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Pediatric COVID-19 vaccination is effective in preventing COVID-19-related hospitalization, but duration of protection of the original monovalent vaccine during SARS-CoV-2 Omicron predominance merits evaluation, particularly given low coverage with updated COVID-19 vaccines. During December 19, 2021-October 29, 2023, the Overcoming COVID-19 Network evaluated vaccine effectiveness (VE) of ≥2 original monovalent COVID-19 mRNA vaccine doses against COVID-19-related hospitalization and critical illness among U.S. children and adolescents aged 5-18 years, using a case-control design. Too few children and adolescents received bivalent or updated monovalent vaccines to separately evaluate their effectiveness. Most case-patients (persons with a positive SARS-CoV-2 test result) were unvaccinated, despite the high frequency of reported underlying conditions associated with severe COVID-19. VE of the original monovalent vaccine against COVID-19-related hospitalizations was 52% (95% CI = 33%-66%) when the most recent dose was administered

Childhood is marked by the rapid accumulation of knowledge and the prolific production of drawings. We conducted a systematic study of how children create and recognize line drawings of visual concepts. We recruited 2-10-year-olds to draw 48 categories via a kiosk at a childrens museum, resulting in >37K drawings. We analyze changes in the category-diagnostic information in these drawings using vision algorithms and annotations of object parts. We find developmental gains in childrens inclusion of category-diagnostic information that are not reducible to variation in visuomotor control or effort. Moreover, even unrecognizable drawings contain information about the animacy and size of the category children tried to draw. Using guessing games at the same kiosk, we find that children improve across childhood at recognizing each others line drawings. This work leverages vision algorithms to characterize developmental changes in childrens drawings and suggests that these changes reflect refinements in childrens internal representations.

Background: Rifampicin (RIF) is a key first-line drug used to treat tuberculosis, a primarily pulmonary disease caused by Mycobacterium tuberculosis. RIF resistance is caused by mutations in rpoB, at the cost of slower growth and reduced transcription efficiency. Antibiotic resistance to RIF is prevalent despite this fitness cost. Compensatory mutations in rpoABC genes have been shown to alleviate the fitness cost of rpoB:S450L, explaining how RIF resistant strains harbor this mutation can spread so rapidly. Unfortunately, the full set of RIF compensatory mutations is still unknown, particularly those compensating for rarer RIF resistance mutations. Objectives: We performed an association study on a globally representative set of 4,309 whole genome sequenced clinical M. tuberculosis isolates to identify novel putative compensatory mutations, determine the prevalence of known and previously reported putative compensatory mutations, and determine which RIF resistance markers associate with these compensatory mutations. Results and conclusions: Of the 1,079 RIF resistant isolates, 638 carried previously reported putative and high-probability compensatory mutations. Our strict criteria identified 46 additional mutations in rpoABC for which no strong prior evidence of their compensatory role exists. Of these, 35 have previously been reported. As such, our independent corroboration adds to the mounting evidence that these 35 also carry a compensatory role. The remaining 11 are novel putative compensatory markers, reported here for the first time. Six of these 11 novel putative compensatory mutations had two or more mutation events. Most compensatory mutations appear to be specifically compensating for the fitness loss due to rpoB:S450L. However, an outbreak of 22 closely related isolates each carried three rpoB mutations, the rare RIFR markers D435G and L452P and the putative compensatory mutation I1106T. This suggests compensation may require specific combinations of rpoABC mutations. Here, we report only mutations that met our very strict criteria. It is highly likely that many additional rpoABC mutations compensate for rare resistance-causing mutations and therefore did not carry the statistical power to be reported here. These findings aid in the identification of RIF resistant M. tuberculosis strains with restored fitness, which pose a greater risk of causing resistant outbreaks.

