R: A Language and Environment for Statistical Computing

η-Secretase processing of APP inhibits neuronal activity in the hippocampus

Willem, M., Tahirovic, S., Busche, M. A., Ovsepian, S. V., Chafai, M., Kootar, S., Hornburg, D., Evans, L. D. B., Moore, S., Daria, A., et al. (2015) · Nature · doi:10.1038/nature14864 · Cited by 398

Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE

Klimentidis, Y. C., Raichlen, D. A., Bea, J., Garcia, D. O., Wineinger, N. E., Mandarino, L. J., Alexander, G. E., Chen, Z., & Going, S. B. (2018) · International Journal of Obesity · doi:10.1038/s41366-018-0120-3 · Cited by 403

Glycans Are a Novel Biomarker of Chronological and Biological Ages

Krištić, J., Vučković, F., Menni, C., Klarić, L., Keser, T., Beceheli, I., Pučić-Baković, M., Novokmet, M., Mangino, M., Thaqi, K., et al. (2014) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glt190 · Cited by 400

Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements

Grundberg, E., Meduri, E., Sandling, J. K., Hedman, Å. K., Keildson, S., Buil, A., Busche, S., Yuan, W., Nisbet, J., Sekowska, M., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.10.004 · Cited by 370

GetReal in network meta-analysis: a review of the methodology

Efthimiou, O., Debray, T. P. A., van Valkenhoef, G., Trelle, S., Panayidou, K., Moons, K. G. M., Reitsma, J. B., Shang, A., Salanti, G., & on behalf of GetReal Methods Review Group (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1195 · Cited by 401

Students’ mental health problems before, during, and after COVID-19 lockdown in Italy

Meda, N., Pardini, S., Slongo, I., Bodini, L., Zordan, M. A., Rigobello, P., Visioli, F., & Novara, C. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2020.12.045 · Cited by 398

Fictitious Inhibitory Differences: How Skewness and Slowing Distort the Estimation of Stopping Latencies

Verbruggen, F., Chambers, C. D., & Logan, G. D. (2013) · Psychological Science · doi:10.1177/0956797612457390 · Cited by 386

A room with a green view: the importance of nearby nature for mental health during the COVID-19 pandemic

Soga, M., Evans, M. J., Tsuchiya, K., & Fukano, Y. (2021) · Ecological Applications · doi:10.1002/eap.2248 · Cited by 389

Randomized, controlled pilot trial of a smartphone app for smoking cessation using acceptance and commitment therapy

Bricker, J. B., Mull, K. E., Kientz, J. A., Vilardaga, R., Mercer, L. D., Akioka, K. J., & Heffner, J. L. (2014) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2014.07.006 · Cited by 340

Dealing With Missing Outcome Data in Randomized Trials and Observational Studies

Groenwold, R. H. H., Donders, A. R. T., Roes, K. C. B., Harrell, F. E., & Moons, K. G. M. (2012) · American Journal of Epidemiology · doi:10.1093/aje/kwr302 · Cited by 398

Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis

Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00420-7 · Cited by 413

Does interference competition with wolves limit the distribution and abundance of coyotes?

BERGER, K. M., & GESE, E. M. (2007) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2007.01287.x · Cited by 398

Multiple Independent Loci at Chromosome 15q25.1 Affect Smoking Quantity: a Meta-Analysis and Comparison with Lung Cancer and COPD

Saccone, N. L., Culverhouse, R. C., Schwantes-An, T.-H., Cannon, D. S., Chen, X., Cichon, S., Giegling, I., Han, S., Han, Y., Keskitalo-Vuokko, K., et al. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001053 · Cited by 395

A comprehensive single cell transcriptional landscape of human hematopoietic progenitors

Pellin, D., Loperfido, M., Baricordi, C., Wolock, S. L., Montepeloso, A., Weinberg, O. K., Biffi, A., Klein, A. M., & Biasco, L. (2019) · Nature Communications · doi:10.1038/s41467-019-10291-0 · Cited by 360

Investigating the replicability of preclinical cancer biology

Errington, T. M., Mathur, M., Soderberg, C. K., Denis, A., Perfito, N., Iorns, E., & Nosek, B. A. (2021) · eLife · doi:10.7554/elife.71601 · Cited by 462

Using the Edmonton Obesity Staging System to predict mortality in a population-representative cohort of people with overweight and obesity.

