Experimental study on evaluation of density, P-wave velocity, thermal conductivity, and thermal diffusion coefficient of granite after thermal treatments by using PCA.

Temperature significantly influences the physical parameters of granite, resulting in variations in the rock's thermal conductivity. In order to examine the impact of changes in multiple physical parameters of granite at different temperatures on the thermal conductivity of rocks, Principal Component Analysis (PCA) was employed to determine the correlation between granite at different temperatures and various physical parameters, including density (ρ), P-wave velocity (P), thermal conductivity (KT), and thermal diffusion coefficient (KD). Utilizing the linear contribution rate, a single indicator 'y' was derived to comprehensively represent the thermal conductivity of rocks. Research findings indicate that within the temperature range of 150-450 °C, the 'y'-value is relatively high, signifying favorable thermal conductivity of the rock. Notably, longitudinal wave velocity demonstrates higher sensitivity to temperature changes compared to other physical parameters.

Methylated derivatives of polycyclic aromatic hydrocarbons in road dust, green belt soil and parking lot dust: occurrence, spatial distribution and emission sources.

Convenient transportation facilities not only bring the higher standard of living to big cities, but also bring some environmental pollution problems. In order to understand the presence and sources of methylated polycyclic aromatic hydrocarbons (Me-PAHs) in environmental samples and their association with total organic carbon (TOC), 49 Me-PAHs were analyzed in road dust, green belt soil and parking lot dust samples in Harbin. The results showed that the ranges of the total Me-PAHs (ΣMe-PAHs) content in road dust were 221-5826 ng/g in autumn and 697-7302 ng/g in spring, and those in green belt soil were 170-2509 ng/g and 155-9215 ng/g in autumn and spring, respectively. And ΣMe-PAHs content in parking lot dust ranged from 269 to 2515 ng/g in surface parking lots and from 778 to 10,052 ng/g in underground parking lots. In these samples, the composition profile of Me-PAHs was dominated by 4-ring Me-PAHs. The results of diagnostic ratios and principal component analysis (PCA) indicated that petrogenic and pyrogenic sources were the main sources of Me-PAHs in the samples. Spearman correlation analysis showed that there was no correlation for Me-PAHs in road dust and green belt soil on the same road. Furthermore, there was a significant positive relationship (0.12 ≤ R2 ≤ 0.67, P < 0.05) between Me-PAHs concentrations and the TOC content. This study demonstrated the presence of Me-PAHs with high concentrations in the road environment samples of Harbin.

Exploiting Principal Component Analysis (PCA) to reveal temperature, buffer and metal ions' role in neuromelanin (NM) synthesis by dopamine (DA) oxidative polymerization.

Neuromelanin (NM) plays a well-established role in neurological disorders pathogenesis; the mechanism of action is still discussed and the investigations in this field are limited by NM's complex and heterogeneous composition, insolubility, and low availability from human brains. An alternative can be offered by synthetic NM obtained from dopamine (DA) oxidative polymerization; however, a deep knowledge of the influence of both physicochemical parameters (T, pH, ionic strength) and other compounds in the reaction media (buffer, metal ions, other catecholamines) on DA oxidation process and, consequently, on synthetic NM features is mandatory to develop reliable NM preparation methodologies. To partially fulfill this aim, the present work focuses on defining the role of temperature, buffer and metal ions on both DA oxidation rate and DA oligomer size. DA oxidation in the specific conditions is monitored by UV-Vis spectroscopy and Principal Component Analysis (PCA) is run either on the raw spectra to model the background absorption increase, related to small DA oligomers formation, or on their first derivative to rationalize DA consumption. After having studied three case studies, 3-Way PCA is applied to directly evaluate the effect of temperature and buffer type on DA oxidation in the presence of different metal ions. Despite the proof-of-concept nature of the work and the number of compounds still to be included in the investigation, the preliminary results and the possibility to further expand the chemometric approach represent an interesting contribution to the field of in vitro simulation of NM synthesis.

Comparative analysis of primary health care attributes between children under and over 3 years of age using the primary care assessment tool.

