Single-cell RNA sequencing reveals different chondrocyte states in femoral cartilage between osteoarthritis and healthy individuals.

Background: Cartilage injury is the main pathological manifestation of osteoarthritis (OA). Healthy chondrocyte is a prerequisite for cartilage regeneration and repair. Differences between healthy and OA chondrocyte types and the role these types play in cartilage regeneration and OA progression are unclear. Method: This study conducted single-cell RNA sequencing (scRNA-seq) on the cartilage from normal distal femur of the knee (NC group) and OA femur (OA group) cartilage, the chondrocyte atlas was constructed, and the differences of cell subtypes between the two groups were compared. Pseudo-time and RNA velocity analysis were both performed to verify the possible differentiation sequence of cell subtypes. GO and KEGG pathway enrichment analysis were used to explore the potential functional characteristics of each cell subtype, and to predict the functional changes during cell differentiation. Differences in transcriptional regulation in subtypes were explored by single-cell regulatory network inference and clustering (SCENIC). The distribution of each cell subtype in cartilage tissue was identified by immunohistochemical staining (IHC). Result: A total of 75,104 cells were included, they were divided into 19 clusters and annotated as 11 chondrocyte subtypes, including two new chondrocyte subtypes: METRNL+ and PRG4+ subtype. METRNL+ is in an early stage during chondrocyte differentiation, and RegC-B is in an intermediate state before chondrocyte dedifferentiation. With cell differentiation, cell subtypes shift from genetic expression to extracellular matrix adhesion and collagen remodeling, and signal pathways shift from HIF-1 to Hippo. The 11 subtypes were finally classified as intrinsic chondrocytes, effector chondrocytes, abnormally differentiated chondrocytes and dedifferentiated chondrocytes. IHC was used to verify the presence and distribution of each chondrocyte subtype. Conclusion: This study screened two new chondrocyte subtypes, and a novel classification of each subtype was proposed. METRNL+ subtype is in an early stage during chondrocyte differentiation, and its transcriptomic characteristics and specific pathways provide a foundation for cartilage regeneration. EC-B, PRG4+ RegC-B, and FC are typical subtypes in the OA group, and the HippO-Taz pathway enriched by these cell subtypes may play a role in cartilage repair and OA progression. RegC-B is in the intermediate state before chondrocyte dedifferentiation, and its transcriptomic characteristics may provide a theoretical basis for intervening chondrocyte dedifferentiation.

Classification and functional origins of stereocomplementary alcohol dehydrogenases for asymmetric synthesis of chiral secondary alcohols: A review.

Alcohol dehydrogenases (ADHs) mediated biocatalytic asymmetric reduction of ketones have been widely applied in the synthesis of optically active secondary alcohols with highly reactive hydroxyl groups ligated to the stereogenic carbon and divided into (R)- and (S)-configurations. Stereocomplementary ADHs could be applied in the synthesis of both enantiomers and are increasingly accepted as the "first of choice" in green chemistry due to the high atomic economy, low environmental factor, 100 % theoretical yield, and high environmentally friendliness. Due to the equal importance of complementary alcohols, development of stereocomplementary ADHs draws increasing attention. This review is committed to summarize recent advance in discovery of naturally evolved and tailor-made stereocomplementary ADHs, unveil the molecular mechanism of stereoselective catalysis in views of classification and functional basis, and provide guidance for further engineering the stereoselectivity of ADHs for the industrial biosynthesis of chiral secondary alcohol of industrial relevance.

Critically-ill COVID-19 susceptibility gene CCR3 shows natural selection in sub-Saharan Africans.

