Harmful algal blooms are increasing globally and pose serious health concerns releasing cyanotoxins. Microcystin-LR (MC-LR), one of the most frequently produced cyanotoxins, has recently been detected in aerosols generated by the normal motions of affected bodies of water. MC-LR aerosol exposure has been linked to a pro-inflammatory influence on the airways of mice, however little is understood about the underlying mechanism or the potential consequences. This study aimed to investigate the pro-inflammatory effects of aerosolized MC-LR on murine airways. C57BL/6 and BALB/c mice were exposed to MC-LR aerosols, as these strains are predisposed to type 1/type 17 and type 2 immune responses, respectively. Exposure to MC-LR induced granulocytic inflammation in C57BL/6 but not BALB/c mice, as observed by increased expression of cytokines MIP-1α, CXCL1, CCL2, and GM-CSF compared with their respective vehicle controls. Furthermore, the upregulation of interleukins IL-17A and IL-12 is consistent with Th1 and Th17 driven type 1/type 17 inflammation. Histological analysis confirmed inflammation in the C57BL/6 lungs, with elevated neutrophils and macrophages in the bronchoalveolar lavage fluid and increased pro-inflammatory oxidized lipids. In contrast, BALB/c mice showed no significant airway inflammation. These results highlight the ability of aerosolized MC-LR to trigger harmful airway inflammation, requiring further research.

Photoplethysmography (PPG) signals, which measure blood volume changes through light absorption, are increasingly used for non-invasive Cardiovascular Disease (CVD) detection. Analyzing PPG signals can help identify irregular heart patterns and other indicators of CVD. This research involves a thorough analysis of CVD classification using the Capnobase dataset, which includes data from 20 CVD subjects and 21 normal subjects. In the initial stage, heuristic optimization algorithms, such as ABC-PSO, the Cuckoo Search algorithm (CSA), and the Dragonfly algorithm (DFA), were applied to reduce the dimension of the PPG data. Next, these Dimensionally Reduced (DR) PPG data are then fed into various classifiers such as Linear Regression(LR), Linear Regression with Bayesian Linear Discriminant Classifier (LR-BLDC), K-Nearest Neighbors (KNN), PCA-Firefly, Linear Discriminant Analysis (LDA), Kernel LDA (KLDA), Probabilistic LDA (ProbLDA), SVM-Linear, SVM-Polynomial, SVM-RBF, to identify CVD. Classifier performance is evaluated using Accuracy, Kappa, MCC, F1 Score, Good Detection Rate(GDR), Error rate, and Jaccard Index(JI). The SVM-RBF classifier for ABC PSO dimensionality reduced values outperforms other classifiers, achieving an accuracy of 95.12% with a MCC of 0.90.

Conventional X-ray therapy (XRT) is commonly applied to suppress cancerous tumors, however it often inflicts collateral damage to nearby healthy tissue. In order to provide a better conformity of the dose distribution in the irradiated tumor, proton therapy (PT) is increasingly being used to treat solid tumors. Furthermore, radiosensitization with gold nanoparticles (GNPs) has been extensively studied to increase the therapeutic ratio. The mechanism of radiosensitization is assumed to be connected with an enhancement of the absorbed dose due to huge photoelectric cross-sections with gold. Nevertheless, numerous theoretical studies mostly based on Monte Carlo (MC) simulations did not provide consistent and thorough picture of dose enhancement and, therefore, radiosensitization effect. Radiosensitization by nanoparticles in PT is even less studied than in XRT. Therefore, we investigate physics picture of GNP-enhanced RT using MC simulation with Geant4 equipped with the most recent physics models, taking into account a wide range of physics processes relevant for realistic PT and XRT. Namely, we measured dose enhancement factors in the vicinity of GNP with diameters ranging from 10 nm to 80 nm. The dose enhancement in the vicinity of GNP reaches high values for XRT, while it is very modest for PT. The macroscopic dose enhancement factors for realistic therapeutic GNP concentrations are rather low for all RT scenarios, therefore other physicochemical and biological mechanisms should be additionally invoked for an explanation of the radiosensitization effect observed in many experiments.