What structures children's early language environment? Large corpora of child-centered naturalistic recordings provide an important window into this question, but most available data centers on young children within the home or in lab contexts interacting primarily with a single caregiver. Here, we characterize children's language experience in a very different kind of environment: the preschool classroom. Children ages 3 – 5 years (N = 26) wore a head-mounted camera in their preschool class, yielding a naturalistic, egocentric view of children's everyday experience across many classroom activity contexts (e.g., sand play, snack time), with >30 hours of video data. Using semi-automatic transcriptions (227,624 words), we find that activity contexts in the preschool classroom vary in both the quality and quantity of the language that children both hear and produce. Together, these findings reinforce prior theories emphasizing the contribution of activity contexts in structuring the variability in children's early learning environments.

Retronychia is commonly underdiagnosed and exhibits classic features of proximal nail fold elevation and nail plate layering. Herein we summarize the literature and discuss cause, diagnosis, and treatment of this condition.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

BackgroundAutoantibodies against type I IFNs occur in approximately 10% of adults with life-threatening coronavirus disease 2019 (COVID-19). The frequency of anti-IFN autoantibodies in children with severe sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is unknown.ObjectiveWe quantified anti-type I IFN autoantibodies in a multicenter cohort of children with severe COVID-19, multisystem inflammatory syndrome in children (MIS-C), and mild SARS-CoV-2 infections.MethodsCirculating anti-IFN-α2 antibodies were measured by a radioligand binding assay. Whole-exome sequencing, RNA sequencing, and functional studies of peripheral blood mononuclear cells were used to study any patients with levels of anti-IFN-α2 autoantibodies exceeding the assay's positive control.ResultsAmong 168 patients with severe COVID-19, 199 with MIS-C, and 45 with mild SARS-CoV-2 infections, only 1 had high levels of anti-IFN-α2 antibodies. Anti-IFN-α2 autoantibodies were not detected in patients treated with intravenous immunoglobulin before sample collection. Whole-exome sequencing identified a missense variant in the ankyrin domain of NFKB2, encoding the p100 subunit of nuclear factor kappa-light-chain enhancer of activated B cells, aka NF-κB, essential for noncanonical NF-κB signaling. The patient's peripheral blood mononuclear cells exhibited impaired cleavage of p100 characteristic of NFKB2 haploinsufficiency, an inborn error of immunity with a high prevalence of autoimmunity.ConclusionsHigh levels of anti-IFN-α2 autoantibodies in children and adolescents with MIS-C, severe COVID-19, and mild SARS-CoV-2 infections are rare but can occur in patients with inborn errors of immunity.

BACKGROUND: Influenza virus is responsible for a large global burden of disease, especially in children. Multiple Organ Dysfunction Syndrome (MODS) is a life-threatening and fatal complication of severe influenza infection. METHODS: We measured RNA expression of 469 biologically plausible candidate genes in children admitted to North American pediatric intensive care units with severe influenza virus infection with and without MODS. Whole blood samples from 191 influenza-infected children (median age 6.4 years, IQR: 2.2, 11) were collected a median of 27 hours following admission; for 45 children a second blood sample was collected approximately seven days later. Extracted RNA was hybridized to NanoString mRNA probes, counts normalized, and analyzed using linear models controlling for age and bacterial co-infections (FDR q

Richter syndrome (RS) arising from chronic lymphocytic leukemia (CLL) exemplifies an aggressive malignancy that develops from an indolent neoplasm. To decipher the genetics underlying this transformation, we computationally deconvoluted admixtures of CLL and RS cells from 52 patients with RS, evaluating paired CLL-RS whole-exome sequencing data. We discovered RS-specific somatic driver mutations (including IRF2BP2, SRSF1, B2M, DNMT3A and CCND3), recurrent copy-number alterations beyond del(9p21)(CDKN2A/B), whole-genome duplication and chromothripsis, which were confirmed in 45 independent RS cases and in an external set of RS whole genomes. Through unsupervised clustering, clonally related RS was largely distinct from diffuse large B cell lymphoma. We distinguished pathways that were dysregulated in RS versus CLL, and detected clonal evolution of transformation at single-cell resolution, identifying intermediate cell states. Our study defines distinct molecular subtypes of RS and highlights cell-free DNA analysis as a potential tool for early diagnosis and monitoring.

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.

