11 research outputs found

    Author Correction: AHR is a Zika virus host factor and a candidate target for antiviral therapy

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    Fil: Giovannoni, Federico. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Laboratorio de Estrategias Antivirales; Argentina. CONICET-Instituto de Química Biológica; Argentina.Fil: Bosch, Irene. Massachusetts Institute of Technology. Institute for Medical Engineering and Science; Estados Unidos. Mount Sinai School of Medicine. Department of Medicine; Estados Unidos.Fil: Manganeli Polonio, Carolina. University of São Paulo. Immunology Department-ICB IV. Neuroimmune Interactions Laboratory; Brasil. University of São Paulo. Scientific Platform Pasteur-USP; Brasil.Fil: Torti, María F. University of São Paulo. Immunology Department-ICB IV. Neuroimmune Interactions Laboratory; Brasil. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Laboratorio de Estrategias Antivirales; Argentina. CONICET-Instituto de Química Biológica; Argentina.Fil: Wheeler, Michael A. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Li, Zhaorong. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Romorini, Leonardo. Fleni. Laboratorio de Investigación Aplicada a las Neurociencias; Argentina.Fil: Rodríguez Varela, María Soledad. Fleni. Laboratorio de Investigación Aplicada a las Neurociencias; Argentina.Fil: Rothhammer, Veit. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Barroso, Andreia. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Tjon, Emily C. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Sanmarco, Liliana M. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Takenaka, Maisa C. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Sadegh Modaresi, Seyed Mohamad. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Gutiérrez-Vázquez, Cristina. Harvard Medical School. Brigham and Women's Hospital. Ann Romney Center for Neurologic Diseases; Estados Unidos.Fil: Ghabdan Zanluqui, Nágela. University of São Paulo. Scientific Platform Pasteur-USP; Brasil. University of São Paulo. School of Medicine. Immunopathology and Allergy Post Graduate Program; Brasil.Fil: Barreto Dos Santos, Nilton. University of São Paulo. Institute of Biomedical Science. Department of Pharmacology; Brasil.Fil: Demarchi Munhoz, Carolina. University of São Paulo. Institute of Biomedical Science. Department of Pharmacology; Brasil.Fil: Wang, Zhongyan. Boston University School of Public Health. Dept. of Environmental Health; Estados Unidos.Fil: Damonte, Elsa B. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica. Laboratorio de Estrategias Antivirales; Argentina. CONICET-Instituto de Química Biológica; Argentina

    Recruitment of the multiple sclerosis cohort within the European Mobilise-D clinical validation study—lessons learnt, baseline demographics and clinical characteristics

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    \ua9 The Author(s) 2026. Background: Multiple sclerosis (MS) is a common cause of disability in working age adults. Current clinical assessments are inadequate at disability assessment or predicting clinically relevant outcomes. Loss of mobility is an important functional disability to people with MS. Mobilise-D aims to develop, validate, and implement a digital mobility solution which measures unsupervised mobility performance across several chronic conditions, including MS, using a single wearable device. Methods: Six hundred two adults with MS, an Expanded Disability Status Scale (EDSS) score of 3.0–6.5, documented disability worsening over the previous 2 years and a 30-day freedom from relapses, were recruited across four European centres. Results: Of 1416 invited, 602 participants (42%) were recruited. Primary recruitment sources were clinicians (42%) and local registries (42%). Among 616 who declined screening, the main reasons were a lack of interest (44%), the time commitment (25%) or the travel involved (13%). Participants had a mean age of 52 years; 64% were female, with a median EDSS score of 5.0. Of those, 56% had relapsing-remitting MS, 33% secondary progressive MS and 10% primary progressive MS. Falls occurred in 58% of participants in the 12 months prior to recruitment. Of those recruited, 556 (93%) participants had valid mobility data recorded. Conclusions: The longitudinal collection of clinical and unsupervised mobility assessments will provide a comprehensive dataset, allowing for the determination of digital mobility assessments’ construct validity, predictive capacity, responsiveness, and clinical meaningfulness. Novel insights into real-world mobility that describe both walking activity and gait outcomes will be gained. Trial registration: The study was registered at the ISRCTN registry on 12/10/2020, titled “Clinical validation of a mobility monitor to measure and predict health outcomes” (ISRCTN Number: 12051706)

    Update on the diagnosis and treatment of neuromyelitis optica spectrum disorders (NMOSD) – revised recommendations of the Neuromyelitis Optica Study Group (NEMOS). Part II: Attack therapy and long-term management

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    International audienceThis manuscript presents practical recommendations for managing acute attacks and implementing preventive immunotherapies for neuromyelitis optica spectrum disorders (NMOSD), a rare autoimmune disease that causes severe inflammation in the central nervous system (CNS), primarily affecting the optic nerves, spinal cord, and brainstem. The pillars of NMOSD therapy are attack treatment and attack prevention to minimize the accrual of neurological disability. Aquaporin-4 immunoglobulin G antibodies (AQP4-IgG) are a diagnostic marker of the disease and play a significant role in its pathogenicity. Recent advances in understanding NMOSD have led to the development of new therapies and the completion of randomized controlled trials. Four preventive immunotherapies have now been approved for AQP4-IgG-positive NMOSD in many regions of the world: eculizumab, ravulizumab - most recently-, inebilizumab, and satralizumab. These new drugs may potentially substitute rituximab and classical immunosuppressive therapies, which were as yet the mainstay of treatment for both, AQP4-IgG-positive and -negative NMOSD. Here, the Neuromyelitis Optica Study Group (NEMOS) provides an overview of the current state of knowledge on NMOSD treatments and offers statements and practical recommendations on the therapy management and use of all available immunotherapies for this disease. Unmet needs and AQP4-IgG-negative NMOSD are also discussed. The recommendations were developed using a Delphi-based consensus method among the core author group and at expert discussions at NEMOS meetings

    Correction to: Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device (Scientific Reports, (2024), 14, 1, (1754), 10.1038/s41598-024-51766-5)

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    \ua9 The Author(s) 2024.Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-024-51766-5, published online 19 January 2024 The original version of this Article contained an error in Figure 7 where an incorrect reference was cited for one of the recommended algorithms for Gait Speed Detection (GSD). The original Figure 7 and accompanying legend appear below. (Figure presented.) Overview over the diferent algorithmic steps of the analytical pipeline with short explanations of the intermediate and fnal outputs of each of the algorithmic blocks; gait sequence detection (GSD), initial contact detection (ICD), cadence estimation (CAD) and stride length estimation (SL). Te algorithm column indicates the used algorithms for the two pipelines P1 (HA, COPD, CHF). (MS, PD, PFF) and P2 (MS, PD, PFF) Short citations for the algorithms are provided below the fgure. For more details see Table 1 in26. In addition, the Supplementary Information 1 file published with this Article contained errors in Tables 1 and 2. The Intraclass Correlation Coefficients (ICCs) for walking speed were incorrectly reported instead of the correct ICC values for stride length and cadence. The original Supplementary Information 1 file is provided below. The original Article and the Supplementary Information 1 file that accompanies the original Article have been corrected