The prevalence of COVID-19 critical illness varies across ethnicities, with recent studies suggesting that genetic factors may contribute to this variation. The aim of this study was to investigate natural selection signals of genes associated with critically-ill COVID-19 in sub-Saharan Africans. Severe COVID-19 SNPs were obtained from the HGI website. Selection signals were assessed in 661 sub-Sahara Africans from 1000 Genomes Project using integrated haplotype score (iHS), cross-population extended haplotype homozygosity (XP-EHH), and fixation index (Fst). Allele frequency trajectory analysis of ancient DNA samples were used to validate the existing of selection in sub-Sahara Africans. We also used Mendelian randomization to decipher the correlation between natural selection and critically-ill COVID-19. We identified that CCR3 exhibited significant natural selection signals in sub-Sahara Africans. Within the CCR3 gene, rs17217831-A showed both high iHS (Standardized iHS = 2) and high XP-EHH (Standardized XP-EHH = 2.5) in sub-Sahara Africans. Allele frequency trajectory of CCR3 rs17217831-A revealed natural selection occurring in the recent 1,500 years. Natural selection resulted in increased CCR3 expression in sub-Sahara Africans. Mendelian Randomization provided evidence that increased blood CCR3 expression and eosinophil counts lowered the risk of critically ill COVID-19. Our findings suggest that sub-Saharan Africans are resistant to critically ill COVID-19 due to natural selection and identify CCR3 as a potential novel therapeutic target.

Single-cell RNA sequencing reveals the impact of mechanical loading on knee tibial cartilage in osteoarthritis.

Articular cartilage degeneration is one of the major pathogenic alterations observed in knee osteoarthritis (KOA). Mechanical stress has been verified to contribute to KOA development. To gain insight into the pathogenic mechanism of KOA development, we investigated chondrocyte subsets under different mechanical loading conditions via single-cell RNA sequencing (scRNA-seq). Articular cartilage tissues from both high mechanical loading (named the OATL group) and low mechanical loading (named the OATN group) surfaces were obtained from the proximal tibia of KOA patients, and scRNA-seq was conducted. Chondrocyte subtypes, including a new subset, HTC-C (hypertrophic chondrocytes-C), and their functions, development and interactions among cell subsets were identified. Immunohistochemical staining was also conducted to verify the existence and location of each chondrocyte subset. Furthermore, differentially expressed genes (DEGs) and their functions between regions with high and low mechanical loading were identified. Based on Gene Ontology terms for the DEGs in each cell type, the characteristic of cartilage degeneration in the OATL region was clarified. Mitochondrial dysfunction may be involved in the KOA process in the OATN region.

DERnet: a deep neural network for end-to-end reconstruction in magnetic particle imaging.

Objective. Magnetic particle imaging (MPI) shows potential for contributing to biomedical research and clinical practice. However, MPI images are effectively affected by noise in the signal as its reconstruction is an ill-posed inverse problem. Thus, effective reconstruction method is required to reduce the impact of the noise while mapping signals to MPI images. Traditional methods rely on the hand-crafted data-consistency (DC) term and regularization term based on spatial priors to achieve noise-reducing and reconstruction. While these methods alleviate the ill-posedness and reduce noise effects, they may be difficult to fully capture spatial features.Approach. In this study, we propose a deep neural network for end-to-end reconstruction (DERnet) in MPI that emulates the DC term and regularization term using the feature mapping subnetwork and post-processing subnetwork, respectively, but in a data-driven manner. By doing so, DERnet can better capture signal and spatial features without relying on hand-crafted priors and strategies, thereby effectively reducing noise interference and achieving superior reconstruction quality.Main results. Our data-driven method outperforms the state-of-the-art algorithms with an improvement of 0.9-8.8 dB in terms of peak signal-to-noise ratio under various noise levels. The result demonstrates the advantages of our approach in suppressing noise interference. Furthermore, DERnet can be employed for measured data reconstruction with improved fidelity and reduced noise. In conclusion, our proposed method offers performance benefits in reducing noise interference and enhancing reconstruction quality by effectively capturing signal and spatial features.Significance. DERnet is a promising candidate method to improve MPI reconstruction performance and facilitate its more in-depth biomedical application.

Single-cell RNA sequencing reveals differences between force application and bearing in ankle cartilage.

