Hibiscus latent Singapore virus (HLSV) and Hibiscus latent Fort Pierce virus (HLFPV) both belong to the genus Tobamovirus in the family Virgaviridae. The genomes of both HLSV and HLFPV consist of a linear positive sense single-stranded RNA of about 6.3 kb. HLSV is the causal agent of hibiscus leaf crinkle disease. Infections of HLSV in hibiscus (Hibiscus rosa-sinensis) have so far only been reported in Singapore, Japan and Malaysia (Srinivasan et al., 2002; Yoshida et al., 2018; Yusop et al., 2021). In 2017, leaf curling and chlorosis symptoms of lantana (Lantana camara) plants were found in Chenshan Botanical Garden, Shanghai, China. To detect potential virus(es) in these lantana samples, leaves from one lantana plant were collected and total RNA was extracted with RNAiso Plus (TaKaRa). A cDNA library was prepared by TruSeq RNA Sample Prep Kit (Illumina) after removing ribosomal RNA by Ribo-ZeroTM rRNA Removal Kit (Epicentre). The paired-end sequencing was then performed on an Illumina NovaSeq 6000. A total of 61,085,018 high quality reads were obtained and de novo assembly by StringTie revealed 124,516 contigs (greater than 50 bp, N50=719 bp) with an average length of 537 bp. BLASTx analyses in the National Center for Biotechnology Information (NCBI) database showed that 1 long contig of 6,305 bp, assembled of 1794 clean reads, shared significant nucleotide similarities with the genomic sequence of HLSV, and 1 contig of 6,271 bp, assembled of 3174 clean reads, shared significant similarities with the genomic sequence of HLFPV, yielding an average coverage of the whole genome at 42.65 and 75.83 per million reads, respectively. To obtain the complete genome of the viral RNA in this lantana sample, eleven overlapping regions covering the entire HLSV viral genome, and nine overlapping regions covering the entire HLFPV viral genome were amplified by reverse transcription-PCR (RT-PCR) and sequenced. In addition, the exact 5' and 3' ends of the genomic RNA of each virus were determined by rapid amplification of the cDNA ends (RACE) (Wang et al. 2020). The complete genome of the identified HLSV, deposited in GenBank: MZ020960, is 6,486 nt in length and shows 98.4% nucleotide sequence identity with HLSV Singapore isolate (GenBank: AF395898). Similar to other HLSV isolates, this virus isolate possesses an internal poly(A) tract of 87 nucleotides, which is crucial to virus replication (Niu et al., 2015). The complete genome of the Lantana HLFPV isolate is 6,463 nt (GenBank MZ020961) including a 73 nt internal poly(A) tract, and has 98.4% nt identity to HLFPV-Japan (AB917427). In two other lantana plants from the same site, the presence of HLSV and HLFPV was confirmed by RT-PCR using the primer pairs (5'-GCATCTGCATAACACGGTTG-3'/5'-ACGTTGTAGTAGACGTTGTTGTAG-3' and 5'-GGACCTTGCTAATCCGCTAAAGTTG-3'/5'-GGTCCATGTCCATCCAGATGCAATC-3'). In addition to the HLSV and HLFPV genomes, BLASTx analysis of three contigs of 3,006 bp, 2,845 bp and 2,200 bp, assembled of 1328, 352 and 2280 clean reads respectively, showed high identity to RNAs 1 (MG182148), 2 (DQ412731) and 3 (KY794710) of cucumber mosaic virus. To the best of our knowledge, this is the first report of L. camara as a new natural host of HLSV and HLFPV, and first identification of a mixed infection of HLSV and HLFPV.
In recent years novel human respiratory disease agents have been described for Southeast Asia and Australia. The causative pathogens were classified as pteropine orthoreoviruses with a strong phylogenetic relationship to orthoreoviruses of bat origin.
The identification of new virus strains is important for the study of infectious disease, but current (or existing) molecular biology methods are limited since the target sequence must be known to design genome-specific PCR primers. Thus, we developed a new method for the discovery of unknown viruses based on the cDNA--random amplified polymorphic DNA (cDNA-RAPD) technique. Getah virus, belonging to the family Togaviridae in the genus Alphavirus, is a mosquito-borne enveloped RNA virus that was identified using the Virus-Discovery-cDNA RAPD (VIDISCR) method.
Williams-Beuren syndrome (WBS) is a common microdeletion syndrome characterized by a 1.5Mb deletion in 7q11.23. The phenotype of WBS has been well described in populations of European descent with not as much attention given to other ethnicities. In this study, individuals with WBS from diverse populations were assessed clinically and by facial analysis technology. Clinical data and images from 137 individuals with WBS were found in 19 countries with an average age of 11 years and female gender of 45%. The most common clinical phenotype elements were periorbital fullness and intellectual disability which were present in greater than 90% of our cohort. Additionally, 75% or greater of all individuals with WBS had malar flattening, long philtrum, wide mouth, and small jaw. Using facial analysis technology, we compared 286 Asian, African, Caucasian, and Latin American individuals with WBS with 286 gender and age matched controls and found that the accuracy to discriminate between WBS and controls was 0.90 when the entire cohort was evaluated concurrently. The test accuracy of the facial recognition technology increased significantly when the cohort was analyzed by specific ethnic population (P-value
Cornelia de Lange syndrome (CdLS) is a dominant multisystemic malformation syndrome due to mutations in five genes-NIPBL, SMC1A, HDAC8, SMC3, and RAD21. The characteristic facial dysmorphisms include microcephaly, arched eyebrows, synophrys, short nose with depressed bridge and anteverted nares, long philtrum, thin lips, micrognathia, and hypertrichosis. Most affected individuals have intellectual disability, growth deficiency, and upper limb anomalies. This study looked at individuals from diverse populations with both clinical and molecularly confirmed diagnoses of CdLS by facial analysis technology. Clinical data and images from 246 individuals with CdLS were obtained from 15 countries. This cohort included 49% female patients and ages ranged from infancy to 37 years. Individuals were grouped into ancestry categories of African descent, Asian, Latin American, Middle Eastern, and Caucasian. Across these populations, 14 features showed a statistically significant difference. The most common facial features found in all ancestry groups included synophrys, short nose with anteverted nares, and a long philtrum with thin vermillion of the upper lip. Using facial analysis technology we compared 246 individuals with CdLS to 246 gender/age matched controls and found that sensitivity was equal or greater than 95% for all groups. Specificity was equal or greater than 91%. In conclusion, we present consistent clinical findings from global populations with CdLS while demonstrating how facial analysis technology can be a tool to support accurate diagnoses in the clinical setting. This work, along with prior studies in this arena, will assist in earlier detection, recognition, and treatment of CdLS worldwide.
Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P