Similar Comparison Research Articles

Decoupling Deep Learning for Enhanced Image Recognition Interpretability

The quest for enhancing the interpretability of neural networks has become a prominent focus in recent research endeavors. Prototype-based neural networks have emerged as a promising avenue for imbuing models with interpretability by gauging the similarity between image components and category prototypes to inform decision-making. However, these networks face challenges as they share similarity activations during both the inference and explanation processes, creating a tradeoff between accuracy and interpretability. To address this issue and ensure that a network achieves high accuracy and robust interpretability in the classification process, this article introduces a groundbreaking prototype-based neural network termed the “Decoupling Prototypical Network” (DProtoNet). This novel architecture comprises encoder, inference, and interpretation modules. In the encoder module, we introduce decoupling feature masks to facilitate the generation of feature vectors and prototypes, enhancing the generalization capabilities of the model. The inference module leverages these feature vectors and prototypes to make predictions based on similarity comparisons, thereby preserving an interpretable inference structure. Meanwhile, the interpretation module advances the field by presenting a novel approach: a “multiple dynamic masks decoder” that replaces conventional upsampling similarity activations. This decoder operates by perturbing images with mask vectors of varying sizes and learning saliency maps through consistent activation. This methodology offers a precise and innovative means of interpreting prototype-based networks. DProtoNet effectively separates the inference and explanation components within prototype-based networks. By eliminating the constraints imposed by shared similarity activations during the inference and explanation phases, our approach concurrently elevates accuracy and interpretability. Experimental evaluations on diverse public natural datasets, including CUB-200-2011, Stanford Cars, and medical datasets like RSNA and iChallenge-PM, corroborate the substantial enhancements achieved by our method compared to previous state-of-the-art approaches. Furthermore, ablation studies are conducted to provide additional evidence of the effectiveness of our proposed components.

Retrieval of Solar Shortwave Irradiance from All-Sky Camera Images

The present work proposes a new model based on a convolutional neural network (CNN) to retrieve solar shortwave (SW) irradiance via the estimation of the cloud modification factor (CMF) from daytime sky images captured by all-sky cameras; this model is named CNN-CMF. To this end, a total of 237,669 sky images paired with SW irradiance measurements obtained by using pyranometers were selected at the following three sites: Valladolid and Izaña, Spain, and Lindenberg, Germany. This dataset was randomly split into training and testing sets, with the latter excluded from the training model in order to validate it using the same locations. Subsequently, the test dataset was compared with the corresponding SW irradiance measurements obtained by the pyranometers in scatter density plots. The linear fit shows a high determination coefficient (R2) of 0.99. Statistical analyses based on the mean bias error (MBE) values and the standard deviation (SD) of the SW irradiance differences yield results close to −2% and 9%, respectively. The MBE indicates a slight underestimation of the CNN-CMF model compared to the measurement values. After its validation, model performance was evaluated at the Antarctic station of Marambio (Argentina), a location not used in the training process. A similar comparison between the model-predicted SW irradiance and pyranometer measurements yielded R2=0.95, with an MBE of around 2% and an SD of approximately 26%. Although the precision provided by the SD at the Marambio station is lower, the MBE shows that the model’s accuracy is similar to previous results but with a slight overestimation of the SW irradiance. Finally, the determination coefficient improved to 0.99, and the MBE and SD are about 3% and 11%, respectively, when the CNN-CMF model is used to estimate daily SW irradiation values.

