Kappa free light chains is a valid tool in the diagnostics of MS: A large multicenter study

To validate kappa free light chain (KFLC) and lambda free light chain (LFLC) indices as a diagnostic biomarker in multiple sclerosis (MS).We performed a multicenter study including 745 patients from 18 centers (219 controls and 526 clinically isolated syndrome (CIS)/MS patients) with a known oligoclonal IgG band (OCB) status. KFLC and LFLC were measured in paired cerebrospinal fluid (CSF) and serum samples. Gaussian mixture modeling was used to define a cut-off for KFLC and LFLC indexes.The cut-off for the KFLC index was 6.6 (95% confidence interval (CI) = 5.2-138.1). The cut-off for the LFLC index was 6.9 (95% CI = 4.5-22.2). For CIS/MS patients, sensitivity of the KFLC index (0.88; 95% CI = 0.85-0.90) was higher than OCB (0.82; 95%CI = 0.79-0.85; p < 0.001), but specificity (0.83; 95% CI = 0.78-0.88) was lower (OCB = 0.92; 95% CI = 0.89-0.96; p < 0.001). Both sensitivity and specificity for the LFLC index were lower than OCB.Compared with OCB, the KFLC index is more sensitive but less specific for diagnosing CIS/MS. Lacking an elevated KFLC index is more powerful for excluding MS compared with OCB but the latter is more important for ruling in a diagnosis of CIS/MS

Atlantic mammal traits: a dataset of morphological traits of mammals in the atlantic forest of south America

Measures of traits are the basis of functional biological diversity. Numerous works consider mean species-level measures of traits while ignoring individual variance within species. However, there is a large amount of variation within species and it is increasingly apparent that it is important to consider trait variation not only between species, but also within species. Mammals are an interesting group for investigating trait-based approaches because they play diverse and important ecological functions (e.g., pollination, seed dispersal, predation, grazing) that are correlated with functional traits. Here we compile a data set comprising morphological and life history information of 279 mammal species from 39,850 individuals of 388 populations ranging from −5.83 to −29.75 decimal degrees of latitude and −34.82 to −56.73 decimal degrees of longitude in the Atlantic forest of South America. We present trait information from 16,840 individuals of 181 species of non-volant mammals (Rodentia, Didelphimorphia, Carnivora, Primates, Cingulata, Artiodactyla, Pilosa, Lagomorpha, Perissodactyla) and from 23,010 individuals of 98 species of volant mammals (Chiroptera). The traits reported include body mass, age, sex, reproductive stage, as well as the geographic coordinates of sampling for all taxa. Moreover, we gathered information on forearm length for bats and body length and tail length for rodents and marsupials. No copyright restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data.Fil: Gonçalves, Fernando. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bovendorp, Ricardo S.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Beca, Gabrielle. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bello, Carolina. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Costa Pereira, Raul. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Muylaert, Renata L.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Rodarte, Raisa R.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Villar, Nacho. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Souza, Rafael. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Graipel, Maurício E.. Universidade Federal de Santa Catarina; BrasilFil: Cherem, Jorge J.. Caipora Cooperativa, Florianopolis; BrasilFil: Faria, Deborah. Universidade Estadual de Santa Cruz; BrasilFil: Baumgarten, Julio. Universidade Estadual de Santa Cruz; BrasilFil: Alvarez, Martín R.. Universidade Estadual de Santa Cruz; BrasilFil: Vieira, Emerson M.. Universidade do Brasília; BrasilFil: Cáceres, Nilton. Universidade Federal de Santa María. Santa María; BrasilFil: Pardini, Renata. Universidade de Sao Paulo; BrasilFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Costa, Leonora Pires. Universidade Federal do Espírito Santo; BrasilFil: Mello, Marco Aurelio Ribeiro. Universidade Federal de Minas Gerais; BrasilFil: Fischer, Erich. Universidade Federal do Mato Grosso do Sul; BrasilFil: Passos, Fernando C.. Universidade Federal do Paraná; BrasilFil: Varzinczak, Luiz H.. Universidade Federal do Paraná; BrasilFil: Prevedello, Jayme A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Cruz-Neto, Ariovaldo P.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Carvalho, Fernando. Universidade do Extremo Sul Catarinense; BrasilFil: Reis Percequillo, Alexandre. Universidade de Sao Paulo; BrasilFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Duarte, José M. B.. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil. Fundación Oswaldo Cruz; BrasilFil: Bernard, Enrico. Universidade Federal de Pernambuco; BrasilFil: Agostini, Ilaria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Lamattina, Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina. Ministerio de Salud de la Nación; ArgentinaFil: Vanderhoeven, Ezequiel Andres. Ministerio de Salud de la Nación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentin

Influence of the LILRA3 Deletion on Multiple Sclerosis Risk : Original Data and Meta-Analysis

Altres ajuts: Junta de Andalucía (JA)- Fondos Europeos de Desarrollo Regional (FEDER) (grant number CTS2704 to FM).Multiple sclerosis (MS) is a neurodegenerative, autoimmune disease of the central nervous system. Genome-wide association studies (GWAS) have identified over hundred polymorphisms with modest individual effects in MS susceptibility and they have confirmed the main individual effect of the Major Histocompatibility Complex. Additional risk loci with immunologically relevant genes were found significantly overrepresented. Nonetheless, it is accepted that most of the genetic architecture underlying susceptibility to the disease remains to be defined. Candidate association studies of the leukocyte immunoglobulin-like receptor LILRA3 gene in MS have been repeatedly reported with inconsistent results. In an attempt to shed some light on these controversial findings, a combined analysis was performed including the previously published datasets and three newly genotyped cohorts. Both wild-type and deleted LILRA3 alleles were discriminated in a single-tube PCR amplification and the resulting products were visualized by their different electrophoretic mobilities. Overall, this meta-analysis involved 3200 MS patients and 3069 matched healthy controls and it did not evidence significant association of the LILRA3 deletion [carriers of LILRA3 deletion: p = 0.25, OR (95% CI) = 1.07 (0.95-1.19)], even after stratification by gender and the HLA-DRB1*15 : 01 risk allele

Identification of the Immunological Changes Appearing in the CSF During the Early Immunosenescence Process Occurring in Multiple Sclerosis

Patients with multiple sclerosis (MS) suffer with age an early immunosenescence process, which influence the treatment response and increase the risk of infections. We explored whether lipid-specific oligoclonal IgM bands (LS-OCMB) associated with highly inflammatory MS modify the immunological profile induced by age in MS. This cross-sectional study included 263 MS patients who were classified according to the presence (M+, n=72) and absence (M-, n=191) of LS-OCMB. CSF cellular subsets and molecules implicated in immunosenescence were explored. In M- patients, aging induced remarkable decreases in absolute CSF counts of CD4+ and CD8+ T lymphocytes, including Th1 and Th17 cells, and of B cells, including those secreting TNF-alpha. It also increased serum anti-CMV IgG antibody titers (indicative of immunosenescence) and CSF CHI3L1 levels (related to astrocyte activation). In contrast, M+ patients showed an age-associated increase of TIM-3 (a biomarker of T cell exhaustion) and increased values of CHI3L1, independently of age. Finally, in both groups, age induced an increase in CSF levels of PD-L1 (an inductor of T cell tolerance) and activin A (part of the senescence-associated secretome and related to inflammaging). These changes were independent of the disease duration. Finally, this resulted in augmented disability. In summary, all MS patients experience with age a modest induction of T-cell tolerance and an activation of the innate immunity, resulting in increased disability. Additionally, M- patients show clear decreases in CSF lymphocyte numbers, which could increase the risk of infections. Thus, age and immunological status are important for tailoring effective therapies in MS.This work was supported by grants FIS-PI15/00513, FIS-PI18/00572 and RD16/0015/0001 from the Instituto de Salud Carlos III. Ministerio de Ciencia e Innovación, Spain and FEDER: "Una manera de hacer Europa"

Kappa free light chains is a valid tool in the diagnostics of MS : A large multicenter study

