Molecular Dynamics Simulation of the Rejuvenation Performance of Waste Cooking Oil with High Acid Value on Aged Asphalt.

Waste cooking oil's (WCO's) potential as a rejuvenator of aged asphalt has received attention in recent years, with the acid value of WCO affecting its rejuvenation effect. This study explored the rejuvenation effect of WCO with a high acid value on aged asphalt by using molecular dynamics simulation. First, the representative molecules of WCO with a high acid value and asphalt were determined. The rejuvenation effect of WCO on aged asphalt was analyzed by adding different contents of WCO to an aged asphalt model. The effect of WCO on the thermodynamic properties of the aged asphalt was analyzed. The results show that WCO can restore the thermodynamic properties of aged asphalt binder to a certain extent. Regarding the microstructure of rejuvenated asphalt, WCO molecules dispersed around asphaltenes weakened the latter's aggregation and improved the colloidal structure of the aged asphalt. In terms of interface adhesion properties, WCO can improve the adhesion properties between asphalt binder and SiO2, but it has limited influence on water sensitivity. The results allowed us to comprehensively evaluate the rejuvenation effect of WCO with a high acid value on aged asphalt and to explore its rejuvenation mechanism.

Dual Starvations Induce Pyroptosis for Orthotopic Pancreatic Cancer Therapy through Simultaneous Deprivation of Glucose and Glutamine.

Pancreatic cancer is a highly fatal disease, and existing treatment methods are ineffective, so it is urgent to develop new effective treatment strategies. The high dependence of pancreatic cancer cells on glucose and glutamine suggests that disrupting this dependency could serve as an alternative strategy for pancreatic cancer therapy. We identified the vital genes glucose transporter 1 (GLUT1) and alanine-serine-cysteine transporter 2 (ASCT2) through bioinformatics analysis, which regulate glucose and glutamine metabolism in pancreatic cancer, respectively. Human serum albumin nanoparticles (HSA NPs) for delivery of GLUT1 and ASCT2 inhibitors, BAY-876/V-9302@HSA NPs, were prepared by a self-assembly process. This nanodrug inhibits glucose and glutamine uptake of pancreatic cancer cells through the released BAY-876 and V-9302, leading to nutrition deprivation and oxidative stress. The inhibition of glutamine leads to the inhibition of the synthesis of the glutathione, which further aggravates oxidative stress. Both of them lead to a significant increase in reactive oxygen species, activating caspase 1 and GSDMD and finally inducing pyroptosis. This study provides a new effective strategy for orthotopic pancreatic cancer treatment by dual starvation-induced pyroptosis. The study for screening metabolic targets using bioinformatics analysis followed by constructing nanodrugs loaded with inhibitors will inspire future targeted metabolic therapy for pancreatic cancer.

Wireless Sensor System Based on Organohydrogel Ionic Skin for Physiological Activity Monitoring.

Supermolecular hydrogel ionic skin (i-skin) linked with smartphones has attracted widespread attention in physiological activity detection due to its good stability in complex scenarios. However, the low ionic conductivity, inferior mechanical properties, poor contact adhesion, and insufficient freeze resistance of most used hydrogels limit their practical application in flexible electronics. Herein, a novel multifunctional poly(vinyl alcohol)-based conductive organohydrogel (PCEL5.0%) with a supermolecular structure was constructed by innovatively employing sodium carboxymethyl cellulose (CMC-Na) as reinforcement material, ethylene glycol as antifreeze, and lithium chloride as a water retaining agent. Thanks to the synergistic effect of these components, the PCEL5.0% organohydrogel shows excellent performance in terms of ionic conductivity (1.61 S m-1), mechanical properties (tensile strength of 70.38 kPa and elongation at break of 537.84%), interfacial adhesion (1.06 kPa to pig skin), frost resistance (-50.4 °C), water retention (67.1% at 22% relative humidity), and remoldability. The resultant PCEL5.0%-based i-skin delivers satisfactory sensitivity (GF = 1.38) with fast response (348 ms) and high precision under different deformations and low temperature (-25 °C). Significantly, the wireless sensor system based on the PCEL5.0% organohydrogel i-skin can transmit signals from physiological activities and sign language to a smartphone by Bluetooth technology and dynamically displays the status of these movements. The organohydrogel i-skin shows great potential in diverse fields of physiological activity detection, human-computer interaction, and rehabilitation medicine.

