bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atrophic Meibomian Gland Dysfunction Induced by Eyelid Margin Cryotherapy with Liquid Nitrogen
Authors: Wang Shu , Li Yulin , Gao Jingfan , Lin Jia , Jin Xin , Zhang Hong 
Published: September 2024

Abstract

Objective
To develop an atrophic Meibomian Gland Dysfunction (MGD) animal model via liquid nitrogen cryotherapy.
Methods
C57 mice underwent eyelid margin exposure to liquid nitrogen for 30 seconds. MG morphology and ocular surface were assessed using stereomicroscopy and a slit lamp microscope at multiple time points post-injury.
Results
Acinar loss and atrophy were observed from day 7, with increased inflammation and apoptosis, and decreased proliferation in acinar cells. Corneal epithelial defects appeared after day 14.
Conclusion
Liquid nitrogen induced selective damage to meibomian acinar cells, simulating MGD pathology effectively, with peak effects at day 21, providing a relevant model for atrophic MGD research.
Vaping versus Smoking: A Quest for Long-term impact in a mouse model
Authors: Massara Layal , Ollivier Anaïs , Dussautoir Romain , Kervoaze Gwenola , Pichavant Muriel , Platel Anne , Kluza Jérôme , Lo-Guidice Jean-Marc , Anthérieu Sébastien , Gosset Philippe 
Published: September 2024

Abstract

Background
Most smokers consider that electronic cigarettes are safer than tobacco and are marketed as safe products. Nevertheless, recent reports show the exposure to high levels of electronic cigarette vapors (ECV) activates lung cells and triggers lung inflammation and structural alterations after chronic exposure. In order to assess the potential harmful effect of moderate exposure to ECV, we investigated in mice, its effect on lung and systemic inflammation and on lung structure and function.
Methods
To reproduce closely the situation frequently encountered in human, we exposed mice during 1h/day during 3 or 6 months with two levels of electronic cigarette power in comparison with mice exposed to cigarette smoke (CS). Lung and systemic inflammation was evaluated by measuring cell recruitment and activation as well as cytokine concentrations. Lung transcriptome, respiratory function and body weight were also measured.
Results
Our data revealed that chronic exposure to moderate levels of ECV increased specifically lung inflammation including NK cells and T lymphocyte recruitment and the production of CXCL1 and CXCL2 chemokines as well as IL-22 after 3 months, these effects being different from the profile induced by CS. Surprisingly, there is no strong overlap between the impact of the 3 types of emissions on lung transcriptome. Modulation of pro-inflammatory pathways are limited to mice exposed to e-cig set to low power. In contrast, alteration of respiratory function is observed in high-power ECV-exposed mice but not at low power, with a different profile than in CS-exposed mice.
Conclusion
Subchronic (or mid-term) exposure to ECV might alter the respiratory function independently of the inflammatory response and in a different manner than CS.
Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Domain Generalization
Authors: Rossi Andrea , Visentin Andrea , Carraro Diego , Prestwich Steven , Brown Kenneth N. 
Published: September 2024

Abstract

Predicting future resource demand in Cloud Computing is essential for optimizing the trade-off between serving customers' requests efficiently and minimizing the provisioning cost. Modelling prediction uncertainty is also desirable to better inform the resource decision-making process, but research in this field is under-investigated. In this paper, we propose univariate and bivariate Bayesian deep learning models that provide predictions of future workload demand and its uncertainty. We run extensive experiments on Google and Alibaba clusters, where we first train our models with datasets from different cloud providers and compare them with LSTM-based baselines. Results show that modelling the uncertainty of predictions has a positive impact on performance, especially on service level metrics, because uncertainty quantification can be tailored to desired target service levels that are critical in cloud applications. Moreover, we investigate whether our models benefit transfer learning capabilities across different domains, i.e.\dataset distributions. Experiments on the same workload datasets reveal that acceptable transfer learning performance can be achieved within the same provider (because distributions are more similar). Also, domain knowledge does not transfer when the source and target domains are very different (e.g.\from different providers), but this performance degradation can be mitigated by increasing the training set size of the source domain.
Visibility Improvement of Hazy Images Using Manipulation of Convex Combination Coefficients of Equi-Hue Planes' Vertices in the RGB Color Space
Authors: Mukaida Mashiho , Koga Takanori , Suetake Noriaki 
Published: September 2024