    Cutaneous malignant melanoma: Update on diagnostic and prognostic biomarkers

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    The incidence of cutaneous malignant melanoma has rapidly increased in recent years in all parts of the world, and melanoma is a leading cause of cancer death. As even relatively small melanomas may have metastatic potential, accurate assessment of progression is critical. Although diagnosis of cutaneous malignant melanoma is usually based on histopathologic criteria, these criteria may at times be inadequate in differentiating melanoma from certain types of benign nevi. As for prognosis, tumor (Breslow) thickness, mitotic rate, and ulceration have been considered the most important prognostic indicators among histopathologic criteria. However, there are cases of thin primary melanomas that have ultimately developed metastases despite complete excision. Given this, an accurate assessment of melanoma progression is critical, and development of molecular biomarkers that identify high-risk melanoma in its early phase is urgently needed. Large-scale genomic profiling has identified considerable heterogeneity in melanoma and suggests subgrouping of tumors by patterns of gene expression and mutation will ultimately be essential to accurate staging. This subgrouping in turn may allow for more targeted therapy. In this review, we aim to provide an update on the most promising new biomarkers that may help in the identification and prognostication of melanoma. © 2014 Lippincott Williams and Wilkins.Al Dhaybi R, 2011, J AM ACAD DERMATOL, V65, P357, DOI 10.1016-j.jaad.2010.07.031; Alonso SR, 2004, AM J PATHOL, V164, P193, DOI 10.1016-S0002-9440(10)63110-0; Alonso SR, 2007, CANCER RES, V67, P3450, DOI 10.1158-0008-5472.CAN-06-3481; Arozarena I, 2011, ONCOGENE, V30, P4531, DOI 10.1038-onc.2011.162; Bachmann IM, 2005, CLIN CANCER RES, V11, P8606, DOI 10.1158-1078-0432.CCR-05-0011; Balch CM, 2009, J CLIN ONCOL, V27, P6199, DOI 10.1200-JCO.2009.23.4799; Balch CM, 2001, J CLIN ONCOL, V19, P3622; BARNHILL RL, 1993, SEMIN DIAGN PATHOL, V10, P47; Bastian BC, 2000, AM J PATHOL, V157, P967, DOI 10.1016-S0002-9440(10)64609-3; Bastian BC, 2003, AM J PATHOL, V163, P1765, DOI 10.1016-S0002-9440(10)63536-5; Bauer J, 2006, DERMATOL THER, V19, P40, DOI 10.1111-j.1529-8019.2005.00055.x; Berger AJ, 2003, CANCER RES, V63, P8103; Berger AJ, 2005, CANCER RES, V65, P11185, DOI 10.1158-0008-5472.CAN-05-2300; Bonazzi VF, 2012, MELANOMA RES, V22, P101, DOI 10.1097-CMR.0b013e32834f6fbb; Bullani RR, 2001, J INVEST DERMATOL, V117, P360, DOI 10.1046-j.0022-202x.2001.01418.x; Carlson JA, 2009, CLIN DERMATOL, V27, P75, DOI 10.1016-j.clindermatol.2008.09.007; Carlson JA, 2005, J AM ACAD DERMATOL, V52, P743, DOI 10.1016-j.jaad.2004.08.034; Casper DJ, 2010, AM J DERMATOPATH, V32, P650, DOI 10.1097-DAD.0b013e3181cf7cc1; Cesinaro AM, 2012, PATHOLOGY, V44, P313, DOI 10.1097-PAT.0b013e328353a0ff; Chen GD, 2011, CANCER EPIDEM BIOMAR, V20, P2212, DOI 10.1158-1055-9965.EPI-11-0472; Chorny JA, 2003, MODERN PATHOL, V16, P525, DOI 10.1097-01.MP.0000072747.08404.38; Cochran AJ, 2009, ARCH DERMATOL, V145, P1176, DOI 10.1001-archdermatol.2009.230; Colman H, 2006, AM J SURG PATHOL, V30, P657, DOI 10.1097-01.pas.0000202048.28203.25; Conway C, 2009, CLIN CANCER RES, V15, P6939, DOI 10.1158-1078-0432.CCR-09-1631; Da Forno PD, 2009, BRIT J DERMATOL, V161, P364, DOI 10.1111-j.1365-2133.2009.09181.x; Da Forno PD, 2008, BRIT J DERMATOL, V158, P4, DOI 10.1111-j.1365-2133.2007.08207.x; Dai DL, 2005, J CLIN ONCOL, V23, P1473, DOI 10.1200-JCO.2005.07.168; Dalton Scott R, 2010, Am J Surg Pathol, V34, P231, DOI 10.1097-PAS.0b013e3181c805c4; Deeds J, 2000, HUM PATHOL, V31, P1346, DOI 10.1016-S0046-8177(00)80003-9; DiVito KA, 2004, CANCER RES, V64, P8773, DOI 10.1158-0008-5472.CAN-04-1387; Duncan LM, 2001, J CLIN ONCOL, V19, P568; Ekmekcioglu S, 2006, INT J CANCER, V119, P861, DOI 10.1002-ijc.21767; Elwood J. Mark, 1994, Current Opinion in Oncology, V6, P179, DOI 10.1097-00001622-199403000-00011; Emley A, 2010, J CUTAN PATHOL, V37, P344, DOI 10.1111-j.1600-0560.2009.01433.x; Fan T, 2011, MOL CANCER RES, V9, P418, DOI 10.1158-1541-7786.MCR-10-0511; Ferrier CM, 2000, BRIT J CANCER, V83, P1351, DOI 10.1054-bjoc.2000.1460; Florenes VA, 2001, J PATHOL, V195, P530; Florenes VA, 2004, AM J CLIN PATHOL, V122, P412, DOI 10.1309-CHFHEYAT44WWP7J3; Frahm SO, 2001, HUM PATHOL, V32, P1376, DOI 10.1053-hupa.2001.29658; Fullen DR, 2006, MODERN PATHOL, V19, P1324, DOI 10.1038-modpathol.3800653; Gaiser T, 2010, MODERN PATHOL, V23, P413, DOI 10.1038-modpathol.2009.177; Gammon B, 2011, J CUTAN PATHOL, V38, P335, DOI 10.1111-j.1600-0560.2010.01667.x; Gammon B, 2012, AM J SURG PATHOL, V36, P81, DOI 10.1097-PAS.0b013e31822d5ff8; Gerami P, 2009, AM J SURG PATHOL, V33, P1146, DOI 10.1097-PAS.0b013e3181a1ef36; Gerami P, 2012, AM J SURG PATHOL, V36, P808, DOI 10.1097-PAS.0b013e31824b1efd; Gerami P, 2011, J CUTAN PATHOL, V38, P329, DOI 10.1111-j.1600-0560.2010.01666.x; Giatromanolaki A, 2003, MELANOMA RES, V13, P493, DOI 10.1097-01.cmr.0000056268.56735.4c; Giehl K A, 2007, J Cutan Pathol, V34, P7, DOI 10.1111-j.1600-0560.2006.00569.x; Gill M, 2004, CANCER, V101, P2636, DOI 10.1002-cncr.20680; Gimotty PA, 2005, J CLIN ONCOL, V23, P8048, DOI 10.1200-JCO.2005.02.0735; Gimotty PA, 2007, J CLIN ONCOL, V25, P1129, DOI 10.1200-JCO.2006.08.1463; Hammock L, 2006, J CUTAN PATHOL, V33, P599, DOI 10.1111-j.1600-0560.2006.00501.x; Hao HY, 2007, BMC CANCER, V7, DOI 10.1186-1471-2407-7-24; Haqq C, 2005, P NATL ACAD SCI USA, V102, P6092, DOI 10.1073-pnas.0501564102; Hazan C, 2002, CANCER, V95, P634, DOI 10.1002-cncr.10685; Healy E, 1996, CANCER RES, V56, P589; Herman JG, 2003, NEW ENGL J MED, V349, P2042, DOI 10.1056-NEJMra023075; Hilliard NJ, 2009, J CUTAN PATHOL, V36, P753, DOI 10.1111-j.1600-0560.2008.01154.x; Hoshimoto S, 2012, J INVEST DERMATOL, V132, P1689, DOI 10.1038-jid.2012.36; Howell PM, 2009, CANCER CONTROL, V16, P200; Ikenberg K, 2012, J CUTAN PATHOL, V39, P324, DOI 10.1111-j.1600-0560.2011.01858.x; Ilmonen S, 2004, HISTOPATHOLOGY, V45, P405, DOI 10.1111-j.1365-2559.2004.01976.x; Jakob JA, 2012, CANCER-AM CANCER SOC, V118, P4014, DOI 10.1002-cncr.26724; Jewell R, 2010, CLIN CANCER RES, V16, P5211, DOI 10.1158-1078-0432.CCR-10-1521; Jonsson L, 2011, J TRANSL MED, V9, DOI 10.1186-1479-5876-9-114; Kageshita T, 2001, BRIT J DERMATOL, V145, P210, DOI 