bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of Patient-Derived Pancreatic Ductal Adenocarcinoma Ex Vivo Tissue for Treatment Response
Authors: Szekerczés Tímea , Selvam Arun Kumar , Moro Carlos Fernández , Elduayen Soledad Pouso , Dillner Joakim , Björnstedt Mikael , Ghaderi Mehran
Published: January 2023

Patient-derived tissue culture models are valuable tools to investigate drug effects and targeted treatment approaches. Resected tumor slices cultured ex vivo have recently gained interest in precision medicine, since they reflect the complex microenvironment of cancer tissue. In this study, we examined the treatment response to an internally developed ex vivo tissue culture model from pancreatic ductal adenocarcinoma (PDAC) and in vitro analysis. Seven PDAC tissues were cultured and subsequently treated with indole-3-pyruvic acid (IPA). IPA, which is known as an agonist of the aryl hydrocarbon receptor (AHR) pathway, has antioxidant properties. Genome-wide transcriptome sequencing analysis revealed activation of AHR pathway genes (CYP1A1 and CYP1B1, p ≤ 0.05). Additionally, significant upregulation of AHR repressor genes AHRR and TiPARP was also observed (p ≤ 0.05), which is indicative of the negative feedback loop activation of AHR pathway signaling. The overall transcriptomic response to IPA indicated that the tissues are biologically active and respond accordingly to exogenous treatment. Cell culture analysis confirmed the significant induction of selected AHR genes by IPA. A morphological examination of the paraffin-embedded formalin-fixed tissue did not show obvious signs of IPA treatment related to tumor cell damage. This study is a proof of concept that ex vivo patient-derived tissue models offer a valuable tool in precision medicine to monitor the effect of personalized treatments.
The Dual Role of Oxidative-Stress-Induced Autophagy in Cellular Senescence: Comprehension and Therapeutic Approaches
Authors: Pantelis Pavlos , Theocharous George , Lagopati Nefeli , Veroutis Dimitris , Thanos Dimitris-Foivos , Lampoglou Giasemi-Panagiota , Pippa Natassa , Gatou Maria-Anna , Tremi Ioanna , Papaspyropoulos Angelos , Kyrodimos Efthymios , Pavlatou Evangelia A. , Gazouli Maria , Evangelou Konstantinos , Gorgoulis Vassilis G.
Published: January 2023

The contemporary lifestyle of the last decade has undeniably caused a tremendous increase in oxidative-stress-inducing environmental sources. This phenomenon is not only connected with the rise of ROS levels in multiple tissues but is also associated with the induction of senescence in different cell types. Several signaling pathways that are associated with the reduction in ROS levels and the regulation of the cell cycle are being activated, so that the organism can battle deleterious effects. Within this context, autophagy plays a significant role. Through autophagy, cells can maintain their homeostasis, as if it were a self-degradation process, which removes the “wounded” molecules from the cells and uses their materials as a substrate for the creation of new useful cell particles. However, the role of autophagy in senescence has both a “dark” and a “bright” side. This review is an attempt to reveal the mechanistic aspects of this dual role. Nanomedicine can play a significant role, providing materials that are able to act by either preventing ROS generation or controllably inducing it, thus functioning as potential therapeutic agents regulating the activation or inhibition of autophagy.
Neural Network Modeling of Microstructure Formation in an AlMg6/10% SiC Metal Matrix Composite and Identification of Its Softening Mechanisms under High-Temperature Deformation
Authors: Smirnov Alexander , Kanakin Vladislav , Konovalov Anatoly
Published: January 2023

The paper investigates the rheological behavior and microstructuring of an AlMg6/10% SiC metal matrix composite (MMC). The rheological behavior and microstructuring of the AlMg6/10% SiC composite is studied for strain rates ranging between 0.1 and 4 s−1 and temperatures ranging from 300 to 500 °C. The microstructure formation is studied using EBSD analysis, as well as finite element simulation and neural network models. The paper proposes a new method of adding data to a training sample, which allows neural networks to correctly predict the behavior of microstructure parameters, such as the average grain diameter, and the fraction and density of low-angle boundaries with scanty initial experimental data. The use of neural networks has made it possible to relate the thermomechanical parameters of deformation to the microstructure parameters formed under these conditions. These dependences allow us to establish that, at strain rates ranging from 0.1 to 4 s−1 and temperatures between 300 to 500 °C, the main softening processes in the AlMg6/10% SiC MMC are dynamic recovery and continuous dynamic recrystallization accompanied, under certain strain and strain rate conditions at 300 and 350 °C, by geometric recrystallization.
Development of Power-Assist Device for a Manual Wheelchair Using Cycloidal Reducer
Authors: Jang Dae-Jin , Kim Yong-Cheol , Hong Eung-Pyo , Kim Gyoo-Suk
Published: January 2023

