Structural changes in amide I and amide II regions of PCOS women analyzed by ATR-FTIR spectroscopy.

The etiology of PCOS is complex and frequently mis or undiagnosed, which may enhance morbidity and reduce the quality of life. Attenuated total reflection- Fourier transform infrared (ATR-FTIR) spectroscopy examines the structural fingerprints of the biochemical compounds and can provide distinct FTIR spectra of the PCOS cases and controls. The present study recruited 61 PCOS cases and 38 control women. The student's t-test was used to compare BMI, WHR, and lipid profile. The FTIR spectral region was compared among both groups using the Mann-Whitney U test and multivariate analysis involved principal component analysis (PCA) and hierarchical cluster analysis (HCA). FTIR spectra of different phenotypes of PCOS were also analyzed using multivariate analysis. In univariate analysis, PCOS women had significantly higher WHR (p = 0.007), BMI (p = 0.04), triglycerides (p = 0.04), and VLDL (p = 0.02) than the controls. The spectral regions of amide I (1700-1600 cm-1) and amide II (1580-1480 cm-1), were significantly greater in the PCOS group than in the controls (p < 0.01 and p < 0.001, respectively). The PCA and HCA revealed a distinct molecular fingerprint for phenotype A (PCOM + OA + HA) and phenotype B (HA + OA). Our study postulated that the spectral regions of amide I and amide II can distinguish between PCOS cases and control women and it may be used for the diagnosis of cases.

Identification of key biomarkers for early warning of diabetic retinopathy using BP neural network algorithm and hierarchical clustering analysis.

Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by abnormal blood glucose metabolism resulting from insufficient insulin secretion or reduced insulin activity. Epidemiological survey results show that about one third of diabetes patients have signs of diabetic retinopathy, and another third may suffer from serious retinopathy that threatens vision. However, the pathogenesis of diabetic retinopathy is still unclear, and there is no systematic method to detect the onset of the disease and effectively predict its occurrence. In this study, we used medical detection data from diabetic retinopathy patients to determine key biomarkers that induce disease onset through back propagation neural network algorithm and hierarchical clustering analysis, ultimately obtaining early warning signals of the disease. The key markers that induce diabetic retinopathy have been detected, which can also be used to explore the induction mechanism of disease occurrence and deliver strong warning signal before disease occurrence. We found that multiple clinical indicators that form key markers, such as glycated hemoglobin, serum uric acid, alanine aminotransferase are closely related to the occurrence of the disease. They respectively induced disease from the aspects of the individual lipid metabolism, cell oxidation reduction, bone metabolism and bone resorption and cell function of blood coagulation. The key markers that induce diabetic retinopathy complications do not act independently, but form a complete module to coordinate and work together before the onset of the disease, and transmit a strong warning signal. The key markers detected by this algorithm are more sensitive and effective in the early warning of disease. Hence, a new method related to key markers is proposed for the study of diabetic microvascular lesions. In clinical prediction and diagnosis, doctors can use key markers to give early warning of individual diseases and make early intervention.

Evaluating spatiotemporal groundwater quality changes in the Rhodope coastal aquifer system (NE Greece) employing a GIS-assisted hybrid approach of multivariate statistics and inverse geochemical modeling.

This research employs a GIS-assisted approach of multivariate statistics and inverse geochemical modeling to unravel the processes driving groundwater salinization in a complex aquifer system. Multivariate statistical methods define the end-member water groups, identifying dominant processes explaining hydrogeochemical variance in wet and dry season water chemistry datasets. Mineral saturation indices (SIs) and inverse geochemical modeling (IGM) investigate potential geochemical reactions and mixing processes responsible for the observed groundwater compositions and their spatiotemporal evolution along reversed flow paths caused by overexploitation in the Rhodope aquifer system. Results reveal that a concise set of reactant and product phases, including CO2(g), H2O, calcite, gypsum, halite, celestite, plagioclase, K-feldspar, illite, and Ca-montmorillonite, along with ion exchange processes (CaX2, MgX2, and NaX), explains the hydrogeochemical evolution of groundwater along reversed flow paths between genetically and compositionally different surface and groundwater bodies. Systematic changes in water chemistry along the flow paths are attributed to mixing of surface waters and/or different groundwater end-members, dilution by a freshwater component, water-rock interaction (WRI) processes, and ion exchange involving Ca/Mg- and/or Na-clays. The chemical evolution represented by IGMs initiates with the mixing of Aegean seawater and Aspropotamos River, incorporating WRI and ion exchange processes (Mg- and Na-clays) to produce the water chemistry of Vistonida Lake, the only surface water body with hydraulic interaction with the groundwater system in the study area. Statistically-defined end-member water groups effectively explain the groundwater flow system and evolutionary processes between hydraulically connected surface and groundwater bodies. Overall, the fusion of multivariate statistical analysis (MVSA), inverse geochemical modeling (IGM), and GIS techniques proves potent and comprehensive, enhancing understanding of groundwater dynamics, improving prediction accuracy, aiding proficient management, and facilitating data-driven decision-making within the realm of groundwater assessment and management.