10.1046-j.1365-2133.2001.04336.x; KanterLewensohn L, 1997, MODERN PATHOL, V10, P917; Karim RZ, 2009, INT J SURG PATHOL, V17, P361, DOI 10.1177-1066896909336177; Karjalainen JM, 1998, J CLIN ONCOL, V16, P3584; Karjalainen JM, 2000, AM J PATHOL, V157, P957, DOI 10.1016-S0002-9440(10)64608-1; Karst AM, 2005, ONCOGENE, V24, P1111, DOI 10.1038-sj.onc.1208374; Kashani-Sabet M, 2009, P NATL ACAD SCI USA, V106, P6268, DOI 10.1073-pnas.0901185106; Kauffmann A, 2008, ONCOGENE, V27, P565, DOI 10.1038-sj.onc.1210700; Korabiowska M, 2002, HISTOL HISTOPATHOL, V17, P805; Korabiowska M, 1997, ANTICANCER RES, V17, P3697; Kouzarides T, 2007, CELL, V128, P693, DOI 10.1016-j.cell.2007.02.005; Kubicki L, 2006, MELANOMA RES, V16, P435; Ladstein RG, 2012, J INVEST DERMATOL, V132, P1247, DOI 10.1038-jid.2011.464; Lee DA, 2006, CANCER, V106, P907, DOI 10.1002-cncr.216868; Leiter U, 2008, ADV EXP MED BIOL, V624, P89, DOI 10.1007-978-0-387-77574-6_8; Li LXL, 2000, AM J DERMATOPATH, V22, P489, DOI 10.1097-00000372-200012000-00002; Li Q, 2004, J CUTAN PATHOL, V31, P633, DOI 10.1111-j.0303-6987.2004.00243.x; Luftl M, 2004, BRIT J DERMATOL, V151, P1213, DOI 10.1111-j.1365-2133.2004.06260.x; Magro CM, 2006, MODERN PATHOL, V19, pS41, DOI 10.1038-modpathol.3800516; Mangini J, 2002, AM J DERMATOPATH, V24, P270, DOI 10.1097-01.DAD.0000014909.27915.1A; Mason A, 2012, J CUTAN PATHOL, V39, P1064; Moreau S, 2012, ANN SURG ONCOL, V19, P4314, DOI 10.1245-s10434-012-2457-5; Mueller DW, 2009, J INVEST DERMATOL, V129, P1740, DOI 10.1038-jid.2008.452; Nguyen T, 2011, EPIGENETICS-US, V6, P388; Nielsen PS, 2013, MODERN PATHOL, V26, P404, DOI 10.1038-modpathol.2012.188; NIEMANN TH, 1993, AM J DERMATOPATH, V15, P441, DOI 10.1097-00000372-199310000-00005; Niezabitowski A, 1999, J SURG ONCOL, V70, P150, DOI 10.1002-(SICI)1096-9098(199903)70:3150::AID-JSO23.0.CO;2-Z; Nishizawa A, 2005, CANCER, V103, P1693, DOI 10.1002-cncr.20984; Nygren AOH, 2005, NUCLEIC ACIDS RES, V33, DOI 10.1093-nar-gni127; Ohsie SJ, 2008, J CUTAN PATHOL, V35, P433, DOI 10.1111-j.1600-0560.2007.00891.x; Onken MD, 2007, CLIN CANCER RES, V13, P2923, DOI 10.1158-1078-0432.CCR-06-2383; Ostmeier H, 2001, BRIT J DERMATOL, V145, P203, DOI 10.1046-j.1365-2133.2001.04335.x; Pacifico MD, 2005, PLAST RECONSTR SURG, V115, P367, DOI 10.1097-01.PRS.0000148417.86768.C9; Palmedo G, 2004, J CUTAN PATHOL, V31, P266, DOI 10.1111-j.0303-6987.2003.00179.x; Pearl RA, 2008, J PLAST RECONSTR AES, V61, P265, DOI 10.1016-j.bjps.2007.04.010; Philippidou D, 2010, CANCER RES, V70, P4163, DOI 10.1158-0008-5472.CAN-09-4512; Piras F, 2007, HISTOPATHOLOGY, V50, P835, DOI 10.1111-j.1365-2559.2007.02695.x; Polsky D, 2002, J NATL CANCER I, V94, P1803; Pouryazdanparast P, 2011, AM J SURG PATHOL, V35, P1405, DOI 10.1097-PAS.0b013e31822678d2; Pouryazdanparast P, 2009, AM J SURG PATHOL, V33, P1396, DOI 10.1097-PAS.0b013e3181a92cbc; Rangel J, 2008, AM J SURG PATHOL, V32, P1207, DOI 10.1097-PAS.0b013e31816fd53c; Rangel J, 2008, CANCER, V112, P144, DOI 10.1002-cncr.23147; Rangel J, 2006, J CLIN ONCOL, V24, P4565, DOI 10.1200-JCO.2006.07.3833; Ribalta T, 2004, AM J SURG PATHOL, V28, P1532, DOI 10.1097-01.pas.0000141389.06925.d5; Ribe A, 2003, MODERN PATHOL, V16, P505, DOI 10.1097-01.MP.0000071128.67149.FD; Richards HW, 2009, PIGM CELL MELANOMA R, V22, P14, DOI 10.1111-j.1755-148X.2008.00534.x; Robertson GP, 2005, CANCER METAST REV, V24, P273, DOI 10.1007-s10555-005-1577-9; Rothberg BEG, 2009, JNCI-J NATL CANCER I, V101, P452, DOI 10.1093-jnci-djp038; Rothhammer T, 2007, PIGM CELL RES, V20, P92, DOI 10.1111-j.600-0749.2007.00367.x; Roush S, 2008, TRENDS CELL BIOL, V18, P505, DOI 10.1016-j.tcb.2008.07.007; Ardekani GS, 2012, PLOS ONE, V7, DOI 10.1371-journal.pone.0047054; Salti GI, 2000, CANCER RES, V60, P5012; Scala S, 2005, CLIN CANCER RES, V11, P1835, DOI 10.1158-1078-0432.CCR-04-1887; Schinke C, 2010, MELANOMA RES, V20, P253, DOI 10.1097-CMR.0b013e328338a35a; Scholzen T, 2000, J CELL PHYSIOL, V182, P311, DOI 10.1002-(SICI)1097-4652(200003)182:3311::AID-JCP13.0.CO;2-9; Schouten JP, 2002, NUCLEIC ACIDS RES, V30, DOI 10.1093-nar-gnf056; Schultz J, 2008, CELL RES, V18, P549, DOI 10.1038-cr.2008.45; Sigalotti L, 2010, J TRANSL MED, V8, DOI 10.1186-1479-5876-8-56; Slipicevic A, 2005, AM J CLIN PATHOL, V124, P528, DOI 10.1309-YT58WWMTA6YR1PRV; Soltani MH, 2005, AM J PATHOL, V166, P1841, DOI 10.1016-S0002-9440(10)62493-5; Sparrow LE, 1998, AM J DERMATOPATH, V20, P12, DOI 10.1097-00000372-199802000-00003; Stefanaki C, 2008, J CUTAN PATHOL, V35, P799, DOI 10.1111-j.1600-0560.2007.00912.x; Straume O, 2000, CLIN CANCER RES, V6, P1845; Straume O, 2002, AM J PATHOL, V160, P1009, DOI 10.1016-S0002-9440(10)64922-X; Takata M, 2005, J DERMATOL SCI, V40, P51, DOI 10.1016-j.jdermsci.2005.06.009; Takata M, 2006, J DERMATOL SCI, V43, P1, DOI 10.1016-j.jdermsci.2006.05.002; Takata M, 2007, BRIT J DERMATOL, V156, P1287, DOI 10.1111-j.1365-2133.2007.07924.x; Talantov D, 2005, CLIN CANCER RES, V11, P7234, DOI 10.1158-1078-0432.CCR-05-0683; Talve L, 1997, INT J CANCER, V74, P255, DOI 10.1002-(SICI)1097-0215(19970620)74:3255::AID-IJC43.0.CO;2-Y; Thies A, 2002, EUR J CANCER, V38, P1708, DOI 10.1016-S0959-8049(02)00105-3; Thies A, 2002, J CLIN ONCOL, V20, P2530, DOI 10.1200-JCO.2002.05.033; Thies A, 2004, J PATHOL, V203, P933, DOI 10.1002-path.1595; Tran TA, 1998, HUM PATHOL, V29, P1085, DOI 10.1016-S0046-8177(98)90418-X; Trolet J, 2009, INVEST OPHTH VIS SCI, V50, P2572, DOI 10.1167-iovs.08-2296; Vaisanen A, 1998, J PATHOL, V186, P51; Vaisanen AH, 2008, HUM PATHOL, V39, P377, DOI 10.1016-j.humpath.2007.06.021; vandenOord JJ, 1996, AM J PATHOL, V149, P1953; Van den Oord JJ, 1998, BRIT J DERMATOL, V138, P615; van Dijk MC, 2005, DIAGN MOL PATHOL, V14, P9, DOI 10.1097-01.pas.0000146701.98954.47; van Dijk MCRF, 2005, AM J SURG PATHOL, V29, P1145, DOI 10.1097-01.pas.0000157749.18591.9e; VINCENT M, 1984, DEV BIOL, V103, P468, DOI 10.1016-0012-1606(84)90334-8; Weinlich G, 2007, J EUR ACAD DERMATOL, V21, P669, DOI 10.1111-j.1468-3083.2006.02051.x; Weinlich G, 2006, BRIT J CANCER, V94, P835, DOI 10.1038-sj.bjc.6603028; White JS, 2006, CANCER GENET CYTOGEN, V170, P29, DOI 10.1016-j.cancergencyto.2006.05.004; Winnepenninckx VR, 2006, J NATL CANCER I, V98, P472, DOI 10.1093-jnci-djj103; Zhang XD, 2004, MOL CANCER THER, V3, P425; Zhang ZZ, 2011, CANCER-AM CANCER SOC, V117, P2719, DOI 10.1002-cncr.25838; Zhuang LQ, 2007, MODERN PATHOL, V20, P416, DOI 10.1038-modpathol.38007500

