A chitosan-based light-curing hydrogel dressing for accelerated healing of infected wounds.

Bacterial infections, excessive reactive oxygen species (ROS) accumulation and a persistent inflammatory response severely impede the wound healing process. In this study, we developed a novel multifunctional hydrogel dressing (LCPN) based on lipoic acid modified chitosan (LAMC), polypyrrole nanoparticles (PPy NPs) and nicotinamide mononucleotide (NMN) for accelerated healing of infected wounds. The synthesized LCPN hydrogel has several properties. Modification of lipoic acid significantly enhances the water solubility of chitosan making it easier to dissolve and absorb wound secretions. Interestingly, owing to the breaking and restructuring of disulfide bonds, LCPN can be quickly bonded under UV light without relying on photoinitiators. In addition, the incorporation of PPy NPs not only enhances the electrical conductivity of LCPN hydrogel, but also confers photothermal antimicrobial capability to LCPN hydrogel. More importantly, the sustained release of NMN in LCPN hydrogel can significantly enhance cell proliferation, migration and antioxidant capacity, which is conducive to accelerated wound healing. In vivo and in vitro experiments have shown that LCPN hydrogel has excellent biocompatibility and the ability to promote wound healing. Therefore, the prepared multifunctional hydrogel is expected to be used as a novel dressing to accelerate wound healing.

TetR family regulator AbrT controls lincomycin production and morphological development in Streptomyces lincolnensis.

BACKGROUND: The TetR family of transcriptional regulators (TFRs), serving as crucial regulators of diverse cellular processes, undergo conformational changes induced by small-molecule ligands, which either inhibit or activate them to modulate target gene expression. Some ligands of TFRs in actinomycetes and their regulatory effects have been identified and studied; however, regulatory mechanisms of the TetR family in the lincomycin-producing Streptomyces lincolnensis remain poorly understood. RESULTS: In this study, we found that AbrT (SLCG_1979), a TetR family regulator, plays a pivotal role in regulating lincomycin production and morphological development in S. lincolnensis. Deletion of abrT gene resulted in increased lincomycin A (Lin-A) production, but delayed mycelium formation and sporulation on solid media. AbrT directly or indirectly repressed the expression of lincomycin biosynthetic (lin) cluster genes and activated that of the morphological developmental genes amfC, whiB, and ftsZ. We demonstrated that AbrT bound to two motifs (5'-CGCGTACTCGTA-3' and 5'-CGTACGATAGCT-3') present in the bidirectional promoter between abrT and SLCG_1980 genes. This consequently repressed abrT itself and its adjacent gene SLCG_1980 that encodes an arabinose efflux permease. D-arabinose, not naturally occurring as L-arabinose, was identified as the effector molecule of AbrT, reducing its binding affinity to abrT-SLCG_1980 intergenic region. Furthermore, based on functional analysis of the AbrT homologue in Saccharopolyspora erythraea, we inferred that the TetR family regulator AbrT may play an important role in regulating secondary metabolism in actinomycetes. CONCLUSIONS: AbrT functions as a regulator for governing lincomycin production and morphological development of S. lincolnensis. Our findings demonstrated that D-arabinose acts as a ligand of AbrT to mediate the regulation of lincomycin biosynthesis in S. lincolnensis. Our findings provide novel insights into ligand-mediated regulation in antibiotic biosynthesis.

Immunotherapeutic hydrogel for co-delivery of STAT3 siRNA liposomes and lidocaine hydrochloride for postoperative comprehensive management of NSCLC in a single application.

