bluuebunny/crossref_metadata_2025 huggingface dataset:
An Intelligent Weighted Object Detector for Feature Extraction to Enrich Global Image Information
Authors: Yan Lingyu , Li Ke , Gao Rong , Wang Chunzhi , Xiong Neal
Published: August 2022

Object detection is a fundamental task in computer vision. To improve the detection accuracy of a detection model without increasing the model weights, this paper modifies the YOLOX model by first replacing some of the traditional convolution operations in the backbone network to reduce the parameter cost of generating feature maps. We design a local feature extraction module to chunk the feature maps to obtain local image features and a global feature extraction module to calculate the correlation between feature points to enrich the feature, and add learnable weights to the feature layers involved in the final prediction to assist the model in detection. Moreover, the idea of feature map reuse is proposed to retain more information from the high-dimensional feature maps. In comparison experiments on the dataset PASCAL VOC 2007 + 2012, the accuracy of the improved algorithm increased by 1.2% over the original algorithm and 2.2% over the popular YOLOv5.
Novel Unbiased Optimal Receding-Horizon Fixed-Lag Smoothers for Linear Discrete Time-Varying Systems
Authors: Kwon Bokyu , Kim Pyung Soo
Published: August 2022

This paper proposes novel unbiased minimum-variance receding-horizon fixed-lag (UMVRHF) smoothers in batch and recursive forms for linear discrete time-varying state space models in order to improve the computational efficiency and the estimation performance of receding-horizon fixed-lag (RHF) smoothers. First, an UMVRHF smoother in batch form is proposed by combining independent receding-horizon local estimators for two separated sub-horizons. The local estimates and their error covariance matrices are obtained based on an optimal receding horizon filter and the smoother in terms of the unbiased minimum variance; they are then optimally combined using Millman’s theorem. Next, the recursive form of the proposed UMVRHF smoother is derived to improve its computational efficiency and extendibility. Additionally, we introduce a method for extending the proposed recursive smoothing algorithm to a posteriori state estimations and propose the Rauch–Tung–Striebel receding-horizon fixed-lag smoother in recursive form. Furthermore, a computational complexity reduction technique that periodically switches the two proposed recursive smoothing algorithms is proposed. The performance and effectiveness of the proposed smoothers are demonstrated by comparing their estimation results with those of previous algorithms for Kalman and receding-horizon fixed-lag smoothers via numerical experiments.
Special Issue on Deep Learning-Based Action Recognition
Authors: Lee Hyo Jong
Published: August 2022

Human action recognition (HAR) has gained popularity because of its various applications, such as human–object interaction [...]
Fatigue Testing of Human Flexor Tendons Using a Customized 3D-Printed Clamping System
Authors: Scholze Mario , Safavi Sarah , Ramezani Maziar , Ondruschka Benjamin , Hammer Niels
Published: August 2022

Improved surgical procedures and implant developments for ligament or tendon repair require an in-depth understanding of tissue load-deformation and fatigue properties. Cyclic testing will provide crucial information on the behavior of these materials under reoccurring loads and on fatigue strength. Sparse data are available describing soft tissue behavior under cyclic loading. To examine fatigue strength, a new technology was trialed deploying 3D-printing to facilitate and standardize cyclic tests aiming to determine tendon fatigue behavior. Cadaveric flexor digitorum tendons were harvested and mounted for tensile testing with no tapering being made, using 3D-printed clamps and holder arms, while ensuring a consistent testing length. Loads ranging between 200 to 510 N were applied at a frequency of 4 Hz, and cycles to failure ranged between 8 and >260,000. S–N curves (Woehler curves) were generated based on the peak stresses and cycles to failure. Power regression yielded a combined coefficient of determination of stress and cycles to failure of R2 = 0.65, while the individual coefficients for tissues of single donors ranged between R2 = 0.54 and R2 = 0.88. The here-presented results demonstrate that S–N curves of human tendons can be obtained using a standardized setting deploying 3D-printing technology.
NDT Method for Line Laser Welding Based on Deep Learning and One-Dimensional Time-Series Data
Authors: Liu Yang , Yuan Kun , Li Tian , Li Sha , Ren Yonggong
Published: August 2022

Welding testing is particularly important in industrial systems, but there are still some deficiencies in terms of testing performance, anti-noise capability and defect identification in current mainstream welding non-destructive testing technologies. With the development of structured-light non-destructive testing technology, deep learning technology, signal processing technology and other fields, various possibilities have emerged that make it possible to propose new ideas for welding non-destructive testing. This study used a laser sensor to propose a non-destructive method for testing welding defects in seam contours. In order to solve the problems of low sampling rates and poor recognition accuracy in traditional methods of welding defect detection, the proposed method introduces image coding into laser sensors and applies deep-learning algorithms to the classification and detection of weld defect images. By preprocessing the weld seam by encoding one-dimensional data as two-dimensional images, this method develops a framework for the detection and classification of pre-coded laser weld seam images. After taking the original extracted weld image center trajectory data as one-dimensional sequence data, we utilized the method of encoding one-dimensional time series data as two-dimensional time-series images. In doing so, the one-dimensional laser data can be encoded into the corresponding two-dimensional images and, with the application of a deep neural network, welding defect classification and detection can be realized. Experimentation was used to verify that the proposed method is of higher accuracy than traditional methods for classifying and detecting defects directly from two-dimensional welding images.
Novel Reversible Comparator Design in Quantum Dot-Cellular Automata with Power Dissipation Analysis
Authors: Vahabi Mohsen , Lyakhov Pavel , Bahar Ali Newaz , Otsuki Akira , Wahid Khan A.
Published: August 2022

