bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroimmunology of Cardiovascular Disease
Authors: Zarate Sara M. , Kirabo Annet , Hinton Antentor O. , Santisteban Monica M. 
Published: April 2024

Abstract
Purpose of Review
Cardiovascular disease (CVD) is a leading cause of death and chronic disability worldwide. Yet, despite extensive intervention strategies the number of persons affected by CVD continues to rise. Thus, there is great interest in unveiling novel mechanisms that may lead to new treatments. Considering this dilemma, recent focus has turned to the neuroimmune mechanisms involved in CVD pathology leading to a deeper understanding of the brain’s involvement in disease pathology. This review provides an overview of new and salient findings regarding the neuroimmune mechanisms that contribute to CVD.

Recent Findings
The brain contains neuroimmune niches comprised of glia in the parenchyma and immune cells at the brain’s borders, and there is strong evidence that these neuroimmune niches are important in both health and disease. Mechanistic studies suggest that the activation of glia and immune cells in these niches modulates CVD progression in hypertension and heart failure and contributes to the inevitable end-organ damage to the brain.

Summary
This review provides evidence supporting the role of neuroimmune niches in CVD progression. However, additional research is needed to understand the effects of prolonged neuroimmune activation on brain function.
Current Perspectives and Progress in Preoperative Portal Vein Embolization with Stem Cell Augmentation (PVESA)
Authors: Barcena Allan John R. , Owens Tyler C. , Melancon Sophie , Workeneh Isias , Tran Cao Hop S. , Vauthey Jean-Nicolas , Huang Steven Y. 
Published: April 2024

AbstractPortal vein embolization with stem cell augmentation (PVESA) is an emerging approach for enhancing the growth of the liver segment that will remain after surgery (i.e., future liver remnant, FLR) in patients with liver cancer. Conventional portal vein embolization (PVE) aims to induce preoperative FLR growth, but it has a risk of failure in patients with underlying liver dysfunction and comorbid illnesses. PVESA combines PVE with stem cell therapy to potentially improve FLR size and function more effectively and efficiently. Various types of stem cells can help improve liver growth by secreting paracrine signals for hepatocyte growth or by transforming into hepatocytes. Mesenchymal stem cells (MSCs), unrestricted somatic stem cells, and small hepatocyte-like progenitor cells have been used to augment liver growth in preclinical animal models, while clinical studies have demonstrated the benefit of CD133 + bone marrow–derived MSCs and hematopoietic stem cells. These investigations have shown that PVESA is generally safe and enhances liver growth after PVE. However, optimizing the selection, collection, and application of stem cells remains crucial to maximize benefits and minimize risks. Additionally, advanced stem cell technologies, such as priming, genetic modification, and extracellular vesicle-based therapy, that could further enhance efficacy outcomes should be evaluated. Despite its potential, PVESA requires more investigations, particularly mechanistic studies that involve orthotopic animal models of liver cancer with concomitant liver injury as well as larger human trials.
Building a strong programme in sociological aesthetics: Helmut Staubmann’s Sociology in a New Key
Authors: Tanner Jeremy James 
Published: April 2024

AbstractHelmut Staubmann’s Sociology in a New Key develops a compelling approach to the sociologies of art and the emotions, based primarily on Talcott Parsons’ Action Theory and Georg Simmel’s formal sociology. This article appraises the key theoretical strategies of Staubmann’s contribution, and the insights they afford, with particular reference to recent work in the ‘New Sociology of Art’ and the ‘Strong Programme’ of Jeffery Alexander and the Yale school.
Age and mean platelet volume-based nomogram for predicting the therapeutic efficacy of metoprolol in Chinese pediatric patients with vasovagal syncope
Authors: Du Xiao-Juan , Huang Ya-Qian , Li Xue-Ying , Liao Ying , Jin Hong-Fang , Du Jun-Bao 
Published: April 2024

Abstract
Background
Vasovagal syncope (VVS) is the most common type of orthostatic intolerance in children. We investigated whether platelet-related factors related to treatment efficacy in children suffering from VVS treated with metoprolol.

Methods
Metoprolol-treated VVS patients were recruited. The median duration of therapy was three months. Patients were followed and divided into two groups, treament-effective group and treatment-ineffective group. Logistic and least absolute shrinkage selection operator regressions were used to examine treatment outcome variables. Receiver-operating characteristic (ROC) curves, precision–recall (PR) curves, calibration plots, and decision curve analyses were used to evaluate the nomogram model.

