Accuracy of 2D and point shear wave elastography-based measurements for diagnosis of esophageal varices: a systematic review and meta-analysis

PURPOSEThe aim of this meta-analysis is to summarize the diagnostic accuracies of point shear wave elas- tography (pSWE) and two-dimensional (2D) SWE for esophageal varices (EV) and varices needing treatment (VNT).METHODSWe conducted a systematic review and meta-analysis of diagnostic accuracy studies. We searched for studies reporting the EV and VNT diagnostic accuracy of pSWE and 2D SWE using PubMed Cen- tral, SCOPUS, MEDLINE, Embase, and Cochrane databases. STATA software“Midas”package was used for meta-analysis.RESULTSA total of 24 studies with 3867 patients were included in the review. Pooled score sensitivities of pSWE were 91% (95% CI, 80%-96%) for EV, and 94% (95% CI, 86%-97%) for VNT. Pooled score sensi- tivities of 2D SWE were 78% (95% CI, 69%-85%) for EV, and 79% (95% CI, 72%-85%) for VNT. Pooled score specificities of pSWE were 70% (95% CI, 60%-78%) for EV, and 59% (95% CI, 40%-75%) for VNT. Pooled score specificities of 2D SWE for EV were 79% (95% CI, 72%-85%) 72% (95% CI, 66%-77%) for VNT. We found significant heterogeneity for all the elastography-based measurements with the chi- square test results and an I2 statistic >75%.CONCLUSIONBoth pSWE and 2D SWE can diagnose EV and VNT with moderate diagnostic accuracy. Further large- scale setting-specific longitudinal studies are required to establish the best modality

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Prognostic Value of Systemic Inflammation Score for Esophageal Cancer Patients Undergoing Surgery: A Systematic Review and Meta-Analysis

Objective The link between inflammation and cancer survival has been the subject of substantial research. The goal of this review is to summarize the evidence on the prognostic value of systemic inflammation score (SIS) in esophageal cancer patients undergoing surgical intervention. Methods PubMed, Scopus, Embase, and Web of Science were searched for relevant articles published until 30th June 2022. We pooled adjusted data on overall survival (OS) and disease-free survival (DFS) using a random-effects meta-analysis model. The review was pre-registered on PROSPER (No. CRD42022340717). Results Eight studies were included. All studies were conducted either in China or Japan. Six studies showed that patients with SIS of 1-2 had poor OS as compared to those with scores of 0 (HR:1.42 95% CI: 1.24, 1.62 I2=25%). SIS of 1 (HR:1.45 95% CI: 1.18, 1.78 I2=0%) and 2 (HR:1.94 95% CI: 1.49, 2.53 I2=0%) were also associated with poor OS. Two studies compared the SIS score of 2 vs 0-1. Meta-analysis indicated that poor OS was associated with SIS of 2 (HR:1.80 95% CI: 1.25, 2.58). Data from three studies showed that the SIS score did not predict DFS (HR:1.40 95% CI: 0.82, 2.39 I2=91%). Conclusion SIS can be a novel prognostic indicator for esophageal cancer patients undergoing surgical intervention. Higher SIS is associated with a poor OS, but it does not predict DFS. Future studies are needed to strengthen the current evidence

Prognostic Value of Systemic Inflammation Score for Esophageal Cancer Patients Undergoing Surgery: A Systematic Review and Meta-Analysis

The link between inflammation and cancer survival has been the subject of substantial research. The goal of this review is to summarize the evidence on the prognostic value of systemic inflammation score (SIS) in esophageal cancer patients undergoing surgical intervention. PubMed, Scopus, Embase, and Web of Science were searched for relevant articles published until 30th June 2022. We pooled adjusted data on overall survival (OS) and disease-free survival (DFS) using a random-effects meta-analysis model. The review was pre-registered on PROSPER (No. CRD42022340717). Eight studies were included. All studies were conducted either in China or Japan. Six studies showed that patients with SIS of 1-2 had poor OS as compared to those with scores of 0 (HR:1.42 95% CI: 1.24, 1.62 I2=25%). SIS of 1 (HR:1.45 95% CI: 1.18, 1.78 I2=0%) and 2 (HR:1.94 95% CI: 1.49, 2.53 I2=0%) were also associated with poor OS. Two studies compared the SIS score of 2 vs 0-1. Meta-analysis indicated that poor OS was associated with SIS of 2 (HR:1.80 95% CI: 1.25, 2.58). Data from three studies showed that the SIS score did not predict DFS (HR:1.40 95% CI: 0.82, 2.39 I2=91%). SIS can be a novel prognostic indicator for esophageal cancer patients undergoing surgical intervention. Higher SIS is associated with a poor OS, but it does not predict DFS. Future studies are needed to strengthen the current evidence.</p