Padwal, R. S., Pajewski, N. M., Allison, D. B., & Sharma, A. M. (2011) · Canadian Medical Association Journal · doi:10.1503/cmaj.110387 · Cited by 392

Revealing the dynamic network structure of the Beck Depression Inventory-II

Bringmann, L. F., Lemmens, L. H. J. M., Huibers, M. J. H., Borsboom, D., & Tuerlinckx, F. (2015) · Psychological Medicine · doi:10.1017/s0033291714001809 · Cited by 371

The hidden burden of eating disorders: an extension of estimates from the Global Burden of Disease Study 2019

Santomauro, D. F., Melen, S., Mitchison, D., Vos, T., Whiteford, H., & Ferrari, A. J. (2021) · The Lancet Psychiatry · doi:10.1016/s2215-0366(21)00040-7 · Cited by 391

Pit and fissure sealants for preventing dental decay in permanent teeth

Ahovuo-Saloranta, A., Forss, H., Walsh, T., Nordblad, A., Mäkelä, M., & Worthington, H. V. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd001830.pub5 · Cited by 391

Gut microbiome diversity is associated with sleep physiology in humans

Smith, R. P., Easson, C., Lyle, S. M., Kapoor, R., Donnelly, C. P., Davidson, E. J., Parikh, E., Lopez, J. V., & Tartar, J. L. (2019) · PLOS ONE · doi:10.1371/journal.pone.0222394 · Cited by 390

Topography of social touching depends on emotional bonds between humans

Suvilehto, J. T., Glerean, E., Dunbar, R. I. M., Hari, R., & Nummenmaa, L. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1519231112 · Cited by 385

Genome Organization Drives Chromosome Fragility

Canela, A., Maman, Y., Jung, S., Wong, N., Callen, E., Day, A., Kieffer-Kwon, K.-R., Pekowska, A., Zhang, H., Rao, S. S. P., et al. (2017) · Cell · doi:10.1016/j.cell.2017.06.034 · Cited by 383

Longitudinal changes in cortical thickness in autism and typical development

Zielinski, B. A., Prigge, M. B. D., Nielsen, J. A., Froehlich, A. L., Abildskov, T. J., Anderson, J. S., Fletcher, P. T., Zygmunt, K. M., Travers, B. G., Lange, N., et al. (2014) · Brain · doi:10.1093/brain/awu083 · Cited by 378

Comparative effectiveness of transitional care services in patients discharged from the hospital with heart failure: a systematic review and network meta-analysis

Van Spall, H. G. C., Rahman, T., Mytton, O., Ramasundarahettige, C., Ibrahim, Q., Kabali, C., Coppens, M., Brian Haynes, R., & Connolly, S. (2017) · European Journal of Heart Failure · doi:10.1002/ejhf.765 · Cited by 381

From lists of behaviour change techniques ( BCT s) to structured hierarchies: Comparison of two methods of developing a hierarchy of BCT s

Cane, J., Richardson, M., Johnston, M., Ladha, R., & Michie, S. (2015) · British Journal of Health Psychology · doi:10.1111/bjhp.12102 · Cited by 376

Defining the transcriptome and proteome in three functionally different human cell lines

Lundberg, E., Fagerberg, L., Klevebring, D., Matic, I., Geiger, T., Cox, J., Älgenäs, C., Lundeberg, J., Mann, M., & Uhlen, M. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.106 · Cited by 373

Catastrophizing-a prognostic factor for outcome in patients with low back pain: a systematic review

Wertli, M. M., Eugster, R., Held, U., Steurer, J., Kofmehl, R., & Weiser, S. (2014) · The Spine Journal · doi:10.1016/j.spinee.2014.03.003 · Cited by 363

“Why Does the Cognitive Reflection Test (Sometimes) Predict Utilitarian Moral Judgment (and Other Things)?”

Baron, J., Scott, S., Fincher, K., & Emlen Metz, S. (2015) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2014.09.003 · Cited by 346

The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis?

