bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Genomic and Transcriptomic Profiling Revealed the Molecular Basis of Starch Promoting the Growth and Proliferation of Balantioides coli
Authors: Zhao Lizhuo , He Kai , Jiang Chuanqi , Wang Guangying , Hu Suhui , Wang Tianqi , Qian Weifeng , Wei Zhiguo , Xiong Jie , Miao Wei , Yan Wenchao
Published: May 2023

Carbohydrates are the main source of nutrition for B. coli, supplying energy for cell growth and development. The research aimed at investigating the mechanism of starch on the growth and replication of B. coli. Single-cell separation was used to isolate single trophozoites of B. coli under a stereomicroscope, transcriptomic profiling was conducted based on the SMART-seq2 single-cell RNA-seq method. Comparative genomic analysis was performed on B. coli and eight other ciliates to obtain specific and expanded gene families of B. coli. GO and KEGG enrichment analysis were used to analyze the key genes of B. coli under the action of starch in the present study. The results of single-cell RNA-seq depicts starch affected the growth and replication of B. coli in two ways: (1) the cell cycle was positively promoted by the activation of the cAMP/PKA signaling pathway via glycolysis; (2) the cell autophagy was suppressed through the PI3K/AKT/mTOR pathway. Genes involved in endocytosis, carbohydrate utilization, and the cAMP/PKA signaling pathway were highly enriched in both specific and expanded gene families of B. coli. Starch can be ingested and hydrolyzed into glucose, in turn affecting various biological processes of B. coli. The molecular mechanism of the effect of starch on the growth and proliferation of B. coli by promoting cell cycle and inhibiting the autophagy of trophozoites has been elucidated in our study.
Evaluation of the Anti-Toxoplasma gondii Efficacy, Cytotoxicity, and GC/MS Profile of Pleopeltis crassinervata Active Subfractions
Authors: Anacleto-Santos Jhony , Calzada Fernando , López-Camacho Perla Yolanda , López-Pérez Teresa de Jesús , Carrasco-Ramírez Elba , Casarrubias-Tabarez Brenda , Fortoul Teresa I. , Rojas-Lemus Marcela , López-Valdés Nelly , Rivera-Fernández Norma
Published: May 2023

Pleopeltis crassinervata (Pc) is a fern that, according to ethnobotanical records, is used in Mexican traditional medicine to treat gastrointestinal ailments. Recent reports indicate that the hexane fraction (Hf) obtained from Pc methanolic frond extract affects Toxoplasma gondii tachyzoite viability in vitro; therefore, in the present study, the activity of different Pc hexane subfractions (Hsf) obtained by chromatographic methods was evaluated in the same biological model. Gas chromatography/mass spectrometry (GC/MS) analysis was carried out for hexane subfraction number one (Hsf1), as it showed the highest anti-Toxoplasma activity with a half-maximal inhibitory concentration (IC50) of 23.6 µg/mL, a 50% cytotoxic concentration (CC50) of 398.7 µg/mL in Vero cells, and a selective index (SI) of 16.89. Eighteen compounds were identified by Hsf1 GC/MS analysis, with the majority being fatty acids and terpenes. Hexadecanoic acid, methyl ester was the most commonly found compound (18.05%) followed by olean-13(18)-ene, 2,2,4a,8a,9,12b,14a-octamethyl-1,2,3,4,4a,5,6,6a,6b,7,8,8a,9,12,12a,12b,13,14,14a,14b-eicosahydropicene, and 8-octadecenoid acid, methyl ester, which were detected at 16.19%, 12.53%, and 12.99%, respectively. Based on the mechanisms of action reported for these molecules, Hsf1 could exert its anti-Toxoplasma activity mainly on T. gondii lipidomes and membranes.
Can Improved Farm Biosecurity Reduce the Need for Antimicrobials in Food Animals? A Scoping Review
Authors: Dhaka Pankaj , Chantziaras Ilias , Vijay Deepthi , Bedi Jasbir Singh , Makovska Iryna , Biebaut Evelien , Dewulf Jeroen
Published: May 2023

Limited and judicious antimicrobial usage (AMU) is considered the key to saving the success of human and veterinary medicine in treating infections. With the limited alternatives for antimicrobials, farm biosecurity (and herd management) is considered a promising tool to mitigate the non-judicious AMU and to maintain animal health, production, and welfare. The present scoping review aims to analyse the effect of farm biosecurity on AMU in livestock systems and formulate recommendations. Peer-reviewed manuscripts published between 2001–2022 were analyzed using the PRISMA framework using PubMed, Scopus, and Science Direct databases. After applying the inclusion criteria, 27 studies were found to assess the effect of farm biosecurity (or management practices) on AMU at the herd/farm level in quantitative/semi-quantitative terms. These studies were carried out in 16 countries, of which 74.1% (20/27) were from 11 European countries. The highest number of studies were from pig farms [51.8% (14/27)], followed by poultry (chicken) farms [25.9% (7/27)], cattle farms [11.1% (3/27)], and a single study from a turkey farm. Two studies include both pig and poultry farms. Most of the studies were cross-sectional [70.4% (19/27)], seven were longitudinal, and one was a case-control study. Complex interactions were observed among factors influencing AMU, such as biosecurity measures, farm characteristics, farmers’ attitudes, availability of animal health services, stewardship, etc. A positive association between farm biosecurity and reduction in AMU was observed in 51.8% (14/27) of the studies, and 18.5% (5/27) showed that improvement in farm management practices was associated with a reduction in AMU. Two studies highlighted that coaching and awareness among farmers might lead to a decrease in AMU. A single study on economic assessment concluded biosecurity practices as a cost-effective way to reduce AMU. On the other hand, five studies showed an uncertain or spurious association between farm biosecurity and AMU. We recommend the reinforcement of the concept of farm biosecurity, especially in lower- and middle-income countries (LMICs). Further, there is a need to strengthen the evidence on the association between farm biosecurity and AMU in region- and species-specific farm settings.
The Antioxidant Effect of Dietary Bioactives Arises from the Interplay between the Physiology of the Host and the Gut Microbiota: Involvement of Short-Chain Fatty Acids
Authors: Cuciniello Rossana , Di Meo Francesco , Filosa Stefania , Crispi Stefania , Bergamo Paolo
Published: May 2023

