Machine Learning Early Detection of SARS-CoV-2 High-Risk Variants.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved many high-risk variants, resulting in repeated COVID-19 waves over the past years. Therefore, accurate early warning of high-risk variants is vital for epidemic prevention and control. However, detecting high-risk variants through experimental and epidemiological research is time-consuming and often lags behind the emergence and spread of these variants. In this study, HiRisk-Detector a machine learning algorithm based on haplotype network, is developed for computationally early detecting high-risk SARS-CoV-2 variants. Leveraging over 7.6 million high-quality and complete SARS-CoV-2 genomes and metadata, the effectiveness, robustness, and generalizability of HiRisk-Detector are validated. First, HiRisk-Detector is evaluated on actual empirical data, successfully detecting all 13 high-risk variants, preceding World Health Organization announcements by 27 days on average. Second, its robustness is tested by reducing sequencing intensity to one-fourth, noting only a minimal delay of 3.8 days, demonstrating its effectiveness. Third, HiRisk-Detector is applied to detect risks among SARS-CoV-2 Omicron variant sub-lineages, confirming its broad applicability and high ROC-AUC and PR-AUC performance. Overall, HiRisk-Detector features powerful capacity for early detection of high-risk variants, bearing great utility for any public emergency caused by infectious diseases or viruses.

Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer.

BACKGROUND: Preoperative risk stratification is significant for the management of endometrial cancer (EC) patients. Radiomics based on magnetic resonance imaging (MRI) in combination with clinical features may be useful to predict the risk grade of EC. AIM: To construct machine learning models to predict preoperative risk stratification of patients with EC based on radiomics features extracted from MRI. METHODS: The study comprised 112 EC patients. The participants were randomly separated into training and validation groups with a 7:3 ratio. Logistic regression analysis was applied to uncover independent clinical predictors. These predictors were then used to create a clinical nomogram. Extracted radiomics features from the T2-weighted imaging and diffusion weighted imaging sequences of MRI images, the Mann-Whitney U test, Pearson test, and least absolute shrinkage and selection operator analysis were employed to evaluate the relevant radiomic features, which were subsequently utilized to generate a radiomic signature. Seven machine learning strategies were used to construct radiomic models that relied on the screening features. The logistic regression method was used to construct a composite nomogram that incorporated both the radiomic signature and clinical independent risk indicators. RESULTS: Having an accuracy of 0.82 along with an area under the curve (AUC) of 0.915 [95% confidence interval (CI): 0.806-0.986], the random forest method trained on radiomics characteristics performed better than expected. The predictive accuracy of radiomics prediction models surpassed that of both the clinical nomogram (AUC: 0.75, 95%CI: 0.611-0.899) and the combined nomogram (AUC: 0.869, 95%CI: 0.702-0.986) that integrated clinical parameters and radiomic signature. CONCLUSION: The MRI-based radiomics model may be an effective tool for preoperative risk grade prediction in EC patients.

Deep Attention Fusion Hashing (DAFH) Model for Medical Image Retrieval.

In medical image retrieval, accurately retrieving relevant images significantly impacts clinical decision making and diagnostics. Traditional image-retrieval systems primarily rely on single-dimensional image data, while current deep-hashing methods are capable of learning complex feature representations. However, retrieval accuracy and efficiency are hindered by diverse modalities and limited sample sizes. OBJECTIVE: To address this, we propose a novel deep learning-based hashing model, the Deep Attention Fusion Hashing (DAFH) model, which integrates advanced attention mechanisms with medical imaging data. METHODS: The DAFH model enhances retrieval performance by integrating multi-modality medical imaging data and employing attention mechanisms to optimize the feature extraction process. Utilizing multimodal medical image data from the Cancer Imaging Archive (TCIA), this study constructed and trained a deep hashing network that achieves high-precision classification of various cancer types. RESULTS: At hash code lengths of 16, 32, and 48 bits, the model respectively attained Mean Average Precision (MAP@10) values of 0.711, 0.754, and 0.762, highlighting the potential and advantage of the DAFH model in medical image retrieval. CONCLUSIONS: The DAFH model demonstrates significant improvements in the efficiency and accuracy of medical image retrieval, proving to be a valuable tool in clinical settings.

Benzimidazole-based structure optimization to discover novel anti-gastric cancer agents targeting ROS/MAPK pathway.