A systematic analysis with the hierarchical cluster analysis strategy on the complex interaction of TERT and CTNNB1 somatic mutations in Vietnamese hepatocellular carcinoma patients.

Telomerase reverse transcriptase (TERT) and ß-catenin (CTNNB1) mutations may occur following the hepatocellular carcinoma (HCC) pathway signal. We conducted a Hierarchical cluster analysis study on 408 patients diagnosed with HCC by pathological surgery, identifying TERT promoter and CTNNB1 exon 3 mutations by sequencing. The overall preclinical characteristics, cumulative cut-point values, and the factors associated with these somatic mutations were analyzed in uni/multidimensional scaling model. HBV(+) HCV(-) HCC male patients who were older than 62.74 years old and have TERT promoter mutation as well as AFP > 489.78 ng/ml got a higher risk of HCC grade more than two from 27 % to 200 % with p < 0.05 (RR are from 1.27 [1.09-1.47] to 3.06 [2.04-4.61]). This mutation was a good indicator of grade 2 risk (HR = 0.37 [2.72-0.16], ß = -1.00, p = 0.019). TERT promoter and CTNNB1 exon 3 mutations independently influenced tumor size and tumor site status in grade 3 and HBV(-) HCV (-) male HCC patients, where the hazard rates, respectively, were 0.28 [0.09-0.89], 0.023 [0.0023-0.23] and 0.06 [0.012-0.32] (ß < 0 and p < 0.01). These two mutations inversely impacted each other the tumor sites status, especially in male HCC patients with grade 2 without B, C hepatitis virus (RRCTNNB1 exon 3 mutate - TERT promoter wildtype = 1.12 [1.04-1.20], p < 0.05). Consequently, the mutations in TERT promoter and CTNNB1 exon 3 may synchronize with other factors or independently impact the hepatocarcinogenesis and are important indicators for HCC prognostic in male patients with very high AFP levels or with moderately as well as poorly differentiated in tumor. Our results serve as the basis for further studies to understand the impact of different factors on the outcome of HCC, especially in monitoring and assessing the cancer risk of patients infect HBV and carry mutations.

Chemical compositions of Eucalyptus sp. Essential oils and the evaluation of their combinations as a promising treatment against ear bacterial infections.

BACKGROUND: The chemical composition and biological activities of Eucalyptus essential oils (EOs) have been documented in numerous studies against multiple infectious diseases. The antibacterial activity of individual Eucalyptus EOs against strains that cause ear infections was investigated in our previous study. The study's antibacterial activity was promising, which prompted us to explore this activity further with EO blends. METHODS: We tested 15 combinations (9 binary combinations and 6 combinations of binary combinations) of Eucalyptus EOs extracted by hydrodistillation from eight Tunisian Eucalyptus species dried leaves against six bacterial strains responsible for ear infections: three bacterial isolates (Haemophilus influenzae, Haemophilus parainfluenzae, and Klebsiella pneumoniae) and three reference bacteria strains (Pseudomonas aeruginosa, ATTC 9027; Staphylococcus aureus, ATCC 6538; and Escherichia coli, ATCC 8739). The EOs were analyzed using GC/FID and GC/MS. The major compounds, as well as all values obtained from the bacterial growth inhibition assay, were utilized for statistical analysis. RESULTS: The antibacterial activity of the EO blends exhibited significant variation within Eucalyptus species, bacterial strains, and the applied methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA), based on the diameters of the inhibition zone, facilitated the identification of two major groups and ten subgroups based on the level of antibacterial activity. The highest antibacterial activity was observed for the mixture of EOs extracted from E. panctata, E. accedens, and E. cladoclayx (paac) as well as E. panctata, E. wandoo, E. accedens, and E. cladoclayx (pwac) using the disc diffusion method. Additionally, significant activity was noted with EOs extracted from E. panctata, E. wandoo (pw) and E. panctata, E. accedens (pa) using the broth microdilution method. CONCLUSION: Our findings suggest that certain EO combinations (paac, pwac, pw, and pa) could be considered as potential alternative treatment for ear infections due to their demonstrated highly promising antibacterial activities.

