Nutritional supplements improve cardiovascular risk factors in overweight and obese patients: A Bayesian network meta-analysis

BackgroundOverweight and obesity are considered as one of the major risk factors for cardiovascular diseases (CVD). At present, many studies have proved that multiple nutritional supplements play an active role in metabolic diseases. However, the comparative efficacy of different nutritional supplements in improving indicators of cardiometabolic risk in obese and overweight patients is uncertain.MethodsCochrane Library, PubMed, Embase, and Web of Science were searched for the period from January 1990 to March 2022. A random-effect model was built in the Bayesian network meta-analysis. The surface under the cumulative ranking analysis (SUCRA) and clustering rank analysis was performed for ranking the effects.ResultsThe study included 65 RCTs with 4,241 patients. In terms of glucose control, probiotic was more conductive to improve FBG (MD: −0.90; 95%CrI: −1.41 to −0.38), FINS (MD: −2.05; 95%CrI: −4.27 to −0.02), HOMA-IR (MD: −2.59; 95%CI −3.42 to −1.76). Probiotic (MD: −11.15, 95%CrI −22.16 to −1.26), omega-3 (MD: −9.45; 95%CrI: −20.69 to −0.93), VD (MD: −17.86; 95%CrI: −35.53 to −0.27), and probiotic +omega-3 (MD: 5.24; 95%CrI: 0.78 to 9.63) were beneficial to the improvement of TGs, TC and HDL-C, respectively. The SUCRA revealed that probiotic might be the best intervention to reduce FBG, FINS, HOMA-IR; Simultaneously, α-lipoic acid, VD, and probiotic + omega-3 might be the best intervention to improve TGs, TC, and HDL-C, respectively. Cluster-rank results revealed probiotic had the best comprehensive improvement effect on glucose metabolism, and probiotic + omega-3 may have a better comprehensive improvement effect on lipid metabolism (cluster-rank value for FBG and FINS: 3290.50 and for TGs and HDL-C: 2117.61).ConclusionNutritional supplementation is effective on CVD risk factors in overweight and obese patients. Probiotic supplementation might be the best intervention for blood glucose control; VD, probiotic + omega-3 have a better impact on improving lipid metabolism. Further studies are required to verify the current findings

Large Language Models Are Semi-Parametric Reinforcement Learning Agents

Inspired by the insights in cognitive science with respect to human memory and reasoning mechanism, a novel evolvable LLM-based (Large Language Model) agent framework is proposed as REMEMBERER. By equipping the LLM with a long-term experience memory, REMEMBERER is capable of exploiting the experiences from the past episodes even for different task goals, which excels an LLM-based agent with fixed exemplars or equipped with a transient working memory. We further introduce Reinforcement Learning with Experience Memory (RLEM) to update the memory. Thus, the whole system can learn from the experiences of both success and failure, and evolve its capability without fine-tuning the parameters of the LLM. In this way, the proposed REMEMBERER constitutes a semi-parametric RL agent. Extensive experiments are conducted on two RL task sets to evaluate the proposed framework. The average results with different initialization and training sets exceed the prior SOTA by 4% and 2% for the success rate on two task sets and demonstrate the superiority and robustness of REMEMBERER

Refined Equivalent Pinhole Model for Large-scale 3D Reconstruction from Spaceborne CCD Imagery

In this study, we present a large-scale earth surface reconstruction pipeline for linear-array charge-coupled device (CCD) satellite imagery. While mainstream satellite image-based reconstruction approaches perform exceptionally well, the rational functional model (RFM) is subject to several limitations. For example, the RFM has no rigorous physical interpretation and differs significantly from the pinhole imaging model; hence, it cannot be directly applied to learning-based 3D reconstruction networks and to more novel reconstruction pipelines in computer vision. Hence, in this study, we introduce a method in which the RFM is equivalent to the pinhole camera model (PCM), meaning that the internal and external parameters of the pinhole camera are used instead of the rational polynomial coefficient parameters. We then derive an error formula for this equivalent pinhole model for the first time, demonstrating the influence of the image size on the accuracy of the reconstruction. In addition, we propose a polynomial image refinement model that minimizes equivalent errors via the least squares method. The experiments were conducted using four image datasets: WHU-TLC, DFC2019, ISPRS-ZY3, and GF7. The results demonstrated that the reconstruction accuracy was proportional to the image size. Our polynomial image refinement model significantly enhanced the accuracy and completeness of the reconstruction, and achieved more significant improvements for larger-scale images.Comment: 24 page

