bluuebunny/crossref_metadata_2025 huggingface dataset:
VulEye: A Novel Graph Neural Network Vulnerability Detection Approach for PHP Application
Authors: Lin Chun , Xu Yijia , Fang Yong , Liu Zhonglin
Published: January 2023

Following advances in machine learning and deep learning processing, cyber security experts are committed to creating deep intelligent approaches for automatically detecting software vulnerabilities. Nowadays, many practices are for C and C++ programs, and methods rarely target PHP application. Moreover, many of these methods use LSTM (Long Short-Term Memory) but not GNN (Graph Neural Networks) to learn the token dependencies within the source code through different transformations. That may lose a lot of semantic information in terms of code representation. This article presents a novel Graph Neural Network vulnerability detection approach, VulEye, for PHP applications. VulEye can assist security researchers in finding vulnerabilities in PHP projects quickly. VulEye first constructs the PDG (Program Dependence Graph) of the PHP source code, slices PDG with sensitive functions contained in the source code into sub-graphs called SDG (Sub-Dependence Graph), and then makes SDG the model input to train with a Graph Neural Network model which contains three stack units with a GCN layer, Top-k pooling layer, and attention layer, and finally uses MLP (Multi-Layer Perceptron) and softmax as a classifier to predict if the SDG is vulnerable. We evaluated VulEye on the PHP vulnerability test suite in Software Assurance Reference Dataset. The experiment reports show that the best macro-average F1 score of the VulEye reached 99% in the binary classification task and 95% in the multi-classes classification task. VulEye achieved the best result compared with the existing open-source vulnerability detection implements and other state-of-art deep learning models. Moreover, VulEye can also locate the precise area of the flaw, since our SDG contains code slices closely related to vulnerabilities with a key triggering sensitive/sink function.
Balanced Loss Function for Accurate Surface Defect Segmentation
Authors: Xie Zhouyang , Shu Chang , Fu Yan , Zhou Junlin , Chen Duanbing
Published: January 2023

The accurate image segmentation of surface defects is challenging for modern convolutional neural networks (CNN)-based segmentation models. This paper identifies that loss imbalance is a critical problem in segmentation accuracy improvement. The loss imbalance problem includes: label imbalance, which impairs the accuracy on less represented classes; easy–hard example imbalance, which misleads the focus of optimization on less valuable examples; and boundary imbalance, which involves an unusually large loss value at the defect boundary caused by label confusion. In this paper, a novel balanced loss function is proposed to address the loss imbalance problem. The balanced loss function includes dynamical class weighting, truncated cross-entropy loss and label confusion suppression to solve the three types of loss imbalance, respectively. Extensive experiments are performed on surface defect benchmarks and various CNN segmentation models in comparison with other commonly used loss functions. The balanced loss function outperforms the counterparts and brings accuracy improvement from 5% to 30%.
Interaction Design Based on Big Data Community Home Care Service Demand Levels
Authors: Jiang Fangyuan , Jang Wan-Sok , Pan Young-Hwan
Published: January 2023

Most of the contemporary models for meeting the majority of the needs of middle-aged and elderly people are community-based, in-home care. Therefore, this paper designs an Interaction model that can meet the need for a rich spiritual and cultural life of the elderly at home. First, the questionnaire content of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) sampling method was designed based on the content of community-based home care services. Then, using the CLHLS sampling method, the survey results of the home care group were collected to form a community of big data consisting of four types of home care service needs. Finally, the Interaction book model was designed based on the hierarchy of service needs obtained from Abraham Maslow’s hierarchy of needs classification method. The experimental results showed that the mean values of the target population’s ratings for the presentation and interface aesthetics of the Interaction mode were 4.34 and 4.19, respectively, the mean value for improving the learning effectiveness of the home-bound population was 4.57, and the mean value for their overall satisfaction was 4.31. It proves that the Interaction model is ideal for practice and can meet the learning needs of the elderly, at-home population from different service demand levels, thus solving the problem of education for the elderly.
A Novel Deep-Learning Model for Remote Driver Monitoring in SDN-Based Internet of Autonomous Vehicles Using 5G Technologies
Authors: Saleh Sherine Nagy , Fathy Cherine
Published: January 2023

The rapid advancement in the Internet of Things (IoT) and its integration with Artificial Intelligence (AI) techniques are expected to play a crucial role in future Intelligent Transportation Systems (ITS). Additionally, the continuous progress in the industry of autonomous vehicles will accelerate and increase their short adoption in smart cities to allow safe, sustainable and accessible trips for passengers in different public and private means of transportation. In this article, we investigate the adoption of 5G different technologies, mainly, the Software-Defined Networks (SDN) to support the communication requirements of delegation of control of level-2 autonomous vehicles to the Remote-Control Center (RCC) in terms of ultra-low delay and reliability. This delegation occurs upon the detection of a drowsy driver using our proposed deep-learning-based technique deployed at the edge to reduce the level of accidents and road congestion. The deep learning-based model was evaluated and produced higher accuracy, precision and recall when compared to other methods. The role of SDN is to implement network slicing to achieve the Quality of Service (QoS) level required in this emergency case. Decreasing the end-to-end delay required to provide feedback control signals back to the autonomous vehicle is the aim of deploying QoS support available in an SDN-based network. Feedback control signals are sent to remotely activate the stopping system or to switch the vehicle to direct teleoperation mode. The mininet-WiFi emulator is deployed to evaluate the performance of the proposed adaptive SDN framework, which is tailored to emulate radio access networks. Our simulation experiments conducted on realistic vehicular scenarios revealed significant improvement in terms of throughput and average Round-Trip Time (RTT).
Efficient Data Delivery Scheme for Large-Scale Microservices in Distributed Cloud Environment
Authors: Pham Van-Nam , Hossain Md. Delowar , Lee Ga-Won , Huh Eui-Nam
Published: January 2023

