bluuebunny/crossref_metadata_2025 huggingface dataset:
Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate
Authors: Schmidt A. , Carslaw K. S. , Mann G. W. , Rap A. , Pringle K. J. , Spracklen D. V. , Wilson M. , Forster P. M.
Published: March 2012

Abstract. Observations and models have shown that continuously degassing volcanoes have a potentially large effect on the natural background aerosol loading and the radiative state of the atmosphere. Here, we use a global aerosol microphysics model to quantify the impact of these volcanic emissions on the cloud albedo radiative forcing under pre-industrial (PI) and present-day (PD) conditions. We find that volcanic degassing increases global annual mean cloud droplet number concentrations by 40% under PI conditions, but by only 10% under PD conditions. Consequently, volcanic degassing causes a global annual mean cloud albedo effect of −1.06 W m−2 in the PI era but only −0.56 W m−2 in the PD era. This non-equal effect is explained partly by the lower background aerosol concentrations in the PI era, but also because more aerosol particles are produced per unit of volcanic sulphur emission in the PI atmosphere. The higher sensitivity of the PI atmosphere to volcanic emissions has an important consequence for the anthropogenic cloud radiative forcing because the large uncertainty in volcanic emissions translates into an uncertainty in the PI baseline cloud radiative state. Assuming a −50/+100% uncertainty range in the volcanic sulphur flux, we estimate the annual mean anthropogenic cloud albedo forcing to lie between −1.16 W m−2 and −0.86 W m−2. Therefore, the volcanically induced uncertainty in the PI baseline cloud radiative state substantially adds to the already large uncertainty in the magnitude of the indirect radiative forcing of climate.
Comparing different meteorological ensemble approaches: hydrological predictions for a flood episode in Northern Italy
Authors: Davolio S. , Diomede T. , Marsigli C. , Miglietta M. M. , Montani A. , Morgillo A.
Published: March 2012

Abstract. Within the framework of coupled meteorological-hydrological predictions, this study aims at comparing two high-resolution meteorological ensembles, covering short and medium range. The two modelling systems have similar characteristics, as almost the same number of members, the model resolution (about 7 km), the driving ECMWF global ensemble prediction system, but are obtained through different methodologies: the former is a multi-model ensemble, based on three mesoscale models (BOLAM, COSMO, and WRF), while the latter follows a single-model approach, based on COSMO-LEPS (Limited-area Ensemble Prediction System), the operational ensemble forecasting system developed within the COSMO consortium. Precipitation forecasts are evaluated in terms of hydrological response, after coupling the meteorological models with a distributed rainfall-runoff model (TOPKAPI) to simulate the discharge of the Reno river (Northern Italy), for a severe weather episode. Although a single case study does not allow for robust and definite conclusions, the comparison among different predictions points out a remarkably better performance of mesoscale model ensemble forecasts compared to global ones. Moreover, the multi-model ensemble outperforms the single model approach.
On the influence of wind and waves on the underwater light field
Authors: Hieronymi M. , Macke A.
Published: March 2012

Abstract. We present a detailed study of the influence of various wind and wave conditions on the distribution of downwelling irradiance within the upper ocean mixed layer down to 100 m water depth. The work is based on a two-dimensional Monte Carlo radiative transfer model with high spatial resolution. We treat conditions that are favorable for the development of extreme light fluctuations, e.g. light at 490 nm and very clear oceanic water. Local wind determines the steepness of capillary-gravity waves which in turn dominate the irradiance variability near the surface. Maximum irradiance peaks that exceed the mean irradiance by a factor of more than 10 can be observed at low wind speeds up to 5 m s−1. Sea states influence the light field much deeper; gravity waves can cause considerable irradiance variability even at 100 m depth. The simulation results show that under realistic conditions 50 % radiative enhancements compared to the mean can still occur at 30 m depth.
In-Hospital Use of Long-Acting Injectable Antipsychotics and Readmission Risk in Patients With First-Admission Schizophrenia in Taiwan
Authors: Chen Wei , Wu Chi-Shin , Liu Chen-Chung , Kuo Po-Hsiu , Chan Hung-Yu , Lin Yi-Hsuan , Chung Yu-Chu Ella , Chen Wei J.
Published: June 2024

Importance

Long-acting injectable antipsychotics (LAIs) can help decrease the rate of nonadherence to medications in patients with schizophrenia, but these drugs are underutilized in clinical practice, especially in Asian countries. One strategy for the early prescription of LAIs is to administer the drugs during patients’ first admission, when they have more time to absorb medication-related knowledge.

Objective

To estimate the prevalence of and risk factors for in-hospital use of LAIs among first-admission patients with schizophrenia in Taiwan and to examine the association of early discontinuation with readmission risk among patients receiving LAIs.

Design, Setting, and Participants

This cohort study included data from a claims database for patients with a first admission for schizophrenia at psychiatric wards in Taiwan from 2004 to 2017. Eligible patients were diagnosed with schizophrenia or schizoaffective disorder at discharge and aged between 15 and 64 years. Data analysis was performed from April to September 2022.

