Polygenic sex determination produces modular sex polymorphism in an African cichlid fish.

For many vertebrates, a single genetic locus initiates a cascade of developmental sex differences in the gonad and throughout the organism, resulting in adults with two phenotypically distinct sexes. Species with polygenic sex determination (PSD) have multiple interacting sex determination alleles segregating within a single species, allowing for more than two genotypic sexes and scenarios where sex genotype at a given locus can be decoupled from gonadal sex. Here we investigate the effects of PSD on secondary sexual characteristics in the cichlid fish Metriaclima mbenjii, where one female (W) and one male (Y) sex determination allele interact to produce siblings with four possible sex classes: ZZXX females, ZWXX females, ZWXY females, and ZZXY males. We find that PSD in M. mbenjii produces an interplay of sex linkage and sex limitation resulting in modular variation in morphological and behavioral traits. Further, the evolution or introgression of a newly acquired sex determiner creates additional axes of phenotypic variation for varied traits, including genital morphology, craniofacial morphology, gastrointestinal morphology, and home tank behaviors. In contrast to single-locus sex determination, which broadly results in sexual dimorphism, polygenic sex determination can induce higher-order sexual polymorphism. The modularity of secondary sexual characteristics produced by PSD provides context for understanding the evolutionary causes and consequences of maintenance, gain, or loss of sex determination alleles in populations.

Household Transmission of Mpox to Children and Adolescents, California, 2022.

BACKGROUND: In California, the 2022 mpox outbreak cumulated 5572 cases, 20% of US cases, as of November 28, 2022; 0.3% of cases were among children <16 years old. The secondary attack rate (SAR) for children sharing households with infected adults is unknown. METHODS: A line list of pediatric mpox household contacts aged <16 years reported through August 31, 2022 was created. It included demographic and clinical information on the contacts. Pediatric contact lists were crossmatched with the state vaccination database to identify those who received postexposure prophylaxis (PEP) with the JYNNEOS vaccine. RESULTS: We identified 129 pediatric household contacts with median age of 7 years (range, 0-15 years). Among 18 symptomatic contacts, 12 (66.7%) underwent mpox testing; 5 (41.2%) were confirmed cases, 6 (50%) were negative, and 1 (0.8%) had an indeterminate result. Six symptomatic children were not tested for mpox (33.3%). Overall, 6 infected contacts were identified, resulting in a SAR of 4.7% (6 of 129). The majority of pediatric household contacts and 4 of 6 infected children identified as Hispanic/Latino. Only 18 children (14%) reported receiving PEP. CONCLUSIONS: The SAR was overall low among pediatric household contacts; none had severe disease. This may be underestimated given low testing rates.

Regulating Singlet-Triplet Energy Gaps through Substituent-Driven Modulation of the Exchange and Coulomb Interactions.

Control of the singlet-triplet energy gap (ΔEST) is central to realizing productive energy conversion reactions, photochemical reaction trajectories, and emergent applications that exploit molecular spin physics. Despite this, no systematic methods have been defined to tune ΔEST in simple molecular frameworks, let alone by an approach that also holds chromophore size and electronic structural parameters (such as the HOMO-LUMO gap) constant. Using a combination of molecular design, photophysical and potentiometric experiments, and quantum chemical analyses, we show that the degree of electron-electron repulsion in excited singlet and triplet states may be finely controlled through the substitution pattern of a simple porphyrin absorber, enabling regulation of relative electronically excited singlet and triplet state energies by the designed restriction of the electron-electron Coulomb (J) and exchange (K) interaction magnitudes. This approach modulates the ΔEST magnitude by controlling the densities of state in the occupied and virtual molecular orbital manifolds, natural transition orbital polarization, and the relative contributions of one electron transitions involving select natural transition orbital pairs. This road map, which regulates electron density overlaps in the occupied and virtual states that define the singlet and triplet wave functions of these chromophores, enables new approaches to preserve excitation energy despite intersystem crossing.

Increasing Incidence of Invasive Group A Streptococcus Disease, Idaho, USA, 2008-2019.

We investigated invasive group A Streptococcus epidemiology in Idaho, USA, during 2008-2019 using surveillance data, medical record review, and emm (M protein gene) typing results. Incidence increased from 1.04 to 4.76 cases/100,000 persons during 2008-2019. emm 1, 12, 28, 11, and 4 were the most common types, and 2 outbreaks were identified. We examined changes in distribution of clinical syndrome, patient demographics, and risk factors by comparing 2008-2013 baseline with 2014-2019 data. Incidence was higher among all age groups during 2014-2019. Streptococcal toxic shock syndrome increased from 0% to 6.4% of cases (p = 0.02). We identified no differences in distribution of demographic or risk factors between periods. Results indicated that invasive group A Streptococcus is increasing among the general population of Idaho. Ongoing surveillance of state-level invasive group A Streptococcus cases could help identify outbreaks, track regional trends in incidence, and monitor circulating emm types.

