CMB: A Comprehensive Medical Benchmark in Chinese

Large Language Models (LLMs) provide a possibility to make a great breakthrough in medicine. The establishment of a standardized medical benchmark becomes a fundamental cornerstone to measure progression. However, medical environments in different regions have their local characteristics, e.g., the ubiquity and significance of traditional Chinese medicine within China. Therefore, merely translating English-based medical evaluation may result in \textit{contextual incongruities} to a local region. To solve the issue, we propose a localized medical benchmark called CMB, a Comprehensive Medical Benchmark in Chinese, designed and rooted entirely within the native Chinese linguistic and cultural framework. While traditional Chinese medicine is integral to this evaluation, it does not constitute its entirety. Using this benchmark, we have evaluated several prominent large-scale LLMs, including ChatGPT, GPT-4, dedicated Chinese LLMs, and LLMs specialized in the medical domain. It is worth noting that our benchmark is not devised as a leaderboard competition but as an instrument for self-assessment of model advancements. We hope this benchmark could facilitate the widespread adoption and enhancement of medical LLMs within China. Check details in \url{https://cmedbenchmark.llmzoo.com/}

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/}

Kushenin Combined with Adefovir Dipivoxil or Entecavir for Chronic Hepatitis B: A Systematic Review and Meta-Analysis

Kushenin (KS) has become a traditional Chinese medicine preparation that plays an important role in treating chronic hepatitis B (CHB). Many clinical studies have discussed its curative effect and safety in combination with adefovir dipivoxil (ADV) or entecavir (ETV) for treating CHB, but there is still a lack of a systematic analysis. Therefore, this study evaluated the efficacy and safety of KS through a meta-analysis to better guide clinical treatment. Seven databases were searched to identify randomized controlled trials (RCTs) concerning KS combined with ADV or ETV for treating CHB. The primary outcomes included serum viral indices and adverse events, and the secondary outcomes were liver function indices. The risk of bias of the included RCTs was appraised by Cochrane software. STATA 15.1 and Review Manager 5.3 software were used for the meta-analysis. Thirty-two RCTs recruiting 3343 patients with CHB were collected for this meta-analysis. KS combined with ETV or ADV led to an amelioration of the CHB index to various degrees. In short, the meta-analysis indicated that the combination group, compared to the single group, showed great improvement in HBeAg seroconversion, frequency of undetectable HBV-DNA levels, loss of serum HBeAg, and loss of serum HBsAg. The combination treatment also decreased serum HBV-DNA levels when compared to the levels after the single treatment. However, KS combined with ADV or ETV displayed no remarkable difference in the incidence of adverse events or in serum ALT levels. Current evidence showed that, compared with the use of either drug alone, KS combined with ADV or ETV can improve the clinical efficacy of CHB treatment

Seismic analysis of Kunshan Xintiandi super high-rise residential building

The Kunshan urban investment project includes 1 office tower, 4 high-rise residential buildings and 1 high-rise commercial building.Each monomer shares a large basement chassis, a total of three basement floors.This design is the second phase (4# residence and corresponding basement).The height of the structure is more than 90 meters, and it is a shear wall structure system. The selection and structure of the structure system are analyzed, and the mechanical performance of the structure is verified through calculation and analysis

Novel Synthesis of Slightly Fluorinated Graphene Quantum Dots with Luminescent and Paramagnetic Properties through Thermal Cutting of Fluorinated Graphene

A novel approach has been developed to synthesize slightly fluorinated graphene quantum dots (GQDs-F) through thermal cutting of highly fluorinated graphene. The fluorinated graphene with substantial structure defects is fragile and is readily attacked. The direct evaporation of abundant CFn (n = 2, 3) groups near structure defects lead to the loss of adjacent skelton C atoms, and the fluorinated graphene can be thermally cut into GQDs-F with a relatively uniform nanosize in pyrolysis at 810 K. The GQDs-F with a low F/C atomic ratio of ca. 0.03 exhibit excitation wavelength-dependent properties with multicolor photoluminescence (PL) from blue to green. At the same time, F adatoms that are most likely located at the edges of GQDs-F have a high efficiency of introducing paramagnetic centres, and GQDs-F show a strong paramagnetism because of sp3-type defects and magnetic zigzag edges. The graphene quantum dots with such multimodal capabilities should have great applied value in material science

Hypoglycemic mechanism of polysaccharide from Cyclocarya paliurus leaves in type 2 diabetic rats by gut microbiota and host metabolism alteration

Diabetes mellitus is a serious threat to human health.Cyclocarya paliurus(Batal.) Iljinskaja (C.paliurus) is one of the traditional herbal medicine and food in China for treating type 2 diabetes, and theC. paliuruspolysaccharides (CP) were found to be one of its major functional constituents. This research aimed at investigating the hypoglycemic mechanism for CP. It was found that CP markedly attenuated the symptoms of diabetes, and inhibited the protein expression ofBax, improved the expression ofBcl-2in pancreas of diabetic rats, normalized hormones secretion and controlled the inflammation which contributed to the regeneration of pancreatic beta-cell and insulin resistance. CP treatment increased the beneficial bacteria genusRuminococcaceaeUCG-005 which was reported to be a key genus for protecting against diabetes, and the fecal short-chain fatty acids levels were elevated. Uric metabolites analysis showed that CP treatment helped to protect with the diabetes by seven significantly improved pathways closely with the nutrition metabolism (amino acids and purine) and energy metabolism (TCA cycle), which could help to build up the intestinal epithelial cell defense for the inflammation associated with the diabetes. Our study highlights the specific mechanism of prebiotics to attenuate diabetes through multi-path of gut microbiota and host metabolism

An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China.

As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever