bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microvascular dynamics regulate post-ischemic muscle damage and regeneration in experimental hindlimb ischemia
Authors: Wirth Galina , Juusola Greta , Tarvainen Santeri , Laakkonen Johanna P. , Korpisalo Petra , Ylä-Herttuala Seppo 
Published: June 2023

Abstract
Tissue microvasculature is known to remodel in response to ischemia. Yet, how this remodeling contributes to the process of post-ischemic recovery is still not completely understood. We studied how microvascular changes relate to post-ischemic muscle repair. Muscle-level microvascular alterations of blood flow and hemoglobin oxygenation, and post-ischemic myofiber and capillary responses were analyzed in aged, healthy C57Bl/6J mice (n = 48) and aged, hyperlipidemic LDLR−/−ApoB100/100 mice (n = 69) after induction of acute hindlimb ischemia using contrast ultrasound, photoacoustic imaging, and histological analyses, respectively. Microvascular responses leading to successful post-ischemic muscle repair in C57Bl/6J mice included an early capillary dilation phase preceding the return of arterial driving pressure followed by an increase in capillary density that further supported satellite cell-induced muscle regeneration. Failure of initial capillary enlargement due to a life-long moderate hypercholesterolemia in LDLR−/−ApoB100/100 mice led to inability to recover arterial driving pressure and resulted in an increase in distal necrosis, chronic tissue damage and a delay in overall recovery after ischemia. To conclude, these data reveal the important role of transient capillary enlargement in initiating a cascade of capillary events that are crucial for a successful post-ischemic muscle recovery. Essentially, the observed dynamic nature of the post-ischemic capillaries should be considered when designing novel treatments targeting the microvasculature in ischemic diseases.
Stock Closing Price Prediction of Indian Tech Companies using Deep Neural Networks
Authors: Divyansh Divyansh , Moonis Abdullah , Raghav Animesh , Walture Aditya , Chouhan Siddharth Singh , Singh Uday Pratap , Saxena Akash 
Published: June 2023

Abstract
In today’s economic world forecast and study of stock market data have got a vital role but, stock price forecasting has been hampered by its nonlinearity and high volatility of financial time series, to maximize the profits and reduce the risk involved the investors are eager to find different ways to forecast upcoming trends. It’s a challenging task to crack stock portfolio allocation in such a suitable way to invest in selected stocks that efficiently minimize the risk involved while capitalizing on profit. The effects of rival stocks in the stock market and the impact of mutation points on the precision of target stock predictions are rarely considered as market sentiment by the current prediction models. To validate which deep learning algorithm is best suited for stock market prediction analysis, we have espoused four deep learning algorithms namely Long Short-Term Memory (LSTM), Autoregressive Integrated Memory (ARIMA), Bi-directional Long Short-Term Memory (Bi-LSTM), and Gate Recurrent Units (GRU). On the basis of these mentioned evaluation parameters i.e., Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) we have done the accuracy tests of the listed deep learning algorithms with evaluative stock prediction graph. Results have shown Bi-LSTM to perform exceptionally well for time series analysis. Regarding LSTM and GRU, the results have more or less stayed the same. While ARIMA gave an un-stable performance thus rendering its usefulness for our analysis.
An A3C-based dynamic task scheduling algorithm for satellite edge computing
Authors: Hu Yifei , Li Guang , Gong Wenbin 
Published: June 2023

Abstract
Satellite edge computing has garnered significant attention as an essential component of 6G. Among various research areas, satellite dynamic task scheduling holds a prominent position. This paper addresses the scenario of satellite dynamic receiving task on-orbit computing and proposes a collaborative approach by offloading the tasks to multiple satellites. To tackle the scheduling problem, a Markov decision process framework is adopted, and a dynamic scheduling algorithm based on the A3C algorithm is proposed. Comparative analysis with three benchmark algorithms reveals that the proposed algorithm excels in reducing both average task delay and satellite load.
3D tracking reveals energy-distance trade-offs in two dominant grazers on a degraded coral reef
Authors: Lilkendey Julian , Zhang Jingjing , Barrelet Cyril , Meares Michael , Larbi Houssam , Subsol Gérard , Chaumont Marc , Sabetian Armagan 
Published: June 2023

