bluuebunny/crossref_metadata_2025 huggingface dataset:
Cell-Penetrating Antimicrobial Peptides with Anti-Infective Activity against Intracellular Pathogens
Authors: Cruz Gabriela Silva , Santos Ariane Teixeira dos , Brito Erika Helena Salles de , Rádis-Baptista Gandhi
Published: December 2022

Cell-penetrating peptides (CPPs) are natural or engineered peptide sequences with the intrinsic ability to internalize into a diversity of cell types and simultaneously transport hydrophilic molecules and nanomaterials, of which the cellular uptake is often limited. In addition to this primordial activity of cell penetration without membrane disruption, multivalent antimicrobial activity accompanies some CPPs. Antimicrobial peptides (AMPs) with cell-penetrability exert their effect intracellularly, and they are of great interest. CPPs with antimicrobial activity (CPAPs) comprise a particular class of bioactive peptides that arise as promising agents against difficult-to-treat intracellular infections. This short review aims to present the antibacterial, antiparasitic, and antiviral effects of various cell-penetrating antimicrobial peptides currently documented. Examples include the antimicrobial effects of different CPAPs against bacteria that can propagate intracellularly, like Staphylococcus sp., Streptococcus sp., Chlamydia trachomatis, Escherichia coli, Mycobacterium sp., Listeria sp., Salmonella sp. among others. CPAPs with antiviral effects that interfere with the intracellular replication of HIV, hepatitis B, HPV, and herpes virus. Additionally, CPAPs with activity against protozoa of the genera Leishmania, Trypanosoma, and Plasmodium, the etiological agents of Leishmaniasis, Chagas’ Disease, and Malaria, respectively. The information provided in this review emphasizes the potential of multivalent CPAPs, with anti-infective properties for application against various intracellular infections. So far, CPAPs bear a promise of druggability for the translational medical use of CPPs alone or in combination with chemotherapeutics. Moreover, CPAPs could be an exciting alternative for pharmaceutical design and treating intracellular infectious diseases.
Binary and Multi-Class Malware Threads Classification
Authors: Ahmed Ismail Taha , Jamil Norziana , Din Marina Md. , Hammad Baraa Tareq
Published: December 2022

The security of a computer system can be harmed by specific applications, such as malware. Malware comprises unwanted, dangerous enemies that aim to compromise the security and generate significant loss. Consequently, Malware Detection (MD) and Malware Classification (MC) has emerged as a key issue for the cybersecurity society. MD only involves locating malware without determining what kind of malware it is, but MC comprises assigning a class of malware to a particular sample. Recently, a few techniques for analyzing malware quickly have been put out. However, there remain numerous difficulties, such as the low classification accuracy of samples from related malware families, the computational complexity, and consumption of resources. These difficulties make detecting and classifying malware very challenging. Therefore, in this paper, we proposed an efficient malware detection and classification technique that combines Segmentation-based Fractal Texture Analysis (SFTA) and Gaussian Discriminant Analysis (GDA). The outcomes of the experiment demonstrate that the SFTA-GDA produces a high classification rate. There are three main steps involved in our malware analysis, namely: (i) malware conversion; (ii) feature extraction; and (iii) classification. We initially convert the RGB malware images into grayscale malware images for effective malware analysis. The SFTA and Gabor features are then extracted from gray-scale images in the feature extraction step. Finally, the classification is carried out by GDA and Naive Bayes (NB). The proposed method is evaluated on a common MaleVis dataset. The proposed SFTA-GDA is the effective choice since it produces the highest accuracy rate across all families of the MaleVis Database. Experimental findings indicate that the accuracy rate was 98%, which is higher than the overall accuracy from the existing state-of-the-art methods.
Development of an Evaluation Method for Deriving the Water Loss Reduction Factors of Water Distribution Systems: A Case Study in Korean Small and Medium Cities
Authors: Choi Young Hwan , Choi Taeho , Yoo Do Guen , Lee Seungyub
Published: December 2022

This study introduces a method that can evaluate the efficiency of leakage management practices and devises a formula to set leakage management goals. To develop the evaluation method for deriving leakage reduction factors, real data from small- and medium-sized cities in South Korea were collected. With the data collected, four leakage management factors (or activities) that could improve revenue water ratio or reduce leakage ratio were identified. With the leakage management factors, correlation analysis was carried out to identify the relationship between independent and dependent variables and within independent variables. Once the relationships were identified, standardization of the data using T-score conversion was carried out to scale all data with different units into similar ranges. Finally, the efficiency of leakage management actions was determined by the formulation of leakage using various data analysis approaches using multiple linear regression analysis and deep neural networks. As a result, pipe replacement was determined as an essential activity to decrease the leakage ratio or increase the revenue water ratio. In addition, annual water loss management actions of the small cities were more actively performed. Furthermore, the performance of data analysis using DNN is more appropriate in data classification, considering the characteristics of time series rather than independent data analysis. Through comparison of the above data classification approaches, the increase or decrease in the leakage ratio/revenue water ratio by the water loss management activity of local water distribution systems can be used to construct a more effective model for classification considering both local and temporal characteristics.
Effect Evaluation of Train Speed and Embankment Stiffness on Ground Vibrations Using Numerical Simulation
Authors: Yang Jiaqiang , Zhu Yulong , Miao Pengyong
Published: December 2022