Exposure

In-hospital use of LAIs with or without early discontinuation.

Main Outcome and Measures

Readmission for any psychotic disorder following discharge from first admission, with risk estimated via multivariable survival regression analysis, including the Cox proportional hazards (CPH) model and accelerated failure time (AFT) model.

Results

Of the 56 211 patients with a first admission for schizophrenia (mean [SD] age, 38.1 [12.1] years; 29 387 men [52.3%]), 46 875 (83.4%) did not receive any LAIs during admission, 5665 (10.1%) received LAIs with early discontinuation, and 3671 (6.5%) received LAIs without early discontinuation. The prevalence of receiving LAIs increased by 4%, from 15.3% (3863 of 25 251 patients) to 19.3% (3013 of 15 608 patients) between 2004-2008 and 2013-2017. After controlling for sex, year, prior antipsychotic use, age at first admission, and length of stay, the CPH regression analysis revealed that the readmission risk increased among patients receiving LAIs with early discontinuation (adjusted hazard ratio [aHR], 1.25; 95% CI, 1.21-1.30) but decreased among patients receiving LAIs without early discontinuation (aHR, 0.88; 95% CI, 0.84-0.92) compared with patients not receiving LAIs. Results remained similar for the AFT model.

Conclusions and Relevance

The incidence of in-hospital use of LAIs among patients with a first admission for schizophrenia has remained low. In this study, early discontinuation of LAIs was associated with readmission risk—specifically, early discontinuation with a higher risk while the lack of early discontinuation with a lower risk compared with treatment with oral antipsychotics alone—which suggests our results have implications for improving the efficacy of LAI administration among patients with a first admission for schizophrenia.
Liver gene transfer for metabolite detoxification in inherited metabolic diseases
Authors: D'Alessio Alfonso M. , Boffa Iolanda , De Stefano Lucia , Soria Leandro R. , Brunetti‐Pierri Nicola
Published: June 2024

Inherited metabolic disorders (IMDs) are a growing group of genetic diseases caused by defects in enzymes that mediate cellular metabolism, often resulting in the accumulation of toxic substrates. The liver is a highly metabolically active organ that hosts several thousands of chemical reactions. As such, it is an organ frequently affected in IMDs. In this article, we review current approaches for liver‐directed gene‐based therapy aimed at metabolite detoxification in a variety of IMDs. Moreover, we discuss current unresolved challenges in gene‐based therapies for IMDs.
Being confident in confidence scores: calibration in deep learning models for camera trap image sequences
Authors: Dussert Gaspard , Chamaillé‐Jammes Simon , Dray Stéphane , Miele Vincent
Published: June 2024

In ecological studies, machine learning models are increasingly being used for the automatic processing of camera trap images. Although this automation facilitates and accelerates the identification step, the results of these models may lack interpretability and their immediate applicability to ecological downstream tasks (e.g. occupancy estimation) remains questionable. In particular, little is known about their calibration, a property that allows confidence scores to be interpreted as probabilities that model's predictions are true. Using a large and diverse European camera trap dataset, we investigate whether deep learning models for species classification in camera trap images are well calibrated. Additionally, as camera traps are often configured to take multiple photos of the same event, we also explore the calibration of predictions aggregated across sequences of images. Finally, we study the effect and the practicality of a post‐hoc calibration method, i.e. temperature scaling, for predictions made at image and sequence levels. Based on five established models and three independent test sets, we show that averaging the logits over the sequence, selecting an appropriate architecture, and optionally using temperature scaling can produce well‐calibrated models. Our findings have clear implication for, for instance, the calculation of error rates or the selection of confidence score thresholds in ecological studies making use of artificial intelligence models.
Deep learning and satellite remote sensing for biodiversity monitoring and conservation
Authors: Pettorelli Nathalie , Williams Jake , Schulte to Bühne Henrike , Crowson Merry
Published: June 2024

In the context of the current nature crisis, being able to reliably and cost‐effectively track subtle changes in the biosphere across adequate spatial and temporal extents and resolutions is crucial. Deep learning represents a group of versatile approaches to image processing tasks that are increasingly combined with satellite remote sensing imagery to monitor biodiversity and inform ecology and conservation, yet an overview of the opportunities and challenges associated with this development has so far been lacking. Here, we provide an interdisciplinary perspective on current research and technological developments associated with satellite remote sensing and deep learning that have the potential to make a difference in biodiversity monitoring and wildlife conservation; highlight challenges to the broader adoption of these approaches by experts operating at the interface between satellite remote sensing and ecology and conservation; and discuss how these can be overcome. By enabling the leveraging of big data and by providing new ways to learn about biodiversity and its dynamics, deep learning approaches promise to become a powerful tool to help address current monitoring needs and knowledge gaps. In certain situations, deep learning approaches may moreover substantially reduce the time and resources required to analyse satellite imagery. However, issues relating to capacity building, reference data access, environmental costs as well as model interpretability, robustness and alignment need to be addressed to successfully capitalize on these opportunities.
Characterization of Porosity Changes during Reaction of Coke and Coke Analogues with CO2 Using Micro‐Computer Tomography
Authors: Longbottom Raymond J. , Jenkins David R. , Dong Xuefeng , Monaghan Brian J.
Published: June 2024