Forecasting intensifying disturbance effects on coral reefs.

Anticipating future changes of an ecosystem's dynamics requires knowledge of how its key communities respond to current environmental regimes. The Great Barrier Reef (GBR) is under threat, with rapid changes of its reef-building hard coral (HC) community structure already evident across broad spatial scales. While several underlying relationships between HC and multiple disturbances have been documented, responses of other benthic communities to disturbances are not well understood. Here we used statistical modelling to explore the effects of broad-scale climate-related disturbances on benthic communities to predict their structure under scenarios of increasing disturbance frequency. We parameterized a multivariate model using the composition of benthic communities estimated by 145,000 observations from the northern GBR between 2012 and 2017. During this time, surveyed reefs were variously impacted by two tropical cyclones and two heat stress events that resulted in extensive HC mortality. This unprecedented sequence of disturbances was used to estimate the effects of discrete versus interacting disturbances on the compositional structure of HC, soft corals (SC) and algae. Discrete disturbances increased the prevalence of algae relative to HC while the interaction between cyclones and heat stress was the main driver of the increase in SC relative to algae and HC. Predictions from disturbance scenarios included relative increases in algae versus SC that varied by the frequency and types of disturbance interactions. However, high uncertainty of compositional changes in the presence of several disturbances shows that responses of algae and SC to the decline in HC needs further research. Better understanding of the effects of multiple disturbances on benthic communities as a whole is essential for predicting the future status of coral reefs and managing them in the light of new environmental regimes. The approach we develop here opens new opportunities for reaching this goal.

Detecting Technical Anomalies in High-Frequency Water-Quality Data Using Artificial Neural Networks.

Anomaly detection (AD) in high-volume environmental data requires one to tackle a series of challenges associated with the typical low frequency of anomalous events, the broad-range of possible anomaly types, and local nonstationary environmental conditions, suggesting the need for flexible statistical methods that are able to cope with unbalanced high-volume data problems. Here, we aimed to detect anomalies caused by technical errors in water-quality (turbidity and conductivity) data collected by automated in situ sensors deployed in contrasting riverine and estuarine environments. We first applied a range of artificial neural networks that differed in both learning method and hyperparameter values, then calibrated models using a Bayesian multiobjective optimization procedure, and selected and evaluated the "best" model for each water-quality variable, environment, and anomaly type. We found that semi-supervised classification was better able to detect sudden spikes, sudden shifts, and small sudden spikes, whereas supervised classification had higher accuracy for predicting long-term anomalies associated with drifts and periods of otherwise unexplained high variability.

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity.

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968-2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33-0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.

Improving the Health of Alaska Native People Through Use of a Policy Change Model and Capacity Building.

Public health training often includes program and education development but not policy, systems, and environmental (PSE) strategies. The Alaska Native Tribal Health Consortium's Good Health and Wellness in Indian Country program works to build tribal PSE change capacity. Trainings included community health assessment, facilitation and leadership engagement, policy and systems, and digital storytelling. From 2014 to 2017, 30 PSE changes were made: 3 tobacco-free healthcare organization policies; 2 tobacco-free tribal resolutions; 1 tobacco-free school district policy; 3 healthy food policies and environmental changes; 4 improvements in patient-provider communication; 13 prediabetes, obesity, and/or tobacco screening and referral policies; 3 improvements to health care facility signage; and 1 Baby-friendly Hospital application, protecting the health of 46,000 tribal community members. Targeted training and technical assistance moved tribal staff from a focus on direct services to population-based improvements. This increased self-efficacy may increase the sustainability of chronic disease public health efforts and improve tribal health.

Cleft and Craniofacial Multidisciplinary Team Clinic: A Look at Attrition Rates for Patients With Complete Cleft Lip and Palate and Nonsyndromic Single-Suture Craniosynostosis.

