Frameshift mutations have been considered of significant importance for the molecular evolution of proteins and their coding genes, while frameshift protein sequences encoded in the alternative reading frames of coding genes have been considered to be meaningless. However, functional frameshifts have been found widely existing. It was puzzling how a frameshift protein kept its structure and functionality while substantial changes occurred in its primary amino-acid sequence. This study shows that the similarities among frameshifts and wild types are higher than random similarities and are determined at different levels. Frameshift substitutions are more conservative than random substitutions in the standard genetic code (SGC). The frameshift substitutions score of SGC ranks in the top 2.0-3.5% of alternative genetic codes, showing that SGC is nearly optimal for frameshift tolerance. In many genes and certain genomes, frameshift-resistant codons and codon pairs appear more frequently than expected, suggesting that frameshift tolerance is achieved through not only the optimality of the genetic code but, more importantly, the further optimization of a specific gene or genome through the usages of codons/codon pairs, which sheds light on the role of frameshift mutations in molecular and genomic evolution. <<<

Bonnie E Gould Rothberg, Tammie E Quest, Sai-Ching J Yeung, Lorraine C Pelosof, David E Gerber, Justin A Seltzer, Jason J Bischof, Charles R Thomas, Nausheen Akhter, Mira Mamtani, Robin E Stutman, Christopher W Baugh, Venkataraman Anantharaman, Nicholas R Pettit, Adam D Klotz, Michael A Gibbs, Demetrios N Kyriacou <<<

Patients with advanced cancer generate 4 million visits annually to emergency departments (EDs) and other dedicated, high-acuity oncology urgent care centers. Because of both the increasing complexity of systemic treatments overall and the higher rates of active therapy in the geriatric population, many patients experiencing acute decompensations are frail and acutely ill. This article comprehensively reviews the spectrum of oncologic emergencies and urgencies typically encountered in acute care settings. Presentation, underlying etiology, and up-to-date clinical pathways are discussed. Criteria for either a safe discharge to home or a transition of care to the inpatient oncology hospitalist team are emphasized. This review extends beyond familiar conditions such as febrile neutropenia, hypercalcemia, tumor lysis syndrome, malignant spinal cord compression, mechanical bowel obstruction, and breakthrough pain crises to include a broader spectrum of topics encompassing the syndrome of inappropriate antidiuretic hormone secretion, venous thromboembolism and malignant effusions, as well as chemotherapy-induced mucositis, cardiomyopathy, nausea, vomiting, and diarrhea. Emergent and urgent complications associated with targeted therapeutics, including small molecules, naked and drug-conjugated monoclonal antibodies, as well as immune checkpoint inhibitors and chimeric antigen receptor T-cells, are summarized. Finally, strategies for facilitating same-day direct admission to hospice from the ED are discussed. This article not only can serve as a point-of-care reference for the ED physician but also can assist outpatient oncologists as well as inpatient hospitalists in coordinating care around the ED visit. <<<

Chromosome replication is performed by a complex and intricate ensemble of proteins termed the replisome, where the DNA polymerases Polδ and Polε, DNA polymerase α-primase (Polα) and accessory proteins including AND-1, CLASPIN and TIMELESS-TIPIN (respectively known as Ctf4, Mrc1 and Tof1-Csm3 in Saccharomyces cerevisiae) are organized around the CDC45-MCM-GINS (CMG) replicative helicase. Because a functional human replisome has not been reconstituted from purified proteins, how these factors contribute to human DNA replication and whether additional proteins are required for optimal DNA synthesis are poorly understood. Here we report the biochemical reconstitution of human replisomes that perform fast and efficient DNA replication using 11 purified human replication factors made from 43 polypeptides. Polε, but not Polδ, is crucial for optimal leading-strand synthesis. Unexpectedly, Polε-mediated leading-strand replication is highly dependent on the sliding-clamp processivity factor PCNA and the alternative clamp loader complex CTF18-RFC. We show how CLASPIN and TIMELESS-TIPIN contribute to replisome progression and demonstrate that, in contrast to the budding yeast replisome, AND-1 directly augments leading-strand replication. Moreover, although AND-1 binds to Polα, the interaction is dispensable for lagging-strand replication, indicating that Polα is functionally recruited via an AND-1-independent mechanism for priming in the human replisome. Collectively, our work reveals how the human replisome achieves fast and efficient leading-strand and lagging-strand DNA replication, and provides a powerful system for future studies of the human replisome and its interactions with other DNA metabolic processes. <<<