The edge computing paradigm has emerged as a new scope within the domain of the Internet of Things (IoT) by bringing cloud services to the network edge in order to construct distributed architectures. To efficiently deploy latency-sensitive and bandwidth-hungry IoT application services, edge computing paradigms make use of devices on the network periphery that are distributed and resource-constrained. On the other hand, microservice architectures are becoming increasingly popular for developing IoT applications owing to their maintainability and scalability advantages. Providing an efficient communication medium for large-scale microservice-based IoT applications constructed from small and independent services to cooperate to deliver value-added services remains a challenge. This paper introduces an event-driven communication medium that takes advantage of Edge–Cloud publish/subscribe brokers for microservice-based IoT applications at scale. Using the interaction model, the involved microservices can collaborate and exchange data through triggered events flexibly and efficiently without changing their underlying business logic. In the proposed model, edge brokers are grouped according to their similarities in event channels and the proximity of their geolocations, reducing the data delivery latency. Moreover, in the proposed system a technique is designed to construct a broker-based utility matrix with constraints in order to strike a balance between delay, relay traffic, and scalability while arranging brokers into proper clusters for efficient data delivery. Rigorous simulation results prove that the proposed publish/subscribe model can provide an efficient interaction medium for microservice-based IoT applications to collaborate and exchange data with low latency, modest relay traffic, and high scalability at scale.
Lid Driven Triangular and Trapezoidal Cavity Flow: Vortical Structures for Steady Solutions and Hopf Bifurcations
Authors: An Bo , Guo Shipeng , Bergadà Josep M.
Published: January 2023

A numerical study of two dimensional lid-driven triangular and trapezoidal cavity flow is performed via using the lattice Boltzmann method (LBM) for steady solutions. The equilateral and right-angled isosceles triangular cavity flow at Reynolds numbers, respectively, 500 and 100 is employed as the benchmark case for code validation. The isosceles right-angled triangular cavity flow is studied for Reynolds numbers sweeping from 100 to 8100. Flow topologies are captured and analyzed. The critical Reynolds number of Hopf bifurcation is predicted by calculating the perturbation decay rate. Two different geometries of right-angled isosceles trapezoidal cavities, bowl-shaped and pyramid-shaped trapezoids, are studied at Reynolds numbers 1000 and 7000. For each type of the trapezoidal cavity, a geometric parameter λ (top-line/base-line ratio) is presented to distinguish different geometries of trapezoidal cavities. The flow patterns regarding the streamlines, vortical structures, and velocity profiles are discussed. The impact of parameter λ on the fluid characteristics are investigated.
Motion Analysis of Balance Pre and Post Sensorimotor Exercises to Enhance Elderly Mobility: A Case Study
Authors: Chen Ji , Romero Roni , Thompson Lara A.
Published: January 2023

Quantitative assessment of movement using motion capture provides insights on mobility which are not evident from clinical evaluation. Here, in older individuals that were healthy or had suffered a stroke, we aimed to investigate their balance in terms of changes in body kinematics and muscle activity. Our research question involved determining the effects on post- compared to pre-sensorimotor training exercises on maintaining or improving balance. Our research hypothesis was that training would improve the gait and balance by increasing joint angles and extensor muscle activities in lower extremities and spatiotemporal measures of stroke and elderly people. This manuscript describes a motion capture-based evaluation protocol to assess joint angles and spatiotemporal parameters (cadence, step length and walking speed), as well as major extensor and flexor muscle activities. We also conducted a case study on a healthy older participant (male, age, 65) and an older participant with chronic stroke (female, age, 55). Both participants performed a walking task along a path with a rectangular shape which included tandem walking forward, right side stepping, tandem walking backward, left side stepping to the starting location. For the stroke participant, the training improved the task completion time by 19 s. Her impaired left leg had improved step length (by 0.197 m) and cadence (by 10 steps/min) when walking forward, and cadence (by 12 steps/min) when walking backward. The non-impaired right leg improved cadence when walking forward (by 15 steps/min) and backward (by 27 steps/min). The joint range of motion (ROM) did not change in most cases. However, the ROM of the hip joint increased significantly by 5.8 degrees (p = 0.019) on the left leg side whereas the ROMs of hip joint and knee joint increased significantly by 4.1 degrees (p = 0.046) and 8.1 degrees (p = 0.007) on the right leg side during backward walking. For the healthy participant, the significant changes were only found in his right knee joint ROM having increased by 4.2 degrees (p = 0.031) and in his left ankle joint ROM having increased by 5.5 degrees (p = 0.006) during the left side stepping.
Tree Seedlings Detection and Counting Using a Deep Learning Algorithm
Authors: Moharram Deema , Yuan Xuguang , Li Dan
Published: January 2023

