Biliary fibrosis is an important but neglected pathological feature in hepatobiliary disorders: from molecular mechanisms to clinical implications.

Fibrosis resulting from pathological repair secondary to recurrent or persistent tissue damage often leads to organ failure and mortality. Biliary fibrosis is a crucial but easily neglected pathological feature in hepatobiliary disorders, which may promote the development and progression of benign and malignant biliary diseases through pathological healing mechanisms secondary to biliary tract injuries. Elucidating the etiology and pathogenesis of biliary fibrosis is beneficial to the prevention and treatment of biliary diseases. In this review, we emphasized the importance of biliary fibrosis in cholangiopathies and summarized the clinical manifestations, epidemiology, and aberrant cellular composition involving the biliary ductules, cholangiocytes, immune system, fibroblasts, and the microbiome. We also focused on pivotal signaling pathways and offered insights into ongoing clinical trials and proposing a strategic approach for managing biliary fibrosis-related cholangiopathies. This review will offer a comprehensive perspective on biliary fibrosis and provide an important reference for future mechanism research and innovative therapy to prevent or reverse fibrosis.

Establishment and validation of a bad outcomes prediction model based on EEG and clinical parameters in prolonged disorder of consciousness.

Objective: This study aimed to explore the electroencephalogram (EEG) indicators and clinical factors that may lead to poor prognosis in patients with prolonged disorder of consciousness (pDOC), and establish and verify a clinical predictive model based on these factors. Methods: This study included 134 patients suffering from prolonged disorder of consciousness enrolled in our department of neurosurgery. We collected the data of sex, age, etiology, coma recovery scales (CRS-R) score, complications, blood routine, liver function, coagulation and other laboratory tests, resting EEG data and follow-up after discharge. These patients were divided into two groups: training set (n = 107) and verification set (n = 27). These patients were divided into a training set of 107 and a validation set of 27 for this study. Univariate and multivariate regression analysis were used to determine the factors affecting the poor prognosis of pDOC and to establish nomogram model. We use the receiver operating characteristic (ROC) and calibration curves to quantitatively test the effectiveness of the training set and the verification set. In order to further verify the clinical practical value of the model, we use decision curve analysis (DCA) to evaluate the model. Result: The results from univariate and multivariate logistic regression analyses suggested that an increased frequency of occurrence microstate A, reduced CRS-R scores at the time of admission, the presence of episodes associated with paroxysmal sympathetic hyperactivity (PSH), and decreased fibrinogen levels all function as independent prognostic factors. These factors were used to construct the nomogram. The training and verification sets had areas under the curve of 0.854 and 0.920, respectively. Calibration curves and DCA demonstrated good model performance and significant clinical benefits in both sets. Conclusion: This study is based on the use of clinically available and low-cost clinical indicators combined with EEG to construct a highly applicable and accurate model for predicting the adverse prognosis of patients with prolonged disorder of consciousness. It provides an objective and reliable tool for clinicians to evaluate the prognosis of prolonged disorder of consciousness, and helps clinicians to provide personalized clinical care and decision-making for patients with prolonged disorder of consciousness and their families.

Genomic and biological insights of bacteriophages JNUWH1 and JNUWD in the arms race against bacterial resistance.

The coevolution of bacteria and bacteriophages has created a great diversity of mechanisms by which bacteria fight phage infection, and an equivalent diversity of mechanisms by which phages subvert bacterial immunity. Effective and continuous evolution by phages is necessary to deal with coevolving bacteria. In this study, to better understand the connection between phage genes and host range, we examine the isolation and genomic characterization of two bacteriophages, JNUWH1 and JNUWD, capable of infecting Escherichia coli. Sourced from factory fermentation pollutants, these phages were classified within the Siphoviridae family through TEM and comparative genomic analysis. Notably, the phages exhibited a viral burst size of 500 and 1,000 PFU/cell, with latent periods of 15 and 20 min, respectively. They displayed stability over a pH range of 5 to 10, with optimal activity at 37°C. The complete genomes of JNUWH1 and JNUWD were 44,785 bp and 43,818 bp, respectively. Phylogenetic analysis revealed their close genetic relationship to each other. Antibacterial assays demonstrated the phages' ability to inhibit E. coli growth for up to 24 h. Finally, through laboratory-driven adaptive evolution, we successfully identified strains for both JNUWH1 and JNUWD with mutations in receptors specifically targeting lipopolysaccharides (LPS) and the lptD gene. Overall, these phages hold promise as additives in fermentation products to counter E. coli, offering potential solutions in the context of evolving bacterial resistance.