This paper presents a transient-dynamic method (TDM), to investigate the dynamic responses of a railway formation under a train moving load using a three-dimensional finite element model. First, the feasibility of the TDM was verified, by comparing the vertical stress in a railway formation calculated using this method with the steady-state method (SSM). Next, the effects of train speed and embankment stiffness on the dynamic response of the railway formation were evaluated using TDM. The numerical results indicated that the vertical displacement/stress of the railway formation were remarkably increased with an increased train speed, within the shear wave velocity of the soft soil. In contrast, the vertical displacement/stress attenuation with the depth of the ground caused by high-speed trains was faster than that caused by low-speed trains. As for the effect of embankment stiffness, the enhancement of embankment stiffness had little effect on the transfer of vertical stress to the underlying soil. Finally, a determination of the dynamic stress for different train speeds was evaluated. This design code may underestimate the dynamic stress in a railway formation in high-speed situations (e.g., v = 112 m/s).
A Comprehensive Review of Face Morph Generation and Detection of Fraudulent Identities
Authors: Hamza Muhammad , Tehsin Samabia , Humayun Mamoona , Almufareh Maram Fahaad , Alfayad Majed
Published: December 2022

A robust facial recognition system that has soundness and completeness is essential for authorized control access to lawful resources. Due to the availability of modern image manipulation technology, the current facial recognition systems are vulnerable to different biometric attacks. Image morphing attack is one of these attacks. This paper compares and analyzes state-of-the-art morphing attack detection (MAD) methods. The performance of different MAD methods is also compared on a wide range of source image databases. Moreover, it also describes the morph image generation techniques along with the limitations, strengths, and drawbacks of each morphing technique. Results are investigated and compared with in-depth analysis providing insight into the vulnerabilities of existing systems. This paper provides vital information that is essential for building a next generation morph attack detection system.
Design and Implementation of Multi-Cyber Range for Cyber Training and Testing
Authors: Park Moosung , Lee Hyunjin , Kim Yonghyun , Kim Kookjin , Shin Dongkyoo
Published: December 2022

It is essential to build a practical environment of the training/test site for cyber training and weapon system test evaluation. In a military environment, cyber training sites should be continuously developed according to the characteristics of the military. Weapons with cyber security capabilities should be deployed through cyber security certification. Recently, each military has been building its own cyber range that simulates its battlefield environment. However, since the actual battlefield is an integrated operation environment, the cyber range built does not reflect the integrated battlefield environment that is interconnected. This paper proposes a configuration plan and operation function to construct a multi-cyber range reflecting the characteristics of each military to overcome this situation. In order to test the multi-cyber range, which has scenario authoring and operation functions, and can faithfully reflect reality, the impact of DDoS attacks is tested. It is a key to real-world mission-based test evaluation to ensure interoperability between military systems. As a result of the experiment, it was concluded that if a DDoS attack occurs due to the infiltration of malicious code into the military network, it may have a serious impact on securing message interoperability between systems in the military network. Cyber range construction technology is being developed not only in the military, but also in school education and businesses. The proposed technology can also be applied to the construction of cyber ranges in industries where cyber-physical systems are emphasized. In addition, it is a field that is continuously developing with the development of technology, such as being applied as an experimental site for learning machine learning systems.
CO2 Emission Analysis for Different Types of Electric Vehicles When Charged from Floating Solar Photovoltaic Systems
Authors: Ramshanker Abinands , Chakraborty Suprava , Elangovan Devaraj , Kotb Hossam , Aboras Kareem M. , Giri Nimay Chandra , Agyekum Ephraim Bonah
Published: December 2022

Renewable energy and electric vehicle technology are the two pillars for achieving a sustainable future. Floating solar power plants use PV modules on water infrastructure to save the land and increase module efficiency. Furthermore, the reduction in evaporation saves water. Electric vehicles are one of the fastest-growing markets and the most successful technologies to combat the problem of energy and climate change. This research aims to construct a floating PV system on the lake of the Vellore Institute of Technology (VIT), to analyze electric vehicle performance and greenhouse gas (GHG) emissions when charged using the installed floating PV system. To address this, a 1.5 MWP floating PV system was simulated and analyzed using Helioscope software. When charged from the proposed floating PV plant, electric bikes, scooters, and cars saved CO2 emissions. When charged from a floating PV, E-bike, E-scooter, and E-car Net CO2 emissions became zero in 25.5, 12.1, and 7.7 months, respectively. After the aforementioned time periods, all three electric vehicle types were zero-emission vehicles. The required charge for all three types of vehicles (1,000,000 km) was analyzed using a floating PV system. E-bike, E-scooter, and E-car CO2 emission savings were −8,516,000 g/kWh, −328,000 g/kWh, and 525,600,000 g/kWh, respectively. All three types of electric vehicles can reduce CO2 emissions for nations that rely on renewable energy, but only electric cars save carbon emissions over fixed distances. Through this research, we finally conclude that electric cars reduce CO2 emissions the most compared to other electric vehicles.
Horticulture 4.0: Adoption of Industry 4.0 Technologies in Horticulture for Meeting Sustainable Farming
Authors: Singh Rajat , Singh Rajesh , Gehlot Anita , Akram Shaik Vaseem , Priyadarshi Neeraj , Twala Bhekisipho
Published: December 2022

