Multivariate Statistical Methods Research Articles

Model for Inverting the Leaf Area Index of Green Plums by Integrating IoT Environmental Monitoring Data and Leaf Relative Content of Chlorophyll Values

The quantitative inversion of the leaf area index (LAI) of green plum trees is crucial for orchard field management and yield prediction. The data on the relative content of chlorophyll (SPAD) in leaves and environmental data from orchards show a significant correlation with LAI. Effectively integrating these two data types for LAI inversion is important to explore. This study proposes a multi−source decision fusion LAI inversion model for green plums based on their adjusted determination coefficient (MDF−ADRS). First, three statistical methods—Pearson, Spearman rank, and Kendall rank correlation analyses—were used to measure the linear relationships between variables, and the six environmental factors most highly correlated with LAI were selected from the orchard’s environmental data. Then, using multivariate statistical analysis methods, LAI inversion models based on environmental feature factors (EFs−PM) and SPAD (SPAD−PM) were established. Finally, a weight optimization allocation strategy was employed to achieve a multi−source decision fusion LAI inversion model for green plums. This strategy adaptively allocates weights based on the predictive performance of each data source. Unlike traditional models that rely on fixed weights or a single data source, this approach allows the model to increase the influence of a key data source when its predictive strength is high and reduce noise interference when it is weaker. This dynamic adjustment not only enhances the model’s robustness under varying environmental conditions but also effectively mitigates potential biases when a particular data source becomes temporarily unreliable. Our experimental results show that the MDF−ADRS model achieves an R2 of 0.88 and an RMSE of 0.39 in the validation set, outperforming other fusion methods. Compared to the EFs−PM and SPAD−PM models, the R2 increased by 0.19 and 0.26, respectively, and the RMSE decreased by 0.16 and 0.22. This model effectively integrates multiple sources of data from green plum orchards, enabling rapid inversion and improving the accuracy of green plum LAI estimation, providing a technical reference for monitoring the growth and managing the production of green plums.

Characterization of Groundwater Geochemistry in an Esker Aquifer in Western Finland Based on Three Years of Monitoring Data

This study investigated the hydrogeochemistry of a shallow Quaternary sedimentary aquifer in an esker deposition in western Finland, where distinct spatial and temporal variability in groundwater hydrogeochemistry has been observed. Field investigation and hydrogeochemical data were obtained from autumn 2010 to autumn 2013. The data were analyzed using the multivariate statistical methods principal component analysis (PCA) and hierarchical cluster analysis (HCA), in conjunction with groundwater classification based on the main ionic composition. The stable isotope ratios of δ18O and δD were used to determine the origin of the groundwater and its connection to surface water bodies. The groundwater geochemistry is characterized by distinct redox zones caused by the influence of organic matter, pyrite oxidation, and preferential flow pathways due to different hydrogeological conditions. The groundwater is of the Ca-HCO3 type and locally of the Ca-HCO3-SO4 type, with low TDS, alkalinity, and pH, but elevated Fe and Mn concentrations, KMnO4 consumption, and, occasionally, Ni concentrations. The decomposition of organic matter adds CO2 to the groundwater, and in this study, the dissolution of CO2 was found to increase the pH and enhance the buffering capacity of the groundwater. The mobility of redox-sensitive elements and trace metals is controlled by pH and redox conditions, which are affected by the pumping rate, precipitation, and temperature. With the expected future increases in precipitation and temperature, the buffering capacity of the aquifer system will enhance the balance between alkalinity from bioactivity and acidity from recharge and pyrite oxidation.

Model-Fitting Weighted Least Squares as an Alternative to Principal Component Analysis for Analyzing Energy-Dispersive X-ray Spectroscopy Spectrum Images.