The maintenance of redox homeostasis is associated with a healthy status while the disruption of this mechanism leads to the development of various pathological conditions. Bioactive molecules such as carbohydrates accessible to the microbiota (MACs), polyphenols, and polyunsaturated fatty acids (PUFAs) are food components best characterized for their beneficial effect on human health. In particular, increasing evidence suggests that their antioxidant ability is involved in the prevention of several human diseases. Some experimental data indicate that the activation of the nuclear factor 2-related erythroid 2 (Nrf2) pathway—the key mechanism in the maintenance of redox homeostasis—is involved in the beneficial effects exerted by the intake of PUFAs and polyphenols. However, it is known that the latter must be metabolized before becoming active and that the intestinal microbiota play a key role in the biotransformation of some ingested food components. In addition, recent studies, indicating the efficacy of the MACs, polyphenols, and PUFAs in increasing the microbial population with the ability to yield biologically active metabolites (e.g., polyphenol metabolites, short-chain fatty acids (SCFAs)), support the hypothesis that these factors are responsible for the antioxidant action on the physiology of the host. The underlying mechanisms through which MACs, polyphenols, and PUFAs might influence the redox status have not been fully elucidated, but based on the efficacy of SCFAs as Nrf2 activators, their contribution to the antioxidant efficacy of dietary bioactives cannot be excluded. In this review, we aimed to summarize the main mechanisms through which MACs, polyphenols, and PUFAs can modulate the host’s redox homeostasis through their ability to directly or indirectly activate the Nrf2 pathway. We discuss their probiotic effects and the role played by the alteration of the metabolism/composition of the gut microbiota in the generation of potential Nrf2-ligands (e.g., SCFAs) in the host’s redox homeostasis.
PGC-1α Is a Master Regulator of Mitochondrial Lifecycle and ROS Stress Response
Authors: Abu Shelbayeh Othman , Arroum Tasnim , Morris Silke , Busch Karin B.
Published: May 2023

Mitochondria play a major role in ROS production and defense during their life cycle. The transcriptional activator PGC-1α is a key player in the homeostasis of energy metabolism and is therefore closely linked to mitochondrial function. PGC-1α responds to environmental and intracellular conditions and is regulated by SIRT1/3, TFAM, and AMPK, which are also important regulators of mitochondrial biogenesis and function. In this review, we highlight the functions and regulatory mechanisms of PGC-1α within this framework, with a focus on its involvement in the mitochondrial lifecycle and ROS metabolism. As an example, we show the role of PGC-1α in ROS scavenging under inflammatory conditions. Interestingly, PGC-1α and the stress response factor NF-κB, which regulates the immune response, are reciprocally regulated. During inflammation, NF-κB reduces PGC-1α expression and activity. Low PGC-1α activity leads to the downregulation of antioxidant target genes resulting in oxidative stress. Additionally, low PGC-1α levels and concomitant oxidative stress promote NF-κB activity, which exacerbates the inflammatory response.
Carbon Nanodots Attenuate Lipid Peroxidation in the LDL Receptor Knockout Mouse Brain
Authors: Erikson Keith M. , El-Khouri Kristina , Petric Radmila , Tang Chenhao , Chen Jinlan , Vasquez Delicia Esther Cardenas , Fordahl Steve C. , Jia Zhenquan
Published: May 2023