An innovative antibody fusion protein targeting PD-L1, VEGF and TGF-ß with enhanced antitumor efficacies.

Immunosuppressive pathways in the tumor microenvironment (TME) are inextricably linked to tumor progression. Mono-therapeutics of immune checkpoint inhibitors (ICIs, e.g. antibodies against programmed cell death protein-1/programmed cell death ligand-1, PD-1/PD-L1) is prone to immune escape while combination therapeutics tends to cause high toxicity and side effects. Therefore, using multi-functional molecules to target multiple pathways simultaneously is becoming a new strategy for cancer therapies. Here, we developed a trifunctional fusion protein, DR30206, composed of Bevacizumab (an antibody against VEGF), and a variable domain of heavy chain of heavy chain antibody (VHH) against PD-L1 and the extracellular domain (ECD) protein of TGF-ß receptor II (TGF-ß RII), which are fused to the N- and C-terminus of Bevacizumab, respectively. The original intention of DR30206 design was to enhance the immune responses pairs by targeting PD-L1 while inhibiting VEGF and TGF-ß in the TME. Our data demonstrated that DR30206 exhibits high antigen-binding affinities and efficient blocking capabilities, the principal drivers of efficacy in antibody therapy. Furthermore, the capability of eliciting antibody-dependent cellular cytotoxicity (ADCC) and mixed lymphocyte reaction (MLR) provides a greater possibility to enhance the immune response. Finally, in vivo experiments showed that the antitumor activity of DR30206 was superior to those of monoclonal antibody of PD-L1 or VEGF, PD-L1 and TGF-ß bispecific antibody or the combination inhibition of PD-L1 and VEGF. Our findings suggest there is a great potential for DR30206 to become a therapeutic for the treatment of multiple cancer types, especially lung cancer, colon adenocarcinoma and breast carcinoma.

LncRNA CCAT1 participates in pancreatic ductal adenocarcinoma progression by forming a positive feedback loop with c-Myc.

Long noncoding RNAs (lncRNAs) play fundamental roles in cancer development; however, the underlying mechanisms for a large proportion of lncRNAs in pancreatic ductal adenocarcinoma (PDAC) have not been elucidated. The expression of colon cancer-associated transcript-1 (CCAT1) in PDAC specimens and cell lines was measured by quantitative real-time polymerase chain reaction (qRT-PCR). The function of CCAT1 was examined in vitro and in vivo. The interactions among CCAT1, miR-24-3p and c-Myc were determined by bioinformatics analysis, RNA immunoprecipitation (RIP), dual-luciferase reporter assay, and rescue experiments. CCAT1 was significantly increased in PDAC, positively correlated with PDAC progression and predicted a worse prognosis. Furthermore, CCAT1 enhanced Adenosine triphosphate (ATP) production to facilitate PDAC cell proliferation, colony formation and motility in vitro and tumor growth in vivo. CCAT1 may serve as an miR-24-3p sponge, thereby counteracting its repression by c-Myc expression. Reciprocally, c-Myc may act as a transcription factor to alter CCAT1 expression by directly targeting its promoter region, thus forming a positive feedback loop with CCAT1. Collectively, these results demonstrate that a positive feedback loop of CCAT1/miR-24-3p/c-Myc is involved in PDAC development, which may serve as a biomarker and therapeutic target for PDAC.

