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Pulmonary arteriovenous malformations (PAVMs) are abnormal vascular connections between pulmonary arteries and veins, often associated with hereditary hemorrhagic telangiectasia (HHT). Most PAVMs are asymptomatic, but life-threatening complications like pulmonary hemorrhage, brain abscesses, and paradoxical emboli can emerge, so prompt diagnosis and treatment are crucial. We report a case of sudden pediatric death in a two-year-old female with no past medical history. Initial vomiting and fast deterioration resulted in a sudden cardiac arrest. The postmortem examination found histological evidence of consistent, extensive lung damage. The absence of the characteristic symptoms made for some challenges when it came to diagnosis, showing precisely that in early life, you could well have many difficulties in catching PAVMs. This case highlights the need to take PAVMs into account as a potential cause of sudden death, particularly when there are no conspicuous symptoms. Awareness among forensic pathologists and consideration of genetic analysis for HHT in such cases is crucial for accurate diagnosis and management.

Infectious bronchitis is an acute respiratory disease of poultry associated with reduced egg production and heavy economic losses in chicken flocks. Rabid and accurate detection of IB virus (IBV) is essential for controlling and preventing the infection. In this study, we developed a rapid, accurate, and instrument less assay to detect IBV. For the first time, reverse transcription- Recombinase polymerase amplification (RT-RPA) coupled with CRISPR/Cas13 (SHERLOCK) was used to rapidly visualize IBV. The novel assay was tested in timing, sensitivity, and specificity. The spike gene (S gene) was used as a target gene for detecting the virus. Three samples were used to optimize the assay; sample form confirmed infected chickens with IB, positive sample (full synthesis of S gene), and negative sample from free IB infected chickens. The results show that the Sherlock-based Cas13 platform is a highly specificity and sensitivity assay for detecting infectious bronchitis virus. The assay detected ten copies per µL of the input RNA. No false positives or cross-reactions were seen when bovine coronavirus (BCV) was used instead of IBV in the tested sample. Readout of the results needs just fifty minutes, including RNA extraction. Furthermore, No instrument was used, and amplification of the virus's nucleic acid was performed at room temperature. Sherlock-based Cas13 should clinically use for rapid diagnosis of infectious bronchitis in chickens. However, further studies and experiments are needed to perform the assay at the sample base without extraction of RNA.

This study focuses on how the chemical makeup of the glass' basic components affects the glass' structure and optical characteristics. Four glass samples have been created for this purpose using the chemical formula; 94 mol% Na2B4O7—(6-x) mol% CeO2 – x mol% Ce(NO3)3, where 0 ≤ x ≤ 6. The Ce cations in this formula have two separate chemical sources, CeO2 and Ce(NO3)3, with CeO2 eventually being replaced by Ce(NO3)3. The standard melt-quenching technique was used to prepare the studied glasses. While X-ray direction (XRD), differential scanning calorimetry (DSC), and UV–vis were used for the structural and optical characterizations. XRD patterns revealed the short-range order glass networks for the prepared samples, while DSC thermograms showed that when CeO2 was replaced with Ce(NO3)3, the glass transition temperature (Tg) decreased, causing the glass stability to improve. The optical characterization resulted in the finding that when CeO2 was replaced with Ce(NO3)3, the Urbach's energy increased with a decrease in bandgap energies, which reflects an increase in the glass homogeneity. Finally, the results may imply that Ce(NO3)3-based glasses can be proposed for usage in applications for UV blockers, radiation shielding, light attenuation, and n-type semiconductors. [ABSTRACT FROM AUTHOR]