COVID-19 vaccination is recommended for persons who are pregnant, breastfeeding, trying to get pregnant now, or who might become pregnant in the future, to protect them from COVID-19.§ Infants are at risk for life-threatening complications from COVID-19, including acute respiratory failure (1). Evidence from other vaccine-preventable diseases suggests that maternal immunization can provide protection to infants, especially during the high-risk first 6 months of life, through passive transplacental antibody transfer (2). Recent studies of COVID-19 vaccination during pregnancy suggest the possibility of transplacental transfer of SARS-CoV-2-specific antibodies that might provide protection to infants (3-5); however, no epidemiologic evidence currently exists for the protective benefits of maternal immunization during pregnancy against COVID-19 in infants. The Overcoming COVID-19 network conducted a test-negative, case-control study at 20 pediatric hospitals in 17 states during July 1, 2021-January 17, 2022, to assess effectiveness of maternal completion of a 2-dose primary mRNA COVID-19 vaccination series during pregnancy against COVID-19 hospitalization in infants. Among 379 hospitalized infants aged

Neutralization capacity of antibodies against Omicron after a prior SARS-CoV-2 infection in children and adolescents is not well studied. Therefore, we evaluated virus-neutralizing capacity against SARS-CoV-2 Alpha, Beta, Gamma, Delta and Omicron variants by age-stratified analyses (5 years of age. As expected, convalescent pediatric COVID-19 and MIS-C cohorts demonstrate higher neutralization titers than hospitalized acute COVID-19 patients. Overall, children and adolescents show some loss of cross-neutralization against all variants, with the most pronounced loss against Omicron. In contrast to SARS-CoV-2 infection, children vaccinated twice demonstrated higher titers against Alpha, Beta, Gamma, Delta and Omicron. These findings can influence transmission, re-infection and the clinical disease outcome from emerging SARS-CoV-2 variants and supports the need for vaccination in children.

Children produce increasingly more recognizable drawings of object concepts throughout childhood. What drives this improvement? Here we explore the role of children's ability to include relevant parts of those objects in their drawings. We crowdsourced part tags for every pen stroke in 2,160 drawings of 16 common object categories that had been produced by children between 4 and 8 years old. These part decompositions revealed both substantial variation in the number and kind of parts that children emphasized, as well as a non-monotonic relationship between the number of parts that children drew and how recognizable their drawing was. We plan to publicly release these data to catalyze further investigation of how children's drawings change across development.

Curiosity is a fundamental driver of human behavior, and yet because of its open-ended nature and the wide variety of behaviors it inspires in different contexts, it is remarkably difficult to study in a laboratory context. A promising approach to developing and testing theories of curiosity is to instantiate them in artificial agents that are able to act and explore in a simulated environment, and then compare the behavior of these agents to humans exploring the same stimuli. Here we propose a new experimental paradigm for examining children's -- and AI agents' -- curiosity about objects' physical interactions. We let them choose which object to drop another object onto in order to create the most interesting effect. We compared adults' (N=155) and children's choices (N=66; 3-7 year-olds) and found that both children and adults show a strong preference for choosing target objects that could potentially contain the dropped object. Adults alone also make choices consistent with achieving support relations. We contextualize our results using heuristic computational models based on 3D physical simulations of the same scenarios judged by participants.

What do infants and young children tend to see in their everyday lives? Relatively little work has examined the categories and objects that tend to be in the infant view during everyday experience, despite the fact that this knowledge is central to theories of category learning. Here, we analyzed the prevalence of the categories (e.g., people, animals, food) in the infant view in a longitudinal dataset of egocentric infant visual experience. Overall, we found a surprising amount of consistency in the broad characteristics of children's visual environment across individuals and across developmental time, in contrast to prior work examining the changing nature of the social signals in the infant view. In addition, we analyzed the distribution and identity of the categories that children tended touch and interact with in this dataset, generalizing previous findings that these objects tended to be distributed in a Zipfian manner. Taken together, these findings take a first step towards characterizing infants' changing visual environment, and call for future work to examine the generalizability of these results and to link them to learning outcomes.