Musculoskeletal Diseases as the Most Prevalent Component of Multimorbidity: A Population-Based Study.

Background/Objectives: Due to their high frequency, common risk factors, and similar pathogenic mechanisms, musculoskeletal disorders (MSDs) are more likely to occur with other chronic illnesses, making them a "component disorder" of multimorbidity. Our objective was to assess the prevalence of multimorbidity and to identify the most common clusters of diagnosis within multimorbidity states, with the primary hypothesis that the most common clusters of multimorbidity are MSDs. Methods: The current study employed data from a population-based 2019 European Health Interview Survey (EHIS). Multimorbidity was defined as a ≥2 diagnosis from the list of 17 chronic non-communicable diseases, and to define clusters, the statistical method of hierarchical cluster analysis (HCA) was performed. Results: Out of 13,178 respondents, multimorbidity was present among 4398 (33.4%). The HCA method yielded six multimorbidity clusters representing the most common diagnoses. The primary multimorbidity cluster, which was prevalent among both genders, age groups, incomes per capita, and statistical regions, consisted of three diagnoses: (1) lower spine deformity or other chronic back problem (back pain), (2) cervical deformity or other chronic problem with the cervical spine, and (3) osteoarthritis. Conclusions: Given the influence of musculoskeletal disorders on multimorbidity, it is imperative to implement appropriate measures to assist patients in relieving the physical discomfort and pain they endure. Public health information, programs, and campaigns should be utilized to promote a healthy lifestyle. Policymakers should prioritize the prevention of MSDs by encouraging increased physical activity and a healthy diet, as well as focusing on improving functional abilities.

Chemical composition, source characteristics, and hygroscopic properties of organic-enriched aerosols in the high Arctic during summer.

Arctic regions are extremely sensitive to global warming. Aerosols are one of the most important short-lived climate-forcing agents affecting the Arctic climate. The present study examines the summertime chemical characteristics and potential sources of various organic and inorganic aerosols at a Norwegian Arctic site, Ny-Ålesund (79°N). The results show that organic matter (OM) accounts for 60 % of the total PM10 mass, followed by sulfate (SO42-). Water-soluble organic carbon (WSOC) contributes 62 % of OC. Photochemical processes involving diverse anthropogenic and biogenic precursor compounds are identified as the major sources of WSOC, while water-insoluble organic carbon (WIOC) aerosols are predominantly linked to primary marine emissions. Despite being a remote pristine site, the aerosols show a sign of chemical aging, evidenced by a significant chloride depletion, which was about 82 % on average during the study period. Nitrogen-containing aerosols are likely stemming from migratory seabird colonies and local dust sources around the sampling site. While biogenic, crustal, and sea salt-derived SO42- account for 37%, 8%, and 5% respectively, the remaining 50% is attributed to anthropogenic SO42-. Through chemical tracers, Pearson correlation coefficient matrix, and Hierarchical Cluster Analysis (HCA), the present study identifies soil biota (terrestrial biogenic) and marine emissions, along with their photochemical oxidation processes, as potential sources of Arctic aerosols during summer, while biomass burning and combustion-related sources have a minor contribution. The chemical closure of hygroscopicity highlights that while organics predominantly control aerosol hygroscopicity in the Arctic summer, specific inorganic components like (NH4)2SO4 can significantly increase it on certain days, affecting aerosol-cloud interactions and climate processes over the Arctic during summer. The present study highlights the high abundance of organics and their vital role in the Arctic climate during summer when natural aerosols are conquered.

The Roles of NOTCH3 p.R544C and Thrombophilia Genes in Vietnamese Patients With Ischemic Stroke: Study Involving a Hierarchical Cluster Analysis.