The sol-gel auto-composition approach was used to produce AgxCo0.5−xZn0.5Fe1.95La0.05O4/5% G (x = 0, 0.01, 0.05, 0.1, 0.25, 0.5 (nanocomposites. Some techniques for characterizing the composite structure such as XRD, SEM, EDX, HR-TEM, SAED, FTIR, Raman, and electron mapping are performed. The structure is indexed to be cubic ferrite with space group Fd-3 m lattice parameters ranging from (8.3823–8.4139 A˚). The crystallite size was determined by four trends to be (27.57–41.72 nm), (30.88–62.18 nm), (80.70–103.6 nm), and (73.12 nm) by Scherer's equation, W-H relation, SEM, and HR-TEM respectively. The strain ε and the line dislocation δ in crystalline and the theoretical density ρXRD are evaluated. EDX and elemental mapping revealed that all elements are present, indicating a good synthesis method. FTIR spectrum shows octahedron absorption band ʋocta at 399–462 cm− 1 and the tetrahedron band tetra at 590–624 cm− 1. The force constant kOct. and kTet. octahedral and tetrahedral are determined to be 1.1854 × 105 and 2.0249 × 105 dyne/cm. The VSM approach estimates the magnetic characteristics of such materials to be ferromagnetic, with a saturation magnetization of 44.60 emu/g decreasing with increasing Ag concentration. The Hc is in 117.95 G, which decreases to 25% with increasing Ag content. Graphene-based nanoparticles offer unique mechanisms of action and broad-spectrum activity against bacteria and cancer cells. The effect of a novel and inventive chemical on gram-positive and gram-negative bacteria was examined. The compound exhibited a significant antibacterial effect on gram-positive bacteria, with a 60% activity compared to the control and 64% activity on gram-negative. Furthermore, the antifungal activity has been evaluated. It also exhibited a great cytotoxic activity on the MDA-MB-231breast cancer cell line, leading to decreased viability by 94.5%, 93.26% and 90.1% for Ag = 0.5, 0.1, and 0, respectively, compared with negative control. Continued study and development in this sector may result in the creation of novel treatment techniques for fighting bacterial infections and cancer. This paper provides a comprehensive study of the current knowledge regarding utilizing zinc, Silver, and cobalt in the context of their antibacterial and anticancer activities. [ABSTRACT FROM AUTHOR]

In this work, new glass systems with composition xV2O5–20CuO–60B2O3–15CaO–(5−x)ZnO which is coded as BCuCa–(5−x)Zn:xV where (0, 1, 2.5 mol.%) were fabricated using the melt-quenching technique with melting temperature 1200 °C to serve as competitive candidates for γ-ray and neutron shielding. XRD and FT-IR were used to characterize the assembled glass samples. The density values of synthesized glasses were increased almost linearly from 2.807 to 2.834 g cm−3, whereas molar volume decreased from 54.894 to 54.174 cm3 mol−1, depending on the addition of V2O5. The γ-ray shielding properties of the prepared glass samples were tested experimentally using P-type HPGe detector in the photon energy range of 0.356–1.332 MeV and theoretically with the help of Monte Carlo (MC) simulations and Phy-X/PSD software in the photon energy range of 0.015–15 MeV. Various nuclear radiation shielding parameters such as linear attenuation coefficient (µ), half value layer (HVL), tenth value layer (TVL), mean free path (MFP), effective atomic number (Zeff), radiation protection efficiency (RPE), and fast neutron removal cross-section (FNRCS) for the prepared glasses have been evaluated at the selected range of photon energies. The experimental data of μ for all the tested glass systems is comparable to that obtained from a theoretical calculation. Also, Monte Carlo calculations were in a fairly good agreement with the Phy-X/PSD data, so that the maximum difference between them was about 2.716%. The outlined results indicated that the glass sample with 2.5-mol % V2O5 (BCuCa–2.5Zn:2.5V) exhibits optimal µ, Zeff, HVL, TVL, and MFP values. BCuCa–2.5Zn:2.5V was also found to have the best value of the FNRCS (about 0.1 cm−1). [ABSTRACT FROM AUTHOR]

