Converting estimated breeding values from the observed to probability scale for health traits.

Dairy cattle health traits are paramount from a welfare and economic viewpoint; therefore, modern breeding programs prioritize the genetic improvement of these traits. Estimated breeding values for health traits are published as the probability of animals staying healthy. They are obtained using threshold models, which assume that the observed binary phenotype (i.e., healthy or sick) is dictated by an underlying normally distributed liability exceeding or not a threshold. This methodology requires significant computing time and faces convergence challenges as it implies a nonlinear system of equations. Linear models have more straightforward computations and provide a robust approximation to threshold models; thus, they could be used to overcome the mentioned challenges. However, linear models yield estimated breeding values on the observed scale, requiring an approximation to the liability scale analogous to that from threshold models to later obtain the estimated breeding values on the probability scale. In addition, the robustness of the approximation of linear to threshold models depends on the amount of information and the incidence of the trait, with extreme incidence (i.e., ≤ 5%) deviating from optimal approximation. Our objective was to test a transformation from the observed to the liability and then to the probability scale in the genetic evaluation of health traits with moderate and very low (extreme) incidence. Data comprised displaced abomasum (5.1M), ketosis (3.6M), lameness (5M), and mastitis (6.3M) records from a Holstein population with a pedigree of 6M animals, of which 1.7M were genotyped. Univariate threshold and linear models were performed to predict breeding values. The agreement between estimated breeding values on the probability scale derived from threshold and linear models was assessed using Spearman rank correlations and comparison of estimated breeding values distributions. Correlations were at least 0.95, and estimated breeding value distributions almost entirely overlapped for all the traits but displaced abomasum, the trait with the lowest incidence (2%). Computing time was ∼3x longer for threshold than for linear models. In this Holstein population, the approximation was suboptimal for a trait with extreme incidence (2%). However, when the incidence was ≥6%, the approximation was robust, and its use is recommended along with linear models for analyzing categorical traits in large populations to ease the computational burden.

Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations.

Mortality is an economically important trait usually handled as a discrete outcome from hatch time until selection in most broiler breeder programs. However, in other species, it has been shown that not only does the genetic component change over time, but there are maternal genetic effects to be considered when mortality is recorded early in life. This study aimed to investigate alternative trait definitions of mortality with varying models and effects. Three years' worth of data were provided by Cobb-Vantress, Inc. and included two mortality traits. The first trait was binary, whether the bird died or not (OM), and the second trait was a categorical weekly mortality trait (WM). After data cleaning, six weeks of data for the two given mortality traits were used to develop five additional trait definitions. The definitions were broiler mortality (BM), early and late mortality (EM & LM), and two traits with repeated records as cumulative or binary (CM and RM, respectively). Variance components were estimated using linear and threshold models to investigate whether either model had a benefit. Genomic breeding values were predicted using the BLUP90 software suite, and linear regression validation (LR) was used to compare trait definitions and models. Heritability estimates ranged from 0.01 (0.00) to 0.16 (0.01) under linear and 0.04 (0.01) to 0.21 (0.01) under threshold models, indicating genetic variability within the population across these trait definitions. The genetic correlation between EM and LM ranged from 0.48 to 0.81 across the different lines, indicating they have divergent genetic backgrounds and should be considered different traits. The LR accuracies showed that EM and LM used together in a two-trait model have comparable accuracies to that of OM while giving a more precise picture of mortality. When including the maternal effect, the direct heritability considerably decreased for EM, indicating that the maternal effect plays an important role in early mortality. Therefore, a suitable approach would be a model with EM and LM while considering the maternal effect for EM. Single nucleotide polymorphism effects were estimated, and no individual SNP explained more than 1% of the additive genetic variance. Additionally, the SNP with the largest effect size and variance were inconsistent across trait definitions. Chicken mortality can be defined in different ways, and reviewing these definitions and models may benefit poultry breeding programs.

Strategies for genomic predictions of an indicine multi-breed population using single-step GBLUP.

