Embolic Strokes in Paroxysmal Atrial Fibrillation: Anticoagulation Failure or Something Else?

Infective endocarditis (IE) often presents with various signs and/or symptoms. However, at times, IE can present without outstanding clinical evidence but may carry devastating consequences if not detected and treated. We present a case of an 81-year-old female with paroxysmal atrial fibrillation who presented to the emergency department with slurred speech. Her National Institutes of Health Stroke Scale (NIHSS) score was one, and her physical examination was unremarkable. Brain imaging revealed bilateral multiple acute supratentorial and infratentorial infarcts. The patient was fully compliant on apixaban and had a dual-chamber pacemaker placed years earlier at an outside facility for unclear reasons. Although initially suspected to have experienced anticoagulation failure (ACF), transesophageal echocardiography (TEE) was ordered to evaluate for possible left atrial appendage closure procedure, which disclosed a mobile, echo-bright structure on the mitral valve consistent with IE. Blood cultures returned positive, the patient was treated with IV antibiotics, and apixaban was resumed. It can be challenging to suspect IE clinically, especially in deceptive or insidious cases with no signs/symptoms. Still, ACF is a diagnosis of exclusion, and all sources of embolic stroke (such as IE) must be thoroughly worked up before assuming treatment failure.

An Artificial Intelligence model for implant segmentation on periapical radiographs.

OBJECTIVE: To segment dental implants on PA radiographs using a Deep Learning (DL) algorithm. To compare the performance of the algorithm relative to ground truth determined by the human annotator. Methodology: Three hundred PA radiographs were retrieved from the radiographic database and consequently annotated to label implants as well as teeth on the LabelMe annotation software. The dataset was augmented to increase the number of images in the training data and a total of 1294 images were used to train, validate and test the DL algorithm. An untrained U-net was downloaded and trained on the annotated dataset to allow detection of implants using polygons on PA radiographs. RESULTS: A total of one hundred and thirty unseen images were run through the trained U-net to determine its ability to segment implants on PA radiographs. The performance metrics are as follows: accuracy of 93.8%, precision of 90%, recall of 83%, F-1 score of 86%, Intersection over Union of 86.4% and loss = 21%. CONCLUSIONS: The trained DL algorithm segmented implants on PA radiographs with high performance similar to that of the humans who labelled the images forming the ground truth.

Max-mixed EWMA control chart for joint monitoring of mean and variance: an application to yogurt packing process.

The Max-Mixed EWMA Exponentially Weighted Moving Average (MM EWMA) control chart is a statistical process control technique used for joint monitoring of the mean and variance of a process. This control chart is designed to detect small and moderate shifts in the mean and variance of a process by comparing the maximum of two statistics, one based on the mean and the other on the variance. In this paper, we propose a new MM EWMA control chart. The proposed chart is compared with existing control charts using simulation studies, and the results show that the chart performs better in detecting small and moderate shifts in both the mean and variance. The proposed chart can be helpful in quality control applications, where joint monitoring of mean and variance is necessary to ensure a product's or process's quality. The real-life application of the proposed control chart on yogurt packing in a cup data set shows the outperformance of the MM EWMA control chart. Both simulations & real-life application results demonstrate the better performance of the proposed chart in detecting smaller shifts during the production process.

Association between Statin Use and Chemotherapy-Induced Cardiotoxicity: A Meta-Analysis.

