A study on construction of a prognosis model for liver cancer based on analgesic targets and screening therapeutic drugs.

BACKGROUND: Liver cancer is one of the most malignant liver diseases in the world, and the 5-year survival rate of such patients is low. Analgesics are often used to cure pain prevalent in liver cancer. The expression changes and clinical significance of the analgesic targets (ATs) in liver cancer have not been deeply understood. OBJECTIVE: The purpose of this study is to clarify the expression pattern of ATs gene in liver cancer and its clinical significance. Through the comprehensive analysis of transcriptome data and clinical parameters, the prognosis model related to ATs gene is established, and the drug information sensitive to ATs is mined. METHODS: The study primarily utilized transcriptomic data and clinical information from liver cancer patients sourced from The Cancer Genome Atlas (TCGA) database. These data were employed to analyze the expression of ATs, conduct survival analysis, gene set variation analysis (GSVA), immune cell infiltration analysis, establish a prognostic model, and perform other bioinformatic analyses. Additionally, data from liver cancer patients in the International Cancer Genome Consortium (ICGC) were utilized to validate the accuracy of the model. Furthermore, the impact of analgesics on key genes in the prognostic model was assessed using data from the Comparative Toxicogenomics Database (CTD). RESULTS: The study investigated the differential expression of 58 ATs genes in liver cancer compared to normal tissues. Patients were stratified based on ATs expression, revealing varied survival outcomes. Functional enrichment analysis highlighted distinctions in spindle organization, centrosome, and spindle microtubule functions. Prognostic modeling identified low TP53 expression as protective, while elevated CCNA2, NEU1, and HTR2C levels posed risks. Commonly used analgesics, including acetaminophen and others, were found to influence the expression of these genes. These findings provide insights into potential therapeutic strategies for liver cancer and shed light on the molecular mechanisms underlying its progression. CONCLUSIONS: The collective analysis of gene signatures associated with ATs suggests their potential as prognostic predictors in hepatocellular carcinoma patients. These findings not only offer insights into cancer therapy but also provide novel avenues for the development of indications for analgesics.

Boosting organic phosphorescence in adaptive host-guest materials by hyperconjugation.

Phosphorescence is ubiquitous in heavy atom-containing organic phosphors, which attracts considerable attention in optoelectronics and bioelectronics. However, heavy atom-free organic materials with efficient phosphorescence are rare under ambient conditions. Herein, we report a series of adaptive host-guest materials derived from dibenzo-heterocyclic analogues, showing host-dependent color-tunable phosphorescence with phosphorescence efficiency of up to 98.9%. The adaptive structural deformation of the guests arises from the hyperconjugation, namely the n→π* interaction, enabling them to inhabit the cavity of host crystals in synergy with steric effects. Consequently, a perfect conformation match between host and guest molecules facilitates the suppression of triplet exciton dissipation, thereby boosting the phosphorescence of these adaptive materials. Moreover, we extend this strategy to a ternary host-guest system, yielding both excitation- and time-dependent phosphorescence with a phosphorescence efficiency of 92.0%. This principle provides a concise way for obtaining efficient and color-tunable phosphorescence, making a major step toward potential applications in optoelectronics.

Mesenchymal Stem Cell-Derived Exosomes Attenuate Murine Cytomegalovirus-Infected Pneumonia via NF-κB/NLRP3 Signaling Pathway.

