bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning Algorithm for Tumor Segmentation and Discrimination of Clinically Significant Cancer in Patients with Prostate Cancer
Authors: Hong Sujin , Kim Seung Ho , Yoo Byeongcheol , Kim Joo Yeon
Published: August 2023

Background: We investigated the feasibility of a deep learning algorithm (DLA) based on apparent diffusion coefficient (ADC) maps for the segmentation and discrimination of clinically significant cancer (CSC, Gleason score ≥ 7) from non-CSC in patients with prostate cancer (PCa). Methods: Data from a total of 149 consecutive patients who had undergone 3T-MRI and been pathologically diagnosed with PCa were initially collected. The labelled data (148 images for GS6, 580 images for GS7) were applied for tumor segmentation using a convolutional neural network (CNN). For classification, 93 images for GS6 and 372 images for GS7 were used. For external validation, 22 consecutive patients from five different institutions (25 images for GS6, 70 images for GS7) representing different MR machines were recruited. Results: Regarding segmentation and classification, U-Net and DenseNet were used, respectively. The tumor Dice scores for internal and external validation were 0.822 and 0.7776, respectively. As for classification, the accuracies of internal and external validation were 73 and 75%, respectively. For external validation, diagnostic predictive values for CSC (sensitivity, specificity, positive predictive value and negative predictive value) were 84, 48, 82 and 52%, respectively. Conclusions: Tumor segmentation and discrimination of CSC from non-CSC is feasible using a DLA developed based on ADC maps (b2000) alone.
PSMA Targeted Molecular Imaging and Radioligand Therapy for Prostate Cancer: Optimal Patient and Treatment Issues
Authors: Hoshi Seiji , Yaginuma Kei , Meguro Satoru , Onagi Akifumi , Matsuoka Kanako , Hata Junya , Sato Yuichi , Akaihata Hidenori , Kataoka Masao , Ogawa Soichiro , Uemura Motohide , Kojima Yoshiyuki
Published: August 2023

Theranostics (therapy + diagnosis) targeting prostate-specific membrane antigen (PSMA) is an emerging therapeutic modality that could alter treatment strategies for prostate cancer. Although PSMA-targeted radioligand therapy (PSMA-RLT) has a highly therapeutic effect on PSMA-positive tumor tissue, the efficacy of PSMA-RLT depends on PSMA expression. Moreover, predictors of treatment response other than PSMA expression are under investigation. Therefore, the optimal patient population for PSMA-RLT remains unclear. This review provides an overview of the current status of theranostics for prostate cancer, focusing on PSMA ligands. In addition, we summarize various findings regarding the efficacy and problems of PSMA-RLT and discuss the optimal patient for PSMA-RLT.
Fuzzy Logic-Based System for Identifying the Severity of Diabetic Macular Edema from OCT B-Scan Images Using DRIL, HRF, and Cystoids
Authors: Tripathi Aditya , Kumar Preetham , Tulsani Akshat , Chakrapani Pavithra Kodiyalbail , Maiya Geetha , Bhandary Sulatha V. , Mayya Veena , Pathan Sameena , Achar Raghavendra , Acharya U. Rajendra
Published: August 2023

Diabetic Macular Edema (DME) is a severe ocular complication commonly found in patients with diabetes. The condition can precipitate a significant drop in VA and, in extreme cases, may result in irreversible vision loss. Optical Coherence Tomography (OCT), a technique that yields high-resolution retinal images, is often employed by clinicians to assess the extent of DME in patients. However, the manual interpretation of OCT B-scan images for DME identification and severity grading can be error-prone, with false negatives potentially resulting in serious repercussions. In this paper, we investigate an Artificial Intelligence (AI) driven system that offers an end-to-end automated model, designed to accurately determine DME severity using OCT B-Scan images. This model operates by extracting specific biomarkers such as Disorganization of Retinal Inner Layers (DRIL), Hyper Reflective Foci (HRF), and cystoids from the OCT image, which are then utilized to ascertain DME severity. The rules guiding the fuzzy logic engine are derived from contemporary research in the field of DME and its association with various biomarkers evident in the OCT image. The proposed model demonstrates high efficacy, identifying images with DRIL with 93.3% accuracy and successfully segmenting HRF and cystoids from OCT images with dice similarity coefficients of 91.30% and 95.07% respectively. This study presents a comprehensive system capable of accurately grading DME severity using OCT B-scan images, serving as a potentially invaluable tool in the clinical assessment and treatment of DME.
Association of the EPAS1 rs7557402 Polymorphism with Hemodynamically Significant Patent Ductus Arteriosus Closure Failure in Premature Newborns under Pharmacological Treatment with Ibuprofen
Authors: Rogel-Ayala Diana G. , Muñoz-Medina José Esteban , Vicente-Juárez Valeria Dejanira , Grether-González Patricia , Morales-Barquet Deneb Algedi , Martínez-García Alfonso de Jesús , Echaniz-Aviles María Olga Leticia , Sevilla-Montoya Rosalba , Martínez-Juárez Alejandro , Artega-Vázquez Jazmin , Angeles-Martínez Javier , Vargas-Alarcón Gilberto , Hidalgo-Bravo Alberto , Monroy-Muñoz Irma Eloisa
Published: August 2023