The origin of an anomalous excess of high-energy (about 100 GeV and higher) positrons in cosmic rays is one of the rare problems in this field which is proposed to be solved with dark matter (DM). Attempts to solve this problem are faced with the issue of having to satisfy the data on cosmic positrons and cosmic gamma-radiation, which inevitably accompanies positron production such as FSR (final state radiation), simultaneously. We have been trying to come up with a solution by means of two approaches: making assumptions (*) about the spatial distribution of the dark matter, and (**) about the physics of its interactions. This work is some small final step of a big investigation regarding the search for gamma suppression by employing the second approach and a model with a doubly charged particle decaying into two positrons (X++→e+e+) is suggested as the most prospective one from those considered before.

1D spin crossover (SCO) solids which convert between the low-spin (LS) and the high-spin (HS) states are widely studied in the literature due to their diverse thermal and optical characters which allows obtaining many original behaviors, such as large thermal hysteresis, incomplete spin tran-sitions, as multi-step spin transitions with self-organized states. In the present work, we investigate the thermal behaviors of a system of two-elastically coupled 1D mononuclear chains, using the electro-elastic model, by including an elastic frustration in the nearest neighbors (nn) bond length distances of each chain. The chains are made of SCO sites that are coupled elastically through springs with their nn and next-nearest neighbors. The elastic inter-chain coupling includes diagonal springs, while the nn inter-chains distance is fixed to that of the high-spin state. The model is solved using MC simulations, performed on the spin states and the lattice distortions. When we only frustrate the first chain, we found a strong effect on the thermal-dependence of the HS fraction of the second chain, whose, by lowering its transition temperature which is also accompanied with the appearance of a significant residual HS fraction at low temperature. In the second step, we frustrate both chains by imposing different frustration rates and found that, for high frustration values, the thermal dependence of the total HS fraction exhibits three step and even four step spin transitions. The careful examination of the spin state structures in the plateau regions revealed the existence of special antiferro-elastic structure of type LSLS-HSHS-LSLS-HSHS along the first chain, and HSHS-LSLS-HSHS-LSLS along the second, also showing that the two chains seem to be antifer-ro-elastically coupled. This type of organization is interesting, because it anticipates the possible existence of periodic structures made of alternate 1D antiferro-like HS-LS strings coupled in the ferro-like fashion along the interchain direction in the 2D case.

Abstract: Seismic performance and loss assessments can have widely varying degrees of uncertainty. An essential issue is whether a particular assessed seismic loss or performance result has sufficient reliability to serve as the basis for risk management decisions and actions, including whether or not a code prescribed performance level is met, or if an assessed loss level is acceptable. A method is developed measuring the reliability of performance and loss assessments for individual buildings and for portfolios. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the evaluation, and the technical validity of the assessment procedure or model. The approach characterizes the uncertainty of each component of the assessment procedure for each building in qualitative terms. The resulting reliability measure is likely to be most useful for the cases where an entity is determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low risk of seismic damage loss over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

Irrigation with water containing a variety of microcystins (MCs) may pose potential threat to normal growth of agricultural plants. The mechanism of microcystin-LR (MC-LR) induced phytotoxicity in rice (Oryza sativa L.) at environmental concentrations is still unknown. Rice seedlings were exposed to MC-LR at concentrations of 0.10, 1.0, 10.0 and 50.0 μg·L−1 in hydroponic nutrient solutions for 7, 15, 20, and 34 days in the current study. The absorption and accumulation in leaf and root tissues, as well as a series of key physio-biochemical process changes in leaves of rice at different exposure time points were measured. Results showed that MC-LR could be detected in rice leaves and roots in all exposure groups, however, a significant accumulation trend of MC-LR in plants (BCF > 1) was only found in the lowest group (0.10 μg·L−1). The time-course study revealed a biphasic response of O2•- levels in rice leaves to the exposure of MC-LR, which was more pronounced in higher concentration groups, which could be attributed to the combined effects of antioxidant and detoxification mechanisms in rice. Exposure to 1.0 - 50.0 μg·L−1 MC-LR resulted in significant depletion of GSH and MDA contents in rice leaves at later exposure times. The changes of nitric oxide synthase (NOS) in rice leaves under MC-LR exposure were firstly investigated in the current study. Low MC-LR concentrations promoted NOS activity, whereas high concentrations inhibited NOS activity during the later exposure times, implying that NO may play a role in MC-LR toxicity in rice. Reduced sucrose synthase (SS) activities in rice exposed to MC-LR can reduce the plant's ability to accumulate carbon and thus may be directly related to the reduction in vegetative growth. These findings suggest that even at low concentrations of MC-LR, terrestrial plants' normal physiological status is disrupted, which, when combined with previous findings, helps reveal the mechanism of MC-LR-induced phytotoxicity.