INTRODUCTION: Child health actions in Brazil have their primary focus on early childhood. A new epidemiological profile is emerging for children after the first one thousand days: an increase in non-communicable chronic diseases. This research aimed to analyze the attributes of Primary Health Care comparatively among different age groups, using three years of age as the cutoff point. METHODS: The study design was cross-sectional and conducted in three Primary Health Care Units and three Ambulatory Medical Assistance facilities in the Western Region of São Paulo. The PCA Tool Brazil was used as the assessment instrument. RESULTS: A total of 311 interviews were conducted with caregivers of children aged 0 to 12 years; 153 children were under three years old, and 158 were three years or older. The attributes that showed statistically significant differences between age groups (< 3 years and > 3 years) were affiliation (4.9 × 3.8), longitudinality (5.7 × 5.2), information system (7.4 × 6.3), and services provided (5.4 × 4.5). Through linear regression analysis, it was observed that there was a trend for better overall and essential scores in the evaluations of the group of children under three years old who attended Primary Health Care Units. CONCLUSION: The comparative analysis of Primary Health Care attributes among pediatric age groups revealed a trend towards higher scores, according to caregivers' perceptions, for children under three years old. This study suggests the need for the implementation of programs that can better address the healthcare needs of children beyond early childhood.

Diagnostic efficacy and interobserver agreement among readers with variable experience of the Prostate Imaging for Recurrence Reporting system with whole-mount histology after androgen deprivation therapy as a reference.

Background: The Prostate Imaging for Recurrence Reporting (PI-RR) system was recently proposed to assess the local recurrence of prostate cancer (PCa), but its exact performance for the prostate after radiotherapy or radical prostatectomy is difficult to determine. We aimed to evaluate the diagnostic performance and interreader agreement of this system using whole-mount histology of the prostate after androgen deprivation therapy (ADT) as the standard of reference. Methods: In total, 119 patients with PCa post-ADT underwent multiparametric magnetic resonance imaging (mp-MRI) before prostatectomy. Three radiologists analyzed the MRI images independently, scoring imaging findings according to PI-RR. Spearman correlation was performed to assess the relationship between the percentage of sectors with residual cancer and PI-RR score. The diagnostic performance for detection of residual cancer was assessed on a per-sector basis. The chi-squared test was used to compare the cancer detection rate (CDR) among readers. Overall and pairwise interreader agreement in assigning PI-RR categories and residual cancer sectors with a score ≥3 or ≥4 were evaluated with the Cohen kappa coefficient. Results: Histology revealed 209 sectors with residual cancer. The percentage of pathologically positive sectors increased with the increase in PI-RR score for all readers. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at a cutoff of score 3 ranged from 74.2% to 83.7%, 86.4% to 92.7%, 51.3% to 64.3%, and 95.4% to 96.9%, respectively, and at a cutoff of score 4, they ranged from 47.4% to 56.5%, 97.9% to 98.6%, 82.5% to 85.3%, and 91.6% to 92.9%, respectively. There was no significant difference among the CDR of readers. In PI-RR categories and detection of residual cancer sectors, overall interreader agreement was moderate for all readers, but agreement was higher between the more experienced readers (moderate to substantial) than between the more and less experienced readers (fair to moderate). Conclusions: MRI scoring with the PI-RR assessment provided accurate evaluation of PCa after ADT, but readers' experience influenced interreader agreement and cancer diagnosis.

Prebiotic levan type fructan from Bacillus subtilis PR-C18 as a potent antibiofilm agent: Structural elucidation and in silico analysis.

