Dendritic Cell Based Tumor Vaccination in Prostate and Renal Cell Cancer: A Systematic Review and Meta-Analysis

BACKGROUND: More than 200 clinical trials have been performed using dendritic cells (DC) as cellular adjuvants in cancer. Yet the key question whether there is a link between immune and clinical response remains unanswered. Prostate and renal cell cancer (RCC) have been extensively studied for DC-based immunotherapeutic interventions and were therefore chosen to address the above question by means of a systematic review and meta-analysis. METHODOLOGY/PRINCIPAL FINDINGS: Data was obtained after a systematic literature search from clinical trials that enrolled at least 6 patients. Individual patient data meta-analysis was performed by means of conditional logistic regression grouped by study. Twenty nine trials involving a total of 906 patients were identified in prostate cancer (17) and RCC (12). Objective response rates were 7.7% in prostate cancer and 12.7% in RCC. The combined percentages of objective responses and stable diseases (SD) amounted to a clinical benefit rate (CBR) of 54% in prostate cancer and 48% in RCC. Meta-analysis of individual patient data (n = 403) revealed the cellular immune response to have a significant influence on CBR, both in prostate cancer (OR 10.6, 95% CI 2.5-44.1) and in RCC (OR 8.4, 95% CI 1.3-53.0). Furthermore, DC dose was found to have a significant influence on CBR in both entities. Finally, for the larger cohort of prostate cancer patients, an influence of DC maturity and DC subtype (density enriched versus monocyte derived DC) as well as access to draining lymph nodes on clinical outcome could be demonstrated. CONCLUSIONS/SIGNIFICANCE: As a 'proof of principle' a statistically significant effect of DC-mediated cellular immune response and of DC dose on CBR could be demonstrated. Further findings concerning vaccine composition, quality control, and the effect of DC maturation status are relevant for the immunological development of DC-based vaccines

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution.C.L. was supported by the Vienna Science and Technology Fund (WWTF VRG13-007); L.M.D. was supported by ERC 647910 (KINSHIP); D.I.B. and N.I. received funding from CONICET, Argentina; L.K., F.K. and Á. Putz were supported by the European Social Fund (EFOP-3.6.1.-16-2016-00004; ‘Comprehensive Development for Implementing Smart Specialization Strategies at the University of Pécs’). K.U. and E. Vergauwe were supported by a grant from the Swiss National Science Foundation (PZ00P1_154911 to E. Vergauwe). T.G. is supported by the Social Sciences and Humanities Research Council of Canada (SSHRC). M.A.V. was supported by grants 2016-T1/SOC-1395 (Comunidad de Madrid) and PSI2017-85159-P (AEI/FEDER UE). K.B. was supported by a grant from the National Science Centre, Poland (number 2015/19/D/HS6/00641). J. Bonick and J.W.L. were supported by the Joep Lange Institute. G.B. was supported by the Slovak Research and Development Agency (APVV-17-0418). H.I.J. and E.S. were supported by a French National Research Agency ‘Investissements d’Avenir’ programme grant (ANR-15-IDEX-02). T.D.G. was supported by an Australian Government Research Training Program Scholarship. The Raipur Group is thankful to: (1) the University Grants Commission, New Delhi, India for the research grants received through its SAP-DRS (Phase-III) scheme sanctioned to the School of Studies in Life Science; and (2) the Center for Translational Chronobiology at the School of Studies in Life Science, PRSU, Raipur, India for providing logistical support. K. Ask was supported by a small grant from the Department of Psychology, University of Gothenburg. Y.Q. was supported by grants from the Beijing Natural Science Foundation (5184035) and CAS Key Laboratory of Behavioral Science, Institute of Psychology. N.A.C. was supported by the National Science Foundation Graduate Research Fellowship (R010138018). We acknowledge the following research assistants: J. Muriithi and J. Ngugi (United States International University Africa); E. Adamo, D. Cafaro, V. Ciambrone, F. Dolce and E. Tolomeo (Magna Græcia University of Catanzaro); E. De Stefano (University of Padova); S. A. Escobar Abadia (University of Lincoln); L. E. Grimstad (Norwegian School of Economics (NHH)); L. C. Zamora (Franklin and Marshall College); R. E. Liang and R. C. Lo (Universiti Tunku Abdul Rahman); A. Short and L. Allen (Massey University, New Zealand), A. Ateş, E. Güneş and S. Can Özdemir (Boğaziçi University); I. Pedersen and T. Roos (Åbo Akademi University); N. Paetz (Escuela de Comunicación Mónica Herrera); J. Green (University of Gothenburg); M. Krainz (University of Vienna, Austria); and B. Todorova (University of Vienna, Austria). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.https://www.nature.com/nathumbehav/am2023BiochemistryGeneticsMicrobiology and Plant Patholog

