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Abstract A fundamental property of infectious agents is their particulate nature: infectivity arises from independently-acting particles rather than as a result of collective action. Assemblies of the protein tau can exhibit seeding behaviour, potentially underlying the apparent spread of tau aggregation in many neurodegenerative diseases. Here we ask whether tau assemblies share with classical pathogens the characteristic of particulate behaviour. We used organotypic hippocampal slice cultures from P301S tau transgenic mice in order to precisely control the concentration of extracellular tau assemblies in neural tissue. Whilst untreated slices displayed no overt signs of pathology, exposure to recombinant tau assemblies could result in the formation of intraneuronal, hyperphosphorylated tau structures. However, seeding ability of tau assemblies did not titrate in a one-hit manner in neural tissue. The results suggest that seeding behaviour of tau arises at high concentrations, with implications for the interpretation of high-dose intracranial challenge experiments and the possible contribution of seeded aggregation to human disease.

The corpus luteum (CL) is an important tissue of the female reproductive process which is established through ovulation of the mature follicle. Pulsatile release of prostaglandin F2α from the uterus leads to the regression of luteal cells and restarts the estrous cycle in most non-primate species. The rapid functional regression of the CL, which coincides with decrease of progesterone production, is followed by its structural regression. Although we now have a better understanding of how the CL is triggered to undergo programmed cell death, the precise mechanisms governing CL protein degradation in a very short period of luteolysis remains unknown. In this context, activation of ubiquitin-proteasome pathway (UPP), unfolded protein response (UPR) and autophagy are potential subcellular mechanisms involved. The ubiquitin-proteasome pathway (UPP) maintains tissue homeostasis in the face of both internal and external stressors. The UPP also controls physiological processes in many gonadal cells. Emerging evidence suggests that UPP dysfunction is involved in male and female reproductive tract dysfunction. Autophagy is activated when cells are exposed to different types of stressors such as hypoxia, starvation, and oxidative stress. While emerging evidence points to an important role for the UPP and autophagy in the CL, the key underlying transcriptional mechanisms have not been well-documented. In this review, we propose how CL regression may be governed by the ubiquitin-proteasome and autophagy pathways. We will further consider potential transcription factors which may regulate these events in the CL.

Ordered assemblies of proteins are found in the postmortem brains of sufferers of several neurodegenerative diseases. The cytoplasmic microtubule associated protein tau and alpha-synuclein (αS) are found in an assembled state in Alzheimer's disease and Parkinson's disease, respectively. An accumulating body of evidence suggests a “prion-like” mechanism of spread of these assemblies through the diseased brain. Under this hypothesis, assembled variants of these proteins promote the conversion of native proteins to the assembled state. This likely inflicts pathology on cells of the brain through a toxic gain-of-function mechanism. Experiments in animal models of tau and αS pathology have demonstrated that the passive transfer of anti-tau or anti-αS antibodies induces a reduction in the levels of assembled proteins. This is further accompanied by improvements in neurological function and preservation of brain volume. Immunotherapy is therefore considered one of the brightest hopes as a therapeutic avenue in an area currently without disease-modifying therapy. Following a series of disappointing clinical trials targeting beta-amyloid, a peptide that accumulates in the extracellular spaces of the AD brain, attention is turning to active and passive immunotherapies that target tau and αS. However, there are several remaining uncertainties concerning the mechanism by which antibodies afford protection against self-propagating protein conformations. This review will discuss current understanding of how antibodies and their receptors can be brought to bear on proteins involved in neurodegeneration. Parallels will be made to antibody-mediated protection against classical viral infections. Common mechanisms that may contribute to protection against self-propagating protein conformations include blocking the entry of protein “seeds” to cells, clearance of immune complexes by microglia, and the intracellular protein degradation pathway initiated by cytoplasmic antibodies via the Fc receptor TRIM21. As with anti-viral immunity, protective mechanisms may be accompanied by the activation of immune signaling pathways and we will discuss the suitability of such activation in the neurological setting.

