The Complete Mitochondrial Genome of the (Cypriniformes: Cyprinidae): Characterization, Phylogeny, and Genetic Diversity Analysis.

: is a species belonging to the Cyprinidae family. The objective of this study is to gain a comprehensive understanding of its evolutionary history and genetic characteristics. : The complete mitochondrial genome of .

Transcriptome Analysis Reveals Sertoli Cells Adapting Through Redox and Metabolic Pathways Under Heat Stress in Goats.

Background/objectives: Climate change-induced temperature elevations pose significant challenges to livestock reproduction, particularly affecting testicular function in small ruminants. This study investigates the acute heat-stress response in goat Sertoli cells (SCs), aiming to elucidate the molecular mechanisms underlying heat-induced damage to male reproductive tissues.

Methods: SCs were isolated from testes of 4-month-old black goats and exposed to heat stress (44 °C for 2.

Characterization of the Mitochondrial Genome of (Astacidea: Cambaridae) and Its Phylogenetic Implications.

Background: is an endangered freshwater crayfish in China, belonging to the genus Cambaroides, that can act as a complementary host for paragonimus. The objective of this study was to examine the complete mitochondrial genome characteristics and their evolutionary relationships within the Astacidea.

Methods: The analysis of gene rearrangements and evolutionary relationships was conducted through the sequencing of the mitochondrial genome of .

The Gene in Silkworm Black Pupae Significantly Affects 30 K Proteins During the Pupal Stage.

: The body color and patterns of insects play important roles in foraging, evading predators, mating, thermoregulation, and environmental adaptation. During the rearing of the QiufengN silkworm strain, a mutant with black pupal cuticle (QiufengNBP) was discovered. Preliminary map-based cloning and sequence analysis indicated that the gene might significantly influence the formation of the black pupa mutant and the expression of 30K proteins.

Identification of Candidate Genes for Sebum Deposition in Pekin Ducks Using Genome-Wide Association Studies.

Background: Sebum deposition is a vital trait influencing meat quality and production efficiency in Pekin ducks. Providing insights into the genetic basis of fat deposition could help improve breeding strategies aimed at producing high-quality meat ducks. This study aimed to identify the genetic mechanisms and lipid metabolism pathways regulating subcutaneous and intramuscular fat deposition in two Pekin duck strains: Nankou No.

Quantitative Trait Loci Mappings for the Sulfur Utilization Efficiency-Related Traits at the Seedling Stage of Wheat.

Background: Sulfur (S) is a vital element for the normal growth and development of plants, performing crucial biological functions in various life processes.

Methods: This study investigated thirteen S utilization efficiency (SUE)-related traits at the seedling stage of wheat using a recombinant inbred line (RIL) population. The quantitative trait loci (QTLs) were mapped by genetic mapping.

Potential Utility of SFB-1 as a Biocontrol Agent for Sweetpotato Black Rot Caused by .

: Sweetpotato black rot, caused by , is a severe fungal disease in sweetpotato production. Biological control strategies represent a promising, environmentally sustainable approach to managing this disease. This study investigates the biocontrol potential of SFB-1 against .

Forensic STR Loci and Schizophrenia: An Exploration of Implications for Forensic Applications and Genetic Privacy.

Background/objectives: Short tandem repeat (STR) loci are widely used in forensic genetics for identification and kinship analysis. Traditionally, these loci were selected to avoid medical associations, but recent studies suggest that loci such as TH01 and D16S539 may be linked to psychiatric conditions like schizophrenia. This study explores these potential associations and considers the privacy implications related to disease susceptibility.

Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

There exist significant challenges for lung adenocarcinoma (LUAD) due to its poor prognosis and limited treatment options, particularly in the advanced stages. It is crucial to identify genetic biomarkers for improving outcome predictions and guiding personalized therapies. In this study, we utilize a multi-step approach that combines principled sure independence screening, penalized regression methods and information gain to identify the key genetic features of the ultra-high dimensional RNA-sequencing data from LUAD patients.

Unraveling the Anthocyanin Regulatory Mechanisms of White Mutation in by Integrative Transcriptome and Metabolome Analysis.

: is a perennial herb of the Verbenaceae family, known for its medicinal properties, wide adaptability, and high resistance. : This research investigated the metabolic pathways of flower color change by combining transcriptome and metabolomics analyses. : In purple flowers and white variants, a total of 118 differentially accumulated metabolites (DAMs), including 20 anthocyanins, and 7627 differentially expressed genes (DEGs) were found.

Genome Insights and Identification of Sex Determination Region and Sex Markers in .

Background: , a member of the Sciaenidae family, is widely distributed across the sea areas near China, Japan, Australia, and South Africa. The aim of this study is to provide a high-quality genome with new technology and to understand the sex determination mechanism of this species.

Methods: We generated a high-quality chromosome-level genome for using PacBio HiFi and Hi-C sequencing technologies.

Network Coding-Enhanced Polar Codes for Relay-Assisted Visible Light Communication Systems.

This paper proposes a novel polar coding scheme tailored for indoor visible light communication (VLC) systems. Simulation results demonstrate a significant reduction in bit error rate (BER) compared to uncoded transmission, with a coding gain of at least 5 dB. Furthermore, the reliable communication area of the VLC system is substantially extended.

Enhanced Control of Nonlinear Systems Under Control Input Constraints and Faults: A Neural Network-Based Integral Fuzzy Sliding Mode Approach.

