Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis

BackgroundOvarian cancer (OC) is a female reproductive system tumor. RNA modifications play key roles in gene expression regulation. The growing evidence demonstrates that RNA methylation is critical for various biological functions, and that its dysregulation is related to the progression of cancer in human.MethodOC samples were classified into different subtypes (Clusters 1 and 2) based on various RNA-modification regulatory genes (RRGs) in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) by nonnegative matrix factorization method (NMF). Based on differently expressed RRGs (DERRGs) between clusters, a pathologically specific RNA-modification regulatory gene signature was constructed with Lasso regression. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic ability of the identified model. The correlations of clinicopathological features, immune subtypes, immune scores, immune cells, and tumor mutation burden (TMB) were also estimated between different NMF clusters and riskscore groups.ResultsIn this study, 59 RRGs in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) were obtained from TCGA database. These RRGs were interactional, and sample clusters based on these regulators were significantly correlated with survival rate, clinical characteristics (involving survival status and pathologic stage), drug sensibility, and immune microenvironment. Furthermore, Lasso regression based on these 21 DERRGs between clusters 1 and 2 constructed a four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1). Based on this signature, 307 OC patients were classified into high- and low-risk groups based on median value of riskscores from lasso regression. This identified signature was significantly associated with overall survival, radiation therapy, age, clinical stage, cancer status, and immune cells (involving CD4+ memory resting T cells, plasma cells, and Macrophages M1) of ovarian cancer patients. Further, GSEA revealed that multiple biological behaviors were significantly enriched in different groups.ConclusionsOC patients were classified into two subtypes per these RRGs. This study identified four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1) in OC, which was an independent prognostic model for patient stratification, prognostic evaluation, and prediction of response to immunotherapy in ovarian cancer by classifying OC patients into high- and low-risk groups

Magnetostratigraphic dating of the Linyi Fauna and implications for sequencing the mammalian faunas on the Chinese Loess Plateau

The Chinese Loess Plateau (CLP) in North China is an important terrestrial archive that witnessed the environmental changes and mammal and early human evolution in Asia over the past 2.6 Ma. Establishing precise ages for the Pleistocene faunas on the CLP is critical for better understanding of these environmental, biological, and archaeological issues. Here we report a new magnetostratigraphic record that places age constraints on the Linyi Fauna on the southeastern CLP. Our investigated 170-m-thick Linyi section mainly consists of two portions: (1) an overlying eolian Quaternary loess-paleosol sequence and (2) underlying fluvial-lacustrine sand and silty clay. Paleomagnetic results suggest that the composite section records the Brunhes chron, Jaramillo and Olduvai subchrons, and successive reverse polarity portions of the intervening Matuyama chron. The Linyi Fauna is located between Jaramillo and Olduvai subchrons in the fluvial-lacustrine interval, with an estimated age of similar to 1.5-1.6 Ma. Combining previously dated faunas, we establish a Pleistocene magnetochronology spanning from 2.54 to 0.65 Ma for the faunas on the CLP

Rapid environmental changes in the Lake Qinghai basin during the late Holocene

The Lake Qinghai Basin is sensitive to global and regional climate change because of its unique geographical location. It is the hotspot for paleoclimate research in East Asia. In this study, we reconstructed the environmental evolution of the Lake Qinghai since ∼9 ka by using a high-resolution peat and fluvial-lacustrine record (Laoyinggou profile) obtained at the foot of Nanshan Mountain. Based on 8 AMS14C dates and lithology, loss on ignition (LOI), total organic matter (TOC), X-ray fluorescence (XRF) core-scanning measurements, ratio of total organic carbon to nitrogen (TOC/TN), and sediment particle sorting coefficients, we show that during the Middle Holocene (∼9–4.4 ka BP) this region was primarily dominated by the Asian summer monsoon, with a consistent, warm, and humid environment. By contrast, during the late Holocene (4.4 ka to present), the climatic context in this area fluctuated dramatically at the millennial scales. The low TOC content, lower TOC/TN ration and strong hydroclimatic indicate six rapid climate change events, which occurred at ∼4.0 ka, ∼3.6 ka, ∼3.2 ka, ∼2.8 ka, ∼2.1 ka, and ∼1.4 ka, all of which coincided to cold episodes in the North Atlantic Ocean