The United Nations emphasized a significant agenda on reducing hunger and protein malnutrition as well as micronutrient (vitamins and minerals) malnutrition, which is estimated to affect the health of up to two billion people. The UN also recognized this need through Sustainable Development Goals (SDG 2 and SDG 12) to end hunger and foster sustainable agriculture by enhancing the production and consumption of fruits and vegetables. Previous studies only stressed the various issues in horticulture with regard to industries, but they did not emphasize the centrality of Industry 4.0 technologies for confronting the diverse issues in horticulture, from production to marketing in the context of sustainability. The current study addresses the significance and application of Industry 4.0 technologies such as the Internet of Things, cloud computing, artificial intelligence, blockchain, and big data for horticulture in enhancing traditional practices for disease detection, irrigation management, fertilizer management, maturity identification, marketing, and supply chain, soil fertility, and weather patterns at pre-harvest, harvest, and post-harvest. On the basis of analysis, the article identifies challenges and suggests a few vital recommendations for future work. In horticulture settings, robotics, drones with vision technology and AI for the detection of pests, weeds, plant diseases, and malnutrition, and edge-computing portable devices that can be developed with IoT and AI for predicting and estimating crop diseases are vital recommendations suggested in the study.
A Simple Portable Magnetometer Based on Magnets and Hall-Effect Sensors Capable of Measuring Magnetic Properties
Authors: Araujo Jefferson F. D. F. , Junior Eloi B. M. , Mendoza Leonardo A. F.
Published: December 2022

A magnetometer based on Hall effect sensors was developed using a 1020 steel base, two magnets (K&J Magnetics, Pipersville, PA, USA), and two Hall effect sensors: MLX-90215 (Melexis Inc., San Jose, CA, USA) and AD-AD22151 (Analog Devices, Inc., Wilmington, MA, USA). Both sensors were assembled on an acrylic support and powered with a 5-volt battery. The readings can be taken using bench multimeters (HP 34401A or Iminipa ET-2042D). The magnetometer records magnetic hysteresis loop and saturation by applying a field of up to 0.33 T at room temperature. The device was tested using magnetic hysteresis data from samples of 99% pure nickel sphere and magnetite microparticles. A dipole magnetic model was used to obtain the moment of the samples. The sensor used for reading the induced magnetic field of the sample AD-AD22151 has a sensitivity can be adjusted from to 110 mV/mT. This device is cheap, versatile, and easy to build, and despite its low accuracy, when compared to commercial equipment, it can be useful in low-budget teaching and research laboratories.
Case Study of an Underpinning Pile Foundation for an Interval Tunnel Crossing an Existing Bridge
Authors: Zhou Yuhang , Liu Yuanming , Chen Qingzhi , Ou Xun , Li Yingxiao
Published: December 2022

When urban subway tunnels cross existing bridge pile foundations, having a pile foundation underpinning that ensures the safe operation of existing bridges while enabling the safe construction of subway tunnels is the focus of attention. This paper takes the running tunnel project from Huaguoyuan West Station to Huaguoyuan East Station of Rail Transit Line 3 in Guiyang City, Guizhou Province as the background. The reasonableness and feasibility of the passive underpinning construction scheme for the Guihuang Viaduct was studied. The construction plan includes the following steps: underpinning pile construction, foundation pit excavation, the concreting of the underpinning bearing platform, and existing pile truncation. In order to ensure the structural safety of the existing viaduct during the construction of the pile foundation underpinning, a 3D numerical model of the construction of pile foundation underpinning and the whole process of tunnel construction was established. The settlement calculation results of the foundation pit and bridge pier were compared and analyzed with the field monitoring data to verify the accuracy of the numerical model. Further detailed analysis of the settlement of the bridge deck, the deformation of the existing piles, the axial forces of the existing piles, and the forces on the underpinning bearing platform was carried out. The results show that the bridge superstructure load can be transferred to the underpinning bearing platform smoothly after the existing pile truncation construction. The removal of obstacle piles during tunnel excavation has a very limited impact on the superstructure of the bridge, proving the reasonableness and feasibility of the construction plan.
Highly Enriched Uranium-Free Medical Radioisotope Production Methods: An Integrative Review
Authors: Nunes Bruno Silveira , Rodrigues Enio Rodrigo Fernandes , Fruscalso Jonathan Alexander Prestes , Nunes Roger Pizzato , Bonatto Alexandre , Alva-Sánchez Mirko Salomón
Published: December 2022

