TME-NET: an interpretable deep neural network for predicting pan-cancer immune checkpoint inhibitor responses.

Immunotherapy with immune checkpoint inhibitors (ICIs) is increasingly used to treat various tumor types. Determining patient responses to ICIs presents a significant clinical challenge. Although components of the tumor microenvironment (TME) are used to predict patient outcomes, comprehensive assessments of the TME are frequently overlooked. Using a top-down approach, the TME was divided into five layers-outcome, immune role, cell, cellular component, and gene. Using this structure, a neural network called TME-NET was developed to predict responses to ICIs. Model parameter weights and cell ablation studies were used to investigate the influence of TME components. The model was developed and evaluated using a pan-cancer cohort of 948 patients across four cancer types, with Area Under the Curve (AUC) and accuracy as performance metrics. Results show that TME-NET surpasses established models such as support vector machine and k-nearest neighbors in AUC and accuracy. Visualization of model parameter weights showed that at the cellular layer, Th1 cells enhance immune responses, whereas myeloid-derived suppressor cells and M2 macrophages show strong immunosuppressive effects. Cell ablation studies further confirmed the impact of these cells. At the gene layer, the transcription factors STAT4 in Th1 cells and IRF4 in M2 macrophages significantly affect TME dynamics. Additionally, the cytokine-encoding genes IFNG from Th1 cells and ARG1 from M2 macrophages are crucial for modulating immune responses within the TME. Survival data from immunotherapy cohorts confirmed the prognostic ability of these markers, with p-values <0.01. In summary, TME-NET performs well in predicting immunotherapy responses and offers interpretable insights into the immunotherapy process. It can be customized at https://immbal.shinyapps.io/TME-NET.

Heparin is an effective treatment for preventing liver failure after hepatectomy.

BACKGROUND: Posthepatectomy liver failure (PHLF) is one of the most important causes of death following liver resection. Heparin, an established anticoagulant, can protect liver function through a number of mechanisms, and thus, prevent liver failure. AIM: To look at the safety and efficacy of heparin in preventing hepatic dysfunction after hepatectomy. METHODS: The data was extracted from Multiparameter Intelligent Monitoring in Intensive Care III (MIMIC-III) v1. 4 pinpointed patients who had undergone hepatectomy for liver cancer, subdividing them into two cohorts: Those who were injected with heparin and those who were not. The statistical evaluations used were unpaired t-tests, Mann-Whitney U tests, chi-square tests, and Fisher's exact tests to assess the effect of heparin administration on PHLF, duration of intensive care unit (ICU) stay, need for mechanical ventilation, use of continuous renal replacement therapy (CRRT), incidence of hypoxemia, development of acute kidney injury, and ICU mortality. Logistic regression was utilized to analyze the factors related to PHLF, with propensity score matching (PSM) aiming to balance the preoperative disparities between the two groups. RESULTS: In this study, 1388 patients who underwent liver cancer hepatectomy were analyzed. PSM yielded 213 matched pairs from the heparin-treated and control groups. Initial univariate analyses indicated that heparin potentially reduces the risk of PHLF in both matched and unmatched samples. Further analysis in the matched cohorts confirmed a significant association, with heparin reducing the risk of PHLF (odds ratio: 0.518; 95% confidence interval: 0.295-0.910; P = 0.022). Additionally, heparin treatment correlated with improved short-term postoperative outcomes such as reduced ICU stay durations, diminished requirements for respiratory support and CRRT, and lower incidences of hypoxemia and ICU mortality. CONCLUSION: Liver failure is an important hazard following hepatic surgery. During ICU care heparin administration has been proved to decrease the occurrence of hepatectomy induced liver failure. This indicates that heparin may provide a hopeful option for controlling PHLF.

Nitrogen-Mediated Promotion of Cobalt-Based Oxygen Evolution Catalyst for Practical Anion-Exchange Membrane Electrolysis.

