Antisense oligonucleotides restore excitability, GABA signalling and sodium current density in a Dravet syndrome model.

Dravet syndrome is an intractable developmental and epileptic encephalopathy caused by de novo variants in SCN1A resulting in haploinsufficiency of the voltage-gated sodium channel Nav1.1. We showed previously that administration of the antisense oligonucleotide STK-001, also called ASO-22, generated using targeted augmentation of nuclear gene output technology to prevent inclusion of the nonsense-mediated decay, or poison, exon 20N in human SCN1A, increased productive Scn1a transcript and Nav1.1 expression and reduced the incidence of electrographic seizures and sudden unexpected death in epilepsy in a mouse model of Dravet syndrome. Here, we investigated the mechanism of action of ASO-84, a surrogate for ASO-22 that also targets splicing of SCN1A exon 20N, in Scn1a+/- Dravet syndrome mouse brain. Scn1a +/- Dravet syndrome and wild-type mice received a single intracerebroventricular injection of antisense oligonucleotide or vehicle at postnatal Day 2. We examined the electrophysiological properties of cortical pyramidal neurons and parvalbumin-positive fast-spiking interneurons in brain slices at postnatal Days 21-25 and measured sodium currents in parvalbumin-positive interneurons acutely dissociated from postnatal Day 21-25 brain slices. We show that, in untreated Dravet syndrome mice, intrinsic cortical pyramidal neuron excitability was unchanged while cortical parvalbumin-positive interneurons showed biphasic excitability with initial hyperexcitability followed by hypoexcitability and depolarization block. Dravet syndrome parvalbumin-positive interneuron sodium current density was decreased compared to wild-type. GABAergic signalling to cortical pyramidal neurons was reduced in Dravet syndrome mice, suggesting decreased GABA release from interneurons. ASO-84 treatment restored action potential firing, sodium current density and GABAergic signalling in Dravet syndrome parvalbumin-positive interneurons. Our work suggests that interneuron excitability is selectively affected by ASO-84. This new work provides critical insights into the mechanism of action of this antisense oligonucleotide and supports the potential of antisense oligonucleotide-mediated upregulation of Nav1.1 as a successful strategy to treat Dravet syndrome.

Driving Mitochondrial Fission Improves Cognitive, but not Motor Deficits in a Mouse Model of Ataxia of Charlevoix-Saguenay.

Autosomal-recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is caused by loss-of-function mutation in the SACS gene, which encodes sacsin, a putative HSP70-HSP90 co-chaperone. Previous studies with Sacs knock-out (KO) mice and patient-derived fibroblasts suggested that SACSIN mutations inhibit the function of the mitochondrial fission enzyme dynamin-related protein 1 (Drp1). This in turn resulted in mitochondrial hyperfusion and dysfunction. We experimentally tested this hypothesis by genetically manipulating the mitochondrial fission/fusion equilibrium, creating double KO (DKO) mice that also lack positive (PP2A/Bß2) and negative (PKA/AKAP1) regulators of Drp1. Neither promoting mitochondrial fusion (Bß2 KO) nor fission (Akap1 KO) influenced progression of motor symptoms in Sacs KO mice. However, our studies identified profound learning and memory deficits in aged Sacs KO mice. Moreover, this cognitive impairment was rescued in a gene dose-dependent manner by deletion of the Drp1 inhibitor PKA/Akap1. Our results are inconsistent with mitochondrial dysfunction as a primary pathogenic mechanism in ARSACS. Instead, they imply that promoting mitochondrial fission may be beneficial at later stages of the disease when pathology extends to brain regions subserving learning and memory.

New sagittal abdominal diameter and transverse abdominal diameter based equations to estimate visceral fat area in type 2 diabetes patients.