Epigallocatechin-3-gallate attenuates fluoride induced apoptosis via PI3K/FoxO1 pathway in ameloblast-like cells.

Fluoride is a double-edged sword. It was widely used for early caries prevention while excessive intake caused a toxicology effect, affected enamel development, and resulted in dental fluorosis. The study aimed to evaluate the protective effect and mechanism of Epigallocatechin-3-gallate (EGCG) on the apoptosis induced by fluoride in ameloblast-like cells. We observed that NaF triggered apoptotic alterations in cell morphology, excessive NaF arrested cell cycle at the G1, and induced apoptosis by up-regulating Bax and down-regulating Bcl-2. NaF activated the insulin-like growth factor receptor (IGFR), and phosphatidylinositol-3-hydroxylase (p-PI3K), while dose-dependently down-regulating the expression of Forkhead box O1 (FoxO1). EGCG supplements reversed the changes in LS8 morphology, the cell cycle, and apoptosis induced by fluoride. These results indicated that EGCG possesses a protective effect against fluoride toxicity. Furthermore, EGCG suppressed the activation of p-PI3K and the down-regulation of FoxO1 caused by fluoride. Collectively, our findings suggested that EGCG attenuated fluoride-induced apoptosis by inhibiting the PI3K/FoxO1 signaling pathway. EGCG may serve as a new alternative method for dental fluorosis prevention, control, and treatment.

An adversarial example attack method based on predicted bounding box adaptive deformation in optical remote sensing images.

Existing global adversarial attacks are not applicable to real-time optical remote sensing object detectors based on the YOLO series of deep neural networks, which makes it difficult to improve the adversarial robustness of single-stage detectors. The existing methods do not work well enough in optical remote sensing images, which may be due to the mechanism of adversarial perturbations is not suitable. Therefore, an adaptive deformation method (ADM) was proposed to fool the detector into generating wrong predicted bounding boxes. Building upon this, we introduce the Adaptive Deformation Method Iterative Fast Gradient Sign Method (ADM-I-FGSM) and Adaptive Deformation Mechanism Projected Gradient Descent (ADM-PGD) against YOLOv4 and YOLOv5. ADM method can obtain the deformation trend values based on the length-to-width ratio of the prediction box, and the adversarial perturbation trend generated based on these trend values has better adversarial effect. Through experiments, we validate that our approach exhibits a higher adversarial success rate compared to the state-of-the-art methods. We anticipate that our unveiled attack scheme will aid in the evaluation of adversarial resilience of these models.

Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.

BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity. METHODS: We retrospectively recruited GSP patients who underwent CT imaging within 48 h of admission from tertiary referral centre. Radiomics and CT features were extracted from CT scans. The clinical and CT features were selected by the random forest algorithm to develop the ML GSP model for the identification of severity of GSP (mild or severe), and its predictive efficacy was compared with radiomics model. The predictive performance was assessed by the area under operating characteristic curve. Calibration curve and decision curve analysis were performed to demonstrate the classification performance and clinical efficacy. Furthermore, we built a web-based open access GSP severity calculator. The study was registered with ClinicalTrials.gov (NCT05498961). RESULTS: A total of 301 patients were enrolled. They were randomly assigned into the training (n = 210) and validation (n = 91) cohorts at a ratio of 7:3. The random forest algorithm identified the level of calcium ions, WBC count, urea level, combined cholecystitis, gallbladder wall thickening, gallstones, and hydrothorax as the seven predictive factors for severity of GSP. In the validation cohort, the areas under the curve for the radiomics model and ML GSP model were 0.841 (0.757-0.926) and 0.914 (0.851-0.978), respectively. The calibration plot shows that the ML GSP model has good consistency between the prediction probability and the observation probability. Decision curve analysis showed that the ML GSP model had high clinical utility. CONCLUSIONS: We built the ML GSP model based on clinical and CT image features and distributed it as a free web-based calculator. Our results indicated that the ML GSP model is useful for predicting the severity of GSP.