To validate kappa free light chain (KFLC) and lambda free light chain (LFLC) indices as a diagnostic biomarker in multiple sclerosis (MS). We performed a multicenter study including 745 patients from 18 centers (219 controls and 526 clinically isolated syndrome (CIS)/MS patients) with a known oligoclonal IgG band (OCB) status. KFLC and LFLC were measured in paired cerebrospinal fluid (CSF) and serum samples. Gaussian mixture modeling was used to define a cut-off for KFLC and LFLC indexes. The cut-off for the KFLC index was 6.6 (95% confidence interval (CI) = 5.2-138.1). The cut-off for the LFLC index was 6.9 (95% CI = 4.5-22.2). For CIS/MS patients, sensitivity of the KFLC index (0.88; 95% CI = 0.85-0.90) was higher than OCB (0.82; 95%CI = 0.79-0.85; p < 0.001), but specificity (0.83; 95% CI = 0.78-0.88) was lower (OCB = 0.92; 95% CI = 0.89-0.96; p < 0.001). Both sensitivity and specificity for the LFLC index were lower than OCB. Compared with OCB, the KFLC index is more sensitive but less specific for diagnosing CIS/MS. Lacking an elevated KFLC index is more powerful for excluding MS compared with OCB but the latter is more important for ruling in a diagnosis of CIS/MS

Kappa free light chains is a valid tool in the diagnostics of MS: A large multicenter study

Objective: To validate kappa free light chain (KFLC) and lambda free light chain (LFLC) indices as a diagnostic biomarker in multiple sclerosis (MS). Methods: We performed a multicenter study including 745 patients from 18 centers (219 controls and 526 clinically isolated syndrome (CIS)/MS patients) with a known oligoclonal IgG band (OCB) status. KFLC and LFLC were measured in paired cerebrospinal fluid (CSF) and serum samples. Gaussian mix- ture modeling was used to define a cut-off for KFLC and LFLC indexes. Results: The cut-off for the KFLC index was 6.6 (95% confidence interval (CI) = 5.2-138.1). The cut-off for the LFLC index was 6.9 (95% CI=4.5-22.2). For CIS/MS patients, sensitivity of the KFLC index (0.88; 95% CI = 0.85-0.90) was higher than OCB (0.82; 95%CI = 0.79-0.85; p < 0.001), but specificity (0.83; 95% CI = 0.78-0.88) was lower (OCB = 0.92; 95% CI = 0.89-0.96; p < 0.001). Both sensitivity and specificity for the LFLC index were lower than OCB. Conclusion: Compared with OCB, the KFLC index is more sensitive but less specific for diagnosing CIS/MS. Lacking an elevated KFLC index is more powerful for excluding MS compared with OCB but the latter is more important for ruling in a diagnosis of CIS/MS

Postresectional lung injury in thoracic surgery pre and intraoperative risk factors: a retrospective clinical study of a hundred forty-three cases

<p>Abstract</p> <p>Introduction</p> <p>Acute respiratory dysfunction syndrome (ARDS), defined as acute hypoxemia accompanied by radiographic pulmonary infiltrates without a clearly identifiable cause, is a major cause of morbidity and mortality after pulmonary resection. The aim of the study was to determine the pre and intraoperative factors associated with ARDS after pulmonary resection retrospectively.</p> <p>Methods</p> <p>Patients undergoing elective pulmonary resection at Adnan Menderes University Medical Faculty Thoracic Surgery Department from January 2005 to February 2010 were included in this retrospective study. The authors collected data on demographics, relevant co-morbidities, the American Society of Anesthesiologists (ASA) Physical Status classification score, pulmonary function tests, type of operation, duration of surgery and intraoperative fluid administration (fluid therapy and blood products). The primary outcome measure was postoperative ARDS, defined as the need for continuation of mechanical ventilation for greater than 48-hours postoperatively or the need for reinstitution of mechanical ventilation after extubation. Statistical analysis was performed with Fisher exact test for categorical variables and logistic regression analysis for continuous variables.</p> <p>Results</p> <p>Of one hundred forty-three pulmonary resection patients, 11 (7.5%) developed postoperative ARDS. Alcohol abuse (p = 0.01, OR = 39.6), ASA score (p = 0.001, OR: 1257.3), resection type (p = 0.032, OR = 28.6) and fresh frozen plasma (FFP)(p = 0.027, OR = 1.4) were the factors found to be statistically significant.</p> <p>Conclusion</p> <p>In the light of the current study, lung injury after lung resection has a high mortality. Preoperative and postoperative risk factor were significant predictors of postoperative lung injury.</p