L’aménagement forestier au Congo engendre-t-il plus de déforestation ?

Un article publié dans Land Use Policy début 2016 arrive à la conclusion a priori étonnante que la déforestation serait, au Congo, plus élevée dans les concessions forestières avec des plans d’aménagement que dans celles qui n’en ont pas. L’analyse d’évaluation d’impact qui a conduit ces chercheurs à un tel résultat se base sur un appariement de parcelles sélectionnées aléatoirement dans des concessions avec et sans plans d’aménagement. Ces chercheurs indiquent que le réseau de routes forestières plus développé dans les concessions aménagées serait un des facteurs explicatifs. L’autre facteur serait le développement local lié aux cahiers des charges des plans d’aménagement, lequel conduirait à une augmentation de la population dans ces concessions et à une déforestation accrue. Notre groupe d’une vingtaine de chercheurs connaissant bien la problématique de l’aménagement forestier en Afrique centrale s’est penché à son tour sur cette question et a analysé la déforestation au niveau des concessions sur le même intervalle de temps. Nos résultats montrent, cette fois, que la déforestation est moins importante dans les concessions avec un plan d’aménagement que dans les autres. Et si l’on compare à production égale la déforestation dans des concessions avec et sans plan d’aménagement, il apparaît que les UFA aménagées sont environ deux fois plus « efficaces », c’est-à-dire qu’on observe deux fois moins de perte de couvert forestier par mètre-cube produit. Nous en concluons qu’il est nécessaire d’analyser précisément la dynamique des différents facteurs de déforestation, et éviter d’imputer mécaniquement à l’aménagement forestier un rôle excessif dans l’évolution dans un sens ou dans l’autre du taux de déboisement. Enfin, toute évaluation doit rappeler que les effets de l’aménagement forestier doivent être mesurés sur le long terme : l’objectif de l’aménagement est de permettre une mise en valeur forestière durable, en conservant l’essentiel du capital productif pour éviter, autant que possible, la conversion à d’autres usages après les cycles de coupe initiaux

Further characterization of an aversive learning task in Drosophila melanogaster: intensity of the stimulus, relearning, and use of rutabaga mutants.

Various learning tasks have been described in Drosophila melanogaster, flies being either tested in groups or at the individual level. Le Bourg and Buecher (Anim Learn Behav 33:330-341, 2002) have designed a task at the individual level: photopositive flies crossing a T-maze learn to prefer the dark exit when the lighted one is associated with the presence of aversive stimuli (humidity and quinine). Previous studies have reported various results (e.g. no effect of age) and the present article further characterizes this task by studying the possible effects of: (1) the intensity of the stimuli (quantity of water or concentration of quinine), (2) various delays between two learning sessions on the learning score at the second session, (3) the rutabaga learning mutation on the learning score. More concentrated quinine solutions increased learning scores but the quantity of water had no effect. Learning scores at the second session were higher with shorter delays between the two learning sessions and retrograde amnesia could decrease this memory score. rutabaga mutants showed learning deficits as in experiments testing groups of flies. This learning task could particularly be used to verify whether learning mutants isolated after experiments testing flies in groups display similar deficits when tested at the individual level