Emotion has a substantial influence on the cognitive processes in humans, including perception, attention, learning, memory, reasoning, and problem solving. Emotion has a particularly strong influence on attention, especially modulating the selectivity of attention as well as motivating action and behavior. This attentional and executive control is intimately linked to learning processes, as intrinsically limited attentional capacities are better focused on relevant information. Emotion also facilitates encoding and helps retrieval of information efficiently. However, the effects of emotion on learning and memory are not always univalent, as studies have reported that emotion either enhances or impairs learning and long-term memory (LTM) retention, depending on a range of factors. Recent neuroimaging findings have indicated that the amygdala and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex mediating memory encoding and formation; and (iii) the hippocampus for successful learning and LTM retention. We also review the nested hierarchies of circular emotional control and cognitive regulation (bottom-up and top-down influences) within the brain to achieve optimal integration of emotional and cognitive processing. This review highlights a basic evolutionary approach to emotion to understand the effects of emotion on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional processing. We also summarize the current state of knowledge on the impact of emotion on memory and map implications for educational settings. In addition to elucidating the memory-enhancing effects of emotion, neuroimaging findings extend our understanding of emotional influences on learning and memory processes; this knowledge may be useful for the design of effective educational curricula to provide a conducive learning environment for both traditional “live” learning in classrooms and “virtual” learning through online-based educational technologies.

The GIMAPs (GTPases of the immunity-associated proteins) are a family of small GTPases expressed prominently in the immune systems of mammals and other vertebrates. In mammals, studies of mutant or genetically-modified rodents have indicated important roles for the GIMAP GTPases in the development and survival of lymphocytes. No clear picture has yet emerged, however, of the molecular mechanisms by which they perform their function(s). Using biotin tag-affinity purification we identified a major, and highly specific, interaction between the human cytosolic family member GIMAP6 and GABARAPL2, one of the mammalian homologues of the yeast autophagy protein Atg8. Chemical cross-linking studies performed on Jurkat T cells, which express both GIMAP6 and GABARAPL2 endogenously, indicated that the two proteins in these cells readily associate with one another in the cytosol under normal conditions. The GIMAP6-GABARAPL2 interaction was disrupted by deletion of the last 10 amino acids of GIMAP6. The N-terminal region of GIMAP6, however, which includes a putative Atg8-family interacting motif, was not required. Over-expression of GIMAP6 resulted in increased levels of endogenous GABARAPL2 in cells. After culture of cells in starvation medium, GIMAP6 was found to localise in punctate structures with both GABARAPL2 and the autophagosomal marker MAP1LC3B, indicating that GIMAP6 re-locates to autophagosomes on starvation. Consistent with this finding, we have demonstrated that starvation of Jurkat T cells results in the degradation of GIMAP6. Whilst these findings raise the possibility that the GIMAPs play roles in the regulation of autophagy, we have been unable to demonstrate an effect of GIMAP6 over-expression on autophagic flux.

Background A 19-year-old woman visited a family medicine clinic to obtain her laboratory test results. This case highlights a close call involving a young woman with a potentially serious condition. Pulmonary embolism (PE) is often overlooked during initial assessments in emergency departments or primary care clinics.Case presentation The patient casually mentioned having a cough toward the end of the consultation, revealing she has been using a salbutamol inhaler due to a family history of asthma. Despite appearing well, she had an audible wheezy cough during the examination.Following a chest X-ray (CXR) that indicated a right lung opacity and possible cardiomegaly, an electrocardiogram (ECG) was arranged. The ECG showed an incomplete right bundle branch block (RBBB) and STT changes in leads V3-V6 and lead 3, prompting her transfer to the emergency department for suspected Pulmonary embolism (PE).Further evaluation confirmed acute on chronic PE, with a positive lupus screen leading to the diagnosis of antiphospholipid syndrome (APS) upon detection of anti-phospholipid antibodies in her serology.Discussion The patient’s case was unique, but a basic CXR was performed to investigate their exertional shortness of breath. This led to appropriate action being taken to ensure the patient’s safety. It is important to note that pulmonary embolism can occur in young individuals, highlighting the need for attentive and skilled healthcare professionals. Basic tests such as CXR and ECG can be crucial in cases of ongoing symptoms where uncertainty exists.

