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Evaluation of the 3D bone morphology of the glenohumeral joint is necessary for pre-surgical planning. Zero echo time (ZTE) magnetic resonance imaging (MRI) provides excellent bone contrast and can potentially be used in the place of computed tomography. Segmentation of the shoulder anatomy, particularly the humeral head and the acetabulum, is needed for the detailed assessment of each anatomy and for pre-surgical preparation. In this study, we compared the performance of two popular deep learning models based on Google’s DeepLab and U-Net to perform automated segmentation on ZTE MRI of human shoulders. Axial ZTE images of normal shoulders (n = 31) acquired at 3-Tesla were annotated for training with DeepLab and 2D U-Net, and the trained model was validated with testing data (n = 13). While both models showed visually satisfactory results for segmenting the humeral bone, U-Net slightly over-estimated while DeepLab under-estimated the segmented area compared to the ground truth. Testing accuracy quantified by Dice score was significantly higher (p < 0.05) for U-Net (88%) than DeepLab (81%) for the humeral segmentation. We have also implemented the U-Net model onto an MRI console for push-button DL segmentation processing. Although this is an early work with limitations, our approach has the potential to improve shoulder MR evaluation hindered by manual post-processing and may provide clinical benefit for quickly visualizing bones of the glenohumeral joint.

Micro-electromechanical systems (MEMS) have the potential to provide low-power phase shifting in silicon photonics, but techniques for designing low-loss devices are necessary for adoption of the technology. Based on coupled mode theory (CMT), we derive analytical expressions relating the loss and, in particular, the phase-dependent loss, to the geometry of the MEMS phase shifters. The analytical model explains the loss mechanisms of MEMS phase shifters and enables simple optimization procedures. Based on that insight, we propose phase shifter geometries that minimize coupling power out of the waveguide. Minimization of the loss is based on mode orthogonality of a waveguide and phase shifter modes. We numerically model such geometries for a silicon nitride MEMS phase shifter over a silicon nitride waveguide, predicting less than −1.08 dB loss over a 2π range and −0.026 dB loss when optimized for a π range. We demonstrate this design framework with a custom silicon nitride process and achieve −0.48 dB insertion loss and less than 0.05 dB transmission variation over a π phase shift. Our work demonstrates the strength of the coupled mode approach for the design and optimization of MEMS phase shifters.

Background: Although the human body generally exhibits bilateral symmetry, achieving perfect symmetry is exceedingly uncommon. During preadolescent development, a face that approximates symmetry is considered both aesthetically and functionally ideal. This study aimed to investigate the relationship between craniofacial traits and hand predominance, using three-dimensional (3D) stereophotogrammetry to discern whether facial soft-tissue characteristics are correlated with hand preference. Materials and Methods: The study involved children aged 9 and 10 years who were free from any diagnosed craniofacial anomalies. Three-dimensional stereophotogrammetry was conducted to analyze their facial morphology, and 37 distinct anatomical landmarks were manually identified using a MATLAB-developed program. Results: A total of 188 Taiwanese children participated in the study. All participants were healthy, with a mean age of 9.79 years. Among them, 93.1% (175) were right-hand predominant, and 6.9% (13) were left-hand predominant. There were no significant differences in linear parameters or facial asymmetry between right-hand-predominant and left-hand-predominant participants (p > 0.05). However, a consistent trend toward right laterality, especially in the right lateral frontal region of the cranium, was observed, as illustrated by heat maps of the average three-dimensional model. Conclusions: The study found no association between facial morphology and hand predominance. A normal asymmetry with a rightward tendency was noted in children aged 9 to 10 years, which was particularly notable in the lateral frontal region of the head.

This study used epigenomic methylation differential expression analysis to identify primary biomarkers in patients with amyotrophic lateral sclerosis (ALS). We combined electronic medical record datasets from MIMIC-IV (United States) and NHIRD (Taiwan) to explore ALS comorbidities in depth and discover any comorbidity-related biomarkers. We also applied word2vec to these two clinical diagnostic medical databases to measure similarities between ALS and other similar diseases and evaluated the statistical assessment of the odds ratio to discover significant comorbidities for ALS subjects. Important and representative DNA methylation biomarker candidates could be effectively selected by cross-comparing similar diseases to ALS, comorbidity-related genes, and differentially expressed methylation loci for ALS subjects. The screened epigenomic and comorbidity-related biomarkers were clustered based on their genetic functions. The candidate DNA methylation biomarkers associated with ALS were comprehensively discovered. Gene ontology annotations were then applied to analyze and cluster the candidate biomarkers into three different groups based on gene function annotations. The results showed that a potential testing kit for ALS detection can be composed of SOD3, CACNA1H, and ERBB4 for effective early screening of ALS using blood samples. By developing an effective DNA methylation biomarker screening mechanism, early detection and prophylactic treatment of high-risk ALS patients can be achieved.

The effect of N-(2-chloro-4-pyridyl)-N′-phenylurea (CPPU) on fruit splitting of ‘Murcott’ tangor fruit (Citrus reticulate × Citrus sinensis) was analyzed throughout two successive seasons during 2020 and 2021. ‘Murcott’ trees were treated with various concentrations of CPPU, 1.0, 5.0, and 10.0 mg·L−1, which significantly reduced the splitting of fruit compared with the control fruit and the gibberellic acid (GA3)-treated fruit (20.0 mg·L−1). The fruit treated with 5.0 mg·L−1 CPPU exhibited higher levels of fruit weight, longitudinal diameter, transverse diameter, peel strength, and peel thickness compared to the control fruit. In addition, the tree sprayed with 5.0 mg·L−1 CPPU had the greatest number of cellular layers and cells at the stylar end calculated in fruit. However, there were no other fruit quality characteristics significantly affected by CPPU and GA3 treatments.

Momordica charantia (bitter melon), a traditional medicinal plant, has been demonstrated to have potential in managing diabetes, gastrointestinal problems, and infections. Among its bioactive compounds, momordicine I, a cucurbitane-type triterpenoid, has attracted attention due to its substantial biological activities. Preclinical studies have indicated that momordicine I possesses antihypertensive, anti-inflammatory, antihypertrophic, antifibrotic, and antioxidative properties, indicating its potential as a therapeutic agent for cardiovascular diseases. Its mechanisms of action include modulating insulin signaling, inhibiting inflammatory pathways, and inducing apoptosis in cancer cells. The proposed mechanistic pathways through which momordicine I exerts its cardiovascular benefits are via the modulation of nitric oxide, angiotensin-converting enzymes, phosphoinositide 3-kinase (PI3K)/ protein kinase B (Akt), oxidative stress, apoptosis and inflammatory pathways. Furthermore, the anti-inflammatory effects of momordicine I are pivotal. Momordicine I might reduce inflammation through the following mechanisms: inhibiting pro-inflammatory cytokines, reducing adhesion molecules expression, suppressing NF-κB activation, modulating the Nrf2 pathway and suppressing c-Met/STAT3 pathway. However, its therapeutic use requires the careful consideration of potential side effects, contraindications, and drug interactions. Future research should focus on elucidating the precise mechanisms of momordicine I, validating its efficacy and safety through clinical trials, and exploring its pharmacokinetics. If proven effective, momordicine I could considerably affect clinical cardiology by acting as a novel adjunct or alternative therapy for cardiovascular diseases. To date, no review article has been published on the role of bitter-melon bioactive metabolites in cardiovascular prevention and therapy. The present work constitutes a comprehensive, up-to-date review of the literature, which highlights the promising therapeutic potential of momordicine I on the cardiovascular system and discusses future research recommendations.