Abnormal cholesterol metabolism can lead to oxidative stress in the brain. Low-density lipoprotein receptor (LDLr) knockout mice are models for studying altered cholesterol metabolism and oxidative stress onset in the brain. Carbon nanodots are a new class of carbon nanomaterials that possess antioxidant properties. The goal of our study was to evaluate the effectiveness of carbon nanodots in preventing brain lipid peroxidation. LDLr knockout mice and wild-type C57BL/6J mice were treated with saline or 2.5 mg/kg bw of carbon nanodots for a 16-week period. Brains were removed and dissected into the cortex, midbrain, and striatum. We measured lipid peroxidation in the mouse brain tissues using the Thiobarbituric Acid Reactive Substances Assay and iron and copper concentrations using Graphite Furnace Atomic Absorption Spectroscopy. We focused on iron and copper due to their association with oxidative stress. Iron concentrations were significantly elevated in the midbrain and striatum of the LDLr knockout mice compared to the C57BL/6J mice, whereas lipid peroxidation was greatest in the midbrain and cortex of the LDLr knockout mice. Treatment with carbon nanodots in the LDLr knockout mice attenuated both the rise in iron and lipid peroxidation, but they had no negative effect in the C57BL/6J mice, indicating the anti-oxidative stress properties of carbon nanodots. We also assessed locomotor and anxiety-like behaviors as functional indicators of lipid peroxidation and found that treatment with carbon nanodots prevented the anxiety-like behaviors displayed by the LDLr knockout mice. Overall, our results show that carbon nanodots are safe and may be an effective nanomaterial for combating the harmful effects caused by lipid peroxidation.
Hybrid Model of Machine Learning Method and Empirical Method for Rate of Penetration Prediction Based on Data Similarity
Authors: Zhou Fei , Fan Honghai , Liu Yuhan , Zhang Hongbao , Ji Rongyi
Published: May 2023

The rate of penetration (ROP) is an important indicator affecting the drilling cost and drilling performance. Accurate prediction of the ROP has important guiding significance for increasing the drilling speed and reducing costs. Recently, numerous studies have shown that machine learning techniques are an effective means to accurately predict the ROP. However, in petroleum engineering applications, its robustness and generalization cannot be guaranteed. The traditional empirical model has good robustness and generalization ability. Based on the quantification of data similarity, this paper establishes a hybrid model combining a machine learning method and an empirical method, which combines the high prediction accuracy of the machine learning method with the good robustness and generalization of the empirical method, overcoming the shortcomings of any single model. The AE-ED (the Euclidean Distance between the input data and reconstructed data from the autoencoder model) is defined to measure the data similarity, and according to the data similarity of each new piece of input data, the hybrid model chooses the corresponding single model to calculate. The results show that the hybrid model is better than any single model, and all the evaluation indicators perform better, making it more suitable for the ROP prediction in this field.
Efficient and Secure Federated Learning for Financial Applications
Authors: Liu Tao , Wang Zhi , He Hui , Shi Wei , Lin Liangliang , An Ran , Li Chenhao
Published: May 2023

Conventional machine learning (ML) and deep learning approaches require sharing customers’ sensitive information with an external credit bureau to generate a prediction model, thereby increasing the risk of privacy leakage. This poses a significant challenge for financial companies. To address this challenge, federated learning has emerged as a promising approach to protect data privacy. However, the high communication costs associated with federated systems, particularly for large neural networks, can be a bottleneck. To mitigate this issue, it is necessary to limit the number and size of communications for practical training of large neural structures. Gradient sparsification is a technique that has gained increasing attention as a method to reduce communication costs, as it updates only significant gradients and accumulates insignificant gradients locally. However, the secure aggregation framework cannot directly employ gradient sparsification. To overcome this limitation, this article proposes two sparsification methods for reducing the communication costs of federated learning. The first method is a time-varying hierarchical sparsification method for model parameter updates, which addresses the challenge of maintaining model accuracy after a high sparsity ratio. This method can significantly reduce the cost of a single communication. The second method is to apply sparsification to the secure aggregation framework. Specifically, the encryption mask matrix is sparsified to reduce communication costs while protecting privacy. Experiments demonstrate that our method can reduce the upload communication costs to approximately 2.9% to 18.9% of the conventional federated learning algorithm under different non-IID experiment settings when the sparsity rate is 0.01.
Research on Magnetohydrodynamic Angular Rate Sensor Denoising for a Space Laser Stabilization Control System
Authors: Su Yunhao , Ma Caiwen , Han Junfeng , Wang Xuan , Wang Yuanyuan , Ji Zhou
Published: May 2023

The magnetohydrodynamic angular rate sensor (MHD ARS) is a high-bandwidth, high-accuracy sensor that is increasingly used to measure spacecraft harmonic vibration. However, the amplitude of harmonic vibration is usually on the order of microradian to milliradian, and the induced electric potential signal of MHD ARS is only on the order of nanovolt to microvolt, which is easily disturbed by noise. In this paper, an improved method based on autocorrelation with Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Wavelet Threshold Denoising (WTD) is proposed to denoise the signal of MHD ARS. Firstly, CEEMDAN is used to decompose noisy signals and obtain intrinsic mode functions (IMFs), and autocorrelation is used to determine the relevant modes where the effective signals are located. Then, the improved threshold and thresholding function are used to denoise the relevant modes. Finally, the denoised signal is obtained by combining the denoised relevant modes. In the experiment, noisy MHD ARS signals were recorded in static and dynamic conditions, and the effects of the proposed method and conventional methods were compared. The results of the Allan variance in the static condition and root-mean-square error in the dynamic condition show that the proposed method can effectively overcome the shortcomings of conventional methods and obtain a better denoising effect.
Gaze Estimation via Strip Pooling and Multi-Criss-Cross Attention Networks
Authors: Yan Chao , Pan Weiguo , Xu Cheng , Dai Songyin , Li Xuewei
Published: May 2023

