Search

Abstract Understanding the molecular mechanisms underlying genetic diseases is challenging due to environmental and genetic factors. Genome-wide association studies (GWAS) have identified numerous genetic loci, but their functional implications are largely unknown. Single-cell multiomics sequencing has emerged as a powerful tool to study disease-specific cell types and their relationship with genetic variants. However, comprehensive databases for exploring these mechanisms across different tissues are lacking. We present the Disease-Related Cell Type database (DRCTdb), integrating GWAS and single-cell multiomics data to identify disease-related cell types and elucidate their regulatory mechanisms. DRCTdb contains well-processed data from 16 studies, covering 4 million cells within 28 tissues. Users can browse relationships and regulatory mechanisms between SNPs of 42 genetic diseases and cell types based on GWAS and single-cell data. DRCTdb also offers data downloads and is available at https://singlecellatlas.top/DRCTDB .

Intestinal symbionts live in insects’ digestive systems and help with food digestion, nitrogen cycling, and energy use. Numerous symbionts, including bacteria, fungi, and protozoa, colonize the posterior gut of termites. Intestinal microbiota affects the Toll or Imd pathways during viral or entomopathogenic fungus infection in mosquitoes, but the role of intestinal symbionts in individual termite immunity is unclear. In the present research, Odontotermes formosanus and Metarhizium robertsii were selected to investigate the potential mechanism of the intestinal bacteria influencing termite innate immune while encountering an entomopathogen using metagenome sequencing and meta-transcriptome sequencing. We found that termite mortality declined within 48 hours under high spore infections and reached semi-lethal status within 72 hours. We sequenced the control and infestation termite and found that the dominant phyla changed below low-abundance flora during infestation. According to function annotation, the functions of spirochetes are significantly different from those of the rest of the phyla, which are mainly enriched in metabolism and cellular processes. There are 261 upregulated and 459 down-regulated DEGs derived from bacteria after infestation. We identified the glutamate-cysteine ligase gene, gshA, which is significantly upregulated in the infected group, and the GSH content in the regular infected group was higher than the 5% kanamycin-infected group. We speculated on a potential mechanism that one or more bacteria belonging to Spirochetes that upregulated gshA gene expression and increased GSH content in the hindgut to integrate with metarhizium toxins and then excrete out of the intestine.

Abstract In this work, a novel multifunctional film with durable antifogging performance and remarkable optical property is designed. By doping and hybridization to build an organic–inorganic siloxane network, the surface achieves long‐lasting wettability and superhydrophilicity with a water contact angle of 0°, which is maintained within 10° for over 130 days. The low refractive index endows the hybrid film with excellent optical property, which the average transmittance (380–1100 nm) of the film is 97.60% with the peak transmittance of 99.48%. By this design, the film performs well in the felt abrasion test, water impact test, X‐cut tape test, tape‐peeling test, chemical stability test, and anti‐dust test. Due to the abundant hydroxyl radicals on the surface, the film also exhibits excellent performance, achieving 92.73% degradation of methylene blue solution (10 ppm) and 39.53% degradation of rhodamine B (10 ppm) with good reproducibility in cyclic measurements.

In order to achieve a breakthrough in the exploration of uranium orebodies in the Changjiang area of Guangdong province in China, the geo-electrochemical exploration method is used for mineral resource prediction. The logarithmically and isometric log-ratio (ilr) transformations are applied to the geo-electrochemical data in this study area to extract geochemical anomalies. The relationship between element associations and mineralization is revealed through descriptive statistical analysis and further biplot analysis. Then, the energy spectrum density–area fractal model (S-A model) is used to identify geochemical backgrounds and anomalies. The results show that: (i) the logarithmically and ilr-transformed data are more uniform, and they more or less obey the rules of normal distribution; (ii) the biplot shows that the ilr-transformed data eliminates the closure effect, and the robust principal component analysis (RPCA) has a better indicative significance for element associations—PC1 reveals the mineralization element association dominated by U and the multiple periods of hydrothermal activity; (iii) the S-A method could extract the local anomalies from different geochemical backgrounds, which indicates mineralization is more reliable. Finally, four favorable prospecting targets are delineated based on the geological and geochemical indicators.

