue pen inks based on the obtained PCA scores. The first three principal components accounted for most of the variance, with PCA score plots showing distinct clusters of samples corresponding to the spectra of each pen. PCA analysis of the large-area ToF-SIMS images further revealed some characteristic spatial patterns and variations across the pen strokes; however, this analysis was less useful for the identification process. On the other hand, MCR provided a more chemically intuitive analysis by extracting pure component spectra from the complex mixtures. Each MCR factor was individually associated with a specific pen, allowing for exact identification of the pen stroke made. MCR score images displayed clear correlations with individual pen strokes, and the associated loadings identified signals at particular m/z values that were characteristic of each pen. This study shows that an efficient method for non-destructive forensic analysis of blue pen strokes can be achieved by combining ToF-SIMS with PCA and MCR. This analytical method provides reliable identification, which is crucial for forgery detection without requiring any sample pretreatment, i.e. the samples (pen strokes) were used just as they were made on paper.

Sharks and rays at Pelabuhan Perikanan Samudera (PPS) Lampulo, Banda Aceh, Indonesia: Morphometric characteristics and differentiators based on multivariate analysis

Tropical marine environments are abundant and diverse; therefore, shark and ray research at fishing port PPS Lampulo, Banda Aceh City was carried out focusing on morphometric characteristics and differences based on multivariate analysis in July 2020 to identify sharks and rays that landed at fishing port PPS Lampulo, Banda Aceh City and determine their primary characteristics. The shark and ray samples used were from the Indian Ocean and the Malacca Strait and measured total length (TL), fork length (FL), and standard length (SL) for sharks and disc width (DW), TL, and disc length (DL) for rays. Principal component analysis (PCA) and discriminant analysis (DA) were performed on the morphometric data. The PCA analysis revealed that sharks and rays caught in Pelabuhan Perikanan Samudera (PPS) Lampulo, Banda Aceh City, can be divided into two distinct groups. The first group of sharks consists of species with large FL and SL morphometrics, namely P. kamoharai, C. plumbeus, P. glauca, and A. superciliosus. The second group of sharks consists of species with large TL morphometrics, specifically A. pelagicus and C. plumbeus. For the ray group, the first group comprises species with large TL and DW morphometrics, represented by A. ocellatus. The second group of rays consists of species with large DL morphometrics, namely P. sephen and H. jenkinsii. The results of DA revealed distinct differences in the size of sharks caught in the Indian Ocean and the Strait of Malacca, specifically in PPS Lampulo, Banda Aceh City. However, no significant differences in size were observed for the rays, regardless of whether their size was measured using DW, TL, or DL.

Construction of a sensor array using TiO2 NRs/CuO/rMIP with imprinted sites regulation as light-activated nanozyme to colorimetric detect fluoroquinolones

Fluoroquinolone antibiotics are widely used in daily life, but their abuse has caused serious problems, so it is very important to detect fluoroquinolones accurately and conveniently. In this study, a light-activated nanozyme sensor array (TiO2 NRs/CuO/rMIP) was prepared, and principal component analysis (PCA) was employed for qualitative and quantitative determination of four fluoroquinolones in water environments. The photoactive sites of TiO2 were determined by photo-deposition of CuO, and the molecularly imprinted sites was anchored to the photoactive site by the composite action between antibiotic templates and CuO, which led to the consistent adjustment of the imprinted sites and photoactive sites, thus enhancing the enzyme-like activity of TiO2 NRs/CuO/rMIP. In Addition, by adjusting the types and proportions of antibiotic templates during the preparation of MIP, TiO2 NRs/CuO/rMIP sensors with different response signals to four fluoroquinolones were prepared, and a sensor array was established based on them. Through an RGB analysis system of smart phone and PCA analysis method, qualitative and quantitative detection of the four fluoroquinolones was realized. The detection range of the four antibiotics was 0.1–3000 μM, which showed a good prospect for the actual detection of antibiotics.

