bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the noncoding RNA regulatory networks of H37Rv- and H37Rv△1759c-infected macrophages
Authors: Tan Chen , Dong Wenqi , Wang Gaoyan , Bai Yajuan , Li Yuxin , Huo Xinyu , Zhao Jing , Lu Wenjia , Lu Hao , Wang Chenchen , Wang Xiangru , Chen Huanchun
Published: March 2023

Noncoding RNAs regulate the process of Mycobacterium tuberculosis (M. tb) infecting the host, but there is no simultaneous transcriptional information of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) and the global regulatory networks of non-coding RNA. Rv1759c, a virulence factor, is a member of protein family containing the proline-glutamic acid (PE) in M. tb, which can increase M. tb survival. To reveal the noncoding RNA regulatory networks and the effect of Rv1759c on non-coding RNA expression during M. tb infection, we collected samples of H37Rv- and H37Rv△1759c-infected macrophages and explored the full transcriptome expression profile. We found 356 mRNAs, 433 lncRNAs, 168 circRNAs, and 12 miRNAs differentially expressed during H37Rv infection, 356 mRNAs, 433 lncRNAs, 168 circRNAs, and 12 miRNAs differentially expressed during H37Rv△1759c infection. We constructed lncRNA/circRNA-miRNA-mRNA regulatory networks during H37Rv and H37Rv△1759c infection. We demonstrated the role of one of the hubs of the networks, hsa-miR-181b-3p, for H37Rv survival in macrophages. We discovered that the expression changes of 68 mRNAs, 92 lncRNAs, 26 circRNAs, and 3 miRNAs were only related to the deletion of Rv1759c by comparing the transcription profiles of H37Rv and H37Rv△1759c. Here, our study comprehensively characterizes the transcriptional profiles in THP1-derived-macrophages infected with H37Rv and H37Rv△1759c, which provides support and new directions for in-depth exploration of noncoding RNA and PE/PPE family functions during the infection process.
From sequences to species: Charting the phytoplasma classification and taxonomy in the era of taxogenomics
Authors: Kirdat Kiran , Tiwarekar Bhavesh , Sathe Shivaji , Yadav Amit
Published: March 2023

Phytoplasma taxonomy has been a topic of discussion for the last two and half decades. Since the Japanese scientists discovered the phytoplasma bodies in 1967, the phytoplasma taxonomy was limited to disease symptomology for a long time. The advances in DNA-based markers and sequencing improved phytoplasma classification. In 2004, the International Research Programme on Comparative Mycoplasmology (IRPCM)- Phytoplasma/Spiroplasma Working Team – Phytoplasma taxonomy group provided the description of the provisional genus ‘Candidatus Phytoplasma’ with guidelines to describe the new provisional phytoplasma species. The unintentional consequences of these guidelines led to the description of many phytoplasma species where species characterization was restricted to a partial sequence of the 16S rRNA gene alone. Additionally, the lack of a complete set of housekeeping gene sequences or genome sequences, as well as the heterogeneity among closely related phytoplasmas limited the development of a comprehensive Multi-Locus Sequence Typing (MLST) system. To address these issues, researchers tried deducing the definition of phytoplasma species using phytoplasmas genome sequences and the average nucleotide identity (ANI). In another attempts, a new phytoplasma species were described based on the Overall Genome relatedness Values (OGRI) values fetched from the genome sequences. These studies align with the attempts to standardize the classification and nomenclature of ‘Candidatus’ bacteria. With a brief historical account of phytoplasma taxonomy and recent developments, this review highlights the current issues and provides recommendations for a comprehensive system for phytoplasma taxonomy until phytoplasma retains ‘Candidatus’ status.
Biotic interactions contribute more than environmental factors and geographic distance to biogeographic patterns of soil prokaryotic and fungal communities
Authors: Liu Yu , Ding Chengxiang , Li Xingfu , Su Derong , He Jing
Published: March 2023

Recent studies have shown distinct soil microbial assembly patterns across taxonomic types, habitat types and regions, but little is known about which factors play a dominant role in soil microbial communities. To bridge this gap, we compared the differences in microbial diversity and community composition across two taxonomic types (prokaryotes and fungi), two habitat types (Artemisia and Poaceae) and three geographic regions in the arid ecosystem of northwest China. To determine the main driving factors shaping the prokaryotic and fungal community assembly, we carried out diverse analyses including null model, partial mantel test and variance partitioning analysis etc. The findings suggested that the processes of community assembly were more diverse among taxonomic categories in comparison to habitats or geographical regions. The predominant driving factor of soil microbial community assembly in arid ecosystem was biotic interactions between microorganisms, followed by environmental filtering and dispersal limitation. Network vertex, positive cohesion and negative cohesion showed the most significant correlations with prokaryotic and fungal diversity and community dissimilarity. Salinity was the major environmental variable structuring the prokaryotic community. Although prokaryotic and fungal communities were jointly regulated by the three factors, the effects of biotic interactions and environmental variables (both are deterministic processes) on the community structure of prokaryotes were stronger than that of fungi. The null model revealed that prokaryotic community assembly was more deterministic, whereas fungal community assembly was structured by stochastic processes. Taken together, these findings unravel the predominant drivers governing microbial community assembly across taxonomic types, habitat types and geographic regions and highlight the impacts of biotic interactions on disentangling soil microbial assembly mechanisms.
Genetic diversity, distribution, and evolution of chicken anemia virus: A comparative genomic and phylogenetic analysis
Authors: Shah Pir Tariq , Bahoussi Amina Nawal , Cui Xiaogang , Shabir Shaista , Wu Changxin , Xing Li
Published: March 2023