Scarce and expensive iridium oxide is still the cornerstone catalyst of polymer-electrolyte membrane electrolyzers for green hydrogen production because of its exceptional stability under industrially relevant oxygen evolution reaction (OER) conditions. Earth-abundant transition metal oxides used for this task, however, show poor long-term stability. We demonstrate here the use of nitrogen-doped cobalt oxide as an effective iridium substitute. The catalyst exhibits a low overpotential of 240 mV at 10 mA cm-2 and negligible activity decay after 1000 h of operation in an alkaline electrolyte. Incorporation of nitrogen dopants not only triggers the OER mechanism switched from the traditional adsorbate evolution route to the lattice oxygen oxidation route but also achieves oxygen nonbonding (ONB) states as electron donors, thereby preventing structural destabilization. In a practical anion-exchange membrane water electrolyzer, this catalyst at anode delivers a current density of 1000 mA cm-2 at 1.78 V and an electrical efficiency of 47.8 kW-hours per kilogram hydrogen.

Long-term outcome of definitive radiotherapy for locally advanced non-small cell lung cancer: A real-world single-center study in the pre-durvalumab era.

BACKGROUND: There was limited research data on large-scale locally advanced non-small cell lung cancer (LA-NSCLC) radical radiotherapy (RT) reported in China. This study examined overall survival (OS), progression-free survival (PFS), treatment effectiveness, and toxicity in patients with LA-NSCLC treated with definitive RT in the pre-durvalumab era. METHODS: A retrospective analysis of demographic information, clinical characteristics, treatment patterns, and clinical outcomes of 789 patients with LA-NSCLC who underwent radical RT at our center between January 2005 and December 2015 was performed. The Kaplan-Meier method and log-rank test were used for survival comparisons, and Cox regression was used for multivariate analysis. RESULTS: There were 328 patients with stage IIIA disease and 461 with stage IIIB disease. By the last follow-up, there were 365 overall deaths and 576 cases of recurrence, metastasis, or death. The median survival time was 31 months. The OS rates at 1, 2, 5, and 10 years were 83.7%, 59.5%, 28.8%, and 18.9%, respectively. PFS rates at 1, 2, 5, and 10 years were 48%, 24.5%, 11.9%, and 5.5%, respectively. Rates of ≥grade 3 acute radiation pneumonitis or esophagitis were 7.6% and 1.9%, respectively. Rates of ≥grade 3 chronic radiation pneumonitis and esophagitis were 11% and 0.4%, respectively. Multivariate analysis showed that the Karnofsky Performance Status (KPS) score, smoking status, and combined chemotherapy were prognostic factors for OS (p < 0.05). Multivariate analysis revealed that combined chemotherapy and radiation dose were prognostic factors for PFS (p < 0.05). CONCLUSIONS: Our center's data showed that the survival prognosis of locally advanced patients receiving RT and chemotherapy in China was consistent with international levels during the same period. Patients with a KPS score of 80 or higher, who had never smoked or received combined RT, had a more favorable prognosis than those with a KPS of less than 80, who had smoked, or only received RT. The combination of RT and chemotherapy, with a reasonable radiation dose, was the key to improving the therapeutic effect.

Radiomic analysis reveals diverse prognostic and molecular insights into the response of breast cancer to neoadjuvant chemotherapy: a multicohort study.

BACKGROUND: Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. METHODS: This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. RESULTS: The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. CONCLUSIONS: Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival.

Global profiling of protein lactylation in microglia in experimental high-altitude cerebral edema.