In very large-scale integration (VLSI) circuits, a partial of energy lost leads to information loss in irreversible computing because, in conventional combinatorial circuits, each bit of information generates heat and power consumption, thus resulting in energy dissipation. When information is lost in conventional circuits, it will not be recoverable, as a result, the circuits are provided based on the reversible logic and according to reversible gates for data retrieval. Since comparators are one of the basic building blocks in digital logic design, in which they compare two numbers, the aim of this research is to design a 1-bit comparator building block based on reversible logic and implement it in the QCA with the minimum cell consumption, less occupied area, and lower latency, as well as to design it in a single layer. The proposed 1-bit reversible comparator is denser, cost-effective, and more efficient in quantum cost, power dissipation, and the main QCA parameters than that of previous works.
Averaging and Stacking Partial Least Squares Regression Models to Predict the Chemical Compositions and the Nutritive Values of Forages from Spectral Near Infrared Data
Authors: Lesnoff Mathieu , Andueza Donato , Barotin Charlène , Barre Philippe , Bonnal Laurent , Fernández Pierna Juan Antonio , Picard Fabienne , Vermeulen Philippe , Roger Jean-Michel
Published: August 2022

Partial least square regression (PLSR) is a reference statistical model in chemometrics. In agronomy, it is used to predict components (response variables y) of chemical composition of vegetal materials from spectral near infrared (NIR) data X collected from spectrometers. PLSR reduces the dimension of the spectral data X by defining vectors that are then used as latent variables (LVs) in a multiple linear model. One difficulty is to determine the relevant dimensionality (number of LVs) for the given data. This step can be very time consuming when many datasets have to be processed and/or the datasets are frequently updated. The paper focuses on an alternative, bypassing the determination of the PLSR dimensionality and allowing for automatizing the predictions. The strategy uses ensemble learning methods, such as averaging or stacking the predictions of a set of PLSR models with different dimensionalities. The paper presents various methods of PLSR averaging and stacking and compares their performances to the usual PLSR on six real datasets on different types of forages. The main finding of the study was the overall superiority of the averaging methods compared to the usual PLSR. We therefore believe that such methods can be recommended to analyze NIR data on forages.
Tracking Wheat Variety and Origin by the Shape Analysis of the Volatiles Fingerprint of Wheat Kernels and Wheat Beers
Authors: De Flaviis Riccardo , Santarelli Veronica , Sacchetti Giampiero
Published: August 2022

The Volatile Organic Compounds (VOCs) of common wheat of different origin (variety and altitude of cultivation) and craft wheat beers produced by using the wheat themselves were analyzed by SPME GC-MS. The VOCs of wheat kernels and wheat beers were compared, and 14 common flavor-active compounds were identified. Principal component analysis was used to describe changes in the profile of common volatiles induced by beer processing. A unifying approach by Generalized Procrustes analysis (GPA), which considers the overall characteristics of the datasets, permitted linking the VOCs of wheat to those of beers and to define a common flavor pattern. Despite the beer processing deeply affecting the overall volatilome profile, a consensus map permitted to clearly classify the VOCs profile of five out of six samples. This work revealed that differences in wheat VOCs induced by wheat variety and cultivation site were reflected in different beer aromatic profiles, highlighting the importance of origin on the wheat and beers’ flavor. This unifying approach to flavor analysis by GPA could be of help in sight of a certification of origin, since it may contribute not only to the definition of wheat origin but also of the “terroir” of wheat beer thereof.
In-Silico Characterization of von Willebrand Factor Bound to FVIII
Authors: Drago Valentina , Di Paola Luisa , Lesieur Claire , Bernardini Renato , Bucolo Claudio , Platania Chiara Bianca Maria
Published: August 2022

Factor VIII belongs to the coagulation cascade and is expressed as a long pre-protein (mature form, 2351 amino acids long). FVIII is deficient or defective in hemophilic A patients, who need to be treated with hemoderivatives or recombinant FVIII substitutes, i.e., biologic drugs. The interaction between FVIII and von Willebrand factor (VWF) influences the pharmacokinetics of FVIII medications. In vivo, full-length FVIII (FL-FVIII) is secreted in a plasma-inactive form, which includes the B domain, which is then proteolyzed by thrombin protease activity, leading to an inactive plasma intermediate. In this work, we analyzed through a computational approach the binding of VWF with two structure models of FVIII (secreted full-length with B domain, and B domain-deleted FVIII). We included in our analysis the atomic model of efanesoctocog alfa, a novel and investigational recombinant FVIII medication, in which the VWF is covalently linked to FVIII. We carried out a structural analysis of VWF/FVIII interfaces by means of protein–protein docking, PISA (Proteins, Interfaces, Structures and Assemblies), and protein contact networks (PCN) analyses. Accordingly, our computational approaches to previously published experimental data demonstrated that the domains A3-C1 of B domain-deleted FVIII (BDD-FVIII) is the preferential binding site for VWF. Overall, our computational approach applied to topological analysis of protein–protein interface can be aimed at the rational design of biologic drugs other than FVIII medications.
Electrical Characteristics of Ultra-High-Performance Concrete Containing Carbon-Based Materials
Authors: Lim Kwangmo , Lee Namkon , Ryu Gumsung , Koh Kyungtaek , Kim Kyongchul
Published: August 2022