ML GSP model based on machine learning has good severity discrimination in both training and validation cohorts (0.916 (0.872­0.958), 0.914 (0.851­0.978), respectively).We built an online user-friendly platform for the ML GSP model to help clinicians better identify the severity of GSP.

A novel approach in biomedical engineering: The use of polyvinyl alcohol hydrogel encapsulating human umbilical cord mesenchymal stem cell-derived exosomes for enhanced osteogenic differentiation and angiogenesis in bone regeneration.

Developing effective methods for alveolar bone defect regeneration is a significant challenge in orthopedics. Exosomes from human umbilical cord mesenchymal stem cells (HUMSC-Exos) have shown potential in bone repair but face limitations due to undefined application methods and mechanisms. To address this, HUMSC-Exos were encapsulated in polyvinyl alcohol (PVA) hydrogel (Exo@PVA) to create a novel material for alveolar bone repair. This combination enhanced the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and human umbilical vein endothelial cells (HUVECs) more effectively than Exos alone. Additionally, Exo@PVA significantly improved alveolar bone regeneration and defect repair in rats. The microRNA-21-5p (miR-21-5p) in Exo@PVA, identified through the GEO database and analyzed via in silico methods, played a crucial role. miR-21-5p promoted BMSC osteogenic differentiation by inhibiting WWP1-mediated KLF5 ubiquitination and enhanced HUVEC angiogenesis by targeting ATP2B4. These findings underscore the potential of an Exo-based approach with PVA hydrogel scaffolds for bone defect repair, operating through the miR-21-5p/WWP1/ATP2B4 signaling axis.

Design-build-test of recombinant Bacillus subtilis chassis cell by lifespan engineering for robust bioprocesses.

Microbial cell factories utilize renewable raw materials for industrial chemical production, providing a promising path for sustainable development. Bacillus subtilis is widely used in industry for its food safety properties, but challenges remain in the limitations of microbial fermentation. This study proposes a novel strategy based on lifespan engineering to design robust B. subtilis chassis cells to supplement traditional metabolic modification strategies that can alleviate cell autolysis, tolerate toxic substrates, and get a higher mass transfer efficiency. The modified chassis cells could produce high levels of l-glutaminase, and tolerate hydroquinone to produce α-arbutin efficiently. In a 5 L bioreactor, the l-glutaminase enzyme activity of the final strain CRE15TG was increased to 2817.4 ± 21.7 U mL-1, about 1.98-fold compared with that of the wild type. The α-arbutin yield of strain CRE15A was increased to 134.7 g L-1, about 1.34-fold compared with that of the WT. To our knowledge, both of the products in this study performed the highest yields reported so far. The chassis modification strategy described in this study can Improve the utilization efficiency of chassis cells, mitigate the possible adverse effects caused by excessive metabolic modification of engineered strains, and provide a new idea for the future design of microbial cell factories.

Effect of Dimethyloxalylglycine on Stem Cells Osteogenic Differentiation and Bone Tissue Regeneration-A Systematic Review.

Dimethyloxalylglycine (DMOG) has been found to stimulate osteogenesis and angiogenesis of stem cells, promoting neo-angiogenesis in bone tissue regeneration. In this review, we conducted a comprehensive search of the literature to investigate the effects of DMOG on osteogenesis and bone regeneration. We screened the studies based on specific inclusion criteria and extracted relevant information from both in vitro and in vivo experiments. The risk of bias in animal studies was evaluated using the SYRCLE tool. Out of the 174 studies retrieved, 34 studies met the inclusion criteria (34 studies were analyzed in vitro and 20 studies were analyzed in vivo). The findings of the included studies revealed that DMOG stimulated stem cells' differentiation toward osteogenic, angiogenic, and chondrogenic lineages, leading to vascularized bone and cartilage regeneration. Addtionally, DMOG demonstrated therapeutic effects on bone loss caused by bone-related diseases. However, the culture environment in vitro is notably distinct from that in vivo, and the animal models used in vivo experiments differ significantly from humans. In summary, DMOG has the ability to enhance the osteogenic and angiogenic differentiation potential of stem cells, thereby improving bone regeneration in cases of bone defects. This highlights DMOG as a potential focus for research in the field of bone tissue regeneration engineering.