Caprin-1 influences autophagy-induced tumor growth and immune modulation in pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is characterized by rapid progression and poor prognosis. Understanding the genetic mechanisms that affect cancer properties and reprogram tumor immune microenvironment will develop new strategies to maximize the benefits for cancer therapies. METHODS: Gene signatures and biological processes associated with advanced cancer and unfavorable outcome were profiled using bulk RNA sequencing and spatial transcriptome sequencing, Caprin-1 was identified as an oncogenesis to expedite pancreatic cancer growth by activating autophagy. The mechanism of Caprin-1 inducing autophagy activation was further explored in vitro and in vivo. In addition, higher level of Caprin-1 was found to manipulate immune responses and inflammatory-related pathways. The immune profiles associated with increased levels of Caprin-1 were identified in human PDAC samples. The roles of CD4+T cells, CD8+T cells and tumor associated macrophages (TAMs) on clinical outcomes prediction were investigated. RESULTS: Caprin-1 was significantly upregulated in advanced PDAC and correlated with poor prognosis. Caprin-1 interacted with both ULK1 and STK38, and manipulated ULK1 phosphorylation which activated autophagy and exerted pro-tumorigenic phenotypes. Additionally, the infiltrated CD4+T cells and tumor associated macrophages (TAMs) were increased in Caprin-1High tissues. The extensive CD4+T cells determined poor clinical outcome in Caprin-1high patients, arguing that highly expressed Caprin-1 may assist cancer cells to escape from immune surveillance. CONCLUSIONS: Our findings establish causal links between the upregulated expression of Caprin-1 and autophagy activation, which may manipulate immune responses in PDAC development. Our study provides insights into considering Caprin-1 as potential therapeutic target for PDAC treatment.

The Prognostic and Immune Significance of CILP2 in Pan-Cancer and Its Relationship with the Progression of Pancreatic Cancer.

Cartilage intermediate layer protein 2 (CILP2) facilitates interactions between matrix components in cartilage and has emerged as a potential prognostic biomarker for cancer. This study aimed to investigate the function and mechanisms of CILP2 in pan-cancer. We evaluated the pan-cancer expression, methylation, and mutation data of CILP2 for its clinical prognostic value. Additionally, we explored the immunological characteristics of CILP2 in pan-cancer and then focused specifically on pancreatic ductal adenocarcinoma (PAAD). The subtype analysis of PAAD identified subtype-specific expression and immunological characteristics. Finally, in vitro and in vivo experiments assessed the impact of CILP2 on pancreatic cancer progression. CILP2 exhibited high expression in most malignancies, with significant heterogeneity in epigenetic modifications across multiple cancer types. The abnormal methylation and copy number variations in CILP2 were correlated with poor prognoses. Upregulated CILP2 was associated with TGFB/TGFBR1 and more malignant subtypes. CILP2 exhibited a negative correlation with immune checkpoints in PAAD, suggesting potential for immunotherapy. CILP2 activated the AKT pathway, and it increased proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) in pancreatic cancer. We demonstrated that CILP2 significantly contributes to pancreatic cancer progression. It serves as a prognostic biomarker and a potential target for immunotherapy.

Evaluation of the Available Energy Value and Amino Acid Digestibility of Brown Rice Stored for 6 Years and Its Application in Pig Diets.