This study examines the impact of adding copper oxide to glasses of the composition B2O3-Li2O-Na2O-CaO-SrO-As2O3-XCuO, which are referred to as BLNCASCu-X glasses. The weight percentages of copper oxide used are 0, 0.25, 0.75, and 1 wt.%. The BLNCASCu-X glass was analyzed using Fourier transforms infrared (FT-IR), Ramman, and X-ray diffraction (X-R-D). Additionally, the physical assets of the glass were examined. Adding CuO resulted in a linear increase in the density of the glasses, from 2.8067 to 2.8340 g.cm−3. Simultaneously, the molar volume of the glasses decreased from 18.6317 to 24.9974 cm3 mol−1. The density (ρ) exhibited a progressive increase from 3.492 to 3.901 g.cm−3, whereas the molar volume (Vm) experienced a drop from 22.311 to 21.216 cm3.mol−1 as the CuO content grew from 0 to 1 wt.%. The radiation shielding properties of the samples were determined experimentally using an HPGe detector at the γ-energies: 0.661 to 1.332 MeVs. The radiation shielding assets of the examined BLNCASCu-X glasses (e.g., the linear attenuation (μ), half value layer (H1/2), etc.) were evaluated using the MC Monte Carlo simulation algorithm and Phy-X software. The results showed an increase in the content of CuO in BLNCASCu-X glasses from 0 to 1 wt. % had a beneficial impact on their radiation characteristics. The linear attenuation (μ) exhibited an ascending trend in the following order: BLNCASCu-0 < BLNCASCu-0.25 < BLNCASCu-0.75 < BLNCASCu-1. The fast neutron removal cross-section values, denoted as ΣR, were determined and demonstrated a consistent rise with increasing part densities of copper and oxygen in the BLNCASCu-X glass systems. It is generally believed that in nuclear applications, the absorption of neutrons and photons is enhanced when CuO is added to B2O3-Li2O-Na2O-CaO-SrO-As2O3 glasses. [ABSTRACT FROM AUTHOR]

Abstract Background Posterior Circulation Syndrome (PCS) presents a diagnostic challenge characterized by its variable and nonspecific symptoms. Timely and accurate diagnosis is crucial for improving patient outcomes. This study aims to enhance the early diagnosis of PCS by employing clinical and demographic data and machine learning. This approach targets a significant research gap in the field of stroke diagnosis and management. Methods We collected and analyzed data from a large national Stroke Registry spanning from January 2014 to July 2022. The dataset included 15,859 adult patients admitted with a primary diagnosis of stroke. Five machine learning models were trained: XGBoost, Random Forest, Support Vector Machine, Classification and Regression Trees, and Logistic Regression. Multiple performance metrics, such as accuracy, precision, recall, F1-score, AUC, Matthew’s correlation coefficient, log loss, and Brier score, were utilized to evaluate model performance. Results The XGBoost model emerged as the top performer with an AUC of 0.81, accuracy of 0.79, precision of 0.5, recall of 0.62, and F1-score of 0.55. SHAP (SHapley Additive exPlanations) analysis identified key variables associated with PCS, including Body Mass Index, Random Blood Sugar, ataxia, dysarthria, and diastolic blood pressure and body temperature. These variables played a significant role in facilitating the early diagnosis of PCS, emphasizing their diagnostic value. Conclusion This study pioneers the use of clinical data and machine learning models to facilitate the early diagnosis of PCS, filling a crucial gap in stroke research. Using simple clinical metrics such as BMI, RBS, ataxia, dysarthria, DBP, and body temperature will help clinicians diagnose PCS early. Despite limitations, such as data biases and regional specificity, our research contributes to advancing PCS understanding, potentially enhancing clinical decision-making and patient outcomes early in the patient’s clinical journey. Further investigations are warranted to elucidate the underlying physiological mechanisms and validate these findings in broader populations and healthcare settings.

Background: Eagle syndrome is a rare condition with a prevalence estimated at 4%, with 0.16% exhibiting symptoms of Eagle’s syndrome resulting from an elongated styloid process or a calcified stylohyoid ligament, compressing over nearby vessels and nerves. Symptoms range from simple headache, neck pain, and odynophagia to cerebral ischemia. Since it can be an incidental finding, management is controversial and ranges from conservative treatment to surgical intervention, including internal carotid stenting and styloidectomy. Clinical presentation: We report two cases of Eagle’s syndrome. Case one (Vascular variant): 44 years old presented with left-sided weakness with Magnetic Resonance Imaging and an angiogram of the brain showing a right middle cerebral artery hemispheric infarct with a right internal carotid artery (ICA) dissection and elongated styloid processes more on the left. The patient’s condition improved with supportive care. He was treated with aspirin, atorvastatin, and an intensive 16-week rehabilitation program. Case two (Classic variant): 41 years old presented with refractory occipital headache and neck pain without vascular insult. Magnetic resonance of both patients showed a long styloid process. Conclusions: Eagle’s Syndrome is a rare entity and perhaps overlooked as an anatomical variant that ought to be considered a possible etiology in atraumatic ICA dissection in patients with no discernable risk factors. As observed in case one, with atraumatic ICA dissection and unremarkable connective tissue disease work-up, highlighting anatomical variant, as an etiology to his ischemic stroke. Styloidectomy should be considered to avert risk of recurrent IC dissections in such patients with atraumatic IC dissection and classic eagle’s syndrome with refractory orofacial pain syndromes exacerbated by head movement or yawning.