N-terminal truncation (N-) and directional proton transfer in an old yellow enzyme enables tunable efficient producing (R)- or (S)-citronellal.

(R)-Citronellal is a valuable molecule as the precursor for the industrial synthesis of (-)-menthol, one of the worldwide best-selling compounds in the flavors and fragrances field. However, its biocatalytic production, even from the optically pure substrate (E)-citral, is inherently limited by the activity of Old Yellow Enzyme (OYE). Herein, we rationally designed a different approach to increase the activity of OYE in biocatalytic production. The activity of OYE from Corynebacterium glutamicum (CgOYE) is increased, as well as superior thermal stability and pH tolerance via truncating the different lengths of regions at N-terminal of CgOYE. Next, we converted the truncation mutant N31-CgOYE, a protein involved in proton transfer for the asymmetric hydrogenation of CC bonds, into highly (R)- and (S)-stereoselective enzymes using only three mutations. The mixture of racemic (E/Z)-citral is reduced into the (R)-citronellal with ee and conversion up to 99 % by the mutant of CgOYE, overcoming the problem of the reduction for the mixtures of (E/Z)-citral in biocatalytic reaction. The present work provides a general and effective strategy for improving the activity of OYE, in which the partially conserved histidine residues provide "tunable gating" for the enantioselectivity for both the (R)- and (S)-isomerases.

Engineering serine hydroxymethyltransferases for efficient synthesis of L-serine in Escherichia coli.

L-serine is a high-value amino acid widely used in the food, medicine, and cosmetic industries. However, the low yield of L-serine has limited its industrial production. In this study, a cellular factory for efficient synthesis of L-serine was obtained by engineering the serine hydroxymethyltransferases (SHMT). Firstly, after screening the SHMT from Alcanivorax dieselolei by genome mining, a mutant AdSHMTE266M with high thermal stability was identified through rational design. Subsequently, an iterative saturating mutant library was constructed by using coevolutionary analysis, and a mutant AdSHMTE160L/E193Q with enzyme activity 1.35 times higher than AdSHMT was identified. Additionally, the target protein AdSHMTE160L/E193Q/E266M was efficiently overexpressed by improving its mRNA stability. Finally, combining the substrate addition strategy and system optimization, the optimized strain BL21/pET28a-AdSHMTE160L/E193Q/E266M-5'UTR-REP3S16 produced 106.06 g/L L-serine, which is the highest production to date. This study provides new ideas and insights for the engineering design of SHMT and the industrial production of L-serine.

Combining protein and metabolic engineering strategies for high-level production of L-theanine in Corynebacterium glutamicum.

L-theanine is a natural non-protein amino acid with wide applications. Thus, a high yield of L-theanine production is required on an industrial scale. Herein, an efficient L-theanine-producing strain of Corynebacterium glutamicum was constructed by combining protein and metabolic engineering. Firstly, a γ-glutamylmethylamide synthetase from Paracoccus aminovorans (PaGMAS) was isolated and engineered by computer-aided design, the resulting mutant E179K/N105R improved L-theanine yield by 36.61 %. Subsequently, to increase carbon flux towards L-theanine production, the gene ggt which degrades L-theanine, the gene alaT which participated in L-alanine synthesis, and the gene NCgl1221 which encodes glutamate-exporting protein were deleted. Finally, ppk gene was overexpressed to enhance intracellular ATP production. The reprogramed strain produced 44.12 g/L L-theanine with a yield of 57.11 % and productivity of 1.16 g/L/h, which is the highest L-theanine titer reported by Corynebacterium glutamicum. This study provides an efficient and economical biosynthetic pathway for the industrial production of L-theanine.

Construction of a plasmid-free L-leucine overproducing Escherichia coli strain through reprogramming of the metabolic flux.

