Assessment of AURKA expression and prognosis prediction in lung adenocarcinoma using machine learning-based pathomics signature.

Objective: This study aimed to develop quantitative feature-based models from histopathological images to assess aurora kinase A (AURKA) expression and predict the prognosis of patients with lung adenocarcinoma (LUAD). Methods: A dataset of patients with LUAD was derived from the cancer genome atlas (TCGA) with information on clinical characteristics, RNA sequencing and histopathological images. The TCGA-LUAD cohort was randomly divided into training (n = 229) and testing (n = 98) sets. We extracted quantitative image features from histopathological slides of patients with LUAD using computational approaches, constructed a predictive model for AURKA expression in the training set, and estimated their predictive performance in the test set. A Cox proportional hazards model was used to assess whether the pathomic scores (PS) generated by the model independently predicted LUAD survival. Results: High AURKA expression was an independent risk factor for overall survival (OS) in patients with LUAD (hazard ratio = 1.816, 95 % confidence intervals = 1.257-2.623, P = 0.001). The model based on histopathological image features had significant predictive value for AURKA expression: the area under the curve of the receiver operating characteristic curve in the training set and validation set was 0.809 and 0.739, respectively. Decision curve analysis showed that the model had clinical utility. Patients with high PS and low PS had different survival rates (P = 0.019). Multivariate analysis suggested that PS was an independent prognostic factor for LUAD (hazard ratio = 1.615, 95 % confidence intervals = 1.071-2.438, P = 0.022). Conclusion: Pathomics models based on machine learning can accurately predict AURKA expression and the PS generated by the model can predict LUAD prognosis.

Cyclodextrin-based host-guest hierarchical fire retardants: Synthesis and novel strategy to endow polylactic acid fire retardancy and UV resistance.

ß-Cyclodextrin (ß-CD) with a cage-like supramolecular structure possesses the hydrophobic internal ring and external hydroxyl groups, which are beneficial for intramolecular interactions known as "host-guest" chemistry. This study presents a ß-CD-based three-functions-in-one and host-guest fire retardant (ßCD-MOF@Schiff base), which incorporates self-crosslinking Schiff base into its cavity and modification of its surface by metal-organic framework (MOF). With the presence of 5 wt% of ßCD-MOF@Schiff base, the LOI value of PLA composites increased to 29 % and showed 15 %, 17 % and 62 % reductions in peak heat release rate (pHRR), total heat release (THR), and the yield of hazard gas carbon monoxide, respectively. The mode action of FR on fire retardation of PLA showed that the FR promoted the char formation with higher thermal stability and graphitization, and modified the decomposition path of PLA. Additionally, the PLA composites exhibited enhanced UV resistance in the UVA and UVB areas with improved UV absorbance and the UPF values improving and doubling. This work develops a new approach to preparing biodegradable FR, which simultaneously endows fire safety and anti-UV properties for PLA.

Development and external validation of a transfer learning-based system for the pathological diagnosis of colorectal cancer: a large emulated prospective study.

Background: The progress in Colorectal cancer (CRC) screening and management has resulted in an unprecedented caseload for histopathological diagnosis. While artificial intelligence (AI) presents a potential solution, the predominant emphasis on slide-level aggregation performance without thorough verification of cancer in each location, impedes both explainability and transparency. Effectively addressing these challenges is crucial to ensuring the reliability and efficacy of AI in histology applications. Method: In this study, we created an innovative AI algorithm using transfer learning from a polyp segmentation model in endoscopy. The algorithm precisely localized CRC targets within 0.25 mm² grids from whole slide imaging (WSI). We assessed the CRC detection capabilities at this fine granularity and examined the influence of AI on the diagnostic behavior of pathologists. The evaluation utilized an extensive dataset comprising 858 consecutive patient cases with 1418 WSIs obtained from an external center. Results: Our results underscore a notable sensitivity of 90.25% and specificity of 96.60% at the grid level, accompanied by a commendable area under the curve (AUC) of 0.962. This translates to an impressive 99.39% sensitivity at the slide level, coupled with a negative likelihood ratio of <0.01, signifying the dependability of the AI system to preclude diagnostic considerations. The positive likelihood ratio of 26.54, surpassing 10 at the grid level, underscores the imperative for meticulous scrutiny of any AI-generated highlights. Consequently, all four participating pathologists demonstrated statistically significant diagnostic improvements with AI assistance. Conclusion: Our transfer learning approach has successfully yielded an algorithm that can be validated for CRC histological localizations in whole slide imaging. The outcome advocates for the integration of the AI system into histopathological diagnosis, serving either as a diagnostic exclusion application or a computer-aided detection (CADe) tool. This integration has the potential to alleviate the workload of pathologists and ultimately benefit patients.

