Hemogenic Endothelial Cells Can Transition to Hematopoietic Stem Cells through a B-1 Lymphocyte-Biased State during Maturation in the Mouse Embryo

Precursors of hematopoietic stem cells (pre-HSCs) have been identified as intermediate precursors during the maturation process from hemogenic endothelial cells to HSCs in the aorta-gonad-mesonephros (AGM) region of the mouse embryo at embryonic day 10.5. Although pre-HSCs acquire an efficient adult-repopulating ability after ex vivo co-culture, their native hematopoietic capacity remains unknown. Here, we employed direct transplantation assays of CD45-VE-cadherin(VC)+KIT+(V+K+) cells (containing pre-HSCs) into immunodeficient neonatal mice that permit engraftment of embryonic hematopoietic precursors. We found that freshly isolated V+K+ cells exhibited significantly greater B-1 lymphocyte-biased repopulating capacity than multilineage repopulating capacity. Additionally, B cell colony-forming assays demonstrated the predominant B-1 progenitor colony-forming ability of these cells; however, increased B-2 progenitor colony-forming ability emerged after co-culture with Akt-expressing AGM endothelial cells, conditions that support pre-HSC maturation into HSCs. Our studies revealed an unexpected B-1 lymphocyte bias of the V+K+ population and acquisition of B-2 potential during commitment to the HSC fate

Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection

Real-world social events typically exhibit a severe class-imbalance distribution, which makes the trained detection model encounter a serious generalization challenge. Most studies solve this problem from the frequency perspective and emphasize the representation or classifier learning for tail classes. While in our observation, compared to the rarity of classes, the calibrated uncertainty estimated from well-trained evidential deep learning networks better reflects model performance. To this end, we propose a novel uncertainty-guided class imbalance learning framework - UCL$_{SED}$, and its variant - UCL-EC$_{SED}$, for imbalanced social event detection tasks. We aim to improve the overall model performance by enhancing model generalization to those uncertain classes. Considering performance degradation usually comes from misclassifying samples as their confusing neighboring classes, we focus on boundary learning in latent space and classifier learning with high-quality uncertainty estimation. First, we design a novel uncertainty-guided contrastive learning loss, namely UCL and its variant - UCL-EC, to manipulate distinguishable representation distribution for imbalanced data. During training, they force all classes, especially uncertain ones, to adaptively adjust a clear separable boundary in the feature space. Second, to obtain more robust and accurate class uncertainty, we combine the results of multi-view evidential classifiers via the Dempster-Shafer theory under the supervision of an additional calibration method. We conduct experiments on three severely imbalanced social event datasets including Events2012\_100, Events2018\_100, and CrisisLexT\_7. Our model significantly improves social event representation and classification tasks in almost all classes, especially those uncertain ones.Comment: Accepted by TKDE 202

A preliminary evaluation of targeted nanopore sequencing technology for the detection of Mycobacterium tuberculosis in bronchoalveolar lavage fluid specimens

ObjectiveTo evaluate the efficacy of targeted nanopore sequencing technology for the detection of Mycobacterium tuberculosis(M.tb.) in bronchoalveolar lavage fluid(BALF) specimens.MethodsA prospective study was used to select 58 patients with suspected pulmonary tuberculosis(PTB) at Henan Chest Hospital from January to October 2022 for bronchoscopy, and BALF specimens were subjected to acid-fast bacilli(AFB) smear, Mycobacterium tuberculosis MGIT960 liquid culture, Gene Xpert MTB/RIF (Xpert MTB/RIF) and targeted nanopore sequencing (TNS) for the detection of M.tb., comparing the differences in the positive rates of the four methods for the detection of patients with different classifications.ResultsAmong 58 patients with suspected pulmonary tuberculosis, there were 48 patients with a final diagnosis of pulmonary tuberculosis. Using the clinical composite diagnosis as the reference gold standard, the sensitivity of AFB smear were 27.1% (95% CI: 15.3-41.8); for M.tb culture were 39.6% (95% CI: 25.8-54.7); for Xpert MTB/RIF were 56.2% (95% CI: 41.2-70.5); for TNS were 89.6% (95% CI: 77.3-96.5). Using BALF specimens Xpert MTB/RIF and/or M.tb. culture as the reference standard, TNS showed 100% (30/30) sensitivity. The sensitivity of NGS for pulmonary tuberculosis diagnosis was significantly higher than Xpert MTB/RIF, M.tb. culture, and AFB smear. Besides, P values of <0.05 were considered statistically significant.ConclusionUsing a clinical composite reference standard as a reference gold standard, TNS has the highest sensitivity and consistency with clinical diagnosis, and can rapidly and efficiently detect PTB in BALF specimens, which can aid to improve the early diagnosis of suspected tuberculosis patients

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

Oriented Sample Solid-State NMR of the Mercury Detoxification Membrane Protein MerFt

Mer proteins are 6 proteins MerA, MerE, MerF, MerT, MerC and MerP performing bacterial mercury detoxification system. One of transmembrane protein MerFt with two a helix was mutated two sets of vicinal cysteines: C21, C22, C71, and C72 with Serine pairs. The truncated structure MerFt, as a nonmetal binding protein and ideal transmembrane model protein to study solution NMR and solid-state NMR sample condition, was successfully expressed as a fusion protein with Ketosteroid Isomerase as an expression tag. CNBr (cyanogen bromide) chemical cleavage was performed to cleave KSI tag in different conditions. The protein was successfully purified with HPLC (High-Performance Liquid Chromatography) and FPLC (Fast protein liquid chromatography) size exclusion. The structural studies of this membrane protein were developed on solution NMR (Nuclear Magnetic Resonance) and solid-state NMR