    The Transcriptomic and Genomic Analysis of Lamin A/C Expression in the Colon and in Colorectal Cancer

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    Lamins A and C, also known as A-type lamins, are type V nuclear intermediate filament proteins which form an interlacing meshwork of filaments subjacent to the inner nuclear membrane termed the nuclear lamina. A-type lamins have been implicated in DNA replication, gene transcription regulation, apoptosis, regulation of growth promoters and nuclear migration. Traditionally, expression of A-type lamins has been associated with differentiated cells. As such, mutations in A-type lamins have been associated with a diverse range of genetic diseases, including premature ageing syndromes and with increased proliferation, especially in tumours. In colorectal cancer, expression of A-type lamins, have been shown to impart an adverse prognosis. In order to understand the underlying biological processes responsible for this adverse outcome in patients with colorectal cancer, I sought to clarify the expression profile of A-type lamins and their binding partners in normal colonic/rectal mucosa, prior to investigating the expression of A-type lamins in colorectal cancers. I used fresh tissue specimens obtained from patients with colorectal cancer for my experiments. A unique finding was the expression of lamin A in the putative stem cell niche of colonic / rectal mucosal crypts. Further studies in the form of a microarray analysis, revealed a very complex picture of up regulation involving various signalling cascades in the cancer samples expressing A-type lamins. There was no evidence to suggest a direct involvement of A-type lamins influencing the Wnt signalling cascade, however, direct involvement of other signalling cascades, such as the IGF signalling cascade, Shh signalling cascade and TGF-β signalling cascades were noted. These signalling cascades were known to influence the Wnt signalling cascades and hence could play a crucial role in the pathogenesis of colorectal cancers expressing A-type lamins. In addition to these important signalling cascades, other key genes involved in apoptosis, growth promoters, cell adhesion, stem cell regulation, oncogenes and tumour suppression, were noted to have a unique expression profile in the cancer sample expressing A-type lamins, not observed in the cancer sample lacking A-type lamin expression. These observations were suggestive of A-type lamins having a diverse range of actions via, as yet, undefined pathways. It would appear that A-type lamins were imparting a more motile, less adherent phenotype with stem cell like features in colorectal cancers expressing A-type lamins. This could explain the observed poor prognosis of patients with colorectal cancers expressing A-type lamins. Creatine kinase brain (CKB), was also identified as an additional, potential, prognostic indicator in the Duke’s B group of patients with colorectal cancer expressing A-type lamins. This potential marker, in conjunction with A-type lamin expression could be used to identify a sub group of Duke’s B patients at high risk. Whether adjuvant therapy in this group would help improve their long term survival is unknown since no study has been done to assess this

    Nonrandom Factors In Modern Human Morphological Diversification: A Study Of Craniofacial Variation In Southern South American Populations