Despite standard treatment for non-small cell lung cancer (NSCLC) being surgical resection, cancer recurrence and complications, such as induction of malignant pleural effusion (MPE) and significant postoperative pain, usually result in treatment failure. In this study, an alginate-based hybrid hydrogel (SOG) is developed that can be injected into the resection surface of the lungs during surgery. Briefly, endoplasmic reticulum-modified liposomes (MSLs) pre-loaded with the signal transducer and activator of transcription 3 (STAT3) small interfering RNA and lidocaine hydrochloride are encapsulated in SOG. Once applied, MSLs strongly downregulated STAT3 expression in the tumor microenvironment, resulting in the apoptosis of lung cancer cells and polarization of tumor-associated macrophages towards the M1-like phenotype. Meanwhile, the release of lidocaine hydrochloride (LID) was beneficial for pain relief and natural killer cell activation. Our data demonstrated MSL@LID@SOG not only efficiently inhibited tumor growth but also potently improved the quality of life, including reduced MPE volume and pain relief in orthotopic NSCLC mouse models, even with a single administration. MSL@LID@SOG shows potential for comprehensive clinical management upon tumor resection in NSCLC, and may alter the treatment paradigms for other cancers.

Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness.

The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.

Canonical and non-canonical functions of p53 isoforms: potentiating the complexity of tumor development and therapy resistance.

Full-length p53 (p53α) plays a pivotal role in maintaining genomic integrity and preventing tumor development. Over the years, p53 was found to exist in various isoforms, which are generated through alternative splicing, alternative initiation of translation, and internal ribosome entry site. p53 isoforms, either C-terminally altered or N-terminally truncated, exhibit distinct biological roles compared to p53α, and have significant implications for tumor development and therapy resistance. Due to a lack of part and/or complete C- or N-terminal domains, ectopic expression of some p53 isoforms failed to induce expression of canonical transcriptional targets of p53α like CDKN1A or MDM2, even though they may bind their promoters. Yet, p53 isoforms like Δ40p53α still activate subsets of targets including MDM2 and BAX. Furthermore, certain p53 isoforms transactivate even novel targets compared to p53α. More recently, non-canonical functions of p53α in DNA repair and of different isoforms in DNA replication unrelated to transcriptional activities were discovered, amplifying the potential of p53 as a master regulator of physiological and tumor suppressor functions in human cells. Both regarding canonical and non-canonical functions, alternative p53 isoforms frequently exert dominant negative effects on p53α and its partners, which is modified by the relative isoform levels. Underlying mechanisms include hetero-oligomerization, changes in subcellular localization, and aggregation. These processes ultimately influence the net activities of p53α and give rise to diverse cellular outcomes. Biological roles of p53 isoforms have implications for tumor development and cancer therapy resistance. Dysregulated expression of isoforms has been observed in various cancer types and is associated with different clinical outcomes. In conclusion, p53 isoforms have expanded our understanding of the complex regulatory network involving p53 in tumors. Unraveling the mechanisms underlying the biological roles of p53 isoforms provides new avenues for studies aiming at a better understanding of tumor development and developing therapeutic interventions to overcome resistance.

BiPLS-RF: A hybrid wavelength selection strategy for laser induced fluorescence spectroscopy of power transformer oil.

In this paper, a method for indirect diagnosis of transformer faults based on the fluorescence spectrum and characteristic wavelength screening of transformer oil has been proposed. Specifically, a hybrid strategy (BiPLS-RF) for establishing the fluorescence spectrum feature screening of transformer oil using backward interval partial least squares (BiPLS) and random forest (RF) has been proposed. Aiming at the problem of transformer fault diagnosis, the laser induced fluorescence (LIF) spectroscopy of transformer oil in different states was first collected, and it is found that the fluorescence spectrum intensity of normal transformer oil was stronger than that of faulty transformer oil. Then the characteristic bands of the original fluorescence spectra were screened by BiPLS. It is found that when the original fluorescence spectra were divided into 15 sub-intervals, the minimum root mean squares error of cross-validation can be obtained by selecting 3 sub-intervals (including 411 wavelengths). On this basis, RF was employed to further screen the characteristic wavelengths and realized the identification of the fluorescence spectrum. It is found that in the RF model composed of 54 trees, the selected 196 characteristic wavelengths of the fluorescence spectrum can minimize the analysis error (0.56%). In addition, the selected characteristic wavelength information was fed into other common classifiers to construct a fluorescence spectrum identification model, which further proved the effectiveness of BiPLS-RF for wavelength selection for LIF spectroscopy of power transformer oil. The results show that it is feasible to use BiPLS-RF to screen the characteristic wavelength of LIF spectroscopy and apply it to transformer fault diagnosis, which provides a new solution for transformer fault diagnosis.