Allele-specific expression (ASE) is a phenomenon in which one allele is preferentially expressed over the other. Genetic and epigenetic factors cause ASE by altering the final composition of a gene's product, leading to expression imbalances that can have functional consequences on phenotypes. Environmental signals also impact allele-specific expression, but how they contribute to this cross talk remains understudied. Here, we explored how genotype, parent-of-origin, tissue, sex, and dietary fat simultaneously influence ASE biases. Male and female mice from a F reciprocal cross of the LG/J and SM/J strains were fed a high or low fat diet. We harnessed strain-specific variants to distinguish between two ASE classes: parent-of-origin-dependent (unequal expression based on parental origin) and sequence-dependent (unequal expression based on nucleotide identity). We present a comprehensive map of ASE patterns in 2853 genes across three tissues and nine environmental contexts. We found that both ASE classes are highly dependent on tissue and environmental context. They vary across metabolically relevant tissues, between males and females, and in response to dietary fat. We also found 45 genes with inconsistent ASE biases that switched direction across tissues and/or environments. Finally, we integrated ASE and QTL data from published intercrosses of the LG/J and SM/J strains. Our ASE genes are often enriched in QTLs for metabolic and musculoskeletal traits, highlighting how this orthogonal approach can prioritize candidate genes. Together, our results provide novel insights into how genetic, epigenetic, and environmental mechanisms govern allele-specific expression, which is an essential step toward deciphering the genotype-to-phenotype map. <<<

We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length (~300bp) and fast runs times (<20hrs) with high base accuracy (Q30 > 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data. <<<

We introduce a strategy for learning image registration without acquired imaging data, producing powerful networks agnostic to contrast introduced by magnetic resonance imaging (MRI). While classical registration methods accurately estimate the spatial correspondence between images, they solve an optimization problem for every new image pair. Learning-based techniques are fast at test time but limited to registering images with contrasts and geometric content similar to those seen during training. We propose to remove this dependency on training data by leveraging a generative strategy for diverse synthetic label maps and images that exposes networks to a wide range of variability, forcing them to learn more invariant features. This approach results in powerful networks that accurately generalize to a broad array of MRI contrasts. We present extensive experiments with a focus on 3D neuroimaging, showing that this strategy enables robust and accurate registration of arbitrary MRI contrasts even if the target contrast is not seen by the networks during training. We demonstrate registration accuracy surpassing the state of the art both within and across contrasts, using a single model. Critically, training on arbitrary shapes synthesized from noise distributions results in competitive performance, removing the dependency on acquired data of any kind. Additionally, since anatomical label maps are often available for the anatomy of interest, we show that synthesizing images from these dramatically boosts performance, while still avoiding the need for real intensity images. Our code is available at doic https://w3id.org/synthmorph. <<<

Tao Zhong, Jingkuan Wei, Kunhua Wu, Liangjun Chen, Fenqiang Zhao, Yuchen Pei, Ya Wang, Hongjiang Zhang, Zhengwang Wu, Ying Huang, Tengfei Li, Li Wang, Yongchang Chen, Weizhi Ji, Yu Zhang, Gang Li, Yuyu Niu <<<