Tree-counting methods based on computer vision technologies are low-cost and efficient in contrast to the traditional tree counting methods, which are time-consuming, laborious, and humanly infeasible. This study presents a method for detecting and counting tree seedlings in images using a deep learning algorithm with a high economic value and broad application prospects in detecting the type and quantity of tree seedlings. The dataset was built with three types of tree seedlings: dragon spruce, black chokeberries, and Scots pine. The data were augmented via several data augmentation methods to improve the accuracy of the detection model and prevent overfitting. Then a YOLOv5 object detection network was built and trained with three types of tree seedlings to obtain the training weights. The results of the experiments showed that our proposed method could effectively identify and count the tree seedlings in an image. Specifically, the MAP of the dragon spruce, black chokeberries, and Scots pine tree seedlings were 89.8%, 89.1%, and 95.6%, respectively. The accuracy of the detection model reached 95.10% on average (98.58% for dragon spruce, 91.62% for black chokeberries, and 95.11% for Scots pine). The proposed method can provide technical support for the statistical tasks of counting trees.
Ensemble-NQG-T5: Ensemble Neural Question Generation Model Based on Text-to-Text Transfer Transformer
Authors: Hwang Myeong-Ha , Shin Jikang , Seo Hojin , Im Jeong-Seon , Cho Hee , Lee Chun-Kwon
Published: January 2023

Deep learning chatbot research and development is exploding recently to offer customers in numerous industries personalized services. However, human resources are used to create a learning dataset for a deep learning chatbot. In order to augment this, the idea of neural question generation (NQG) has evolved, although it has restrictions on how questions can be expressed in different ways and has a finite capacity for question generation. In this paper, we propose an ensemble-type NQG model based on the text-to-text transfer transformer (T5). Through the proposed model, the number of generated questions for each single NQG model can be greatly increased by considering the mutual similarity and the quality of the questions using the soft-voting method. For the training of the soft-voting algorithm, the evaluation score and mutual similarity score weights based on the context and the question–answer (QA) dataset are used as the threshold weight. Performance comparison results with existing T5-based NQG models using the SQuAD 2.0 dataset demonstrate the effectiveness of the proposed method for QG. The implementation of the proposed ensemble model is anticipated to span diverse industrial fields, including interactive chatbots, robotic process automation (RPA), and Internet of Things (IoT) services in the future.
Polarization Transmission of Visible Light in Inhomogeneous Sea Fog Particle Environment
Authors: Zhan Juntong , Bao Shicheng , Zhang Su , Li Yingchao , Fu Qiang , Duan Jin , Zhang Wei
Published: January 2023

Sea fog is a weather phenomenon suspended in the ocean-atmosphere boundary layer. This phenomenon makes the horizontal visibility of the sea atmosphere less than 1 km. Sea fog reduces sea surface visibility. Moreover, the inhomogeneous sea fog particles in the transmission channel result in the absorption and scattering of photons, which seriously affect the performance of optical detection instruments. Polarization imaging detection can solve this problem. However, the evolution law of transmission characteristics between polarized light and inhomogeneous sea fog particles remains unclear. Therefore, we use the equivalent analysis method to improve Monte Carlo, and finally construct the inhomogeneous particle scattering model. The influence of wavelength and relative humidity on DOP (Degree of Polarization) was calculated by the model. The simulated sea fog was created using brine with a preset concentration, and then established an experimental system close to the actual sea fog environment. Indoor polarized light transmission experiments verified the inhomogeneous particle scattering model. Results showed that the accuracy of the inhomogeneous particle scattering model can reach more than 75%. In the visible band, the DOP decreases with the wavelength increase. DOP450 (Degree of Polarization at 450nm wavelength) is approximately 3–10% higher than DOP532, and DOP532 is approximately 5% higher than DOP671. The relative humidity increases from 45% to 85%, and DOP increases by 10–15%. Therefore, in the visible band, the wavelength and relative humidity are inversely proportional to DOP.
Mechanical Fault Feature Extraction under Underdamped Conditions Based on Unsaturated Piecewise Tri-Stable Stochastic Resonance
Authors: Zhao Shuai , Shi Peiming
Published: January 2023

In the case of the rapid development of large machinery, the research of mechanical fault signal feature extraction is of great significance, it can not only ensure the development of the economy but also ensure safety. Stochastic resonance (SR) is of widespread use in feature extraction of mechanical fault signals due to its excellent signal extraction capability. Compared with an overdamped state, SR in an underdamped state is equivalent to one more filtering of the signal, so the signal-to-noise ratio (SNR) of the output signal will be further improved. In this article, based on the piecewise tri-stable SR (PTSR) obtained from previous studies, the feature extraction of mechanical fault signals is carried out under underdamped conditions, and it is found that the SNR of the output signal is further improved. The simulation signals and experimental signals are used to verify that PTSR has better output performance under underdamped conditions.
Observer-Based Model Reference Tracking Control of the Markov Jump System with Partly Unknown Transition Rates
Authors: Song Weiqiang , Jin Aijuan
Published: January 2023

This paper deals with the model reference tracking control problem of linear systems based on the observer for Markov jump systems with unknown transition rates. The main contributions are as follows: Firstly, we designed a descriptor observer for a given model by the matrix transformation. Then, a tracking control law composed of a feedforward compensator and feedback control law was designed by calculating variations based on the designed observer. The feedback part can stabilize the system. The feedforward part is the complete parametric feedforward tracking compensator. The two parts can be solved separately, and a controller that can make the system stable is proposed under the condition that transition rates are partially unknown through the Lyapunov stability theory. The feedforward parametric solution is given by the generalized Sylvester equation. The algorithm and criteria are proved by several examples and compared with the existing conclusions.
Identification of the Best Cut-Off Value of PIVKA-II for the Surveillance of Patients at Risk of Hepatocellular Carcinoma Development
Authors: Caviglia Gian Paolo , Abate Maria Lorena , Troshina Giulia , Carucci Patrizia , Rolle Emanuela , Risso Alessandra , Burlone Michela Emma , Albè Alice , Crevola Martina , Musso Emma Clara , Rosso Chiara , Armandi Angelo , Olivero Antonella , Minisini Rosalba , Saracco Giorgio Maria , Bugianesi Elisabetta , Pirisi Mario , Ciancio Alessia , Gaia Silvia
Published: January 2023