Deep-seated mineralization prediction is an important scientific problem in the area of mineral resources exploration. The 3D metallogenic information extraction of geology and geochemistry can be of great help. This study uses 3D modeling technology to intuitively depict the spatial distribution of orebodies, fractures, and intrusive rocks. In particular, the geochemical models of 12 elements are established for geochemical metallogenic information extraction. Subsequently, the front halo element association of As-Sb-Hg, the near-ore halo element association of Au-Ag-Cu-Pb-Zn, and the tail halo element association of W-Mo-Bi are identified. Upon this foundation, the 3D convolutional neural network model is built and used for deep-seated mineralization prediction, which expresses a high performance (AUC = 0.99). Associated with the metallogenic regularity, two mineral exploration targets are delineated, which might be able to serve as beneficial achievements for deep exploration in the Zaozigou gold deposit.

Ultrabithorax (Ubx) is a member of the Hox gene group involved in cell fate decisions, cell proliferation and organ identity. Its function has been extensively researched in Drosophila melanogaster but little is known about it in Lepidoptera. To uncover the function of Ubx in the development of lepidopterans, we constructed the Ubx overexpression (UbxOE) strain based on the Nistari strain of Bombyx mori. The UbxOE strain showed a small body size, transparent intersegmental membrane and abnormal posterior silk gland (PSG). In the current study, we focused on the effect of Ubx overexpression on the posterior silk gland. As the major protein product of PSG, the mRNA expression of fibroin heavy chain (Fib-H) and fibroin light chain (Fib-L) was upregulated three times in UbxOE, but the protein expression of Fib-H and Fib-L was not significantly different. We speculated that the overexpression of Ubx downregulated the expression of Myc and further caused abnormal synthesis of the spliceosome and ribosome. Abnormalities of the spliceosome and ribosome affected the synthesis of protein in the PSG and changed its morphology.

Bombyx mori is an important economic insect, its economic value mainly reflected in the silk yield. The major functional genes affecting the silk yield of B. mori have not been determined yet. Bombyx mori vacuolar protein sorting-associated protein 13d (BmVps13d) has been identified, but its function is not reported. In this study, BmVps13d protein shared 30.84% and 34.35% identity with that of in Drosophila melanogaster and Homo. sapiens, respectively. The expressions of BmVps13d were significantly higher in the midgut and silk gland of JS (high silk yield) than in that of L10 (low silk yield). An insertion of 9 bp nucleotides and two deficiencies of adenine ribonucleotides in the putative promoter region of BmVps13d gene in L10 resulted in the decline of promoter activity was confirmed using dual luciferase assay. Finally, the functions of BmVps13d in B. mori were studied using the CRISPR/Cas9 system, and the mutation of BmVps13d resulted in a 24.7% decline in weight of larvae, as well as a 27.1% (female) decline and a 11.8% (male) decline in the silk yield. This study provides a foundation for studying the molecular mechanism of silk yield and breeding the silkworm with high silk yield.

This paper focuses on researching the scientific problem of deep extraction and inference of favorable geological and geochemical information about mineralization at depth, based on which a deep mineral resources prediction model is established and machine learning approaches are used to carry out deep quantitative mineral resources prediction. The main contents include: (i) discussing the method of 3D geochemical anomaly extraction under the multi-fractal content-volume (C-V) models, extracting the 12 element anomalies and constructing a 3D geochemical anomaly data volume model for laying the data foundation for researching geochemical element distribution and association; (ii) extracting the element association characteristics of primary geochemical halos and inferring deep metallogenic factors based on compositional data analysis (CoDA), including quantitatively extracting the geochemical element associations corresponding to ore-bearing structures (Sb-Hg) based on a data-driven CoDA framework, quantitatively identifying the front halo element association (As-Sb-Hg), near-ore halo element association (Au-Ag-Cu-Pb-Zn) and tail halo element association (W-Mo-Co-Bi), which provide quantitative indicators for the primary haloes’ structural analysis at depth; (iii) establishing a deep geological and geochemical mineral resources prediction model, which is constructed by five quantitative mineralization indicators as input variables: fracture buffer zone, element association (Sb-Hg) of ore-bearing structures, metallogenic element Au anomaly, near-ore halo element association Au-Ag-Cu-Pb-Zn and the ratio of front halo to tail halo (As-Sb-Hg)/(W-Mo-Bi); and (iv) three-dimensional MPM based on the maximum entropy model (MaxEnt) and Gaussian mixture model (GMM), and delineating exploration targets at depth. The results show that the C-V model can identify the geological element distribution and the CoDA method can extract geochemical element associations in 3D space reliably, and the machine learning methods of MaxEnt and GMM have high performance in 3D MPM.

