Background and Purpose: Fentanyls and nitazenes are μ opioid receptor agonists responsible for a large number of opioid overdose deaths. Here, we compared the potency, dissociation kinetics and antagonism by naloxone at the μ receptor of several fentanyl and nitazene analogues and compared them to morphine and DAMGO. Experimental Approach: In vitro assays of G protein activation and signalling and arrestin recruitment were performed. AtT20 cells expressing μ receptors were loaded with a membrane potential dye and changes in fluorescence used to determine agonist potency, dissociation kinetics and susceptibility to antagonism by naloxone. BRET experiments were undertaken in HEK293T cells expressing μ opioid receptors, to assess Gi protein activation and β-arrestin 2 recruitment. Key Results: The rate of agonist dissociation from the μ receptor varied, with morphine, DAMGO, alfentanil and fentanyl dissociating rapidly whereas isotonitazene, etonitazene, ohmefentanyl and carfentanil dissociated slowly. Slowly dissociating agonists were more resistant to antagonism by naloxone. For carfentanil, the slow rate of dissociation was not due to G protein receptor kinase-mediated arrestin recruitment as its rate of dissociation was not affected by inhibition of GRKs with Compound 101. The in vitro relative potencies of fentanyls and nitazenes compared to morphine were much lower than that previously observed in in vivo experiments. Conclusions and Implications: With fentanyls and nitazenes, that slowly dissociate from the opioid receptor, antagonism by naloxone is pseudo competitive. In overdoses involving fentanyls and nitazenes higher doses of naloxone may be required for reversal than those normally used to reverse heroin overdose.

Background and purpose: Toll like receptors (TLR) 4 and 7/8 play an important role in mediating the inflammatory effects of bacterial and viral pathogens. IRAK4 is an important regulator of TLR signalling, and hence is a potential therapeutic target in diseases characterised by increased lung inflammatory signalling. Experimental approach: We used an established murine model of acute lung inflammation, and studied human lung tissue ex vivo to investigate the effects of inhibiting IRAK4 on lung inflammatory pathways. Key results: We show that TLR4 stimulation produces an inflammatory response characterised by neutrophil influx and TNFα production in murine lungs, and that these responses are markedly reduced in IRAK4 kinase-dead mice. In addition, we characterise a novel selective IRAK4 inhibitor, BI1543673 and show that this compound is able to reduce LPS induced airway inflammation in wild type mice. BI1543673 also reduced inflammatory responses to both TLR4 and TLR 7/8 stimulation in human lung tissue studied ex vivo. Conclusions and implications: These data show demonstrate a key role for IRAK4 signalling in lung inflammation, and suggest that IRAK4 inhibition has potential utility for treating lung diseases characterised by inflammatory responses driven through TLR4 and TLR 7/8.

This paper presents a theoretical inquiry into the domain of secure artificial superintelligence (ASI). The paper introduces an architectural pattern tailored to fulfill friendly alignment criteria. Friendly alignment refers to a failsafe artificial intelligence alignment that lacks supervision, while still having a benign effect on humans.  The proposed solution is based on a biomimetic approach to emulate functional aspects of biological consciousness. This approach is aiming to achieve Synthetic Sentiency. It establishes "morality" that secures alignment  in systems of any proportion. This functional feature set is drawn from a cross-section of evolutionary and psychiatric frameworks.  Furthermore, the paper assesses the architectural potential, practical utility, and limitations of this approach. Notably, the architectural pattern supports straightforward implementation by allowing application of simple algorithms, which despite the simplicity can effectively produce an infinite derivative order, directly influencing alignment strength. The alignment strength can be adjusted by manipulating this order, enhancing adaptability and usability of the solution under constraints in practical applications.