APD-YOLOv7: Enhancing Sustainable Farming through Precise Identification of Agricultural Pests and Diseases Using a Novel Diagonal Difference Ratio IOU Loss

The diversity and complexity of the agricultural environment pose significant challenges for the collection of pest and disease data. Additionally, pest and disease datasets often suffer from uneven distribution in quantity and inconsistent annotation standards. Enhancing the accuracy of pest and disease recognition remains a challenge for existing models. We constructed a representative agricultural pest and disease dataset, FIP6Set, through a combination of field photography and web scraping. This dataset encapsulates key issues encountered in existing agricultural pest and disease datasets. Referencing existing bounding box regression (BBR) loss functions, we reconsidered their geometric features and proposed a novel bounding box similarity comparison metric, DDRIoU, suited to the characteristics of agricultural pest and disease datasets. By integrating the focal loss concept with the DDRIoU loss, we derived a new loss function, namely Focal-DDRIoU loss. Furthermore, we modified the network structure of YOLOV7 by embedding the MobileViTv3 module. Consequently, we introduced a model specifically designed for agricultural pest and disease detection in precision agriculture. We conducted performance evaluations on the FIP6Set dataset using mAP75 as the evaluation metric. Experimental results demonstrate that the Focal-DDRIoU loss achieves improvements of 1.12%, 1.24%, 1.04%, and 1.50% compared to the GIoU, DIoU, CIoU, and EIoU losses, respectively. When employing the GIoU, DIoU, CIoU, EIoU, and Focal-DDRIoU loss functions, the adjusted network structure showed enhancements of 0.68%, 0.68%, 0.78%, 0.60%, and 0.56%, respectively, compared to the original YOLOv7. Furthermore, the proposed model outperformed the mainstream YOLOv7 and YOLOv5 models by 1.86% and 1.60%, respectively. The superior performance of the proposed model in detecting agricultural pests and diseases directly contributes to reducing pesticide misuse, preventing large-scale pest and disease outbreaks, and ultimately enhancing crop yields. These outcomes strongly support the promotion of sustainable agricultural development.

CIEC: Cross-tissue Immune Cell Type Enrichment and Expression Map Visualization for Cancer.

Single-cell transcriptome sequencing technology has been applied to decode the cell types and functional states of immune cells, revealing their tissue-specific gene expression patterns and functions in cancer immunity. Comprehensive assessments of immune cells within and across tissues will provide us with a deeper understanding of the tumor immune system in general. Here, we present Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), the first web-based application that integrates database and enrichment analysis to estimate the cross-tissue immune cell type or state. CIEC version 1.0 consists of 480 samples covering primary tumor, adjacent normal tissue, lymph node, metastasis tissue, and peripheral blood from 323 cancer patients. By applying integrative analysis, we constructed an immune cell-type/state map for each context and adopted our previously developed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm to estimate the enrichment for context-specific immune cell type/state. In addition, CIEC also provides an easy-to-use online interface for users to comprehensively analyze the immune cell characteristics mapped across multiple tissues, including expression map, correlation, similar genes detection, signature score, and expression comparison. We believe that CIEC will be a valuable resource for exploring the intrinsic characteristics of immune cells in cancer patients and for potentially guiding novel cancer-immune biomarker development and immunotherapy strategies. CIEC is freely accessible at http://ciec.gene.ac/.

B-127 The Effect of Hemolysis on Potassium Measurement in a Community Setting: The Marching Error