Long-term storage may reduce the nutritional quality of brown rice, so the present study aimed to evaluate the nutritional values of long-term-stored nutrition in pig diets. In Exp. 1, 18 Landrace × Yorkshire (L × Y) barrows with an initial body weight (IBW) of 25.48 ± 3.21 kg were randomly assigned to three treatments, including a corn-based diet, one-year-stored brown rice (BR1) diet, and six-year-stored brown rice (BR6) diet, to determine the digestible energy (DE) and metabolizable energy (ME) values of stored brown rice. In Exp. 2, 24 barrows (L × Y; IBW: 22.16 ± 2.42 kg) fixed with ileal T-cannula were randomly allotted to four dietary treatments, including a corn diet, two stored brown rice diets, and a nitrogen-free diet, to evaluate the amino acid (AA) digestibility of the stored brown rice. In Exp. 3 and 4, 108 crossbred weaned piglets (L × Y; IBW: 9.16 ± 0.89 kg) and 90 crossbred growing pigs (L × Y; IBW: 48.28 ± 3.51 kg) were allotted to three treatment diets, including a control diet and two stored brown rice diets, respectively, to investigate the application of stored brown rice in weaned piglets and fully grown pig diets. The results indicated that there was no significant difference in the DE and ME values between corn and stored brown rice (p > 0.05), while the apparent ileal digestibility (AID) of arginine, histidine, asparagine + aspartic acid (Asx), and the standardized ileal digestibility (SID) of arginine and histidine were higher in the stored brown rice diet compared to the corn diet (p < 0.05). Compared to the corn, the stored brown rice showed no significant effects on growth performance, nutrient-apparent total tract digestibility (ATTD), and serum biochemical indices (p > 0.05) but showed decreased activity in the various digestive enzymes in the duodenum, jejunum, and ileum of the weaned piglets (p < 0.05). Also, the stored brown rice diet showed no significant effects on growth performance, carcass traits, meat quality, as well as the fatty acid profiles in the longissimus dorsi muscle of fully grown pigs compared with the corn diet (p > 0.05). In conclusion, the brown rice stored for 6 years under good conditions had no obvious changes in the available energy and nutrient values. Although it may reduce digestive enzyme activity in the small intestines of the piglets, the stored brown rice showed no obvious adverse effects on growth performance and meat quality and can be effectively used in pig diets.

Gut microbiota aggravates neutrophil extracellular traps-induced pancreatic injury in hypertriglyceridemic pancreatitis.

Hypertriglyceridemic pancreatitis (HTGP) is featured by higher incidence of complications and poor clinical outcomes. Gut microbiota dysbiosis is associated with pancreatic injury in HTGP and the mechanism remains unclear. Here, we observe lower diversity of gut microbiota and absence of beneficial bacteria in HTGP patients. In a fecal microbiota transplantation mouse model, the colonization of gut microbiota from HTGP patients recruits neutrophils and increases neutrophil extracellular traps (NETs) formation that exacerbates pancreatic injury and systemic inflammation. We find that decreased abundance of Bacteroides uniformis in gut microbiota impairs taurine production and increases IL-17 release in colon that triggers NETs formation. Moreover, Bacteroides uniformis or taurine inhibits the activation of NF-κB and IL-17 signaling pathways in neutrophils which harness NETs and alleviate pancreatic injury. Our findings establish roles of endogenous Bacteroides uniformis-derived metabolic and inflammatory products on suppressing NETs release, which provides potential insights of ameliorating HTGP through gut microbiota modulation.

circEIF3I facilitates the recruitment of SMAD3 to early endosomes to promote TGF-ß signalling pathway-mediated activation of MMPs in pancreatic cancer.

BACKGROUND: Among digestive tract tumours, pancreatic ductal adenocarcinoma (PDAC) shows the highest mortality trend. Moreover, although PDAC metastasis remains a leading cause of cancer-related deaths, the biological mechanism is poorly understood. Recent evidence demonstrates that circular RNAs (circRNAs) play important roles in PDAC progression. METHODS: Differentially expressed circRNAs in normal and PDAC tissues were screened via bioinformatics analysis. Sanger sequencing, RNase R and actinomycin D assays were performed to confirm the loop structure of circEIF3I. In vitro and in vivo functional experiments were conducted to assess the role of circEIF3I in PDAC. MS2-tagged RNA affinity purification, mass spectrometry, RNA immunoprecipitation, RNA pull-down assay, fluorescence in situ hybridization, immunofluorescence and RNA-protein interaction simulation and analysis were performed to identify circEIF3I-interacting proteins. The effects of circEIF3I on the interactions of SMAD3 with TGFßRI or AP2A1 were measured through co-immunoprecipitation and western blotting. RESULTS: A microarray data analysis showed that circEIF3I was highly expressed in PDAC cells and correlated with TNM stage and poor prognosis. Functional experiments in vitro and in vivo revealed that circEIF3I accelerated PDAC cells migration, invasion and metastasis by increasing MMPs expression and activity. Mechanistic research indicated that circEIF3I binds to the MH2 domain of SMAD3 and increases SMAD3 phosphorylation by strengthening the interactions between SMAD3 and TGFßRI on early endosomes. Moreover, AP2A1 binds with circEIF3I directly and promotes circEIF3I-bound SMAD3 recruitment to TGFßRI on early endosomes. Finally, we found that circEif3i exerts biological functions in mice similar to those of circEIF3I in humans PDAC. CONCLUSIONS: Our study reveals that circEIF3I promotes pancreatic cancer progression. circEIF3I is a molecular scaffold that interacts with SMAD3 and AP2A1 to form a ternary complex, that facilitates the recruitment of SMAD3 to early endosomes and then activates the TGF-ß signalling pathway. Hence, circEIF3I is a potential prognostic biomarker and therapeutic target in PDAC.