Chondrocytes are the major functional elements of articular cartilage. Force has been demonstrated to influence the structure and function of articular cartilage and chondrocytes. Therefore, it is necessary to evaluate chondrocytes under different force conditions to gain deep insight into chondrocyte function. Six cartilage tissues from the distal tibia (referred to as the AT group) and five cartilage tissues from the trochlear surface of the talus (referred to as the ATa group) were obtained from 6 donors who had experienced fatal accidents. Single-cell RNA sequencing was used on these samples. A total of 149,816 cells were analyzed. Nine chondrocyte subsets were ultimately identified. Pseudotime analyses, enrichment analyses, cell-cell interaction studies, and single-cell regulatory network inference and clustering were performed for each cell type, and the differences between the AT and ATa groups were analyzed. Immunohistochemical staining was used to verify the existence of each chondrocyte subset and its distribution. The results suggested that reactive oxygen species related processes were active in the force-applied region, while tissue repair processes were common in the force-bearing region. Although the number of prehypertrophic chondrocytes was small, these chondrocytes seemed to play an important role in the ankle.

Single-cell RNA sequencing reveals distinct chondrocyte states in femoral cartilage under weight-bearing load in Rheumatoid arthritis.

Introduction: Rheumatoid arthritis (RA) is a common autoimmune joint disease, the pathogenesis of which is still unclear. Cartilage damage is one of the main manifestations of the disease. Chondrocytes are the main functional component of articular cartilage, which is relevant to disease progression. Mechanical loading affects the structure and function of articular cartilage and chondrocytes, but the effect of weight bearing on chondrocytes in rheumatoid arthritis is still unclear. Methods: In this paper, single-cell RNA sequencing (scRNA-seq) was performed on collected cartilage from the weight-bearing region (Fb group) and non-weight-bearing region (Fnb group) of the femur, and the differences between the Fb and Fnb groups were analyzed by cell type annotation, pseudotime analysis, enrichment analysis, cell interactions, single-cell regulatory network inference and clustering (SCENIC) for each cell type. Results: A total of 87,542 cells were analyzed and divided into 9 clusters. Six chondrocyte subpopulations were finally identified by cellular annotation, and two new chondrocyte subtypes were annotated as immune-associated chondrocytes. The presence of each chondrocyte subpopulation and its distribution were verified using immunohistochemical staining (IHC). In this study, the atlas of femoral cartilage in knee rheumatoid arthritis and 2 new immune-related chondrocytes were validated using scRNA-seq and IHC, and chondrocytes in the weight-bearing and non-weight-bearing regions of the femur were compared. There might be a process of macrophage polarization transition in MCs in response to mechanical loading, as in macrophages. Conclusion: Two new immune-associated chondrocytes were identified. MCs have contrasting functions in different regions, which might provide insight into the role of immune and mechanical loading on chondrocytes in the development of knee rheumatoid osteoarthritis.

Radiological evidence of rapid growth acceleration of a small part solid nodule found to be large-cell carcinoma of the lung.

BACKGROUND: With the widespread use of low-dose computed tomography for lung cancer screening, the detection rate of pulmonary lesions manifesting as ground-glass opacities (GGOs) has been increasing dramatically. The volume doubling time (VDT) has been introduced in clinical practice to monitor the potential growth rate of GGOs during long-term follow-up periods. CASE PRESENTATION: A 72-year-old never-smoker female diagnosed with mixed GGO manifested abruptly accelerated growth with sudden decreased VDT from 400 to 36 days. A thoracoscopic left lower lobectomy with mediastinal lymph node dissection was performed, and the diagnosis was stage IB large-cell neuroendocrine carcinoma (LCNEC). Next-generation sequencing of the tumor highlights an EML4-ALK gene fusion. CONCLUSIONS: The LCNEC may present as GGO with longer VDT in the early stage. VDT should calculate by the whole size either on the entire tumor diameter or on consolidation diameter. It is recommended that meticulous long-term follow-up with dynamic VDT monitoring may help select high-risk GGOs performing timely semi-elective surgical resection in clinical practice.

Genetic variants in HFE are associated with non-alcoholic fatty liver disease in lean individuals.