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    The causes of craniofacial variation among human populations have been the subject of controversy. In this work, we studied aboriginal populations from southern South America, the last continental region peopled by humans and with a wide range of ecological conditions. Because of these characteristics, southern South America provides a unique opportunity to study the relative importance of random and nonrandom factors in human diversification. Previous craniometric studies recognized remarkable differences among populations from this region, usually resorting to random factors as the main explanation. In contrast, here we suggest, using tests based on quantitative genetic models, that: (1) the rate of craniofacial divergence among these populations is too high and (2) the patterns of variation within and between populations are too different to be explained by genetic drift alone. In addition, the among-sample craniofacial variation is correlated with climate and diet but not with mtDNA variation. We suggest that the influence of nonrandom factors (e.g., plasticity, selection) on human craniofacial diversification in regions with large ecological variation is more important than generally acknowledged and capable to generate large craniofacial divergence in a short period of time. These results bring nonrandom factors into focus for the interpretation of human craniofacial variation. © 2009 The Author(s).634978993Ackermann, R.R., Cheverud, J.M., Discerning evolutionary processes in patterns of tamarin (genus Saguinus) craniofacial variation (2002) Am. J. Phys. Anthropol., 117, pp. 260-271Ackermann, R.R., Cheverud, J.M., Detecting genetic drift versus selection in human evolution (2004) Proc. Natl. Acad. Sci. USA, 101, pp. 17946-17951Adams, D.C., Rohlf, F.J., Slice, D.E., Geometric morphometrics: Ten years of progress following the 'revolution.' (2004) Ital. J. Zool., 71, pp. 5-16Anderson, D.G., Gillam, J.C., Paleoindian interaction and mating networks: Reply to Moore and Moseley (2001) Am. Antiq., 66, pp. 530-535Barton, N.H., Briggs, D.E.G., Eisen, J.A., Goldstein, D.B., Patel, N.H., (2007) Evolution., , and. Cold Spring Harbor Laboratory Press, New YorkBeals, K.L., Smith, C.L., Dodd, S.M., Climate and the evolution of brachycephalization (1983) Am. J. Phys. Anthropol., 62, pp. 425-437Berberián, E.E., Nielsen, A.E., (2001) Historia Argentina Prehispánica., , and. Brujas, Córdoba, ArgentinaBernal, V., Procesos de diferenciación biológica entre poblaciones humanas del Holoceno tardío de Patagonia. Una aproximación desde la variación métrica dental (2008) Ph.D. Dissertation., , Universidad Nacional de La Plata, La Plata, ArgentinaBernal, V., Perez, S.I., Gonzalez, P.N., Variation and causal factors of craniofacial robusticity in Patagonian hunter-gatherers from the late Holocene (2006) Am. J. Hum. Biol., 18, pp. 748-765Binford, L.R., Constructing frames of reference (2000) An Analytical Method for Archaeological Theory Building Using Hunter-gatherer and Environmental Data Sets., , Univ. of California Press, Berkeley, CABookstein, F.L., Morphometric tools for landmark data (1991) Geometry and Biology., , Cambridge Univ. Press, CambridgeBookstein, F.L., Landmark methods for forms without landmarks: Localizing group differences in outline shape (1997) Med. Image Anal., 1, pp. 225-243Bookstein, F.L., Streissguth, A.P., Sampson, P.D., Connor, P.D., Barr, H.M., Corpus callosum shape and neuropsychological deficits in adult males with heavy fetal alcohol exposure (2002) Neuroimage, 15, pp. 233-251Borrero, L.A., The prehistoric exploration and colonization of Fuego-Patagonia (1999) J. World Prehistory, 13, pp. 321-355Brandt, M., Siegel, M.I., The effects of stress on cortical bone thickness in rodents (1978) Am. J. Phys. Anthropol., 49, pp. 31-34Buikstra, J., Ubelaker, D., (1994) Standards for Data Collection from Human Skeletal Remains, , and. Arkansas Archaeological Survey, Research Series 44, FayettevilleCadien, J., Harris, E., Jones, W., Mandarino, L., Biological lineages, skeletal populations and microevolution (1976) Yearb. Phys. Anthropol., 18, pp. 194-201Carroll, S.P., Hendry, A.P., Reznick, D.N., Fox, C.W., Evolution on ecological time-scales (2007) Funct. Ecol., 21, pp. 387-393Carson, E.A., Maximum likelihood estimation of human craniometric heritabilities (2006) Am. J. Phys. Anthropol., 131, pp. 169-180Cavalli-Sforza, L.L., Bodmer, W.F., (1971) The Genetics of Human Populations., , and. General Publishing Company, TorontoCavalli-Sforza, L.L., Menozzi, P., Piazza, A., (1994) The History and Geography of Human Genes., , and. Princeton Univ. Press, Princeton, NJCheverud, J.M., Phenotipic, genetic and environmental morphological integration in the cranium (1982) Evolution, 36, pp. 499-516Cheverud, J.M., A comparison of genetic and phenotypic correlations (1988) Evolution, 42, pp. 958-968Cheverud, J.M., Morphological integration in the saddle-back tamarin (Saguinus fuscicollis) cranium (1995) Am. Nat., 145, pp. 63-89Cheverud, J.M., The relationship between development and evolution through heritable variation (2007) Tinkering: The Microevolution of Development., pp. 55-65. , Pp. in. G. Bock. and. J. Goode, eds. John Wiley & Sons, Ltd., West Sussex, UKCurtis, N., Kupczik, K., O'Higgins, P., Moazen, M., Fagan, M., Predicting skull loading: Applying multibody dynamics analysis to a macaque skull (2008) Anat. Rec., 291, pp. 491-501Dejean, C.B., Lanata, J.L., Martino, L., Carnese, F.R., Osella, A., Demografía y distribución de haplogrupos mitocondriales durante la dispersión inicial en las Américas (2007) Revista Argentina de Antropología Biológica., 9, p. 51Fenner, J., Cross-cultural estimation of the human generation interval for use in genetics-based population divergence studies (2005) Am. J. Phys. Anthropol., 128, pp. 415-423Frisancho, A.R., (1996) Human Adaptation and Accommodation., , The Univ. of Michigan Press, Ann. Arbor, MIGarcía-Bour, J., Pérez-Pérez, A., Álvarez, S., Fernández, E., López-Parra, A.M., Arroyo-Pardo, E., Turbón, D., Early population differentiation in extinct aborigines from Tierra del Fuego-Patagonia: Ancient mtDNA sequences and Y-chromosome STR characterization (2004) Am. J. Phys. Anthropol., 123, pp. 361-370Gil, A., Shelnut, N., Neme, G., Tykot, R., Michieli, C., Isótopos estables y dieta humana en el centro oeste: Datos muestras de San Juan (2006) Revista Cazadores Y Recolectores del Cono Sur., 1, pp. 149-161Gower, J.C., Statistical