Background: Chemotherapy-induced cardiac dysfunction (CIC) is a significant and concerning complication observed among cancer patients. Despite the demonstrated cardioprotective benefits of statins in various cardiovascular diseases, their effectiveness in mitigating CIC remains uncertain. Objective: This meta-analysis aims to comprehensively evaluate the potential cardioprotective role of statins in patients with CIC. Methods: A systematic literature search was conducted using PubMed, Embase, and Scopus databases to identify relevant articles published from inception until 10th May 2023. The outcomes were assessed using pooled odds ratio (OR) for categorical data and mean difference (MD) for continuous data, with corresponding 95% confidence intervals (95% CIs). Results: This meta-analysis comprised nine studies involving a total of 5532 patients, with 1904 in the statin group and 3628 in the non-statin group. The pooled analysis of primary outcome shows that patients who did not receive statin suffer a greater decline in the LVEF after chemotherapy compared to those who receive statin (MD, 3.55 (95% CI: 1.04-6.05), p = 0.01). Likewise, we observed a significantly higher final mean LVEF among chemotherapy patients with statin compared to the non-statin group of patients (MD, 2.08 (95% CI: 0.86-3.30), p > 0.001). Additionally, there was a lower risk of incident heart failure in the statin group compared to the non-statin group of patients (OR, 0.41 (95% CI: 0.27-0.62), p < 0.001). Lastly, the change in the mean difference for LVEDV was not statistically significant between the statin and non-statin groups (MD, 1.55 (95% CI: -5.22-8.33), p = 0.65). Conclusion: Among patients of CIC, statin use has shown cardioprotective benefits by improving left ventricular function and reducing the risk of heart failure.

Visual resource extraction and artistic communication model design based on improved CycleGAN algorithm.

Through the application of computer vision and deep learning methodologies, real-time style transfer of images becomes achievable. This process involves the fusion of diverse artistic elements into a single image, resulting in the creation of innovative pieces of art. This article centers its focus on image style transfer within the realm of art education and introduces an ATT-CycleGAN model enriched with an attention mechanism to enhance the quality and precision of style conversion. The framework enhances the generators within CycleGAN. At first, images undergo encoder downsampling before entering the intermediate transformation model. In this intermediate transformation model, feature maps are acquired through four encoding residual blocks, which are subsequently input into an attention module. Channel attention is incorporated through multi-weight optimization achieved via global max-pooling and global average-pooling techniques. During the model's training process, transfer learning techniques are employed to improve model parameter initialization, enhancing training efficiency. Experimental results demonstrate the superior performance of the proposed model in image style transfer across various categories. In comparison to the traditional CycleGAN model, it exhibits a notable increase in structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) metrics. Specifically, on the Places365 and selfi2anime datasets, compared with the traditional CycleGAN model, SSIM is increased by 3.19% and 1.31% respectively, and PSNR is increased by 10.16% and 5.02% respectively. These findings provide valuable algorithmic support and crucial references for future research in the fields of art education, image segmentation, and style transfer.

Prognostic Value of Neutrophil-to-Lymphocyte Ratio in Patients with Acute Decompensated Heart Failure: A Meta-Analysis.

Background: Inflammation plays a pivotal role in the pathogenesis of both acute and chronic heart failure. Recent studies showed that the neutrophil-to-lymphocyte ratio (NLR) could be related to adverse outcomes in patients with cardiovascular diseases. We sought to evaluate whether NLR could predict mortality in patients with acute heart failure by means of a meta-analysis. Methods: A comprehensive literature search was performed in PubMed, Embase, and Cochrane databases through January 2023 for studies evaluating the association of NLR with mortality in patients with acute heart failure. Primary outcomes were in-hospital mortality and long-term all-cause mortality. Endpoints were pooled using a random-effects DerSimonian-and-Laird model and were expressed as a hazard ratio (HR) or mean difference (MD) with their corresponding 95% confidence intervals. Results: A total of 15 studies with 15,995 patients with acute heart failure were included in the final study. Stratifying patients based on a cut-off NLR, we found that high NLR was associated with a significantly higher in-hospital mortality [HR 1.54, 95% CI (1.18-2.00), p < 0.001] and long-term all-cause mortality [HR 1.61, 95% CI (1.40-1.86), p < 0.001] compared to the low-NLR group. Comparing the highest against the lowest NLR quartile, it was shown that patients in the highest NLR quartile has a significantly heightened risk of long-term all-cause mortality [HR 1.77, 95% CI (1.38-2.26), p < 0.001] compared to that of lowest NLR quartile. However, the risks of in-hospital mortality were compared between both quartiles of patients [HR 1.78, 95% CI (0.91-3.47), p = 0.09]. Lastly, NLR values were significantly elevated among non-survivors compared to survivors during index hospitalization [MD 5.07, 95% CI (3.34-6.80), p < 0.001] and during the follow-up period [MD 1.06, 95% CI (0.54-1.57), p < 0.001]. Conclusions: Elevated NLR was associated with an increased risk of short- and long-term mortality and could be a useful tool or incorporated in the risk stratification in patients with acute heart failure.