BACKGROUND: High-altitude cerebral edema (HACE) is considered an end-stage acute mountain sickness (AMS) that typically occurs in people after rapid ascent to 2500 m or more. While hypoxia is a fundamental feature of the pathophysiological mechanism of HACE, emerging evidence suggests that inflammation serves as a key risk factor in the occurrence and development of this disease. However, little is known about the molecular mechanism underlying their crosstalk. METHODS: A mouse HACE model was established by combination treatment with hypobaric hypoxia exposure and lipopolysaccharides (LPS) stimulation. Lactylated-proteomic analysis of microglia was performed to reveal the global profile of protein lactylation. Molecular modeling was applied to evaluate the 3-D modeling structures. A combination of experimental approaches, including western blotting, quantitative real-time reverse transcriptionpolymerase chain reaction (qRT-PCR), and enzyme-linked immunosorbent assay (ELISA), confocal microscopy and RNA interference, were used to explore the underlying molecular mechanisms. RESULTS: We found that hypoxia exposure increased the lactate concentration and lactylation in mouse HACE model. Moreover, hypoxia aggravated the microglial neuroinflammatory response in a lactate-dependent manner. Global profiling of protein lactylation has shown that a large quantity of lysine-lactylated proteins are induced by hypoxia and preferentially occur in protein complexes, such as the NuRD complex, ribosome biogenesis complex, spliceosome complex, and DNA replication complex. The molecular modeling data indicated that lactylation could affect the 3-D theoretical structure and increase the solvent accessible surface area of HDAC1, MTA1 and Gatad2b, the core members of the NuRD complex. Further analysis by knockdown or selectively inhibition indicated that the NuRD complex is involved in hypoxia-mediated aggravation of inflammation. CONCLUSIONS: These results revealed a comprehensive profile of protein lactylation in microglia and suggested that protein lysine lactylation plays an important role in the regulation of protein function and subsequently contributes to the neuroinflammatory response under hypoxic conditions.

Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder.

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/ß-hydrolase domain-containing 6 (ABHD6), ß 1,3-N-acetylglucosaminyltransferase-9(ß3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, ß3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Computed tomography three-dimensional reconstruction in the diagnosis of bleeding small intestinal polyps: A case report.

BACKGROUND: Computed tomography (CT) small bowel three-dimensional (3D) reconstruction is a powerful tool for the diagnosis of small bowel disease and can clearly show the intestinal lumen and wall as well as the outside structure of the wall. The horizontal axis position can show the best adjacent intestinal tube and the lesion between the intestinal tubes, while the coronal position can show the overall view of the small bowel. The ileal end of the localization of the display of excellent, and easy to quantitative measurement of the affected intestinal segments, the sagittal position for the rectum and the pre-sacral lesions show the best, for the discovery of fistulae is also helpful. Sagittal view can show rectal and presacral lesions and is useful for fistula detection. It is suitable for the assessment of inflammatory bowel disease, such as assessment of disease severity and diagnosis and differential diagnosis of the small bowel and mesenteric space-occupying lesions as well as the judgment of small bowel obstruction points. CASE SUMMARY: Bleeding caused by small intestinal polyps is often difficult to diagnose in clinical practice. This study reports a 29-year-old male patient who was admitted to the hospital with black stool and abdominal pain for 3 months. Using the combination of CT-3D reconstruction and capsule endoscopy, the condition was diagnosed correctly, and the polyps were removed using single-balloon enteroscopy-endoscopic retrograde cholangiopancreatography without postoperative complications. CONCLUSION: The role of CT-3D in gastrointestinal diseases was confirmed. CT-3D can assist in the diagnosis and treatment of gastrointestinal diseases in combination with capsule endoscopy and small intestinal microscopy.

Photoelectrochemical properties of self-powered corundum-structured Ga2O3nanorod array/fluorine-doped SnO2photodetectors modulated by precursor concentrations.