Patients with cirrhosis are at risk of hepatocellular carcinoma (HCC) development and, according to current guidelines, should undergo surveillance by ultrasound at six month intervals. Due to the known limitations of surveillance strategies based on ultrasonography, the use of tumor biomarkers, although debated, is common practice in many centers. The aim of the study was to identify the best cut-off value for one of such biomarkers, protein induced by vitamin K absence, or antagonist-II (PIVKA-II). We retrospectively enrolled 1187 patients with liver cirrhosis: 205 with a diagnosis of HCC (median age 67 years, 81.0% males) and 982 without tumor (median age 64 years, 56.2% males). During a median follow-up (FU) of 34.6 (11.4–43.7) months, 118 out of 982 (12.0%) patients developed HCC. Serum PIVKA-II was assessed by chemiluminescence immunoassay on the Lumipulse® G600 II platform (Fujirebio, Tokyo, Japan). In the overall cohort (n = 1187), PIVKA-II showed an area under the curve (AUC) of 0.802 for HCC detection. The best cut-off value that maximized sensitivity was 50 mAU/mL (sensitivity = 80%, specificity = 64%). In the 982 patients without HCC at baseline, PIVKA-II > 50 mAU/mL was associated with an increased risk of HCC development during the FU (HR = 1.74, 95% CI 1.21–2.51; p = 0.003)). In conclusion, the evaluation of serum PIVKA-II showed a good performance for HCC detection; a cut-off value > 50 mAU/mL could be suitable for the surveillance of patients who are at risk of developing HCC.
Insomnia in Patients Undergoing Hypoglossal Nerve Stimulation Therapy for Obstructive Sleep Apnea
Authors: Pordzik Johannes , Ludwig Katharina , Seifen Christopher , Huppertz Tilman , Bahr-Hamm Katharina , Matthias Christoph , Gouveris Haralampos
Published: January 2023

Hypoglossal nerve stimulation (HGNS) is a treatment for obstructive sleep apnea (OSA) patients with intolerance of positive airway pressure therapy. Comorbid insomnia is quite prevalent in OSA patients. We investigated the impact of insomnia and excessive daytime sleepiness (EDS) on polysomnography metrics after HGNS treatment. Data of 27 consecutive patients (9 female; mean age 55.52 ± 8.6 years) were retrospectively evaluated. Insomnia was assessed using the ISI (insomnia severity index) and EDS using the Epworth sleepiness scale (ESS). The median ISI was reduced significantly 3 months after HGNS activation (preoperative: 19; postoperative: 14; p < 0.01). Significant correlations emerged between preoperative ISI and postoperative AHI (apnea/hypopnea index; Spearman’s rho = 0.4, p < 0.05), ∆ AHI (r = −0.51, p < 0.01) and ∆ ODI (oxygen desaturation index; r = −0.48, p < 0.05). ISI correlated strongly with EES both preoperatively (r = 0.46; p < 0.02) and postoperatively (r = 0.79; p < 0.001). Therefore, HGNS therapy is associated with a significant reduction of insomnia-related symptoms, in addition to the improvement in respiratory metrics in OSA. Nonetheless, the preoperative severity of patient-reported insomnia symptoms was inversely correlated with the respiratory PSG-outcomes after HGNS. Insomnia should be considered in studies of EDS in OSA patients, especially those treated with HGNS.
Taste Compounds and Polyphenolic Profile of Tomato Varieties Cultivated with Beneficial Microorganisms: A Chemical Investigation on Nutritional Properties and Sensory Qualities
Authors: Morelli Carlo Francesco , Cutignano Adele , Speranza Giovanna , Abbamondi Gennaro Roberto , Rabuffetti Marco , Iodice Carmine , De Prisco Rocco , Tommonaro Giuseppina
Published: January 2023

There is a strong need to develop eco-sustainable agricultural techniques to improve crop yields while preserving biomolecule contents and reducing the adverse environmental impact of agro-chemicals. The use of microorganisms in agriculture represents an attractive and innovative solution. Herein, a chemical study on the nutritional and sensory qualities of San Marzano Cirio 3 (SMC3), Corbarino (CO) and Brandywine (BW) tomato varieties cultivated with and without effective microorganisms (EM) is reported. LC–MS analysis of the methanolic extracts allowed for the identification of 21 polyphenol derivatives. In different proportions among the studied varieties, the two main polyphenols were rutin and naringenin chalcone; the latter was isolated and chemically identified by complementary HR-ESIMS/MS and NMR methods. SMC3 and CO were richer in naringenin chalcone. Conversely, BW showed higher proportions of rutin; however, in all cases, the relative amounts of the two polyphenols considered together increased over the other minor components after the EM treatment. The qualitative and quantitative HPLC analyses of taste-active compounds (aspartic acid, glutamic acid, AMP and GMP) revealed a significant difference in aspartic and glutamic acids and ribonucleotide contents according to the cultivation condition (±EM), particularly in BW. This study provides chemical data in support of the use of EM green technology for the cultivation of edible agricultural products, such as tomato preserves, and may even improve nutritional and sensory qualities while safeguarding the environment.
Claspin-Dependent and -Independent Chk1 Activation by a Panel of Biological Stresses
Authors: Hsiao Hao-Wen , Yang Chi-Chun , Masai Hisao
Published: January 2023