Reactivation and infection with cytomegalovirus (CMV) are frequently observed in recipients of solid organ transplants, bone marrow transplants, and individuals with HIV infection. This presents an increasing risk of allograft rejection, opportunistic infection, graft failure, and patient mortality. Among immunocompromised hosts, interstitial pneumonia is the most critical clinical manifestation of CMV infection. Recent studies have demonstrated the potential therapeutic benefits of exosomes derived from mesenchymal stem cells (MSC-exos) in preclinical models of acute lung injury, including pneumonia, ARDS, and sepsis. However, the role of MSC-exos in the pathogenesis of infectious viral diseases, such as CMV pneumonia, remains unclear. In a mouse model of murine CMV-induced pneumonia, we observed that intravenous administration of mouse MSC (mMSC)-exos reduced lung damage, decreased the hyperinflammatory response, and shifted macrophage polarization from the M1 to the M2 phenotype. Treatment with mMSC-exos also significantly reduced the infiltration of inflammatory cells and pulmonary fibrosis. Furthermore, in vitro studies revealed that mMSC-exos reversed the hyperinflammatory phenotype of bone marrow-derived macrophages infected with murine CMV. Mechanistically, mMSC-exos treatment decreased activation of the NF-κB/NLRP3 signaling pathway both in vivo and in vitro. In summary, our findings indicate that mMSC-exo treatment is effective in severe CMV pneumonia by reducing lung inflammation and fibrosis through the NF-κB/NLRP3 signaling pathway, thus providing promising therapeutic potential for clinical CMV infection.

Identification of miR-20b-5p as an inhibitory regulator in cardiac differentiation via TET2 and DNA hydroxymethylation.

BACKGROUND: Congenital heart disease (CHD) is a prevalent congenital cardiac malformation, which lacks effective early biological diagnosis and intervention. MicroRNAs, as epigenetic regulators of cardiac development, provide potential biomarkers for the diagnosis and treatment of CHD. However, the mechanisms underlying miRNAs-mediated regulation of cardiac development and CHD malformation remain to be further elucidated. This study aimed to explore the function of microRNA-20b-5p (miR-20b-5p) in cardiac development and CHD pathogenesis. METHODS AND RESULTS: miRNA expression profiling identified that miR-20b-5p was significantly downregulated during a 12-day cardiac differentiation of human embryonic stem cells (hESCs), whereas it was markedly upregulated in plasma samples of atrial septal defect (ASD) patients. Our results further revealed that miR-20b-5p suppressed hESCs-derived cardiac differentiation by targeting tet methylcytosine dioxygenase 2 (TET2) and 5-hydroxymethylcytosine, leading to a reduction in key cardiac transcription factors including GATA4, NKX2.5, TBX5, MYH6 and cTnT. Additionally, knockdown of TET2 significantly inhibited cardiac differentiation, which could be partially restored by miR-20b-5p inhibition. CONCLUSIONS: Collectively, this study provides compelling evidence that miR-20b-5p functions as an inhibitory regulator in hESCs-derived cardiac differentiation by targeting TET2, highlighting its potential as a biomarker for ASD.

Nomograms combining computed tomography-based body composition changes with clinical prognostic factors to predict survival in locally advanced cervical cancer patients.

OBJECTIVE: To explore the value of body composition changes (BCC) measured by quantitative computed tomography (QCT) for evaluating the survival of patients with locally advanced cervical cancer (LACC) underwent concurrent chemoradiotherapy (CCRT), nomograms combined BCC with clinical prognostic factors (CPF) were constructed to predict overall survival (OS) and progression-free survival (PFS). METHODS: Eighty-eight patients with LACC were retrospectively selected. All patients underwent QCT scans before and after CCRT, bone mineral density (BMD), subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), paravertebral muscle area (PMA) were measured from two sets of computed tomography (CT) images, and change rates of these were calculated. RESULTS: Multivariate Cox regression analysis showed ΔBMD, ΔSFA, SCC-Ag, LNM were independent factors for OS (HR = 3.560, 5.870, 2.702, 2.499, respectively, all P < 0.05); ΔPMA, SCC-Ag, LNM were independent factors for PFS (HR = 2.915, 4.291, 2.902, respectively, all P < 0.05). Prognostic models of BCC combined with CPF had the highest predictive performance, and the area under the curve (AUC) for OS and PFS were 0.837, 0.846, respectively. The concordance index (C-index) of nomograms for OS and PFS were 0.834, 0.799, respectively. Calibration curves showed good agreement between the nomograms' predictive and actual OS and PFS, decision curve analysis (DCA) showed good clinical benefit of nomograms. CONCLUSION: CT-based body composition changes and CPF (SCC-Ag, LNM) were associated with survival in patients with LACC. The prognostic nomograms combined BCC with CPF were able to predict the OS and PFS in patients with LACC reliably.