Developing a novel causal inference algorithm for personalized biomedical causal graph learning using meta machine learning.

BACKGROUND: Modeling causality through graphs, referred to as causal graph learning, offers an appropriate description of the dynamics of causality. The majority of current machine learning models in clinical decision support systems only predict associations between variables, whereas causal graph learning models causality dynamics through graphs. However, building personalized causal graphs for each individual is challenging due to the limited amount of data available for each patient. METHOD: In this study, we present a new algorithmic framework using meta-learning for learning personalized causal graphs in biomedicine. Our framework extracts common patterns from multiple patient graphs and applies this information to develop individualized graphs. In multi-task causal graph learning, the proposed optimized initial guess of shared commonality enables the rapid adoption of knowledge to new tasks for efficient causal graph learning. RESULTS: Experiments on one real-world biomedical causal graph learning benchmark data and four synthetic benchmarks show that our algorithm outperformed the baseline methods. Our algorithm can better understand the underlying patterns in the data, leading to more accurate predictions of the causal graph. Specifically, we reduce the structural hamming distance by 50-75%, indicating an improvement in graph prediction accuracy. Additionally, the false discovery rate is decreased by 20-30%, demonstrating that our algorithm made fewer incorrect predictions compared to the baseline algorithms. CONCLUSION: To the best of our knowledge, this is the first study to demonstrate the effectiveness of meta-learning in personalized causal graph learning and cause inference modeling for biomedicine. In addition, the proposed algorithm can also be generalized to transnational research areas where integrated analysis is necessary for various distributions of datasets, including different clinical institutions.

Corrosion Behavior of Ni-Cr Alloys with Different Cr Contents in NaCl-KCl-MgCl2.

This study investigates the corrosion behavior of Ni-Cr binary alloys, including Ni-10Cr, Ni-15Cr, Ni-20Cr, Ni-25Cr, and Ni-30Cr, in a NaCl-KCl-MgCl2 molten salt mixture through gravimetric analysis. Corrosion tests were conducted at 700 °C, with the maximum immersion time reaching up to 100 h. The corrosion rate was determined by measuring the mass loss of the specimens at various time intervals. Verifying corrosion rates by combining mass loss results with the determination of element dissolution in molten salts using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). Detailed examinations of the corrosion products and morphology were conducted using X-ray diffraction (XRD) and scanning electron microscopy (SEM). Micro-area elemental analysis on the corroded surfaces was performed using an energy dispersive spectrometer (EDS), and the elemental distribution across the corrosion cross-sections was mapped. The results indicate that alloys with lower Cr content exhibit superior corrosion resistance in the NaCl-KCl-MgCl2 molten salt under an argon atmosphere compared to those with higher Cr content; no corrosion products were retained on the surfaces of the lower Cr alloys (Ni-10Cr, Ni-15Cr). For the higher Cr alloys (Ni-20Cr, Ni-25Cr, Ni-30Cr), after 20 h of corrosion, a protective layer was observed in certain areas. The formation of a stable Cr2O3 layer in the initial stages of corrosion for high-Cr content alloys, which reacts with MgO in the molten salt to form a stable MgCr2O4 spinel structure, provides additional protection for the alloys. However, over time, even under argon protection, the MgCr2O4 protective layer gradually degrades due to chloride ion infiltration and chemical reactions at high temperatures. Further analysis revealed that chloride ions play a pivotal role in the corrosion process, not only facilitating the destruction of the Cr2O3 layer on the alloy surfaces but also possibly accelerating the corrosion of the metallic matrix through electrochemical reactions. In conclusion, the corrosion behavior of Ni-Cr alloys in the NaCl-KCl-MgCl2 molten salt environment is influenced by a combination of factors, including Cr content, chloride ion activity, and the formation and degradation of protective layers. This study not only provides new insights into the corrosion resistance of Ni-Cr alloys in high-temperature molten salt environments but also offers significant theoretical support for the design and optimization of corrosion-resistant alloy materials.