Chicken infectious anemia (CIA) is an immunosuppressive poultry disease that causes aplastic anemia, immunosuppression, growth retardation and lymphoid tissue atrophy in young chickens and is responsible for huge economic losses to the poultry industry worldwide. The disease is caused by the chicken anemia virus (CAV), which belongs to the genus Gyrovirus, family Anelloviridae. Herein, we analyzed the full-length genomes of 243 available CAV strains isolated during 1991–2020 and classified them into two major clades, GI and GII, divided into three and four sub-clades, GI a-c, and GII a-d, respectively. Moreover, the phylogeographic analysis revealed that the CAVs spread from Japan to China, China to Egypt and subsequently to other countries, following multiple mutational steps. In addition, we identified eleven recombination events within the coding and non-coding regions of CAV genomes, where the strains isolated in China were the most active and involved in ten of these events. Furthermore, the amino acids variability analysis indicated that the variability coefficient exceeded the estimation limit of 1.00 in VP1, VP2, and VP3 proteins coding regions, demonstrating substantial amino acid drift with the rise of new strains. The current study offers robust insights into the phylogenetic, phylogeographic and genetic diversity characteristics of CAV genomes that may provide valuable data to map the evolutionary history and facilitate preventive measures of CAVs.
Isolation and characterization of algicidal bacteria from freshwater aquatic environments in China
Authors: Ren Sanguo , Jin Yuanpei , Ma Jianan , Zheng Ningning , Zhang Jie , Peng Xingyu , Xie Bo
Published: March 2023

Algicidal bacteria can inhibit the growth of algae or lyse algal cells, thus playing roles in shaping aquatic microbial communities and maintaining the functions of aquatic ecosystems. Nevertheless, our understanding of their diversities and distributions remains limited. In this study, we collected water samples from 17 freshwater sites in 14 cities in China and screened a total of 77 algicidal bacterial strains using several prokaryotic cyanobacteria and eukaryotic algae as target strains. According to their target-specificities, these strains were classified into three subgroups, cyanobacterial algicidal bacteria, algal algicidal bacteria, and broad-target algicidal bacteria, each displaying distinctive compositions and geographical distribution patterns. They are assigned to Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes bacterial phyla, of which Pseudomonas and Bacillus are the most abundant gram-negative and gram-positive genus, respectively. A number of bacterial strains, such as Inhella inkyongensis and Massilia eburnean, are suggested as new algicidal bacteria. The diverse taxonomies, algal-inhibiting abilities and distributions of these isolates have suggested that there are rich algicidal bacterial resources in these aquatic environments. Our results provide new microbial resources for algal-bacterial interaction studies, and shed new insights into how algicidal bacteria can be used in the control of harmful algal blooms, as well as in algal biotechnology.
Real-time vehicle target detection in inclement weather conditions based on YOLOv4
Authors: Wang Rui , Zhao He , Xu Zhengwei , Ding Yaming , Li Guowei , Zhang Yuxin , Li Hua
Published: March 2023

As a crucial component of the autonomous driving task, the vehicle target detection algorithm directly impacts driving safety, particularly in inclement weather situations, where the detection precision and speed are significantly decreased. This paper investigated the You Only Look Once (YOLO) algorithm and proposed an enhanced YOLOv4 for real-time target detection in inclement weather conditions. The algorithm uses the Anchor-free approach to tackle the problem of YOLO preset anchor frame and poor fit. It better adapts to the detected target size, making it suitable for multi-scale target identification. The improved FPN network transmits feature maps to unanchored frames to expand the model's sensory field and maximize the utilization of model feature data. Decoupled head detecting head to increase the precision of target category and location prediction. The experimental dataset BDD-IW was created by extracting specific labeled photos from the BDD100K dataset and fogging some of them to test the proposed method's practical implications in terms of detection precision and speed in Inclement weather conditions. The proposed method is compared to advanced target detection algorithms in this dataset. Experimental results indicated that the proposed method achieved a mean average precision of 60.3%, which is 5.8 percentage points higher than the original YOLOv4; the inference speed of the algorithm is enhanced by 4.5 fps compared to the original, reaching a real-time detection speed of 69.44 fps. The robustness test results indicated that the proposed model has considerably improved the capacity to recognize targets in inclement weather conditions and has achieved high precision in real-time detection.
Case report: Successful anterior temporal lobectomy in drug-resistant temporal lobe epilepsy associated with Sotos syndrome
Authors: Favi Bocca Leonardo , Pereira Rodrigues Thiago , Bortholin Thiago , Targas Yacubian Elza Márcia , Carrete Júnior Henrique , Guaranha Mirian , Silva Centeno Ricardo
Published: March 2023