The ever-growing need for radiopharmaceuticals, i.e., compounds containing pharmaceutical drugs and radioisotopes used for medical diagnostic imaging (SPECT/PET scan) and treating neoplasms, is significantly leading to an increased demand for such substances in hospitals and clinics worldwide. Currently, most large-scale productions of radioisotopes required for radiopharmaceuticals are carried out in research reactors, via the fission of highly enriched uranium. However, because large amounts of radioactive waste are produced as byproducts in this process, new greener methods are needed for radioisotope production. This work presents an integrative literature review and summarizes enriched uranium-free methods for radioisotope production, accomplished through the adoption of new reaction routes, distinct acceleration technologies, or by using other physical processes. This review considered forty-eight studies published from 2010 to 2021 on three established virtual databases. Among these selected works, a cyclotron is the most adopted HEU-free method for radioisotope production, and 44Sc, 68Ga, and 99mTc are the medical radioisotopes most often reported as produced by using the investigated HEU-free production methods.
Micro-Vibration Signal Denoising Algorithm of Spectral Morphology Fitting Based on Variational Mode Decomposition
Authors: Yu Caizhi , Lu Yutai , Li Yue , Wang Peng , Sun Changku
Published: December 2022

Environmental micro-vibration has a significant impact on the proper functioning of semiconductor production and testing equipment such as the Czochralski growth furnace, polishing machine, photoetching machine, scanning electron microscope, etc. Low-frequency micro vibration has a significant influence on the normal operation of high-precision machining and testing equipment, and even causes irreversible damage to the equipment. Therefore, the micro-vibration test has important theoretical significance and engineering value for guiding the vibration isolation design of an electronic industrial workshop and ensuring the stable operation of various precision equipment in the workshop. As the observed acceleration signal is affected by noise introduced by the acceleration sensor itself, the signal processing circuit, the external power supply and interference from environmental factors, direct integration operations can lead to problems such as baseline drift and signal distortion in the calculation results. Aiming at the problem of noise interference in the micro-vibration measurement process, this paper proposed a micro-vibration signal denoising algorithm of spectral morphology fitting based on variational mode decomposition. The observed acceleration signal is decomposed into several orders of finite bandwidth intrinsic mode function components. The asymmetric Gaussian mixture model is used to complete the fitting of the spectral curves of each order of intrinsic mode function components. We can obtain the relevant parameters of the asymmetric Gaussian mixture model curves to complete the division of the effective information frequency band and finally achieve the denoising of the observed acceleration signal. Finally, the algorithm of this paper is compared with traditional denoising algorithms through numerical simulation examples and comparative experiments on denoising effects. The results show that the proposed algorithm has higher accuracy and anti-noise ability.
Supervised Machine Learning and Deep Learning Techniques for Epileptic Seizure Recognition Using EEG Signals—A Systematic Literature Review
Authors: Nafea Mohamed Sami , Ismail Zool Hilmi
Published: December 2022

Electroencephalography (EEG) is a complicated, non-stationary signal that requires extensive preprocessing and feature extraction approaches to be accurately analyzed. In recent times, Deep learning (DL) has shown great promise in exploiting the characteristics of EEG signals as it can learn relevant features from raw data autonomously. Although studies involving DL have become more common in the last two years, the topic of whether DL truly delivers advantages over conventional Machine learning (ML) methodologies remains unsettled. This study aims to present a detailed overview of the main challenges in the field of seizure detection, prediction, and classification utilizing EEG data, and the approaches taken to solve them using ML and DL methods. A systematic review was conducted surveying peer-reviewed publications published between 2017 and 16 July 2022 using two scientific databases (Web of Science and Scopus) totaling 6822 references after discarding duplicate publications. Whereas 2262 articles were screened based on the title, abstract, and keywords, only 214 were eligible for full-text assessment. A total of 91 papers have been included in this survey after meeting the eligible inclusion and exclusion criteria. The most significant findings from the review are summarized, and several important concepts involving ML and DL for seizure detection, prediction, and classification are discussed in further depth. This review aims to learn more about the different approaches for identifying different types and stages of epileptic seizures, which may then be employed to enhance the lives of epileptic patients in the future, as well as aid experts in the field.
Effects on Biomarkers in Stress Ecology Studies. Well, So What? What Now?
Authors: Lemos Marco F. L. , Duarte Bernardo , Fonseca Vanessa F. , Novais Sara C.
Published: December 2022

Effects assessed at higher levels of biological organization (populations and communities) are the consequence of the sum of effects on individuals, which usually result from impacts at cellular and molecular levels. Given this rationale, these lower levels of biological organization are more responsive at an early stage, making them potential resources that can be used as early warning endpoints to address environmental stress. In this way, the information concerning effects at the molecular level of biological organization (e.g., transcripts, proteins, or metabolites) allows for an early assessment of future ecosystem problems, which may eventually enable a timely intervention before the impacts become visible and irreversible. However, despite providing an early warning and a better understanding of the toxicity mechanisms, enabling the protection of biological integrity, the most significant setback is that these endpoints may fail to foresee later impacts on the environment due to the ecosystem resilience or a weak link to the effects in the following level of biological organization, making these tools simply too conservative for stakeholders’ interests. Hence, an approach targeting lower levels of biological organization will greatly benefit from addressing potential effects at higher levels. This can be achieved by establishing a link in biological organization, where the effects assessed at the lower end of biological organization are linked with the high probability of causing an effect at the other end, inducing changes in populations and communities, and eventually altering ecosystems in the future.
Characterization of Short Chain Fatty Acids Produced by Selected Potential Probiotic Lactobacillus Strains
Authors: Thananimit Suchera , Pahumunto Nuntiya , Teanpaisan Rawee
Published: December 2022

