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Subcutaneous fat and intramuscular fat (IMF) deposition are closely related to meat production and pork quality. Dingyuan pig, as a native pig breed in China, low selection leads to obvious genetic and phenotypic differences in the population. Individuals with extreme fat content in the population are ideal models for studying the mechanism of fat deposition. In this study, we used RNA-Seq and tandem mass tags-based (TMT) proteomics to analyze the key pathways and genes that specifically regulate subcutaneous fat and IMF deposition in Dingyuan pigs. We identified 191 differentially expressed genes (DEGs) and 61 differentially abundant proteins (DAPs) in the high and low back fat thickness (HBF, LBF) groups, 85 DEGs and 12 DAPs were obtained in the high and low intramuscular fat (HIMF, LIMF) groups. The functional analysis showed that the DEGs and DAPs in the backfat groups were mainly involved in carbohydrates, amino acids, and fatty acids metabolism, whereas the IMF groups were involved in the insulin pathway, longevity, and some disease-related pathways. We found 40 candidate genes that might tissue-specifically lipids deposition for subcutaneous and intramuscular fat. Our research provides theoretical reference materials for the improvement of fat deposition traits of local pig breeds in my country.

With the development of nanomedicine, nanomaterials have been widely used, offering specific drug delivery to target sites, minimal side effects, and significant therapeutic effects. The kidneys have filtration and reabsorption functions, with various potential target cell types and a complex structural environment, making the strategies for kidney function protection and recovery after injury complex. This also lays the foundation for the application of nanomedicine in kidney diseases. Currently, evidence in preclinical and clinical settings supports the feasibility of targeted therapy for kidney diseases using drug delivery based on nanomaterials. The prerequisite for nanomedicine in treating kidney diseases is the use of carriers with good biocompatibility, including nanoparticles, hydrogels, liposomes, micelles, dendrimer polymers, adenoviruses, lysozymes, and elastin-like polypeptides. These carriers have precise renal uptake, longer half-life, and targeted organ distribution, protecting and improving the efficacy of the drugs they carry. Additionally, attention should also be paid to the toxicity and solubility of the carriers. While the carriers mentioned above have been used in preclinical studies for targeted therapy of kidney diseases both in vivo and in vitro, extensive clinical trials are still needed to ensure the short-term and long-term effects of nano drugs in the human body. This review will discuss the advantages and limitations of nanoscale drug carrier materials in treating kidney diseases, provide a more comprehensive catalog of nanocarrier materials, and offer prospects for their drug-loading efficacy and clinical applications. [Display omitted] •Nanomaterials aid kidney disease drug delivery.•Evidence backs nanomaterial use in targeted kidney therapy.•Biocompatible nanocarriers improve kidney drug delivery.

Transcriptome profiles established using high-throughput sequencing can be effectively used for screening genome-wide differentially expressed genes (DEGs). RNA sequences (from RNA-seq) and microRNA sequences (from miRNA-seq) from the tissues of longissimus dorsi muscle of two indigenous Chinese pig breeds (Diannan Small-ear pig [DSP] and Tibetan pig [TP]) and two introduced pig breeds (Landrace [LL] and Yorkshire [YY]) were examined using HiSeq 2000 to identify and compare the differential expression of functional genes related to muscle growth and lipid deposition. We obtained 27.18 G clean data through the RNA-seq and detected that 18,208 genes were positively expressed and 14,633 of them were co-expressed in the muscle tissues of the four samples. In all, 315 DEGs were found between the Chinese pig group and the introduced pig group, 240 of which were enriched with functional annotations from the David database and significantly enriched in 27 Gene Ontology (GO) terms that were mainly associated with muscle fiber contraction, cadmium ion binding, response to organic substance and contractile fiber part. Based on functional annotation, we identified 85 DEGs related to growth traits that were mainly involved in muscle tissue development, muscle system process, regulation of cell development, and growth factor binding, and 27 DEGs related to lipid deposition that were mainly involved in lipid metabolic process and fatty acid biosynthetic process. With miRNA-seq, we obtained 23.78 M reads and 320 positively expressed miRNAs from muscle tissues, including 271 known pig miRNAs and 49 novel miRNAs. In those 271 known miRNAs, 20 were higher and 10 lower expressed in DSP-TP than in LL-YY. The target genes of the 30 miRNAs were mainly participated in MAPK, GnRH, insulin and Calcium signaling pathway and others involved cell development, growth and proliferation, etc. Combining the DEGs and the differentially expressed (DE) miRNAs, we drafted a network of 46 genes and 18 miRNAs for regulating muscle growth and a network of 15 genes and 16 miRNAs for regulating lipid deposition. We identified that CAV2, MYOZ2, FRZB, miR-29b, miR-122, miR-145-5p and miR-let-7c, etc, were key genes or miRNAs regulating muscle growth, and FASN, SCD, ADORA1, miR-4332, miR-182, miR-92b-3p, miR-let-7a and miR-let-7e, etc, were key genes or miRNAs regulating lipid deposition. The quantitative expressions of eight DEGs and seven DE miRNAs measured with real-time PCR certified that the results of differential expression genes or miRNAs were reliable. Thus, 18,208 genes and 320 miRNAs were positively expressed in porcine longissimus dorsi muscle. We obtained 85 genes and 18 miRNAs related to muscle growth and 27 genes and 16 miRNAs related to lipid deposition, which provided new insights into molecular mechanism of the economical traits in pig.