Understanding the porosity of coke and how it changes during reaction is key for understanding coke reactivity and minimizing coke consumption in the blast furnace. The change in porosity of coke and coke analogue samples after reaction with CO2 is assessed using high‐resolution micro‐computer tomography (micro‐CT) scans. High‐resolution micro‐CT scans (2.35 μm voxel−1) are carried out before and after reaction with CO2 at 1100 °C. 3D micro‐CT measurements are validated against standard 2D measurements, and used to quantitatively assess the porosity evolution in the samples. The porosity and pore connectivity of the coke and analogue samples increase in reaction with CO2. Most of the increase in porosity occurs in the pores <60 μm. Inert maceral‐derived component (IMDC) regions in coke A are more reactive than reactive maceral‐derived component (RMDC) regions. This is possibly related to the higher proportion of fine pores in unreacted IMDC compared to RMDC. Characterization of larger coke and coke analogue samples using micro‐CT at lower resolution (9.65–16.72 μm voxel−1) allows the rate‐controlling mechanism to be determined as likely to be mixed control, with both chemical reaction and pore diffusion‐controlling reaction rate. This finding demonstrates that high‐ and lower‐resolution micro‐CT datasets should be considered complementary.
Disclosures 15: Can you send information to a potential employer?
Authors: Rainsberger Richard
Published: June 2024

FERPA regulations require you to keep a record of a disclosure of education records if that disclosure is for nondirectory information released to a third party. The record of the disclosure must include (1) the record(s) disclosed, (2) the party receiving the record(s), and (3) the legitimate interest that the party had in requesting the information. “Legitimate interest” is not defined in the regulations. It is different than, but similar to, our frequently mentioned “legitimate educational interest.” The term suggests a much broader meaning. To demonstrate a “legitimate interest,” the requesting party must show that the requested information is necessary to fulfill a recognized function or responsibility of the requesting party.
Game changers in international higher education
Authors: Dennis Marguerite J.
Published: June 2024

In an earlier column this year, I shared some of the game changers in U.S. higher education. This month's article will feature some of the game changers taking place worldwide. The purpose of both articles is to bring awareness to policies and initiatives that may impact your administrative work now and, potentially, in the future.
GABA-fortified synbiotic guava beverage: formulation and evaluation of neuroprotective properties using cell-based assays
Authors: Divyashri G. , Suprajaa V. , Nairy Chirag Umesh , Sastry Aditi , Sanjana R. M. , Sharada B. , Murthy T. P. Krishna
Published: June 2024

In recent years, the use of fermented fruit juices to offer protection against mental illness has been increasing enormously. The present study, aimed at formulating a synbiotic fruit beverage for mental well-being using fructo-oligosaccharide (FOS), Gamma-aminobutyric acid (GABA) and Lactobacillus rhamnosus. Guava extract (abbreviated as fruit extract, FE; 10%) supplemented with FOS (1%) fermented for 48 h using L. rhamnosus, was then fortified with 0.05% GABA (FE + FOS + GABA). This GABA-fortified fermented guava beverage exhibited significant in-vitro antioxidant activity as measured by using 2,2-diphenyl-1-picrylhydrazyl (IC50 value of 0.451 ± 0.05 mg/ml) and ferrous reducing antioxidant capacity (A700 nm value of 0.68 ± 0.06) assays. Fermentation also enhanced total phenolics and flavonoids by 27.63% and 27.41%, respectively. Furthermore, GABA-fortified fermented guava beverage showed a significant neuroprotective effect by negatively modulating oxidative stress and upregulating activity of antioxidant enzymes (superoxide dismutase and catalase) in rotenone treated neuronal cell lines. Taken together, our research findings clearly indicate the propensity of GABA-fortified fermented guava beverage to protect against rotenone mediated neuronal cell damage. Even though the underlying molecular mechanisms need further research, in conclusion, our study demonstrates that the GABA-fortified fermented guava beverage effectively confers neuroprotective effects in vitro, suggesting its potential as a functional beverage for promoting brain health.