2D TiO2 nanosheets decorated via sphere-like BiVO4: a promising non-toxic material for liquid phase photocatalysis and bacterial eradication.

An in-depth investigation was conducted on a promising composite material (BiVO4/TiO2), focusing on its potential toxicity, photoinduced catalytic properties, as well as its antibiofilm and antimicrobial functionalities. The preparation process involved the synthesis of 2D-TiO2 using the lyophilization method, which was subsequently functionalized with sphere-like BiVO4. Finally, we developed BiVO4/TiO2 S-scheme heterojunctions which can greatly promote the separation of electron-hole pairs to achieve high photocatalytic performance. The evaluation of concentration- and time-dependent viability inhibition was performed on human lung carcinoma epithelial A549 cells. This assessment included the estimation of glutathione levels and mitochondrial dehydrogenase activity. Significantly, the BiVO4/TiO2 composite demonstrated minimal toxicity towards A549 cells. Impressively, the BiVO4/TiO2 composite exhibited notable photocatalytic performance in the degradation of rhodamine B (k =0.135 min-1) and phenol (k = 0.016 min-1). In terms of photoinduced antimicrobial performance, the composite effectively inactivated both gram-negative E. coli and gram-positive E. faecalis bacteria upon 60-min of UV-A light exposure, resulting in a significant log6(log10CFU/mL) reduction in bacterial count. These promising results can be attributed to the unique 2D morphology of TiO2 modified by sphere-like BiVO4, leading to an increased generation of (intracellular)hydroxyl radicals, which plays a crucial role in treatments of both organic pollutants and bacteria.

On topological analysis of two-dimensional covalent organic frameworks via M-polynomial.

Covalent organic frameworks (ZnP-COFs) made of zinc-porphyrin have become effective materials with a variety of uses, including gas storage and catalysis. To simulate the structural and electrical features of ZnP-COFs, this study goes into the computation of polynomials utilizing degree-based indices. We gave a methodical study of these polynomial computations using Excel, illustrating the complex interrelationships between the various indices. Degree-based indices provide valuable insights into the connectivity of vertices within a network. M-polynomials, on the other hand, offer a mathematical framework for representing and studying the properties of 2D COFs. By encoding structural information into a polynomial form, M-polynomials facilitate the calculation of various topological indices, including the Wiener index, Zagreb indices, and more. The different behavior of ZnP-COFs based on degree-based indices was illustrated graphically, and this comparison provided insightful information for prospective applications and the construction of innovative ZnP-COF structures. Moreover, we discuss the relevance of these techniques in the broader context of materials science and the design of functional covalent organic frameworks.

Ratiometric Fluorescence and Chromogenic Probe for Trace Detection of Selected Transition Metals.