The global demand for therapeutic prebiotics persuades the quest for novel exopolysaccharides that can retard the growth of pathobionts and healthcare-associated pathogens. In this regard, an exopolysaccharide (3.69 mg/mL) producing strain showing prebiotic and antibiofilm activity was isolated from indigenous pineapple pomace of Tripura and identified as Bacillus subtilis PR-C18. Zymogram analysis revealed EPS PR-C18 was synthesized by levansucrase (∼57 kDa) with a maximal activity of 4.62 U/mg. Chromatography techniques, FTIR, and NMR spectral data revealed the homopolymeric nature of purified EPS with a molecular weight of 3.40 × 104 Da. SEM and rheological study unveiled its microporous structure and shear-thinning effect. Furthermore, EPS PR-C18 showed remarkable emulsification, flocculation, water retention, water solubilization, and antioxidant activity. DSC-TGA data demonstrated its high thermostability and cytotoxicity analysis verified its nontoxic biocompatible nature. In addition, the antibiofilm activity of EPS PR-C18 was validated using molecular docking, molecular simulation, MM-GBSA and PCA studies, which exhibited its strong binding affinity (-20.79 kcal/moL) with PelD, a virulence factor from Pseudomonas aeruginosa. Together, these findings support the future exploitation of EPS PR-C18 as an additive or adjuvant in food and pharmaceutical sectors.

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood.

INTRODUCTION: We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood. MATERIALS AND METHODS: We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47). RESULTS: A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%. CONCLUSION: A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

Estimation of soil erodibility in Peninsular Malaysia: A case study using multiple linear regression and artificial neural networks.

Soil erodibility (K) is an essential component in estimating soil loss indicating the soil's susceptibility to detach and transport. Data Computing and processing methods, such as artificial neural networks (ANNs) and multiple linear regression (MLR), have proven to be helpful in the development of predictive models for natural hazards. The present case study aims to assess the efficiency of MLR and ANN models to forecast soil erodibility in Peninsular Malaysia. A total of 103 samples were collected from various sites and K values were calculated using the Tew equation developed for Malaysian soil. From several extracted parameters, the outcomes of correlation and principal component analysis (PCA) revealed the influencing factors to be used in the development of ANN and MLR models. Based on the correlation and PCA results, two sets of influencing factors were employed to develop predictive models. Two MLR (MLR-1 and MLR-2) models and four neural networks (NN-1, NN-2, NN-3, and NN-4) optimized using Levenberg-Marquardt (LM) and scaled conjugate gradient (SCG) were developed and evaluated. The model performance validation was conducted using the coefficient of determination (R2), mean squared error (MSE), root mean squared error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE). The analysis showed that ANN models outperformed MLR models. The R2 values of 0.446 (MLR-1), 0.430 (MLR-2), 0.894 (NN-1), 0.855 (NN-2), 0.940 (NN-3), and 0.826 (NN-4); MSE values of 0.0000306 (MLR-1), 0.0000315 (MLR-2), 0.0000158 (NN-1), 0.0000261 (NN-2), 0.0000318 (NN-3), and 0.0000216 (NN-4) suggested the higher accuracy and lower modelling error of ANN models as compared with MLR. This study could provide an empirical basis and methodological support for K factor estimation in the region.

Chemical sensing of common microorganisms found in biopharmaceutical industries using MIR laser spectroscopy and multivariate analysis.

Mid-infrared laser spectroscopy was used to investigate common bacteria encountered in biopharmaceutical industries. The study involved the detection of bacteria using quantum cascade laser spectroscopy coupled to a grazing angle probe (QCL-GAP). Substrates similar to surfaces commonly used in biopharmaceutical industries were used as support media for the samples. Reflectance measurements were assisted by Multivariate Analysis (MVA) to assemble a powerful spectroscopic technique with classification and identification resources. The species analyzed, Staphylococcus aureus, Staphylococcus epidermidis, and Micrococcus luteus, were used to challenge the technique's capability to discriminate from microorganisms of the same family. Principal Components Analysis and Partial Least Squares-Discriminant Analysis differentiated between the bacterial species, using QCL-GAP-MVA as the reference. Spectral differences in the bacterial membrane were used to determine if these microorganisms were present in the samples analyzed. Results herein provided effective discrimination for the bacteria under study with high sensitivity and specificity.

Determination of the maximum bioaccumulation capacity of various metals in leaves of two Tillandsia species.