Given the malignancy of gastric cancer, developing highly effective and low-toxic targeted drugs is essential to prolong patient survival and improve patient outcomes. In this study, we conducted structural optimizations based on the benzimidazole scaffold. Notably, compound 8 f presented the most potent antiproliferative activity in MGC803 cells and induced cell cycle arrest at the G0/G1 phase. Further mechanistic studies demonstrated that compound 8 f caused the apoptosis of MGC803 cells by elevating intracellular reactive oxygen species (ROS) levels and activating the mitogen-activated protein kinase (MAPK) signaling pathway, accompanied by corresponding markers change. In vivo investigations additionally validated the inhibitory effect of compound 8 f on tumor growth in xenograft models bearing MGC803 cells without obvious toxicity. Our studies suggest that compound 8 f holds promise as a potential and safe lead compound for developing anti-gastric cancer agents.

GenBase: A Nucleotide Sequence Database.

The rapid advancement of sequencing technologies poses challenges in managing the large volume and exponential growth of sequence data efficiently and on time. To address this issue, we present GenBase (https://ngdc.cncb.ac.cn/genbase), an open-access data repository that follows the International Nucleotide Sequence Database Collaboration (INSDC) data standards and structures, for efficient nucleotide sequence archiving, searching, and sharing. As a core resource within the National Genomics Data Center (NGDC) of the China National Center for Bioinformation (CNCB; https://ngdc.cncb.ac.cn), GenBase offers bilingual submission pipeline and services, as well as local submission assistance in China. GenBase also provides a unique Excel format for metadata description and feature annotation of nucleotide sequences, along with a real-time data validation system to streamline sequence submissions. As of April 23, 2024, GenBase received 68,251 nucleotide sequences and 689,574 annotated protein sequences across 414 species from 2319 submissions. Out of these, 63,614 (93%) nucleotide sequences and 620,640 (90%) annotated protein sequences have been released and are publicly accessible through GenBase's web search system, File Transfer Protocol (FTP), and Application Programming Interface (API). Additionally, in collaboration with INSDC, GenBase has constructed an effective data exchange mechanism with GenBank and started sharing released nucleotide sequences. Furthermore, GenBase integrates all sequences from GenBank with daily updates, demonstrating its commitment to actively contributing to global sequence data management and sharing.

IFI207, a young and fast-evolving protein, controls retroviral replication via the STING pathway.

Mammalian AIM-2-like receptor (ALR) proteins bind nucleic acids and initiate production of type I interferons or inflammasome assembly, thereby contributing to host innate immunity. In mice, the Alr locus is highly polymorphic at the sequence and copy number level, and we show here that it is one of the most dynamic regions of the genome. One rapidly evolving gene within this region, Ifi207, was introduced to the Mus genome by gene conversion or an unequal recombination event a few million years ago. Ifi207 has a large, distinctive repeat region that differs in sequence and length among Mus species and even closely related inbred Mus musculus strains. We show that IFI207 controls murine leukemia virus (MLV) infection in vivo and that it plays a role in the STING-mediated response to cGAMP, dsDNA, DMXXA, and MLV. IFI207 binds to STING, and inclusion of its repeat region appears to stabilize STING protein. The Alr locus and Ifi207 provide a clear example of the evolutionary innovation of gene function, possibly as a result of host-pathogen co-evolution.IMPORTANCEThe Red Queen hypothesis predicts that the arms race between pathogens and the host may accelerate evolution of both sides, and therefore causes higher diversity in virulence factors and immune-related proteins, respectively . The Alr gene family in mice has undergone rapid evolution in the last few million years and includes the creation of two novel members, MndaL and Ifi207. Ifi207, in particular, became highly divergent, with significant genetic changes between highly related inbred mice. IFI207 protein acts in the STING pathway and contributes to anti-retroviral resistance via a novel mechanism. The data show that under the pressure of host-pathogen coevolution in a dynamic locus, gene conversion and recombination between gene family members creates new genes with novel and essential functions that play diverse roles in biological processes.

Comparative genomic sequencing to characterize Mycoplasma pneumoniae genome, typing, and drug resistance.

