Are vitamin B12 and folate deficiency clinically important after roux-en-Y gastric bypass?

Although iron, vltamm B₁₂, and folate deficiency have been well documented after gastric bypass operations performed for morbid obesity, there is surprisingly little information on either the natural course or the treatment of these deficiencies in Roux-en-Y gastric bypass (RYGB) patients Durmg a l0-year period, a complete blood count and serum levels of iron, total iron-binding capacity, vltamin B₁₂, and folate were obtained in 348 patients preoperatively and postoperatively at 6-month intervals for the first 2 years, then annually thereafter The principal objectives of this study were to determine how readily patients who developed metabolic deficiencies after Roux-en-Y gastric bypass responded to postoperative supplements of the deficient micronutrient and to learn whether the risk of developmg these deficiencies decreases over time Hemoglobin and hematocrit levels were slgnificantly decreased at all postoperative intervals in comparison to preoperative values Moreover, at each successive interval through 5 years, hemoglobin and hematocrit were decreased signifiantly compared to the preceding interval Folate levels were significantly increased compared to preoperative levels at all time intervals Iron and vltamin B₁₂ levels were lower than preoperative measurements and remained relatively stable postoperatively Half of the low hemoglobin levels were not associated with iron deficiency Taking multivltamin supplements resulted in a lower incidence of folate deficiency but did not prevent iron or vitamin B₁₂ deficiency Oral supplementation of iron and vitamin B₁₂ corrected defiaencies in 43% and 81% of cases, respectively Folate deficiency was almost always corrected with multivitamins alone No patient had symptoms that could be attributed to either vitamin B₁₂ or folate deficiency Conversely, many patients had symptoms of iron deficiency and anenua Lack of symptoms of vitamin B₁₂ and folate deficiency suggests that these deficiencies are not clinically important after RYGB Conversely, iron deficiency and anemia are potentially serious problems after RYGB, particularly in younger women Hence we recommend prophylactic oral iron supplements to premenopausal women who undergo RYGB     

Exclusion of known gene for enamel development in two Brazilian families with amelogenesis imperfecta

Background

Functional rehabilitation of patients afflicted with severe mandibular and maxillary alveolar atrophy might be challenging especially in malformed patients.

Methods

Treatment planning using sinus lifting and implant placement before Le Fort I maxillary osteotomy in a patient with severe mandibular and posterior maxillary alveolar atrophy and skelettal class-III conditions due to cleft palate are described.

Results

A full functional and esthetic rehabilitation of the patient was achieved by a stepwise surgical approach performed through sinus lifting as the primary approach followed by implant placement and subsequent Le Fort I maxillary osteotomy to correct the maxillo-mandibular relation.

Conclusion

Stabilisation of the maxillary complex by a sinus lifting procedure in combination with computer aided implant placement as preorthodontic planning procedure before Le Fort I maxillary osteotomy seems to be suitable in order to allow ideal oral rehabilitation especially in malformed patients.     

Patients’ preferred mode of travel to the orthopaedic theatre

AIM: To determine the preferred mode of travel to the operating theatre for elective orthopaedic patients.METHODS: Data was collected prospectively over a 2-wk period at an elective Orthopaedic Treatment Centre. Patients were asked to complete a patient satisfaction questionnaire following their surgery on their experience and subsequent preferred mode of transport to theatre. The data was then recorded in a tabulated format and analysed with percentages. Fisher’s exact test was used to determine if there was any statistical association between patients’ preference to walk and various groups; in-patient or day case procedures, and whether patients were < 60 years or > 60 years of age.RESULTS: Seventy patients (40 females and 30 males) fully completed the questionnaire. In total there were 33 d-cases and 37 in-patients. The spectrum of orthopaedic sub-specialties included was knee (41%), hip (17%), foot and ankle (24%), spine (13%) and upper limb (4%). Patient satisfaction for overall experience of travelling to theatre was either excellent (77%) or good (23%). Following their experience of travelling to theatre, 87% (95%CI: 79%-95%) of the total cohort would have preferred to walk to the operating theatre. There was a statistically significant association (P = 0.003) between patients’ preference to walk and whether they were day-case or in-patients. Similarly, there was a statistically significance association (P = 0.028) between patients’ preference to walk and whether they were < 60 years or > 60 years of age.CONCLUSION: This study confirms the majority of Orthopaedic elective patients would prefer to walk to theatre, when given the choice and if practically possible.     