The combination of Butyricicoccus pullicaecorum and 3-hydroxyanthranilic acid prevents postmenopausal osteoporosis by modulating gut microbiota and Th17/Treg.

BACKGROUND: Postmenopausal osteoporosis (PMO) is a chronic condition characterized by decreased bone strength. This study aims to investigate the effects and mechanisms of the combination of Butyricicoccus pullicaecorum (Bp) and 3-hydroxyanthranilic acid (3-HAA) on PMO. METHODS: The effects of Bp and 3-HAA on PMO were evaluated in ovariectomized (OVX) rats by assessing stereological parameters, femur microstructure, and autophagy levels. The T helper (Th) 17/Regulatory T (Treg) cells of rats were detected using flow cytometric analysis. Furthermore, the impact of Bp and 3-HAA on the gut microbiota of rats was assessed using 16S rRNA gene sequencing. The correlation between the gut microbiota of rats and Th17/Treg immune factors, as well as femoral stereo parameters, was separately assessed using Spearman rank correlation analysis. RESULTS: Bp and 3-HAA treatments protected OVX rats by promoting osteogenesis and inhibiting autophagy. Compared to the Sham group, OVX rats showed an increase in Th17 cells and a decrease in Treg cells. Bp and 3-HAA reversed these changes. Enterorhabdus and Pseudomonas were significantly enriched in OVX rats. Bp and 3-HAA regulated the gut microbiota of OVX rats, enriching pathways related to nutrient metabolism and immune function. There was a correlation between the gut microbiota and the Th17/Treg, as well as femoral stereo parameters. The concurrent administration of Bp and 3-HAA medication facilitated the enrichment of gut microbiota associated with the improvement of PMO. CONCLUSION: The combination therapy of Bp and 3-HAA can prevent PMO by modulating the gut microbiota and restoring Th17/Treg immune homeostasis.

Preparation and High-Temperature Resistance Properties of Phenolic Resin/Phosphate Hybrid Coatings.

In this study, a novel fabrication method was used to synthesize phenolic resin/phosphate hybrid coatings using aluminum dihydrogen phosphate (Al(H2PO4)3, hereafter denoted as Al), SC101 silica sol (Si) as the primary film-forming agent, and phenolic resin (PF) as the organic matrix. This approach culminated in the formation of Al+Si+PF organo-inorganic hybrid coatings. Fourier-transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) results confirmed the successful integration of hybrid structures within these coatings. The crystalline structure of the coatings post-cured at various temperatures was elucidated using X-ray diffraction (XRD). Additionally, the surface and cross-sectional morphologies were meticulously analyzed using scanning electron microscopy (SEM), offering insights into the microstructural properties of the coatings. The coatings' porosities under diverse thermal and temporal regimes were quantitatively evaluated using advanced image processing techniques, revealing a significant reduction in porosity to a minimum of 5.88% following a thermal oxidation process at 600 °C for 10 h. The antioxidant efficacy of the phosphate coatings was rigorously assessed through cyclic oxidation tests, which revealed their outstanding performance. Specifically, at 300 °C across 300 h of cyclic oxidation, the weight losses recorded for phosphate varnish and the phenolic resin-infused phosphate coatings were 0.15 mg·cm-2 and 0.09 mg·cm-2, respectively. Furthermore, at 600 °C and over an identical period, the weight reduction was noted as 0.21 mg·cm-2 for phosphate varnish and 0.085 mg·cm-2 for the hybrid coatings, thereby substantiating the superior antioxidation capabilities of the phenolic resin hybrid coatings in comparison to the pure phosphate varnish.