This paper presents the design process and driving performance test results of a power-assist module to which a cycloidal reducer is applied in order to convert a manual wheelchair into an electric wheelchair. The types of electrification modules currently used to electrify manual wheelchairs include front-mounted, rear-mounted, and powered wheels. These assist devices are either difficult to carry and transport independently or require excellent hand dexterity to operate. To overcome this problem, a cycloidal reducer with no pin roller, and a novel cycloidal curve were designed to develop a small and easy-to-handle power-assist module that was tested by installing this reducer to a manual wheelchair. As a result of the test, the maximum speed of the wheelchair was 6 km/h, the maximum slope that this wheelchair can climb is 20%, and 0.358 Ah was consumed while the wheelchair moved 360 m in the current consumption test. This showed that it is possible to develop a small-sized power-assist module. In addition, the user can easily electrify the manual wheelchair by adding a small weight without replacing the manual wheel. The power-assist module consists of a DC servo motor, cycloidal reducer, battery, and joystick.
Stress Inversion and Fault Instability in the Source Region of the 2021 (MS 5.0) Yingjiang Earthquake
Authors: Li Aitang , Xie Chaodi , Ji Yingfeng , Zhu Weiling , Xu Yan , Wang Guangming , Zhao Xiaoyan
Published: January 2023

On 12 June 2021, an earthquake with MS 5.0 occurred in Yingjiang, adjacent to eastern Myanmar, where seismic activity is frequent due to plate collision. To explore the mechanism of this earthquake, the regional stress field of the Yingjiang zone was inverted using the focal mechanisms of 187 historical earthquakes in this area. Furthermore, based on the obtained orientation of the principal stress axes and the stress shape ratio, the fault slip tendency (Ts) was also estimated to evaluate fault instability in the study area. The stress variation results show that the diffusion and migration of the aftershocks suggested strike–slip-type stress accumulation in Yingjiang with a principal compressive stress axis direction-oriented NNE–SSW. Fault slip tendency results show that the seismogenic faults feature strikes within the ranges of 40~80° and 110~150° and dips of 60~90° and exhibit enhanced stress coupling. The distribution of the aftershock sequence is conjectured to have a high correlation with local fluid migration and was likely controlled by the hydrated rock-induced ruptures of the stressed fault systems near the source region. This study provides insights into potential earthquake risks in this region.
Cocoa Bean Shell as Promising Feedstock for the Production of Poly(3-hydroxybutyrate) (PHB)
Authors: Sánchez Marta , Laca Amanda , Laca Adriana , Díaz Mario
Published: January 2023

Cocoa bean shell (CBS), a by-product of the chocolate industry, has been employed as a substrate to obtain poly(3-hydroxybutyrate) (PHB) by fermentation with Bacillus firmus. With this aim, acid-thermal hydrolysis of CBS (20% w/v) was conducted at 135 °C for 10 min so that broths rich in fermentable sugars were obtained. These broths, both non-centrifuged and centrifuged, were employed as fermentation media. Significant polymer production was obtained from the broth with solids (non-centrifuged) with a yield of 107 mg of PHB/g dry matter. These results indicated that the presence of CBS solids played an important role in microorganism metabolism, with them being fundamental to the production of PHB. Experimental data were fitted by a model based on irreversible first-order reactions, and kinetic constants were obtained for solubilisation, hydrolysis, and sugar consumption. Although, several studies on obtaining PHB from other agri-food residues have been published, this is the first work on PHB production from CBS, with the study obtaining promising results with PHB concentrations similar or even higher than the others previously reported.
Impact of Virtual Reality Simulation in Endodontics on the Learning Experiences of Undergraduate Dental Students
Authors: Ba-Hattab Raidan , Helvacioglu-Yigit Dilek , Anweigi Lamyia , Alhadeethi Tayeb , Raja Mahwish , Atique Sundus , Daas Hanin , Glanville Rebecca , Celikten Berkan , Orhan Kaan , Ali Kamran
Published: January 2023

We aimed to evaluate the impact of Virtual Reality Dental Simulators (VRDS) on preclinical training in endodontics for undergraduate dental students. Purposive sampling technique was used to target undergraduate dental students at two dental schools: in Qatar and Turkey. After training on endodontic access cavity preparation on upper anterior teeth using acrylic teeth on dental mannequins and virtual reality haptic dental simulator, a questionnaire based on a combination of open- and closed-ended items was distributed to the participants. The sample included 60 dental undergraduate students. The participants reported positive experiences with VRDS and 76% considered it to be helpful in improving their fine motor skills. Endodontic access cavity preparation on VRDS was perceived to be similar to natural and acrylic teeth by 73.34% and 53% of participants, respectively. Overall, 85% of participants supported the use of VRDS training to supplement conventional training on dental mannequins but also recommended the need for improvements in VRDS training in endodontics. The findings of this study underscore the benefits of VRDS in endodontics. Future research involving larger samples from multiple institutions may help to optimize VRDS in undergraduate dental education.
Comparative Study on Adsorption of Crystal Violet and Chromium (VI) by Activated Carbon Derived from Spent Coffee Grounds
Authors: Loulidi Ilyasse , Jabri Maria , Amar Abdelouahed , Kali Abderahim , A. Alrashdi Awad , Hadey Chaimaa , Ouchabi Mbarka , Abdullah Palsan Sannasi , Lgaz Hassane , Cho Youngjae , Boukhlifi Fatima
Published: January 2023

