Evaluation of Plasma Extracellular Vesicle MicroRNA Signatures for Lung Adenocarcinoma and Granuloma With Monte-Carlo Feature Selection Method

Extracellular Vesicle (EV) is a compilation of secreted vesicles, including micro vesicles, large oncosomes, and exosomes. It can be used in non-invasive diagnosis. MicroRNAs (miRNAs) processed by exosomes can be detected by liquid biopsy. To objectively evaluate the discriminative ability of miRNAs from whole plasma, EV and EV-free plasma, we analyzed the miRNA expression profiles in whole plasma, EV and EV-free plasma of 10 lung adenocarcinoma and 9 granuloma patients. With Monte-Carlo feature selection method, the top discriminative miRNAs in whole plasma, EV and EV-free plasma were identified, and they were quite different. Using the Repeated Incremental Pruning to Produce Error Reduction (RIPPER) method, we learned the classification rules: in whole plasma, granuloma patients did not express hsa-miR-223-3p while the lung adenocarcinoma patients expressed hsa-miR-223-3p; in EV, the hsa-miR-23b-3p was highly expressed in granuloma patients but not lung adenocarcinoma patients; in EV-free plasma, hsa-miR-376a-3p was expressed in granuloma patients but barely expressed in lung adenocarcinoma patients. For prediction performance, whole plasma had the highest weighted accuracy and EV outperformed EV-free plasma. Our results suggested that EV can be used as lung cancer biomarker. However, since it is less stable and not easy to detect, there are still technological difficulties to overcome

Reducing Carbon Footprint Inequality of Household Consumption in Rural Areas:Analysis from Five Representative Provinces in China

Household consumption carbon footprint and inequality reductions are vital for a sustainable society, especially for rural areas. This study, focusing on rural China, one of the fastest growing economies with a massive population, explored the carbon footprint and inequality of household consumption using the latest micro household survey data of 2018 linked to environmental extended input–-output analysis. The results show that in 2018 in rural China, the average household carbon footprint is 2.46 tons CO2-eq per capita, which is around one-third of China’s average footprint, indicating the large potential for further growth. Housing (45.32%), transportation (20.45%), and food (19.62%) are the dominant contributors to the carbon footprint. Meanwhile, great inequality, with a Gini coefficient of 0.488, among rural households is observed, which is largely due to differences in type of house built or purchased (explaining 24.44% of the variation), heating (18.10%), car purchase (12.44%), and petrol consumption (12.44%). Provinces, average education, and nonfarm income are among the important factors influencing the inequality. In the process of urbanization and rural revitalization, there is a high possibility that the household carbon footprint continues to increase, maintaining high levels of inequality. The current energy transition toward less carbon-intensive fuels in rural China is likely to dampen the growth rates of carbon footprints and potentially decrease inequality. Carbon intensity decrease could significantly reduce carbon footprints, but increase inequality. More comprehensive measures to reduce carbon footprint and inequality are needed, including transitioning to clean energy, poverty alleviation, reduction of income inequality, and better health care coverage

Observation of strong attenuation within the photonic band gap of multiconnected networks

We theoretically and experimentally study a photonic band gap (PBG) material made of coaxial cables. The coaxial cables are waveguides for the electromagnetic waves and provide paths for direct wave interference within the material. Using multiconnected coaxial cables to form a unit cell, we realize PBGs via (i) direct interference between the waveguides within each cell and (ii) scattering among different cells. We systematically investigate the transmission of EM waves in our PBG materials and discuss the mechanism of band gap formation. We observe experimentally for the first time the wide band gap with strong attenuation caused by direct destructive interference

HuatuoGPT, towards Taming Language Model to Be a Doctor

In this paper, we present HuatuoGPT, a large language model (LLM) for medical consultation. The core recipe of HuatuoGPT is to leverage both \textit{distilled data from ChatGPT} and \textit{real-world data from doctors} in the supervised fine-tuned stage. The responses of ChatGPT are usually detailed, well-presented and informative while it cannot perform like a doctor in many aspects, e.g. for integrative diagnosis. We argue that real-world data from doctors would be complementary to distilled data in the sense the former could tame a distilled language model to perform like doctors. To better leverage the strengths of both data, we train a reward model to align the language model with the merits that both data bring, following an RLAIF (reinforced learning from AI feedback) fashion. To evaluate and benchmark the models, we propose a comprehensive evaluation scheme (including automatic and manual metrics). Experimental results demonstrate that HuatuoGPT achieves state-of-the-art results in performing medical consultation among open-source LLMs in GPT-4 evaluation, human evaluation, and medical benchmark datasets. It is worth noting that by using additional real-world data and RLAIF, the distilled language model (i.e., HuatuoGPT) outperforms its teacher model ChatGPT in most cases. Our code, data, and models are publicly available at \url{https://github.com/FreedomIntelligence/HuatuoGPT}. The online demo is available at \url{https://www.HuatuoGPT.cn/}

