DRG-LLaMA : Tuning LLaMA Model to Predict Diagnosis-related Group for Hospitalized Patients

In the U.S. inpatient payment system, the Diagnosis-Related Group (DRG) is pivotal, but its assignment process is inefficient. The study introduces DRG-LLaMA, an advanced large language model (LLM) fine-tuned on clinical notes to enhance DRGs assignment. Utilizing LLaMA as the foundational model and optimizing it through Low-Rank Adaptation (LoRA) on 236,192 MIMIC-IV discharge summaries, our DRG-LLaMA-7B model exhibited a noteworthy macro-averaged F1 score of 0.327, a top-1 prediction accuracy of 52.0%, and a macro-averaged Area Under the Curve (AUC) of 0.986, with a maximum input token length of 512. This model surpassed the performance of prior leading models in DRG prediction, showing a relative improvement of 40.3% and 35.7% in macro-averaged F1 score compared to ClinicalBERT and CAML, respectively. Applied to base DRG and complication or comorbidity (CC)/major complication or comorbidity (MCC) prediction, DRG-LLaMA achieved a top-1 prediction accuracy of 67.8% and 67.5%, respectively. Additionally, our findings indicate that DRG-LLaMA's performance correlates with increased model parameters and input context lengths

Microbial functionality as affected by experimental warming of a temperate mountain forest soil—A metaproteomics survey

Soil microbes play an important role in terrestrial carbon (C) cycling, but their functional response to global warming remains yet unclear. Soil metaproteomics has the potential to contribute to a better understanding of warming effects on soil microbes as proteins specifically represent active microbes and their physiological functioning. To quantify warming effects on microbial proteins and their distribution among different functional and phylogenetic groups, we sampled forest soil that had been artificially warmed (+4 °C) during seven consecutive growing seasons and analyzed its metaproteomic fingerprint and linked to soil respiration as a fundamental ecosystem service. Bacterial protein abundances largely exceeded fungal abundances at the study site but protein abundances showed only subtle differences among control and warmed soil at the phylum and class level, i.e. a temperature-induced decrease in Firmicutes, an increase in Agaricomycetes and Actinobacteria, and a decrease in the Asco/Basidiomycota ratio. Community function in warmed soil showed a clear trend towards increased proteins involved in microbial energy production and conversion, related to the increased CO2 efflux from warmed soil as a result of stress environmental conditions. The differences in community function could be related to specific phyla using metaproteomics, indicating that microbial adaptation to long-term soil warming mainly changed microbial functions, which is related to enhanced soil respiration. The response of soil respiration to warming (+35% soil CO2 efflux during sampling) has not changed over time. Accordingly, potential long-term microbial adaptations to soil warming were too subtle to affect soil respiration rates or, were overlaid by other co-varying factors (e.g. substrate availability)

DRG-LLaMA : tuning LLaMA model to predict diagnosis-related group for hospitalized patients

Abstract In the U.S. inpatient payment system, the Diagnosis-Related Group (DRG) is pivotal, but its assignment process is inefficient. The study introduces DRG-LLaMA, an advanced large language model (LLM) fine-tuned on clinical notes to enhance DRGs assignment. Utilizing LLaMA as the foundational model and optimizing it through Low-Rank Adaptation (LoRA) on 236,192 MIMIC-IV discharge summaries, our DRG-LLaMA -7B model exhibited a noteworthy macro-averaged F1 score of 0.327, a top-1 prediction accuracy of 52.0%, and a macro-averaged Area Under the Curve (AUC) of 0.986, with a maximum input token length of 512. This model surpassed the performance of prior leading models in DRG prediction, showing a relative improvement of 40.3% and 35.7% in macro-averaged F1 score compared to ClinicalBERT and CAML, respectively. Applied to base DRG and complication or comorbidity (CC)/major complication or comorbidity (MCC) prediction, DRG-LLaMA achieved a top-1 prediction accuracy of 67.8% and 67.5%, respectively. Additionally, our findings indicate that DRG-LLaMA ’s performance correlates with increased model parameters and input context lengths

Microbial communities and residues in robinia- and poplarbased alley-cropping systems under organic and integrated management

Organic farming and agroforestry are considered as sustainable alternative agricultural practices for intensive agriculture. In a long-term field trial in Scheyern Germany, we evaluated the effects of 21-year organic farming and 4-year agroforestry (robinia and poplar) on microbial community and microbial residues. Microbial biomass and microbial community were determined by fumigation–extraction method and the analysis of phospholipid fatty acid (PLFA), respectively. Microbial residues were evaluated by the measurement of amino sugars. The results showed that organic farming had significantly positive effect on soil organic carbon (SOC) but that it tended to decrease microbial biomass C (MBC), PLFA functional guilds, muramic acid (MurN), and glucosamine (GlcN). Robinia system, however, significantly increased SOC and had the potential to enhance MBC, PLFA functional guilds especially Gram (?), but it tended to decrease MurN and GlcN, in comparison with poplar system. The hedgerow tree did not show significantly positive effect on SOC and microbial properties except the abundance of fungi and Gram (?) bacterial, after 4-year establishment period. The principal component analysis of the PLFA profile showed that in comparison with other investigated treatments, robinia system under organic farming had significantly a different microbial community structure. It also indicated tree species-specific effect on microbial community in the organic farming was stronger than that in the integrated farming. In summary, the short-term introduction of trees into an existing agricultural system will not substantially change the microbial biomass, but it has certain influence on the abundance of specific microbial groups in the hedgerow. Although organic farming did not show positive effect on overall microbial indices, we still see positive effect on SOC after 21-year organic farming and its additive effect with robinia on SOC in current study. We expect that alley-cropping agroforestry system that combines organic farming and robinia hedgerow has a great potential for sequestering SOC and developing sustainable agroecosystems with time

