Predictors of transition to schizophrenia and other long-lasting non-affective psychoses in first-episode patients with acute and transient psychotic disorders: A validation study

Background and objectives Almost half of the individuals with a first-episode of psychosis who initially meet criteria for acute and transient psychotic disorder (ATPD) will have had a diagnostic revision during their follow-up, mostly toward schizophrenia. This study aimed to determine the proportion of diagnostic transitions to schizophrenia and other long-lasting non-affective psychoses in patients with first-episode ATPD, and to examine the validity of the existing predictors for diagnostic shift in this population. Methods We designed a prospective two-year follow-up study for subjects with first-episode ATPD. A multivariate logistic regression analysis was performed to identify independent variables associated with diagnostic transition to persistent non-affective psychoses. This prediction model was built by selecting variables on the basis of clinical knowledge. Results Sixty-eight patients with a first-episode ATPD completed the study and a diagnostic revision was necessary in 30 subjects at the end of follow-up, of whom 46.7% transited to long-lasting non-affective psychotic disorders. Poor premorbid adjustment and the presence of schizophreniform symptoms at onset of psychosis were the only variables independently significantly associated with diagnostic transition to persistent non-affective psychoses. Conclusion Our findings would enable early identification of those inidividuals with ATPD at most risk for developing long-lasting non-affective psychotic disorders, and who therefore should be targeted for intensive preventive interventions. (AU)

Impact of Preoperative Neutrophil to Prealbumin Ratio Index (NPRI) on Short-Term Complications and Long-Term Prognosis in Patients Undergoing Laparoscopic Radical Surgery for Colorectal Cancer.

Objective: This study aims to evaluate the impact and predictive value of the preoperative NPRI on short-term complications and long-term prognosis in patients undergoing laparoscopic radical surgery for colorectal cCancer (CRC). Methods: A total of 302 eligible CRC patients were included, assessing five inflammation-and nutrition-related markers and various clinical features for their predictive impact on postoperative outcomes. Emphasis was on the novel indicator NPRI to elucidate its prognostic and predictive value for perioperative risks. Results: Multivariate logistic regression analysis identified a history of abdominal surgery, prolonged surgical duration, CEA levels ≥5 ng/mL, and NPRI ≥ 3.94 × 10-2 as independent risk factors for postoperative complications in CRC patients. The Clavien--Dindo complication grading system highlighted the close association between preoperative NPRI and both common and severe complications. Multivariate analysis also identified a history of abdominal surgery, tumor diameter ≥5 cm, poorly differentiated or undifferentiated tumors, and NPRI ≥ 2.87 × 10-2 as independent risk factors for shortened overall survival (OS). Additionally, a history of abdominal surgery, tumor maximum diameter ≥5 cm, tumor differentiation as poor/undifferentiated, NPRI ≥ 2.87 × 10-2, and TNM Stage III were determined as independent risk factors for shortened disease-free survival (DFS). Survival curve results showed significantly higher 5-year OS and DFS in the low NPRI group compared to the high NPRI group. The incorporation of NPRI into nomograms for OS and DFS, validated through calibration and decision curve analyses, attested to the excellent accuracy and practicality of these models. Conclusion: Preoperative NPRI independently predicts short-term complications and long-term prognosis in patients undergoing laparoscopic colorectal cancer surgery, enhancing predictive accuracy when incorporated into nomograms for patient survival.

Mapping soil trace metal distribution using remote sensing and multivariate analysis.

Trace metal soil contamination poses significant risks to human health and ecosystems, necessitating thorough investigation and management strategies. Researchers have increasingly utilized advanced techniques like remote sensing (RS), geographic information systems (GIS), geostatistical analysis, and multivariate analysis to address this issue. RS tools play a crucial role in collecting spectral data aiding in the analysis of trace metal distribution in soil. Spectroscopy offers an effective understanding of environmental contamination by analyzing trace metal distribution in soil. The spatial distribution of trace metals in soil has been a key focus of these studies, with factors influencing this distribution identified as soil type, pH levels, organic matter content, land use patterns, and concentrations of trace metals. While progress has been made, further research is needed to fully recognize the potential of integrated geospatial imaging spectroscopy and multivariate statistical analysis for assessing trace metal distribution in soils. Future directions include mapping multivariate results in GIS, identifying specific anthropogenic sources, analyzing temporal trends, and exploring alternative multivariate analysis tools. In conclusion, this review highlights the significance of integrated GIS and multivariate analysis in addressing trace metal contamination in soils, advocating for continued research to enhance assessment and management strategies.