The ability to rapidly recognize words and link them to referents in context is central to children's early language development. This ability, often called word recognition in the developmental literature, is typically studied in the looking-while-listening paradigm, which measures infants' fixation on a target object (vs. a distractor) after hearing a target label. We present a large-scale, open database of infant and toddler eye-tracking data from looking-while-listening tasks. The goal of this effort is to address theoretical and methodological challenges in measuring vocabulary development. We present two analyses of the current database (N=1,320): (1) capturing age-related changes in infants' word recognition while generalizing across item-level variability and (2) assessing how a central methodological decision -- selecting the time window of analysis -- impacts the reliability of measurement. Future efforts will expand the scope of the current database to advance our understanding of participant-level and item-level variation in children's vocabulary development.

OBJECTIVE:Neonates with seizures have a high risk of mortality and neurological morbidity. We aimed to describe the experience of parents caring for neonates with seizures. DESIGN:This prospective, observational and multicentre (Neonatal Seizure Registry) study enrolled parents of neonates with acute symptomatic seizures. At the time of hospital discharge, parents answered six open-ended response questions that targeted their experience. Responses were analysed using a conventional content analysis approach. RESULTS:144 parents completed the open-ended questions (732 total comments). Four themes were identified. Sources of strength: families valued medical team consensus, opportunities to contribute to their child's care and bonding with their infant. Uncertainty: parents reported three primary types of uncertainty, all of which caused distress: (1) the daily uncertainty of the intensive care experience; (2) concerns about their child's uncertain future and (3) lack of consensus between members of the medical team. Adapting family life: parents described the many ways in which they anticipated their infant's condition would lead to adaptations in their family life, including adjusting their family's lifestyle, parenting approach and routine. Many parents described financial and work challenges due to caring for a child with medical needs. Emotional and physical toll: parents reported experiencing anxiety, fear, stress, helplessness and loss of sleep. CONCLUSIONS:Parents of neonates with seizures face challenges as they adapt to and find meaning in their role as a parent of a child with medical needs. Future interventions should target facilitating parent involvement in clinical and developmental care, improving team consensus and reducing the burden associated with prognostic uncertainty.

We sought to understand the role of parent engagement in overcoming barriers to care for youth re-entering the community following incarceration. For this mixed methods study, we conducted quantitative surveys on healthcare needs and access with youth (n = 50) at 1-month post-incarceration, and semi-structured interviews with a subset of these youth (n = 27) and their parents (n = 34) at 1, 3, and 6-months post-incarceration (total 94 interviews). Differences by race/ethnicity and gender were assessed using Chi square test of proportions. We performed thematic analysis of interview transcripts to examine the role of parent engagement in influencing youths' access to healthcare during reentry. Most youth were from racial/ethnic minority groups and reported multiple ACEs. Girls, compared to boys, had higher ACE scores (p = 0.03), lower family connectedness (p = 0.03), and worse general health (p = 0.02). Youth-identified barriers to care were often parent-dependent and included lack of: affordable care (22%), transportation (16%), and accompaniment to health visits (14%). Two major themes emerged from the qualitative interviews: (1) parents motivate youth to seek healthcare during reentry and (2) parents facilitate the process of youth seeking healthcare during reentry. Parents are instrumental in linking youth to healthcare during reentry, dispelling prevailing myths that parents of incarcerated youth are inattentive and that youth do not want their help. Efforts that support and enhance parent engagement in access to care during reentry, such as by actively involving parents in pre-release healthcare planning, may create stronger linkages to care.

The faces and hands of caregivers and other social partners offer a rich source of social and causal information thatmay be critical for infants cognitive and linguistic development. Previous work using manual annotation strategies andcross-sectional data has found systematic changes in the proportion of faces and hands in the egocentric perspective ofyoung infants. Here, we examine the prevalence of faces and hands in a longitudinal collection of nearly 1700 headcamvideos collected from three children along a span of 6 to 32 months of agethe SAYCam dataset (Sullivan, Mei, Perfors,Wojcik, & Frank, under review). To analyze these naturalistic infant egocentric videos, we first validated the use of amodern convolutional neural network of pose detection (OpenPose) for the detection of faces and hands. We then appliedthis model to the entire dataset, and found a higher proportion of hands in view than previous reported and a moderatedecrease the proportion of faces in childrens view across age. In addition, we found variability in the proportion offaces/hands viewed by different children in different locations (e.g., living room vs. kitchen), suggesting that individualactivity contexts may shape the social information that infants experience.