Brazilian livestock breeding programmes strive to enhance the genetics of beef cattle, with a strong emphasis on the Nellore breed, which has an extensive database and has achieved significant genetic progress in the last years. There are other indicine breeds that are economically important in Brazil; however, these breeds have more modest sets of phenotypes, pedigree and genotypes, slowing down their genetic progress as their predictions are less accurate. Combining several breeds in a multi-breed evaluation could help enhance predictions for those breeds with less information available. This study aimed to evaluate the feasibility of multi-breed, single-step genomic best linear unbiased predictor genomic evaluations for Nellore, Brahman, Guzerat and Tabapua. Multi-breed evaluations were contrasted to the single-breed ones. Data were sourced from the National Association of Breeders and Researchers of Brazil and included pedigree (4,207,516), phenotypic (328,748), and genomic (63,492) information across all breeds. Phenotypes were available for adjusted weight at 210 and 450 days of age, and scrotal circumference at 365 days of age. Various scenarios were evaluated to ensure pedigree and genomic information compatibility when combining different breeds, including metafounders (MF) or building the genomic relationship matrix with breed-specific allele frequencies. Scenarios were compared using the linear regression method for bias, dispersion and accuracy. The results showed that using multi-breed evaluations significantly improved accuracy, especially for smaller breeds like Guzerat and Tabapua. The validation statistics indicated that the MF approach provided accurate predictions, albeit with some bias. While single-breed evaluations tended to have lower accuracy, merging all breeds in multi-breed evaluations increased accuracy and reduced dispersion. This study demonstrates that multi-breed genomic evaluations are proper for indicine beef cattle breeds. The MF approach may be particularly beneficial for less-represented breeds, addressing limitations related to small reference populations and incompatibilities between G and A22. By leveraging genomic information across breeds, breeders and producers can make more informed selection decisions, ultimately improving genetic gain in these cattle populations.

Effect of genotyping density on the detection of runs of homozygosity and heterozygosity in cattle.

Runs of homozygosity (ROHom) are contiguous stretches of homozygous regions of the genome. In contrast, runs of heterozygosity (ROHet) are heterozygosity-rich regions. The detection of these two types of genomic regions (ROHom and ROHet) is influenced by the parameters involved in their identification and the number of available single-nucleotide polymorphisms (SNPs). The present study aimed to test the effect of chip density in detecting ROHom and ROHet in the Italian Simmental cattle breed. A sample of 897 animals were genotyped at low density (50k SNP; 397 individuals), medium density (140k SNP; 348 individuals), or high density (800k SNP; 152 individuals). The number of ROHom and ROHet per animal (nROHom and nROHet, respectively) and their average length were calculated. ROHom or ROHet shared by more than one animal and the number of times a particular SNP was inside a run were also computed (SNPROHom and SNPROHet). As the chip density increased, the nROHom increased, whereas their average length decreased. In contrast, the nROHet decreased and the average length increased as the chip density increased. The most repeated ROHom harbored no genes, whereas in the most repeated ROHet four genes (SNRPN, SNURF, UBE3A, and ATP10A) previously associated with reproductive traits were found. Across the 3 datasets, 31 SNP, located on Bos taurus autosome (BTA) 6, and 37 SNP (located on BTA21) exceeded the 99th percentile in the distribution of the SNPROHom and SNPROHet, respectively. The genomic region on BTA6 mapped the SLIT2, PACRGL, and KCNIP4 genes, whereas 19 and 18 genes were mapped on BTA16 and BTA21, respectively. Interestingly, most of genes found through the ROHet analysis were previously reported to be related to health, reproduction, and fitness traits. The results of the present study confirm that the detection of ROHom is more reliable when the chip density increases, whereas the ROHet trend seems to be the opposite. Genes and quantitative trait loci (QTL) mapped in the highlighted regions confirm that ROHet can be due to balancing selection, thus related to fitness traits, health, and reproduction, whereas ROHom are mainly involved in production traits. The results of the present study strengthened the usefulness of these parameters in analyzing the genomes of livestock and their biological meaning.

Runs of homozygosity (ROHom), continuous stretches of homozygous loci, and runs of heterozygosity (ROHet), continuous stretches of heterozygous loci, may be due to directional (ROHom) or balancing selection (ROHet) and are interesting to analyze those shared among animals within a population and the genes they harbor. The detection of both types of genomic regions is influenced by genotyping density and involved parameters. Thus, this work aimed to study the impact of the BeadChip density on the ROHom and ROHet detection in the Italian Simmental cattle breed. Results showed that the ROHom detection is more reliable as the density increases, whereas a more cryptic pattern was observed for ROHet. Interestingly, the hypothesis on how these two types of runs arise was supplied by the results of this study. The genes mapped on the highlighted ROHet were mainly associated with fitness traits, health, and reproduction, whereas those found in the ROHom were associated with production traits.

Atraumatic Spontaneous Transvaginal Small Bowel Evisceration: A Rare Surgical Emergency.

Abdominal pain ranks as the predominant cause for emergency department consultations. Although rare, transvaginal evisceration of the small intestine necessitates immediate surgical intervention due to its potential to induce intestinal ischemia and peritonitis. Key risk factors include postmenopausal status, a history of gynecologic surgery, and heightened abdominal pressure. Clinical presentation typically involves pain and protrusion of intestinal contents or even abdominal viscera. Diagnosis relies on thorough clinical assessment, and treatment strategies should be tailored to each patient. Here, we describe the case of a 65-year-old female patient with a non-traumatic evisceration of the ileum, who had undergone total abdominal hysterectomy following anterior colpocele a year ago, subsequently necessitating exploratory laparotomy and repair of the vaginal ampulla.