Recently, carbon materials with unique properties, such as high tensile strength and electrical conductivity, have been extensively investigated for the multi-functionalization of concrete. Previous studies mainly focused on improving the performance of normal-strength concrete using carbon nanomaterials, such as carbon nanotubes and graphene nanoplates. Therefore, this study analyzed the effect of carbon materials on ultra-high-performance concrete (UHPC) mixed with steel fibers, which has an outstanding mechanical performance. In addition, length effects were investigated for carbon fibers with nanometer, micrometer, and millimeter sizes. The influences of carbon materials on 120 MPa UHPC were investigated, including expanded graphite, a well-known superior conductivity material. Electrical conductivity, compressive strength, tensile strength, and electrical conductivity were analyzed experimentally. As a result, compressive strength tends to decrease as the concentrations of carbon materials increase, and chopped fiber has the best performance at 10.5 MPa in terms of tensile strength. Since the electrical conductivity of chopped fiber was observed to be significantly higher than that of other materials at 6.6 times, millimeter-sized fiber would be most suitable as a carbon material for concrete. This study could guide future research on the multi-functionalization of UHPC with carbon-based materials, including mechanical and electrical conductivity performances.
Effect of Fuel Sloshing on the Damping of a Scaled Wing Model—Experimental Testing and Numerical Simulations
Authors: Constantin Lucian , De Courcy Joe J. , Titurus Branislav , Rendall Thomas C. S. , Cooper Jonathan E. , Gambioli Francesco
Published: August 2022

Vertical sloshing of liquid-filled tanks has been shown to induce substantial dissipative effects. Building upon these previous results obtained on simpler sloshing systems, a scaled wing prototype is presented here, equipped with a fuel tank that allows the observation of liquid sloshing and quantification of induced dynamic effects. Based on experiments conducted at a 50% filling level for a baffled wing fuel tank model, substantial additional damping effects were demonstrated with liquid inside the tank regardless of the vertical acceleration amplitude. A numerical model based on a finite element wing structural model and a surrogate 1DOF fluid model was explored, with numerical simulations showing good agreement compared to experiments throughout the decaying motion of the system.
Aerodynamic Characteristics of Supersonic Rocket-Sled Involving Waverider Geometry
Authors: Yu Yuanyuan , Wang Bin , Xu Changyue , Sun Jianhong
Published: August 2022

Rocket-sleds belong to a category of large-scale test platforms running on the ground which are mainly used for launching tests of weapon equipment and performance tests of airborne equipment. In the present study, a dynamic grid method was used to simulate the running process of an axisymmetric slender rocket-sled (ASRS) and a reversed waverider rocket-sled (RWRRS). The aerodynamic characteristics were studied and the ability of the waverider to control the shockwave with the ground effect was confirmed. In addition to reducing shockwave oscillation, the RWRRS was also able to increase lift and reduce drag. By means of power spectral density analysis, the characteristic frequencies of shockwave oscillations related to shock-wave/rail-fastener interaction were analyzed and a harmonic phenomenon was observed. Furthermore, the ability of the waverider rocket-sled to reduce pressure oscillation was confirmed by comparing the sound pressure level value.
The Performance of ECMWF Ensemble Prediction System for European Extreme Fires: Portugal/Monchique in 2018
Authors: Durão Rita , Alonso Catarina , Gouveia Célia
Published: August 2022

At the beginning of August 2018, Portugal experienced a severe heat episode over a few days that consequently increased the probability of wildfire events. Due to the advection of an anomalous very hot and dry air mass, severe fire-prone meteorological conditions were forecasted mainly over southern Portugal, in the Monchique region. Together with the significant fuel amount accumulated since the last extreme wildfire in August 2003, all the unfavorable conditions were set to drive a severe fire over this region. The Monchique fire started on 3 August 2018, being very hard to suppress and lasting for seven days, with a burnt area of 27,000 ha. Regarding the need to have operational early warning tools, this work aims to evaluate the reliability of fire probabilistic products, up to 72 h ahead, together with the use of fire radiative power products, as support tools in fire monitoring and resource activities. To accomplish this goal, we used the fire probabilistic products of the Ensemble Prediction System, provided by the Copernicus Atmosphere Monitoring Service. Among available fire danger rating systems, the Fire Weather Index and the Fine Fuels Moisture Code of the Canadian Forest Fire Weather Index System were selected to assess the meteorological fire danger. The assessment of the fire intensity was based on the Fire Radiative Energy released, considering the Fire Radiative Power, delivered in near real-time, by EUMETSAT Land Surface Analysis Satellite Applications Facility. The exceptional fire danger over southern Portugal that favors the ignition of the Monchique fire and its severity was essential driven by two important factors: (i) the anomalous fire weather danger, before and during the event; (ii) the accumulated fuel amount, since the last severe event occurred in 2003, over the region. Results show that the selected fire probabilistic products described the meteorological fire danger observed well, and the LSA-SAF products revealed the huge amount of fire energy emitted, in line with the difficulties faced by authorities to suppress the Monchique fire.
Using Covering Reduction to Identify Reducts for Object-Oriented Concept Lattices
Authors: Liu Guilong
Published: August 2022

