Increasing inhomogeneity of the global ocean

Author Posting. © American Geophysical Union, 2022. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 49(12), (2022): e2021GL097598, https://doi.org/10.1029/2021GL097598.The ocean is inhomogeneous in hydrographic properties with diverse water masses. Yet, how this inhomogeneity has evolved in a rapidly changing climate has not been investigated. Using multiple observational and reanalysis datasets, we show that the spatial standard deviation (SSD) of the global ocean has increased by 1.4 ± 0.1% in temperature and 1.5 ± 0.1% in salinity since 1960. A newly defined thermohaline inhomogeneity index, a holistic measure of both temperature and salinity changes, has increased by 2.4 ± 0.1%. Climate model simulations suggest that the observed ocean inhomogeneity increase is dominated by anthropogenic forcing and projected to accelerate by 200%–300% during 2015–2100. Geographically, the rapid upper-ocean warming at mid-to-low latitudes dominates the temperature inhomogeneity increase, while the increasing salinity inhomogeneity is mainly due to the amplified salinity contrast between the subtropical and subpolar latitudes.This work is supported by the Strategic Priority Research Program of Chinese Academy of Sciences (grant XDB42000000 and XDB40000000), the National Key R&D Program of China (2017YFA0603200), and the Shandong Provincial Natural Science Foundation (ZR2020JQ17), and the U.S. National Science Foundation Physical Oceanography Program (OCE- 2048336).2022-12-2

Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing

Background: Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis. Methods: We conducted differential gene expression analysis on patient samples from The Cancer Genome Atlas (TCGA) and enriched our understanding of gene functions. Using the least absolute selection and shrinkage operator (LASSO) regression, we established a risk model and validated it using an independent dataset from the International Cancer Genome Consortium (ICGC). Clinical variables were incorporated into a nomogram to predict overall survival (OS), and machine learning was used to explore the risk factor characteristics’ impact on PCa prognosis. Our prognostic model was confirmed using various databases, including single-cell RNA-sequencing datasets (scRNA-seq), the Cancer Cell Line Encyclopedia (CCLE), PCa cell lines, and tumor tissues. Results: We identified 83 differentially expressed genes (DEGs). Furthermore, WASIR1, KRTAP5-1, TLX1, KIF4A, and IQGAP3 were determined to be significant risk factors for OS and progression-free survival (PFS). Based on these five risk factors, we developed a risk model and nomogram for predicting OS and PFS, with a C-index of 0.823 (95% CI, 0.766–0.881) and a 10-year area under the curve (AUC) value of 0.788 (95% CI, 0.633–0.943). Additionally, the 3-year AUC was 0.759 when validating using ICGC. KRTAP5-1 and WASIR1 were found to be the most influential prognosis factors when using the optimized machine learning model. Finally, the established model was interrelated with immune cell infiltration, and the signals were found to be differentially expressed in PCa cells when using scRNA-seq datasets and tissues. Conclusions: We engineered an original and novel prognostic model based on five gene signatures through TCGA and machine learning, providing new insights into the risk of scarification and survival prediction for PCa patients in clinical practice

The Molecular Gut-Brain Axis in Early Brain Development

Millions of nerves, immune factors, and hormones in the circulatory system connect the gut and the brain. In bidirectional communication, the gut microbiota play a crucial role in the gut-brain axis (GBA), wherein microbial metabolites of the gut microbiota regulate intestinal homeostasis, thereby influencing brain activity. Dynamic changes are observed in gut microbiota as well as during brain development. Altering the gut microbiota could serve as a therapeutic target for treating abnormalities associated with brain development. Neurophysiological development and immune regulatory disorders are affected by changes that occur in gut microbiota composition and function. The molecular aspects relevant to the GBA could help develop targeted therapies for neurodevelopmental diseases. Herein, we review the findings of recent studies on the role of the GBA in its underlying molecular mechanisms in the early stages of brain development. Furthermore, we discuss the bidirectional regulation of gut microbiota from mother to infant and the potential signaling pathways and roles of posttranscriptional modifications in brain functions. Our review summarizes the role of molecular GBA in early brain development and related disorders, providing cues for novel therapeutic targets

BI-D1870 Induces Mitotic Dysfunction and Apoptosis in Neuroblastoma by Regulating the PI3K-Akt-mTORC1 Signal Axis

Introduction: Neuroblastoma (NB) is one of the most common extracranial solid malignant tumors in children. The 5-year survival rate of high-risk or refractory NB is less than 50%. Therefore, developing new effective therapeutics for NB remains an urgent challenge. Materials and Methods: Based on the NB dataset TARGET-NBL in the TCGA database, the prognosis-related genes were analyzed using univariate cox regression (p 1 and 150 hub genes with HR Results: Both the in vivo and in vitro experiments showed that BI-D1870 could inhibit tumor proliferation and induce tumor apoptosis. Furthermore, we proved that BI-D1870 caused G2/M phase arrest and mitosis damage in cells. RNA-seq of cells showed that BI-D1870 may inhibit the growth of NB by inhibiting the PI3K-Akt-mTOR axis. Western blot and immunofluorescence testing showed that BI-D1870 inhibited the PI3K-Akt-mTORC1 signal pathway to regulate the phosphorylation of RPS6 and 4E BP1 proteins, inhibit protein translation, and inhibit microtubule formation, thus preventing mitotic proliferation and inducing apoptosis. Conclusions: This study provides strong support that BI-D1870 may be a potential adjuvant therapy for NB

Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters

Abstract Objective To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). Materials and methods Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT–Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve. Results Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT–Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT–Radiology nomogram was established based on the DECT–Radiology model, which showed the highest net benefit and satisfactory consistency. Conclusions The DECT–Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. Critical relevance statement The DECT–Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. Key points • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT–Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression. Graphical Abstrac

What is global health? Key concepts and clarification of misperceptions

The call for “Working Together to Build a Community of Shared Future for Mankind” requires us to improve people’s health across the globe, while global health development entails a satisfactory answer to a fundamental question: “What is global health?” To promote research, teaching, policymaking, and practice in global health, we summarize the main points on the definition of global health from the Editorial Board Meeting of Global Health Research and Policy, convened in July 2019 in Wuhan, China. The meeting functioned as a platform for free brainstorming, in-depth discussion, and post-meeting synthesizing. Through the meeting, we have reached a consensus that global health can be considered as a general guiding principle, an organizing framework for thinking and action, a new branch of sciences and specialized discipline in the large family of public health and medicine. The word “global” in global health can be subjective or objective, depending on the context and setting. In addition to dual-, multi-country and global, a project or a study conducted at a local area can be global if it (1) is framed with a global perspective, (2) intends to address an issue with global impact, and/or (3) seeks global solutions to an issue, such as frameworks, strategies, policies, laws, and regulations. In this regard, global health is eventually an extension of “international health” by borrowing related knowledge, theories, technologies and methodologies from public health and medicine. Although global health is a concept that will continue to evolve, our conceptualization through group effort provides, to date, a comprehensive understanding. This report helps to inform individuals in the global health community to advance global health science and practice, and recommend to take advantage of the Belt and Road Initiative proposed by China