Background Early diagnosis of chronic periprosthetic joint infection (CPJI) is crucial for ensuring effective treatment and improving patient outcomes. However, many auxiliary diagnostic tests are challenging to implement on a large scale due to economic and technical constraints, making CPJI diagnosis difficult. This study aims to design and validate a combined diagnostic model based on commonly used serological tests to evaluate its diagnostic value for CPJI and develop a diagnostic nomogram. Methods A retrospective study from January 2019 to February 2024 involving 170 patients undergoing knee and hip arthroplasty revision for CPJI and aseptic loosening (AL) was conducted across two medical centers. These patients were divided into the training set and validation set. Patients were categorized into CPJI and AL groups based on infection status. Serological tests conducted upon admission were collected, and single-factor and multi-factor logistic regression analyses were used to identify independent diagnostic factors for early infection. These factors were integrated to construct a nomogram model. The model's performance was evaluated using the receiver operating characteristic area under the curve (AUC), Hosmer–Lemeshow test, decision curve analysis (DCA), and calibration curve, with external validation conducted on the validation set. Results Multivariate logistic regression analysis showed that C-reactive protein (CRP), procalcitonin (PCT), and Platelet count/mean platelet volume ratio (PVR) were independent diagnostic factors for CPJI ( p  < 0.05). The AUCs for diagnosing CPJI using these individual factors were 0.806, 0.616, and 0.700 ( p  < 0.05), respectively, while their combined detection achieved an AUC of 0.861 ( p  < 0.05). The DCA clinical impact curve shows the combined model has good clinical utility when the threshold probability of infection presence is between 0.16 and 0.95. Similar results were obtained in the external validation cohort, with the combined detection having an AUC of 0.893. Conclusion The combined diagnostic model of CRP, PCT, and PVR significantly improves the The combined diagnostic model of CRP, PCT, and PVR significantly improves the diagnostic performance for CPJI compared to individual serum biomarkers. It exhibits good sensitivity, specificity, and clinical applicability, providing valuable references for CPJI diagnosis.

The use of Bacillus subtilis in synthetic biology and metabolic engineering is highly desirable to take advantage of the unique metabolic pathways present in this organism. To do this, an evaluation of B. subtilis' intrinsic biological parts is required to determine the best strategies to accurately regulate metabolic circuits and expression of target proteins. The strengths of promoter candidates were evaluated by measuring relative fluorescence units of a green fluorescent protein reporter, integrated into B. subtilis' chromosome. A total of 84 predicted promoter sequences located upstream of different classes of proteins including heat shock proteins, cell-envelope proteins, and proteins resistant against toxic metals (based on similarity) and other kinds of genes were tested. The expression levels measured ranged from 0.0023 to 4.53-fold of the activity of the well-characterized strong promoter P43. No significant shifts were observed when strains, carrying different promoter candidates, were cultured at high temperature or in media with ethanol, but some strains showed increased activity when cultured under high osmotic pressure. Randomly selected promoter candidates were tested and found to activate transcription of thermostable β-galactosidase (bgaB) at a similar level, implying the ability of these sequences to function as promoter elements in multiple genetic contexts. In addition, selected promoters elevated the final production of both cytoplasmic bgaB and secreted protein α-amylase to about fourfold and twofold, respectively. The generated data allows a deeper understanding of B. subtilis' metabolism and will facilitate future work to develop this organism for synthetic biology.