Geosynthetic-reinforced embankments are subject to two primary failure mechanisms: bond failure and rupture. Bond failure occurs when the critical slip surface extends beyond the reinforced zone, while rupture occurs when the slip surface intersects the reinforcement. For a specified factor of safety and reinforcement length, there exists a minimum tensile strength of the reinforcement required to ensure bond failure only. Increasing the tensile strength beyond this minimum does not alter the failure mechanism or the factor of safety. Conversely, extending the reinforcement length while keeping the tensile strength below this critical value may lead to rupture failure at the same factor of safety. This study utilizes Monte Carlo simulation to perform a probabilistic stability analysis of these failure mechanisms in embankments with varying soil types and slope angles. The analysis evaluates safety margins in terms of the factor of safety and probability of failure. Furthermore, this study investigates the impact of cross-correlation between soil strength parameters, demonstrating that realistic values of the correlation coefficient can reduce the probability of failure for both failure mechanisms.

The segment in an underwater shield tunnel is influenced by the change of earth pressure and water pressure. Therefore, the law of segment deformation should be mastered for the safe operation of the tunnel. To obtain the law of segment deformation under varying earth pressure, loading conditions of constant water pressure and without water pressure were considered. In this study, the numerical simulation and scale model experiment were carried to analyze the strain, curvature, and displacement of the segment. The results show that the strain amplitude of segments is reduced by the water pressure under a range of earth pressure. When the earth pressure ranges from 0 MPa to 2.4 MPa and the water pressure 0.33 MPa, the displacement of the vault and arch waist exhibit a decreased rate of 7.916 mm/MPa and an increased rate of 5.416 mm/MPa, respectively. Under the combined effects of constant water pressure and varying earth pressure, the curvature of the segment tends to stabilize after a rapid change with a maximum of 0.004 m−1.

Shield tunnels’ structural stability is challenged due to the fact that they are often built under rivers, lakes, and oceans. It is crucial to execute the structural deformation perception of the shield tunnel. Fiber Bragg grating (FBG) sensing technology is sensitive to deformation information, making it one of the greatest options for shield tunnels to perceive structural deformation. In this study, a 1:20 scale model test was carried out to investigate the deformation perception of the shield tunnel structure under three different layouts of surface-mounted FBG sensors. The deformation law of the tunnel is discussed, under the condition of two-factor cross fusion and especially under the condition of constant water pressure and soil pressure change. The results indicate that, under the combined action of water and soil pressure, the uniform water pressure of 0.33 MPa has a stabilizing effect on the segment strain under the vertical load of 0.4 MPa. The traditional four-point layout and the 18° uniform layout are more effective in detecting changes in local tunnel curvature and strain, respectively, compared to the 36° uniform layout mode. It is advised that the traditional four-point layout be used to collect information for other sections’ monitoring and that the 18° uniform layout is for harsh terrain conditions.

This study presents an innovative home energy management system (HEMS) that incorporates PV, WTs, and hybrid backup storage systems, including a hydrogen storage system (HSS), a battery energy storage system (BESS), and electric vehicles (EVs) with vehicle-to-home (V2H) technology. The research, conducted in Liaoning Province, China, evaluates the performance of the HEMS under various demand response (DR) scenarios, aiming to enhance resilience, efficiency, and energy independence in green buildings. Four DR scenarios were analyzed: No DR, 20% DR, 30% DR, and 40% DR. The findings indicate that implementing DR programs significantly reduces peak load and operating costs. The 40% DR scenario achieved the lowest cumulative operating cost of $749.09, reflecting a 2.34% reduction compared with the $767.07 cost in the No DR scenario. The integration of backup systems, particularly batteries and fuel cells (FCs), effectively managed energy supply, ensuring continuous power availability. The system maintained a low loss of power supply probability (LPSP), indicating high reliability. Advanced optimization techniques, particularly the reptile search algorithm (RSA), are crucial in enhancing system performance and efficiency. These results underscore the potential of hybrid backup storage systems with V2H technology to enhance energy independence and sustainability in residential energy management.

Elastic polymer composite materials possess physical properties such as softness, durability, and heat preservation, making them suitable for designing flexible, snug, and highly ductile devices. While polymers are generally electrical insulators, they can become electrically conductive when doped with carbon powder. Carbon can strongly interact with polymers, enabling the composites to exhibit electrical conductivity through this adsorption process. By heating and melting the polymer and incorporating thin but heavily concentrated carbon powder, these composites can achieve electrical properties similar to those of conductors or semiconductors. This study examines the adsorption and electrical properties of elastic polymer composite materials, focusing on aspects such as resistance temperature characteristics and conductivity. The results indicate that electrically conductive elastic polymers have potential applications in electrothermal devices, thermostatic control systems, sensors, and variable resistors. Additionally, scanning electron microscopy (SEM) is employed to analyze the material’s structure for further research.

(1) Background: Mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) progresses to dementia at a higher annual rate, while other MCIs may remain stable or even improve over time. Discriminating progressive from non-progressive cases of MCI is crucial and challenging. (2) Methods: A retrospective study of individuals with MCI was conducted at a university hospital located in southern Taiwan. The researchers collected demographic data, comorbidities, the scores of cognitive tests, three easy Z-score imaging system (eZIS) indicators (severity, extent, and ratio), Fazekas scale scores, mesial temporal atrophy (MTA) scores, clinical outcomes including deterioration of Cognitive Abilities Screening Instrument, Mini-mental State Examination, Clinical Dementia Rating Sum of Box scores, and the conversion from MCI to dementia. Those who converted to dementia in three years and non-converters were compared by the three eZIS indicators to test the predictive utility, and the clinical outcomes were evaluated by regression and ROC curve analysis. (3) Results: The three eZIS indicators were significantly higher in the group of progressive MCI than in stable MCI. eZIS severity is positively correlated with a deterioration in the scores of the Cognitive Abilities Screening Instrument and Clinical Dementia Rating Sum of Box. eZIS severity is also positively correlated with conversion from MCI to dementia. The AUC for severity is 0.719, and the optimal cutoff value of severity for predicting conversion is 1.22. (4) Conclusions: During three years of follow-up, MCI individuals with greater eZIS severity were significantly associated with worse cognitive assessment scores and a higher conversion rate to dementia.

Adenomyosis, endometriosis of the uterus, is associated with an increased likelihood of abnormal endometrial molecular expressions thought to impair implantation and early embryo development, resulting in disrupted fertility, including the local effects of sex steroid and pituitary hormones, immune responses, inflammatory factors, and neuroangiogenic mediators. In the recent literature, all of the proposed pathogenetic mechanisms of adenomyosis reduce endometrial receptivity and alter the adhesion molecule expression necessary for embryo implantation. The evidence so far has shown that adenomyosis causes lower pregnancy and live birth rates, higher miscarriage rates, as well as adverse obstetric and neonatal outcomes. Both pharmaceutical and surgical treatments for adenomyosis seem to have a positive impact on reproductive outcomes, leading to improved pregnancy and live birth rates. In addition, adenomyosis has negative impacts on reproductive outcomes in patients undergoing assisted reproductive technology. This association appears less significant after patients follow a long gonadotropin-releasing hormone agonist (GnRHa) protocol, which improves implantation rates. The pre-treatment of GnRHa can also be beneficial before engaging in natural conception attempts. This review aims to discover adenomyosis-associated infertility and to provide patient-specific treatment options.