To analyze the characteristics of Mycoplasma pneumoniae as well as macrolide antibiotic resistance through whole-genome sequencing and comparative genomics. Thirteen clinical strains isolated from 2003 to 2019 were selected, 10 of which were resistant to erythromycin (MIC >64 µg/mL), including 8 P1-type I and 2 P1-type II. Three were sensitive (<1 µg/mL) and P1-type II. One resistant strain had an A→G point mutation at position 2064 in region V of the 23S rRNA, the others had it at position 2063, while the three sensitive strains had no mutation here. Genome assembly and comparative genome analysis revealed a high level of genome consistency within the P1 type, and the primary differences in genome sequences concentrated in the region encoding the P1 protein. In P1-type II strains, three specific gene mutations were identified: C162A and A430G in L4 gene and T1112G mutation in the CARDS gene. Clinical information showed seven cases were diagnosed with severe pneumonia, all of which were infected with drug-resistant strains. Notably, BS610A4 and CYM219A1 exhibited a gene multi-copy phenomenon and shared a conserved functional domain with the DUF31 protein family. Clinically, the patients had severe refractory pneumonia, with pleural effusion, necessitating treatment with glucocorticoids and bronchoalveolar lavage. The primary variations between strains occur among different P1-types, while there is a high level of genomic consistency within P1-types. Three mutation loci associated with specific types were identified, and no specific genetic alterations directly related to clinical presentation were observed.IMPORTANCEMycoplasma pneumoniae is an important pathogen of community-acquired pneumonia, and macrolide resistance brings difficulties to clinical treatment. We analyzed the characteristics of M. pneumoniae as well as macrolide antibiotic resistance through whole-genome sequencing and comparative genomics. The work addressed primary variations between strains that occur among different P1-types, while there is a high level of genomic consistency within P1-types. In P1-type II strains, three specific gene mutations were identified: C162A and A430G in L4 gene and T1112G mutation in the CARDS gene. All the strains isolated from severe pneumonia cases were drug-resistant, two of which exhibited a gene multi-copy phenomenon, sharing a conserved functional domain with the DUF31 protein family. Three mutation loci associated with specific types were identified, and no specific genetic alterations directly related to clinical presentation were observed.

Analysis of Genetic Diversity and Population Structure of Endemic Endangered Goose (Anser cygnoides) Breeds Based on Mitochondrial CYTB.

The analysis of the genetic diversity and historical dynamics of endemic endangered goose breeds structure has attracted great interest. Although various aspects of the goose breed structure have been elucidated, there is still insufficient research on the genetic basis of endemic endangered Chinese goose breeds. In this study, we collected blood samples from Lingxiang White (LX), Yan (YE), Yangjiang (YJ), Wuzong (WZ), Xupu (XP), and Baizi (BZ) geese (Anser cygnoides) and used Sanger sequencing to determine the partial sequence of the cytochrome b (CYTB) gene in a total of 180 geese. A total of 117 polymorphic sites were detected in the 707 bp sequence of the mtDNA CYTB gene after shearing and correction, accounting for approximately 16.55% of the entire sequence. The AT content (51.03%) of the processed sequence was slightly higher than the GC content (48.97%), indicating a preference for purine bases. The YJ, YE, and WZ breeds had the highest population genetic diversity, with a haplotype diversity greater than 0.9 (Hd > 0.9) and average population nucleotide difference of 8.01 (K > 8.01). A total of 81 haplotypes were detected and divided into six major branches. Among the six goose breeds, there were frequent genetic exchanges among LX, YJ, YE, and WZ geese (Nm > 15.00). We analyzed the distribution of base-mismatch differences in goose breeds and tested their historical dynamics for neutrality in Tajima's D and Fu's Fs. For YJ and WZ geese, Tajima's D > 0, but the difference was not significant (p > 0.05). The actual values for the two breeds exhibited multimodal Poisson distributions. The population patterns of the WZ and YJ geese are purportedly relatively stable, and the breeds have not experienced population expansions or bottleneck effects, which is consistent with the neutrality test results. This study provides new insights into the diverse genetic origins and historical dynamics that sustain endemic endangered goose breeds.

Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications.

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

The protective effect of vitamin D supplementation as adjunctive therapy to antidepressants on brain structural and functional connectivity of patients with major depressive disorder: a randomized controlled trial.