Tillandsia species are plants from the Bromeliaceae family which display biomonitoring capacities in both active and passive modes. The bioaccumulation potential of Tillandsia aeranthos (Loisiel.) Desf. and Tillandsia bergeri Mez acclimated to Southern/Mediterranean Europe has never been studied. More generally, few studies have detailed the maximum accumulation potential of Tillandsia leaves through controlled experiments. The aim of this study is to evaluate the maximum accumulation values of seven metals (Co, Cu, Mn, Ni, Pb, Pt, and Zn) in T. aeranthos and T. bergeri leaves. Plants were immersed in different mono elemental metallic solutions of Co (II), Cu (II), Mn (II), Ni (II), Pb (II), Pt (IV), and Zn (II) ions at different concentrations. In addition, cocktail solutions of these seven metals at different concentrations were prepared to study the main differences and the potential selectivity between metals. After exposure, the content of these metals in the leaves were measured by inductively coupled plasma-optical emission spectrometry. Data sets were evaluated by a fitted regression hyperbola model and principal component analysis, maximum metal loading capacity, and thermodynamic affinity constant were determined. The results showed important differences between the two species, with T. bergeri demonstrating higher capacity and affinity for metals than T. aeranthos. Furthermore, between the seven metals, Pb and Ni showed higher enrichment factors (EF). T. bergeri might be a better bioaccumulator than T. aeranthos with marked selectivity for Pb and Ni, metals of concern in air quality biomonitoring.

Chemical composition and source apportionment of ambient PM2.5 in a coastal urban area, Northern Poland.

Coastal urban areas impact atmospheric chemistry and air quality through various sources, interactions, and processes. This study examines the mass concentrations of fine mode (PM2.5) aerosol and its major and trace components (Al, As, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mo, Mn, Na, Ni, Pb, Sb, Se, Sr, Te, Ti, Tl, V, Zn). The comprehensive field measurements were conducted in Poland between September 2019 and May 2020. Seasonal distribution and drivers of these pollutants showed considerable variability. In winter, higher concentrations were observed for Pb, Co, and As due to the higher contribution of pyrogenic emission. The Principal Component Analysis provided evidence of anthropogenic sources of trace species associated with coal combustion by industry/power plants, brake wear-related emissions, vehicle emissions, shipping activities, road-resuspended dust, and urban construction activities. These results showed that major chemical elements (Ca, Na, Fe, Mg, Al, and K) contributed to 4.07-34.0% of all components. Se, Zn, and Br contributed 1.29%, 1.25%, and 1.04%, respectively, while other tracers ranged between 0.07% and 0.95%. The diagnostic ratio of V/Ni remained stable between 0.45 and 0.46 during the cold season, then increased in spring, indicating that ship emissions were an important source of these metals during the warm season.

The Effect of Processing Conditions on the Microstructure of Homopolymer High-Density Polyethylene Blends: A Multivariate Approach.

In this work, a multivariate approach was utilized for gaining some insights into the processing-structure-properties relationships in polyethylene-based blends. In particular, two high-density polyethylenes (HDPEs) with different molecular weights were melt-compounded using a twin-screw extruder, and the effects of the screw speed, processing temperature and composition on the microstructure of the blends were evaluated based on a Design of Experiment-multilinear regression (DoE-MLR) approach. The results of the thermal characterization, interpreted trough the MLR (multilinear regression) response surfaces, demonstrated that the composition of the blends and the screw rotation speed are the two most important parameters in determining the crystallinity of the materials. Furthermore, the rheological data were examined using a Principal Component Analysis (PCA) multivariate approach, highlighting also in this case the most prominent effect of the weight ratio of the two base polymers and the screw rotation speed.

Archetype analysis and the PHATE algorithm as methods to describe and visualize pregnant women's levels of physical activity knowledge.