Abstract Background Potassium is one of the most sensitive analytes to in-vitro hemolysis. To detect this error, modern clinical chemistry analyzers calculate the hemolysis index (HI) to estimate the degree of specimen hemolysis. Recently, Roche Diagnostics lowered the acceptable potassium HI limit from 100 to 20 and recommended laboratories avoid using specimens with an HI>20. The goal of this study was to determine a clinically acceptable HI cut-off for potassium at our community reference laboratory, relying on patient data from routine laboratory operation. Methods Plasma venous potassium, sodium, and HI test results from community patients measured on Roche cobas 8000 ISE and c701 modules between September 2022 to December 2023 were extracted from the Roche Infinity Middleware (n=1,101,897). Data was divided into groups based on HI which ranged from 0 to 300. The sample pool with the lowest level of hemolysis (HI≤10) was defined as the base group. Mean and standard deviation of potassium for each HI group was calculated and the difference in the mean between each group compared to the base group was calculated as both absolute and percent ΔK. Percent changes in critical values for both potassium and sodium as a function of hemolysis were calculated for each HI group. Measurement uncertainty (MU) for potassium was calculated using a top-down approach. Data were analyzed in Rstudio and Microsoft Excel. Results The vast majority of potassium specimens (83.8%) were stratified into the HI base group (HI ≤10) and 96.8 % had an HI ≤ 20, the cut-off recommended by Roche. The mean potassium level for each HI group increased as the degree of hemolysis in the specimens became more elevated. A MU-derived analytically significant shift of ΔK>0.1 mmol/L was observed for the bin HI 21-30. Depending on the employed total allowable error limit, clinically significant shifts in mean potassium levels were observed at HI bin 41-50 (RCPA: ΔK>0.2 mmol/L) or HI bin 101-150 (EFLM-derived reference change value: ΔK>10.1% and CLIA: ΔK>0.5mmol/L. The shift in patient potassium values seen as HI increased led to a change in critical results reporting frequencies. In the base group (HI≤10), 0.06% and 0.07% of results had low (<2.6 mmol/L) or high (>6.2 mmol/L) critical potassium values, respectively. When HI was 101-300, 0.00 and 15.7% of results had low or high critical potassium values. A similar comparison performed with sodium did not show the same shift in reported critical values. Linear regression of ΔK plotted vs HI produced the equation ΔK=0.0051xHI, validating the equation of Martinez-Morillo and Alvarez published previously using paired hemolyzed/non-hemolyzed potassium laboratory data. Conclusions In community patients, in-vitro hemolysis produced analytically significant errors at an HI of 20. Clinically significant errors occurred between an HI of 40-100. Past HI 100, mean ΔKs of 0.5-1.20 mmol/L were seen in our population. This shift in patient values as a function of hemolysis led to a change in critical result reporting, suggesting the generation of both factious critically high potassium results and the masking of critically low potassium results in our patient population.

Assessing the Recreational Fishers and their Catches based on Social Media Platforms: Privacy and Ethical Data Analysis Considerations

Social Media (SM) can offer insights to track recreational Fishing (Rf); Many Limitations Hinder Its Practical Application. The proportion and characteristics of RFs that share their catches remain unidentified. The objective was to enhance the surveillance abilities of RF by utilizing SM information. This study focuses on the sharing economy information transmission, network optimization of SM platforms, and privacy protection issues during data transmission. The study starts with the data transmission characteristics in SM platforms, analyzes the data ethics in SM information transmission from the perspectives of natural and economic data attributes, and then focuses on the privacy protection principles in network information transmission. Then, a privacy protection scheme based on a locally sensitive hash algorithm is constructed, and finally, an information transmission scheme and method optimization based on a network optimization module are proposed. The research gathered data using physical (face-to-face) surveys and digital (email) surveys to define marine RF that post catches on online platforms (“sharers”), together with additional demographic and fishing data. A comparative analysis was conducted on the computational convergence and accuracy of different privacy protection methods, and the optimal rule framework for data privacy protection was discussed. The observation results show that the efficiency of information transmission using the Minhash-SSNR method is slightly inferior to that using the OSNR-SSNR method. Minhash technology is based on a similarity comparison of dimensionality-reduced data. This leads to data causing the initially highly similar two sets of lists to be misjudged as not having enough similarity, thereby reducing some potential information dissemination opportunities and affecting the efficacy of information transmission. It can be seen that the Minhash-SSNR strategy can effectively send information to nodes with high similarity, preventing excessive information duplication within the system. Although the Minhash-SSNR strategy has a certain degree of decline in information transmission efficiency, it accounts for only about 5% compared to the OSNR-SSNR strategy, ensuring the essential operational stability of SM opportunity networks without significant impact. With few learning and training times, the network information transmission optimization module proposed in this study quickly achieved a lower exponential error. As the number of training sessions gradually increases, the exponential error of the network information transmission optimization module in this study is small, and the prediction accuracy of the method is high. RFs who captured a prize, iconic, or symbolic species tended to discuss their catches more. This research signifies significant progress in incorporating SM information to oversee RFs.