BACKGROUND: Growing evidence points to the pivotal role of vitamin D in the pathophysiology and treatment of major depressive disorder (MDD). However, there is a paucity of longitudinal research investigating the effects of vitamin D supplementation on the brain of MDD patients. METHODS: We conducted a double-blind randomized controlled trial in 46 MDD patients, who were randomly allocated into either VD (antidepressant medication + vitamin D supplementation) or NVD (antidepressant medication + placebos) groups. Data from diffusion tensor imaging, resting-state functional MRI, serum vitamin D concentration, and clinical symptoms were obtained at baseline and after an average of 7 months of intervention. RESULTS: Both VD and NVD groups showed significant improvement in depression and anxiety symptoms but with no significant differences between the two groups. However, a greater increase in serum vitamin D concentration was found to be associated with greater improvement in depression and anxiety symptoms in VD group. More importantly, neuroimaging data demonstrated disrupted white matter integrity of right inferior fronto-occipital fasciculus along with decreased functional connectivity between right frontoparietal and medial visual networks after intervention in NVD group, but no changes in VD group. CONCLUSIONS: These findings suggest that vitamin D supplementation as adjunctive therapy to antidepressants may not only contribute to improvement in clinical symptoms but also help preserve brain structural and functional connectivity in MDD patients.

The Hippocampal Subfield Volume Reduction and Plasma Biomarker Changes in Mild Cognitive Impairment and Alzheimer's Disease.

Background: The hippocampus consists of histologically and functionally distinct subfields, which shows differential vulnerabilities to Alzheimer's disease (AD)-associated pathological changes. Objective: To investigate the atrophy patterns of the main hippocampal subfields in patients with mild cognitive impairment (MCI) and AD and the relationships among the hippocampal subfield volumes, plasma biomarkers and cognitive performance. Methods: This cross-sectional study included 119 patients stratified into three categories: normal cognition (CN; N = 40), MCI (N = 39), and AD (N = 40). AD-related plasma biomarkers were measured, including amyloid-ß (Aß)42, Aß40, Aß42/Aß40 ratio, p-tau181, and p-tau217, and the hippocampal subfield volumes were calculated using automated segmentation and volumetric procedures implemented in FreeSurfer. Results: The subiculum body, cornu ammonis (CA) 1-head, CA1-body, CA4-body, molecular_layer_HP-head, molecular_layer_HP-body, and GC-ML-DG-body volumes were smaller in the MCI group than in the CN group. The subiculum body and CA1-body volumes accurately distinguished MCI from CN (area under the curve [AUC] = 0.647-0.657). The subiculum-body, GC-ML-DG-body, CA4-body, and molecular_layer_HP-body volumes accurately distinguished AD from MCI (AUC = 0.822-0.833) and AD from CN (AUC = 0.903-0.905). The p-tau 217 level served as the best plasma indicator of AD and correlated with broader hippocampal subfield volumes. Moreover, mediation analysis demonstrated that the subiculum-body volume mediated the associations between the p-tau217 and p-tau181 levels, and the Montreal Cognitive Assessment and Auditory Verbal Learning Test recognition scores. Conclusions: Hippocampal subfields with distinctive atrophy patterns may mediate the effects of tau pathology on cognitive function. The subiculum-body may be the most clinically meaningful hippocampal subfield, which could be an effective target region for assessing disease progression.

Abnormal amplitude of low-frequency fluctuations associated with sleep efficiency in major depressive disorder.

BACKGROUND: Sleep disturbance is one of the most frequent somatic symptoms in major depressive disorder (MDD), but the neural mechanisms behind it are not well understood. Sleep efficiency (SE) is a good indicator of early awakening and difficulty falling asleep in MDD patients. Our study aimed to investigate the relationship between sleep efficiency and brain function in MDD patients. METHODS: We recruited 131 MDD patients from the Fourth People's Hospital in Hefei, and 71 well-matched healthy controls who were enrolled from the community. All subjects underwent resting-state functional MRI. Brain function was measured using the fractional amplitude of low-frequency fluctuation (fALFF), sleep efficiency was objectively measured by polysomnography (PSG), and clinical scales were used to evaluate depressive symptoms and sleep status. Multivariate regression analysis was performed to assess the relationship between the amplitude of the low frequency fluctuation fraction and sleep efficiency. RESULT: Three brain regions with relevance to sleep efficiency in MDD patients were found: inferior occipital gyrus (Number of voxels = 25, peak MNI coordinate x/y/z = -42/-81/-6, Peak intensity = 4.3148), middle occipital gyrus (Number of voxels = 55, peak MNI coordinate x/y/z = -30/-78/18, Peak intensity = 5.111), and postcentral gyrus (Number of voxels = 26, peak MNI coordinate x/y/z = -27/-33/60, Peak intensity = 4.1263). But there was no significant relationship between fALFF and SE in the healthy controls. CONCLUSION: The reduced sleep efficiency in MDD may be related to their lower neural activity in the inferior occipital gyrus, middle occipital gyrus, and postcentral gyrus. The findings may provide a potential neuroimaging basis for the clinical intervention in patients with major depressive disorder with sleep disturbances.