OBJECTIVE: Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) are considered gold standards for measuring visceral fat area (VFA). However, their relatively high prices and potential radiation exposure limit their widespread use in clinical practice and everyday life. Therefore, our study aims to develop a VFA estimated equation based on sagittal abdominal diameter (SAD) and transverse abdominal diameter (TAD) using anthropometric indexes. To the best of our knowledge, there have been limited studies investigating this aspect thus far. METHODS: This study was designed as a cross-sectional, retrospective cohort survey. A total of 288 patients (167 males and 121 females) aged 18-80 with type 2 diabetes (T2D) were consecutively collected from a multicenter hospital, and VFA was measured by CT. Subsequently, variables highly correlated with VFA were screened through general linear correlation analysis. A stepwise regression analysis was then conducted to develop a VFA estimated equation. Discrepancies between the estimated and actual VFA values were assessed using the Bland-Altman method to validate the accuracy of the equation. RESULTS: In the female T2D population, triglyceride (TG), SAD, TAD were found to be independently correlated with VFA; in the male T2D population, BMI, TG, SAD and TAD showed independent correlations with VFA. Among these variables, SAD exhibited the strongest correlation with VFA (r = 0.83 for females, r = 0.88 for males), followed by TAD (r = 0.69 for females, r = 0.79 for males). Based on these findings, a VFA estimated equation was developed for the T2D population: VFA (male) =-364.16 + 15.36*SAD + 0.77*TG + 9.41*TAD - 5.00*BMI (R2 = 0.75, adjusted R2 = 0.74); VFA(female)=-170.87 + 9.72*SAD-24.29*(TG^-1) + 3.93*TAD (R2 = 0.69, adjusted R2 = 0.68). Both models demonstrated a good fit. The Bland-Altman plot indicated a strong agreement between the actual VFA values and the estimated values, the mean differences were close to 0, and the majority of differences fell within the 95% confidence interval. CONCLUSIONS: In the T2D population, a VFA estimated equation is developed by incorporating SAD and TAD along with other measurement indices. This equation demonstrates a favorable estimated performance, suggesting to the development of novel and practical VFA estimation models in the future study.

Bilinear Distance Feature Network for Semantic Segmentation in PowerLine Corridor Point Clouds.

Semantic segmentation of target objects in power transmission line corridor point cloud scenes is a crucial step in powerline tree barrier detection. The massive quantity, disordered distribution, and non-uniformity of point clouds in power transmission line corridor scenes pose significant challenges for feature extraction. Previous studies have often overlooked the core utilization of spatial information, limiting the network's ability to understand complex geometric shapes. To overcome this limitation, this paper focuses on enhancing the deep expression of spatial geometric information in segmentation networks and proposes a method called BDF-Net to improve RandLA-Net. For each input 3D point cloud data, BDF-Net first encodes the relative coordinates and relative distance information into spatial geometric feature representations through the Spatial Information Encoding block to capture the local spatial structure of the point cloud data. Subsequently, the Bilinear Pooling block effectively combines the feature information of the point cloud with the spatial geometric representation by leveraging its bilinear interaction capability thus learning more discriminative local feature descriptors. The Global Feature Extraction block captures the global structure information in the point cloud data by using the ratio between the point position and the relative position, so as to enhance the semantic understanding ability of the network. In order to verify the performance of BDF-Net, this paper constructs a dataset, PPCD, for the point cloud scenario of transmission line corridors and conducts detailed experiments on it. The experimental results show that BDF-Net achieves significant performance improvements in various evaluation metrics, specifically achieving an OA of 97.16%, a mIoU of 77.48%, and a mAcc of 87.6%, which are 3.03%, 16.23%, and 18.44% higher than RandLA-Net, respectively. Moreover, comparisons with other state-of-the-art methods also verify the superiority of BDF-Net in point cloud semantic segmentation tasks.

Compact continuous-wave solid-state Raman lasers at 707 and 714†nm for laser trapping and cooling of atomic strontium and radium.

Two compact laser sources at 707 and 714 nm are realized efficiently by using a diode-pumped a-cut Nd:YVO4 laser with intracavity stimulated Raman scattering and sum-frequency generation (SFG). The fundamental wave at 1342 nm is generated by the 4F3/2 → 4I13/2 transition in Nd:YVO4 crystal. The Raman Stokes waves at 1496 and 1526 nm were obtained by placing the c-axis of the Nd:YVO4 crystal along the Ng and Nm axes of an Np-cut KGW crystal, respectively. LBO crystals with critical phase matching are used to perform the intracavity SFG of fundamental and Stokes waves. At a pump power of 36 W, the maximum output powers at 707 and 714 nm can reach 2.72 and 3.14 W, corresponding to light-to-light conversion efficiencies of 7.5% and 8.7%, respectively. The developed 707 and 714 nm laser sources are practically useful in laser trapping and cooling related to atomic strontium and radium.

Selectable two-wavelength Nd:YVO4 Raman laser at 671 and 714†nm.