Deep learning techniques for gaze estimation usually determine gaze direction directly from images of the face. These algorithms achieve good performance because face images contain more feature information than eye images. However, these image classes contain a substantial amount of redundant information that may interfere with gaze prediction and may represent a bottleneck for performance improvement. To address these issues, we model long-distance dependencies between the eyes via Strip Pooling and Multi-Criss-Cross Attention Networks (SPMCCA-Net), which consist of two newly designed network modules. One module is represented by a feature enhancement bottleneck block based on fringe pooling. By incorporating strip pooling, this residual module not only enlarges its receptive fields to capture long-distance dependence between the eyes but also increases weights on important features and reduces the interference of redundant information unrelated to gaze. The other module is a multi-criss-cross attention network. This module exploits a cross-attention mechanism to further enhance long-range dependence between the eyes by incorporating the distribution of eye-gaze features and providing more gaze cues for improving estimation accuracy. Network training relies on the multi-loss function, combined with smooth L1 loss and cross entropy loss. This approach speeds up training convergence while increasing gaze estimation precision. Extensive experiments demonstrate that SPMCCA-Net outperforms several state-of-the-art methods, achieving mean angular error values of 10.13° on the Gaze360 dataset and 6.61° on the RT-gene dataset.
Automatic Clustering for Improved Radio Environment Maps in Distributed Applications
Authors: Ben Chikha Haithem , Alaerjan Alaa
Published: May 2023

Wireless communication greatly contributes to the evolution of new technologies, such as the Internet of Things (IoT) and edge computing. The new generation networks, including 5G and 6G, provide several connectivity advantages for multiple applications, such as smart health systems and smart cities. Adopting wireless communication technologies in these applications is still challenging due to factors such as mobility and heterogeneity. Predicting accurate radio environment maps (REMs) is essential to facilitate connectivity and improve resource utilization. The construction of accurate REMs through the prediction of reference signal received power (RSRP) can be useful in densely distributed applications, such as smart cities. However, predicting an accurate RSRP in the applications can be complex due to intervention and mobility aspects. Given the fact that the propagation environments can be different in a specific area of interest, the estimation of a common path loss exponent for the entire area produces errors in the constructed REM. Hence, it is necessary to use automatic clustering to distinguish between different environments by grouping locations that exhibit similar propagation characteristics. This leads to better prediction of the propagation characteristics of other locations within the same cluster. Therefore, in this work, we propose using the Kriging technique, in conjunction with the automatic clustering approach, in order to improve the accuracy of RSRP prediction. In fact, we adopt K-means clustering (KMC) to enhance the path loss exponent estimation. We use a dataset to test the proposed model using a set of comparative studies. The results showed that the proposed approach provides significant RSRP prediction capabilities for constructing REM, with a gain of about 3.3 dB in terms of root mean square error compared to the case without clustering.
New Physicochemical Methodology for the Determination of the Surface Thermodynamic Properties of Solid Particles
Authors: Hamieh Tayssir
Published: May 2023

The study of the surface thermodynamic properties of solid materials is primordial for the determination of the dispersive surface energy, polar enthalpy of adsorption and Lewis’s acid base properties of solid particles. The inverse gas chromatography technique (IGC) at infinite dilution is the best surface technique for the determination of the surface physicochemical properties of materials. (1) Background: This paper was devoted to studying the surface properties of solid materials, such as alumina, titania and silica particles, using the IGC technique. (2) Methods: Different methods and molecular models, such as the spherical, cylindrical, Van der Waals, Redlich–Kwong, Kiselev and geometric models, were used to determine the London dispersive surface energy of solid surfaces. The Hamieh model was also used and highlighted the thermal effect on the surface area of solvents. (3) Results: The variations of the dispersive surface energy and the free energy of adsorption were determined for solid particles as a function of the temperature, as well as their Lewis’s acid base constants. Alumina surfaces were proved to exhibit a strong Lewis amphoteric character three times more basic than acidic, titanium dioxide more strongly basic than acidic and silica surface exhibited the stronger acidity. (4) Conclusions: The new methodology, based on the Hamieh model, gave the more accurate results of the physicochemical properties of the particle surfaces.
Traits of Adaptive Outdoor Thermal Comfort in a Tropical Urban Microclimate
Authors: Fong Chng Saun , Manavvi Suneja , Priya Radhakrishnan Shanthi , Ramakreshnan Logaraj , Sulaiman Nik Meriam , Aghamohammadi Nasrin
Published: May 2023

Urban heat islands (UHIs) are negatively impacting the quality of the urban environment and outdoor thermal comfort (OTC) levels, which have raised concerns regarding their impact on urban health and well-being. Understanding of OTC level is crucial, particularly in tropical cities with year-round high temperatures and humidity. A study was conducted in Kuala Lumpur (KL), Malaysia, to determine the OTC level in a selected urban area through microclimate measurements and questionnaire surveys with 1157 respondents. Over half of the urban dwellers reported thermal discomfort, with a high perceived OTC level, indicating strong thermal adaptive behaviours among the urban dwellers despite the physiological stress. Confounding factors such as urban morphology, land cover and human activity patterns also influence the OTC level in the tropical city. The findings emphasize the need for interventions to improve the urban environment and promote better outdoor thermal comfort for city dwellers through measures such as green infrastructure, UHI mitigation and increasing public awareness.
Examination of Factors Affecting the Likelihood of Whether Individuals Would Purchase Cartilage Conduction Hearing Aids
Authors: Takai Shunsuke , Sato Takeshi , Miyakura Yuya , Adachi Mika , Honkura Yohei , Yamauchi Daisuke , Katori Yukio
Published: May 2023