Recurrence of rectal cancer on the pelvic sidewall after lateral lymph node dissection.

PURPOSE: Although lateral lymph node dissection has been performed to prevent lateral pelvic recurrence in locally advanced lower rectal cancer, the incidence of lateral pelvic recurrence after this procedure has not been investigated. Therefore, this study aimed to investigate the long-term outcomes of patients who underwent lateral pelvic lymph node dissection, with a particular focus on recurrence patterns. METHODS: This was a retrospective study conducted at a single high-volume cancer center in Japan. A total of 493 consecutive patients with stage II-III rectal cancer who underwent lateral lymph node dissection between January 2005 and August 2022 were included. The primary outcome measures included patterns of recurrence, overall survival, and relapse-free survival. Patterns of recurrence were categorized as lateral or central pelvic. RESULTS: Among patients who underwent lateral lymph node dissection, 18.1% had pathologically positive lateral lymph node metastasis. Lateral pelvic recurrence occurred in 5.5% of patients after surgery. Multivariate analysis identified age > 75 years, lateral lymph node metastasis, and adjuvant chemotherapy as independent risk factors for lateral pelvic recurrence. Evaluation of the recurrence rate by dissection area revealed approximately 1% of recurrences in each area after dissection. CONCLUSION: We demonstrated the prognostic outcome and limitations of lateral lymph node dissection for patients with advanced lower rectal cancer, focusing on the incidence of recurrence in the lateral area after the dissection. Our study emphasizes the clinical importance of lateral lymph node dissection, which is an essential technique that surgeons should acquire.

Neonatal heart transplantation in the United States: Trends and outcomes.

BACKGROUND: Heart transplantation in the neonatal period is associated with excellent survival. However, outcomes data are scant and have been obtained primarily from two single-center reports within the United States. We sought to analyze the outcomes of all neonatal heart transplants performed in the United States using the United Network for Organ Sharing (UNOS) dataset. METHODS: The UNOS dataset was queried for patients who underwent infant heart transplantation from 1987 to 2021. Patients were divided into two groups based on age - neonates (<=31 days), and older infants (32 days-365 days). Demographic and clinical characteristics were analyzed and compared, along with follow up survival data. RESULTS: Overall, 474 newborns have undergone heart transplantation in the United States since 1987. Freedom from death or re-transplantation for neonates was 63.5%, 58.8% and 51.6% at 5, 10, and 20 years, respectively. Patients in the newborn group had lower unadjusted survival compared to older infants (p < .001), but conditional 1-year survival was higher in neonates (p = .03). On multivariable analysis, there was no significant difference in survival between the two age groups (p = .43). Black race, congenital heart disease diagnosis, earlier surgical era, and preoperative mechanical circulatory support use were associated with lower survival among infant transplants (p < .05). CONCLUSIONS: Neonatal heart transplantation is associated with favorable long-term clinical outcomes. Neonates do not have a significant survival advantage over older infants. Widespread applicability is limited by the small number of available donors. Efforts to expand the donor pool to include non-standard donor populations ought to be considered.

Multivariate curve resolution-based data fusion approaches applied in 1H NMR metabolomic analysis of healthy cohorts.