Spectrum imaging with energy-dispersive X-ray spectroscopy (EDS) has become ubiquitous in material characterization using electron microscopy. Multivariate statistical methods, commonly principal component analysis (PCA), are often used to aid analysis of the resulting multidimensional datasets; PCA can provide denoising prior to further analysis or grouping of pixels into distinct phases with similar signals. However, it is well known that PCA can introduce artifacts at low signal-to-noise ratios. Unfortunately, when evaluating the benefits and risks with PCA, it is often compared only against raw data, where it tends to shine; alternative data analysis methods providing a fair point of comparison are often lacking. Here, we directly compare PCA with a strategy based on (the conceptually and computationally simpler) weighted least squares (WLS). We show that for four representative cases, model fitting of the sum spectrum followed by WLS (mfWLS) consistently outperforms PCA in terms of finding and accurately describing compositional gradients and inclusions and as a preprocessing step to clustering. Additionally, we demonstrate that some common artifacts and biases displayed by PCA are avoided with the mfWLS approach. In summary, mfWLS can provide a superior option to PCA for analysis of EDS spectrum images as the signal is simply and accurately modeled.

Pregnancy detection based on blood serum sample Raman spectroscopy.

In this research, women were diagnosed as pregnant based on blood serum samples Raman spectroscopy. Raman spectroscopy is a vibrational technique that provides information on the chemical composition of samples. The Raman techniques have significantly impacted the study of various degenerative diseases, particularly cancer detection, using less invasive methods such as the analysis of blood serum samples. Additionally, these techniques have been used to study the health status of patients, which is often difficult to monitor using conventional techniques. This study obtained serum samples from 12 women diagnosed as pregnant and 11 non-pregnant volunteers (controls). Spectra were collected using a LabRAM HR800 Raman Spectrometer (Horiba Jobin-Yvon) with an 830 nm wavelength laser. For each serum sample, 10 Raman spectra were obtained by focusing the laser, using a microscope objective, on different points of the sample with an exposure time of 40 seconds and an irradiation power of 17 mW. The raw spectra were processed using baseline correction and smoothing to remove noise, fluorescence, and shot noise. Subsequently, the spectra were normalized and analyzed using the multivariate statistical method of Principal Component Analysis (PCA). In these spectra, the characteristic bands of main blood serum biomolecules such as phenylalanine (Phe), tyrosine (Tyr), glutathione, amide III, phospholipid, carotene, and tryptophan (Trp) can be observed. Nevertheless, when analyzing the average spectra of pregnant and non-pregnant women, the main spectral differences were associated with variations in molecules like glutathione, tryptophan (Trp), tyrosine, and phenylalanine, which occur during the first trimesters of pregnancy. This aligns with findings previously reported by other studies. Furthermore, the serum samples from pregnant and non-pregnant patients can be effectively discriminated using PCA applied to the Raman spectra, revealing two distinct clusters in the PCA plot corresponding to each group's status. The results demonstrate that pregnancy can be determined based on blood serum samples Raman spectroscopy with sensitivity and specificity. Although there are very effective devices on the market to determine pregnancy based on the Human Chorionic Gonadotropin (HCG) hormone detection in urine samples, these preliminary results indicate an alternative method known as Raman spectroscopy. On the other hand, the results could also suggest the possibility of carrying out other gynecological or fetal-related studies in women using these Raman techniques.

Sustainable management of drinking water quality in the locality of Massouro, Chad

This study evaluates the quality of drinking groundwater in the city of Moussoro using geochemical, bacterial, and multivariate statistical methods. Access to safe drinking water is a major concern for the population in these regions, as the distribution of this resource is unequal across continents and is often affected by human activities, making it vulnerable. The analysis revealed two categories of water: potable and non-potable. The presence of pollutant indicators, such as Escherichia coli (E. coli) and total coliforms, was observed in most samples. This presence indicates water contamination and requiring monitoring and treatment before it is consumed by the population. Overall, most of the physicochemical parameters comply with the World Health Organisation guidelines for drinking water. However, the concentration of ammonium (NH4+) was high. Pollution elements such as ammonium (NH4+) and E. coli, indicate that human activities also contribute to water mineralisation. The study could ensure sustainable access to safe drinking water, thereby enhancing the overall quality of life in Moussoro.