BACKGROUND: L-Leucine is a high-value amino acid with promising applications in the medicine and feed industries. However, the complex metabolic network and intracellular redox imbalance in fermentative microbes limit their efficient biosynthesis of L-leucine. RESULTS: In this study, we applied rational metabolic engineering and a dynamic regulation strategy to construct a plasmid-free, non-auxotrophic Escherichia coli strain that overproduces L-leucine. First, the L-leucine biosynthesis pathway was strengthened through multi-step rational metabolic engineering. Then, a cooperative cofactor utilization strategy was designed to ensure redox balance for L-leucine production. Finally, to further improve the L-leucine yield, a toggle switch for dynamically controlling sucAB expression was applied to accurately regulate the tricarboxylic acid cycle and the carbon flux toward L-leucine biosynthesis. Strain LEU27 produced up to 55 g/L of L-leucine, with a yield of 0.23 g/g glucose. CONCLUSIONS: The combination of strategies can be applied to the development of microbial platforms that produce L-leucine and its derivatives.

Combinatorial protein engineering and transporter engineering for efficient synthesis of L-Carnosine in Escherichia coli.

L-Carnosine has various physiological functions and is widely used in cosmetics, medicine, food additives, and other fields. However, the yield of L-Carnosine obtained by biological methods is far from the level of industrial production. Herein, a cell factory for efficient synthesis of L-Carnosine was constructed based on transporter engineering and protein engineering. Firstly, a dipeptidase (SmpepD) was screened from Serratia marcescens through genome mining to construct a cell factory for synthesizing L-Carnosine. Subsequently, through rationally designed SmPepD, a double mutant T168S/G148D increased the L-Carnosine yield by 41.6% was obtained. Then, yeaS, a gene encoding the exporter of L-histidine, was deleted to further increase the production of L-Carnosine. Finally, L-Carnosine was produced by one-pot biotransformation in a 5 L bioreactor under optimized conditions with a yield of 133.2 mM. This study represented the highest yield of L-Carnosine synthesized in microorganisms and provided a biosynthetic pathway for the industrial production of L-Carnosine.

Image classification adversarial attack with improved resizing transformation and ensemble models.

Convolutional neural networks have achieved great success in computer vision, but incorrect predictions would be output when applying intended perturbations on original input. These human-indistinguishable replicas are called adversarial examples, which on this feature can be used to evaluate network robustness and security. White-box attack success rate is considerable, when already knowing network structure and parameters. But in a black-box attack, the adversarial examples success rate is relatively low and the transferability remains to be improved. This article refers to model augmentation which is derived from data augmentation in training generalizable neural networks, and proposes resizing invariance method. The proposed method introduces improved resizing transformation to achieve model augmentation. In addition, ensemble models are used to generate more transferable adversarial examples. Extensive experiments verify the better performance of this method in comparison to other baseline methods including the original model augmentation method, and the black-box attack success rate is improved on both the normal models and defense models.

Laparoscopic versus open surgical management in elderly patients with rectal cancer aged 70 and older.

Background: This retrospective study aimed to compare the short- and long-term surgical outcomes of laparoscopic surgery versus open surgery in elderly patients with rectal cancer. Patients and Methods: Elderly patients (≥70 years old) with rectal cancer who received radical surgery were retrospectively analysed. Patients were matched (1:1 ratio) using propensity score matching (PSM), with age, sex, body mass index, American Society of Anesthesiologists score and tumour-node-metastasis staging included as covariates. Baseline characteristics, post-operative complications, short- and long-term surgical outcomes and overall survival (OS) were compared between the two matched groups. Results: Sixty-one pairs were selected after PSM. Patients with laparoscopic surgery had a longer duration of operation time, lower estimated blood loss, shorter duration of post-operative analgesics administered, time to first flatus, time to first oral diet and post-operative hospitalisation stay than those observed in patients with open surgery (All P < 0.05). The incidence of post-operative complications in the open surgery group was numerically higher than that occurred in the laparoscopic surgery group (30.6% vs. 17.7%). Median OS was 67.0 months (95% confidence interval [CI], 62.2-71.8) in the laparoscopic surgery group and 65.0 months (95% CI, 59.9-70.1) in the open surgery group, however, Kaplan-Meier curves indicated that no significant differences in OS (Log-rank test, P = 0.535) were noted between the two matched groups. Conclusions: Compared with the open surgery, laparoscopic surgery had the advantages of less trauma and faster recovery, and provided similar long-term prognostic outcome in elderly patients with rectal cancer.