Polymers can be natural or synthetic and are largely used in several applications due to their versatile properties. Polymers can vary widely in their properties and applications, and they are a fundamental part of our everyday life. Polypropylene (PP) is a thermoplastic polymer from the polyolefin family. It is among the most widely used plastics in various automotive and packaging industries. Although PP is widely used in commodity range, still its applications are restricted in niche areas due to lack of toughness which can be improved by incorporation of rubbery materials or fillers. Graphene (G) is one of the nanomaterials used to strengthen polypropylene. Graphene is recognized for its outstanding thermo-mechanical properties, making it a highly desirable material in various fields of science and technology. Benefits gained by incorporation of graphene nanoparticles into polypropylene are studied by researchers. In this study, a finite element analysis is performed which shows the mechanical behaviour of PP and G using ANSYS, which is one of the most powerful finite element analysis (FEA) softwares that can help to perform such simulations to understand stress, strain, deformation of components before actual experimentation. The bending load of 100 N and 1400 N in vertical z-direction are applied for 100% PP model, 100% G model and 50% PP+50% G model and the linear part of stress-strain curve is captured in this analysis.

Abstract Well-known continuous distributions such as Beta and Kumaraswamy distribution are useful for modeling the datasets which are based on unit interval [0,1]. But every distribution is not always useful for all types of data sets, rather it depends on the shapes of data as well. In this research, a three-parameter new distribution named bounded exponentiated Weibull (BEW) distribution is defined to model the data set with the support of unit interval [0,1]. Some fundamental distributional properties for the BEW distribution have been investigated. For modeling dependence between measures in a dataset, a bivariate extension of the BEW distribution is developed, and graphical shapes for the bivariate BEW distribution have been shown. Several estimation methods have been discussed to estimate the parameters of the BEW distribution and to check the performance of the estimator, a Monte Carlo simulation study has been done. Afterward, the applications of the BEW distribution are illustrated using COVID-19 data sets. The proposed distribution shows a better fit than many well-known distributions. Lastly, a quantile regression model from bounded exponentiated Weibull distribution is developed, and its graphical shapes for the probability density function (PDF) and hazard function have been shown.

The focus on sustainable utilization of agricultural waste is currently a leading area of scientific research, driving significant advancements in technology and circular economy models. The fundamental capacity of bio-based products, bioprocessing techniques, and the crucial involvement of microbial treatments are opening opportunities for efficient solutions in various industries. One of the most popular green vegetables, peas are members of the Fabaceae family and have a pod-like structure. Every year, a significant amount of pea pods is discarded as waste products of peas that have negative impacts on our environment. In this comprehensive review, we explore innovative methods for utilizing pea pods to minimize their environmental footprint and optimize their viability across multiple industries. A large portion of the pea processing industry's output consists of pea pods. Variety of proteins, with major classes being globulin and albumin (13%), dietary fiber (43–58%), and minerals are abundant in these pods. Because of their diverse physiochemical properties, they find applications in many diverse fields. The porous pea pods comprised cellulose (61.35%) and lignin (22.12%), which could make them superior adsorbents. The components of these byproducts possess valuable attributes that make them applicable across treatment of wastewater, production of biofuels, synthesis of biocolors, development of nutraceuticals, functional foods, and enzymes for the textile industry, modification of oil, and inhibition of steel corrosion.

Considering the substantial increase in deployment, photovoltaics are hovering to emerge as the predominant worldwide energy producer in the foreseeable future. Nevertheless, the operating efficiency and endurance of photovoltaic (PV) systems are significantly stalled by the heightened operating temperatures encountered by solar radiation. This article comprehensively analyzes novel active and passive PV cooling techniques, encompassing their operational mechanisms, cooling efficiency, and eventual implementations in solar devices. Extensive scholarly research has examined various PV cooling methods and techniques to optimize system cooling and efficiency. The primary goal of this effort is to compile a reference for future researchers and specialists by reviewing and comparing the results of current investigations. The study also comprised a bibliometric analysis that provides valuable insights into the influence of research on incorporating cooling systems into solar systems. These insights play a decisive role in recognizing new trends and progressing the field towards more efficient systems, hence advancing upcoming development. Furthermore, an extensive classification and assessment of every conceivable cooling technology was furnished to facilitate a comparison among diverse cooling methodologies. The research was structured in a tabular manner, containing the following details for each cooling technique: solar panel type, cooling method, cooling fluid or substance used, research category, average temperature reduction resulting from cooling, and enhanced electrical efficiency. The study indicates that cooling methods significantly enhance electrical efficiency, with potential increases varying from 0.28 % to 97.6 %. Additionally, this application is assessed to decrease the solar panel's operative temperature, ranging from 0.8 °C to 39.9 °C.