Rationale:First discovered in 1990, the endocannabinoid system (ECS) was initially shown to have an intimate relationship with central areas of the nervous system associated with pain, reward, and motivation. Recently, however, the ECS has been extensively implicated in the cardiovascular system with contractility, heart rate, blood pressure, and vasodilation. Emerging data demonstrates modulation of the ECS plays an essential role in cardio metabolic risk, atherosclerosis, and can even limit damage to cardiomyocytes during ischemic events.Patient Concerns:This case describes a 63-year-old male who presented to a primary care physician for a medical cannabis (MC) consult due to unstable angina (UA) not relieved by morphine or cardiac medications; having failed all first- and second-line poly-pharmaceutical therapies. The patient reported frequent, unprovoked, angina and exertional dyspnea.Diagnosis:Having a complex cardiac history, the patient first presented 22 years ago after a suspected myocardial infarction (MI). He re-presented in 2010 and underwent stent placement at that time for inoperable triple-vessel coronary artery disease (CAD) which was identified via percutaneous transluminal coronary angioplasty. UA developed on follow up and, despite medical management over the past 6 years, his UA became progressively debilitating.Interventions and Outcomes:In conjunction with his standard cardiac care, patient had a gradual lessening of UA related pain, including frequency and character, after using an edible form of medical cannabis (MC) (1:1 CBD:THC). Following continued treatment, he ceased long term morphine treatment and describes the pain as no longer crippling. As demonstrated by his exercise tolerance tests, the patient experienced an improved functional capacity and reported an increase in his daily functioning, and overall activity.Lessons:This case uniquely highlights MC in possibly reducing the character, quality, and frequency of UA; while concordantly improving functional cardiac capacity in a patient with CAD. Additional case reports are necessary to verify this.

To assess the degree to which it has met its commitments under the Paris Agreement, Morocco is called upon to carry out carbon assessments and transparent evaluations. Within the forestry sector, little is known about the role of Morocco’s forests in contributing to carbon uptake. With this aim, we applied for the first time in literature the 3-PG model to Cedrus atlantica ((Endl.) Manetti ex Carrière, 1855), which represents about 131.800 ha of Morocco’s forest area (i.e. Azrou forest). Through the Differential Evolution - Markov Chains (DE-MC) we tested and assessed the sensitivity and calibrated the 3-PG model. This process-based model provided significant results regarding the carbon sequestration capacity. The results showed the following: i- Parameters related to stand properties, canopy structure, and processes, as well as biomass partitioning, are the most important or sensitive for the performance of the model; ii- The DE-MC method optimized the values of the 3-PG parameters which was confirmed by the means of Gelman-Rubin convergence test; iii- According to the predictions of the calibrated 3-PG, the Net Primary Production in the pure Azrou forest varies between 0.32 and 7.88 tC.ha−1.yr−1, it is equal in average to 4.9 tC.ha−1.yr−1, which given the total area corresponds to 7078 tC.yr−1.