In the context of the circular economy, used coffee grounds were transformed into powdered activated carbon by chemical activation using potassium hydroxide. Its characterisation was conducted in comparison with that of a commercial activated carbon by scanning electron microscopy (SEM) coupled with energy dispersive X-ray microanalysis (EDX), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Boehm titration, and point zero charge (pHPZC) and by determination of the methylene blue number (MBN) and the iodine number (IN). Performance of the prepared activated carbon was tested in the adsorption of the cationic dye crystal violet (CV) and hexavalent chromium. Batch adsorption tests were carried out and the effects of operating parameters were studied. The results collected on the adsorption kinetics show that the adsorption followed pseudo-second order kinetics and that the Langmuir isotherm best fits the equilibrium data for crystal violet and hexavalent chromium. The thermodynamic study showed that the adsorption of both adsorbates is spontaneous and exothermic and leads to a decrease in disorder at the solid–liquid interfaces. These results indicate that this activated carbon can be used as an alternative adsorbent to remove cationic dyes and heavy metals from aqueous solutions.
Characteristics, Secondary Transformation Potential and Health Risks of Atmospheric Volatile Organic Compounds in an Industrial Area in Zibo, East China
Authors: Wang Baolin , Li Ziang , Liu Zhenguo , Sun Yuchun , Wang Chen , Xiao Yang , Lu Xiaochen , Yan Guihuan , Xu Chongqing
Published: January 2023

As an important anthropogenic source of volatile organic compounds (VOCs), industrial emissions have a significant impact on air quality and human health. In this study, the characteristics, chemical reactivities, and health risks of VOCs around an industrial park in Zibo were analyzed at two sampling sites. The results showed that the concentrations of total VOCs at Dongzhang Community (DZ) and Special School (SS) sites were 113.12 ppb and 139.40 ppb, respectively, with oxygenated VOCs (OVOCs) as the most abundant species, accounting for 42–45%, followed by alkanes (19.3–19.6%). Diurnal variation of OVOCs exhibited noticeable peaks at 3:00, which may be related to the nighttime sneaky emissions of some enterprises. OVOCs were the species with the highest photochemical activity, with an average contribution of 56.5% to OH radical loss rate and 57% to ozone generation. In addition, OVOCs contributed 40% to secondary organic aerosol formation potential at both sites, second only to aromatics (55%). Acrolein and 1,2-dichloropropane presented the highest non-cancer and cancer risks to human health. The results highlight the importance of OVOCs in some industrial areas.
Quantum Electrodynamics of Dicke States: Resonant One-Photon Exchange Energy and Entangled Decay Rate
Authors: Jentschura Ulrich D. , Adhikari Chandra M.
Published: January 2023

We calculate the fully retarded one-photon exchange interaction potential between electrically neutral, identical atoms, one of which is assumed to be in an excited state, by matching the scattering matrix (S matrix) element with the effective Hamiltonian. Based on the Feynman prescription, we obtain the imaginary part of the interaction energy. Our results lead to precise formulas for the distance-dependent enhancement and suppression of the decay rates of entangled superradiant and subradiant Dicke states (Bell states), as a function of the interatomic distance. The formulas include a long-range tail due to entanglement. We apply the result to an example calculation involving two hydrogen atoms, one of which is in an excited P state.
The Influence of Hedge, Arbitrage, and After-Hours Trading on the Holding Returns of TAIEX Futures
Authors: Lin Chien-Chih , Lee Yuan Chung , Su Chien-Jen , Lin Pei-Ling
Published: January 2023

This study points out a new explanation of the non-trading effect of financial derivatives from the perspective of hedging demand. We examine the influence of hedging demand on the non-trading effect of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) Futures. By dividing the sample period into trading period and non-trading period and testing the difference between the risk premiums in these two intervals, we find that there is a non-trading effect in TAIEX Futures, which means that the holding returns of TAIEX Futures in the non-trading period are higher than those in the trading period. By estimating a dummy-regression model, the evidence shows that when the VIX (Taiwan Index Option Volatility Index) indicator is relatively high, the non-trading effect will be more significant, indicating that the non-trading effect may come from investors’ hedging needs. In addition, it is found that when the futures index is higher than the spot index, the non-trading effect becomes less obvious. The possible reason is that when there is a positive spread in index futures, investors will expect a bull market, thus reducing the hedging demand of index futures. In the end, we find that the liquidity in the after-hours trading session is poor, resulting in high hedging costs, and forcing investors to hedge during the regular trading period. Therefore, the after-hours trading of TAIEX Futures fails to reduce the non-trading effect.
Artificial Intelligence in Pharmaceutical and Healthcare Research
Authors: Bhattamisra Subrat Kumar , Banerjee Priyanka , Gupta Pratibha , Mayuren Jayashree , Patra Susmita , Candasamy Mayuren
Published: January 2023