Hepatitis B is a worldwide viral infection that causes cirrhosis, hepatocellular cancer, the need for liver transplantation, and death. This work proposed a mathematical representation of Hepatitis B Virus (HBV) transmission traits emphasizing the significance of applied mathematics in comprehending how the disease spreads. The work used an updated Atangana-Baleanu fractional difference operator to create a fractional-order model of HBV. The qualitative assessment and well-posedness of the mathematical framework were looked at, and the global stability of equilibrium states as measured by the Volterra-type Lyapunov function was summarized. The exact answer was guaranteed to be unique using the Lipschitz condition. Additionally, there were various analyses of this new type of operator to support the operator's efficacy. We observe that the explored discrete fractional operators will be $ \chi^2 $-increasing or decreasing in certain domains of the time scale $ \mathbb{N}_j: = {j, j + 1, ... } $ by looking at the fundamental characteristics of the proposed discrete fractional operators along with $ \chi $-monotonicity descriptions. For numerical simulations, solutions were constructed in the discrete generalized form of the Mittag-Leffler kernel, highlighting the impacts of the illness caused by numerous causes. The order of the fractional derivative had a significant influence on the dynamical process utilized to construct the HBV model. Researchers and policymakers can benefit from the suggested model's ability to forecast infectious diseases such as HBV and take preventive action.

Abstract The quasi-Poisson regression model is used for count data and is preferred over the Poisson regression model in the case of over-dispersed count data. The quasi-likelihood estimator is used to estimate the regression coefficients of the quasi-Poisson regression model. The quasi-likelihood estimator gives sub-optimal estimates if regressors are highly correlated—multicollinearity issue. Biased estimation methods are often used to overcome the multicollinearity issue in the regression model. In this study, we explore the ridge estimator for the quasi-Poisson regression model to mitigate the multicollinearity issue. Furthermore, we propose various ridge parameter estimators for this model. We derive the theoretical properties of the ridge estimator and compare its performance with the quasi-likelihood estimator in terms of matrix and scalar mean squared error. We further compared the proposed estimator numerically through a Monte Carlo simulation study and a real-life application. We found that both the simulation and application results show the superiority of the ridge estimator, particularly with the best ridge parameter estimator, over the quasi-likelihood estimator in the presence of multicollinearity issue.

Our study pioneers an innovative use of unsupervised machine learning, a powerful tool for navigating unclassified data, to unravel the complexities of subsurface seismic activities and extract meaningful patterns. Our central objective is to comprehensively characterize seismicity within an active region by identifying distinct seismic clusters in spatial distribution, thereby gaining a deeper understanding of subsurface stress distribution and tectonic dynamics. Employing a diverse range of clustering algorithms, with particular emphasis on Fuzzy C-Means (FCM), our research meticulously dissects the intricate physical processes that govern a complex tectonic zone. This technique effectively delineates distinct tectonic zones, aligning seamlessly with established seismological knowledge and underscoring the transformative potential of Artificial Intelligence (AI) in analyzing regional subsurface phenomena, even under conditions of data scarcity. Moreover, associating earthquakes with specific seismogenic structures significantly enhances seismic hazard analyses, potentially paving the way for autonomous insights that inform engineering hazard assessments.

A new network of 16 broadband seismic stations is operational in the northern Chhattisgarh region to monitor the seismicity arising in the otherwise seismically quiescent zone. Ambient noise is comprehensively analyzed to evaluate station performance and validate the data quality. Power spectral densities are computed for all stations, comparing ambient noise levels against global limits for data from November 2022 to December 2023. Results indicate that noise levels consistently fall within global noise limits. The study emphasizes the pronounced effect of instrumental tilt on the horizontal components of broadband seismometers. Spatial variation of ambient noise levels across various period bands of the noise spectrum highlights the contribution of diverse noise sources such as anthropogenic activities, surface waves, body waves, and barometric effects. Seasonal variations in short-period, microseism, and long-period bands reveal temporal variation of noise levels. Diurnal variation in the short-period band indicates a prominent effect of cultural noise. Furthermore, the proximity of seismic stations to major mining areas induces high noise levels in the very short-period band during blasting activities compared to non-blasting periods. Our study thus explores the variability of the ambient noise environment while validating the robustness and stability of the seismic installation across the study region.

