Aberrant Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Wilson’s Disease

Both abnormalities of resting-state cerebral blood flow (CBF) and functional connectivity in Wilson’s disease (WD) have been identified by several studies. Whether the coupling of CBF and functional connectivity is imbalanced in WD remains largely unknown. To assess this possibility, 27 patients with WD and 27 sex- and age-matched healthy controls were recruited to acquire functional MRI and arterial spin labeling imaging data. Functional connectivity strength (FCS) and CBF were calculated based on standard gray mask. Compared to healthy controls, the CBF–FCS correlations of patients with WD were significantly decreased in the basal ganglia and the cerebellum and slightly increased in the prefrontal cortex and thalamus. In contrast, decreased CBF of patients with WD occurred predominately in subcortical and cognitive- and emotion-related brain regions, including the basal ganglia, thalamus, insular, and inferior prefrontal cortex, whereas increased CBF occurred primarily in the temporal cortex. The FCS decrease in WD patients was predominately in the basal ganglia and thalamus, and the increase was primarily in the prefrontal cortex. These findings suggest that aberrant neurovascular coupling in the brain may be a possible neuropathological mechanism underlying WD

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

The complete mitochondrial genome of the lichenized fungi Usnea jiangxiensis (Ascomycota: Parmeliaceae)

Usnea is a genus of lichenized Ascomycete that grows in moist mountain areas. It is a food for wild animals and can also be used as medicine. We describe the complete mitochondrial genome of the lichenized fungi Usnea jiangxiensis. It is a circular molecule of 62,531 bp in size, and all genes show the typical gene arrangement conforming to the mold consensus. The mitochondrial genome sequence of U. jiangxiensis and other eight species were used for phylogenetic analysis by the maximum likelihood method. Phylogenetic analysis demonstrated that U. jiangxiensis most closely related to U. ceratina. The complete chloroplast genomes of U. jiangxiensis would be useful for future investigation of genetics, evolution and clinical identification of Usnea species

The complete chloroplast genome sequence of medicinal plant, Artemisia lavandulaefolia YC

As part of a genome sequencing project for Artemisia lavandulaefolia YC (A. lavandulaefolia YC), a complete chloroplast (chl)genome was assembled as a single circular dsDNA of 151,199 bp. It is composed of a large single-copy (LSC), a small single-copy (SSC) and two inverted repeat (IR) regions of 82,909 bp, 18,390 bp and 24,950 bp, respectively. Overall GC contents of the genome were 37.5%. The A. lavandulaefolia YC chloroplast genome has a total of 117 genes including 82 protein-coding genes, 31 tRNA genes, and 4 rRNA genes. Phylogenetic analysis based on the chloroplast genome demonstrated that A. lavandulaefolia YC most closely related to Artemisia motana. The complete chloroplast genomes of A. lavandulaefolia YC would be useful for future investigation of genetics, evolution and clinical identification of artemisia species

HarDNet and Dual-Code Attention Mechanism Based Model for Medical Images Segmentation

During the formation of medical images, they are easily disturbed by factors such as acquisition devices and tissue backgrounds, causing problems such as blurred image backgrounds and difficulty in differentiation. In this paper, we combine the HarDNet module and the multi-coding attention mechanism module to optimize the two stages of encoding and decoding to improve the model segmentation performance. In the encoding stage, the HarDNet module extracts medical image feature information to improve the segmentation network operation speed. In the decoding stage, the multi-coding attention module is used to extract both the position feature information and channel feature information of the image to improve the model segmentation effect. Finally, to improve the segmentation accuracy of small targets, the use of Cross Entropy and Dice combination function is proposed as the loss function of this algorithm. The algorithm has experimented on three different types of medical datasets, Kvasir-SEG, ISIC2018, and COVID-19CT. The values of JS were 0.7189, 0.7702, 0.9895, ACC were 0.8964, 0.9491, 0.9965, SENS were 0.7634, 0.8204, 0.9976, PRE were 0.9214, 0.9504, 0.9931. The experimental results showed that the model proposed in this paper achieved excellent segmentation results in all the above evaluation indexes, which can effectively assist doctors to diagnose related diseases quickly and improve the speed of diagnosis and patients’ quality of life