Taxonomic Study of Three Novel <i>Paenibacillus</i> Species with Cold-Adapted Plant Growth-Promoting Capacities Isolated from Root of <i>Larix gmelinii</i>

Exploration of the novel species of the genus Paenibacillus with plant-growth promoting characteristics at the low-temperature environment is of great significance for the development of psychrotolerant biofertilizer in forestry and agriculture. During the course of isolation of root endophytes of Larix gmelinii in the island frozen soil, three strains designated as T3-5-0-4, N1-5-1-14 and N5-1-1-5 were isolated. The three strains showed plant growth-promoting properties at the low temperature, such as phosphate solubilization, indole-3-acetic acid biosynthesis and siderophore production. According to pairwise sequence analyses of the 16S rRNA genes, the three strains represent putatively novel taxa within the genus Paenibacillus. The strains have typical chemotaxonomic characteristics of the genus Paenibacillus by having meso-diaminopimelic acid as diagnostic diamino acid, anteiso-C15:0 as the predominant fatty acid and MK-7 as the predominant menaquinone. The polar lipid profiles of all strains contained diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylethanolamine. The sizes of the genomes of the stains ranged from 5.66 to 9.07 Mb and the associated G+C contents ranged from 37.9% to 44.7%. Polyphasic taxonomic study including determination of genome relatedness indices revealed that the strains are representatives of three novel species in the genus Paenibacillus. Consequently, isolates T3-5-0-4, N1-5-1-14 and N5-1-1-5 are proposed as novel species for which the names of Paenibacillus endoradicis sp. nov. (CFCC15691T = KCTC43441T), Paenibacillus radicibacter sp. nov, (CFCC15694T = KCTC43442T) and Paenibacillus radicis sp. nov. (CFCC15710T = KCTC43173T), respectively. Moreover, analysis for biosynthetic genes showed that the strains have potential for plant growth-promoting characteristics, plant rhizospheres colonization and low-temperature adaption, most of which are consistent with the results of the bioactivity test

Comprehensive experimental study of microbial respiration during self-heating in biomass storage piles

As a critical renewable energy source, biomass has substantial potential for reducing carbon emissions and promoting sustainable development. However, its long-term storage in large volumes for modern bioenergy poses challenges due to inherent self-heating driven by exothermic microbial, physical and chemical processes, which can lead to spontaneous ignition and severe fire incidents. While physical and chemical aspects of self-heating in biomass piles greatly benefit from extensive research and experience borrowed from coal pile self-heating, microbial activities in biomass self-heating have received less attention. To address this knowledge gap, we conduct a series of comprehensive studies to gain a deeper understanding of microbial activities in biomass self-heating, aiming to develop a numerical model for reliably predicting biomass self-heating and minimizing fire risks in stored biomass. This paper presents the results of our experimental investigation into microbial respiration during biomass storage. Six commonly used biomass feedstocks with varying initial moisture content are subjected to different storage conditions over a seven-day testing period, during which the main metabolic byproduct (CO2) released from microbial degradation of the biomass is continuously measured. Our findings reveal that an increase in feedstock moisture content significantly enhances microbial activity when the initial moisture content is below 136 %. However, further increases in initial moisture content do not notably enhance, and in some cases, may even weaken microbial activity. Additionally, a temperature range of 25 °C to 45 °C is identified as conducive to rapid microbial decomposition for different biomass materials, and deviation from this range results in a significant reduction in microbial activity. Furthermore, under identical temperature and initial moisture content conditions, the order of carbon dioxide evolution rate is as follows: corn stalk &gt; soybean hull &gt; rice straw &gt; wheat straw &gt; cotton stalk &gt; pepper stalk. Our respiration intensity test results also create a fundamental experimental database for model development and validation, and contribute to the broader understanding of biomass storage and its associated challenges.</p