The Sotos syndrome is an autosomal dominant disorder characterized by haploinsufficiency of NSD1 gene, with some individuals affected by epilepsy and, rarely, drug-resistant seizures. A 47-years-old female patient with Sotos syndrome was diagnosed with focal-onset seizures in left temporal lobe, left-side hippocampal atrophy, and neuropsychological testing with decreased performance in several cognitive domains. Patient was treated with left-side temporal lobe resection and developed complete awake seizure control in 3-years of follow-up, with marked improvement in quality-of-life. In selected, clinically concordant patients, resective surgeries may play a significant role in improving patient's quality of life and seizure control.
Look at me now! Enfacement illusion over computer-generated faces
Authors: La Rocca Stefania , Gobbo Silvia , Tosi Giorgia , Fiora Elisa , Daini Roberta
Published: March 2023

According to embodied cognition research, one’s bodily self-perception can be illusory and temporarily shifted toward an external body. Similarly, the so-called “enfacement illusion” induced with a synchronous multisensory stimulation over the self-face and an external face can result in implicit and explicit changes in the bodily self. The present study aimed to verify (i) the possibility of eliciting an enfacement illusion over computer-generated faces and (ii) which multisensory stimulation condition was more effective. A total of 23 participants were asked to look at a gender-matched avatar in three synchronous experimental conditions and three asynchronous control conditions (one for each stimulation: visuotactile, visuomotor, and simple exposure). After each condition, participants were asked to complete a questionnaire assessing both the embodiment and the enfacement sensations to address different facets of the illusion. Results suggest a stronger effect of synchronous vs. asynchronous stimulation, and the difference was more pronounced for the embodiment items of the questionnaire. We also found a greater effect of visuotactile and visuomotor stimulations as compared to the simple exposure condition. These findings support the enfacement illusion as a new paradigm to investigate the ownership of different face identities and the specific role of visuotactile and visuomotor stimulations with virtual reality stimuli.
Optimizing automated white matter hyperintensity segmentation in individuals with stroke
Authors: Ferris Jennifer K. , Lo Bethany P. , Khlif Mohamed Salah , Brodtmann Amy , Boyd Lara A. , Liew Sook-Lei
Published: March 2023

White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.
CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning
Authors: Diekmann Nicolas , Vijayabaskaran Sandhiya , Zeng Xiangshuai , Kappel David , Menezes Matheus Chaves , Cheng Sen
Published: March 2023

Reinforcement learning (RL) has become a popular paradigm for modeling animal behavior, analyzing neuronal representations, and studying their emergence during learning. This development has been fueled by advances in understanding the role of RL in both the brain and artificial intelligence. However, while in machine learning a set of tools and standardized benchmarks facilitate the development of new methods and their comparison to existing ones, in neuroscience, the software infrastructure is much more fragmented. Even if sharing theoretical principles, computational studies rarely share software frameworks, thereby impeding the integration or comparison of different results. Machine learning tools are also difficult to port to computational neuroscience since the experimental requirements are usually not well aligned. To address these challenges we introduce CoBeL-RL, a closed-loop simulator of complex behavior and learning based on RL and deep neural networks. It provides a neuroscience-oriented framework for efficiently setting up and running simulations. CoBeL-RL offers a set of virtual environments, e.g., T-maze and Morris water maze, which can be simulated at different levels of abstraction, e.g., a simple gridworld or a 3D environment with complex visual stimuli, and set up using intuitive GUI tools. A range of RL algorithms, e.g., Dyna-Q and deep Q-network algorithms, is provided and can be easily extended. CoBeL-RL provides tools for monitoring and analyzing behavior and unit activity, and allows for fine-grained control of the simulation via interfaces to relevant points in its closed-loop. In summary, CoBeL-RL fills an important gap in the software toolbox of computational neuroscience.
Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke
Authors: Gava Umberto A. , D’Agata Federico , Tartaglione Enzo , Renzulli Riccardo , Grangetto Marco , Bertolino Francesca , Santonocito Ambra , Bennink Edwin , Vaudano Giacomo , Boghi Andrea , Bergui Mauro
Published: March 2023

Objective

In this study, we investigate whether a Convolutional Neural Network (CNN) can generate informative parametric maps from the pre-processed CT perfusion data in patients with acute ischemic stroke in a clinical setting.

Methods

The CNN training was performed on a subset of 100 pre-processed perfusion CT dataset, while 15 samples were kept for testing. All the data used for the training/testing of the network and for generating ground truth (GT) maps, using a state-of-the-art deconvolution algorithm, were previously pre-processed using a pipeline for motion correction and filtering. Threefold cross validation had been used to estimate the performance of the model on unseen data, reporting Mean Squared Error (MSE). Maps accuracy had been checked through manual segmentation of infarct core and total hypo-perfused regions on both CNN-derived and GT maps. Concordance among segmented lesions was assessed using the Dice Similarity Coefficient (DSC). Correlation and agreement among different perfusion analysis methods were evaluated using mean absolute volume differences, Pearson correlation coefficients, Bland-Altman analysis, and coefficient of repeatability across lesion volumes.

Results

The MSE was very low for two out of three maps, and low in the remaining map, showing good generalizability. Mean Dice scores from two different raters and the GT maps ranged from 0.80 to 0.87. Inter-rater concordance was high, and a strong correlation was found between lesion volumes of CNN maps and GT maps (0.99, 0.98, respectively).