Results
Among the 72 patients who complete the follow-up, treatment-effective group and treatment-ineffective group included 42 (58.3%) and 30 (41.7%) cases, respectively. The patients in the treatment-effective group exhibited higher mean platelet volume (MPV) [(11.0 ± 1.0) fl vs. (9.8 ± 1.0) fl, P < 0.01] and platelet distribution width [12.7% (12.3%, 14.3%) vs. 11.3% (10.2%, 12.2%), P < 0.01] than those in the treatment-ineffective group. The sex ratio was significantly different (P = 0.046). A fit model comprising age [odds ratio (OR) = 0.766, 95% confidence interval (CI) = 0.594–0.987] and MPV (OR = 5.613, 95% CI = 2.297–13.711) might predict therapeutic efficacy. The area under the curve of the ROC and PR curves was computed to be 0.85 and 0.9, respectively. The P value of the Hosmer–Lemeshow test was 0.27. The decision curve analysis confirmed that managing children with VVS based on the predictive model led to a net advantage ranging from 0.01 to 0.58. The nomogram is convenient for clinical applications.

Conclusion
A novel nomogram based on age and MPV can predict the therapeutic benefits of metoprolol in children with VVS.
Water-Based Epidemiological Investigation of Hepatitis E Virus in South Africa
Authors: Salemane Karabo , Coetzee Leanne Z. , Pocock Gina , Genthe Bettina , Taylor Maureen B. , Mans Janet 
Published: April 2024

AbstractHepatitis E virus (HEV) is an emerging zoonotic pathogen that exhibits great host diversity. The primary means of transmission of the virus in low- and middle-income countries is contaminated water, often due to a lack of access to proper sanitation, which leads to faecal contamination of water sources. Environmental surveillance is an important tool that can be used to monitor virus circulation and as an early warning system for outbreaks. This study was conducted to determine the prevalence and genetic diversity of HEV in wastewater, surface water (rivers and standpipe/ablution water), and effluent from a piggery in South Africa. A total of 536 water samples were screened for HEV using real-time reverse transcription-polymerase chain reaction. Overall, 21.8% (117/536) of the wastewater, river, and ablution water samples tested positive for HEV, whereas 74.4% (29/39) of the samples from the piggery tested positive. Genotyping revealed sequences belonging to HEV genotypes 3 (98%, 53/54) and 4 (2%, 1/54), with subtypes 3c, 3f, and 4b being identified.
Design optimization of Yb-doped fiber lasers for operation in radiation environments
Authors: Tao Mengmeng , Wang Yamin , Wang Ke , Chen Hongwei , Ye Jingfeng , Shen Yanlong , Wang Dahui , Ye Xisheng 
Published: April 2024

AbstractRadiation hardening should be considered for various active fiber systems operated in adverse environments to reduce their sensitivity to complex ionizing radiations. And, architecture optimization through numerical simulation provides an efficient choice. Here, introducing radiation effects into the conventional fiber laser model, a radiation model concerning the design optimization of low- and moderate-power Yb-doped fiber lasers is developed. And, experiments at different radiation levels up to 750 Gy are carried out for validation, demonstrating the ability of this model to correctly simulate the performance of the Yb-doped fiber laser in harsh environments. Then, with this model, impacts of active fiber length, pump scheme, and pump allocation on the output characteristics of Yb-doped fiber lasers are analyzed numerically. And, optimization of Yb-doped fiber lasers are conducted through architecture design. Simulations show that a proper design with relatively short active fiber and dynamic pump allocation can remarkably improve the radiation tolerance of Yb-doped fiber lasers.
Streamflow prediction using support vector regression machine learning model for Tehri Dam
Authors: Sharma Bhanu , Goel N. K. 
Published: April 2024