The development rule of feathers and application of hair root tissue in sex identification of Yangzhou geese.

Accurate gender identification is crucial for the study of bird reproduction and evolution. The current study aimed to explore and evaluate the effectiveness of a noninvasive method for gender identification in Yangzhou geese. In this experiment, 600 goose eggs were collected. Hair root tissues were used for PCR amplification, molecular sequencing, and anal inversion for early sex recognition in goslings. According to the DNA amplification results for the feather pulp tissue of 2-wk-old geese, bands appeared at 436 bp (CHD1-Z) and 330 bp (CHD1-W) upon gel electrophoresis. This method considered the base of goose feathers to accelerate the process of gender recognition. By examining the sex of anatomized poultry for verification, the accuracy rate of PCR gel electrophoresis and molecular sequencing sex identification was 100%, whereas the average accuracy rate of anal inversion was 97.41%. In the comparison of feather growth trends at 0 to 18 wk of age, the feather root weight (FRW), feather root length (FRL), feather branch length (FBL), and feather shaft diameter (FSD) of Yangzhou goose of the same age were not significantly different between males and females (P > 0.05). At 6 wk of age, the FRW, FRL, and FSD in males and FRL in females increased rapidly; their growth increased by 84.43, 67.58, 45.10, and 69.42%, respectively. At 10 wk of age, the male FRL, male FBL, and female FBL increased by 37.31, 34.81, and 21.72, respectively. The Boltzmann model was found to be the best-fitting model for the feathers of male Yangzhou geese. Early sex identification based on feather growth trends between the sexes is not feasible. This study provides a convenient and reliable technical means for early sex identification of waterfowl and serves as an ecological strategy for protecting the reproduction of poultry populations.

Murine leukemia virus infection of non-dividing dendritic cells is dependent on nucleoporins.

Retroviral reverse transcription starts within the capsid and uncoating and reverse transcription are mutually dependent. There is still debate regarding the timing and cellular location of HIV's uncoating and reverse transcription and whether it occurs solely in the cytoplasm, nucleus or both. HIV can infect non-dividing cells because there is active transport of the preintegration complex (PIC) across the nuclear membrane, but Murine Leukemia Virus (MLV) is thought to depend on cell division for replication and whether MLV uncoating and reverse transcription is solely cytoplasmic has not been studied. Here, we used NIH3T3 and primary mouse dendritic cells to determine where the different stages of reverse transcription occur and whether cell division is needed for nuclear entry. Our data strongly suggest that in both NIH3T3 cells and dendritic cells (DCs), the initial step of reverse transcription occurs in the cytoplasm. However, we detected MLV RNA/DNA hybrid intermediates in the nucleus of dividing NIH3T3 cells and non-dividing DCs, suggesting that reverse transcription can continue after nuclear entry. We also confirmed that the MLV PIC requires cell division to enter the nucleus of NIH3T3 cells. In contrast, we show that MLV can infect non-dividing primary DCs, although integration of MLV DNA in DCs still required the viral p12 protein. Knockdown of several nuclear pore proteins dramatically reduced the appearance of integrated MLV DNA in DCs but not NIH3T3 cells. Additionally, MLV capsid associated with the nuclear pore proteins NUP358 and NUP62 during infection. These findings suggest that simple retroviruses, like the complex retrovirus HIV, gain nuclear entry by traversing the nuclear pore complex in non-mitotic cells.

Floor eggs in goose breeders: patterns, genetic and environmental influences, and physiological indexes.