Review of calibration strategies for discrete element model in quasi-static elastic deformation.

This study first reviewed theories of the mechanical response of structures under loading, and the discrete element method provides a route for studying mechanical response including elastic deformation and structure failure. However, the direct acquisition of the microscopic parameters from the governing equations of the discrete element method via experiments encounters challenges. One possible strategy to obtain these microscopic parameters is parameter calibration that are widely used by researchers. Secondly, the governing equations and failure criterion of the discrete element method are summarized, and the microscopic parameters that would be calibrated are pinpointed. Next, the principles of classical calibration methods of discrete element method are explicated in detail, alongside the validation and discussion of their properties. Lastly, this study examined the applicability of calibrated parameters and points out that the size ratio, porosity, maximum radius, and minimum radius of particles should be identical in both the geometric calibration model and that for applications.

Reversing skin cancer adversarial examples by multiscale diffusive and denoising aggregation mechanism.

Reliable skin cancer diagnosis models play an essential role in early screening and medical intervention. Prevailing computer-aided skin cancer classification systems employ deep learning approaches. However, recent studies reveal their extreme vulnerability to adversarial attacks - often imperceptible perturbations to significantly reduce the performances of skin cancer diagnosis models. To mitigate these threats, this work presents a simple, effective, and resource-efficient defense framework by reverse engineering adversarial perturbations in skin cancer images. Specifically, a multiscale image pyramid is first established to better preserve discriminative structures in the medical imaging domain. To neutralize adversarial effects, skin images at different scales are then progressively diffused by injecting isotropic Gaussian noises to move the adversarial examples to the clean image manifold. Crucially, to further reverse adversarial noises and suppress redundant injected noises, a novel multiscale denoising mechanism is carefully designed that aggregates image information from neighboring scales. We evaluated the defensive effectiveness of our method on ISIC 2019, a largest skin cancer multiclass classification dataset. Experimental results demonstrate that the proposed method can successfully reverse adversarial perturbations from different attacks and significantly outperform some state-of-the-art methods in defending skin cancer diagnosis models.

Enhanced Cell Wall and Cell Membrane Activity Promotes Heat Adaptation of Enterococcus faecium.

Enterococcus faecium (E. faecium) is widely used in foods and is known as a probiotic to treat or prevent diarrhea in pets and livestock. However, the poor resistance of E. faecium to high temperature processing procedures limits its use. Strain domestication is a low-cost and effective method to obtain high-temperature-resistant strains. In this study, heat treatment was performed from 45 °C to 70 °C and the temperature was gradually increased by 5 °C every 3 days. After domestication, the survival rates of the high temperature adaptation strain RS047-wl under 65 °C water bath for 40 min was 11.5 times higher than WT RS047. Moreover, the saturated fatty acid (SFA) contents in cell membrane and the cell volume significantly increased in the RS047-wl. The combined transcriptomic, metabolomic, and proteomics analysis results showed a significant enhancement of cell wall and membrane synthesis ability in the RS047-wl. In conclusion, one of the main factors contributing to the improved high temperature resistance of RS047-wl was its enhanced ability to synthesize cell wall and membrane, which helped maintain normal cell morphology. Developing a high-temperature-resistant strain and understanding its mechanism enables it to adapt to high temperatures. This lays the groundwork for its future development and application.

Expanded Multivariable Models to Assist Patient Selection for Long-Acting Cabotegravir + Rilpivirine Treatment: Clinical Utility of a Combination of Patient, Drug Concentration, and Viral Factors Associated With Virologic Failure.