A compact efficient continuous wave (CW) laser with selectable two wavelengths at 671 and 714 nm is developed. The laser cavity comprises an Nd-doped and an undoped YVO4 crystal to generate the fundamental wave at 1342 nm and the first-Stokes Raman wave at 1525 nm, respectively. A single LBO crystal with the cut angle in the XZ plane is designed to achieve the selectable phase-matching via the thermal tuning for the second harmonic generation (SHG) of 1342 nm and the sum frequency generation (SFG) of 1342 and 1525 nm. At a pump power of 40 W, the optimal output powers at 671 and 714 nm can reach 4.5 and 1.8 W, respectively. The present compact CW laser source at 671 and 714 nm has practical usefulness for laser spectroscopy and numerous applications.

Analysis of NDM-1 and IMP-8 carbapenemase producing Raoultella planticola clinical isolates.

Object of our study was to analyze the carriage of resistance genes in carbapenem-resistant Raoultella planticola (CRRP) by whole genome sequencing (WGS). Three strains of CRRP (named WF0027, WF3597 and WF3648) were collected for clinical analysis and susceptibility of antimicrobial agents was determined. The WGS of three strains was done by Illumina platform and strain identification was performed by average nucleotide identity, and the antibiotic resistance genes carried by the three strains were detected by ABRicate software. Whole genome data of 46 CRRP strains were downloaded from the National Center for Biotechnology Information (NCBI) database, and the evolutionary tree was constructed by genomic single nucleotide polymorphism together with this study strains. Antimicrobial susceptibility testing revealed that WF3597 and WF3648 were susceptible to tigecycline and colistin, while exhibited resistance to 24 antimicrobial agents. WF0027 was resistant to 18 antimicrobial agents. A total of 25 resistance genes were identified using ABRicate software. WF0027 carried blaIMP-8, whereas WF3597 and WF3648 carried blaNDM-1 carbapenem resistance gene. As predicted by the PlasmidFinder, WF3597 and WF3648 carried one plasmid IncFII(p14)_1_p14, whereas WF0027 carried five plasmids. Evolutionary tree results show all strains are clustered into six groups, the strains WF3597 and WF3648 belonged to the same evolutionary group (E clade) and WF0027 belonged to the F clade. Three CRRP strains in our study carried carbapenem resistance genes (blaNDM-1 or blaIMP-8) and were resistant to multiple antimicrobial agents, posing a significant challenge for clinical treatment.

First Report of Leaf Spot Caused by Alternaria alternata on Cyclocodon lancifolius in China.

Cyclocodon lancifolius Bunge in the family Campanulaceae, and commonly known as Hong Guo Ginseng, is found in the Indonesia, Philippines, Vietnam, Japan, and China. The leaves and roots of C. lancifolius are widely used as tonics by ethnic minorities in Guizhou and Hunan Provinces in China. In addition, the fruit is edible, and it is a new resource for both medicine and food. In June 2022, symptoms of leaf spot (Fig 1 A and B.) were observed on C. lancifolius plants in the medicinal plant greenhouse of Guizhou University of Traditional Chinese Medicine (106°61'E, 26°39'N), Guizhou Province. The incidence of leaf spot on C. lancifolius was approximately 40 to 70% of all leaves in canopy. Early symptoms on leaves were small circular or irregular brown spots. As the disease progressed the lesions gradually expanded, and multiple lesions coalesced to form large irregular brown spots. Eventually the seedlings died and leaves of mature plants wilted. In order to isolate the pathogen, ten leaf pieces (5×5 mm) were cut from the junction of the diseased and the healthy tissues, surface sterilized with 75% ethanol for 30 s, 0.1% mercuric chloride (HgCl2) solution for 60 s, rinsed in sterile water three times, finally dried and placed on potato dextrose agar (PDA) and cultured in the dark at 27°C for 4 days. Five purified fungal isolates were obtained by single spore isolation. The colonies were olivaceous to dark olive with white margins and abundant aerial mycelia. On potato carrot agar (PCA) medium, these fungi produced septate conidiophores. Conidia were obclavate or ellipsoid, brown, with one to four transverse septa and one to two longitudinal septa. Spores measured 7.64 to 14.20 × 3.32 to 6.38 µm (n=50). These morphological characteristics are consistent with Alternaria alternata (S. P. Wiltshire. 1933). To further confirm the identification, four genomic DNA regions including the ribosomal DNA internal transcribed spacer (ITS), translation elongation factor 1-a gene (TEF), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), RNA polymerase II second largest subunit (RPB2), and Alternaria major allergen gene (Alt a1) were amplified and sequenced with primers ITS1/ITS4 (White et al. 1990), TEF1-728F/TEF1-986R (Carbone and Kohn 1999), gpd1/gpd2 (Berbee et al. 1999), RPB2-5F/RPB2-7cR (Liu et al. 1999), and Alt-for/Alt-rev (Hong et al. 2005), respectively. Sequences were deposited in GenBank with accession Nos. ITS: OQ128111, OQ690707, and OQ690708; TEF: OQ200380, OQ700996, and OQ700998; GAPDH: OQ200378, OQ700993, and OQ700995; RPB2:OQ200379, OQ701002, and OQ701004; Alt: OQ675614, OQ700999, and OQ701001. In a BLAST search, the sequences were 99-100% identical with corresponding sequences of A. alternata. A maximum likelihood phylogenetic tree was constructed with the combined sequence data sets of ITS, TEF, GAPDH, RPB2, and Alt a1 using MEGA 11. The isolate DHY0, DHY1, and DHY3 clustered with A. alternata (J. H. C. Woudenberg et al. 2015) (Fig. 2). To fulfill Koch's postulates, leaves on three healthy 3-month-old potted C. lancifolius seedlings were wounded with sterile needles and inoculated with 5 mm diameter mycelium, which was covered moist by sterile cotton for 24 h. Sterile water was used as the control. After inoculation, the plants were incubated at 27°C, 85% relative humidity, and a 12 h photoperiod. The experiment was repeated three times. Fifteen days after inoculation, all the leaves showed leaf spot symptoms that were similar to those observed in the greenhouse, while control leaves were asymptomatic (Fig. 1). A. alternata was successfully re-isolated from the symptomatic leaves and identified by morphology and the molecular methods described above. This pathogen has been reported to cause a leaf disease in a wide range of vegetables (Zhang et al. 2021), flowers (Zhang et al. 2022), and medicinal plants (Xing et al. 2020). To the best of our knowledge, this is the first report of A. alternata causing leaf spot on C. lancifolius in China. The accurate identification of this pathogen will provide a basis for the prevention and control of C. lancifolius leaf spot disease in the future.