Molecular signatures distinguish senescent cells from inflammatory cells in aged mouse callus stromal cells.

Cellular senescence plays important roles in age-related diseases, including musculoskeletal disorders. Senescent cells (SCs) exert a senescence-associated secretory phenotype (SASP) by producing SASP factors, some of which overlap with factors produced by inflammatory cells (Inf-Cs). However, the differences between SCs and Inf-Cs and how they interact with each other during fracture repair have not been well studied. Here, we analyzed single cell RNA sequencing data of aged mouse fracture callus stromal cells. We defined Inf-Cs as cells that express NF-κB Rela/Relb, SCs as cells that express the senescence genes, Cdkn1a, Cdkn2a or Cdkn2c, and inflammatory SCs (Inf-SCs) as cells that express both NF-κB and senescence genes. Differentially expressed genes and pathway analyses revealed that Inf-SCs and SCs had a similar gene expression profile and upregulated pathways that are related to DNA damage/oxidation-reduction and cellular senescence, while Inf-Cs expressed different gene signatures and pathways from SCs and Inf-SCs, mainly related to inflammation. Cellchat software analysis indicated that SCs and Inf-SCs are potential ligand-producing cells that affect Inf-Cs as target cells. Cell culture experiments demonstrated that SC conditioned medium promoted inflammatory gene expression by callus-derived mesenchymal progenitor cells, and Inf-Cs had reduced osteoblast differentiation capacity. In summary, we have identified three cell subclusters associated with inflammation and senescence in callus stromal cells, predicted potential effects of Inf-SCs and SCs on Inf-Cs by production of active ligands, and demonstrated that when mesenchymal progenitors acquire inflammatory phenotypes their osteogenic potential is reduced.

The roles of bone remodeling in normal hematopoiesis and age-related hematological malignancies.

Prior research establishing that bone interacts in coordination with the bone marrow microenvironment (BMME) to regulate hematopoietic homeostasis was largely based on analyses of individual bone-associated cell populations. Recent advances in intravital imaging has suggested that the expansion of hematopoietic stem cells (HSCs) and acute myeloid leukemia cells is restricted to bone marrow microdomains during a distinct stage of bone remodeling. These findings indicate that dynamic bone remodeling likely imposes additional heterogeneity within the BMME to yield differential clonal responses. A holistic understanding of the role of bone remodeling in regulating the stem cell niche and how these interactions are altered in age-related hematological malignancies will be critical to the development of novel interventions. To advance this understanding, herein, we provide a synopsis of the cellular and molecular constituents that participate in bone turnover and their known connections to the hematopoietic compartment. Specifically, we elaborate on the coupling between bone remodeling and the BMME in homeostasis and age-related hematological malignancies and after treatment with bone-targeting approaches. We then discuss unresolved questions and ambiguities that remain in the field.

Piezo1-mediated M2 macrophage mechanotransduction enhances bone formation through secretion and activation of transforming growth factor-ß1.

Macrophages are multifunctional immune system cells that are essential for the mechanical stimulation-induced control of metabolism. Piezo1 is a non-selective calcium channel expressed in multifarious tissues to convey mechanical signals. Here, a cellular model of tension was used to study the effect of mechanical stretch on the phenotypic transformation of macrophages and its mechanism. An indirect co-culture system was used to explore the effect of macrophage activation on bone marrow mesenchymal stem cells (BMSCs), and a treadmill running model was used to validate the mechanism in vivo for in vitro studies. p53 was acetylated and deacetylated by macrophages as a result of mechanical strain being detected by Piezo1. This process is able to polarize macrophages towards M2 and secretes transforming growth factor-beta (TGF-ß1), which subsequently stimulates BMSCs migration, proliferation and osteogenic differentiation. Knockdown of Piezo1 inhibits the conversion of macrophages to the reparative phenotype, thereby affecting bone remodelling. Blockade of TGF-ß I, II receptors and Piezo1 significantly reduced exercise-increased bone mass in mice. In conclusion, we showed that mechanical tension causes calcium influx, p53 deacetylation, macrophage polarization towards M2 and TGF-ß1 release through Piezo1. These events support BMSC osteogenesis.