An object-oriented concept lattice, as an important generalization of classic concept lattices, is a bridge between formal concept analysis and rough set theory. This paper presents an application of covering reduction in formal concept analysis. It studies attribute reduction, object reduction, and bireduction for object-oriented concept lattices. We show that attribute and object reductions for object-oriented concept lattices are equivalent to covering reductions. Using a Boolean matrix transformation, we derive the corresponding algorithms to identify all reducts. In contrast to existing discernibility matrix-based reduction algorithms for object-oriented concept lattices, our algorithms omit the calculation of concept lattices, discernibility matrices, and discernibility functions. The algorithms save substantial time and are a significant improvement over discernibility matrix-based techniques.
Expression of the ripAA Gene in the Soilborne Pseudomonas mosselii Can Promote the Control Efficacy against Tobacco Bacterial Wilt
Authors: Zhuo Tao , Chen Shiting , Wang Dandan , Fan Xiaojing , Zhang Xiaofeng , Zou Huasong
Published: August 2022

The environmental bacterium Pseudomonas mosselii produces antagonistic secondary metabolites with inhibitory effects on multiple plant pathogens, including Ralstonia solanacearum, the causal agent of bacterial wilt. In this study, an engineered P. mosselii strain was generated to express R. solanacearum ripAA, which determines the incompatible interactions with tobacco plants. The ripAA gene, together with its native promoter, was integrated into the P. mosselii chromosome. The resulting strain showed no difference in antimicrobial activity against R. solanacearum. Promoter-LacZ fusion and RT-PCR experiments demonstrated that the ripAA gene was transcribed in culture media. Compared with that of the wild type, the engineered strain reduced the disease index by 9.1% for bacterial wilt on tobacco plants. A transcriptome analysis was performed to identify differentially expressed genes in tobacco plants, and the results revealed that ethylene- and jasmonate-dependent defense signaling pathways were induced. These data demonstrates that the engineered P. mosselii expressing ripAA can improve biological control against tobacco bacterial wilt by the activation of host defense responses.
Micrococcus lylae MW407006 Pigment: Production, Optimization, Nano-Pigment Synthesis, and Biological Activities
Authors: Shahin Yahya H. , Elwakil Bassma H. , Ghareeb Doaa A. , Olama Zakia A.
Published: August 2022

Bacterial pigments (e.g., melanin and carotenoids) are considered to be among the most important secondary metabolites due to their various pharmacological activities against cancer and microbial resistance. Different pigmented bacterial strains were isolated from soil samples from El Mahmoudiyah governance and screened for their antimicrobial activity. The most promising pigment producer was identified as Micrococcus lylae MW407006; furthermore, the produced pigment was identified as echinenone (β-carotene pigment). The pigment production was optimized through a central composite statistical design to maximize the biomass production, pigment concentration, and the antimicrobial activity. It was revealed that the most significant fermentation parameters were the glucose (as a carbon source) and asparagine (as a nitrogen source) concentrations. Nano-echinenone was synthesized using the ball milling technique, characterized, and finally assessed for potential antimicrobial, antioxidant, and antitumor activities. The data revealed that the synthesized nano-echinenone had higher antimicrobial activity than the crude pigment. The cytotoxic potency of echinenone and nano-echinenone was investigated in different cell lines (normal and cancer cells). The inhibition of cell proliferation and induction of cell death was observed in Caco-2 and Hep-G2 cells. The data proved that nano-echinenone is a suitable candidate for use as a safe antimicrobial and anti-hepatocellular-carcinoma agent.
Influence of an Upper Limb Isometric Task in Perceived and Performance Fatigability of Elderly Subjects: A Quasi-Experimental Study
Authors: Silva-Migueis Helena , Martínez-Jiménez Eva María , Casado-Hernández Israel , Dias Adriano , Monteiro Ana Júlia , Martins Rodrigo B. , Romero-Morales Carlos , López-López Daniel , Gómez-Salgado Juan
Published: August 2022

Isometric activity can be used as a strategy to improve health, fitness, and functional performance in the elderly population, but differences in fatigability may occur. This study aimed to understand fatigability behavior during an upper limb isometric task (ULIT) and the role of health status and physical activity in the fatigability of elderly participants. Thirty-two (32) elderly participants (72.5 ± 5.18 years) were instructed to perform ULIT. The Borg CR10 scale and task failure point (TTF) were used to measure perceived and performance fatigability. Self-reported measures were used to assess the quality of life and physical activity level. A significant relationship between perceived and performance fatigability was found only in the final phase of activity (p < 0.01). Significant correlations were found between perceived fatigability and the social functioning dimension (p < 0.05), and between performance fatigability (TTF) and BMI (p < 0.01), physical functioning (p < 0.01), and role functioning/physical (p < 0.05) dimensions. In conclusion, ULIT produces changes in fatigability of elderly people, which are positively related in the final stage of the activity. Changes in fatigability are negatively related to BMI. It is also negatively related to health, social functioning, physical functioning and role functioning/physical quality of life dimensions.
Role of Caspase Family in Intervertebral Disc Degeneration and Its Therapeutic Prospects
Authors: Li Lei , He Jiale , Zhang Guangzhi , Chen Haiwei , Luo Zhangbin , Deng Bo , Zhou Yuan , Kang Xuewen
Published: August 2022