Lazic, S. E. (2010) · BMC Neuroscience · doi:10.1186/1471-2202-11-5 · Cited by 381

Genome-Wide Association Identifies Nine Common Variants Associated With Fasting Proinsulin Levels and Provides New Insights Into the Pathophysiology of Type 2 Diabetes

Strawbridge, R. J., Dupuis, J., Prokopenko, I., Barker, A., Ahlqvist, E., Rybin, D., Petrie, J. R., Travers, M. E., Bouatia-Naji, N., Dimas, A. S., et al. (2011) · Diabetes · doi:10.2337/db11-0415 · Cited by 356

Defining the biological basis of radiomic phenotypes in lung cancer

Grossmann, P., Stringfield, O., El-Hachem, N., Bui, M. M., Rios Velazquez, E., Parmar, C., Leijenaar, R. T., Haibe-Kains, B., Lambin, P., Gillies, R. J., et al. (2017) · eLife · doi:10.7554/elife.23421 · Cited by 365

Microglia Require CD4 T Cells to Complete the Fetal-to-Adult Transition

Pasciuto, E., Burton, O. T., Roca, C. P., Lagou, V., Rajan, W. D., Theys, T., Mancuso, R., Tito, R. Y., Kouser, L., Callaerts-Vegh, Z., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.026 · Cited by 368

Fecal microbiota transfer between young and aged mice reverses hallmarks of the aging gut, eye, and brain

Parker, A., Romano, S., Ansorge, R., Aboelnour, A., Le Gall, G., Savva, G. M., Pontifex, M. G., Telatin, A., Baker, D., Jones, E., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01243-w · Cited by 368

Estimating genetic kin relationships in prehistoric populations

Monroy Kuhn, J. M., Jakobsson, M., & Günther, T. (2018) · PLOS ONE · doi:10.1371/journal.pone.0195491 · Cited by 330

Museum specimens reveal loss of pollen host plants as key factor driving wild bee decline in The Netherlands

Scheper, J., Reemer, M., van Kats, R., Ozinga, W. A., van der Linden, G. T. J., Schaminée, J. H. J., Siepel, H., & Kleijn, D. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1412973111 · Cited by 357

Prediction of Psilocybin Response in Healthy Volunteers

Studerus, E., Gamma, A., Kometer, M., & Vollenweider, F. X. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030800 · Cited by 369

ESTIMATING MODERATING EFFECTS IN PLS-SEM AND PLSc-SEM: INTERACTION TERM GENERATION*DATA TREATMENT

Becker, J.-M., Ringle, C. M., & Sarstedt, M. (2018) · Journal of Applied Structural Equation Modeling · doi:10.47263/jasem.2(2)01 · Cited by 375

2023 American Society of Anesthesiologists Practice Guidelines for Preoperative Fasting: Carbohydrate-containing Clear Liquids with or without Protein, Chewing Gum, and Pediatric Fasting Duration—A Modular Update of the 2017 American Society of Anesthesiologists Practice Guidelines for Preoperative Fasting *

Joshi, G. P., Abdelmalak, B. B., Weigel, W. A., Harbell, M. W., Kuo, C. I., Soriano, S. G., Stricker, P. A., Tipton, T., Grant, M. D., Marbella, A. M., et al. (2023) · Anesthesiology · doi:10.1097/aln.0000000000004381 · Cited by 375

A general modular framework for gene set enrichment analysis

Ackermann, M., & Strimmer, K. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-47 · Cited by 358

The Challenging Experience Questionnaire: Characterization of challenging experiences with psilocybin mushrooms

Barrett, F. S., Bradstreet, M. P., Leoutsakos, J.-M. S., Johnson, M. W., & Griffiths, R. R. (2016) · Journal of Psychopharmacology · doi:10.1177/0269881116678781 · Cited by 366

Membership and behavior of ultra-low-diversity pathogen communities present in the gut of humans during prolonged critical illness

Zaborin, A., Smith, D., Garfield, K., Quensen, J., Shakhsheer, B., Kade, M., Tirrell, M., Tiedje, J., Gilbert, J. A., Zaborina, O., et al. (2014) · mBio · doi:10.1128/mbio.01361-14 · Cited by 367

mapDamage: testing for damage patterns in ancient DNA sequences

Ginolhac, A., Rasmussen, M., Gilbert, M. T. P., Willerslev, E., & Orlando, L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr347 · Cited by 363

