Granulation-embedded autologous skin grafting improves healing chronic wounds at high altitudes: a pilot study.

BACKGROUND: The management of chronic wounds presents a challenge for surgeons. In this pilot study, the authors established a novel auto-grafting approach for chronic wounds and evaluated its efficacy. PURPOSE: The objective of this pilot study was to observe the clinical efficacy of granulation-embedded skin grafting for the treatment of chronic wounds at high altitudes. METHODS: The data of 45 patients with chronic wounds were obtained from the medical records of the Yushu People's Hospital. Patients were divided into stamp skin-grafting and granulation-embedded skin-grafting groups. Skin graft survival rate, wound coverage rate, and wound-healing time were observed and recorded. The length of hospital stay and 1% total body surface area (TBSA) treatment cost were compared. RESULTS: Significant differences were noted in skin graft survival rate (94% ± 3% vs 86% ± 3%, P < .01), wound coverage rate on postoperative day 7 (61% ± 16% vs 54% ± 18%, P < .01), and wound-healing times (23 ± 2.52 days vs 31 ± 3.61 days, P < .05). The length of hospital stay and 1% TBSA treatment cost were significantly reduced in the granulation-embedded skin grafting group (P < .05). CONCLUSIONS: Granulation-embedded skin grafting can improve the healing of chronic wounds at high altitudes. These findings provide a new approach to the clinical treatment of chronic wounds.

Borg extrachromosomal elements of methane-oxidizing archaea have conserved and expressed genetic repertoires.

Borgs are huge extrachromosomal elements (ECE) of anaerobic methane-consuming "Candidatus Methanoperedens" archaea. Here, we used nanopore sequencing to validate published complete genomes curated from short reads and to reconstruct new genomes. 13 complete and four near-complete linear genomes share 40 genes that define a largely syntenous genome backbone. We use these conserved genes to identify new Borgs from peatland soil and to delineate Borg phylogeny, revealing two major clades. Remarkably, Borg genes encoding nanowire-like electron-transferring cytochromes and cell surface proteins are more highly expressed than those of host Methanoperedens, indicating that Borgs augment the Methanoperedens activity in situ. We reconstructed the first complete 4.00 Mbp genome for a Methanoperedens that is inferred to be a Borg host and predicted its methylation motifs, which differ from pervasive TC and CC methylation motifs of the Borgs. Thus, methylation may enable Methanoperedens to distinguish their genomes from those of Borgs. Very high Borg to Methanoperedens ratios and structural predictions suggest that Borgs may be capable of encapsulation. The findings clearly define Borgs as a distinct class of ECE with shared genomic signatures, establish their diversification from a common ancestor with genetic inheritance, and raise the possibility of periodic existence outside of host cells.

Tbxt alleviates senescence and apoptosis of nucleus pulposus cells through Atg7 mediated autophagy activation during intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) is a significant cause of low back pain, characterized by excessive senescence and apoptosis of nucleus pulposus cells (NPCs). However, the precise mechanisms behind this senescence and apoptosis remains unclear. This study aimed to investigate the role of Tbxt in IDD both in vitro and in vivo, using a hydrogen peroxide (H2O2)-induced NPCs senescence and apoptosis model, as well as a rat acupuncture IDD model. Firstly, the expression of p16 and cleaved-caspase 3 significantly increased in degenerated human NPCs, accompanied by a decrease in Tbxt expression. Knockdown of Tbxt exacerbated senescence and apoptosis in the H2O2-induced NPCs degeneration model. Conversely, upregulation of Tbxt alleviated these effects induced by H2O2. Mechanistically, bioinformatic analysis revealed that the direct downstream target genes of Tbxt were highly enriched in autophagy-related pathways and overexpression of Tbxt significantly activated autophagy in NPCs. Moreover, the administration of the autophagy inhibitor, 3-methyladenine, impeded the impact of Tbxt on the processes of senescence and apoptosis in NPCs. Further investigation revealed that Tbxt enhances autophagy by facilitating the transcription of ATG7 through its interaction with a specific motif within the promoter region. In conclusion, this study suggests that Tbxt mitigates H2O2-induced senescence and apoptosis of NPCs by activating ATG7-mediated autophagy.