Patent ductus arteriosus (PDA) is frequent in preterm newborns, and its incidence is inversely associated with the degree of prematurity. The first choice of pharmacological treatment is ibuprofen. Several genes, including EPAS1, have been proposed as probable markers associated with a genetic predisposition for the development of PDA in preterm infants. EPAS 1 NG_016000.1:g.84131C>G or rs7557402 has been reported to be probably benign and associated with familial erythrocytosis by the Illumina Clinical Services Laboratory. Other variants of EPAS1 have been previously reported to be benign for familial erythrocytosis because they decrease gene function and are positive for familial erythrocytosis because the overexpression of EPAS1 is a key factor in uncontrolled erythrocyte proliferation. However, this could be inconvenient for ductal closure, since for this process to occur, cell proliferation, migration, and differentiation should take place, and a decrease in EPAS1 gene activity would negatively affect these processes. Single-nucleotide polymorphisms (SNPs) in EPAS1 and TFAP2B genes were searched with high-resolution melting and Sanger sequencing in blood samples of preterm infants with hemodynamically significant PDA treated with ibuprofen at the National Institute of Perinatology. The variant rs7557402, present in the EPAS1 gene eighth intron, was associated with a decreased response to treatment (p = 0.007, OR = 3.53). The SNP rs7557402 was associated with an increased risk of pharmacological treatment failure. A probable mechanism involved could be the decreased activity of the product of the EPAS1 gene.
Depression and Malnutrition for Prediction of Mortality after Transcatheter Aortic Valve Replacement: A Registry Study of a Tertiary Referral Hospital
Authors: Geers Jolien , Van den Bussche Karen , Vandeloo Bert , Kimenai Dorien M. , Van Loo Ines , Michiels Vincent , Plein Daniele , Beckers Stefan , Muylle Teun , Lieten Siddhartha , Cosyns Bernard , Compté Nathalie , Argacha Jean-François
Published: August 2023

Moderate to severe frailty is a predictor of a poor outcome after transcatheter aortic valve replacement (TAVR), but little is known about the prognostic importance of different geriatric frailty markers in an overall fit or pre-frail geriatric population undergoing TAVR. This retrospective study aimed to examine the incremental value of adding patient frailty markers to conventional surgical risk score to predict all-cause mortality in relatively fit elderly patients undergoing TAVR. Overall patient frailty was assessed using the comprehensive geriatric assessment frailty index (CGA-FI). Multivariable Cox regression models were used to evaluate relationships of different geriatric frailty markers with all-cause mortality and single and combined frailty models were compared to a baseline model that included EuroSCORE II factors. One hundred relatively fit geriatric patients (84 ± 4 years old, mean CGA-FI 0.14 ± 0.05) were included, and 28% died during a median follow-up of 24 months. After adjustment, risk of depression (geriatric depression scale 15 (GDS-15)) and malnutrition remained significantly associated with all-cause mortality (HR 4.381, 95% CI 1.787–10.743; p = 0.001 and HR 3.076, 95% CI 1.151–8.217; p = 0.025, respectively). A combined frailty marker model including both GDS-15 and malnutrition on top of EuroSCORE II improved the discriminative ability to predict all-cause mortality (change in c-index: + 0.044). Screening for those frailty markers on top of the traditionally used EuroSCORE II may improve risk stratification and prognosis in relatively fit geriatric patients undergoing TAVR.
Clinical Applications of Endobronchial Ultrasound (EBUS) Scope: Challenges and Opportunities
Authors: Biondini Davide , Tinè Mariaenrica , Semenzato Umberto , Daverio Matteo , Scalvenzi Francesca , Bazzan Erica , Turato Graziella , Damin Marco , Spagnolo Paolo
Published: August 2023

Endobronchial Ultrasound (EBUS) has been widely used to stage lung tumors and to diagnose mediastinal diseases. In the last decade, this procedure has evolved in several technical aspects, with new tools available to optimize tissue sampling and to increase its diagnostic yield, like elastography, different types of needles and, most recently, miniforceps and cryobiopsy. Accordingly, the indications for the use of the EBUS scope into the airways to perform the Endobronchial Ultrasound–TransBronchial Needle Aspiration (EBUS-TBNA) has also extended beyond the endobronchial and thoracic boundaries to sample lesions from the liver, left adrenal gland and retroperitoneal lymph nodes via the gastroesophageal tract, performing the Endoscopic UltraSound with Bronchoscope-guided Fine Needle Aspiration (EUS-B-FNA). In this review, we summarize and critically discuss the main indication for the use of the EBUS scope, even the more uncommon, to underline its utility and versatility in clinical practice.
A Probabilistic Result on Impulsive Noise Reduction in Topological Data Analysis through Group Equivariant Non-Expansive Operators
Authors: Frosini Patrizio , Gridelli Ivan , Pascucci Andrea
Published: August 2023

In recent years, group equivariant non-expansive operators (GENEOs) have started to find applications in the fields of Topological Data Analysis and Machine Learning. In this paper we show how these operators can be of use also for the removal of impulsive noise and to increase the stability of TDA in the presence of noisy data. In particular, we prove that GENEOs can control the expected value of the perturbation of persistence diagrams caused by uniformly distributed impulsive noise, when data are represented by L-Lipschitz functions from R to R.
Entropy: An Inspiring Tool for Characterizing Turbulence–Combustion Interaction in Swirling Flames via Direct Numerical Simulations of Non-Premixed and Premixed Flames
Authors: Su Jingke , Liu Anxiong , Xiao Hualin , Luo Kun , Fan Jianren
Published: August 2023