The COVID-19 pandemic, which is caused by the SARS-CoV-2 virus, has resulted in extensive health challenges globally. While SARS-CoV-2 primarily targets the respiratory system, clinical studies have revealed that it could also affect multiple organs, including the heart, kidneys, liver, and brain, leading to severe complications. To unravel the intricate molecular interactions between the virus and host tissues, we performed an integrated transcriptomic analysis to investigate the effects of SARS-CoV-2 on various organs, with a particular focus on the relationship between renal failure and COVID-19. A comparative analysis showed that SARS-CoV-2 triggers a systemic immune response in the brain, heart, and kidney tissues, characterized by significant upregulation of cytokine and chemokine secretion, along with enhanced migration of lymphocytes and leukocytes. A weighted gene co-expression network analysis demonstrated that SARS-CoV-2 could also induce tissue-specific transcriptional profiling. More importantly, single-cell sequencing revealed that COVID-19 patients with renal failure exhibited lower metabolic activity in lung epithelial and B cells, with reduced ligand–receptor interactions, especially CD226 and ICAM, suggesting a compromised immune response. A trajectory analysis revealed that COVID-19 patients with renal failure exhibited less mature alveolar type 1 cells. Furthermore, these patients showed potential fibrosis in the hearts, liver, and lung increased extracellular matrix remodeling activities. However, there was no significant metabolic dysregulation in the liver of COVID-19 patients with renal failure. Candidate drugs prediction by Drug Signatures database and LINCS L1000 Antibody Perturbations Database underscored the importance of considering multi-organ effects in COVID-19 management and highlight potential therapeutic strategies, including targeting viral entry and replication, controlling tissue fibrosis, and alleviating inflammation.

Triple-negative breast cancer (TNBC) represents a challenging malignancy with limited treatment options and a poor prognosis. Adjuvant therapies, including chemotherapy and immune checkpoint inhibitors (ICI), are commonly employed following breast conservation surgery. However, these treatments can lead to various adverse effects, including cutaneous complications and connective tissue disorders. Here, we present the case of a 54-year-old woman with TNBC who developed morphea, a form of localized scleroderma, following adjuvant chemotherapy and pembrolizumab administration. This case highlights the rarity of drug-induced morphea and emphasizes the importance of recognizing and managing such adverse events in breast cancer patients. We discuss the clinical characteristics, diagnostic challenges, and treatment considerations associated with drug-induced scleroderma-like lesions, as well as the potential mechanisms underlying their development. Furthermore, we review the literature on the incidence, clinical features, and outcomes of scleroderma-like lesions induced by chemotherapy and ICIs. This case underscores the need for increased awareness of immune-related adverse events in patients receiving immunotherapy, as well as the importance of individualized treatment approaches to optimize patient care and outcomes.

Clostridioides difficile infection (CDI) worsens inflammatory bowel disease (IBD) prognosis. While fecal microbiota transplantation (FMT) is effective for refractory or recurrent CDI (rrCDI), comparative success rates between IBD and non-IBD patients are scarce. This study addresses this gap. A retrospective cohort study was conducted at Chang Gung Memorial Hospital from April 2019 to October 2023. Patients receiving FMT for rrCDI were categorized into IBD and non-IBD groups. Baseline characteristics and outcomes were compared at one month and one year, with successful FMT defined as the resolution of diarrhea without CDI recurrence. The study included 88 patients: 30 with IBD and 58 without IBD. The IBD group was younger, with fewer comorbidities. Success rates at one month were similar between groups (IBD: 80.0% vs. non-IBD: 78.9%, p = 0.908), as were negative toxin tests (IBD: 83.3% vs. non-IBD: 63.8%, p = 0.174). One-year success rates (IBD: 70.0% vs. non-IBD: 67.6%, p = 0.857) and eradication rates (IBD: 94.4% vs. non-IBD: 73.9%, p = 0.112) were also similar. Poor bowel preparation predicted FMT failure at one month (OR = 0.23, p = 0.019). No safety issues were reported. FMT is a safe, effective treatment for rrCDI, demonstrating similar success rates in patients with and without IBD.

During the long-term operation of tunnels, surrounding rock undergoes creep effects under environmental loads, resulting in changes in the aging evolution model of stress and deformation in surrounding rock and lining, which affects the long-term operational safety of the tunnel. Therefore, using the model test device for time-dependent characteristics of stress and deformation of weak surrounding rock and lining structure in operational tunnels, taking into account the influence of tunnel burial depth and lateral pressure coefficient of surrounding rock, a model test on time-dependent characteristics of stress and deformation in weak surrounding rock and lining structure was conducted, and the stress and deformation time-varying curves at key locations of surrounding rock and lining were obtained. The time characteristics of surrounding rock stress, the contact force between surrounding rock and lining, internal force, and displacement of lining structure were analyzed. Research findings indicate that the stress of surrounding rock, the internal force and displacement of lining structure, and the contact force between surrounding rock and lining all increase and tend to be stable over time under constant load. This implies that the stress and deformation of the surrounding rock and lining structure exhibit time-dependent changes. With changes in burial depth and lateral pressure coefficient, significant variations are observed in the various indicators of stress and deformation in the surrounding rock and lining structure, indicating both time-dependent and long-term characteristics in terms of stress and deformation. The research results provide basic data support for the study of the time-dependent characteristics of stress and deformation between weak surrounding rock and lining structures in operational tunnels and can provide theoretical and technical guidance for the long-term service status discrimination and disaster prevention and control of operational tunnels.

Background: Obesity is a global concern, driving the search for alternative treatments beyond lifestyle changes and medications. Laser acupuncture (LA) shows promise in obesity management, yet few studies compare it with FDA-approved medications. This study aimed to assess and compare LA’s impact with liraglutide on weight reduction in obese individuals. Methods: Data from the Chang Gung Research Database (CGRD) (2013–2018) were analyzed. Primary outcomes included changes in body weight and BMI within 180 days, with secondary outcomes measuring the proportion achieving 5%, 10%, and 15% weight loss. Adverse events were also assessed. Results: Of 745 subjects (173 LA users, 572 liraglutide users), LA users lost more weight by day 180 (5.82 ± 4.39 vs. 2.38 ± 5.75 kg; p < 0.001) and had a greater BMI reduction (−2.27 ± 1.73 vs. −0.93 ± 2.25 kg/m2; p < 0.001). More LA users achieved 5% and 10% weight loss compared to liraglutide users (64.2% vs. 22.7%, 26.6% vs. 4.2%; all p < 0.001). After balancing baseline differences, LA’s benefits remained significant. No adverse events were reported with LA. Conclusions: LA may offer superior weight reduction compared to liraglutide. Future studies should explore LA alone or in combination with liraglutide for obesity management.