Deep graph contrastive learning model for drug-drug interaction prediction.

Drug-drug interaction (DDI) is the combined effects of multiple drugs taken together, which can either enhance or reduce each other's efficacy. Thus, drug interaction analysis plays an important role in improving treatment effectiveness and patient safety. It has become a new challenge to use computational methods to accelerate drug interaction time and reduce its cost-effectiveness. The existing methods often do not fully explore the relationship between the structural information and the functional information of drug molecules, resulting in low prediction accuracy for drug interactions, poor generalization, and other issues. In this paper, we propose a novel method, which is a deep graph contrastive learning model for drug-drug interaction prediction (DeepGCL for brevity). DeepGCL incorporates a contrastive learning component to enhance the consistency of information between different views (molecular structure and interaction network), which means that the DeepGCL model predicts drug interactions by integrating molecular structure features and interaction network topology features. Experimental results show that DeepGCL achieves better performance than other methods in all datasets. Moreover, we conducted many experiments to analyze the necessity of each component of the model and the robustness of the model, which also showed promising results. The source code of DeepGCL is freely available at https://github.com/jzysj/DeepGCL.

Prediction of the axillary lymph-node metastatic burden of breast cancer by 18F-FDG PET/CT-based radiomics.

BACKGROUND: The axillary lymph-node metastatic burden is closely associated with treatment decisions and prognosis in breast cancer patients. This study aimed to explore the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT)-based radiomics in combination with ultrasound and clinical pathological features for predicting axillary lymph-node metastatic burden in breast cancer. METHODS: A retrospective analysis was conducted and involved 124 patients with pathologically confirmed early-stage breast cancer who had undergone 18F-FDG PET/CT examination. The ultrasound, PET/CT, and clinical pathological features of all patients were analysed, and radiomic features from PET images were extracted to establish a multi-parameter predictive model. RESULTS: The ultrasound lymph-node positivity rate and PET lymph-node positivity rate in the high nodal burden group were significantly higher than those in the low nodal burden group (χ2 = 19.867, p < 0.001; χ2 = 33.025, p < 0.001). There was a statistically significant difference in the PET-based radiomics score (RS) for predicting axillary lymph-node burden between the high and low lymph-node burden groups. (-1.04 ± 0.41 vs. -1.47 ± 0.41, t = -4.775, p < 0.001). The ultrasound lymph-node positivity (US_LNM) (odds ratio [OR] = 3.264, 95% confidence interval [CI] = 1.022-10.423), PET lymph-node positivity (PET_LNM) (OR = 14.242, 95% CI = 2.960-68.524), and RS (OR = 5.244, 95% CI = 3.16-20.896) are all independent factors associated with high lymph-node burden (p < 0.05). The area under the curve (AUC) of the multi-parameter (MultiP) model was 0.895, which was superior to those of US_LNM, PET_LNM, and RS models (AUC = 0.703, 0.814, 0.773, respectively), with statistically significant differences (Z = 2.888, 3.208, 3.804, respectively; p = 0.004, 0.002, < 0.001, respectively). Decision curve analysis indicated that the MultiP model provided a higher net benefit for all patients. CONCLUSION: A MultiP model based on PET-based radiomics was able to effectively predict axillary lymph-node metastatic burden in breast cancer. TRIAL REGISTRATION: This study was registered with ClinicalTrials.gov (registration number: NCT05826197) on May 7, 2023.

Bidirectional regulation of levodopa-induced dyskinesia by a specific neural ensemble in globus pallidus external segment.

Levodopa-induced dyskinesia (LID) is an intractable motor complication arising in Parkinson's disease with the progression of disease and chronic treatment of levodopa. However, the specific cell assemblies mediating dyskinesia have not been fully elucidated. Here, we utilize the activity-dependent tool to identify three brain regions (globus pallidus external segment [GPe], parafascicular thalamic nucleus, and subthalamic nucleus) that specifically contain dyskinesia-activated ensembles. An intensity-dependent hyperactivity in the dyskinesia-activated subpopulation in GPe (GPeTRAPed in LID) is observed during dyskinesia. Optogenetic inhibition of GPeTRAPed in LID significantly ameliorates LID, whereas reactivation of GPeTRAPed in LID evokes dyskinetic behavior in the levodopa-off state. Simultaneous chemogenetic reactivation of GPeTRAPed in LID and another previously reported ensemble in striatum fully reproduces the dyskinesia induced by high-dose levodopa. Finally, we characterize GPeTRAPed in LID as a subset of prototypic neurons in GPe. These findings provide theoretical foundations for precision medication and modulation of LID in the future.