Abstract

Images captured in foggy or hazy environments can exhibit whitening and reduced contrast. Various methods have been proposed to enhance the visibility of hazy images with degraded quality. However, these conventional methods may cause degradation, such as unnatural color changes and artifacts, in the resultant image. To address this problem, we propose a haze-removal method for image visibility improvement using manipulation of convex combination coefficients of equi-hue planes' vertices, which correspond to white, black, and pure colors in the RGB color space. The proposed method begins with a pre-processing step containing contrast enhancement of the lightness component using a multi-scale image enhancement method with S-shaped functions. Then, for saturation enhancement, the convex combination coefficients of white are reduced and those of pure colors are increased in the lightness-enhanced image to achieve haze removal. Experiments were conducted using real hazy images and artificially synthesized images, and the effectiveness of the proposed method was verified by comparison with conventional methods. From the experimental results, we confirmed that the proposed method sufficiently improves the visibility of hazy images while suppressing unnatural color changes and artifacts.
Switch-like Gene Expression Modulates Disease Susceptibility
Authors: Gokcumen Omer 
Published: September 2024

Abstract

A fundamental challenge in biomedicine is understanding the mechanisms predisposing individuals to disease. While previous research has suggested that switch-like gene expression is crucial in driving biological variation and disease susceptibility, a systematic analysis across multiple tissues is still lacking. By analyzing transcriptomes from 943 individuals across 27 tissues, we identified 1,013 switch-like genes. We found that only 31 (3.1%) of these genes exhibit switch-like behavior across all tissues. These universally switch-like genes appear to be genetically driven, with large exonic genomic structural variants explaining five (~ 18%) of them. The remaining switch-like genes exhibit tissue-specific expression patterns. Notably, tissue-specific switch-like genes tend to be switched on or off in unison within individuals, likely under the influence of tissue-specific master regulators, including hormonal signals. Among our most significant findings, we identified hundreds of concordantly switched-off genes in the stomach and vagina that are linked to gastric cancer (41-fold, p < 10− 4) and vaginal atrophy (44-fold, p < 10− 4), respectively. Experimental analysis of vaginal tissues revealed that low systemic levels of estrogen lead to a significant reduction in both the epithelial thickness and the expression of the switch-like gene ALOX12. We propose a model wherein the switching off of driver genes in basal and parabasal epithelium suppresses cell proliferation therein, leading to epithelial thinning and, therefore, vaginal atrophy. Our findings underscore the significant biomedical implications of switch-like gene expression and lay the groundwork for potential diagnostic and therapeutic applications.
Trehalose catalytic shift is an intrinsic factor in Mycobacterium tuberculosis that enhances phenotypic heterogeneity and multidrug resistance
Authors: Eoh Hyungjin , Lee Jae Jin , Swanson Daniel , Lee Sun-Kyung , Dihardjo Stephanie , Lee Gi Yong , S Gelle , Maskill Emily , Taylor Zachary , Nieuwenhze Michael Van , Singh Abhyudai , Lee Jong-Seok , Eum Seok-Yong , Cho Sang-Nae , Swarts Benjamin 
Published: September 2024

Abstract

Drug-resistance (DR) in many bacterial pathogens often arises from the repetitive formation of drug-tolerant bacilli, known as persisters. However, it is unclear whether Mycobacterium tuberculosis (Mtb), the bacterium that causes tuberculosis (TB), undergoes a similar phenotypic transition. Recent metabolomics studies have identified that a change in trehalose metabolism is necessary for Mtb to develop persisters and plays a crucial role in metabolic networks of DR-TB strains. The present study used Mtb mutants lacking the trehalose catalytic shift and showed that the mutants exhibited a significantly lower frequency of the emergence of DR mutants compared to wildtype, due to reduced persister formation. The trehalose catalytic shift enables Mtb persisters to survive under bactericidal antibiotics by increasing metabolic heterogeneity and drug tolerance, ultimately leading to development of DR. Intriguingly, rifampicin (RIF)-resistant bacilli exhibit cross-resistance to a second antibiotic, due to a high trehalose catalytic shift activity. This phenomenon explains how the development of multidrug resistance (MDR) is facilitated by the acquisition of RIF resistance. In this context, the heightened risk of MDR-TB in the lineage 4 HN878 W-Beijing strain can be attributed to its greater trehalose catalytic shift. Genetic and pharmacological inactivation of the trehalose catalytic shift significantly reduced persister formation, subsequently decreasing the incidence of MDR-TB in HN878 W-Beijing strain. Collectively, the trehalose catalytic shift serves as an intrinsic factor of Mtb responsible for persister formation, cross-resistance to multiple antibiotics, and the emergence of MDR-TB. This study aids in the discovery of new TB therapeutics by targeting the trehalose catalytic shift of Mtb.
131 genetic loci highlight immunological pathways and tissues in nasal polyposis and asthma
Authors: Saarentaus Elmo , Fischer-Rasmussen Kasper , Sliz Eeva , Bizaki-Vallaskangas Argyro , Laitinen Tarja , Toppila-salmi Sanna , Kankaanranta Hannu , Kettunen Johannes , Bønnelykke Klaus , Palotie Aarno , Mäkitie Antti 
Published: September 2024