OBJECTIVE: To evaluate attrition rates prior to expected completion of team care for children with complete cleft lip and palate (cleft) or nonsyndromic single-suture craniosynostosis (synostosis). DESIGN: A single-institution retrospective review of attendance data from 2002 to 2016. SETTING: Single cleft and craniofacial center in the United States. PATIENTS/PARTICIPANTS: A sample of 983 patients with either cleft or synostosis. Patients who were more than 2 to 3 years from their last visit were considered lost to follow-up. Patients with cleft older than 16 years or synostosis over 11 years were considered graduated from team care. RESULTS: Survival analysis shows that in our patients with cleft, 25% leave before age 8 and over 60% are lost from team by age 16. In patients with synostosis, 25% leave before age 6 and 45% are lost by age 11. Cox regression showed underrepresented minorities being 1.7 times more likely to become lost in the cleft group (hazard ratio: 1.66, 95% confidence interval [CI]: 1.01-2.74). CONCLUSIONS: Overall, attrition rates were high at our institution. Many patients are lost to follow-up prior to receiving key medical interventions. Improved family education and personalized care are needed to help ensure continuity of care.

Community and Street-Scale Supports for Walking in the US Virgin Islands Before the 2017 Hurricanes.

OBJECTIVES: To determine the prevalence of community and street-scale design features that promote walking across the US Virgin Islands (USVI). METHODS: In May 2016, the USVI Department of Health, with technical assistance from the Centers for Disease Control and Prevention, conducted a territory-wide audit with a validated tool. We selected street segments (n = 1114) via a 2-stage sampling method, and estimates were weighted to be representative of publicly accessible street length. RESULTS: Overall, 10.7% of the street length contained a transit stop, 11.3% had sidewalks, 21.7% had at least 1 destination (e.g., stores, restaurants), 27.4% had a traffic calming feature (e.g., speed humps), and 53.2% had at least some street lighting. Several features were less prevalent on residential streets compared with commercial streets, including transit stops, sidewalks, destinations, and street lighting (P < .01). CONCLUSIONS: Across the USVI, community and street-scale features supportive of walking were uncommon. Improving community and street-scale design in the USVI, particularly in residential areas, could increase physical activity by enhancing walkability and therefore improve public health. These data can be used to inform community planning in the USVI.

Prevalence of master plans supportive of active living in US municipalities.

Community planning documents can play an important role in promoting the design and maintenance of walkable communities. This study estimates the prevalence among US municipalities of (1) community wide planning documents and (2) inclusion of plan objectives supportive of active living within these documents. Data from the 2014 National Survey of Community-Based Policy and Environmental Supports for Healthy Eating and Active Living (CBS HEAL), a survey of local officials, were analyzed (n = 2005). Prevalence of comprehensive or general plans, 3 specific plan types, and 3 objectives supportive of active living were analyzed using survey weights to create national estimates. Overall, 64% of municipalities had a comprehensive/general plan, 46% had a transportation plan, 48% had a bicycle or pedestrian plan and 76% had a land use plan. Of municipalities with a plan, 78% included at least one of the three objectives measured supportive of active living. Differences in presence of plans and objectives were observed by population size of the municipality, urban status, region, and median education. Helping communities, especially smaller or rural municipalities and those with lower median education levels, create and adopt planning documents supportive of active living may be an important step in creating more walkable communities.

Genetic sex determination in Astatotilapia calliptera, a prototype species for the Lake Malawi cichlid radiation.

East African cichlids display extensive variation in sex determination systems. The species Astatotilapia calliptera is one of the few cichlids that reside both in Lake Malawi and in surrounding waterways. A. calliptera is of interest in evolutionary studies as a putative immediate outgroup species for the Lake Malawi species flock and possibly as a prototype ancestor-like species for the radiation. Here, we use linkage mapping to test association of sex in A. calliptera with loci that have been previously associated with genetic sex determination in East African cichlid species. We identify a male heterogametic XY system segregating at linkage group (LG) 7 in an A. calliptera line that originated from Lake Malawi, at a locus previously shown to act as an XY sex determination system in multiple species of Lake Malawi cichlids. Significant association of genetic markers and sex produce a broad genetic interval of approximately 26 megabases (Mb) using the Nile tilapia genome to orient markers; however, we note that the marker with the strongest association with sex is near a gene that acts as a master sex determiner in other fish species. We demonstrate that alleles of the marker are perfectly associated with sex in Metriaclima mbenjii, a species from the rock-dwelling clade of Lake Malawi. While we do not rule out the possibility of other sex determination loci in A. calliptera, this study provides a foundation for fine mapping of the cichlid sex determination gene on LG7 and evolutionary context regarding the origin and persistence of the LG7 XY across diverse, rapidly evolving lineages.

