Shaofu Zhuyu Decoction Regresses Endometriotic Lesions in a Rat Model

The current therapies for endometriosis are restricted by various side effects and treatment outcome has been less than satisfactory. Shaofu Zhuyu Decoction (SZD), a classic traditional Chinese medicinal (TCM) prescription for dysmenorrhea, has been widely used in clinical practice by TCM doctors to relieve symptoms of endometriosis. The present study aimed to investigate the effects of SZD on a rat model of endometriosis. Forty-eight female Sprague-Dawley rats with regular estrous cycles went through autotransplantation operation to establish endometriosis model. Then 38 rats with successful ectopic implants were randomized into two groups: vehicle- and SZD-treated groups. The latter were administered SZD through oral gavage for 4 weeks. By the end of the treatment period, the volume of the endometriotic lesions was measured, the histopathological properties of the ectopic endometrium were evaluated, and levels of proliferating cell nuclear antigen (PCNA), CD34, and hypoxia inducible factor- (HIF-) 1α in the ectopic endometrium were detected with immunohistochemistry. Furthermore, apoptosis was assessed using the terminal deoxynucleotidyl transferase (TdT) deoxyuridine 5′-triphosphate (dUTP) nick-end labeling (TUNEL) assay. In this study, SZD significantly reduced the size of ectopic lesions in rats with endometriosis, inhibited cell proliferation, increased cell apoptosis, and reduced microvessel density and HIF-1α expression. It suggested that SZD could be an effective therapy for the treatment and prevention of endometriosis recurrence

AceGPT, Localizing Large Language Models in Arabic

This paper explores the imperative need and methodology for developing a localized Large Language Model (LLM) tailored for Arabic, a language with unique cultural characteristics that are not adequately addressed by current mainstream models like ChatGPT. Key concerns additionally arise when considering cultural sensitivity and local values. To this end, the paper outlines a packaged solution, including further pre-training with Arabic texts, supervised fine-tuning (SFT) using native Arabic instructions and GPT-4 responses in Arabic, and reinforcement learning with AI feedback (RLAIF) using a reward model that is sensitive to local culture and values. The objective is to train culturally aware and value-aligned Arabic LLMs that can serve the diverse application-specific needs of Arabic-speaking communities. Extensive evaluations demonstrated that the resulting LLM called `AceGPT' is the SOTA open Arabic LLM in various benchmarks, including instruction-following benchmark (i.e., Arabic Vicuna-80 and Arabic AlpacaEval), knowledge benchmark (i.e., Arabic MMLU and EXAMs), as well as the newly-proposed Arabic cultural \& value alignment benchmark. Notably, AceGPT outperforms ChatGPT in the popular Vicuna-80 benchmark when evaluated with GPT-4, despite the benchmark's limited scale. % Natural Language Understanding (NLU) benchmark (i.e., ALUE) Codes, data, and models are in https://github.com/FreedomIntelligence/AceGPT.Comment: https://github.com/FreedomIntelligence/AceGP

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology

Joint DOA and DOD Estimation Based on Tensor Subspace with Partially Calibrated Bistatic MIMO Radar

A joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation algorithm based on tensor subspace approach for partially calibrated bistatic multiple-input multiple-output (MIMO) radar is proposed. By exploiting the multidimensional structure of the received data, a third-order measurement tensor is constructed. Consequently, the tensor-based signal subspace is achieved using the higher-order singular value decomposition (HOSVD). To achieve accurate DOA estimation with partially calibrated array, a closed-form solution is provided to estimate the gain-phase uncertainties of the transmit and receive arrays by modeling the imperfections of the arrays. Simulation results demonstrate the effectiveness of the proposed calibration algorithm

Integrating ANNs and Cellular Automata–Markov Chain to Simulate Urban Expansion with Annual Land Use Data

Accurately simulating and predicting the urban expansion process, especially in expeditious urbanization areas, is an important aspect of managing limited land resources and adjusting flawed land use policies. This research was conducted on the basis of a high-temporal-resolution land use dataset to precisely model urban expansion in a rapidly developing zone by integrating the Artificial Neural Network (ANN), cellular automata (CA), and Markov Chain (MC). An urban suitability index (USI) map was created using ANN and fed to CA–MC to identify possible changed-to-urban cells. Two ANNs, multiple-layer perceptron (MLP) and long short-term memory network (LSTM), were implemented as simulation models for comparison. Due to its ability to capture more temporal information, LSTM outperformed MLP in modeling urban expansion dynamics over a short temporal interval. The simulated results were validated by (fuzzy) kappa simulation and the results revealed that the combination of ANN and CA–MC can precisely model the urban development locations due to its strength in revealing the nonlinear relationship between the expansion process and its drivers. The same model was applied to southern Auckland, and the compared results show that the most simulated variance is caused by the land use policies implemented by different types of governments

