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Background: Sepsis constitutes a condition that involves life-threatening organ dysfunction induced by severe infection. This nested case–control study investigated risk factors for severe sepsis and whether antipsychotic use is associated with severe sepsis risk in patients with schizophrenia, a topic that has not been comprehensively explored in previous studies. Methods: We selected 39,432 patients with schizophrenia aged between 15 and 65 years from Taiwan's Psychiatric Inpatient Medical Claims database for the period 2000–2012. The case group comprised patients with severe sepsis after their first psychiatric admission (n = 1382). The case and control groups were randomly matched (1:4) by age, sex and first psychiatric admission (year) and finally comprised 1382 and 5528 individuals, respectively. We employed multivariable conditional logistic regression to identify (1) risk factors (physical illnesses and nonpsychiatric medications) and (2) antipsychotic–severe sepsis associations. Results: Higher numbers of psychiatric admissions and physical illnesses such as delirium, cerebrovascular disease and cancer were significantly associated with a higher risk of severe sepsis. Furthermore, severe sepsis was associated with the use of antithrombotic agents, systemic corticosteroids and agents targeting the renin–angiotensin system. Clozapine (adjusted risk ratio = 1.65) and quetiapine (adjusted risk ratio = 1.59) use were associated with an increased risk of severe sepsis. The use of more than one antipsychotic drug could further increase this risk. Conclusion: Several physical illnesses and nonpsychiatric medications increase the risk of severe sepsis in patients with schizophrenia. Specifically, clozapine or quetiapine use significantly increased the risk of severe sepsis in these patients. [ABSTRACT FROM AUTHOR]

Background Objective Method Results and Conclusions Cultivating students' problem‐solving knowledge and skills in the workspace has been regarded as a primary goal in technical and vocational education. To this end, students are usually guided to complete the learning of workspace knowledge and skills by following the question, prompt, interaction and evaluation (QPIE) procedure.In conventional instruction, when teachers present questions of real cases to students, most of the class time is spent on the demonstration of relevant techniques and prompts. Meanwhile, trainers in conventional classrooms often have to guide multiple students simultaneously, making it challenging to provide individual guidance. Therefore, the present study proposed an AR (Augmented Reality)‐based QPIE training mode.To show the effectiveness of the proposed mode, this study recruited two classes of students from a technological university as the participants, and conducted an experiment using a unit of a professional training course. One class of 22 learners adopted the AR‐QPIE training mode, while the other class of 22 learners used the conventional QPIE (C‐QPIE) training mode.The results revealed that the AR‐QPIE training mode enhanced learners' learning achievement, self‐confidence, and several dimensions of learning perceptions more than the C‐QPIE training mode. Besides, in terms of the evaluation of case‐handling performance, the AR‐QPIE training mode could also significantly enhance learners' memory, comprehension, judgement, and calculation abilities in comparison with the C‐QPIE training mode. Yet, no significant differences in the application abilities could be found between the two groups. The proposed training mode of this study could train learners' case‐handling performance, and improve their self‐confidence in the workspace. [ABSTRACT FROM AUTHOR]

Background: In advanced head and neck cancer (HNC) patients, 50–60% experience loco-regional relapse and distant metastasis. Boron neutron capture therapy (BNCT) has shown remarkable therapeutic response in recurrent HNC, but there is still a 70% chance of local recurrence. This study aimed to identify a suitable liquid biomarker to assess patient response following BNCT. Myeloid-derived suppressor cells (MDSCs) are immune-suppressive cells that inhibit cytotoxic T cells. Circulating MDSC levels have been linked to the clinical stage and prognosis in HNSCC. Methods: Five patients with recurrent head and neck cancer underwent a treatment regimen that commenced with BNCT, followed by fractionated image-guided intensity-modulated radiotherapy (IG-IMRT). Liquid biopsy analysis via flow cytometry and tumor volume analysis by clinical imaging were conducted at three stages: before BNCT, before the first fraction of IG-IMRT, and one month after the last fraction of IG-IMRT. Results: Compared to other MDSC subtypes, monocytic MDSCs (M-MDSCs) exhibited a notable correlation with tumor volume. This strong correlation was observed at all testing time points except one month after BNCT treatment. Conclusions: This case series highlights a strong link between tumor size and circulating M-MDSC levels before BNCT and one month after the last IG-IMRT treatment in recurrent head and neck cancer patients. These results suggest that the level of circulating M-MDSCs could be a marker for monitoring tumor progression in recurrent HNC patients following radiation therapy, including BNCT. [ABSTRACT FROM AUTHOR]

Rapid urbanization has an accelerated impact on catchment hydrology and geomorphology due to land use and land cover changes as a result of anthropogenic development activities in river catchment areas that cause increased surface runoff and higher sediment yield. The present study investigates the channel changes and sediment transport phenomena, including bed material movement from the upstream to the estuaries of the Pahang River Basin, Peninsula Malaysia. The river geometry survey associated with the spatial variation in sediment transport has confirmed that changes in river bed profile occur due to the erosion and sediment deposition along the Pahang River. The sediment size distribution for the Pahang River was very coarse sand and gravel after the December 2014 flood. The river geometry survey showed a gentle slope that can induce lower discharge typical of alluvial rivers relating to flood events. Quantitative assessment of sediment load is, therefore, of critical importance for future river basin management. [ABSTRACT FROM AUTHOR]

A sequential nucleophilic substitution method produces rotaxanes from anion-sensitive pseudorotaxanes. First, a nucleophilic bulky tertiary aniline interlocks a pseudorotaxane to form a surrogate rotaxane; this unit then functions as a leaving group for a set of bulky nucleophiles, affording rotaxanes with various linking functionalities, along with the bulky aniline recovered in its original form. [ABSTRACT FROM AUTHOR]

In recent years, smart healthcare technologies used to facilitate precision medicine in clinical practice have increasingly become a topic of discussion. Nurses and nurse preceptors are critical professionals in hospitals, and are also the frontline staff using smart healthcare. The purpose of this study was to investigate nurses' and nurse preceptors' perceptions of smart healthcare (including learning motivation, learning attitudes, and personal innovativeness) and the differences in their conceptions of learning in smart healthcare technology contexts. The research findings showed that nurse preceptors had higher mean scores than nurses for learning motivation, learning attitudes, and personal innovativeness in smart healthcare, especially for learning attitudes and personal innovativeness. The nurse preceptors' conceptions of learning in smart healthcare technology contexts were also more diverse than those of nurses. The main differences are that nurses' drawings showed a healthcare setting where learners (both patients and nurses) use computers to connect to cloud services for online visits, and where patients can engage in online health education learning activities via computers or mobile devices. The nurse preceptors' drawings focused on the delivery of nursing knowledge and skills to learners via VR technologies, helping diagnose patients, analyzing medical data, and predicting healthcare through smart healthcare technologies. [ABSTRACT FROM AUTHOR]

Consider the problem of finding a point furthest from x for each point x in a metric space ([ n ] , d) , where [ n ] = { 1 , 2 , ... , n }. We prove this problem to have a deterministic O (n) -time 1 / 3 -approximation algorithm. As a corollary, the maximum spanning tree problem in metric spaces has a deterministic O (n) -time 1 / 3 -approximation algorithm. We also give a Monte Carlo O (n 1. 5 log n) -time algorithm outputting, for each x ∈ [ n ] , a point y x ∈ [ n ] satisfying d (x , y x) ≥ Δ / 2 , where Δ ≡ max x , y ∈ [ n ] d (x , y). As a corollary, we have a Monte Carlo O (n 1. 5 log n) -time algorithm for finding a spanning tree of weight at least (1 / 2 − o (1)) Δ n in ([ n ] , d). [ABSTRACT FROM AUTHOR]