Replication stress has been suggested to be an ultimate trigger of carcinogenesis. Oncogenic signal, such as overexpression of CyclinE, has been shown to induce replication stress. Here, we show that various biological stresses, including heat, oxidative stress, osmotic stress, LPS, hypoxia, and arsenate induce activation of Chk1, a key effector kinase for replication checkpoint. Some of these stresses indeed reduce the fork rate, inhibiting DNA replication. Analyses of Chk1 activation in the cell population with Western analyses showed that Chk1 activation by these stresses is largely dependent on Claspin. On the other hand, single cell analyses with Fucci cells indicated that while Chk1 activation during S phase is dependent on Claspin, that in G1 is mostly independent of Claspin. We propose that various biological stresses activate Chk1 either directly by stalling DNA replication fork or by some other mechanism that does not involve replication inhibition. The former pathway predominantly occurs in S phase and depends on Claspin, while the latter pathway, which may occur throughout the cell cycle, is largely independent of Claspin. Our findings provide evidence for novel links between replication stress checkpoint and other biological stresses and point to the presence of replication-independent mechanisms of Chk1 activation in mammalian cells.
Selenium-Substituted Monomethine Cyanine Dyes as Selective G-Quadruplex Spectroscopic Probes with Theranostic Potential
Authors: Fabijanić Ivana , Kurutos Atanas , Tomašić Paić Ana , Tadić Vanja , Kamounah Fadhil S. , Horvat Lucija , Brozovic Anamaria , Crnolatac Ivo , Radić Stojković Marijana
Published: January 2023

The binding interactions of six ligands, neutral and monocationic asymmetric monomethine cyanine dyes comprising benzoselenazolyl moiety with duplex DNA and RNA and G-quadruplex structures were evaluated using fluorescence, UV/Vis (thermal melting) and circular dichroism (CD) spectroscopy. The main objective was to assess the impact of different substituents (methyl vs. sulfopropyl vs. thiopropyl/thioethyl) on the nitrogen atom of the benzothiazolyl chromophore on various nucleic acid structures. The monomethine cyanine dyes with methyl substituents showed a 100-fold selectivity for G-quadruplex versus duplex DNA. Study results indicate that cyanines bind with G-quadruplex via end π-π stacking interactions and possible additional interactions with nucleobases/phosphate backbone of grooves or loop bases. Cyanine with thioethyl substituent distinguishes duplex DNA and RNA and G-quadruplex structures by distinctly varying ICD signals. Furthermore, cell viability assay reveals the submicromolar activity of cyanines with methyl substituents against all tested human cancer cell lines. Confocal microscopy analysis shows preferential accumulation of cyanines with sulfopropyl and thioethyl substituents in mitochondria and indicates localization of cyanines with methyl in nucleus, particularly nucleolus. This confirms the potential of examined cyanines as theranostic agents, possessing both fluorescent properties and cell viability inhibitory effect.
Risk of Chronic Kidney Disease in Pneumoconiosis: Results from a Retrospective Cohort Study (2008–2019)
Authors: Wei Chao-Hsuan , Li Chia-Hsiang , Shen Te-Chun , Hung Yu-Tung , Tu Chih-Yen , Hsia Te-Chun , Hsu Wu-Huei , Hsu Chung Y.
Published: January 2023

Background: Pneumoconiosis has considerable comorbidities, most notably pulmonary and cardiovascular diseases. However, the relationship between pneumoconiosis and chronic kidney disease (CKD) is largely unknown. The present study aimed to use a retrospective cohort study design to further clarify the association between pneumoconiosis and subsequent CKD risk. Methods: This is a nationwide, population-based, retrospective cohort study that used data from Taiwan’s National Health Insurance Database. Between 2008 and 2018, 17,952 newly diagnosed patients were included in the pneumoconiosis cohort, while 71,808 individuals without pneumoconiosis were included in the comparison cohort, with a propensity score matching for age, gender, and date of pneumoconiosis diagnosis. The development of CKD was monitored until the end of 2019. The risk was assessed using Cox proportional hazard regression models. Results: After controlling for age, gender, and comorbidity, the overall incidence of CKD was 1.69-fold higher in the pneumoconiosis cohort than in the comparison cohort (19.71 vs. 11.76 per 1000 person-years, respectively, p < 0.001), with an adjusted hazard ratio of 1.83 (95% confidence interval: 1.73–1.93). Stratified analyses by age group, gender, and presence of comorbidity revealed that the adjusted hazard ratios of CKD associated with pneumoconiosis remained significant (8/9). Furthermore, pneumoconiosis and tri-high (hypertension, hyperglycemia, and hyperlipidemia) interact positively with CKD development (p < 0.001). Conclusion: Patients with pneumoconiosis had a significantly higher risk of developing CKD than those without. Pneumoconiosis combined with hypertension, hyperglycemia, or hyperlipidemia would increase the risk even further. More studies are required to understand the possible pathophysiological mechanisms.
Liquid Biopsy Detecting Circulating Tumor Cells in Patients with Non-Small Cell Lung Cancer: Preliminary Results of a Pilot Study
Authors: Mastromarino Maria Giovanna , Parini Sara , Azzolina Danila , Habib Sara , De Marni Marzia Luigia , Luise Chiara , Restelli Silvia , Baietto Guido , Trisolini Elena , Massera Fabio , Papalia Esther , Bora Giulia , Carbone Roberta , Casadio Caterina , Boldorini Renzo , Rena Ottavio
Published: January 2023