AbstractAccurate and reliable streamflow prediction is critical for optimising water resource management, reservoir flood operations, watershed management, and urban water management. Many researchers have published on streamflow prediction using techniques like Rainfall-Runoff modelling, Time series Models, Data-driven models, Artificial intelligence, etc. Still, there needs to be generalised method practise in the real world. The resolution of this issue lies in selecting different methods for a particular study area. This paper uses the Support vector regression machine learning model to predict the streamflow for the Tehri Dam, Uttarakhand, India, at the Daily and Ten Daily time steps. Two cases are considered in predicting daily and ten daily time steps. The first case includes four input variables: Discharge, Rainfall, Temperature, and Snow cover area. The second case comprises only three input variables: Rainfall, Temperature, and Snow cover area. Radial Kernel is used to overcome the space complexity in the datasets. The K-fold cross-validation is suitable for prediction as it averages the prediction error rate after evaluating the SVR model’s performance on various subsets of the training data. The streamflow data for daily and ten daily time steps have been collected from 2006 to 2020. The calibration period is from 2006 to 2016, and the validation period is from 2017 to 2020. Nash Sutcliffe Efficiency (NSE) and Coefficient of determination (R2) are used as the accuracy indicator in this manuscript. The lag has been observed in the daily prediction time series when three input variables are considered. For other scenarios, the respective model shows excellent results at both the temporal scale and the parametres, which play a vital role in prediction. The study also enhances the effect on the potential use of input parametres in the machine learning model.
Contribution to advancing aquifer geometric mapping using machine learning and deep learning techniques: a case study of the AL Haouz-Mejjate aquifer, Marrakech, Morocco
Authors: El Mezouary Lhoussaine , Hadri Abdessamad , Kharrou Mohamed Hakim , Fakır Younes , Elfarchouni Abderrahman , Bouchaou Lhoussaine , Chehbouni Abdelghani 
Published: April 2024

AbstractGroundwater resources in Morocco often face sustainability challenges due to increased exploitation and climate change. Specifically, the Al-Haouz-Mejjate groundwater in the Marrakesh region is faced with overexploitation and insufficient recharge. However, the complex subsurface geometries hamper hydrogeological modeling, characterization, and effective management. Reliably estimating aquifer substrate topography is critical for groundwater models but is challenged by limited direct measurements. This study develops nonlinear machine learning models to infer substrate depths by fusing sparse borehole logs with regional geospatial data. A Gaussian process regression approach provided robust holistic mapping, leveraging flexibility, and uncertainty quantification. Supplementary neural network architectures focus on isolating specific variable relationships, like surface elevation–substrate. Model accuracy exceeded 0.8 R-squared against validation boreholes. Spatial visualizations confirmed consistency across landscape transects. Elevation and piezometric data proved most predictive, though multivariate inputs were required for the lowest errors. The results highlight the power of statistical learning to extract meaningful patterns from disparate hydrological data. However, model opacity and the need for broader training datasets remain barriers. Overall, the work demonstrates advanced machine learning as a promising avenue for illuminating complex aquifer geometries essential for sustainability. Hybrid approaches that use both data-driven and physics-based methods can help solve long-standing problems with hydrogeological characterization.
Effects of semaglutide-loaded lipid nanocapsules on metabolic dysfunction-associated steatotic liver disease
Authors: Domingues Inês , Yagoubi Hafsa , Zhang Wunan , Marotti Valentina , Kambale Espoir K. , Vints Katlijn , Sliwinska Malgorzata Alicja , Leclercq Isabelle A. , Beloqui Ana 
Published: April 2024

AbstractMetabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent chronic liver disease that can progress to end-stage conditions with life-threatening complications, but no pharmacologic therapy has been approved. Drug delivery systems such as lipid nanocapsules (LNC) are very versatile platforms that are easy to produce and can induce the secretion of the native glucagon-like peptide 1 (GLP-1) when orally administered. GLP-1 analogs are currently being studied in clinical trials in the context of MASLD. Our nanosystem provides with increased levels of the native GLP-1 and increased plasmatic absorption of the encapsulated GLP-1 analog (semaglutide). Our goal was to use our strategy to demonstrate a better outcome and a greater impact on the metabolic syndrome associated with MASLD and on liver disease progression with our strategy compared with the oral marketed version of semaglutide, Rybelsus®. Therefore, we studied the effect of our nanocarriers on a dietary mouse model of MASLD, the Western diet model, during a daily chronic treatment of 4 weeks. Overall, the results showed a positive impact of semaglutide-loaded lipid nanocapsules towards the normalization of glucose homeostasis and insulin resistance. In the liver, there were no significant changes in lipid accumulation, but an improvement in markers related to inflammation was observed. Overall, our strategy had a positive trend on the metabolic syndrome and at reducing inflammation, mitigating the progression of the disease. Oral administration of the nanosystem was more efficient at preventing the progression of the disease to more severe states when compared to the administration of Rybelsus®, as a suspension.Graphical abstract
Generating operators between Banach spaces
Authors: Kadets Vladimir , Martín Miguel , Merí Javier , Quero Alicia 
Published: April 2024