The mode rotator is an important component in a PLC-based mode-division multiplexing (MDM) system, which is used to implement high-order modes with vertical intensity peaks, such as LP11b mode conversions from LP11a in PLC chips. In this paper, an LP11 mode rotator based on a polymer/silica hybrid inverted ridge waveguide is demonstrated. The proposed mode rotator is composed of an asymmetrical waveguide with a trench. According to the simulation results, the broadband conversion efficiency between the LP11a and LP11b modes is greater than 98.5%, covering the C-band after optimization. The highest mode conversion efficiency (MCE) is 99.2% at 1550 nm. The large fabrication tolerance of the proposed rotator enables its wide application in on-chip MDM systems.

A complete framework of predicting the attributes of sea clutter under different operational conditions, specified by wind speed, wind direction, grazing angle, and polarization, is proposed for the first time. This framework is composed of empirical spectra to characterize sea-surface profiles under different wind speeds, the Monte Carlo method to generate realizations of sea-surface profiles, the physical-optics method to compute the normalized radar cross-sections (NRCSs) from individual sea-surface realizations, and regression of NRCS data (sea clutter) with an empirical probability density function (PDF) characterized by a few statistical parameters. JONSWAP and Hwang ocean-wave spectra are adopted to generate realizations of sea-surface profiles at low and high wind speeds, respectively. The probability density functions of NRCSs are regressed with K and Weibull distributions, each characterized by two parameters. The probability density functions in the outlier regions of weak and strong signals are regressed with a power-law distribution, each characterized by an index. The statistical parameters and power-law indices of the K and Weibull distributions are derived for the first time under different operational conditions. The study reveals succinct information of sea clutter that can be used to improve the radar performance in a wide variety of complicated ocean environments. The proposed framework can be used as a reference or guidelines for designing future measurement tasks to enhance the existing empirical models on ocean-wave spectra, normalized radar cross-sections, and so on.

Chloride is one of the most abundant ions in sea water, which is more available than fresh water. Due to lack of H2O adsorbate states near the valence band maximum (VBM) edge, the difficulty of water dissociation incidents has been reported on the rutile TiO2 surface as the excitation energy is around the band gap energy of TiO2. It is interesting whether the extra chloride can be a benefit to the water dissociation or not. In this study, the models of chlorine adatoms placed on the rutile TiO2 (110)/water interface are constructed using ab initio methods. The time-dependent spatial charges, bond-lengths of water molecules, and Hirshfeld charges are calculated by real-time time-dependent density functional theory and the Ehrenfest dynamics theory for investigating the excited state nonadiabatic dynamics of water dissociation. This study presents two photoinduced water-splitting pathways related to chlorine and analyzes the photogenerated hole along the reactions. The first step of water dissociation relies on the localized competition of oxygen charges between the dissociated water and the bridge site of TiO2 for transforming the water into hydroxyl and hydrogen by photoinduced driving force.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent type of liver disease worldwide. The exact pathophysiology behind MASLD remains unclear; however, it is thought that a combination of factors or “hits” act as precipitants for disease onset and progression. Abundant evidence supports the roles of diet, genes, metabolic dysregulation, and the intestinal microbiome in influencing the accumulation of lipids in hepatocytes and subsequent progression to inflammation and fibrosis. Currently, there is no cure for MASLD, but lifestyle changes have been the prevailing cornerstones of management. Research is now focusing on the intestinal microbiome as a potential therapeutic target for MASLD, with the spotlight shifting to probiotics, antibiotics, and fecal microbiota transplantation. In this review, we provide an overview of how intestinal microbiota interact with the immune system to contribute to the pathogenesis of MASLD and metabolic dysfunction-associated steatohepatitis (MASH). We also summarize key microbial taxa implicated in the disease and discuss evidence supporting microbial-targeted therapies in its management.

Cardiovascular disease (CVD) represents a substantial global health challenge, with its impact on mortality and morbidity rates surpassing that of cancer. The present study was designed to explore the cardioprotective properties of anthocyanin (ACN), a compound derived from black barley, against oxidative stress-induced damage in myocardial cells and to uncover the molecular mechanisms at play. Utilizing both in vitro and in vivo experimental models, our findings indicate that ACN notably reduced cell damage caused by oxidative stress and effectively prevented apoptosis. High-throughput RNA sequencing analysis has shed light on the mechanism by which ACN achieves its antioxidative stress effects, implicating the PTEN-Akt signaling pathway. ACN was found to modulate PTEN expression levels, which in turn influences the Akt pathway, leading to a reduction in apoptotic processes. This novel insight lays the groundwork for the potential clinical utilization of ACN in the management of CVD. While this study has shed light on some of the functions of ACN, it is important to recognize that natural compounds often interact with multiple molecular targets and engage in intricate signaling cascades. Future research endeavors will concentrate on further elucidating the regulatory mechanisms by which ACN influences PTEN expression, with the goal of enhancing our comprehension and expanding the therapeutic potential of ACN in the treatment of cardiovascular conditions.

The need to manufacture components out of copper is significantly increasing, particularly in the solar technology, semiconductor, and electric vehicle sectors. In the past few decades, infrared laser (IR) and green laser (GL) have been the primary technologies used to address this demand, especially for small or thin components. However, with the increased demand for energy saving, alternative joint techniques such as blue diode laser (BDL) are being actively explored. In this paper, bead-on-plate welding experiments on 0.2 mm thick pure copper samples employing a BDL are presented. Two sets of parameters were carefully selected in this investigation, namely Cu-1: Power (P) = 200 W; Speed (s) = 1 mm/s; and angle = 0°, and Cu-2: P = 200 W; s = 5 mm/s; and angle = 10°. The results from both sets of parameters produced defect-free full penetration welds. Hardness test results indicated relatively softer weld zones compared with the base metal. Tensile test samples fractured in the weld zones. Overall, the samples welded with Cu-1 parameters showed better mechanical properties, such as strength and elongation, than those welded with the Cu-2 parameters. The tensile strength and elongation obtained from Cu-1 were marginally lower than those of the unwelded pure copper. The outcomes from this research provide an alternative welding technique that is able to produce reliable, strong, and precise joints, particularly for small and thin components, which can be very challenging to produce.

Adding fibers into cement to form fiber-reinforced soil cement material can effectively enhance its physical and mechanical properties. In order to investigate the effect of fiber type and dosage on the strength of fiber-reinforced soil cement, polypropylene fibers (PPFs), polyvinyl alcohol fibers (PVAFs), and glass fibers (GFs) were blended according to the mass fraction of the mixture of cement and dry soil (0.5%, 1%, 1.5%, and 2%). Unconfined compressive strength tests, split tensile strength tests, scanning electron microscopy (SEM) tests, and mercury intrusion porosimetry (MIP) pore structure analysis tests were conducted. The results indicated that the unconfined compressive strength of the three types of fiber-reinforced soil cement peaked at a fiber dosage of 0.5%, registering 26.72 MPa, 27.49 MPa, and 27.67 MPa, respectively. The split tensile strength of all three fiber-reinforced soil cement variants reached their maximum at a 1.5% fiber dosage, recording 2.29 MPa, 2.34 MPa, and 2.27 MPa, respectively. The predominant pore sizes in all three fiber-reinforced soil cement specimens ranged from 10 nm to 100 nm. Furthermore, analysis from the perspective of energy evolution revealed that a moderate fiber dosage can minimize energy loss. This paper demonstrates that the unconfined compressive strength test, split tensile strength test, scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) pore structure analysis offer theoretical underpinnings for the utilization of fiber-reinforced soil cement in helical pile core stiffening and broader engineering applications.