Cardiopulmonary progenitors facilitate cardiac repair via exosomal transfer of miR-27b-3p targeting the SIK1-CREB1 axis.

Ischemic heart disease, especially myocardial infarction (MI), is one of the leading causes of death worldwide, and desperately needs effective treatments, such as cell therapy. Cardiopulmonary progenitors (CPPs) are stem cells for both heart and lung, but their repairing role in damaged heart is still unknown. Here, we obtained CPPs from E9.5 mouse embryos, maintained their stemness while expanding, and identified their characteristics by scRNA-seq, flow cytometry, quantitative reverse transcription-polymerase chain reaction, and differentiation assays. Moreover, we employed mouse MI model to investigate whether CPPs could repair the injured heart. Our data identified that CPPs exhibit hybrid fibroblastic, endothelial, and mesenchymal state, and they could differentiate into cell lineages within the cardiopulmonary system. Moreover, intramyocardial injection of CPPs improves cardiac function through CPPs exosomes (CPPs-Exo) by promotion of cardiomyocytic proliferation and vascularization. To uncover the underlying mechanism, we used miRNA-seq, bulk RNA-seq, and bioinformatic approaches, and found the highly expressed miR-27b-3p in CPPs-Exo and its target gene Sik1, which can influence the transcriptional activity of CREB1. Therefore, we postulate that CPPs facilitate cardiac repair partially through the SIK1-CREB1 axis via exosomal miR-27b-3p. Our study offers a novel insight into the role of CPPs-Exo in heart repair and highlights the potential of CPPs-Exo as a promising therapeutic strategy for MI.

Chemotherapy-Enabled Colorectal Cancer Immunotherapy of Self-Delivery Nano-PROTACs by Inhibiting Tumor Glycolysis and Avoiding Adaptive Immune Resistance.

The chemo-regulation abilities of chemotherapeutic medications are appealing to address the low immunogenicity, immunosuppressive lactate microenvironment, and adaptive immune resistance of colorectal cancer. In this work, the proteolysis targeting chimera (PROTAC) of BRD4 (dBET57) is found to downregulate colorectal cancer glycolysis through the transcription inhibition of c-Myc, which also inhibits the expression of programmed death ligand 1 (PD-L1) to reverse immune evasion and avoid adaptive immune resistance. Based on this, self-delivery nano-PROTACs (designated as DdLD NPs) are further fabricated by the self-assembly of doxorubicin (DOX) and dBET57 with the assistance of DSPE-PEG2000. DdLD NPs can improve the stability, intracellular delivery, and tumor targeting accumulation of DOX and dBET57. Meanwhile, the chemotherapeutic effect of DdLD NPs can efficiently destroy colorectal cancer cells to trigger a robust immunogenic cell death (ICD). More importantly, the chemo-regulation effects of DdLD NPs can inhibit colorectal cancer glycolysis to reduce the lactate production, and downregulate the PD-L1 expression through BRD4 degradation. Taking advantages of the chemotherapy and chemo-regulation ability, DdLD NPs systemically activated the antitumor immunity to suppress the primary and metastatic colorectal cancer progression without inducing any systemic side effects. Such self-delivery nano-PROTACs may provide a new insight for chemotherapy-enabled tumor immunotherapy.

Tidal inundation and plant growth/decay impact redox-sensitive metal geochemistry and fluxes in salt marsh porewater.

