MetaGPT: Meta Programming for Multi-Agent Collaborative Framework

Recently, remarkable progress has been made in automated task-solving through the use of multi-agents driven by large language models (LLMs). However, existing works primarily focuses on simple tasks lacking exploration and investigation in complicated tasks mainly due to the hallucination problem. This kind of hallucination gets amplified infinitely as multiple intelligent agents interact with each other, resulting in failures when tackling complicated problems.Therefore, we introduce MetaGPT, an innovative framework that infuses effective human workflows as a meta programming approach into LLM-driven multi-agent collaboration. In particular, MetaGPT first encodes Standardized Operating Procedures (SOPs) into prompts, fostering structured coordination. And then, it further mandates modular outputs, bestowing agents with domain expertise paralleling human professionals to validate outputs and reduce compounded errors. In this way, MetaGPT leverages the assembly line work model to assign diverse roles to various agents, thus establishing a framework that can effectively and cohesively deconstruct complex multi-agent collaborative problems. Our experiments conducted on collaborative software engineering tasks illustrate MetaGPT's capability in producing comprehensive solutions with higher coherence relative to existing conversational and chat-based multi-agent systems. This underscores the potential of incorporating human domain knowledge into multi-agents, thus opening up novel avenues for grappling with intricate real-world challenges. The GitHub repository of this project is made publicly available on: https://github.com/geekan/MetaGP

Changes in microstates of first-episode untreated nonsuicidal self-injury adolescents exposed to negative emotional stimuli and after receiving rTMS intervention

BackgroundNonsuicidal self-injury (NSSI) is a common mental health threat in adolescents, peaking in adolescence with a lifetime prevalence of ~17%–60%, making it a high-risk risk factor for suicide. In this study, we compared changes in microstate parameters in depressed adolescents with NSSI, depressed adolescents, and healthy adolescents during exposure to negative emotional stimuli, and further explored the improvement of clinical symptoms and the effect of microstate parameters of repetitive transcranial magnetic stimulation (rTMS) in depressed adolescents with NSSI, and more evidence was provided for potential mechanisms and treatment optimization for the occurrence of NSSI behaviors in adolescents.MethodsSixty-six patients with major depressive disorder (MDD) exhibiting NSSI behavior (MDD + NSSI group), 52 patients with MDD (MDD group), and 20 healthy subjects (HC group) were recruited to perform neutral and negative emotional stimulation task. The age range of all subjects was 12–17 years. All participants completed the Hamilton Depression Scale, the Patient Health Questionnaire-9, the Ottawa Self-Injury Scale and a self-administered questionnaire to collect demographic information. We provided two different treatments to 66 MDD adolescents with NSSI; 31 patients received medication and completed post-treatment scale assessments and EEG acquisitions, and 21 patients received medication combined with rTMS and completed post-treatment scale assessments and EEG acquisitions. Multichannel EEG was recorded continuously from 64 scalp electrodes using the Curry 8 system. EEG signal preprocessing and analysis was performed offline, using the EEGLAB toolbox in MATLAB. Use the Microstate Analysis Toolbox in EEGLAB for segmentation and computation of microstates, and calculate a topographic map of the microstate segmentation of the EEG signal for a single subject in each dataset, and four parameters were obtained for each microstate classification: global explained variance (GEV), mean duration (Duration), average number of occurrences per second (Occurrence), and average percentage of total analysis time occupied (Coverage), which were then statistically analyzed.ResultsOur results indicate that MDD adolescents with NSSI exhibit abnormalities in MS 3, MS 4, and MS 6 parameters when exposed to negative emotional stimuli compared to MDD adolescents and healthy adolescents. The results also showed that medication combined with rTMS treatment improved depressive symptoms and NSSI performance more significantly in MDD adolescents with NSSI compared to medication treatment, and affected MS 1, MS 2, and MS 4 parameters in MDD adolescents with NSSI, providing microstate evidence for the moderating effect of rTMS.ConclusionMDD adolescents with NSSI showed abnormal changes in several microstate parameters when receiving negative emotional stimuli, and compared to those not receiving rTMS treatment, MDD adolescents with NSSI treated with rTMS showed more significant improvements in depressive symptoms and NSSI performance, as well as improvements in EEG microstate abnormalities

A dual AAV system enables the Cas9-mediated correction of a metabolic liver disease in newborn mice

Many genetic liver diseases present in newborns with repeated, often lethal, metabolic crises. Gene therapy using non-integrating viruses such as AAV is not optimal in this setting because the non-integrating genome is lost as developing hepatocytes proliferate1,2. We reasoned that newborn liver may be an ideal setting for AAV-mediated gene correction using CRISPR/Cas9. Here we intravenously infuse two AAVs, one expressing Cas9 and the other expressing a guide RNA and the donor DNA, into newborn mice with a partial deficiency in the urea cycle disorder enzyme, ornithine transcarbamylase (OTC). This resulted in reversion of the mutation in 10% (6.7% – 20.1%) of hepatocytes and increased survival in mice challenged with a high-protein diet, which exacerbates disease. Gene correction in adult OTC-deficient mice was lower and accompanied by larger deletions that ablated residual expression from the endogenous OTC gene, leading to diminished protein tolerance and lethal hyperammonemia on a chow diet

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Rolling Bearing Weak Fault Feature Extraction under Variable Speed Conditions via Joint Sparsity and Low-Rankness in the Cyclic Order-Frequency Domain

