Near-infrared imaging for visualizing the synergistic relationship between autophagy and NFS1 protein during multidrug resistance using an ICT-TICT integrated platform

Drug resistance is a major challenge for cancer treatment, and its identification is crucial for medical research. However, since drug resistance is a multi-faceted phenomenon, it is important to simultaneously evaluate multiple target fluctuations. Recently developed fluorescence-based probes that can simultaneously respond to multiple targets offer many advantages for real-time and in situ monitoring of cellular metabolism, including ease of operation, rapid reporting, and their non-invasive nature. As such we developed a dual-response platform (Vis-H2S) with integrated ICT-TICT to image H2S and viscosity in mitochondria, which could simultaneously track fluctuations in cysteine desulfurase (NFS1 protein and H2S inducer) and autophagy during chemotherapy-induced multidrug resistance. This platform could monitor multiple endogenous metabolites and the synergistic relationship between autophagy and NFS1 protein during multidrug resistance induced by chemotherapy. The results indicated that chemotherapeutic drugs simultaneously up-regulate the levels of NFS1 protein and autophagy. It was also found that the NFS1 protein was linked with autophagy, which eventually led to multidrug resistance. As such, this platform could serve as an effective tool for the in-depth exploration of drug resistance mechanisms.

Convergence Analysis of Distributed Gradient Descent Algorithms With One and Two Momentum Terms

For the centralized optimization, it is well known that adding one momentum term (also called the heavy-ball method) can obtain a faster convergence rate than the gradient method. However, for the distributed counterpart, there is quite few results about the effect of added momentum terms on the convergence rate. This article is aimed at studying the issue in the distributed setup, where N agents minimize the sum of their individual cost functions using local communication over a network. The cost functions are twice continuously differentiable. We first study the algorithm with one momentum term and develop a distributed heavy-ball (D-HB) method by adding one momentum term on to the distributed gradient algorithm. By borrowing tools from the control theory, we provide a simple convergence proof and an explicit expression of the optimal convergence rate. Furthermore, we consider adding two momentum terms case and propose a distributed double-heavy-ball (D-DHB) method. We show that adding one momentum term allows faster convergence while adding two momentum terms does not perform any superiorities. Finally, simulation examples are given to illustrate our findings.

An iterative reconstruction algorithm for unsupervised PET image

Objective.In recent years, convolutional neural networks (CNNs) have shown great potential in positron emission tomography (PET) image reconstruction. However, most of them rely on many low-quality and high-quality reference PET image pairs for training, which are not always feasible in clinical practice. On the other hand, many works improve the quality of PET image reconstruction by adding explicit regularization or optimizing the network structure, which may lead to complex optimization problems.Approach.In this paper, we develop a novel iterative reconstruction algorithm by integrating the deep image prior (DIP) framework, which only needs the prior information (e.g. MRI) and sinogram data of patients. To be specific, we construct the objective function as a constrained optimization problem and utilize the existing PET image reconstruction packages to streamline calculations. Moreover, to further improve both the reconstruction quality and speed, we introduce the Nesterov's acceleration part and the restart mechanism in each iteration.Main results.2D experiments on PET data sets based on computer simulations and real patients demonstrate that our proposed algorithm can outperform existing MLEM-GF, KEM and DIPRecon methods.Significance.Unlike traditional CNN methods, the proposed algorithm does not rely on large data sets, but only leverages inter-patient information. Furthermore, we enhance reconstruction performance by optimizing the iterative algorithm. Notably, the proposed method does not require much modification of the basic algorithm, allowing for easy integration into standard implementations.

T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer

OBJECTIVE

To investigate whether T2-weighted imaging (T2WI)-based intratumoral and peritumoral radiomics can predict extranodal extension (ENE) and prognosis in patients with resectable rectal cancer.

METHODS

One hundred sixty-seven patients with resectable rectal cancer including T3T4N + cases were prospectively included. Radiomics features were extracted from intratumoral, peritumoral 3 mm, and peritumoral-mesorectal fat on T2WI images. Least absolute shrinkage and selection operator regression were used for feature selection. A radiomics signature score (Radscore) was built with logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each Radscore. A clinical-radiomics nomogram was constructed by the most predictive radiomics signature and clinical risk factors. A prognostic model was constructed by Cox regression analysis to identify 3-year recurrence-free survival (RFS).

RESULTS

Age, cT stage, and lymph node-irregular border and/or adjacent fat invasion were identified as independent clinical risk factors to construct a clinical model. The nomogram incorporating intratumoral and peritumoral 3 mm Radscore and independent clinical risk factors achieved a better AUC than the clinical model in the training (0.799 vs. 0.736) and validation cohorts (0.723 vs. 0.667). Nomogram-based ENE (hazard ratio [HR] = 2.625, 95% CI = 1.233-5.586, p = 0.012) and extramural vascular invasion (EMVI) (HR = 2.523, 95% CI = 1.247-5.106, p = 0.010) were independent risk factors for predicting 3-year RFS. The prognostic model constructed by these two indicators showed good performance for predicting 3-year RFS in the training (AUC = 0.761) and validation cohorts (AUC = 0.710).

CONCLUSION

The nomogram incorporating intratumoral and peritumoral 3 mm Radscore and clinical risk factors could predict preoperative ENE. Combining nomogram-based ENE and MRI-reported EMVI may be useful in predicting 3-year RFS.

CRITICAL RELEVANCE STATEMENT

A clinical-radiomics nomogram could help preoperative predict ENE, and a prognostic model constructed by the nomogram-based ENE and MRI-reported EMVI could predict 3-year RFS in patients with resectable rectal cancer.

KEY POINTS

• Intratumoral and peritumoral 3 mm Radscore showed the most capability for predicting ENE. • Clinical-radiomics nomogram achieved the best predictive performance for predicting ENE. • Combining clinical-radiomics based-ENE and EMVI showed good performance for 3-year RFS.

S-nitrosothiol homeostasis maintained by ADH5 facilitates STING-dependent host defense against pathogens

Oxidative (or respiratory) burst confers host defense against pathogens by generating reactive species, including reactive nitrogen species (RNS). The microbial infection-induced excessive RNS damages many biological molecules via S-nitrosothiol (SNO) accumulation. However, the mechanism by which the host enables innate immunity activation during oxidative burst remains largely unknown. Here, we demonstrate that S-nitrosoglutathione (GSNO), the main endogenous SNO, attenuates innate immune responses against herpes simplex virus-1 (HSV-1) and Listeria monocytogenes infections. Mechanistically, GSNO induces the S-nitrosylation of stimulator of interferon genes (STING) at Cys257, inhibiting its binding to the second messenger cyclic guanosine monophosphate-adenosine monophosphate (cGAMP). Alcohol dehydrogenase 5 (ADH5), the key enzyme that metabolizes GSNO to decrease cellular SNOs, facilitates STING activation by inhibiting S-nitrosylation. Concordantly, Adh5 deficiency show defective STING-dependent immune responses upon microbial challenge and facilitates viral replication. Thus, cellular oxidative burst-induced RNS attenuates the STING-mediated innate immune responses to microbial infection, while ADH5 licenses STING activation by maintaining cellular SNO homeostasis.