Lung cancer is still the leading cause of cancer-related death worldwide. Interest is growing towards early detection and advances in liquid biopsy to isolate circulating tumor cells (CTCs). This pilot study aimed to detect epithelial CTCs in the peripheral blood of early-stage non-small cell lung cancer (NSCLC) patients. We used Smart BioSurface® (SBS) slide, a nanoparticle-coated slide able to immobilize viable nucleated cellular fraction without pre-selection and preserve cell integrity. Forty patients undergoing lung resection for NSCLC were included; they were divided into two groups according to CTC value, with a cut-off of three CTCs/mL. All patients were positive for CTCs. The mean CTC value was 4.7(± 5.8 S.D.) per ml/blood. In one patient, next generation sequencing (NGS) analysis of CTCs revealed v-raf murine sarcoma viral oncogene homolog B(BRAF) V600E mutation, which has also been identified in tissue biopsy. CTCs count affected neither overall survival (OS, p = 0.74) nor progression-free survival (p = 0.829). Multivariable analysis confirmed age (p = 0.020) and pNodal-stage (p = 0.028) as negative predictors of OS. Preliminary results of this pilot study suggest the capability of this method in detecting CTCs in all early-stage NSCLC patients. NGS on single cell, identified as CTC by immunofluorescence staining, is a powerful tool for investigating the molecular landscape of cancer, with the aim of personalized therapies.
Short-Term Safety and Psychosocial Impact of the BNT162b2 mRNA COVID-19 Vaccine in Cancer Patients—An Italian Single-Center Experience
Authors: Persano Irene , Cani Massimiliano , Del Rio Benedetta , Ferrari Giorgia , Garbo Edoardo , Parlagreco Elena , Pisano Chiara , Cetoretta Valeria , Delcuratolo Marco Donatello , Turco Fabio , Audisio Alessandro , Cecchi Cristina , Leone Gianmarco , Napoli Valerio Maria , Bertaglia Valentina , Bianco Valentina , Capelletto Enrica , D’Amiano Carmen , Di Maio Massimo , Gianetta Martina , Novello Silvia , Passiglia Francesco , Scagliotti Giorgio Vittorio , Bironzo Paolo
Published: January 2023

Safety data regarding BNT162b2 in cancer patients (CPs) are scarce. Herein we report the side effects (SEs), the adverse events (AEs), and the patient-reported outcomes (PROs) following BNT162b2 administration in CPs treated at the San Luigi Gonzaga University Hospital. All CPs who agreed to participate in our vaccination campaign received BNT162b2 and were included in the descriptive analysis. An anonymous questionnaire investigating the occurrence of SEs/AEs and PROs was administered to the study population 21 days after the first dose. Pearson’s chi-squared test was used to estimate the risk of experiencing SEs/AEs according to selected variables. A total of 997 patients were included in the study: 62.0% had stage IV cancer, and 68.8% were receiving an active treatment, of whom 15.9% were receiving immunotherapy. SEs/AEs were recorded in 37.1% of cases after the first dose and in 48.5% of cases after the second dose. The most common SEs were muscle pain/local rash (27.9% and 28%, after the first and second dose, respectively). Patients older than 70 years showed lower risk of SEs/AEs, while women showed a higher risk. Before receiving the vaccine, 18.2% of patients felt fearful and/or insecure about the vaccination. After the first dose, 57.5% of patients changed their feelings positively. Our data support the short-term safety of BNT162b2 in CPs, regardless of disease stage and concurrent treatments. Overall, the vaccination showed a positive impact on quality of life.
Who Should Not Be Surveilled for HCC Development after Successful Therapy with DAAS in Advanced Chronic Hepatitis C? Results of a Long-Term Prospective Study
Authors: Ciancio Alessia , Ribaldone Davide Giuseppe , Spertino Matteo , Risso Alessandra , Ferrarotti Debora , Caviglia Gian Paolo , Carucci Patrizia , Gaia Silvia , Rolle Emanuela , Sacco Marco , Saracco Giorgio Maria
Published: January 2023