Short-chain fatty acids (SCFAs), particularly butyrate, have received considerable attention with regard to their anti-cancer efficacy in delaying or preventing colorectal cancer. Several studies have reported that certain probiotic strains could produce SCFAs; however, different strains yielded different amounts of SCFAs. This study explored the ability to produce SCFAs of the following probiotic strains: Lacticaseibacillus paracasei SD1, Lacticaseibacillus rhamnosus SD4, Lacticaseibacillus rhamnosus SD11, and Lacticaseibacillus rhamnosus GG. L. paracasei SD1 and L. rhamnosus SD11 exhibited high butyrate production, particularly when the strains were combined. The functions of the SCFAs were further characterized; the SCFAs exerted a positive anti-cancer effect in the colon via various actions, including inhibiting the growth of the pathogens related to colon cancer, such as Fusobacterium nucleatum and Porphyromonas gingivalis; suppressing the growth of cancer cells; and stimulating the production of the anti-inflammatory cytokine IL-10 and antimicrobial peptides, especially human β-defensin-2. In addition, the SCFAs suppressed pathogen-stimulated pro-inflammatory cytokines, especially IL-8. The results of this study indicated that selected probiotic strains, particularly L. paracasei SD1 in combination with L. rhamnosus SD11, may serve as good natural sources of bio-butyrate, which may be used as biotherapy for preventing or delaying the progression of colon cancer.
Comprehensive Analysis of Transcriptomics and Genetic Alterations Identifies Potential Mechanisms Underlying Anthracycline Therapy Resistance in Breast Cancer
Authors: Liu Zihao , Gao Jingbo , Gu Ran , Shi Yu , Hu Hong , Liu Jianlan , Huang Jiefeng , Zhong Caineng , Zhou Wenbin , Yang Yaping , Gong Chang
Published: December 2022

Anthracycline is a mainstay of treatment for breast cancer patients because of its antitumor activity. However, anthracycline resistance is a critical barrier in treating breast cancer. Thus, it is of great importance to uncover the molecular mechanisms underlying anthracycline resistance in breast cancer. Herein, we integrated transcriptome data, genetic alterations data, and clinical data of The Cancer Genome Atlas (TCGA) to identify the molecular mechanisms involved in anthracycline resistance in breast cancer. Two hundred and four upregulated genes and 1376 downregulated genes were characterized between the anthracycline-sensitive and anthracycline-resistant groups. It was found that drug resistance-associated genes such as ABCB5, CYP1A1, and CYP4Z1 were significantly upregulated in the anthracycline-resistant group. The gene set enrichment analysis (GSEA) suggested that the P53 signaling pathway, DNA replication, cysteine, and methionine metabolism pathways were associated with anthracycline sensitivity. Somatic TP53 mutation was a common genetic abnormality observed in the anthracycline-sensitive group, while CDH1 mutation was presented in the anthracycline-resistant group. Immune infiltration patterns were extremely different between the anthracycline-sensitive and anthracycline-resistant groups. Immune-associated chemokines and cytokines, immune regulators, and human leukocyte antigen genes were significantly upregulated in the anthracycline-sensitive group. These results reveal potential molecular mechanisms associated with anthracycline resistance.
Antipsychotics in the Treatment of Children and Adolescents with Anorexia Nervosa: A Systematic Review
Authors: Pruccoli Jacopo , Bergonzini Luca , La Tempa Angela , Parmeggiani Antonia
Published: December 2022

Evidence about the use of pharmacologic agents in the treatment of Anorexia Nervosa (AN) is lacking, especially in childhood and adolescence. A systematic scoping review was conducted to outline current literature evidence about the use of antipsychotics in this population. A total of 499 studies were identified with the initial search, and 28 of these studies were selected regarding the use of olanzapine (n = 13), risperidone (n = 4), aripiprazole (n = 3), chlorpromazine (n = 3), pimozide (n = 1) clotiapine (n = 1) and multiple antipsychotics (n = 3) in these patients. Overall, major side effects were reported infrequently; improvements in psychopathology and weight measures have been suggested in the majority of the considered studies. Nonetheless, the lack of RCT or good-quality studies strongly limits the generalizability of results in clinical practice.
Efficacy and Safety of Cabozantinib in Patients with Advanced or Metastatic Renal Cell Carcinoma: A Multicenter Retrospective Cohort Study
Authors: Iinuma Koji , Tomioka-Inagawa Risa , Kameyama Koji , Taniguchi Tomoki , Kawada Kei , Ishida Takashi , Nagai Shingo , Enomoto Torai , Ueda Shota , Kawase Makoto , Takeuchi Shinichi , Kawase Kota , Kato Daiki , Takai Manabu , Nakane Keita , Koie Takuya
Published: December 2022