Artificial intelligence (AI) is a branch of computer science that allows machines to work efficiently, can analyze complex data. The research focused on AI has increased tremendously, and its role in healthcare service and research is emerging at a greater pace. This review elaborates on the opportunities and challenges of AI in healthcare and pharmaceutical research. The literature was collected from domains such as PubMed, Science Direct and Google scholar using specific keywords and phrases such as ‘Artificial intelligence’, ‘Pharmaceutical research’, ‘drug discovery’, ‘clinical trial’, ‘disease diagnosis’, etc. to select the research and review articles published within the last five years. The application of AI in disease diagnosis, digital therapy, personalized treatment, drug discovery and forecasting epidemics or pandemics was extensively reviewed in this article. Deep learning and neural networks are the most used AI technologies; Bayesian nonparametric models are the potential technologies for clinical trial design; natural language processing and wearable devices are used in patient identification and clinical trial monitoring. Deep learning and neural networks were applied in predicting the outbreak of seasonal influenza, Zika, Ebola, Tuberculosis and COVID-19. With the advancement of AI technologies, the scientific community may witness rapid and cost-effective healthcare and pharmaceutical research as well as provide improved service to the general public.
Impact of Artificial Intelligence on COVID-19 Pandemic: A Survey of Image Processing, Tracking of Disease, Prediction of Outcomes, and Computational Medicine
Authors: Almotairi Khaled H. , Hussein Ahmad MohdAziz , Abualigah Laith , Abujayyab Sohaib K. M. , Mahmoud Emad Hamdi , Ghanem Bassam Omar , Gandomi Amir H.
Published: January 2023

Integrating machine learning technologies into artificial intelligence (AI) is at the forefront of the scientific and technological tools employed to combat the COVID-19 pandemic. This study assesses different uses and deployments of modern technology for combating the COVID-19 pandemic at various levels, such as image processing, tracking of disease, prediction of outcomes, and computational medicine. The results prove that computerized tomography (CT) scans help to diagnose patients infected by COVID-19. This includes two-sided, multilobar ground glass opacification (GGO) by a posterior distribution or peripheral, primarily in the lower lobes, and fewer recurrences in the intermediate lobe. An extensive search of modern technology databases relating to COVID-19 was undertaken. Subsequently, a review of the extracted information from the database search looked at how technology can be employed to tackle the pandemic. We discussed the technological advancements deployed to alleviate the communicability and effect of the pandemic. Even though there are many types of research on the use of technology in combating COVID-19, the application of technology in combating COVID-19 is still not yet fully explored. In addition, we suggested some open research issues and challenges in deploying AI technology to combat the global pandemic.
Exploring the Major Trends and Emerging Themes of Artificial Intelligence in the Scientific Leading Journals amidst the COVID-19 Era
Authors: Soliman Mohammad , Fatnassi Tarek , Elgammal Islam , Figueiredo Ronnie
Published: January 2023

Artificial intelligence (AI) has recently become the focus of academia and practitioners, reflecting the substantial evolution of scientific production in this area, particularly during the COVID-19 era. However, there is no known academic work exploring the major trends and the extant and emerging themes of scientific research production of AI leading journals. To this end, this study is to specify the research progress on AI among the top-tier journals by highlighting the development of its trends, topics, and key themes. This article employs an integrated bibliometric analysis using evaluative and relational metrics to analyze, map, and outline the key trends and themes of articles published in the leading AI academic journals, based on the latest CiteScore of Scopus-indexed journals between 2020 and 2021. The findings depict the major trends, conceptual and social structures, and key themes of AI leading journals’ publications during the given period. This paper represents valuable implications for concerned scholars, research centers, higher education institutions, and various organizations within different domains. Limitations and directions for further research are outlined.
In Vitro 3D Modeling of Neurodegenerative Diseases
Authors: Louit Aurélie , Galbraith Todd , Berthod François
Published: January 2023

The study of neurodegenerative diseases (such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, or amyotrophic lateral sclerosis) is very complex due to the difficulty in investigating the cellular dynamics within nervous tissue. Despite numerous advances in the in vivo study of these diseases, the use of in vitro analyses is proving to be a valuable tool to better understand the mechanisms implicated in these diseases. Although neural cells remain difficult to obtain from patient tissues, access to induced multipotent stem cell production now makes it possible to generate virtually all neural cells involved in these diseases (from neurons to glial cells). Many original 3D culture model approaches are currently being developed (using these different cell types together) to closely mimic degenerative nervous tissue environments. The aim of these approaches is to allow an interaction between glial cells and neurons, which reproduces pathophysiological reality by co-culturing them in structures that recapitulate embryonic development or facilitate axonal migration, local molecule exchange, and myelination (to name a few). This review details the advantages and disadvantages of techniques using scaffolds, spheroids, organoids, 3D bioprinting, microfluidic systems, and organ-on-a-chip strategies to model neurodegenerative diseases.
Ultrastructure of a Mechanoreceptor of the Trichoid Sensilla of the Insect Nabis rugosus: Stimulus-Transmitting and Bio-Sensory Architecture
Authors: Chakilam Shashikanth , Gaidys Rimvydas , Brożek Jolanta
Published: January 2023