Graphical Abstract
VR Scene Detail Enhancement Method Based on Depth Reinforcement Learning Algorithm
Authors: Feng Changbao , Tong Xin , Zhu Meili , Qu Feng
Published: June 2024

In virtual reality, due to factors such as light sources and surface materials of objects, the details of the scene exhibit extremely complex changes, making it difficult to capture environmental modeling relationships and reducing the quality of scene details. Therefore, a VR scene detail enhancement method based on deep reinforcement learning algorithm is proposed. Using the Total Variation (TV) denoising algorithm to decompose the VR scene, the VR scene is divided into two parts: noisy and non-noisy, to complete the noise removal. Based on the denoised VR scene, a Hessian matrix is constructed to extract VR scene features using the SURF algorithm. Using deep reinforcement learning algorithms to train and process the extracted VR visual features, introducing meta-learning within the gradient descent method, updating the parameters of the deep reinforcement learning Expose framework, and accelerating the training speed of the deep reinforcement learning Expose framework. By designing L1 loss, structural similarity loss, content perception loss, and sharpness loss functions, the enhancement effect of VR visual details can be improved. The experimental results show that the proposed method enhances the gray-scale values and distribution of VR scene detail images to be higher and more uniform. When the magnification is different, the studied method can effectively enhance the signal-to-noise ratio of VR scenes. Therefore, it indicates that the VR scene detail enhancement effect of the method proposed in this article is good.
Analysis of the ion collection model in the ExB probe
Authors: Yamauchi Toyofumi , Rovey Joshua
Published: June 2024

An ExB probe is a pass-band velocity filter for an ion beam. The ExB probe measurement is related to the ion velocity distribution function (IVDF); however, the finite pass-band filter window size leads to differences in the true IVDF and measured ExB probe spectrum. We derive for the first time an analytical ExB probe transmittancy matrix and use it to examine differences in the IVDF and the probe spectrum. The probe spectra are compared to a synthetically defined test IVDF to study how probe geometry and ion species affect the differences. It is found that the difference in the probe spectrum and the true IVDF is dependent on the ion species, and the deviation is larger for heavier ions. The peak velocity of the spectrum was shifted by up to 13%, and the velocity spread was broadened by up to 276%. The relative ion species fraction is calculated from the probe spectra by two different methods and compared to the true fraction. Using the approach of this work, direct integration of the spectrum resulted in a 2% difference, while a more common approach from literature overestimated one ion species by 184%.
Analyzing the urban–rural divide: the role of location, time, and breach characteristics in U.S. hospital security incidents, 2012–2021
Authors: Munoz-Cornejo Gilbert , Sakowski Julie , Lee Joonghee , Parks Ashley
Published: June 2024

This analysis describes how cybersecurity breaches vary between urban and rural hospitals, how they differ over time, and how they differ across different types and locations of breaches within hospitals. Utilizing data from the U.S. Department of Health and Human Services Office for Civil Rights on incidents from 2012 to 2021 that affected 500 or more individuals, we studied breaches in 237 community hospitals, distinguishing between 185 urban and 52 rural facilities. Using Poisson and Quasi-Poisson regression models, we found a significant yearly increase in data breaches, especially in urban hospitals. Hacking/IT incidents were the most common breaches, particularly prevalent in urban settings, while unauthorized access/disclosure occurred frequently. Email and network servers were the primary locations of breaches in urban and rural hospitals. These findings indicate differences between urban and rural hospitals in data security incidents, suggesting areas for further research.
Machine learning optimization for hybrid electric vehicle charging in renewable microgrids
Authors: Hassan Marwa
Published: June 2024

Renewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources, reducing greenhouse gas emissions. This paper proposes a machine learning approach, leveraging Gaussian Process (GP) and Krill Herd Algorithm (KHA), for energy management in renewable microgrids with a reconfigurable structure based on remote switching of tie and sectionalizing. The method utilizes Gaussian Process (GP) for modeling hybrid electric vehicle (HEV) charging demand. To counteract HEV charging effects, two scenarios are explored: coordinated and intelligent charging. A novel optimization method inspired by the Krill Herd Algorithm (KHA) is introduced for the complex problem, along with a self-adaptive modification to tailor solutions to specific situations. Simulation on an IEEE microgrid demonstrates efficiency in both scenarios. The predictive model yields a remarkably low Mean Absolute Percentage Error (MAPE) of 1.02381 for total HEV charging demand. Results also reveal a reduction in microgrid operation cost in the intelligent charging scenario compared to coordinated charging.
Immunohistochemical-properties of the dermal embryonic telocytes
Authors: Soliman Soha A.
Published: June 2024

The current investigation aims to study the embryonic dermis formed in the early stages of development and identify the initial interstitial components of the dermis that serve as biological and structural scaffolds for the development of the dermal tissue. To investigate the dermal structure, the current study used morphological and immunological techniques. TCs identified by TEM. They had a cell body and unique podomeres and podoms. They formed a 3D network spread throughout the dermis. Homocellular contact established between them, as well as heterocellular contacts with other cells. Immunohistochemical techniques using specific markers for TCss CD34, CD117, and VEGF confirmed TC identification. TCs represent the major interstitial component in the dermal tissue. They established a 3D network, enclosing other cells and structures. Expression of VEGF by TC promotes angiogenesis. TCs establish cellular contact with sprouting endothelial cells. At the site of cell junction with TCs, cytoskeletal filaments identified and observed to form the pseudopodium core that projects from endothelial cells. TCs had proteolytic properties that expressed MMP-9, CD68, and CD21. Proteolytic activity aids in the removal of components of the extracellular matrix and the phagocytosis of degraded remnants to create spaces to facilitate the development of new dermal structures. In conclusion, TCs organized the scaffold for the development of future dermal structures, including fibrous components and skin appendages. Studying dermal TCs would be interested in the possibility of developing therapeutic strategies for treating different skin disorders and diseases.
Effective recognition design in 8-ball billiards vision systems for training purposes based on Xception network modified by improved Chaos African Vulture Optimizer
Authors: Pan WenKai , Zhu Dong , Wang Jutao , Zhu Haiyan
Published: June 2024