[Quantitative analysis of risk assessment indicators for re-introduction of imported malaria in China]

OBJECTIVE

To quantitatively analyze the risk indicators of re-introduction of imported malaria in China and their weighting coefficients, so as to investigate the difference in the contribution of risk indicators included in the current risk assessment framework for re-introduction of imported malaria in China to the risk assessment of re-introduction of imported malaria.

METHODS

Publications pertaining to the risk assessment framework for re-introduction of imported malaria in China that reported the risk indicators and their weighting coefficients were retrieved in PubMed, Web of Science, CNKI, Wanfang Data, and VIP with terms of "malaria", "re-introduction/re-transmission/re-establishment", "risk assessment/risk evaluation/risk prediction" from the inception of the database through 3 August 2023, and literature search was performed in Google Scholar to ensure the comprehensiveness of the retrieval. Basic characteristics of included studies were extracted using pre-designed information extraction forms by two investigators, and data pertaining to risk indicators of re-introduction of imported malaria were cross-checked by these two investigators. The risk indicators included in the risk assessment framework for re-introduction of imported malaria in China and their weighting coefficients were visualized with the Nightingale's rose diagrams using the software R 4.2.1, and the importance of risk indictors was evaluated with the frequency of risk indicators included in the risk assessment framework and the ranking of weighting coefficients of risk indicators. In addition, the capability of risk indicators screened by different weighting methods was compared by calculating the ratio of the maximum to the minimum of the weighting coefficients of the risk indicators screened by different weighting methods.

RESULTS

A total of 2 138 publications were retrieved, and following removal of duplications and screening, a total of 8 publications were included in the final analysis. In these 8 studies, 8 risk assessment frameworks for re-introduction of imported malaria in China and 52 risk indicators of re-introduction of imported malaria were reported, in which number of imported malaria cases (n = 8) and species of malaria vectors were more frequently included in the risk assessment frameworks (n = 8), followed by species of imported malaria parasites (n = 6) and population density of local malaria vectors (n = 6), and species of local malaria vectors (n = 6), number of imported malaria cases (n = 5) and species of imported malaria parasites had the three highest weighting coefficients (n = 4). The weighting methods included expert scoring method, combination of expert scoring method and analytic hierarchy process, and combination of expert scoring method and entropy weight method in these 8 studies, and the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by the expert scoring method were 1.143 to 2.241, while the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by combination of the expert scoring method and analytic hierarchy process were 34.970 to 162.000.

CONCLUSIONS

Number of imported malaria cases, species of imported malaria parasites, species of local malaria vectors and population density of local malaria vectors are core indicators in the current risk assessment framework for re-introduction of imported malaria in China. Combination of the expert scoring method and analytic hierarchy process is superior to the expert scoring method alone for weighting the risk indicators.

Dinaciclib exerts a tumor-suppressing effect via β-catenin/YAP axis in pancreatic ductal adenocarcinoma

Dinaciclib, a cyclin-dependent kinase-5 (CDK5) inhibitor, has significant anti-tumor properties. However, the precise mechanism of dinaciclib requires further investigation. Herein, we investigated the anti-tumor functions and molecular basis of dinaciclib in pancreatic ductal adenocarcinoma (PDAC). PDAC and matched para-carcinoma specimens were collected from the patients who underwent radical resection. Immunohistochemistry was performed to assess CDK5 expression. Cell proliferation ability, migration, and invasion were measured using Cell Counting Kit-8, wound healing, and transwell assay, respectively. The cell cycle and apoptosis were assessed using flow cytometry. Gene expression was examined using RNA-seq and quantitative real-time PCR. Protein expression of proteins was measured by western blot analysis and immunofluorescence microscopy. Tumor-bearing mice were intraperitoneally injected with dinaciclib. CDK5 is highly expressed in PDAC. The expression level of CDK5 was significantly related to tumor size, T stage, and the American Joint Committee on Cancer stage. High CDK5 expression can predict poor survival in PDAC patients. In addition, the expression level of CDK5 might be an independent prognostic factor for PDAC patients. Dinaciclib inhibits the growth and motility of PDAC cells and induces apoptosis and cell cycle arrest in the G2/M phase. Mechanistically, dinaciclib down-regulated yes-associated protein (YAP) mRNA and protein expression by reducing β-catenin expression. Moreover, dinaciclib significantly inhibited PDAC cell growth in vivo . Our findings reveal a novel anti-tumor mechanism of dinaciclib in which it decreases YAP expression by down-regulating β-catenin at the transcriptional level rather than by activating Hippo pathway-mediated phosphorylation-dependent degradation.

Body composition changes in patients with differentiated thyroid cancer after iodine-131 treatment and short-term levothyroxine replacement and suppression therapy

PURPOSE

The purposes of this study were to assess the changes in body composition in patients who underwent thyroidectomy due to differentiated thyroid cancer (DTC) after radioactive iodine therapy (RAI) and short-term levothyroxine (LT4) supplementation and to explore the correlations between body composition distribution and corresponding blood indices.

METHODS

Fifty-seven thyroidectomized DTC patients were included. Serum was tested for several biochemical indices of thyroid function, lipids, and bone metabolism, and body composition parameters were measured via dual-energy X-ray absorptiometry before and 4-6 weeks after RAI and LT4 supplementation.

RESULTS

The body composition of DTC patients changed after RAI. Fat mass in all parts of the body decreased (range of relative change (RRC) -12.97--2.80%). Bone mineral content (BMC) increased throughout the body (relative change (RC) 12.12%), head (RC 36.23%), pelvis (RC 9.00%), and legs (RC 3.15%). Similarly, bone mineral density (BMD) increased in different regions (RRC 3.60-26.43%), except for the arms. Notably, lean mass in the arms (RC 4.30%) and legs (RC 3.67%) increased, while that in the head decreased (RC -2.75%), while total lean mass did not change at 4-6 weeks after LT4 supplementation. Furthermore, changes in fat distribution in the android region were related to the changes in total cholesterol (r = -0.390) and low-density lipoprotein cholesterol (r = -0.354), and changes in the BMC and BMD of the lumbar spine were positively associated with the changes in calcitonin (r = 0.302 and 0.325, respectively).

CONCLUSIONS

After RAI and short-term LT4 supplementation in DTC patients, body composition rapidly and positively changed and was characterized by decreased fat mass and increased BMC and BMD.