The knowledge of physical activity (PA) recommended for pregnant women and practical application of it has positive impact on the outcome. Nevertheless, it is estimated that in high-income countries over 40% of pregnant women are insufficiently physically active. One of the reasons is insufficient knowledge pregnant women have about allowed effort during pregnancy and both recommended and not recommended physical activities. Description of knowledge about physical activity the women have and distinguishing patterns of their knowledge is becoming an increasingly important issue. A common approach to handle survey data that reflect knowledge involves clustering methods or Principal Component Analysis (PCA). Nevertheless, new procedures of data analysis are still being sought. Using survey data collected by the Institute of Mother and Child Archetypal analysis has been applied to detect levels of knowledge reflected by answers given in a questionnaire and to derive patterns of knowledge contained in the data. Next, PHATE (Potential of Heat-diffusion for Affinity-based Trajectory Embedding) algorithm has been used to visualize the results and to get a deeper insight into the data structure. The results were compared with picture derived from PCA. Three archetypes representing three patterns of knowledge have been distinguished and described. The presentation of complex data in a low dimension was obtained with help of PHATE. The formations revealed by PHATE have been successfully described in terms of knowledge levels reflected by the survey. Finally, comparison of PHATE with PCA has been shown. Archetype analysis combined with PHATE provides novel opportunities in examining nonlinear structure of survey data and allows for visualization that captures complex relations in the data. PHATE has made it possible to distinguish sets of objects that have common features but were captured neither by Archetypal analysis nor PCA. Moreover, for our data, PHATE provides an image of data structure which is more detailed than interpretation of PCA.

Phytochemical composition of Lagenaria siceraria fruits from KwaZulu-Natal and Limpopo, South Africa.

Lagenaria siceraria (Molina) Standley is a food and medicinal source with anti-proliferative, anti-fertility, anti-HIV and anti-cancerous properties. The current study investigated the phytochemical constituents of L. siceraria fruits using gas chromatography/mass spectrometry (GC-MS). Five isoprenoids present in all investigated landraces were 1-Dodecene, 2,3-Dimethyldodecane, E-15-Heptadecenal, Eicosane, and Tridecane, 6-propyl. Lighter metabolites such as 1-Dodecene and 2,3-Dimethyldodecane were recorded at a shorter retention time range of 9.08-16.29 min over a lower relative peak area ranging from 1.09 to 6.97%. However, heavier compounds (E-15-Heptadecenal, Eicosane and Tridecane, 6-propyl) had a longer retention time range of 13.42-18.00 mins over a higher relative peak area range of 2.25-11.41%. Cluster analysis grouped landraces into 5 clusters (I -V) according to their fruit and seed attributes, and isoprenoid units significant to each cluster. Terpenoids were the prominent phytochemicals present in fruits. This is the most comprehensive study on the fruit phytochemical constituents of different L. siceraria landraces to date.

ASPMN Position Statement: Authorized Agent Controlled Analgesia.

The American Society for Pain Management Nursing (ASPMN) has reviewed and updated its position statement on the use of authorized agent controlled analgesia (AACA) for patients who are unable to independently utilize a self-dosing analgesic infusion pump, commonly known as patient-controlled analgesia (PCA). ASPMN continues to support the use of AACA to provide timely and effective pain management while promoting equitable care for vulnerable patient populations who are unable to use PCA. ASPMN does not support the use of "PCA by Proxy" in which unauthorized individuals activate PCA for a patient. This position statement includes an updated review of the evidence related to AACA. Clinical practice recommendations for authorized agents, nurses, prescribers, and organizations are provided with an emphasis on the importance of appropriate authorized agent selection, education, diligent patient assessment and medication management.

Assessment of the application of selected metal-organic frameworks as advanced sorbents in passive extraction used in the monitoring of contaminants of emerging concern in surface waters.