Flaxseed oil cake improves basil (Ocimum basilicum L.) yield under drought stress by increasing herb biomass and quality of essential oil

Oil cakes are agro-industrial wastes produced in large quantities, with still untapped potential in plant production. Basil is one of the most economical essential oil crops cultivated worldwide, requiring sustainable production methods. This greenhouse experiments evaluated the effects of flaxseed oil cake (FOC) added to peat substrate at the rates of 5, 10, and 20 g dm−3 on herbal yield, content of bioactive compounds and mineral elements, antioxidant activity, and essential oil composition of basil (Ocimum basilicum 'Dark Opal'), grown under well-watered and drought stressed conditions. Two-way ANOVA, principal components analysis (PCA), and correlation networks were applied to associate the data. PCA analysis indicated variability in basil responses to the different treatments, with each treatment forming distinct clusters. The study revealed the beneficial effect of FOC on basil herb yield under water stress. Applying 10 g dm−3 FOC was the most effective in mitigating drought stress in basil. Under drought stress conditions, FOC at the rate of 10 g dm−3 increased fresh weight by 63.9 % and herb dry weight by 59.9 % compared with the peat-only substrate plants. As FOC rates increased, the nitrogen level of plant tissues and substrates increased while reducing sugars, total polyphenols, and total flavonoids content decreased. GC-MS analysis of basil essential oil showed that the main compounds were τ-cadinol (10.79–12.54 %), linalool (4.93–10.01 %), methyl eugenol (4.11–6.71 %), α-bergamotene (3.11–5.48 %) and eugenol (2.10–5.05 %). Drought stress lowed the linalool, methyl eugenol and α-bergamotene concentrations compared with the well-watered plants. However, adding FOC increased the accumulation of linalool and methyl eugenol in all of the FOC treatments under drought stress. Analysis of the differential network showed that the fresh and dry weight and the methyl-eugenol content as “hub” parameters correlated with most traits of basil grown under well-watered and drought stress conditions. In conclusion, using FOC at appropriate levels can effectively reduce plant herb yield loss caused by water stress.

Associations of exposure to volatile organic compounds with sleep health and potential mediators: analysis of NHANES data.

The effect of environmental pollution on sleep has been widely studied, yet the relationship between exposure to volatile organic compounds (VOCs) and sleep health requires further exploration. We aimed to investigate the single and mixed effect of urinary VOC metabolites on sleep health and identify potential mediators. Data for this cross-sectional study was collected from the National Health and Nutrition Examination Surveys (NHANES) (2005-2006, 2011-2014). A weighted multivariate logistic regression was established to explore the associations of 16 VOCs with four sleep outcomes. Following the selection of important VOCs through the least absolute shrinkage and selection operator (LASSO) regression, principal component analyses (PCA), weight quantile sum (WQS), and Bayesian kernel machine regression (BKMR) analyses were conducted to explore the associations between exposure to single and mixed VOCs and sleep outcomes, as well as identify the most contributing components. A mediation analysis was performed to explore the potential effect of depression scores. Of the 3,473 participants included in the study, a total of 618 were diagnosed with poor sleep patterns. In logistic regression analyses, 7, 10, 1, and 5 VOCs were significantly positively correlated with poor sleep patterns, abnormal sleep duration, trouble sleeping, and sleep disorders, respectively. The PCA analysis showed that PC1 was substantially linked to a higher risk of poor sleep patterns and its components. The WQS model revealed a positive association between VOC mixture of increased concentrations and poor sleep patterns [OR (95% CI): 1.285 (1.107, 1.493)], abnormal sleep duration [OR (95% CI): 1.154 (1.030, 1.295)], trouble sleeping [OR (95% CI): 1.236 (1.090, 1.403)] and sleep disorders [OR (95% CI): 1.378 (1.118, 1.705)]. The BKMR model found positive associations of the overall VOC exposure with poor sleep patterns, trouble sleeping, and sleep disorders. PCA, WQS, and BKMR models all confirmed the significant role of N-acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) in poor sleep patterns and its components. The depression score was a mediator between the positive VOC mixture index and the four sleep outcomes. Exposure to single and mixed VOCs negatively affected the sleep health of American population, with AMCC playing a significant role. The depression score was shown to mediate the associations of VOC mixtures with poor sleep patterns and its components.