Longitudinal brain imaging atlases with densely sampled time-points and ancillary anatomical information are of fundamental importance in studying early developmental characteristics of human and non-human primate brains during infancy, which feature extremely dynamic imaging appearance, brain shape and size. However, for non-human primates, which are highly valuable animal models for understanding human brains, the existing brain atlases are mainly developed based on adults or adolescents, denoting a notable lack of temporally densely-sampled atlases covering the dynamic early brain development. To fill this critical gap, in this paper, we construct a comprehensive set of longitudinal brain atlases and associated tissue probability maps (gray matter, white matter, and cerebrospinal fluid) with totally 12 time-points from birth to 4 years of age (i.e., 1, 2, 3, 4, 5, 6, 9, 12, 18, 24, 36, and 48 months of age) based on 175 longitudinal structural MRI scans from 39 typically-developing cynomolgus macaques, by leveraging state-of-the-art computational techniques tailored for early developing brains. Furthermore, to facilitate region-based analysis using our atlases, we also provide two popular hierarchy parcellations, i.e., cortical hierarchy maps (6 levels) and subcortical hierarchy maps (6 levels), on our longitudinal macaque brain atlases. These early developing atlases, which have the densest time-points during infancy (to the best of our knowledge), will greatly facilitate the studies of macaque brain development. <<<

Spatiotemporal (four-dimensional) infant-dedicated brain atlases are essential for neuroimaging analysis of early dynamic brain development. However, due to the substantial technical challenges in the acquisition and processing of infant brain MR images, 4D atlases densely covering the dynamic brain development during infancy are still scarce. Few existing ones generally have fuzzy tissue contrast and low spatiotemporal resolution, leading to degraded accuracy of atlas-based normalization and subsequent analyses. To address this issue, in this paper, we construct a 4D structural MRI atlas for infant brains based on the UNC/UMN Baby Connectome Project (BCP) dataset, which features a high spatial resolution, extensive age-range coverage, and densely sampled time points. Specifically, 542 longitudinal T1w and T2w scans from 240 typically developing infants up to 26-month of age were utilized for our atlas construction. To improve the co-registration accuracy of the infant brain images, which typically exhibit dynamic appearance with low tissue contrast, we employed the state-of-the-art registration method and leveraged our generated reliable brain tissue probability maps in addition to the intensity images to improve the alignment of individual images. To achieve consistent region labeling on both infant and adult brain images for facilitating region-based analysis across ages, we mapped the widely used Desikan cortical parcellation onto our atlas by following an age-decreasing mapping manner. Meanwhile, the typical subcortical structures were manually delineated to facilitate the studies related to the subcortex. Compared with the existing infant brain atlases, our 4D atlas has much higher spatiotemporal resolution and preserves more structural details, and thus can boost accuracy in neurodevelopmental analysis during infancy. <<<

Jing Xiong, Seong Su Kang, Zhihao Wang, Xia Liu, Tan-Chun Kuo, Funda Korkmaz, Ashley Padilla, Sari Miyashita, Pokman Chan, Zhaohui Zhang, Pavel Katsel, Jocoll Burgess, Anisa Gumerova, Kseniia Ievleva, Damini Sant, Shan-Ping Yu, Valeriia Muradova, Tal Frolinger, Daria Lizneva, Jameel Iqbal, Ki A Goosens, Sakshi Gera, Clifford J Rosen, Vahram Haroutunian, Vitaly Ryu, Tony Yuen, Mone Zaidi, Keqiang Ye <<<

Alzheimer's disease has a higher incidence in older women, with a spike in cognitive decline that tracks with visceral adiposity, dysregulated energy homeostasis and bone loss during the menopausal transition. Inhibiting the action of follicle-stimulating hormone (FSH) reduces body fat, enhances thermogenesis, increases bone mass and lowers serum cholesterol in mice. Here we show that FSH acts directly on hippocampal and cortical neurons to accelerate amyloid-β and Tau deposition and impair cognition in mice displaying features of Alzheimer's disease. Blocking FSH action in these mice abrogates the Alzheimer's disease-like phenotype by inhibiting the neuronal C/EBPβ-δ-secretase pathway. These data not only suggest a causal role for rising serum FSH levels in the exaggerated Alzheimer's disease pathophysiology during menopause, but also reveal an opportunity for treating Alzheimer's disease, obesity, osteoporosis and dyslipidaemia with a single FSH-blocking agent. <<<