In dynamic coastal ecosystems, environmental factors can play important roles in the biogeochemical cycle of redox-sensitive metals. This work is focused on the impact of tidal inundation, plant growth and decay on the biogeochemical cycle of redox-sensitive metals (e.g., Fe, Mn, Mo, V and U) in salt marsh wetlands. Samples were collected from the salt marsh wetlands of the Yellow River Estuary under different tidal states and growth stages of plants (Phragmites australis). Compared to the concentration of redox-sensitive metals in the river water and seawater near the study area, Fe, Mn and U were enriched in salt marsh wetland, which might become a potential source of Fe, Mn and U in the coastal sea. Tidal inundation, plant growth and decay can affect redox-sensitive metals through changes in redox conditions; the plant can also affect them directly via root absorption or plant residue decomposition, especially for Mo. Calculations of diffusion flux between sediment porewater and tidal water show that these processes can increase diffusion by at least 16.7 % or decrease it by at least 65.7 %, even reversing the direction of diffusion, which can affect the accumulation of redox-sensitive metals in salt marsh wetlands. The results showed that tidal inundation and the decay of plant residue were not conducive to the accumulation of Fe and Mn but were beneficial to the accumulation of V and U in salt marsh wetlands. The plant growth showed the opposite pattern. The accumulation of Mo in salt marsh wetlands largely depends on ingestion by plants and the decay of plant residue. This research provides a scientific basis for the budget calculation of redox-sensitive metals in salt marsh wetlands.

Development of a nomogram based on body composition analysis of quantitative computed tomography combined with clinical prognostic factors to predict disease-free survival after surgery and adjuvant chemotherapy in patients with gastric cancer.

Background: Patients with gastric cancer (GC) have a high recurrence rate after surgery. To predict disease-free survival (DFS), we investigated the value of body composition changes (BCCs) measured by quantitative computed tomography (QCT) in assessing the prognosis of patients with GC undergoing resection combined with adjuvant chemotherapy and to construct a nomogram model in combination with clinical prognostic factors (CPFs). Methods: A retrospective study of 60 patients with GC between February 2015 and June 2019 was conducted. Pre- and posttreatment CT images of patients was used to measure bone mineral density (BMD), subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), paravertebral muscle area (PMA), and the rate of BCC was calculated. CPFs such as maximum tumor diameter (MTD), human epidermal growth factor receptor-2 (HER2), and Ki-67 were derived from postoperative pathological findings. Independent prognostic factors affecting DFS in GC were screened via univariate and multivariate Cox regression analysis. The Kaplan-Meier method and log-rank test were used to plot survival curves and compare the curves between groups, respectively. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves to evaluate the efficacy of the nomogram. Results: The results of multivariate Cox regression analysis showed that ΔBMD [hazard ratio (HR): 4.577; 95% confidence interval (CI): 1.483-14.132; P=0.008], ΔPMA (HR: 5.784; 95% CI: 1.251-26.740; P=0.025), HER2 (HR: 4.819; 95% CI: 2.201-10.549; P<0.001), and maximal tumor diameter (HR: 3.973; 95% CI: 1.893-8.337; P<0.001) were independent factors influencing DFS. ΔBMD, ΔSFA, ΔVFA, ΔTFA, and ΔPMA were -3.86%, -23.44%, -19.57%, -22.45%, and -5.94%, respectively. The prognostic model of BCCs combined with CPFs had the highest predictive performance. Decision curve analysis (DCA) indicated good clinical benefit for the prognostic nomogram. The concordance index of the prognostic nomogram was 0.814, and the area under the curve (AUC) of predicting 2- and 3-year DFS were 0.879 and 0.928, respectively. The calibration curve showed that the nomogram-predicted DFS aligned well with the actual DFS. Conclusions: The prognostic nomogram combining BCCs and CPFs was able to reliably predict the DFS of patients with GC.

[Characterization of genetic variants in children with refractory epilepsy].