BACKGROUND: Metabolomics plays a critical role in deciphering metabolic alterations within individuals, demanding the use of sophisticated analytical methodologies to navigate its intricate complexity. While many studies focus on single biofluid types, simultaneous analysis of multiple matrices enhances understanding of complex biological mechanisms. Consequently, the development of data fusion methods enabling multiblock analysis becomes essential for comprehensive insights into metabolic dynamics. RESULTS: This study introduces a novel guideline for jointly analyzing diverse metabolomic datasets (serum, urine, metadata) with a focus on metabolic differences between groups within a healthy cohort. The guideline presents two fusion strategies, 'Low-Level data fusion' (LLDF) and 'Mid-Level data fusion' (MLDF), employing a sequential application of Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), linking the outcomes of successive analyses. MCR-ALS is a versatile method for analyzing mixed data, adaptable at various stages of data processing-encompassing resonance integration, data compression, and exploratory analysis. The LLDF and MLDF strategies were applied to 1H NMR spectral data extracted from urine and serum samples, coupled with biochemical metadata sourced from 145 healthy volunteers. SIGNIFICANCE: Both methodologies effectively integrated and analysed multiblock datasets, unveiling the inherent data structure and variables associated with discernible factors among healthy cohorts. While both approaches successfully detected sex-related differences, the MLDF strategy uniquely revealed components linked to age. By applying this analysis, we aim to enhance the interpretation of intricate biological mechanisms and uncover variations that may not be easily discernible through individual data analysis.

Multivariate analysis and mathematical modeling of the informativeness of patients cases data in chronic pancreatitis associated with concomitant pathology.

OBJECTIVE: Aim: To investigate and analyze homeostatic disorders in patients with a combination of Chronic Pancreatitis(CP) and Arterial Hypertension (AH) and to develop correcting ways of the detected changes. PATIENTS AND METHODS: Materials and Methods: General clinical, laboratory-instrumental examination of 121 patients, who were undergoing inpatient treatment with a diagnosis of Chronic Pancreatitis in combination with Arterial Hypertension of the II stage during 2021-2022. RESULTS: Results: In the majority of cases of patients signs the increasing in IL-1,6 and Cortisol levels were found. A decrease in Ca to the lower limit of the norm was observed (2.18 ± 0.26 mmol/l to the data of control group patients (2.32 ± 0.12 mmol/l, p= 0.01 ), the levels of trace elements Zn and Se were determined within the reference values. The Atherogenic Index was increased 1.8 times and was significantly different from the control group date. During the FE-1 study, a decrease in the level of this indicator was revealed by 151.71±13.91 mg/g of feces, both to the values of reference values and a significant difference to the data of the control group (241.28±29.17 mg/g of feces, p<0 .05). CONCLUSION: Conclusions: Based on the multivariate linear regression analysis of the obtained data, formulas have been developed that can be used to predict the dynamics of the dependent variable (FE-1, IL-1, Selenium level, Glutathione Peroxidase, blood pressure) according to changes in the studied influencing factors.

Genetic and Lifestyle Risk Factors of Metabolic Dysfunction-Associated Fatty Liver Disease and Its Relationship with Premature Coronary Artery Disease: A Study on the Pars Cohort.

BACKGROUND: The main objective of this study is to identify the risk factors of metabolic dysfunction-associated fatty liver disease (MAFLD) in coronary artery disease (CAD) patients. METHODS: The present retrospective cohort study is part of the Pars Cohort Study (PCS). The participants were categorized as having MAFLD or not. The pattern of independent variables in patients was compared with those who did not have MAFLD. All variables were retained in the multivariable logistic regression model. RESULTS: Totally, 1862 participants with CAD were enrolled in this study. MAFLD was diagnosed in 647 (40.1%) participants. Gender, diabetes, hypertension, tobacco, opium, alcohol, age, weight, waist circumference, cholesterol, HDL, triglyceride, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were significantly different in MAFLD and non-MAFLD patients. Also, the results of multivariable logistic regression show male gender (OR=0.651, 95% CI: 0.470‒0.902, P value=0.01) and opium consumption (OR=0.563, 95% CI: 0.328‒0.968, P value<0.001) to be negative risk factors of MAFLD occurrence in CAD patients. Having diabetes (OR=2.414, 95% CI: 1.740-3.349, P value<0.001), high waist circumference (OR=1.078, 95% CI: 1.055‒1.102, P value<0.01), high triglyceride (OR=1.005, 95% CI: 1.001‒1.008, P value=0.006), and high ALT (OR=1.039, 95% CI: 1.026‒1.051, P value<0.01) were positive risk factors of MAFLD in CAD patients. CONCLUSION: Our study found that consuming opium decreases the likelihood of MAFLD in CAD patients, since these patients have decreased appetite and lower body mass index (BMI). On the other hand, female gender, having diabetes, high waist circumference, high triglyceride levels, and high ALT levels increase the probability of MAFLD in CAD patients.