A technique for intraoperative creation of patient-specific titanium mesh implants

Prefabricated, patient-specific alloplastic implants for cranioplasty reduce surgical complexity, decrease operative times, minimize exposure and risk of contamination, and have resulted in improved aesthetic results. However, in creating a prefabricated custom implant using a patient’s computed tomography data, a stable, unalterable defect must be clearly defined before surgery. In the event that an intraoperative modification of an exiting skull defect is required, or in cases of tumour resection in which the size of the skull defect is unknown preoperatively, these prefabricated implants cannot be used. The ideal method for alloplastic cranioplasty would enable cost-effective creation of a patient-specific implant with the capacity for intraoperative modification.The present article describes a novel technique of cranioplasty that uses a patient’s computed tomography data to create a custom forming tool (ie, mold), enabling intraoperative creation of a patient-specific titanium mesh implant. The utility of these implants in creating a custom reconstructive solution in cases in which the size of the skull defect is unknown preoperatively will be demonstrated using two case presentations.     

Immunohistochemical localization of membrane and alpha-granule proteins in human megakaryocytes: application to plastic-embedded bone marrow biopsy specimens

Using a new technique for antigen localization, we have demonstrated platelet proteins in megakaryocytes in plastic-embedded biopsy specimens of normal human bone marrow. In a series of 25 specimens, megakaryocytes showed labeling with antibodies to the integral membrane glycoproteins IIIa, IIb, and the IIb-IIIa complex; granule membrane protein 140; and five alpha-granule matrix proteins: thrombospondin, factor VIII-related antigen, beta-thromboglobulin, platelet factor 4, and fibrinogen. The antibodies to the membrane glycoproteins IIIa, IIb, and IIb-IIIa produced diffuse cytoplasmic staining and heavier staining on the plasma membrane, whereas the antibodies to the alpha-granule matrix proteins produced a distinct granular staining within the cytoplasm. Staining for granule membrane protein 140 was also granular in distribution. Rare mononuclear cells consistent with megakaryocyte precursors were labeled with these markers. Other enzyme histochemical and lectin-binding studies showed that the enzyme alpha-naphthyl acetate esterase, the lectin Ulex europaeus I, and the periodic-acid Schiff reaction were consistent, but not specific, markers of megakaryocytes. This immunohistochemical technique should facilitate the examination of qualitative and quantitative changes in megakaryocytes in a variety of physiologic and pathologic processes.     

Low birth weights contribute to high rates of early-onset chronic renal failure in the Southeastern United States

BACKGROUND: The southeastern United States is a region in which rates of cardiovascular and renal diseases are excessive. Within the Southeast, South Carolina has unusually high rates of end-stage renal disease (ESRD) in young people, with more than 70% of cases attributed to hypertension and diabetes. OBJECTIVE: To determine whether the increased vulnerability to early-onset ESRD might originate through impaired renal development in utero as measured by low birth weight. METHODS: Patients who were diagnosed with renal failure and undergoing dialysis from 1991 through 1996 were identified from the ESRD registry maintained by the Southeastern Kidney Council, Raleigh, NC. Birth weights reported on birth certificates were selected for the ESRD cases and non-ESRD controls who were born in South Carolina in 1950 and later. Birth weights were compared for 1230 cases and 2460 controls who were matched for age, sex, and race. RESULTS: Low birth weight was associated with ESRD among men and women as well as blacks and whites. Among people whose birth weight was less than 2.5 kg, the odds ratio for ESRD was 1.4 (95% confidence interval, 1.1-1.8) compared with people who weighed 3 to 3.5 kg. This association was present for renal failure resulting from diabetes, hypertension, and other causes. CONCLUSIONS: Low birth weights, which reflect adverse effects on development in utero, contribute to the early onset of ESRD in South Carolina. Since low birth weight increases the risk of ESRD from multiple causes, the data suggest that an adverse environment in utero impairs kidney development and makes it more vulnerable to damage from a range of pathological processes.     

Pathoscope: Species identification and strain attribution with unassembled sequencing data