A Review of Data-Driven Intelligent Monitoring for Geological Drilling Processes

The exploration and development of resources and energy are fundamental to human survival and development, and geological drilling is a key method for deep resource and energy exploration. Intelligent monitoring technology can achieve anomaly detection, fault diagnosis, and fault prediction in the drilling process, which is crucial for ensuring production safety and improving drilling efficiency. The drilling process is characterized by complex geological conditions, variable working conditions, and low information value density, which pose a series of difficulties and challenges for intelligent monitoring. This paper reviews the research progress of the data-driven intelligent monitoring of geological drilling processes, focusing on the above difficulties and challenges. It mainly includes multivariate statistics, machine learning, and multi-model fusion. Multivariate statistical methods can effectively handle and analyze complex geological drilling data, while machine learning methods can efficiently extract key patterns and trends from a large amount of geological drilling data. Multi-model fusion methods, by combining the advantages of the first two methods, enhance the ability to handle complex multivariable and nonlinear problems. This review shows that existing research still faces problems such as limited data processing capabilities and insufficient model generalization capabilities. Improving the efficiency of data processing and the generalization capability of models may be the main research directions in the future.

Factors influencing management of dry cell battery waste: a case of Greater Accra Region in Ghana

Indiscriminate disposal of dry cell battery (DCB) waste contributes to environmental and public health issues in developing countries such as Ghana, due to the toxic nature of this specific waste. Accordingly, a study was conducted in Accra, Ghana, to determine the socio-economic and demographic factors influencing handling DCB waste, aiming a sustainable environment. Using a random sampling technique, a descriptive cross-sectional survey was conducted, encompassing 367 respondents from the Accra-Tema Metropolitan areas and Tema West Municipal Assembly in Greater Accra, Ghana. Using descriptive and multivariate statistical methods, the survey data were analysed with the Statistical Package for Social Sciences (SPSS) version 27. The results of this study show that female gender and residential area are likely to positively influence the use of DCB at home. Education significantly affects the use of DCB and its proper disposal. The results also suggest that 78% of the respondents disposed of DCB waste in waste bins. The mean monthly income of the respondents stands at USD 270, which is average and likely partially to positively influence the disposal of the DCB. The data collected revealed that female gender, age group, family size, and education level influence the indiscriminate disposal of DCB waste and DCB waste recycling. The results highlight that educated females above the age of 55, with a monthly income, are likely to properly segregate DCB waste. This study contributes to the knowledge gap in relation to dry cell battery waste management (DCBWM) in developing countries, aiming to advance global sustainability. This study is expected to contribute to educate and create awareness in managing DCB waste to reduce its indiscriminate disposal which leads to environmental pollution and negatively affects human health and environmental sustainability in Ghana.

Approach to Weighting the Success Criteria of Toll Road Project of Government Cooperation with Business Entities Procurement Model

In providing funding for toll road development projects, many developing countries are im-plementing PPP pro-curement schemes including Indonesia. This funding scheme is believed to be an innovative procurement process model and has good prospects for the future of the construc-tion industry in the world. However, in its implementation, the Indonesian government is currently faced with various problems that have the potential to have a negative impact on the management and development of toll roads in Indo-nesia. Therefore, the main objective of this research is to develop a method of evaluating the success of PPP-themed toll road projects and determining the current and future strategy of PPP-themed toll road development projects. Methodology This research, using an exploratory sequential mixed methods approach, involves four stages of research. Through a Systematic Literature Review (SLR) of reputable scientific journals from various countries, a questionnaire survey was developed. The survey results were analyzed using multivariate statistical methods with the help of Par-tial Least square analysis software (PLS-SEM), analytical hierarchy process (AHP) and Relative Importance Index (RII) methods. The results of this research found 20 critical success indicators and four dimensions of project success. This study produces a new way to assess the success of PPP-themed toll road projects that is very important and can inspire the government in making policies, legislation and regulations as well as innovative strategies in develop-ing PPP-themed toll roads.