Oxygen vacancy is crucial to the optical properties in In 2 O 3 , however, the single oxygen vacancy model fails to explain the observed multi-peak emission in the experiment. Herein, we have theoretically investigated the diversity of oxygen vacancy distribution, revealing the relationship between the defect configurations and the optical properties. Combining the first-principles calculations and bayesian regularized artificial neural networks, we demonstrate that the structural stability can be remarkably enhanced by multi-oxygen vacancy aggregation, which will evolve with the defect concentration and temperature. Notably, our results indicate that the single oxygen vacancy will induce the emission peaks centered at 1.35 eV, while multi-peak emission near 2.35 eV will be attributed to the distribution of aggregated double oxygen vacancies. Our findings provide a comprehensive understanding of multi-peak emission observed in In 2 O 3 , and the rules of the vacancy distribution may be extended for other metal oxides to modulate the optical properties in practice. [ABSTRACT FROM AUTHOR]

Multiferroics refer to materials with two or more ferroic orders in one phase within a specific temperature range, including ferroelectricity, ferroelasticity, and ferromagnetism which have been widely used in sensors, actuators, and memory devices. Among them, hybrid perovskites exhibiting multiferroicity are generally limited to low dimensions (0D–2D). Designing 3D lead‐free perovskite multiferroics remains a challenge due to Goldschmidt's tolerance factor limitation. Here, a multiferroic perovskite (R‐3AP)RbBr3 (1; 3AP = 3‐ammoniopyrrolidinium) is successfully synthesized by introducing homochirality to the 3D ferroelectric (Rac‐3AP)RbBr3, achieving both ferroelasticity and ferroelectricity. Compound 1 undergoes a structure phase transition at 401 K belonging to Aizu notation 432F2(s), which has 12 ferroelectric equivalent polarization directions and 6 polar axes. Furthermore, 1 exhibits reversible second harmonic generation switching effects. Moreover, while the temperature varies, the reversible and rapid changes of ferroelastic domains in 1 are observed using a polarizing microscope, indicating that it is a ferroelastic material. This work provides a practical method for designing and synthesizing molecule‐based multiferroics. [ABSTRACT FROM AUTHOR]

Copper (Cu) is the most attractive electrocatalyst for CO2 reduction to multi‐carbon (C2+) products with high economic value in considerable amounts. However, the rational design of a structurally stable Cu‐based catalyst that can achieve high activity and stability towards C2+ products remain a grand challenge. Here, a highly stable nickel oxygenate/Cu electrocatalyst is developed with abundant NiOOH/Cu interfaces by in situ electrochemical reconstruction. The nickel oxygenate/Cu electrocatalyst achieves a superior Faradaic efficiency of 86.3 ± 3.0% and a record partial current density of 2085 A g−1 for C2+ products with long‐term stability. In situ experimental and theoretical studies demonstrates that the exceptional performance in generating C2+ products is attributed to the presence of the NiOOH/Cu interfaces which increase *CO coverage, lower energy barrier for *CO coupling and stabilize *OCCO simultaneously. This work provides new insights into the rational design of electrocatalysts to achieve stable and efficient electrocatalytic CO2 reduction capabilities. [ABSTRACT FROM AUTHOR]

Urban agglomerations (UAs), which serve as pivotal hubs for economic and innovative convergence, play a crucial role in enhancing internal circulation and strengthening external linkages. This study utilizes the China city-level multi-regional input-output tables, incorporating the Dagum Gini coefficient and kernel density estimation methods, to perform a thorough quantitative analysis. Disparities within the national and global value chains ("dual value chains") of Chinese UAs from 2012 to 2017 were assessed. Additionally, the logarithmic mean Divisia index (LMDI) method was applied to disaggregate the drivers of both national and global intermediate inputs (NII and GII). The study's key findings include the following: (1) The national value chain (NVC) within UAs exhibits robust growth, contrasting with the decline in the global value chain (GVC). (2) The inter-UA disparity contribution rate significantly surpasses the combined rates of intra-UA contribution and super-variation density. (3) Distinct evolutionary peak trends are discerned among various UAs within the "dual value chains", highlighting diverse spatial polarization characteristics and expansiveness. (4) The growth of the NVC has transitioned from a negative to a positive impact on NII, while the decline in GVC has substantially counteracted GII growth. Economic and demographic factors notably drive positive improvements in both NII and GII, whereas the efficiency of outflows presents a negative driving effect. Based on these findings, this study offers strategic recommendations to facilitate the effective integration of UAs into the new development paradigm, thereby providing a scientific basis for related decision-making processes. [ABSTRACT FROM AUTHOR]

Objectives: Cervical disc herniation (CDH) leads to pain, numbness, and potential disability. Percutaneous endoscopic cervical discectomy (PECD) offers an anterior or posterior approach. This study aims to compare postoperative disc height and angle changes one year after PECD, considering both approaches. Methods: We retrospectively reviewed the data from patients with CDH who underwent PECD from October 2017 to July 2022. Cervical disc height was measured using the preoperative and one-year postoperative magnetic resonance imaging (MRI) examinations. Lordotic angle (LA), global alignment angle (GAA), segmental alignment angle (SAA), and slippage distance (SD) at the surgical level were measured on radiographs in the neutral, flexion, and extension positions. Results: Thirty-eight patients who underwent posterior PECD (PPECD) and five patients who underwent anterior PECD (APECD) were included in the evaluation. The mean age of the patients was 47.4 years (range: 29–69 years). There was a significant difference in the preoperative and one-year postoperative GAA and SAA in extension in the PPECD group (p = 0.003 and 0.031, respectively). The mean decreased disc height one-year postoperative was 1.30 mm in the APECD group and 0.3 mm in the PPECD group by MRI. A significant disc height decrease was observed in the APECD group (p < 0.001). Conclusions: Treating CDH with PPECD or APECD is feasible, as it can relieve symptoms and reduce disability. Stability remained unaffected during the first year after surgery, even though there was an increase in angulation during extension. Despite a significant decrease in disc space following APECD, patients reported significant symptom improvement and no new symptoms. [ABSTRACT FROM AUTHOR]

Professional trainers play an important role in helping new recruits adapt to the workplace. In general hospitals, training courses for clinical teachers still adopt the lecture method. Such a teacher training approach focuses on the way of delivering knowledge and skills, while the training for their teaching of case handling as well as their self-worth and self-confidence could be insufficient. In order to cope with this problem, the present study proposed a ChatGPT-based training mode (ChatGPT-TM) for professional development. To verify its effects, we conducted an experiment in a “Using ChatGPT in Case Teaching” course for clinical teachers in hospitals, and explored their learning achievement, self-worth, self-confidence, and learning perceptions using the ChatGPT training mode (ChatGPT-TM) and the conventional training mode (C-TM). The results showed that the ChatGPT-TM could effectively enhance clinical teachers’ learning achievement in case teaching, self-worth, and self-confidence in comparison with the C-TM. The main contribution of this study is that it revealed that ChatGPT could allow clinical teachers to carry out reflection, verify references, and integrate theory and practice, which improved their learning achievement, made them realize their self-worth, and increased their self-confidence in performing professional training tasks. [ABSTRACT FROM AUTHOR]

The Ti-MIL-125 metal-organic framework (MOF) functions as a nanoreactor, producing carbon quantum dots (CQDs) within its structure and forming CQD/MOF composites. Similarly, a Pt-CQD/MOF three-component composite is synthesized. Their properties, along with those of CQDs and MOF-free-CQDs (mf -CQDs) enclosed within the MOF, undergo assessment and comparison. Integrating CQDs and Pt minimally alters the MOF structure but reduces specific surface areas due to incorporation. The emitted wavelength of CQD/MOF (570 nm) differs from pristine CQDs (450 nm) and mf -CQDs (496 nm), indicating MOF influence on CQDs' growth and photoluminescence. HOMO and LUMO levels of CQDs/MOF, measured via ultraviolet photoelectron spectroscopy and low-energy inverse photoelectron spectroscopy, are more positive than those of the MOF, suggesting heterogeneous junction formation, aiding electron separation. CQD/MOF exhibits a modest photocatalytic hydrogen evolution rate of 20.4 μmol/g/h. Conversely, Pt-CQD/MOF significantly boosts the rate to 2213 μmol/g/h, underscoring Pt's pivotal catalytic role. [Display omitted] • Ti-MIL-125 MOF functioned as the nanoreactor in the synthesis of CQD. • The MOFs and the CQDs captured inside form the CQD/MOF composites. • The CQDs and those inside MOFs showed different emission wavelengths but similar QY. • Pt particles were incorporated into CQD/MOF for preparing Pt-CQD/MOF composites. • The rate of H 2 generation by Pt-CQD/MOF reached 2213 μ mol h⁻1g⁻1. [ABSTRACT FROM AUTHOR]