Herein, corundum-structured Ga2O3(α-Ga2O3) nanorod array/fluorine-doped SnO2(FTO) structures have been fabricated by hydrothermal and thermal annealing processes with different precursor concentrations from 0.01 to 0.06 M. The diameter and length of the nanorod arrays are much larger with increasing precursor concentrations due to more nucleation sites and precursor ions participating in the reaction procedures. The optical bandgap decreases from 4.75 to 4.47 eV because of the tensile stress relieving with increasing the precursor concentrations. Based on self-powered photoelectrochemical (PEC) photodetectors, the peak responsivity is improved from ∼0.33 mA W-1for 0.06 M to ∼1.51 mA W-1for 0.02 M. Schottky junctions can be formed in PEC cells. More photogenerated carriers can be produced in wider depletion region. From Mott-Schottky plots, the depletion regions become much wider with decreasing the precursor concentrations. Therefore, the enhance responsivity is owing to the wider depletion regions. Due to the reduced possibility of photogenerated holes captured by traps ascribed from fewer green and yellow luminescence defects, smaller charge transfer resistance, and shorter transportation route, the decay time becomes much faster through decreasing the precursor concentrations. Compared with the other self-poweredα-Ga2O3-nanorod-array-based PEC photodetectors, it shows the fastest response time (decay time of 0.005 s/0.026 s) simply modulated by precursor concentrations for the first time without employing complex precursors, seed layers or special device designs. Compared with other high-responsivity monoclinic Ga2O3(ß-Ga2O3) self-powered photodetectors, our devices also show comparable response speed with simple control and design. This work provides the realization of fast-speed self-powered Ga2O3based solar-blind ultraviolet photodetectors by simple modulation processes and design, which is a significant guidance for their applications in warnings, imaging, computing, communication and logic circuit, in the future.

Hydrogel-exosome system in tissue engineering: A promising therapeutic strategy.

Characterized by their pivotal roles in cell-to-cell communication, cell proliferation, and immune regulation during tissue repair, exosomes have emerged as a promising avenue for "cell-free therapy" in clinical applications. Hydrogels, possessing commendable biocompatibility, degradability, adjustability, and physical properties akin to biological tissues, have also found extensive utility in tissue engineering and regenerative repair. The synergistic combination of exosomes and hydrogels holds the potential not only to enhance the efficiency of exosomes but also to collaboratively advance the tissue repair process. This review has summarized the advancements made over the past decade in the research of hydrogel-exosome systems for regenerating various tissues including skin, bone, cartilage, nerves and tendons, with a focus on the methods for encapsulating and releasing exosomes within the hydrogels. It has also critically examined the gaps and limitations in current research, whilst proposed future directions and potential applications of this innovative approach.

Hydrogel-based immunoregulation of macrophages for tissue repair and regeneration.

The rational design of hydrogel materials to modulate the immune microenvironment has emerged as a pivotal approach in expediting tissue repair and regeneration. Within the immune microenvironment, an array of immune cells exists, with macrophages gaining prominence in the field of tissue repair and regeneration due to their roles in cytokine regulation to promote regeneration, maintain tissue homeostasis, and facilitate repair. Macrophages can be categorized into two types: classically activated M1 (pro-inflammatory) and alternatively activated M2 (anti-inflammatory and pro-repair). By regulating the physical and chemical properties of hydrogels, the phenotypic transformation and cell behavior of macrophages can be effectively controlled, thereby promoting tissue regeneration and repair. A full understanding of the interaction between hydrogels and macrophages can provide new ideas and methods for future tissue engineering and clinical treatment. Therefore, this paper reviews the effects of hydrogel components, hardness, pore size, and surface morphology on cell behaviors such as macrophage proliferation, migration, and phenotypic polarization, and explores the application of hydrogels based on macrophage immune regulation in skin, bone, cartilage, and nerve tissue repair. Finally, the challenges and future prospects of macrophage-based immunomodulatory hydrogels are discussed.