The investigation of the interaction between fluorescent carbon dots labeling silk fibroin using a fluorescence microscope-surface plasmon resonance system.

The use of fluorescent carbon dots (CDs) as highly precise biolabeling probes has been widespread in the fields of live cell imaging and protein labeling due to their small size and excellent photoluminescence ability to accurately target specific molecules with surface chemical properties. However, there was a lack of research on the interaction between CDs and labeled molecules. In this work, we presented a novel investigation strategy, the fluorescence microscopy-surface plasmon resonance (FM-SPR) system, which combined the use of fluorescence microscopy and wavelength modulation surface plasmon resonance to study the interaction between CDs and labeled molecules in real-time. Using this system, simultaneously recorded the SPR signals and the fluorescence images on the surface of the FM-SPR sensor chip. We observed the dynamic curve and fluorescence images of the interaction between green emissive nitrogen-doped carbon dots (N-CDs) and silk fibroin (SF) in real-time. The kinetic parameters, the quantitative analysis, and the investigation of the binding could be achieved. The results showed a strong linear relationship between the change in SPR signals and the concentration of N-CDs, with a linear coefficient of 0.99913. The linear detection range was 2.5 µg/mL-100 µg/mL, and the real lowest detection limit reached 0.5 µg/mL. Additionally, the green fluorescence points in the imaging region on the FM-SPR sensor chip increased with the concentration of N-CDs, which was consistent with the change in SPR signals. Using this system we also acquired the association rate and dissociation rate of N-CDs to SF which were 2.65 × 10-5/s and 1.52 × 10-5/s, respectively. This demonstrated the effectiveness of our method in quantitatively analyzing SF labeled with N-CDs.

IL-38 promotes the development of prostate cancer.

Introduction: Prostate Cancer (PCa) remains a significant concern in male cancer-related mortality. Tumour development is intricately regulated by the complex interactions between tumour cells and their microenvironment, making it essential to determine which is/are key factor(s) that influence the progression of PCa within the tumour microenvironment. Materials and methods: The current study utilised histopathology and immunohistochemistry to determine the expression of IL-38 in PCa and analysed the correlation between the expression level of IL-38 within PCa and clinical pathological characteristics. Results: There was a significant increase in IL-38 expression in PCa tissues compared to adjacent non-PCa tissues (P < 0.0001). In addition, IL-38 expression was significantly higher in tumour cells with a high proliferation index compared to those with a low value-added index. ROC curve analysis demonstrated that IL-38 has high specificity and sensitivity for the diagnosis of PCa (AUC=0.76). Moreover, we Probed the cellular source of IL-38 in prostate cancer tissue by immunofluorescence double staining. Additionally, within PCa, the expression of IL-38 was inversely correlated with the expression levels of CD8 and PD-1. Survival analysis revealed a significantly lower overall survival rate for PCa patients with high IL-38 expression (P=0.0069), and when IL-38 was co-expressed with CD8, the survival rate of the IL-38high/CD8low group was decreased significantly. Multivariate analysis indicated that the expression level of IL-38 and TNM staging were independent predictors of survival in PCa patients. Conclusion: These findings suggest that IL-38 plays a crucial role in the development of PCa, and the exploration of the correlation between IL-38 and various immune factors in the tumour microenvironment further reveals its mechanism of action, making it a potential target for immunotherapy in PCa.

