Identifying novel acute pancreatitis sub-phenotypes using total serum calcium trajectories.

BACKGROUND: Acute pancreatitis (AP) has heterogeneous clinical features, and identifying clinically relevant sub-phenotypes is useful. We aimed to identify novel sub-phenotypes in hospitalized AP patients using longitudinal total serum calcium (TSC) trajectories. METHODS: AP patients had at least two TSC measurements during the first 24 h of hospitalization in the US-based critical care database (Medical Information Mart for Intensive Care-III (MIMIC-III) and MIMIC-IV were included. Group-based trajectory modeling was used to identify calcium trajectory phenotypes, and patient characteristics and treatment outcomes were compared between the phenotypes. RESULTS: A total of 4518 admissions were included in the analysis. Four TSC trajectory groups were identified: "Very low TSC, slow resolvers" (n = 65; 1.4% of the cohort); "Moderately low TSC" (n = 559; 12.4%); "Stable normal-calcium" (n = 3875; 85.8%); and "Fluctuating high TSC" (n = 19; 0.4%). The "Very low TSC, slow resolvers" had the lowest initial, maximum, minimum, and mean TSC, and highest SOFA score, creatinine and glucose level. In contrast, the "Stable normal-calcium" had the fewest ICU admission, antibiotic use, intubation and renal replace treatment. In adjusted analysis, significantly higher in-hospital mortality was noted among "Very low TSC, slow resolvers" (odds ratio [OR], 7.2; 95% CI, 3.7 to 14.0), "moderately low TSC" (OR, 5.0; 95% CI, 3.8 to 6.7), and "Fluctuating high TSC" (OR, 5.6; 95% CI, 1.5 to 20.6) compared with the "Stable normal-calcium" group. CONCLUSIONS: We identified four novel sub-phenotypes of patients with AP, with significant variability in clinical outcomes. Not only the absolute TSC levels but also their trajectories were significantly associated with in-hospital mortality.

Golden-flower fungus (Eurotiwm Cristatum) presents fungal flower aroma as well as accelerates the aging of white tea (Shoumei).

Golden-flower fungus (Eurotiwm Cristatum, EC) is widely inoculated in dark tea to endow a typical fungal floral aroma. Recently, Golden Flower White Tea (GFWT), prepared by transplanting EC-mediated fermentation to white tea (Shoumei, SM) to reform the roughness and coarseness, has attracted much attention attributed to coordinated flavor. However, the bio-chemistry reactions between EC and SM, along with origination of composited aroma are still unclear. Thus, the rejected EC, GFWT leaves and stems after EC removal were separated by layer-by-layer stripping following sensory evaluation, volatiles and microstructure analysis to uncover aroma formation mechanism. In GFWT, EC presents fungal flower aroma rather than contribution of extracellular enzymes secreted by fungus in Fu brick tea. Moreover, the short "flowering process" (7 days) endows SM with a stale, jujube, and sweet aroma, which is regarded as the typical characteristic of aged white tea. This inspires EC-mediated fermentation as a promising rapid aging process.

The Global and Regional Prevalence of Hospital-Acquired Carbapenem-Resistant Klebsiella pneumoniae Infection: A Systematic Review and Meta-analysis.