BACKGROUND: Previously reported post hoc multivariable analyses exploring predictors of confirmed virologic failure (CVF) with cabotegravir + rilpivirine long-acting (CAB + RPV LA) were expanded to include data beyond week 48, additional covariates, and additional participants. METHODS: Pooled data from 1651 participants were used to explore dosing regimen (every 4 or every 8 weeks), demographic, viral, and pharmacokinetic covariates as potential predictors of CVF. Prior dosing regimen experience was accounted for using 2 populations. Two models were conducted in each population-baseline factor analyses exploring factors known at baseline and multivariable analyses exploring baseline factors plus postbaseline model-predicted CAB/RPV trough concentrations (4 and 44 weeks postinjection). Retained factors were evaluated to understand their contribution to CVF (alone or in combination). RESULTS: Overall, 1.4% (n = 23/1651) of participants had CVF through 152 weeks. The presence of RPV resistance-associated mutations, human immunodeficiency virus-1 subtype A6/A1, and body mass index ≥30 kg/m2 were associated with an increased risk of CVF (P < .05 adjusted incidence rate ratio), with participants with ≥2 of these baseline factors having a higher risk of CVF. Lower model-predicted CAB/RPV troughs were additional factors retained for multivariable analyses. CONCLUSIONS: The presence of ≥2 baseline factors (RPV resistance-associated mutations, A6/A1 subtype, and/or body mass index ≥30 kg/m2) was associated with increased CVF risk, consistent with prior analyses. Inclusion of initial model-predicted CAB/RPV trough concentrations (≤first quartile) did not improve the prediction of CVF beyond the presence of a combination of ≥2 baseline factors, reinforcing the clinical utility of the baseline factors in the appropriate use of CAB + RPV LA.

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms.

This article focuses on conditional generative modeling (CGM) for image data with continuous, scalar conditions (termed regression labels). We propose the first model for this task which is called continuous conditional generative adversarial network (CcGAN). Existing conditional GANs (cGANs) are mainly designed for categorical conditions (e.g., class labels). Conditioning on regression labels is mathematically distinct and raises two fundamental problems: (P1) since there may be very few (even zero) real images for some regression labels, minimizing existing empirical versions of cGAN losses (a.k.a. empirical cGAN losses) often fails in practice; and (P2) since regression labels are scalar and infinitely many, conventional label input mechanisms (e.g., combining a hidden map of the generator/discriminator with a one-hot encoded label) are not applicable. We solve these problems by: (S1) reformulating existing empirical cGAN losses to be appropriate for the continuous scenario; and (S2) proposing a naive label input (NLI) mechanism and an improved label input (ILI) mechanism to incorporate regression labels into the generator and the discriminator. The reformulation in (S1) leads to two novel empirical discriminator losses, termed the hard vicinal discriminator loss (HVDL) and the soft vicinal discriminator loss (SVDL) respectively, and a novel empirical generator loss. Hence, we propose four versions of CcGAN employing different proposed losses and label input mechanisms. The error bounds of the discriminator trained with HVDL and SVDL, respectively, are derived under mild assumptions. To evaluate the performance of CcGANs, two new benchmark datasets (RC-49 and Cell-200) are created. A novel evaluation metric (Sliding Fréchet Inception Distance) is also proposed to replace Intra-FID when Intra-FID is not applicable. Our extensive experiments on several benchmark datasets (i.e., RC-49, UTKFace, Cell-200, and Steering Angle with both low and high resolutions) support the following findings: the proposed CcGAN is able to generate diverse, high-quality samples from the image distribution conditional on a given regression label; and CcGAN substantially outperforms cGAN both visually and quantitatively.

Tumor Cell Derived Lnc-FSD2-31:1 Contributes to Cancer-Associated Fibroblasts Activation in Pancreatic Ductal Adenocarcinoma Progression through Extracellular Vesicles Cargo MiR-4736.