C Domínguez Conde, C Xu, L B Jarvis, D B Rainbow, S B Wells, T Gomes, S K Howlett, O Suchanek, K Polanski, H W King, L Mamanova, N Huang, P A Szabo, L Richardson, L Bolt, E S Fasouli, K T Mahbubani, M Prete, L Tuck, N Richoz, Z K Tuong, L Campos, H S Mousa, E J Needham, S Pritchard, T Li, R Elmentaite, J Park, E Rahmani, D Chen, D K Menon, O A Bayraktar, L K James, K B Meyer, N Yosef, M R Clatworthy, P A Sims, D L Farber, K Saeb-Parsy, J L Jones, S A Teichmann <<<

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing. <<<

Reference genomes are required to understand the diverse roles of microorganisms in ecology, evolution, human and animal health, but most species remain uncultured. Here we present a sequence composition-independent approach to recover high-quality microbial genomes from deeply sequenced metagenomes. Multiple metagenomes of the same community, which differ in relative population abundances, were used to assemble 31 bacterial genomes, including rare (<1% relative abundance) species, from an activated sludge bioreactor. Twelve genomes were assembled into complete or near-complete chromosomes. Four belong to the candidate bacterial phylum TM7 and represent the most complete genomes for this phylum to date (relative abundances, 0.06-1.58%). Reanalysis of published metagenomes reveals that differential coverage binning facilitates recovery of more complete and higher fidelity genome bins than other currently used methods, which are primarily based on sequence composition. This approach will be an important addition to the standard metagenome toolbox and greatly improve access to genomes of uncultured microorganisms. <<<

The mechanisms and key factors involved in tumor environments for lung metastasis of CRC are still unclear. Here, using clinical samples from lung metastases of CRC patients, we found that intestinal immune network for IgA production was significantly dysregulated in lung metastases of CRC. Single-cell RNA sequencing discovered a subtype of B cells positive for Erbin, one member of the leucine-rich repeat and PDZ domain (LAP) family, was involved in the lung metastases. Erbin deletion in B cells suppressed lung metastasis of CRC in vivo. And, deletion of Erbin in B cells enhanced the killing effects of CD8 T cells on tumor cells. Mechanistically, Erbin knockout attenuated TGFβ-mediated suppression of migration of CXCR5 IgA cells and STAT6-mediated PD1 expression. Our study uncovered a key role of Erbin in regulating PD1 IgA B cells in lung metastasis of CRC. Targeting Erbin as well as combined use of neutralizing B cells and antibodies neutralizing PD1 suppresses lung metastasis of CRC in mice, suggesting the potential option for treatment of lung metastasis of CRC. <<<

Hai-Liang Zhang, Bing-Xin Hu, Zhi-Ling Li, Tian Du, Jia-Lu Shan, Zhi-Peng Ye, Xiao-Dan Peng, Xuan Li, Yun Huang, Xian-Ying Zhu, Yu-Hong Chen, Gong-Kan Feng, Dajun Yang, Rong Deng, Xiao-Feng Zhu <<<

The accumulation of lipid peroxides is recognized as a determinant of the occurrence of ferroptosis. However, the sensors and amplifying process of lipid peroxidation linked to ferroptosis remain obscure. Here we identify PKCβII as a critical contributor of ferroptosis through independent genome-wide CRISPR-Cas9 and kinase inhibitor library screening. Our results show that PKCβII senses the initial lipid peroxides and amplifies lipid peroxidation linked to ferroptosis through phosphorylation and activation of ACSL4. Lipidomics analysis shows that activated ACSL4 catalyses polyunsaturated fatty acid-containing lipid biosynthesis and promotes the accumulation of lipid peroxidation products, leading to ferroptosis. Attenuation of the PKCβII-ACSL4 pathway effectively blocks ferroptosis in vitro and impairs ferroptosis-associated cancer immunotherapy in vivo. Our results identify PKCβII as a sensor of lipid peroxidation, and the lipid peroxidation-PKCβII-ACSL4 positive-feedback axis may provide potential targets for ferroptosis-associated disease treatment. <<<