Background: Due to scarce therapeutic options, hospital-acquired infections caused by Klebsiella pneumoniae (KP), particularly carbapenem-resistant KP (CRKP), pose enormous threat to patients' health worldwide. This study aimed to characterize the epidemiology and risk factors of CRKP among nosocomial KP infections. Method: MEDLINE, Embase, PubMed, and Google Scholar were searched for studies reporting CRKP prevalence from inception to 30 March 2023. Data from eligible publications were extracted and subjected to meta-analysis to obtain global, regional, and country-specific estimates. To determine the cause of heterogeneity among the selected studies, prespecified subgroup analyses and meta-regression were also performed. Odds ratios of CRKP-associated risk factors were pooled by a DerSimonian and Laird random-effects method. Results: We retained 61 articles across 14 countries and territories. The global prevalence of CRKP among patients with KP infections was 28.69% (95% CI, 26.53%-30.86%). South Asia had the highest CRKP prevalence at 66.04% (95% CI, 54.22%-77.85%), while high-income North America had the lowest prevalence at 14.29% (95% CI, 6.50%-22.0%). In the country/territory level, Greece had the highest prevalence at 70.61% (95% CI, 56.77%-84.45%), followed by India at 67.62% (95% CI, 53.74%-81.79%) and Taiwan at 67.54% (95% CI, 58.65%-76.14%). Hospital-acquired CRKP infections were associated with the following factors: hematologic malignancies, corticosteroid therapies, intensive care unit stays, mechanical ventilations, central venous catheter implantations, previous hospitalization, and antibiotic-related exposures (antifungals, carbapenems, quinolones, and cephalosporins). Conclusions: Study findings highlight the importance of routine surveillance to control carbapenem resistance and suggest that patients with nosocomial KP infection have a very high prevalence of CRKP.

Gut Microbiome and Stroke: a Bidirectional Mendelian Randomisation Study in East Asian and European Populations.

BACKGROUND AND AIMS: Observational studies have implicated the involvement of gut microbiome in stroke development. Conversely, stroke may disrupt the gut microbiome balance, potentially causing systemic infections exacerbated brain infarction. However, the causal relationship remains controversial or unknown. To investigate bidirectional causality and potential ethnic differences, we conducted a bidirectional two-sample Mendelian randomisation (MR) study in both East Asian (EAS) and European (EU) populations. METHODS: Leveraging the hitherto largest genome-wide association study (GWAS) summary data from the MiBioGen Consortium (n=18 340, EU) and BGI (n=2524, EAS) for the gut microbiome, stroke GWAS data from the GIGASTROKE Consortium(264 655 EAS and 1 308 460 EU), we conducted bidirectional MR and sensitivity analyses separately for the EAS and EU population. RESULTS: We identified nominally significant associations between 85 gut microbiomes taxa in EAS and 64 gut microbiomes taxa in EU with stroke or its subtypes. Following multiple testing, we observed that genetically determined 1 SD increase in the relative abundance of species Bacteroides pectinophilus decreased the risk of cardioembolic stroke onset by 28% (OR 0.72 (95% CI 0.62 to 0.84); p=4.22e-5), and that genetically determined 1 SD increase in class Negativicutes resulted in a 0.76% risk increase in small vessel stroke in EAS. No significant causal association was identified in the EU population and the reverse MR analysis. CONCLUSION: Our study revealed subtype-specific and population-specific causal associations between gut microbiome and stroke risk among EAS and EU populations. The identified causality holds promise for developing a new stroke prevention strategy, warrants further mechanistic validation and necessitates clinical trial studies.

Early warning system enables accurate mortality risk prediction for acute gastrointestinal bleeding admitted to intensive care unit.

Acute gastrointestinal (GI) bleeding are potentially life-threatening conditions. Early risk stratification is important for triaging patients to the appropriate level of medical care and intervention. Patients admitted to intensive care unit (ICU) has a high mortality, but risk tool is scarce for these patients. This study aimed to develop and validate a risk score to improve the prognostication of death at the time of patient admission to ICU. We developed and internally validated a nomogram for mortality in patients with acute GI bleeding from the eICU Collaborative Research Database (eICU-CRD), and externally validated it in patients from the Medical Information Mart for Intensive Care III database (MIMIC-III) and Wuhan Tongji Hospital. The performance of the model was assessed by examining discrimination (C-index), calibration (calibration curves) and usefulness (decision curves). 4750 patients were included in the development cohort, with 1184 patients in the internal validation cohort, 1406 patients in the MIMIC-III validation cohort, and 342 patients in the Tongji validation cohort. The nomogram, which incorporated ten variables, showed good calibration and discrimination in the training and validation cohorts, yielded C-index ranged from 0.832 (95%CI 0.811-0.853) to 0.926 (95CI% 0.905-0.947). The nomogram-defined high-risk group had a higher mortality than the low-risk group (44.8% vs. 3.5%, P < 0.001; 41.4% vs 3.1%, P < 0.001;53.6% vs 7.5%, P < 0.001; 38.2% vs 4.2%, P < 0.001). The model performed better than the conventional Glasgow-Blatchford score, AIMS65 and the newer Oakland and Sengupta scores for mortality prediction in both the derivation and validation cohorts concerning discrimination and usefulness. Our nomogram is a reliable prognostic tool that might be useful to identify high-risk acute GI bleeding patients admitted to ICU.