Intervertebral disc degeneration (IVDD) is a common musculoskeletal degenerative disease worldwide, of which the main clinical manifestation is low back pain (LBP); approximately, 80% of people suffer from it in their lifetime. Currently, the pathogenesis of IVDD is unclear, and modern treatments can only alleviate its symptoms but cannot inhibit or reverse its progression. However, in recent years, targeted therapy has led to new therapeutic strategies. Cysteine-containing aspartate proteolytic enzymes (caspases) are a family of proteases present in the cytoplasm. They are evolutionarily conserved and are involved in cell growth, differentiation, and apoptotic death of eukaryotic cells. In recent years, it has been confirmed to be involved in the pathogenesis of various diseases, mainly by regulating cell apoptosis and inflammatory response. With continuous research on the pathogenesis and pathological process of IVDD, an increasing number of studies have shown that caspases are closely related to the IVDD process, especially in the intervertebral disc (IVD) cell apoptosis and inflammatory response. Therefore, herein we study the role of caspases in IVDD with respect to the structure of caspases and the related signaling pathways involved. This would help explore the strategy of regulating the activity of the caspases involved and develop caspase inhibitors to prevent and treat IVDD. The aim of this review was to identify the caspases involved in IVDD which could be potential targets for the treatment of IVDD.
Detergent-Free Isolation of Membrane Proteins and Strategies to Study Them in a Near-Native Membrane Environment
Authors: Krishnarjuna Bankala , Ramamoorthy Ayyalusamy
Published: August 2022

Atomic-resolution structural studies of membrane-associated proteins and peptides in a membrane environment are important to fully understand their biological function and the roles played by them in the pathology of many diseases. However, the complexity of the cell membrane has severely limited the application of commonly used biophysical and biochemical techniques. Recent advancements in NMR spectroscopy and cryoEM approaches and the development of novel membrane mimetics have overcome some of the major challenges in this area. For example, the development of a variety of lipid-nanodiscs has enabled stable reconstitution and structural and functional studies of membrane proteins. In particular, the ability of synthetic amphipathic polymers to isolate membrane proteins directly from the cell membrane, along with the associated membrane components such as lipids, without the use of a detergent, has opened new avenues to study the structure and function of membrane proteins using a variety of biophysical and biological approaches. This review article is focused on covering the various polymers and approaches developed and their applications for the functional reconstitution and structural investigation of membrane proteins. The unique advantages and limitations of the use of synthetic polymers are also discussed.
Combination of Dexamethasone and Tofacitinib Reduces Xenogeneic MSC-Induced Immune Responses in a Mouse Model of Alzheimer’s Disease
Authors: Lee Na Kyung , Myeong Su Hyeon , Hwang Jung Won , Sa Jason K. , Son Hyo Jin , Kim Hee Jin , Jang Hyemin , Chang Jong Wook , Na Duk L.
Published: August 2022

We have recently reported on how transplantation of human mesenchymal stem cells (MSCs) into the mouse parenchyma generated immune responses. To facilitate the clinical translation of MSC-based AD therapy, the safety and efficacy of human derived MSCs (hMSCs) must be confirmed in the pre-clinical stage. Thus, it is imperative to investigate measures to reduce immune responses exerted via xenotransplantation. In this study, immunosuppressants were co-administered to mice that had received injections of hMSCs into the parenchyma. Prior to performing experiments using transgenic AD mice (5xFAD), varying immunosuppressant regimens were tested in wild-type (WT) mice and the combination of dexamethasone and tofacitinib (DexaTofa) revealed to be effective in enhancing the persistence of hMSCs. According to transcriptome sequencing and immunohistochemical analyses, administration of DexaTofa reduced immune responses generated via transplantation of hMSCs in the parenchyma of 5xFAD mice. Significant mitigation of amyloid burden, however, was not noted following transplantation of hMSCs alone or hMSCs with DexaTofa. The efficacy of the immunosuppressant regimen should be tested in multiple AD mouse models to promote its successful application and use in AD stem cell therapy.
Rapid and Efficient Extraction of Cell-Free DNA Using Homobifunctional Crosslinkers
Authors: Seong HyeonAh , Park Junsoo , Bae Minju , Shin Sehyun
Published: August 2022

Since its discovery in circulating blood seven decades ago, cell-free DNA (cfDNA) has become a highly focused subject in cancer management using liquid biopsy. Despite its clinical utility, the extraction of cfDNA from blood has many technical difficulties, including a low efficiency of recovery and long processing times. We introduced a magnetic bead-based cfDNA extraction method using homobifunctional crosslinkers, including dimethyl suberimidate dihydrochloride (DMS). Owing to its bifunctional nature, DMS can bind to DNA through either covalent or electrostatic bonding. By adopting amine-conjugated magnetic beads, DMS–DNA complexes can be rapidly isolated from blood plasma. Using standard washing and eluting processes, we successfully extracted cfDNA from plasma within 10 min. This method yielded a 56% higher extraction efficiency than that of a commercial product (QIAamp kit). Furthermore, the instant binding mechanism of amine coupling between the microbeads and DMS–DNA complexes significantly reduced the processing time. These results highlight the potential of this magnetic bead-based homobifunctional crosslinker platform for extraction of cfDNA from blood plasma.
Targeting the Complement Cascade for Treatment of Dry Age-Related Macular Degeneration
Authors: Patel Prem N. , Patel Parth A. , Land Matthew R. , Bakerkhatib-Taha Ibrahim , Ahmed Harris , Sheth Veeral
Published: August 2022

Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss in the elderly population. AMD is characterized in its late form by neovascularization (wet type) or geographic atrophy of the retinal pigment epithelium cell layer (dry type). Regarding the latter type, there is growing evidence supporting an association between the pathophysiology of dry AMD and key proteins in the complement cascade. The complement cascade works as a central part of the innate immune system by defending against foreign pathogens and modified self-tissues. Through three distinct pathways, a series of plasma and membrane-associated serum proteins are activated upon identification of a foreign entity. Several of these proteins have been implicated in the development and progression of dry AMD. Potential therapeutic targets include C1q, C3, C5, complement factors (B, D, H, I), membrane attack complex, and properdin. In this review, we provide an understanding of the role of the complement system in dry AMD and discuss the emerging therapies in early phase clinical trials. The tentative hope is that these drugs may offer the potential to intervene at earlier stages in dry AMD pathogenesis, thereby preventing progression to late disease.
miRNome and Proteome Profiling of Small Extracellular Vesicles Secreted by Human Glioblastoma Cell Lines and Primary Cancer Stem Cells
Authors: Cifola Ingrid , Fratini Federica , Cardinali Beatrice , Palmieri Valentina , Gatti Giuliana , Selmi Tommaso , Donzelli Sara , Sacconi Andrea , Cesarini Valeriana , Marei Hany E. , Papi Massimilano , Blandino Giovanni , Cenciarelli Carlo , Falcone Germana , D’Agnano Igea
Published: August 2022

Glioblastoma (GBM) is the most common and aggressive brain tumor in adults. Despite available therapeutic interventions, it is very difficult to treat, and a cure is not yet available. The intra-tumoral GBM heterogeneity is a crucial factor contributing to poor clinical outcomes. GBM derives from a small heterogeneous population of cancer stem cells (CSCs). In cancer tissue, CSCs are concentrated within the so-called niches, where they progress from a slowly proliferating phase. CSCs, as most tumor cells, release extracellular vesicles (EVs) into the surrounding microenvironment. To explore the role of EVs in CSCs and GBM tumor cells, we investigated the miRNA and protein content of the small EVs (sEVs) secreted by two GBM-established cell lines and by GBM primary CSCs using omics analysis. Our data indicate that GBM-sEVs are selectively enriched for miRNAs that are known to display tumor suppressor activity, while their protein cargo is enriched for oncoproteins and tumor-associated proteins. Conversely, among the most up-regulated miRNAs in CSC-sEVs, we also found pro-tumor miRNAs and proteins related to stemness, cell proliferation, and apoptosis. Collectively, our findings support the hypothesis that sEVs selectively incorporate different miRNAs and proteins belonging both to fundamental processes (e.g., cell proliferation, cell death, stemness) as well as to more specialized ones (e.g., EMT, membrane docking, cell junction organization, ncRNA processing).
The Role of Matrix Metalloproteinase Single-Nucleotide Polymorphisms in the Clinicopathological Properties of Breast Cancer
Authors: Bartnykaitė Agnė , Savukaitytė Aistė , Bekampytė Justina , Ugenskienė Rasa , Laukaitienė Danguolė , Korobeinikova Erika , Gudaitienė Jurgita , Juozaitytė Elona
Published: August 2022

(1) Background. Breast cancer is the leading cancer type among women. Despite convenient diagnostics at early stages, there is a need for continuous monitoring to predict more aggressive or recurring breast cancer forms. The evidence suggests that the detection of genetic biomarkers could help in improving disease management and reduce mortality. Matrix metalloproteinases (MMPs) are a large family of enzymes that perform physiologically relevant functions and have the potential properties to be biomarkers for cancer assessment. We aimed to evaluate the contribution and association of single-nucleotide polymorphisms (SNPs) in MMP genes (MMP1, MMP2, MMP3, MMP7, MMP8, MMP9) with clinicopathological breast-cancer features. (2) Methods. In this study, 100 breast cancer patients were genotyped by polymerase chain reaction–restriction fragment length polymorphism methodology (PCR–RFLP). (3) Results. The presence of the MMP7 rs11568818 A allele was associated with lower chances for poorly differentiated breast cancer. The lower possibility for HER2-positive breast cancer was associated with the presence of the MMP9 rs3918242 C allele. (4) Conclusions. These results indicate that MMP7 rs11568818 and MMP9 rs3918242 are potential biomarkers for the anticipation of breast cancer aggressiveness.
Probing the Hepatitis B Virus E-Antigen with a Nanopore Sensor Based on Collisional Events Analysis
Authors: Bucataru Ioana C. , Dragomir Isabela , Asandei Alina , Pantazica Ana-Maria , Ghionescu Alina , Branza-Nichita Norica , Park Yoonkyung , Luchian Tudor
Published: August 2022