The design and development of a fluorescence sensor aimed at detecting and quantifying trace amounts of toxic transition metal ions within environmental, biological, and aquatic samples has garnered significant attention from diagnostic and testing laboratories, driven by the imperative to mitigate the health risks associated with these contaminants. In this context, we present the utilization of a heterocyclic symmetrical Schiff Base derivative for the purpose of fluorogenic and chromogenic detection of Co2+, Cu2+ and Hg2+ ions. The characterization of the ligand involved a comprehensive array of techniques, including physical assessments, optical analyses, NMR, FT-IR, and mass spectrometric examinations. The mechanism of ligand-metal complexation was elucidated through the utilization of photophysical parameters and FT-IR spectroscopic analysis, both before and after the interaction between the ligand and the metal salt solution. The pronounced alterations observed in absorption and fluorescence spectra, along with the distinctive chromogenic changes, following treatment with Co2+, Cu2+ and Hg2+, affirm the successful formation of complexes between the ligands and the treated metal ions. Notably, the receptor's complexation response exhibited selectivity towards Co(II), Cu(II), and Hg(II), with no observed chromogenic changes, spectral variations, or band shifts for the various tested metal ions, including Na+, Ag+, Ni2+, Mn2+, Pd2+, Pb2+, Cd2+, Zn2+, Sn2+, Fe2+, Fe3+, Cr3+ and Al3+. This absence of interaction between these metal ions and the ligand could be attributed to their compact or inadequately conducive conduction bands for complexation with the ligand's structural composition. To quantify the sensor's efficacy, fluorescence titration spectra were employed to determine the detection limits for Co2+, Cu2+ and Hg2+, yielding values of 2.92 × 10-8, 8.91 × 10-8, and 4.39 × 10-3 M, respectively. The Benesi-Hildebrand plots provided association constant values for the ligand-cobalt, ligand-copper, and ligand-mercury complexes as 0.74, 2.52, and 13.89 M-1, respectively.

pH-sensitive docetaxel-loaded chitosan/thiolated hyaluronic acid polymeric nanoparticles for colorectal cancer.

Aim: This study aimed to develop and evaluate pH-sensitive docetaxel-loaded thiolated hyaluronic acid (HA-SH) nanoparticles (NPs) for targeted treatment of colon cancer. Materials & methods: HA-SH, synthesized via oxidation and subsequent covalent linkage to cysteamine, served as the precursor for developing HA-SH NPs through polyelectrolyte complexation involving chitosan and thiol-bearing HA. Results & conclusion: HA-SH NPs displayed favorable characteristics, with small particle sizes (184-270 nm), positive zeta potential (15.4-18.6 mV) and high entrapment efficiency (91.66-95.02%). In vitro, NPs demonstrated potent mucoadhesion and enhanced cytotoxicity compared with free docetaxel. In vivo assessments confirmed safety and biocompatibility, suggesting HA-SH NPs as promising pH-sensitive drug carriers with enhanced antitumor activity for colorectal cancer treatments.

Efficient nanostructured materials to reduce nutrient leaching to overcome environmental contaminants.

Nutrient leaching is a major reason for fresh and ground water contamination. Menthol is the major bioactive ingredient of Mentha arvensis L. and one of the most traded products of global essential oil market. The indigenous production of menthol crystals in developing countries of the world can prove to be the backbone for local growers and poor farmers. Therefore, present research was designed to check the effects of nano-structured plant growth regulators (PGRs) (28-homobrassinolide and ethephon) with reduced leaching potentials on the essential oil and menthol (%) of Mentha arvensis L. The prepared nano-formulations were characterized by Fourier transform infrared (FTIR) spectroscopy, Laser induced breakdown spectroscopy (LIBS), Differential scanning colorimetry-thermal gravimetric analysis (DSC-TGA), Scanning electron microscopy (SEM), Atomic absorption spectrometry (AAS) and Zeta potential and Zeta size analysis. The menthol (%) was determined by modified spectrophotometric and gas chromatographic (GC) method. The highest essential oil (%) was obtained by the application of 28-homobrassinolide-Zn-NPs-L-II (0.92 ± 0.09%) and ethephon-Ca-NPs-L-III (0.91 ± 0.05%) as compared to the control (0.65 ± 0.03%) and blank (0.62 ± 0.09%). The highest menthol (%) was obtained by applying 28-homobrassinolide-Ca-NPs-L-I (80.06 ± 0.07%), 28-homobrassinolide-Ca-NPs-L-II (80.48 ± 0.09%) and 28-homobrassinolide-Ca-NPs-L-III (80.84 ± 0.11%) and ethephon-Ca-NPs-L-III (81.53 ± 0.17%) and ethephon-Zn-NPs-L-II (81.93 ± 0.26%) as compared to control (67.19 ± 0.14%) and blank (63.93 ± 0.17%).