Cartilage conduction hearing aids (CC-HAs) are a novel type of hearing aid relying on cartilage conduction, the so-called third auditory conduction pathway. However, CC-HAs have only recently entered routine clinical use, and therefore data on their usefulness are lacking. The purpose of this study was to examine the possibility of assessing whether individual patients would show good adaptation to CC-HAs. Thirty-three subjects (41 ears in total) underwent a free trial of CC-HAs. Age, disease category, and the pure-tone threshold of air and bone conduction, unaided field sound threshold, aided field sound threshold, and functional gain (FG) at 0.25, 0.5, 1, 2, and 4 kHz were compared between patients who subsequently purchased and did not purchase the CC-HAs. Overall, 65.9% of the subjects purchased CC-HAs after the trial. In comparison to non-purchasers, those who decided to purchase CC-HAs showed better pure tone hearing thresholds at high frequencies for both air conduction (2 and 4 kHz) and bone conduction (1, 2, and 4 kHz), as well as for aided thresholds in the sound field (1, 2, and 4 kHz) when using CC-HAs. Therefore, the high-frequency hearing thresholds of subjects trialing CC-HAs might be helpful for identifying those who are likely to benefit from them.
Distance and Similarity Measures of Intuitionistic Fuzzy Parameterized Intuitionistic Fuzzy Soft Matrices and Their Applications to Data Classification in Supervised Learning
Authors: Memiş Samet , Arslan Burak , Aydın Tuğçe , Enginoğlu Serdar , Camcı Çetin
Published: May 2023

Intuitionistic fuzzy parameterized intuitionistic fuzzy soft matrices (ifpifs-matrices), proposed by Enginoğlu and Arslan in 2020, are worth utilizing in data classification in supervised learning due to coming into prominence with their ability to model decision-making problems. This study aims to define the concepts metrics, quasi-, semi-, and pseudo-metrics and similarities, quasi-, semi-, and pseudo-similarities over ifpifs-matrices; develop a new classifier by using them; and apply it to data classification. To this end, it develops a new classifier, i.e., Intuitionistic Fuzzy Parameterized Intuitionistic Fuzzy Soft Classifier (IFPIFSC), based on six pseudo-similarities proposed herein. Moreover, this study performs IFPIFSC’s simulations using 20 datasets provided in the UCI Machine Learning Repository and obtains its performance results via five performance metrics, accuracy (Acc), precision (Pre), recall (Rec), macro F-score (MacF), and micro F-score (MicF). It also compares the aforementioned results with those of 10 well-known fuzzy-based classifiers and 5 non-fuzzy-based classifiers. As a result, the mean Acc, Pre, Rec, MacF, and MicF results of IFPIFSC, in comparison with fuzzy-based classifiers, are 94.45%, 88.21%, 86.11%, 87.98%, and 89.62%, the best scores, respectively, and with non-fuzzy-based classifiers, are 94.34%, 88.02%, 85.86%, 87.65%, and 89.44%, the best scores, respectively. Later, this study conducts the statistical evaluations of the performance results using a non-parametric test (Friedman) and a post hoc test (Nemenyi). The critical diagrams of the Nemenyi test manifest the performance differences between the average rankings of IFPIFSC and 10 of the 15 are greater than the critical distance (4.0798). Consequently, IFPIFSC is a convenient method for data classification. Finally, to present opportunities for further research, this study discusses the applications of ifpifs-matrices for machine learning and how to improve IFPIFSC.
Non-Invasive Hybrid Ultrasound Stimulation of Visual Cortex In Vivo
Authors: Gong Chen , Li Runze , Lu Gengxi , Ji Jie , Zeng Yushun , Chen Jiawen , Chang Chifeng , Zhang Junhang , Xia Lily , Nair Deepthi S. Rajendran , Thomas Biju B. , Song Brian J. , Humayun Mark S. , Zhou Qifa
Published: May 2023

The optic nerve is the second cranial nerve (CN II) that connects and transmits visual information between the retina and the brain. Severe damage to the optic nerve often leads to distorted vision, vision loss, and even blindness. Such damage can be caused by various types of degenerative diseases, such as glaucoma and traumatic optic neuropathy, and result in an impaired visual pathway. To date, researchers have not found a viable therapeutic method to restore the impaired visual pathway; however, in this paper, a newly synthesized model is proposed to bypass the damaged portion of the visual pathway and set up a direct connection between a stimulated visual input and the visual cortex (VC) using Low-frequency Ring-transducer Ultrasound Stimulation (LRUS). In this study, by utilizing and integrating various advanced ultrasonic and neurological technologies, the following advantages are achieved by the proposed LRUS model: 1. This is a non-invasive procedure that uses enhanced sound field intensity to overcome the loss of ultrasound signal due to the blockage of the skull. 2. The simulated visual signal generated by LRUS in the visual-cortex-elicited neuronal response in the visual cortex is comparable to light stimulation of the retina. The result was confirmed by a combination of real-time electrophysiology and fiber photometry. 3. VC showed a faster response rate under LRUS than light stimulation through the retina. These results suggest a potential non-invasive therapeutic method for restoring vision in optic-nerve-impaired patients using ultrasound stimulation (US).
Comparative Analysis of the Venom Proteins from Two Eupelmid Egg Parasitoids Anastatus japonicus and Mesocomys trabalae
Authors: Zhao Qian-Yu , Chen Xu , Wang Run-Zhi , Chen Yong-Ming , Zang Lian-Sheng
Published: May 2023