This article focuses on entropy generation in the combustion field, which serves as a useful indicator to quantify the interaction between turbulence and combustion. The study is performed on the direct numerical simulations (DNS) of high pressure non-premixed and premixed swirling flames. By analyzing the entropy generation in thermal transport, mass transport, and chemical reactions, it is found that the thermal transport, driven by the temperature gradient, plays a dominant role. The enstrophy transport analysis reveals that the responses of individual terms to combustion can be measured by the entropy: the vortex stretching and the dissipation terms increase monotonically with the increasing entropy. In high entropy regions, the turbulence behaves as the “cigar shaped” state in the non-premixed flame, while as the axisymmetric state in the premixed flame. A substantial increase in the normal Reynolds stress with the entropy is observed. This is due to the competition between two terms promoted by the entropy, i.e., the velocity–pressure gradient correlation term and the shear production term. As a result, the velocity–pressure gradient correlation tends to isotropize turbulence by transferring energy increasingly from the largest streamwise component to the other smaller normal components of Reynolds stress and is dominated by the fluctuating pressure gradient that increases along the entropy. The shear production term increases with the entropy due to the upgrading alignment of the eigenvectors of strain rate and Reynolds stress tensors.
Person Re-Identification Method Based on Dual Descriptor Feature Enhancement
Authors: Lin Ronghui , Wang Rong , Zhang Wenjing , Wu Ao , Sun Yang , Bi Yihan
Published: August 2023

Person re-identification is a technology used to identify individuals across different cameras. Existing methods involve extracting features from an input image and using a single feature for matching. However, these features often provide a biased description of the person. To address this limitation, this paper introduces a new method called the Dual Descriptor Feature Enhancement (DDFE) network, which aims to emulate the multi-perspective observation abilities of humans. The DDFE network uses two independent sub-networks to extract descriptors from the same person image. These descriptors are subsequently combined to create a comprehensive multi-view representation, resulting in a significant improvement in recognition performance. To further enhance the discriminative capability of the DDFE network, a carefully designed training strategy is employed. Firstly, the CurricularFace loss is introduced to enhance the recognition accuracy of each sub-network. Secondly, the DropPath operation is incorporated to introduce randomness during sub-network training, promoting difference between the descriptors. Additionally, an Integration Training Module (ITM) is devised to enhance the discriminability of the integrated features. Extensive experiments are conducted on the Market1501 and MSMT17 datasets. On the Market1501 dataset, the DDFE network achieves an mAP of 91.6% and a Rank1 of 96.1%; on the MSMT17 dataset, the network achieves an mAP of 69.9% and a Rank1 of 87.5%. These outcomes outperform most SOTA methods, highlighting the significant advancement and effectiveness of the DDFE network.
Thermodynamical versus Logical Irreversibility: A Concrete Objection to Landauer’s Principle
Authors: Lairez Didier
Published: August 2023

Landauer’s principle states that the logical irreversibility of an operation, such as erasing one bit, whatever its physical implementation, necessarily implies its thermodynamical irreversibility. In this paper, a very simple counterexample of physical implementation (that uses a two-to-one relation between logic and thermodynamic states) is given that allows one bit to be erased in a thermodynamical quasistatic manner (i.e., one that may tend to be reversible if slowed down enough).
Applications Enabled by FPGA-Based Technology
Authors: Guerrieri Andrea , Upegui Andres , Gantel Laurent
Published: August 2023

Field-programmable gate array (FPGA) technology represents a potential alternative to classical CPUs and GPUs in the post-Moore era from edge computing to data centers [...]
Tunnel Lining Crack Recognition Algorithm Integrating SK Attention and Cascade Neural Network
Authors: Liu Keqiang , Zhong Shisheng , Wang Rui , Zhou Peiying , Zhao Xiaodong , Liu Xingen
Published: August 2023

Cracks are one of the main types of tunnel-lining defects. At present, there are no particularly good methods for identifying tunnel-lining cracks. The methods that are used are associated with problems such as poor robustness, low detection efficiency, and inconsistency in defect identification. Vision-based crack identification algorithms that use images of tunnel-lining cracks are also affected by problems such as weak features, irregular shapes, random development, and small proportions. In light of this, we propose in this paper a neural network that integrates U-net and FPN (feature pyramid network) pyramid structure characteristics. Because of its ability to output deep feature information, an SK (selective kernel) attention mechanism was integrated to increase the weight of effective feature regions and improve the detection accuracy of feature maps. An RPN (region proposal network) regional detection network was used for multi-scale regional screening, and non-maximum suppression was used to eliminate repeated anchor frames between different regions. The continuity of cracks was determined using adaptive regional expansion. The region segmentation network was also combined with multi-scale feature maps. Finally, the segmentation results for regions of fine features could be mapped to the whole image to identify cracks, thereby solving the problem that arises when textural features of cracks are weak and cannot be accurately identified. For testing purposes, photos of tunnel-lining crack defects were used. The algorithm described in this paper was able to combine deep and shallow features to identify more abundant crack features, and the recognition accuracy of the crack classification network reached 98.51%. With respect to crack segmentation, the algorithm’s segmentation accuracy reached 94.55%, and its single processing time reached 60.76 ms, indicating more accurate and efficient segmentation performance, compared with FCNs (fully convolutional networks) and classical U-net networks.
Development of Carbon Nanotube Yarn Supercapacitors and Energy Storage for Integrated Structural Health Monitoring
Authors: Binfaris Abdulrahman S. , Zestos Alexander G. , Abot Jandro L.
Published: August 2023