Water pollution has become a critical global concern requiring effective monitoring techniques and robust protection strategies. Contaminants of emerging concern (CECs) are increasingly detected in various water sources, with their harmful effects on humans and ecosystems continually evolving. Based on literature reports highlighting the promising sorption properties of metal-organic frameworks (MOFs), the aim of this study was to evaluate the suitability of NH2-MIL-125 (Ti) and UiO-66 (Ce) as sorbents in passive sampling devices (MOFs-PSDs) for the collection and extraction of a wide group of CECs. Solvothermal methods were used to synthesize MOFs, and the characterization of the obtained materials was performed using field-emission scanning electron microscopy (FE-SEM), powder X-ray diffractometry (pXRD) and Fourier-transform infrared (FTIR) spectroscopy. The research demonstrated the sorption capabilities of the tested MOFs, the ease and rapidity of their chemical regeneration and the possibility of reuse as sorbents. Using chemometric analysis, the structural properties of CECs determining the sorption efficiency on the surface of NH2-MIL-125 (Ti) were identified. The MOFs-PSDs were lab-calibrated to examine the kinetics of analytes sorption and determine the sampling rates (Rs). MOFs-PSDs and CNTs-PSDs (PSDs containing carbon nanotubes as a sorbent) were then placed in the Elblag River and the Vistula Lagoon to sampling and extraction of the target compounds from the water. CNTs-PSDs were selected, based on our previous research, for the comparison of the effectiveness of the MOFs-PSDs in environmental monitoring. MOFs-PSDs were successfully used in monitoring of CECs in water. The time-weighted average concentrations (CTWA) of 2-hydroxycarbamazepine, carbamazepine-10,11-epoxide, p-nitrophenol, 3,5-dichlorophenol and caffeine were determined in the Elblag River and CTWA of metoprolol, diclofenac, 2-hydroxycarbamazepine, carbamazepine-10,11-epoxide, p-nitrophenol, 3,5-dichlorophenol and caffeine were determine in the Vistula Lagoon using MOFs-PSDs and a high-performance liquid chromatography coupled with triple quadrupole mass spectrometer.

Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease.

Introduction: Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods: Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results: Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion: We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions.

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region's significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Quantitative integrative taxonomy informs species delimitation in Teloschistaceae (lichenized Ascomycota): the genus Wetmoreana as a case study.

The genus Wetmoreana was studied using quantitative integrative taxonomy methods to resolve the genus delimitation and explore its taxonomy diversity at the species level. As a result, the genus Fulgogasparrea is synonymized with Wetmoreana, and the latter includes 15 formally described species, one subspecies, and three further, thus far undescribed species: W. appressa, W. awasthii comb. nov., W. bahiensis sp. nov., W. brachyloba comb. nov., W. brouardii, W. chapadensis comb. nov., W. circumlobata sp. nov., W. decipioides, W. intensa comb. nov., W. ochraceofulva comb. nov., W. rubra sp. nov., W. sliwae sp. nov., W. sliwae ssp. subparviloba subsp. nov., W. subnitida comb. nov., W. texana, and W. variegata sp. nov. Eleven of 19 examined taxa are newly placed within this genus or confirmed to belong to it. Two species, W. awasthii and W. intensa, are transferred to Wetmoreana without additional analysis but based on previous studies. The W. brouardii and W. ochraceofulva species complexes are discussed in detail. Additionally, Caloplaca muelleri and C. rubina var. evolutior are transferred to Squamulea, and the latter is elevated to the species rank.

Efficiency of clustering methods and self-organizing maps of Adriatic sardines and anchovies regarding organochlorine and fatty acid burden.

The Adriatic Sea plays a crucial role as both a significant fishing ground and a thriving trading market for small pelagic edible fish. Recognized for their nutritional value, these fish are esteemed for their high protein content and abundance of polyunsaturated omega-3 and omega-6 fatty acids, making them a sought-after and healthful food choice. Nevertheless, pelagic species can also serve as a reservoir for lipophilic organochlorine pollutants, posing potential risks to human health. In this study, we compared traditional classification methods traditional principal component analysis (PCA) and Ward's clustering with an advanced self-organizing map (SOM) algorithm in determining distribution patterns of 24 organochlorines and 19 fatty acids in sardine and anchovy samples taken from the eastern Adriatic. The outcomes reveal the strengths and weaknesses of the three approaches (PCA, Ward's clustering, and SOM). However, it is evident that SOM has proven to be the most effective in offering detailed information and data visualization. Although sardines and anchovies exhibit similar distribution patterns for p,p'-DDE, PCB-28, PCB-138, PCB-153, PCB-118, and PCB-170, they differ in the concentrations of fatty acids such as stearic, palmitic, myristic, oleic, docosapentaenoic, and docosahexaenoic acid. Our findings supply valuable insights for environmental authorities and fish consumers concerning the potential risks associated with organochlorines in these two types of fish.