Clinical Value of Human Endogenous Retrovirus-H Long Terminal Repeat Associating 2 (HHLA2) in Small Cell Lung Cancer.

Objective: Human endogenous retrovirus-H long terminal repeat associating 2 (HHLA2) is a new immune checkpoint in the B7 family, and the value of HHLA2 in small cell lung cancer (SCLC) is unknown. Methods: We retrospectively detected HHLA2 expression by immunohistochemistry in SCLC patients. Moreover, plasma biomarkers of SCLC were detected retrospectively. Results: Seventy-four percent of SCLC patients exhibited HHLA2 expression. HHLA2 staining was localised within the nucleus of SCLC cells, while no staining was detected in normal lung tissue specimens. The correlation between HHLA2 expression and clinical factors was also analysed. Limited stage (LS) SCLC was more common than extensive stage (ES) SCLC among patients with HHLA2 staining. SCLC patients without metastasis had higher HHLA2 expression than SCLC patients with metastasis. HHLA2 expression was more frequently detected in the group with a tumour size greater than 5 cm than in the group with a tumour size less than 5 cm. The proportion of patients with HHLA2-positive staining was greater in the stage III and IV SCLC groups than in the stage I and II SCLC groups. A high proportion of SCLC patients with HHLA2-positive staining had a survival time <2 years. Neuron-specific enolase (NSE), CEA and Ki-67 levels were measured. The NSE level in the HHLA2-positive group was significantly greater than that in the HHLA2-negative group. The CEA and Ki-67 levels did not significantly differ between the HHLA2-positive and HHLA2-negative patients, nor were age, sex, smoking status, nodal metastasis status, Karnofsky Performance Scale (KPS) score, or Ki-67 expression score. HHLA2-positive SCLC patients had higher tumour stages and shorter 2-year survival times than HHLA2-negative patients did. Conclusion: The new immune molecule HHLA2 may be an ideal clinical biomarker for predicting SCLC progression and could serve as a new immunotherapy target in SCLC.

Infection with SARS-CoV-2 can cause pancreatic impairment.

Evidence suggests associations between COVID-19 patients or vaccines and glycometabolic dysfunction and an even higher risk of the occurrence of diabetes. Herein, we retrospectively analyzed pancreatic lesions in autopsy tissues from 67 SARS-CoV-2 infected non-human primates (NHPs) models and 121 vaccinated and infected NHPs from 2020 to 2023 and COVID-19 patients. Multi-label immunofluorescence revealed direct infection of both exocrine and endocrine pancreatic cells by the virus in NHPs and humans. Minor and limited phenotypic and histopathological changes were observed in adult models. Systemic proteomics and metabolomics results indicated metabolic disorders, mainly enriched in insulin resistance pathways, in infected adult NHPs, along with elevated fasting C-peptide and C-peptide/glucose ratio levels. Furthermore, in elder COVID-19 NHPs, SARS-CoV-2 infection causes loss of beta (ß) cells and lower expressed-insulin in situ characterized by islet amyloidosis and necrosis, activation of α-SMA and aggravated fibrosis consisting of lower collagen in serum, an increase of pancreatic inflammation and stress markers, ICAM-1 and G3BP1, along with more severe glycometabolic dysfunction. In contrast, vaccination maintained glucose homeostasis by activating insulin receptor α and insulin receptor ß. Overall, the cumulative risk of diabetes post-COVID-19 is closely tied to age, suggesting more attention should be paid to blood sugar management in elderly COVID-19 patients.

Adaptive functions of structural variants in human brain development.

Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV map in a population of 562 rhesus macaques, verified by in-house benchmarks of eight macaque genomes with long-read sequencing and another one with genome assembly. This map indicates stronger selective constrains on inversions at regulatory regions, suggesting a strategy for prioritizing them with the most important functions. Accordingly, we identified 75 human-specific inversions and prioritized them. The top-ranked inversions have substantially shaped the human transcriptome, through their dual effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof of concept, we linked APCDD1, located on one of these inversions and down-regulated specifically in humans, to neuronal maturation and cognitive ability. We thus highlight inversions in shaping the human uniqueness in brain development.

Circular RNA Expression of Peripheral Blood Mononuclear Cells Associated with Risk of Acute Exacerbation in Smoking Chronic Obstructive Pulmonary Disease.

Purpose: Circular RNAs (circRNAs) are newly identified endogenous non-coding RNAs that function as crucial gene modulators in the development of several diseases. By assessing the expression levels of circRNAs in peripheral blood mononuclear cells (PBMCs) from patients with chronic obstructive pulmonary disease (COPD), this study attempted to find new biomarkers for COPD screening. Patients and Methods: We confirmed altered circRNA expression in PBMCs of COPD (n=41) vs controls (n=29). Further analysis focused on the highest and lowest circRNA expression levels. The T-test is used to assess the statistical variances in circRNAs among COPD patients in the smoking and non-smoking cohorts. Additionally, among smokers, the Spearman correlation test assesses the association between circRNAs and clinical indicators. Results: Two circRNAs, hsa_circ_0042590 and hsa_circ_0049875, that were highly upregulated and downregulated in PBMCs from COPD patients were identified and verified. Smokers with COPD had lower hsa_circ_0042590 and higher hsa_circ_0049875, in comparison to non-smokers. There was a significant correlation (r=0.52, P<0.01) between the number of acute exacerbations (AEs) that smokers with COPD experienced in the previous year and the following year (r=0.67, P<0.001). Moreover, hsa_circ_0049875 was connected to the quantity of AEs in the year prior (r=0.68, P<0.0001) as well as the year after (r=0.72, P<0.0001). AUC: 0.79, 95% CI: 0.1210-0.3209, P<0.0001) for hsa_circ_0049875 showed a strong diagnostic value for COPD, according to ROC curve analysis. Hsa_circ_0042590 showed a close second with an AUC of 0.83 and 95% CI: -0.1972--0.0739 (P <0.0001). Conclusion: This research identified a strong correlation between smoking and hsa_circ_0049875 and hsa_circ_0042590 in COPD PBMCs. The number of AEs in the preceding and succeeding years was substantially linked with the existence of hsa_circ_0042590 and hsa_circ_0049875 in COPD patients who smoke. Additionally, according to our research, hsa_circ_0049875 and hsa_circ_0042590 may be valuable biomarkers for COPD diagnosis.

Prediction model and assessment of malnutrition in patients with stable chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) combined with malnutrition results in decreased exercise capacity and a worse quality of life. We aimed to develop an observational case-control study to explore the effective and convenient method to identify potential individuals is lacking. This study included data from 251 patients with COPD and 85 participants in the control group. Parameters and body composition were compared between groups, and among patients with varied severity. The LASSO approach was employed to select the features for fitting a logistic model to predict the risk of malnutrition in patients with stable COPD. Patients with COPD exhibited significantly lower 6-min walk distance (6MWD), handgrip strength, fat-free mass index (FFMI), skeletal muscle mass (SMM) and protein. The significant predictors identified following LASSO selection included 6MWD, waist-to-hip ratio (WHR), GOLD grades, the COPD Assessment Test (CAT) score, and the prevalence of acute exacerbations. The risk score model yielded good accuracy (C-index, 0.866 [95% CI 0.824-0.909]) and calibration (Brier score = 0.150). After internal validation, the adjusted C-index and Brier score were 0.849, and 0.165, respectively. This model may provide primary physicians with a simple scoring system to identify malnourished patients with COPD and develop appropriate rehabilitation interventions.

CD64 plays a key role in diabetic wound healing.