Real-time monitoring, simple operation, and cheaper methods for detecting immunological proteins hold the potential for a solid influence on proteomics and human biology, as they can promote the onset of timely diagnoses and adequate treatment protocols. In this work we present an exploratory study suggesting the applicability of resistive-pulse sensing technology in conjunction with the α-hemolysin (α-HL) protein nanopore, for the detection of the chronic hepatitis B virus (HBV) e-antigen (HBeAg). In this approach, the recognition between HBeAg and a purified monoclonal hepatitis B e antibody (Ab(HBeAg)) was detected via transient ionic current spikes generated by partial occlusions of the α-HL nanopore by protein aggregates electrophoretically driven toward the nanopore’s vestibule entrance. Despite the steric hindrance precluding antigen, antibody, or antigen–antibody complex capture inside the nanopore, their stochastic bumping with the nanopore generated clear transient blockade events. The subsequent analysis suggested the detection of protein subpopulations in solution, rendering the approach a potentially valuable label-free platform for the sensitive, submicromolar-scale screening of HBeAg targets.
A Computational Modeling and Simulation Workflow to Investigate the Impact of Patient-Specific and Device Factors on Hemodynamic Measurements from Non-Invasive Photoplethysmography
Authors: Fine Jesse , McShane Michael J. , Coté Gerard L. , Scully Christopher G.
Published: August 2022

Cardiovascular disease is the leading cause of death globally. To provide continuous monitoring of blood pressure (BP), a parameter which has shown to improve health outcomes when monitored closely, many groups are trying to measure blood pressure via noninvasive photoplethysmography (PPG). However, the PPG waveform is subject to variation as a function of patient-specific and device factors and thus a platform to enable the evaluation of these factors on the PPG waveform and subsequent hemodynamic parameter prediction would enable device development. Here, we present a computational workflow that combines Monte Carlo modeling (MC), gaussian combination, and additive noise to create synthetic dataset of volar fingertip PPG waveforms representative of a diverse cohort. First, MC is used to determine PPG amplitude across age, skin tone, and device wavelength. Then, gaussian combination generates accurate PPG waveforms, and signal processing enables data filtration and feature extraction. We improve the limitations of current synthetic PPG frameworks by enabling inclusion of physiological and anatomical effects from body site, skin tone, and age. We then show how the datasets can be used to examine effects of device characteristics such as wavelength, analog to digital converter specifications, filtering method, and feature extraction. Lastly, we demonstrate the use of this framework to show the insensitivity of a support vector machine predictive algorithm compared to a neural network and bagged trees algorithm.
Measurements of Anti-SARS-CoV-2 Antibody Levels after Vaccination Using a SH-SAW Biosensor
Authors: Cheng Chia-Hsuan , Peng Yu-Chi , Lin Shu-Min , Yatsuda Hiromi , Liu Szu-Heng , Liu Shih-Jen , Kuo Chen-Yen , Wang Robert Y. L.
Published: August 2022

To prevent the COVID-19 pandemic that threatens human health, vaccination has become a useful and necessary tool in the response to the pandemic. The vaccine not only induces antibodies in the body, but may also cause adverse effects such as fatigue, muscle pain, blood clots, and myocarditis, especially in patients with chronic disease. To reduce unnecessary vaccinations, it is becoming increasingly important to monitor the amount of anti-SARS-CoV-2 S protein antibodies prior to vaccination. A novel SH-SAW biosensor, coated with SARS-CoV-2 spike protein, can help quantify the amount of anti-SARS-CoV-2 S protein antibodies with 5 μL of finger blood within 40 s. The LoD of the spike-protein-coated SAW biosensor was determined to be 41.91 BAU/mL, and the cut-off point was determined to be 50 BAU/mL (Youden’s J statistic = 0.94733). By using the SH-SAW biosensor, we found that the total anti-SARS-CoV-2 S protein antibody concentrations spiked 10–14 days after the first vaccination (p = 0.0002) and 7–9 days after the second vaccination (p = 0.0116). Furthermore, mRNA vaccines, such as Moderna or BNT, could achieve higher concentrations of total anti-SARS-CoV-2 S protein antibodies compared with adenovirus vaccine, AZ (p < 0.0001). SH-SAW sensors in vitro diagnostic systems are a simple and powerful technology to investigate the local prevalence of COVID-19.
Fluorescence-Based Measurements of Membrane-Bound Angiotensin Converting Enzyme 2 Activity Using Xenopus Laevis Oocytes
Authors: Fast Luise , Ågren Richard , Zeberg Hugo
Published: August 2022