An Improved Modified Universal Ultra-Wideband Antenna Designed for Step Frequency Continuous Wave Ground Penetrating Radar System

Step Frequency Continuous Wave Ground Penetrating Radar (SFCW-GPR), as a tool for nondestructive testing of shallow soil surface targets, the realization of the function of SFCW-GPR is mainly based on the theory of refraction, reflection and scattering of electromagnetic wave in the discontinuity of dielectric constant. So, the UWB antenna system, an important part of SFCW-GPR, becomes more indispensable. In this paper, an improved modified universal antenna is designed, simulated and fabricated. Based on a typical Bow-tie antenna, it is modified by the methods of lumped loads, cavity-backed loading and structure loading. The simulated and measured results show that the UWB antenna has 1.36 GHz bandwidth from 0.64 to 2.0 GHz with three resonant wavelength peaks, and having been modified and improved, the UWB antenna performances including voltage standing-wave ratio (VSWR), input impedance, the boresight gain and current distribution, are much better than the typical Bow-tie antenna. In addition, the results of verification experiment of Step Frequency Continuous Wave (SFCW) show that the antenna can be applied to the working scenarios of SFCW-GPR

Robust angle estimation for MIMO radar with the coexistence of mutual coupling and colored noise

This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method.Published versio

Assessing Potential Factors Influencing the Efficacy of Immune Checkpoint Inhibitors with Radiation in Advanced Non-Small-Cell Lung Cancer Patients: A Systematic Review and Meta-Analysis

Objective. Recent evidence suggests that combining radiotherapy (RT) with immune checkpoint inhibitors (ICIs) may result in better outcomes. In this study, we assessed the efficacy and safety of ICI plus radiation versus ICI alone and explored potential factors affecting its efficacy in advanced non-small-cell lung cancer (NSCLC) patients. Methods. The databases including PubMed and Embase were searched to retrieve eligible studies comparing the efficacy and safety outcomes in advanced NSCLC patients after ICIs ± RT treatments. We performed subgroup analyses to identify potential prognostic factors from radiation details and study types. The odds ratio (OR) of objective response rate (ORR) and disease control rate (DCR), hazard ratio (HR) of progression-free survival (PFS) and overall survival (OS), and risk ratio (RR) of adverse events were used to represent the outcome effects. Results. 26 eligible studies with 14192 cases were included. The results showed that the ORR (OR = 0.63, 95% CI: 0.42, 0.93; p = 0.02) and DCR (OR = 0.55, 95% CI: 0.36, 0.82; p < 0.01) of RT + ICIs groups were significantly higher than those of the ICIs alone group. The median PFS and OS for ICIs versus RT + ICIs were 2.2 versus 4.4 months and 9.0 versus 13.4 months, respectively. Patients in the ICIs plus RT group had a significantly better PFS (HR = 0.72, 95% CI: 0.64, 0.81; p < 0.01) and OS (HR = 0.74, 95% CI: 0.65, 0.83; p < 0.01) when compared to those in the ICIs group. In terms of adverse events, the risk of pneumonia was not significantly increased in patients treated with both ICIs and RT when compared to ICIs group alone (risk ratio = 0.89; 95% CI: 0.55, 1.44; p = 0.63). The correlation analysis found that PFS was significantly correlated with OS (p = 0.02). The subgroup analysis results showed that significant improvements in OS were observed in non-palliative RT group (HR = 0.29, 95% CI: 0.13, 0.65; p < 0.01) and extracranial RT group (HR = 0.70, 95% CI: 0.59, 0.83; p < 0.01). RT type could also be a prognostic factor associated with the OS (for conventional RT: HR = 0.68 and p = 0.22; for stereotactic body radiation therapy: HR = 0.77 and p < 0.01). However, concerning RT timing, the results showed a similar trend in reducing mortality risk (for previous RT: HR = 0.64 and p = 0.21; for concurrent RT: HR = 0.35 and p = 0.16). Conclusion. RT plus ICIs is associated with improved survival for advanced NSCLC patients, especially for those with non-palliative RT. Further clinical trials are needed to validate its effect on survival outcomes