Benthic Microbes on the Shore of Southern Lake Taihu Exhibit Ecological Significance and Toxin-Producing Potential Through Comparison with Planktonic Microbes

Water quality and aquatic ecosystems along lakeshores are vital for ecological balance and human well-being. However, research has primarily focused on plankton, with benthic niches being largely overlooked. To enhance understanding of benthic microbial communities, we utilized 16S and 18S rRNA sequencing alongside multivariate statistical methods to analyze samples from the shoreline of Lake Taihu in Huzhou City, Zhejiang Province. Our results reveal a marked difference in species composition between benthic and planktonic microorganisms, with benthic cyanobacteria predominantly comprising filamentous genera like Tychonema, while 95% of planktonic cyanobacteria were Cyanobium. The β-diversity of benthic microorganisms was notably higher than that of planktonic counterparts. The neutral community model indicated that stochastic processes dominated planktonic microbial assembly, while deterministic processes prevailed in benthic communities. Null models showed that homogeneous selection influenced benthic community assembly, whereas planktonic communities were affected by undominated processes and dispersal limitation. Network analysis indicated that planktonic networks were more stable than benthic networks. Importantly, dominant benthic cyanobacterial genera posed potential toxin risks, highlighting the need for enhanced monitoring and ecological risk assessment. Overall, these findings enhance our understanding of benthic and planktonic microbial communities in lakeshores and offer valuable insights for aquatic assessment and management in eutrophicated environments.

Study on Evaluation of Fruit Aroma of Plum Variety Resources Based on Headspace Solid-Phase Microextraction Combined with Gas Chromatography-Mass Spectrometry.

To explore the characteristics of and variations in aroma components across different plum varieties and maturity stages, this study employed headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS). This method was used to systematically analyze the aroma components of 12 early-maturing, 15 medium-maturing, and 11 late-maturing plum varieties. The variations in volatile components among these three germplasm types were then compared using multivariate statistical methods. The examination revealed that 138 aromatic components were meticulously identified and quantified, such as 26 aldehydes, 63 esters, 13 ketones, 30 alcohols, and six other compounds. Thirteen main aroma compounds including acetic acid hexyl ester, (Z)-3-hexen-1-ol acetate, hexanal, 1-hexanol, 3-hexenal, butanoic acid butyl ester, (E)-2-hexen-1-ol, hexanoic acid butyl ester, propanoic acid butyl ester, (E)-2-hexenal, L-.alpha.-terpineol, (Z)-2-hexen-1-ol acetate, and 1-butanol were considered dominant. The orthogonal partial least squares discriminant analysis (OPLS-DA) combined with variable importance projection (VIP) results showed that 24 differential aroma compounds were screened out from 38 varieties of plum fruits based on their differences in aroma components, which can be used to distinguish plum fruits at different ripening times. Twenty-four aroma-contributing compounds were identified based on their odor activity values (OAVs). Among these, 14 key aroma components with OAVs ≥ 10 were highlighted. In summary, the aroma compounds of early- and late-maturing plum germplasm exhibited rich diversity, with significant differences in aroma components between plums of varying maturity and germplasm. These differences can serve as indicators for identifying different plum germplasm.

Comparative Cardiovascular Risks of Radical Prostatectomy and External Beam Radiation Therapy in Early-Stage Prostate Cancer: A Comprehensive Retrospective Analysis.