Many existing control techniques proposed in the literature tend to overlook faults and physical limitations in the systems, which significantly restricts their applicability to practical, real-world systems. Consequently, there is an urgent necessity to advance the control and synchronization of such systems in real-world scenarios, specifically when faced with the challenges posed by faults and physical limitations in their control actuators. Motivated by this, our study unveils an innovative control approach that combines a neural network-based sliding mode algorithm with fuzzy logic systems to handle nonlinear systems.

Robust Model-Free Identification of the Causal Networks Underlying Complex Nonlinear Systems.

Inferring causal networks from noisy observations is of vital importance in various fields. Due to the complexity of system modeling, the way in which universal and feasible inference algorithms are studied is a key challenge for network reconstruction. In this study, without any assumptions, we develop a novel model-free framework to uncover only the direct relationships in networked systems from observations of their nonlinear dynamics.

Quantum Computing in Community Detection for Anti-Fraud Applications.

Fraud detection within transaction data is crucial for maintaining financial security, especially in the era of big data. This paper introduces a novel fraud detection method that utilizes quantum computing to implement community detection in transaction networks. We model transaction data as an undirected graph, where nodes represent accounts and edges indicate transactions between them.

Identification and Bioactivity Analysis of a Novel Species, sp. nov. Bos-x6-28, Isolated from Feces of the Yak ().

The identification of novel bacterial species from the intestines of yaks residing on the Qinghai-Tibet Plateau is pivotal in advancing our understanding of host-microbiome interactions and represents a promising avenue for microbial drug discovery. In this study, we conducted a polyphasic taxonomic analysis and bioactive assays on a strain, designated Bos-x6-28, isolated from yak feces. The findings revealed that strain Bos-x6-28 shares a high 16S rRNA gene sequence similarity (98.

Classical and Modern Models for Biofilm Studies: A Comprehensive Review.

Biofilms are structured microbial communities that adhere to various abiotic and biotic surfaces, where organisms are encased in an exo-polysaccharide matrix. Organisms within biofilms use various mechanisms that help them resist external challenges, such as antibiotics, rendering them more resistant to drugs. Therefore, researchers have attempted to develop suitable laboratory models to study the physical features of biofilms, their resistance mechanisms against antimicrobial agents, and their gene and protein expression profiles.

Fusion Partner Facilitates Expression of Cell-Penetrating Peptide L2 in .

Background: L2 is formed by combining the pheromone of () and a cell-penetrating peptide (CPP) with cell-penetrating selectivity. L2 has more significant penetration and better specificity for killing . However, the production of AMPs by chemical synthesis is always a challenge because of the production cost.

Emotion Recognition Model of EEG Signals Based on Double Attention Mechanism.

Background: Emotions play a crucial role in people's lives, profoundly affecting their cognition, decision-making, and interpersonal communication. Emotion recognition based on brain signals has become a significant challenge in the fields of affective computing and human-computer interaction.

Methods: Addressing the issue of inaccurate feature extraction and low accuracy of existing deep learning models in emotion recognition, this paper proposes a multi-channel automatic classification model for emotion EEG signals named DACB, which is based on dual attention mechanisms, convolutional neural networks, and bidirectional long short-term memory networks.

Peer Status Influences In-Group Favoritism in Pain Empathy During Middle Childhood: Evidence from Behavioral and Event-Related Potentials Studies.

Background/objectives: Empathy for pain enhances our ability to perceive pain and recognize potential dangers. Empathic bias occurs when members of the in-group evoke more intense empathic responses compared to out-group members. In the process of interacting with peers, children develop peer status and spontaneously form peer groups.

The Impact of Selective Spatial Attention on Auditory-Tactile Integration: An Event-Related Potential Study.

Background: Auditory-tactile integration is an important research area in multisensory integration. Especially in special environments (e.g.

Within- and Between-Person Correlates of Affect and Sleep Health Among Health Science Students.

Background/objectives: To examine the relationships between state affect and sleep health at within- and between-person levels among health science students.

Methods: A correlational design was used and 54 health science students were included. The participants completed baseline and 7-day ambulatory assessments in a free-living setting.

Effects of Route Complexity and Lighting on Route Following in Alzheimer's Disease and Posterior Cortical Atrophy.

Objective: Visual processing deficits arising in dementia are associated with particular functional disability. This study aimed to investigate the effects of the built environment on mobility and navigation in people with dementia-related visual loss.

Methods: Participants with posterior cortical atrophy (PCA; "visual-variant Alzheimer's"; n = 11), typical Alzheimer's disease (tAD; N = 10), and controls (n = 13) repeatedly walked down routes within a simplified real-world setting.

Contributions of the Primary Sensorimotor Cortex and Posterior Parietal Cortex to Motor Learning and Transfer.

Background: Transferring learned manipulations to new manipulation tasks has enabled humans to realize thousands of dexterous object manipulations in daily life. Two-digit grasp and three-digit grasp manipulations require different fingertip forces, and our brain can switch grasp types to ensure good performance according to motor memory. We hypothesized that several brain areas contribute to the execution of the new type of motor according to the motor memory.

Non-Invasive Monitoring of Cerebral Edema Using Ultrasonic Echo Signal Features and Machine Learning.

Objectives: Cerebral edema, a prevalent consequence of brain injury, is associated with significant mortality and disability. Timely diagnosis and monitoring are crucial for patient prognosis. There is a pressing clinical demand for a real-time, non-invasive cerebral edema monitoring method.