The shared circulating diagnostic biomarkers and molecular mechanisms of systemic lupus erythematosus and inflammatory bowel disease.

Background: Systemic lupus erythematosus (SLE) is a multi-organ chronic autoimmune disease. Inflammatory bowel disease (IBD) is a common chronic inflammatory disease of the gastrointestinal tract. Previous studies have shown that SLE and IBD share common pathogenic pathways and genetic susceptibility, but the specific pathogenic mechanisms remain unclear. Methods: The datasets of SLE and IBD were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified using the Limma package. Weighted gene coexpression network analysis (WGCNA) was used to determine co-expression modules related to SLE and IBD. Pathway enrichment was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis for co-driver genes. Using the Least AbsoluteShrinkage and Selection Operator (Lasso) regressionand Support Vector Machine-Recursive Feature Elimination (SVM-RFE), common diagnostic markers for both diseases were further evaluated. Then, we utilizedthe CIBERSORT method to assess the abundance of immune cell infiltration. Finally,we used the single-cell analysis to obtain the location of common diagnostic markers. Results: 71 common driver genes were identified in the SLE and IBD cohorts based on the DEGs and module genes. KEGG and GO enrichment results showed that these genes were closely associated with positive regulation of programmed cell death and inflammatory responses. By using LASSO regression and SVM, five hub genes (KLRF1, GZMK, KLRB1, CD40LG, and IL-7R) were ultimately determined as common diagnostic markers for SLE and IBD. ROC curve analysis also showed good diagnostic performance. The outcomes of immune cell infiltration demonstrated that SLE and IBD shared almost identical immune infiltration patterns. Furthermore, the majority of the hub genes were commonly expressed in NK cells by single-cell analysis. Conclusion: This study demonstrates that SLE and IBD share common diagnostic markers and pathogenic pathways. In addition, SLE and IBD show similar immune cellinfiltration microenvironments which provides newperspectives for future treatment.

Brachyury promotes extracellular matrix synthesis through transcriptional regulation of Smad3 in nucleus pulposus.

Metabolic dysfunction of the extracellular matrix (ECM) is one of the primary causes of intervertebral disc degeneration (IVDD). Previous studies have demonstrated that the transcription factor Brachyury (Bry) has the potential to promote the synthesis of collagen II and aggrecan, while the specific mechanism is still unknown. In this study, we used a lipopolysaccharide (LPS)-induced model of nucleus pulposus cell (NPC) degeneration and a rat acupuncture IVDD model to elucidate the precise mechanism through which Bry affects collagen II and aggrecan synthesis in vitro and in vivo. First, we confirmed Bry expression decreased in degenerated human nucleus pulposus (NP) cells (NPCs). Knockdown of Bry exacerbated the decrease in collagen II and aggrecan expression in the lipopolysaccharide (LPS)-induced NPCs degeneration in vitro model. Bioinformatic analysis indicated that Smad3 may participate in the regulatory pathway of ECM synthesis regulated by Bry. Chromatin immunoprecipitation followed by quantitative polymerase chain reaction (ChIP-qPCR) and luciferase reporter gene assays demonstrated that Bry enhances the transcription of Smad3 by interacting with a specific motif on the promoter region. In addition, Western blot and reverse transcription-qPCR assays demonstrated that Smad3 positively regulates the expression of aggrecan and collagen II in NPCs. The following rescue experiments revealed that Bry-mediated regulation of ECM synthesis is partially dependent on Smad3 phosphorylation. Finally, the findings from the in vivo rat acupuncture-induced IVDD model were consistent with those obtained from in vitro assays. In conclusion, this study reveals that Bry positively regulates the synthesis of collagen II and aggrecan in NP through transcriptional activation of Smad3.NEW & NOTEWORTHY Mechanically, in the nucleus, Bry enhances the transcription of Smad3, leading to increased expression of Smad3 protein levels; in the cytoplasm, elevated substrate levels further lead to an increase in the phosphorylation of Smad3, thereby regulating collagen II and aggrecan expression. Further in vivo experiments provide additional evidence that Bry can alleviate IVDD through this mechanism.