Functional investigations of enzymes involving cellular expression systems are important for pharmacological studies. The precise control of expression is challenging in transiently transfected mammalian cell lines. Here, we explored the ability of Xenopus laevis oocytes to express a membrane-bound enzyme for functional characterization using standard 96-well plates and a fluorescence-based plate reader assay. We microinjected oocytes with cRNA encoding the angiotensin converting enzyme 2 (ACE2) and measured the enzymatic activity in single oocytes using a commercial fluorescence-based assay. The injected oocytes showed up to a 50-fold increase in fluorescence compared to uninjected oocytes. This fluorescence intensity was dose-dependent on the amount of ACE2 cRNA. These results suggest that Xenopus oocytes can be used for the functional evaluation of membrane-bound enzymes, decreasing the experimental workload.
Neutrophil-to-Lymphocyte, Monocyte-to-Lymphocyte, Platelet-to-Lymphocyte Ratio and Systemic Immune-Inflammatory Index in Different States of Bipolar Disorder
Authors: Dadouli Katerina , Janho Michel B. , Hatziefthimiou Apostolia , Voulgaridi Ioanna , Piaha Konstantina , Anagnostopoulos Lemonia , Ntellas Panagiotis , Mouchtouri Varvara A. , Bonotis Konstantinos , Christodoulou Nikolaos , Speletas Matthaios , Hadjichristodoulou Christos
Published: August 2022

The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammatory (SII) index, which provide a simple, rapid, inexpensive method to measure the level of inflammation, have been examined as potential inflammatory biomarkers of bipolar disorder (BD) in several studies. We conducted a case-control study recruiting 180 BD patients and 407 healthy controls. BD patients who met the inclusion criteria and were hospitalized due to BD at the psychiatry clinic of the University General Hospital of Larisa, Greece, until September 2021 were included in the study. Among them, 111 patients experienced a manic episode and 69 patients experienced a depressive episode. Data including a complete blood count were retrieved from their first admission to the hospital. Bipolar patients had a higher NLR, MLR and SII index compared to healthy controls when they were experiencing a manic episode (p < 0.001) and a depressive episode (p < 0.001). MLR was increased with large effect size only in patients expressing manic episodes. Neutrophils and NLR had the highest area under the curve with a cutoff of 4.38 and 2.15 in the ROC curve, respectively. Gender-related differences were mainly observed in the SII index, with males who were expressing manic episodes and females expressing depressive episodes having an increased index compared to healthy controls. The NLR, MLR and SII index were significantly higher in patients with BD than in healthy controls, which implies a higher grade of inflammation in BD patients.
Effects of Stimulus Frequency, Intensity, and Sex on the Autonomic Response to Transcutaneous Vagus Nerve Stimulation
Authors: Yokota Hirotake , Edama Mutsuaki , Hirabayashi Ryo , Sekine Chie , Otsuru Naofumi , Saito Kei , Kojima Sho , Miyaguchi Shota , Onishi Hideaki
Published: August 2022

This study aimed to determine how transcutaneous vagus nerve stimulation (tVNS) alters autonomic nervous activity by comparing the effects of different tVNS frequencies and current intensities. We also investigated the sex-dependent autonomic response to tVNS. Thirty-five healthy adult participants were stimulated using a tVNS stimulator at the left cymba conchae while sitting on a reclining chair; tVNS-induced waveform changes were then recorded for different stimulus frequencies (Experiment 1: 3.0 mA at 100 Hz, 25 Hz, 10 Hz, 1 Hz, and 0 Hz (no stimulation)) and current intensities (Experiment 2: 100 Hz at 3.0 mA, 1.0 mA, 0.2 mA (below sensory threshold), and 0 mA (no stimulation)) using an electrocardiogram. Pulse widths were set at 250 µs in both experiment 1 and 2. Changes in heart rate (HR), root-mean-square of the difference between two successive R waves (RMSSD), and the ratio between low-frequency (LF) (0.04–0.15 Hz) and high-frequency (HF) (0.15–0.40 Hz) bands (LF/HF) in spectral analysis, which indicates sympathetic and parasympathetic activity, respectively, in heart rate variability (HRV), were recorded for analysis. Although stimulation at all frequencies significantly reduced HR (p = 0.001), stimulation at 100 Hz had the most pronounced effect (p = 0.001) in Experiment 1 and was revealed to be required to deliver at 3.0 mA in Experiment 2 (p = 0.003). Additionally, participants with higher baseline sympathetic activity experienced higher parasympathetic response during stimulation, and sex differences may exist in the autonomic responses by the application of tVNS. Therefore, our findings suggest that optimal autonomic changes induced by tVNS to the left cymba conchae vary depending on stimulating parameters and sex.
Examining Predictors of Different ABA Treatments: A Systematic Review
Authors: Cerasuolo Mariangela , Simeoli Roberta , Nappo Raffaele , Gallucci Maria , Iovino Luigi , Frolli Alessandro , Rega Angelo
Published: August 2022

In the recent literature, there is a broad consensus on the effectiveness of Applied Behavior Analysis interventions for autism spectrum disorder (ASD). Despite their proven efficacy, research in clinical settings shows that these treatments are not equally effective for all children and the issue of which intervention should be chosen for an individual remains a common dilemma. The current work systematically reviewed studies on predictors and moderators of response to different types of evidence-based treatment for children with ASD. Specifically, our goal was to critically review the relationships between pre-treatment child characteristics and specific treatment outcomes, covering different aspects of functioning (i.e., social, communicative, adaptive, cognitive, motor, global functioning, play, and symptom severity). Our results questioned the binomial “better functioning-better outcome”, emphasizing the complex interplay between pre-treatment child characteristics and treatment outcomes. However, some pre-treatment variables seem to act as prerequisites for a specific treatment, and the issue of “what works for whom and why” remains challenging. Future research should focus on the definition of evidence-based decision-making models that capture those individual factors through which a specific intervention will exert its effects.