Temporal dynamics of genetic parameters and SNP effects for performance and disorder traits in poultry undergoing genomic selection.

Accurate genetic parameters are crucial for predicting breeding values and selection responses in breeding programs. Genetic parameters change with selection, reducing additive genetic variance and changing genetic correlations. This study investigates the dynamic changes in genetic parameters for residual feed intake (RFI), gain (GAIN), breast percentage (BP), and femoral head necrosis (FHN) in a broiler population that undergoes selection, both with and without the use of genomic information. Changes in single nucleotide polymorphism (SNP) effects were also investigated when including genomic information. The dataset containing 200,093 phenotypes for RFI, 42,895 for BP, 203,060 for GAIN, and 63,349 for FHN was obtained from 55 mating groups. The pedigree included 1,252,619 purebred broilers, of which 154,318 were genotyped with a 60K Illumina Chicken SNP BeadChip. A Bayesian approach within the GIBBSF90 + software was applied to estimate the genetic parameters for single-, two-, and four-trait models with sliding time intervals. For all models, we used genomic-based (GEN) and pedigree-based approaches (PED), meaning with or without genotypes. For GEN (PED), heritability varied from 0.19 to 0.2 (0.31 to 0.21) for RFI, 0.18 to 0.11 (0.25 to 0.14) for GAIN, 0.45 to 0.38 (0.61 to 0.47) for BP, and 0.35 to 0.24 (0.53 to 0.28) for FHN, across the intervals. Changes in genetic correlations estimated by GEN (PED) were 0.32 to 0.33 (0.12 to 0.25) for RFI-GAIN, -0.04 to -0.27 (-0.18 to -0.27) for RFI-BP, -0.04 to -0.07 (-0.02 to -0.08) for RFI-FHN, -0.04 to 0.04 (0.06 to 0.2) for GAIN-BP, -0.17 to -0.06 (-0.02 to -0.01) for GAIN-FHN, and 0.02 to 0.07 (0.06 to 0.07) for BP-FHN. Heritabilities tended to decrease over time while genetic correlations showed both increases and decreases depending on the traits. Similar to heritabilities, correlations between SNP effects declined from 0.78 to 0.2 for RFI, 0.8 to 0.2 for GAIN, 0.73 to 0.16 for BP, and 0.71 to 0.14 for FHN over the eight intervals with genomic information, suggesting potential epistatic interactions affecting genetic trait architecture. Given rapid genetic architecture changes and differing estimates between genomic and pedigree-based approaches, using more recent data and genomic information to estimate variance components is recommended for populations undergoing genomic selection to avoid potential biases in genetic parameters.

Genetic parameters are used to predict breeding values for individuals in breeding programs undergoing selection. However, inaccurate genetic parameters can cause breeding values to be biased, and genetic parameters can change over time due to multiple factors. This study aimed to investigate how genetic parameters changed over time in a broiler population using time intervals and observing the behavior of single nucleotide polymorphism (SNP) effects. We studied four traits related to production and disorders while also studying the impact of using genomic information on the estimates. Genetic variances showed an overall decreasing trend, whereas residual variances increased during each interval, resulting in decreasing heritability estimates. Genetic correlations between traits varied but with no major changes over time. Estimates tended to be lower when genomic information was included in the analysis. SNP effects showed changes over time, indicating changes to the genetic background of this population. Using outdated variance components in a population under selection may not represent the current population. Furthermore, when genomic selection is practiced, accounting for this information while estimating variance components is important to avoid biases.

In-Hospital Violence and Its Impact on Critical Care Practitioners.

OBJECTIVES: To provide a narrative review of hospital violence (HV) and its impact on critical care clinicians. DATA SOURCES: Detailed search strategy using PubMed and OVID Medline for English language articles describing HV, risk factors, precipitating events, consequences, and mitigation strategies. STUDY SELECTION: Studies that specifically addressed HV involving critical care medicine clinicians or their practice settings were selected. The time frame was limited to the last 15 years to enhance relevance to current practice. DATA EXTRACTION: Relevant descriptions or studies were reviewed, and abstracted data were parsed by setting, clinician type, location, social media events, impact, outcomes, and responses (agency, facility, health system, individual). DATA SYNTHESIS: HV is globally prevalent, especially in complex care environments, and correlates with a variety of factors including ICU stay duration, conflict, and has recently expanded to out-of-hospital occurrences; online violence as well as stalking is increasingly prevalent. An overlap with violent extremism and terrorism that impacts healthcare facilities and clinicians is similarly relevant. A number of approaches can reduce HV occurrence including, most notably, conflict management training, communication initiatives, and visitor flow and access management practices. Rescue training for HV occurrences seems prudent. CONCLUSIONS: HV is a global problem that impacts clinicians and imperils patient care. Specific initiatives to reduce HV drivers include individual training and system-wide adaptations. Future methods to identify potential perpetrators may leverage machine learning/augmented intelligence approaches.