Non-specific uptake of 18F-FAPI-04 in the pancreas and its related factors: a post-hoc analysis of an ongoing prospective clinical trial.

This study aimed to analyze the characteristics of the non-specific uptake (NSU) of 18F-labeled fibroblast activation protein inhibitor (18F-FAPI) of the pancreas and investigate the related factors. Totally, 78 patients who underwent both 18F-fluorodeoxyglucose (FDG) and 18F-FAPI PET/CT examinations were divided into normal (n = 53) and NSU (n = 25) groups. The differences in general information, medical history, laboratory indexes and uptake were compared. Receiver operating characteristic (ROC) curves were used to analyze the optimal cut-off values. The correlations between 18F-FAPI-SUVmax and blood cell analysis, liver function indexes, tumor markers, and inflammatory indices were analyzed. The logistic regression model was used to estimate the independent factors. Both 18F-FAPI (4.48 ± 0.98 vs. 2.01 ± 0.53, t = 11.718, P < 0.05) and 18F-FDG (2.23 ± 0.42 vs. 2.02 ± 0.44, t = 2.036, P = 0.045) showed significantly higher in NSU group. Patients in the NSU group tended to be complicated with a history of drinking (P = 0.034), chronic liver diseases (P = 0.006), and surgery of gastrectomy (P = 0.004). ROC analysis showed cutoff values of 3.25 and 2.05 for 18F-FAPI and 18F-FDG in identifying the NSU. Patients in the NSU group showed less platelet count, higher platelet volume, higher total bilirubin, direct or indirect bilirubin (P < 0.05). Platelet count, platelet crit, large platelet ratio, aspartate aminotransferase (AST), α-L-fucosidase, and total, direct or indirect bilirubin were correlated with 18F-FAPI-SUVmax (P < 0.05). AST [1.099 (1.014, 1.192), P = 0.021] and total bilirubin [1.137 (1.035, 1.249), P = 0.007] were two independent factors in the step forward logistic regression, and platelet/% [1.079 (1.004, 1.160), P = 0.039] and total bilirubin [1.459 (1.016, 2.095), P = 0.041] were two independent factors in the step backward logistic regression for the prediction of pancreatic uptake of 18F-FAPI. 18F-FAPI-PET/CT was better than 18F-FDG in predicting the pancreatic NSU, and NSU is related to a history of drinking, chronic liver diseases, gastrectomy, heteromorphic platelet, and impaired liver function.

Emergence and ongoing outbreak of ST80 vancomycin-resistant Enterococcus faecium in Guangdong province, China from 2021 to 2023: a multicenter, time-series and genomic epidemiological study.

BACKGROUND: Surveillance systems revealed that the prevalence of vancomycin-resistant Enterococcus faecium (VREfm) has increased. We aim to investigate the epidemiological and genomic characteristics of VREfm in China. METHODS: We collected 20,747 non-redundant E. faecium isolates from inpatients across 19 hospitals in six provinces between January 2018 and June 2023. VREfm was confirmed by antimicrobial susceptibility testing. The prevalence was analyzed using changepoint package in R. Genomic characteristics were explored by whole-genome sequencing. RESULTS: 5.59% (1159/20,747) of E. faecium isolates were resistant to vancomycin. The prevalence of VREfm increased in Guangdong province from 5% before 2021 to 20-50% in 2023 (p < 0.0001), but not in the other five provinces. Two predominant clones before 2021, ST17 and ST78, were substituted by an emerging clone, ST80, from 2021 to 2023 (88.63%, 195/220). All ST80 VREfm from Guangdong formed a single lineage (SC11) and were genetically distant from the ST80 VREfm from other countries, suggesting a regional outbreak. All ST80 VREfm in SC11 carried a new type of plasmid harbouring a vanA cassette, which was embedded in a Tn1546-like structure flanked by IS1678 and ISL3. However, no conjugation-related gene was detected and no transconjugant was obtained in conjugation experiment, indicating that the outbreak of ST80 VREfm could be attributed to clonal transmission. CONCLUSIONS: We revealed an ongoing outbreak of ST80 VREfm with a new vanA-harbouring plasmid in Guangdong, China. This clone has also been identified in other provinces and countries, foreboding a risk of wider spreading shortly. Continuous surveillance is needed to inform public health interventions.