OBJECTIVE: To analyze the characteristics of genetic variants among children with refractory epilepsy (RE). METHODS: One hundred and seventeen children with RE who had presented at the Affiliated Jinhua Hospital of Zhejiang University School of Medicine from January 1, 2018 to November 21, 2019 were selected as the study subjects. The children were divided into four groups according to their ages of onset: < 1 year old, 1 ~ 3 years old, 3 ~ 12 years old, and >= 12 years old. Clinical data and results of trio-whole exome sequencing were retrospectively analyzed. RESULTS: In total 67 males and 50 females were included. The age of onset had ranged from 4 days to 14 years old. Among the 117 patients, 33 (28.21%) had carried pathogenic or likely pathogenic variants. The detection rates for the < 1 year old, 1 ~ 3 years old and >= 3 years old groups were 53.85% (21/39), 12.00% (3/25) and 16.98% (9/53), respectively, with a significant difference among the groups (χ2 = 19.202, P < 0.001). The detection rates for patients with and without comorbidities were 33.33% (12/36) and 25.93% (21/81), respectively (χ2 = 0.359, P = 0.549). Among the 33 patients carrying genetic variants, 27 were single nucleotide polymorphisms (SNPs) or insertion/deletions (InDels), and 6 were copy number variations (CNVs). The most common mutant genes were PRRT2 (15.15%, 5/33) and SCN1A (12.12%, 4/33). Among children carrying genetic variants, 72.73% (8/11) had attained clinical remission after adjusting the medication according to the references. CONCLUSION: 28.21% of RE patients have harbored pathogenic or likely pathogenic variants or CNVs. The detection rate is higher in those with younger age of onset. PRRT2 and SCN1A genes are more commonly involved. Adjusting medication based on the types of affected genes may facilitate improvement of the remission rate.

PFKFB3-driven vascular smooth muscle cell glycolysis promotes vascular calcification via the altered FoxO3 and lactate production.

A link between increased glycolysis and vascular calcification has recently been reported, but it remains unclear how increased glycolysis contributes to vascular calcification. We therefore investigated the role of PFKFB3, a critical enzyme of glycolysis, in vascular calcification. We found that PFKFB3 expression was upregulated in calcified mouse VSMCs and arteries. We showed that expression of miR-26a-5p and miR-26b-5p in calcified mouse arteries was significantly decreased, and a negative correlation between Pfkfb3 mRNA expression and miR-26a-5p or miR-26b-5p was seen in these samples. Overexpression of miR-26a/b-5p significantly inhibited PFKFB3 expression in VSMCs. Intriguingly, pharmacological inhibition of PFKFB3 using PFK15 or knockdown of PFKFB3 ameliorated vascular calcification in vD3 -overloaded mice in vivo or attenuated high phosphate (Pi)-induced VSMC calcification in vitro. Consistently, knockdown of PFKFB3 significantly reduced glycolysis and osteogenic transdifferentiation of VSMCs, whereas overexpression of PFKFB3 in VSMCs induced the opposite effects. RNA-seq analysis and subsequent experiments revealed that silencing of PFKFB3 inhibited FoxO3 expression in VSMCs. Silencing of FoxO3 phenocopied the effects of PFKFB3 depletion on Ocn and Opg expression but not Alpl in VSMCs. Pyruvate or lactate supplementation, the product of glycolysis, reversed the PFKFB3 depletion-mediated effects on ALP activity and OPG protein expression in VSMCs. Our results reveal that blockade of PFKFB3-mediated glycolysis inhibits vascular calcification in vitro and in vivo. Mechanistically, we show that FoxO3 and lactate production are involved in PFKFB3-driven osteogenic transdifferentiation of VSMCs. PFKFB3 may be a promising therapeutic target for the treatment of vascular calcification.

Changes of active particulate uranium under the Water-Sediment Regulation Scheme in the lower Yellow River: Potential impact to the uranium flux into the global ocean.