Species-Specific quantification of bioactive boswellic acids in Boswellia resin using NIR spectroscopy, HPLC and Multivariate data analysis.

The bioactive compounds Acetyl-11-keto-ß-boswellic acid (AKBA) and 11-keto-ß-boswellic acid (KBA), found in the resin of the Boswellia tree, exhibit anti-inflammatory properties, rendering Boswellia resin an intriguing natural medicinal products. However, the content of boswellic acids varies across different Boswellia species and proper knowledge of its species-dependent nature, as well as alternatives to the resource- and time-intensive HPLC analysis, are lacking. Here we present a comprehensive investigation into the boswellic acid content of seven Boswellia species from ten countries and introduce a novel and non-destructive Near-Infrared spectroscopy method for predicting boswellic acid concentrations in solid resin samples. The HPLC-UV reference analysis revealed AKBA concentrations of up to 7.27 % (w/w) with KBA concentrations reaching up to 1.28 % (w/w). Principal Component Analysis of the HPLC and NIR spectroscopy data unveiled species-specific variations, facilitating differentiation based on boswellic acid content, characteristic chromatograms and NIR spectra. Using the HPLC-UV quantification as reference, we developed a Partial Least Squares regression model based on NIR spectra of the resin samples. This model demonstrated highly satisfactory predictive capabilities for AKBA content, achieving a root mean square error of prediction of 0.74 % (w/w) and an R2val of 0.79 in independent test set validation. Although the model was less effective for predicting KBA content, it still offered valuable estimates. The spectroscopic method introduced in this study provides a cost-effective and solvent-free approach for predicting boswellic acid content, demonstrating the potential for application in non-laboratory settings through the use of miniaturized NIR spectrometers. Consequently, this method aligns well with the principles of green chemistry and addresses the growing demand for alternative analytical techniques.

Chemical Characterization of the Essential Oil Compositions of Mentha spicata and M. longifolia ssp. cyprica from the Mediterranean Basin and Multivariate Statistical Analyses.

This present study aims to characterize the essential oil compositions of the aerial parts of M. spicata L. and endemic M. longifolia ssp. cyprica (Heinr. Braun) Harley by using GC-FID and GC/MS analyses simultaneously. In addition, it aims to perform multivariate statistical analysis by comparing with the existing literature, emphasizing the literature published within the last two decades, conducted on both species growing within the Mediterranean Basin. The major essential oil components of M. spicata were determined as carvone (67.8%) and limonene (10.6%), while the major compounds of M. longifolia ssp. cyprica essential oil were pulegone (64.8%) and 1,8-cineole (10.0%). As a result of statistical analysis, three clades were determined for M. spicata: a carvone-rich chemotype, a carvone/trans-carveol chemotype, and a pulegone/menthone chemotype, with the present study result belonging to the carvone-rich chemotype. Carvone was a primary determinant of chemotype, along with menthone, pulegone, and trans-carveol. In M. longifolia, the primary determinants of chemotype were identified as pulegone and menthone, with three chemotype clades being pulegone-rich, combined menthone/pulegone, and combined menthone/pulegone with caryophyllene enrichment. The primary determinants of chemotype were menthone, pulegone, and caryophyllene. The present study result belongs to pulegone-rich chemotype.

Dietary anthocyanin is associated with a lower prevalence of hyperuricemia independently of metabolic syndrome among females: Results from NHANES 2007-2010 and 2017-2018.