BACKGROUND: The etiology of ischemic stroke is multifactorial. Several gene mutations have been identified as leading causes of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a hereditary disease that causes stroke and other neurological symptoms. OBJECTIVE: We aimed to identify the variants of NOTCH3 and thrombophilia genes, and their complex interactions with other factors. METHODS: We conducted a hierarchical cluster analysis (HCA) on the data of 100 patients diagnosed with ischemic stroke. The variants of NOTCH3 and thrombophilia genes were identified by polymerase chain reaction with confronting 2-pair primers and real-time polymerase chain reaction. The overall preclinical characteristics, cumulative cutpoint values, and factors associated with these somatic mutations were analyzed in unidimensional and multidimensional scaling models. RESULTS: We identified the following optimal cutpoints: creatinine, 83.67 (SD 9.19) µmol/L; age, 54 (SD 5) years; prothrombin (PT) time, 13.25 (SD 0.17) seconds; and international normalized ratio (INR), 1.02 (SD 0.03). Using the Nagelkerke method, cutpoint 50% values of the Glasgow Coma Scale score; modified Rankin scale score; and National Institutes of Health Stroke Scale scores at admission, after 24 hours, and at discharge were 12.77, 2.86 (SD 1.21), 9.83 (SD 2.85), 7.29 (SD 2.04), and 6.85 (SD 2.90), respectively. CONCLUSIONS: The variants of MTHFR (C677T and A1298C) and NOTCH3 p.R544C may influence the stroke severity under specific conditions of PT, creatinine, INR, and BMI, with risk ratios of 4.8 (95% CI 1.53-15.04) and 3.13 (95% CI 1.60-6.11), respectively (Pfisher<.05). It is interesting that although there are many genes linked to increased atrial fibrillation risk, not all of them are associated with ischemic stroke risk. With the detection of stroke risk loci, more information can be gained on their impacts and interconnections, especially in young patients.

Water quality assessment of Bheemasandra Lake, South India: A blend of water quality indices, multivariate data mining techniques, and GIS.

An integrated approach combining water quality indices (WQIs), multivariate data mining, and geographic information system (GIS) was employed to examine the water quality of Bheemasandra Lake, located adjacent to a sewage treatment plant (STP) in Tumakuru city, India. The analysis of 22 lake water samples, examined before and after the monsoons, revealed that the physicochemical parameters namely - electrical conductivity, biochemical oxygen demand, turbidity, total dissolved solids, ammoniacal nitrogen, nitrates, phosphates, magnesium, total hardness, total alkalinity, and calcium - exceeded the acceptable limits stipulated by national and international standards. The Canadian Council of Ministers of the Environment WQI (pre-monsoon: 25.3; post-monsoon: 33.9) and weighted arithmetic WQI (pre-monsoon: 3398; post-monsoon: 2093) designated the water as unsafe for drinking. Irrigation WQIs (sodium adsorption ratio, sodium percentage, residual sodium carbonate, magnesium hazard, permeability index, and potential salinity) implied water's suitability for irrigation. However, electrical conductivity indicated otherwise. Industrial WQIs (Larson-Skold Index, Langelier Index, Aggressive Index, and Puckorius Scaling Index) illustrated scaling propensity and the chloride sulfate mass ratio alluded galvanic corrosion potential. Hierarchical cluster analysis gathered 22 sampling points into two clusters (cluster 1: relatively lower polluted regions; cluster 2: highly polluted regions) for each season based on similarities in water features. Principal component analysis extracted four (79.07% cumulative variance) and six (87.14% cumulative variance) principal components before and after the monsoons, respectively. These components identified the primary pollution sources as urban sewage and natural lithological processes. WQI maps, created using the inverse distance weighted interpolation technique, enhanced the visualization of spatial-temporal variations. This study highlights the dire consequences of urbanization, STP pollution, and sewage management failures, necessitating that concerned authorities should implement policies and measures to curb the negative impacts on the environment and public health.

Region-specific activation in the accumbens nucleus by itch with modified scratch efficacy in mice - a model-free multivariate analysis.