Background: The prevalence of microbial infectious diseases is a major contributor to morbidity and mortality on a global scale due to the emergence of antibiotic-resistant microbes, despite the fact that many new antibiotics have been introduced for several decades. In present scenario, the potential utilization of natural plant derived extracts for medicinal and therapeutic purposes has increased remarkably due to adverse effects of synthetic drugs and resistance among pathogenic microbes. Aim of the study: Verbascum thapsus L. (Common mullein) has been traditionally used as a medicine for lung, skin and throat and many other disorders since time immemorial, therefore, the current study was aimed to evaluate the antimicrobial activity of leaf and root extracts of Verbascum thapsus against pathogenic bacterial and fungal strains and its phytochemical composition by spectral studies. Methods: Soxhlet extraction method was employed for extraction process by using varying polarity solvents like hexane, ethyl acetate and methanol. Phytochemical analysis of methanol extract was determined by Fourier Transform-Infrared Spectroscopy (FTIR) and Gas Chromatography-Mass Spectrometry (GC–MS). Antimicrobial activity was evaluated by determining the MIC and MBC/MFC of each extract by broth dilution method. Results: The antimicrobial competence of each extract sample was evaluated against six pathogenic bacterial strains and three fungal strains. Methanolic extract of leaves and the ethyl acetate extract of roots of Verbascum thapsus exhibited significant zones of inhibition against all the tested microorganisms. The highest inhibition zone was observed against the bacterial strain Bacillus subtilis (24.1±0.18 mm) followed by Streptococcus pyogenes (22.9±0.64 mm) and the fungal strain Aspergillus niger (22.8±0.55 mm) at a concentration of 500 μg/ml. Methanolic leaf extract strongly inhibited the growth of tested microbial strains with MIC ranged from 15.625 to 125 μg/ml. The FTIR and GCMS analysis confirms the presence of bioactive compound, possessing broad range of therapeutic activities. Conclusion: This Presence of various important phytoconstituents and broad-spectrum antimicrobial activity points Verbascum thapsus as a promising source for the isolations of molecules responsible for antimicrobial activities.

Aims 1. To measure the extent to which medication orders in inpatient prescription charts conform to the section in BNF (British National Formulary) on prescription writing. 2. To implement changes with the intention of improving prescriptions and administration records. Methods Prescription charts of patients admitted in adult male and female psychiatry ward were analysed in three cycles, (1 September to 20 October 2022, then 1st December to 31st 2022 and then: 1st January 2023 to 28th February 2023) which added up to a total of 431, 170 and 490 prescriptions in respective cycles. Each drug prescription was examined to see if it met the standards outlined in BNF. Percentage of prescriptions meeting each standard was calculated in each cycle. First Cycle was followed by presentation of BNF guidelines of prescription writing on 7th December 2022 and copies of those BNF guidelines were placed at both male and female nursing counters. After 1 month, a short re-audit was done to assess the improvement which was satisfactory but this audit's results were not presented. Lastly, after one year of presentation of BNF guidelines in the department, two months of prescription charts were re-audited in cycle 3. Results •Cycle 1: Initial evaluation revealed significant discrepancies in prescription accuracy and adherence to administration protocols. Key areas for improvement were identified and discussed with the postgraduate residents. •Cycle 2: Following the implementation of targeted interventions, a re-evaluation showed measurable improvements in prescription accuracy and compliance with administration protocols. However, areas for further improvement were still identified, particularly in the documentation of prescription changes. •Cycle 3: The final cycle demonstrated further improvements in prescription practices, with a significant reduction in discrepancies and errors. •Legibility remained high across all cycles, with a slight improvement in Cycle 3. •The use of generic drug names saw a remarkable increase from 40.6% in Cycle 1 to 84.69% in Cycle 3, indicating a strong adherence to best practices. •Block letters usage improved significantly from 17% in Cycle 1 to 71.42% in Cycle 3, enhancing the clarity of prescriptions. •The practice of providing a start date saw near-perfect compliance by Cycle 3, increasing from 82.8% in Cycle 1 to 99.18%. Other findings were similar as well. Conclusion The audit successfully demonstrated the effectiveness of clinical audits in improving prescription quality in male and female adult wards. It highlighted the effectiveness of the interventions and the importance of continuous monitoring and feedback.