A multicenter retrospective study was conducted to evaluate the efficacy and safety of cabozantinib in patients with advanced or metastatic renal cell carcinoma (mRCC). We enrolled 53 patients with mRCC who received cabozantinib at eight institutions in Japan. The primary endpoint was overall survival (OS). The secondary endpoints were objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). In addition, we analyzed prognostic factors in patients with mRCC treated with cabozantinib. The median follow-up period was 8 months, and the median OS was 20.0 months. The ORR and DCR were 39.6% and 83.0%, respectively. The median PFS was 11.0 months. PFS was significantly shorter in patients previously treated with at least two tyrosine kinase inhibitors and in those with C-reactive protein (CRP) ≥ 1.27 mg/dL (p = 0.021 and p = 0.029, respectively). Adverse events of any grade and grades ≥3 occurred in 42 (79.2%) and 10 (18.9%) patients, respectively. Cabozantinib is a useful treatment option for patients with mRCC and may benefit from earlier use. In this study, CRP ≥ 1.27 mg/dL is a poor prognostic factor in patients treated with cabozantinib, and careful follow-up may be required in treating patients with high CRP.
Systemic Rotenone Administration Causes Extra-Nigral Alterations in C57BL/6 Mice
Authors: Thomas Broome Sarah , Castorina Alessandro
Published: December 2022

Systemic administration of rotenone replicates several pathogenic and behavioural features of Parkinson’s disease (PD), some of which cannot be explained by deficits of the nigrostriatal pathway. In this study, we provide a comprehensive analysis of several neurochemical alterations triggered by systemic rotenone administration in the CNS of C57BL/6 mice. Mice injected with either 1, 3 or 10 mg/kg rotenone daily via intraperitoneal route for 21 days were assessed weekly for changes in locomotor and exploratory behaviour. Rotenone treatment caused significant locomotor and exploratory impairment at dosages of 3 or 10 mg/kg. Molecular analyses showed reductions of both TH and DAT expression in the midbrain, striatum and spinal cord, accompanied by altered expression of dopamine receptors and brain-derived neurotrophic factor (BDNF). Rotenone also triggered midbrain-restricted inflammatory responses with heightened expression of glial markers, which was not seen in extra-nigral regions. However, widespread alterations of mitochondrial function and increased signatures of oxidative stress were identified in both nigral and extra-nigral regions, along with disruptions of neuroprotective peptides, such as pituitary adenylate cyclase-activating polypeptide (PACAP), vasoactive intestinal peptide (VIP) and activity-dependent neuroprotective protein (ADNP). Altogether, this study shows that systemic rotenone intoxication, similarly to PD, causes a series of neurochemical alterations that extend at multiple CNS levels, reinforcing the suitability of this pre-clinical model for the study extra-nigral defects of PD.
Current Status of Measurement Accuracy for Total Hemoglobin Concentration in the Clinical Context
Authors: Stawschenko Elena , Schaller Tim , Kern Benjamin , Bode Berit , Dörries Frank , Kusche-Vihrog Kristina , Gehring Hartmut , Wegerich Philipp
Published: December 2022

Objective: The main objective of this investigation is to provide data about the accuracy of total hemoglobin concentration measurements with respect to clinical settings, and to devices within the categories of point-of-care and reference systems. In particular, tolerance of hemoglobin concentrations below 9 g/dL that have become common in clinical practice today determines the need to demonstrate the limits of measurement accuracy in patient care. Methods: Samples extracted from six units of heparinized human blood with total hemoglobin concentrations ranging from 3 to 18 g/dL were assigned to the test devices in a random order. The pool of test devices comprised blood gas analyzers, an automatic hematology analyzer, a laboratory reference method, and the point-of-care system HemoCue. To reduce the pre-analytic error, each sample was measured three times. Due to the characteristics of the tested devices and methods, we selected the mean values of the data from all these devices, measured at the corresponding total hemoglobin concentrations, as the reference. Main results: The measurement results of the test devices overlap within strict limits (R2 = 0.999). Only the detailed analysis provides information about minor but systematic deviations. In the group of clinically relevant devices, which are involved in patient blood management decisions, the relative differences were within the limit of +/− 5 % for values down to 3 g/dL. Conclusions: A clinically relevant change of +/− 0.5 g/dL of total hemoglobin concentration can be detected with all selected devices and methods. Compliance with more stringent definitions—these are the relative differences of 5 % in relation to the corresponding reference values and the clinically adapted thresholds in the format of a tolerance level analysis—was achieved by the clinical devices assessed here.
SERS Sensor for Human Glycated Albumin Direct Assay Based on Machine Learning Methods
Authors: Slipchenko Ekaterina A. , Boginskaya Irina A. , Safiullin Robert R. , Ryzhikov Ilya A. , Sedova Marina V. , Afanasev Konstantin N. , Nechaeva Natalia L. , Kurochkin Ilya N. , Merzlikin Alexander M. , Lagarkov Andrey N.
Published: December 2022

In this study, a non-labeled sensor system for direct determining human glycated albumin levels for medical application is proposed. Using machine learning methods applied to surface-enhanced Raman scattering (SERS) spectra of human glycated albumin and serum human albumin enabled the avoidance of complex sample preparation. By implementing linear discriminant analysis and regularized linear regression, classification and regression problems were solved based on the spectra obtained as a result of the experiment. The results show that, coupled with data augmentation and a special cross-validation procedure, the methods we employed yield better results in the corresponding tasks in comparison with popular random forest methods and the support vector method. The results show that SERS, in combination with machine learning methods, can be a powerful and effective tool for the simple and direct assay of protein mixtures.
Droplet-Based Microfluidic Platform for High Spatiotemporal Resolved Single-Cell Signaling Profiling
Authors: Sun Yingnan , Tian Qingqing , Liu Yongshu , Xing Kunming , Li Yuyan , Liu Yumin , Zhang Shusheng
Published: December 2022