Profiles of Intolerance of Uncertainty Among 108,540 Adolescents: Associations with Sociodemographic Variables and Mental Health.

Intolerance of uncertainty (IU) is widely considered a transdiagnostic risk and maintaining factor for psychiatric disorders. However, little is known about the overall nature and profile of IU among adolescents. This study aims to investigate the profiles of IU among Chinese adolescents and explore their associations with sociodemographic characteristics and mental health problems. A sample of 108,540 adolescents provided data on IU, sociodemographic characteristics, and mental health via an online platform. Latent profile analysis revealed three profiles: Low IU, Medium IU, and High IU. Girls, older adolescents, and those with specific sociodemographics were more likely to belong to the "High IU" profile. Furthermore, the "High IU" profile was associated with the highest risk of several mental health problems. These findings provided valuable information for early prevention and intervention strategies targeting IU and highlighted the importance of IU-based interventions for mental health among adolescents.

NeDSeM: Neutrosophy Domain-Based Segmentation Method for Malignant Melanoma Images.

Skin lesion segmentation is the first and indispensable step of malignant melanoma recognition and diagnosis. At present, most of the existing skin lesions segmentation techniques often used traditional methods like optimum thresholding, etc., and deep learning methods like U-net, etc. However, the edges of skin lesions in malignant melanoma images are gradually changed in color, and this change is nonlinear. The existing methods can not effectively distinguish banded edges between lesion areas and healthy skin areas well. Aiming at the uncertainty and fuzziness of banded edges, the neutrosophic set theory is used in this paper which is better than fuzzy theory to deal with banded edge segmentation. Therefore, we proposed a neutrosophy domain-based segmentation method that contains six steps. Firstly, an image is converted into three channels and the pixel matrix of each channel is obtained. Secondly, the pixel matrixes are converted into Neutrosophic Set domain by using the neutrosophic set conversion method to express the uncertainty and fuzziness of banded edges of malignant melanoma images. Thirdly, a new Neutrosophic Entropy model is proposed to combine the three memberships according to some rules by using the transformations in the neutrosophic space to comprehensively express three memberships and highlight the banded edges of the images. Fourthly, the feature augment method is established by the difference of three components. Fifthly, the dilation is used on the neutrosophic entropy matrixes to fill in the noise region. Finally, the image that is represented by transformed matrix is segmented by the Hierarchical Gaussian Mixture Model clustering method to obtain the banded edge of the image. Qualitative and quantitative experiments are performed on malignant melanoma image dataset to evaluate the performance of the NeDSeM method. Compared with some state-of-the-art methods, our method has achieved good results in terms of performance and accuracy.