This paper presents the ultrastructure morphology of Nabis rugosus trichoid sensilla using SEM and TEM data, along with a two-dimensional model of the trichoid sensilla developed in Amira software. The SEM images show the shape and scattering of the trichoid mechanosensilla over the N. rugosus flagellomere. The TEM images present the ultrastructural components, in which the hair rises from the socket via the joint membrane. The dendrite sheath is connected at the base of the hair shaft, surrounded by the lymph space and the socket septum. This dendrite sheath contains a tubular body with microtubules separated by the membrane (M) and granules (Gs). This study presents a model and simulation of the trichoid sensilla sensing mechanism, in which the hair deflects due to the application of external loading above it and presses the dendrite sheath attached to the hair base. The dendrite sheath is displaced by the applied force, transforming the transversal loading into a longitudinal deformation of the microtubules. Due to this longitudinal deformation, electric potential develops in the microtubule’s core, and information is delivered to the brain through the axon. The sensilla’s pivot point or point of rotation is presented, along with the relationship between the hair shaft length, the pivot point, and the electric potential distribution in the microtubules. This study’s results can be used to develop ultra-sensitive, bioinspired sensors based on these ultrastructural components and their biomechanical studies.
Transcranial Direct Current Stimulation Modulates EEG Microstates in Low-Functioning Autism: A Pilot Study
Authors: Kang Jiannan , Fan Xiwang , Zhong Yiwen , Casanova Manuel F. , Sokhadze Estate M. , Li Xiaoli , Niu Zikang , Geng Xinling
Published: January 2023

Autism spectrum disorder (ASD) is a heterogeneous disorder that affects several behavioral domains of neurodevelopment. Transcranial direct current stimulation (tDCS) is a new method that modulates motor and cognitive function and may have potential applications in ASD treatment. To identify its potential effects on ASD, differences in electroencephalogram (EEG) microstates were compared between children with typical development (n = 26) and those with ASD (n = 26). Furthermore, children with ASD were divided into a tDCS (experimental) and sham stimulation (control) group, and EEG microstates and Autism Behavior Checklist (ABC) scores before and after tDCS were compared. Microstates A, B, and D differed significantly between children with TD and those with ASD. In the experimental group, the scores of microstates A and C and ABC before tDCS differed from those after tDCS. Conversely, in the control group, neither the EEG microstates nor the ABC scores before the treatment period (sham stimulation) differed from those after the treatment period. This study indicates that tDCS may become a viable treatment for ASD.
The Human Mercaptopyruvate Sulfurtransferase TUM1 Is Involved in Moco Biosynthesis, Cytosolic tRNA Thiolation and Cellular Bioenergetics in Human Embryonic Kidney Cells
Authors: Ogunkola Moses Olalekan , Guiraudie-Capraz Gaelle , Feron Francois , Leimkühler Silke
Published: January 2023

Sulfur is an important element that is incorporated into many biomolecules in humans. The incorporation and transfer of sulfur into biomolecules is, however, facilitated by a series of different sulfurtransferases. Among these sulfurtransferases is the human mercaptopyruvate sulfurtransferase (MPST) also designated as tRNA thiouridine modification protein (TUM1). The role of the human TUM1 protein has been suggested in a wide range of physiological processes in the cell among which are but not limited to involvement in Molybdenum cofactor (Moco) biosynthesis, cytosolic tRNA thiolation and generation of H2S as signaling molecule both in mitochondria and the cytosol. Previous interaction studies showed that TUM1 interacts with the L-cysteine desulfurase NFS1 and the Molybdenum cofactor biosynthesis protein 3 (MOCS3). Here, we show the roles of TUM1 in human cells using CRISPR/Cas9 genetically modified Human Embryonic Kidney cells. Here, we show that TUM1 is involved in the sulfur transfer for Molybdenum cofactor synthesis and tRNA thiomodification by spectrophotometric measurement of the activity of sulfite oxidase and liquid chromatography quantification of the level of sulfur-modified tRNA. Further, we show that TUM1 has a role in hydrogen sulfide production and cellular bioenergetics.
Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer
Authors: Perkovic Matea Nikolac , Jaganjac Morana , Milkovic Lidija , Horvat Tea , Rojo David , Zarkovic Kamelija , Ćorić Marijana , Hudolin Tvrtko , Waeg Georg , Orehovec Biserka , Zarkovic Neven
Published: January 2023

An oxidative degradation product of the polyunsaturated fatty acids, 4-hydroxynonenal (4-HNE), is of particular interest in cancer research due to its concentration-dependent pleiotropic activities affecting cellular antioxidants, metabolism, and growth control. Although an increase in oxidative stress and lipid peroxidation was already associated with prostate cancer progression a few decades ago, the knowledge of the involvement of 4-HNE in prostate cancer tumorigenesis is limited. This study investigated the appearance of 4-HNE-protein adducts in prostate cancer tissue by immunohistochemistry using a genuine 4-HNE monoclonal antibody. Plasma samples of the same patients and samples of the healthy controls were also analyzed for the presence of 4-HNE-protein adducts, followed by metabolic profiling using LC-ESI-QTOF-MS and GC-EI-Q-MS. Finally, the analysis of the metabolic pathways affected by 4-HNE was performed. The obtained results revealed the absence of 4-HNE-protein adducts in prostate carcinoma tissue but increased 4-HNE-protein levels in the plasma of these patients. Metabolomics revealed a positive association of different long-chain and medium-chain fatty acids with the presence of prostate cancer. Furthermore, while linoleic acid positively correlated with the levels of 4-HNE-protein adducts in the blood of healthy men, no correlation was obtained for cancer patients indicating altered lipid metabolism in this case. The metabolic pathway of unsaturated fatty acids biosynthesis emerged as significantly affected by 4-HNE. Overall, this is the first study linking 4-HNE adduction to plasma proteins with specific alterations in the plasma metabolome of prostate cancer patients. This study revealed that increased 4-HNE plasma protein adducts could modulate the unsaturated fatty acids biosynthesis pathway. It is yet to be determined if this is a direct result of 4-HNE or whether they are produced by the same underlying mechanisms. Further mechanistic studies are needed to grasp the biological significance of the observed changes in prostate cancer tumorigenesis.
Combination Analysis of Ferroptosis and Immune Status Predicts Patients Survival in Breast Invasive Ductal Carcinoma
Authors: Yang Yang , Luo Dankun , Gao Wenqi , Wang Qiang , Yao Wenchao , Xue Dongbo , Ma Biao
Published: January 2023

Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients’ prognoses. These two processes cooperatively regulate different developmental stages of tumors and could be considered important tumor therapeutic targets. However, reliable prognostic markers screened based on the combination of ferroptosis and tumor immune status have not been well characterized. Here, we chose the ssGSEA and ESTIMATE algorithms to evaluate the ferroptosis and immune status of a TCGA breast invasive ductal carcinoma (IDC) cohort, which revealed their correlation characteristics as well as patients’ prognoses. The WGCNA algorithm was used to identify genes related to both ferroptosis and immunity. Univariate COX, LASSO regression, and multivariate Cox regression models were used to screen prognostic-related genes and construct prognostic risk models. Based on the ferroptosis and immune scores, the cohort was divided into three groups: a high-ferroptosis/low-immune group, a low-ferroptosis/high-immune group, and a mixed group. These three groups exhibited distinctive survival characteristics, as well as unique clinical phenotypes, immune characteristics, and activated signaling pathways. Among them, low-ferroptosis and high-immune statuses were favorable factors for the survival rates of patients. A total of 34 differentially expressed genes related to ferroptosis-immunity were identified among the three groups. After univariate, Lasso regression, and multivariate stepwise screening, two key prognostic genes (GNAI2, PSME1) were identified. Meanwhile, a risk prognosis model was constructed, which can predict the overall survival rate in the validation set. Lastly, we verified the importance of model genes in three independent GEO cohorts. In short, we constructed a prognostic model that assists in patient risk stratification based on ferroptosis-immune-related genes in IDC. This model helps assess patients’ prognoses and guide individualized treatment, which also further eelucidatesthe molecular mechanisms of IDC.
Alterations in Carbohydrate Quantities in Freeze-Dried, Relative to Fresh or Frozen Maize Leaf Disks
Authors: Dirk Lynnette M. A. , Zhao Tianyong , May John , Li Tao , Han Qinghui , Zhang Yumin , Sahib Mohammad R. , Downie Allan Bruce
Published: January 2023

For various reasons, leaves are occasionally lyophilized prior to storage at −80 °C and preparing extracts. Soluble carbohydrate identity and quantity from maize leaf disks were ascertained in two separate years using anion exchange HPLC with pulsed electrochemical detection. Analyses were made from disks after freezing in liquid nitrogen with or without subsequent lyophilization (both years) or directly after removal from plants with or without lyophilization (only in the second year). By adding the lyophilizing step, galactose content consistently increased and, frequently, so did galactoglycerols. The source of the galactose increase with the added lyophilizing step was not due to metabolizing raffinose, as the raffinose synthase (rafs) null mutant leaves, which do not make that trisaccharide, also had a similar increase in galactose content with lyophilization. Apparently, the ester linkages attaching free fatty acids to galactoglycerolipids of the chloroplast are particularly sensitive to cleavage during lyophilization, resulting in increases in galactoglycerols. Regardless of the galactose source, a systematic error is introduced for carbohydrate (and, most likely, also chloroplast mono- or digalactosyldiacylglycerol) amounts when maize leaf samples are lyophilized prior to extraction. The recognition of lyophilization as a source of galactose increase provides a cautionary note for investigators of soluble carbohydrates.
Topological Considerations in Biomolecular Condensation
Authors: Das Debapriya , Deniz Ashok A.
Published: January 2023

Biomolecular condensation and phase separation are increasingly understood to play crucial roles in cellular compartmentalization and spatiotemporal regulation of cell machinery implicated in function and pathology. A key aspect of current research is to gain insight into the underlying physical mechanisms of these processes. Accordingly, concepts of soft matter and polymer physics, the thermodynamics of mixing, and material science have been utilized for understanding condensation mechanisms of multivalent macromolecules resulting in viscoelastic mesoscopic supramolecular assemblies. Here, we focus on two topological concepts that have recently been providing key mechanistic understanding in the field. First, we will discuss how percolation provides a network-topology-related framework that offers an interesting paradigm to understand the complex networking of dense ‘connected’ condensate structures and, therefore, their phase behavior. Second, we will discuss the idea of entanglement as another topological concept that has deep roots in polymer physics and important implications for biomolecular condensates. We will first review some historical developments and fundamentals of these concepts, then we will discuss current advancements and recent examples. Our discussion ends with a few open questions and the challenges to address them, hinting at unveiling fresh possibilities for the modification of existing knowledge as well as the development of new concepts relevant to condensate science.
COVID-19 and Thymoquinone: Clinical Benefits, Cure, and Challenges
Authors: El-Sayed Shimaa Abd El-Salam , Rizk Mohamed Abdo
Published: January 2023