The role of cellular senescence in metabolic diseases and the potential for senotherapeutic interventions.

Cellular senescence represents an irreversible state of cell cycle arrest induced by various stimuli strongly associated with aging and several chronic ailments. In recent years, studies have increasingly suggested that the accumulation of senescent cells is an important contributor to the decline of organ metabolism, ultimately resulting in metabolic diseases. Conversely, the elimination of senescent cells can alleviate or postpone the onset and progression of metabolic diseases. Thus, a close relationship between senescent cells and metabolic diseases is found, and targeting senescent cells has emerged as an alternative therapy for the treatment of metabolic diseases. In this review, we summarize the role of cellular senescence in metabolic diseases, explore relevant therapeutic strategies for metabolic diseases by removing senescent cells, and provide new insights into the treatment of metabolic diseases.

Variation analysis of photonic lantern mode control ability under mode oscillation: a new approach.

In this Letter, we present a novel, to the best of our knowledge, image-based approach to analyze the mode control ability of a photonic lantern employed in diode laser beam combining, aiming to achieve a stable beam output. The proposed method is founded on theories of power flow and mode coupling and is validated through experiments. The findings demonstrate that the analysis of the beam combining process is highly reliable when the main mode component of the output light is the fundamental mode. Moreover, it is experimentally demonstrated that the mode control performance of the photonic lantern significantly influences the beam combining loss and the fundamental mode purity. In the essence of the variation-based analysis, a key advantage of the proposed method is its applicability even in the situation of a poor combined beam stability. The experiment only requires the collection of the far-field light images of the photonic lantern to characterize the model control ability, achieving an accuracy greater than 98%.

Bond-selective intensity diffraction tomography.

Recovering molecular information remains a grand challenge in the widely used holographic and computational imaging technologies. To address this challenge, we developed a computational mid-infrared photothermal microscope, termed Bond-selective Intensity Diffraction Tomography (BS-IDT). Based on a low-cost brightfield microscope with an add-on pulsed light source, BS-IDT recovers both infrared spectra and bond-selective 3D refractive index maps from intensity-only measurements. High-fidelity infrared fingerprint spectra extraction is validated. Volumetric chemical imaging of biological cells is demonstrated at a speed of ~20 s per volume, with a lateral and axial resolution of ~350 nm and ~1.1 µm, respectively. BS-IDT's application potential is investigated by chemically quantifying lipids stored in cancer cells and volumetric chemical imaging on Caenorhabditis elegans with a large field of view (~100 µm x 100 µm).

