Aquaporin-1 Deficiency Protects Against Myocardial Infarction by Reducing Both Edema and Apoptosis in Mice

Many studies have determined that AQP1 plays an important role in edema formation and resolution in various tissues via water transport across the cell membrane. The aim of this research was to determine both if and how AQP1 is associated with cardiac ischemic injury, particularly the development of edema following myocardial infarction (MI). AQP1+/+ and AQP1−/− mice were used to create the MI model. Under physiological conditions, AQP1−/− mice develop normally; however, in the setting of MI, they exhibit cardioprotective properties, as shown by reduced cardiac infarct size determined via NBT staining, improved cardiac function determined via left ventricular catheter measurements, decreased AQP1-dependent myocardial edema determined via water content assays and decreased apoptosis determined via TUNEL analysis. Cardiac ischemia caused by hypoxia secondary to AQP1 deficiency stabilized the expression of HIF-1α in endothelial cells and subsequently decreased microvascular permeability, resulting in the development of edema. The AQP1-dependent myocardial edema and apoptosis contributed to the development of MI. AQP1 deficiency protected cardiac function from ischemic injury following MI. Furthermore, AQP1 deficiency reduced microvascular permeability via the stabilization of HIF-1α levels in endothelial cells and decreased cellular apoptosis following MI

Protective effect of dehydroandrographolide on obstructive cholestasis in bile duct-ligated mice

Background: Dehydroandrographolide (DA) is the main contributor to the therapeutic properties of the medicinal plant Andrographis paniculata (AP). However, it is unknown whether DA has a hepatoprotective effect on obstructive cholestasis in mice and humans. Methods: We administered DA to mice for 5 days prior to bile duct ligation (BDL) and for the 7 days. Liver function markers, liver histology and necrosis, compensatory responses of hepatocytes, liver fibrosis and the expression of hepatic fibrogenesis markers were evaluated in BDL mice and/or human LX-2 cells. Results: Mice treated with DA demonstrated lower levels of serum alanine transarninase (ALT), milder liver damage, liver necrosis and fibrosis formation than in vehicle control with carboxymethylcellulose (CMC) mice after BDL. DA treatment also enhanced the Mrp3 expression of hepatocytes but not Mrp4 following BDL. Further, DA treatment in BDL mice significantly reduced liver mRNA and/or protein expression of Tgf-β, Col1a1, α-Sma and Mmp2. This result was also supported by hydroxyproline analysis. The molecular mechanisms of DA treatment were also assessed in human hepatic stellate cell line (LX-2 cell). DA treatment significantly inhibited Tgf-β-induced Col1a1, Mmp2 and α-Sma expression in human LX-2 cells. These data suggested that DA treatment reduced liver damage through development of a hepatic adaptive response and inhibition of the activation of HSCs, which led to a reduction in liver fibrosis formation in BDL mice. Conclusions: DA treatment protected against liver damage and fibrosis following BDL and might be an effective therapy for extrahepatic cholestasis due to bile duct obstruction

Diverse and Expressive Speech Prosody Prediction with Denoising Diffusion Probabilistic Model

Expressive human speech generally abounds with rich and flexible speech prosody variations. The speech prosody predictors in existing expressive speech synthesis methods mostly produce deterministic predictions, which are learned by directly minimizing the norm of prosody prediction error. Its unimodal nature leads to a mismatch with ground truth distribution and harms the model's ability in making diverse predictions. Thus, we propose a novel prosody predictor based on the denoising diffusion probabilistic model to take advantage of its high-quality generative modeling and training stability. Experiment results confirm that the proposed prosody predictor outperforms the deterministic baseline on both the expressiveness and diversity of prediction results with even fewer network parameters.Comment: Proceedings of Interspeech 2023 (doi: 10.21437/Interspeech.2023-715), demo site at https://thuhcsi.github.io/interspeech2023-DiffVar

OS-Copilot: Towards Generalist Computer Agents with Self-Improvement

Autonomous interaction with the computer has been a longstanding challenge with great potential, and the recent proliferation of large language models (LLMs) has markedly accelerated progress in building digital agents. However, most of these agents are designed to interact with a narrow domain, such as a specific software or website. This narrow focus constrains their applicability for general computer tasks. To this end, we introduce OS-Copilot, a framework to build generalist agents capable of interfacing with comprehensive elements in an operating system (OS), including the web, code terminals, files, multimedia, and various third-party applications. We use OS-Copilot to create FRIDAY, a self-improving embodied agent for automating general computer tasks. On GAIA, a general AI assistants benchmark, FRIDAY outperforms previous methods by 35%, showcasing strong generalization to unseen applications via accumulated skills from previous tasks. We also present numerical and quantitative evidence that FRIDAY learns to control and self-improve on Excel and Powerpoint with minimal supervision. Our OS-Copilot framework and empirical findings provide infrastructure and insights for future research toward more capable and general-purpose computer agents.Comment: Project page: https://os-copilot.github.i

SnakeGAN: A Universal Vocoder Leveraging DDSP Prior Knowledge and Periodic Inductive Bias