Abstract

The coexistence of asthma and chronic rhinosinusitis with nasal polyposis (CRSwNP) is associated with allergic phenotypes, disease severity and failure of first-line treatment for both asthma and CRSwNP. Recent studies have highlighted shared genetic components for these diseases.
To better understand this shared component, we performed genome-wide meta-analyses of asthma (n = 71,481), CRSwNP (n = 9626) and chronic rhinosinusitis without nasal polyposis (CRSsNP, n = 15,448) in FinnGen and UKB (685,602 controls).
We detected 131 genomic associations, including 17 novel loci for asthma, 33 novel loci for CRSwNP, and one for CRSsNP. A shared impact on asthma and CRSwNP was observed at 71 loci. A cross-trait meta-analysis using all disorders further implicated 17 loci associated with asthma or asthma and CRSwNP. These loci largely cluster into three groups, with a shared risk being the most frequent. We also found 17 nonsynonymous associating variants, including a novel TP63 missense variant linked with CRSwNP (OR = 1.519 [1.331–1.734]). Gene set analyses confirmed enrichment of type 2 inflammation genes, and linked FOXP3 signaling to CRSwNP.
Our results highlight new shared and separate genetic pathways for CRSwNP and asthma. These provide several avenues of further investigation in functional and epidemiological follow-up, and evidence for immunological and non-immunological mechanisms behind both diseases.
Optimizing EDM for titanium alloys: an in-depth comparison of five MCDM techniques
Authors: Nguyen Van-Canh , Vu Dinh-Toan , Tran Quoc-Hung , Kieu Van Quang , Nguyen Trong Mai 
Published: September 2024

This experimental study investigates the effect of the cutting parameters of the Electrical Discharge Machining (EDM) process of Ti-6Al-4V alloy material on surface roughness (Ra), cutting time (t) and Material Removal Rate (MRR) then solve the Multiple Objective Optimization Problem using separate Multi-Criteria Decision-Making (MCDM) methods namely Entropy-Weighted TOPSIS (E-TOPSIS), MOORA, SAW, VIKOR, and WPM. Focusing on nine 3-levels variants including Operating Voltage (OV), Pulse-On Time (Ton), Pulse-Off Time (Toff), Short-Circuit Off Time (AFF), Secondary Voltage (SV), Feed Rate (WF), Tension (WT), Water Pressure (WL) and Material Cutting Speed (F). Due to the large number of variants studied, the Taguchi L27 experimental design was chosen to reduce the number of experiments while still ensuring reliability in assessing the impact of technological parameters on responses in the study. The optimization results from the different methods indicated two distinct optimal outcomes. According to the E-TOPSIS, MOORA, and SAW, the optimal result is a Ra of 3.27 µm, a t of 7.37 min, and an MRR of 7.45 mm3/min. This result suggests a balanced and harmonious optimization among all criteria. On the other hand, the figures VIKOR and WPM methods are 2.87 µm, 9.57 min, and 5.74 mm3/min, respectively. These results indicate a higher priority for certain criteria, reflected in the lower Ra, longer cutting time, and a smaller MRR in comparison to the figures for the remaining MCDM methods. The different optimal results achieved by various methods highlight that each method is suited to and excels with different sets of values. Therefore, in each specific research or production process, comparing and choosing results calculated by different methods provides a comprehensive view, aiding in making appropriate decisions
The Impact of Psychological Empowerment of Nurses on their Job Involvement: A Descriptive Correlational Study
Authors: Ghasemi Sina , Torabi Mohammad , Jamasbi Mehrdad Maleki 
Published: September 2024

Background
Psychological empowerment and job involvement of employees are critical indicators of healthcare organizational performance. These two factors are essential when managing workplace changes, enhancing individual and overall organizational performance, and increasing the job security of nurses.

Objective
This study explored how nurses perceive their psychological empowerment and job involvement and the relationship between these two factors.

Methods
This descriptive-correlational research was conducted on nurses working in 3 hospitals affiliated with Hamadan University of Medical Sciences in 2023. The sampling method used was quota-random sampling. The data related to the study were collected from valid questionnaires related to Spreitzer's developed Psychological Empowerment and Kanungo's Job Involvement. The data analysis was also conducted at the descriptive and inferential statistics level using SPSS version 16 software.

Results
In this study, 65.9% (N=128) of the participants were female and 34.1% (N=66) were male. The results showed that the level of nurses' perception of psychological empowerment and job involvement was at an average level. Also, the results showed a significant relationship between the total psychological empowerment score and nurses' job involvement (P-value<0.001, r=0.587).