Analyzing dynamic phonetic data using generalized additive mixed modeling: A tutorial focusing on articulatory differences between L1 and L2 speakers of English

Wieling, M. (2018) · Journal of Phonetics · doi:10.1016/j.wocn.2018.03.002 · Cited by 362

Development of the Valuing Questionnaire (VQ)

Smout, M., Davies, M., Burns, N., & Christie, A. (2014) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2014.06.001 · Cited by 350

Gut microbiota in Parkinson's disease: Temporal stability and relations to disease progression

Aho, V. T. E., Pereira, P. A. B., Voutilainen, S., Paulin, L., Pekkonen, E., Auvinen, P., & Scheperjans, F. (2019) · eBioMedicine · doi:10.1016/j.ebiom.2019.05.064 · Cited by 361

Finding the self by losing the self: neural correlates of ego-dissolution under psilocybin

Lebedev, A. V., Lövdén, M., Rosenthal, G., Feilding, A., Nutt, D. J., & Carhart-Harris, R. L. (2015) · Human Brain Mapping · doi:10.1002/hbm.22833 · Cited by 339

A comprehensive meta-analysis on Problematic Facebook Use

Marino, C., Gini, G., Vieno, A., & Spada, M. M. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.02.009 · Cited by 378

An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer

Staudenmayer, J., Pober, D., Crouter, S., Bassett, D., & Freedson, P. (2009) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00465.2009 · Cited by 361

The Very Efficient Assessment of Need for Cognition: Developing a Six-Item Version

Lins de Holanda Coelho, G., H. P. Hanel, P., & J. Wolf, L. (2020) · Assessment · doi:10.1177/1073191118793208 · Cited by 358

Models of accuracy in repeated-measures designs

Dixon, P. (2008) · Journal of Memory and Language · doi:10.1016/j.jml.2007.11.004 · Cited by 359

Host-Protozoan Interactions Protect from Mucosal Infections through Activation of the Inflammasome

Chudnovskiy, A., Mortha, A., Kana, V., Kennard, A., Ramirez, J. D., Rahman, A., Remark, R., Mogno, I., Ng, R., Gnjatic, S., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.076 · Cited by 325

Experimental reductions of delay discounting and impulsive choice: A systematic review and meta-analysis.

Rung, J. M., & Madden, G. J. (2018) · Journal of Experimental Psychology: General · doi:10.1037/xge0000462 · Cited by 358

Acoustic sequences in non‐human animals: a tutorial review and prospectus

Kershenbaum, A., Blumstein, D. T., Roch, M. A., Akçay, Ç., Backus, G., Bee, M. A., Bohn, K., Cao, Y., Carter, G., Cäsar, C., et al. (2016) · Biological Reviews · doi:10.1111/brv.12160 · Cited by 337

The impact of chatbot conversational skill on engagement and perceived humanness

Schuetzler, R. M., Grimes, G. M., & Scott Giboney, J. (2020) · Journal of Management Information Systems · doi:10.1080/07421222.2020.1790204 · Cited by 357

Resting-state functional connectivity of subgenual anterior cingulate cortex in depressed adolescents

Connolly, C. G., Wu, J., Ho, T. C., Hoeft, F., Wolkowitz, O., Eisendrath, S., Frank, G., Hendren, R., Max, J. E., Paulus, M. P., et al. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.05.036 · Cited by 356

Studying the influence of package shape and colour on consumer expectations of milk desserts using word association and conjoint analysis

Ares, G., & Deliza, R. (2010) · Food Quality and Preference · doi:10.1016/j.foodqual.2010.03.006 · Cited by 357

Error, signal, and the placement of Ctenophora sister to all other animals

Whelan, N. V., Kocot, K. M., Moroz, L. L., & Halanych, K. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1503453112 · Cited by 331

Above‐ and belowground biomass allocation in Tibetan grasslands

Yang, Y., Fang, J., Ji, C., & Han, W. (2009) · Journal of Vegetation Science · doi:10.1111/j.1654-1103.2009.05566.x · Cited by 356