Derivation of indirect predictions using genomic recursions across generations in a broiler population.

Genomic estimated breeding values (GEBV) of animals without phenotypes can be indirectly predicted using recursions on GEBV of a subset. To maximize predictive ability of indirect predictions (IP), the subset must represent the independent chromosome segments segregating in the population. We aimed to 1) determine the number of animals needed in recursions to maximize predictive ability, 2) evaluate equivalency IP-GEBV, and 3) investigate trends in predictive ability of IP derived from recent vs. distant generations or accumulating phenotypes from recent to past generations. Data comprised pedigree of 825K birds hatched over 12 overlapping generations, phenotypes for body weight (BW; 820K), residual feed intake (RF; 200K) and weight gain during a trial period (WG; 200K), and breast meat percent (BP; 43K). A total of 154K birds (last six generations) had genotypes. The number of animals that maximize predictive ability was assessed based on the number of largest eigenvalues explaining 99% of variation in the genomic relationship matrix (1Me = 7,131), twice (2Me), or a fraction of this number (i.e., 0.75, 0.50, or 0.25Me). Equivalency between IP and GEBV was measured by correlating these two sets of predictions. GEBV were obtained as if generation 12 (validation animals) was part of the evaluation. IP were derived from GEBV of animals from generations 8 to 11 or generations 11, 10, 9, or 8. IP predictive ability was defined as the correlation between IP and adjusted phenotypes. The IP predictive ability increased from 0.25Me to 1Me (11%, on average); the change from 1Me to 2Me was negligible (0.6%). The correlation IP-GEBV was the same when IP were derived from a subset of 1Me animals chosen randomly across generations (8 to 11) or from generation 11 (0.98 for BW, 0.99 for RF, WG, and BP). A marginal decline in the correlation was observed when IP were based on GEBV of animals from generation 8 (0.95 for BW, 0.98 for RF, WG, and BP). Predictive ability had a similar trend; from generation 11 to 8, it changed from 0.32 to 0.31 for BW, from 0.39 to 0.38 for BP, and was constant at 0.33(0.22) for RF(WG). Predictive ability had a slight to moderate increase accumulating up to four generations of phenotypes. 1Me animals provide accurate IP, equivalent to GEBV. A minimum decay in predictive ability is observed when IP are derived from GEBV of animals from four generations back, possibly because of strong selection or the model not being completely additive.

Genomic estimated breeding values (GEBV) of genotyped animals without phenotypes can be obtained by indirect predictions (IP) using recursions on GEBV from a subset. Our objectives were to 1) evaluate the number of animals needed in recursions to maximize predictive ability, 2) assess equivalency between IP and GEBV, and 3) investigate trends in predictive ability of IP derived from recent vs. distant generations or accumulating phenotypes from recent to past generations. The number of animals (7,131) in the recursions that provided high-predictive ability was equal to the number of largest eigenvalues explaining 99% of variation in the genomic relationship matrix. IP and GEBV were equivalent (correlation ≥ 0.98). IP predictive ability was similar when recursions were based on animals from recent or distant generations; it marginally decayed with animals from four generations apart. The decline in predictive ability can be explained by strong selection or the model not being fully additive. A slight to moderate increase in IP predictive ability was observed accumulating up to four generations of phenotypes. If GEBV of animals in the subset chosen for recursions are estimated using sufficient data, animals can be from up to four generations back without significant loss in predictive ability.

Efficient ways to combine data from broiler and layer chickens to account for sequential genomic selection.