The UAF1-USP1 Deubiquitinase Complex Stabilizes cGAS and Facilitates Antiviral Responses

Cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS) detects cytoplasmic microbial DNA and self-DNA from genomic instability, initiates innate immunity, and plays fundamental roles in defense against viruses and the development of various diseases. The cellular cGAS level determines the magnitude of the response to DNA. However, the underlying mechanisms of the control of cGAS stability, especially its feedback regulation during viral infection, remain largely unknown. In this study, we show that viral infection induces the expression of the UAF1-USP1 deubiquitinase complex in primary peritoneal macrophages (PMs) of C57BL/6J mice. UAF1-USP interacts with cGAS, selectively cleaves its K48-linked polyubiquitination, and thus stabilizes its protein expression in PMs and HEK293T cells. Concordantly, the UAF1-USP1 deubiquitinase complex enhances cGAS-dependent type I IFN responses in PMs. Uaf1 deficiency and ML323 (a specific inhibitor of UAF1-USP1 deubiquitinase complex) attenuates cGAS-triggered antiviral responses and facilitates viral replication both in vitro and in vivo. Thus, our study uncovers a positive feedback mechanism of cGAS-dependent antiviral responses and suggests the UAF1-USP1 complex as a potential target for the treatment of diseases caused by aberrant cGAS activation.

Targeting transcription factors through an IMiD independent zinc finger domain

Immunomodulatory imide drugs (IMiDs) degrade specific C2H2 zinc finger degrons in transcription factors, making them effective against certain cancers. SALL4, a cancer driver, contains seven C2H2 zinc fingers in four clusters, including an IMiD degron in zinc finger cluster two (ZFC2). Surprisingly, IMiDs do not inhibit growth of SALL4 expressing cancer cells. To overcome this limit, we focused on a non-IMiD degron, SALL4 zinc finger cluster four (ZFC4). By combining AlphaFold and the ZFC4-DNA crystal structure, we identified a potential ZFC4 drug pocket. Utilizing an in silico docking algorithm and cell viability assays, we screened chemical libraries and discovered SH6, which selectively targets SALL4-expressing cancer cells. Mechanistic studies revealed that SH6 degrades SALL4 protein through the CUL4A/CRBN pathway, while deletion of ZFC4 abolished this activity. Moreover, SH6 led to significant 62% tumor growth inhibition of SALL4+ xenografts in vivo and demonstrated good bioavailability in pharmacokinetic studies. In summary, these studies represent a new approach for IMiD independent drug discovery targeting C2H2 transcription factors in cancer.

Immunotherapy, targeted therapy, and their cross talks in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a challenging malignancy with limited treatment options beyond surgery and chemotherapy. Recent advancements in targeted therapies and immunotherapy, including PD-1 and PD-L1 monoclonal antibodies, have shown promise, but their efficacy has not met expectations. Biomarker testing and personalized medicine based on genetic mutations and other biomarkers represent the future direction for HCC treatment. To address these challenges and opportunities, this comprehensive review discusses the progress made in targeted therapies and immunotherapies for HCC, focusing on dissecting the rationales, opportunities, and challenges for combining these modalities. The liver's unique physiology and the presence of fibrosis in many HCC patients pose additional challenges to drug delivery and efficacy. Ongoing efforts in biomarker development and combination therapy design, especially in the context of immunotherapies, hold promise for improving outcomes in advanced HCC. Through exploring the advancements in biomarkers and targeted therapies, this review provides insights into the challenges and opportunities in the field and proposes strategies for rational combination therapy design.

The Potential Role of Pyrroloquinoline Quinone to Regulate Thyroid Function and Gut Microbiota Composition of Graves' Disease in Mice

Graves' disease (GD) is an autoimmune disorder disease, and its prevalence continues to increase worldwide. Pyrroloquinoline quinone (PQQ) is a naturally antioxidant compound in milk, vegetables, and meat. We aim to identify the treatment efficacy of PQQ on GD and its regulatory effect on intestinal microbiota. The GD mice model was built by an adenovirus expressing autoantigen thyroid-stimulating hormone receptor (Ad-TSHR289). Fecal samples were collected for 16S rDNA sequencing after PQQ pretreatments (20, 40, or 60 mg/kg BW/day) for 4 weeks. Thyroid and intestine functions were measured. The levels of serum TSHR and T4 were significantly raised, and the thyroid gland size was typically enlarged in the GD group than in controls, reversed by PQQ therapy. After PQQ replenishment, IL6 and TNFα levels in small intestine tissues were lower than those in the GD group, with Nrf2 and HO1 levels improved. Also, the PQQ supplement could maintain the mucosal epithelial barrier impaired by GD. In microbial analyses, PQQ treatment could prompt the diversity recovery of gut microbiota and reconstruct the microbiota composition injured by GD. Lactobacillus served as the most abundant genus in all groups, and the abundance of Lactobacillus was increased in the GD group than in control and PQQ groups. Besides, Lactobacillus was highly correlative with all samples and the top 50 genera. PQQ supplementation regulates thyroid function and relieves intestine injury. PQQ changes the primary composition and abundance of GD's intestine microbiota by moderating Lactobacillus, which may exert in the pathogenesis and progression of GD.

Integrated microbiome and metabolome analysis reveals a distinct microbial and metabolic signature in Graves' disease and hypothyroidism

Recent studies reveal that imbalanced microbiota is related to thyroid diseases. However, studies on the alterations in fecal metabolites in Graves' disease and clinical hypothyroidism patients are insufficient. Here, we identified 21 genera and 53 metabolites that were statistically significant among Graves' disease patients, hypothyroidism patients, and controls integrating microbiome and untargeted metabolome analysis. Disease groups revealed a decreased abundance in butyrate-producing microbiota and an increased abundance in potentially pathogenic microbiota. Lipids molecules were the major differential metabolites identified in all fecal samples. Network analysis recognized that microbiota may affect thyroid function by targeting specific metabolites. We further identified specific microbiota and metabolites that could distinguish Graves' disease patients, hypothyroidism patients, and controls. Our study reveals a distinct microbial and metabolic signature in hypothyroidism patients and Graves' disease patients and further validates the potential role of microbiota in thyroid diseases, providing new ideas for future research into the etiology and clinical intervention of thyroid diseases.

Global food trade alleviates transgressions of planetary boundaries at the national scale

Food systems are among the leading causes for transgression of planetary boundaries globally, which define the safe operating space for humanity. We quantify unsustainable environmental impacts of food systems, indicated by the transgression of national-scale planetary boundaries (i.e., the safe operating space for food production in each country), from both production and consumption perspectives of 189 countries/regions around the world. A multi-regional input-output model is used to map the global transfers of the national-scale transgression of planetary boundaries, including freshwater use, land change, and biogeochemical flows (nitrogen and phosphorus). Our results show that China is a major global unsustainable water and nitrogen exporter and an unstable land and phosphorus importer. This means that water and nitrogen uses in China are used to support food demands in other countries, and food consumption in China requires unsustainable land and phosphorus uses elsewhere. In contrast, the US is a major exporter of unsustainable water, land, and nitrogen uses but only an importer of unsustainable phosphorus for food consumption. Globally, compared to a counterfactual scenario where there is no food trade among any countries, food trade saves massive transgressions of planetary boundaries (270 km3 of water, 18 million tons of nitrogen, 7 million tons of phosphorus, and 5,431 million km2 of land). Alleviation of national-scale planetary boundary transgression has been achieved primarily in the US, China, Saudi Arabia, etc., while aggravation was incurred in Pakistan, Australia, Argentina, and so forth.