Comprehensive source identification of heavy metals in atmospheric particulate matter in a megacity: A case study of Hangzhou

Megacities face significant pollution challenges, particularly the elevated levels of heavy metals (HMs) in particulate matter (PM). Despite the advent of interdisciplinary and advanced methods for HM source analysis, integrating and applying these approaches to identify HM sources in PM remains a hurdle. This study employs a year-long daily sampling dataset for PM1 and PM1-10 to examine the patterns of HM concentrations under hazy, clean, and rainy conditions in Hangzhou City, aiming to pinpoint the primary sources of HMs in PM. Contrary to other HMs that remained within acceptable limits, the annual average concentrations of Cd and Ni were found to be 20.6 ± 13.6 and 46.9 ± 34.8 ng/m³, respectively, surpassing the World Health Organization's limits by 4.1 and 1.9 times. Remarkably, Cd levels decreased on hazy days, whereas Ni levels were observed to rise on rainy days. Using principal component analysis (PCA), enrichment factor (EF), and backward trajectory analysis, Fe, Mn, Cu, and Zn were determined to be primarily derived from traffic emissions, and there was an interaction between remote migration and local emissions in haze weather. Isotope analysis reveals that Pb concentrations in the Hangzhou region were primarily influenced by emissions from unleaded gasoline, coal combustion, and municipal solid waste incineration, with additional impact from long-range transport; it also highlights nuanced differences between PM1 and PM1-10. Pb isotope and PCA analyses indicate that Ni primarily stemmed from waste incineration emissions. This explanation accounts for the observed higher Ni concentrations on rainy days. Backward trajectory cluster analysis revealed that southern airflows were the primary source of high Cd concentrations on clean days in Hangzhou City. This study employs a multifaceted approach and cross-validation to successfully delineate the sources of HMs in Hangzhou's PM. It offers a methodology for the precise and reliable analysis of complex HM sources in megacity PM.

Relationship between amide ratio assessed by Fourier-transform infrared spectroscopy: A biomarker candidate for polycythemia vera disease.

The study utilized Fourier transform infrared (FTIR) spectroscopy coupled with chemometrics to investigate protein composition and structural changes in the blood serum of patients with polycythemia vera (PV). Principal component analysis (PCA) revealed distinct biochemical properties, highlighting elevated absorbance of phospholipids, amides, and lipids in PV patients compared to healthy controls. Ratios of amide I/amide II and amide I/amide III indicated alterations in protein structures. Support vector machine analysis and receiver operating characteristic curves identified amide I as a crucial predictor of PV, achieving 100% accuracy, sensitivity, and specificity, while amide III showed a lower predictive value (70%). PCA analysis demonstrated effective differentiation between PV patients and controls, with key wavenumbers including amide II, amide I, and CH lipid vibrations. These findings underscore the potential of FTIR spectroscopy for diagnosing and monitoring PV.

Development of Novel Hybrid Intelligent Predictive Models for Dilution Prediction in Underground Sub-level Mining