A small indentation embedded in a microchannel creates a surface energy well (SEW) for a confined droplet due to surface energy release. Inspired by this, we developed a SEW-based microfluidic platform to realize high spatiotemporal-resolved signal profiling at the single-cell level applying droplet stimulus on a single chip. The method allows for controlled droplet replacement within only 3 s with almost 100% exchange efficiency, reliable single-cell patterning of adherent cells and successive treatment of adherent cells with reagent droplets. Furthermore, the PDGFR/Akt pathway served as a model system for evaluating the performance of the SEW-based method in determining the effects of ligand stimulation duration (3 s to 3 min) on receptor phosphorylation. The novel strategy offers a general platform for probing the temporal dynamics of single cells, as well for monitoring rapid chemical reactions in various applications.
Observational Tools Using Video Recordings of Parent-Child Feeding Interactions: A Narrative Review
Authors: D’Angeli Gessica , Mesce Martina , Cerniglia Luca , Cimino Silvia
Published: December 2022

Current research has confirmed that the quality of the caregiver-child relationship influences the child’s emotional and behavioral development. Play and feeding contexts, for example, are the best contexts to observe mother-child or father-child interaction. The observation of feeding interaction establishes involvement on the part of both parties and identifies relationship characteristics. The purpose of this study is to select and describe the most frequently used observational methods during feeding interactions in the first three years of a child’s life. Instruments that employ video recordings of mealtimes will be detailed to highlight the relevance that specific tools have nowadays. Finally, the SVIA (Scala di Valutazione delle Interazioni Alimentari), a technique for analyzing food interactions by observation that has also been utilized remotely, will be offered. This is intended to provide practitioners and researchers with an overview of tools while also taking into consideration the present scenario in which digital tools are increasingly being employed in health and clinical settings. Furthermore, the purpose of this paper is to review the various observational methods of the parent-child relationship to assist future practitioners and researchers in the field in making an accurate assessment of caregiver-child interaction and selecting a valid tool for the early recognition of problematic relationships and identifying the most appropriate treatment modalities.
Anti-Aging, Anti-Acne, and Cytotoxic Activities of Houttuynia cordata Extracts and Phytochemicals Analysis by LC-MS/MS
Authors: Phosri Santi , Kiattisin Kanokwan , Intharuksa Aekkhaluck , Janon Raveeporn , Na Nongkhai Tanat , Theansungnoen Tinnakorn
Published: December 2022

Although many biological properties of Houttuynia cordata have been found, its anti-aging and anti-acne effects have not yet been investigated. This study was aimed to evaluate the in vitro anti-aging and anti-acne activities of H. cordata extracts and their cytotoxic activities and phytochemicals analyzed with liquid chromatography with tandem mass spectrometry (LC-MS/MS). Dried aerial parts of H. cordata were given different extractions. The aqueous and ethanolic extracts obtained were named HCA and HCE, respectively, and used to screen total phenolic and flavonoid contents. In vitro anti-aging, skin-related antimicrobial, scanning electron microscopy (SEM), in vitro cytotoxic, and LC-MS/MS analyses were performed. The total phenolic contents of the HCA and HCE were 5.11 ± 0.25 and 27.02 ± 1.07 mg gallic acid equivalent (GAE)/g dry extract while their total flavonoid contents were 104.94 ± 5.16 and 571.86 ± 2.86 mg quercetin equivalent (QE)/g dry extract, respectively. The HCA and HCE inhibited the activities of collagenase (28.33–46.00%), elastase (30.00–34.33%), and hyaluronidase (93.87–98.72%). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the HCA against Cutibacterium acnes DMST14916 were 5.77 and 5.77 mg/mL while those of the HCE were 2.47 and 2.47 mg/mL, respectively. Cell collapses of C. acnes after treatment with the extracts were observed with SEM. The HCE was not toxic to macrophages, keratinocytes, and fibroblasts up to 400 mg/mL. The HCA showed toxicity against macrophages at 62.5 mg/mL and both skin cells at 250 mg/mL. The main phytochemicals in the extracts were identified with LC-MS/MS. Phenolic compounds, flavonoids, and flavonoid derivatives in H. cordata extracts could be major phytochemicals to possess a broad spectrum of biological activities including antioxidant, antimicrobial, and anti-aging activities. The findings from this study showed that the HCE has potential anti-aging and anti-acne properties while having non-cytotoxic activities on the immune and skin cells. These results indicate that the extract is probably advantageous in the development of skincare cosmeceutics and beauty treatments.
Current Trends in Green Solvents: Biocompatible Ionic Liquids
Authors: Tzani Andromachi , Karadendrou Maria-Anna , Kalafateli Styliani , Kakokefalou Vasiliki , Detsi Anastasia
Published: December 2022