Graph Signal Smoothness Based Feature Learning of Brain Functional Networks in Schizophrenia

In this paper we study the brain functional network of schizophrenic patients based on resting-state fMRI data. Different from the region of interest (ROI)-level brain networks that describe the connectivity between brain regions, this paper constructs a subject-level brain functional network that describes the similarity between subjects from a graph signal processing (GSP) perspective. Based on the subject graph, we introduce the concept of graph signal smoothness to analyze the abnormal brain regions (feature brain regions) in which schizophrenic patients produce abnormal functional connections and to quantitatively rank the degree of abnormality of brain regions. We find that in the patients' brain networks, many new connections appear and some common connections are strengthened. The feature brain regions can be easily found according to the value of connection differences. Finally, we validate the learned feature brain regions by the results of two types of statistical analyses (ROI-to-ROI analysis and seed-to-voxel analysis), and the feature brain regions derived from graph signal smoothness are indeed the brain regions with significant differences in the statistical analysis, which illustrates the potential of graph signal smoothness for use in quantitative analysis of brain networks.

[Difference in Brain Age Between Alzheimer's Disease and Mild Cognitive Impairment]

Objective To investigate the brain age differences between Alzheimer's disease(AD)and mild cognitive impairment(MCI)patients,and further explore the correlations between brain age gap(BAG)and clinical features.Methods The clinical data and radiologic findings of 132 probable AD and AD-derived MCI patients diagnosed at Beijing Tiantan Hospital,Capital Medical University from December 2018 to July 2021 were retrospectively analyzed.According to the diagnostic criteria for AD and MCI,the patients were assigned into AD and MCI groups.In addition,156 volunteers without neurological diseases and other severe diseases were recruited as the control group.The general data,Montreal cognitive assessment(MoCA)score,and mini-mental state examination(MMSE)score were compared among the three groups.The deep learning-based brain age prediction model was employed to calculate the BAGs of the three groups.Spearman correlation analysis was conducted to explore the correlations between BAG and clinical features.Results The 132 patients included 106 patients in the AD group and 26 patients in the MCI group.The MoCA and MMSE scores followed an ascending trend of AD group Collapse

Key Words

• Alzheimer’s disease
• MRI
• brain age
• mild cognitive impairment

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MESH Headings

• Humans
• Alzheimer Disease
• Retrospective Studies
• Cognitive Dysfunction
• Brain/diagnostic imaging

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Grants Collapse

Affiliation(s)

Ming Meng Department of Radiology, Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China
Ren Wei Department of Radiology, Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China
Jun Sun Department of Radiology, Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China
Li Chai Department of Radiology, Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China
Ji-Wei Jiang Department of Neurology,Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China
Jun Xu Department of Neurology,Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China
Yun-Yun Duan Department of Radiology, Beijing Tiantan Hospital,Capital Medical University,Beijing 100070,China

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Human footprints in the Global South accelerate biomass carbon loss in ecologically sensitive regions

Human activities have placed significant pressure on the terrestrial biosphere, leading to ecosystem degradation and carbon losses. However, the full impact of these activities on terrestrial biomass carbon remains unexplored. In this study, we examined changes in global human footprint (HFP) and human-induced aboveground biomass carbon (AGBC) losses from 2000 to 2018. Our findings show an increasing trend in HFP globally, resulting in the conversion of wilderness areas to highly modified regions. These changes have altered global biomes' habitats, particularly in tropical and subtropical regions. We also found accelerated AGBC loss driven by HFP expansion, with a total loss of 19.99 ± 0.196 PgC from 2000 to 2018, especially in tropical regions. Additionally, AGBC is more vulnerable in the Global South than in the Global North. Human activities threaten natural habitats, resulting in increasing AGBC loss even in strictly protected areas. Therefore, scientifically guided planning of future human activities is crucial to protect half of Earth through mitigation and adaptation under future risks of climate change and global urbanization.

Antibody-mediated antigen loss switches augmented immunity to antibody-mediated immunosuppression

Antibodies against fetal red blood cell (RBC) antigens can cause hemolytic disease of the fetus and newborn (HDFN). Reductions in HDFN due to anti-RhD antibodies have been achieved through use of Rh immune globulin (RhIg), a polyclonal antibody preparation that causes antibody-mediated immunosuppression (AMIS), thereby preventing maternal immune responses against fetal RBCs. Despite the success of RhIg, it is only effective against 1 alloantigen. The lack of similar interventions that mitigate immune responses toward other RBC alloantigens reflects an incomplete understanding of AMIS mechanisms. AMIS has been previously attributed to rapid antibody-mediated RBC removal, resulting in B-cell ignorance of the RBC alloantigen. However, our data demonstrate that antibody-mediated RBC removal can enhance de novo alloimmunization. In contrast, inclusion of antibodies that possess the ability to rapidly remove the target antigen in the absence of detectable RBC clearance can convert an augmented antibody response to AMIS. These results suggest that the ability of antibodies to remove target antigens from the RBC surface can trigger AMIS in situations in which enhanced immunity may otherwise occur. In doing so, these results hold promise in identifying key antibody characteristics that can drive AMIS, thereby facilitating the design of AMIS approaches toward other RBC antigens to eliminate all forms of HDFN.

Brain Network Analysis of Schizophrenia Patients Based on Hypergraph Signal Processing

Since high-order relationships among multiple brain regions-of-interests (ROIs) are helpful to explore the pathogenesis of neurological diseases more deeply, hypergraph-based brain networks are more suitable for brain science research. Unlike the existing hypergraph based brain network (brain hypernetwork), where hyperedges containing the same number of ROIs are assumed to have equal weights (to some extent, the network is unweighted), and the underlying structure is described only by an incidence/adjacency matrix, in this paper, we propose a framework for constructing a truly weighted brain hypernetwork described by an adjacency tensor. Considering the relationships among vertices within a hyperedge, we propose a novel hyperedge weight estimation method and convert the incidence matrix into a weighted adjacency tensor. On the basis of tensor decomposition, we apply hypergraph signal processing tools, such as hypergraph Fourier transform, to analyze and compare the spectrum between schizophrenia patients and normal controls. It is found that there are more high frequency components in the spectrum of patients than controls, and the average amplitude is significantly greater than that of controls. Instead of extracting some simple topological features from brain hypernetworks for classification, we innovatively use the hypergraph spectrum and the spectral signal as classification features, and the classification results on two public datasets demonstrate the effectiveness of our proposed method.

[Risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on the machine learning]

OBJECTIVE

To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province.

METHODS

Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency.

RESULTS

A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%).

CONCLUSIONS

Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.