Developing efficient, sustainable, and high-performance energy storage systems is essential for advancing various industries, including integrated structural health monitoring. Carbon nanotube yarn (CNTY) supercapacitors have the potential to be an excellent solution for this purpose because they offer unique material properties such as high capacitance, electrical conductivity, and energy and power densities. The scope of the study included fabricating supercapacitors using various materials and characterizing them to determine the capacitive properties, energy, and power densities. Experimental studies were conducted to investigate the energy density and power density behavior of CNTYs embedded in various electrochemical-active matrices to monitor the matrices’ power process and the CNTY supercapacitors’ life-cyclic response. The results showed that the CNTY supercapacitors displayed excellent capacitive behavior, with nearly rectangular CV curves across a range of scan rates. The energy density and power density of the supercapacitors fluctuated between a minimum of 3.89 Wh/kg and 8 W/kg while the maximum was between 6.46 Wh/kg and 13.20 W/kg. These CNTY supercapacitors are being tailored to power CNTY sensors integrated into a variety of structures that could monitor damage, strain, temperature, and others.
Modeling of Specific Energy in the Gear Honing Process
Authors: Wang Fuwei , Chen Yuanlong , Gao Yang , Liang Yuan , Wang Ruimin , Zhao Defang
Published: August 2023

Gear honing is a cost-efficient method for the finishing of hardened gears in which material removal is realized through honing wheel and workpiece gear interactions. There are a number of indicators used for evaluating the degrees of these interactions, among which specific energy is a more appropriate one than the others since it is capable of quantifying the amount of energy consumption during the material removal process. Nevertheless, models for the prediction of specific energy in gear honing have not been thoroughly investigated. This work presents a theoretical model of specific energy to quantitatively evaluate the material removal efficiency in the external gear honing process. To develop the model, an analytical material removal rate and a honing force model are proposed, and the feasibility of the proposed model is validated against external gear honing experiments. The correlations of specific energy with processing parameters are investigated and the material removal efficiency scores of external gear honing and grinding are compared and discussed. The present approach enables an in-depth understanding of the abrasive–material interactions in the gear honing process and the effects of processing parameters on material removal efficiency.
Low-Emission Waste-to-Energy Method of Liquid Fuel Combustion with a Mixture of Superheated Steam and Carbon Dioxide
Authors: Sadkin Ivan , Mukhina Mariia , Kopyev Evgeny , Sharypov Oleg , Alekseenko Sergey
Published: August 2023

Waste-to-energy approaches, aimed at using cheap energy carriers (oil production and refining waste, etc.), require the creation of new technologies with high energy efficiency and low emissions. One of the environmentally friendly methods is a superheated steam injection (SIM) into the combustion zone. At the same time, trends in CO2 reduction and recycling make carbon dioxide more attractive to use together with, or instead of, steam. This paper experimentally investigated the possibility of upgrading SIM to steam and the carbon dioxide injection method (SCIM) or the carbon dioxide injection method (CIM), where superheated steam and carbon dioxide are supplied together or completely replaced by CO2. In the example of diesel fuel, the characteristics of the combustion of liquid hydrocarbons in the presence of a mixture of superheated steam with CO2 in a spray burner are obtained and compared. It shows that a high completeness of fuel combustion is observed for all the studied modes. The analysis of combustion product composition demonstrates that when replacing the superheated steam with carbon dioxide, the levels of CO and NOx in the combustion products increase by 25%. All the investigated regimes comply with the EN:267 standard. The results obtained show that it is possible to realize SCIM and CIM approaches for waste-to-energy with the use of CO2.
Drilling Conditions Classification Based on Improved Stacking Ensemble Learning
Authors: Yang Xinyi , Zhang Yanlong , Zhou Detao , Ji Yong , Song Xianzhi , Li Dayu , Zhu Zhaopeng , Wang Zheng , Liu Zihao
Published: August 2023

The classification of drilling conditions is a crucial task in the drilling process, playing a vital role in improving drilling efficiency and reducing costs. In this study, we propose an improved stacking ensemble learning algorithm with the objective of enhancing the performance of drilling conditions classification. Additionally, this algorithm aims to have a positive impact on automated drilling time estimation and the continuous improvement of efficiency. In our experimental setup, we employed various base learners, such as random forests, support vector machine, and the K-nearest neighbors algorithm, as initial models for the task of drilling conditions classification. To improve the model’s expressive power and feature relevance specifically for this task, we enhanced the meta-model component of the stacking algorithm by incorporating feature engineering techniques. The experimental results show that the improved ensemble learning algorithm achieves an accuracy and recall rate of 97% and 98%, respectively. Through continuous improvement in drilling operations, the average sliding time is reduced by 21.1%, and the average Rate of Penetration (ROP) is increased by 15.65%. This research holds significant importance for engineering practice in the drilling industry, providing robust support for optimizing and enhancing the drilling process.
Load Frequency Control Using the Particle Swarm Optimisation Algorithm and PID Controller for Effective Monitoring of Transmission Line
Authors: Ogar Vincent N. , Hussain Sajjad , Gamage Kelum A. A.
Published: August 2023