In today’s world, the outbreak of the coronavirus disease 2019 (COVID-19) has spread throughout the world, causing severe acute respiratory syndrome (SARS) and several associated complications in various organs (heart, liver, kidney, and gastrointestinal tract), as well as significant multiple organ dysfunction, shock, and even death. In order to overcome the serious complications associated with this pandemic virus and to prevent SARS-CoV-2 entry into the host cell, it is necessary to repurpose currently available drugs with a broad medicinal application as soon as they become available. There are several therapeutics under investigation for improving the overall prognosis of COVID-19 patients, but none of them has demonstrated clinical efficacy to date, which is disappointing. It is in this pattern that Nigella sativa seeds manifest their extensive therapeutic effects, which have been reported to be particularly effective in the treatment of skin diseases, jaundice, and gastrointestinal problems. One important component of these seeds is thymoquinone (TQ), which has a wide range of beneficial properties, including antioxidant and anti-inflammatory properties, as well as antibacterial and parasitic properties, in addition to anticarcinogenic, antiallergic, and antiviral properties. This comprehensive review discussed the possibility of an emerging natural drug with a wide range of medical applications; the use of TQ to overcome the complications of COVID-19 infection; and the challenges that are impeding the commercialization of this promising phytochemical compound. TQ is recommended as a highly effective weapon in the fight against the novel coronavirus because of its dual antiviral action, in addition to its capacity to lessen the possibility of SARS-CoV-2 penetration into cells. However, future clinical trials are required to confirm the role of TQ in overcoming the complications of COVID-19 infection.
Nano-Zirconium Dioxide Catalyzed Multicomponent Synthesis of Bioactive Pyranopyrazoles That Target Cyclin Dependent Kinase 1 in Human Breast Cancer Cells
Authors: Basappa Basappa , Poonacha Lisha K. , Xi Zhang , Vishwanath Divakar , Yang Ji-Rui , Nagaraja Omantheswara , Swamynayaka Ananda , Madegowda Mahendra , Chinnathambi Arunachalam , Alharbi Sulaiman Ali , Gurudatt Doddahosuru Mahadevappa , Pandey Vijay , Shivananju Nanjundaswamy , Ahn Kwang Seok , Sethi Gautam , Lobie Peter E. , Shubha Priya Babu
Published: January 2023

Small molecules are being used to inhibit cyclin dependent kinase (CDK) enzymes in cancer treatment. There is evidence that CDK is a drug-target for cancer therapy across many tumor types because it catalyzes the transfer of the terminal phosphate of ATP to a protein that acts as a substrate. Herein, the identification of pyranopyrazoles that were CDK inhibitors was attempted, whose synthesis was catalyzed by nano-zirconium dioxide via multicomponent reaction. Additionally, we performed an in-situ analysis of the intermediates of multicomponent reactions, for the first-time, which revealed that nano-zirconium dioxide stimulated the reaction, as estimated by Gibbs free energy calculations of spontaneity. Functionally, the novel pyranopyrazoles were tested for a loss of cell viability using human breast cancer cells (MCF-7). It was observed that compounds 5b and 5f effectively produced loss of viability of MCF-7 cells with IC50 values of 17.83 and 23.79 µM, respectively. In vitro and in silico mode-of-action studies showed that pyranopyrazoles target CDK1 in human breast cancer cells, with lead compounds 5b and 5f having potent IC50 values of 960 nM and 7.16 μM, respectively. Hence, the newly synthesized bioactive pyranopyrazoles could serve as better structures to develop CDK1 inhibitors against human breast cancer cells.
Cardiotoxicity of Selected Vascular Endothelial Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients with Renal Cell Carcinoma
Authors: Franczyk Beata , Rysz Jacek , Ławiński Janusz , Ciałkowska-Rysz Aleksandra , Gluba-Brzózka Anna
Published: January 2023

Renal cell carcinoma (RCC) is one of the most frequent malignant neoplasms of the kidney. The therapeutic options available for the treatment of advanced or metastatic RCC include vascular endothelial growth factor receptor (VEGFR)-targeted molecules, for example, tyrosine kinase inhibitors (TKI). Various VEGFR-TKIs proved to be effective in the treatment of patients with solid tumours. The combination of two drugs may prove most beneficial in the treatment of metastatic RCC; however, it also enhances the risk of toxicity compared to monotherapy. Specific VEGFR-TKIs (e.g., sunitinib, sorafenib or pazopanib) may increase the rate of cardiotoxicity in metastatic settings. VEGF inhibitors modulate multiple signalling pathways; thus, the identification of the mechanism underlying cardiotoxicity appears challenging. VEGF signalling is vital for the maintenance of cardiomyocyte homeostasis and cardiac function; therefore, its inhibition can be responsible for the reported adverse effects. Disturbed growth factor signalling pathways may be associated with endothelial dysfunction, impaired revascularization, the development of dilated cardiomyopathy, cardiac hypertrophies and altered peripheral vascular load. Patients at high cardiovascular risk at baseline could benefit from clinical follow-up in the first 2–4 weeks after the introduction of targeted molecular therapy; however, there is no consensus concerning the surveillance strategy.
The Influence of the Number of Spiking Neurons on Synaptic Plasticity
Authors: Uleru George-Iulian , Hulea Mircea , Barleanu Alexandru
Published: January 2023