The biosensors based on transcription factors (TFs) are widely used in high throughput screening of metabolic overproducers. The unsatisfactory performances (narrow detection and dynamic ranges) of biosensors limit their practical application and need more improvement. In this study, using the TF LysG (sensing lysine) as an example, a biosensor optimization method was constructed by growth-coupled screening of TF random mutant libraries. The better the performance of the biosensor, the faster the strain grows under screening pressure. A LysGE15D, A54D, and I164V-based biosensors were obtained, which were about 2-fold of the control in the detection and dynamic ranges. A lysine high-producer was screened effectively using the optimized biosensor with the production at 1.51 ± 0.30 g/L in flasks (2.22-fold of the original strain). This study provided a promising strategy for optimizing TF-based biosensors and was of high potential to be applied in the lysine high-producers screening process.

Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein–protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan‐Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.

3D printing technology, also known as rapid prototyping (RP) technology and additive manufacturing (AM) technology, is a digital manufacturing technology that integrates computer, mechanical, electronic, laser, materials, and other technologies. Since its inception for more than 30 years, it has received full attention from countries around the world and has been widely applied in aerospace, biomedical, automotive manufacturing, creative modeling, and daily consumer goods. More importantly, its own development has also gained a variety of technical routes and process plans, resulting in a wide variety of 3D printing processes. Moreover, it is constantly evolving and iteratively developing, and more 3D printing processes will inevitably be produced. Based on its original concept of “dimension” and the fundamental principle of “accumulation” in 3D printing, a new perspective of the minimum geometric elements for accumulation was applied to categorize numerous 3D printing processes into four types: zero-dimensional spot buildup by beam, zero-dimensional spot buildup by powder, one-dimensional line buildup by extrusion or jet, and two-dimensional lamination buildup by thin sheet. Furthermore, typical 3D printing processes of each type, and a total of fourteen specific 3D printing processes in the whole paper, were detailed introduced, including patent information, basic principles and processes, forming materials, application characteristics, etc. This paper is expected to provide a systematic review and comprehensive understanding of 3D printing technologies.

(Gd0.93−xTb0.07Eux)2O3 (x = 0–0.10) phosphors shows great potential for applications in the lighting and display areas. (Gd0.93−xTb0.07Eux)2O3 phosphors with controlled morphology were prepared by a hydrothermal method, followed by calcination at 1100 °C. XRD, FE-SEM, PL/PLE, luminescent decay analysis and thermal stability have been performed to investigate the Eu3+ content and the effects of hydrothermal conditions on the phase variation, microstructure, luminescent properties and energy transfer. Optimum excitation wavelength at ~308 nm nanometer ascribed to the 4f8-4f75d1 transition of Tb3+, the (Gd0.93−xTb0.07Eux)2O3 phosphors display both Tb3+and Eu3+ emission with the strongest emission band at ~611 nm. For increasing Eu3+ content, the Eu3+ emission intensity increased as well while the Tb3+ emission intensity decreased owing to Tb3+→Eu3+ energy transfer. The energy transfer efficiencies were calculated and the energy transfer mechanism was discussed in detail. The lifetime for both the Eu3+ and Tb3+ emission decreases with the Eu3+ addition, the former is due to the formation of resonant energy transfer net, and the latter is because of contribution by Tb3+→Eu3+ energy transfer. The phosphor morphology can be controlled by adjusting the hydrothermal condition (reaction pH), and the morphological influence to the luminescent properties (PL/PLE, decay lifetime, etc.) has been studied in detail.

Studies have shown that hepatocellular carcinoma (HCC) heterogeneity is a main cause leading to failure of treatment. Technology of single-cell sequencing (scRNA) could more accurately reveal the essential characteristics of tumor genetics. From the Gene Expression Omnibus (GEO) database, HCC scRNA-seq data were extracted. The FindCluster function was applied to analyze cell clusters. Autophagy-related genes were acquired from the MSigDB database. The ConsensusClusterPlus package was used to identify molecular subtypes. A prognostic risk model was built with the Least Absolute Shrinkage and Selection Operator (LASSO)-Cox algorithm. A nomogram including a prognostic risk model and multiple clinicopathological factors was constructed. Eleven cell clusters labeled as various cell types by immune cell markers were obtained from the combined scRNA-seq GSE149614 dataset. ssGSEA revealed that autophagy-related pathways were more enriched in malignant tumors. Two autophagy-related clusters (C1 and C2) were identified, in which C1 predicted a better survival, enhanced immune infiltration, and a higher immunotherapy response. LASSO-Cox regression established an eight-gene signature. Next, the HCCDB18, GSA14520, and GSE76427 datasets confirmed a strong risk prediction ability of the signature. Moreover, the low-risk group had enhanced immune infiltration and higher immunotherapy response. A nomogram which consisted of RiskScore and clinical features had better prediction ability. To precisely assess the prognostic risk, an eight-gene prognostic stratification signature was developed based on the heterogeneity of HCC immune cells.