Introduction: Wound healing poses a clinical challenge in diabetes mellitus (DM) due to compromised host immunity. CD64, an IgG-binding Fcgr1 receptor, acts as a pro-inflammatory mediator. While its presence has been identified in various inflammatory diseases, its specific role in wound healing, especially in DM, remains unclear. Objectives: We aimed to investigate the involvement of CD64 in diabetic wound healing using a DM animal model with CD64 KO mice. Methods: First, we compared CD64 expression in chronic skin ulcers from human DM and non-DM skin. Then, we monitored wound healing in a DM mouse model over 10 days, with or without CD64 KO, using macroscopic and microscopic observations, as well as immunohistochemistry. Results: CD64 expression was significantly upregulated (1.25-fold) in chronic ulcerative skin from DM patients compared to non-DM individuals. Clinical observations were consistent with animal model findings, showing a significant delay in wound healing, particularly by day 7, in CD64 KO mice compared to WT mice. Additionally, infiltrating CD163+ M2 macrophages in the wounds of DM mice decreased significantly compared to non-DM mice over time. Delayed wound healing in DM CD64 KO mice correlated with the presence of inflammatory mediators. Conclusion: CD64 seems to play a crucial role in wound healing, especially in DM conditions, where it is associated with CD163+ M2 macrophage infiltration. These data suggest that CD64 relies on host immunity during the wound healing process. Such data may provide useful information for both basic scientists and clinicians to deal with diabetic chronic wound healing.

Effects of Ionic Liquids on Piezoelectric Properties of Electrospun Poly(L-lactic acid) Nanofiber Membranes.

The development of environmentally friendly, degradable piezoelectric materials is of great significance for the environment. Poly(L-lactic acid) (PLLA) is a promising piezoelectric material as a degradable material. Here, we have introduced a series of ionic liquids (ILs) into PLLA spinning solution, and the PLLA/IL composite nanofiber membranes are prepared by electrospinning method. When the conductivity of the spinning solution is below 400 µS·cm-1, the addition of ILs, especially [EMIm][PF6], can significantly improve the morphology and piezoelectric properties of the PLLA/IL composite nanofiber membrane with the output voltage of 2.3 V under the pressure of 5 N, which is 4 times that of the PLLA nanofiber membrane. The improvement of the piezoelectric properties of PLLA/IL nanofiber membrane may be due to the high dipole moment generated by the C=O dipole after the interaction between the O atom in C=O on the PLLA molecular chain and the [EMIm]+ cation in the IL. This work has elucidated the effects of ILs on the properties of spinning solution and the piezoelectric properties of PLLA, which can provide a theoretical basis for the selection of the preparation system of piezoelectric polymer and inspire the development of environmentally friendly flexible piezoelectric materials.

Multifunctional polylactic acid sensing fabric based on biomass flame retardants for intelligent fire early-warning.

Today, building materials emit many hazardous gases in the event of a fire, causing great harm to human health and the environment. Therefore, it is of great significance to develop bio-based flame retardant materials and to realize preventive measures to reduce fires or their damage. In this work, we fabricated a novel multifunctional fire early-warning polylactic acid-based fabric (MFR-PBF) by coating MXene nanosheet, phytic acid @ furfurylamine (PA@FA) and ammonium polyphosphate (APP) via an eco-friendly layer-by-layer assembly method. MFR-PBF showed outstanding flame retardancy including a limiting oxygen index value of 35 % and better char formation capacity. More importantly, MFR-PBF exhibited sensitive fire early-warning capability (∼1 s) and excellent cyclic alarm stability (>15 cycles) due to the excellent semiconductor responsiveness (light and heat) and the significant catalytic char formation effect. Moreover, MFR-PBF is comfortable, flexible and strong enough to sew onto firefighter uniform to detect a variety of human motions, which can be monitored in the internet by using a LoRa emitter and a gateway. In addition, the controllable heating performance rendered MFR-PBF as a potential portable heater. This work provides new insights into the preparation and application of intelligent fire early-warning fabrics in the smart fire protection and Internet of Things.