In broiler breeding, superior individuals for growth become parents and are later evaluated for reproduction in an independent evaluation; however, ignoring broiler data can produce inaccurate and biased predictions. This research aimed to determine the most accurate, unbiased, and time-efficient approach for jointly evaluating reproductive and broiler traits. The data comprised a pedigree with 577K birds, 146K genotypes, phenotypes for three reproductive (egg production [EP], fertility [FE], hatch of fertile eggs [HF]; 9K each), and four broiler traits (body weight [BW], breast meat percent [BP], fat percent [FP], residual feed intake [RF]; up to 467K). Broiler data were added sequentially to assess the impact on the quality of predictions for reproductive traits. The baseline scenario (RE) included pedigrees, genotypes, and phenotypes for reproductive traits of selected animals; in RE2, we added their broiler phenotypes; in RE_BR, broiler phenotypes of nonselected animals, and in RE_BR_GE, their genotypes. We computed accuracy, bias, and dispersion of predictions for hens from the last two breeding cycles and their sires. We tested three core definitions for the algorithm of proven and young to find the most time-efficient approach: two random cores with 7K and 12K animals and one with 19K animals, containing parents and young animals. From RE to RE_BR_GE, changes in accuracy were null or minimal for EP (0.51 in hens, 0.59 in roosters) and HF (0.47 in hens, 0.49 in roosters); for FE in hens (roosters), it changed from 0.4 (0.49) to 0.47 (0.53). In hens (roosters), bias (additive SD units) decreased from 0.69 (0.7) to 0.04 (0.05) for EP, 1.48 (1.44) to 0.11 (0.03) for FE, and 1.06 (0.96) to 0.09 (0.02) for HF. Dispersion remained stable in hens (roosters) at ~0.93 (~1.03) for EP, and it improved from 0.57 (0.72) to 0.87 (1.0) for FE and from 0.8 (0.79) to 0.88 (0.87) for HF. Ignoring broiler data deteriorated the predictions' quality. The impact was significant for the low heritability trait (0.02; FE); bias (up to 1.5) and dispersion (as low as 0.57) were farther from the ideal value, and accuracy losses were up to 17.5%. Accuracy was maintained in traits with moderate heritability (~0.3; EP and HF), and bias and dispersion were less substantial. Adding information from the broiler phase maximized accuracy and unbiased predictions. The most time-efficient approach is a random core with 7K animals in the algorithm for proven and young.

In breeding programs with sequential selection, the estimation of breeding values becomes biased and inaccurate if the information from the past selection is ignored. We investigated the impact of incorporating broiler data (traits for past selection) into the evaluation of broiler reproductive traits. Including all the information increased the computing demands; therefore, we tested three core definitions for the algorithm for proven and young to determine the most accurate, unbiased, and time-efficient approach for jointly evaluating broiler and reproductive traits. When we ignored broiler data, the estimated breeding values for reproductive traits were biased (up to ~1.5 additive standard deviations). For low heritability traits, accuracy was reduced by up to 17.5%, and breeding values were overestimated (dispersion ~ 0.6). In contrast, incorporating broiler data eliminated bias and overestimation; and it maximized accuracy. A random core definition for the algorithm for proven and young with a number of animals equal to the number of the largest eigenvalues explaining 99% of the variation in the genomic relationship matrix is the most time-efficient, keeping accurate and unbiased predictions in the joint evaluation of broiler and reproductive traits.

Assessment of Genetic Diversity, Runs of Homozygosity, and Signatures of Selection in Tropical Milking Criollo Cattle Using Pedigree and Genomic Data.

The objective of this study was to evaluate the genetic diversity of the Tropical Milking Criollo cattle (TMC) breed in Mexico through parameters derived from pedigree and genomic information assessment. The pedigree file consisted of 3780 animals. Seventy-nine bovines were genotyped with the medium-density single nucleotide polymorphism chip and considered a reference population for pedigree analysis. The effective population size and the probability of gene origin used to assess the evolution of genetic diversity were calculated with pedigree information. Inbreeding coefficients were evaluated based on pedigree (FPed), the genomic relationship matrix (FGRM), and runs of homozygosity (FROH) of different length classes. The average inbreeding was 2.82 ± 2.66%, −0.7 ± 3.8%, and 10.9 ± 3.0% for FPED, FGRM, and FROH, respectively. Correlation between FPED and FROH was significant only for runs of homozygosity > 4 Mb, indicating the FPED of a population with an average equivalent complete generation of five only recovers the most recent inbreeding. The parameters of the probability of gene origin indicated the existence of genetic bottlenecks and the loss of genetic diversity in the history of the TMC cattle population; however, pedigree and genomic information revealed the existence of current sufficient genetic diversity to design a sustainable breeding program.

Absence of microglia promotes diverse pathologies and early lethality in Alzheimer's disease mice.

Microglia are strongly implicated in the development and progression of Alzheimer's disease (AD), yet their impact on pathology and lifespan remains unclear. Here we utilize a CSF1R hypomorphic mouse to generate a model of AD that genetically lacks microglia. The resulting microglial-deficient mice exhibit a profound shift from parenchymal amyloid plaques to cerebral amyloid angiopathy (CAA), which is accompanied by numerous transcriptional changes, greatly increased brain calcification and hemorrhages, and premature lethality. Remarkably, a single injection of wild-type microglia into adult mice repopulates the microglial niche and prevents each of these pathological changes. Taken together, these results indicate the protective functions of microglia in reducing CAA, blood-brain barrier dysfunction, and brain calcification. To further understand the clinical implications of these findings, human AD tissue and iPSC-microglia were examined, providing evidence that microglia phagocytose calcium crystals, and this process is impaired by loss of the AD risk gene, TREM2.