Abstract
In-depth understanding of animal movement ecology, including energy expenditure and internal energy budgeting, is crucial for deciphering the intricate dynamics of ecosystem functioning. It essentially reveals resource partitioning and energy flows among foraging organisms within their habitats. Ecosystems under severe anthropogenic stress, such as degraded coral reefs, serve as valuable model habitats for examining how patchy resource availability impacts the foraging behavior and internal energy budgets of herbivores. In this study, we employed stereo-video measurements, Artificial Intelligence (AI)-driven object recognition, and 3D tracking techniques to explore resource partitioning and energy budgets of two dominant grazers, Brown surgeonfish Acanthurus nigrofuscus and Yellowtail tang Zebrasoma xanthurum, on a degraded coral reef in Eilat, Israel. We compared feeding preferences, bite rates, and inter bite distances to comprehend the mechanisms underlying functional trait expression and resource partitioning in these key grazers. A. nigrofuscus demonstrated a strategy that allowed a higher rate of food intake within given time frames, while Z. xanthurum exhibited a more generalist approach, traversing larger distances between food patches. However, our measurements of energy expenditure did not reveal significant differences between the two species. We found that the unique foraging strategies and feeding preferences of A. nigrofuscus and Z. xanthurum may underlie the observed energy-distance trade-offs, which were determined by factors such as resource availability and feeding niches. By applying AI-generated 3D trajectories, we achieved a granular analysis of fish movement and foraging behavior. This approach demonstrates the innovative potential of blending AI-generated 3D data with traditional stereo-video measurements, thus advancing our understanding of animal movement ecology. A detailed understanding can inform and enhance management and conservation strategies, providing insights into the adaptation of grazers to resource availability within degraded ecosystems. The approach of deriving energy expenditure from automatically generated 3D trajectories of animal movements could prove to be a novel and valuable indicator of ecosystem health.
Cardiac metabolism assessed by MR spectroscopy in the heart of patients with obesity and diabetes: knowledge discovery via Bayesian networks and random forest classification
Authors: Hanninger Ina , Levelt Eylem , Rayner Jennifer J , Rodgers Chistopher T , Neubauer Stefan , Grau Vicente , Rider Oliver J , Valkovič Ladislav 
Published: June 2023

Abstract
Recent developments in Magnetic resonance spectroscopy (MRS) techniques have demonstrated great potential for the quantification of myocardial energy metabolites, enabling an in-depth glimpse into the energetic state of the heart to better explain the onset and severity of disease states. However, more evidence is required to establish its clinical impact and explanatory power compared to other diagnostic variables.
In this study, Random Forest classification was used on data from 197 subjects to discriminate between patients with and without diabetes and obesity using 31P-MRS and 1H-MRS measurements of cardiac energetics, along with MRI measures of cardiac function. Achieving 91.67%, 73.08% and 88.89% test accuracies, SHAP (SHapley Additive exPlanations) feature importances indicate a higher predictive impact of metabolic metrics for classifying the diabetic heart compared to global function metrics, gained through most common imaging techniques. Bayesian networks generated through structure learning of the data further suggests a potential causal association of increased visceral fat, increased LVMass resulting in decreased PCr/ATP, and increased cardiac lipid levels attributed to these disease states. Through the results, we have been able to showcase the importance of MRS measurements, both in distinguishing between diseases with clinically-relevant accuracy and furthermore its causal connection to other cardiac parameters.
Spatial estimation of soil erosion risk using RUSLE model in District Swat, Eastern Hindu Kush, Pakistan
Authors: Khan Abdullah , Rahman Atta-ur , Mahmood Shakeel 
Published: June 2023