IntroductionBlastic plasmacytoid dendritic cell neoplasm (BPDCN) is an uncommon hematologic malignancy originating from plasmacytoid dendritic cells (1). These cells harbor a specific immunophenotype, positive for CD4 and CD56 and negative for CD3 and CD19(2). The BPDCN is classified as a separate category besides acute myeloid leukemia and B/T cell leukemia/lymphoma in the 2022 World Health Organization Classification of Hematolymphoid Tumors 5th edition (1). It commonly involves skin, and skin lesions including nodules and papules can be the only disease presentation; however, it can involve bone marrow, lymph nodes and spleen (3, 4). Leukemic reaction may also occur. Breast tissue infiltration by BPDCN has been reported in one case (4). Aggressive course and poor prognosis of the patient as well as diagnosis difficulties for pathologists and clinicians are problems that have not been resolved so far. Here we describe a case of BPDCN, someone who presented with a forehead skin lesion with focus on histopathologic diagnosis. Immunophenotyping by immunohistochemistry methods confirmed the diagnosis.

Florida, U.S.A. is a hotspot of biological invasions with over 500 non-native species reported. Reptiles encompass the majority of non-native wildlife with over 50 species established, many of which are sympatric and are identified as invasive due to their impacts to the environment, economy, and human health and safety. Reports of new non-native reptiles occur and many established non-native reptiles continue to expand their ranges in Florida, increasing the need for multi-taxa detection and monitoring capabilities. Invasive constrictor snakes are a primary focus of management efforts due to life history traits that favor successful establishment and dispersal in Florida as well as their impacts to native wildlife and Everglades restoration efforts. While traditional survey methods that rely on visual detections fail to reliably detect invasive constrictors, environmental DNA (eDNA) has proven to be a promising method for detection of cryptic and rare species across the landscape. To address emerging needs for multi-species detection and monitoring in Florida we developed the first tetraplex dPCR assay designed for detection of four species of invasive constrictor snakes, including Burmese pythons (Python bivittatus), northern African pythons (P. sebae), boa constrictors (Boa constrictor), and rainbow boas (Epicrates cenchria). In this tetraplex assay, no cross-amplification across species was documented. This assay serves as a valuable tool for faster and more accurate monitoring efforts of these invasive species in south Florida.

1. Temperature is commonly acknowledged as one of the primary forces driving ectotherm vector populations, most notably by influencing metabolic rates and survival. Although numerous experiments have shown this for a wide variety of organisms, the vast majority has been conducted at constant temperatures and changes therein, while temperature is far from constant in nature, and includes seasonal and diurnal cycles. As fluctuating temperatures have been described to affect metabolic processes at (sub)cellular level, this calls for studies evaluating the relative importance of temperature fluctuations and the changes therein. 2. To gain insight in the effects of temperature fluctuations on ectotherm development, survival, and sex-ratio, we developed an inexpensive, easily reproducible, and open-source, Arduino-based temperature control system, which emulates natural sinusoidal fluctuations around the average temperature. We used this novel setup to compare the effects of constant (mean) temperatures, most commonly used in experiments, block schemes and natural sinusoidal fluctuations as well as an extreme variant with twice its amplitude using the cosmopolitan mosquito species Culex pipiens s.l. as a study organism. 3. Our system accurately replicated the preprogrammed temperature treatments under outdoor conditions, even more accurately than traditional methods. While no effects were detected on survival and sex-ratio within the ranges of variation evaluated, development was sped up considerably by including temperature fluctuations, especially during pupation, where development under constant temperatures took almost a week (30%) longer than under natural fluctuations. Doubling the amplitude further decreased development time by 1.5 days. 4. These results highlight the importance of including (natural) oscillations in experiments on ectotherm organisms – both aquatic and terrestrial – that use temperature as a variable. Ultimately, these results have major repercussions for downstream effects at larger scales that may be studied with applications such as ecological niche models, disease risk models and assessing ecosystem services that rely on ectotherm organisms.

Aim: This study evaluated the use of machine learning in leveraging drug ADME data to develop a novel anticholinergic burden (AB) scale and compared its performance to previously published scales. Methods: Experimental and in silico ADME data were collected for antimuscarinic activity, blood-brain barrier penetration, bioavailability, chemical structure and P-gp substrate profile. These five ADME properties were used to train an unsupervised model to assign anticholinergic burden scores to drugs. The performance of the model was evaluated through 10-fold cross-validation and compared with the clinical ACB scale and non-clinical ATS scale which is based primarily on muscarinic binding affinity. Results: In silico software (ADMET predictor ®) used for screening drugs for their blood-brain barrier (BBB) penetration correctly identified some drugs that do not cross the BBB. The mean AUC for the unsupervised and ACB scale based on five selected features was 0.76 and 0.64 respectively. The unsupervised model agreed with the ACB scale on the classification of more than half of the drugs (n=49 of m=88) and agreed on the classification of less than half the drugs in the ATS scale (n=12/25). Conclusion: Our findings suggest that the commonly used ACB scale may misclassify certain drugs due to their inability to cross the BBB. On the other hand, the ATS scale would misclassify drugs solely depending on muscarinic binding affinity without considering ADME properties. Machine learning models can be trained on these features to build classification models that are easy to update and have greater generalizability.