"Iridium Signature" Mass Spectrometric Probes: New Tools Integrated in a Liquid Chromatography-Mass Spectrometry Workflow for Routine Profiling of Nitric Oxide and Metabolic Fingerprints in Cells

Nitric oxide (NO) is a highly reactive signaling molecule involved in diverse biological processes. Simultaneous profiling of NO and associated metabolic fingerprints in a single assay allows more accurate assessments of cell states and offers the possibility to better understand its exact biological roles. Herein, a multiplexing LC-MS workflow was established for simultaneous detection of intracellular NO and various metabolites based on a novel "iridium signature" mass spectrometric probe (Ir-MSP841). This Ir-MSP841 can convert highly liable NO to a stable permanently charged triazole product (Ir-TP852), enabling direct MS detection of NO. This ^191/193Ir-signature mass spectrometric probe-based approach is endowed with overwhelming advantages of interference-free, high quantitative accuracy, and great sensitivity (limit of detection down to 0.14 nM). It also reveals good linearity over a wide concentration range 12.5-500 nM and has been successfully employed for exploring the release behaviors of three representative NO donors in cells. Meanwhile, metabolic profiling results reveal that varying the concentrations of NO has distinct effects on various cellular metabolites. This study provides a robust, sensitive, and versatile method for simultaneous detection of NO and numerous metabolites in a single LC-MS run and expands its applications in biomedical research.

PET Image Reconstruction With Kernel and Kernel Space Composite Regularizer

Led by the kernelized expectation maximization (KEM) method, the kernelized maximum-likelihood (ML) expectation maximization (EM) methods have recently gained prominence in PET image reconstruction, outperforming many previous state-of-the-art methods. But they are not immune to the problems of non-kernelized MLEM methods in potentially large reconstruction variance and high sensitivity to iteration numbers, and the difficulty in preserving image details and suppressing image variance simultaneously. To solve these problems, this paper derives, using the ideas of data manifold and graph regularization, a novel regularized KEM (RKEM) method with a kernel space composite regularizer for PET image reconstruction. The composite regularizer consists of a convex kernel space graph regularizer that smooths the kernel coefficients, a concave kernel space energy regularizer that enhances the coefficients' energy, and a composition constant that is analytically set to guarantee the convexity of composite regularizer. The composite regularizer renders easy use of PET-only image priors to overcome KEM's difficulty caused by the mismatch of MR prior and underlying PET images. Using this kernel space composite regularizer and the technique of optimization transfer, a globally convergent iterative algorithm is derived for RKEM reconstruction. Tests and comparisons on the simulated and in vivo data are presented to validate and evaluate the proposed algorithm, and demonstrate its better performance and advantages over KEM and other conventional methods.

Selenoprotein K enhances STING oligomerization to facilitate antiviral response

Stimulator-of-interferon gene (STING) is a vital element of the innate immune system against DNA viruses. Optimal activation of STING is crucial for maintaining immune homeostasis and eliminating invading viruses, and the oligomerization of STING is an essential prerequisite for STING activation. However, the mechanism of cGAMP-induced STING oligomerization in ER remains unclear. Selenoproteins are crucial for various physiological processes. Here, we identified that the endoplasmic reticulum (ER)-located transmembrane selenoprotein K (SELENOK) was induced during virus infection and facilitated innate immune responses against herpes simplex virus-1 (HSV-1). Mechanistically, SELENOK interacts with STING in the ER and promotes STING oligomerization, which in turn promotes its translocation from the ER to the Golgi. Consequently, Selenok deficiency suppresses STING-dependent innate responses and facilitates viral replication in vivo. Thus, the control of STING activation by selenium-mediated SELENOK expression will be a priming therapeutic strategy for the treatment of STING-associated diseases.

Imaging changes in the polarity of lipid droplets during NAFLD-Induced ferroptosis via a red-emitting fluorescent probe with a large Stokes shift

Cell death resulting from ferroptosis is a consequence of the accumulation of lipid peroxides that are produced when lipids and reactive oxygen species (ROS) interact. This process is dependent on iron and alters the structure and polarity of lipid droplets (LDs). Unlike reactive fluorescent probes, environment-sensitive fluorescent probes can accurately monitor metabolic activities by sensing the intracellular environment of living organisms. To this end, we developed a polarity-sensitive fluorescent probe LIP-Ser that anchors to LDs and can be used to monitor changes in the polarity of LDs during ferroptosis by in situ imaging. LIP-Ser has a red-emitting (λ_em = 634 nm) and a large Stokes shift (Δλ = 161 nm in 1,4-dioxane), which avoids it from autofluorescence interference and crosstalk between excitation and emission spectra, thereby preventing low signal-to-noise ratio and severe fluorescence self-quenching during imaging. Additionally, LIP-Ser is used in this study to demonstrate that non-alcoholic fatty liver disease (NAFLD) promotes ferroptosis at the cellular and in vivo levels, and that inhibition of cellular ferroptosis effectively reduces the damage caused by NAFLD to cells and mouse liver tissue.

Endoplasmic Reticulum Peroxynitrite Fluctuations in Hypoxia-Induced Endothelial Injury and Sepsis with a Two-Photon Fluorescence Probe

Sepsis is a serious systemic inflammatory disease that frequently results in death. Early diagnosis and timely targeted interventions could improve the therapeutic effect. Recent work has revealed that the reactive oxygen species (ROS) in the endoplasmic reticulum (ER) and hypoxia-induced endothelial injury play significant roles in sepsis. However, the relationship between the levels of peroxynitrite (ONOO^-) and hypoxia-induced endothelial injury as well as different states of sepsis remain unexplored. Herein, we developed a unique two-photon fluorescent probe (ER-ONOO^-) for detecting ONOO^- in aqueous solution that has high sensitivity, high selectivity, and ultrafast response time. In addition, ER-ONOO^- was successfully used to evaluate the levels of ONOO^- at the ER with three kinds of methods in a hypoxia-induced endothelial injury model. Furthermore, ER-ONOO^- is capable of monitoring the changes in organ fluorescence through ONOO^- variation in different stages of a cecum ligation and puncture (CLP) mouse model. Moreover, we also confirmed that the endoplasmic reticulum stress and oxidative stress participated in the CLP model. Consequently, this research can provide a reliable tool for studying ONOO^- fluctuation in sepsis and provide new insights into the pathogenic and therapeutic mechanisms involved.

Emerging new global soil governance structure in agrifood systems: Taking the “4 per 1,000” initiative as an example

Food systems emit 21%-37% of the global greenhouse gases (GHGs). Soil degradation, accelerated by global warming, poses a threat to over 40% of the land surfaces, threatening food security. Keeping soils alive and healthy could not only play a part in food security, but also in sequestrating GHGs for climate mitigation. In 2015, the “4 per 1,000” Initiative was launched in Paris COP21, indicating that a “4‰” annual growth rate of the soil organic carbon sequestration could hold the temperature increase within 1.5°C−2°C. However, major GHG emitting countries haven't signed the 4‰ Initiative at national level. Political willingness need to be encouraged though institutional innovations in the global soil governance (GSG). This article conducts a comprehensive policy review for the 4‰ Initiative and attempts to develop the concept of global soil governance from an aspect of New Common But Differentiated Responsibility. The SOC sink targets reveal that countries like China, India, the UK, the US, and France take more pains than those like Australia, Russia, and Canada. A new “soil carbon rich” and “soil carbon poor” divide is perceived, which needs to be taken into the GSG as a restructuring motivation for setting a more practical and integrated framework. In that sense, some developed countries face similar challenges as the developing countries do, but could contribute more in finance and technology. Bandwagon of applying sustainable agricultural land management (SALM) methodology in carbon markets implies that soil-climate co-benefits get greater practical momentum with quantified trading platforms, which may stimulate potentiality if embodied in Article 6 of the Paris Agreement.