Parasitic wasps are abundant and diverse Hymenoptera insects that lay their eggs inside or on the external surface of the host and inject venom into the host to create a more favorable environment for the larvae to survive and regulate the host’s immunity, metabolism, and development. But research on the composition of egg parasitoid venom is very limited. In this study, we used a combination of transcriptomic and proteomic approaches to identify the protein fractions of the venom in both eupelmid egg parasitoids, Anastatus japonicus and Mesocomys trabalae. We identified 3422 up-regulated venom gland genes (UVGs) in M. trabalae and 3709 in A. japonicus and analyzed their functions comparatively. By proteome sequencing, we identified 956 potential venom proteins in the venom pouch of M. trabalae, of which 186 were contained in UVGs simultaneously. A total of 766 proteins were detected in the venom of A. japonicus, of which 128 venom proteins were highly expressed in the venom glands. At the same time, the functional analysis of these identified venom proteins was carried out separately. We found the venom proteins in M. trabalae are well known but not in A. japonicus, which may be related to the host range. In conclusion, identifying venom proteins in both egg parasitoid species provides a database for studying the function of egg parasitoid venom and its parasitic mechanism.
Roles of Specialized Chromatin and DNA Structures at Subtelomeres in Schizosaccharomyces pombe
Authors: Kanoh Junko
Published: May 2023

Eukaryotes have linear chromosomes with domains called telomeres at both ends. The telomere DNA consists of a simple tandem repeat sequence, and multiple telomere-binding proteins including the shelterin complex maintain chromosome-end structures and regulate various biological reactions, such as protection of chromosome ends and control of telomere DNA length. On the other hand, subtelomeres, which are located adjacent to telomeres, contain a complex mosaic of multiple common segmental sequences and a variety of gene sequences. This review focused on roles of the subtelomeric chromatin and DNA structures in the fission yeast Schizosaccharomyces pombe. The fission yeast subtelomeres form three distinct chromatin structures; one is the shelterin complex, which is localized not only at the telomeres but also at the telomere-proximal regions of subtelomeres to form transcriptionally repressive chromatin structures. The others are heterochromatin and knob, which have repressive effects in gene expression, but the subtelomeres are equipped with a mechanism that prevents these condensed chromatin structures from invading adjacent euchromatin regions. On the other hand, recombination reactions within or near subtelomeric sequences allow chromosomes to be circularized, enabling cells to survive in telomere shortening. Furthermore, DNA structures of the subtelomeres are more variable than other chromosomal regions, which may have contributed to biological diversity and evolution while changing gene expression and chromatin structures.
Structural Basis of PE_PGRS Polymorphism, a Tool for Functional Modulation
Authors: Kramarska Eliza , De Maio Flavio , Delogu Giovanni , Berisio Rita
Published: May 2023

Background: The mycobacterial PE_PGRS protein family is present only in pathogenic strains of the genus mycobacterium, such as Mtb and members of the MTB complex, suggesting a likely important role of this family in pathogenesis. Their PGRS domains are highly polymorphic and have been suggested to cause antigenic variations and facilitate pathogen survival. The availability of AlphaFold2.0 offered us a unique opportunity to better understand structural and functional properties of these domains and a role of polymorphism in Mtb evolution and dissemination. Methods: We made extensive use of AlphaFold2.0 computations and coupled them with sequence distribution phylogenetic and frequency analyses, and antigenic predictions. Results: Modeling of several polymorphic forms of PE_PGRS33, the prototype of the PE_PGRS family and sequence analyses allowed us to predict the structural impact of mutations/deletions/insertions present in the most frequent variants. These analyses well correlate with the observed frequency and with the phenotypic features of the described variants. Conclusions: Here, we provide a thorough description of structural impacts of the observed polymorphism of PE_PGRS33 protein and we correlate predicted structures to the known fitness of strains containing specific variants. Finally, we also identify protein variants associated with bacterial evolution, showing sophisticated modifications likely endowed with a gain-of-function role during bacterial evolution.
Special Issue “Role of NRF2 in Disease: Novel Molecular Mechanisms and Therapeutic Approaches II”
Authors: Lastres-Becker Isabel
Published: May 2023

This Special Issue (https://www [...]
The Italian Framework of Bipolar Disorders in the Elderly: Old and Current Issues and New Suggestions for the Geriatric Psycho-Oncology Research
Authors: Frisardi Vincenza , Pollorsi Chiara , Sambati Luisa , Macchiarulo Maria , Fabbo Andrea , Neviani Francesca , Menchetti Marco , Chattat Rabih
Published: May 2023