Background and aims: The identification of patients with Hepatitis C Virus (HCV)-positive advanced chronic liver disease (aCLD) successfully treated by Direct Acting Antiviral Agents (DAAs) who really benefit from Hepatocellular Carcinoma (HCC) surveillance programs is still a matter of debate. We performed a long-term prospective cohort study on F3-F4 HCV-positive patients achieving Sustained Virologic Response (SVR) after DAAs treatment in order to identify patients who can safely suspend surveillance. Methods: 1000 patients with HCV-positive aCLD obtaining SVR by DAAs from January 2015 to December 2017 were divided into four groups according to baseline elastographic, ultrasonographic, clinical and biochemical features: (1) Group 1: 324 patients with Liver Stiffness Measurement (LSM) ≥ 9.5 ≤ 14.5 kPa, FIB-4 < 3.25 and APRI < 1.5 (2) Group 2: 133 patients with LSM ≥ 9.5 ≤ 14.5 kPa, FIB-4 ≥ 3.25 and/or APRI ≥ 1.5 (3) Group 3: 158 patients with LSM > 14.5 kPa, FIB-4 < 3.25 and APRI < 1.5 (4) Group 4: 385 patients with LSM > 14.5 kPa, FIB-4 ≥ 3.25 and/or APRI ≥ 1.5. FIB-4 and APRI scores were calculated at baseline and at SVR achievement. Each patient was surveiled twice-yearly by ultrasound for a median follow-up of 48 months. Results: among Group 1 patients, 1/324 (0.3%) developed HCC (0.09/100 patients/year [PY]), compared to 6/133 (4.5%) Group 2 patients (1.22/100 PY, p = 0.0009), 10/158 (6.3%) Group 3 patients (1.68/100 PY, p = 0.0001), 54/385 (14.0%) Group 4 patients (4.01/100 PY, p < 0.0001). HCC incidence was significantly lower in Group 2 compared to Group 3 (p = 0.004) and in Group 3 compared to Group 4 (p = 0.009). HCC risk fell in patients showing a decrease of FIB-4/APRI scores. Conclusions: the risk of HCC occurrence is negligible in about 90% of HCV-positive patients with baseline LSM ≥ 9.5 ≤ 14.5 kPa plus FIB-4 < 3.25 and APRI < 1.5 achieving SVR. Among this particular subset of patients, FIB-4/APRI scores may represent an accurate and inexpensive tool to distinguish patients not needing long-term HCC surveillance.
Multi-Mechanistic and Therapeutic Exploration of Nephroprotective Effect of Traditional Ayurvedic Polyherbal Formulation Using In Silico, In Vitro and In Vivo Approaches
Authors: Gaurav  , Sharma Ikshit , Khan Mohammad Umar , Zahiruddin Sultan , Basist Parakh , Ahmad Sayeed
Published: January 2023

Based on traditional therapeutic claims, NEERI KFT (a traditional Ayurvedic polyherbal preparation) has been innovatively developed in recent time on the decades of experience for treating kidney dysfunction. Due to the lack of scientific evidence, the present investigations are needed to support the rationale use of NEERI KFT. Considering the facts, the study investigated the nephroprotective effect of NEERI KFT against kidney dysfunction using in silico, in vitro and in vivo approaches. In this study, phytochemical and network pharmacology studies were performed for the developed formulation to evaluate the molecular mechanism of NEERI KFT in the amelioration of kidney disease. In vitro nephroprotective and antioxidant effect of NEERI KFT was determined on HEK 293 cells against cisplatin-induced cytotoxicity and oxidative stress. In vivo nephroprotective effect of NEERI KFT was determined against cisplatin-induced nephrotoxicity in Wistar rats, via assessing biochemical markers, antioxidant enzymes and inflammatory cytokines such as TNF-α, IL-1β, CASP-3, etc. The results showed that the compounds such as gallic acid, caffeic acid and ferulic acid are the major constituents of NEERI KFT, while network pharmacology analysis indicated a strong interaction between polyphenols and several genes (CASPs, ILs, AGTR1, AKT, ACE2, SOD1, etc.) involved in the pathophysiology of kidney disease. In vivo studies showed a significant (p < 0.05) ameliorative effect on biochemical markers and antioxidant enzymes (SOD, CAT, GSH, etc.), and regulates inflammatory cytokine (TNF-α, IL-1β, CASP-3) expression in kidney tissue. Hence, it can be concluded that NEERI KFT subsequently alleviates renal dysfunction mediated by cisplatin via attenuating oxidative and inflammatory stress, thus preserving the normalcy of kidney function.
Internet of Things (IoT)-Based Environmental Monitoring and Control System for Home-Based Mushroom Cultivation
Authors: Chong Jiu Li , Chew Kit Wayne , Peter Angela Paul , Ting Huong Yong , Show Pau Loke
Published: January 2023

The control and monitoring of the environmental conditions in mushroom cultivation has been a challenge in the mushroom industry. Currently, research has been conducted to implement successful remote environmental monitoring, or, in some cases, remote environmental control, yet there is not yet a combination of both these systems providing live stream images or video. As a result, this research aimed to design and develop an Internet of things (IoT)-based environmental control and monitoring system for mushroom cultivation, whereby the growth conditions of the mushrooms, such as temperature, humidity, light intensity, and soil moisture level, are remotely monitored and controlled through a mobile and web application. Users would be able to visualize the growth of the mushroom remotely by video and images through the Internet. The respective sensors are implemented into the mushroom cultivation process and connected to the NodeMCU microcontroller, which collects and transfers the data to the cloud server, enabling remote access at any time through the end device with internet connection. The control algorithm regulates the equipment within the cultivational chamber autonomously, based on feedback from the sensors, in order to retain the optimum environment for the cultivation of mushrooms. The sensors were tested and compared with manual readings to ensure their accuracy. The implementation of IoT toward mushroom cultivation would greatly contribute to the advancement of the current mushroom industry which still applies the traditional cultivation approach.
Highly Sensitive Multiplex Detection of Molecular Biomarkers Using Hybridization Chain Reaction in an Encoded Particle Microfluidic Platform
Authors: Rutten Iene , Daems Devin , Leirs Karen , Lammertyn Jeroen
Published: January 2023