Tenuous dilution estimates in underground mine production scheduling continue to cause significant variations between schedule forecasts and actual production. This arises partly from the inference of dilution from predecessor stopes’ performance, disregarding that these stopes would have undergone multiple intermediate design changes between scheduling and actual mining. The resultant drill and blast-influenced dilution factors gradually lose its robustness over longer planning horizons or when applied to greenfield or brownfield expansions that do not have prior performance data. To overcome this problem, a new methodology is proposed to predict dilution in underground sub-level open stoping (SLOS) using basic geological, geotechnical and stope design attributes available in the early stage of mine planning. The method utilises principal component analysis (PCA), classification and regression tree (CART) algorithm and stepwise selection and elimination (SSE) analysis. First, SSE analysis was conducted to identify the most important independent variables to be used with the CART algorithm (i.e., the SSE-CART model) to provide a predictive model. PCA analysis was then performed, and the new principal components were used to propose a new comparative model (i.e., the PCA-CART model). Low R2 values were observed for both models, necessitating the consolidation of dilution categories to increase the models’ prediction bandwidth. The hybrid PCA-CART model outperformed the SSE-CART model with overall F1 score prediction accuracy of 72% and target dilution category prediction accuracy of over 93% against SSE-CART’s 70% and 72%, respectively. Importantly, this study revealed a 13% minimum underestimation of dilution relative to the original design stopes.

O-098 The transcriptome of endometrial organoids of fertile and subfertile women exposed to seminal plasma of fertile men

Abstract Study question What is the effect of seminal plasma (SP) from fertile males on the transcriptome of endometrial epithelial organoids of fertile and subfertile women? Summary answer Transcriptomic changes in fertile and subfertile endometrial organoids are observed upon treatment with SP, related to hormone- and immune-regulation, reproduction and cellular organisation. What is known already Clinical studies have demonstrated the potential beneficial effect of intrauterine SP (liquid fraction of semen) insemination during assisted reproductive technology (ART), resulting in higher implantation- and pregnancy rates. However, the molecular mechanism by which SP exerts its function remains unclear. SP components such as TGF-β1 or IL-8 have the potential capacity of conditioning the uterus for pregnancy. SP has shown to induce significant transcriptional changes in 2D endometrial epithelial cells. 3D self-organising human endometrial organoids have been established over the last years, mimicking a more in vivo-like physiology, and therefore may better represent the interaction of the endometrium with SP. Study design, size, duration Endometrial tissue biopsies from fertile (n = 5) and subfertile (n = 5; subfertile defined as women not having reached clinical pregnancy after at least 12 months of regular unprotected intercourse) were used to establish endometrial epithelial organoids. Subsequently, SP from fertile males (n = 5) was collected and pooled. Endometrial organoids were cultured in complex media supplemented with 1 µM 17β-estradiol (E2) and incubated with or without (control) 1% SP for 6 h. Participants/materials, setting, methods RNA sequencing was performed using NextSeq600 (Illumina). Significant DEGs upon SP exposure were identified using DESeq2 (Fold Change (FC) of ≥ 1.5 or ≤ -1.5). Eight selected DEGs were validated by qPCR in one cell line. Principal Component Analysis (PCA) was performed to compare endometrium donor correlation. Gene Set Enrichment Analysis (GSEA; v4.3.2) was then used to identify overrepresented pathways and gene ontology (GO) gene sets (P &amp;lt; 0.05; False Discovery Rate (FDR) &amp;lt; 0.25). Main results and the role of chance High heterogeneity between donors was observed, regardless of their fertility phenotype. PCA analysis indicated clustering based on donor rather than SP treatment or phenotype. Moreover, the number of significantly DEGs ranged from 629 to 2332. Treatment with SP resulted in identification of 105 significant DEGs (p &amp;lt; 0.05) among all donors (fertile and subfertile) from which 80 DEGs were upregulated and 25 DEGs were downregulated. Several of these DEGs were also reported to be affected by SP in other 2D epithelial cultures studies. Interesting DEGs include progesterone-associated endometrial protein (PAEP; log2FC 2.0 ± 1.0), interleukin-6 (IL6; log2FC 4.5 ± 1.5), insulin-like growth factor-binding protein 3 (IGFBP3; log2FC 1.1 ± 0.2) and mucin 6 (MUC6; log2FC 3.7 ± 1.6). GSEA analysis identified gene set enrichment of pathways and biological processes related to hormone- and immune regulation, reproduction, and cellular organisation in all endometrial organoids treated with SP. Preliminary RNAseq validation with qPCR showed comparable expression patterns for 8 genes (e.g. PAEP and IL6). Moreover, expression of these genes was uniform when using a distinct SP batch (n = 6; fertile males). No clear differential response between fertile and subfertile organoids upon SP exposure was observed. Limitations, reasons for caution The apical-inside organisation of the organoids (i.e. SP interaction from the basolateral side) should be taken into account, since in vivo interaction will be apically. Moreover, high heterogeneity between donors was observed between and within the fertility phenotypes. Therefore, conclusions based on fertility phenotypes should be drawn with caution. Wider implications of the findings Understanding the effect of SP on the endometrium will shed light on male-female reproductive tract crosstalk, which is omitted during ART. Future research should focus on identifying key regulatory SP molecules and functional studies should include apical SP interaction. Potentially providing therapeutic options for improving success rates in ART. Trial registration number Not applicable