A Liver-Enriched Long Non-Coding RNA, lncLSTR, Regulates Systemic Lipid Metabolism in Mice

SummaryLong non-coding RNAs (lncRNAs) constitute a significant portion of mammalian genome, yet the physiological importance of lncRNAs is largely unknown. Here, we identify a liver-enriched lncRNA in mouse that we term liver-specific triglyceride regulator (lncLSTR). Mice with a liver-specific depletion of lncLSTR exhibit a marked reduction in plasma triglyceride levels. We show that lncLSTR depletion enhances apoC2 expression, leading to robust lipoprotein lipase activation and increased plasma triglyceride clearance. We further demonstrate that the regulation of apoC2 expression occurs through an FXR-mediated pathway. LncLSTR forms a molecular complex with TDP-43 to regulate expression of Cyp8b1, a key enzyme in the bile acid synthesis pathway, and engenders an in vivo bile pool that induces apoC2 expression through FXR. Finally, we demonstrate that lncLSTR depletion can reduce triglyceride levels in a hyperlipidemia mouse model. Taken together, these data support a model in which lncLSTR regulates a TDP-43/FXR/apoC2-dependent pathway to maintain systemic lipid homeostasis

One-Two-One Network for Compression Artifacts Reduction in Remote Sensing

Compression artifacts reduction (CAR) is a challenging problem in the field of remote sensing. Most recent deep learning based methods have demonstrated superior performance over the previous hand-crafted methods. In this paper, we propose an end-to-end one-two-one (OTO) network, to combine different deep models, i.e., summation and difference models, to solve the CAR problem. Particularly, the difference model motivated by the Laplacian pyramid is designed to obtain the high frequency information, while the summation model aggregates the low frequency information. We provide an in-depth investigation into our OTO architecture based on the Taylor expansion, which shows that these two kinds of information can be fused in a nonlinear scheme to gain more capacity of handling complicated image compression artifacts, especially the blocking effect in compression. Extensive experiments are conducted to demonstrate the superior performance of the OTO networks, as compared to the state-of-the-arts on remote sensing datasets and other benchmark datasets. The source code will be available here: https://github.com/bczhangbczhang/

TRIM29 acts as a potential senescence suppressor with epigenetic activation in nasopharyngeal carcinoma.

Epigenetic alterations marked by DNA methylation are frequent events during the early development of nasopharyngeal carcinoma (NPC). We identified that TRIM29 is hypomethylated and overexpressed in NPC cell lines and tissues. TRIM29 silencing not only limited the growth of NPC cells in vitro and in vivo, but also induced cellular senescence, along with reactive oxygen species (ROS) accumulation. Mechanistically, we found that TRIM29 interacted with voltage-dependent anion-selective channel 1 (VDAC1) to activate mitophagy clearing up damaged mitochondria, which are the major source of ROS. In patients with NPC, high levels of TRIM29 expression are associated with an advanced clinical stage. Moreover, we detected hypomethylation of TRIM29 in patient nasopharyngeal swab DNA. Our findings indicate that TRIM29 depends on VDAC1 to induce mitophagy and prevents cellular senescence by decreasing ROS. Detection of aberrantly methylated TRIM29 in the nasopharyngeal swab DNA could be a promising strategy for the early detection of NPC

Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimation

In this paper, we study the problem of end-to-end multi-person pose estimation. State-of-the-art solutions adopt the DETR-like framework, and mainly develop the complex decoder, e.g., regarding pose estimation as keypoint box detection and combining with human detection in ED-Pose, hierarchically predicting with pose decoder and joint (keypoint) decoder in PETR. We present a simple yet effective transformer approach, named Group Pose. We simply regard $K$-keypoint pose estimation as predicting a set of $N\times K$ keypoint positions, each from a keypoint query, as well as representing each pose with an instance query for scoring $N$ pose predictions. Motivated by the intuition that the interaction, among across-instance queries of different types, is not directly helpful, we make a simple modification to decoder self-attention. We replace single self-attention over all the $N\times(K+1)$ queries with two subsequent group self-attentions: (i) $N$ within-instance self-attention, with each over $K$ keypoint queries and one instance query, and (ii) $(K+1)$ same-type across-instance self-attention, each over $N$ queries of the same type. The resulting decoder removes the interaction among across-instance type-different queries, easing the optimization and thus improving the performance. Experimental results on MS COCO and CrowdPose show that our approach without human box supervision is superior to previous methods with complex decoders, and even is slightly better than ED-Pose that uses human box supervision. $\href{https://github.com/Michel-liu/GroupPose-Paddle}{\rm Paddle}$ and $\href{https://github.com/Michel-liu/GroupPose}{\rm PyTorch}$ code are available.Comment: Accepted by ICCV 202

Identification of a Novel UT-B Urea Transporter in Human Urothelial Cancer

The urea transporter UT-B is widely expressed and has been studied in erythrocyte, kidney, brain and intestines. Interestingly, UT-B gene has been found more abundant in bladder than any other tissue. Recently, gene analyses demonstrate that SLC14A1 (UT-B) gene mutations are associated with bladder cancer, suggesting that urea transporter UT-B may play an important role in bladder carcinogenesis. In this study, we examined UT-B expression in bladder cancer with human primary bladder cancer tissues and cancer derived cell lines. Human UT-B has two isoforms. We found that normal bladder expresses long form of UT-B2 but was lost in 8 of 24 (33%) or significantly downregulated in 16 of 24 (67%) of primary bladder cancer patients. In contrast, the short form of UT-B1 lacking exon 3 was detected in 20 bladder cancer samples. Surprisingly, a 24-nt in-frame deletion in exon 4 in UT-B1 (UT-B1Δ24) was identified in 11 of 20 (55%) bladder tumors. This deletion caused a functional defect of UT-B1. Immunohistochemistry revealed that UT-B protein levels were significantly decreased in bladder cancers. Western blot analysis showed a weak UT-B band of 40 kDa in some tumors, consistent with UT-B1 gene expression detected by RT-PCR. Interestingly, bladder cancer associate UT-B1Δ24 was barely sialylated, reflecting impaired glycosylation of UT-B1 in bladder tumors. In conclusion, SLC14A1 gene and UT-B protein expression are significantly changed in bladder cancers. The aberrant UT-B expression may promote bladder cancer development or facilitate carcinogenesis induced by other carcinogens

Terlipressin May Decrease In-Hospital Mortality of Cirrhotic Patients with Acute Gastrointestinal Bleeding and Renal Dysfunction: A Retrospective Multicenter Observational Study

Acute gastrointestinal bleeding (GIB) rapidly reduces effective blood volume, thereby precipitating acute kidney injury (AKI). Terlipressin, which can induce splanchnic vasoconstriction and increase renal perfusion, has been recommended for acute GIB and hepatorenal syndrome in liver cirrhosis. Thus, we hypothesized that terlipressin might be beneficial for cirrhotic patients with acute GIB and renal impairment. In this Chinese multi-center study, 1644 cirrhotic patients with acute GIB were retrospectively enrolled. AKI was defined according to the International Club of Ascites (ICA) criteria. Renal dysfunction was defined as serum creatinine (sCr) > 133 μmol/L at admission and/or any time point during hospitalization. Incidence of renal impairment and in-hospital mortality were the primary end-points. The incidence of any stage ICA-AKI, ICA-AKI stages 1B, 2, and 3, and renal dysfunction in cirrhotic patients with acute GIB was 7.1%, 1.8%, and 5.0%, respectively. The in-hospital mortality was significantly increased by renal dysfunction (14.5% vs. 2.2%, P < 0.001) and ICA-AKI stages 1B, 2, and 3 (11.1% vs. 2.8%, P = 0.011), but not any stage ICA-AKI (5.7% vs. 2.7%, P = 0.083). The in-hospital mortality was significantly decreased by terlipressin in patients with renal dysfunction (3.6% vs. 20.0%, P = 0.044), but not in those with any stage ICA-AKI (4.5% vs. 6.0%, P = 0.799) or ICA-AKI stages 1B, 2, and 3 (0.0% vs. 14.3%, P = 0.326). Renal dysfunction increased the in-hospital mortality of cirrhotic patients with acute GIB. Terlipressin might decrease the in-hospital mortality of cirrhotic patients with acute GIB and renal dysfunction. NCT03846180 ( https://clinicaltrials.gov )