Objectives: Predicting stroke mortality is crucial for personalized care. This study aims to design and evaluate a machine learning model to predict one-year mortality after a stroke. Materials and methods: Data from the National Multiethnic Stroke Registry was utilized. Eight machine learning (ML) models were trained and evaluated using various metrics. SHapley Additive exPlanations (SHAP) analysis was used to identify the influential predictors. Results: The final analysis included 9840 patients diagnosed with stroke were included in the study. The XGBoost algorithm exhibited optimal performance with high accuracy (94.5%) and AUC (87.3%). Core predictors encompassed National Institutes of Health Stroke Scale (NIHSS) at admission, age, hospital length of stay, mode of arrival, heart rate, and blood pressure. Increased NIHSS, age, and longer stay correlated with higher mortality. Ambulance arrival and lower diastolic blood pressure and lower body mass index predicted poorer outcomes. Conclusions: This model's predictive capacity emphasizes the significance of NIHSS, age, hospital stay, arrival mode, heart rate, blood pressure, and BMI in stroke mortality prediction. Specific findings suggest avenues for data quality enhancement, registry expansion, and real-world validation. The study underscores machine learning's potential for early mortality prediction, improving risk assessment, and personalized care. The potential transformation of care delivery through robust ML predictive tools for Stroke outcomes could revolutionize patient care, allowing for personalized plans and improved preventive strategies for stroke patients. However, it is imperative to conduct prospective validation to evaluate its practical clinical effectiveness and ensure its successful adoption across various healthcare environments.

In this study, Mn2O3/PVC, a polyvinyl chloride doped with various Mn2O3 nanoparticles, is prepared, and characterized. Solution casting was used to create Mn2O3/PVC polymeric nanocomposite films. The X-ray diffraction method verified that the Mn2O3NPs were effectively disseminated in a PVC matrix with a single-phase structure. According to the Debye-Scherer formula, the crystallite size of Mn2O3 nanoparticles is 22.08 nm. The casting process is expected to cause Mn2O3 nanoparticles in the PVC matrix to aggregate. Through the construction of a hydrogen bond, FTIR validated the Mn2O3/PVC nanocomposite's physical interaction. According to UV/Vis/IR analysis, the optical energy gap values decrease as Mn2O3 NP concentration increases. This indicates that complexes of charge transfer between the polymer and Mn-ions are developing. The investigated material demonstrated good optical limiting performance when laser sources of 533 nm were used instead of laser sources of 632.8 nm. Mn2O3/PVC nanocomposite can function as a photocatalyst to enhance the efficiency of Carmine dye photodegradation. The most effective Mn2O3/PVC nanocomposite film for the visible photocatalysis of Carmine dye is 3.33 wt% Mn2O3/PVC. Mn2O3/PVC has been shown to be a promising material for use in photocatalytic, optoelectronic, and electronic applications. [ABSTRACT FROM AUTHOR]

This study focuses on the influence of low-concentration additions of NiCl2 on the overall properties of lead arseborate oxide glasses. In this regard, small amounts, in grams, of NiCl2 were added, separately, to the main constituents of the lead-arseboarte glass, according to the chemical formula [23 wt% B2O3–11 wt.% Na2O–20 wt. CaO–23 wt.% PbO–23 wt.% As2O3] % + x NiCl2, where x = 0.25, 0.5, 0.75, and 1 g, to prepare a glass series of four samples using the fast quenching technique. The structural and optical characterizations of the prepared samples have been described based on X-ray diffraction (XRD) measurements, Fourier transform infrared charts (FTIR), and UV–Vis spectra. The X-ray diffraction (XRD) patterns did not contain any crystalline peaks but only two broad humps which revealed that all samples possess short-range order structures. At the same time, the FTIR charts showed different structural units. The UV–Vis spectra demonstrated that the absorption edge spectra changed to a higher wavelength with an increase in NiCl2 dopants, accompanied by a drop in optical transmittance, particularly in the visible range. As the NiCl2 dopants increased, the values of the optical energy gaps reduced while the mass attenuation remained constant, and the effective atomic number, bulk density, microhardness, absorption index, and characteristic relaxation time increased. Regardless of sample thickness, a novel methodology has been proposed to determine both the optical band gaps and the optical loss. The novel method and the widely used one (Tauc relation) demonstrated excellent agreement. The results suggest the NiCl2-rich sample is a primary material for radiation shielding applications as a carrier for radioactive sources and preserving them, or for preserving radioactive waste and high-reflection and UV-blocking glass coating. [ABSTRACT FROM AUTHOR]