With the annual Water-Sediment Regulation Scheme (WSRS) transporting large amounts of suspended particulate matter (SPM) to the sea within several days, the behavior of uranium in the Yellow River during the WSRS is crucial to better understand the uranium flux. In this study, the active forms (the exchangeable, carbonate bounded, Fe/Mn oxides bounded, organic matter bounded) and the residual form of particulate uranium were extracted by the sequential extraction method and their uranium contents were measured respectively. Results show that the content of total particulate uranium was 1.43-2.56 µg/g and the active forms accounts for 11-32 %. Particle size and redox environment are the two main factors controlling the active particulate uranium. The flux of active particulate uranium at Lijin was 4.7 tons during 2014 WSRS, which was about 50 % of the dissolved uranium flux for the same period. Thus, the terrestrial uranium flux is significantly modified by artificial regulation.

Altered limbic functional connectivity in individuals with subjective cognitive decline: Converging and diverging findings across Chinese and German cohorts.

INTRODUCTION: It remains unclear whether functional brain networks are consistently altered in individuals with subjective cognitive decline (SCD) of diverse ethnic and cultural backgrounds and whether the network alterations are associated with an amyloid burden. METHODS: Cross-sectional resting-state functional magnetic resonance imaging connectivity (FC) and amyloid-positron emission tomography (PET) data from the Chinese Sino Longitudinal Study on Cognitive Decline and German DZNE Longitudinal Cognitive Impairment and Dementia cohorts were analyzed. RESULTS: Limbic FC, particularly hippocampal connectivity with right insula, was consistently higher in SCD than in controls, and correlated with SCD-plus features. Smaller SCD subcohorts with PET showed inconsistent amyloid positivity rates and FC-amyloid associations across cohorts. DISCUSSION: Our results suggest an early adaptation of the limbic network in SCD, which may reflect increased awareness of cognitive decline, irrespective of amyloid pathology. Different amyloid positivity rates may indicate a heterogeneous underlying etiology in Eastern and Western SCD cohorts when applying current research criteria. Future studies should identify culture-specific features to enrich preclinical Alzheimer's disease in non-Western populations. HIGHLIGHTS: Common limbic hyperconnectivity across Chinese and German subjective cognitive decline (SCD) cohorts was observed. Limbic hyperconnectivity may reflect awareness of cognition, irrespective of amyloid load. Further cross-cultural harmonization of SCD regarding Alzheimer's disease pathology is required.

Individual Proportion Loss of Functional Connectivity Strength: A Novel Individual Functional Connectivity Biomarker for Subjective Cognitive Decline Populations.

High individual variation in the subjective cognitive decline (SCD) population makes functional connectivity (FC) biomarkers unstable. This study proposed a novel individual FC index, named individual proportion loss of functional connectivity strength (IPLFCS), and explored potential biomarkers for SCD using this new index. We proposed an IPLFCS analysis framework and compared it with traditional FC in Chinese and Western cohorts. Post hoc tests were used to determine biomarkers. Pearson's correlation analysis was used to investigate the correlation between neuropsychological scores or cortical amyloid deposits and IPLFCS biomarkers. Receiver operating characteristic curves were utilized to evaluate the ability of potential biomarkers to distinguish between groups. IPLFCS of the left middle temporal gyrus (LMTG) was identified as a potential biomarker. The IPLFC was correlated with the traditional FC (r = 0.956, p < 0.001; r = 0.946, p < 0.001) and cortical amyloid deposition (r = -0.245, p = 0.029; r = -0.185, p = 0.048) in both cohorts. Furthermore, the IPLFCS decreased across the Alzheimer's disease (AD) continuum. Its diagnostic efficiency was superior to that of existing fMRI biomarkers. These findings suggest that IPLFCS of the LMTG could be a potential biomarker of SCD.

Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine.