Shifting from the typical 4e– pathway to H2O in electrochemical oxygen reduction to the 2e– pathway to H2O2 is increasingly recognized as an environmentally friendly approach for producing H2O2. However, the competitive 4e− pathway is a significant obstacle to the production of H2O2 since H2O is the thermodynamically favored product. Here, a series of Pt, Pd, and Rh active atoms diluted within inert‐Au matrices with precisely controlled atomic arrangements and coordination environments are synthesized via facet engineering for O2‐to‐H2O2 production. Surprisingly, individually dispersed Pt atoms within the Au surface enclosed by the square atomic arrangements exhibit superior H2O2 selectivity and achieve a maximum selectivity of 90% at 0.36 V versus the reversible hydrogen electrode. Operando synchrotron ambient pressure X‐ray photoelectron spectroscopy identifies the presence of *OOH key intermediates on these isolated Pt active sites. Grand canonical density‐functional theory also reveals that the kinetic energy barrier for the 2e− pathway (0.08 eV; OOH* + H+ + e− → H2O2) on the isolated Pt sites is significantly lower than the 4e− pathway (0.29 eV; OOH* + H+ + e− → O* + H2O). This work enables atomic‐scale control in dilute binary alloy surfaces with specific configurations of isolated active atoms and provides essential guidance for catalyst design to boost O2‐to‐H2O2 production. [ABSTRACT FROM AUTHOR]

The identification of risk factors for future prediabetes in young men remains largely unexamined. This study enrolled 6247 young ethnic Chinese men with normal fasting plasma glucose at the baseline (FPGbase), and used machine learning (Mach-L) methods to predict prediabetes after 5.8 years. The study seeks to achieve the following: 1. Evaluate whether Mach-L outperformed traditional multiple linear regression (MLR). 2. Identify the most important risk factors. The baseline data included demographic, biochemistry, and lifestyle information. Two models were built, where Model 1 included all variables and Model 2 excluded FPGbase, since it had the most profound effect on prediction. Random forest, stochastic gradient boosting, eXtreme gradient boosting, and elastic net were used, and the model performance was compared using different error metrics. All the Mach-L errors were smaller than those for MLR, thus Mach-L provided the most accurate results. In descending order of importance, the key factors for Model 1 were FPGbase, body fat (BF), creatinine (Cr), thyroid stimulating hormone (TSH), WBC, and age, while those for Model 2 were BF, white blood cell, age, TSH, TG, and LDL-C. We concluded that FPGbase was the most important factor to predict future prediabetes. However, after removing FPGbase, WBC, TSH, BF, HDL-C, and age were the key factors after 5.8 years. [ABSTRACT FROM AUTHOR]

Background: Both sleep-related breathing disorders (SRBDs) and HIV infection can interfere with normal sleep architecture, and also cause physical and psychological distress. We aimed to understand the differences in the obstructive patterns, sleep architecture, physical and psychological distress when compared between people living with HIV (PLWH) and matched the severity of SRBDs controls. Methods: A comparative study using matched case-control design was conducted. Men with HIV infection (case group) were enrolled from 2016 to 2019. A control group with HIV seronegative men were matched for SRBDs severity, and were selected from sleep medicine center database for comparison. Results: The mean age of the 108 men (including 54 cases and 54 matched controls) was 33.75 years. Central-apnea index (CI) was higher in the case group rather than matched controls (mean CI, 0.34 vs. 0.17, p = 0.049). PLWH had a lower mean percentage of stage 3 sleep (10.26% vs. 13.94%, p = 0.034) and a higher percentage of rapid eye movement sleep (20.59% vs. 17.85%, p = 0.011) compared to matched controls. Nocturnal enuresis and sleepiness causing traffic accidents were more frequent complaint in PLWH compared to controls. Conclusions: Early detected SRBDs and subtypes in PLWH to begin treatment for the underlying cause could reduce the risk of sleepiness-related traffic accidents. [ABSTRACT FROM AUTHOR]

Three new copper(II) complexes, [CuClL] (1), [CuBrL]n (2) and [CuL(NCS)]n (3), derived from the Schiff base 2,4-dichloro-6-((2-pyrrolidin-1-ylethylimino)methyl)phenol (HL) have been prepared and characterized by spectroscopic methods, as well as single crystal X-ray determination. The Cu atom in complex 1 is in square planar coordination, and those in complexes 2 and 3 are in square pyramidal coordination. The Schiff base ligand coordinates to the Cu atoms through phenolate oxygen, imino nitrogen and pyrrolidine nitrogen. The antibacterial activities of the Schiff base and the three copper complexes have been assayed on the bacteria Staphylococcus aureus and Escherichia coli and the yeast Candida parapsilosis. [ABSTRACT FROM AUTHOR]

Our previous study discovered that sucrose and other non-reducing sugars (e.g., trehalose and raffinose) could be used to improve the electrotransfer (ET) of molecular cargo, including DNA, mRNA, and ribonucleoprotein in various cell lines and primary human cells in vitro and in vivo. To understand the molecular mechanisms of this improvement, we used RNA sequencing technology to analyze changes in the cell transcriptome after sucrose treatment. The results from our analysis demonstrated that the sucrose treatment upregulated phospholipase A2 and V-ATPase gene families, which could potentially influence the acidity of intracellular vesicles through augmenting vesicle fusion and the influx of proton, respectively. To determine how this upregulation affects ET efficiency, we treated cells with pharmaceutical inhibitors of phospholipase A2 and V-ATPase. The data demonstrated that the treatment with the phospholipase A2 inhibitor could reverse the ET improvement elicited by the sucrose treatment. The V-ATPase inhibitor treatment either had little influence or further enhanced the effect of the sucrose treatment on the ET efficiency. These observations provide a molecular explanation for our previous findings, demonstrating that the sucrose treatment primarily enhanced the ET efficiency by promoting vesicle trafficking and fusion through the activation of phospholipase A2. [ABSTRACT FROM AUTHOR]

In the supplier–retailer–consumer system, the retailer's replenishment and pricing strategies impact the entire transaction process, forming a comprehensive trading market. Suppliers offer advance-cash-credit payments to retailers, while retailers provide customers with cash-credit payment options. In the current health-conscious consumer market, purchasing decisions are influenced not only by commodity prices but also by the freshness of products, particularly perishable goods. Growing awareness of climate change and the advent of carbon emission policies have raised concerns about the environmental costs of business transactions. This study focuses on perishable products whose demand is influenced by both price and freshness. It explores the adoption of various payment methods by suppliers and retailers, as well as the impact of carbon emission cap-and-trade policies or carbon tax policies on management and pricing strategies. Suitable inventory models are established to determine the optimal replenishment and pricing strategies for maximizing the current value of total profit. We illustrate that the current value of total profit demonstrates joint concavity concerning both the selling price and the replenishment time. Finally, we verify the proposed models using numerical examples and present the findings of sensitivity analyses. The findings of this study yield several valuable insights for inventory management of perishable goods. [ABSTRACT FROM AUTHOR]