Impact of the Discordance Between Scales of Memorial Sloan-Kettering Cancer Center and International Metastatic Renal Cell Carcinoma Database Consortium in Patients' Prognosis With Metastatic Renal Cancer.

Background: In Mexico, about 30% of renal cancer patients are diagnosed in a metastatic state. Despite the recent advances in the treatment of cancer, metastatic renal cancer is still an incurable illness. Thus, identifying prognostic factors helps improve prognosis accuracy and survival prediction for patients. Methods: In this study, we retrospectively analyzed 26 patients with histological diagnosis of renal cell carcinoma, including clear cell and other subtypes in stage IV (metastatic), recurrent or unresectable disease. We performed a multivariate analysis of overall survival regarding the congruity between prognostic scales. Results: Our results showed a significant difference in favor of patients with congruity between scales for progression-free survival (18.9 vs. 3.1 months; P = 0.048) and a tendency towards better overall survival in patients with the congruity of both scales compared to the discordant patients (112 vs. 32 months; P = 0.99). Conclusion: This study highlights the discordance between Memorial Sloan-Kettering Cancer Center and International Metastatic Renal Cell Carcinoma Database Consortium scales, which was associated with worse prognosis with a significant difference in progression-free survival but not in overall survival.

Feedlot pens with greenhouse roofs improve beef cattle performance in temperate weather.

Muddy pens can negatively affect welfare and performance of feedlot beef cattle. In some regions with temperate weather, plastic greenhouse covers, above the entire pens are used to fatten cattle in a clean and dry environment. The objective of this research was to investigate effects of greenhouse roofed pens on beef cattle feedlot performance in temperate weather. Data were collected from a feedlot located in Central Mexico between 2016 and 2019. The study included 1,062 closeouts of pens with 68,305 crossbred bulls fed in pens with or without a greenhouse roof. Feeding ranged from 82 to 210 d, depending on the initial weight of cattle, which ranged from 255 to 511 kg. For each pen, average daily dry matter intake (DMI; kg of DMI·animal-1·d-1), average daily gain (ADG, kg·animal-1·d-1), and feed efficiency (G:F, ADG/DMI) were measured. Factorial analyses were performed to test the interaction and main effects of initial weight grouping (light, medium, and heavy), roof, and season as fixed effects, and year as a random effect. None of the three-way interactions were significant (P > 0.51). There was no initial weight grouping × roof interactions for DMI and ADG (P > 0.31). There was (P = 0.03) an initial weight grouping × roof interaction for G:F, as pens of all initial weight groups had greater (P < 0.01) G:F in pens with greenhouse roof than its counterpart in pens without greenhouse roof, but the advantage was greater for pens with light cattle (0.178 vs. 0.166; P < 0.01). There was no initial weight grouping × season interactions for all variables (P > 0.39). There was no roof × season interaction for DMI (P = 0.47), but there were interactions for ADG and G:F (P < 0.01). The ADG was not different (P > 0.13) during summer and autumn based on the roofing system, but pens with greenhouse roofs had greater ADG during spring (1.70 vs. 1.61) and winter (1.68 vs. 1.64; P ≤ 0.01). The G:F was greater (P < 0.01) in all seasons for pens with a greenhouse roof, with the most prominent advantage during spring (0.173 vs. 0.160). There were main effects for cattle initial weight grouping and roof for all variables (P < 0.01). Season affected DMI and G:F (P < 0.01). Pens with greenhouse roofs had decreased DMI (9.70 vs. 9.86), greater ADG (1.67 vs. 1.63), and increased G:F (0.173 vs. 0.166) compared to pens without greenhouse roofs (P < 0.01). Pens with greenhouse roofs in feedlots located in temperate regions positively affect beef cattle performance.

Probing the mechanism of the peroxiredoxin decamer interaction with its reductase sulfiredoxin from the single molecule to the solution scale.

Peroxiredoxins from the Prx1 subfamily (Prx) are highly regulated multifunctional proteins involved in oxidative stress response, redox signaling and cell protection. Prx is a homodimer that associates into a decamer. The monomer C-terminus plays intricate roles in Prx catalytic functions, decamer stability and interaction with its redox partner, the small reductase sulfiredoxin (Srx), that regulates the switching between Prx cellular functions. As only static structures of covalent Prx-Srx complexes have been reported, whether Srx binding dissociates the decameric assembly and how Prx subunit flexibility impacts complex formation are unknown. Here, we assessed the non-covalent interaction mechanism and dynamics in the solution of Saccharomyces cerevisiae Srx with the ten subunits of Prx Tsa1 at the decamer level via a combination of multiscale biophysical approaches including native mass spectrometry. We show that the ten subunits of the decamer can be saturated by ten Srx molecules and that the Tsa1 decamer in complex with Srx does not dissociate in solution. Furthermore, the binding events of atomic force microscopy (AFM) tip-grafted Srx molecules to Tsa1 individual subunits were relevant to the interactions between free molecules in solution. Combined with protein engineering and rapid kinetics, the observation of peculiar AFM force-distance signatures revealed that Tsa1 C-terminus flexibility controls Tsa1/Srx two-step binding and dynamics and determines the force-induced dissociation of Srx from each subunit of the decameric complex in a sequential or concerted mode. This combined approach from the solution to the single-molecule level offers promising prospects for understanding oligomeric protein interactions with their partners.