AbstractWe introduce and study the notion of generating operators as those norm-one operators $$G:X\longrightarrow Y$$

G
:
X
⟶
Y

such that for every $$0<\delta <1$$

0
<
δ
<
1

, the set $$\{x\in X:\Vert x\Vert \leqslant 1,\ \Vert Gx\Vert >1-\delta \}$$

{
x
∈
X
:
‖
x
‖
⩽
1
,

‖
G
x
‖
>
1
-
δ
}

generates the unit ball of X by closed convex hull. This class of operators includes isometric embeddings, spear operators (actually, operators with the alternative Daugavet property), and other examples like the natural inclusions of $$\ell _1$$

ℓ
1

into $$c_0$$

c
0

and of $$L_\infty [0,1]$$

L
∞

[
0
,
1
]

into $$L_1[0,1]$$

L
1

[
0
,
1
]

. We first present a characterization in terms of the adjoint operator, make a discussion on the behaviour of diagonal generating operators on $$c_0$$

c
0

-, $$\ell _1$$

ℓ
1

-, and $$\ell _\infty $$

ℓ
∞

-sums, and present examples in some classical Banach spaces. Even though rank-one generating operators always attain their norm, there are generating operators, even of rank-two, which do not attain their norm. We discuss when a Banach space can be the domain of a generating operator which does not attain its norm in terms of the behaviour of some spear sets of the dual space. Finally, we study when the set of all generating operators between two Banach spaces X and Y generates all non-expansive operators by closed convex hull. We show that this is the case when $$X=L_1(\mu )$$

X
=

L
1

(
μ
)

and Y has the Radon-Nikodým property with respect to $$\mu $$
μ
. Therefore, when $$X=\ell _1(\Gamma )$$

X
=

ℓ
1

(
Γ
)

, this is the case for every target space Y. Conversely, we also show that a real finite-dimensional space X satisfies that generating operators from X to Y generate all non-expansive operators by closed convex hull only in the case that X is an $$\ell _1$$

ℓ
1

-space.
A novel additive for enhancing biomass energy production from agro-industrial wastes: synthesis of hydrophobic nanoporous silica aerogel and its effect on methane production
Authors: Gulsen Akbay Habibe Elif , Basgoz Oykum , Guler Omer 
Published: April 2024

Abstract
Anaerobic digestion (AD) is one of the most preferred processes for the treatment of organic waste. However, additional processes such as co-digestion, pretreatment, and additive addition continue to be explored to remove the limits on the applicability of AD. This study investigated the effects of hydrophobic nanoporous silica aerogel (NpSA) synthesized from waste rice husks on the anaerobic co-digestion (AnCD) of the mixture consisting of sewage sludge and fruit processing industry wastes. All bioreactors containing NpSA-free, 0.1 g, 0.2 g, 0.5 g, and 1 g NpSA (0.03–0.3 gNpSA/gVSadded) were operated in a mesophilic-batch process. Biogas and methane yields increased from 346 mL/gVS (NpSA-free) to 387 mL/gVS and from 231 mL/gVS (NpSA-free) to 288 mL/gVS, respectively, with 0.1 g NpSA addition. NpSA additive increased biogas production in all bioreactors compared to the blank. However, biogas production rate and methane content increased faster at lower doses of NpSA. Maximum soluble chemical oxygen demand (sCOD), protein, carbohydrate, and volatile solid (VS) reductions were between 45–71%, 35–54%, 44–65%, and 34–91% for NpSA added mixtures, respectively. The hydrophobic NpSA additive was effective in improving the AnCD performance and biogas/methane production. Experimental results fit the kinetic models frequently preferred in such AD processes. In addition, the possible energy and financial potential of the produced methane were also discussed, and it was determined that the direct sale of methane gas produced by the addition of NpSA in the global market could provide 1.4 $/Lmixture more financial gain than the mixture NpSA-free.