Erratum - LncRNA gadd7 promotes mitochondrial membrane potential decrease and apoptosis of alveolar type II epithelial cells by positively regulating MFN1 in an in vitro model of hyperoxia-induced acute lung injury.

This corrects the article published in European Journal of Histochemistry 2023;67:3535. doi: 10.4081/ejh.2023.3535.

Association between illness perception and social alienation among maintenance hemodialysis patients: The mediating role of fear of progression.

PURPOSE: This study aimed to investigate the mediating role of fear of progression on illness perception and social alienation among maintenance hemodialysis (MHD) patients. BACKGROUND: MHD is frequently accompanied by increased pain and complications such as itchy skin, chronic fatigue, and muscle spasms. Cardiovascular disease rates are also elevated among MHD patients, which can heighten their anxiety regarding prognosis and treatment discomfort. This chronic fear may severely impact social functioning, leading patients to withdraw from interpersonal interactions and experience heightened helplessness and loneliness. Further investigation is necessary to understand the factors behind the high level of social alienation in MHD patients and their underlying mechanisms. DESIGN: A cross-sectional study guided by the STROBE. METHODS: A convenience sample of 230 MHD patients were enrolled from January to May 2023. Data including demographic and clinical characteristics, illness perception, fear of progression, and social alienation were collected. Descriptive analysis and Pearson correlations were conducted using IBM SPSS version 25.0. The mediating effect was analyzed using Model 4 of the PROCESS macro for SPSS, with the Bootstrap method employed to assess its significance. RESULTS: The score of social alienation in MHD patients was high, with illness perception and fear of progression both significantly correlated with social alienation. In the mediating effects model, illness perception can predict social alienation in MHD patients, and fear of progression use plays a part in mediating the process by which illness perception affects social alienation. The Kappa Squared (κ2) value of 21.9%, suggests a medium effect size. CONCLUSIONS: Illness perception directly predicts social alienation in MHD patients and exerts an indirect effect through the mediating role of fear of progression. Suggests that healthcare professionals should concentrate on MHD patients with high negative illness perceptions to alleviate their fear of progression, thereby decreasing the level of social alienation and enhancing their integration into society.

Sequence characteristics, genetic diversity and phylogenetic analysis of the Cucurbita ficifolia (Cucurbitaceae) chloroplasts genome.

BACKGROUND: Curcubita ficifolia Bouché (Cucurbitaceae) has high value as a food crop and medicinal plant, and also has horticultural value as rootstock for other melon species. China is home to many different cultivars, but the genetic diversity of these resources and the evolutionary relationships among them, as well as the differences between C. ficifolia and other Cucurbita species, remain unclear. RESULTS: We investigated the chloroplast (cp) genomes of 160 C. ficifolia individuals from 31 populations in Yunnan, a major C. ficifolia production area in China. We found that the cp genome of C. ficifolia is ~151 kb and contains 128 genes, of which 86 are protein coding genes, 34 encode tRNA, and eight encode rRNAs. We also identified 64 SSRs, mainly AT repeats. The cp genome was found to contain a total of 204 SNP and 57 indels, and a total of 21 haplotypes were found in the 160 study individuals. The reverse repeat (IR) region of C. ficifolia contained a few differences compared with this region in the six other Cucurbita species. Sequence difference analysis demonstrated that most of the variable regions were concentrated in the single copy (SC) region. Moreover, the sequences of the coding regions were found to be more similar among species than those of the non-coding regions. The phylogenies reconstructed from the cp genomes of 61 representative species of Cucurbitaceae reflected the currently accepted classification, in which C. ficifolia is sister to the other Cucurbita species, however, different interspecific relationships were found between Cucurbita species. CONCLUSIONS: These results will be valuable in the classification of C. ficifolia genetic resources and will contribute to our understanding of evolutionary relationships within the genus Cucurbita.

Precise detection of awareness in disorders of consciousness using deep learning framework.