The P522R protective variant of PLCG2 promotes the expression of antigen presentation genes by human microglia in an Alzheimer's disease mouse model.

The P522R variant of PLCG2, expressed by microglia, is associated with reduced risk of Alzheimer's disease (AD). Yet, the impact of this protective mutation on microglial responses to AD pathology remains unknown. Chimeric AD and wild-type mice were generated by transplanting PLCG2-P522R or isogenic wild-type human induced pluripotent stem cell microglia. At 7 months of age, single-cell and bulk RNA sequencing, and histological analyses were performed. The PLCG2-P522R variant induced a significant increase in microglial human leukocyte antigen (HLA) expression and the induction of antigen presentation, chemokine signaling, and T cell proliferation pathways. Examination of immune-intact AD mice further demonstrated that the PLCG2-P522R variant promotes the recruitment of CD8+ T cells to the brain. These data provide the first evidence that the PLCG2-P522R variant increases the capacity of microglia to recruit T cells and present antigens, promoting a microglial transcriptional state that has recently been shown to be reduced in AD patient brains.

Surnames and population structure in the Doctrine of Belén, Altos de Arica, Viceroyalty of Peru (1750-1813).

The analysis of multiple population structures (biodemographic, genetic and socio-cultural) and their inter-relations contribute to a deeper understanding of population structure and population dynamics. Genetically, the population structure corresponds to the deviation of random mating conditioned by a limited number of ancestors, by restricted migration in the social or geographic space, or by preference for certain consanguineous unions. Through the isonymic method, surname frequency and distribution across the population can supply quantitative information on the structure of a human population, as they constitute universal socio-cultural variables. Using documentary sources to undertake the Doctrine of Belén's (Altos de Arica, Chile) historical demography reconstruction between 1763 and 1820, this study identified an indigenous population with stable patronymics. The availability of complete marriage, baptism and death records, low rates of migration and the significant percentage of individuals registered and constantly present in this population favoured the application of the isonymic method. The aim of this work was to use given names and surnames recorded in these documentary sources to reconstruct the population structure and migration pattern of the Doctrine of Belén between 1750 and 1813 through the isonymic method. The results of the study were consistent with the ethno-historical data of this ethnic space, where social cohesion was, in multiple ways, related to the regulation of daily life in colonial Andean societies.

Prevalence and Molecular Profile of Breast Carcinoma Using Immunohistochemistry Markers in Mexican Women.

BACKGROUND: In Mexico, breast cancer is the leading cause of death by malignant tumors in women aged 20 and older. The World Health Organization estimates that 69% of deaths caused by breast cancer occur in developing countries. Little is known about the prevalence of breast carcinoma in Mexico and its molecular subclassification. METHODS: This retrospective cross-sectional study included patients who underwent a mastectomy (single, radical or lumpectomy) or a breast tumor biopsy (core-needle or excisional) from January 2002 to December 2018. The primary purpose of the study was to determine the prevalence and molecular profile of breast in comprehensive cancer center in Mexico and compare our results with those published in the US. This study was approved by our scientific and bioethical committee. RESULTS: The final analysis included 379 patients. The youngest patient was 23 years old and the oldest patient was 89; the mean age at diagnosis was 54.63 years. Patients of 40 years old or younger accounted for 48 of the cases (12.66%) and those older than 40 accounted for 331 of the cases (87.33%). The molecular subclassification showed luminal A subtype in 139 cases (36.67%), luminal B subtype in 143 cases (37.73%), human epidermal growth factor receptor 2-positive carcinomas in 32 cases (8.44%) and triple-negative carcinomas in 65 cases (17.15%). Diabetes mellitus was present in 43 patients (11.34%), hypertension in 78 patients (20.58%), obesity in 82 patients (21.63%) and 66 patients reported being treated with exogenous hormone therapy (17.41%). CONCLUSIONS: Breast carcinoma occurs at an earlier age in Mexican women compared to women in the US. Hormone-positive tumors were found to be more prevalent in older patients, while high-grade tumors were more frequently identified in younger patients.

Investigating the persistence of accuracy of genomic predictions over time in broilers.