Designers rely on sketching to visualize and refine their initial ideas, and virtual reality (VR) tools now facilitate sketching in immersive 3D environments. However, little research has been conducted on the differences in the visual and spatial processes involved in 3D versus 2D sketching and their effects on cognition. This study investigated potential differences in spatial and visual functions related to the use of 3D versus 2D sketching media by analyzing functional magnetic resonance imaging (fMRI) data. We recruited 20 healthy, right-handed students from the Department of Horticulture and Landscape Architecture with at least three years of experience in freehand landscape drawing. Using an Oculus Quest VR headset controller and a 12.9-inch iPad Pro with an Apple Pencil, we tested participants individually with 3D and 2D sketching, respectively. When comparing 2D and 3D sketches, our fMRI results revealed significant differences in the activation of several brain regions, including the right middle temporal gyrus, both sides of the parietal lobe, and the left middle occipital gyrus. We also compared different sketching conditions, such as lines, geometrical objects (cube), and naturalistic objects (perspective view of a tree), and found significant differences in the spatial and visual recognition of brain areas that support visual recognition, composition, and spatial perception. This finding suggests that 3D sketching environments, such as VR, may activate more visual–spatial functions during sketching compared to 2D environments. The result highlights the potential of immersive sketching environments for design-related processes and spatial thinking. [ABSTRACT FROM AUTHOR]

Background Few studies have evaluated mental health disorders comprehensively among patients with prostate cancer on long-term follow-up. The primary aim of our study was to assess the incidence of mental health disorders among patients with prostate cancer compared with a general population cohort. A secondary aim was to investigate potential risk factors for mental health disorders among patients with prostate cancer. Methods Cohorts of 18 134 patients with prostate adenocarcinomas diagnosed between 2004 and 2017 and 73470 men without cancer matched on age, birth state, and follow-up time were identified. Mental health diagnoses were identified from electronic health records and statewide health-care facilities data. Cox proportional hazard models were used to estimate hazard ratios. All statistical tests were 2-sided. Results The hazard ratios for mood disorders, including depression, among prostate cancer survivors increased for all follow-up periods compared with the general population. The hazard ratios for any mental illness increased with Hispanic, Black, or multiple races; people who were underweight or obese; those with advanced prostate cancer; and those undergoing their first course cancer treatment. We also observed statistically significantly increased hazard ratios for mental health disorders among patients with lower socioeconomic status (P  < .0001) and increasing duration of androgen-deprivation therapy (P  = .0348). Prostate cancer survivors had a 61% increased hazard ratio for death with a depression diagnosis. Conclusion Prostate cancer diagnosis was associated with a higher risk of mental health disorders compared with the general population, which was observed as long as 10-16 years after cancer diagnosis. Providing long-term mental health support may be beneficial to increasing life expectancy for patients with prostate cancer. [ABSTRACT FROM AUTHOR]

Ample evidence has indicated shifts in distribution of fish populations in response to environmental stress. However, most studies focused at the whole population scale. This neglects the spatial dynamics between groups of different body size (body size groups), that fundamentally shapes the spatial structure of a population. Here, we explored the mechanisms that modulate spatial dynamics of body size groups, and applied our analyses to three North Sea fish populations which experienced severe declines in biomass from 1977 to 2019: Atlantic cod Gadus morhua, haddock Melanogrammus aeglefinus and whiting Merlangius merlangius. All three populations exhibited strong declines in the overlapped area between body size groups in winter over 43 years, yet their mechanisms differed. These declines were either due to 1) different magnitudes of contraction of the distribution area of body size groups; and/or 2) different speeds and directions of spatial shift among various body size groups, both increasing spatial segregation within populations. These patterns were either associated with ocean warming, and/or declining population biomass, and such associations often varied according to distinct body size groups. Increasing spatial segregation between size groups of a population likely hampers life‐cycle connectivity and stability to local perturbations. Our analytical approach provides a powerful tool for identifying vulnerable populations under environmental stress and can be generalized to study a variety of size/age structured populations at various ecosystem types. [ABSTRACT FROM AUTHOR]

The enzyme‐resistant thioglycosides are highly valuable immunogens because of their enhanced metabolic stability. We report the first synthesis of a family of thiooligosaccharides related to the capsular polysaccharides (CPS) of Campylobacter jejuni HS:4 for potential use in conjugate vaccines. The native CPS structures of the pathogen consist of a challenging repeating disaccharide formed with β(1→4)‐linked 6‐deoxy‐β‐D‐ido‐heptopyranoside and N‐acetyl‐D‐glucosamine; the rare 6‐deoxy‐ido‐heptopyranosyl backbone and β‐anomeric configuration of the former monosaccharide makes the synthesis of this family of antigens very challenging. So far, no synthesis of the thioanalogs of the CPS antigens have been reported. The unprecedented synthesis presented in this work is built on an elegant approach by using β‐glycosylthiolate as a glycosyl donor to open the 2,3‐epoxide functionality of pre‐designed 6‐deoxy‐β‐D‐talo‐heptopyranosides. Our results illustrated that this key trans‐thioglycosylation can be designed in a modular and regio and stereo‐selective manner. Built on the success of this novel approach, we succeeded the synthesis of a family of thiooligosaccharides including a thiohexasaccharide which is considered to be the desired antigen length and complexity for immunizations. We also report the first direct conversion of base‐stable but acid‐labile 2‐trimethylsilylethyl glycosides to glycosyl‐1‐thioacetates in a one‐pot manner. [ABSTRACT FROM AUTHOR]

This paper investigates a wind speed oscillation event that occurred near the coastline of central Taiwan in the afternoon of 17 February 2018, using data from observations and numerical simulations. The observed wind speeds at 100-m altitude displayed a fast-oscillating pattern of about 6 cycles between strong winds of approximately 21 m s−1 and weak winds of around 2 m s−1, with periods of about 10 min. The pressure anomalies fluctuated in antiphase with the wind speed anomalies. The synoptic analysis revealed the influence of a continental high pressure system, resulting in a cold-air outbreak over Taiwan. The cold north-northeasterly winds split into two branches upon encountering Taiwan's topography, with ridging off the east coast and a lee trough off the west coast of Taiwan. Wind oscillations were detected in the low-level cold air offshore the west coast of Taiwan, depicted by wavelike structures in wind speeds, sea level pressure, and potential temperature. The perturbations were identified as Kelvin-Helmholtz billows characterized by regions of strong wind speeds, warm and dry air, sinking motions, and low pressure collocated with each other, while regions of weaker wind speeds, cooler and moister air, ascending motions, and high pressure were associated with each other. With terrain contributing to favorable conditions, the large vertical and horizontal wind shears resulted from the southward acceleration of low-level cold air and the northward movement of the lee trough played an important role in initiating the wind oscillations. [ABSTRACT FROM AUTHOR]

Background: Cultivating staff's professional English has become an imperative and challenging issue in English as a Foreign Language (EFL) countries. English for medical professionals is also the common language around the world for publishing new medical knowledge or reports. Therefore, Medical English for Health Professionals (MEHP) is a crucial required professional training program in nursing education. Its purpose is to improve nursing students' professional English so that they can directly understand the clinical medical information related to patients, thereby reading the latest international medical knowledge and participating in research themselves. Objective: The MEHP program is commonly conducted in a large‐scale class using the lecturing approach, which is a passive learning mode lacking opportunities for individual students to experience learning contexts and to receive advice and guidance from the teacher. To solve this problem, the present study proposed a motivation model‐based professional English gaming approach. Method: To verify the effects of the proposed approach, a quasi‐experiment was conducted in an MEHP program of a university to explore the effects of the approach on nursing students' learning achievements. In addition, the higher and lower achievers' behavioural patterns, as well as their perceptions of the learning approach, were investigated. Results and Conclusions: The results showed that the motivation model‐based digital gaming approach improved the students' professional English achievements in the "application" dimension as well as their positive perceptions of learning professional English more than the conventional learning approach. Moreover, when learning with the proposed approach, the higher achievers revealed more positive behavioural patterns than the lower achievers. The main contributions of the study are the proposal of a motivation model‐based digital gaming approach, and showing the effectiveness of the proposed approach in helping trainees gain a deeper understanding of professional English and facilitating their positive learning behaviours in a course for medical English. Practitioner notes: What is already known about this topic: Scholars have indicated the importance of situating learners in authentic contexts.Digital games can provide learning contexts for English as Foreign Language (EFL) learners.Digital games have potential to motivate EFL learners to actively learn and practice English. What this paper adds: A motivation model‐based digital gaming approach is proposed for professional English learning.A digital game has been implemented for Medical English for Health Professionals (MEHP) based on the proposed approach.An experiment has been conducted to examine the effectiveness of the approach and to analyse learners' behaviours using the proposed approach. Implications for practice and/or policy: The motivation model‐based digital gaming approach has great potential in improving learners' professional achievements.The motivation model‐based digital gaming approach can promote learners' positive behavioural patterns.It is recommended to apply the approach to other professional English courses for EFL learners. [ABSTRACT FROM AUTHOR]