A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common malignant tumor that seriously affects human health. Previous studies have indicated that abnormal levels of glycosylation promote progression and poor prognosis of lung cancer. Thus, the present study aimed to explore the prognostic signature related to glycosyltransferases (GTs) for LUAD. METHODS: The gene expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and GTs were obtained from the GlycomeDB database. Differentially expressed GTs-related genes (DGTs) were identified using edge package and Venn diagram. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ingenuity pathway analysis (IPA) methods were used to investigate the biological processes of DGTs. Subsequently, Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct a prognostic model for LUAD. Kaplan-Meier (K-M) analysis was adopted to explore the overall survival (OS) of LUAD patients. The accuracy and specificity of the prognostic model were evaluated by receiver operating characteristic analysis (ROC). In addition, single-sample gene set enrichment analysis (ssGSEA) algorithm was used to analyze the infiltrating immune cells in the tumor environment. RESULTS: A total of 48 DGTs were mainly enriched in the processes of glycosylation, glycoprotein biosynthetic process, glycosphingolipid biosynthesis-lacto and neolacto series, and cell-mediated immune response. Furthermore, B3GNT3, MFNG, GYLTL1B, ALG3, and GALNT13 were screened as prognostic genes to construct a risk model for LUAD, and the LUAD patients were divided into high- and low-risk groups. K-M curve suggested that patients with a high-risk score had shorter OS than those with a low-risk score. The ROC analysis demonstrated that the risk model efficiently diagnoses LUAD. Additionally, the proportion of infiltrating aDCs (p < 0.05) and Tgds (p < 0.01) was higher in the high-risk group than in the low-risk group. Spearman's correlation analysis manifested that the prognostic genes (MFNG and ALG3) were significantly correlated with infiltrating immune cells. CONCLUSION: In summary, this study established a novel GTs-related risk model for the prognosis of LUAD patients, providing new therapeutic targets for LUAD. However, the biological role of glycosylation-related genes in LUAD needs to be explored further.

Identification of characteristic aroma and bacteria related to aroma evolution during long-term storage of compressed white tea.

Compressed white tea (CWT) is a reprocessed tea of white tea. Long-term storage has greatly changed its aroma characteristics, but the material basis and transformation mechanism of its unique aroma are still unclear. In this study, flavor wheel, headspace gas chromatography ion mobility spectroscopy, chemometrics, and microbiomics were applied to study the flavor evolution and important aroma components during long-term storage of CWT, and core functional bacteria were screened. During long-term storage, the aroma of CWT gradually changed from sweet, fruity and floral to stale flavor, woody and herbal. A total of 56 volatile organic compounds (VOCs) were identified, 54 of which were significantly differences during storage. The alcohols content was the highest during 1-5 years of storage, the esters content was the highest during 7-13 years of storage, and the aldehydes content was the highest during 16 years of storage. Twenty-nine VOCs were identified as important aroma components, which were significantly correlated with 6 aroma sub-attributes (P < 0.05). The functional prediction of bacterial community reminded that bacterial community could participate in the transformation of VOCs during storage of CWT. Twenty-four core functional bacteria were screened, which were significantly associated with 29 VOCs. Finally, 23 characteristic differential VOCs were excavated, which could be used to identify CWT in different storage years. Taken together, these findings provided new insights into the changes in aroma characteristics during storage of CWT and increased the understanding of the mechanism of characteristic aroma formation during storage.

Improving the estimation of alpine grassland fractional vegetation cover using optimized algorithms and multi-dimensional features.

BACKGROUND: Fractional vegetation cover (FVC) is an important basic parameter for the quantitative monitoring of the alpine grassland ecosystem on the Qinghai-Tibetan Plateau. Based on unmanned aerial vehicle (UAV) acquisition of measured data and matching it with satellite remote sensing images at the pixel scale, the proper selection of driving data and inversion algorithms can be determined and is crucial for generating high-precision alpine grassland FVC products. METHODS: This study presents estimations of alpine grassland FVC using optimized algorithms and multi-dimensional features. The multi-dimensional feature set (using original spectral bands, 22 vegetation indices, and topographical factors) was constructed from many sources of information, then the optimal feature subset was determined based on different feature selection algorithms as the driving data for optimized machine learning algorithms. Finally, the inversion accuracy, sensitivity to sample size, and computational efficiency of the four machine learning algorithms were evaluated. RESULTS: (1) The random forest (RF) algorithm (R2: 0.861, RMSE: 9.5%) performed the best for FVC inversion among the four machine learning algorithms driven by the four typical vegetation indices. (2) Compared with the four typical vegetation indices, using multi-dimensional feature sets as driving data obviously improved the FVC inversion accuracy of the four machine learning algorithms (R2 of the RF algorithm increased to 0.890). (3) Among the three variable selection algorithms (Boruta, sequential forward selection [SFS], and permutation importance-recursive feature elimination [PI-RFE]), the constructed PI-RFE feature selection algorithm had the best dimensionality reduction effect on the multi-dimensional feature set. (4) The hyper-parameter optimization of the machine learning algorithms and feature selection of the multi-dimensional feature set further improved FVC inversion accuracy (R2: 0.917 and RMSE: 7.9% in the optimized RF algorithm). CONCLUSION: This study provides a highly precise, optimized algorithm with an optimal multi-dimensional feature set for FVC inversion, which is vital for the quantitative monitoring of the ecological environment of alpine grassland.