This article aims to address the optimization problems for continuous-time first-order and second-order multi-agent systems (MASs) with matrix-weighted networks. The matrix-weighted network is used to model the interdependence between agents’ multidimensional states, providing an effective approach to analyzing complex systems. The goal of optimization is that agents exponentially converge to the optimal value of the global cost function, which is formed by a sum of local cost functions. To achieve this goal, distributed optimization algorithms based on Hessian matrix and gradient information are constructed. Additionally, the edge-based event-triggered mechanism is utilized to avoid communicating with all neighbors at the time of event triggering while theoretically excluding Zeno behavior. The results show that the proposed algorithm can ensure that the intelligent body can achieve the optimization goal while reducing energy consumption. Eventually, an application is presented to substantiate the theoretical results.

N-trans-cinnamoyltyramine (NTCT) has been identified from an allelopathic Vietnamese rice accession OM 5930. The study employed a rigorous analysis of NTCT’s effects on shoot and root growth across multiple plant species. Notably, barnyardgrass and red sprangletop exhibited significant reductions in shoot and root growth with increasing NTCT concentrations, indicating a dose-dependent response (from 0.024 μM to 24 μM). Weedy rice accessions PI 653426 and PI 653431 also display dose-dependent effects, with notable declines in both shoot and root growth (from 0.25 μM to 15.6 μM and from 0.44 μM to 85.8 μM, respectively). Additionally, NTCT demonstrates potent inhibitory effects on palmer amaranth, timothy, canola, cress, and lettuce, with increasing concentrations leading to substantial reductions in growth across all species (Average from 2.4 μM). Linear regression analysis reveals the ED50 values for NTCT, providing critical insights into the concentration required for 50% growth inhibition in each species. These values range from 0.19 to 166.1 μM for shoots and from 1.74 to 33.07 μM for roots, highlighting the varying sensitivities among the test plant species. The findings underscore NTCT’s efficacy in suppressing the growth of a wide range of weeds, including both grasses and broadleaf species. The compound shows promise for sustainable weed management practices, particularly in addressing herbicide-resistant weeds in diverse ecological settings. By elucidating NTCT’s inhibitory and species-specific responses, this study contributes valuable insights to the development of eco-friendly herbicidal agents for effective weed control

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Herpes simplex encephalitis complicated with vasculitis in a young Male: A case reportDr. Sebhatleab T.1, Dr.Abel T. 1Dr.Estifanos B2,Dr.Zablon M 3, Dr.Merchaye A.3, Dr. Raja T.41. Department of Internal Medicine, School of Health Sciences, Addis Ababa University, Addis Ababa.2.Department of Neurology, School of Health Sciences, Addis Ababa University, Addis Ababa3.Bethzatha General Hospital, Addis Ababa, Ethiopia4.Department of Radiology, School of Health Sciences, Addis Ababa University, Addis Ababa

Coronary Artery Intramural Hematoma Causing Myocardial Infarction Mimicking Pseudoaneurysm or dissection from Trauma: A Case Report and Literature Review