Conclusion

The agreement between our CNN-based perfusion maps and the state-of-the-art deconvolution-algorithm perfusion analysis maps, highlights the potential of machine learning methods applied to perfusion analysis. CNN approaches can reduce the volume of data required by deconvolution algorithms to estimate the ischemic core, and thus might allow the development of novel perfusion protocols with lower radiation dose deployed to the patient.
Therapeutic effects of CD133 + Exosomes on liver function after stroke in type 2 diabetic mice
Authors: Venkat Poornima , Gao Huanjia , Findeis Elizabeth L. , Chen Zhili , Zacharek Alex , Landschoot-Ward Julie , Powell Brianna , Lu Mei , Liu Zhongwu , Zhang Zhenggang , Chopp Michael
Published: March 2023

Background and purpose

Non-alcoholic fatty liver disease (NAFLD) is known to adversely affect stroke recovery. However, few studies investigate how stroke elicits liver dysfunction, particularly, how stroke in type 2 diabetes mellitus (T2DM) exacerbates progression of NAFLD. In this study, we test whether exosomes harvested from human umbilical cord blood (HUCBC) derived CD133 + cells (CD133 + Exo) improves neuro-cognitive outcome as well as reduces liver dysfunction in T2DM female mice.

Methods

Female, adult non-DM and T2DM mice subjected to stroke presence or absence were considered. T2DM-stroke mice were randomly assigned to receive PBS or Exosome treatment group. CD133 + Exo (20 μg/200 μl PBS, i.v.) was administered once at 3 days after stroke. Evaluation of neurological (mNSS, adhesive removal test) and cognitive function [novel object recognition (NOR) test, odor test] was performed. Mice were sacrificed at 28 days after stroke and brain, liver, and serum were harvested.

Results

Stroke induces severe and significant short-term and long-term neurological and cognitive deficits which were worse in T2DM mice compared to non-DM mice. CD133 + Exo treatment of T2DM-stroke mice significantly improved neurological function and cognitive outcome indicated by improved discrimination index in the NOR and odor tests compared to control T2DM-stroke mice. CD133 + Exo treatment of T2DM stroke significantly increased vascular and white matter/axon remodeling in the ischemic brain compared to T2DM-stroke mice. However, there were no differences in the lesion volume between non-DM stroke, T2DM-stroke and CD133 + Exo treated T2DM-stroke mice. In T2DM mice, stroke induced earlier and higher TLR4, NLRP3, and cytokine expression (SAA, IL1β, IL6, TNFα) in the liver compared to heart and kidney, as measured by Western blot. T2DM-stroke mice exhibited worse NAFLD progression with increased liver steatosis, hepatocellular ballooning, fibrosis, serum ALT activity, and higher NAFLD Activity Score compared to T2DM mice and non-DM-stroke mice, while CD133 + Exo treatment significantly attenuated the progression of NAFLD in T2DM stroke mice.

Conclusion

Treatment of female T2DM-stroke mice with CD133 + Exo significantly reduces the progression of NAFLD/NASH and improves neurological and cognitive function compared to control T2DM-stroke mice.
Mentha rotundifolia (L.) Huds. aqueous extract attenuates H2O2 induced oxidative stress and neurotoxicity
Authors: Boualam Khadija , Bouhaddou Nezha , Sobeh Mansour , Tabyaoui Mohamed , Taghzouti Khalid
Published: March 2023

Introduction

Oxidative stress plays a causal role in neurodegenerative diseases. The aim of this study is to evaluate the antioxidant and neuroprotective effects ofMentha rotundifolia(L.) Huds (M. rotundifolia), a widely used Moroccan plant in traditional medicine.

Methods

The chemical composition ofM. rotundifoliaaqueous extract was analyzed by liquid chromatography coupled to mass spectrometry (LC-MS). 2,2-diphenyl 1-picrylhydrazyl (DPPH) and 2,2′-azino-bis 3-ethylbenzothiazoline-6-sulfonic acid (ABTS+) assays were used to assess itsin vitroantioxidant activity. H2O2was utilized to induce oxidative stress and neurotoxicityin vivo. Behavioral changes were evaluated using Open Field, Y-maze and Rotarod tests. Hyperalgesia was assessed using the tail immersion test.

Results and discussion

The LC-MS/MS analysis revealed high content of kaempferol glucuronide (85%) at the extract. IC50values of the DPPH and ABTS were 26.47 and 41.21 μg/mL, respectively. Pre-treatments withM. rotundifoliaextract attenuated the behavioral changes induced by H2O2. In addition, the latency of tail withdrawal increased significantly in the treated groups suggesting central analgesic effect ofM. rotundifoliaextract. Moreover, the extract attenuated the deleterious effects of H2O2and improved all liver biomarkers. The obtained results suggested thatM. rotundifoliahad remarkable antioxidant and neuroprotective effects and may prevent oxidative stress related disorders.
Identification for the cortical 3-Hinges folding pattern based on cortical morphological and structural features
Authors: Cao Chunhong , Li Yongquan , Zhang Lele , Hu Fang , Gao Xieping
Published: March 2023