Generative adversarial network (GAN)-based neural vocoders have been widely used in audio synthesis tasks due to their high generation quality, efficient inference, and small computation footprint. However, it is still challenging to train a universal vocoder which can generalize well to out-of-domain (OOD) scenarios, such as unseen speaking styles, non-speech vocalization, singing, and musical pieces. In this work, we propose SnakeGAN, a GAN-based universal vocoder, which can synthesize high-fidelity audio in various OOD scenarios. SnakeGAN takes a coarse-grained signal generated by a differentiable digital signal processing (DDSP) model as prior knowledge, aiming at recovering high-fidelity waveform from a Mel-spectrogram. We introduce periodic nonlinearities through the Snake activation function and anti-aliased representation into the generator, which further brings the desired inductive bias for audio synthesis and significantly improves the extrapolation capacity for universal vocoding in unseen scenarios. To validate the effectiveness of our proposed method, we train SnakeGAN with only speech data and evaluate its performance for various OOD distributions with both subjective and objective metrics. Experimental results show that SnakeGAN significantly outperforms the compared approaches and can generate high-fidelity audio samples including unseen speakers with unseen styles, singing voices, instrumental pieces, and nonverbal vocalization.Comment: Accepted by ICME 202

Anti-Inflammatory Activity of Dehydroandrographolide by TLR4/NF-κB Signaling Pathway Inhibition in Bile Duct-Ligated Mice

Background/Aims: Clinically, biliary obstruction is often accompanied by progressive inflammation. Dehydroandrographolide (DA) possesses anti-inflammatory properties. However, the anti-inflammatory activities of DA in cholestatic liver injury remain unclear. Methods: Mice were administered with DA by intraperitoneal injection after bile duct ligation (BDL) on day 1. Then mice were subjected to an ileocecal vein injection of lipopolysaccharide (LPS). Liver function markers, histology, pro-inflammatory cytokine levels, NF-κB activation and fibrosis formation were evaluated in BDL mice with LPS. LPS binding to primary Kupffer cells was examined by high-content cytometers. Results: DA was shown to greatly lower initially higher than normal levels of alanine aminotransferase (ALT) and total bilirubin (TBIL) in the serum and liver of BDL mice with LPS. DA exerted hepatic protective effects that were also confirmed by prolonged survival of BDL mice with LPS. Liver histopathology showed reduced inflammatory cellular infiltration, bile duct proliferation, and biliary necrosis with DA treatment. Furthermore, DA reduced the expression levels of tumor necrosis factor (TNF)-α and interleukin (IL)-6 in liver tissue and plasma and showed decreased NF-κB activation in BDL mice with LPS. DA could prevent LPS binding to primary Kupffer cells in the normal liver and BDL mice liver. DA also suppressed LPS-stimulated inflammatory responses by blocking the interaction between LPS and TLR4 in primary Kupffer cells and human LX-2 cells, thereby inhibiting NF-κB activation. Conclusion: DA inhibition of inflammation against liver damage following BDL with LPS may be a promising agent for the treatment of cholestatic liver injury

Closing the gap between open source and commercial large language models for medical evidence summarization.

Large language models (LLMs) hold great promise in summarizing medical evidence. Most recent studies focus on the application of proprietary LLMs. Using proprietary LLMs introduces multiple risk factors, including a lack of transparency and vendor dependency. While open-source LLMs allow better transparency and customization, their performance falls short compared to the proprietary ones. In this study, we investigated to what extent fine-tuning open-source LLMs can further improve their performance. Utilizing a benchmark dataset, MedReview, consisting of 8161 pairs of systematic reviews and summaries, we fine-tuned three broadly-used, open-sourced LLMs, namely PRIMERA, LongT5, and Llama-2. Overall, the performance of open-source models was all improved after fine-tuning. The performance of fine-tuned LongT5 is close to GPT-3.5 with zero-shot settings. Furthermore, smaller fine-tuned models sometimes even demonstrated superior performance compared to larger zero-shot models. The above trends of improvement were manifested in both a human evaluation and a larger-scale GPT4-simulated evaluation

Bionic Optimization Design of Electronic Nose Chamber for Oil and Gas Detection

In this paper, a miniaturized bionic electronic nose system is developed in order to solve the problems arising in oil and gas detection for large size and inflexible operation in downhole. The bionic electronic nose chamber is designed by mimicking human nasal turbinate structure, V-groove structure on shark skin surface and flow field distribution around skin surface. The sensitivity of the bionic electronic nose system is investigated through experimentation. Radial Basis Function (RBF) and Support Vector Machines (SVM) of 10-fold cross validation are used to compare the recognition performance of the bionic electronic nose system and common one. The results show that the sensitivity of the bionic electronic nose system with bionic composite chamber (chamber B) is significantly improved compared with that with common chamber (chamber A). The recognition rate of chamber B is 4.27% higher than that of chamber A for the RBF algorithm, while for the SVM algorithm, the recognition rate of chamber B is 5.69% higher than that of chamber A. The three-dimensional simulation model of the chamber is built and verified by Computational Fluid Dynamics (CFD) simulation analysis The number of vortices in chamber B is fewer than that in chamber A. The airflow velocity near the sensors inside chamber B is slower than that inside chamber A. The vortex intensity near the sensors in chamber B is 2. 27 times as much as that in chamber A, which facilitates gas molecules to fully contact with the sensor surface and increases the intensity of sensor signal, and the contact strength and time between odorant molecules and sensor surface. Based on the theoretical investigation and test validation, it is believed that the proposed bionic electronic nose system with bionic composite chamber has potential for oil and gas detection in downhole