Cervical cancer is one of the ailments that endangers the health of women all over the world and causes infertility. Fortunately, this disease can be avoided. Both the results and participation rates of the current preventative strategy remain poor. Hence, preventative or early detection methods remain challenging and open. In gynecology and computer science fields, few studies on identifying cervical cancer are based on behavior risk factor and machine learning. Moreover, various social and behavioral aspects might often make it more difficult to detect cervical cancer especially in low‑ and middle‑income countries (LMICs). Accordingly, focus on predicting the presence of cervical cancer through behavioral risk factors is the basic structure of this research. We proposed an approach to classify cervical cancer from a social-behavioral perspective using logistic regression to predict cervical cancer. We got significantly improved outcomes than the existing methods. Moreover, we used feature engineering to formulate less dimensionality as a pre-processing step and optimized parameters to be prepared for classification phase. The results proved that using the logistic regression with regularization type L1 had a promising performance. The accuracy of Logistic Regression (LR) L1 was 97.2%. Such results support the proposed work as a reliable classification predictive tool.

The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling disordered protein interactions and unfolded states of globular proteins. It is based on the CABS coarse-grained protein model that uses a Monte Carlo (MC) sampling scheme and a knowledge-based statistical force field. We review several case studies showing that description of protein disordered states resulting from CABS simulations is consistent with experimental data. The case studies comprise investigations of protein-peptide binding and protein folding processes. The CABS model has been recently made available as the simulation engine of multiscale modeling tools enabling studies of protein-peptide docking and protein flexibility. Those tools offer customization of the modeling process, driving the conformational search using distance restraints, reconstruction of selected models to all-atom resolution and studies of large protein systems in a reasonable computational time. Therefore, CABS can be combined in integrative modeling pipelines incorporating experimental data and other modeling tools of various resolution.

Artificial groundwater recharge is commonly used for drinking water supply. The resulting water quality is highly dependent on the raw water quality. In many cases, pre-treatment is required. Pre-treatment improves the drinking water quality, although how and to what extent it affects the subsequent pond water quality and infiltration process, is still unknown. We evaluated two treatment systems by applying different pre-treatment methods for raw water from a eutrophic and temperate lake. An artificial recharge pond was divided into two parts, where one received raw water, only filtered through a micro-screen with 500 µm pores (control treatment), while the other part received pre-treated lake water using chemical flocculation with polyaluminium chloride (PACl) combined with sand filtration, i.e. continuous contact filtration (contact filter treatment). Water quality such as cyanobacterial biomass, microcystin-LR as well as organic matter and nutrients were measured in both treatment processes. We found cyanobacterial biomass and microcystin-LR level after the contact filter treatment was significantly different from the control treatment and also significantly different in the pond water. In addition, with contact filter treatment, total phosphorus (TP) and organic matter removal were significantly improved in the end water, TP was reduced by 96 % (< 20 µg/L) and the total organic carbon (TOC) was reduced by 66 % instead of 55 % (TOC content around 2.1 mg/L instead of 3.0 mg/L). This full-scale onsite experiment demonstrated effective pre-treatment would benefit a more stable water quality system, with less variance and lower cyanotoxin risk. In a broader drinking water management perspective, the presented method is promising to reduce cyanotoxin risk, as well as TP and TOC, which are all predicted to increase with global warming and extreme weather.

People who suffer a mild traumatic brain injury (mTBI) have heterogeneous symptoms and disease trajectories, which make it difficult to precisely diagnose and assess complications long-term. Insufficient information is available regarding how to precisely diagnose and assess mTBI. This study identified and compared deficits in cognitive, psychosocial, visual functions, and balance performance between college students with and without histories of mTBI. Global DNA methylation ratio (5-mC%) in blood was also compared as a peripheral epigenetic marker. Twenty-five volunteers participated in this pilot study, including 11 mTBI cases (27.3% females; mean age of 28.7 years, SD=5.92) and 14 healthy controls (64.3% females; mean age of 22.0, SD=4.13). All the participants were assessed for cognitive (by NIH toolbox—executive function, memory, and processing speed), psychological (by PROMIS—depression, anxiety, and sleep disturbances), visual function (by King-Devick and binocular accommodative tests), postural balance performance (by a force plate), and blood 5-mC% (global methylation) levels. Students with mTBI reported significantly poorer episodic memory, severe anxiety, and more sleep disturbance problems. They also had higher blood 5-mC% level (all p’s<.05). No significant differences were found in visual function and postural balance. These findings validate changes in cognitive, psychosocial, and global DNA methylation long after mTBI.