Itch is a protective/defensive function with divalent motivational drives. Itch itself elicits an unpleasant experience, which triggers the urge to scratch, relieving the itchiness. Still, it can also result in dissatisfaction when the scratch is too intense and painful or unsatisfactory due to insufficient scratch effect. Therefore, it is likely that the balance between the unpleasantness/pleasure and satisfaction/unsatisfaction associated with itch sensation and scratching behavior is determined by complex brain mechanisms. The physiological/pathological mechanisms underlying this balance remain largely elusive. To address this issue, we targeted the "reward center" of the brain, the nucleus accumbens (NAc), in which itch-responsive neurons have been found in rodents. We examined how neurons in the NAc are activated or suppressed during histamine-induced scratching behaviors in mice. The mice received an intradermal injection of histamine or saline at the neck, and the scratching number was analyzed by recording the movement of the bilateral hind limbs for about 45 min after injection. To experimentally manipulate the scratch efficacy in these histamine models, we compared histamine's behavioral and neuronal effects between mice with intact and clipped nails on the hind paws. As expected, the clipping of the hind limb nail increased the number of scratches after the histamine injection. In the brains of mice exhibiting scratching behaviors, we analyzed the expression of the c-fos gene (Fos) as a readout of an immediate activation of neurons during itch/scratch and dopamine receptors (Drd1 and Drd2) using multiplex single-molecule fluorescence in situ hybridization (RNAscope) in the NAc and surrounding structures. We performed a model-free analysis of gene expression in geometrically divided NAc subregions without assuming the conventional core-shell divisions. The results indicated that even within the NAc, multiple subregions responded differentially to various itch/scratch conditions. We also found different clusters with neurons showing similar or opposite changes in Fos expression and the correlation between scratch number and Fos expression in different itch/scratch conditions. These regional differences and clusters would provide a basis for the complex role of the NAc and surrounding structures in encoding the outcomes of scratching behavior and itchy sensations.

Study on Quality Characteristic of Chebulae Fructus and Its Adulterants and Degradation Pathway of Hydrolyzable Tannins.

Chebulae Fructus (CF) is known as one of the richest sources of hydrolyzable tannins (HTs). In this study, ultra-performance liquid chromatography coupled with a photodiode array detector method was established for simultaneous determination of the 12 common phenolcarboxylic and tannic constituents (PTCs). Using this method, quantitative analysis was accomplished in CF and other four adulterants, including Terminaliae Belliricae Fructus, Phyllanthi Fructus, Chebulae Fructus Immaturus, and Canarii Fructus. Based on a quantitative analysis of the focused compounds, discrimination of CF and other four adulterants was successfully accomplished by hierarchical cluster analysis and principal component analysis. Additionally, the total contents of the 12 compounds that we focused on in this study were unveiled as 148.86 mg/g, 96.14 mg/g, and 18.64 mg/g in exocarp, mesocarp, and endocarp and seed of CF, respectively, and PTCs were witnessed to be the most abundant in the exocarp of CF. Noticeably, the HTs (chebulagic acid, chebulanin acid, chebulinic acid, and punicalagin) were observed to be ultimately degraded to chebulic acid, gallic acid, and ellagic acid during sunlight-drying of the fresh fruits. As a result, our study indicated that CF and its adulterants could be distinguished by the observed 12 PTCs, which were mainly distributed in the exocarp of the fruits. The HTs were prone to degrade into the three simple phenolcarboxylic acids during drying or processing, allowing us to obtain a more comprehensive understanding of the PTCs, with great significance in the improved quality of CF and related products.

The influence of drying and storage conditions on the volatilome and cannabinoid content of Cannabis sativa L. inflorescences.

The increasing interest in hemp and cannabis poses new questions about the influence of drying and storage conditions on the overall aroma and cannabinoids profile of these products. Cannabis inflorescences are subjected to drying shortly after harvest and then to storage in different containers. These steps may cause a process of rapid deterioration with consequent changes in precious secondary metabolite content, negatively impacting on the product quality and potency. In this context, in this work, the investigation of the effects of freeze vs tray drying and three storage conditions on the preservation of cannabis compounds has been performed. A multi-trait approach, combining both solid-phase microextraction (SPME) two-dimensional gas chromatography coupled to mass spectrometry (SPME-GC × GC-MS) and high-performance liquid chromatography (HPLC), is presented for the first time. This approach has permitted to obtain the detailed characterisation of the whole cannabis matrix in terms of volatile compounds and cannabinoids. Moreover, multivariate statistical analyses were performed on the obtained data, helping to show that freeze drying conditions is useful to preserve cannabinoid content, preventing decarboxylation of acid cannabinoids, but leads to a loss of volatile compounds which are responsible for the cannabis aroma. Furthermore, among storage conditions, storage in glass bottle seems more beneficial for the retention of the initial VOC profile compared to open to air dry tray and closed high-density polyethylene box. However, the glass bottle storage condition causes formation of neutral cannabinoids at the expenses of the highly priced acid forms. This work will contribute to help define optimal storage conditions useful to produce highly valuable and high-quality products.