Methyltransferase-like 3-induced N6-methyladenosine upregulation promotes oral squamous cell carcinoma by through p38

BACKGROUND

Oral squamous cell carcinoma (OSCC), a main type of squamous cell cancer, is associated with considerable morbidity and mortality. Recent reports suggested methyltransferase-like 3 (METTL3)-mediated N6-methyladenosine (m6A) modification to be an essential regulator in the fate determination of stem cells. However, the functional significance of METTL3 in OSCC remains largely unknown.

METHODS

METTL3 expression was examined in OSCC patient samples, followed by correlation analysis against clinical tumor features. Functional assays, such as assessment of surface marker expression, colony forming, BrdU incorporation, tumor xenograft assay, and m6A dot blot, were conducted to study the impact of METTL3 knockdown (KD) in OSCC cells.

RESULTS

High METTL3 expression was positively correlated with more severe clinical features of OSCC tumors. METTL3 KD caused impairment of stem-like capacities in OSCC cells, such as tumorigenicity in vivo and colony-forming ability in vitro. Furthermore, METTL3-KD and cycloleucine, a methylation inhibitor, decreased m6A levels and down-regulated p38 expression in OSCC cells. On the contrary, the impaired cell proliferation capacity of OSCC cells after METTL3-KD was restored by exogenous expression of p38.

CONCLUSION

Our findings identified m6A methyltransferase METTL3 as a key element in the regulation of tumorigenesis in OSCC.

Natural product manoalide promotes EGFR-TKI sensitivity of lung cancer cells by KRAS-ERK pathway and mitochondrial Ca2+ overload-induced ferroptosis

Background: Manoalide (MA), a proven natural inhibitor of PLA2 has anticancer effects, but its potential application and mechanism as an anticancer drug to promote EGFR-TKI sensitivity in lung cancer cells have not been studied. Methods: KRAS-mutated lung cancer cells and organoids, acquired osimertinib-resistant lung cancer cell lines HCC827OR, were used as EGFR-TKI-resistant models. CCK-8, clone formation, apoptosis assays, and calcein-AM staining were performed to investigate the inhibitory effects of MA in lung cancer cells and organoids. The flow cytometry or confocal microscope was used to detect lipid droplets, ROS, lipid peroxidation, mitochondria Ca²⁺, and iron content. The oxygen consumption rate (OCR) and fatty acid oxidation (FAO) were used to estimate the effect of MA on mitochondrial function. Results: MA inhibits the proliferation of KRAS-mutated lung cancer cells and organoids. In addition, MA induces ER stress in a ROS-dependent mechanism. The ROS induced by MA is mainly in mitochondrial and causes lipid peroxidation, thereby inhibiting mitochondrial FAO metabolism and promoting the accumulation of lipid droplets. MA also suppresses the KRAS-ERK pathway through ROS and promotes the sensitivity of KRAS-mutated lung cancer cells and organoids to osimertinib. Furthermore, MA induces ferroptosis by suppressing the NRF2-SLC7A11 axis and mitochondrial Ca²⁺ overload induced-FTH1 pathways to promote the sensitivity of osimertinib-resistant lung cancer cells to osimertinib. Conclusions: MA is a candidate EGFR-TKI sensitizer in KRAS-mutated and osimertinib-resistant lung cancer cells.

Tracking Autophagy Process with a TBET and AIE-Based Ratiometric Two-Photon Viscosity Probe

Autophagy is a cellular self-degrading process that plays a key role in cellular health and functioning. Since autophagy disorder is related to many diseases, it is highly important to detect autophagy. This study aimed to establish a dual-sensing mechanism-based ratiometric viscosity-sensitive lysosome-targeted two-photon fluorescent probe Vis-sun to track the autophagy process (the increase in lysosome viscosity during autophagy) by combining through bond energy transfer (TBET) and aggregation-induced emission (AIE). The introduction of TBET not only overcame the interference of background signals but also achieved the baseline separation of two emission peaks, thus reducing the crosstalk between emissions, as well as the noninvasive bio-sensing of biological targets and long-term real-time tracer imaging by introducing AIE. In vitro experiments showed that the fluorescence intensity at 485 nm decreased gradually on increasing the volume ratio of water to tetrahydrofuran (V_water/V_THF), while the fluorescence intensity at 605 nm increased significantly. Also, the fluorescence signal was maximized when the water content reached 100%. At the same time, the probe exhibited a significant dependence on the ambient viscosity. Therefore, the dynamic monitoring of lysosome viscosity during autophagy and the in situ imaging of autophagy fluctuations during stroke-induced neuroinflammation were successfully achieved by implementing Vis-sun lysosome anchoring with morpholine.

PSMG2-controlled proteasome-autophagy balance mediates the tolerance for MEK-targeted therapy in triple-negative breast cancer

Although the MAPK pathway is aberrantly activated in triple-negative breast cancers (TNBCs), the clinical outcome of MEK-targeted therapy is still poor. Through a genome-wide CRISPR-Cas9 library screening, we find that inhibition of PSMG2 sensitizes TNBC cells BT549 and MB468 to the MEK inhibitor AZD6244. Mechanistically, PSMG2 knockdown impairs proteasome function, which in turn activates autophagy-mediated PDPK1 degradation. The PDPK1 degradation significantly enhances AZD6244-induced tumor cell growth inhibition by interrupting the negative feedback signals toward the AKT pathway. Consistently, co-targeting proteasomes and MEK with inhibitors synergistically suppresses tumor cell growth. The autophagy inhibitor chloroquine partially relieves the PDPK1 degradation and reverses the growth inhibition induced by combinatorial inhibition of MEK and proteasome. The combination regimen with the proteasome inhibitor MG132 plus AZD6244 synergistically inhibits tumor growth in a 4T1 xenograft mouse model. In summary, our study not only unravels the mechanism of MEK inhibitor resistance but also provides a combinatorial therapeutic strategy for TNBC in clinics.

SALL4: An Intriguing Therapeutic Target in Cancer Treatment

Spalt-Like Transcription Factor 4 (SALL4) is a critical factor for self-renewal ability and pluripotency of stem cells. On the other hand, various reports show tight relation of SALL4 to cancer occurrence and metastasis. SALL4 exerts its effects not only by inducing gene expression but also repressing a large cluster of genes through interaction with various epigenetic modifiers. Due to high expression of SALL4 in cancer cells and its silence in almost all adult tissues, it is an ideal target for cancer therapy. However, targeting SALL4 meets various challenges. SALL4 is a transcription factor and designing appropriate drug to inhibit this intra-nucleus component is challenging. On the other hand, due to lack of our knowledge on structure of the protein and the suitable active sites, it becomes more difficult to reach the appropriate drugs against SALL4. In this review, we have focused on approaches applied yet to target this oncogene and discuss the potential of degrader systems as new therapeutics to target oncogenes.