Diffusion weighted (DW) MRI facilitates non-invasive quantification of tissue microstructure and, in combination with appropriate signal processing, three-dimensional estimates of fibrous orientation. In recent years, attention has shifted from the diffusion tensor model, which assumes a unimodal Gaussian diffusion displacement profile to recover fibre orientation (with various well-documented limitations), towards more complex high angular resolution diffusion imaging (HARDI) analysis techniques. Spherical deconvolution (SD) approaches assume that the fibre orientation density function (fODF) within a voxel can be obtained by deconvolving a 'common' single fibre response function from the observed set of DW signals. In practice, this common response function is not known a priori and thus an estimated fibre response must be used. Here the establishment of this single-fibre response function is referred to as 'calibration'. This work examines the vulnerability of two different SD approaches to inappropriate response function calibration: (1) constrained spherical harmonic deconvolution (CSHD)--a technique that exploits spherical harmonic basis sets and (2) damped Richardson-Lucy (dRL) deconvolution--a technique based on the standard Richardson-Lucy deconvolution. Through simulations, the impact of a discrepancy between the calibrated diffusion profiles and the observed ('Target') DW-signals in both single and crossing-fibre configurations was investigated. The results show that CSHD produces spurious fODF peaks (consistent with well known ringing artefacts) as the discrepancy between calibration and target response increases, while dRL demonstrates a lower over-all sensitivity to miscalibration (with a calibration response function for a highly anisotropic fibre being optimal). However, dRL demonstrates a reduced ability to resolve low anisotropy crossing-fibres compared to CSHD. It is concluded that the range and spatial-distribution of expected single-fibre anisotropies within an image must be carefully considered to ensure selection of the appropriate algorithm, parameters and calibration. Failure to choose the calibration response function carefully may severely impact the quality of any resultant tractography. <<<

This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific--it is what it is by how it differs from alternative experiences; integration says that it is unified--irreducible to non-interdependent components; exclusion says that it has unique borders and a particular spatio-temporal grain. These axioms are formalized into postulates that prescribe how physical mechanisms, such as neurons or logic gates, must be configured to generate experience (phenomenology). The postulates are used to define intrinsic information as "differences that make a difference" within a system, and integrated information as information specified by a whole that cannot be reduced to that specified by its parts. By applying the postulates both at the level of individual mechanisms and at the level of systems of mechanisms, IIT arrives at an identity: an experience is a maximally irreducible conceptual structure (MICS, a constellation of concepts in qualia space), and the set of elements that generates it constitutes a complex. According to IIT, a MICS specifies the quality of an experience and integrated information ΦMax its quantity. From the theory follow several results, including: a system of mechanisms may condense into a major complex and non-overlapping minor complexes; the concepts that specify the quality of an experience are always about the complex itself and relate only indirectly to the external environment; anatomical connectivity influences complexes and associated MICS; a complex can generate a MICS even if its elements are inactive; simple systems can be minimally conscious; complicated systems can be unconscious; there can be true "zombies"--unconscious feed-forward systems that are functionally equivalent to conscious complexes. <<<