The Cortical 3-Hinges Folding Pattern (i.e., 3-Hinges) is one of the brain's hallmarks, and it is of great reference for predicting human intelligence, diagnosing eurological diseases and understanding the brain functional structure differences among gender. Given the significant morphological variability among individuals, it is challenging to identify 3-Hinges, but current 3-Hinges researches are mainly based on the computationally expensive Gyral-net method. To address this challenge, this paper aims to develop a deep network model to realize the fast identification of 3-Hinges based on cortical morphological and structural features. The main work includes: (1) The morphological and structural features of the cerebral cortex are extracted to relieve the imbalance between the number of 3-Hinges and each brain image's voxels; (2) The feature vector is constructed with the K nearest neighbor algorithm from the extracted scattered features of the morphological and structural features to alleviate over-fitting in training; (3) The squeeze excitation module combined with the deep U-shaped network structure is used to learn the correlation of the channels among the feature vectors; (4) The functional structure roles that 3-Hinges plays between adolescent males and females are discussed in this work. The experimental results on both adolescent and adult MRI datasets show that the proposed model achieves better performance in terms of time consumption. Moreover, this paper reveals that cortical sulcus information plays a critical role in the procedure of identification, and the cortical thickness, cortical surface area, and volume characteristics can supplement valuable information for 3-Hinges identification to some extent. Furthermore, there are significant structural differences on 3-Hinges among adolescent gender.
Electroacupuncture and manual acupuncture at LR3 and ST36 have attenuating effects on hypertension and subsequent cognitive dysfunction in spontaneously hypertensive rats: A preliminary resting-state functional magnetic resonance imaging study
Authors: Liu Ji-peng , Li Yin-yin , Yang Ke-zhen , Shi Shu-feng , Gong Yu , Tao Zhuang , Tong Yi , Sun Jiao , Yue Bing-nan , Li Xiao-lu , Gao Xin-yu , Liu Qing-guo , Xu Meng
Published: March 2023

Introduction

Chronic hypertension may have a contributory role toward cognitive impairment. Acupuncture exerts protective effects on cognitive functions while controlling the blood pressure. However, the neural mechanism underlying the dual attenuating effect of acupuncture remains unclear. In this study, we investigated the effects of electroacupuncture (EA) and manual acupuncture (MA) on the functional activity of the brain regions of spontaneously hypertensive rats (SHRs) by through resting-state functional magnetic resonance imaging (rs-fMRI). We also evaluated the differences in these functional activities between the EA and MA groups.

Methods

We randomly assigned 30 SHRs into the EA, MA, and model (SHR) groups. Wistar Kyoto rats (n = 10) were used as normal control (WKY). The interventions were administered once every alternate day for 12 weeks. The systolic blood pressure of all rats was recorded every 2 weeks until the end of the intervention. After the intervention, rs-fMRI scanning was performed to access the whole brain data of rats randomly selected from each group evenly. The amplitude of low frequency fluctuation (ALFF) analysis, regional homogeneity (ReHo) analysis, and functional connectivity (FC) analysis were also conducted. The Morris water maze (MWM) test was conducted to evaluate the learning and memory of the rats. Hematoxylin-eosin staining and Nissl staining were performed to observe histopathological changes in the key brain regions.

Results

We demonstrated that, when compared with the SHR group, the EA and MA groups had significantly lower blood pressure and better performance for behavioral test indices, and that the effect of EA was better than that of MA. ALFF and ReHo analyses revealed enhancement of the neuronal activity of some functionally impaired brain areas in the EA and MA groups. The main callback brain regions included the hypothalamus, entorhinal cortex, brain stem, prelimbic cortex, cingulate cortex, corpus callosum, and cerebellum. The FC analysis demonstrated that EA and MA enhanced the functional connectivity between the seeds and brain regions such as the brain stem, entorhinal cortex, hippocampus, prelimbic cortex, and cerebellum. The pathological test of the entorhinal cortex also verified the protective effect of acupuncture on the neuronal functional activity.

Discussion

Our findings suggested that EA and MA exhibited attenuating effects on hypertension and cognitive dysfunction by enhancing the functional activities in the corresponding brain regions. Moreover, EA activated more callback brain regions and functional connectivity than MA, which may explain why the effect of EA was better than that of MA.
EEG driving fatigue detection based on log-Mel spectrogram and convolutional recurrent neural networks
Authors: Gao Dongrui , Tang Xue , Wan Manqing , Huang Guo , Zhang Yongqing
Published: March 2023