A fast responsive and cell membrane-targetable near-infrared H2S fluorescent probe for drug resistance bioassays in chemotherapy

A cell membrane-targeted near-infrared fluorescent probe, CMCu-H₂S, was fabricated through employing hydrophobic chains and cyclen-Cu²⁺ as targeting and recognition groups, respectively. NIR fluorescence of CMCu-H₂S can significantly increase after reacting with H₂S by removing the quenchable Cu²⁺. This probe exhibited high selectivity and an extremely fast response rate. Cell imaging results demonstrated that there was a close relationship between the overexpression of NFS1 and drug resistance and inhibition of NFS1 was beneficial for improving the efficacy of chemotherapy.

Clinical significance of pancreatic calcifications: a 15-year single-center observational study

Objectives

Pancreatic calcifications (PC) are considered specific for chronic pancreatitis (CP), but PC may also be present in non-CP diseases. The aims are to understand the pattern of calcifications in different diseases and to determine they were related to malignant diseases.

Methods

A retrospective study was performed including patients with PC or CP undergoing surgery in the Department of General Surgery of Ruijin Hospital from January 2003 to June 2018.

Results

PC were observed in 168 (4.5%) of the 3755 patients with pancreatic lesions treated during the study period. The majority of patients with PC had three kinds of CP (73.2%) while 26.8% had other five kinds of non-CP diseases. In patients with non-CP diseases, the incidence of PC in malignant intraductal papillary mucinous neoplasm (IPMN) was significantly higher than benign IPMN (8.3% vs. 0.7%, p = 0.004). In patients of CP with pancreatic mass (n = 81), PC (Odds ratio = 28.6, p = 0.000), advanced age (> 55 years) and parenchymal atrophy were independent predictors for malignancy. In patients of CP without pancreatic mass (n = 110), there were 82 cases (74.5%) with PC and 5 cases (4.5%) with pancreatic ductal adenocarcinoma. The regression model of risk factors was not successful.

Conclusions

The disease spectrum with PC was very diverse. PC may be related to malignant IPMN in non-CP diseases and is related to malignancy in the patients of CP with pancreatic mass and indications for resection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00725-9.

Tracking autophagy process with a through bond energy transfer-based ratiometric two-photon viscosity probe

Autophagy is a self-degradation process in cells, which is of vital significance to the health and operation of organisms. Due to the increase of lysosomal viscosity during autophagy, viscosity probes that specifically accumulate in lysosome are powerful tools for monitoring autophagy and investigating related diseases. However, there is still a lack of viscosity-sensitive ratiometric autophagy probes, which restricts the tracking of autophagy with high accuracy in complex physiological environment. Herein, a viscosity-responsive, lysosome targeted two-photon fluorescent probe Lyso-Vis was designed based on through bond energy transfer (TBET) mechanism. The TBET-based probe achieved the separation of two emission baselines, which greatly improved the resolution and reliability of sensing and imaging. Under 810 nm two-photon excitation, the emission intensity ratio of the red and green channel increased with a viscosity dependent manner. Lyso-Vis not only for the first time realized ratiometric sensing of lysosomal viscosity during autophagy process, but also visualized the association of autophagy with inflammation and stroke, and it was applied to explore the activation and inhibition of autophagy during stroke in mice.

Demethylation and Up-Regulation of an Oncogene after Hypomethylating Therapy

BACKGROUND

Although hypomethylating agents are currently used to treat patients with cancer, whether they can also reactivate and up-regulate oncogenes is not well elucidated.

METHODS

We examined the effect of hypomethylating agents on SALL4, a known oncogene that plays an important role in myelodysplastic syndrome and other cancers. Paired bone marrow samples that were obtained from two cohorts of patients with myelodysplastic syndrome before and after treatment with a hypomethylating agent were used to explore the relationships among changes in SALL4 expression, treatment response, and clinical outcome. Leukemic cell lines with low or undetectable SALL4 expression were used to study the relationship between SALL4 methylation and expression. A locus-specific demethylation technology, CRISPR-DNMT1-interacting RNA (CRISPR-DiR), was used to identify the CpG island that is critical for SALL4 expression.

RESULTS

SALL4 up-regulation after treatment with hypomethylating agents was observed in 10 of 25 patients (40%) in cohort 1 and in 13 of 43 patients (30%) in cohort 2 and was associated with a worse outcome. Using CRISPR-DiR, we discovered that demethylation of a CpG island within the 5' untranslated region was critical for SALL4 expression. In cell lines and patients, we confirmed that treatment with a hypomethylating agent led to demethylation of the same CpG region and up-regulation of SALL4 expression.

CONCLUSIONS

By combining analysis of patient samples with CRISPR-DiR technology, we found that demethylation and up-regulation of an oncogene after treatment with a hypomethylating agent can indeed occur and should be further studied. (Funded by Associazione Italiana per la Ricerca sul Cancro and others.).

Simultaneous tracking of autophagy and oxidative stress during stroke with an ICT-TBET integrated ratiometric two-photon platform

Over recent years, fluorescent probes exhibiting simultaneous responses to multiple targets have been developed for in situ, real-time monitoring of cellular metabolism using two photon fluorescence sensing techniques due to numerous advantages including ease of operation, rapid reporting, high resolution, long visualization time and being non-invasive. However, due to interference from different fluorescence channels during simultaneous monitoring of multiple targets and the lack of ratiometric capability amongst the available probes, the accuracy in tracing metabolic processes has been restricted. With this research, using a through-bond energy transfer (TBET) mechanism, we designed a viscosity and peroxynitrite (ONOO^-) mitochondria-targeting two-photon ratiometric fluorescent probe Mito-ONOO. Our results indicated that with decreasing levels of mitochondrial viscosity and increasing levels of ONOO^-, the maximum of the emission wavelength of the probe shifted from 621 nm to 495 nm under 810 nm two-photon excitation. The baselines for the two emission peaks were significantly separated (Δλ = 126 nm), improving the resolution and reliability of bioimaging. Moreover, by ratiometric analysis during oxygen-glucose deprivation/reoxygenation (OGD/R, commonly used to simulate cell ischemia/reperfusion injury), the real-time visualization of the metabolic processes of autophagy and oxidative stress was possible. Our research indicated that during cellular oxygen-glucose deprivation/reoxygenation, cells produce ONOO^-, causing cellular oxidative stress and cellular autophagy after 15 min, as such Mito-ONOO exhibits the potential for the monitoring and diagnosis of stroke, as well as providing insight into potential treatments, and drug design.