Innovative multi-stage matching for counting anything

Few-shot counting (FSC) is the task of counting the number of objects in an image that belong to the same category, by using a provided exemplar pattern. By replacing the exemplar, we can effectively count anything, even in cases where we have no prior knowledge of that category’s exemplar. However, due to the variations within the same category and the impact of inter-class similarity, it is challenging to achieve accurate intra-class similarity matching using conventional similarity comparison methods. To tackle these issues, we propose a novel few-shot counting method called Multi-stage Exemplar Attention Match Network (MEAMNet), which increases the accuracy of matching, reduces the impact of noise, and enhances similarity feature matching. Specifically, we propose a multi-stage matching strategy to obtain more stable and effective matching results by acquiring similar feature in different feature spaces. In addition, we propose a novel feature matching module called Exemplar Attention Match (EAM). With this module, the intra-class similarity representation in each stage will be enhanced to achieve a better matching of the key feature. Experimental results indicate that our method not only significantly surpasses the state-of-the-art (SOTA) methods in most evaluation metrics on the FSC-147 dataset but also achieves comprehensive superiority on the CARPK dataset. This highlights the outstanding accuracy and stability of our matching performance, as well as its exceptional transferability. We will release the code at https://github.com/hzg0505/MEAMNet.

Lead–lag effect of research between conference papers and journal papers in data mining

AbstractThe examination of the lead–lag effect between different publication types, incorporating a temporal dimension, is very significant for assessing research. In this article, we introduce a novel framework to quantify the lead–lag effect between the research topics of conference papers and journal papers. We first identify research topics via the text‐embedding‐based topic modeling technique BERTopic, then extract the research topics of each time slice, construct and visualize the similarity matrix of topics to reveal the time‐lag direction and finally quantify the lead–lag effect by four proposed indicators, as well as by average influence topic similarity comparison maps. We conduct a detailed analysis of 19,166 bibliographic data for top conference papers and journal papers from 2015 to 2019 in the data mining field, calculate the similarity of topics obtained by BERTopic between each time slice divided by quarters. The results show that journal paper topics lag behind conference paper topics in the data mining field. The most significant lead–lag effect is 2.5 years, with approximately 33.45% of topics affected by this lag. The methodology presented here holds potential for broader application in the analysis of lead–lag effects across diverse research areas, offering valuable insights into the state of research development and informing policy decisions.This article is categorized under: Application Areas > Science and Technology

White coat hypertension in acute retinal vein occlusion

PurposeTo investigate the association between white-coat hypertension (WCH) and acute retinal vein occlusion (RVO).MethodsIn this retrospective case-control study, patients aged 40 years or older diagnosed with acute-phase RVO were included. Patients with other pathologies served as non-RVO controls. Blood pressure (BP) was measured in the office during their initial visit, and information about home BP and hypertension (HTN) medication was obtained through interviews. After 1:2 age and sex-matching between the RVO and non-RVO groups, the proportions of HTN cases were compared. A similar comparison was made in subgroups with or without HTN medication.ResultsFifty-one patients with RVO and 102 with non-RVO were included in the analysis. For the entire cohort, the RVO group exhibited a significantly greater proportion of WCH and sustained HTN compared to the non-RVO group. In the subgroup without HTN treatment, the proportion of WCH or sustained HTN was still significantly higher in the RVO group. However, in the subgroup receiving HTN treatment, the proportion of WCH or sustained HTN was higher in the RVO group than in the non-RVO group, though not statistically significant.ConclusionThis case-control study suggests that WCH may be associated with RVO, particularly in patients without HTN treatment. Given that interventions for WCH have not been standardized, a more detailed and prospective study is warranted to elucidate the risk of WCH for RVO and other retinal vascular diseases.