Patient safety education for undergraduate medical students: a systematic review

<p>Abstract</p> <p>Background</p> <p>To reduce harm caused by health care is a global priority. Medical students should be able to recognize unsafe conditions, systematically report errors and near misses, investigate and improve such systems with a thorough understanding of human fallibility, and disclose errors to patients. Incorporating the knowledge of how to do this into the medical student curriculum is an urgent necessity. This paper aims to systematically review the literature about patient safety education for undergraduate medical students in terms of its content, teaching strategies, faculty availability and resources provided so as to identify evidence on how to promote patient safety in the curriculum for medical schools. This paper includes a perspective from the faculty of a medical school, a major hospital and an Evidence Based Medicine Centre in Sichuan Province, China.</p> <p>Methods</p> <p>We searched MEDLINE, ERIC, Academic Source Premier(ASP), EMBASE and three Chinese Databases (Chinese Biomedical Literature Database, CBM; China National Knowledge Infrastructure, CNKI; Wangfang Data) from 1980 to Dec. 2009. The pre-specified form of inclusion and exclusion criteria were developed for literature screening. The quality of included studies was assessed using Darcy Reed and Gemma Flores-Mateo criteria. Two reviewers selected the studies, undertook quality assessment, and data extraction independently. Differing opinions were resolved by consensus or with help from the third person.</p> <p>Results</p> <p>This was a descriptive study of a total of seven studies that met the selection criteria. There were no relevant Chinese studies to be included. Only one study included patient safety education in the medical curriculum and the remaining studies integrated patient safety into clinical rotations or medical clerkships. Seven studies were of a pre and post study design, of which there was only one controlled study. There was considerable variation in relation to contents, teaching strategies, faculty knowledge and background in patient safety, other resources and outcome evaluation in these reports. The outcomes from including patient safety in the curriculum as measured by medical students' knowledge, skills, and attitudes varied between the studies.</p> <p>Conclusions</p> <p>There are only a few relevant published studies on the inclusion of patient safety education into the undergraduate curriculum in medical schools either as a selective course, a lecture program, or by being integrated into the existing curriculum even in developed countries with advanced health and education systems. The integration of patient safety education into the existing curriculum in medical schools internationally, provides significant challenges.</p

Geochemical characteristics of surface dune sand in the Mu Us Desert, Inner Mongolia, and implications for reconstructing the paleoenvironment

We present a new dataset from 28 active and 13 stabilizedesemi stabilized dunefields in the Mu Us Desert to report the geochemical macroscale properties as well as reveal the relationship between various chemical ratios and modern climate conditions among different types of Mu Us sandy landscapes. We find that several chemical-weathering indexes, such as CIA, CIW, CPA, and WIP, can be used for the reconstruction of the paleoclimate and servel conditions. One should be cautious in interpreting the weathering intensity using these chemical ratios at a given deposition site when the geochemical background is unknown. This preliminary geochemistry study shows that stabilizedesemi stabilized dunefields, which are influenced by Asian summer monsoon (ASM) precipitation, are analogous to buried paleosols, whereas active dunefields, which are controlled by Asian winter monsoon (AWM) wind, resemble paleo-dune sand. The comparison with the geochemical results from an excellent dune-paleosol succession implies that stronger ASM and AWM periods could have recurred 8-9 times in the Mu Us Desert during the early Holocene. (C) 2017 Published by Elsevier Ltd

Multi-modal Queried Object Detection in the Wild

We introduce MQ-Det, an efficient architecture and pre-training strategy design to utilize both textual description with open-set generalization and visual exemplars with rich description granularity as category queries, namely, Multi-modal Queried object Detection, for real-world detection with both open-vocabulary categories and various granularity. MQ-Det incorporates vision queries into existing well-established language-queried-only detectors. A plug-and-play gated class-scalable perceiver module upon the frozen detector is proposed to augment category text with class-wise visual information. To address the learning inertia problem brought by the frozen detector, a vision conditioned masked language prediction strategy is proposed. MQ-Det's simple yet effective architecture and training strategy design is compatible with most language-queried object detectors, thus yielding versatile applications. Experimental results demonstrate that multi-modal queries largely boost open-world detection. For instance, MQ-Det significantly improves the state-of-the-art open-set detector GLIP by +7.8% zero-shot AP on the LVIS benchmark and averagely +6.3% AP on 13 few-shot downstream tasks, with merely 3% pre-training time required by GLIP. Code is available at https://github.com/YifanXu74/MQ-Det.Comment: Under revie

Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization

Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary. Recent work resorts to the rich knowledge in pre-trained vision-language models. However, existing methods are ineffective in proposal-level vision-language alignment. Meanwhile, the models usually suffer from confidence bias toward base categories and perform worse on novel ones. To overcome the challenges, we present MEDet, a novel and effective OVD framework with proposal mining and prediction equalization. First, we design an online proposal mining to refine the inherited vision-semantic knowledge from coarse to fine, allowing for proposal-level detection-oriented feature alignment. Second, based on causal inference theory, we introduce a class-wise backdoor adjustment to reinforce the predictions on novel categories to improve the overall OVD performance. Extensive experiments on COCO and LVIS benchmarks verify the superiority of MEDet over the competing approaches in detecting objects of novel categories, e.g., 32.6% AP50 on COCO and 22.4% mask mAP on LVIS

Climate impacts of 2009/2010 mixed-type El Niño on double ITCZs over the eastern Pacific Ocean

A double intertropical convergence zone (ITCZ) pattern emerges over the eastern Pacific Ocean in March-April. Their inter-annual variabilities may exert major climatic and ecological effects. El Niño-Southern Oscillation (ENSO) can significantly regulate the inter-annual variability of double ITCZs. ENSO diversity has increased in recent years. A mixed-type El Niño occurred in 2009/2010. Our results reveal that the meridional SSTA pattern in mixed-type El Niño is a combination of “SST warming with a maximum at the equator” (i.e., EP-type delta SST) and “north-warm and south-cold” (i.e., CP-type delta SST) patterns. In a mixed-type El Niño, both meridional EP-type and CP-type delta SST played a role and had corresponding climate impacts. Under the coordinated modulation of EP-type and CP-type delta SST in a mixed-type El Niño, the climate effect of EP-type delta SST (increasing equatorial precipitation) is weakened; while the climate effect of CP-type delta SST (enhancing the northern ITCZ and weakening the southern ITCZ) is amplified. The climate effect of mixed-type El Niño finally resembles that of typical CP-type El Niños, intensifying the north-south asymmetry of the eastern Pacific double ITCZs. This study will contribute to a better understanding of the impacts of ENSO diversity on double ITCZs in the eastern Pacific region

MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Multimodal Large Language Model (MLLM) relies on the powerful LLM to perform multimodal tasks, showing amazing emergent abilities in recent studies, such as writing poems based on an image. However, it is difficult for these case studies to fully reflect the performance of MLLM, lacking a comprehensive evaluation. In this paper, we fill in this blank, presenting the first MLLM Evaluation benchmark MME. It measures both perception and cognition abilities on a total of 14 subtasks. In order to avoid data leakage that may arise from direct use of public datasets for evaluation, the annotations of instruction-answer pairs are all manually designed. The concise instruction design allows us to fairly compare MLLMs, instead of struggling in prompt engineering. Besides, with such an instruction, we can also easily carry out quantitative statistics. A total of 10 advanced MLLMs are comprehensively evaluated on our MME, which not only suggests that existing MLLMs still have a large room for improvement, but also reveals the potential directions for the subsequent model optimization.Comment: https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Model

A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise

The surge of interest towards Multi-modal Large Language Models (MLLMs), e.g., GPT-4V(ision) from OpenAI, has marked a significant trend in both academia and industry. They endow Large Language Models (LLMs) with powerful capabilities in visual understanding, enabling them to tackle diverse multi-modal tasks. Very recently, Google released Gemini, its newest and most capable MLLM built from the ground up for multi-modality. In light of the superior reasoning capabilities, can Gemini challenge GPT-4V's leading position in multi-modal learning? In this paper, we present a preliminary exploration of Gemini Pro's visual understanding proficiency, which comprehensively covers four domains: fundamental perception, advanced cognition, challenging vision tasks, and various expert capacities. We compare Gemini Pro with the state-of-the-art GPT-4V to evaluate its upper limits, along with the latest open-sourced MLLM, Sphinx, which reveals the gap between manual efforts and black-box systems. The qualitative samples indicate that, while GPT-4V and Gemini showcase different answering styles and preferences, they can exhibit comparable visual reasoning capabilities, and Sphinx still trails behind them concerning domain generalizability. Specifically, GPT-4V tends to elaborate detailed explanations and intermediate steps, and Gemini prefers to output a direct and concise answer. The quantitative evaluation on the popular MME benchmark also demonstrates the potential of Gemini to be a strong challenger to GPT-4V. Our early investigation of Gemini also observes some common issues of MLLMs, indicating that there still remains a considerable distance towards artificial general intelligence. Our project for tracking the progress of MLLM is released at https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models.Comment: Total 120 pages. See our project at https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Model