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.

A Novel Approach to Analyze Disparities in Colorectal Cancer Screening and Mortality.

INTRODUCTION: Reducing disparities in colorectal cancer (CRC) screening rates and mortality remains a priority. Mitigation strategies to reduce these disparities have largely been unsuccessful. The primary aim is to determine variables in models of healthcare utilization and their association with CRC screening and mortality in North Carolina. METHODS: A cross-sectional analysis of publicly available data across North Carolina using variable reduction techniques with clustering to evaluate association of CRC screening rates and mortality was performed. RESULTS: Three million sixty-five thousand five hundred thirty-seven residents (32.1%) were aged 50 y or more. More than two-thirds (68.8%) were White, while 20.5% were Black. Approximately 61% aged 50 y or more underwent CRC screening (range: 44.0%-80.5%) and had a CRC mortality of 44.8 per 100,000 (range 22.8 to 76.6 per 100,000). Cluster analysis identified two factors, designated social economic education index (factor 1) and rural provider index (factor 2) for inclusion in the multivariate analysis. CRC screening rates were associated with factor 1, consisting of socioeconomic and education variables, and factor 2, comprised of the number of providers per 10,000 individuals aged 50 y or more and rurality. An increase in both factors 1 and 2 by one point would result in an increase in CRC screening rated by 6.8%. CRC mortality was associated with factor 2. An increase in one point in factor 1 results in a decrease in mortality risk by 10.9%. CONCLUSIONS: In North Carolina, using variable reduction with clustering, CRC screening rates were associated with the inter-relationship of the number of providers and rurality, while CRC mortality was associated with the inter-relationship of social, economic, and education variables.

Antidiabetic potency and molecular insights of natural products bearing indole moiety: A systematic bioinformatics investigation targeting AKT1.

Diabetic mellitus (DM) is a chronic disorder, and type 2 DM (T2DM) is the most prevalent among all categories (nearly 90%) across the globe every year. With the availability of potential drugs, the prevalence rate has remained uncontrollable, while natural resources showed a promising potency, and exploring such potential candidates at the preclinical stage is essential. An extensive literature search selected 89 marine and plant-derived indole derivatives with anti-inflammatory, antioxidant, lipid-lowering, etc., activities. However, as we know, drugs have not been able to convert from 'lead' to 'mainstream' due to inadequate drug-ability profiles, as our systematic investigation proved and selected herdmanine_A (HERD_A) and penerpene_D (PENE_D) as the most potential antidiabetic candidates from the library of indole derivatives. Based on our previous network pharmacology study, we selected three new target enzymes: Acetyl-CoA carboxylase 2 (ACACB; PDB ID: 3JRX), cyclin-dependent kinase 4 (CDK4; PDB ID: 3G33), and alpha serine/threonine-protein kinase 1 (AKT1; PDB ID: 3O96) to assess the antidiabetic potency of selected indole derivatives through binding energy or docking score. To conduct molecular docking studies with these enzymes, we used the PyRx-AutoDock platform. Furthermore, molecular dynamic simulation at 100 ns, physicochemical analysis, pharmacokinetics, toxicity assessment, and drug-likeness evaluation suggested that HERD_A and penerpene PENE_D were the most potent inhibitors against AKT1 compared to koenimbine (most potential based on the recorded IC50 value) and murrayakonine_A (most potential based on the docking score). In summary, HERD_A and/or PENE_D have the potential to be used as alternative therapeutic agent for the treatment of diabetes after some pharmacological investigation.

Noninvasive Assessment of Chicken Egg Fertility during Incubation Using HSSE-GC-MS VOC Profiling.