Evaluating the Physicochemical Properties-Activity Relationship and Discovering New 1,2-Dihydropyridine Derivatives as Promising Inhibitors for PIM1-Kinase: Evidence from Principal Component Analysis, Molecular Docking, and Molecular Dynamics Studies.

In this study, we evaluated the physicochemical properties related to the previously reported anticancer activity of a dataset comprising thirty 1,2-dihydropyridine derivatives. We utilized Principal Component Analysis (PCA) to identify the most significant influencing factors. The PCA analysis showed that the first two principal components accounted for 59.91% of the total variance, indicating a strong correlation between the molecules and specific descriptors. Among the 239 descriptors analyzed, 18 were positively correlated with anticancer activity, clustering with the 12 most active compounds based on their IC50 values. Six of these variables-LogP, Csp3, b_1rotN, LogS, TPSA, and lip_don-are related to drug-likeness potential. Thus, we then ranked the 12 compounds according to these six variables and excluded those violating the drug-likeness criteria, resulting in a shortlist of nine compounds. Next, we investigated the binding affinity of these nine shortlisted compounds with the use of molecular docking towards the PIM-1 Kinase enzyme (PDB: 2OBJ), which is overexpressed in various cancer cells. Compound 6 exhibited the best docking score among the docked compounds, with a docking score of -11.77 kcal/mol, compared to -12.08 kcal/mol for the reference PIM-1 kinase inhibitor, 6-(5-bromo-2-hydroxyphenyl)-2-oxo-4-phenyl-1,2-dihydropyridine-3-carbonitrile. To discover new PIM-1 kinase inhibitors, we designed nine novel compounds featuring hybrid structures of compound 6 and the reference inhibitor. Among these, compound 31 displayed the best binding affinity, with a docking score of -13.11 kcal/mol. Additionally, we performed PubChem database mining using the structure of compound 6 and the similarity search tool, identifying 16 structurally related compounds with various reported biological properties. Among these, compound 52 exhibited the best binding affinity, with a docking score of -13.03 kcal/mol. Finally, molecular dynamics (MD) studies were conducted to confirm the stability of the protein-ligand complexes obtained from docking the studied compounds to PIM-1 kinase, validating the potential of these compounds as PIM-1 kinase inhibitors.

Revealing the effect of X-ray or proton brain irradiation on systemic inflammation and leukocyte subpopulation interplay in rodents.