Driver fatigue detection is one of the essential tools to reduce accidents and improve traffic safety. Its main challenge lies in the problem of how to identify the driver's fatigue state accurately. Existing detection methods include yawning and blinking based on facial expressions and physiological signals. Still, lighting and the environment affect the detection results based on facial expressions. In contrast, the electroencephalographic (EEG) signal is a physiological signal that directly responds to the human mental state, thus reducing the impact on the detection results. This paper proposes a log-Mel spectrogram and Convolution Recurrent Neural Network (CRNN) model based on EEG to implement driver fatigue detection. This structure allows the advantages of the different networks to be exploited to overcome the disadvantages of using them individually. The process is as follows: first, the original EEG signal is subjected to a one-dimensional convolution method to achieve a Short Time Fourier Transform (STFT) and passed through a Mel filter bank to obtain a logarithmic Mel spectrogram, and then the resulting logarithmic Mel spectrogram is fed into a fatigue detection model to complete the fatigue detection task for the EEG signals. The fatigue detection model consists of a 6-layer convolutional neural network (CNN), bi-directional recurrent neural networks (Bi-RNNs), and a classifier. In the modeling phase, spectrogram features are transported to the 6-layer CNN to automatically learn high-level features, thereby extracting temporal features in the bi-directional RNN to obtain spectrogram-temporal information. Finally, the alert or fatigue state is obtained by a classifier consisting of a fully connected layer, a ReLU activation function, and a softmax function. Experiments were conducted on publicly available datasets in this study. The results show that the method can accurately distinguish between alert and fatigue states with high stability. In addition, the performance of four existing methods was compared with the results of the proposed method, all of which showed that the proposed method could achieve the best results so far.
The role of selenoproteins in neurodevelopment and neurological function: Implications in autism spectrum disorder
Authors: Behl Supriya , Mehta Sunil , Pandey Mukesh K.
Published: March 2023

Selenium and selenoproteins play a role in many biological functions, particularly in brain development and function. This review outlines the role of each class of selenoprotein in human brain function. Most selenoproteins play a large antioxidant role within the brain. Autism spectrum disorder (ASD) has been shown to correlate with increased oxidative stress, and the presumption of selenoproteins as key players in ASD etiology are discussed. Further, current literature surrounding selenium in ASD and selenium supplementation studies are reviewed. Finally, perspectives are given for future directions of selenoprotein research in ASD.
Early development of infant gut microbiota in relation to breastfeeding and human milk oligosaccharides
Authors: Chichlowski Maciej , van Diepen Janna A. , Prodan Andrei , Olga Laurentya , Ong Ken K. , Kortman Guus A. M. , Dunger David B. , Gross Gabriele
Published: March 2023

Background

Infant gut microbiota composition is influenced by various factors early in life. Here, we investigate associations between infant gut microbiome development, infant age, breastfeeding duration, and human milk oligosaccharides (HMO) composition in breastmilk.

Methods

A total of 94 mother-infant pairs were recruited as part of the Cambridge Baby Growth and Breastfeeding Study (CBGS-BF) (Cambridge, UK). Infant stool samples (n= 337) were collected at 2 week, 6 week, 3 month, and 6 month of age. The 16S rRNA V3-V4 rRNA region was sequenced using MiSeq Illumina to determine microbiota composition and diversity. Mother’s hindmilk samples were collected at birth, 2 week, 6 week, 3 month, and 6 month postpartum. Concentrations of five neutral [2′FL, 3′FL, lacto-N-fucopentaose 1 (LNFP1), LNnT, LNT] and two acidic (3′SL, and 6′SL) HMOs were measured in all milk samples using High-Performance Anion-Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD). We explored the associations between infant gut microbiome parameters and age, duration of exclusive breastfeeding (EBF), and levels of individual HMOs.

Results

Bifidobacteriumwas the most abundant genus in infant stool at all-time points, irrespective of breastfeeding duration, with an overall mean relative abundance of 70%. The relative abundance ofB. bifidumin stool from infants who were breastfed for longer than 6 months was significantly higher compared to the infant breastfed up to 3 months (p= 0.0285). Alpha-diversity (both Shannon and ASV-level Richness) of infant gut microbiota showed a biphasic change with infant age, decreasing from 2 weeks until 3 months and then increasing until 6 months of age.Bifidobacteriumrelative abundance was associated with higher concentrations of 2′FL and LNFP1 in breastmilk across all time-points (p= 0.049 and 0.017, respectively), with trends toward a higher abundance ofB. longumspecies. No significant association withBifidobacteriumwas found for breastmilk LNnT, 3′SL, and 6′SL levels.

Conclusion

Our study is in line with previous data demonstrating that EBF duration in the first months of life impacts infant gut microbiota composition. The observed links between specific HMOs in breastmilk and bacteria in infant stool provide evidence of how mother’s milk affects infant microbiome development.
Documentation of the evidence-diagnosis link predicts nutrition diagnosis resolution in the Academy of Nutrition and Dietetics' diabetes mellitus registry study: A secondary analysis of Nutrition Care Process outcomes
Authors: Colin Casey , Arikawa Andrea , Lewis Sherri , Cooper Melissa , Lamers-Johnson Erin , Wright Lauri , Papoutsakis Constantina
Published: March 2023

Objectives

To describe nutrition care documentation patterns and investigate predictors of nutrition diagnosis resolution.

Methods

This is a secondary data analysis of a 2-year pragmatic, quasi-experimental study conducted in outpatient clinics where nutrition care was provided to adults with diabetes Type 1 or 2 from May 2017 to June 2019 (n = 564 patients). The main outcome measures were frequency of standardized Nutrition Care Process (NCP) terms, NCP links, nutrition diagnosis resolution and predictors of nutrition diagnosis resolution. Predictors of diagnosis resolution were identified using a multivariable logistic regression model.

