Tuberous sclerosis with visceral leishmaniasis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Visceral leishmaniasis, a tropical infectious disease, is a major public health problem in India. Tuberous sclerosis, a congenital neuro-ectodermosis, is an uncommon disease which requires life long treatment.</p> <p>Case presentation</p> <p>A 15-year-old Indian patient, presented to the outpatient department of our institute with a high-grade fever for two months, splenomegaly and a history of generalized tonic-clonic convulsions since childhood. The clinical and laboratory findings suggested visceral leishmaniasis with tuberous sclerosis. The patient was treated with miltefosine and antiepileptics.</p> <p>Conclusion</p> <p>The patient responded well and in a follow up six months after presentation, she was found free of visceral leishmaniasis and seizures. Diagnosis and treatment of this rare combination of diseases is difficult.</p

Fast Statistical Alignment

We describe a new program for the alignment of multiple biological sequences that is both statistically motivated and fast enough for problem sizes that arise in practice. Our Fast Statistical Alignment program is based on pair hidden Markov models which approximate an insertion/deletion process on a tree and uses a sequence annealing algorithm to combine the posterior probabilities estimated from these models into a multiple alignment. FSA uses its explicit statistical model to produce multiple alignments which are accompanied by estimates of the alignment accuracy and uncertainty for every column and character of the alignment—previously available only with alignment programs which use computationally-expensive Markov Chain Monte Carlo approaches—yet can align thousands of long sequences. Moreover, FSA utilizes an unsupervised query-specific learning procedure for parameter estimation which leads to improved accuracy on benchmark reference alignments in comparison to existing programs. The centroid alignment approach taken by FSA, in combination with its learning procedure, drastically reduces the amount of false-positive alignment on biological data in comparison to that given by other methods. The FSA program and a companion visualization tool for exploring uncertainty in alignments can be used via a web interface at http://orangutan.math.berkeley.edu/fsa/, and the source code is available at http://fsa.sourceforge.net/

Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

Background A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment. Results In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased. Conclusions The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign webcite

Investors’ Reactions to Revision Restatements: An Examination of Investment Position and Quantitative Reconciliation

Thesis (Ph.D.)--University of Washington, 2019Revision restatements are a growing phenomenon in which firms correct errors related to prior financials. Revision restatements are permitted only when firms consider the errors individually immaterial for the periods in which they occurred, but material when combined across periods. Unlike reissuance restatements, firms do not issue a stand-alone filing but instead simply correct the historical values in the next set of issued financial statements. Archival research finds that revision restatements predict negative firm outcomes, such as future material errors and material weaknesses. I draw from psychology and accounting research to predict that investors fail to fully process these restatements. Using an experiment, I find that when a firm corrects prior earnings downward, prospective investors update their beliefs more than current investors and consider the errors to be more material. When the firm makes the revision restatement easier to process by providing a quantitative reconciliation, there is a greater increase in how much prospective investors update their beliefs compared to current investors, who do not update at all. This study contributes to the emerging literature on revision restatements, the existing accounting literature on the continued influence effect, motivated reasoning and quantitative reconciliations, and the regulatory debate on materiality

Endoscopic drainage versus percutaneous drainage for the management of infected walled-off necrosis: a comparative analysis

Background: Comparative data on percutaneous catheter drainage (PCD) vs EUS-guided drainage (EUS-D) for management of symptomatic walled-off-necrosis (WON), specially infected WON with/without organ failure(OF) is limited. Methods: Patients with symptomatic WON were divided into two groups of PCD and EUS-D, depending on the modality of drainage. Resolution of OF, adverse events, and other outcome measures were recorded. The two modalities were compared among infected WON sub-cohort and also degree of solid component (SC). Results: 218 patients (175 males; 80.3%) were included who underwent either PCD (n&nbsp;=&nbsp;102) or EUS-D (n&nbsp;=&nbsp;116). Clinical success was significantly higher in the EUS-D group (92.1% vs 64.6%; p &lt;&nbsp;0.0001) and even for infected WON (n&nbsp;=&nbsp;128) (p&nbsp;=&nbsp;0.004), with higher (p&nbsp;=&nbsp;0.007) and faster (p&nbsp;&lt;&nbsp;0.0001) OF resolution. Other outcome measures including mortality were significantly higher in the PCD group. Among subgroups, PCD with &gt;40% SC had the worst clinical success/OF resolution rates, while EUS-D with &lt;40% SC had the best outcomes. Conclusion: EUS-D should be preferred over PCD in the management of WON, infected or otherwise, for higher clinical success, and higher/faster resolution of OF. PCD should be avoided in WON with&gt;40% SC

Snowball Vs. House-to-House Technique for Measuring Annual Incidence of Kala-azar in the Higher Endemic Blocks of Bihar, India: A Comparison.

Visceral Leishmaniasis, commonly known as kala-azar, is widely prevalent in Bihar. The National Kala-azar Control Program has applied house-to-house survey approach several times for estimating Kala-azar incidence in the past. However, this approach includes huge logistics and operational cost, as occurrence of kala-azar is clustered in nature. The present study aims to compare efficiency, cost and feasibility of snowball sampling approach to house-to-house survey approach in capturing kala-azar cases in two endemic districts of Bihar, India.A community based cross-sectional study was conducted in two highly endemic Primary Health Centre (PHC) areas, each from two endemic districts of Bihar, India. Snowball technique (used to locate potential subjects with help of key informants where subjects are hard to locate) and house-to-house survey technique were applied to detect all the new cases of Kala-azar during a defined reference period of one year i.e. June, 2010 to May, 2011. The study covered a total of 105,035 households with 537,153 populations. Out of total 561 cases and 17 deaths probably due to kala-azar, identified by the study, snowball sampling approach captured only 221 cases and 13 deaths, whereas 489 cases and 17 deaths were detected by house-to-house survey approach. Higher value of McNemar's χ² statistics (64; p1) indicates that most of the kala-azar cases missed by snowball sampling were captured by house-to-house approach with 13% of omission.Snowball sampling was not found sensitive enough as it captured only about 50% of VL cases. However, it captured about 77% of the deaths probably due to kala-azar and was found more cost-effective than house-to-house approach. Standardization of snowball approach with improved procedure, training and logistics may enhance the sensitivity of snowball sampling and its application in national Kala-azar elimination programme as cost-effective approach for estimation of kala-azar burden