Aims Individuals with severe mental illnesses are at an increased risk of morbidity and mortality from cardiovascular diseases compared with the general population. Dyslipidaemia is a well-established contributor to CVD risk, alongside factors such as obesity, hypertension, smoking, diabetes, and a sedentary lifestyle. Many patients with severe mental illnesses often exhibit a combination of these risk factors. Notably, second-generation antipsychotics, particularly clozapine, are associated with a significant risk to elevate lipid levels. However, dyslipidaemia is a treatable condition, and various interventions are available to decrease the risk, ultimately reducing the associated morbidity and mortality. Therefore, NICE guidelines recommend monitoring of lipid profile initially at baseline, 3 months and then annually and cardiovascular risk assessment by validated tools like QRISK3 or Assign Score (validated tool used in Scotland). The first aim of this audit was to see if a lipid profile had been done within the past 12 months in patients on clozapine treatments and second aim was to see if cardiovascular risk had been assessed using a validated tool i.e. Assign Score and lastly to check if lipid results and Assign Score had been communicated to the General Practitioner. Methods The audit included 40 patients receiving clozapine treatment under the care of this local CMHT. We excluded 13 patients who were already on statin medication, those newly initiated on clozapine within the last three months or those who were aged below 30 years or above 74 years. The data collection spans from October 2022 to October 2023. Our analysis focused on bloods results in the last 12 months. After that, we searched for the cardiovascular risk assessment in last 12 months of patients’ electronic notes. Additionally, a comprehensive review of all communication records with General Practitioners was undertaken. Results Lipid profile testing was done in 22 of 27 (81.1%) of the audited patients, revealing that a significant proportion, 59.9% (13 of 22), exhibited elevated total cholesterol levels exceeding 5mmol/L. However, the assessment of cardiovascular risk within the specified timeframe was notably low, with only 1 of 27 (3.70%) of the audited patients undergoing this evaluation. Furthermore, communication with General Practitioners (GPs) regarding lipid profiles was observed in a mere 4 of 22 (18.18%) of cases where such testing was conducted. Conclusion The clinical audit showed a good level of compliance with lipid profile monitoring; however, notable deficiencies were noted in the assessment of cardiovascular risk and communication with GPs. These findings emphasized the need to enhance our compliance with protocols for a more comprehensive approach to safeguard the cardiovascular health of patients receiving clozapine. As a result, we have proposed improvement strategy at our local CMHT meeting involving the implementation of a structured process, wherein the clozapine clinic nurse initiates an electronic task for the relevant medic to review the results. The medic is then tasked with calculating the cardiovascular risk and communicating both lipid results and the risk assessment to the GP, ensuring their inclusion in the annual review correspondence and subsequent management. A repeat audit will be done after 12 months.

In this paper, we present a dynamic model of syphilis. The goal of this work is to provide a mathematical model for syphilis disease that contains information about the suspect, infected, recovered, and exposed. Boundedness, positivity, and unique solutions at equilibrium points are used in the qualitative and quantitative study of a proposed model using the power law kernel. The Routh-Hurwitz stability criteria are used to address the model's local and global stability. Chaos control will use the regulate for linear responses approach to bring the system to stabilize according to its points of equilibrium. Using Lyapunov function tests, the global stability of free and endemic equilibrium points is confirmed. The Lipschitz condition and fixed point theory are utilized to satisfy the requirements for the existence and uniqueness of the exact solution. The generalized form of the power law kernel is solved using a two-step Lagrange polynomial method to investigate the impact of the fractional operator using numerical simulations that illustrate the effects of various parameters on the illness.