Room-Temperature Growth of Square-Millimeter Single-Crystalline Two-Dimensional Metal Halides on Silicon.

Silicon is the cornerstone of electronics and photonics. In this context, almost all integrated devices derived from two-dimensional (2D) materials stay rooted in silicon technology. However, as the growth substrate, silicon has long been thought to be a hindrance for growing 2D materials through bottom-up methods that require high growth temperatures, and thus, indirect routes are usually considered instead. Although promising growth of large-area 2D materials on silicon has been demonstrated, the direct growth of single-crystalline materials using low-thermal-budget synthesis methods remains challenging. Here, we report the room-temperature growth of millimeter-scale single-crystal 2D metal halides on silicon substrates with a hydroxyl-terminated surface. Theoretical calculations reveal that the activation energy for surface diffusion can be reduced by an order of magnitude by terminating the surface with hydroxyl groups, from which on-silicon growth is greatly facilitated at room temperature and enables a 4-order-of-magnitude increase in area. The high quality and uniformity of the resulting single crystals are further evidenced. The optoelectronic devices employing the as-grown materials show an ultralow dark current of 10-13 A and a high detectivity of 1013 Jones, thereby corroborating a weak-light detection ability. These results would point to a rich space of surface modulation that can be used to surmount current limitations and demonstrate a promising strategy for growing 2D materials directly on silicon at room temperature to produce large single crystals.

Determination of pulmonary vessel alteration in Chinese male smokers by quantitative computed tomography measurements: a retrospective study.

Background: The blood volume of intraparenchymal vessels is reported to be increased in smokers. However, the blood volume can be affected by many confounders besides tobacco exposure. This study aimed to investigate the association between cigarette smoking and pulmonary blood volume after adjusting the related factors in a large cohort of Chinese males. Methods: In this retrospective study, male participants admitted to the First Affiliated Hospital of Xi'an Jiaotong University for annual health assessment between February 2017 and February 2018 were enrolled. All subjects underwent non-contrast chest computed tomography (CT) scans, and 152 subjects underwent a review CT scan 2-3 years later. A three-dimensional approach was employed to segment the lung and intrapulmonary vessels and quantitative CT (QCT) measurements, including lung volume (LV), intrapulmonary vessel volume (IPVV), low-attenuation area <-950 Hounsfield unit (LAA-950 and LAA-950%), and mean lung density (MLD). Linear regression was used to estimate the association between IPVV and the smoking index (SI). A paired t-test was used to compare the QCT parameters between the initial and follow-up CT scans. Results: A total of 656 male participants were enrolled and classified into three subgroups: non-smokers (n=311), current smokers (n=267), and former smokers (n=78). The IPVV of current smokers (134.62±23.96 vs. 120.76±25.52 mL) and former smokers (130.79±25.13 vs. 120.76±25.52 mL) were significantly larger than that of non-smokers (P<0.05). A higher SI was associated with greater IPVV [non-standardized coefficient: 0.167, 95% confidence interval (CI): 0.086-0.248]. For current smokers, the IPVV of the follow-up scan significantly increased compared to its baseline scan (135.49±28.60 vs. 129.73±29.75 mL, t=-2.326, P=0.02), but for the non-smokers and former smokers, the IPVV of the follow-up scan did not increase or decrease compared to the baseline scan (P>0.05). Conclusions: Pulmonary vascular volumes detectable on non-contrast CT are associated with cigarette exposure, and smoking cessation may prevent pulmonary vasculature remodeling.

Stereoscopic artificial compound eyes for spatiotemporal perception in three-dimensional space.