Interleukin (IL)-8 plays a vital role in regulating inflammation and breast cancer formation by activating CXCR1/2. We previously designed an antagonist peptide, (RF16), to inhibits the activation of downstream signaling pathways by competing with IL-8 in binding to CXCR1/2, thereby inhibiting IL-8-induced chemoattractant monocyte binding. To evaluate the effect of the RF16 peptide on breast cancer progression, triple-negative MDA-MB-231 and ER-positive MCF-7 breast cancer cells were used to investigate whether RF16 can inhibit the IL-8-induced breast cancer metastasis. Using growth, proliferation, and invasiveness assays, the results revealed that RF16 reduced cell proliferation, migration, and invasiveness in MDA-MB-231 cells. The RF16 peptide also regulated the protein and mRNA expressions of epithelial–mesenchymal transition (EMT) markers in IL-8-stimulated MDA-MB-231 cells. It also inhibited downstream IL-8 signaling and the IL-8-induced inflammatory response via the mitogen-activated protein kinase (MAPK) and Phosphoinositide 3-kinase (PI3K) pathways. In the xenograft tumor mouse model, RF16 synergistically reinforces the antitumor efficacy of docetaxel by improving mouse survival and retarding tumor growth. Our results indicate that RF16 significantly inhibited IL-8-stimulated cell growth, migration, and invasion in MDA-MB-231 breast cancer cells by blocking the activation of p38 and AKT cascades. It indicated that the RF16 peptide may serve as a new supplementary drug for breast cancer. [ABSTRACT FROM AUTHOR]

Abrupt changes in system states and dynamical behaviors are often observed in natural systems; such phenomena, named regime shifts, are explained as transitions between alternative steady states (more generally, attractors). Various methods have been proposed to detect regime shifts from time series data, but a generic detection method with theoretical linkage to underlying dynamics is lacking. Here, we provide a novel method named Nested-Library Analysis (NLA) to retrospectively detect regime shifts using empirical dynamic modeling (EDM) rooted in theory of attractor reconstruction. Specifically, NLA determines the time of regime shift as the cutting point at which sequential reduction of the library set (i.e., the time series data used to reconstruct the attractor for forecasting) optimizes the forecast skill of EDM. We illustrate this method on a chaotic model of which changing parameters present a critical transition. Our analysis shows that NLA detects the change point in the model system and outperforms existing approaches based on statistical characteristics. In addition, NLA empirically detected a real-world regime shift event revealing an abrupt change of Pacific Decadal Oscillation index around the mid-1970s. Importantly, our method can be easily generalized to various systems because NLA is equation-free and requires only a single time series. Author summary: Abrupt shifts in system dynamics, referred to as regime shifts, are common in natural systems and pose significant challenges for system management and risk assessment. Accurately detecting the change point that separates pre- and post-regime shift periods is crucial, as the data collected after regime shift can be more informative to forecast future system states. While numerous methods have been proposed to tackle this issue, identifying change points in chaotic systems remains difficult, in which regime shift signals can be concealed by chaotic dynamics. To address this issue, we propose Nested-Library Analysis (NLA), a machine learning method rooted in a data-driven, nonparametric framework for nonlinear dynamical systems, known as Empirical Dynamic Modeling (EDM). NLA effectively identifies the change points from time series data, even when the shifts in dynamics are nearly imperceptible due to chaotic behavior, surpassing the existing change point detection methods. As such, our method offers a generic solution for revealing the timing of regime shifts in a various type of dynamical system. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is the most aggressive and fatal breast cancer subtype. Nowadays, chemotherapy remains the standard treatment of TNBC, and immunotherapy has emerged as an important alternative. However, the high rate of TNBC recurrence suggests that new treatment is desperately needed. Schisandrin B (Sch B) has recently revealed its anti-tumor effects in cancers such as cholangiocarcinoma, hepatoma, glioma, and multi-drug-resistant breast cancer. However, there is still a need to investigate using Sch B in TNBC treatment. Interleukin (IL)-1β, an inflammatory cytokine that can be expressed and produced by the cancer cell itself, has been suggested to promote BC proliferation and progression. In the current study, we present evidence that Sch B can significantly suppress the growth, migration, and invasion of TNBC cell lines and patient-derived TNBC cells. Through inhibition of inflammasome activation, Sch B inhibits interleukin (IL)-1β production of TNBC cells, hindering its progression. This was confirmed using an NLRP3 inhibitor, OLT1177, which revealed a similar beneficial effect in combating TNBC progression. Sch B treatment also inhibits IL-1β-induced EMT expression of TNBC cells, which may contribute to the anti-tumor response. [ABSTRACT FROM AUTHOR]

Background: Ruling out obstructive coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) is time‐consuming and challenging. This study developed a deep learning (DL) model to assist in detecting obstructive CAD on CCTA to streamline workflows. Methods: In total, 2929 DICOM files and 7945 labels were extracted from curved planar reformatted CCTA images. A modified Inception V3 model was adopted. To validate the artificial intelligence (AI) model, two cardiologists labelled and adjudicated the classification of coronary stenosis on CCTA. The model was trained to differentiate the coronary artery into binary stenosis classifications <50% and ≥50% stenosis. Using the quantitative coronary angiography (QCA) consensus results as a reference standard, the performance of the AI model and CCTA radiology readers was compared by calculating Cohen's kappa coefficients at patient and vessel levels. The net reclassification index was used to evaluate the net benefit of the DL model. Results: The diagnostic accuracy of the AI model was 92.3% and 88.4% at the patient and vessel levels, respectively. Compared with CCTA radiology readers, the AI model had a better agreement for binary stenosis classification at both patient and vessel levels (Cohen kappa coefficient:.79 vs..39 and.77 vs..40, p <.0001). The AI model also exhibited significantly improved model discrimination and reclassification (Net reclassification index =.350; Z = 4.194; p <.001). Conclusions: The developed AI model identified obstructive CAD, and the model results correlated well with QCA results. Incorporating the model into the reporting system of CCTA may improve workflows. [ABSTRACT FROM AUTHOR]

The basolateral amygdala (BLA) and the nucleus accumbens core (NAcc) share some similar behavioral functions, such as associative learning, Pavlovian to instrumental transfer, and choice behavior. However, their prefrontal anatomical inputs have not been well characterized before, especially the collateral projections. In this study, we analyzed the distribution and collateralization of projections to the BLA and the NAcc from the prefrontal cortices (PFC), including the prelimbic (PL) and the infralimbic (IL) divisions of the medial prefrontal cortex (mPFC) and the subregions of the orbitofrontal cortex (OFC), such as the medial OFC (MO), the lateral OFC (LO), and the ventral OFC (VO). Double retrograde tracing approach was used, in which Cholera toxin subunit B conjugated with the Alexa Fluor 488 (CTB-AF488) or Alexa Fluor 594 (CTB-AF594) were unilaterally injected into the BLA and the NAcc, respectively, in male Long-Evans rats (n = 6). Among the sampled neurons, prefrontal projection to the BLA or the NAcc is more robust on the ipsilateral side, and more robust from the PL, the IL, and the MO compared to from the LO and the VO. The majority of the projections from the PFC to the BLA and/or the NAcc are confined in deep layer. In addition, for each of the prefrontal areas, about 15–25% BLA-projecting neurons send collateral projections to the NAcc, and vice versa. In conclusion, our data suggested that prefrontal control over the BLA and the NAcc is not entirely independent. The functional importance of the collateral projections awaits further examination. [ABSTRACT FROM AUTHOR]