Pancreatic ductal adenocarcinoma (PDAC) presents with high mortality and short overall survival. Cancer-associated fibroblasts (CAFs) act as refuge for cancer cells in PDAC. Mechanisms of intracelluar communication between CAFs and cancer cells need to be explored. Long noncoding RNAs (lncRNAs) are involved in the modulation of oncogenesis and tumor progression of PDAC; however, specific lncRNAs and their mechanism of action have not been clarified clearly in tumoral microenvironment. This work aims to identify novel lncRNAs involved in cellular interaction between cancer cells and CAFs in PDAC. To this end, differentially expressed lncRNAs between long-term and short-term survival PDAC patients are screened. Lnc-FSD2-31:1 is found to be significantly increased in long-term survival patients. This work then discovers that tumor-derived lnc-FSD2-31:1 restrains CAFs activation via miR-4736 transported by extracellular vesicles (EVs) in vitro and in vivo. Mechanistically, EVs-derived miR-4736 suppresses autophagy and contributes to CAFs activation by targeting ATG7. Furthermore, blocking miR-4736 suppresses tumor growth in genetically engineered KPC (LSL-KrasG12D/+, LSL-Trp53R172H/+, and Pdx-1-Cre) mouse model of PDAC. This study demonstrates that intratumoral lnc-FSD2-31:1 modulates autophagy in CAFs resulting in their activation through EVs-derived miR-4736. Targeting miR-4736 may be a potential biomarker and therapeutic target for PDAC.

Divide and Conquer: A Flexible Deep Learning Strategy for Exploring Metabolic Heterogeneity from Mass Spectrometry Imaging Data.

Research on metabolic heterogeneity provides an important basis for the study of the molecular mechanism of a disease and personalized treatment. The screening of metabolism-related sub-regions that affect disease development is essential for the more focused exploration on disease progress aberrant phenotypes, even carcinogenesis and metastasis. The mass spectrometry imaging (MSI) technique has distinct advantages to reveal the heterogeneity of an organism based on in situ molecular profiles. The challenge of heterogeneous analysis has been to perform an objective identification among biological tissues with different characteristics. By introducing the divide-and-conquer strategy to architecture design and application, we establish here a flexible unsupervised deep learning model, called divide-and-conquer (dc)-DeepMSI, for metabolic heterogeneity analysis from MSI data without prior knowledge of histology. dc-DeepMSI can be used to identify either spatially contiguous regions of interest (ROIs) or spatially sporadic ROIs by designing two specific modes, spat-contig and spat-spor. Comparison results on fetus mouse data demonstrate that the dc-DeepMSI outperforms state-of-the-art MSI segmentation methods. We demonstrate that the novel learning strategy successfully obtained sub-regions that are statistically linked to the invasion status and molecular phenotypes of breast cancer as well as organizing principles during developmental phase.

SSD-KD: A self-supervised diverse knowledge distillation method for lightweight skin lesion classification using dermoscopic images.

Skin cancer is one of the most common types of malignancy, affecting a large population and causing a heavy economic burden worldwide. Over the last few years, computer-aided diagnosis has been rapidly developed and make great progress in healthcare and medical practices due to the advances in artificial intelligence, particularly with the adoption of convolutional neural networks. However, most studies in skin cancer detection keep pursuing high prediction accuracies without considering the limitation of computing resources on portable devices. In this case, the knowledge distillation (KD) method has been proven as an efficient tool to help improve the adaptability of lightweight models under limited resources, meanwhile keeping a high-level representation capability. To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin disease classification. Our method models an intra-instance relational feature representation and integrates it with existing KD research. A dual relational knowledge distillation architecture is self-supervised trained while the weighted softened outputs are also exploited to enable the student model to capture richer knowledge from the teacher model. To demonstrate the effectiveness of our method, we conduct experiments on ISIC 2019, a large-scale open-accessed benchmark of skin diseases dermoscopic images. Experiments show that our distilled MobileNetV2 can achieve an accuracy as high as 85% for the classification tasks of 8 different skin diseases with minimal parameters and computing requirements. Ablation studies confirm the effectiveness of our intra- and inter-instance relational knowledge integration strategy. Compared with state-of-the-art knowledge distillation techniques, the proposed method demonstrates improved performance. To the best of our knowledge, this is the first deep knowledge distillation application for multi-disease classification on the large-scale dermoscopy database. Our codes and models are available at https://github.com/enkiwang/Portable-Skin-Lesion-Diagnosis.