Arthropods' eyes are effective biological vision systems for object tracking and wide field of view because of their structural uniqueness; however, unlike mammalian eyes, they can hardly acquire the depth information of a static object because of their monocular cues. Therefore, most arthropods rely on motion parallax to track the object in three-dimensional (3D) space. Uniquely, the praying mantis (Mantodea) uses both compound structured eyes and a form of stereopsis and is capable of achieving object recognition in 3D space. Here, by mimicking the vision system of the praying mantis using stereoscopically coupled artificial compound eyes, we demonstrated spatiotemporal object sensing and tracking in 3D space with a wide field of view. Furthermore, to achieve a fast response with minimal latency, data storage/transportation, and power consumption, we processed the visual information at the edge of the system using a synaptic device and a federated split learning algorithm. The designed and fabricated stereoscopic artificial compound eye provides energy-efficient and accurate spatiotemporal object sensing and optical flow tracking. It exhibits a root mean square error of 0.3 centimeter, consuming only approximately 4 millijoules for sensing and tracking. These results are more than 400 times lower than conventional complementary metal-oxide semiconductor-based imaging systems. Our biomimetic imager shows the potential of integrating nature's unique design using hardware and software codesigned technology toward capabilities of edge computing and sensing.

Ex vivo liver resection and auto-transplantation as an alternative for the treatment of liver malignancies: Progress and challenges.

Hepatectomy is still the major curative treatment for patients with liver malignancies. However, it is still a big challenge to remove the tumors in the central posterior area, especially if their location involves the retrohepatic inferior vena cava and hepatic veins. Ex vivo liver resection and auto-transplantation (ELRA), a hybrid technique of the traditional liver resection and transplantation, has brought new hope to these patients and therefore becomes a valid alternative to liver transplantation. Due to its technical difficulty, ELRA is still concentrated in a few hepatobiliary centers that have experienced surgeons in both liver resection and liver transplantation. The efficacy and safety of this technique has already been demonstrated in the treatment of benign liver diseases, especially in the advanced alveolar echinococcosis. Recently, the application of ELRA for liver malignances has gained more attention. However, standardization of clinical practice norms and international consensus are still lacking. The prognostic impact in these oncologic patients also needs further evaluation. In this review, we summarized the principles and recent progresses on ELRA.

Vision-Based On-Road Nighttime Vehicle Detection and Tracking Using Improved HOG Features.

The lack of discernible vehicle contour features in low-light conditions poses a formidable challenge for nighttime vehicle detection under hardware cost constraints. Addressing this issue, an enhanced histogram of oriented gradients (HOGs) approach is introduced to extract relevant vehicle features. Initially, vehicle lights are extracted using a combination of background illumination removal and a saliency model. Subsequently, these lights are integrated with a template-based approach to delineate regions containing potential vehicles. In the next step, the fusion of superpixel and HOG (S-HOG) features within these regions is performed, and the support vector machine (SVM) is employed for classification. A non-maximum suppression (NMS) method is applied to eliminate overlapping areas, incorporating the fusion of vertical histograms of symmetrical features of oriented gradients (V-HOGs). Finally, the Kalman filter is utilized for tracking candidate vehicles over time. Experimental results demonstrate a significant improvement in the accuracy of vehicle recognition in nighttime scenarios with the proposed method.

All-Inorganic Perovskite Solar Cells: Defect Regulation and Emerging Applications in Extreme Environments.

All-inorganic perovskite solar cells (PSCs), such as CsPbX3, have garnered considerable attention recently, as they exhibit superior thermodynamic and optoelectronic stabilities compared to the organic-inorganic hybrid PSCs. However, the power conversion efficiency (PCE) of CsPbX3 PSCs is generally lower than that of organic-inorganic hybrid PSCs, as they contain higher defect densities at the interface and within the perovskite light-absorbing layers, resulting in higher non-radiative recombination and voltage loss. Consequently, defect regulation has been adopted as an important strategy to improve device performance and stability. This review aims to comprehensively summarize recent progresses on the defect regulation in CsPbX3 PSCs, as well as their cutting-edge applications in extreme scenarios. The underlying fundamental mechanisms leading to the defect formation in the crystal structure of CsPbX3 PSCs are firstly discussed, and an overview of literature-adopted defect regulation strategies in the context of interface, internal, and surface engineering is provided. Cutting-edge applications of CsPbX3 PSCs in extreme environments such as outer space and underwater situations are highlighted. Finally, a summary and outlook are presented on future directions for achieving higher efficiencies and superior stability in CsPbX3 PSCs.