Load frequency control (LFC) plays a critical role in maintaining the stability and reliability of the power system. With the increasing integration of renewable energy sources and the growth of complex interconnected grids, efficient and robust LFC strategies are in high demand. In recent years, the combination of particle swarm optimisation (PSO) and proportional-integral-derivative (PID) controllers, known as PSP-PID, has been used as a promising approach to enhance the performance of LFC systems. This article focuses on modelling, simulation, optimisation, advanced control techniques, expert knowledge, and iterative refinement of the power system to help achieve suitable PID settings that provide reliable control of the load frequency in the transmission line. The performance indices of the proposed algorithm are measured by the integral time absolute error (ITAE), which is 0.0005757 with 0.9994 Ki, 0.7741 Kp, and 0.1850 Kd. The model system dynamics are tested by varying the load frequency from 300 MW to 350 MW at a load variation of 0.2. The suggested controller algorithm is relatively reliable and accurate in power system management and protection load frequency control compared to conventional methods. This work can be improved by including more generating stations synchronised into a single network.
Facial Expressions of Urban Forest Visitors Jointly Exposed to Air Pollution and Regional Climate
Authors: Wang Xiaopei , Meng Lingquan , Liu Yifeng , Wei Hongxu
Published: August 2023

Urban forests have important functions to alleviate air pollution, adjust the regional climate, and promote visitors’ mental health and well-being. Humans’ perceptions towards both atmospheric particulate matter (PM) and meteorological factors can be a gauge for assessing the functional services of urban forests. The geographical locations of host cities experiencing urbanization could take part in effects on emotional states of forest visitors. In this study, a total of 6309 facial photos of urban forest visitors were obtained from social networks in 42 cities of mainland China. Happy, sad, and neutral emotions were rated as percent scores in 2020, when the same-day air pollutants, meteorological factors, and socioeconomic indicators were recorded. The positive emotional index (PEI) was calculated as the difference between happy scores and sad scores. The results reveal that severe air pollutants (jointly PM2.5 > 75 μg/m3, PM10 > 150 μg/m3, and AQI > 150) were more frequently found in cities in the northeastern and northern areas of China. The forest visitors in the northeastern cities showed higher happiness scores compared to the visitors in other regions. The Quasi-Poisson regression suggested that high scores of happiness were frequently disclosed in weathers with low PM10. High scores of sadness were regressed on exposure to cities with a low GDP per capita and low total retail sales but with a high GDP at low-longitudinal and high-latitudinal locations with low levels of PM2.5 pollution, relative humidity, and wind velocity and a high temperature. The happiness score and PEI showed high-value aggregations in mega-sized cities (population over 10 million), such as Beijing and Zhengzhou, and in a metro-sized city (population of 5–10 million in Langfang) from climate regions of China.
Towards Efficient Resource Allocation for Federated Learning in Virtualized Managed Environments
Authors: Nikolaidis Fotis , Symeonides Moysis , Trihinas Demetris
Published: August 2023

Federated learning (FL) is a transformative approach to Machine Learning that enables the training of a shared model without transferring private data to a central location. This decentralized training paradigm has found particular applicability in edge computing, where IoT devices and edge nodes often possess limited computational power, network bandwidth, and energy resources. While various techniques have been developed to optimize the FL training process, an important question remains unanswered: how should resources be allocated in the training workflow? To address this question, it is crucial to understand the nature of these resources. In physical environments, the allocation is typically performed at the node level, with the entire node dedicated to executing a single workload. In contrast, virtualized environments allow for the dynamic partitioning of a node into containerized units that can adapt to changing workloads. Consequently, the new question that arises is: how can a physical node be partitioned into virtual resources to maximize the efficiency of the FL process? To answer this, we investigate various resource allocation methods that consider factors such as computational and network capabilities, the complexity of datasets, as well as the specific characteristics of the FL workflow and ML backend. We explore two scenarios: (i) running FL over a finite number of testbed nodes and (ii) hosting multiple parallel FL workflows on the same set of testbed nodes. Our findings reveal that the default configurations of state-of-the-art cloud orchestrators are sub-optimal when orchestrating FL workflows. Additionally, we demonstrate that different libraries and ML models exhibit diverse computational footprints. Building upon these insights, we discuss methods to mitigate computational interferences and enhance the overall performance of the FL pipeline execution.
How I Manage Chronic Lymphocytic Leukemia
Authors: Nasnas Patrice , Cerchione Claudio , Musuraca Gerardo , Martinelli Giovanni , Ferrajoli Alessandra
Published: August 2023