Graphical Abstract
Comprehensive risk factor predictions for 3-year survival among HIV-associated and disseminated cryptococcosis involving lungs and central nervous system
Authors: Wu Luling , Fu Xuemin , Pütz Benno , Zhang Renfang , Liu Li , Song Wei , Weng Ling , Shao Yueming , Zheng Zhihang , Xun Jingna , Han Ximei , Wang Ting , Shen Yinzhong , Lu Hongzhou , Müller-Myhsok Bertram , Chen Jun 
Published: April 2024

Abstract
Background
The global mortality rate resulting from HIV-associated cryptococcal disease is remarkably elevated, particularly in severe cases with dissemination to the lungs and central nervous system (CNS). Regrettably, there is a dearth of predictive analysis regarding long-term survival, and few studies have conducted longitudinal follow-up assessments for comparing anti-HIV and antifungal treatments.

Methods
A cohort of 83 patients with HIV-related disseminated cryptococcosis involving the lung and CNS was studied for 3 years to examine survival. Comparative analysis of clinical and immunological parameters was performed between deceased and surviving individuals. Subsequently, multivariate Cox regression models were utilized to validate mortality predictions at 12, 24, and 36 months.

Results
Observed plasma cytokine levels before treatment were significantly lower for IL-1RA (p < 0.001) and MCP-1 (p < 0.05) when in the survivor group. Incorporating plasma levels of IL-1RA, IL-6, and high-risk CURB-65 score demonstrated the highest area under curve (AUC) value (0.96) for predicting 1-year mortality. For 1-, 2- and 3-year predictions, the single-factor model with IL-1RA demonstrated superior performance compared to all multiple-variate models (AUC = 0.95/0.78/0.78).

Conclusions
IL-1RA is a biomarker for predicting 3-year survival. Further investigations to explore the pathogenetic role of IL-1RA in HIV-associated disseminated cryptococcosis and as a potential therapeutic target are warranted.
The Physiologically Difficult Airway and Management Considerations
Authors: Mosier Jarrod 
Published: April 2024

Abstract
Purpose of Review
This paper evaluates the recent literature regarding the physiologically difficult airway.

Recent Findings
Adverse events mainly desaturation, cardiovascular collapse, and cardiac arrest remain common complications. This risk is greatly increased in patients with altered physiology prior to intubation. Studies published over the last 5 years have explored many aspects surrounding the epidemiology, risks, and approach to managing the physiologically difficult airway.

Summary
Important work has been done to identify directly modifiable risks of complications related to the physiologically difficult airway, but a large percentage of patients remain at high risk despite optimizing induction agents, preoxygenation, and first attempt success.
Trajectory analysis of circulating tumor cells through contorted deterministic lateral displacement array for unruptured trapping: a simulation study
Authors: Bhattacharjee Rituraj , Kumar R. 
Published: April 2024

AbstractDuring the multistage process of cancer spread, fragments of cells branch out from the primitive tumor tissue and scatter throughout the body by blood flow stream or lymph, which are termed as circulating tumor cells (CTCs), regarded as an important biomarker for early cancer diagnosis. Deterministic lateral displacement (DLD) is one of the most efficient passive type particle isolation techniques which functions on asymmetrical laminar flow diversion around the placed microposts forming an array, based on the critical dimeter of the device. In this simulation study, complete trajectory analysis of CTCs and WBCs has been performed using COMSOL Multiphysics software with respect to the angular orientation of sample inlet channel. A simulated model of an asymmetric DLD array-based microfluidic device with latest empirical expression for critical diameter has been presented with optimized sample inlet orientation so as to maintain perfect separation efficiency of CTCs along with arrangement for unruptured trapping of CTCs and WBCs. The approximate CTC isolation efficiency was obtained above 95% for sample inlet inclinations up to 0.5°, and further tilt showed reduction in efficiency. Migration angle of CTC trajectory for the modeled device was obtained around 15° for both the sample inlet orientations leading to least intermingling of CTCs and WBCs. A smaller number of CTC–WBC interaction points was observed for clockwise sample inlet tilt compared to the anticlockwise displacement reducing possibilities of cell rupture. The shear rate around central microposts was found to be higher as well in clockwise sample inlet orientation. This simulation study establishes that sample inlet clockwise tilting of maximum around 0.5°–0.7° leads to better CTC isolation and provides better chances of unruptured trapping of cells at the designated outlets. The results of this study provide an approach toward further optimization of DLD devices' functioning and, thus, could help fabricate better DLD-based microfluidic devices for efficient trapping of CTCs.