A Comprehensive Method for Assessing Meat Freshness Using Fusing Electronic Nose, Computer Vision, and Artificial Tactile Technologies

The traditional methods cannot be used to meet the requirements of rapid and objective detection of meat freshness. Electronic nose (E-Nose), computer vision (CV), and artificial tactile (AT) sensory technologies can be used to mimic humans’ compressive sensory functions of smell, look, and touch when making judgement of meat quality (freshness). Though individual E-Nose, CV, and AT sensory technologies have been used to detect the meat freshness, the detection results vary and are not reliable. In this paper, a new method has been proposed through the integration of E-Nose, CV, and AT sensory technologies for capturing comprehensive meat freshness parameters and the data fusion method for analysing the complicated data with different dimensions and units of six odour parameters of E-Nose, 9 colour parameters of CV, and 4 rubbery parameters of AT for effective meat freshness detection. The pork and chicken meats have been selected for a validation test. The total volatile base nitrogen (TVB-N) assays are used to define meat freshness as the standard criteria for validating the effectiveness of the proposed method. The principal component analysis (PCA) and support vector machine (SVM) are used as unsupervised and supervised pattern recognition methods to analyse the source data and the fusion data of the three instruments, respectively. The experimental and data analysis results show that compared to a single technology, the fusion of E-Nose, CV, and AT technologies significantly improves the detection performance of various freshness meat products. In addition, partial least squares (PLS) is used to construct TVB-N value prediction models, in which the fusion data is input. The root mean square error predictions (RMSEP) for the sample pork and chicken meats are 1.21 and 0.98, respectively, in which the coefficient of determination () is 0.91 and 0.94. This means that the proposed method can be used to effectively detect meat freshness and the storage time (days)

Clinical efficacy and tendon integrity of patients with subscapularis tear by the technique of arthroscopic single external row repair

BackgroundWith the development of arthroscopic technology and equipment, arthroscopy can effectively repair the tear of the subscapular muscle. However, it is difficult to expose the subscapular muscle and operate it under a microscope. In this study, the SwiveLock® C external row anchor under arthroscopy was applied to repair the tear of the subscapular muscle in a single row, which is relatively easy to operate with reliable suture and fixation, and its efficacy was evaluated.PurposeThis study aimed to assess the clinical efficacy and the tendon integrity of patients who had subscapularis tears by adopting the single-row repair technique with a SwiveLock® C external row anchor.MethodsPatients who had the subscapular muscle tear either with or without retraction were included, and their follow-up time was at least 1 year. The degree of tendon injury was examined by magnetic resonance imaging (MRI) and confirmed by arthroscopy. The tendon was repaired in an arthroscopic manner by utilizing the single-row technique at the medial margin of the lesser tuberosity. One double-loaded suture SwiveLock® C anchor was applied to achieve a strong fixation between the footprint and tendon. The range of motion, pain visual simulation score, American Shoulder and Elbow Surgeons (ASES) score, and Constant score of shoulder joint were evaluated for each patient before the operation, 3 months after the operation, and at least 1 year after the operation.ResultsIn total, 110 patients, including 31 males and 79 females, with an average age of 68.28 ± 8.73 years were included. Arthroscopic repair of the subscapular tendon with SwiveLock® C external anchor can effectively improve the range of motion of the shoulder joint. At the last follow-up, the forward flexion of the shoulder joint increased from 88.97 ± 26.33° to 138.38 ± 26.48° (P < 0.05), the abduction range increased from 88.86 ± 25.27° to 137.78 ± 25.64° (P < 0.05), the external rotation range increased from 46.37 ± 14.48° to 66.49 ± 14.15° (P < 0.05), and the internal rotation range increased from 40.03 ± 9.01° to 57.55 ± 7.43° (P < 0.05). The clinical effect is obvious. The constant shoulder joint score increased from 40.14 ± 15.07 to 81.75 ± 11.00 (P < 0.05), the ASES score increased from 37.88 ± 13.24 to 82.01 ± 9.65 (P < 0.05), and the visual analog scale score decreased from 5.05 ± 2.11 to 1.01 ± 0.85 (P < 0.05). In the 6th month after the operation, two cases (1.81%) were confirmed to have re-tears via MRI.ConclusionIn this study, we repaired the subscapularis muscle with a single-row technique fixed by SwiveLock® C anchor and FiberWire® sutures and evaluated its efficacy. The results showed that the clinical effect of single-row arthroscopic repair was satisfactory and that reliable tendon healing could be achieved