Encoding modelling for working memory research: Pattern similarity, representational geometry, and model comparison

Encoding modelling for working memory research: Pattern similarity, representational geometry, and model comparison

Mesoscale simulation method for preplaced aggregate concrete based on physics engine

Preplaced aggregate concrete (PAC) has up to 60 % aggregate volume content, making mesoscale modelling difficult. A novel mesoscale simulation method based on physics engine was proposed in this study to accurately simulate the coarse aggregate skeleton of PAC. Unlike in conventional mesoscale simulations, point-to-point contacts between aggregates were formed due to virtual gravity in the physics engine. To verify this novel method, mechanical property and shrinkage behavior tests of PAC were conducted under different aggregate gradings and with different expansive agents. For the mechanical property test, the simulation results were compared with the test results in terms of the aggregate stacking state, failure mode, stress–strain curve, and mechanical property parameters. Repeatability and aggregate shape analyses were performed using finite element (FE) model. A similar comparison between the simulation and test results was also performed for the shrinkage behavior. A shrinkage coefficient reflecting the relationship between grout and PAC shrinkage was proposed. This novel mesoscale simulation method based on physics engine is particularly suitable for PAC. However, it is not limited to PAC and can be applied to the simulation of conventional concrete, thus solving the problem of traditional simulation methods that struggle to achieve a high aggregate fraction.

Transforming of scalp EEGs with different channel locations by REST for comparative study

ObjectiveThe diversity of electrode placement systems brought the problem of channel location harmonization in large-scale electroencephalography (EEG) applications to the forefront. Therefore, our goal was to resolve this problem by introducing and assessing the reference electrode standardization technique (REST) to transform EEGs into a common electrode distribution with computational zero reference at infinity offline. MethodsSimulation and eye-closed resting-state EEG datasets were used to investigate the performance of REST for EEG signals and power configurations. ResultsREST produced small errors (the root mean square error (RMSE): 0.2936–0.4583; absolute errors: 0.2343–0.3657) and high correlations (>0.9) between the estimated signals and true ones. The comparison of configuration similarities in power among various electrode distributions revealed that REST induced infinity reference could maintain a perfect performance similar (>0.9) to that of true one. ConclusionThese results demonstrated that REST transformation could be adopted to resolve the channel location harmonization problem in large-scale EEG applications.

Tree growth history, legacy of large-scale forest management and climatic variability in North Finland

Tree growth history was investigated in North Finland to study the recently observed reduction in Scots pine growth. Tree-ring records from the National Forest Inventory (NFI) were compared to changes that have occurred in forest management activities and to variations in the North Atlantic Oscillation (NAO), as similar comparisons have not been previously made with NFI data. A phase of increased growth was dated to the early 1970s when the forest management activities were intensified on a large scale. More recently, growth has notably declined since the early 2000s which coincides with reduced activity to clean the ditches to ensure they are draining the substrate adequately. The growth reduction appeared greater for trees from stands with higher basal area. Trees representing sites where the first cleaning of the stand (thinning) had been carried out did not show reduced growth. NAO indices correlated positively with growth, especially during the cold season. An interpretation on the value of snow conditions in a dynamic interaction with management history/stand density is put forth to explain the growth decline observed in NFI data over the past two decades.

Characterization of gut symbionts from wild-caught Drosophila and other Diptera: description of Utexia brackfieldae gen. nov., sp. nov., Orbus sturtevantii sp. nov., Orbus wheelerorum sp. nov, and Orbus mooreae sp. nov.