Nucleolin lactylation contributes to intrahepatic cholangiocarcinoma pathogenesis via RNA splicing regulation of MADD.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinoma (iCCA) is a fatal malignancy of the biliary system. The lack of a detailed understanding of oncogenic signaling or global gene expression alterations has impeded clinical iCCA diagnosis and therapy. The role of protein lactylation, a newly unraveled post-translational modification that orchestrates gene expression, remains largely elusive in the pathogenesis of iCCA. METHODS: Proteomics analysis of clinical iCCA specimens and adjacent tissues was performed to screen for proteins aberrantly lactylated in iCCA. Mass spectrometry, macromolecule interaction and cell behavioral studies were employed to identify the specific lactylation sites on the candidate protein(s) and to decipher the downstream mechanisms responsible for iCCA development, which were subsequently validated using a xenograft tumor model and clinical samples. RESULTS: Nucleolin (NCL), the most abundant RNA-binding protein in the nucleolus, was identified as a functional lactylation target that correlates with iCCA occurrence and progression. NCL was lactylated predominantly at lysine 477 by the acyltransferase P300 in response to a hyperactivity of glycolysis, and promoted the proliferation and invasion of iCCA cells. Mechanistically, lactylated NCL bound to the primary transcript of MAP kinase-activating death domain protein (MADD) and led to efficient translation of MADD by circumventing alternative splicing that generates a premature termination codon. NCL lactylation, MADD translation and subsequent ERK activation promoted xenograft tumor growth and were associated with overall survival in patients with iCCA. CONCLUSION: NCL is lactylated to upregulate MADD through an RNA splicing-dependent mechanism, which potentiates iCCA pathogenesis via the MAPK pathway. Our findings reveal a novel link between metabolic reprogramming and canonical tumor-initiating events, and uncover biomarkers that can potentially be used for prognostic evaluation or targeted treatment of iCCA. IMPACT AND IMPLICATIONS: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy with largely uncharacterized pathogenetic mechanisms. Herein, we demonstrated that glycolysis promotes P300-catalyzed lactylation of nucleolin, which upregulates MAP kinase-activating death domain protein (MADD) through precise mRNA splicing and activates ERK signaling to drive iCCA development. These findings unravel a novel link between metabolic rewiring and canonical oncogenic pathways, and reveal new biomarkers for prognostic assessment and targeting of clinical iCCA.

Enhancement of Tumorigenicity, Spheroid Niche, and Drug Resistance of Pancreatic Cancer Cells in Three-Dimensional Culture System.

The three-dimensional (3D) cell culture technique has been applied comprehensively as a variable platform for medical research, biochemical signal pathway analysis, and evaluation of anti-tumor treatment response due to an excellent recapitulation of a tumor microenvironment (TME) in the in vitro cultured cancer cells. Pancreatic cancer (PaC) is one of the toughest malignancies with a complex TME and refractory treatment response. To comprehensively study the TME of PaC, there is an eager need to develop a 3D culture model to decompose the cellular components and their cross interactions. Herein, we establish a 3D PaC culture system with cancer stem cell (CSC) and scalability properties. To validate our model, we tested the individual PaC cell and the combined effects with cancer-associated fibroblasts (CAFs) on cancer tumorigenicity, the cellular interaction through the CXCR3/CXCL10 axis, and cellular responses reflection of anti-cancer treatments. With the help of our 3D technology, a simulated malignant spheroid with important stromal populations and TME physiochemical properties may be successfully recreated. It can be used in a wide range of preclinical research and helpful in advancing basic and translational cancer biology.

Generative adversarial network-based synthesis of contrast-enhanced MR images from precontrast images for predicting histological characteristics in breast cancer.

Objective. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a sensitive tool for assessing breast cancer by analyzing tumor blood flow, but it requires gadolinium-based contrast agents, which carry risks such as brain retention and astrocyte migration. Contrast-free MRI is thus preferable for patients with renal impairment or who are pregnant. This study aimed to investigate the feasibility of generating contrast-enhanced MR images from precontrast images and to evaluate the potential use of synthetic images in diagnosing breast cancer.Approach. This retrospective study included 322 women with invasive breast cancer who underwent preoperative DCE-MRI. A generative adversarial network (GAN) based postcontrast image synthesis (GANPIS) model with perceptual loss was proposed to generate contrast-enhanced MR images from precontrast images. The quality of the synthesized images was evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The diagnostic performance of the generated images was assessed using a convolutional neural network to predict Ki-67, luminal A and histological grade with the area under the receiver operating characteristic curve (AUC). The patients were divided into training (n= 200), validation (n= 60), and testing sets (n= 62).Main results. Quantitative analysis revealed strong agreement between the generated and real postcontrast images in the test set, with PSNR and SSIM values of 36.210 ± 2.670 and 0.988 ± 0.006, respectively. The generated postcontrast images achieved AUCs of 0.918 ± 0.018, 0.842 ± 0.028 and 0.815 ± 0.019 for predicting the Ki-67 expression level, histological grade, and luminal A subtype, respectively. These results showed a significant improvement compared to the use of precontrast images alone, which achieved AUCs of 0.764 ± 0.031, 0.741 ± 0.035, and 0.797 ± 0.021, respectively.Significance. This study proposed a GAN-based MR image synthesis method for breast cancer that aims to generate postcontrast images from precontrast images, allowing the use of contrast-free images to simulate kinetic features for improved diagnosis.