Abstract

Soil erosion is a natural geomorphic process with the potential to damage fertile land. In this study, soil erosion risk is spatially estimated in District Swat by applying Revised Universal Soil Loss Equation (RUSLE). The RUSLE parameters that trigger soil erosion including rainfall erosivity, soil erodibility, topography, cover management, and support practices were derived from monthly rainfall data obtained from Pakistan Metrology Department, soil texture map from Soil Survey of Pakistan and Digital Soil Map of the World database, land use land cover extracted from SPOT 5 satellite image, whereas slope and digital terrain extracted from Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM). It was found from the analysis that out of the total reported area, 34.5% falls in the area affected by very high soil erosion. The results of spatial pattern and erosion proneness of the study region have been further classified into very low (45%), low (8.5%), moderate (7%), high (5.2%), and very high zones (34.5%). The results show that the study area requires effective mitigation strategies to curtail the precious soil. This study has the potential to assist the decision makers and planners for soil loss risk reduction.
Impact of historical and future land use land cover on spatial-temporal variation of discharge and sediment load of Upper Tapi Basin, India
Authors: Malani Urvashi , Yadav SanjayKumar M. 
Published: June 2023

Abstract
Trend detection of discharge and sediment load is vital to adopt suitable conservation measures as per the changes occurring. In the present study, trends of daily streamflow and sediment load for Upper Tapi Basin are analyzed using Mann-Kendall, modified Mann-Kendall, and innovative trend analysis and change points are found using Pettitt tests from 1985 to 2020 to determine time series' trend with the statistical significance. Land use land cover (LULC) for Upper Tapi Basin is prepared for three decades (1989–2020). Innovative trend analysis has shown non-monotonicity in the time series with a decreasing trend. The streamflow is found to be significantly decreasing in the basin. A decline in sediment load is observed in Burhanpur and Gopalkheda while there is an increasing trend in Yerli G.S. The rise in anthropogenic activities is the main reason behind the reduction in suspended sediment load (SSL) over the basin. The decadal analysis of LULC showed an increase in built-up area (18.3%), barren land (5–8%), waterbodies (1.2–1.9%) agricultural land (50–60.79%) and a decrease in vegetation (from 43 to 21%). The LULC for 2030 is predicted with Land Change Modeler (LCM) in IDRISI Terrset. The estimated LULC shows that the built-up area will expand as agricultural land decreases. The overall study indicates that anthropogenic activities will increase in the future. The findings of this study will aid in decision making for river basin water resource management, as well as understanding the influence of human-caused activities on flow and sediment load variance.
Nanotechnology as an efficient and effective alternative for wastewater treatment: an overview
Authors: Pérez Heilyn , Quintero García Omar Jasiel , Amezcua-Allieri Myriam Adela , Rodríguez Vázquez Refugio 
Published: June 2023

Abstract

The increase in the surface and groundwater contamination due to global population growth, industrialization, proliferation of pathogens, emerging pollutants, heavy metals, and scarcity of drinking water represents a critical problem. Because of this problem, particular emphasis will be placed on wastewater recycling. Conventional wastewater treatment methods may be limited due to high investment costs or, in some cases, poor treatment efficiency. To address these issues, it is necessary to continuously evaluate novel technologies that complement and improve these traditional wastewater treatment processes. In this regard, technologies based on nanomaterials are also being studied. These technologies improve wastewater management and constitute one of the main focuses of nanotechnology. The following review describes wastewater's primary biological, organic, and inorganic contaminants. Subsequently, it focuses on the potential of different nanomaterials (metal oxides, carbon-based nanomaterials, cellulose-based nanomaterials), membrane, and nanobioremediation processes for wastewater treatment. The above is evident from the review of various publications. However, nanomaterials’ cost, toxicity, and biodegradability need to be addressed before their commercial distribution and scale-up. The development of nanomaterials and nanoproducts must be sustainable and safe throughout the nanoproduct life cycle to meet the requirements of the circular economy.
PaSTe. Blockade of the Lipid Phenotype of Prostate Cancer as
Metabolic Therapy: A Theoretical Proposal
Authors: Romo-Perez Adriana , Domínguez-Gómez Guadalupe , Chávez-Blanco Alma D. , González-Fierro Aurora , Correa-Basurto José , Dueñas-González Alfonso 
Published: June 2023

Background:
Prostate cancer is the most frequently diagnosed malignancy in
112 countries and is the leading cause of death in eighteen. In addition to continuing research
on prevention and early diagnosis, improving treatments and making them more
affordable is imperative. In this sense, the therapeutic repurposing of low-cost and widely
available drugs could reduce global mortality from this disease. The malignant
metabolic phenotype is becoming increasingly important due to its therapeutic implications.
Cancer generally is characterized by hyperactivation of glycolysis, glutaminolysis,
and fatty acid synthesis. However, prostate cancer is particularly lipidic; it exhibits increased
activity in the pathways for synthesizing fatty acids, cholesterol, and fatty acid
oxidation (FAO).