OBJECTIVE: Known for anti-inflammatory and antioxidant properties, flavonoid has phytoestrogenic effects, but it is unclear whether its role in hyperuricemia and metabolic syndrome (MetS) differs by gender. Moreover, given the strong association between hyperuricemia and MetS, we aimed to explore whether flavonoid is a protective factor for hyperuricemia, independently of MetS, in different genders. METHODS: Data for 2007-2010 and 2017-2018 were obtained from the National Health and Nutrition Examination Survey (NHANES) and the Food and Nutrient Database for Dietary Studies (FNDDS). To assess the association among flavonoid, hyperuricemia, and MetS, multivariate logistic regression and subgroup analyses were conducted. Besides, to investigate whether the association between flavonoid and hyperuricemia was independent of MetS, multivariate logistic regression models were further conducted to explore the association between flavonoid and MetS among females with hyperuricemia and to investigate the association between flavonoid and hyperuricemia among females after excluding MetS. RESULT: Among 5356 females, anthocyanin intake was inversely associated with the prevalence of hyperuricemia (Q4 vs. Q1: OR 0.49, 95% CI 0.31 to 0.76), and MetS (Q4 vs. Q1: OR 0.68, 95% CI 0.50 to 0.93). Furthermore, subgroup analyses showed the beneficial association between anthocyanin and hyperuricemia among females aged 40 to 59 years and menopausal. However, among 5104 males, no significant association was observed after adjustment for covariates (Q4 vs. Q1: OR 0.81, 95% CI 0.56 to 1.18). While in 372 females with hyperuricemia, no significant association was found between MetS and anthocyanin (Q4 vs. Q1: OR 0.88, 95% CI 0.31 to 2.49). Meanwhile, among 3335 females after excluding MetS, there was still a significant association between anthocyanin and a lower prevalence of hyperuricemia (Q4 vs. Q1: OR 0.38, 95% CI 0.17 to 0.85). CONCLUSION: Dietary anthocyanin is associated with a lower prevalence of hyperuricemia independently of MetS among females. Foods rich in anthocyanin should be emphasized for females, especially those aged 40 to 59 years and menopausal, which may be of potential significance in the prevention of hyperuricemia.

MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation.

BACKGROUND: Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored. METHODS: We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example. RESULTS: In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect. CONCLUSIONS: Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping.

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presents significant challenges due to the absence of standardized methodologies and reliable techniques for coupling analysis of these two modalities. In this study, we introduced a novel method, i.e., the collaborative multi-output variational Gaussian process convergent cross-mapping (CMVGP-CCM) approach to advance coupling analysis of EEG and fNIRS. To validate the robustness and reliability of the CMVGP-CCM method, we conducted extensive experiments using chaotic time series models with varying noise levels, sequence lengths, and causal driving strengths. In addition, we employed the CMVGP-CCM method to explore the NVC between EEG and fNIRS signals collected from 26 healthy participants using a working memory (WM) task. Results revealed a significant causal effect of EEG signals, particularly the delta, theta, and alpha frequency bands, on the fNIRS signals during WM. This influence was notably observed in the frontal lobe, and its strength exhibited a decline as cognitive demands increased. This study illuminates the complex connections between brain electrical activity and cerebral blood flow, offering new insights into the underlying NVC mechanisms of WM.

Factors related to the low-risk perception of driving after cannabis use.

INTRODUCTION: Modifying risk perceptions related to driving after cannabis use (DACU) could deter individuals from enacting this behavior, as low-risk perception is associated with DACU engagement. This study identified sociodemographic characteristics, substance use, other driving behaviors, peer norms, and psychological characteristics that are associated with lower risk perception regarding DACU. METHODS: Canadian drivers aged 17-35 who have used cannabis in the past year (n = 1,467) completed an online questionnaire. A multivariate linear regression model allowed for identifying variables associated with the low-risk perception of DACU (i.e. believing it to be safe as one's driving ability is not impaired by cannabis or by being high). RESULTS: Lower risk perception of DACU was associated with identifying as male, weekly to daily cannabis use, engagement in DACU, general risky driving behaviors, being a passenger of a driver who engages in DACU, number of friends who engage in DACU, and peer approval of DACU. Having driven under the influence of alcohol, living in urban areas, having received traffic tickets in the past three years, and declaring past-week irritability and cognitive problems were associated with holding a higher risk perception related to DACU. DISCUSSION: Road education and prevention programs should target attitudes and perceptions regarding risks shaped by sociocultural norms and past risky driving experiences. They need to reach out more specifically to drivers with the identified characteristics associated with the low-risk perception of DACU. These interventions can potentially help reduce the rate of individuals who engage in this behavior.