methods of comparing different multivariate analyses of the same data (1971) Mathematics in the Archaeological and Historical Sciences., pp. 138-149. , Pp. in. F. R. Hodson, D. G. Kendall. and. P. Tautu, eds. Edinburgh Univ. Press, EdinburghHair, J.F., Tatham, R.L., Anderson, R.E., Black, W., (1998) Multivariate Data Analysis., , and. Prentice Hall, New YorkHallgrímsson, B.K., Willmore, C.D., Cooper, D.M.L., Craniofacial variability and modularity in macaques and mice (2004) J. Exp. Zool. (Mol. Dev. Evol.), 302, pp. 207-225Hallgrímsson, B., Lieberman, D.E., Liu, W., Hutchinson, A.F., Jirik, F.R., Epigenetic interactions and the structure of phenotypic variation in the cranium (2007) Evol. Dev., 9, pp. 76-91Hanken, J., Hall, B., (1993) The Skull., , and. Univ. of Chicago Press, ChicagoHarvati, K., Weaver, T.D., Human cranial anatomy and the differential preservation of population history and climate signatures (2006) Anat. Rec. Part a, 288, pp. 1225-1233Hernández, M., Lalueza Fox, C., García-Moro, C., Fueguian cranial morphology: The adaptation to a cold, harsh environment (1997) Am. J. Phys. Anthropol., 103, pp. 103-117Hendry, A.P., Kinnison, M.T., The pace of modern life: Measuring rates of contemporary microevolution (1999) Evolution, 53, pp. 1637-1653Holliday, T.W., Body proportions in Late Pleistocene Europe and modern human origins (1997) J. Hum. Evol., 32, pp. 423-447Hunt, G., Phenotypic variance inflation in fossil samples: An empirical assessment. (2004) Paleobiology, 30, pp. 487-506Hunt, G., Bell, M.A., Travis, M.P., Evolution toward a new adaptive optimum: Phenotypic evolution in a fossil stickleback lineage (2007) Evolution, 623, pp. 700-710Jackson, D.A., PROTEST: A Procrustean randomization test of community environment concordance (1995) Écoscience, 2, pp. 297-303Katzmarzyk, P.T., Leonard, W.R., Climatic influences on human body size and proportions: Ecological adaptations and secular trends (1998) Am. J. Phys. Anthropol., 106, pp. 483-503Kelly, J., Grammer, S., Tykot, R.H., Belardi, J., Borrero, L., Gomez-Otero, J., Guichón, R., Integrating archaeological, ethnographic and analytical subsistence data: A case study from Patagonia, South America. (2001) 66th Annual Meeting of the Society for American Archaeology., , New Orleans, LouisianaKennett, D.J., Winterhalder, B., (2006) Behavioral Ecology and the Transition to Agriculture., , and. Univ. of California Press, Berkeley, CAKlingenberg, C.P., Monteiro, L.R., Distances and directions in multidimensional shape spaces: Implications for morphometric applications (2005) Syst. Biol., 54, pp. 678-688Lahr, M.M., Patterns of modern human diversification: Implications for Amerindian origins (1995) Yearb. Phys. Anthropol., 38, pp. 163-198Lalueza, C., Pérez-Pérez, A., Prats, E., Cornudella, L., Turbón, D., Lack of founding Amerindian mitochondrial DNA lineages in extinct aborigines from Tierra del Fuego-Patagonia (1997) Hum. Mol. Genet., 6, pp. 41-46Lanata, J.L., Martino, L., Osella, A., Garcia-Herbst, A., Ambiente y demografía durante la dispersión humana inicial en Sudamérica. (2006) Ecología Histórica: Interacciones Sociedad-ambiente en Distintas Escalas Espacio Temporales., , and. In. C. López. and. G. Ospina. eds. Universidad Tecnológica de Pereira, Pereira, Colombia. In pressLande, R., Statistical tests for natural selection on quantitative characters (1977) Evolution, 31, pp. 442-444Lande, R., Quantitative genetic analysis of multivariate evolution, applied to brain: Body size allometry (1979) Evolution, 33, pp. 402-416Legendre, P.F.J., Lapointe, Casgrain, P., Modeling brain evolution from behavior: A permutational regressio approach (1994) Evolution, 48, pp. 1487-1499Leonard, W.R., Snodgrass, J.J., Sorensen, M.V., Metabolic adaptation in indigenous Siberian populations (2005) Annu. Rev. Anthropol., 34, pp. 451-471Lemos, B., Marroig, G., Cerqueira, R., Evolutionary rates and stabilizing selection in large-bodied opossum skulls (Didelphimorphia: Didelphidae) (2001) J. Zool. (Lond.), 255, pp. 181-189Levin, S.A., The problem of pattern and scale in ecology: The Robert H. MacArthur award lecture (1992) Ecology, 73, pp. 1943-1967Lieberman, D.E., Pearson, O.M., Mowbray, K.M., Basicranial influence on overall cranial shape (2000) J. Hum. Evol., 38, pp. 291-315Lockwood, C.A., Kimbel, W.H., Lynch, J.M., Morphometrics and hominoid phylogeny: Support for a chimpanzee-human clade and differentiation among great ape subspecies (2004) Proc. Natl. Acad. Sci. USA, 101, pp. 4356-4360Losos, J.B., Uncertainty in the reconstruction of ancestral character states and limitations on the use of phylogenetic comparative methods (1999) Anim. Behav., 58, pp. 1319-1324Losos, J.B., U'Arheit, K.I., Schoener, T.M., Adaptive differentiation following experimental island colonization in Anolis lizards (1997) Nature, 387, pp. 70-73Lynch, M., The rate of morphological evolution in mammals from the standpoint of the neutral expectation (1990) Am. Nat., 136, pp. 727-741Marriog, G., Cheverud, J., Cranial evolution in Sakis (Pithecia, Platyrrhini) I: Interspecific differentiation and allometric patterns (2004) Am. J. Phys. Anthropol., 125, pp. 266-278Mitteroecker, P., Bookstein, F., The evolutionary role of modularity and integration in the hominoid cranium (2008) Evolution, 62, pp. 943-958Monteiro, L.R., Gomes Jr., J.L., Morphological divergence rate tests for natural selection: Uncertainty of parameter estimation and robustness of results (2005) Genet. Mol. Biol., 28, pp. 345-355Moraga, M., Rocco, P., Miquel, J.F., Nervi, F., Llop, E., Chakraborty, R., Rothhammer, F., Carvallo, P., Mitochondrial DNA polymorphisms in Chilean aboriginal populations: Implications for the peopling of the southern cone of the continent (2000) Am. J. Phys. Anthropol., 113, pp. 19-29Morriss-Kay, G.M., Derivation of the mammalian skull vault (2001) J. Anat., 199, pp. 143-151Moss, M.L., Young, R.W., A functional approach to craniology (1960) Am. J. Phys. Anthropol., 18, pp. 281-292Neves, W.A., Powell, J.F., Ozolins, E.G., Extra-continental morphological affinities of Palli Aike, Southern Chile (1999) Interciencia, 24, pp. 258-263Oksanen, J., Kindt, R., Legendre, P., O'Hara, B., Simpson, G.L., Stevens, M.H.H., (2008) Vegan: Community Ecology Package, , http://cran.r-project.org, and. R package version 1.11-4Opperman, L.A., Cranial sutures as intramembranous bone growth sites (2000) Dev. Dyn., 219, pp. 472-485Opperman, L.A., Gakunga, P.T., Carlson, D.S., Genetic factors influencing morphogenesis and growth of sutures and synchondroses in the craniofacial complex (2005) Semin. Orthod., 11, pp. 199-208Pearson, O.M., Activity, climate, and postcranial robusticity implications for modern human origins and scenarios of adaptive change (2000) Curr. Anthropol., 41, pp. 569-207Pearson, O.M., Millones, M., Rasgos esqueletales de adaptación al clima y a la actividad entre los habitantes aborígenes de Tierra del Fuego (2005) Magallania, 33, pp. 37-50Peres-Neto, P.R., Jackson, D.A., How well do multivariate data sets match? the advantages of a Procrustean superimposition approach over the Mantel test (2001) Oecologia (Berl.)