The risk of cardiac disease mortality has recently become a focal point of concern within the medical community for patients with prostate cancer (PCa). Given that radical prostatectomy (RP) and external beam radiation therapy (EBRT) are the main treatment modalities for localized PCa, their specific impact on cardiovascular-specific mortality (CSM) remains unclear. This study explored the specific effects of RP and EBRT on CSM risk to guide clinical treatment decisions. Data from patients aged 45-74years, who were diagnosed with T1-2N0M0 stage PCa from the SEER database (2010-2015), were used. Multivariate statistical methods, including propensity score matching (PSM), competing risk regression, COX regression analysis, and Fine-Gray testing, were applied to assess the impact of RP and EBRT on CSM risk. Among 146,082 T1-2 stage PCa patients, cardiac disease emerged as the primary cause of death, surpassing PCa itself. Multifactorial COX regression and competing risk regression analyses indicated that local treatments do not increase CSM risk. Further analysis revealed a significant increase in CSM risk for patients undergoing only EBRT compared with those undergoing only RP (hazard ratio [HR] = 2.71, 95% confidence interval [CI] 1.96-3.74, P < 0.001), with subsequent PSM adjustment, further confirming a significantly reduced risk in the RP treatment group (HR 0.23, 95% CI 0.13-0.40, P < 0.001). T1-2 stage PCa patients face a significant risk of CSM, with RP offering a potential advantage over EBRT in reducing this risk. These findings encourage clinicians to comprehensively consider the potential impact on cardiac health when formulating treatment plans, providing crucial guidance for optimizing treatment strategies.

Optimizing rosemary oil nanoemulsion loaded with nelfinavir and epigallocatechin gallate: A Design Expert® endorsed approach for enhanced neuroAIDS management

This study focuses on optimizing the delivery of Nelfinavir (NFV), a vital protease inhibitor in antiretroviral therapy, and Epigallocatechin gallate (EGCG), a potent adjunctive anti- human immunodeficiency virus (anti-HIV) agent found in green tea. The challenge lies in NFV's low intrinsic dissolution rate, significant p-gp efflux, and high hepatic metabolism, necessitating frequent and high-dose administration. Our objective was to develop a nanoemulsion loaded with NFV and EGCG to enhance oral delivery, expediting antiretroviral effects for NeuroAIDS treatment. After meticulous excipient screening, we selected Tween 40 as the surfactant and polyethylene glycol 400 (PEG 400) as the co-surfactant. Employing a Quality by Design (QbD) approach with statistical multivariate methods, we optimized the nanoemulsion that exhibited a droplet size of 83.21 nm, polydispersity index (PDI) of 2.289, transmittance of 95.20 %, zeta potential of 1.495 mV, pH of 6.95, refractive index of 1.40, viscosity of 24.00 ± 0.42 mPas, and conductivity of 0.162 μS/cm. Pharmacokinetic studies demonstrated superior in vivo absorption of the optimized nanoemulsion compared to NFV and EGCG suspension. The optimized nanoemulsion showcased higher Cmax of NFV (9.75 ± 1.23 μg/ml) and EGCG (27.7 ± 1.22 μg/ml) in the brain, along with NFV (26.44 ± 1.44 μg/ml) and EGCG (313.20 ± 5.53 μg/ml) in the plasma. This study advocates for the potential of NFV and EGCG-loaded nanoemulsion in combination antiretroviral therapy (cART) for effective NeuroAIDS management.

Heavy metal dynamics in riverine mangrove systems: A case study on content, migration, and enrichment in surface sediments, pore water, and plants in Zhanjiang, China