Results

The most prevalent resolved diagnoses were excessive carbohydrate intake (32%), undesirable food choices (21%) and excessive energy intake (13%). The top etiology was food and nutrition related knowledge deficit (57%) and interventions were drawn mainly from the Nutrition Education domain (64%). One hundred forty-six patient cases (26%) had at least one follow-up visit and 26% of those with a follow-up (n = 38) had a resolved diagnosis. The presence of the evidence-diagnosis NCP link in documentation predicted diagnosis resolution (OR = 2.80, 95% CI 1.30–6.02; p = 0.008).

Conclusion

Most diagnoses were caused by patients' lack of knowledge and respective interventions focused on nutrition education. Odds of diagnosis resolution improved when the signs and symptoms of the diagnosis were documented during assessment (evidence-diagnosis NCP link). Training dietitians on NCP links may be important to resolve nutrition diagnoses. Presented findings are hypothesis generating.
Enteral formula compared to Nissen-Fundoplication: Data from a retrospective analysis on tolerance, utility, applicability, and safeness in children with neurological diseases
Authors: Trovato Chiara Maria , Capriati Teresa , Bolasco Giulia , Brusco Carla , Santariga Emma , Laureti Francesca , Campana Carmen , Papa Valentina , Mazzoli Bianca , Corrado Silvia , Tambucci Renato , Maggiore Giuseppe , Diamanti Antonella
Published: March 2023

Objectives and study

Approximately 46–90% of children with neurological disorders (NDs) suffer from gastrointestinal diseases, such as gastro-esophageal reflux disease (GERD), constipation, or malnutrition. Therefore, enteral feeding is often necessary to achieve nutritional requirements. The treatment of GERD could be based on pharmacological therapy, nutritional treatment (changing the type of formula), or surgical treatment (Nissen Fundoplication, NF). The aim of this study was to describe and compare resource consumption between NE based on different formulas and NF in patients with ND.

Methods

We performed a retrospective analysis on all children with neurological damage (age: 29 days−17 years) treated from January 2009 to January 2019 due to nutritional problems and food and/or gastrointestinal intolerances. For all patients, demographic and anthropometric characteristics, symptoms, type of nutrition (formula and enteral access), and number and type of outpatient or emergency room visits were collected. Patients with <24 months of age at the closing of the database and with <24 months of follow-up were excluded.

Results

Out of 376 children, 309 children (M: 158; median age: 4 IQR 1–10) were enrolled, among which, 65 patients (NF group M: 33; median age: 5.3 IQR 1.8–10.7) underwent NF. Vomit, GERD, and dysphagia were more represented in the NF group (p < 0.05). Our analysis shows that the NF group seems to present a lower number of hospitalization and a lower number of visits for non-GI disorders, but a higher number of visits for GI disorders compared to non-NF. In the NF group, a higher prevalence of the use of amino-acid-based formula and free diet is observed, with a trend for the lower prevalence of casein-based or whey+casein-based formula (Fisher test p = 0.072). The median cost of a patient enrolled in the database is € 19,515 ± 540 ($ 20,742.32 ± 573.96) per year, with no significant difference between the two groups. Regarding formula, at baseline, 76 children consumed a free diet, 24 a casein-based formula, 139 a whey+casein-based formula, 46 a whey-based formula, and 24 an amino-acid-based formula.

Conclusions

In conclusion, compared to EN, NF may not improve the clinical aspect and related costs in children with NDs. Considering the psychological and QoL burden for patients, in a “step-up” strategy, EN could be proposed as an efficient alternative to NF.
Variations of main quality components of matcha from different regions in the Chinese market
Authors: Luo Ying , Zhang Yazhao , Qu Fengfeng , Qian Wenjun , Wang Peiqiang , Zhang Xuzhou , Zhang Xinfu , Hu Jianhui
Published: March 2023

Matcha has a unique aroma of seaweed-like, which is popular with Chinese consumers. In order to effectively understand and use matcha for drinks and tea products, we roundly analyzed the variation of main quality components of 11 matcha samples from different regions in the Chinese market. Most of matcha samples had lower ratio of tea polyphenols to amino acids (RTA), and the RTA of 9 samples of matcha was less than 10, which is beneficial to the formation of fresh and mellow taste of matcha. The total volatile compounds concentrations by HS-SPME were 1563.59 ~ 2754.09 mg/L, among which terpenoids, esters and alcohols were the top three volatile components. The total volatile compounds concentrations by SAFE was 1009.21 ~ 1661.98 mg/L, among which terpenoids, heterocyclic compounds and esters ranked the top three. The 147 volatile components with high concentration (>1 mg/L) and no difference between samples are the common odorants to the 11 samples of matcha. The 108 distinct odorants had differences among the matcha samples, which were important substances leading to the different aroma characteristics. Hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) showed that 11 samples of matcha were well clustered according to different components. Japanese matcha (MT, MY, ML, MR, MJ) could be clustered into two categories. The aroma composition of Guizhou matcha (GM1, GM2) was similar to that of Japanese matcha, 45 volatile components (decanal, pyrazine, 3,5-diethyl-2-methyl-, 1-hexadecanol, etc. were its characteristic aroma components. The aroma characteristics of Shandong matcha and Japanese matcha (ML, MR, MJ) were similar, 15 volatile components (γ-terpinene, myrtenol, cis-3-hexenyl valerate, etc.) were its characteristic aroma components. While Jiangsu matcha and Zhejiang matcha have similar aroma characteristics due to 225 characteristic aroma components (coumarin, furan, 2-pentyl-, etc). In short, the difference of volatile components formed the regional flavor characteristics of matcha. This study clarified the compound basis of the flavor difference of matcha from different regions in the Chinese market, and provided a theoretical basis for the selection and application of matcha in drinks and tea products.
The treatment of transarterial chemoembolization/hepatic arterial infusion chemotherapy combined with lenvatinib and PD-1 inhibitor is effective against hepatocellular carcinoma with portal vein tumor thrombus: A systematic review
Authors: Yuanren Gao , Yin Linan , Liu Ruibao , Cui Yali
Published: March 2023