Volatile organic compounds (VOCs) carry crucial information about chicken egg fertility. Assessing the fertility before incubation holds immense potential for poultry industry efficiency. Our study used headspace sorptive extraction-gas chromatography-mass spectrometry to analyze egg VOCs before and during the initial 12 incubation days. A total of 162 VOCs were identified. Hexanal was significantly higher in unfertilized eggs, whereas compounds such as propan-2-ol, propan-2-one, and carboxylic acids were higher in fertilized eggs. Furthermore, the obtained multiple logistic regression model outperformed the partial least-squares-discriminant analysis (PLS-DA) model, demonstrating lower complexity and superior performance. Fertile eggs were accurately identified in the validation set in 68-75% of the cases during the initial 4 days, to 85 and 100% on days 6 and 8. Finally, hierarchical cluster analysis in fertilized eggs revealed the clustering of VOCs of the same chemical class, indicative of their shared biochemical origin. This suggests a promising direction for future research aimed at understanding the biological information embedded in VOCs and their relationship to biochemical processes during embryo development.

Fluorescent multichannel sensor array based on three carbon dots derived from Tibetan medicine waste for the quantification and discrimination of multiple heavy metal ions in water.

A fluorescent multichannel sensor array has been established based on three carbon dots derived from Tibetan medicine waste for rapid quantification and discrimination of six heavy metal ions. Due to the chelation between metal ions and carbon dots (CDs), this fluorescence "turn off" mode sensing array can quantify six metal ions as low as "µM" level. Moreover, the six heavy metal ions display varying quenching effects on these three CDs owing to diverse chelating abilities between each other, producing differential fluorescent signals for three sensing channels, which can be plotted as specific fingerprints and converted into intuitive identification profiles via principal component analysis (PCA) and hierarchical cluster analysis (HCA) technologies to accurately distinguish Cu2+, Fe3+, Mn2+, Ag+, Ce4+, and Ni2+ with the minimum differentiated concentration of 5 µM. Valuably, this sensing array unveils good sensitivity, exceptional selectivity, ideal stability, and excellent anti-interference ability for both mixed standards and actual samples. Our contribution provides a novel approach for simultaneous determination of multiple heavy metal ions in environmental samples, and it will inspire the development of other advanced optical sensing array for simultaneous quantification and discrimination of multiple targets.

HPLC Fingerprint Analysis of Cibotii rhizoma from Different Regions and Identification of Common Peaks by LC-MS.

To establish the fingerprint of Cibotii rhizoma using high-performance liquid chromatography (HPLC) and evaluate the quality of Cibotii rhizoma from different regions using chemometrics to identify the potential quality markers, thirteen batches of Cibotii rhizoma samples were analyzed. the similarity evaluation system of TCM chromatographic fingerprint similarity evaluation was used to confirm common peaks. The SPSS 27 software was used for hierarchical cluster analysis (HCA), and SIMCA 14.1 software was used for principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Moreover, a batch of Cibotii rhizoma was selected for LC-MS analysis and speculated on 15 common components. HPLC fingerprint were established, 15 common peaks were matched, two chromatographic peaks were identified using standard substances (protocatechuic acid and protocatechuic aldehyde), and 13 common components were inferred through liquid chromatograph-mass spectrometer (LC-MS). The 13 batches of the samples showed good similarities (>0.910). The results of HCA, PCA and OPLS-DA showed that 13 batches of samples were divided into three groups, and different markers were selected. The method is simple, rapid and reproducible, and can provide a reference for the overall quality evaluation of Cibotii rhizoma.

Essential oil composition, morphological characterization, phenolic content and antioxidant activity of Iranian populations of Hymenocrater longiflorus Benth. (Lamiaceae).