Wound healing in movable parts poses challenges due to frequent activities, leading to delayed recovery and heightened susceptibility to bacterial infections and inflammation. Although hydrogel-based dressings have been explored, their therapeutic effectiveness is limited by their poor resistance to stimuli and low mechanical strength. Here, to address this issue, we present a novel self-activated multifunctional PHC bandage that not only prevents bacterial infection but also capitalizes on the inherent mobility of the affected area to expedite the wound healing process. The PHC bandage was fabricated by incorporating photothermal copper bismuth sulfide (Cu3BiS3) nanoparticles (NPs) into piezoelectric and pyroelectric polyvinylidene fluoride (PVDF). Upon exposure to near-infrared light, the embedded Cu3BiS3 nanoparticles generate localized heat, activating the PVDF and inducing the production of abundant reactive oxygen species for bacterial inactivation. Furthermore, the continuous movement of the wounded area triggers the PVDF to generate a sustained electrical field, promoting cell migration and proliferation to facilitate wound healing. Importantly, the robust encapsulation of PVDF ensures secure containment of the loaded Cu3BiS3 nanoparticles, improving the biocompatibility and sustainable utilization of this innovative wound dressing. This innovative design offers a promising and effective solution to improve wound healing in movable parts, potentially revolutionizing wound care technology.

A case of ST-elevation MI with revascularization by PCI complicated by bacterial pericarditisAnderson Ariaga MD1, Felicia Zhang OMS III2, Pradnya Brijmohan Bhattad MD3, Nili Gujadhur MD1Vassar Brothers Medical Center, Poughkeepsie, NYTouro College of Osteopathic Medicine, Middletown, NYCardiovascular Medicine, Saint Vincent Hospital, UMass Chan Medical School, MACorresponding author: Anderson Ariaga. andersonariaga@yahoo.com. +14437948630Author Note Disclosures: The authors report no external funding source for this study. The authors also declare no conflict of interest. This study has not been published anywhere or presented as a poster anywhere till date of submission. No grants/funding available for this study. Patient consent was obtained prior to submission.Keywords : Myocardial infarction, Revascularization, Bacterial Pericarditis

It has been four years since the emergence of the COVID-19 pandemic, and the ongoing threat it poses to human health and life un-derscores the continued need for the development of antiviral medications as a means of mitigating future viral outbreaks. In this study, we present a novel class of antiviral compounds known as naphthoquinone-fused enediyne sugar polysulfates, which have demonstrated efficacy against coronaviruses by targeting the conserved receptor binding domain on spike proteins. These compounds induce irreversible damage to the viral structure, resulting in inhibition of viral infection at nanomolar concentrations with minimal cytotoxic effects. Notably, the selectivity index of these compounds exceeds 50,000, suggesting significant potential for further de-velopment in antiviral therapeutics against coronavirus.

Copper(I)-catalyzed temperature- and oxidant-induced selective synthesis of pentathiepinoindoles and diindole tetrasulfides is demonstrated. Among them, unsymmetric tetrathiadiindole compounds were synthesized for the first time. In this strategy, the key intermediate biindolyls were in situ generated through Cu-catalyzed direct C–H transformations of indoles. The biindolyls could be selectively converted into the corresponding products by fine-tuning reaction conditions. More than 50 polythioindole products were synthesized with excellent regioselectivity and broad functional group tolerance.

Abstract: The utilization of renewable solar energy for the photocatalytic transformation of carbon dioxide (CO2) into valuable chemical substances is considered an optimal strategy to simultaneously address climate challenges and tackle energy scarcity. Herein, we prepared heterojunction photocatalysts UiO-66-NH2/ZnIn2S4, which were successfully applied in the photocatalytic reduction of CO2. The yield of the main product CO, for the optimal UiO-66-NH2/ZnIn2S4-2 sample could reach up to 57 μmol g-1 h-1 when converting CO2 under the visible light irradiation, which was approximately 3.35 and 2.71 times higher than that achieved by the individual UiO-66-NH2 and ZnIn2S4 samples, respectively. The better photocatalytic performance of the UiO-66-NH2/ZnIn2S4-2 composites can be attributed to its synergistic effect resulting from tight interfacial contacts, special charge transfer pathways and excellent CO2 adsorption capacity. Furthermore, the intimate contact between UiO-66-NH2 and flower-like ZnIn2S4 accelerates electron transmission while effectively suppressing the quenching of photogenerated carriers. This research provides vital knowledge for the rational design of heterostructures aimed at enhancing the efficiency of CO2 photocatalysis for solar fuel production.