An intensive care unit (ICU) is a special ward in the hospital for patients who require intensive care. It is equipped with many instruments monitoring patients’ vital signs and supported by the medical staff. However, continuous monitoring demands a massive workload of medical care. To ease the burden, we aim to develop an automatic detection model to monitor when brain anomalies occur. In this study, we focus on electroencephalography (EEG), which monitors the brain electroactivity of patients continuously. It is mainly for the diagnosis of brain malfunction. We propose the gated-recurrent-unit-based (GRU-based) model for detecting brain anomalies; it predicts whether the spike or sharp wave happens within a short time window. Based on the banana montage setting, the proposed model exploits characteristics of multiple channels simultaneously to detect anomalies. It is trained, validated, and tested on separated EEG data and achieves more than 90% testing performance on sensitivity, specificity, and balanced accuracy. The proposed anomaly detection model detects the existence of a spike or sharp wave precisely; it will notify the ICU medical staff, who can provide immediate follow-up treatment. Consequently, it can reduce the medical workload in the ICU significantly.

In this study, gilthead sea bream (Sparus aurata) fast muscle myoblasts were stimulated with two pro-growth treatments, amino acids (AA) and insulin-like growth factor 1 (Igf-1), to analyze the transcriptional response of mRNAs, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and to explore their possible regulatory network using bioinformatic approaches. AA had a higher impact on transcription (1795 mRNAs changed) compared to Igf-1 (385 mRNAs changed). Both treatments stimulated the transcription of mRNAs related to muscle differentiation (GO:0042692) and sarcomere (GO:0030017), while AA strongly stimulated DNA replication and cell division (GO:0007049). Both pro-growth treatments altered the transcription of over 100 miRNAs, including muscle-specific miRNAs (myomiRs), such as miR-133a/b, miR-206, miR-499, miR-1, and miR-27a. Among 111 detected lncRNAs (>1 FPKM), only 30 were significantly changed by AA and 11 by Igf-1. Eight lncRNAs exhibited strong negative correlations with several mRNAs, suggesting a possible regulation, while 30 lncRNAs showed strong correlations and interactions with several miRNAs, suggesting a role as sponges. This work is the first step in the identification of the ncRNAs network controlling muscle development and growth in gilthead sea bream, pointing out potential regulatory mechanisms in response to pro-growth signals.

Excited state calculations are performed to predict the electronic structure and optical absorption characteristics of Cu-doped anatase TiO2 nanofilms, focusing on their (101) and (001) surface terminations. Using model structures that successfully represent the equilibrium positions of deposited Cu atoms on the TiO2 surface, a comprehensive analysis of the absorption spectra for each considered model is made. The proposed modeling reveals phenomena when photogenerated electrons from TiO2 tend to accumulate in the vicinity of the deposited Cu atoms exposed to photon energies surpassing the band gap of TiO2 (approximately 3.2 eV). The crucial transition states that are essential for the creation of potential photocatalytic materials are identified through detailed calculations of the excited states. These insights hold substantial promise for the strategic design of advanced photocatalytic materials. The obtained results provide a base for subsequent analyses, facilitating the determination of heightened surface reactivity, photostimulated water splitting, and antibacterial properties.

Background: Cytomegalovirus (CMV) gastrointestinal (GI) diseases impact both immunocompromised and immunocompetent individuals, yet comprehensive studies highlighting the differences between these groups are lacking. Methods: In this retrospective study (January 2000 to July 2022) of 401 patients with confirmed CMV GI diseases, we categorized them based on immunological status and compared manifestations, treatments, outcomes, and prognostic factors. Results: The immunocompromised patients (n = 193) showed older age, severe illnesses, and higher comorbidity rates. GI bleeding, the predominant manifestation, occurred more in the immunocompetent group (92.6% vs. 63.6%, p = 0.009). Despite longer antiviral therapy, the immunocompromised patients had higher in-hospital (32.2% vs. 18.9%, p = 0.034) and overall mortality rates (91.1% vs. 43.4%, p < 0.001). The independent factors influencing in-hospital mortality in the immunocompromised patients included GI bleeding (OR 5.782, 95% CI 1.257–26.599, p = 0.024) and antiviral therapy ≥ 14 days (OR 0.232, 95% CI 0.059–0.911, p = 0.036). In the immunocompetent patients, age (OR 1.08, 95% CI 1.006–1.159, p = 0.032), GI bleeding (OR 10.036, 95% CI 1.183–85.133, p = 0.035), and time to diagnosis (OR 1.029, 95% CI 1.004–1.055, p = 0.021) were significant prognostic factors, with the age and diagnosis time cut-offs for survival being 70 years and 31.5 days, respectively. Conclusions: GI bleeding is the most common manifestation and prognostic factor in both groups. Early diagnosis and effective antiviral therapy can significantly reduce in-hospital mortality.

External ventricular drains (EVDs) are common in intensive care for neurocritical patients affected by different illnesses. Nurses play an essential role to ensure safe care, and guidelines are tools to implement evidence-based care. Thus, the aim of this study was to develop and evaluate the quality of a clinical guideline for critically ill patients with EVDs. Methodological research was conducted. The guideline development was based on a scoping review about nursing care to patients with EVDs. The guideline evaluation occurred in two phases: evaluation of its methodological rigor, with application of the Appraisal of Guidelines Research and Evaluation II to four experts on guidelines evaluation; and the Delphi technique, with a panel of nine specialists in neurocritical care, performed in two rounds. Data were analyzed by descriptive statistics and content validity ratio. In the first phase of the evaluation, three domains did not reach consensus, being reformulated. The second phase was conducted in two rounds, with nine and eight participants respectively, with 13 recommendations being reformulated and reassessed between rounds, inclusion of an EVD weaning category, and two flowcharts on patient’s transport and mobility. Therefore, the guideline can be incorporated into nursing care practices. Further studies are necessary to assess its impact on clinical practice.

Alzheimer’s disease (AD) and vascular dementia (VaD) are the two most common forms of dementia. However, their neuropsychological and pathological features often overlap, making it difficult to distinguish between AD and VaD. In addition to clinical consultation and laboratory examinations, clinical dementia diagnosis in Taiwan will also include Tc-99m-ECD SPECT imaging examination. Through machine learning and deep learning technology, we explored the feasibility of using the above clinical practice data to distinguish AD and VaD. We used the physiological data (33 features) and Tc-99m-ECD SPECT images of 112 AD patients and 85 VaD patients in the Taiwanese Nuclear Medicine Brain Image Database to train the classification model. The results, after filtering by the number of SVM RFE 5-fold features, show that the average accuracy of physiological data in distinguishing AD/VaD is 81.22% and the AUC is 0.836; the average accuracy of training images using the Inception V3 model is 85% and the AUC is 0.95. Finally, Grad-CAM heatmap was used to visualize the areas of concern of the model and compared with the SPM analysis method to further understand the differences. This research method can quickly use machine learning and deep learning models to automatically extract image features based on a small amount of general clinical data to objectively distinguish AD and VaD.