The study focused on the morphological and chemical characteristics of 200 Hymenocrater longiflorus Benth. genotypes found in natural habitats of eight regions in west of Iran. The primary objective of the study was to assess the morphological and phytochemical variability within populations grown in their natural habitats, with the aim of identifying their potential for domestication and utilization in pre-breeding programs. The plant height (PH) ranged from 50.32 to 69.65 cm, with the highest observed in population P8. The internode distances ranged from 4.7 to 6.47 cm, with the maximum distance found in P4. Flower lengths varied from 1.95 to 2.45 cm, with the minimum and maximum values observed in P4 and P3, respectively. The highest leaf length (5.20 cm) and width (3.87 cm) were recorded in P2. The aerial parts of the plant were utilized to extraction and determine the essential oil (EO) content and composition, which ranged from 0.40 to 0.78% (v/w). The analysis of EO by gas chromatography (GC) and gas chromatography mass spectrometry (GC/MS) identified 26 compounds, constituting 99-99.5% of the EOs. The main compounds in the EO and their percentage range (v/w DW) were tau-cadinol (0.62-55.56), mono (2-ethylhexyl) phthalate (8.10-94.70), elemol (0.21-19.11), ß-spathulenol (0.08-14.39), 4-terpineol (0.23-10.19), and ß-eudesmol (0.21-9.94). The main chemical groups found in EOs included oxygenated sesquiterpenes (1.12-68.43), and phthalates (9.73-94.72). Cluster analysis revealed three distinct chemotypes: chemotype I (populations 1 and 2) with major components of mono (2-ethylhexyl) phthalate, tau-cadinol, and α-elemol; chemotype II (population 5) rich in mono (2-ethylhexyl) phthalate; and chemotype III (populations 3, 4, 6-8) containing tau-cadinol, ß-eudesmol, and 4-terpineol. The study also evaluated total phenolic, total flavonoid, and DPPH free radical scavenging activity in the fifty percent inhibitory concentration (IC50) in leaf and flower samples of the genotypes, along with estimating total anthocyanin content in the flower samples. The total phenolic content (TPC) in leaf and flower samples ranged from 7.89 to 107.18 mg GAE/g DW and 39.98 to 86.62 mg gallic acid equivalent (GAE)/g DW, respectively. Total flavonoid content (TFC) ranged from 81.04 to 143.46 mg QUE/g DW in leaf samples and from 94.82 to 133.26 mg quercetin equivalent (QUE)/g DW in flower samples. DPPHsc IC50 (µg/mL) ranged from 0.65 to 78.74 in leaf samples and from 4.38 to 7.71 in flower samples. Anthocyanin content ranged from 1.89 to 3.75 mg cyanidin-3-glucoside equivalent (C3GE)/g DW among populations. Canonical correspondence analysis and simple correlation demonstrated a strong association and correlations among the studied attributes. The negative correlations between leaf DPPH (DPPH L) IC50 and TFC (- 0.73), TPC (- 0.63), Elemol (- 0.90), and EO (- 0.85) indicate that these compounds have a significant impact on the antioxidant activity of the leaves. Furthermore, Fruit DPPH (DPPH F) IC50 showed a negative correlation with TPC (- 0.79) and TFC (- 0.78), but a positive correlation with flower anthocyanins (0.51), (Z)-ß-Farnesene (0.66), and 4-Terpineol (0.57). Circular cluster analysis categorized the genotypes of all individuals in the eight studied populations into three main categories based on all the studied traits, indicating significant variation in phytochemical and morphological traits among populations, surpassing the within-populations variation.

Natural Radioactivity in Raw Building Materials for Underground Parking Lots and Assessment of Radiological Health Risk for the Population.

This article reports the results of an investigation into the activity concentration of natural radionuclides in raw building materials for underground parking lots, together with the assessment of the radiation hazard for the public related to exposure to ionizing radiations. To this purpose, high-purity germanium (HPGe) γ-ray spectrometry was employed in order to quantify the average specific activity of 226Ra, 232Th, and 40K natural radioisotopes. With the aim to assess any possible radiological health risk for the population, the absorbed γ-dose rate (D), the annual effective dose equivalent outdoor (AEDEout) and indoor (AEDEin), the activity concentration index (I), and the alpha index (Iα) were also estimated, resulting in values that were lower than the maximum recommended ones for humans. Finally, the extent of the correlations existing between the observed radioactivity and radiological parameters and of these parameters with the analyzed samples was quantified through statistical analyses, including Pearson's correlation, a principal component analysis (PCA), and a hierarchical cluster analysis (HCA). As a result, three clusters of the investigated samples were recognized based on their chemical composition and mineralogical nature. Noteworthily, this paper covers a certain gap in science since its topic does not appear in literature in this form. Thus, the authors underline the importance of this work to global knowledge in the environmental research and public health fields.