BackgroundPaediatric acute respiratory distress syndrome (PARDS) is associated with high mortality in children, but until recently no paediatric-specific diagnostic criteria existed. The Pediatric Acute Lung Injury Consensus Conference (PALICC) definition was developed to overcome limitations of the Berlin definition, which was designed and validated for adults. We aimed to determine the incidence and outcomes of children who meet the PALICC definition of PARDS.MethodsIn this international, prospective, cross-sectional, observational study, 145 paediatric intensive care units (PICUs) from 27 countries were recruited, and over a continuous 5 day period across 10 weeks all patients were screened for enrolment. Patients were included if they had a new diagnosis of PARDS that met PALICC criteria during the study week. Exclusion criteria included meeting PARDS criteria more than 24 h before screening, cyanotic heart disease, active perinatal lung disease, and preparation or recovery from a cardiac intervention. Data were collected on the PICU characteristics, patient demographics, and elements of PARDS (ie, PARDS risk factors, hypoxaemia severity metrics, type of ventilation), comorbidities, chest imaging, arterial blood gas measurements, and pulse oximetry. The primary outcome was PICU mortality. Secondary outcomes included 90 day mortality, duration of invasive mechanical and non-invasive ventilation, and cause of death.FindingsBetween May 9, 2016, and June 16, 2017, during the 10 study weeks, 23 280 patients were admitted to participating PICUs, of whom 744 (3·2%) were identified as having PARDS. 95% (708 of 744) of patients had complete data for analysis, with 17% (121 of 708; 95% CI 14-20) mortality, whereas only 32% (230 of 708) of patients met Berlin criteria with 27% (61 of 230) mortality. Based on hypoxaemia severity at PARDS diagnosis, mortality was similar among those who were non-invasively ventilated and with mild or moderate PARDS (10-15%), but higher for those with severe PARDS (33% [54 of 165; 95% CI 26-41]). 50% (80 of 160) of non-invasively ventilated patients with PARDS were subsequently intubated, with 25% (20 of 80; 95% CI 16-36) mortality. By use of PALICC PARDS definition, severity of PARDS at 6 h after initial diagnosis (area under the curve [AUC] 0·69, 95% CI 0·62-0·76) discriminates PICU mortality better than severity at PARDS diagnosis (AUC 0·64, 0·58-0·71), and outperforms Berlin severity groups at 6 h (0·64, 0·58-0·70; p=0·01).InterpretationThe PALICC definition identified more children as having PARDS than the Berlin definition, and PALICC PARDS severity groupings improved the stratification of mortality risk, particularly when applied 6 h after PARDS diagnosis. The PALICC PARDS framework should be considered for use in future epidemiological and therapeutic research among children with PARDS.FundingUniversity of Southern California Clinical Translational Science Institute, Sainte Justine Children's Hospital, University of Montreal, Canada, Réseau en Santé Respiratoire du Fonds de Recherche Quebec-Santé, and Children's Hospital Los Angeles, Department of Anesthesiology and Critical Care Medicine.

How do children’s visual concepts change across childhood,and how might these changes be reflected in their drawings?Here we investigate developmental changes in children’s abil-ity to emphasize the relevant visual distinctions between objectcategories in their drawings. We collected over 13K drawingsfrom children aged 2-10 years via a free-standing drawing sta-tion in a children’s museum. We hypothesized that older chil-dren would produce more recognizable drawings, and that thisgain in recognizability would not be entirely explained by con-current development in visuomotor control. To measure recog-nizability, we applied a pretrained deep convolutional neuralnetwork model to extract a high-level feature representation ofall drawings, and then trained a multi-way linear classifier onthese features. To measure visuomotor control, we developedan automated procedure to measure their ability to accuratelytrace complex shapes. We found consistent gains in the recog-nizability of drawings across ages that were not fully explainedby children’s ability to accurately trace complex shapes. Fur-thermore, these gains were accompanied by an increase in howdistinct different object categories were in feature space. Over-all, these results demonstrate that children’s drawings includemore distinctive visual features as they grow older.