Chronic lymphocytic leukemia (CLL), is a hematologic malignancy characterized by the uncontrolled proliferation of mature B lymphocytes. CLL is the most prevalent leukemia in Western countries. Its presentation can range from asymptomatic with the incidental finding of absolute lymphocytosis on a routine blood test, to symptomatic disease requiring immediate intervention. Prognosis of the disease is defined by the presence or absence of specific mutations such as TP53, chromosomal abnormalities such as del(17p), a type of IGHV mutational status, and elevation of B2M and LDH. Treatment of CLL in the United States and Europe has evolved over the recent years thanks to the development of targeted therapies. The standard of care has shifted from traditional chemoimmunotherapy approaches to targeted therapies including Bruton tyrosine kinase inhibitors (BTKis) and BCL2 inhibitors, administered either as monotherapy or in combination with CD20 monoclonal antibodies. Several clinical trials have also recently evaluated combinations of BTKi and venetoclax and showed the combination to be well tolerated and able to induce deep remissions. Targeted therapies have a good safety profile overall; however, they also have unique toxicities that are important to recognize. Diarrhea, fatigue, arthralgia, infections, cytopenias, bleeding, and cardiovascular toxicities (including atrial fibrillation, ventricular arrhythmias, and hypertension) are the adverse events (AEs) commonly associated with BTKis. Initiation of therapy with venetoclax requires close monitoring because of the risk for tumor lysis syndrome associated with this agent, particularly in patients with a high disease burden. Development of newer target therapies is ongoing and the therapeutic landscape in CLL is expanding rapidly.
Real-World Effectiveness in Hypertension and Hyperlipidemia Collaborative Management between Pharmacies and Primary Care in Portugal: A Multicenter Pragmatic Controlled Trial (USFarmácia®)
Authors: Costa Suzete , Biscaia José Luís , Horta Maria Rute , Romano Sónia , Guerreiro José , Heudtlass Peter , Cary Maria , Romão Mariana , Teixeira Rodrigues António , Miranda Ana , Martins Ana Paula , Bento Ana Sofia , Pereira João , Mateus Céu , Helling Dennis K.
Published: August 2023

There is evidence of the efficacy of collaborative health interventions with pharmacies and primary care providers but little of its real-world effectiveness. We aimed to assess the effectiveness and discuss the design and challenges of hypertension and hyperlipidemia management between pharmacies and primary care providers using real-world data exchange between providers and experimental bundled payment. This was a pragmatic, quasi-experimental controlled trial. We collected patient-level data from primary care prescription claims and Electronic Medical Record databases, a pharmacy claims database, and patient telephone surveys at several time points. The primary outcomes were changes in blood pressure and total cholesterol. We used matched controls with difference-in-differences estimators in a Generalized Linear Model (GLM) and controlled interrupted time series (CITS). We collected additional data for economic and qualitative studies. A total of 6 Primary Care Units, 20 pharmacies, and 203 patients entered the study. We were not able to observe significant differences in the effect of intervention vs. control. We experienced challenges that required creative strategies. This real-world trial was not able to show effectiveness, likely due to limitations in the primary care technology which affected the sample size. It offers, however, valuable lessons on methods, strategies, and data sources, paving the way for more real-world effectiveness trials to advance value-based healthcare.
Migraine Treatment: Towards New Pharmacological Targets
Authors: Silvestro Marcello , Iannone Luigi Francesco , Orologio Ilaria , Tessitore Alessandro , Tedeschi Gioacchino , Geppetti Pierangelo , Russo Antonio
Published: August 2023

Migraine is a debilitating neurological condition affecting millions of people worldwide. Until a few years ago, preventive migraine treatments were based on molecules with pleiotropic targets, developed for other indications, and discovered by serendipity to be effective in migraine prevention, although often burdened by tolerability issues leading to low adherence. However, the progresses in unravelling the migraine pathophysiology allowed identifying novel putative targets as calcitonin gene-related peptide (CGRP). Nevertheless, despite the revolution brought by CGRP monoclonal antibodies and gepants, a significant percentage of patients still remains burdened by an unsatisfactory response, suggesting that other pathways may play a critical role, with an extent of involvement varying among different migraine patients. Specifically, neuropeptides of the CGRP family, such as adrenomedullin and amylin; molecules of the secretin family, such as pituitary adenylate cyclase-activating peptide (PACAP) and vasoactive intestinal peptide (VIP); receptors, such as transient receptor potential (TRP) channels; intracellular downstream determinants, such as potassium channels, but also the opioid system and the purinergic pathway, have been suggested to be involved in migraine pathophysiology. The present review provides an overview of these pathways, highlighting, based on preclinical and clinical evidence, as well as provocative studies, their potential role as future targets for migraine preventive treatment.
Optimizing the First Step of the Biocatalytic Process for Green Leaf Volatiles Production: Lipase-Catalyzed Hydrolysis of Three Vegetable Oils
Authors: Faillace Eva , Brunini-Bronzini de Caraffa Virginie , Mariani Magali , Berti Liliane , Maury Jacques , Vincenti Sophie
Published: August 2023

Green leaf volatiles (GLVs), including short chain volatile aldehydes, are widely used in the flavor and food industries because of their fresh aroma. To meet the growing demand for natural GLVs with high added value, the use of biocatalytic processes appears as a relevant application. In such processes, vegetable oils are bioconverted into GLVs. First, the triacylglycerols of the oils are hydrolyzed by a lipase. Then, the free polyunsaturated fatty acids are converted by a lipoxygenase. Finally, volatile C6 or C9 aldehydes and 9- or 12-oxoacids are produced with a hydroperoxide lyase. Optimization of each biocatalytic step must be achieved to consider a scale-up. In this study, three oils (sunflower, hempseed, and linseed oils) and three lipases (Candida rugosa, Pseudomonas fluorescens, and Rhizomucor miehei lipases) have been tested to optimize the first step of the process. The experimental design and response surface methodology (RSM) were used to determine the optimal hydrolysis conditions for each oil. Five factors were considered, i.e., pH, temperature, reaction duration, enzyme load, and oil/aqueous ratio of the reaction mixture. Candida rugosa lipase was selected as the most efficient enzyme to achieve conversion of 96 ± 1.7%, 97.2 ± 3.8%, and 91.8 ± 3.2%, respectively, for sunflower, hempseed, and linseed oils under the defined optimized reaction conditions.
Benzenesulfonamide Analogs: Synthesis, Anti-GBM Activity and Pharmacoprofiling
Authors: Murugesan Akshaya , Konda Mani Saravanan , Thiyagarajan Ramesh , Palanivel Suresh , Gurbanov Atash V. , Zubkov Fedor I. , Kandhavelu Meenakshisundaram
Published: August 2023