Appropriateness of intended antibiotic prescribing using clinical case vignettes in primary care, and related factors.

BACKGROUND: Factors associated with the appropriateness of antibiotic prescribing in primary care have been poorly explored. In particular, the impact of computerised decision-support systems (CDSS) remains unknown. OBJECTIVES: We aim at investigating the uptake of CDSS and its association with physician characteristics and professional activity. METHODS: Since May 2022, users of a CDSS for antibiotic prescribing in primary care in France have been invited, when registering, to complete three case vignettes assessing clinical situations frequently encountered in general practice and identified as at risk of antibiotic misuse. Appropriateness of antibiotic prescribing was defined as the rate of answers in line with the current guidelines, computed by individuals and by specific questions. Physician's characteristics associated with individual appropriate antibiotic prescribing (< 50%, 50-75% and > 75% appropriateness) were identified by multivariate ordinal logistic regression. RESULTS: In June 2023, 60,067 physicians had registered on the CDSS. Among the 13,851 physicians who answered all case vignettes, the median individual appropriateness level of antibiotic prescribing was 77.8% [Interquartile range, 66.7%-88.9%], and was < 50% for 1,353 physicians (10%). In the multivariate analysis, physicians' characteristics associated with appropriateness were prior use of the CDSS (OR = 1.71, 95% CI 1.56-1.87), being a general practitioner vs. other specialist (OR = 1.34, 95% CI 1.20-1.49), working in primary care (OR = 1.14, 95% CI 1.02-1.27), mentoring students (OR = 1.12, 95% CI 1.04-1.21) age (OR = 0.69 per 10 years increase, 95% CI 0.67-0.71). CONCLUSION: Individual appropriateness for antibiotic prescribing was high among CDSS users, with a higher rate in young general practitioners, previously using the system. CDSS could improve antibiotic prescribing in primary care.

Individual appropriateness for antibiotic prescribing is high among CDSS users.CDSS use could passively improve antibiotic prescribing in primary care.Factors associated with appropriateness for antibiotic prescribing for primary care diseases are: prior use of CDSS, general practice speciality vs. other specialities, younger age and mentoring of students.

Multivariate statistical analysis of bioavailability of heavy metals and mineral characterization in selected species of coastal flora.

This study presents a thorough investigation into the concentration of heavy metals and mineral composition within four distinct coastal flora species: Cyperus conglomeratus, Halopyrum mucronatum, Sericostem pauciflorum, and Salvadora persica. Employing rigorous statistical methodologies such as Pearson coefficient correlation, principal component analysis (PCA), analysis of variance (ANOVA), and interclass correlation (ICC), we aimed to elucidate the bioavailability of heavy metals, minerals, and relevant physical characteristics. The analysis focused on essential elements including copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), magnesium (Mg2+), calcium (Ca2+), sodium (Na+), potassium (K+), and chloride (Cl-), all of which are known to play pivotal roles in the ecological dynamics of coastal ecosystems. Through PCA, we discerned distinctive patterns within PC1 to PC4, collectively explaining an impressive 99.65% of the variance observed in heavy metal composition across the studied flora species. These results underscore the profound influence of environmental factors on the mineral composition of coastal flora, offering critical insights into the ecological processes shaping these vital ecosystems. Furthermore, significant correlations among mineral contents in H. mucronatum; K+ with content of Na+ (r = 0.989) and Mg2+ (r = 0.984); as revealed by ICC analyses, contributed to a nuanced understanding of variations in electrical conductivity (EC), pH levels, and ash content among the diverse coastal flora species. By shedding light on heavy metal and mineral dynamics in coastal flora, this study not only advances our scientific understanding but also provides a foundation for the development of targeted environmental monitoring and management strategies aimed at promoting the ecological sustainability and resilience of coastal ecosystems in the face of ongoing environmental challenges.

Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.

Multivariate analysis of the phytochemical composition and antioxidant properties in twenty-five accessions across three Achillea species.

This study explored the chemical composition, antioxidant activity, and total phenol content of aerial parts from 25 accessions of three Achillea species (Achillea wilhelmsii C. Koch, Achillea vermicularis Trin., and Achillea tenuifolia Lam.). The plants were collected from various natural habitats across Iran, encompassing regions such as Central, Western, Southern, Northern, Western, and Northwestern parts of the country. Subsequently, they were grown together under field conditions. The study revealed significant variation in essential oil yields among accessions of A. wilhelmsii, ranging from 0.01 to 0.107%, A. vermicularis with a range of 0.075 to 1.5%, and A. tenuifolia showing a variation of 0.1 to 2%. The study utilized Gas Chromatography-Mass Spectrometry (GC-MS) analysis, revealing 75, 49, and 75 compounds in the essential oils of A. wilhelmsii, A. tenuifolia, and A. vermicularis, respectively. Major components included camphor, 1,8-cineole, anethole, α-pinene, and phytol in A. wilhelmsii, 1,8-cineole, camphor, levo-carvone, and δ-terpinene in A. vermicularis, and ß-cubebene, elixene, ß-sesquiphellandrene, 1,8-cineole, camphor, and δ-terpinene in A. tenuifolia. The essential oil compositions of A. wilhelmsii and A. vermicularis were predominantly characterized by oxygenated monoterpenes, whereas that of A. tenuifolia was characterized by sesquiterpenes. Cluster analysis grouped accessions into three clusters, with A. tenuifolia forming a distinct group. Principal Component Analysis (PCA) triplot (62.21% of total variance) confirmed these results and provided insights into compound contributions. Furthermore, total phenolic content and antioxidant activity of the accessions of three species were assessed over 2 years. A. tenuifolia exhibited the highest levels in both categories, with statistically significant linear regression between antioxidant activity and total phenol content for A. tenuifolia and A. wilhelmsii. These findings emphasize significant phytochemical diversity within Achillea species, positioning them as promising natural sources of antioxidants. Further exploration and selection of specific accessions within each species are crucial for unlocking their medicinal potential and supporting cultivation and conservation efforts.

Correlation between triglyceride glucose-body mass index and hypertension risk: evidence from a cross-sectional study with 60,283 adults in eastern China.

BACKGROUND: Insulin resistance (IR) and obesity are established risk factors for hypertension, with triglyceride-glucose (TyG) serving as a recognized surrogate marker for IR. The aim of this study was to investigate the association between TyG-BMI and hypertension in the general population. METHODS: A total of 60,283 adults aged ≥18 years who underwent face-to-face questionnaires, anthropometric measurements, and laboratory examination were included in this study. Multivariable logistic regression models and receiver operating characteristic curve (ROC) were used to determine the association between TyG-BMI and hypertension. The restricted cubic spline model was used for the dose-response analysis. RESULTS: After fully adjusting for confounding variables, multivariate logistic regression model showed a stable positive association between TyG-BMI and hypertension (OR: 1.61 per SD increase; 95% CI: 1.55-1.67; P-trend < 0.001). The multivariate adjusted OR and 95% CI for the highest TyG-BMI quartile compared with the lowest quartile were 2.52 (95% CI 2.28-2.78). Dose-response analysis using restricted cubic spline confirmed that the association between TyG-BMI index and hypertension was linear. Subgroup analyses showed that stronger associations between TyG-BMI index and hypertension were detected in young and middle-aged individuals (P for interaction < 0.05). ROC analysis showed that TyG-BMI index could better predict the risk of hypertension than other parameters (TyG-BMI cut-off value: 207.105, AUC: 0.719, sensitivity 65.5%, specificity 66.8%), particularly among young and middle-aged people. CONCLUSION: The TyG-BMI index was independently associated with hypertension in the study population. Further studies are required to confirm this relationship.