., 129, pp. 169-178Perez, S.I., Bernal, V., Gonzalez, P., Differences between sliding semilandmarks methods: Implications for shape analyses of human populations (2006) J. Anat., 208, pp. 769-784Perez, S.I., Bernal, V., Gonzalez, P., Morphological differentiation of aboriginal human populations from Tierra del Fuego (Patagonia): Implications for South American peopling (2007) Am. J. Phys. Anthropol., 133, pp. 1067-1079Perez, S.I., Bernal, V., Gonzalez, P., Evolutionary relationships among prehistoric human populations: An evaluation of facial morphometric data employing molecular based genealogies (2007) Hum. Biol., 79, pp. 25-50Pucciarelli, H.M., The effects of race, sex, and nutrition on craniofacial differentiation in rats. a multivariate analysis (1980) Am. J. Phys. Anthropol., 53, pp. 359-368Pucciarelli, H.M., Growth of the functional components of the rat skull and its alteration by nutritional effects. a multivariate analysis (1981) Am. J. Phys. Anthropol., 56, pp. 33-41Pucciarelli, H.M., Oyhenart, E.E., Effects of maternal food restriction during lactation on craniofacial growth in weanling rats (1987) Am. J. Phys. Anthropol., 72, pp. 67-75Rae, T.C., Strand Viearsdóttir, U., Jeffery, N., Steegmann Jr., A.T., Developmental response to cold stress in cranial morphology of Rattus: Implications for the interpretation of climatic adaptation in fossil hominins (2006) Proc. R. Soc. Lond. B, 273, pp. 2605-2610(2008) R: A Language and Environment for Statistical Computing., , http://www.R-project.org, R Development Core Team. R Foundation for Statistical Computing, Vienna, AustriaRelethford, J.H., Craniometric variation among modern human populations (1994) Am. J. Phys. Anthropol., 95, pp. 53-62Relethford, J.H., Apportionment of global human genetic diversity based on craniometrics and skin color (2002) Am. J. Phys. Anthropol., 118, pp. 393-398Relethford, J.H., Global patterns of isolation by distance based on genetic and morphological data (2004) Hum. Biol., 76, pp. 499-513Reznick, D.N., Shaw, F.H., Rodd, F.H., Shaw, R.G., Evaluation of the rate of evolution in natural populations of guppies (Poecilia reticlrlatri) (1997) Science, 275, pp. 1934-1937Riesenfeld, A., The effect of extreme temperatures and starvation on the body proportions of the rat (1973) Am. J. Phys. Anthropol., 39, pp. 427-460Riesenfeld, A., The role of body mass in thermoregulation (1981) Am. J. Phys. Anthropol., 55, pp. 95-99Roberts, D.F., Body weight, race and climate (1953) Am. J. Phys. Anthropol., 11, pp. 533-558Roff, D.A., The evolution of genetic correlations: An analysis of patterns (1996) Evolution, 50, pp. 1392-1403Rohlf, F.J., Relative warps analysis and an example of its application to Mosquito wings (1993) Contributions to Morphometrics., pp. 132-159. , Pp. in. L. F. Marcus, E. Bello. and. A. García-Valdecasas, eds. Monografías del Museo Nacional de Ciencias Naturales, MadridRohlf, F.J., (2007) Tps Serie Softwares, , http://life.bio.sunysb.edu/morph/, Available atRohlf, F.J., Slice, D.E., Extensions of the Procrustes Method for the optimal superimposition of landmarks (1990) Syst. Zool., 39, pp. 40-59Roseman, C.C., Detecting interregionally diversifying natural selection on modern human cranial form by using matched molecular and morphometric data (2004) Proc. Natl. Acad. Sci. USA, 101, pp. 12824-12829Rothhammer, F., Silva, C., Craniometrical variation among South American prehistoric populations: Climatic, altitudinal, chronological and geographic contributions (1990) Am. J. Phys. Anthropol., 82, pp. 9-17Ruff, C.B., Morphological adaptation to climate in modern and fossil hominids (1994) Yearb. Phys. Anthropol., 37, pp. 65-107Sardi, M.L., Ramirez-Rozzi, F.V., A cross-sectional study of human craniofacial growth (2005) Ann. Hum. Biol., 32, pp. 390-396Sardi, M.L., Ramírez-Rozzi, F., González-José, R., Pucciarelli, H.M., South Amerindian craniofacial morphology: Diversity and implications for Amerindian evolution (2005) Am. J. Phys. Anthropol., 128, pp. 747-756Scheuer, L., Black, S., (2000) Developmental Juvenile Osteology., , and. Academic Press, LondonSchluter, D., (2000) The Ecology of Adaptative Radiation., , Oxford Univ. Press, New YorkSheets, H.D., Mitchell, C.E., Why the null matters: Statistical tests, random walks and evolution (2001) Genetica, 112-113, pp. 105-125Slatkin, M., Gene flow and the geographic structure of natural populations (1987) Science, 236, pp. 787-792(1961) Climatic Database of Servicio Meteorológico Nacional, , http://www.smn.gov.ar/, SMN. Available atSober, E., Reconstructing the past (1988) Parsimony, Evolution and Inference., , The MIT Press, Cambridge, MASperber, G.H., (2001) Craniofacial Development., , BC Decker Inc., HamiltonSpicer, G.S., Morphological evolution of the Drosophila virilis species group as assessed by rate tests for natural selection on quantitative characters (1993) Evolution, 47, pp. 1240-1254Steegmann, A.T., Platner, W.S., Experimental cold modification of cranio-facial morphology (1968) Am. J. Phys. Anthropol., 28, pp. 17-30Steward, J.H., (1950) Handbook of South American Indians., , Pub. Official, WashingtonStynder, D.D., Ackermann, R.R., Sealy, J.C., Craniofacial variation and population continuity during the South African Holocene (2007) Am. J. Phys. Anthropol., 134, pp. 489-500Turelli, M., Gillespie, J.H., Lande, R., Rate tests for selection on quantitative characters during macroevolution and microevolution (1988) Evolution, 42, pp. 1085-1089Vitzthum, V.J., A number no greater than the sum of its parts: The use and abuse of heritability (2003) Hum. Biol., 75, pp. 539-558Weaver, T.D., Roseman, C.C., Stringer, C.B., Were neandertal and modern human cranial differences produced by natural selection or genetic drift? (2007) J. Hum. Evol., 53, pp. 135-145Wobst, M., Boundary conditions for paleolithic social systems: A simulation approach (1974) Am. Antiq., 39, pp. 147-17