In the continuous combat against diseases, there is the need for tools that enable an improved diagnostic efficiency towards higher information density combined with reduced time-to-result and cost. Here, a novel fully integrated microfluidic platform, the Evalution™, is evaluated as a potential solution to this need. Encoded microparticles combined with channel-based microfluidics allow a fast, sensitive and simultaneous detection of several disease-related biomarkers. Since the binary code is represented by physically present holes, 210 different codes can be created that will not be altered by light or chemically induced degradation. Exploiting the unique features of this multiplex platform, hybridization chain reaction (HCR) is explored as a generic approach to reach the desired sensitivity. Compared to a non-amplified reference system, the sensitivity was drastically improved by a factor of 104, down to low fM LOD values. Depending on the HCR duration, the assay can be tuned for sensitivity or total assay time, as desired. The huge potential of this strategy was further demonstrated by the successful detection of a multiplex panel of six different nucleic acid targets including viruses and bacteria. The ability to not only discriminate these two categories but, with the same effort, also virus strains (human adenovirus and human bocavirus), virus subtypes (human adenovirus type B and D) and antibiotic-resistant bacteria (Streptococcus pneumonia), exemplifies the specificity of the developed approach. The effective, yet highly simplified, isothermal and protein-enzyme-free signal amplification tool reaches an LOD ranging from as low as 33 ± 4 to 151 ± 12 fM for the different targets. Moreover, direct detection in a clinically relevant sample matrix was verified, resulting in a detection limit of 309 ± 80 fM, approximating the low fM levels detectable with the gold standard analysis method, PCR, without the drawbacks related to protein enzymes, thermal cycling and elaborate sample preparation steps. The reported strategy can be directly transferred as a generic approach for the sensitive and specific detection of various target molecules in multiplex. In combination with the high-throughput capacity and reduced reagent consumption, the Evalution™ demonstrates immense potential in the next generation of diagnostic tools towards more personalized medicine.
Visible CCD Camera-Guided Photoacoustic Imaging System for Precise Navigation during Functional Rat Brain Imaging
Authors: Wang Yuhling , Chen Yu-Lin , Huang Chih-Mao , Chen Li-Tzong , Liao Lun-De
Published: January 2023

In photoacoustic (PA) imaging, tissue absorbs specific wavelengths of light. The absorbed energy results in thermal expansion that generates ultrasound waves that are reconstructed into images. Existing commercial PA imaging systems for preclinical brain imaging are limited by imprecise positioning capabilities and inflexible user interfaces. We introduce a new visible charge-coupled device (CCD) camera-guided photoacoustic imaging (ViCPAI) system that integrates an ultrasound (US) transducer and a data acquisition platform with a CCD camera for positioning. The CCD camera accurately positions the US probe at the measurement location. The programmable MATLAB-based platform has an intuitive user interface. In vitro carbon fiber and in vivo animal experiments were performed to investigate the precise positioning and imaging capabilities of the ViCPAI system. We demonstrated real-time capturing of bilateral cerebral hemodynamic changes during (1) forelimb electrical stimulation under normal conditions, (2) forelimb stimulation after right brain focal photothrombotic ischemia (PTI) stroke, and (3) progression of KCl-induced cortical spreading depression (CSD). The ViCPAI system accurately located target areas and achieved reproducible positioning, which is crucial in animal and clinical experiments. In animal experiments, the ViCPAI system was used to investigate bilateral cerebral cortex responses to left forelimb electrical stimulation before and after stroke, showing that the CBV and SO2 in the right primary somatosensory cortex of the forelimb (S1FL) region were significantly changed by left forelimb electrical stimulation before stroke. No CBV or SO2 changes were observed in the bilateral cortex in the S1FL area in response to left forelimb electrical stimulation after stroke. While monitoring CSD progression, the ViCPAI system accurately locates the S1FL area and returns to the same position after the probe moves, demonstrating reproducible positioning and reducing positioning errors. The ViCPAI system utilizes the real-time precise positioning capability of CCD cameras to overcome various challenges in preclinical and clinical studies.
Biosensors for the Determination of Protein Biomarkers
Authors: Lukaszewski Zenon , Gorodkiewicz Ewa
Published: January 2023

Circulating body fluids such as blood, urea, saliva, cerebrospinal fluid, etc [...]
From Piezoelectric Nanogenerator to Non-Invasive Medical Sensor: A Review
Authors: Zhu Qiliang , Wu Tong , Wang Ning
Published: January 2023

Piezoelectric nanogenerators (PENGs) not only are able to harvest mechanical energy from the ambient environment or body and convert mechanical signals into electricity but can also inform us about pathophysiological changes and communicate this information using electrical signals, thus acting as medical sensors to provide personalized medical solutions to patients. In this review, we aim to present the latest advances in PENG-based non-invasive sensors for clinical diagnosis and medical treatment. While we begin with the basic principles of PENGs and their applications in energy harvesting, this review focuses on the medical sensing applications of PENGs, including detection mechanisms, material selection, and adaptive design, which are oriented toward disease diagnosis. Considering the non-invasive in vitro application scenario, discussions about the individualized designs that are intended to balance a high performance, durability, comfortability, and skin-friendliness are mainly divided into two types: mechanical sensors and biosensors, according to the key role of piezoelectric effects in disease diagnosis. The shortcomings, challenges, and possible corresponding solutions of PENG-based medical sensing devices are also highlighted, promoting the development of robust, reliable, scalable, and cost-effective medical systems that are helpful for the public.