This paper presents a novel Topological Distributed Multi-Rate State Estimator (TDMRSE) for designing a Distributed Output Feedback Exponential Sliding Mode Consensus (DOFESMC) protocol for a Discrete Multi-Agent System (DMAS) to achieve the leader-follower consensus. First, a topological distributed multi-rate state estimator is proposed for a DMAS using the graph theory where the stack of output at each agent is measured at a faster sampling rate than the input in DMAS. Then, the estimated state variables of each agent are used to design the DOFESMC protocol for DMAS to achieve the consensus by ensuring the minimal consensus effort, the minimum time for achieving the consensus, and the deviation of agents from the consensus of the order O(T^3). The condition for global consensus stability of DMAS with the proposed DOFESMC protocol is derived using the Lyapunov theory. The proposed DOFESMC protocol is validated in simulation and experiment on a DMAS comprised of 2-Degree of Freedom (DOF) robotic arms connected in a given communication topology. Moreover, the proposed protocol is compared with the protocol designed using a distributed Luenberger observer for consensus performance in terms of Integrated Square Error, control effort for consensus, and deviation from consensus. It is inferred from the simulation and experimental results that the proposed DOFESMC protocol with TDMRSE outperforms the protocol designed with a distributed Luenberger observer.

Aim of the Study This study aimed to investigate the effects of the n-hexane fraction of the ethanolic seed extract of PG (NFESEPG) on hypertension induced by Nω-nitro-L-arginine methyl ester (L-NAME) in rats. Specifically, the study examined the impact of NFESEPG on blood pressure, oxidative stress markers, NO concentration, angiotensin-converting enzyme (ACE) and arginase activities, and cardiac biomarkers in hypertensive rats. Materials and Methods The study involved collecting, identifying, and processing the PG plant to obtain the ethanolic seed extract. The extract was then partitioned with solvents to isolate the n-hexane fraction. Hypertension was induced in rats by oral administration of L-NAME for ten days, while concurrent treatment with NFESEPG at two doses (200 and 400 mg/kg/day) was administered orally. Blood pressure was measured using a non-invasive tail-cuff method, and various biochemical parameters were assessed. Results Treatment with both doses of NFESEPG significantly reduced systolic and diastolic blood pressure in L-NAME-induced hypertensive rats. Additionally, NFESEPG administration increased NO concentration and decreased ACE and arginase activities, malondialdehyde (MDA) levels, and cardiac biomarkers in hypertensive rats. Conclusions The findings indicate that NFESEPG effectively lowered blood pressure in hypertensive rats induced by L-NAME, potentially through mechanisms involving the modulation of oxidative stress, NO bioavailability, and cardiac biomarkers. These results suggest the therapeutic potential of NFESEPG in managing hypertension and related cardiovascular complications.

In the realm of traditional representation learning for Natural Language Processing (NLP) tasks, the prevalent approach involves leveraging large language models like BERT, GPT-2, XLNet, and others, which demonstrate their prowess when trained on extensive datasets. However, the quest for effective representation learning becomes a formidable challenge when data is scarce or costly to acquire, such as in specialised domains and low-resource languages. This challenge stems from the scarcity of suitable algorithms and the inherent difficulties in learning representations from limited data. In this study, we introduce a novel and groundbreaking technique, the Attention-sequence Bidirectional Long Short-Term Memory (ABiLSTM), to tackle this challenge head-on. This method amalgamates the strengths of attention mechanisms and bidirectional Long Short-Term Memory (LSTM) networks, bolstering the model’s ability to capture intricate patterns and dependencies within sequential data, particularly in scenarios involving small or constrained datasets. Through empirical analysis, we delve into the intricate dynamics of neural network architectures, specifically examining the impact of varying numbers of hidden layers and the occurrence of training errors. These aspects are scrutinised in the context of unsupervised pretraining methods, with a focus on their effectiveness in generating robust and informative representations for open relation extraction tasks. Furthermore, we propose the use of knowledge graph techniques to tackle the challenge of imbalanced data during information extraction processes. Our study demonstrates that the use of ABiLSTM yields superior results in open relation extraction tasks, even when dealing with small or limited datasets. This advancement represents a significant contribution to the fields of natural language understanding and information extraction.