Biocompatible Ionic Liquids (Bio-ILs) are a new class of ILs that are task-specifically designed to derive from naturally occurring compounds and/or derivatives thereof, as well as molecules well known for their biocompatibility (e.g., active pharmaceutical ingredients or non-toxic bioactive compounds) in terms of sustainability and biocompatibility. Owing to their remarkable physicochemical properties that can be tailor made to comply with the requirements of each application, Bio-ILs have emerged as novel, efficient and green technology, appropriate for a vast variety of scientific fields. Herein, this review describes the state-of-the-art scientific research regarding the synthesis, characterization and applications of Bio-ILs reported in the literature for the period between 2020 and 2022.
The Nephrotoxicity of Drugs Used in Causal Oncological Therapies
Authors: Hałka Janusz , Spaleniak Sebastian , Kade Grzegorz , Antosiewicz Stefan , Sigorski Dawid
Published: December 2022

In recent years, a dynamic development of oncology has been observed, resulting from the increasingly frequent occurrence of neoplasms and therefore, increasing population of patients. The most effective form of therapy for cancer patients is complex multidisciplinary specialized disease management, including nephro-oncology care. Different forms of renal function impairment are frequently diagnosed in cancer patients. They are caused by different co-morbidities existing before starting the oncologic treatment as well as the direct undesirable effects of this therapy which may cause temporary or irreversible damage of the urinary system—especially kidneys. According to different therapeutic programs, in such cases the degree of renal damage is often crucial for the possibility of further anti-cancer treatment. Medical personnel responsible for delivering care to oncology patients should be properly educated on current methods of prevention and treatment of renal complications resulting from anti-cancer therapy. The development of oncologic medicines design, including especially immuno-oncological agents, obliges us to learn new patomechanisms determining potential adverse effects, including renal complications. This publication is focused on the most important undesirable nephrotoxic effects of the frequently used anti-cancer drugs.
Development of in House ELISAs to Detect Antibodies to SARS-CoV-2 in Infected and Vaccinated Humans by Using Recombinant S, S1 and RBD Proteins
Authors: Yilmaz Aysun , Turan Nuri , Kocazeybek Bekir Sami , Dinc Harika Oyku , Tali Hasan Emre , Aydin Ozge , Tali Hamid Besim , Yilmaz Semaha Gul , Konukoglu Dildar , Borekci Sermin , Bold Dashzeveg , Roman Sosa Gleyder , Gungordu Nejdiye , Vardaloglu Ilgim , Gareayaghi Nesrin , Guzel Mine , Guner Ebru , Sadeyen Jean-Remy , Chang Pengxiang , Iqbal Munir , Richt Juergen A. , Yilmaz Huseyin
Published: December 2022

(1) Background: The aim of this study was to produce in-house ELISAs which can be used to determine SARS-CoV-2-specific antibody levels directed against the spike protein (S), the S1 subunit of S and the receptor binding domain (RBD) of S in SARS-CoV-2 vaccinated and infected humans. (2) Methods: Three in-house ELISAs were developed by using recombinant proteins of SARS-CoV-2, namely the S, S1 and RBD proteins. Specificity and sensitivity evaluations of these tests were performed using sera from SARS-CoV-2-infected (n = 70) and SARS-CoV-2-vaccinated (n = 222; CoronaVac vaccine) humans in Istanbul, Turkey. The analyses for the presence of SARS-CoV-2-specific antibodies were performed using the in-house ELISAs, a commercial ELISA (Abbott) and a commercial surrogate virus neutralization test (sVNT). We also analyzed archival human sera (n = 50) collected before the emergence of COVID-19 cases in Turkey. (3) Results: The sensitivity of the in-house S, S1 and RBD ELISAs was found to be 88.44, 90.17 and 95.38%, while the specificity was 72.27, 89.08 and 89.92%, respectively, when compared to the commercial SARS-CoV-2 antibody test kit. The area under curve (AUC) values were 0.777 for the in-house S ELISA, 0.926 for the S1 ELISA, and 0.959 for the RBD ELISA. The kappa values were 0.62, 0.79 and 0.86 for the S, S1 and RBD ELISAs, respectively. (4) Conclusions: The in-house S1 and RBD ELISAs developed in this study have acceptable performance characteristics in terms of sensitivity, specificity, AUC and kappa values. In particular, the RBD ELISA seems viable to determine SARS-CoV-2-specific antibody levels, both in infected and vaccinated people, and help mitigate SARS-CoV-2 outbreaks and spread.
Compositional Sequence Generation in the Entorhinal–Hippocampal System
Authors: McNamee Daniel C. , Stachenfeld Kimberly L. , Botvinick Matthew M. , Gershman Samuel J.
Published: December 2022

Neurons in the medial entorhinal cortex exhibit multiple, periodically organized, firing fields which collectively appear to form an internal representation of space. Neuroimaging data suggest that this grid coding is also present in other cortical areas such as the prefrontal cortex, indicating that it may be a general principle of neural functionality in the brain. In a recent analysis through the lens of dynamical systems theory, we showed how grid coding can lead to the generation of a diversity of empirically observed sequential reactivations of hippocampal place cells corresponding to traversals of cognitive maps. Here, we extend this sequence generation model by describing how the synthesis of multiple dynamical systems can support compositional cognitive computations. To empirically validate the model, we simulate two experiments demonstrating compositionality in space or in time during sequence generation. Finally, we describe several neural network architectures supporting various types of compositionality based on grid coding and highlight connections to recent work in machine learning leveraging analogous techniques.