Chromosome map of the Siamese cobra: did partial synteny of sex chromosomes in the amniote represent “a hypothetical ancestral super-sex chromosome” or random distribution?

Background Unlike the chromosome constitution of most snakes (2n=36), the cobra karyotype shows a diploid chromosome number of 38 with a highly heterochromatic W chromosome and a large morphologically different chromosome 2. To investigate the process of sex chromosome differentiation and evolution between cobras, most snakes, and other amniotes, we constructed a chromosome map of the Siamese cobra (Naja kaouthia) with 43 bacterial artificial chromosomes (BACs) derived from the chicken and zebra finch libraries using the fluorescence in situ hybridization (FISH) technique, and compared it with those of the chicken, the zebra finch, and other amniotes. Results We produced a detailed chromosome map of the Siamese cobra genome, focusing on chromosome 2 and sex chromosomes. Synteny of the Siamese cobra chromosome 2 (NKA2) and NKAZ were highly conserved among snakes and other squamate reptiles, except for intrachromosomal rearrangements occurring in NKA2. Interestingly, twelve BACs that had partial homology with sex chromosomes of several amniotes were mapped on the heterochromatic NKAW as hybridization signals such as repeat sequences. Sequence analysis showed that most of these BACs contained high proportions of transposable elements. In addition, hybridization signals of telomeric repeat (TTAGGG)n and six microsatellite repeat motifs ((AAGG)8, (AGAT)8, (AAAC)8, (ACAG)8, (AATC)8, and (AAAAT)6) were observed on NKAW, and most of these were also found on other amniote sex chromosomes. Conclusions The frequent amplification of repeats might involve heterochromatinization and promote sex chromosome differentiation in the Siamese cobra W sex chromosome. Repeat sequences are also shared among amniote sex chromosomes, which supports the hypothesis of an ancestral super-sex chromosome with overlaps of partial syntenies. Alternatively, amplification of microsatellite repeat motifs could have occurred independently in each lineage, representing convergent sex chromosomal differentiation among amniote sex chromosomes

Clinical risk-scoring algorithm to forecast scrub typhus severity

Pamornsri Sriwongpan,1,2 Pornsuda Krittigamas,3 Hutsaya Tantipong,4 Jayanton Patumanond,5 Chamaiporn Tawichasri,6 Sirianong Namwongprom1,71Clinical Epidemiology Program, Chiang Mai University, Chiang Mai, Thailand; 2Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; 3Department of General Pediatrics, Nakornping Hospital, Chiang Mai, Thailand; 4Department of Medicine, Chonburi Hospital, Chonburi, Thailand; 5Clinical Epidemiology Program, Thammasat University, Bangkok, Thailand; 6Clinical Epidemiology Society at Chiang Mai, Chiang Mai, Thailand; 7Department of Radiology, Chiang Mai University, Chiang Mai, ThailandPurpose: To develop a simple risk-scoring system to forecast scrub typhus severity.Patients and methods: Seven years' retrospective data of patients diagnosed with scrub typhus from two university-affiliated hospitals in the north of Thailand were analyzed. Patients were categorized into three severity groups: nonsevere, severe, and dead. Predictors for severity were analyzed under multivariable ordinal continuation ratio logistic regression. Significant coefficients were transformed into item score and summed to total scores.Results: Predictors of scrub typhus severity were age >15 years, (odds ratio [OR] =4.09), pulse rate >100/minute (OR 3.19), crepitation (OR 2.97), serum aspartate aminotransferase >160 IU/L (OR 2.89), serum albumin ≤3.0 g/dL (OR 4.69), and serum creatinine >1.4 mg/dL (OR 8.19). The scores which ranged from 0 to 16, classified patients into three risk levels: non-severe (score ≤5, n=278, 52.8%), severe (score 6–9, n=143, 27.2%), and fatal (score ≥10, n=105, 20.0%). Exact severity classification was obtained in 68.3% of cases. Underestimations of 5.9% and overestimations of 25.8% were clinically acceptable.Conclusion: The derived scrub typhus severity score classified patients into their severity levels with high levels of prediction, with clinically acceptable under- and overestimations. This classification may assist clinicians in patient prognostication, investigation, and management. The scoring algorithm should be validated by independent data before adoption into routine clinical practice.Keywords: severe scrub typhus, risk-scoring system, clinical prediction rule, prognostic predictor

Validation of a clinical risk-scoring algorithm for severe scrub typhus

Pamornsri Sriwongpan,1,2 Jayanton Patumanond,3 Pornsuda Krittigamas,4 Hutsaya Tantipong,5 Chamaiporn Tawichasri,6 Sirianong Namwongprom1,7 1Clinical Epidemiology Program, Faculty of Medicine, Chiang Mai University, Chiang Mai, 2Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai, 3Clinical Epidemiology Program, Faculty of Medicine, Thammasat University, Bangkok, 4Department of General Pediatrics, Nakornping Hospital, Chiang Mai, 5Department of Medicine, Chonburi Hospital, Chonburi, 6Clinical Epidemiology Society at Chiang Mai, Chiang Mai, 7Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand Objective: The aim of the study reported here was to validate the risk-scoring algorithm for prognostication of scrub typhus severity. Methods: The risk-scoring algorithm for prognostication of scrub typhus severity developed earlier from two general hospitals in Thailand was validated using an independent dataset of scrub typhus patients in one of the hospitals from a few years later. The predictive performances of the two datasets were compared by analysis of the area under the receiver-operating characteristic curve (AuROC). Classification of patients into non-severe, severe, and fatal cases was also compared. Results: The proportions of non-severe, severe, and fatal patients by operational definition were similar between the development and validation datasets. Patient, clinical, and laboratory profiles were also similar. Scores were similar in both datasets, both in terms of discriminating non-severe from severe and fatal patients (AuROC =88.74% versus 91.48%, P=0.324), and in discriminating fatal from severe and non-severe patients (AuROC =88.66% versus 91.22%, P=0.407). Over- and under-estimations were similar and were clinically acceptable. Conclusion: The previously developed risk-scoring algorithm for prognostication of scrub typhus severity performed similarly with the validation data and the first dataset. The scoring algorithm may help in the prognostication of patients according to their severity in routine clinical practice. Clinicians may use this scoring system to help make decisions about more intensive investigations and appropriate treatments. Keywords: severity, clinical prediction rule, algorithm, prognosis, Thailan