The palm family is a major source of invasive woody plants because of their long history of introductions outside their native range in tropical and subtropical regions for their use as food and ornamentals. Areca triandra Roxb. Ex Buch-Ham, was introduced to Sri Lanka in 1867 through the Royal Botanic Gardens, Peradeniya has been grown as an ornamental for over a century. This study shows its naturalization in the southwest humid lowlands and is invasive. Population and reproductive characteristics were studied in Meethirigala and Yagirala Forest Reserves. In each location, stems > 1m height and crown cover were sampled in three plots of 400 m2 (20 m × 20 m) and the ground layer < 1 m height sampled through four 1 m x 1 m plots within each 400 m2 (total of 24 plots). A. triandra accounted for 56% - 66% of stems > 1 m height, 52% - 76% crown cover, and 64% - 77% of stems and seedlings in the ground layer < 1 m height. Clump formation was high with 30% - 51% having 2 - 7 stems, compared to single stems of 12% - 26%. Fruit production was prolific, each infructescence yielding 140 - 250 fruits and each clump of multiple stems producing 1 - 3 infructescence. This resulted in a total of 250 - 440 fruits per clump, translating up to 8000 fruits per 20 m × 20 m plot; bright red, fleshy fruits attracted avian and mammalian frugivores aiding seed dispersal. The palm favored disturbed forest edges, and shady understory habitats displacing native understory, suppressing native canopy regeneration. The Invasiveness Assessment Protocol indicated moderate risk from A. triandra in the wet zone, exposing vulnerability of Sri Lanka’s highly fragmented biodiverse rain forests. This emphasizes the need for urgent action of this species.

Title: Unfolding a potential trigger of liver injury in Psoriasis based on literature review and management approach, a case reportThe author encloses herewith a manuscript entitled “Unfolding a potential trigger of liver injury in Psoriasis based on literature review and management approach, a case report “for publication in a prestigious journal ”Clinical Case Reports Wiley Online. The Corresponding author of this manuscript is Saba Nabavi Monfared, PHARMD and the authors’ contribution as mentioned below with their responsibility in the research.

Compared with traditional methods, the use of additive manufacturing in metallic components offers advantages in terms of achievable geometries and material savings, making this technique very attractive for the design and construction of mechanical parts. However, nowadays this technique has two major drawbacks. First of all, during the manufacturing process, internal pores appear in the components that give rise to a lower resistance to fatigue when compared with parts manufactured with traditional process. On the other hand, the fatigue behaviour of parts made by additive manufacturing strongly depends on the constructive parameters selected for their manufacturing, being the number of these parameters high and some of them inherent to the used manufacturing equipment. In relation to this variability in the behaviour, the present work analyses a series of Scalmalloy® specimens made by three different manufacturers. Is important to note that during the manufacturing process these three manufactures used the same layer thickness and posterior heat treatment. In this analysis, the fatigue and tensile strength, the resulting microstructure, the crack surface shape and cause of failure in fatigue tests will be compared. Finally, the effect of the mean stress in a fatigue cycle is analysed, showing that it should be treated in a different way compared to classical manufacturing.

The development of internal cracks in asphalt concrete can be seen as a sign of macro crack development. To explore the influence of different loading rates on the crack resistance of panel asphalt concrete, based on the theory of fracture mechanics, DIC digital image correlation technology was used as a test method for crack propagation of specimens. SCB (Semi-circular bending)tests were carried out on panel asphalt concrete with different loading rates (0.05, 0.2, 1, 3, 5,1 0 mm/min). The effects of different loading rates on the fracture index and full-field strain of asphalt concrete were analyzed. the results showed that when the loading rate increases from 0.05 mm/min to 10mm/min, the stress intensity factor ( KIC) and fracture energy ( Gf) increase, and the crack resistance index ( CRI) shows the opposite law; With the increase of loading rate, the strain (Exx, Eyy) corresponding to the peak load gradually decreases. After reaching the peak strength, with the increase of load displacement, the crack of the sample gradually expands along the edge of the coarse aggregate at a low loading rate, and the crack penetrates the coarse aggregate at a high loading rate; There are obvious differences in crack morphology of asphalt concrete specimens under different loading rates, When the loading rate is 0.05-1 mm/min, the crack morphology is tortuously rising. When the loading rate is 3-10mm/min, the crack morphology develops almost vertically upward along the pre-crack. The results of the study can provide a reference for the development of cracks and fracture behavior of panel asphalt concrete under different loading rates.