[Influence of Land Use Change on Ecosystem Service Value Based on GEE in the Beijing-Tianjin-Hebei Region from 1998 to 2018].

In sustainable development assessment of the Beijing-Tianjin-Hebei region, the ability to dynamically estimate the value of ecosystem services is of great significance. This study considers the Beijing-Tianjin-Hebei region as the research area, based on the google earth engine (GEE); the classification and decision tree (CART) classification algorithm was adopted to supervise and classify the Landsat Thematic Mapper/Operational Land Imager (TM/OLI) images in the study area in 1998, 2003, 2008, 2013, and 2018, and land use types in these five periods were obtained. Quantitative analysis of the dynamic changes of land use in the Beijing-Tianjin-Hebei region from 1998 to 2018 was carried out. Then, the ecosystem service value (ESV) equivalent estimation method was used to quantitatively estimate the ESV in the Beijing-Tianjin-Hebei region and combine it with a 15 km×15 km scale grid to detect its temporal and spatial dynamics. The main results were as follows. ① From 1998 to 2018, the area of construction land (increased by 16.67%) and grassland (reduced by 13.73%) in the six land use types in the Beijing-Tianjin-Hebei region was the largest, and the change in the proportion of water bodies (0.2%) was the smallest. ② The total value of ESV in the Beijing-Tianjin-Hebei region experienced a short-term increase from 1998 to 2003 (an increase of 91.97×108 yuan), and continued to decrease from 2003 to 2018 (a decrease of 239.07×108 yuan), mainly related to the expansion of construction land area in the other three time periods excluding 1998 and 2003. Among the six land use types, the forest provides the highest value of ecosystem services, and the construction land and unused land provide the lowest value of ecosystem services. ③ The ESV time-space analysis based on the 15 km×15 km scale grid showed that the ESV medium area in the Beijing-Tianjin-Hebei region gradually decreased from 1998 to 2018, the ESV lower area and the higher area gradually increased, and the ESV lower-area growth rate was higher than for the higher area. ④ The revised value of the Beijing-Tianjin-Hebei region (sensitivity coefficient range 0-0.83) has good significance and reliability. In future economic development, the Beijing-Tianjin-Hebei region should rationally optimize the land use pattern and strengthen the protection of forest land, grassland, water bodies and cultivated land.

kW-class fiber-coupled diode laser source based on dense spectral multiplexing of an ultra-narrow channel spacing.

A dense spectral multiplexing structure based on the reflective volume Bragg gratings is introduced to realize the diode laser multiplexing with an ultra-narrow channel spacing of 1.5 nm. With the combination of polarization multiplexing and coarse spectral multiplexing, a diode laser source producing 2045 W power from an output fiber with a core diameter of 105 µm and NA of 0.2 is achieved at an injection current of 10 A. The electro-optical and optical-optical efficiency of the laser source is 42% and 76%, respectively. Experimental results demonstrate the ability of dense spectral multiplexing based on VBG to realize high output power and brightness.