Cytomegalovirus (CMV) is a potential pathogen that causes gastrointestinal (GI) tract diseases regardless of host immunity. In contrast to immunocompromised individuals, immunocompetent patients lack a comprehensive overview of the gastrointestinal manifestations. This study aims to provide a comprehensive summary of the current evidence regarding presentations, diagnostics, management, risk assessment, and outcomes in immunocompetent patients with CMV GI disease. A thorough literature search of English publications up to April 2022 was conducted across electronic databases to identify relevant articles, with eligible case series selected for detailed analysis. The majority of immunocompetent patients affected by CMV GI disease are typically elderly, critically ill, or burdened with comorbidities that compromise immunity. Clinical presentations range from subtle symptoms to severe surgical conditions, including instances of mortality. Specific clinical presentations, blood test results, or endoscopic features are lacking, necessitating reliance on histopathological tests such as immunohistochemistry staining for diagnosis. While antiviral therapy may offer benefits in improving outcomes, careful individual assessment is warranted due to diverse comorbidities and potential side effects. Mortality rates vary considerably based on underlying medical conditions and therapeutic approaches. It is imperative for clinicians to maintain vigilance for CMV GI disease among high-risk groups, despite their baseline immunocompetence, in order to enhance clinical outcomes.

It may be possible to enhance adults’ cognitive health and promote healthy aging through processing speed training using the Useful Field of View (UFOV) related activities and software. This study investigated the impact of utilizing UFOV on processing speed improvement in older adults in response to the growing global attention on cognitive health and aging issues. In this quasi-experimental study, 22 individuals (mean age ± SD = 71.9 ± 4.8) participated in the experimental group, and 20 community-based participants (mean age ± SD = 67.1 ± 4.8) were in the control group. The intervention involved ten sessions of UFOV training, each lasting 60 min, conducted twice a week for the experimental group while the control group engaged in volunteer service activities. Measurements of Counting Back, Fabrica, Double-Decision, and Hawkeye were administered to all participants before and after the intervention. The results showed significant improvements in the experimental group for the four measurements (p ≤ 0.01, 0.05, 0.001, 0.001) and non-significant gains in the control group (p ≥ 0.05) for all. Furthermore, mixed repeated-measures ANOVA analysis, with time 1 pre-test measures as the covariate, revealed significant interaction effects between time and group for all measurement indicators (p = 0.05, 0.01, 0.05) except for Fabrica (p > 0.05). In conclusion, these findings support the effectiveness of UFOV cognitive training interventions in enhancing specific cognitive abilities.

MicroRNAs are small regulatory molecules that control gene expression. An emerging property of muscle miRNAs is the cooperative regulation of transcriptional and epitranscriptional events controlling muscle phenotype. miR-155 has been related to muscular dystrophy and muscle cell atrophy. However, the function of miR-155 and its molecular targets in muscular dystrophies remain poorly understood. Through in silico and in vitro approaches, we identify distinct transcriptional profiles induced by miR-155-5p in muscle cells. The treated myotubes changed the expression of 359 genes (166 upregulated and 193 downregulated). We reanalyzed muscle transcriptomic data from dystrophin-deficient patients and detected overlap with gene expression patterns in miR-155-treated myotubes. Our analysis indicated that miR-155 regulates a set of transcripts, including Aldh1l, Nek2, Bub1b, Ramp3, Slc16a4, Plce1, Dync1i1, and Nr1h3. Enrichment analysis demonstrates 20 targets involved in metabolism, cell cycle regulation, muscle cell maintenance, and the immune system. Moreover, digital cytometry confirmed a significant increase in M2 macrophages, indicating miR-155’s effects on immune response in dystrophic muscles. We highlight a critical miR-155 associated with disease-related pathways in skeletal muscle disorders.

A new algorithm named PolyCISAMR is introduced to automatically generate high-fidelity conforming finite element (FE) meshes for two-dimensional polycrystalline microstructures. PolyCISAMR extends the capabilities of the Conforming to Interface Structured Adaptive Mesh Refinement (CISAMR) algorithm, which transforms a structured grid overlaid on the domain geometry into a high-quality conforming mesh. The PolyCISAMR approach uses a segregated meshing strategy, where CISAMR is used to discretize each grain independently and the resulting matching meshes are merged to form the final FE model. In addition, this article presents a set of integrated algorithms for processing low-resolution images of a polycrystal, reconstructed using DREAM.3D software (Version 6.5.121), to generate NURBS characterizations for each grain prior to mesh generation. Example problems demonstrate the effectiveness of PolyCISAMR in creating high-quality meshes for various polycrystalline metallic microstructures along with corresponding crystal plasticity finite element (CPFE) simulations.

Many studies have been exploring the use of bone graft materials (BGMs) and mesenchymal stem cells in bone defect reconstruction. However, the regeneration potential of Algipore (highly purified hydroxyapatite) and Biphasic (hydroxyapatite/beta-tricalcium phosphate) BGMs combined with bone marrow–derived mesenchymal stem cells (BMSCs) remains unclear. Therefore, we evaluated their osseointegration capacities in reconstructing peri-implant bone defects. The cellular characteristics of BMSCs and the material properties of Algipore and Biphasic were assessed in vitro. Four experimental groups—Algipore, Biphasic, Algipore+BMSCs, and Biphasic+BMSCs—were designed in a rabbit tibia peri-implant defect model. Implant stability parameters were measured. After 4 and 8 weeks of healing, all samples were evaluated using micro-CT, histological, and histomorphometric analysis. In the energy-dispersive X-ray spectroscopy experiment, the Ca/P ratio was higher for Algipore (1.67) than for Biphasic (1.44). The ISQ values continuously increased, and the PTV values gradually decreased for all groups during the healing period. Both Algipore and Biphasic BGM promoted new bone regeneration. Higher implant stability and bone volume density were observed when Algipore and Biphasic BGMs were combined with BMSCs. Biphasic BGM exhibited a faster degradation rate than Algipore BGM. Notably, after eight weeks of healing, Algipore with BSMCs showed more bone–implant contact than Biphasic alone (p < 0.05). Both Algipore and Biphasic are efficient in reconstructing peri-implant bone defects. In addition, Algipore BGM incorporation with BSMCs displayed the best performance in enhancing implant stability and osseointegration potential.

The integration of topics on Sustainable Development Goals (SDGs) into project-based learning (PBL) and design thinking (DT) was attempted for the instructional design of a virtual reality (VR) course in this study. It was investigated how to enhance the students’ understanding of the SDGs and promote critical thinking and design thinking skills by integrating SDG topics into PBL and DT. A research design with mixed methods was created based on quantitative and qualitative data from the reflections and feedback of students and teachers. The findings suggested that SDG topics in PBL and DT provided students with a meaningful and engaging learning experience and enhanced their understanding of the interconnections between the SDGs. The importance of incorporating real-world challenges into the instructional design of VR courses and the potential of VR technology were highlighted to support SDG-related learning outcomes. Integrating SDG into PBL and DT was effective for the instructional design of VR courses by preparing students to become responsible global citizens and contribute to achieving the SDGs.