Non-culture based surveys show that the bacterial family Orbaceae is widespread in guts of insects, including wild Drosophila. Relatively few isolates have been described, and none has been described from Drosophila. We present the isolation and characterization of five strains of Orbaceae from wild-caught flies of the genera Drosophila (Diptera: Drosophilidae) and Neogriphoneura (Diptera: Lauxaniidae). Cells are generally rod-shaped, mesophilic, and measure 0.8-2.0 µm long by 0.3-0.5 µm wide. Optimal growth was observed under ambient atmosphere. Reconstruction of phylogenies from the 16S rRNA gene and from single-copy orthologs verify placement of these strains within Orbaceae. Cells exhibited similar fatty acid profiles to those of other Orbaceae. Strain lpD01T shared 74% average nucleotide identity (ANI) with its closest relatives Ca. Schmidhempelia bombi Bimp and Zophobihabitans entericus IPMB12T. Results from multiple genome-wide similarity comparisons indicate lpD01T should be classified as a novel species within a novel genus. The major respiratory quinone for lpD01T is ubiquinone Q-8. lpD02T, lpD03, lpD04T, and BiBT are more closely related to Orbus hercynius CN3T (76, 77, 76, and 77% ANI, respectively) than to other described Orbaceae. Genomic and phylogenetic analyses suggest that lpD03 and lpD04T belong to the same species and that lpD02T, lpD03/lpD04T, and BiBT are each novel species of the genus Orbus. The proposed names of these strains are Utexia brackfieldae gen. nov., sp. nov. (type strain lpD01T =NCIMB 15517T =ATCC TSD-399T), Orbus sturtevantii sp. nov (type strain lpD02T =NCIMB 15518T =ATCC TSD-400T), Orbus wheelerorum sp. nov. (type strain lpD04T =NCIMB 15520T =ATCC TSD-401T), and Orbus mooreae sp. nov (type strain BiBT=NCIMB 15516T =ATCC TSD-402T). The isolation and characterization of these strains expands the repertoire of culturable bacteria naturally associated with insects, including the model organism D. melanogaster.

Effectiveness of Audio-Tactile Performance Versus Other Oral Health Education Methods in Improving Oral Health in Visually Impaired Children and Adolescents: A Systematic Review.

The aim of this study was to compare the effectiveness of audio-tactile performance (ATP) versus other oral health education methods in improving the oral health status of visually challenged children and adolescents. The review was carried out based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search was performed on the effectiveness of ATP in improving the oral health of visually impaired children. The search was conducted in Scopus, Google Scholar, PubMed, Embase, Lilacs, Web of Science, and Cochrane until December 2022. The risk-of-bias tool for randomized trials (RoB-2) was used to analyze the risk of bias. Meta-analysis was carried out for included studies that made similar comparisons and reported the same outcome measures. The initial search retrieved 368 records, of which nine studies were included for qualitative synthesis. Out of the nine included studies, five studies were included for quantitative synthesis. Two studies evaluating plaque index at 180 days (MD = -0.10; p = 0.0009; CI = -0.17 to -0.02) and five studies evaluating gingival index at 90 days (MD = -0.15; p < 0.00001; CI= -0.21 to -0.09) exhibited a significant mean difference favoring ATP. Three studies that evaluated gingival index at 30 days and 180 days showed significant mean differences (MD = -0.27; p < 0.000; CI = -0.40 to -0.15 and MD = -0.09; p = 0.01; CI= -0.15 to -0.02) favoring ATP. The ATP technique produced significant improvements in oral health when compared with other conventional techniques. However, the studies had high heterogeneity, and hence, the result must be inferred with caution.

FSDedup: Feature-Aware and Selective Deduplication for Improving Performance of Encrypted Non-Volatile Main Memory

Enhancing the endurance, performance, and energy efficiency of encrypted Non-Volatile Main Memory (NVMM) can be achieved by minimizing written data through inline deduplication. However, existing approaches applying inline deduplication to encrypted NVMM suffer from substantial performance degradation due to high computing, memory footprint, and index-lookup overhead to generate, store, and query the cryptographic hash (fingerprint). In the preliminary ESD [ 14 ], we proposed the Error Correcting Code (ECC) assisted selective deduplication scheme, utilizing the ECC information as a fingerprint to identify similar data effectively and then leveraging the selective deduplication technique to eliminate a large amount of redundant data with high reference counts. In this article, we proposed FSDedup. Compared with ESD, FSDedup could leverage the prefetch cache to reduce the read overhead during similarity comparison and utilize the cache refresh mechanism to identify further and eliminate more redundant data. Extensive experimental evaluations demonstrate that FSDedup can enhance the performance of the NVMM system further than the ESD. Experimental results show that FSDedup can improve both write and read speed by up to 1.8×, enhance Instructions Per Cycle by up to 1.5×, and reduce energy consumption by up to 2.0×, compared to ESD.