The tropomyosin receptor kinase A (TrkA) family of receptor tyrosine kinases (RTKs) emerge as a potential target for glioblastoma (GBM) treatment. Benzenesulfonamide analogs were identified as kinase inhibitors possessing promising anticancer properties. In the present work, four known and two novel benzenesulfonamide derivatives were synthesized, and their inhibitory activities in TrkA overexpressing cells, U87 and MEF cells were investigated. The cytotoxic effect of benzenesulfonamide derivatives and cisplatin was determined using trypan blue exclusion assays. The mode of interaction of benzenesulfonamides with TrkA was predicted by docking and structural analysis. ADMET profiling was also performed for all compounds to calculate the drug likeness property. Appropriate QSAR models were developed for studying structure–activity relationships. Compound 4-[2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl]-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfon-amide (AL106) and 4-[2-(1,3-dioxo-1,3-dihydro-2H-inden-2-ylidene)hydrazinyl]-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfonamide (AL107) showed acceptable binding energies with the active sites for human nerve growth factor receptor, TrkA. Here, AL106 was identified as a potential anti-GBM compound, with an IC50 value of 58.6 µM with a less toxic effect in non-cancerous cells than the known chemotherapeutic agent, cisplatin. In silico analysis indicated that AL106 formed prominent stabilizing hydrophobic interactions with Tyr359, Ser371, Ile374 and charged interactions with Gln369 of TrkA. Furthermore, in silico analysis of all benzenesulfonamide derivatives revealed that AL106 has good pharmacokinetics properties, drug likeness and toxicity profiles, suggesting the compound may be suitable for clinical trial. Thus, benzenesulfonamide analog, AL106 could potentially induce GBM cell death through its interaction with TrkA and might be an attractive strategy for developing a drug targeted therapy to treat glioblastoma.
New Highly Selective BACE1 Inhibitors and Their Effects on Dendritic Spine Density In Vivo
Authors: Pratsch Katrin , Unemura Chie , Ito Mana , Lichtenthaler Stefan F. , Horiguchi Naotaka , Herms Jochen
Published: August 2023

β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) is considered a therapeutic target to combat Alzheimer’s disease by reducing β-amyloid in the brain. To date, all clinical trials involving the inhibition of BACE1 have been discontinued due to a lack of efficacy or undesirable side effects such as cognitive worsening. The latter could have been the result of the inhibition of BACE at the synapse where it is expressed in high amounts. We have previously shown that prolonged inhibition of BACE interferes with structural synaptic plasticity, most likely due to the diminished processing of the physiological BACE substrate Seizure protein 6 (Sez6) which is exclusively processed by BACE1 and is required for dendritic spine plasticity. Given that BACE1 has significant amino acid similarity with its homolog BACE2, the inhibition of BACE2 may cause some of the side effects, as most BACE inhibitors do not discriminate between the two. In this study, we used newly developed BACE inhibitors that have a different chemotype from previously developed inhibitors and a high selectivity for BACE1 over BACE2. By using longitudinal in vivo two-photon microscopy, we investigated the effect on dendritic spine dynamics of pyramidal layer V neurons in the somatosensory cortex in mice treated with highly selective BACE1 inhibitors. Treatment with those inhibitors showed a reduction in soluble Sez6 (sSez6) levels to 27% (elenbecestat, Biogen, Eisai Co., Ltd., Tokyo, Japan), 17% (Shionogi compound 1) and 39% (Shionogi compound 2), compared to animals fed with vehicle pellets. We observed a significant decrease in the number of dendritic spines with Shionogi compound 1 after 21 days of treatment but not with Shionogi compound 2 or with elenbecestat, which did not show cognitive worsening in clinical trials. In conclusion, highly selective BACE1 inhibitors do alter dendritic spine density similar to non-selective inhibitors if soluble (sSez6) levels drop too much. Low-dose BACE1 inhibition might be reasonable if dosing is carefully adjusted to the amount of Sez6 cleavage, which can be easily monitored during the first week of treatment.
Molecular Modeling Unveils the Effective Interaction of B-RAF Inhibitors with Rare B-RAF Insertion Variants
Authors: Scaini Maria Chiara , Piccin Luisa , Bassani Davide , Scapinello Antonio , Pellegrini Stefania , Poggiana Cristina , Catoni Cristina , Tonello Debora , Pigozzo Jacopo , Dall’Olmo Luigi , Rosato Antonio , Moro Stefano , Chiarion-Sileni Vanna , Menin Chiara
Published: August 2023

