Development and evaluation of a prototype non-woven fabric filter for purification of malaria-infected blood

BACKGROUND: Many malaria-related studies depend on infected red blood cells (iRBCs) as fundamental material; however, infected blood samples from human or animal models include leukocytes (white blood cells or WBCs), especially difficult to separate from iRBCs in cases involving Plasmodium vivax. These host WBCs are a source of contamination in biology, immunology and molecular biology studies, requiring their removal. Non-woven fabric (NWF) has the ability to adsorb leukocytes and is already used as filtration material to deplete WBCs for blood transfusion and surgery. The present study describes the development and evaluation of a prototype NWF filter designed for purifying iRBCs from malaria-infected blood. METHODS: Blood samples of P. vivax patients were processed separately by NWF filter and CF11 column methods. WBCs and RBCs were counted, parasite density, morphology and developing stage was checked by microscopy, and compared before and after treatment. The viability of filtrated P. vivax parasites was examined by in vitro short-term cultivation. RESULTS: A total of 15 P. vivax-infected blood samples were treated by both NWF filter and CF11 methods. The WBC removal rate of the NWF filter method was 99.03%, significantly higher than the CF11 methods (98.41%, P < 0.01). The RBC recovery rate of the NWF filter method was 95.48%, also significantly higher than the CF11 method (87.05%, P < 0.01). Fourteen in vitro short-term culture results showed that after filter treatment, P. vivax parasite could develop as normal as CF11 method, and no obvious density, developing stage difference were fund between two methods. CONCLUSIONS: NWF filter filtration removed most leukocytes from malaria-infected blood, and the recovery rate of RBCs was higher than with CF11 column method. Filtrated P. vivax parasites were morphologically normal, viable, and suitable for short-term in vitro culture. NWF filter filtration is simple, fast and robust, and is ideal for purification of malaria-infected blood

Studies on some active components and antimicrobial activities of the fermentation broth of endophytic fungi DZY16 Isolated from Eucommia ulmoides Oliv.

Research into plant-derived endophytic fungi has grown in recent decades. Endophytic fungi still have enormous potential to inspire and influence modern agriculture. In this study, the endophytic fungi DZY16 isolated from Eucommia ulmoides Oliv. was tested for its bioactive components and antimicrobial activities using phenol-sulfuric acid method, high performance liquid chromatography method and growth inhibition measurements. The results show that variation trend of extracellular polysaccharide content at different growth stages of the strain DZY16 and the maximum content of extracellular polysaccharide was 2.02 g/L at the sixth day. Moreover, the fermentation broth of the DZY16 contained guanosine, uridine and adenosine; the contents were 1.54 mg/g, 1.07 mg/g and 1.36 mg/g respectively. On the other hand, the strongest antimicrobial activity was exhibited by the acetylacetate extract of strain DZY16 against Rhizoctonia solani and Gibberella zeae, showing 59.84 and 70.86% respectively. The strain DZY16 was identified by internal transcribed spacer (ITS) sequence as belonging to Nigrospora. The results indicate that the endophytic fungi DZY16 of the plant E. ulmoides Oliv. is a promising source of novel bioactive compounds.Keywords: Eucommia ulmoides Oliv., endophytic fungi, extracellular polysaccharide, nucleotides, antimicrobial activityAfrican Journal of Biotechnology Vol. 12(15), pp. 1862-186

Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning

Self-supervised learning is an efficient pre-training method for medical image analysis. However, current research is mostly confined to specific-modality data pre-training, consuming considerable time and resources without achieving universality across different modalities. A straightforward solution is combining all modality data for joint self-supervised pre-training, which poses practical challenges. Firstly, our experiments reveal conflicts in representation learning as the number of modalities increases. Secondly, multi-modal data collected in advance cannot cover all real-world scenarios. In this paper, we reconsider versatile self-supervised learning from the perspective of continual learning and propose MedCoSS, a continuous self-supervised learning approach for multi-modal medical data. Unlike joint self-supervised learning, MedCoSS assigns different modality data to different training stages, forming a multi-stage pre-training process. To balance modal conflicts and prevent catastrophic forgetting, we propose a rehearsal-based continual learning method. We introduce the k-means sampling strategy to retain data from previous modalities and rehearse it when learning new modalities. Instead of executing the pretext task on buffer data, a feature distillation strategy and an intra-modal mixup strategy are applied to these data for knowledge retention. We conduct continuous self-supervised pre-training on a large-scale multi-modal unlabeled dataset, including clinical reports, X-rays, CT scans, MRI scans, and pathological images. Experimental results demonstrate MedCoSS's exceptional generalization ability across nine downstream datasets and its significant scalability in integrating new modality data. Code and pre-trained weight are available at https://github.com/yeerwen/MedCoSS

Ferrocen­yl(meth­yl)diphenyl­silane

In the title mol­ecule, [Fe(C5H5)(C18H17Si)], the distances of the Fe atom from the centroids of the unsubstituted and substituted cyclo­penta­dienyl (Cp) rings are 1.651 (1) and 1.646 (1) Å, respectively. The dihedral angle between the two Cp rings is 3.20 (17)°. The crystal packing is mainly stabilized by van der Waals forces

Attention Mechanisms in Medical Image Segmentation: A Survey

Medical image segmentation plays an important role in computer-aided diagnosis. Attention mechanisms that distinguish important parts from irrelevant parts have been widely used in medical image segmentation tasks. This paper systematically reviews the basic principles of attention mechanisms and their applications in medical image segmentation. First, we review the basic concepts of attention mechanism and formulation. Second, we surveyed over 300 articles related to medical image segmentation, and divided them into two groups based on their attention mechanisms, non-Transformer attention and Transformer attention. In each group, we deeply analyze the attention mechanisms from three aspects based on the current literature work, i.e., the principle of the mechanism (what to use), implementation methods (how to use), and application tasks (where to use). We also thoroughly analyzed the advantages and limitations of their applications to different tasks. Finally, we summarize the current state of research and shortcomings in the field, and discuss the potential challenges in the future, including task specificity, robustness, standard evaluation, etc. We hope that this review can showcase the overall research context of traditional and Transformer attention methods, provide a clear reference for subsequent research, and inspire more advanced attention research, not only in medical image segmentation, but also in other image analysis scenarios.Comment: Submitted to Medical Image Analysis, survey paper, 34 pages, over 300 reference

Topological triply-degenerate point with double Fermi arcs

Unconventional chiral particles have recently been predicted to appear in certain three dimensional (3D) crystal structures containing three- or more-fold linear band degeneracy points (BDPs). These BDPs carry topological charges, but are distinct from the standard twofold Weyl points or fourfold Dirac points, and cannot be described in terms of an emergent relativistic field theory. Here, we report on the experimental observation of a topological threefold BDP in a 3D phononic crystal. Using direct acoustic field mapping, we demonstrate the existence of the threefold BDP in the bulk bandstructure, as well as doubled Fermi arcs of surface states consistent with a topological charge of 2. Another novel BDP, similar to a Dirac point but carrying nonzero topological charge, is connected to the threefold BDP via the doubled Fermi arcs. These findings pave the way to using these unconventional particles for exploring new emergent physical phenomena

Diferrocen­yl(meth­yl)phenyl­silane

In the title mol­ecule, [Fe2(C5H5)2(C17H16Si)], the cyclo­penta­dienyl rings linked to the same Fe atom are approximately eclipsed and the inter­planar angles are 1.8 (2) and 3.4 (2)°. The Fe atom is slightly closer to the substituted cyclo­penta­dienyl ring