Incorporating the neutrosophic framework into kernel regression for predictive mean estimation.

In traditional statistics, all research endeavors revolve around utilizing precise, crisp data for the predictive estimation of population mean in survey sampling, when the supplementary information is accessible. However, these types of estimates often suffer from bias. The major aim is to uncover the most accurate estimates for the unknown value of the population mean while minimizing the mean square error (MSE). We have employed the neutrosophic approach, which is the extension of classical statistics that deals with the uncertain, vague, and indeterminate information, and proposed a neutrosophic predictive estimator of finite population mean using the kernel regression. The proposed estimator does not yield a single numerical value but instead provides an interval range within which the population parameter is likely to exist. This approach enhances the efficiency of the estimators by offering an estimated interval that encompasses the unknown value of the population mean with the least possible mean squared error (MSE). The simulation-based efficiency of the proposed estimator is discussed using the Sine, Bump and real-time temperature data set of Islamabad by using symmetric (Gaussian) kernel. The proposed non-parametric neutrosophic estimator has shown more effective results under the various bandwidth selectors than the adapted neutrosophic estimators.

Recent Advances of carbon Pathways for Sustainable Environment development.

Carbon dots (CDs) are an emerging type of carbon nanomaterial with strong biocompatibility, distinct chemical and physical properties, and low toxicity. CDs may emit fluorescence in the ultraviolet (UV) to near-infrared (NIR) range, which renders them beneficial for biomedical applications. CDs are usually made from carbon precursors and can be synthesized using top-down and bottom-up methods and it can be easily functionalized using different methods. For specific cases of biomedical applications carbon dot functionalization augments the materials' characteristics. Novel functionalization techniques are still being investigated. This review will look at the benefits of functionalization to attain a high yield and various biological applications. Biomedical applications such as photodynamic and photothermal therapy, biosensing, bioimaging, and antiviral and antibacterial properties will be covered in this review. The future applications of green synthesized carbon dots will be determined in part by this review.

Genetic variant in TNF-α gene and its plasma level in relation to obstructive sleep apnoea in the Pakistani population.

OBJECTIVE: To assess the link between tumour necrosis factor-alpha -308 guanine/adenine polymorphism and tumour necrosis factor-alpha plasma levels in relation to obstructive sleep apnoea. METHODS: The cross-sectional study was conducted from December 2018 to March 2021 at the sleep clinic of Dow University Hospital, Karachi, on obstructive sleep apnoea patients and healthy controls. Epworth Sleep Scale score was used to determine daytime sleepiness, while full-night polysomnography was carried out for obstructive sleep apnoea confirmation and categorisation according to severity. Blood sample collection was followed by deoxyribonucleic acid extraction and plasma tumour necrosis factor-alpha measurement using enzyme-linked immunosorbent assay. Genotype distribution and allelic frequency were assessed. Data was analysed using SPSS 20. RESULTS: Out of the 225 subjects, with a mean age of 47.68±9.88 years, 132 (58.7%) were males, and 93 (41.3%) were females. Among them, 150 (66.7%) were patients, and 75 (33.3%) were controls. Heterozygous tumour necrosis factor-alpha -308 guanine/adenine genotypes were significantly higher among the patients (p<0.05). Minor allele - 308 adenine showed an association with obstructive sleep apnoea, its severity, higher tumour necrosis factor-alpha levels, neck circumference, excessive daytime sleepiness and the presence of hypertension (p<0.05). CONCLUSIONS: Tumour necrosis factor-alpha -308 adenine allele and higher tumour necrosis factor-alpha levels were found to be linked with obstructive sleep apnoea. The polymorphism also showed an association with hypertension in obstructive sleep apnoea patients.

Development of low-cost and high-efficiency solar modules based on perovskite solar cells for large-scale applications.