Objective: To explore the short- and long-term effects of lower-limb endurance training on chronic obstructive pulmonary disease outpatients. Design: Prospective quasi-experimental study. Setting: 1383-bed teaching hospital in Taiwan. Participants: Overall, 69 outpatients diagnosed with chronic obstructive pulmonary disease were enrolled. A total of 60 patients completed the study. Intervention: Training group: Lower-limb endurance training; control group: Education only. Main measures: The modified medical research council score, chronic obstructive pulmonary disease assessment test score, pulmonary function test, and number of acute exacerbation within a year. Results: The training group showed significant improvement in the chronic obstructive pulmonary disease assessment test total score, modified medical research council score (both P < 0.001) at third month sustaining to 12th month (P < 0.001) and presented less events of acute exacerbation (P = 0.011) at 12th month. The chronic obstructive pulmonary disease assessment test decreased by 8 points sustaining to 12th month. The training group presented significant post-training functional capacity improvements in 6-min walking distance, lowest oxygen saturation during 6-min walking test, peak workload, maximum inspiratory/ expiratory pressures, and calf circumference. Conclusions: The lower-limb endurance training improved perceived dyspnea in daily activity and health status after completion of training and sustaining for a year. The lower-limb endurance training alleviated disease impacted on reduced acute exacerbations. [ABSTRACT FROM AUTHOR]

Human interleukin-10 (IL-10) is an immunosuppressive and anti-inflammatory cytokine, and its expression is upregulated in tumor tissues and serum samples of patients with various cancers. Because of its immunosuppressive nature, IL-10 has also been suggested to be a factor leading to tumor cells' evasion of immune surveillance and clearance by the host immune system. In this study, we refined a peptide with 20 amino acids, named NK20a, derived from the binding region of IL-10 on the basis of in silico analysis of the complex structure of IL-10 with IL-10Ra, the ligand binding subunit of the IL-10 receptor. The binding ability of the peptide was confirmed through in vitro biophysical biolayer interferometry and cellular experiments. The IL-10 inhibitory peptide exerted anticancer effects on lymphoma B cells and could abolish the suppression effect of IL-10 on macrophages. NK20a was also conjugated with gold nanoparticles to target the chemotherapeutic 5-fluorouracil (5-FU)-loaded nanoparticles to enhance the anticancer efficacy of 5-FU against the breast cancer cell line BT-474. Our study demonstrated that NK20a designed in silico with improved binding affinity to the IL-10 receptor can be used as a tool in developing anticancer strategies. Human interleukin-10 (IL-10) is known to be an immunosuppressive cytokine for anti-inflammation, however, IL-10 can enable the evasion of tumor cells through immunosuppression of the host immune system. Here, the authors develop an IL-10 inhibitory peptide, NK20a, that displays anticancer effects, and show that its conjugation with chemotherapeutic gold nanoparticles enhances their anticancer efficacy. [ABSTRACT FROM AUTHOR]

Background: Taiwan's warm and humid climate and dense population provide a suitable environment for the breeding of pests. The three major urban insects in Taiwan are house flies, cockroaches, and mosquitoes. In cases where a disease outbreak or high pest density necessitates chemical control, selecting the most effective insecticide is crucial. The resistance of pests to the selected environmental insecticide must be rapidly assessed to achieve effective chemical control and reduce environmental pollution. Methods: In this study, we evaluated the resistance of various pests, namely, house flies (Musca domestica L.), cockroaches (Blattella germanica L. and Periplaneta americana), and mosquitoes (Aedes aegypti and Ae. albopictus) against 10 commonly used insecticides. Rapid insecticide resistance bioassays were performed using discriminating doses or concentrations of the active ingredients of insecticides. Results: Five field strains of M. domestica (L.) are resistant to all 10 commonly used insecticides and exhibit cross- and multiple resistance to four types of pyrethroids and three types of organophosphates, propoxur, fipronil, and imidacloprid. None of the five field strains of P. americana are resistant to any of the tested insecticides, and only one strain of B. germanica (L.) is resistant to permethrin. One strain of Ae. albopictus is resistant to pirimiphos-methyl, whereas five strains of Ae. aegypti exhibit multiple resistance to pyrethroids, organophosphates, and other insecticides. Conclusions: In the event of a disease outbreak or high pest density, rapid insecticide resistance bioassays may be performed using discriminating doses or concentrations to achieve precise and effective chemical control, reduce environmental pollution, and increase control efficacy. [ABSTRACT FROM AUTHOR]

Metaplastic breast carcinoma is an invasive carcinoma with a high differentiation rate of the neoplastic epithelium toward mesenchymal-like epithelium. It comprises of only less than 1% of all breast cancers. Although 80% to 90% of metaplastic breast carcinomas are triple-negative cancers, they usually have worse outcomes than other triple-negative breast cancers (TNBCs). Metaplastic carcinoma is also often refractory to cytotoxic chemotherapy. Here, we reported a case of a 61-year-old female patient, presenting with a solitary and pedunculated mass in the right axillary tail breast tissue, whose biopsy revealed metaplastic breast carcinoma with chondroid differentiation. She had failed neoadjuvant chemotherapy and immunotherapy. Although she received debulking surgery, the tumor regrew even faster before surgery. Despite receiving palliative chemotherapy, the patient died 11 weeks after surgery. This case draws attention to physicians that early recognition and surgery may be more beneficial than chemotherapy in combating metaplastic breast carcinoma. [ABSTRACT FROM AUTHOR]

PURPOSE: In 2021, 59.6% of low-risk patients with prostate cancer were under active surveillance (AS) as their first course of treatment. However, few studies have investigated AS and watchful waiting (WW) separately. The objectives of this study were to develop and validate a population-level machine learning model for distinguishing AS and WW in the conservative treatment group, and to investigate initial cancer management trends from 2004 to 2017 and the risk of chronic diseases among patients with prostate cancer with different treatment modalities. METHODS: In a cohort of 18,134 patients with prostate adenocarcinoma diagnosed between 2004 and 2017, 1,926 patients with available AS/WW information were analyzed using machine learning algorithms with 10-fold cross-validation. Models were evaluated using performance metrics and Brier score. Cox proportional hazard models were used to estimate hazard ratios for chronic disease risk. RESULTS: Logistic regression models achieved a test area under the receiver operating curve of 0.73, F -score of 0.79, accuracy of 0.71, and Brier score of 0.29, demonstrating good calibration, precision, and recall values. We noted a sharp increase in AS use between 2004 and 2016 among patients with low-risk prostate cancer and a moderate increase among intermediate-risk patients between 2008 and 2017. Compared with the AS group, radical treatment was associated with a lower risk of prostate cancer–specific mortality but higher risks of Alzheimer disease, anemia, glaucoma, hyperlipidemia, and hypertension. CONCLUSION: A machine learning approach accurately distinguished AS and WW groups in conservative treatment in this decision analytical model study. Our results provide insight into the necessity to separate AS and WW in population-based studies. [ABSTRACT FROM AUTHOR]

In professional training courses, developing incumbents' professional knowledge and problem-solving skills when facing clinical and urgent situations is a crucial point. In conventional professional training, usually the learning content is delivered in a lecture-based mode using instructional videos with some case studies. In such a training mode, trainees are more passive and cannot immerse themselves in the contexts since there is a lack of opportunity to experience the process of coping with problems when accidents occur. Moreover, trainers generally do not have sufficient practice and are unable to think in depth regarding how to use the learned knowledge and skills to deal with practical cases. To tackle this problem, an experiential learning-based virtual reality approach is proposed in the present study. Accordingly, a virtual reality-based learning environment was implemented; moreover, a quasi-experimental study was carried out to verify the effectiveness of this approach in a professional training program of a hospital by exploring its influences on nursing staff's learning achievement and perceptions from diverse angles. The experimental results showed that the proposed approach better enhanced the nursing staff's learning achievement, learning attitudes, and problem-solving skills in comparison with the conventional teaching mode. [ABSTRACT FROM AUTHOR]