DWI/FLAIR mismatch assessment for ischemic stroke patients shows promising results in determining if patients are eligible for recombinant tissue-type plasminogen activator (r-tPA) treatment. However, the mismatch criteria suffer from two major issues: binary classification of a non-binary problem and the subjectiveness of the assessor. In this article, we present a simple automatic method for segmenting stroke-related parenchymal hyperintensities on FLAIR, allowing for an automatic and continuous DWI/FLAIR mismatch assessment. We further show that our method’s segmentations have comparable inter-rater agreement (DICE 0.820, SD 0.12) compared to that of two neuro-radiologists (DICE 0.856, SD 0.07), that our method appears robust to hyper-parameter choices (suggesting good generalizability), and lastly, that our methods continuous DWI/FLAIR mismatch assessment correlates to mismatch assessments made for a cohort of wake-up stroke patients at hospital submission. The proposed method shows promising results in automating the segmentation of parenchymal hyperintensity within ischemic stroke lesions and could help reduce inter-observer variability of DWI/FLAIR mismatch assessment performed in clinical environments as well as offer a continuous assessment instead of the current binary one.

The enteric nervous system (ENS) is an essential network of neurons and glia in the bowel wall. Defects in ENS development can result in Hirschsprung disease (HSCR), a life-threatening condition characterized by severe constipation, abdominal distention, bilious vomiting, and failure to thrive. A growing body of literature connects HSCR to alterations in miRNA expression, but there are limited data on the normal miRNA landscape in the developing ENS. We sequenced small RNAs (smRNA-seq) and messenger RNAs (mRNA-seq) from ENS precursor cells of mid-gestation Ednrb-EGFP mice and compared them to aggregated RNA from all other cells in the developing bowel. Our smRNA-seq results identified 73 miRNAs that were significantly enriched and highly expressed in the developing ENS, with miR-9, miR-27b, miR-124, miR-137, and miR-488 as our top 5 miRNAs that are conserved in humans. However, contrary to prior reports, our follow-up analyses of miR-137 showed that loss of Mir137 in Nestin-cre, Wnt1-cre, Sox10-cre, or Baf53b-cre lineage cells had no effect on mouse survival or ENS development. Our data provide important context for future studies of miRNAs in HSCR and other ENS diseases and highlight open questions about facility-specific factors in development.

The intersection of biomedicine and radio frequency (RF) engineering has fundamentally transformed self-health monitoring by leveraging soft and wearable electronic devices. This paradigm shift presents a critical challenge, requiring these devices and systems to possess exceptional flexibility, biocompatibility, and functionality. To meet these requirements, traditional electronic systems, such as sensors and antennas made from rigid and bulky materials, must be adapted through material science and schematic design. Notably, in recent years, extensive research efforts have focused on this field, and this review article will concentrate on recent advancements. We will explore the traditional/emerging materials for highly flexible and electrically efficient wearable electronics, followed by systematic designs for improved functionality and performance. Additionally, we will briefly overview several remarkable applications of wearable electronics in biomedical sensing. Finally, we provide an outlook on potential future directions in this developing area.

With growing attention being devoted to autonomous vehicle (AV) safety, people have recently attached importance to high-definition (HD) maps. HD maps are not limited by environmental factors and can limit AVs driving in certain lanes. HD maps provide accurate auxiliary information on factors such as road geometry, traffic sign placement, and traffic topology. Nowadays, most HD maps are made from point clouds data, and this data contains accurate 3D position information. However, the production costs associated with HD maps are substantial. This article proposes an algorithm that reduces a great amount of time and human resource. The algorithm is divided into three phases, lane lines’ extraction from point clouds, modelling lane lines with attributes, and building OpenDRIVE file. The algorithm extracts lane lines resting on intensity value within the range of roads. Next, it models lane lines by cubic spline interpolation with the result of first phase, and build the OpenDRIVE file following the announcement of OpenDRIVE. The final result is compared with the verified HD map from the mapping company to analyze the accuracy. The root mean square (RMSE) obtained were 0.069 and 0.079 m for 2D and 3D maps, respectively.

Microbiota is associated with our bodily functions and microenvironment. A healthy, balanced gut microbiome not only helps maintain mucosal integrity, prevents translocation of bacterial content, and contributes to immune status, but also associates with estrogen metabolism. Gut dysbiosis and estrobolome dysfunction have hence been linked to certain estrogen-dependent diseases, including endometriosis. While prior studies on microbiomes and endometriosis have shown conflicting results, most of the observed microbial differences are seen in the genital tract. This case-control study of reproductive-age women utilizes their fecal and urine samples for enzymatic, microbial, and metabolic studies to explore if patients with endometriosis have distinguishable gut microbiota or altered estrogen metabolism. While gut β-glucuronidase activities, microbial diversity, and abundance did not vary significantly between patients with or without endometriosis, fecal samples of patients with endometriosis were more enriched by the Erysipelotrichia class and had higher folds of four estrogen/estrogen metabolites. Further studies are needed to elucidate what these results imply and whether there indeed is an association or causation between gut microbiota and endometriosis.

This study develops a framework for determining the material parameters of layered engineered wood in a nondestructive manner. The motivation lies in enhancing nondestructive evaluation (NDE) and quality assurance (QA) for engineered wood or mass timber, promising construction materials for sustainable and resilient civil structures. The study employs static compression tests, guided wave measurements, and a genetic algorithm (GA) to solve the inverse problem of determining the mechanical properties of a laminated veneer lumber (LVL) bar. Miniature LVL samples are subjected to compression tests to derive the elastic moduli and Poisson’s ratios. Due to the intrinsic heterogeneity, the destructive compression tests yield large coefficients of variances ranging from 2.5 to 73.2%. Dispersion relations are obtained from spatial–temporal sampling of dynamic responses of the LVL bar. The GA pinpoints optimal mechanical properties by updating orthotropic elastic constants of the LVL material, and thereby dispersion curves, in a COMSOL simulation in accordance with experimental dispersion relations. The proposed framework can support estimation accuracy with errors less than 10% for most elastic constants. Focusing on vertical flexural modes, the estimated elastic constants generally resemble reference values from compression tests. This is the first study that evaluates the feasibility of using guided waves and multi-variable optimization to gauge the mechanical traits of LVL and establishes the foundation for further advances in the study of layered engineered wood structures.

Background: Managing patients with atrial fibrillation (AF) and comorbid heart failure (HF) with reduced (HFrEF) or mildly reduced ejection fraction (HFmrEF) is of clinical importance but a great challenge. This study aimed to evaluate the clinical benefit of the combined radiofrequency catheter ablation (RFCA) and left atrial appendage closure (LAAC) procedure in AF patients complicated with systolic HF. Methods: AF patients with HFrEF or HFmrEF who underwent the combined RFCA and LAAC procedure were prospectively enrolled in the LAACablation registry. The procedural complications and long-term outcomes were evaluated. Another cohort of AF patients with systolic HF who did not undergo either RFCA or LAAC were used for prognosis comparison. Results: Among 802 AF patients who underwent the combined procedure, 65 patients were comorbid with systolic HF (25 with HFrEF and 40 with HFmrEF). The overall procedural complication rate was 9.2%, which was mainly attributed to acute decompensated HF (6.2%). Accompanied with markedly reduced AF burden (from median [25th, 75th percentile]: 100 [100, 100] to 0 [0, 1.2]%, p < 0.001), upward trajectories of cardiac function were observed in 51 (78.4%) patients, showing improvement in New York Heart Classification (p < 0.01), natriuretic peptide levels (from 1492 [809, 3259] to 413 [163, 880] pg/mL, p < 0.001) and left ventricular EF (from 42.6 ± 5.3 to 53.8 ± 8.2%, p < 0.001). During the 27-month follow-up period, death, thromboembolism, major bleeding, and HF rehospitalization were observed in three, one, one, and four patients, respectively. The observed event rates showed a significant reduction compared with the non-procedure AF-HF cohort (n = 138; for composite endpoint: hazard ratio: 2.509, 95% confidence interval: 1.415–4.449, p = 0.002) and with the respective rates predicted by risk scores. Conclusions: Combining RFCA and LAAC achieves acceptable safety and credible long-term efficacy in AF patients with systolic HF. Further randomized studies are warranted in a larger patient cohort.