Metformin promotes lifespan through mitohormesis via the peroxiredoxin PRDX-2

De Haes, W., Frooninckx, L., Van Assche, R., Smolders, A., Depuydt, G., Billen, J., Braeckman, B. P., Schoofs, L., & Temmerman, L. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1321776111 · Cited by 355

D614G Spike Mutation Increases SARS CoV-2 Susceptibility to Neutralization

Weissman, D., Alameh, M.-G., de Silva, T., Collini, P., Hornsby, H., Brown, R., LaBranche, C. C., Edwards, R. J., Sutherland, L., Santra, S., et al. (2021) · Cell Host & Microbe · doi:10.1016/j.chom.2020.11.012 · Cited by 324

IGF-I induced genes in stromal fibroblasts predict the clinical outcome of breast and lung cancer patients

Rajski, M., Zanetti-Dällenbach, R., Vogel, B., Herrmann, R., Rochlitz, C., & Buess, M. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-1 · Cited by 355

A Functional Genomics Approach to Understand Variation in Cytokine Production in Humans

Li, Y., Oosting, M., Smeekens, S. P., Jaeger, M., Aguirre-Gamboa, R., Le, K. T. T., Deelen, P., Ricaño-Ponce, I., Schoffelen, T., Jansen, A. F. M., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.017 · Cited by 324

GATA6 expression distinguishes classical and basal-like subtypes in advanced pancreatic cancer

O’Kane, G. M., Grünwald, B. T., Jang, G.-H., Masoomian, M., Picardo, S., Grant, R. C., Denroche, R. E., Zhang, A., Wang, Y., Miller, J. K., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-3724 · Cited by 352

Drug repositioning: a machine-learning approach through data integration

Napolitano, F., Zhao, Y., Moreira, V. M., Tagliaferri, R., Kere, J., D’Amato, M., & Greco, D. (2013) · Journal of Cheminformatics · doi:10.1186/1758-2946-5-30 · Cited by 349

Interventions for suicide and self-injury: A meta-analysis of randomized controlled trials across nearly 50 years of research.

Fox, K. R., Huang, X., Guzmán, E. M., Funsch, K. M., Cha, C. B., Ribeiro, J. D., & Franklin, J. C. (2020) · Psychological Bulletin · doi:10.1037/bul0000305 · Cited by 351

Experimental Evaluation of Seaweeds as a Vector for Microplastics into Marine Food Webs

Gutow, L., Eckerlebe, A., Giménez, L., & Saborowski, R. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.5b02431 · Cited by 346

Working memory training revisited: A multi-level meta-analysis of n-back training studies

Soveri, A., Antfolk, J., Karlsson, L., Salo, B., & Laine, M. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1217-0 · Cited by 371

Spatial covariance between biodiversity and other ecosystem service priorities

Anderson, B. J., Armsworth, P. R., Eigenbrod, F., Thomas, C. D., Gillings, S., Heinemeyer, A., Roy, D. B., & Gaston, K. J. (2009) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2009.01666.x · Cited by 348

Sensitive periods of amygdala development: the role of maltreatment in preadolescence

Pechtel, P., Lyons-Ruth, K., Anderson, C. M., & Teicher, M. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.04.025 · Cited by 342

Why the cross-lagged panel model is almost never the right choice

Lucas, R. E. (2023) · Advances in Methods and Practices in Psychological Science · doi:10.1177/25152459231158378 · Cited by 361

Assessing the Attitude Towards Artificial Intelligence: Introduction of a Short Measure in German, Chinese, and English Language

Sindermann, C., Sha, P., Zhou, M., Wernicke, J., Schmitt, H. S., Li, M., Sariyska, R., Stavrou, M., Becker, B., & Montag, C. (2021) · KI - Künstliche Intelligenz · doi:10.1007/s13218-020-00689-0 · Cited by 343

The seven deadly sins of comparative analysis

FRECKLETON, R. P. (2009) · Journal of Evolutionary Biology · doi:10.1111/j.1420-9101.2009.01757.x · Cited by 339

Oligotyping analysis of the human oral microbiome

Eren, A. M., Borisy, G. G., Huse, S. M., & Mark Welch, J. L. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409644111 · Cited by 347