This research paper presents a comprehensive investigation into the utilization of color image processing technologies and deep learning algorithms in the development of a robot vision system specifically designed for 8-ball billiards. The sport of billiards, with its various games and ball arrangements, presents unique challenges for robotic vision systems. The proposed methodology addresses these challenges through two main components: object detection and ball pattern recognition. Initially, a robust algorithm is employed to detect the billiard balls using color space transformation and thresholding techniques. This is followed by determining the position of the billiard table through strategic cropping and isolation of the primary table area. The crucial phase involves the intricate task of recognizing ball patterns to differentiate between solid and striped balls. To achieve this, a modified convolutional neural network is utilized, leveraging the Xception network optimized by an innovative algorithm known as the Improved Chaos African Vulture Optimization (ICAVO) algorithm. The ICAVO algorithm enhances the Xception network's performance by efficiently exploring the solution space and avoiding local optima. The results of this study demonstrate a significant enhancement in recognition accuracy, with the Xception/ICAVO model achieving remarkable recognition rates for both solid and striped balls. This paves the way for the development of more sophisticated and efficient billiards robots. The implications of this research extend beyond 8-ball billiards, highlighting the potential for advanced robotic vision systems in various applications. The successful integration of color image processing, deep learning, and optimization algorithms shows the effectiveness of the proposed methodology. This research has far-reaching implications that go beyond just billiards. The cutting-edge robotic vision technology can be utilized for detecting and tracking objects in different sectors, transforming industrial automation and surveillance setups. By combining color image processing, deep learning, and optimization algorithms, the system proves its effectiveness and flexibility. The innovative approach sets the stage for creating advanced and productive robotic vision systems in various industries.
The influence of intraoral cryotherapy on postoperative pain and substance P in symptomatic apical periodontitis: randomized clinical study
Authors: Hamza Esraa Mohammed , Abd El Aziz Tarek Mustafa , Obeid Maram Farouk
Published: June 2024

Cryotherapy is widely utilized in medicine, particularly for pain management. This randomized clinical trial aimed to assess the effect of intraoral cold pack application (cryotherapy) on postoperative pain (POP) and the level of Substance P (SP) in patients with symptomatic apical periodontitis (SAP). Enrolled patients were randomly assigned to either cryotherapy or control group. After adequate anesthesia, access cavity, and biomechanical preparation of the root canal system were completed, the first apical fluid (AF) sample (S1) was obtained. A custom-made intraoral ice-gel pack was applied for 30 min in the cryotherapy group, while no intervention was performed in the control group. The second AF sample (S2) was collected 30 min later in both groups. Patients were asked to complete the Visual Analogue Scale (VAS) questionnaire to assess their POP. Quantification of SP in AF samples was performed using the enzyme-linked immunosorbent assay (ELISA) test. Data were analyzed statistically, revealing a significant reduction in POP and SP levels in the cryotherapy group compared to the control group (P ≤ 0.05). Furthermore, a moderate positive correlation was observed between SP levels and POP (P ≤ 0.05). In conclusion, intraoral cryotherapy represents a simple and cost-effective option for controlling POP and reducing inflammation levels in patients with SAP.
Prediction of post-delivery hemoglobin levels with machine learning algorithms
Authors: Aghajanian Sepehr , Jafarabady Kyana , Abbasi Mohammad , Mohammadifard Fateme , Bakhshali Bakhtiari Mina , Shokouhi Nasim , Saleh Gargari Soraya , Bakhtiyari Mahmood
Published: June 2024

Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, enabling timely transfer and implementation of prophylactic therapies. We attempted to utilize machine learning (ML) using basic pre-labor clinical data and laboratory measurements to predict postpartum Hemoglobin (Hb) in non-complicated singleton pregnancies. The local databases of two academic care centers on patient delivery were incorporated into the current study. Patients with preexisting coagulopathy, traumatic cases, and allogenic blood transfusion were excluded from all analyses. The association of pre-delivery variables with 24-h post-delivery hemoglobin level was evaluated using feature selection with Elastic Net regression and Random Forest algorithms. A suite of ML algorithms was employed to predict post-delivery Hb levels. Out of 2051 pregnant women, 1974 were included in the final analysis. After data pre-processing and redundant variable removal, the top predictors selected via feature selection for predicting post-delivery Hb were parity (B: 0.09 [0.05–0.12]), gestational age, pre-delivery hemoglobin (B:0.83 [0.80–0.85]) and fibrinogen levels (B:0.01 [0.01–0.01]), and pre-labor platelet count (B*1000: 0.77 [0.30–1.23]). Among the trained algorithms, artificial neural network provided the most accurate model (Root mean squared error: 0.62), which was subsequently deployed as a web-based calculator: https://predictivecalculators.shinyapps.io/ANN-HB. The current study shows that ML models could be utilized as accurate predictors of indirect measures of PPH and can be readily incorporated into healthcare systems. Further studies with heterogenous population-based samples may further improve the generalizability of these models.
Comparison of the diagnostic accuracy of the Pluslife Mini Dock RHAM technology with Abbott ID Now and Cepheid GenXpert: A retrospective evaluation study
Authors: Herrmann Laura , Breuer Juliana , Duc Tuan Ngo , Thomé Nicole , Ghazaani Fatemeh , Kamhieh-Milz Sundrela , Kamhieh-Milz Julian , Pfützner Andreas
Published: June 2024

Rapid and sensitive detection of pathogens is critical in interrupting the transmission chain of infectious diseases. Currently, real-time (RT-)PCR represents the gold standard for the detection of SARS-CoV-2. RNase HII-assisted amplification (RHAM) is a promising technology, enabling reliable point-of-care (PoC) testing; however, its diagnostic accuracy has not yet been investigated. The present study compared the Pluslife Mini Dock (RHAM technology), with Abbott ID Now and Cepheid GeneXpert IV. The positive percent agreement (PPA) and negative percent agreement (NPA) were determined in 100 SARS-CoV-2 positive and 210 SARS-CoV-2 negative samples. Further, the reliability of the Pluslife Mini Dock was investigated in different SARS-CoV-2 variants (Delta and Omicron subvariants). The PPA was 99.00% for Pluslife, 100.00% for Abbott ID Now, and 99.00% for Cepheid GeneXpert, with an NPA of 100.00%, 98.90%, and 93.72%, respectively. Abbott ID Now demonstrated the highest rate of invalid results. All SARS-CoV-2 analysed variants were detected by the Pluslife device. Altogether, the Pluslife Mini Dock demonstrated a PPA of 99.16% (235/237) for CT < 36 and an NPA of 100.00% (313/313), respectively. In conclusion, the Pluslife Mini Dock demonstrated better analytical performance than Abbott ID Now and Cepheid GeneXpert IV, representing a highly accurate and rapid PoC alternative to RT-PCR.
Development of a predictive nomogram for in-hospital death risk in multimorbid patients with hepatocellular carcinoma undergoing Palliative Locoregional Therapy
Authors: Yao Rucheng , Zheng Bowen , Hu Xueying , Ma Baohua , Zheng Jun , Yao Kecheng
Published: June 2024

Patients diagnosed with hepatocellular carcinoma (HCC) often present with multimorbidity, significantly contributing to adverse outcomes, particularly in-hospital mortality. This study aimed to develop a predictive nomogram to assess the impact of comorbidities on in-hospital mortality risk in HCC patients undergoing palliative locoregional therapy. We retrospectively analyzed data from 345 hospitalized HCC patients who underwent palliative locoregional therapy between January 2015 and December 2022. The nomogram was constructed using independent risk factors such as length of stay (LOS), hepatitis B virus (HBV) infection, hypertension, chronic obstructive pulmonary disease (COPD), anemia, thrombocytopenia, liver cirrhosis, hepatic encephalopathy (HE), N stage, and microvascular invasion. The model demonstrated high predictive accuracy with an AUC of 0.908 (95% CI: 0.859–0.956) for the overall dataset, 0.926 (95% CI: 0.883–0.968) for the training set, and 0.862 (95% CI: 0.728–0.994) for the validation set. Calibration curves indicated a strong correlation between predicted and observed outcomes, validated by statistical tests. Decision curve analysis (DCA) and clinical impact curves (CIC) confirmed the model's clinical utility in predicting in-hospital mortality. This nomogram offers a practical tool for personalized risk assessment in HCC patients undergoing palliative locoregional therapy, facilitating informed clinical decision-making and improving patient management.
Endothelial dysfunction in retinal vessels of hemodialysis patients compared to healthy controls
Authors: Günthner Roman , Lorenz Georg , Braunisch Matthias Christoph , Angermann Susanne , Matschkal Julia , Hausinger Renate , Kuchler Timon , Glaser Patrizia , Schicktanz Felix , Haller Bernhard , Heemann Uwe , Streese Lukas , Hanssen Henner , Kotliar Konstantin , Schmaderer Christoph
Published: June 2024