Functional genomics and taxonomic insights into heavymetaltolerant novel bacterium Brevibacterium metallidurans sp. nov. NCCP-602T isolated from tannery effluent in Pakistan.

The strain designated NCCP-602T was isolated from tannery effluent, and displayed aerobic, gram-positive, rod-shaped cells that were characterized by oxidase negative, catalase positive, and non-motile features. The most favourable growth conditions were observed at a temperature of 30°C, pH 7.0, and NaCl concentration of 1% (w/v). It tolerated heavy metals at high concentrations of chromium (3600 ppm), copper (3300 ppm), cadmium (3000 ppm), arsenic (1200 ppm) and lead (1500 ppm). The results of phylogenetic analysis, derived from sequences of the 16S rRNA gene, indicated the position of strain NCCP-602T within genus Brevibacterium and showed that it was closely related to Brevibacterium ammoniilyticum JCM 17537T. Strain NCCP-602T formed a robust branch that was clearly separate from closely related taxa. A comparison of 16S rRNA gene sequence similarity and dDDH values between the closely related type strains and strain NCCP-602T provided additional evidence supporting the classification of strain NCCP-602T as a distinct novel genospecies. The polar lipid profile included diphosphatidylglycerol, glycolipid, phospholipids and amino lipids. MK-7 and MK-8 were found as the respiratory quinones, while anteiso-C15:0, iso-C15:0, iso-C16:0, iso-C17:0, and anteiso-C17:0 were identified as the predominant cellular fatty acids (> 10%). Considering the convergence of phylogenetic, phenotypic, chemotaxonomic, and genotypic traits, it is suggested that strain NCCP-602T be classified as a distinct species Brevibacterium metallidurans sp. nov. within genus Brevibacterium with type strain NCCP-602T (JCM 18882T = CGMCC1.62055T).

Dual-task performance and brain morphologic characteristics in Parkinson's disease.

Introduction Parkinson's disease (PD) reduces an individual's capacity for automaticity which limits their ability to perform two tasks simultaneously, negatively impacting daily function. Understanding the neural correlates of dual-tasks (DT) may pave the way for targeted therapies. To better understand automaticity in PD, we aimed to explore whether individuals with differing DT performances possessed differences in brain morphologic characteristics. Methods Data were obtained from 34 individuals with PD and 47 healthy older adults including: 1) demographics (age, sex), 2) disease severity (Movement Disorder Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Hoehn &amp; Yahr, levodopa equivalent daily dose (LEDD)), 3) cognition (Montreal Cognitive Assessment), 4) Levodopa Equivalent Daily Dose, 5) single task- and DT- performance during a DT-Timed-Up-and-Go test utilizing a serial-subtraction task, and 6) Cortical thicknesses and subcortical volumes obtained from volumetric MRI. Participants were categorized as low or high DT performers if their combined DT-effect was greater than the previously determined mean value for healthy older adults (μ=74.2). Nonparametric testing using Quade's ANCOVA was conducted to compare cortical thicknesses and brain volumes between the highDT and lowDT groups while controlling for covariates: age, sex, MDS-UPDRS part III, LEDD, and intracranial volume. Secondarily, similar comparisons were made between the healthy older adult group the highDT and lowDT groups. Lastly, a hierarchical linear regression model was conducted regressing combined DT-effect on covariates (block one) and cortical thicknesses (block 2) in stepwise fashion. Results The highDT group had thicker cortices than the lowDT group in the right primary somatosensory (p=0.001), bilateral primary motor (p=&lt;0.001, left; p=0.002, right), bilateral supplementary motor area (p=0.001, left; p&lt;0.001, right), and mean of the bilateral hemispheres (p=0.001, left; p&lt;0.001, right). Of note, left primary cortex thickness (p=0.002), left prefrontal cortex thickness (p&lt;0.001), and right supplementary motor area thickness (p=0.003) differed when adding a healthy comparison group. Additionally, the regression analysis found that the left paracentral lobule thickness explained 20.8% of the variability in combined DT-effect (p=0.011) beyond the influence of covariates. Conclusions These results suggest regions underlying dual-task performance; specifically, a convergence of neural control relying sensorimotor integration, motor planning, and motor activation to achieve higher levels of DT performance for individuals with PD.