Cadmium sulfide was prepared by first turning it into a powder, which was then used to evaporate heat to create thin films. Additionally, the spray pyrolysis method was used to produce films of cadmium sulfide. A structural comparison using the crystallize size and lattice parameters. Furthermore for the prepared samples, an analysis of their optical characteristics was conducted through measurements of absorbance, transmission, and reflection, resulting in the determination of the energy gap. [ABSTRACT FROM AUTHOR]

The pursuit of efficient and sustainable energy storage solutions has fueled significant interest in the development of advanced materials for supercapacitors. Among these, two-dimensional (2D) materials undoubtingly have emerged as promising candidates due to their unique structural and electrochemical properties. To address the inherent challenges such as restacking, limited ion-accessibility, limited scalability, stability under operational conditions, and the intricate balance between surface area and conductivity that hinder the practical application of 2D materials, this article delves into innovative approaches and emerging strategies and prospects that aim to enhance their performance and durability. A systematic exploration of synthesis methods, structural characteristics, and electrochemical performance as supercapacitor electrodes of key 2D materials, including graphene, MXenes, transition metal dichalcogenides (TMDCs), black phosphorous and phosphorene and their composites has been discussed. The discussion will extend to recent breakthroughs and innovations, shedding light on how researchers are leveraging the unique properties of 2D materials to overcome existing challenges in supercapacitor technology. Beyond mere documentation, this review seeks to inspire future research directions, foster interdisciplinary collaborations, and contribute to the ongoing evolution of energy storage technologies towards a more sustainable and efficient future., Competing Interests: The authors declare no financial conflict of interest., (This journal is © The Royal Society of Chemistry.)

Design: This retrospective cohort study aimed to investigate the risk and variables of tooth loss for teeth adjacent to dental implants compared to teeth nonadjacent to implants. The study followed the STROBE guidelines and was approved by the Institutional Review Board., Cohort Selection: The study included patients treated with dental implants at UCSF School of Dentistry between 2000 and 2020. The inclusion criteria for teeth adjacent to implants required the implant to support a fixed prosthesis and a follow-up period of at least 12 months. Nonadjacent teeth also required a follow-up period of at least 12 months. Teeth were excluded if they had a hopeless prognosis or were planned for extraction before the completion of restorative treatment., Data Analysis: Data were extracted from electronic health records, including patient demographics, dental histories, and outcomes for teeth adjacent and nonadjacent to implants. Statistical analyses, including Kaplan-Meier survival plots, log-rank tests, and multivariate logistic regression, were used to compare tooth survival and identify aetiologies of tooth loss., Results: The study included 787 patients, with 2048 teeth adjacent and 15,637 teeth nonadjacent to implants. The 10-year cumulative survival rate was 89.2% for teeth adjacent to implants and 99.3% for nonadjacent teeth. Teeth adjacent to implants had a significantly higher risk of tooth loss (Odds Ratio [OR] 13.15). The primary etiology of tooth loss adjacent to implants was root fracture (45.2%), followed by caries (28.9%), periodontitis (24.1%), and endodontic failure (1.8%). For nonadjacent teeth, periodontitis was the leading cause of tooth loss (51.9%)., Conclusions: The study found that teeth adjacent to dental implants had a significantly higher risk of tooth loss, primarily due to root fractures. The findings suggest that dental implants may act as an iatrogenic factor, increasing the risk of complications for adjacent teeth. Conservative management of natural dentition should be prioritized, with emphasis on stringent periodontal surveillance and effective home care. Future research should focus on prospective studies to further explore these associations and improve clinical outcomes., (© 2024. The Author(s).)