高效健全的银行体系是实体经济高质量发展的基石,本文基于2004—2017年105家商业银行数据构建时变"银行—股东"网络,从社会网络这一非正式制度视角考察网络结构对银行效率的影响和微观机制。研究发现:时变"银行—股东"网络中心度提升对银行效率具有积极影响,网络位置越中心,网络广度、中介程度越高,银行效率相对越高;在纳入表内外风险资产作为非期望产出进行效率估算后,网络中心度与银行效率的这一正向关系依然成立,但作用幅度有所降低;在传导机制上,网络中心度的提升通过"竞争机制"和"资源共享机制"改善银行整体效率。同时,银行的交叉持股水平、产权性质及银行类型会对网络结构与银行效率间的关系产生异质性影响。本研究为商业银行进行效率管理提供了来自非正式制度的全新分析视角,也为有关部门制定银行体系的发展战略提供了一定参考。 <<<

Stefanie Warnat-Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Händler, Peter Pickkers, N Ahmad Aziz, Sofia Ktena, Florian Tran, Michael Bitzer, Stephan Ossowski, Nicolas Casadei, Christian Herr, Daniel Petersheim, Uta Behrends, Fabian Kern, Tobias Fehlmann, Philipp Schommers, Clara Lehmann, Max Augustin, Jan Rybniker, Janine Altmüller, Neha Mishra, Joana P Bernardes, Benjamin Krämer, Lorenzo Bonaguro, Jonas Schulte-Schrepping, Elena De Domenico, Christian Siever, Michael Kraut, Milind Desai, Bruno Monnet, Maria Saridaki, Charles Martin Siegel, Anna Drews, Melanie Nuesch-Germano, Heidi Theis, Jan Heyckendorf, Stefan Schreiber, Sarah Kim-Hellmuth, COVID-19 Aachen Study (COVAS), Jacob Nattermann, Dirk Skowasch, Ingo Kurth, Andreas Keller, Robert Bals, Peter Nürnberg, Olaf Rieß, Philip Rosenstiel, Mihai G Netea, Fabian Theis, Sach Mukherjee, Michael Backes, Anna C Aschenbrenner, Thomas Ulas, Deutsche COVID-19 Omics Initiative (DeCOI), Monique M B Breteler, Evangelos J Giamarellos-Bourboulis, Matthijs Kox, Matthias Becker, Sorin Cheran, Michael S Woodacre, Eng Lim Goh, Joachim L Schultze <<<

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine. <<<

Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based approaches due to discrete binary activation and complex spatial-temporal dynamics. Considering the huge success of ResNet in deep learning, it would be natural to train deep SNNs with residual learning. Previous Spiking ResNet mimics the standard residual block in ANNs and simply replaces ReLU activation layers with spiking neurons, which suffers the degradation problem and can hardly implement residual learning. In this paper, we propose the spike-element-wise (SEW) ResNet to realize residual learning in deep SNNs. We prove that the SEW ResNet can easily implement identity mapping and overcome the vanishing/exploding gradient problems of Spiking ResNet. We evaluate our SEW ResNet on ImageNet, DVS Gesture, and CIFAR10-DVS datasets, and show that SEW ResNet outperforms the state-of-the-art directly trained SNNs in both accuracy and time-steps. Moreover, SEW ResNet can achieve higher performance by simply adding more layers, providing a simple method to train deep SNNs. To our best knowledge, this is the first time that directly training deep SNNs with more than 100 layers becomes possible. <<<

Volunteer role identity is regarded the direct and proximal cause of sustained volunteerism. Self-determination theory suggests that the quality of motivation greatly affects performance and well-being in various contexts. Therefore, this study investigated cross-lagged effects (over a time period of 16 months) between self-determined and controlled motivation, on the one hand, and two types of volunteer role identities, on the other hand: general role identity (GRI) and organization-specific role identity (OSRI). Analyses confirmed positive time-lagged effects of self-determined motivation on both GRI and OSRI. Time-lagged effects in opposite direction were significantly weaker; only OSRI showed a positive impact on subsequent self-determined motivation. OSRI (but not GRI) also had a positive lagged effect on controlled motivation. Overall, this study supported the idea that self-determined motivation represents a causal antecedent of volunteer role identities. <<<