The main advantages of spiking neural networks are the high biological plausibility and their fast response due to spiking behaviour. The response time decreases significantly in the hardware implementation of SNN because the neurons operate in parallel. Compared with the traditional computational neural network, the SNN use a lower number of neurons, which also reduces their cost. Another critical characteristic of SNN is their ability to learn by event association that is determined mainly by postsynaptic mechanisms such as long-term potentiation. However, in some conditions, presynaptic plasticity determined by post-tetanic potentiation occurs due to the fast activation of presynaptic neurons. This violates the Hebbian learning rules that are specific to postsynaptic plasticity. Hebbian learning improves the SNN ability to discriminate the neural paths trained by the temporal association of events, which is the key element of learning in the brain. This paper quantifies the efficiency of Hebbian learning as the ratio between the LTP and PTP effects on the synaptic weights. On the basis of this new idea, this work evaluates for the first time the influence of the number of neurons on the PTP/LTP ratio and consequently on the Hebbian learning efficiency. The evaluation was performed by simulating a neuron model that was successfully tested in control applications. The results show that the firing rate of postsynaptic neurons post depends on the number of presynaptic neurons pre, which increases the effect of LTP on the synaptic potentiation. When post activates at a requested rate, the learning efficiency varies in the opposite direction with the number of pres, reaching its maximum when fewer than two pres are used. In addition, Hebbian learning is more efficient at lower presynaptic firing rates that are divisors of the target frequency of post. This study concluded that, when the electronic neurons additionally model presynaptic plasticity to LTP, the efficiency of Hebbian learning is higher when fewer neurons are used. This result strengthens the observations of our previous research where the SNN with a reduced number of neurons could successfully learn to control the motion of robotic fingers.
A Proposal of Bioinspired Soft Active Hand Prosthesis
Authors: Toro-Ossaba Alejandro , Tejada Juan C. , Rúa Santiago , López-González Alexandro
Published: January 2023

Soft robotics have broken the rigid wall of interaction between humans and robots due to their own definition and manufacturing principles, allowing robotic systems to adapt to humans and enhance or restore their capabilities. In this research we propose a dexterous bioinspired soft active hand prosthesis based in the skeletal architecture of the human hand. The design includes the imitation of the musculoskeletal components and morphology of the human hand, allowing the prosthesis to emulate the biomechanical properties of the hand, which results in better grips and a natural design. CAD models for each of the bones were developed and 3D printing was used to manufacture the skeletal structure of the prosthesis, also soft materials were used for the musculoskeletal components. A myoelectric control system was developed using a recurrent neural network (RNN) to classify the hand gestures using electromyography signals; the RNN model achieved an accuracy of 87% during real time testing. Objects with different size, texture and shape were tested to validate the grasping performance of the prosthesis, showing good adaptability, soft grasping and mechanical compliance to object of the daily life.
Cerebrospinal Fluid Homer-3 Autoantibodies in a Patient with Amnestic Mild Cognitive Impairment
Authors: Hansen Niels , Radenbach Katrin , Rentzsch Kristin , Fox Janosch , Wiltfang Jens , Bartels Claudia
Published: January 2023

(1) Background: Homer-3 antibodies are associated with cerebellar disease ranging from subacute degeneration to cerebellitis. However, cognitive impairment associated with Homer-3 autoantibodies has not been reported until now. (2) Methods: in retrospect, we systematically studied clinical, cranial magnetic resonance imaging (cMRI), electroencephalography (EEG) and lumbar puncture data, including neural autoantibodies of a clinical case. (3) Results: we describe the case of a 56-year-old woman presenting with amnestic mild cognitive impairment in association with serum and CSF detection of Homer-3 autoantibodies and a depressive syndrome. cMRI revealed cerebellar atrophy. CSF analysis showed elevated ptau181 protein. Applying the criteria for an autoimmune psychiatric syndrome revealed a plausible autoimmune basis for the mild cognitive impairment. (4) Discussions: our case report demonstrates an amnestic mild cognitive impairment and depressive symptoms associated with Homer-3 autoantibodies as a novel feature of Homer-3 antibody-related disease. We also propose that cognitive dysfunction might result from impaired AMPAR signaling in the hippocampus induced by Homer-3 antibodies, which will have to be verified in further research.
The Influence of Herd Mentality on Rating Bias and Popularity Bias: A Bi-Process Debiasing Recommendation Model Based on Matrix Factorization
Authors: Su Xinjie , Li Peng , Zhu Xinru
Published: January 2023

To reduce the impact of rating bias and popularity bias in recommender system, and make the recommender system reach a balance between recommendation utility and debias effect at the same time, we propose a bi-process debiasing recommendation model based on matrix factorization. Firstly, considering the problem that the user’s ratings are affected by the herd mentality, which leads to a consistency between the rating and the selection of rating items, resulting in the power-law distribution, the k-times parabolic fuzzy distribution was used to fuse the user’s age to redistribute the ratings. Secondly, the loss function is optimized by the continuously increasing flow and popularity of items. Finally, user emotion and item popularity are combined to construct user psychological tendency, which is divided into three levels: strong, medium and weak, and different levels are given different weights. To verify the performance of the model, the experimental results on real datasets show that the model proposed in this paper not only effectively reduces the recommendation bias but also ensures the recommendation utility.