Endothelial dysfunction is a key factor promoting atherosclerosis and cardiovascular complications. Hemodialysis patients typically show various cardiovascular complications and impaired retinal venular dilation has been described as a risk factor for mortality. Non-invasive retinal vessel analysis provides insight into the microvasculature and endothelial function. Static retinal vessel analysis determines arteriolar and venular vessel diameters and dynamic retinal vessel analysis measures microvascular function by flicker-light induced stimulation, which results in physiological dilation of retinal vessels. We measured 220 healthy individuals and compared them to our preexisting cohort of hemodialysis patients (275 for static and 214 for dynamic analysis). Regarding static vessel diameters, hemodialysis patients and healthy individuals did not significantly differ between vessel diameters. Dynamic retinal vessel analysis showed attenuated dilation of the arteriole of hemodialysis patients with 1.6% vs 2.3% in healthy individuals (p = 0.009). Case–control matching for age (mean 65.4 years) did not relevantly diminish the difference. Hemodialysis patients also exhibited reduced venular dilation after matching for age (3.2% vs 3.8%, p = 0.019). Hemodialysis patients showed microvascular dysfunction compared to healthy individuals when using dynamic retinal vessel analysis. Further studies should focus on dynamic retinal vessel analysis which can add insights into the microvascular function and risk factors in multimorbid patients.
Europe as a secondary distribution hub in the worldwide invasion of the potato cyst nematode Globodera rostochiensis
Authors: Esquibet Magali , Mwangi James M. , Kiewnick Sebastian , Wang Xiaohong , Mimee Benjamin , Handayani Nurul Dwi , Bert Wim , Helder Johannes , Wainer John , Sakata Itaru , Garcia Nathan , Grenier Eric , Montarry Josselin
Published: June 2024

The potato cyst nematode Globodera rostochiensis originates from the Andean Mountain region in South America and has unintentionally been introduced to all inhabited continents. Several studies have examined the population genetic structure of this pest in various countries by using microsatellite markers. However, merging microsatellite data produced from different laboratories is challenging and can introduce uncertainty when interpreting the results. To overcome this challenge and to explore invasion routes of this pest, we have genotyped 22 G. rostochiensis populations from all continents. Within populations, the highest genetic diversity was observed in the South American populations, the European populations showed an intermediate level of genetic diversity and the remaining populations were the less diverse. This confirmed pre-existing knowledge such as a first introduction event from South America to Europe, but the less diverse populations could originate either from South America or from Europe. At the continental scale, STRUCTURE genetic clustering output indicated that North America and Asia have experienced at least two introduction events. Comparing different evolutionary scenarios, the Approximate Bayesian Computation analysis showed that Europe served as a secondary distribution centre for the invasion of G. rostochiensis into all other continents (North America, Africa, Asia and Oceania).
Study of the impact of structural factors and cleaning efficiency in reducing hazardous litter density and its related pollution in urban environment
Authors: Morovati Maryam , Parsa Sheida , Panahande Maryam , Hossaini Motlagh Amin , Parseh Iman
Published: June 2024

Cigarette filter is the most common hazardous litter that contains many pollutants including PAHs. The durability of this litter in the urban environment has an important effect on the rate of pollutant leakage. In this study, the leakage rate of PAHs from the littered cigarette filters was estimated by considering the affecting parameters on their durability in the urban environment. The results showed that the density of littered cigarette filters in the studied locations was 0.00048–0.13563 g/m2. The maximum spatial variation of the littered cigarette filter was 225 times. The average leakage of the total studied PAHs was estimated to be 2.048 µg/10 m2. The impact of structural factors and efficiency of urban cleaning in the estimated leakage was at most 2.4 times. It is necessary to change the behavior of citizens in littering the cigarette filter, considering its durability in the urban environment, to reduce the environmental and health consequences caused by the leakage of PAHs.
Integrated analysis of single-cell RNA sequencing and bulk RNA data reveals gene regulatory networks and targets in dilated cardiomyopathy
Authors: Zhang Min , Zhang Xin , Niu Jiayin , Hua Cuncun , Liu Pengfei , Zhong Guangzhen
Published: June 2024

Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients.
Serum protein profiling reveals mechanism of activated thrombus formation in patients with stroke and atrial fibrillation
Authors: Mun Sora , Kim Jae Guk , Lee Soo Joo , Kim Doojin , Lee Jiyeong , Kang Hee-Gyoo
Published: June 2024

Stroke is an acute cerebrovascular disease in which blood flow to the brain is suddenly disrupted, causing damage to nerve cells. It involves complex and diverse pathophysiological processes and the treatment strategies are also diverse. The treatment for patients with stroke and atrial fibrillation (AF) is aimed at suppressing thrombus formation and migration. However, information regarding the protein networking involved in different thrombus formation pathways in patients with AF and stroke is insufficient. We performed protein profiling of patients with ischemic stroke with and without AF to investigate the mechanisms of thrombus formation and its pathophysiological association while providing helpful information for treating and managing patients with AF. These two groups were compared to identify the protein networks related to thrombus formation in AF. We observed that patients with ischemic stroke and AF had activated inflammatory responses induced by C-reactive protein, lipopolysaccharide-binding protein, and alpha-1-acid glycoprotein 1. In contrast, thyroid hormones were increased due to a decrease in transthyretin and retinol-binding protein 4 levels. The mechanism underlying enhanced cardiac activity, vasodilation, and the resulting thrombosis pathway were confirmed in AF. These findings will play an essential role in improving the prevention and treatment of AF-related stroke.
Folic acid-modified nanocrystalline cellulose for enhanced delivery and anti-cancer effects of crocin
Authors: Soltani Mozhgan , Farhadi Amin , Rajabi Sarah , Homayouni‐Tabrizi Masoud , Hussein Fatimah Sameer , Mohammadian Navid
Published: June 2024