Background: Older adults with mood disorders constitute a heterogeneous group in a complex spectrum interlinked with physical comorbidities. Worldwide, Bipolar disorders in older people (OABD) remain underestimated and underdiagnosed. OABD is challenging in the clinical setting and is associated with adverse outcomes (increased risk of anti-social behaviour triggered by inappropriate drugs and increased incidence of health deficits, including cancer). This article aims to describe the state of the art of OABD in the Italian framework and provide a new field of research. Methods: We performed an overview of the literature, selecting our target population (over 65 years) and synthesising the main challenging issues. By exploiting the Italian database from the Minister of Health in 2021, we analysed epidemiological data in the age range 65–74 years and 75–84 years old. Results: Females showed the highest prevalence and incidence in both groups, with a regional difference across the country but more evident in the Autonomous Provinces of Bolzano and Trento for the 65–74 years range. Several projects recently focused on this topic, and the urgency to define better the epidemiological framework is mandatory. Conclusions: This study represented the first attempt to report the comprehensive Italian framework on OABD aimed at fostering research activities and knowledge.
Blood pH Analysis in Combination with Molecular Medical Tools in Relation to COVID-19 Symptoms
Authors: Siebert Hans-Christian , Eckert Thomas , Bhunia Anirban , Klatte Nele , Mohri Marzieh , Siebert Simone , Kozarova Anna , Hudson John W. , Zhang Ruiyan , Zhang Ning , Li Lan , Gousias Konstantinos , Kanakis Dimitrios , Yan Mingdi , Jiménez-Barbero Jesús , Kožár Tibor , Nifantiev Nikolay E. , Vollmer Christian , Brandenburger Timo , Kindgen-Milles Detlef , Haak Thomas , Petridis Athanasios K.
Published: May 2023

The global outbreak of SARS-CoV-2/COVID-19 provided the stage to accumulate an enormous biomedical data set and an opportunity as well as a challenge to test new concepts and strategies to combat the pandemic. New research and molecular medical protocols may be deployed in different scientific fields, e.g., glycobiology, nanopharmacology, or nanomedicine. We correlated clinical biomedical data derived from patients in intensive care units with structural biology and biophysical data from NMR and/or CAMM (computer-aided molecular modeling). Consequently, new diagnostic and therapeutic approaches against SARS-CoV-2 were evaluated. Specifically, we tested the suitability of incretin mimetics with one or two pH-sensitive amino acid residues as potential drugs to prevent or cure long-COVID symptoms. Blood pH values in correlation with temperature alterations in patient bodies were of clinical importance. The effects of biophysical parameters such as temperature and pH value variation in relation to physical-chemical membrane properties (e.g., glycosylation state, affinity of certain amino acid sequences to sialic acids as well as other carbohydrate residues and lipid structures) provided helpful hints in identifying a potential Achilles heel against long COVID. In silico CAMM methods and in vitro NMR experiments (including 31P NMR measurements) were applied to analyze the structural behavior of incretin mimetics and SARS-CoV fusion peptides interacting with dodecylphosphocholine (DPC) micelles. These supramolecular complexes were analyzed under physiological conditions by 1H and 31P NMR techniques. We were able to observe characteristic interaction states of incretin mimetics, SARS-CoV fusion peptides and DPC membranes. Novel interaction profiles (indicated, e.g., by 31P NMR signal splitting) were detected. Furthermore, we evaluated GM1 gangliosides and sialic acid-coated silica nanoparticles in complex with DPC micelles in order to create a simple virus host cell membrane model. This is a first step in exploring the structure–function relationship between the SARS-CoV-2 spike protein and incretin mimetics with conserved pH-sensitive histidine residues in their carbohydrate recognition domains as found in galectins. The applied methods were effective in identifying peptide sequences as well as certain carbohydrate moieties with the potential to protect the blood–brain barrier (BBB). These clinically relevant observations on low blood pH values in fatal COVID-19 cases open routes for new therapeutic approaches, especially against long-COVID symptoms.
Plasmonic Nanopillars—A Brief Investigation of Fabrication Techniques and Biological Applications
Authors: Ahn Heesang , Kim Soojung , Oh Sung Suk , Park Mihee , Kim Seungchul , Choi Jong-ryul , Kim Kyujung
Published: May 2023

Nanopillars (NPs) are submicron-sized pillars composed of dielectrics, semiconductors, or metals. They have been employed to develop advanced optical components such as solar cells, light-emitting diodes, and biophotonic devices. To integrate localized surface plasmon resonance (LSPR) with NPs, plasmonic NPs consisting of dielectric nanoscale pillars with metal capping have been developed and used for plasmonic optical sensing and imaging applications. In this study, we studied plasmonic NPs in terms of their fabrication techniques and applications in biophotonics. We briefly described three methods for fabricating NPs, namely etching, nanoimprinting, and growing NPs on a substrate. Furthermore, we explored the role of metal capping in plasmonic enhancement. Then, we presented the biophotonic applications of high-sensitivity LSPR sensors, enhanced Raman spectroscopy, and high-resolution plasmonic optical imaging. After exploring plasmonic NPs, we determined that they had sufficient potential for advanced biophotonic instruments and biomedical applications.
FB-CCNN: A Filter Bank Complex Spectrum Convolutional Neural Network with Artificial Gradient Descent Optimization
Authors: Xu Dongcen , Tang Fengzhen , Li Yiping , Zhang Qifeng , Feng Xisheng
Published: May 2023