Mangroves serve a crucial role as metal accumulators in tropical and subtropical marine ecosystems, particularly in riverine mangroves, which frequently interact with terrestrial sources. In this study, we focused on the Gaoqiao and Jiuzhou Rivers within the Zhanjiang mangrove forest in Guangdong, China, and collected leaves and surface sediments from the dominant mangrove plant, Aegiceras corniculatum, near the riverbanks. We focused on seven heavy metals (Cr, Cu, Zn, As, Cd, Pb, and Hg) in mangrove leaves, surface sediments, and pore water due to their environmental significance and frequent occurrence in mangrove ecosystems. We employed multivariate statistical methods and pollution indicators to assess the potential sources and risk levels of heavy metals in these sediments. Our results reveal that the concentrations of the seven heavy metals in the sediments of the Gaoqiao and Jiuzhou Rivers varied significantly, ranging from 0.03 mg/kg to 100.00 mg/kg. Cd posed the highest ecological risk, followed by Hg and As. The comprehensive potential ecological risk in the Gaoqiao River was lower than that in the Jiuzhou River, likely due to the distribution of industrial enterprises (such as printing and cement plants) in the upper reaches of the Jiuzhou River. Additionally, the heavy metal content in the leaves and pore water of A. corniculatum ranged from 0.01 to 51.58 mg/kg and 0.001 to 133.70 μg/L, respectively. There was a significant correlation between the heavy metal concentrations in the leaves and the pore water of A. corniculatum. Notably, the leaves of A. corniculatum exhibited a remarkable Hg-enrichment capability, highlighting its potential as a mercury accumulator. Most heavy metals in A. corniculatum leaves, pore water, and sediment were concentrated in the middle and upper reaches of the river, primarily due to anthropogenic terrestrial inputs from residential production activities upstream. Consequently, heavy metal pollution in riverine mangroves is primarily associated with human activities such as aquaculture, agricultural planting, and industrial production.

The Effect of Multidisciplinary Care on Polypharmacy in Advanced Cancer Patients near the End of Life

Abstract Objectives Multidisciplinary Team (MDT) aims to integrate cancer patient care plans and provide holistic care to improve clinical outcomes and quality of life. However, there is a lack of empirical evidence regarding the effect of MDT on polypharmacy in advanced cancer patients near the end of life, which warrants further investigation. Methods This retrospective cohort study utilizes the National Health Insurance Research Database (NHIRD), Taiwan Cancer Registry, and Cause of Death Statistics, provided by the Health and Welfare Data Science Center (HWDC), Ministry of Health and Welfare (MOHW). The study subjects were patients who were diagnosed with stage III or IV cancer, aged 65 or above, experienced recurrence or metastasis, and who died between 2014 and 2020. Propensity score matching (PSM) was employed, followed by analysis using the Generalized Estimating Equation (GEE) to examine the differences in the risk of polypharmacy in the last 30 days before death. In addition, to confirm the robustness of the results, we conducted two different sensitivity tests: the first way is to use different ages as sample selection criteria and only include people who died over 75 years old as study subjects; the second way is to use conditional logistic regression models as a multivariate statistical method. Results There were 35537 samples before matching, including 4942 who received MDT care and 30595 who did not. After 1:1 matching, 9884 patients were finally included in the analysis. The prevalence of polypharmacy significantly decreased during the study period from 59.90% to 58.80% (p = 0.03; trend test). When examined through different PIM criteria, patients who received care from MDT exhibited a lower risk of polypharmacy (OR = 0.91, 95% CI = 0.84-0.98). Conclusions Advanced cancer patients who received care from MDT during the end-of-life period had a significantly lower risk of polypharmacy. Key messages • The prevalence of polypharmacy significantly decreased during the study period from 2014 to 2020 among advanced cancer patients. • Advanced cancer patients who received care from MDT during the end-of-life period had a significantly lower risk of polypharmacy.

Quantifying phenotypic variability of indigenous chickens using morphometric traits by applying multivariate analysis: Input for sustainable rural chicken farming