Dynamic Comparison of Binding Pocket of Berberine Protein Crystals

Introduction: Berberine is an important isoquinoline alkaloid that has various pharmacological properties. The comparison of the binding pocket similarity of berberine is regarded as the starting point for deciphering various activities. Eight berberine protein crystals were clustered and studied by molecular dynamics (MD) simulations to investigate common features of berberine binding pockets. Method: Root Mean Square Deviation (RMSD) results showed that berberine was able to bind to each protein in a stable manner. Residue analysis showed that the stability of residue composition of different protein pockets varied. This is also consistent with the results of the pocket similarity analysis: PS-score curves of most proteins fluctuated to varying degrees. The binding pocket of 3BTI in homogeneous protein analysis exhibited high stability (PS-scoremean = 0.703 and PS-scoremin = 0.5664). Pocket similarity analysis between two heterologous proteins showed that most of PS-score values were in the interval of 0.3-0.35, and PS-score values of 3D6Y were relatively high when compared with the other three proteins. Results: Pocket residue matching analysis showed that GLU145/VAL147/ILE182/TYR229/GLU253 in 3D6Y can be matched structurally to the corresponding residues in 1JUM, 2QVD, and 5Y0V, respectively, which can be considered as an important pocket feature for the berberine binding. Nevertheless, the obtained matched residues are limited to the category of pocket structural similarity. Conclusion: This was the first study in which dynamic comparison of berberine binding pockets were used to discover pocket patterns. These results were of great significance for the polypharmacological study, the identification of potential off-targets, and the repurposing of berberine. conclusion: This was the first study in which dynamic comparisons of berberine binding pockets were used to discover interaction patterns. These results were of great significance for the polypharmacological study, the identification of potential off-targets, and the repurposing of berberine.

Adsorption of terbium (III) on DGA and LN resins: Thermodynamics, isotherms, and kinetics

Two commercially available extraction chromatography (EXC) resins containing N,N,N’,N’-tetra-n-octyldiglycolamide (DGA Resin, Normal, 50 – 100 μm) and Bis(2-ethylhexyl) phosphate (LN Resin, 100 – 150 μm) were used as adsorbents to study fundamental adsorption properties such as thermodynamic values, equilibrium isotherms, and kinetic uptake models for terbium(III) adsorption. Weight distribution ratios (Dw) for terbium on DGA and LN resins were measured using a [160Tb]Tb3+radiometric tracer in nitric acid as a function of acidity, temperature, initial analyte concentration, and equilibrium time. The Dw values showed increasing binding affinity for DGA resin at high nitric acid concentrations and decreasing binding affinity for LN resins. Thermodynamic studies for DGA and LN resins revealed that the Gibbs free energy (ΔG) increased consistently with temperature. To model equilibrium data, increasingly higher parameter equilibrium isotherm models (Henry (1) < Langmuir, Freundlich (2) < Redlich-Peterson (3) < Fritz-Schluender (4)) were compared on their root mean squared errors (RMSE) and adjusted determination coefficients to determine the most applicable model. In all cases, the empirical four-parameter Fritz-Schluender isotherm demonstrated a superior fit. Similar comparisons for reaction-based kinetic models (Pseudo-first-order < Pseudo-second-order < Pseudo-n-order) revealed that the higher-order PNO model yielded a superior fit of kinetic data for both resins. However, in some cases, adsorption isotherms and kinetic models could also be modeled by a lower-order model with minimal change in error parameters. Weber-Morris plots revealed that two linear sections are observed for each resin, where the first linear segment is attributed to fast (film diffusion) adsorption of terbium, followed by slower intraparticle diffusion of terbium through the pores as the rate-limiting step. Based on the Weber-Morris plot, both film and intraparticle diffusion are involved in controlling the kinetic rate of adsorption for DGA and LN resins.