How do children’s representations of object categories changeas they grow older? As they learn about the world aroundthem, they also express what they know in the drawings theymake. Here, we examine drawings as a window into how chil-dren represent familiar object categories, and how this changesacross childhood. We asked children (age 3-10 years) to drawfamiliar object categories on an iPad. First, we analyzed theirsemantic content, finding large and consistent gains in howwell children could produce drawings that are recognizable toadults. Second, we quantified their perceptual similarity toadult drawings using a pre-trained deep convolutional neuralnetwork, allowing us to visualize the representational layoutof object categories across age groups using a common featurebasis. We found that the organization of object categories inolder children’s drawings were more similar to that of adultsthan younger children’s drawings. This correspondence wasstrong in the final layers of the neural network, showing thatolder children’s drawings tend to capture the perceptual fea-tures critical for adult recognition. We hypothesize that thisimprovement reflects increasing convergence between chil-dren’s representations of object categories and that of adults;future work will examine how these age-related changes re-late to children’s developing perceptual and motor capacities.Broadly, these findings point to drawing as a rich source ofinsight into how children represent object concepts.

The ability to process social information is a critical compo-nent of children’s early language and cognitive development.However, as children reach their first birthday, they begin tolocomote themselves, dramatically affecting their visual ac-cess to this information. How do these postural and locomotorchanges affect children’s access to the social information rele-vant for word-learning? Here, we explore this question by us-ing head-mounted cameras to record 36 infants’ (8-16 monthsof age) egocentric visual perspective and use computer visionalgorithms to estimate the proportion of faces and hands in in-fants’ environments. We find that infants’ posture and orienta-tion to their caregiver modulates their access to social informa-tion, confirming previous work that suggests motoric develop-ments play a significant role in the emergence of children’s lin-guistic and social capacities. We suggest that the combined useof head-mounted cameras and the application of new computervision techniques is a promising avenue for understanding thestatistics of infants’ visual and linguistic experience.

The title compound, [Mn(2)O(2)(C(10)H(24)N(4))(2)](C(24)H(20)B)(2)Cl·2CH(3)CN, is a mixed-valent Mn(III)/Mn(IV) oxide-bridged mangan-ese dimer with one chloride and two tetra-phenyl-borate counter-anions. There are two non-coordinated mol-ecules of acetonitrile in the formula unit. A center of inversion is present between the two metal atoms, and, consequently, there is no distinction between Mn(III) and Mn(IV) metal centers. In the Mn(2)O(2) core, the Mn-O distances are 1.817 (3) and 1.821 (3) Å. The cyclam ligand is in the cis configuration. The chloride counter-anion resides on a center of symmetry, whereas the tetra-phenyl-borate counter-anion is in a general position. The cyclam ligand is hydrogen bonded to the acetonitrile as well as to the chloride anion. One of the phenyl rings of the anion and the acetonitrile solvent molecule are each disordered over two sets of sites.

The title compound, [Mn(2)O(2)(C(10)H(24)N(4))(2)](C(24)H(20)B)(2)Cl·2CH(3)CN, is a mixed-valent Mn(III)/Mn(IV) oxide-bridged mangan-ese dimer with one chloride and two tetra-phenyl-borate counter-anions. There are two non-coordinated mol-ecules of acetonitrile in the formula unit. A center of inversion is present between the two metal atoms, and, consequently, there is no distinction between Mn(III) and Mn(IV) metal centers. In the Mn(2)O(2) core, the Mn-O distances are 1.817 (3) and 1.821 (3) Å. The cyclam ligand is in the cis configuration. The chloride counter-anion resides on a center of symmetry, whereas the tetra-phenyl-borate counter-anion is in a general position. The cyclam ligand is hydrogen bonded to the acetonitrile as well as to the chloride anion. One of the phenyl rings of the anion and the acetonitrile solvent molecule are each disordered over two sets of sites.