This paper pioneers the use of the extreme learning machine (ELM) approach for surface roughness prediction in ultra-precision milling, leveraging the excellent fitting ability with small datasets and the fast learning speed of the extreme learning machine method. By providing abundant machining information, the machining parameters and force signal data are fused on the feature level to further improve ELM prediction accuracy. An ultra-precision milling experiment was designed and conducted to verify our proposed data-fusion-based ELM method. The results show that the ELM with data fusion outperforms other state-of-art methods in surface roughness prediction. It achieves an impressively low mean absolute percentage error of 1.6% while requiring a mere 18 s for model training.

Dyslipidemia is a critical factor in the development of atherosclerosis and consequent cardiovascular disease. Numerous pieces of evidence demonstrate the association between air pollution and abnormal blood lipids. Although the results of epidemiological studies on the link between air pollution and blood lipids are unsettled due to different research methods and conditions, most of them corroborate the harmful effects of air pollution on blood lipids. Mechanism studies have revealed that air pollution may affect blood lipids via oxidative stress, inflammation, insulin resistance, mitochondrial dysfunction, and hypothalamic hormone and epigenetic changes. Moreover, there is a risk of metabolic diseases associated with air pollution, including fatty liver disease, diabetes mellitus, and obesity, which are often accompanied by dyslipidemia. Therefore, it is biologically plausible that air pollution affects blood lipids. The overall evidence supports that air pollution has a deleterious effect on blood lipid health. However, further research into susceptibility, indoor air pollution, and gaseous pollutants is required, and the issue of assessing the effects of mixtures of air pollutants remains an obstacle for the future.

Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect for preventing dementia in post-menopausal women. However, the results were still controversial. The association between cholesterol levels and incident dementia in older women is not fully understood either. We conducted a retrospective analysis on a cohort of non-demented women aged older than 50 years, which was registered in the History-based Artificial Intelligence Clinical Dementia Diagnostic System database from September 2015 to August 2021. We followed this cohort longitudinally to examine the rates of conversion to dementia. Using a Cox regression model, we investigated the impact of the quartile of total cholesterol (TC) levels on incident dementia, adjusting for age, sex, education, neuropsychiatric symptoms, neuropsychological assessments, HRT, as well as various vascular risk factors and medications. We examined a cohort of 787 participants, comprising 539 (68.5%) individuals who did not develop dementia (non-converters). Among these non-converters, 68 individuals (12.6%) were treated with HRT. By contrast, there were 248 (31.5%) who did develop dementia (converters). Among the converters, 28 individuals (11.3%) were treated with HRT. The average follow-up durations were 2.9 ± 1.5 and 3.3 ± 1.6 years for non-converters and converters, respectively. Compared to the lowest quartile of TC levels (201) quartiles, respectively (all p < 0.05). However, the low-density lipoprotein cholesterol (LDL-C) level and HRT did not alter the rate of conversion to dementia. In conclusion, the lowest quartile of TC increased incident dementia in post-menopausal women without dementia; however, HRT did not contribute to conversion to dementia. Some studies suggest that post-menopausal women who have reduced estrogen levels might have an increased risk of Alzheimer’s disease if they also have high cholesterol. Nonetheless, the evidence is inconclusive, as not all studies support this finding. The “Lower LDL-C is better” strategy for preventing cardiac vascular disease should be re-examined for the possible serial adverse effects of new onset dementia due to very low cholesterol levels.

The outreach of healthcare services is a challenge to remote areas with affected populations. Fortunately, remote health monitoring (RHM) has improved the hospital service quality and has proved its sustainable growth. However, the absence of security may breach the health insurance portability and accountability act (HIPAA), which has an exclusive set of rules for the privacy of medical data. Therefore, the goal of this work is to design and implement the adaptive Autonomous Protocol (AutoPro) on the patient’s remote healthcare (RHC) monitoring data for the hospital using fully homomorphic encryption (FHE). The aim is to perform adaptive autonomous FHE computations on recent RHM data for providing health status reporting and maintaining the confidentiality of every patient. The autonomous protocol works independently within the group of prime hospital servers without the dependency on the third-party system. The adaptiveness of the protocol modes is based on the patient’s affected level of slight, medium, and severe cases. Related applications are given as glucose monitoring for diabetes, digital blood pressure for stroke, pulse oximeter for COVID-19, electrocardiogram (ECG) for cardiac arrest, etc. The design for this work consists of an autonomous protocol, hospital servers combining multiple prime/local hospitals, and an algorithm based on fast fully homomorphic encryption over the torus (TFHE) library with a ring-variant by the Gentry, Sahai, and Waters (GSW) scheme. The concrete-ML model used within this work is trained using an open heart disease dataset from the UCI machine learning repository. Preprocessing is performed to recover the lost and incomplete data in the dataset. The concrete-ML model is evaluated both on the workstation and cloud server. Also, the FHE protocol is implemented on the AWS cloud network with performance details. The advantages entail providing confidentiality to the patient’s data/report while saving the travel and waiting time for the hospital services. The patient’s data will be completely confidential and can receive emergency services immediately. The FHE results show that the highest accuracy is achieved by support vector classification (SVC) of 88% and linear regression (LR) of 86% with the area under curve (AUC) of 91% and 90%, respectively. Ultimately, the FHE-based protocol presents a novel system that is successfully demonstrated on the cloud network.

The multifaceted nature and swift progression of Amyotrophic Lateral Sclerosis (ALS) pose considerable challenges to our understanding of its evolution and interplay with comorbid conditions. This study seeks to elucidate the temporal dynamics of ALS progression and its interaction with associated diseases. We employed a principal tree-based model to decipher patterns within clinical data derived from a population-based database in Taiwan. The disease progression was portrayed as branched trajectories, each path representing a series of distinct stages. Each stage embodied the cumulative occurrence of co-existing diseases, depicted as nodes on the tree, with edges symbolizing potential transitions between these linked nodes. Our model identified eight distinct ALS patient trajectories, unveiling unique patterns of disease associations at various stages of progression. These patterns may suggest underlying disease mechanisms or risk factors. This research re-conceptualizes ALS progression as a migration through diverse stages, instead of the perspective of a sequence of isolated events. This new approach illuminates patterns of disease association across different progression phases. The insights obtained from this study hold the potential to inform doctors regarding the development of personalized treatment strategies, ultimately enhancing patient prognosis and quality of life.