Despite environmentally influenced performance traits in farm animals, variations in morphometric characters reflect unswerving genetic effects. In this study, body weight and body dimension measurements of indigenous chickens reared in four rural communities were investigated using multivariate statistical procedures to elucidate the existence of phenotypic variability between chicken populations. The study districts were selected based on higher indigenous chicken population, geographic distance, and agro-ecological distinctiveness. Eleven morphometric traits were measured on 1060 adult chickens from the districts. The results revealed that there were significant (p < 0.0001) variations between populations across districts. Significantly (P < 0.0001) higher mean values for morphometric traits were obtained in chickens reared in the Hula (highland district) than in those of the three districts. Likewise, multivariate discriminant analysis showed that most of the variables had significant power to differentiate the chicken populations into separate groups. Accordingly, three discriminant functions were extracted, of which the first two explained 95.6 % of the total variances in the populations. Moreover, in cluster analysis, chickens were differentiated into two sub-groups: Hula as a separate population, and Shebedino, Aleta Chuko and Boricha populations clustered together. Furthermore, the discriminant analysis correctly assigned 56.7 %, 55.1 %, 51.5 %, and 53.3 % to their source populations of Hula, Aleta Chuko, Shebedino, Hula, and Boricha, respectively, showing high mixing and mobility of chickens across neighboring districts. Therefore, this study confirmed the existence of significant morphometric variability between the studied populations, which could be used as a valuable source of information for selective breeding and sustainable use of indigenous chickens, particularly for rural farmers who almost rely on phenotypic features to select breeding stocks. In addition, the higher morphometric measurements shown for Hula chickens should be confirmed by on-station evaluation, and further molecular tools should be applied to validate the genetic distinctiveness of the studied chicken populations.

Study on serum metabolomics characteristics of obese patients with erectile dysfunction.

Erectile dysfunction (ED) is a common male sexual health problem that can be associated with obesity. This study aimed to identify serum metabolic differences and pathways related to ED in obese men using non-targeted metabolomics techniques. We included 54 obese male patients with (n = 27) and without (n = 27) ED. We collected 5 mL of fasting elbow vein blood and analyzed serum metabolites using ultra-high-performance liquid chromatography-mass spectrometry. Multivariate statistical methods (principal component analysis and orthogonal partial least squares discriminant analysis) were used to identify differential metabolites between the groups. Finally, pathway analysis using the Kyoto encyclopedia of genes and genomes database identified 4 differential metabolic pathways in obese men with ED compared to obese men without ED. A total of 77 differential metabolites were identified in obese men with ED compared to the control group (obese men without ED) using a threshold of variable importance in the projection > 1 and P < .05. Pathway analysis revealed 4 main differences: glycine, serine and threonine metabolism, glycerophospholipid metabolism, aminoacyl-tRNA biosynthesis, and D-glutamine and D-glutamate metabolism. Specific metabolites associated with these pathways included betaine aldehyde, choline, L-threonine, phosphatidylcholine, L-serine, and D-glutamine. Our findings suggest abnormalities in fatty acid metabolism, phospholipid metabolism, and amino acid metabolism between obese men with and without ED. Metabolites such as betaine aldehyde, choline, L-threonine, phosphatidylcholine, L-serine, and D-glutamine may be potential biomarkers for distinguishing obese men with ED.

Synthetic Cathinones' Comprehensive Screening and Classification by Voltammetric and Chemometric Analyses: A Powerful Method for On-Site Forensic Applications.

The use of synthetic cathinones (SCs) has increased in recent years, posing significant public health problems due to their adverse effects and potential for fatal poisonings. The structural diversity and rapid emergence of new SC analogues create challenges for law enforcement and drug screening techniques. This work presents for the first time the electrochemical detection of SCs using differential pulse voltammetry (DPV) on a boron-doped diamond electrode (BDDE). We analyzed 15 SCs, including well-known compounds such as mephedrone, methylone, and ephylone, revealing distinct electrochemical profiles with two characteristic reduction peaks (R1 and R2). The method was optimized in Britton-Robinson buffer (0.1 mol L-1, pH 8.0) and demonstrated a high selectivity and sensitivity. Multivariate statistical methods, including principal component analysis and hierarchical cluster analysis, classified SCs into six distinct groups. The DPV optimization and analytical parameter determination, including the limit of detection (LOD), were performed for the least electroactive SC, 4'-methyl-α-pyrrolidinohexanophenone, yielding an LOD of 3.8 μmol L-1, suitable for screening street samples. Interference studies with common illicit drugs and adulterants confirmed the selectivity of the DPV-BDDE method. Preliminary identification of SCs in 46 real seized samples was successfully performed using this method with results validated by liquid chromatography-mass spectrometry (LC-MS). The method also identified three SCs not included in the original set: bupropion, benzylone, and dipentylone. The DPV-BDDE method offers a rapid, robust, and portable approach for the selective screening of SCs in forensic applications, demonstrating significant advantages over traditional colorimetric tests.