Modulation of Porcine Gut Microbiota and Microbiome: Hologenomic, Dietary, and Endogenous Factors.

Global pig production contributes to about 35% of the world's meat production and consumption [...].

Post-death Vesicles of Senescent Bone Marrow Mesenchymal Stromal Polyploids Promote Macrophage Aging and Breast Cancer.

Potential systemic factors contributing to aging-associated breast cancer (BC) remain elusive. Here, we reveal that the polyploid giant cells (PGCs) that contain more than two sets of genomes prevailing in aging and cancerous tissues constitute 5-10% of healthy female bone marrow mesenchymal stromal cells (fBMSCs). The PGCs can repair DNA damage and stimulate neighboring cells for clonal expansion. However, dying PGCs in advanced-senescent fBMSCs can form "spikings" which are then separated into membraned mtDNA-containing vesicles (Senescent PGC-Spiking Bodies; SPSBs). SPSB-phagocytosed macrophages accelerate aging with diminished clearance on BC cells and protumor M2 polarization. SPSB-carried mitochondrial OXPHOS components are enriched in BC of elder patients and associated with poor prognosis. SPSB-incorporated breast epithelial cells develop aggressive characteristics and PGCs resembling the polyploid giant cancer cells (PGCCs) in clonogenic BC cells and cancer tissues. These findings highlight an aging BMSC-induced BC risk mediated by SPSB-induced macrophage dysfunction and epithelial cell precancerous transition. SIGNIFICANCE: Mechanisms underlying aging-associated cancer risk remain unelucidated. This work demonstrates that polyploid giant cells (PGCs) in bone marrow mesenchymal stromal cells (BMSCs) from healthy female bone marrow donors can boost neighboring cell proliferation for clonal expansion. However, the dying-senescent PGCs in the advanced-senescent fBMSCs can form "spikings" which are separated into mitochondrial DNA (mtDNA)-containing spiking bodies (senescent PGC-spiking bodies; SPSBs). The SPSBs promote macrophage aging and breast epithelial cell protumorigenic transition and form polyploid giant cancer cells. These results demonstrate a new form of ghost message from dying-senescent BMSCs, that may serve as a systemic factor contributing to aging-associated immunosuppression and breast cancer risk.

Relationship of solid fuels use with cognitive function and efficacy of switching to cleaner fuels or using ventilation: A systematic review and meta-analysis.

BACKGROUND: A growing number of studies have examined the relation between solid fuels use and cognitive function in the mid-elderly, but results are inconsistent. Therefore, a systematic review and meta-analysis was carried out to evaluate their relevance and the efficacy of switching to cleaner fuels or using ventilation. METHOD: We used PubMed, Web of Science, and Cochrane Library databases to identify 17 studies in which the primary outcome variable was cognitive function decline or cognitive disorders, and the exposure measure was solid fuels use. The final search date of August 31, 2023. The effect size of odds ratio (OR), regression coefficient (ß), and 95% confidence interval (CI) were pooled. Heterogeneity and the possibility of publication bias were assessed by using the Q-statistic and Begg's test, respectively. RESULT: Among the 17 included papers, the study participants were ≥45 years old. Eleven studies assessed the relationship between solid fuels use and cognitive function decline [number of studies (n) = 11, ß = -0.144; I2 = 97.7%]. Five studies assessed the relationship between solid fuels use and cognitive disorders (n = 5, OR = 1.229; I2 = 41.1%). Switching from using solid fuels to clean fuels could reduce the risk of cognitive function decline as compared to those who remained on using solid fuels (n = 2; ß = 0.710; I2 = 82.4%). Among participants using solid fuels, who cooked without on ventilated stoves were correlated with an enhanced risk of cognitive disorders as compared to participants who cooked with ventilated stoves (n = 2; OR = 1.358; I2 = 44.7%). CONCLUSION: Our meta-analysis showed a negative relationship between solid fuels use with cognitive function, and a positive relationship with cognitive disorders. Cleaner fuels, using ventilation, improved cookstoves can reduce the adverse health hazards of solid fuels use.