Diabetes mellitus is a chronic disease that affects millions of people worldwide. Article focuses on detecting the presence of diabetes in patients using microarray gene data obtained from the pancreas. Handle the high-dimensional nature of the data, four different dimensionality reduction techniques, namely Bessel Function, Discrete Cosine Transform (DCT), Least Square Linear Regression (LSLR), and Artificial Algae Algorithm (AAA) are used. After reduced the data, Meta-heuristic algorithms are applied like Dragonfly Optimization Algorithm (DOA) and Elephant Herding Optimization Algorithm (EHO) for feature selection. Ten classification techniques are using to classify the data in both the format like without feature selection method and with feature selection method. The classification techniques are Non-Linear Regression (NLR), Linear Regression (LR), Gaussian Mixture Model (GMM), Expectation Maximum (EM), Bayesian Linear Discriminant Classifier (BLDC), Logistic Regression (LoR), Softmax Discriminant Classifier (SDC), Support Vector Machine (SVM) with linear kernel, Support Vector Machine (SVM) with polynomial kernel, and Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. Results showed that the AAA with SVM(RBF) achieved an accuracy of 90% without feature selection. However, when feature selection was applied, with EHO of AAA with SVM(RBF) exhibited the highest accuracy of 95.714%, followed closely by with DOA of AAA with SVM (RBF) at 94.28%.

In this paper, we study the effect of decreasing aperture diameter on signal transmission from the scintillator to the PMT. The apertures have been inserted directly between the scintillator and the photomultiplier. Three different aperture diameters have been used over a wide energy range.A newly developed fast digital spectrometer has been utilised for experimental measurement in the radial channel of the VR-1 research reactor. The detector signals with and without inserted apertures have been measured and evaluated. The aim of our research was to determine the effect of the apertures on the spectral quality, energy range and the evaluated physical quantities.

Bacillus species produce different classes of antimicrobial and antioxidant substances: peptides or proteins with different structural composition and molecular mass and a broad range of volatile organic compounds (VOCs), some of which may serve as biomarkers for microorganism identification. The aim of this study is the identification of biologically active compounds synthesized by five Bacillus species using gas chromatography coupled to mass spectrometry (GC–MS). The current study profoundly enhances the knowledge of antibacterial and antioxidant metabolites ensuring the unambiguous identification of VOCs produced by some Bacillus species, which were isolated from vegetable samples of potato, carrot, and tomato. Phylogenetic and biochemical studies were used to identify the bacterial isolates after culturing. Phylogenetic analysis proved that five bacterial isolates BSS12, BSS13, BSS16, BSS21, and BSS25 showed 99% nucleotide sequence similarities with Bacillus safensis AS-08, Bacillus cereus WAB2133, and Bacillus acidiproducens NiuFun, Bacillus toyonesis FORT 102 and Bacillus thuringiensis F3, respectively. The crude extract was prepared from bacterial isolates to assess the antibiotic resistance potency and the antimicrobial potential against various targeted multidrug-resistant strains, including Candida albicans, Candida krusei, Enterococcus hirae, Escherichia coli, Klebsiella aerogenes, Klebsiella pneumoniae, Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus group B, Streptococcus mutans, Shigella sonnei, Salmonella enteritidis, Serratia marcescens, Pseudomonas aeruginosa, and Proteus vulgaris. GC–MS analysis of bacterial strains found that VOCs from Bacillus species come in a variety of chemical forms, such as ketones, alcohols, terpenoids, alkenes, etc. Overall, 69 volatile organic compounds were identified from five Bacillus species, and all five were found to share different chemical classes of volatile organic components, which have a variety of pharmacological applications. However, 8 antibacterial compounds with different concentrations were commonly found in all five species: acetoin, acetic acid, butanoic acid, 2-methyl-, oxime-, methoxy-phenyl, phenol, 1,2-benzenedicarboxylic acid, bis(2-methylpropyl) ester, nonanoic acid, and hexadecanoic acid, methyl. The biology and physiology of Bacillus can be better understood using these results, which can also be used to create novel biotechnological procedures and applications. Moreover, because of its exceptional ability to synthesize and produce a variety of different antibacterial compounds, Bacillus species can serve as natural and universal carriers for antibiotic compounds in the form of probiotic cultures and strains to fight different pathogens, including mycobacteria.