The Food and Drug Administration (FDA) has approved MAPK inhibitors as a treatment for melanoma patients carrying a mutation in codon V600 of the BRAF gene exclusively. However, BRAF mutations outside the V600 codon may occur in a small percentage of melanomas. Although these rare variants may cause B-RAF activation, their predictive response to B-RAF inhibitor treatments is still poorly understood. We exploited an integrated approach for mutation detection, tumor evolution tracking, and assessment of response to treatment in a metastatic melanoma patient carrying the rare p.T599dup B-RAF mutation. He was addressed to Dabrafenib/Trametinib targeted therapy, showing an initial dramatic response. In parallel, in-silico ligand-based homology modeling was set up and performed on this and an additional B-RAF rare variant (p.A598_T599insV) to unveil and justify the success of the B-RAF inhibitory activity of Dabrafenib, showing that it could adeptly bind both these variants in a similar manner to how it binds and inhibits the V600E mutant. These findings open up the possibility of broadening the spectrum of BRAF inhibitor-sensitive mutations beyond mutations at codon V600, suggesting that B-RAF V600 WT melanomas should undergo more specific investigations before ruling out the possibility of targeted therapy.
Unravelling the Collective Calcium Dynamics of Physiologically Aged Astrocytes under a Hypoxic State In Vitro
Authors: Mitroshina Elena V. , Krivonosov Mikhail I. , Pakhomov Alexander M. , Yarullina Laysan E. , Gavrish Maria S. , Mishchenko Tatiana A. , Yarkov Roman S. , Vedunova Maria V.
Published: August 2023

Astrocytes serve many functions in the brain related to maintaining nerve tissue homeostasis and regulating neuronal function, including synaptic transmission. It is assumed that astrocytes are crucial players in determining the physiological or pathological outcome of the brain aging process and the development of neurodegenerative diseases. Therefore, studies on the peculiarities of astrocyte physiology and interastrocytic signaling during aging are of utmost importance. Calcium waves are one of the main mechanisms of signal transmission between astrocytes, and in the present study we investigated the features of calcium dynamics in primary cultures of murine cortical astrocytes in physiological aging and hypoxia modeling in vitro. Specifically, we focused on the assessment of calcium network dynamics and the restructuring of the functional network architecture in primary astrocytic cultures. Calcium imaging was performed on days 21 (“young” astrocyte group) and 150 (“old” astrocyte group) of cultures’ development in vitro. While the number of active cells and frequency of calcium events were decreased, we observed a reduced degree of correlation in calcium dynamics between neighboring cells, which was accompanied by a reduced number of functionally connected cells with fewer and slower signaling events. At the same time, an increase in the mRNA expression of anti-apoptotic factor Bcl-2 and connexin 43 was observed in “old” astrocytic cultures, which can be considered as a compensatory response of cells with a decreased level of intercellular communication. A hypoxic episode aggravates the depression of the connectivity of calcium dynamics of “young” astrocytes rather than that of “old” ones.
New Insights into the Reparative Angiogenesis after Myocardial Infarction
Authors: Martín-Bórnez Marta , Falcón Débora , Morrugares Rosario , Siegfried Geraldine , Khatib Abdel-Majid , Rosado Juan A. , Galeano-Otero Isabel , Smani Tarik
Published: August 2023

Myocardial infarction (MI) causes massive loss of cardiac myocytes and injury to the coronary microcirculation, overwhelming the limited capacity of cardiac regeneration. Cardiac repair after MI is finely organized by complex series of procedures involving a robust angiogenic response that begins in the peri-infarcted border area of the infarcted heart, concluding with fibroblast proliferation and scar formation. Efficient neovascularization after MI limits hypertrophied myocytes and scar extent by the reduction in collagen deposition and sustains the improvement in cardiac function. Compelling evidence from animal models and classical in vitro angiogenic approaches demonstrate that a plethora of well-orchestrated signaling pathways involving Notch, Wnt, PI3K, and the modulation of intracellular Ca2+ concentration through ion channels, regulate angiogenesis from existing endothelial cells (ECs) and endothelial progenitor cells (EPCs) in the infarcted heart. Moreover, cardiac repair after MI involves cell-to-cell communication by paracrine/autocrine signals, mainly through the delivery of extracellular vesicles hosting pro-angiogenic proteins and non-coding RNAs, as microRNAs (miRNAs). This review highlights some general insights into signaling pathways activated under MI, focusing on the role of Ca2+ influx, Notch activated pathway, and miRNAs in EC activation and angiogenesis after MI.
EP300 as a Molecular Integrator of Fibrotic Transcriptional Programs
Authors: Rubio Karla , Molina-Herrera Alejandro , Pérez-González Andrea , Hernández-Galdámez Hury Viridiana , Piña-Vázquez Carolina , Araujo-Ramos Tania , Singh Indrabahadur
Published: August 2023

Fibrosis is a condition characterized by the excessive accumulation of extracellular matrix proteins in tissues, leading to organ dysfunction and failure. Recent studies have identified EP300, a histone acetyltransferase, as a crucial regulator of the epigenetic changes that contribute to fibrosis. In fact, EP300-mediated acetylation of histones alters global chromatin structure and gene expression, promoting the development and progression of fibrosis. Here, we review the role of EP300-mediated epigenetic regulation in multi-organ fibrosis and its potential as a therapeutic target. We discuss the preclinical evidence that suggests that EP300 inhibition can attenuate fibrosis-related molecular processes, including extracellular matrix deposition, inflammation, and epithelial-to-mesenchymal transition. We also highlight the contributions of small molecule inhibitors and gene therapy approaches targeting EP300 as novel therapies against fibrosis.