Widespread extracellular electron transfer pathways for charging microbial cytochrome OmcS nanowires via periplasmic cytochromes PpcABCDE.

Extracellular electron transfer (EET) via microbial nanowires drives globally-important environmental processes and biotechnological applications for bioenergy, bioremediation, and bioelectronics. Due to highly-redundant and complex EET pathways, it is unclear how microbes wire electrons rapidly (>106 s-1) from the inner-membrane through outer-surface nanowires directly to an external environment despite a crowded periplasm and slow (<105 s-1) electron diffusion among periplasmic cytochromes. Here, we show that Geobacter sulfurreducens periplasmic cytochromes PpcABCDE inject electrons directly into OmcS nanowires by binding transiently with differing efficiencies, with the least-abundant cytochrome (PpcC) showing the highest efficiency. Remarkably, this defined nanowire-charging pathway is evolutionarily conserved in phylogenetically-diverse bacteria capable of EET. OmcS heme reduction potentials are within 200 mV of each other, with a midpoint 82 mV-higher than reported previously. This could explain efficient EET over micrometres at ultrafast (<200 fs) rates with negligible energy loss. Engineering this minimal nanowire-charging pathway may yield microbial chassis with improved performance.

Curvature-enhanced graph convolutional network for biomolecular interaction prediction.

Geometric deep learning has demonstrated a great potential in non-Euclidean data analysis. The incorporation of geometric insights into learning architecture is vital to its success. Here we propose a curvature-enhanced graph convolutional network (CGCN) for biomolecular interaction prediction. Our CGCN employs Ollivier-Ricci curvature (ORC) to characterize network local geometric properties and enhance the learning capability of GCNs. More specifically, ORCs are evaluated based on the local topology from node neighborhoods, and further incorporated into the weight function for the feature aggregation in message-passing procedure. Our CGCN model is extensively validated on fourteen real-world bimolecular interaction networks and analyzed in details using a series of well-designed simulated data. It has been found that our CGCN can achieve the state-of-the-art results. It outperforms all existing models, as far as we know, in thirteen out of the fourteen real-world datasets and ranks as the second in the rest one. The results from the simulated data show that our CGCN model is superior to the traditional GCN models regardless of the positive-to-negative-curvature ratios, network densities, and network sizes (when larger than 500).

Detection of peach soluble solids based on near-infrared spectroscopy with High Order Spatial Interaction network.

BACKGROUND: Due to the scalability of deep learning technology, researchers have applied it to the non-destructive testing of peach internal quality. In addition, the soluble solids content (SSC) is an important internal quality indicator that determines the quality of peaches. Peaches with high SSC have a sweeter taste and better texture, making them popular in the market. Therefore, SSC is an important indicator for measuring peach internal quality and making harvesting decisions. RESULTS: This article presents the High Order Spatial Interaction Network (HOSINet), which combines the Position Attention Module (PAM) and Channel Attention Module (CAM). Additionally, a feature wavelength selection algorithm similar to the Group-based Clustering Subspace Representation (GCSR-C) is used to establish the Position and Channel Attention Module-High Order Spatial Interaction (PC-HOSI) model for peach SSC prediction. The accuracy of this model is compared with traditional machine learning and traditional deep learning models. Finally, the permutation algorithm is combined with deep learning models to visually evaluate the importance of feature wavelengths. Increasing the order of the PC-HOSI model enhances its ability to learn spatial correlations in the dataset, thus improving its predictive performance. CONCLUSION: The optimal model, PC-HOSI model, performed well with an order of 3 (PC-HOSI-3), with a root mean square error of 0.421 °Brix and a coefficient of determination of 0.864. Compared with traditional machine learning and deep learning algorithms, the coefficient of determination for the prediction set was improved by 0.07 and 0.39, respectively. The permutation algorithm also provided interpretability analysis for the predictions of the deep learning model, offering insights into the importance of spectral bands. These results contribute to the accurate prediction of SSC in peaches and support research on interpretability of neural network models for prediction. © 2024 Society of Chemical Industry.