Background: Stomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stress can promote cancer by increasing mutagenicity, genomic instability, cell survival, proliferation, and stress resistance pathways. As a direct and indirect result of oncogenic mutations, cancer depends on cellular metabolic reprogramming. However, their roles in STAD remain unclear. Method: 743 STAD samples from GEO and TCGA platforms were selected. Oxidative stress and metabolism-related genes (OMRGs) were acquired from the GeneCard Database. A pan-cancer analysis of 22 OMRGs was first performed. We categorized STAD samples by OMRG mRNA levels. Additionally, we explored the link between oxidative metabolism scores and prognosis, immune checkpoints, immune cell infiltration, and sensitivity to targeted drugs. A series of bioinformatics technologies were employed to further construct the OMRG-based prognostic model and clinical-associated nomogram. Results: We identified 22 OMRGs that could evaluate the prognoses of patients with STAD. Pan-cancer analysis concluded and highlighted the crucial part of OMRGs in the appearance and development of STAD. Subsequently, 743 STAD samples were categorized into three clusters with the enrichment scores being C2 (upregulated) > C3 (normal) > C1 (downregulated). Patients in C2 had the lowest OS rate, while C1 had the opposite. Oxidative metabolic score significantly correlates with immune cells and immune checkpoints. Drug sensitivity results reveal that a more tailored treatment can be designed based on OMRG. The OMRG-based molecular signature and clinical nomogram have good accuracy for predicting the adverse events of patients with STAD. Both transcriptional and translational levels of ANXA5, APOD, and SLC25A15 exhibited significantly higher in STAD samples. Conclusion: The OMRG clusters and risk model accurately predicted prognosis and personalized medicine. Based on this model, high-risk patients might be identified in the early stage so that they can receive specialized care and preventative measures, and choose targeted drug beneficiaries to deliver individualized medical services. Our results showed oxidative metabolism in STAD and led to a new route for improving PPPM for STAD.

A review of brain imaging biomarker genomics in Alzheimer's disease: implementation and perspectives.

Alzheimer's disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

Preoperative Prediction Value of Pelvic Lymph Node Metastasis of Endometrial Cancer: Combining of ADC Value and Radiomics Features of the Primary Lesion and Clinical Parameters.

Objective: To investigate the value of apparent diffusion coefficient (ADC) value of endometrial cancer (EC) primary lesion and magnetic resonance imaging (MRI) three-dimensional (3D) radiomics features combined with clinical parameters for preoperative prediction of pelvic lymph node metastasis (PLNM). Methods: A total of 136 patients with EC confirmed by postoperative pathology were retrospectively reviewed and analyzed. Patients were randomly divided into training set (n = 95) and test set (n = 41) at a ratio of 7 : 3. Radiomics features based on T2WI, DWI, and contrast-enhanced T1WI (CE-T1WI) sequence were extracted and screened, and then radiomics score (Rads-score) was calculated. Clinical parameters and ADC value of EC primary lesion were measured and collected, and their correlation with PLNM was analyzed. Receiver operating characteristic (ROC) curve was plotted to assess the diagnostic efficacy of the model. A nomogram for PLNM was created based on the multivariate logistic regression model. Results: The ADC value of the EC primary lesion showed inverse correlation with PLNM, while CA125 and Rads-score were positively associated with PLNM. A predictive model was proposed based on ADC value, Rads-score, CA125, and MR-reported pelvic lymph node status (PLNS) for PLNM in EC. The area under the curve (AUC) of the model is 0.940; the sensitivity and specificity (87.1% and 90.6%) of the model were significantly higher than that of the MRI morphological signs. Conclusion: A combination of ADC value, MRI 3D radiomics features of the EC primary lesion, and clinical parameters generated a prediction model for PLNM in EC and had a good diagnostic performance; it was a useful supplement to MR-reported PLNS based on MRI morphological signs.

Effect of PRECEDE-PROCEED-Model-Based Health Education on the Life Quality and 5-HTT Gene Expression of Patients with Gastric Cancer after Surgery.