The brain–computer interface (BCI) provides direct communication between human brains and machines, including robots, drones and wheelchairs, without the involvement of peripheral systems. BCI based on electroencephalography (EEG) has been applied in many fields, including aiding people with physical disabilities, rehabilitation, education and entertainment. Among the different EEG-based BCI paradigms, steady-state visual evoked potential (SSVEP)-based BCIs are known for their lower training requirements, high classification accuracy and high information transfer rate (ITR). In this article, a filter bank complex spectrum convolutional neural network (FB-CCNN) was proposed, and it achieved leading classification accuracies of 94.85 ± 6.18% and 80.58 ± 14.43%, respectively, on two open SSVEP datasets. An optimization algorithm named artificial gradient descent (AGD) was also proposed to generate and optimize the hyperparameters of the FB-CCNN. AGD also revealed correlations between different hyperparameters and their corresponding performances. It was experimentally demonstrated that FB-CCNN performed better when the hyperparameters were fixed values rather than channel number-based. In conclusion, a deep learning model named FB-CCNN and a hyperparameter-optimizing algorithm named AGD were proposed and demonstrated to be effective in classifying SSVEP through experiments. The hyperparameter design process and analysis were carried out using AGD, and advice on choosing hyperparameters for deep learning models in classifying SSVEP was provided.
Tooth-Cutting-Induced Maxillary Malocclusion Exacerbates Cognitive Deficit in a Mouse Model of Vascular Dementia
Authors: Lee Young-Jun , Lim Chiyeon , Lim Sehyun , Cho Suin
Published: May 2023

Treatments to restore the balance of the temporomandibular joint (TMJ) are performed in the field of complementary and alternative medicine; however, evidence supporting this approach remains weak. Therefore, this study attempted to establish such evidence. Bilateral common carotid artery stenosis (BCAS) operation, which is commonly used for the establishment of a mouse model of vascular dementia, was performed, followed by tooth cutting (TEX) for maxillary malocclusion to promote the imbalance of the TMJ. Behavioural changes, changes in nerve cells and changes in gene expression were assessed in these mice. The TEX-induced imbalance of the TMJ caused a more severe cognitive deficit in mice with BCAS, as indicated by behavioural changes in the Y-maze test and novel object recognition test. Moreover, inflammatory responses were induced via astrocyte activation in the hippocampal region of the brain, and the proteins involved in inflammatory responses were found to be involved in these changes. These results indirectly show that therapies that restore the balance of the TMJ can be effectively used for the management of cognitive-deficit-related brain diseases associated with inflammation.
Inquiring about Loss Aversion of Achievement Value
Authors: Wu Chung-Chin
Published: May 2023

According to the achievement motivation theory, in achievement context, students may have to not only approach success/gain (e.g., strive to get a better grade) but also avoid failure/loss (e.g., avoid performing worse). However, these two types of achievement motivation have often been investigated separately. In contrast, loss aversion, a central argument in prospect theory, posits that avoiding losses has a greater impact on preferences than does approaching gains; suggesting that gain approach and loss avoidance should be treated as asymmetric forces that can be analyzed simultaneously to study approach to gain and avoidance to loss among students in terms of grades. The main purposes of this study were to propose an alternative measure to frame the dynamic evaluation process in the context of achievement that considers students’ sensitivity to performance change, and to further investigate students’ loss aversion in relation to grades through intrapersonal and interpersonal comparisons. A total of 41 and 72 college students participated in study 1 and study 2, respectively. One-way repeated measure ANOVA was conducted for the former sample while the single sample t-tests and independent sample ANOVA were used for the latter. Through the implementation of this alternative measure, the results revealed that (1) college students were more sensitive to performance changes than to their current or final performance, and (2) loss aversion was dependent on the referents. Students were averse to interpersonal loss, but not to intrapersonal loss. These findings indicate the usefulness of the proposed measure for investigating the asymmetric responses between two types of achievement motivation, and the proposed measure can be used to extend and revise the explanatory boundaries of prospect theory and self-discrepancy theory.
Targeting Iron-Sulfur Clusters in Cancer: Opportunities and Challenges for Ferroptosis-Based Therapy
Authors: Lee Jaewang , Roh Jong-Lyel
Published: May 2023

Iron dysregulation is a hallmark of cancer, characterized by an overexpression of genes involved in iron metabolism and iron-sulfur cluster (ISC) biogenesis. Dysregulated iron homeostasis increases intracellular labile iron, which may lead to the formation of excess cytotoxic radicals and make it vulnerable to various types of regulated cell death, including ferroptosis. The inhibition of ISC synthesis triggers the iron starvation response, increasing lipid peroxidation and ferroptosis in cancer cells treated with oxidative stress-inducing agents. Various methods, such as redox operations, iron chelation, and iron replacement with redox-inert metals, can destabilize or limit ISC formation and function, providing potential therapeutic strategies for cancer treatment. Targeting ISCs to induce ferroptosis represents a promising approach in cancer therapy. This review summarizes the state-of-the-art overview of iron metabolism and ferroptosis in cancer cells, the role of ISC modulation in ferroptosis, and the potential of targeting ISCs for ferroptosis induction in cancer therapy. Further research is necessary to develop and validate these strategies in clinical trials for various cancers, which may ultimately lead to the development of novel and effective treatments for cancer patients.