A floor egg is an egg that is not laid in the nest, which is a prevalent issue in many fowl breeder farms, lowering egg collection efficiency, hatching performance, and economic benefits. Although the pattern and influencing factors of floor laying have been extensively reported in chickens and ducks, it is not clear in geese. Herein, the Yangzhou goose breeders were selected, and the time and location preferences, genetic and environmental influences, and physiological indexes in floor laying were investigated. The results revealed distinct time and location preferences existed. More floor eggs were laid from 2:00 to 5:00 and 8:00 to 12:00 am, with a concentration observed in the feed trough. Moreover, the proportion of floor eggs was higher at the early stage than at other stages of the laying cycle, and the fast-growing line laid more floor eggs than dual-purpose and high-yielding lines (P < 0.05). In addition to genetic factors, the effect of environmental influences on floor eggs was also surveyed. More floor eggs were observed in the family housing system than in large-group and small-population housing systems, and geese who reared in north-facing houses laid more floor eggs than in south-facing houses (P < 0.05). Physiological indexes were compared between floor-laying and nest-laying geese. Significantly decreased serum progesterone and prolactin levels were detected, alongside down-regulated gene expressions of progesterone receptor in ovaries, oxytocin receptor in both pituitary and ovaries, corticotropin-releasing hormone in ovaries, and dopamine receptor D2 in hypothalamus and ovaries in floor-laying geese compared to nest-laying geese (P < 0.05). In addition, a practical and inexpensive approach of adding a single decoy egg to the nest box effectively reduced the proportion of floor eggs (P < 0.05). Taken together, these data provide scientific information for patterns, genetic and environmental influences, and physiological indexes of floor eggs, thereby contributing to effective control of floor laying in goose breeders' production.

Lipidomics reveals lipid changes in the intramuscular fat of geese at different growth stages.

The quality (color, tenderness, juiciness, protein content, and fat content) of poultry meat is closely linked to age, with older birds typically exhibiting increased intramuscular fat (IMF) deposition. However, specific lipid metabolic pathways involved in IMF deposition remain unknown. To elucidate the mechanisms underlying lipid changes, we conducted a study using meat geese at 2 distinct growth stages (70 and 300 d). Our findings regarding the approximate composition of the meat revealed that as the geese aged 300 d, their meat acquired a chewier texture and displayed higher levels of IMF. Liquid chromatography-mass spectrometry (LC-MS) was employed for lipid profiling of the IMF. Using a lipid database, we identified 849 lipids in the pectoralis muscle of geese. Principal component analysis and orthogonal partial least squares discriminant analysis were used to distinguish between the 2 age groups and identify differential lipid metabolites. As expected, we observed significant changes in 107 lipids, including triglycerides, diglycerides, phosphatidylethanolamine, alkyl-glycerophosphoethanolamine, alkenyl-glycerophosphoethanolamine, phosphatidylcholine, phosphatidylinositol, lysophosphatidylserine, ceramide-AP, ceramide-AS, free fatty acids, cholesterol lipids, and N-acyl-lysophosphatidylethanolamine. Among these, the glyceride molecules exhibited the most pronounced changes and played a pivotal role in IMF deposition. Additionally, increased concentration of phospholipid molecules was observed in breast muscle at 70 d. Unsaturated fatty acids attached to lipid side chain sites enrich the nutritional value of goose meat. Notably, C16:0 and C18:0 were particularly abundant in the 70-day-old goose meat. Pathway analysis demonstrated that glycerophospholipid and glyceride metabolism were the pathways most significantly associated with lipid changes during goose growth, underscoring their crucial role in lipid metabolism in goose meat. In conclusion, this work provides an up-to-date study on the lipid composition and metabolic pathways of goose meat and may provide a theoretical basis for elucidating the nutritional value of goose meat at different growth stages.

TCOD: an integrated resource for tropical crops.

Tropical crops are vital for tropical agriculture, with resource scarcity, functional diversity and extensive market demand, providing considerable economic benefits for the world's tropical agriculture-producing countries. The rapid development of sequencing technology has promoted a milestone in tropical crop research, resulting in the generation of massive amount of data, which urgently needs an effective platform for data integration and sharing. However, the existing databases cannot fully satisfy researchers' requirements due to the relatively limited integration level and untimely update. Here, we present the Tropical Crop Omics Database (TCOD, https://ngdc.cncb.ac.cn/tcod), a comprehensive multi-omics data platform for tropical crops. TCOD integrates diverse omics data from 15 species, encompassing 34 chromosome-level de novo assemblies, 1 255 004 genes with functional annotations, 282 436 992 unique variants from 2048 WGS samples, 88 transcriptomic profiles from 1997 RNA-Seq samples and 13 381 germplasm items. Additionally, TCOD not only employs genes as a bridge to interconnect multi-omics data, enabling cross-species comparisons based on homology relationships, but also offers user-friendly online tools for efficient data mining and visualization. In short, TCOD integrates multi-species, multi-omics data and online tools, which will facilitate the research on genomic selective breeding and trait biology of tropical crops.

BioKA: a curated and integrated biomarker knowledgebase for animals.

Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap in non-human animal disease understanding and breeding research. To address this limitation, we present BioKA (Biomarker Knowledgebase for Animals, https://ngdc.cncb.ac.cn/bioka), a curated and integrated knowledgebase encompassing multiple animal species, diseases/traits, and annotated resources. Currently, BioKA houses 16 296 biomarkers associated with 951 mapped diseases/traits across 31 species from 4747 references, including 11 925 gene/protein biomarkers, 1784 miRNA biomarkers, 1043 mutation biomarkers, 773 metabolic biomarkers, 357 circRNA biomarkers and 127 lncRNA biomarkers. Furthermore, BioKA integrates various annotations such as GOs, protein structures, protein-protein interaction networks, miRNA targets and so on, and constructs an interactive knowledge network of biomarkers including circRNA-miRNA-mRNA associations, lncRNA-miRNA associations and protein-protein associations, which is convenient for efficient data exploration. Moreover, BioKA provides detailed information on 308 breeds/strains of 13 species, and homologous annotations for 8784 biomarkers across 16 species, and offers three online application tools. The comprehensive knowledge provided by BioKA not only advances human disease research but also contributes to a deeper understanding of animal diseases and supports livestock breeding.

Dimensional subtyping of first-episode drug-naïve major depressive disorder: A multisite resting-state fMRI study.

Major depressive disorder (MDD) is a heterogeneous syndrome, and understanding its neural mechanisms is crucial for the advancement of personalized medicine. However, conventional subtyping studies often categorize MDD patients into a single subgroup, neglecting the continuous interindividual variations. This implies a pressing need for a dimensional approach. 230 first-episode drug-naïve MDD patients and 395 healthy controls were obtained from 5 sites via the Rest-meta-MDD project. A Bayesian model was used to decompose the resting-state functional connectivity (RSFC) into multiple distinct RSFC patterns (refer to as "factors"), and each individual was allowed to express multiple factors to varying degrees (dimensional subtyping). The associations between demographic and clinical variables with the identified factors were calculated. We identified three latent factors with distinct but partially overlapping hypo- and hyper-RSFC patterns. Most participants co-expressed multiple latent factors. All factors shared abnormal RSFC involving the default mode network and frontoparietal network, but the directionality partially differed across factors. All factors were not significantly associated with demographic and clinical variables. These findings shed light on the interindividual variability in MDD and could form the basis for developing novel therapeutic approaches that capitalize on the heterogeneity of MDD.

Temperature Elevation during Semen Delivery Deteriorates Boar Sperm Quality by Promoting Apoptosis.

Semen delivery practice is crucial to the efficiency of artificial insemination using high-quality boar sperm. The present study aimed to evaluate the effect of a common semen delivery method, a Styrofoam box, under elevated temperatures on boar sperm quality and functionality and to investigate the underlying molecular responses of sperm to the temperature rise. Three pooled semen samples from 10 Duroc boars (3 ejaculates per boar) were used in this study. Each pooled semen sample was divided into two aliquots. One aliquot was stored at a constant 17 °C as the control group. Another one was packaged in a well-sealed Styrofoam box and placed in an incubator at 37 °C for 24 h to simulate semen delivery on hot summer days and subsequently transferred to a refrigerator at 17 °C for 3 days. The semen temperature was continuously monitored. The semen temperature was 17 °C at 0 h of storage and reached 20 °C at 5 h, 30 °C at 14 h, and 37 °C at 24 h. For each time point, sperm quality and functionality, apoptotic changes, expression levels of phosphorylated AMPK, and heat shock proteins HSP70 and HSP90 were determined by CASA, flow cytometry, and Western blotting. The results showed that elevated temperature during delivery significantly deteriorated boar sperm quality and functionality after 14 h of delivery. Storage back to 17 °C did not recover sperm motility. An increased temperature during delivery apparently promoted the conversion of sperm early apoptosis to late apoptosis, showing a significant increase in the expression levels of Bax and Caspase 3. The levels of phosphorylated AMPK were greatly induced by the temperature rise to 20 °C during delivery but reduced thereafter. With the temperature elevation, expression levels of HSP70 and HSP90 were notably increased. Our results indicate that a temperature increase during semen delivery greatly damages sperm quality and functionality by promoting sperm apoptosis. HSP70 and HSP90 could participate in boar sperm resistance to temperature changes by being associated with AMPK activation and anti-apoptotic processes.