Questionable research practices in ecology and evolution

Fraser, H., Parker, T., Nakagawa, S., Barnett, A., & Fidler, F. (2018) · PLOS ONE · doi:10.1371/journal.pone.0200303 · Cited by 346

Statistical and Methodological Considerations for the Interpretation of Intranasal Oxytocin Studies

Walum, H., Waldman, I. D., & Young, L. J. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.06.016 · Cited by 347

The global gap in treatment coverage for major depressive disorder in 84 countries from 2000–2019: A systematic review and Bayesian meta-regression analysis

Moitra, M., Santomauro, D., Collins, P. Y., Vos, T., Whiteford, H., Saxena, S., & Ferrari, A. J. (2022) · PLOS Medicine · doi:10.1371/journal.pmed.1003901 · Cited by 355

Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data

Wang, T., Li, B., Nelson, C. E., & Nabavi, S. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2599-6 · Cited by 286

Impact of Physical Exercise on Substance Use Disorders: A Meta-Analysis

Wang, D., Wang, Y., Wang, Y., Li, R., & Zhou, C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110728 · Cited by 340

Anxiety and climate change: a validation of the Climate Anxiety Scale in a German-speaking quota sample and an investigation of psychological correlates

Wullenkord, M. C., Tröger, J., Hamann, K. R. S., Loy, L. S., & Reese, G. (2021) · Climatic Change · doi:10.1007/s10584-021-03234-6 · Cited by 344

Risk for mental disorders associated with sexual assault: a meta-analysis

Dworkin, E. R. (2020) · Trauma, Violence, & Abuse · doi:10.1177/1524838018813198 · Cited by 347

Deep Brain Stimulation of the Ventral Anterior Limb of the Internal Capsule for Treatment-Resistant Depression: A Randomized Clinical Trial

Bergfeld, I. O., Mantione, M., Hoogendoorn, M. L. C., Ruhé, H. G., Notten, P., van Laarhoven, J., Visser, I., Figee, M., de Kwaasteniet, B. P., Horst, F., et al. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2016.0152 · Cited by 336

Fear-avoidance beliefs—a moderator of treatment efficacy in patients with low back pain: a systematic review

Wertli, M. M., Rasmussen-Barr, E., Held, U., Weiser, S., Bachmann, L. M., & Brunner, F. (2014) · The Spine Journal · doi:10.1016/j.spinee.2014.02.033 · Cited by 343

Implanted pluripotent stem-cell-derived pancreatic endoderm cells secrete glucose-responsive C-peptide in patients with type 1 diabetes

Ramzy, A., Thompson, D. M., Ward-Hartstonge, K. A., Ivison, S., Cook, L., Garcia, R. V., Loyal, J., Kim, P. T. W., Warnock, G. L., Levings, M. K., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.10.003 · Cited by 342

Faecal sludge management with the larvae of the black soldier fly (Hermetia illucens)—From a hygiene aspect

Lalander, C., Diener, S., Magri, M. E., Zurbrügg, C., Lindström, A., & Vinnerås, B. (2013) · Science of The Total Environment · doi:10.1016/j.scitotenv.2013.04.033 · Cited by 340

Microplastic contamination of drinking water: A systematic review

Danopoulos, E., Twiddy, M., & Rotchell, J. M. (2020) · PLOS ONE · doi:10.1371/journal.pone.0236838 · Cited by 341

Conformists and Mavericks: The Empirics of Frequency-Dependent Cultural Transmission

EFFERSON, C., LALIVE, R., RICHERSON, P., MCELREATH, R., & LUBELL, M. (2008) · Evolution and Human Behavior · doi:10.1016/j.evolhumbehav.2007.08.003 · Cited by 336

Intestinal Microbiota in Healthy Adults: Temporal Analysis Reveals Individual and Common Core and Relation to Intestinal Symptoms

Jalanka-Tuovinen, J., Salonen, A., Nikkilä, J., Immonen, O., Kekkonen, R., Lahti, L., Palva, A., & de Vos, W. M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023035 · Cited by 340

Biological invasions: a field synopsis, systematic review, and database of the literature

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Rumen metagenome and metatranscriptome analyses of low methane yield sheep reveals a Sharpea-enriched microbiome characterised by lactic acid formation and utilisation

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