Metabolomic signature of sperm in men with obesity-associated asthenozoospermia.

Obese men have a significantly increased risk of developing asthenozoospermia. Sperm motility is directly related to cellular energy supply and metabolic status. Sperm metabolomics research based on Gas chromatography-mass spectrometry (GC-MS) technology can provide useful information for the pathological mechanism, diagnosis, and treatment of obesity-associated asthenozoospermia. Sperm samples were obtained from a healthy control group (n = 49) and patients with obesity-associated asthenozoospermia (n = 40). After the analysis of sperm samples using GC-MS, various multivariate statistical methods such as principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were conducted. A total of 56 metabolites were identified in the sperm samples. Among them, 19 differential metabolites were found between the two groups. Metabolites such as glutamic acid, fumaric acid, and cysteine were significantly downregulated in the sperm of patients with obesity-associated asthenozoospermia, while metabolites like palmitic acid, stearic acid, and alanine were significantly upregulated. The differential metabolites were enriched in D-glutamine and D-glutamate metabolism; proline, aspartate, and glutamate metabolism; glutathione metabolism and the other metabolic pathways. Obesity may influence the composition of metabolic products in sperm, and metabolomic analysis proves beneficial for the future diagnosis and treatment of obesity-associated asthenozoospermia.

SWATH-MS Based Secretome Proteomic Analysis of Pseudomonas aeruginosa Against MRSA.

The study uses Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH)-MS in conjunction with secretome proteomics to identify key proteins that Pseudomonas aeruginosa secretes against methicillin-resistant Staphylococcus aureus (MRSA). Variations in the inhibition zones indicated differences in strain resistance. Multivariate statistical methods were applied to filter the proteomic results, revealing five potential protein biomarkers, including Peptidase M23. Gene ontology (GO) analysis and sequence alignment supported their antibacterial activity. Thus, SWATH-MS provides a comprehensive understanding of the secretome of P. aeruginosa in its action against MRSA, guiding future antibacterial research.

The Structure of the Late Bronze Age Population of Western Siberia: Craniometric Evidence

To assess the sources of population differentiation in Late Bronze Age Western Siberia, measurements of 68 cranial samples of this and earlier periods were processed with multivariate statistical methods. Results support the idea of at least two post-Afanasyevo migrations to Siberia from the west—pre-Andronovo and Andronovo. The former was represented by Chaa-Khol, Yelunino, and Samus people. Those associated with Karakol culture partly resemble the above and partly both autochthonous populations—that of Baraba (“Northern Eurasian formation”) and that of Okunev culture (“Southern Eurasian formation”), which appear to be two extremes of a single continuum. Differences between the two Andronovo traditions, Fedorovka and Alakul, are likely due to the local substratum in the former rather than to various origins. The Karasuk group arose through admixture between Okunev and Andronovo. People associated with the classic Karasuk culture are closer to the former, while those of the Kamenny Log stage tend toward the latter. People of the Upper Irtysh and the Mongun-Taiga people from Baidag III resemble those of Karasuk. Two pooled groups, Irmen and Mongun-Taiga, and the Pakhomovskaya sample indicate a possible admixture between both autochthonous formations, Northern and Southern, as well as Andronovo and Karasuk. Among the so-called Andronoid groups, only Yelovka and Pakhomovskaya, as well as a sample from Yelovka I, suggest admixture between Andronovans and Western Siberian natives, while Cherkaskul and Korchazhka, like the Late Krotovo groups from Sopka and Cherno-Ozerye and the Begazy-Dandybai group of Baraba, deviate from the Northern Eurasian formation toward Okunev rather than Andronovo. Among the two Eurasian formations, the Southern one (i.e., Okunev) was more affected by admixture between the autochthones and the immigrants.