The absolute lymphocyte count (ALC), lymphocyte-to-monocyte ratio (LMR), and neutrophil-to-lymphocyte ratio (NLR) offer convenient means to assess systemic inflammation post-cancer treatment, which influences treatment outcomes. Understanding these biomarker variations and leukocyte subpopulation interplay is crucial for optimizing radiotherapy. Herein, leukocyte subpopulations (T-CD4+, T-CD8+, B-cells, NK-cells, neutrophils, monocytes) during and after brain irradiation (using X-rays or Protons) in tumor-free mice were used to compute ALC, LMR, and NLR, on which radiation parameter influence was assessed by principal component analysis (PCA). NLR kinetics were further examined using modeling. Leukocyte subpopulations interplays and their response to radiation parameters were examined using PCA and correlation analysis. Under X-rays, ALC and LMR decreased, with ALC recovered to baseline after irradiation, but not LMR. Both X-rays and protons increased the NLR during irradiation, recovering in protons but not X-rays. Both irradiation volume and dose rate had a pronounced effect on the NLR. Leukocyte subpopulation interplay was observed under X-rays and protons, normalizing in the proton group by day 28. Lymphopenia was observed in all lymphocyte subpopulations under X-ray irradiation but not protons. The recovery patterns varied among the subpopulations. Neutrophil counts increased during irradiation, with the recovery of protons, but not X-rays, by day 28. Interplays between NK-cells and myeloid subpopulations were evident under X-rays but not protons. Importantly, no interplay was detected between myeloid cells and T/B-cells, indicating that LMR and NLR variations were primarily due to independent responses to brain irradiation. A tumor-free experimental mouse model was used to study the effects of brain radiotherapy on systemic immunity. When administering fractionated irradiation with a total dose of 20 Gy using a vertical beam to either the whole brain or hemi-brain, proton irradiation had fewer adverse impacts on the immune system compared to X-rays in tumor-free rodents.

How can the surgeon choose preoperatively the most appropriate antibiotic prophylaxis vs therapy in pediatric acute appendicitis?

The aim of this study was to find statistically valid criteria to preoperatively divide acute appendicitis into simple and complicated to enable surgeons to administer the most appropriate antibiotic prophylaxis/therapy before surgery. We retrospectively reviewed a cohort of patients who underwent appendectomy from January 2022 to December 2023. Patients included were 0-14 years of age. Exclusion criteria included patients who underwent interval appendectomy or concurrent procedures at the same time of appendectomy. We divided patients into two groups: simple (group S) and complicated (group C) appendicitis according to intraoperative finding. Generalized linear model (GLM) with logit function was developed to identify the predictive variables of the type of appendicitis (S vs C) in terms of CRP value, neutrophils percentage and WBC count adjusted for age and sex of patients. Finally, principal component analysis (PCA) was carried out to identify the cutoff value of statistically significant variables found in the previous analysis. One hundred and twenty patients were eligible (N female = 49, N male = 71) for the study. 74 and 46 patients were included in groups S and C, respectively. In a preliminary analysis using univariate and multivariate GLM, only CRP (p value = < 0.001) and neutrophils percentage (p value = 0.02) were predictive variables for the type of appendicitis. The GLM shows a statistical lower value of CRP (adjusted odds ratio [OR] per unit, 0.17 [95% CI, 0.08-0.39]) and neutrophil percentage (adjusted OR per unit, 0.37 [95% CI, 0.16-0.86]) in the S group compared to C adjusted to age and sex. PCA analysis revealed a P-ROC cutoff of 4.2 mg/dl and 80.1 of CRP value (AUC = 84%) and neutrophil percentage (AUC = 70%), respectively. We willperform a prospective study giving preoperative prophylactic cefazolin to patients with a CRP value under 4.2 mg/dl and amoxicillin-clavulanate therapy to patient with CRP value over 4.2 mg/dl.

Stabilization of residual mercury from gold mining as metacinnabar and cinnabar in ball mills on a pilot scale