Objective: This meta-analysis aimed to ascertain the efficacy of non-invasive brain stimulation (NIBS)—comprising repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS)—for depression in traumatic brain injury (TBI) patients. Methods: Comprehensive searches were conducted in PubMed, Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials up to 28 January 2023. Random-effects models assessed the treatment effects, and heterogeneity was evaluated through I2 statistics and funnel plot inspection. Results: From 10 trials (234 participants; 8 rTMS, 2 tDCS), NIBS was found significantly more effective than sham in alleviating depressive symptoms (SMD: 0.588, 95% CI: 0.264–0.912; p < 0.001). rTMS, specifically, showed higher efficacy (SMD: 0.707, 95% CI: 0.306–1.108; p = 0.001) compared to sham, whereas tDCS outcomes were inconclusive (SMD: 0.271, 95% CI: −0.230 to 0.771; p = 0.289). Meta-regression found no correlation with the number of sessions, treatment intensity, or total dose. Notably, while post-treatment effects were significant, they diminished 1–2 months post intervention. Adverse events associated with NIBS were minimal, with no severe outcomes like seizures and suicide reported. Conclusions: rTMS emerged as a potent short-term intervention for depression in TBI patients, while tDCS findings remained equivocal. The long-term efficacy of NIBS is yet to be established, warranting further studies. The low adverse event rate reaffirms NIBS's potential safety. [ABSTRACT FROM AUTHOR]

Background: Angiotensin receptor blockers (ARBs) are considered an alternative to angiotensin-converting enzyme inhibitors (ACEIs) in patients with acute myocardial infarction (AMI), but in the era of extensive use of preventive therapies and percutaneous coronary intervention, this has not been adequately evaluated in Asians. Methods: This retrospective cohort study used data from the Taiwan National Health Insurance Research Database. In total, 52,620 patients initially hospitalized due to AMI between 2002 and 2015 were assessed. Results: After propensity score matching, 14,993 patients each were assigned to ACEI and ARB groups. Patients who received ARBs had significantly lower all-cause mortality (adjusted hazard ratio [aHR]: 0.82; 95% confidence interval [CI]: 0.75–0.90) and hospitalization for heart failure (aHR: 0.92; 95% CI: 0.85–0.99) compared with those who received ACEIs at 18 month follow-up. No significant difference was observed between the two groups in terms of major adverse cardiovascular events (aHR: 098; 95% CI: 0.90–1.07), cardiovascular death (aHR: 0.82; 95% CI: 0.68–1.00), ischemia stroke (aHR: 0.93; 95% CI: 0.77–1.11), and nonfatal myocardial infarction (aHR: 1.04; 95% CI: 0.93–1.17). ARBs showed benefits in many subgroups in terms of all-cause mortality and cardiovascular death. Conclusions: Real-world data demonstrate that ARBs might be associated with lower all-cause mortality and hospitalization for heart failure compared with ACEIs among patients with AMI. [ABSTRACT FROM AUTHOR]

Real-world data sources can facilitate essential understanding of the epidemiological features of anaphylaxis. However, the accuracy of case-identifying definitions based on diagnosis codes for anaphylaxis in healthcare databases remains understudied. We conducted a cross-sectional study analyzing claims data from the largest multi-institutional healthcare system in Taiwan during 2017–2021. We included patients with incident anaphylaxis identified by either ICD-10-CM codes for anaphylaxis (Group 1) or ICD-10-CM codes for severe allergic or drug adverse events and additional modifier codes for acute allergy events (Group 2). We randomly selected 20% of the cases to determine the positive predictive value (PPV) of anaphylaxis case-identifying definitions in Groups 1 and 2 after review of electronic medical records by two physicians. From the original cohort (n = 2,176), we randomly selected 433 patients with either a diagnosis of anaphylaxis (Group 1), or a diagnosis of severe allergic and drug adverse events with additional modifier codes for acute allergy events (Group 2). In Group 1, we judged 135 / 170 patients as true anaphylaxis cases, giving a PPV of 79.4% (95% CI: 73.3–85.5). In Group 2, we judged 47 / 263 patients as true anaphylaxis cases, giving a PPV of 17.9% (95% CI: 13.3–22.5). In conclusion, acceptable PPVs were observed when anaphylaxis cases were identified by ICD-10-CM codes for anaphylaxis, but not by ICD-10-CM codes for severe allergic or drug adverse event with additional modifier codes for acute allergy events. Our multi-institutional findings could serve as a fundamental reference for further studies of anaphylaxis based on real-world healthcare databases. [ABSTRACT FROM AUTHOR]

Abstract Although artificial intelligence (AI) is currently a prominent technology that has received increasing attention, the factors affecting users’ AI device adoption for healthcare were less discussed. Drawing on affordance-actualization theory and literature on AI, uniqueness theory, and healthcare, we developed a research model to explain users’ adoption intention of AI devices in the healthcare context. Data collected from 307 potential users in China were used to test the proposed model. Our findings indicated that data capture, classification, and social affordances impacted self-monitoring significantly, while data capture and social affordances were the predators of uniqueness enhancement. The self-monitoring, on the other hand, had a positive influence on uniqueness enhancement. Finally, our results revealed that self-monitoring and uniqueness enhancement have significant effects on AI adoption. From the findings, theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Background: The International Society of Urological Pathology (ISUP) grade and positive surgical margins (PSMs) after radical prostatectomy (RP) may reflect the prognosis of prostate cancer (PCa) patients. This study aimed to investigate whether DCE-MRI parameters (i.e., Ktrans, kep, and IAUC) could predict ISUP grade and PSMs after RP. Method: Forty-five PCa patients underwent preoperative DCE-MRI. The clinical characteristics and DCE-MRI parameters of the 45 patients were compared between the low- and high-risk (i.e., ISUP grades III-V) groups and between patients with or without PSMs after RP. Multivariate logistic regression analysis was used to identify the significant predictors of placement in the high-risk group and PSMs. Results: The DCE parameter Ktrans-max was significantly higher in the high-risk group than in the low-risk group (p = 0.028) and was also a significant predictor of placement in the high-risk group (odds ratio [OR] = 1.032, 95% confidence interval [CI] = 1.005–1.060, p = 0.021). Patients with PSMs had significantly higher prostate-specific antigen (PSA) titers, positive biopsy core percentages, Ktrans-max, kep-median, and kep-max than others (all p < 0.05). Of these, positive biopsy core percentage (OR = 1.035, 95% CI = 1.003–1.068, p = 0.032) and kep-max (OR = 1.078, 95% CI = 1.012–1.148, p = 0.020) were significant predictors of PSMs. Conclusion: Preoperative DCE-MRI parameters, specifically Ktrans-max and kep-max, could potentially serve as preoperative imaging biomarkers for postoperative PCa prognosis based on their predictability of PCa risk group and PSM on RP, respectively. [ABSTRACT FROM AUTHOR]

The structural analysis of proteins is a major domain of biomedical research. Such analysis requires resolved three-dimensional structures of proteins. Advancements in computer technology have led to progress in biomedical research. In silico prediction and modeling approaches have facilitated the construction of protein structures, with or without structural templates. In this study, we used three neural network-based de novo modeling approaches—AlphaFold2 (AF2), Robetta-RoseTTAFold (Robetta), and transform-restrained Rosetta (trRosetta)—and two template-based tools—the Molecular Operating Environment (MOE) and iterative threading assembly refinement (I-TASSER)—to construct the structure of a viral capsid protein, hepatitis C virus core protein (HCVcp), whose structure have not been fully resolved by laboratory techniques. Templates with sufficient sequence identity for the homology modeling of complete HCVcp are currently unavailable. Therefore, we performed domain-based homology modeling for MOE simulations. The templates for each domain were obtained through sequence-based searches on NCBI and the Protein Data Bank. Then, the modeled domains were assembled to construct the complete structure of HCVcp. The full-length structure and two truncated forms modeled using various computational tools were compared. Molecular dynamics (MD) simulations were performed to refine the structures. The root mean square deviation of backbone atoms, root mean square fluctuation of Cα atoms, and radius of gyration were calculated to monitor structural changes and convergence in the simulations. The model quality was evaluated through ERRAT and phi–psi plot analysis. In terms of the initial prediction for protein modeling, Robetta and trRosetta outperformed AF2. Regarding template-based tools, MOE outperformed I-TASSER. MD simulations resulted in compactly folded protein structures, which were of good quality and theoretically accurate. Thus, the predicted structures of certain proteins must be refined to obtain reliable structural models. MD simulation is a promising tool for this purpose. [ABSTRACT FROM AUTHOR]