Background & Aims: Around 20% of patients with non-alcoholic fatty liver disease (NAFLD) are lean. Increasing evidence suggests that lean NAFLD is a unique subtype of the disease. We aimed to explore the metabolic profile, genetic basis, causal risk factors, and clinical sequelae underlying lean NAFLD. Methods: NAFLD was diagnosed by whole liver proton density fat fraction ≥5%. Whole liver proton density fat fraction and hepatic iron were quantified using magnetic resonance imaging in the UK Biobank. Individuals in this study were stratified according to the World Health Organization criteria of obesity, into lean, overweight, and obese. Mediation analysis, Mendelian randomisation analysis, and Bayesian networks were used to identify a risk factor or a clinical sequela of lean/obese NAFLD. Results: Lean NAFLD manifested a distinct metabolic profile, featured by elevated hepatic iron and fasting glucose. Four loci, namely, HFE rs1800562, SLC17A3-SLC17A2-TRIM38 rs9348697, PNPLA3 rs738409, and TM6SF2 rs58542926, were associated with lean NAFLD (p <5 × 10-8). HFE rs1800562 was specifically associated with lean NAFLD and demonstrated a significant mediation effect through elevating hepatic iron. Type 2 diabetes was the most pronounced clinical sequela of lean NAFLD, followed by liver cirrhosis. Conclusions: Our study suggested that HFE plays a potential steatogenic role rather than regulating iron homoeostasis in patients with lean NAFLD. The increased liver iron deposition is associated with lean NAFLD, whereas obese NAFLD is not related to hepatic iron. The clinical management of patients with lean NAFLD shall be concerned with the prevention and treatment of type 2 diabetes and liver cirrhosis. Impact and implications: Lean NAFLD has a distinct natural history from obese NAFLD. This study underscored liver iron content and the genetic variant of the iron homoeostasis gene HFE as major risks of lean NAFLD, in addition to the unique metabolic profile. The development of type 2 diabetes or liver cirrhosis shall be closely monitored and prevented in patients with lean NAFLD.

Systemic inflammation influences the prognosis of patients with radically resected non-small cell lung cancer and correlates with the immunosuppressive microenvironment.

The impact of host condition on prognosis of non-small cell lung cancer (NSCLC) and the interaction between host and NSCLC remain unclear. This study investigated the association between systemic inflammation and prognosis and characteristics of radically resected NSCLC. This study consisted of a cohort study and an exploratory study of institutional prospective databases. All participants underwent video-assisted thoracoscopic lobectomy as the primary treatment. Systemic inflammation was assessed before surgery using the advanced lung cancer inflammation index and the systemic inflammation response index. Next-generation sequencing and multiplex immunofluorescence analysis were conducted to delineate tumor characteristics. In the cohort study including 1507 participants, high inflammation was associated with poor disease-free survival and overall survival before and after propensity score matching and in multivariable analysis. Systemic inflammation showed good prognostic value for stage IA-IB NSCLC, and the prognostic value diminished with upstaging of NSCLC. In the exploratory study including 217 adenocarcinomas, tumor microenvironment of high inflammation group showed a greater abundance of PDL1+ tumor cells and immune cells, which were independent from driver gene mutations and clinicopathological characteristics. Spatial analysis demonstrated a higher frequency of immune-suppressed cellular neighborhood, increased avoidance between immune cells and PDL1- tumor cells and compromised immune killing and presentation in tumor microenvironment of high inflammation group. Systemic inflammation showed limited association with genomic mutations. Systemic inflammation may influence the prognosis of NSCLC at both the systematic level and the local immune response. The correlation between high inflammation and immunosuppressive microenvironment indicates a novel thread for anticancer treatment.

Artificial-intelligence-based computed tomography histogram analysis predicting tumor invasiveness of lung adenocarcinomas manifesting as radiological part-solid nodules.