Conclusions
Based on the results, increasing each dimension of PE among nurses can significantly enhance their job involvement, subsequently improving the quality of patient care and reducing additional costs. Job involvement has been tied to nurse health and quality of care. Given the significant positive relationship between job involvement and psychological empowerment, attention must be given to empowering nurses psychologically.
Investigating the State of Self-Expression and its Relationship with Adjustment and Self-Efficacy of Students: Evidence From a Cross-sectional Study in Southern Iran
Authors: Yusefi Ali Reza , Nasabi Narjes Sadat , Bahmaei Jamshid , Askarpour Hedyeh , Bordbar Shima 
Published: September 2024

Introduction
The ability to express themselves, adjustment, and self-efficacy play an important role in the academic success of students. The purpose of this research was to investigate the state of self-expression and its relationship with adjustment and self-efficacy of University students of Medical Sciences in 2024.

Methods
This descriptive-analytical cross-sectional study was conducted on 290 students of various fields studying in the first semester of 2023-2024. Data were collected using standard self-expression, adjustment, and self-efficacy questionnaires. Data were analyzed with SPSS software version 23 using descriptive and inferential statistics, and t-test, ANOVA, and Pearson’s correlation coefficient were performed at a 5% significance level.

Results
The mean and standard deviation of self-expression, adjustment, and self-efficacy of the students were respectively 92.48 ± 17.36 out of 200, 123.87 ± 15.94 out of 335, and 48.31 ± 11.25 out of 85. This indicates the average level of self-expression and self-efficacy, as well as poor adjustment. Also, a statistically significant direct correlation was observed between self-expression with adjustment (p=0.002, r=0.328) and self-efficacy (p<0.001, r=0.516).

Conclusion
Self-expression and self-efficacy were estimated at a medium level, and adjustment was estimated at a low level. Based on the results, with the improvement of self-expression, the students' adjustment and self-efficacy will improve. Therefore, it is suggested that the officials of the university provide the conditions for improving the self-expression of students through educational workshops and increase their self-confidence and self-esteem. Subsequently, paying attention to the needs of students and trying to solve their problems will help to reduce incompatibility.
Multi-Objective Low-carbon Optimization of UHVDC System Based on AP-NSGA-II Algorithm
Authors: Lei Luo , Jun Yang , Bingyuan Tan , Xiong Xiao , Yizhou Chen , Jicheng Yu 
Published: September 2024

Background:
Ultra-High Voltage Direct Current (UHVDC) system has a wide range of
applications in the energy field, and its transmission process will cause a large amount of carbon
loss. To reduce carbon loss under the premise of ensuring safety, it is necessary to construct a
carbon loss model of the UHVDC transmission system.

Methods:
In this study, we propose a multi-objective optimization model to achieve the goal of
low-carbon emissions, which considers carbon transaction costs and equipment safety and proposes
initialization improvement and congestion improvement.

Results:
Compared with the mainstream optimization algorithms, the results show that the improved
model achieves at least a 29.97 % effect in reducing carbon loss, reduces the carbon loss
by 1222.79 t, meets the requirements of the low carbon loss, transaction cost and high safety, and
realizes the triple goals of UHVDC transmission system.

Conclusion:
The model we proposed can effectively reduce carbon loss and carbon trading costs
on the premise of ensuring safety.
Preliminary In silico Analysis of Echinococcus granulosus Calreticulin for Enhanced Vaccine Design against Cystic Echinococcosis
Authors: Gorgin Zahra , Yousefi Mahzad , Ghiabi Shadan , Elahinia Ali , Yousefi Hamed , Aghmyouni Zahra Fadaeian , Jahani Negar , Asgari Amirhossein , Hamedi Erfan , Rajabi Romina , Rahmanian Parham , Hashemi Saeed , Zandieh Mohammad Arad , Majidiani Hamidreza , Motahari Alireza 
Published: September 2024

Background:
A neglected zoonosis, Cystic Echinococcosis (CE), is most common in
developing nations worldwide. Vaccination is, therefore, helpful in preventing this disease.

Objective:
Predicting the main biochemical properties of E. granulosus Calreticulin (CRT) and its
possible B-cell and T-cell-binding epitopes as a valuable candidate for immunization was the goal
of the current study.

Methods:
Predictions were made to determine biochemical, antigenic, structural, and subcellular
characteristics, along with the immunogenic epitopes, using several online servers.

Results:
The extracellular 48.15 KDa protein exhibited no allergenicity, while possessing hydrophilicity
(GRAVY: -0.785), stability (instability: 33.88), tolerance to a wide range of temperatures
(aliphatic: 62.45), and 59 post-translational modification sites. The secondary structure mostly
comprised random coils and extended strands. The 3D model was generated using the Robetta
server (confidence: 0.72), and was rehashed and confirmed subsequently. Common B-cell epitopes
were discovered by three servers and screened for antigenic, allergenic, and solubility traits.
Moreover, MHC-associated epitopes for mice and humans were predicted in E. granulosus CRT
with subsequent screening.

Conclusion:
This work offers a foundation for further investigation in order to design an effective
vaccination against CE. Further empirical research on the examined protein solely or in combination
with other antigens is needed.