Waste liquid mercury generated as a by-product of the Merrill–Crowe process in gold mining and recovered from mercury-containing waste must be stabilized for secure storage or disposal. This study developed a procedure for mercury stabilization. A ball mill with a 0.5 m3 capacity and a rotational speed of 43 rpm was used to stabilize the residual mercury with sulfur. The treatments were conducted for 30, 60, and 90 min at mercury: sulfur molar ratios of 1.0, 0.8, and 0.67. The ball loading ratio was 7.0 with residual mercury, and the temperature was below 40 °C. The treatment efficiency was evaluated by measuring the concentrations of mercury and other metals using the Toxicity Characteristic Leaching Procedure (TCLP), examining the stabilized residual mercury by X-ray diffraction, and conducting bioassays on Daphnia magna and Lactuca sativa. Principal component analysis (PCA) was performed on the aforementioned variables. The 90-min treatment, with a mercury-to-sulfur molar ratio of 0.67, stabilized mercury mainly as cinnabar compared with the other treatments and presented leachate mercury values below the detection limit <0.003. The leachate from the treatments also showed values of 21.28–38.44 toxic units, classified as very toxic, and generated toxicity, particularly for D. magna, because of the presence of other metals such as Al, Ba, B, Ca, Cu, Cr, Fe, Mn, Ni, and Zn. The variability of the residues in the PCA analysis was explained by the treatment effect and the presence of other metals in the residual mercury. The stabilized residual mercury obtained was classified as non-hazardous and could be stored or disposed of as ordinary waste in a security landfill.

Explorando la genética de tres poblaciones de la raza Cerdo Pelón en México

The objective of this research was to carry out a molecular genetic characterization of three Hairless Pig (HP) breed populations located in México in the states of Nayarit, Oaxaca and Yucatán to identify variations, selection effects and population genetic relationships. From blood samples, a total of 163 animals from three populations of HP were successfully genotyped. Genotyped SNP data was employed to compute genetic diversity, population structure and landscape genetic analysis. The parameters of minor allele frequency (MAF), observed heterozygosity (Ho) and Wright’s fixation index (FIS) pointed out that the population of Nayarit is the one with the greatest genetic diversity (MAF: 0.362, Ho: 0.336, FIS: 0.061). Principal Component Analysis (PCA) and a Neighbor-joining phylogenetic tree analysis showed diversification among the three HP populations and pointed out a closer genetic relationship between the HP populations and the Iberian pig breed. The Admixture analysis showed as well common ancestry shared from commercial and Iberian breeds in the HP populations in different gradients. For the analysis of the relationships between geographic and genetic distances, Mantel test was computed and the results described a distribution pattern of the geographical locations along the genetic distances similar to the clustering pattern of the PCA and Neighbor-joining phylogenetic tree analysis. The results obtained manage to present the HP poor conservation state and the need to stablish a genetic conservation program meaning an effort to prevent the loss of a significant cultural, natural and genetic resource. Keywords: genetic diversity, landscape genetics, native breeds, genetic resources.

DETECTION OF WHITE RICE ADULTERANTS IN LAMPUNG ROBUSTA COFFEE EXTRACT USING FT-IR METHOD BY FINGERPRINT ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS

Lampung Province has 3 areas that produce coffee: West Lampung, Tanggamus, and Waykanan, which can produce 51,484 tons of coffee annually. The high demand for coffee and limited harvest are some factors that cause the addition of adulterants to coffee products such as corn, soybeans, rye, coffee beans, and rice. This study aims to detect rice adulterants in Lampung robusta coffee using the FTIR spectrophotometric method combined with chemometric analysis using the PCA (Principal Component Analysis) method. FTIR spectrophotometric method combined with chemometric analysis using PCA (Principal Component Analysis) method. The PCA method was validated using the cross-validation method. Samples were taken from 3 Lampung coffees on the market. The extraction process was carried out on Lampung coffee and Lampung rice from 3 regions using 96% ethanol. After concentrating, the coffee and rice extracts were measured using FTIR and read in the 4000-650 cm-1 wave number range. Different wave number curves were obtained between coffee and rice. A pre-processing chemometric analysis was performed, which resulted in the classification of Robusta coffee and rice using PC1 and PC2 (50% and 24%). The results of PCA analysis showed that PC1 and PC2 in the three Lampung coffee samples, samples A and C, did not contain adulterants, while sample B was suspected of containing white rice. Keywords: Alduteran, FTIR, Chemometrics, PCA, Lampung Robusta Coffee.