Background: Tumor invasiveness plays a key role in determining surgical strategy and patient prognosis in clinical practice. The study aimed to explore artificial-intelligence-based computed tomography (CT) histogram indicators significantly related to the invasion status of lung adenocarcinoma appearing as part-solid nodules (PSNs), and to construct radiomics models for prediction of tumor invasiveness. Methods: We identified surgically resected lung adenocarcinomas manifesting as PSNs in Peking University People's Hospital from January 2014 to October 2019. Tumors were categorized as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) by comprehensive pathological assessment. The whole cohort was randomly assigned into a training (70%, n=832) and a validation cohort (30%, n=356) to establish and validate the prediction model. An artificial-intelligence-based algorithm (InferRead CT Lung) was applied to extract CT histogram parameters for each pulmonary nodule. For feature selection, multivariate regression models were built to identify factors associated with tumor invasiveness. Logistic regression classifier was used for radiomics model building. The predictive performance of the model was then evaluated by ROC and calibration curves. Results: In total, 299 AIS/MIAs and 889 IACs were included. In the training cohort, multivariate logistic regression analysis demonstrated that age [odds ratio (OR), 1.020; 95% CI, 1.004-1.037; p=0.017], smoking history (OR, 1.846; 95% CI, 1.058-3.221; p=0.031), solid mean density (OR, 1.014; 95% CI, 1.004-1.024; p=0.008], solid volume (OR, 5.858; 95% CI, 1.259-27.247; p = 0.037), pleural retraction sign (OR, 3.179; 95% CI, 1.057-9.559; p = 0.039), variance (OR, 0.570; 95% CI, 0.399-0.813; p=0.002), and entropy (OR, 4.606; 95% CI, 2.750-7.717; p<0.001) were independent predictors for IAC. The areas under the curve (AUCs) in the training and validation cohorts indicated a better discriminative ability of the histogram model (AUC=0.892) compared with the clinical model (AUC=0.852) and integrated model (AUC=0.886). Conclusion: We developed an AI-based histogram model, which could reliably predict tumor invasiveness in lung adenocarcinoma manifesting as PSNs. This finding would provide promising value in guiding the precision management of PSNs in the daily practice.

Associations between dietary fatty acid patterns and non-alcoholic fatty liver disease in typical dietary population: A UK biobank study.

Background and Aims: Dietary fatty acid composition is associated with non-alcoholic fatty liver disease (NAFLD). Few evidence had identified a clear role of dietary fatty acid composition of typical diet in NAFLD. We aimed to investigate the relationship between dietary patterns and NAFLD in populations with typical diets and to explore the effect of fatty acid composition in dietary patterns on NAFLD. Methods: Principal component analysis was used to identify 4 dietary patterns in UK Biobank participants. Logistic regression was used to estimate the association between dietary patterns and NAFLD. Mediation analysis was performed to evaluate the extent to which the relationship between dietary patterns and NAFLD was explained by dietary fatty acid combinations, as surrogated by serum fatty acids measured by nuclear magnetic resonance. Results: A dietary fatty acid pattern (DFP1) characterized by "PUFA enriched vegetarian" was negatively associated with NAFLD risk. Serum fatty acids were significantly associated with DFP1 and NAFLD. Mediation analysis showed SFA (27.8%, p < 0.001), PUFA (25.1%, p < 0.001), ω-6 PUFA (14.3%, p < 0.001), LA (15.6%, p < 0.001) and DHA (10%, p < 0.001) had a significant indirect effect on the association between DFP1 and NAFLD. A dietary pattern characterized by "PUFA enriched carnivore" (DFP2) was not associated with NAFLD risk. Conclusion: A "PUFA enriched vegetarian" dietary pattern with increased LA and DHA, may be beneficial for the treatment or prevention of NAFLD, while a "PUFA enriched carnivore" dietary pattern may not be harmful to NAFLD.

Super-stable mineralization of Cu, Cd, Zn and Pb by CaAl-layered double hydroxide: Performance, mechanism, and large-scale application in agriculture soil remediation.

The synthesized CaAl-layered double hydroxide (CaAl-LDH) shows excellent performance in potentially toxic metals (PTMs) removal, and the removal capacity of CaAl-LDH toward Cu2+, Zn2+ and Pb2+ in aqueous solution is 502.4, 315.2 and 600.0 mg/g respectively. Cu2+ and Zn2+ are removed through isomorphic substitution of laminate Ca and dissolution-reprecipitation, leading to the formation of CuAl-LDH and ZnAl-LDH mineralization products. Pb2+ is removed by the complexation and precipitation to form Pb3(CO3)2(OH)2. The application of CaAl-LDH in laboratory-scale soil remediation shows that target PTMs are gradually mineralized into relatively stable oxidizable and residual state, and the immobilization efficiency of available Cu, Zn, Cd and Pb reaches 84.62 %, 98.66 %, 96.81 % and 70.27 % respectively. In addition, practical application in farmland results in the significant reduction of available Cu, Zn, Cd and Pb with the immobilization efficiency of 30.15 %, 67.30 % and 57.80 % and 38.71 % respectively. Owing to the super-stable mineralization effect of CaAl-LDH, the content of PTMs in the roots, stems and grains of cultivated buckwheat also decreases obviously, and the growth and yield of buckwheat are not adversely affected but improved. The above prove that the super-stable mineralization based on CaAl-LDH is a promising scheme for the remediation of PTMs contaminated agriculture soil.