Gut microbiota-derived nicotinamide mononucleotide alleviates acute pancreatitis by activating pancreatic SIRT3 signalling.

BACKGROUND AND PURPOSE: Gut microbiota dysbiosis induced by acute pancreatitis (AP) exacerbates pancreatic injury and systemic inflammatory responses. The alleviation of gut microbiota dysbiosis through faecal microbiota transplantation (FMT) is considered a potential strategy to reduce tissue damage and inflammation in many clinical disorders. Here, we aim to investigate the effect of gut microbiota and microbiota-derived metabolites on AP and further clarify the mechanisms associated with pancreatic damage and inflammation. EXPERIMENTAL APPROACH: AP rat and mouse models were established by administration of caerulein or sodium taurocholate in vivo. Pancreatic acinar cells were exposed to caerulein and lipopolysaccharide in vitro to simulate AP. KEY RESULTS: Normobiotic FMT alleviated AP-induced gut microbiota dysbiosis and ameliorated the severity of AP, including mitochondrial dysfunction, oxidative damage and inflammation. Normobiotic FMT induced higher levels of NAD+ (nicotinamide adenine dinucleotide)-associated metabolites, particularly nicotinamide mononucleotide (NMN). NMN administration mitigated AP-mediated mitochondrial dysfunction, oxidative damage and inflammation by increasing pancreatic NAD+ levels. Similarly, overexpression of the NAD+ -dependent mitochondrial deacetylase sirtuin 3 (SIRT3) alleviated the severity of AP. Furthermore, SIRT3 deacetylated peroxiredoxin 5 (PRDX5) and enhanced PRDX5 protein expression, thereby promoting its antioxidant and anti-inflammatory activities in AP. Importantly, normobiotic FMT-mediated NMN metabolism induced SIRT3-PRDX5 pathway activation during AP. CONCLUSION AND IMPLICATIONS: Gut microbiota-derived NMN alleviates the severity of AP by activating the SIRT3-PRDX5 pathway. Normobiotic FMT could be served as a potential strategy for AP treatment.

A modified single-needle continuous suture of duct-to-mucosa pancreaticojejunostomy in pancreaticoduodenectomy.

Background: The pancreatic reconstruction technique decides the incidence of postoperative pancreatic fistulas (POPF) in pancreaticoduodenectomy (PD). This study aims to evaluate the safety of modified single-needle continuous suture (SNCS) of duct-to-mucosa and compare the efficacy with double-layer continuous suture (DLCS) of duct-mucosa pancreaticojejunostomy (PJ) in open PD (OPD). Methods: A total of 266 patients that received PD between January 2019 and May 2023 were retrospectively analyzed. Among them, 130 patients underwent DLCS, and 136 patients underwent SNCS [73 OPD and 63 laparoscopic PD (LPD)]. The primary outcome was clinically relevant POPF (CR-POPF) according to the definition of the revised 2016 International Study Group of Pancreatic Fistula (ISGPF). Propensity score matching (PSM) was conducted to reduce confounding bias. Results: A total of 66 pairs were successfully matched using PSM in OPD. No significant difference was observed in the occurrence of CR-POPF between the two groups (9.1% vs. 21.2%, P=0.052). However, the median duration of operation and PJ was shorter in the SNCS group. The incidence of CR-POPF in LPD was 9.5%. Furthermore, regarding the alternative fistula risk score (a-FRS), the CR-POPF rate were 2.1%, 10.5%, and 15.6% in low-, intermediate-, and high-risk groups (P=0.067). Conclusions: The SNCS is a facile, safe, and effective PJ technique and does not increase the incidence of POPF, regardless of a-FRS stratification, pancreatic texture, and main pancreatic duct (MPD) size.