Soil microbial community and microbial residues respond positively to minimum tillage under organic farming in Southern Germany

In a field trial comprising organic farming and minimum tillage management strategies in Scheyern, Germany, we evaluated the long-term (21-year) effects of organic farming (use of a diverse crop rotation with legume cover crop and without application of synthetic fertilizer or pesticides) and minimum tillage (6–8 cm depth) on the microbial community structure and microbial residues in Cambisols. Organic farming had a positive effect on microbial biomass, total phospho-lipid fatty acids (PLFA), Gram (+) bacteria, Gram (-) bacteria and the arbuscular mycorrhizal fungi (AMF) indicator PLFA 16:1v5 and amino sugars. The increase in presence of Gram (+) bacteria when compared to integrated farming was also reflected by increased content of bacterial muramic acid (MurN), i.e. an increased formation of bacterial residues. Minimum tillage significantly increased microbial biomass N and the fungal PLFA 18:2v6,9, averaging the values of upper (0–8 cm) and deeper (12–25 cm) soil, but had no effects on PLFA 16:1v5. Minimum tillage generally resulted in a negative depth gradient of almost all microbial properties analyzed. The only important exception was fungal galactosamine (GlcN), which led to increases in the fungal C/bacterial C ratio and in the contribution of microbial residue C to SOC in the deeper soil. Significant second order tillage management interactions indicated that minimum tillage effects on microbial biomass and PLFA indices (Gram (+) and (i15:0 + i17:0)/(a15:0 + a17:0)) were much stronger in the organic farming system than in the integrated farming system. Redundancy analysis (RDA) showed SOC and H2O content predominantly affected the microbial community structure in the present study. Minimum tillage in combination with organic farming appears to be an effective agricultural strategy that enhances soil microbial biomass, microbial residues and bacterial and fungal abundances. The results indicate that the positive effects of minimum tillage on microbial community can be enhanced by organic farming. Microbial residues as a fraction of SOC respond faster to farming management than to tillage

Soil physicochemical and microbial characteristics of contrasting land-use types along soil depth gradients

Soil physicochemical properties can be regarded as an important tool to assess soil health, which further form a base for biological activity in soil. These soil physicochemical properties are comparable in identical land-uses and so reflect similar soil microbial properties. However, the changes in land-use types and their effects on soil physicochemical and microbial properties are largely debated and rather unclear. The aim of this study is to assess the impact of land-use types and soil depth on physicochemical properties (Organic C, total N, C/N ratio, available phosphorus, bulk density, pH and electrical conductivity), nitrogen forms (Nitrate-N, ammonium-N, organic N, mineralizable N, microbial biomass N and extractable organic N) as well as microbial indices (basal respiration, respiratory quotient, microbial quotient, microbial biomass). Land use types- farmland, orchard, grassland and abandoned land served as horizontal factors while soils at 0-10 cm, 10-30 cm and 30-60 cm depth were used as vertical factors for accessing the physicochemical and microbial properties. Discriminant analyses (DA) indicated that soil microbial properties were affected by both land-use types and soil depths than nitrogen and physicochemical properties in our study. We found that the overall trend of percentage of discriminant function 1 (DF1) was highest for microbial indices (similar to 90%) > nitrogen (similar to 80%) > physicochemical properties (similar to 70%). All investigated soil properties differed with higher significance by land-use types than by soil depths. The results further indicated that among all investigated soil properties in different land-use types, electrical conductivity, mineralizable nitrogen and microbial biomass carbon served as best discriminating indices. Regarding soil depths, total organic carbon followed by mineralizable nitrogen and basal respirations were found to be the decisive indicators of soil conditions. Overall, our results demonstrate the sensitivity of various soil properties and their differential provenience along horizontal and/or vertical gradients. These outcomes suggest that differences in land-use types are reflected in soil physicochemical properties that are actual drivers of soil microbial properties in this region. Thus they are promising guideline tools for further studies related to soil quality, soil management and sustainability in long run

CARMA1 Regulation of Regulatory T Cell Development Involves Modulation of Interleukin-2 Receptor Signaling*

T cell receptor-stimulated NF-κB activation requires CARMA1 and is negatively regulated by the deubiquitinase CYLD. Recent studies suggest that CARMA1 regulates regulatory T cell (Treg) development, although the role of NF-κB in this event is incompletely understood. We show that CYLD deficiency causes constitutive NF-κB activation in thymocytes, which is associated with enhanced frequency of Treg cells. The NF-κB activation in CYLD-deficient thymocytes is independent of CARMA1, because the NF-κB activation was also detected in CYLD/CARMA1 double knock-out thymocytes. Interestingly, although loss of CYLD causes NF-κB activation in the CARMA1-deficient thymocytes, the CYLD deficiency fails to rescue the defect of CARMA1 knock-out mice in Treg development. Furthermore, inhibition of canonical NF-κB by an IκBα transgene only partially inhibits Treg development. We demonstrate that CARMA1 regulates IL-2 receptor signaling and controls the IL-2-stimulated maturation of Treg precursors to mature Tregs. These results suggest that the role of CARMA1 in Treg regulation involves both NF-κB activation and IL-2 receptor signaling