Non-coding RNA LEVER sequestration of PRC2 can mediate long range gene regulation

Polycomb Repressive Complex 2 (PRC2) is an epigenetic regulator required for gene silencing during development. Although PRC2 is a well-established RNA-binding complex, the biological function of PRC2-RNA interaction has been controversial. Here, we study the gene-regulatory role of the inhibitory PRC2-RNA interactions. We report a nuclear long non-coding RNA, LEVER, which mapped 236 kb upstream of the β-globin cluster as confirmed by Nanopore sequencing. LEVER RNA interacts with PRC2 in its nascent form, and this prevents the accumulation of the H3K27 repressive histone marks within LEVER locus. Interestingly, the accessible LEVER chromatin, in turn, suppresses the chromatin interactions between the ε-globin locus and β-globin locus control region (LCR), resulting in a repressive effect on ε-globin gene expression. Our findings validate that the nascent RNA-PRC2 interaction inhibits local PRC2 function in situ. More importantly, we demonstrate that such a local process can in turn regulate the expression of neighboring genes.

Identification of a long non-coding RNA LEVER, that inhibits the Polycomb Repressive Complex 2 (PRC2) and controls nearby embryonic form of beta-globin gene, provides additional evidence for PRC2-RNA functional interaction.

Case Report: Mucocele-Like Tumor of the Breast Associated With Ductal Carcinoma In Situ

Mucocele-like tumor of the breast is histologically characterized as mucin-containing cysts with mucin leaking to the stroma. It could be associated with atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). We report a case of mucocele-like tumor of the breast associated with DCIS confirmed by paraffin section. We review the literature and discuss the imaging features, pathology, and clinical management of the lesion. These lesions demonstrate characteristic imaging features, and we especially highlight the MR characteristics, as they have not been well documented. Performing a diagnostic fine-needle aspiration cytology (FNAC) of mucocele-like tumor carries a risk of tumor underestimation; therefore, excision for all mucocele-like tumors is suggested to be the best approach. However, some recent reports recommend close follow-up for patients with low-risk factors who have mucocele-like tumor without atypia on FNAC.

Near-Infrared in and out: Observation of Autophagy during Stroke via a Lysosome-Targeting Two-Photon Viscosity-Dependent Probe

Fluorescence imaging using probes with two-photon excitation and near-infrared emission is currently the most popular in situ method for monitoring biological species or events, with a large imaging depth, low background fluorescence, low optical damage, and high spatial and temporal resolution. Nevertheless, current fluorescent dyes with near-infrared emission still have some disadvantages such as poor water solubility, low fluorescence quantum yield, and small two-photon absorption cross sections. These drawbacks are mainly caused by the structural characteristics of dyes with large conjugation surfaces but lacking strong and rigid structures. Herein, a lysosome-targeted and viscosity-sensitive probe (NCIC-VIS) is designed and synthesized. The protonation of morpholine not only helps anchor NCIC-VIS to the lysosome but also significantly enhances its water solubility. More importantly, its viscosity can increase the rigid structure of NCIC-VIS, which will improve the fluorescence quantum yield and the two-photon absorption cross section due to the imposed restrictions on molecular torsion. Based on the abovementioned characteristics, the real-time imaging of cellular autophagy (could increase the viscosity of lysosomes) was realized using NCIC-VIS. The results demonstrated that the level of autophagy was significantly enhanced in mice during stroke, while the inhibition of oxidative stress significantly reduced the degree of autophagy. The study corroborates that oxidative stress induced by stroke can lead to the development of autophagy.

Graph Signal Processing Approach to QSAR/QSPR Model Learning of Compounds

Quantitative relationship between the activity/property and the structure of compound is critical in chemical applications. To learn this quantitative relationship, hundreds of molecular descriptors have been designed to describe the structure, mainly based on the properties of vertices and edges of molecular graph. However, many descriptors degenerate to the same values for different compounds with the same molecular graph, resulting in model failure. In this paper, we design a multidimensional signal for each vertex of the molecular graph to derive new descriptors with higher discriminability. We treat the new and traditional descriptors as the signals on the descriptor graph learned from the descriptor data, and enhance descriptor dissimilarity using the Laplacian filter derived from the descriptor graph. Combining these with model learning techniques, we propose a graph signal processing based approach to obtain reliable new models for learning the quantitative relationship and predicting the properties of compounds. We also provide insights from chemistry for the boiling point model. Several experiments are presented to demonstrate the validity, effectiveness and advantages of the proposed approach.

Diverse functions of long noncoding RNAs in acute myeloid leukemia: emerging roles in pathophysiology, prognosis, and treatment resistance

PURPOSE OF REVIEW

Advancements in the next-generation sequencing technologies have identified rare transcripts of long noncoding RNAs (lncRNAs) in the genome of cancers, including in acute myeloid leukemia (AML). The purpose of this review is to highlight the contribution of lncRNAs in AML pathogenesis, prognosis, and chemoresistance.

RECENT FINDINGS

Several studies have recently reported that deregulated lncRNAs are novel key players in the development of AML and are associated with AML pathophysiology and may serve as prognostic indicators. A few aberrantly expressed lncRNAs that correlated with the recurrent genetic mutations in AML such as NPM1 and RUNX1 have recently been characterized. Moreover, a few lncRNAs in MLL-rearranged leukemia have been described. Additionally, the involvement of lncRNAs in AML chemoresistance has been postulated.

SUMMARY

Investigating the functional roles of the noncoding regions including lncRNAs, may provide novel insights into the pathophysiology, refine the prognostic schema, and provide novel therapeutic treatment strategies in AML.

Alterations of Gut Microbiome and Metabolite Profiles Associated With Anabatic Lipid Dysmetabolism in Thyroid Cancer

BACKGROUND

Currently, the high morbidity of individuals with thyroid cancer (TC) is an increasing health care burden worldwide. The aim of our study was to investigate the relationship among the gut microbiota community, metabolites, and the development of differentiated thyroid cancer.

METHODS

16S rRNA gene sequencing and an integrated LC-MS-based metabolomics approach were performed to obtain the components and characteristics of fecal microbiota and metabolites from 50 patients with TC and 58 healthy controls (HCs).

RESULTS

The diversity and richness of the gut microbiota in the TC patients were markedly decreased. The composition of the gut microbiota was significantly altered, and the Bacteroides enterotype was the dominant enterotype in TC patients. Additionally, the diagnostic validity of the combined model (three genera and eight metabolites) and the metabolite model (six metabolites) were markedly higher than that of the microbial model (seven genera) for distinguishing TC patients from HCs. LEfSe analysis demonstrated that genera (g_Christensenellaceae_R-7_group, g_Eubacterium_coprostanoligenes_group) and metabolites [27-hydroxycholesterol (27HC), cholesterol] closely related to lipid metabolism were greatly reduced in the TC group. In addition, a clinical serum indicator (total cholesterol) and metabolites (27HC and cholesterol) had the strongest influence on the sample distribution. Furthermore, functional pathways related to steroid biosynthesis and lipid digestion were inhibited in the TC group. In the microbiota-metabolite network, 27HC was significantly related to metabolism-related microorganisms (g_Christensenellaceae_R-7_group).

CONCLUSIONS

Our research explored the characteristics of the gut microecology of patients with TC. The findings of this study will help to discover risk factors that affect the occurrence and development of TC in the intestinal microecology.