Understanding the effects of revegetated shrubs on fluxes of energy, water, and gross primary productivity in a desert steppe ecosystem using the STEMMUS-SCOPE model

Revegetation is one of the most effective ways to combat desertification and soil erosion in semiarid and arid regions. However, the impact of the perturbation of revegetation on ecohydrological processes, particularly its effects on the interplay between hydrological processes and vegetation growth under water stress, requires further investigation. This study evaluated the effects of revegetation on the energy, water, and carbon fluxes in a desert steppe in Yanchi County, Ningxia Province, northwest China, by simulating two vegetated scenarios (shrub-grassland ecosystem and grassland ecosystem) using the STEMMUS-SCOPE (Simultaneous Transfer of Energy, Mass and Momentum in Unsaturated Soil-Soil Canopy Observation of Photosynthesis and Energy fluxes) model. The model was validated by field observations from May to September of 2016-2019. The evaluation of revegetation effects relied on comparing simulated fluxes between two vegetated scenarios in 2016 and 2019. In both scenarios, turbulent energy was dominated by latent heat flux, which was stronger in the shrub-grassland ecosystem (+7%). A higher leaf area index and root water uptake of C3 shrubs (Caragana intermedia) resulted in increased carbon fixation (+83%) and transpiration (+72%) of the shrub-grassland ecosystem compared to the C3 grassland ecosystem. Accompanied by a marked increase in root water uptake (+123%), revegetation intensified water consumption beyond the levels of received precipitation. These results highlight the critical importance of considering both energy and water budgets in water-limited ecosystems during ecological restoration to avert soil water depletion.</p

Spatiotemporal sampling strategy for characterization of hydraulic properties in heterogeneous soils

Accurate characterization and prediction of soil moisture distribution and solute transport in vadose zone require detailed knowledge of the spatial distribution of soil hydraulic properties. Since the direct measurements of these unknown properties are challenging, many studies invert the soil hydraulic parameters by incorporating observation data (e.g., soil moisture and pressure head) at selected point sampling locations into soil moisture flow models. However, a cost-effective sampling strategy for where and when to collect the data, which is vital for saving the costs for monitoring and data interpretation, is relatively rare compared to the direct parameter retrieving efforts. Here, an optimal spatial–temporal sampling strategy was proposed based on cross-correlation analysis between observed state variables and soil hydraulic parameters. Besides, the effects of meteorological condition, observation type, bottom boundary condition, and correlation scale of soil hydraulic parameters are also demonstrated. The proposed sampling strategy was assessed by both synthetic numerical experiments and a real-world case study. Results suggest the retrieval accuracy of heterogeneous soil is acceptable if the spatial/temporal sampling interval is set to be one spatial/temporal correlation length of soil moisture. Besides, surface observation contains the most plentiful information which could be used to derive root-zone soil moisture/parameters, but this ability depends on the correlation scale of soil hydraulic parameters. Besides, the temporal value of soil moisture depends on meteorological condition. It is not necessary to sample repeatedly during dry periods, but more attention should be paid to the observations after rainfall events

Case report: Subcutaneous Mycobacterium haemophilum infection in an immunocompetent patient after lipolysis injections

Mycobacterium haemophilum is a slow-growing, aerobic mycobacterium that acts as a pathogen in immunocompromised adult patients and immunocompetent children. There are only a few rare cases in the literature describing this species as a cause of subcutaneous infections. Here, we describe a subcutaneous infection caused by M. haemophilum in an immunocompetent female after lipolysis injections at an unqualified beauty salon, suggesting that this bacteria can also be a potential causative agent of adverse events in medical aesthetics. In addition, M. haemophilum caused lesions not only at the injection sites and adjacent areas but also invaded distant sections through the subcutaneous sinus tracts. Thus, early diagnosis and appropriate treatment are vital to prevent further deterioration and improve prognosis