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as "DeepDOC", and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data.

Effects of aflatoxin and fumonisin on gene expression of growth factors and inflammation-related genes in a human hepatocyte cell line.

Aflatoxin B1 (AFB1) and fumonisin B1 (FB1) are mycotoxins widely distributed in maize and maized-based products, often occurring together. The implications of co-exposure to aflatoxin and fumonsin for human health are numerous, but a particular concern is the potential of FB1 to modulate AFB1 hepatotoxicity. This study evaluated the toxicity of these mycotoxins, alone or combined, in a human non-tumorigenic liver cell line, HHL-16 cells, and assessed the effects of AFB1 and FB1 on expression of genes involved in immune and growth factor pathways. The results demonstrated that in HHL-16 cells, both AFB1 and FB1 had dose-dependent and time-dependent toxicity, and the combination of them showed a synergistic toxicity in the cells. Moreover, AFB1 caused upregulation of IL6, CCL20, and BMP2, and downregulation of NDP. In combination of AFB1 with FB1, gene expression levels of IL6 and BMP2 were significantly higher compared to individual FB1 treatment, and had a tendency to be higher than individual AFB1 treatment. This study shows that FB1 may increase the hepatoxicity of AFB1 through increasing the inflammatory response and disrupting cell growth pathways.

Increased Adrenocorticotropic Hormone Levels Predict Recovery of Consciousness in Patients With Disorders of Consciousness.

The potential influence of pituitary-related hormones (including both pituitary gland and target gland hormones) on functional recovery after traumatic brain injury has been observed. However, the relationship between these hormones and the recovery of consciousness in patients with disorders of consciousness (DOC) remains unclear. In this retrospective and observational study, 208 patients with DOC were recruited. According to the Glasgow Outcome Scale (GOS) scores after 6 months, patients with DOC were categorized into two subgroups: a favorable prognosis subgroup (n = 38) comprising those who regained consciousness (GOS score ≥3), and a poor prognosis subgroup (n = 156) comprising those who remained in DOC (GOS score <3). Comparative analyses of pituitary-related hormone levels between the two subgroups were conducted. Further, a binary logistic regression analysis was conducted to assess the predictive value of pituitary-related hormones for the patients' prognosis. The favorable prognosis subgroup showed a significant increase in adrenocorticotropic hormone (ACTH) levels (p = 0.036). Moreover, higher ACTH levels and shorter days since injury were significantly associated with a better prognosis, with odds ratios (ORs) of 0.928 (95% confidence interval [CI] = 0.873-0.985, p = 0.014) and 1.015 (95% CI = 1.005-1.026, p = 0.005), respectively. A subsequent receiver operating characteristic (ROC) analysis demonstrated the potential to predict patients' prognosis with an area under the curve value of 0.78, an overall accuracy of 75.5%, a sensitivity of 77.5%, and a specificity of 66.7%. Our findings indicate that ACTH levels could serve as a clinically valuable and convenient predictor for patients' prognosis.

Enhanced Optic Nerve Expansion and Altered Ultrastructure of Elastic Fibers Induced by Lysyl Oxidase Inhibition in a Mouse Model of Marfan Syndrome.