Background

Lenvatinib combined with programmed cell death protein-1 inhibitor has achieved good survival results in the treatment of hepatocellular carcinoma with portal vein tumor thrombus. Transarterial chemoembolization (TACE) or hepatic arterial infusion chemotherapy (HAIC) has attracted attention because of its high response rate and favorable survival rate in patients with liver cancer and portal vein tumor thrombus. This study aimed to compare the efficacy and safety of Lenvatinib combined with programmed cell death protein-1 inhibitor plus transarterial chemoembolization or hepatic arterial infusion chemotherapy in patients with hepatocellular carcinoma with portal vein tumor thrombus.

Method

We searched PubMed, Embase and the Cochrane Library for studies. These included randomized controlled trials or clinical trials of Lenvatinib plus programmed cell death protein-1 inhibitor plus transarterial chemoembolization or hepatic arterial infusion chemotherapy (intervention group) versus Lenvatinib plus programmed cell death protein-1 inhibitor or Lenvatinib plus transarterial chemoembolization/hepatic arterial infusion chemotherapy or Lenvatinib alone (control group) in liver cancer with portal vein tumor thrombus The primary outcomes were overall survival and progression-free time, and the secondary outcomes were response rate and the rate of adverse events. According to the heterogeneity among different studies, Revman5.4 was used to conduct fixed effect or random effect model analysis.

Results

Five clinical trials were included, including 311 cases in the intervention group and 309 cases in the control group. In terms of efficacy, compared with the control group, the overall survival (HR=1.88, 95%CI: 1.57-2.25, P < 0.00001) and progression-free survival (HR=1.62, 95%CI: 1.41-1.86, P < 0.00001), better efficacy, and better disease response than the control group. In terms of safety, the risk of treatment-related adverse events in the intervention group was higher than that in the control group, and White Blood cell count decreased (RR=0.72, 95%CI: 0.38-1.37, P=0.32), Platelet count decreased (RR=0.99, 95%CI: 0.65-1.51, P=0.96) and Total bilirubin increased (RR=0.86, 95%CI: Increased) 0.88-1.28, P=0.46) were lower than those in the control group, and the rest were higher than those in the control group, and the differences in some results were statistically significant.

Conclusions

Transarterial chemoembolization or hepatic arterial infusion chemotherapy combined with Lenvatinib plus programmed cell death protein-1 inhibitor can effectively delay the progression, prolong the survival period and improve the quality of life of liver cancer patients with portal vein tumor thrombus.
A noninvasive nomogram model based on CT features to predict DNA mismatch repair deficiency in gastric cancer
Authors: Chen Jie-Yu , Tong Ya-Han , Chen Hai-Yan , Yang Yong-Bo , Deng Xue-Ying , Shao Guo-Liang
Published: March 2023

Objectives

DNA mismatch repair deficiency (dMMR) status has served as a positive predictive biomarker for immunotherapy and long-term prognosis in gastric cancer (GC). The aim of the present study was to develop a computed tomography (CT)-based nomogram for preoperatively predicting mismatch repair (MMR) status in GC.

Methods

Data from a total of 159 GC patients between January 2020 and July 2021 with dMMR GC (n=53) and MMR-proficient (pMMR) GC (n=106) confirmed by postoperative immunohistochemistry (IHC) staining were retrospectively analyzed. All patients underwent abdominal contrast-enhanced CT. Significant clinical and CT imaging features associated with dMMR GC were extracted through univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) and internal validation of the cohort data were performed.

Results

The nomogram contained four potential predictors of dMMR GC, including gender (odds ratio [OR] 9.83, 95% confidence interval [CI] 3.78-28.20, P < 0.001), age (OR 3.32, 95% CI 1.36-8.50, P = 0.010), tumor size (OR 5.66, 95% CI 2.12-16.27, P < 0.001) and normalized tumor enhancement ratio (NTER) (OR 0.15, 95% CI 0.06-0.38, P < 0.001). Using an optimal cutoff value of 6.6 points, the nomogram provided an area under the curve (AUC) of 0.895 and an accuracy of 82.39% in predicting dMMR GC. The calibration curve demonstrated a strong consistency between the predicted risk and observed dMMR GC. The DCA justified the relatively good performance of the nomogram model.

Conclusion

The CT-based nomogram holds promise as a noninvasive, concise and accurate tool to predict MMR status in GC patients, which can assist in clinical decision-making.