Modelling dendritic ecological networks in space: an integrated network perspective.

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Indexing and partitioning the spatial linear model for large data sets.

We consider four main goals when fitting spatial linear models: 1) estimating covariance parameters, 2) estimating fixed effects, 3) kriging (making point predictions), and 4) block-kriging (predicting the average value over a region). Each of these goals can present different challenges when analyzing large spatial data sets. Current research uses a variety of methods, including spatial basis functions (reduced rank), covariance tapering, etc, to achieve these goals. However, spatial indexing, which is very similar to composite likelihood, offers some advantages. We develop a simple framework for all four goals listed above by using indexing to create a block covariance structure and nearest-neighbor predictions while maintaining a coherent linear model. We show exact inference for fixed effects under this block covariance construction. Spatial indexing is very fast, and simulations are used to validate methods and compare to another popular method. We study various sample designs for indexing and our simulations showed that indexing leading to spatially compact partitions are best over a range of sample sizes, autocorrelation values, and generating processes. Partitions can be kept small, on the order of 50 samples per partition. We use nearest-neighbors for kriging and block kriging, finding that 50 nearest-neighbors is sufficient. In all cases, confidence intervals for fixed effects, and prediction intervals for (block) kriging, have appropriate coverage. Some advantages of spatial indexing are that it is available for any valid covariance matrix, can take advantage of parallel computing, and easily extends to non-Euclidean topologies, such as stream networks. We use stream networks to show how spatial indexing can achieve all four goals, listed above, for very large data sets, in a matter of minutes, rather than days, for an example data set.

Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data.

Real-time monitoring using in-situ sensors is becoming a common approach for measuring water-quality within watersheds. High-frequency measurements produce big datasets that present opportunities to conduct new analyses for improved understanding of water-quality dynamics and more effective management of rivers and streams. Of primary importance is enhancing knowledge of the relationships between nitrate, one of the most reactive forms of inorganic nitrogen in the aquatic environment, and other water-quality variables. We analysed high-frequency water-quality data from in-situ sensors deployed in three sites from different watersheds and climate zones within the National Ecological Observatory Network, USA. We used generalised additive mixed models to explain the nonlinear relationships at each site between nitrate concentration and conductivity, turbidity, dissolved oxygen, water temperature, and elevation. Temporal auto-correlation was modelled with an auto-regressive-moving-average (ARIMA) model and we examined the relative importance of the explanatory variables. Total deviance explained by the models was high for all sites (99%). Although variable importance and the smooth regression parameters differed among sites, the models explaining the most variation in nitrate contained the same explanatory variables. This study demonstrates that building a model for nitrate using the same set of explanatory water-quality variables is achievable, even for sites with vastly different environmental and climatic characteristics. Applying such models will assist managers to select cost-effective water-quality variables to monitor when the goals are to gain a spatial and temporal in-depth understanding of nitrate dynamics and adapt management plans accordingly.

Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score.

Catchment and riparian degradation has resulted in declining ecosystem health of streams worldwide. With restoration a priority in many regions, there is an increasing interest in the scale at which land use influences stream ecosystem health. Our goal was to use a substantial data set collected as part of a monitoring program (the Southeast Queensland, Australia, Ecological Health Monitoring Program data set, collected at 116 sites over six years) to identify the spatial scale of land use, or the combination of spatial scales, that most strongly influences overall ecosystem health. In addition, we aimed to determine whether the most influential scale differed for different aspects of ecosystem health. We used linear-mixed models and a Bayesian model-averaging approach to generate models for the overall aggregated ecosystem health score and for each of the five component indicators (fish, macroinvertebrates, water quality, nutrients, and ecosystem processes) that make up the score. Dense forest close to the survey site, mid-dense forest in the hydrologically active near-stream areas of the catchment, urbanization in the riparian buffer, and tree cover at the reach scale were all significant in explaining ecosystem health, suggesting an overriding influence of forest cover, particularly close to the stream. Season and antecedent rainfall were also important explanatory variables, with some land-use variables showing significant seasonal interactions. There were also differential influences of land use for each of the component indicators. Our approach is useful given that restoring general ecosystem health is the focus of many stream restoration projects; it allowed us to predict the scale and catchment position of restoration that would result in the greatest improvement of ecosystem health in the regions streams and rivers. The models we generated suggested that good ecosystem health can be maintained in catchments where 80% of hydrologically active areas in close proximity to the stream have mid-dense forest cover and moderate health can be obtained with 60% cover.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species-juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)-in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69-95%, 51-87%, and 86-100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.