Crocin is a carotenoid compound in saffron with anti-cancer properties. However, its therapeutic application is limited by its low absorption, bioavailability, and stability, which can be overcome through nanocarrier delivery systems. This study used surface-modified Nano-crystalline cellulose (NCC) to deliver crocin to cancer cells. NCC modified with CTAB were loaded with crocin and then conjugated with folic acid (NCF-CR-NPs). The synthesized nanoparticles (NPs) were characterized using FTIR, XRD, DLS, and FESEM. The crystallinity index of NCC was 66.64%, higher than microcrystalline cellulose (61.4%). The crocin loading and encapsulation efficiency in NCF-CR-NPs were evaluated. Toxicity testing by MTT assay showed that NCF-CR-NPs had higher toxicity against various cancer cell lines, including colon cancer HT-29 cells (IC50 ~ 11.6 μg/ml), compared to free crocin. Fluorescent staining, flow cytometry, and molecular analysis confirmed that NCF-CR-NPs induced apoptosis in HT-29 cells by increasing p53 and caspase 8 expression. The antioxidant capacity of NCF-CR-NPs was also evaluated using ABTS and DPPH radical scavenging assays. NCF-CR-NPs exhibited high free radical scavenging ability, with an IC50 of ~ 46.5 μg/ml for ABTS. In conclusion, this study demonstrates the potential of NCF-CR-NPs to deliver crocin to cancer cells effectively. The NPs exhibited enhanced anti-cancer and antioxidant activities compared to free crocin, making them a promising nanocarrier system for crocin-based cancer therapy.
Albiflorenes A–L, polyoxygenated cyclohex(a/e)ne diterpene esters from Kaempferia albiflora
Authors: Booranaseensuntorn Pornpuk , Boonsombat Jutatip , Thongnest Sanit , Batsomboon Paratchata , Reuk-Ngam Nanthawan , Khlaychan Panita , Ruchisansakun Saroj , Kittakoop Prasat , Techasakul Supanna , Mahidol Chulabhorn , Ruchirawat Somsak
Published: June 2024

Twelve polyoxygenated cyclohex(a/e)ne diterpene esters, named albiflorenes A–L (1–12), were isolated from the whole plants of Kaempferia albiflora, known as “Prao Mang Mum.” Their structures and relative stereochemistry were determined by extensive spectroscopic analysis. Furthermore, the comparison of experimental electronic circular dichroism (ECD) curves with the curves predicted by TDDFT was used to determine the absolute configurations. Albiflorenes contain polyoxygenated cyclohexane (or cyclohexene) derivatives, which are linked to either isopimarane or abietane diterpene acid units. The discovery marks the first occurrence of a conjugate between polyoxygenated cyclohexane (or cyclohexene) rings and diterpenoids. Among the isolates, albiflorene C specifically exhibited antibacterial activity against Bacillus cereus with MIC and MBC values of 3.13 and 6.25 μg/mL, respectively.
Pioneering advanced security solutions for reinforcement learning-based adaptive key rotation in Zigbee networks
Authors: Fang Xiaofen , Zheng Lihui , Fang Xiaohua , Chen Weidong , Fang Kunli , Yin Lingpeng , Zhu Han
Published: June 2024

In the rapidly evolving landscape of Internet of Things (IoT), Zigbee networks have emerged as a critical component for enabling wireless communication in a variety of applications. Despite their widespread adoption, Zigbee networks face significant security challenges, particularly in key management and network resilience against cyber attacks like distributed denial of service (DDoS). Traditional key rotation strategies often fall short in dynamically adapting to the ever-changing network conditions, leading to vulnerabilities in network security and efficiency. To address these challenges, this paper proposes a novel approach by implementing a reinforcement learning (RL) model for adaptive key rotation in Zigbee networks. We developed and tested this model against traditional periodic, anomaly detection-based, heuristic-based, and static key rotation methods in a simulated Zigbee network environment. Our comprehensive evaluation over a 30-day period focused on key performance metrics such as network efficiency, response to DDoS attacks, network resilience under various simulated attacks, latency, and packet loss in fluctuating traffic conditions. The results indicate that the RL model significantly outperforms traditional methods, demonstrating improved network efficiency, higher intrusion detection rates, faster response times, and superior resource management. The study underscores the potential of using artificial intelligence (AI)-driven, adaptive strategies for enhancing network security in IoT environments, paving the way for more robust and intelligent Zigbee network security solutions.