Objective:
Based on a literature review, we propose the PaSTe regimen (Pantoprazole,
Simvastatin, Trimetazidine) as a metabolic therapy for prostate cancer. Pantoprazole and
simvastatin inhibit the enzymes fatty acid synthase (FASN) and 3-hydroxy-3-methylglutaryl-
coenzyme A reductase (HMGCR), therefore, blocking the synthesis of fatty acids
and cholesterol, respectively. In contrast, trimetazidine inhibits the enzyme 3-β-Ketoacyl-
CoA thiolase (3-KAT), an enzyme that catalyzes the oxidation of fatty acids (FAO).
It is known that the pharmacological or genetic depletion of any of these enzymes has antitumor
effects in prostatic cancer.

Results:
Based on this information, we hypothesize that the PaSTe regimen will have increased
antitumor effects and may impede the metabolic reprogramming shift. Existing
knowledge shows that enzyme inhibition occurs at molar concentrations achieved in plasma
at standard doses of these drugs.

Conclusion:
We conclude that this regimen deserves to be preclinically evaluated because
of its clinical potential for the treatment of prostate cancer.
CENPF Upregulation is Associated with Immunosuppressive Status and Poor Clinical Outcomes in Lung Adenocarcinoma Validated by qRT-PCR
Authors: Xu Zhiyun , Xu Dafu , You Zhenbing , Tian Wenze 
Published: June 2023

Objective:
CENPF-differentially expressed in various types of cancers—is a marker of
poor prognosis. However, studies on the impact of CENPF on patient prognosis in lung adenocarcinoma
regarding immune infiltration are lacking.

Methods:
CENPF expression profiles were analyzed in the GEO and TCGA databases. qRT-PCR
was used to verify CENPF mRNA expression in lung adenocarcinoma cell lines. The prognostic
value of CENPF was evaluated by combining data from clinical samples in the GEPIA2 and
TCGA databases. Metascape and WebGestalt were used for enrichment analysis of gene sets most
positively associated with CENPF. Immune cell infiltration score data were retrieved from TCGA
and the correlation between CENPF expression and immune cell infiltration was analyzed.

Results:
CENPF expression was elevated in 29 types of cancer. CENPF was highly expressed and
increased with tumor grade in lung adenocarcinoma. Immunohistochemical and qRT-PCR analyses
revealed that CENPF expression was upregulated in lung adenocarcinoma tissues and cells. High expression
of CENPF significantly worsened prognoses in patients with multiple malignancies, including
lung adenocarcinoma. Results from gene set enrichment analysis indicated significant enrichment
of the progesterone-mediated oocyte maturation pathway. Immune infiltration analysis revealed that
CD4+ Th2 cell infiltration was significantly higher in the high CENPF expression group.

Conclusion:
Upregulation of CENPF expression was related to poor progression-free survival, disease-
free survival, and overall survival in patients with lung adenocarcinoma. High expression of
CENPF was markedly related to genes associated with the immune checkpoint. Lung adenocarcinoma
samples with high CENPF expression had increased CD4+ Th2 cell infiltration. Our findings
indicate that CENPF promotes CD4+ Th2 cell infiltration through oncogenic activity and may be
used as a biomarker for predicting patient outcomes in lung adenocarcinoma.
Literature Review on Crotalus durissus terrificus Toxins: From a Perspective
of Structural Biology and Therapeutic Applications
Authors: Macedo Jamile Mariano , de Lima Anderson Maciel , Kayano Anderson Makoto , Souza Mateus Farias , da Silva Oliveira Iolanda , Gomez Garay Ana Fidelina , Rocha Anderson Maciel , Zuliani Juliana Pavan , Soares Andreimar Martins 
Published: June 2023

Background:
The venom of Crotalus durissus terrificus, as well as its fractions, has intrigued
research groups worldwide who are working to isolate, characterize, and find possible biotechnological
applications. A number of studies have elucidated that these fractions and their derivatives
possess pharmacological properties, which can enable the development of new drug prototypes with
anti-inflammatory, antinociceptive, antitumor, antiviral, and antiparasitic applications.