Solar energy has emerged as a viable and competitive renewable resource due to its abundance and cost-effectiveness. To meet the global energy demands, there is a growing need for efficient devices with unique compositions. In this study, we designed and analyzed a perovskite solar cell (PSC) incorporating methylammonium tin iodide (CH3NH3SnI3) as the active optical absorber material, tin iodide (SnO2) as the electron transport layer (ETL), and copper thiocyanate (CuSCN) as the hole transport layer (HTL) using SCAPS-1D software for numerical investigations. Subsequently, the optimized outcomes were implemented in the PVSyst software package to derive the characteristics of a solar module based on the proposed novel solar cell composition. The objective of our research was to enhance the stability of solar cell for use in solar module. This was achieved by optimizing the thicknesses of the compositional layers which resulted in the enhancement of excess electron and hole mobilities and a reduction in defect densities, thereby leading to an improvement in the device performance. The optimization of excess electron and hole mobilities, as well as defect densities, was conducted to improve the device performance. SCAPS calculations indicated that the perovskite absorber layer (CH3NH3SnI3) may achieve the best possible performance with a maximum optimized thickness of 3.2 µm. The optimized thickness value for CuSCN-HTL and SnO2-ETL were found to be 0.07 µm and 0.05 µm respectively resulting in a maximum power conversion efficiency (PCE) of 23.57%. Variations in open circuit voltage (Voc), short circuit current (Jsc), fill factor (FF %), and quantum efficiency (QE) associated with the optimized thickness values of all layers in the ITO/SnO2/CH3NH3SnI3/CuSCN/Mo composition were critically analyzed. The use of these input parameters resulted in power creation of 557.4 W for a module consisting of 72 cells with an annual performance ratio of 80.3%. These recent investigations are expected to be effective in the design and fabrication of eco-friendly and high-performance solar cells in terms of efficiency.

Mo-based MXenes: Synthesis, properties, and applications.

Ti-MXene allows a range of possibilities to tune their compositional stoichiometry due to their electronic and electrochemical properties. Other than conventionally explored Ti-MXene, there have been ample opportunities for the non-Ti-based MXenes, especially the emerging Mo-based MXenes. Mo-MXenes are established to be remarkable with optoelectronic and electrochemical properties, tuned energy, catalysis, and sensing applications. In this timely review, we systematically discuss the various organized synthesis procedures, associated experimental tunning parameters, physiochemical properties, structural evaluation, stability challenges, key findings, and a wide range of applications of emerging Mo-MXene over Ti-MXenes. We also critically examined the precise control of Mo-MXenes to cater to advanced applications by comprehensively evaluating the summary of recent studies using artificial intelligence and machine learning tools. The critical future perspectives, significant challenges, and possible outlooks for successfully developing and using Mo-MXenes for various practical applications are highlighted.

A meta-analysis of outcomes of aspiration thrombectomy for high and intermediate-risk pulmonary embolism.

BACKGROUND: Aspiration thrombectomy has gained popularity in patients with massive and sub-massive pulmonary embolism (PE) and having contraindications to thrombolysis. METHODS: A meta-analysis was conducted including studies on aspiration thrombectomy in patients with high-risk and intermediate-risk PE. The pooled odds ratio for efficacy parameters, including change in heart rate, blood pressure and right ventricle/left ventricle (RV/LV) ratio, and safety parameters including major bleeding and stroke, was calculated using a random effects model. RESULTS: The meta-analysis of 24 selected studies revealed that intermediate and high-risk pulmonary embolism (PE) patients demonstrated significant improvements: modified Miller score odds ratio of 10.60, mean pulmonary artery pressure reduction by 0.04 mm Hg, and an overall all-cause mortality odds ratio of 0.10. Considerable heterogeneity was observed in various outcomes. CONCLUSION: Aspiration thrombectomy has success rates in both high-risk and intermediate-risk PE, however, procedural risks, including bleeding, must be anticipated.