This study aimed to investigate the effect of PRECEDE-PROCEED-Model-based health education on the life quality of patients with gastric cancer after surgery. Also, the effect of this model was evaluated on 5-HTT gene expression as a gene related to depression. For this purpose, a total of 32 gastric cancer patients who were hospitalized in this hospital between March 2019 and September 2020 were enrolled in this study after surgery and, according to the time of admission, were divided into the control group and observation group, with 16 patients in each group. Patients in the control group were nursed regularly, while those in the observation group, in addition to the regular nursing, would receive the PRECEDE-PROCEED-Model-based health education. Post-surgery life quality of patients in two groups was compared from the following aspects: Rehabilitation process, pain assessment, rate of complications and The Short-Form (SF-36) Health Survey. The expression of the 5-HTT gene was performed by the Real-time qPCR technique. The results of this study showed that after surgery, the extubation time and the time of hospital discharge of patients in the observation group were all earlier than those in the control group, while the score of pain assessment and rate of complication was much lower in the observation group, and the SF-36 score of patients was much higher (all P < 0.05). The results of 5-HTT gene expression showed that there was no significant difference between the control and observation groups before the intervention. But one month after the intervention, gene expression in the observation group was significantly reduced compared to the control group (p <0.01). This significant decrease was also seen two months after the intervention (p <0.05). As mentioned before, the expression of the 5-HTT gene increases during the depression, therefore improvement of the patient's condition and quality of life decreased the expression of this gene. Hence, PRECEDE-PROCEED-Model-Based Health Education plays an influential role in reducing the expression of this gene. However, the passage of time has not been ineffective in lowering 5-HTT expression. In general, PRECEDE-PROCEED-Model-based health education could help patients establish a good system of health knowledge, which could encourage the patients to avoid the negative mood, optimize the rehabilitation process, improve the post-surgery rehabilitation and, finally, ameliorate the life quality of patients after surgery.

Carrier free nanomedicine for synergistic cancer therapy by initiating apoptosis and paraptosis.

Although photodynamic therapy (PDT) has been well-known as a promising anti-tumor treatment, its limited therapeutic efficiency remains to be a large challenge. In this study, a carrier free nanomedicine (designated as PyroMor) is developed to greatly initiate cell apoptosis and paraptosis for synergistic cancer therapy. Pyropheophorbide-a (Pyro) and morusin (Mor) are capable of self-assembling into PyroMor, which has been testified to have superiority of improved stability, cellular internalization, and biocompatibility. Because of efficient cellular uptake behavior, PyroMor could induce cellular paraptosis by Mor-caused vacuolation in mitochondria, ER and cytoplasm, contributing to improving the PDT efficacy of Pyro. Therefore, self-delivery PyroMor is able to accomplish synergistic anti-tumor effect via stimulation of cell apoptosis as well as paraptosis. In addition, in vivo studies also clarify that PyroMor presents passive tumor targeting delivery, leading to robust repressive effect on tumor proliferation with negligible systemic toxicity. This strategy of combined cancer therapy by initiating both cell apoptosis and paraptosis extremely benefits to the development of precise and effective cancer therapy in clinic.

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment.

Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 127) and the Xuanwu Hospital of Capital Medical University, Beijing, China (N = 84). During follow-up (mean 80.60 months), 23 participants in the ADNI cohort converted to cognitive impairment. ARGMPs were identified using the scaled subprofile model/principal component analysis method, and cross-validations were conducted in both independent cohorts. A survival analysis was further conducted to calculate the predictive effect of conversion risk by using ARGMPs. The results showed that ARGMPs were characterized by hypometabolism with increasing age primarily in the bilateral medial superior frontal gyrus, anterior cingulate and paracingulate gyri, caudate nucleus, and left supplementary motor area and hypermetabolism in part of the left inferior cerebellum. The expression network scores of ARGMPs were significantly associated with chronological age (R = 0.808, p < 0.001), which was validated in both the ADNI and Xuanwu cohorts. Individuals with higher network scores exhibited a better predictive effect (HR: 0.30, 95% CI: 0.1340 ~ 0.6904, p = 0.0068). These findings indicate that ARGMPs derived from CN participants may represent a novel index for characterizing brain ageing and predicting high conversion risk into cognitive impairment.