Objective:
This review presents a systematic study on Crotalus durissus terrificus, the most notable
crotalid subspecies in South America, focusing on the composition, toxicological mechanisms, structural
aspects, and applications of the main venom toxins (convulxin, gyroxin, crotamine, crotoxin, and
their subunits).

Conclusion:
The authors have found that research on this snake and its toxins is still an area of focus,
despite that almost a century has passed since the isolation of crotoxin. Several applications of these
proteins in the development of novel drugs and bioactive substances have also been demonstrated.
Establishment of a Rat Model of Infraorbital Neuroinflammation Under
CT Guidance
Authors: Zeng Chen , Zhang Chuan , Xiao Ruhui , Li Yehan , Luo Xing , Deng Hao , Yang Hanfeng 
Published: June 2023

Introduction:
The aim is to establish a rat model of infraorbital neuroinflammation with
less trauma, stable pain, and a long duration of pain. The pathogenesis of TN is not fully clear.
There are various models of TN in rats with different disadvantages, such as damaging the surrounding
structures and inaccuracy of location for infraorbital nerve (ION). We aim to establish a
rat model of infraorbital neuroinflammation with minimal trauma, a simple operation, and accurate
positioning under CT guidance to help us study the pathogenesis of trigeminal neuralgia.

Methods:
Thirty-six adult male Sprague Dawley rats (180-220 g) were randomly divided into 2
groups and injected with talc suspension or saline through the infraorbital foramen (IOF) under CT
guidance. Mechanical thresholds were measured in the right ION innervation region of 24 rats over
12 postoperative weeks. At 4 weeks, 8 weeks, and 12 weeks after the operation, the inflammatory
involvement of the surgical area was evaluated by MRI, and neuropathy was observed using a
transmission electron microscope (TEM).

Results:
The talc group had a significant decrease in the mechanical threshold at 3 days after surgery
that continued until 12 weeks post-operation, and the talc group had a significantly lower mechanical
threshold than the saline group 10 weeks post-operation. The talc group had significantly
impaired trigeminal nerve (TGN) myelin after 8 weeks post-operation.

Conclusions:
The rat model of infraorbital neuroinflammation established by CT-guided injection
of talc into the IOF is a simple operation that results in less trauma, stable pain, and a long duration
of pain. Moreover, infraorbital neuroinflammation in peripheral branches of the TGN can cause
demyelination of the TGN in the intracranial segment.
Female Sexual Function following Pelvic Organ Prolapse Reconstruction:
A Case Serial Study
Authors: Rahayu Sri , Fakhrizal Edy , Yulis Hamidy Muhammad 
Published: June 2023

Background:
Pelvic organ prolapse (POP) may reduce women's quality of life and is one of the most important aspects in the occurrence of sexual dysfunction.

Objective:
This study aimed to assess sexual function in POP women with pelvic floor dysfunction pre and post-surgery.

Methods:
This study was a prospective cohort study. Using the total sampling technique at Arifin Achmad Hospital, Indonesia, the study recruited women who underwent POP surgery with active sexual function from July 2020 to December 2021. The pelvic floor disorder was evaluated through Pelvic Floor Distress Inventory (PFDI) questionnaires validated in the Indonesian language, pre, and post-surgery. The assessment of sexual function was carried out using the Indonesian linguistic validation of the Female Sexual Function Index (FSFI) questionnaires before and after surgery.

Results:
There was a decrease in the average value of pelvic floor disorder scores before and six months after surgery (P< 0.05). However, the sexual function increased with a cut-off score of FSFI > 20.25 at 3 and 6 months post-surgery, respectively as much as 61.1% (11/18 subjects) and 72.2% (13/18 subjects), compared to the pre-surgery sexual function scores by 7.8% (5/18 subjects). Out of the 6 domains of sexual function, an increase was found in the sexual arousal domain (P<0.05).

Conclusion:
There is a decrease in pelvic floor disorder and an increase in sexual function, particularly an increment in sexual arousal at six months post-surgery.