Two major constituents of exfoliation material, fibrillin-1 and lysyl oxidase-like 1 (encoded by FBN1 and LOXL1), are implicated in exfoliation glaucoma, yet their individual contributions to ocular phenotype are minor. To test the hypothesis that a combination of FBN1 mutation and LOXL1 deficiency exacerbates ocular phenotypes, the pan-lysyl oxidase inhibitor ß-aminopropionitrile (BAPN) was used to treat adult wild-type (WT) mice and mice heterozygous for a missense mutation in Fbn1 (Fbn1C1041G/+) for 8 weeks and their eyes were examined. Although intraocular pressure did not change and exfoliation material was not detected in the eyes, BAPN treatment worsened optic nerve and axon expansion in Fbn1C1041G/+ mice, an early sign of axonal damage in rodent models of glaucoma. Disruption of elastic fibers was detected only in Fbn1C1041G/+ mice, which increased with BAPN treatment, as shown by histologic and immunohistochemical staining of the optic nerve pia mater. Transmission electron microscopy showed that Fbn1C1041G/+ mice had fewer microfibrils, smaller elastin cores, and a lower density of elastic fibers compared with WT mice in control groups. BAPN treatment led to elastin core expansion in both WT and Fbn1C1041G/+ mice, but an increase in the density of elastic fiber was confined to Fbn1C1041G/+ mice. LOX inhibition had a stronger effect on optic nerve and elastic fiber parameters in the context of Fbn1 mutation, indicating the Marfan mouse model with LOX inhibition warrants further investigation for exfoliation glaucoma pathogenesis.

Research on workflow recognition for liver rupture repair surgery.

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery.

Coupled strategy based on regulator manipulation and medium optimization empowers the biosynthetic overproduction of lincomycin.

The biosynthesis of bioactive secondary metabolites, specifically antibiotics, is of great scientific and economic importance. The control of antibiotic production typically involves different processes and molecular mechanism. Despite numerous efforts to improve antibiotic yields, joint engineering strategies for combining genetic manipulation with fermentation optimization remain finite. Lincomycin A (Lin-A), a lincosamide antibiotic, is industrially fermented by Streptomyces lincolnensis. Herein, the leucine-responsive regulatory protein (Lrp)-type regulator SLCG_4846 was confirmed to directly inhibit the lincomycin biosynthesis, whereas indirectly controlled the transcription of SLCG_2919, the first reported repressor in S. lincolnensis. Inactivation of SLCG_4846 in the high-yield S. lincolnensis LA219X (LA219XΔ4846) increases the Lin-A production and deletion of SLCG_2919 in LA219XΔ4846 exhibits superimposed yield increment. Given the effect of the double deletion on cellular primary metabolism of S. lincolnensis, Plackett-Burman design, steepest ascent and response surface methodologies were utilized and employed to optimize the seed medium of this double mutant in shake flask, and Lin-A yield using optimal seed medium was significantly increased over the control. Above strategies were performed in a 15-L fermenter. The maximal yield of Lin-A in LA219XΔ4846-2919 reached 6.56 g/L at 216 h, 55.1 % higher than that in LA219X at the parental cultivation (4.23 g/L). This study not only showcases the potential of this strategy to boost lincomycin production, but also could empower the development of high-performance actinomycetes for other antibiotics.

Identification of aging-related genes in diagnosing osteoarthritis via integrating bioinformatics analysis and machine learning.

BACKGROUND: Osteoarthritis (OA) is one of the main causes of pain and disability in the world, it may be caused by many factors. Aging plays a significant role in the onset and progression of OA. However, the mechanisms underlying it remain unknown. Our research aimed to uncover the role of aging-related genes in the progression of OA. METHODS: In Human OA datasets and aging-related genes were obtained from the GEO database and the HAGR website, respectively. Bioinformatics methods including Gene Ontology (GO), Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment, and Protein-protein interaction (PPI) network analysis were used to analyze differentially expressed aging-related genes (DEARGs) in the normal control group and the OA group. And then weighted gene coexpression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO) regression, and the Random Forest (RF) machine learning algorithms were used to find the hub genes. RESULTS: Four overlapping hub genes: HMGB2, CDKN1A, JUN, and DDIT3 were identified. According to the nomogram model and receiver operating characteristic (ROC) curve analysis, four hub DEARGs had good diagnostic value in distinguishing normal from OA. Furthermore, the qRT-PCR test demonstrated that HMGB2, CDKN1A, JUN, and DDIT3 mRNA expression levels were lower in OA group than in normal group. CONCLUSION: Finally, these four-hub aging-related genes may help us understand the underlying mechanism of aging in osteoarthritis and could be used as possible diagnostic and therapeutic targets.