Rolling bearings are critical to the normal operation of mechanical systems, which often undergo time-varying working conditions. When the local defects appear on a rolling bearing, the transient impulses will generate and be covered by the strong background noise. Therefore, extracting the rolling bearing weak fault feature with time-varying speed is critical to mechanical system diagnosis. A weak fault feature extraction strategy of rolling bearing under time-varying working conditions is proposed. Firstly, the order-frequency spectral correlation (OFSC) is computed for transferring the measured signal into a higher dimensional space. Then, the joint sparsity and low-rankness constraint is imposed on OFSC to detect the time-varying faulty characteristics. An algorithm in the alternating direction method of multipliers (ADMM) framework is derived. Finally, the enhanced envelope order spectrum (EEOS) is applied to further detect the defective features, which can make the fault features more obvious. The feasibility of the proposed method is confirmed by simulations and an experimental case

Uncertainty Quantification for Infrasound Propagation in the Atmospheric Environment

The propagation of infrasound in the atmosphere is influenced by atmospheric environmental parameters, which affect the precise localization of the infrasound source. Therefore, it has become crucial to quantify the influence of atmospheric environmental parameters on infrasound propagation. First, in this paper, the tau-p model is chosen as the physical model of infrasound propagation in a non-uniform moving medium. The atmospheric environmental parameters affecting infrasound propagation are determined. Secondly, the atmospheric environmental parameter distribution data are generated using the Sobol sampling method. Third, the generated atmospheric data are incorporated into the physical model of infrasound propagation to solve the output. Finally, Sobol sensitivity analysis is performed for each parameter, and the atmospheric parameter with the largest Sobol index is identified as the one with the most significant influence on infrasound propagation

Uncertainty Quantification for Infrasound Propagation in the Atmospheric Environment

The propagation of infrasound in the atmosphere is influenced by atmospheric environmental parameters, which affect the precise localization of the infrasound source. Therefore, it has become crucial to quantify the influence of atmospheric environmental parameters on infrasound propagation. First, in this paper, the tau-p model is chosen as the physical model of infrasound propagation in a non-uniform moving medium. The atmospheric environmental parameters affecting infrasound propagation are determined. Secondly, the atmospheric environmental parameter distribution data are generated using the Sobol sampling method. Third, the generated atmospheric data are incorporated into the physical model of infrasound propagation to solve the output. Finally, Sobol sensitivity analysis is performed for each parameter, and the atmospheric parameter with the largest Sobol index is identified as the one with the most significant influence on infrasound propagation

Dietary supplementation with pyrroloquinoline quinone promotes growth, relieves weaning stress, and regulates metabolism of piglets compared with adding zinc oxide

Hindered growth often occurs because of psychological and environmental stress during the weaning period of piglets. This study aimed to compare the effects of growth performance, diarrhea indices, digestibility of nutrients, antioxidant capacity, neurotransmitters levels and metabolism of weaned pigs fed diets supplemented with pyrroloquinoline quinone (PQQ) and zinc oxide (ZnO). Pigs weaned at d 28 (n = 108) were fed with three different diets including: the basal diet (CTRL group), the basal diet supplemented with 3.0 mg/kg PQQ (PQQ group) and the basal diet containing 1,600 mg/kg ZnO (ZNO group). During the first 14 d, weaned pigs fed the diet supplemented with PQQ and ZnO decreased feed to gain ratio and diarrhea rate (P < 0.01). Compared with the CTRL group, average daily gain was increased in weaned pigs in the PQQ group from d 15 to 28 (P = 0.03). Compared with the CTRL group, pigs fed PQQ and ZnO supplemented diets showed improved apparent total tract digestibility (ATTD) of nutrients (P ≤ 0.05). During the overall experimental period, the concentration of malondialdehyde was decreased in plasma of pigs in the PQQ and ZNO groups compared with the CTRL group (P < 0.05). At d 28, the concentration of vasoactive intestinal peptide (VIP) and calcitonin gene-related peptide (CGRP) was lower in plasma of weaned pigs in the PQQ and ZNO groups compared with the CTRL group (P < 0.05). There was no difference between the PQQ and ZNO group in growth performance, ATTD of nutrition, antioxidant capacity and neurotransmitters levels. PQQ increased 3-methoxy-4-hydroxymandelate (P < 0.05) compared with the CTRL group. According to metabolomic analysis, erucamide, formononetin and 3-methyl-L-histidine were up-regulated in the PQQ group (P < 0.05). Compared with the CTRL group, aloesin and dibutyl adipate were down-regulated in the PQQ group (P < 0.05). In conclusion, similar to ZnO, PQQ improves growth performance, digestibility of nutrients, antioxidant capacity, neuromodulation and metabolism of weaned pigs. Thus, like ZnO, PQQ can be effectively applied in weaned pigs

Targeted sequencing of the BDNF gene in young Chinese Han people with major depressive disorder

Abstract Background Adolescence and young adulthood are considered the peak age for the emergence of many psychiatric disorders, in particular major depressive disorder (MDD). Previous research has shown substantial heritability for MDD. In addition, the brain‐derived neurotrophic factor (BDNF) gene is known to be associated with MDD. However, there has been no study conducting targeted sequencing of the BDNF gene in young MDD patients so far. Method To examine whether the BDNF gene is associated with the occurrence of MDD in young patients, we used targeted sequencing to detect the BDNF gene variants in 259 young Chinese Han people (105 MDD patients and 154 healthy subjects). Results The BDNF variant rs4030470 was associated with MDD in young Chinese Han people (uncorrected p = 0.046), but this was no longer significant after applying FDR correction (p = 0.552, after FDR correction). We did not find any significant differences in genotype or haplotype frequencies between the case and control groups, and furthermore discovered no rare mutation variants any of the 259 subjects. Conclusion Our results do not support an association of the BDNF gene variants with MDD in young people in the Chinese Han population