Identification of Key Diagnostic Markers and Immune Infiltration in Osteoarthritis.

BACKGROUND: Osteoarthritis (OA) is a worldwide chronic disease of the articulating joints. An increasing body of data demonstrates the immune system's involvement in osteoarthritis. The molecular mechanisms of OA are still unclear. This study aimed to search for OA immunerelated hub genes and determine appropriate diagnostic markers to help the detection and treatment of the disease. METHODS: Gene expression data were downloaded from the GEO database. Firstly, we analyzed and identified the differentially expressed genes (DEGs) using R packages. Meanwhile, ssGSEA was used to determine the activation degree of immune-related genes (IRGs), and WGCNA analysis was applied to search for co-expressed gene modules associated with immune cells. Then, critical networks and hub genes were found in the PPI network. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analyzed the biological functions of genes. The ability of the hub genes to differentiate OA from controls was assessed by the area under the ROC curve. A miRNA and transcription factor (TF) regulatory network was constructed according to their relationship with hub genes. Finally, the validation of hub genes was carried out by qPCR. RESULTS: In total, 353 DEGs were identified in OA patients compared with controls, including 222 upregulated and 131 downregulated genes. WGCNA successfully identified 34 main functional modules involved in the pathogenesis of OA. The most crucial functional module involved in OA included 89 genes. 19 immune-related genes were obtained by overlapping DEGs with the darkgrey module. The String database was constructed using the protein-protein interaction (PPI) network of 19 target genes, and 7 hub genes were identified by MCODE. ROC curve showed that 7 hub genes were potential biomarkers of OA. The expression levels of hub genes were validated by qPCR, and the results were consistent with those from bioinformatic analyses. CONCLUSION: Immune-related hub genes, including TYROBP, ITGAM, ITGB2, C1QC, MARCO, C1QB, and TLR8, may play critical roles in OA development. ITGAM had the highest correction on immune cells.

Lung adenocarcinoma manifesting as subsolid nodule potentially represents tumour in the equilibrium phase of immunoediting.

Lung adenocarcinomas manifesting as subsolid nodules (SSN-LUADs) possess distinct dormant behaviour. This study was designed to compare the immune landscapes of normal lungs (nLungs), SSN-LUADs and LUADs manifesting as solid nodules (SN-LUADs) so as to better understand the status of anti-tumour immunity in SSN-LUADs. Mass cytometry by time-of-flight analysis was performed on 299, 570 single cells from nLung, SSN-LUAD and SN-LUAD tissues. The immune cells were identified by phenotype, and the percentages of different immune cell subclusters were compared between SSN-LUADs, SN-LUADs and nLungs. Elevated percentage of CD8+ T cells were identified in SSN-LUADs compared with in nLungs and SN-LUADs. Elevated CD56bright NK cells and decreased CD56dim NK cells were identified in both SSN-LUADs and SN-LUADs compared with in nLungs. The immune landscape of SSN-LUAD fits the theory of equilibrium phase of immunoediting, thus functional adaptive anti-tumour immunity but impaired innate anti-tumour immunity potentially contributes to the maintaining of its dormant behaviour.

Plasmonic enhanced photocatalytic activity of Ag/TiO2 tube-in-tube fibers.

Ag nanoparticle was found to significantly enhance the photocatalytic activity of self-organized TiO2 nanotube structures. Herein, novel Ag/TiO2 tube-in-tube fibers have been prepared by a facile electrospinning technology and calcination process. Employed as the photocatalyst, the composite could efficiently catalyze the photodegradation of the model organic pollutant, rhodamine B under visible light irradiation, exhibiting a superior photocatalytic activity than the undoped TiO2 tube-in-tube fibers. This enhanced activity has been ascribed to plasmonic characteristics of Ag nanoparticles, which promote the light absorption and charge transfer feasibility. The simple, low-cost and green fabrication route of the composite provides a novel means for preparing similar materials, holding great promise for wider application in the future.

[A generative adversarial network-based unsupervised domain adaptation method for magnetic resonance image segmentation].

Intelligent medical image segmentation methods have been rapidly developed and applied, while a significant challenge is domain shift. That is, the segmentation performance degrades due to distribution differences between the source domain and the target domain. This paper proposed an unsupervised end-to-end domain adaptation medical image segmentation method based on the generative adversarial network (GAN). A network training and adjustment model was designed, including segmentation and discriminant networks. In the segmentation network, the residual module was used as the basic module to increase feature reusability and reduce model optimization difficulty. Further, it learned cross-domain features at the image feature level with the help of the discriminant network and a combination of segmentation loss with adversarial loss. The discriminant network took the convolutional neural network and used the labels from the source domain, to distinguish whether the segmentation result of the generated network is from the source domain or the target domain. The whole training process was unsupervised. The proposed method was tested with experiments on a public dataset of knee magnetic resonance (MR) images and the clinical dataset from our cooperative hospital. With our method, the mean Dice similarity coefficient (DSC) of segmentation results increased by 2.52% and 6.10% to the classical feature level and image level domain adaptive method. The proposed method effectively improves the domain adaptive ability of the segmentation method, significantly improves the segmentation accuracy of the tibia and femur, and can better solve the domain transfer problem in MR image segmentation.

Single-cell RNA sequence presents atlas analysis for chondrocytes in the talus and reveals the potential mechanism in coping with mechanical stress.

Chondrocytes are indispensable for the function of cartilage because they provide the extracellular matrix. Therefore, gaining insight into the chondrocytes may be helpful in understanding cartilage function and pinpointing potential therapeutical targets for diseases. The talus is a part of the ankle joint, which serves as the major large joint that bears body weight. Compared with the distal tibial and fibula, the talus bears much more mechanical loading, which is a risk factor for osteoarthritis (OA). However, in most individuals, OA seems to be absent in the ankle, and the cartilage of the talus seems to function normally. This study applied single-cell RNA sequencing to demonstrate atlas for chondrocyte subsets in healthy talus cartilage obtained from five volunteers, and chondrocyte subsets were annotated. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for each cell type, cell-cell interactions, and single-cell regulatory network inference and clustering for each cell type were conducted, and hub genes for each cell type were identified. Immunohistochemical staining was used to confirm the presence and distribution of each cell type. Two new chondrocyte subsets were annotated as MirCs and SpCs. The identified and speculated novel microenvironment may pose different directions in chondrocyte composition, development, and metabolism in the talus.

Directed reconstruction of a novel ancestral alcohol dehydrogenase featuring shifted pH-profile, enhanced thermostability and expanded substrate spectrum.

Ancestral enzymes are promising for industrial biotechnology due to high stability and catalytic promiscuity. An effective protocol was developed for the directed resurrection of ancestral enzymes. Employing genome mining with diaryl alcohol dehydrogenase KpADH as the probe, descendant enzymes D10 and D11 were firstly identified. Then through ancestral sequence reconstruction, A64 was resurrected with a specific activity of 4.3 U·mg-1. The optimum pH of A64 was 7.5, distinct from 5.5 of D10. The T15 50 and Tm values of A64 were 57.5 °C and 61.7 °C, significantly higher than those of the descendant counterpart. Substrate spectrum of A64 was quantitively characterized with a Shannon-Wiener index of 2.38, more expanded than D10, especially, towards bulky ketones in Group A and B. A64 also exhibited higher enantioselectivity. This study provides an effective protocol for constructing of ancestral enzymes and an efficient ancestral enzyme of industrial relevance for asymmetric synthesis of chiral alcohols.