Emerging next-generation sequencing technologies have revolutionized the collection of genomic data for applications in bioforensics, biosurveillance, and for use in clinical settings. However, to make the most of these new data, new methodology needs to be developed that can accommodate large volumes of genetic data in a computationally efficient manner. We present a statistical framework to analyze raw next-generation sequence reads from purified or mixed environmental or targeted infected tissue samples for rapid species identification and strain attribution against a robust database of known biological agents. Our method, Pathoscope, capitalizes on a Bayesian statistical framework that accommodates information on sequence quality, mapping quality, and provides posterior probabilities of matches to a known database of target genomes. Importantly, our approach also incorporates the possibility that multiple species can be present in the sample and considers cases when the sample species/strain is not in the reference database. Furthermore, our approach can accurately discriminate between very closely related strains of the same species with very little coverage of the genome and without the need for multiple alignment steps, extensive homology searches, or genome assembly—which are time-consuming and labor-intensive steps. We demonstrate the utility of our approach on genomic data from purified and in silico “environmental” samples from known bacterial agents impacting human health for accuracy assessment and comparison with other approaches.The accurate and rapid identification of species and strains of pathogens is an essential component of biosurveillance from both human health and biodefense perspectives (Vaidyanathan 2011). For example, misidentification was among the issues that resulted in a 3-wk delay in accurate diagnosis of the recent outbreak of hemorrhagic Escherichia coli being due to strain O104:H4, resulting in over 3800 infections across 13 countries in Europe with 54 deaths (Frank et al. 2011). The most accurate diagnostic information, necessary for species identification and strain attribution, comes from the most refined level of biological data—genomic DNA sequences (Eppinger et al. 2011). Advances in DNA-sequencing technologies allows for the rapid collection of extraordinary amounts of genomic data, yet robust approaches to analyze this volume of data are just developing, from both statistical and algorithmic perspectives.Next-generation sequencing approaches have revolutionized the way we collect DNA sequence data, including for applications in pathology, bioforensics, and biosurveillance. Given a particular clinical or metagenomic sample, our goal is to identify the specific species, strains, or substrains present in the sample, as well as accurately estimate the proportions of DNA originating from each source genome in the sample. Current approaches for next-gen sequencing usually have read lengths between 25 and 1000 bp; however, these sequencing technologies include error rates that vary by approach and by samples. Such variation is typically less important for species identification given the relatively larger genetic divergences among species than among individuals within species. But for strain attribution, sequencing error has the potential to swamp out discriminatory signal in a data set, necessitating highly sensitive and refined computational models and a robust database for both species identification and strain attribution.Current methods for classifying metagenomic samples rely on one or more of three general approaches: composition or pattern matching (McHardy et al. 2007; Brady and Salzberg 2009; Segata et al. 2012), taxonomic mapping (Huson et al. 2007; Meyer et al. 2008; Monzoorul Haque et al. 2009; Gerlach and Stoye 2011; Patil et al. 2012; Segata et al. 2012), and whole-genome assembly (Kostic et al. 2011; Bhaduri et al. 2012). Composition and pattern-matching algorithms use predetermined patterns in the data, such as taxonomic clade markers (Segata et al. 2012), k-mer frequency, or GC content, often coupled with sophisticated classification algorithms such as support vector machines (McHardy et al. 2007; Patil et al. 2012) or interpolated Markov Models (Brady and Salzberg 2009) to classify reads to the species of interest. These approaches require intensive preprocessing of the genomic database before application. In addition, the classification rule and results can often change dramatically depending on the size and composition of the genome database.Taxonomy-based approaches typically rely on a “lowest common ancestor” approach (Huson et al. 2007), meaning that they identify the most specific taxonomic group for each read. If a read originates from a genomic region that shares homology with other organisms in the database, the read is assigned to the lowest taxonomic group that contains all of the genomes that share the homologous region. These methods are typically highly accurate for higher-level taxonomic levels (e.g., phylum and family), but experience reduced accuracy at lower levels (e.g., species and strain) (Gerlach and Stoye 2011). Furthermore, these approaches are not informative when the reads originate from one or more species or strains that are closely related to each other or different organisms in the database. In these cases, all of the reads can be reassigned to higher-level taxonomies, thus failing to identify the specific species or strains contained in the sample.Assembly-based algorithms can often lead to the most accurate strain identification. However, these methods also require the assembly of a whole genome from a sample, which is a computationally difficult and time-consuming process that requires large numbers of reads to achieve an adequate accuracy—often on the order of 50–100× coverage of the target genome (Schatz et al. 2010). Given current sequencing depths, obtaining this level of coverage is usually possible for purified samples, but coverage levels may not be sufficient for mixed samples or in multiplexed sequencing runs. Assembly approaches are further complicated by the fact that data collection at a crime scene or hospital might include additional environmental components in the biological sample (host genome or naturally occurring bacterial and viral species), thus requiring multiple filtering and alignment steps in order to obtain reads specific to the pathogen of interest.Here we describe an accurate and efficient approach to analyze next-generation sequence data for species identification and strain attribution that capitalizes on a Bayesian statistical framework implemented in the new software package Pathoscope v1.0. Our approach accommodates information on sequence quality, mapping quality, and provides posterior probabilities of matches to a known database of reference genomes. Importantly, our approach incorporates the possibility that multiple species can be present in the sample or that the target strain is not even contained within the reference database. It also accurately discriminates between very closely related strains of the same species with much less than 1× coverage of the genome and without the need for sequence assembly or complex preprocessing of the database or taxonomy. No other method in the literature can identify species or substrains in such a direct and automatic manner and without the need for large numbers of reads. We demonstrate our approach through application to next-generation DNA sequence data from a recent outbreak of the hemorrhagic E. coli (O104:H4) strain in Europe (Frank et al. 2011; Rohde et al. 2011; Turner 2011) and on purified and in silico mixed samples from several other known bacterial agents that impact human health. Software and data examples for our approach are freely available for download at https://sourceforge.net/projects/pathoscope/.