• Bi-NH 2 -BDC is prepared by a simple solvothermal method. • Bi-NH 2 -BDC has excellent adsorption and photocatalytic properties for DCF. • The adsorption of DCF is due to hydrogen bonding, π-π conjugation and electrostatic interaction. • Bi-NH 2 -BDC is a reusable and stable photocatalyst. The mass production and widespread use of Pharmaceuticals and Personal Care Products (PPCPs) have posed a serious threat to the water environment and public health. In this work, a green metal-based Metal Organic Framework (MOF) Bi-NH 2 -BDC was prepared and characterized, and the adsorption characteristics of Bi-NH 2 -BDC were investigated with typical PPCPs—diclofenac sodium (DCF). It was found that DCF mainly covered the adsorbent surface as a single molecular layer, the adsorption reaction was a spontaneous, entropy-increasing exothermic process and the adsorption mechanisms between Bi-NH 2 -BDC and DCF were hydrogen bonding, π-π interactions and electrostatic interactions. In addition, Bi-NH 2 -BDC also had considerable photocatalytic properties, and its application in adsorbent desorption treatment effectively solved the problem of secondary pollution, achieving a green and sustainable adsorption desorption cycle. [Display omitted] [ABSTRACT FROM AUTHOR]

COVID-19 vaccines work by introducing components of the virus or its genetic material to activate the immune system and prevent the development of the disease. However, some research studies have suggested a potential link between COVID-19 vaccination and an increased risk of autoimmune diseases. Proposed mechanisms for this link include molecular mimicry, adjuvants, and bystander activation. It is important to note that these mechanisms are hypotheses and further research is needed to confirm their role. Additionally, COVID-19 itself may also induce or precipitate autoimmune conditions. COVID-19 vaccines have shown promise in mitigating the risk of autoimmune diseases associated with COVID-19. However, more research is needed to understand the relationship between antiviral medications and the reduction of subsequent autoimmune diseases in the context of COVID-19. [Extracted from the article]

The coiled ice-storage-based air conditioning system plays a significant role in enhancing grid peak regulation and improving cooling economy. This paper presents theoretical and experimental studies conducted on the ice storage process of coiled ice storage air conditioning technology. The cooling of water is divided into two stages:10.0 °C to 4.0 °C and 4.0 °C to below 0.0 °C. Initially, the ice storage process forms an ice layer with a thickness of 2.50 mm on the lower surface of the coil, but eventually, the ice layer on the upper surface becomes 3.85 mm thicker than the lower surface as a result of the natural convection of water and density reversal at 4.0 °C. Furthermore, the impact of three coils with different thermal conductivity on the ice storage process was evaluated. It was observed that the thermal conductivity of R-HDPE (reinforced high-density polyethylene) was only 2.6 W/(m·K) higher than HDPE (high-density polyethylene), yet it reduced the freezing time by 34.85%, while the thermal conductivity of steel was 37.4 W/(m·K) higher than R-HDPE, but only decreased the freezing time by 9.40%. The results demonstrated that the rate of ice accumulation increased with thermal conductivity. However, when the coil material's thermal conductivity surpassed that of ice, the further increase of thermal conductivity gradually weakened its impact on the ice storage rate. [ABSTRACT FROM AUTHOR]

Early, express, and reliable detection of cancer can provide a favorable prognosis and decrease mortality. Tumor biomarkers have been proven to be closely related to tumor occurrence and development. Conventional tumor biomarker detection based on genomic, proteomic, and metabolomic methods is time and equipment-consuming and always needs a specific target marker. Surface-enhanced Raman scattering (SERS), as a non-invasive ultrasensitive and label-free vibrational spectroscopy technique, can detect cancer-related biomedical changes in biofluids. In this paper, 110 serum samples were collected from 30 healthy controls and 80 cancer patients (including 30 bladder cancer (BC), 30 adrenal cancer (AC), and 20 acute myeloid leukemia (AML)). One microliter of blood serum was mixed with 1 μl silver colloid and then was air-dried for SERS measurements. After spectral data augmentation, one-dimensional convolutional neural network (1D-CNN) was proposed for precise and rapid identification of healthy and three different cancers with high accuracy of 98.27%. After gradient-weighted class activation mapping (Grad-CAM) based spectral interpretation, the contributions of SERS peaks corresponding to biochemical substances indicated the most potential biomarkers, i.e., L-tyrosine in bladder cancer; acetoacetate and riboflavin in adrenal cancer and phospholipids, amide-I, and α-Helix in acute myeloid leukemia, which might provide an insight into the mechanism of intelligent diagnosis of different cancers based on label-free serum SERS. The integration of label-free SERS and deep learning has great potential for the rapid, reliable, and non-invasive detection of cancers, which may significantly improve the precise diagnosis in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Approximately 10% to 20% of myasthenia gravis (MG) patients have experienced a myasthenic crisis (MC), which contributes to morbidity and mortality. MC triggered by infection is associated with poor outcomes. However, there is a lack of prognostic factors that clinicians can utilize to target interventions for preventing recurrent infection-triggered MC. This study aimed to characterize clinical manifestations, comorbidities, and biochemical profiles associated with recurrent infection-triggered MC in MG patients. Methods: This retrospective study included 272 MG patients hospitalized with an infection requiring at least 3 days of antibiotics from January 2001 to December 2019. Patients were further stratified into non-recurrent or recurrent infection groups. Clinical features such as gender, age, concomitant diseases, acetylcholine receptor antibodies and biochemical data (including electrolytes and coagulants), muscle strength of pelvic and shoulder girdle, bulbar and respiratory function, management with an endotracheal tube, Foley catheter, or plasmapheresis, duration of hospitalization, and culture pathogens were recorded. Results: The recurrent infection group was significantly older than the non-recurrent group (median age, 58.5 versus 52.0 years). Pneumonia was the most common infection and Klebsiella pneumoniae was the most common pathogen. The presence of concomitant diabetes mellitus, activated partial thromboplastin time prolongation, the duration of hospitalization, and hypomagnesaemia were independently associated with recurrent infection. The presence of deep vein thrombosis, thymic cancer, and electrolyte imbalances i.e., hypokalemia, and hypoalbuminemia were significantly associated with a risk for infection. The influence of endotracheal intubation, anemia, and plasmapheresis during hospitalization were inconsistent. Conclusions: The independent risk factors for recurrent infections in MG patients identified in this study include the presence of concomitant diabetes mellitus, hypomagnesaemia, activated partial thromboplastin time prolongation, and longer duration of hospitalization, highlighting the need for targeted interventions to prevent recurrent infections in this population. Further research and prospective studies are warranted to validate these findings and refine interventions for optimizing patient care. [ABSTRACT FROM AUTHOR]

A microscopic finite element model validated by the quasi-static mechanical test on lithium ion battery cell is presented in this study. The investigated condition involves three-point bending and cell discharge test, which include the mechanical response and thermal response of lithium ion battery cell. The cell is investigated through computational simulation. Results show great correlation between the experiment and finite element simulation. A microscopic model requires a greater effort during simulation. Investigating the fracture on steel casing and cell core is possible by considering the fracture mechanism in steel shell and jelly roll. The classic von-Mises criterion is applied to predict the failure of carbon steel shell, and the maximum von-Mises strain criterion is used to investigate the jelly roll region. On the basis of the verified battery cell model, battery package with microscopic model, including cell core (cathode, anode, and separator) is constructed to analyze the mechanical response of battery pack. The von-Mises criterion is used to predict the fracture point location of the battery pack with various packing modes and packing densities. [ABSTRACT FROM AUTHOR]