Monomodular and multifunctional processive endocellulases: implications for swine nutrition and gut microbiome.

Poor efficiency of dietary fibre utilization not only limits global pork production profit margin but also adversely affects utilization of various dietary nutrients. Poor efficiency of dietary nutrient utilization further leads to excessive excretion of swine manure nutrients and results in environmental impacts of emission of major greenhouse gases (GHG), odor, nitrate leaching and surface-water eutrophication. Emission of the major GHG from intensive pork production contributes to global warming and deteriorates heat stress to pigs in tropical and sub-tropical swine production. Exogenous fibre enzymes of various microbial cellulases, hemicellulases and pectinases have been well studied and used in swine production as the non-nutritive gut modifier feed enzyme additives in the past over two decades. These research efforts have aimed to improve growth performance, nutrient utilization, intestinal fermentation as well as gut physiology, microbiome and health via complementing the porcine gut symbiotic microbial fibrolytic activities towards dietary fibre degradation. The widely reported exogenous fibre enzymes include the singular use of respective cellulases, hemicellulases and pectinases as well as their multienzyme cocktails. The currently applied exogenous fibre enzymes are largely limited by their inconsistent in vivo efficacy likely due to their less defined enzyme stability and limited biochemical property. More recently characterized monomodular, multifunctional and processive endoglucanases have the potential to be more efficaciously used as the next-generation designer fibre biocatalysts. These newly emerging multifunctional and processive endoglucanases have the potential to unleash dietary fibre sugar constituents as metabolic fuels and prebiotics, to optimize gut microbiome, to maintain gut permeability and to enhance performance in pigs under a challenged environment as well as to parallelly unlock biomass to manufacture biofuels and biomaterials.

Deconvolution-Based Pharmacokinetic Analysis to Improve the Prediction of Pathological Information of Breast Cancer.

Pharmacokinetic (PK) parameters, revealing changes in the tumor microenvironment, are related to the pathological information of breast cancer. Tracer kinetic models (e.g., Tofts-Kety model) with a nonlinear least square solver are commonly used to estimate PK parameters. However, the method is sensitive to noise in images. To relieve the effects of noise, a deconvolution (DEC) method, which was validated on synthetic concentration-time series, was proposed to accurately calculate PK parameters from breast dynamic contrast-enhanced magnetic resonance imaging. A time-to-peak-based tumor partitioning method was used to divide the whole tumor into three tumor subregions with different kinetic patterns. Radiomic features were calculated from the tumor subregion and whole tumor-based PK parameter maps. The optimal features determined by the fivefold cross-validation method were used to build random forest classifiers to predict molecular subtypes, Ki-67, and tumor grade. The diagnostic performance evaluated by the area under the receiver operating characteristic curve (AUC) was compared between the subregion and whole tumor-based PK parameters. The results showed that the DEC method obtained more accurate PK parameters than the Tofts method. Moreover, the results showed that the subregion-based Ktrans (best AUCs = 0.8319, 0.7032, 0.7132, 0.7490, 0.8074, and 0.6950) achieved a better diagnostic performance than the whole tumor-based Ktrans (AUCs = 0.8222, 0.6970, 0.6511, 0.7109, 0.7620, and 0.5894) for molecular subtypes, Ki-67, and tumor grade. These findings indicate that DEC-based Ktrans in the subregion has the potential to accurately predict molecular subtypes, Ki-67, and tumor grade.