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2; on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of data, and a decrease of ~7% was observed when the training population included only 1 year of data. Training sets including genomic information provided an increase in accuracy and persistence of genomic predictions compared with training sets without genomic data. The two most recent years of pedigree, phenotypic, and genomic data were sufficient to maintain prediction accuracies in selection candidates. Similar conclusions were obtained using validation populations per year.

Plaque-associated human microglia accumulate lipid droplets in a chimeric model of Alzheimer's disease.

BACKGROUND: Disease-associated microglia (DAMs), that surround beta-amyloid plaques, represent a transcriptionally-distinct microglial profile in Alzheimer's disease (AD). Activation of DAMs is dependent on triggering receptor expressed on myeloid cells 2 (TREM2) in mouse models and the AD TREM2-R47H risk variant reduces microglial activation and plaque association in human carriers. Interestingly, TREM2 has also been identified as a microglial lipid-sensor, and recent data indicates lipid droplet accumulation in aged microglia, that is in turn associated with a dysfunctional proinflammatory phenotype. However, whether lipid droplets (LDs) are present in human microglia in AD and how the R47H mutation affects this remains unknown. METHODS: To determine the impact of the TREM2 R47H mutation on human microglial function in vivo, we transplanted wild-type and isogenic TREM2-R47H iPSC-derived microglial progenitors into our recently developed chimeric Alzheimer mouse model. At 7 months of age scRNA-seq and histological analyses were performed. RESULTS: Here we report that the transcriptome of human wild-type TREM2 and isogenic TREM2-R47H DAM xenografted microglia (xMGs), isolated from chimeric AD mice, closely resembles that of human atherosclerotic foam cells. In addition, much like foam cells, plaque-bound xMGs are highly enriched in lipid droplets. Somewhat surprisingly and in contrast to a recent in vitro study, TREM2-R47H mutant xMGs exhibit an overall reduction in the accumulation of lipid droplets in vivo. Notably, TREM2-R47H xMGs also show overall reduced reactivity to plaques, including diminished plaque-proximity, reduced CD9 expression, and lower secretion of plaque-associated APOE. CONCLUSIONS: Altogether, these results indicate lipid droplet accumulation occurs in human DAM xMGs in AD, but is reduced in TREM2-R47H DAM xMGs, as it occurs secondary to TREM2-mediated changes in plaque proximity and reactivity.

Changes in genomic predictions when new information is added.

The stability of genomic evaluations depends on the amount of data and population parameters. When the dataset is large enough to estimate the value of nearly all independent chromosome segments (~10K in American Angus cattle), the accuracy and persistency of breeding values will be high. The objective of this study was to investigate changes in estimated breeding values (EBV) and genomic EBV (GEBV) across monthly evaluations for 1 yr in a large genotyped population of beef cattle. The American Angus data used included 8.2 million records for birth weight, 8.9 for weaning weight, and 4.4 for postweaning gain. A total of 10.1 million animals born until December 2017 had pedigree information, and 484,074 were genotyped. A truncated dataset included animals born until December 2016. To mimic a scenario with monthly evaluations, 2017 data were added 1 mo at a time to estimate EBV using best linear unbiased prediction (BLUP) and GEBV using single-step genomic BLUP with the algorithm for proven and young (APY) with core group fixed for 1 yr or updated monthly. Predictions from monthly evaluations in 2017 were contrasted with the predictions of the evaluation in December 2016 or the previous month for all genotyped animals born until December 2016 with or without their own phenotypes or progeny phenotypes. Changes in EBV and GEBV were similar across traits, and only results for weaning weight are presented. Correlations between evaluations from December 2016 and the 12 consecutive evaluations were ≥0.97 for EBV and ≥0.99 for GEBV. Average absolute changes for EBV were about two times smaller than for GEBV, except for animals with new progeny phenotypes (≤0.12 and ≤0.11 additive genetic SD [SDa] for EBV and GEBV). The maximum absolute changes for EBV (≤2.95 SDa) were greater than for GEBV (≤1.59 SDa). The average(maximum) absolute GEBV changes for young animals from December 2016 to January and December 2017 ranged from 0.05(0.25) to 0.10(0.53) SDa. Corresponding ranges for animals with new progeny phenotypes were from 0.05(0.88) to 0.11(1.59) SDa for GEBV changes. The average absolute change in EBV(GEBV) from December 2016 to December 2017 for sires with ≤50 progeny phenotypes was 0.26(0.14) and for sires with >50 progeny phenotypes was 0.25(0.16) SDa. Updating the core group in APY without adding data created an average absolute change of 0.07 SDa in GEBV. Genomic evaluations in large genotyped populations are as stable and persistent as the traditional genetic evaluations, with less extreme changes.