Based on the observation and reanalysis data, the relationship between Madden-Julian Oscillation (MJO) over the Maritime Continent (MC) and the tropical Pacific-Indian Ocean temperature anomaly mode is analyzed. The results showed that the MJO over the MC region (100°-140°E, 10°S-5°N) (referred to as MC-MJO) possesses prominent interannual and interdecadal variations and seasonally "phase-locked" features. MC-MJO is strongest in the boreal winter and weakest in the boreal summer. Winter MC-MJO kinetic energy variation has significant relationships with the El Niño-Southern Oscillation (ENSO) in winter and the Indian Ocean Dipole (IOD) in autumn, but it correlates better with the tropical Pacific-Indian Ocean associated mode (PIOAM). The correlation coefficient between the winter MC-MJO kinetic energy index and the autumn PIOAM index is as high as -0.43. This means that when the positive (negative) autumn PIOAM anomaly strengthens, the MJO kinetic energy over the winter MC region weakens (strengthens). However, the correlation between the MC-MJO convection and PIOAM in winter is significantly weaker. The propagation of MJO over the Maritime Continent differs significantly in the contrast phases of PIOAM. During the positive phase of the PIOAM, the eastward propagation of the winter MJO kinetic energy always fails to move across the MC region and cannot enter the western Pacific. However, during the negative phase of the PIOAM, the anomalies of MJO kinetic energy over the MC is not significantly. MJO can propagate farther eastward and enter the western Pacific. One thing must be pointed out that there is a significant difference between the propagation of MJO convection over the MC region in winter and that of the MJO kinetic energy. That said, the MJO convection is more likely to extend to the western Pacific in the positive phases of PIOAM than in the negative phases

Scientific knowledge evolves in small steps, with occasional backsteps to correct inaccuracies, all occurring within a competitive environment. This perspective for the first time looks at the history of latency-related RNA (LR-RNA) that was later renamed latency-associated transcript (LAT). At the 1986 International Herpesvirus Workshop (IHW) meeting in Leeds, England, Daniel L Rock and Anthony B Nesburn first reported the discovery of human herpes virus 1 (HSV-1) latency-related (LR)-RNA that is antisense to ICP0. Less than a month after the IHW meeting a paper was submitted to Science magazine and 8 months later appeared in print thanking “D. Rock for suggesting RNA complementary to the ICP0 message may be present in latently infected cells”. This perspective is not a review of LAT literature but intends to clarify the timeline of LAT discovery and subsequent breakthroughs such as reactivation, apoptosis, CD8+ T cell exhaustion, and LAT expression in different cell types detected during latency. While many review articles have been written about LAT since 1987, the most comprehensive and balanced review about LAT was written by Dr. David Bloom’s group (1). In this overview, I will discuss our original collaboration with Dr. Dan Rock and subsequent work that our group performed, which is still ongoing. Finally, I will discuss the controversies associated with LAT from its inception to current times.

It is estimated that 3 billion tons of concrete are used globally each year. Cement is a critical component of concrete, and its production accounts for nearly 5-7% of global carbon dioxide (CO2) emissions. Producing one ton of concrete (OPC) releases approximately one ton of CO2. These CO2 emissions contribute to the greenhouse effect, leading to global warming, polar ice cap melting, sea level rise, coastal city flooding, land desertification, decreased agricultural productivity, ecosystem damage, and adverse effects on human health. This situation is concerning, and there is an urgent need to minimize CO2 emissions from the cement industry. This paper focuses on incorporating various materials into concrete to increase its strength and reduce emissions of CO2 and other harmful substances, thereby mitigating the impacts of the greenhouse effect and achieving the great vision of carbon neutrality. The study theoretically analyzes the issues of coconut shell disposal in Southeast Asia and waste tire disposal in Europe and the United States. This paper uses Abaqus to model and analyze various green concretes and compares the data with that of ordinary concrete.