    Correction to: Update on the diagnosis and treatment of neuromyelitis optica spectrum disorders (NMOSD) – revised recommendations of the Neuromyelitis Optica Study Group (NEMOS). Part II: Attack therapy and long-term management

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    Dyadic Coping of NMOSD and MOGAD patients and their partners: a sociological and psychological examination of strategies (CoMMOnsense-Study)

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    Background Neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated diseases (MOGAD) impose psychological burdens on patients. Chronic illnesses create challenges for both patients and their partners, who also play a crucial role in managing disease-related stress. Despite its relevance, little is known about the role of dyadic coping (DC) in these conditions. This study investigates DC in NMOSD and MOGAD, aiming to provide clinical recommendations.Methods The CoMMOnsense-Study is a cross-sectional, prospective study of 59 NMOSD and 50 MOGAD patients and their respective partners, recruited from 15 centres of the German Neuromyelitis Optica Study Group registry. Participants completed self-report questionnaires on DC, depression, anxiety and quality of relationship. Correlation analyses were performed to compare findings based on antibody status. Subsequently, multivariate regression analyses were conducted to identify relevant predictors of DC.Results Patients with NMOSD and MOGAD demonstrated higher levels of depressive symptoms (NMOSD: p=0.007; MOGAD: p=0.023) and stress communication scores (NMOSD: p=0.022; MOGAD: p=0.013) than their partners. Negative coping was low across all subgroups (Stanine 1). Despite high DC and relationship quality, discrepancies were observed in the coping perceptions between partners.Conclusions Coping is highly shared within partnerships affected by NMOSD and MOGAD, while discrepancies in coping perceptions and protective buffering suggest the presence of unfavourable coping mechanisms. Reducing protective buffering and illness-related distortions shows potential areas for enhancing DC
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