This paper focuses on the scientific problem of quantitative mineralization prediction at large depth in the Zaozigou gold deposit, west Qinling, China. Five geological and geochemical indicators are used to establish geological and geochemical quantitative prediction model. Machine learning and Deep learning algorithms are employed for 3D Mineral Prospectivity Mapping (MPM). Especially, the Student Teacher Ore-induced Anomaly Detection (STOAD) model is proposed based on the knowledge distillation (KD) idea combined with Deep Auto-encoder (DAE) network model. Compared to DAE, STOAD uses three outputs for anomaly detection and can make full use of information from multiple levels of data for greater overall robustness. The results show that the quantitative mineral resources prediction by applying the STOAD model has a good performance, where the value of Area Under Curve (AUC) is 0.97. Finally, three main mineral exploration targets are delineated for further investigation.

In Bombyx mori, as an important economic insect, it was first found that some strains were completely refractory to infection with Autographa californica nucleopolyhedrovirus (AcMNPV) through intrahemocelical injection; whereas almost all natural strains had difficulty resisting Bombyx mori nucleopolyhedrovirus (BmNPV), which is also a member of the family Baculoviridae. Previous genetics analysis research found that this trait was controlled by a potentially corresponding locus on chromosome 3, but the specific gene and mechanism was still unknown. With the help of the massive silkworm strain re-sequencing dataset, we performed the Genome-Wide Association Studies (GWAS) to identify the gene related to the resistance of AcMNPV in this study. The GWAS results showed that the Niemann-Pick type C1 (NPC-1) gene was the most associated with the trait. The knockdown experiments in BmN cells showed that BmNPC1 has a successful virus suppression infection ability. We found a small number of amino acid mutations among different resistant silkworms, which indicates that these mutations contributed to the resistance of AcMNPV. Furthermore, inhibition of the BmNPC1 gene also changed the viral gene expression of the AcMNPV, which is similar to the expression profile in the transcriptome data of p50 and C108 strains.

The smoothing effect of data interpolation could cause useful information loss in geochemical mapping, and the uncertainty assessment of geochemical anomaly could help to extract reasonable anomalies. In this paper, multiple-point geostatistical simulation and local singularity analysis (LSA) are proposed to identify regional geochemical anomalies and potential mineral resources areas. Taking Cu geochemical data in the Mila Mountain Region, southern Tibet, as an example, several conclusions were obtained: (1) geochemical mapping based on the direct sampling (DS) algorithm of multiple-point geostatistics can avoid the smoothing effect through geochemical pattern simulation; (2) 200 realizations generated by the direct sampling simulation reflect the uncertainty of an unsampled value, and the geochemical anomaly of each realization can be extracted by local singularity analysis, which shows geochemical anomaly uncertainty; (3) the singularity-quantile (S-Q) analysis method was used to determine the separation thresholds of E-type α, and uncertainty analysis was carried out on the copper anomaly to obtain the anomaly probability map, which should be more reasonable than the interpolation-based geochemical map for geochemical anomaly identification. According to the anomaly probability and favorable geological conditions in the study area, several potential mineral resource targets were preliminarily delineated to provide direction for subsequent mineral exploration.