A high-density and high-confinement tokamak plasma regime for fusion energy.

The tokamak approach, utilizing a toroidal magnetic field configuration to confine a hot plasma, is one of the most promising designs for developing reactors that can exploit nuclear fusion to generate electrical energy1,2. To reach the goal of an economical reactor, most tokamak reactor designs3-10 simultaneously require reaching a plasma line-averaged density above an empirical limit-the so-called Greenwald density11-and attaining an energy confinement quality better than the standard high-confinement mode12,13. However, such an operating regime has never been verified in experiments. In addition, a long-standing challenge in the high-confinement mode has been the compatibility between a high-performance core and avoiding large, transient edge perturbations that can cause very high heat loads on the plasma-facing-components in tokamaks. Here we report the demonstration of stable tokamak plasmas with a line-averaged density approximately 20% above the Greenwald density and an energy confinement quality of approximately 50% better than the standard high-confinement mode, which was realized by taking advantage of the enhanced suppression of turbulent transport granted by high density-gradients in the high-poloidal-beta scenario14,15. Furthermore, our experimental results show an integration of very low edge transient perturbations with the high normalized density and confinement core. The operating regime we report supports some critical requirements in many fusion reactor designs all over the world and opens a potential avenue to an operating point for producing economically attractive fusion energy.

A new experimental evidence-weighted signaling pathway resource in FlyBase.

Research in model organisms is central to the characterization of signaling pathways in multicellular organisms. Here, we present the comprehensive and systematic curation of 17 Drosophila signaling pathways using the Gene Ontology framework to establish a dynamic resource that has been incorporated into FlyBase, providing visualization and data integration tools to aid research projects. By restricting to experimental evidence reported in the research literature and quantifying the amount of such evidence for each gene in a pathway, we captured the landscape of empirical knowledge of signaling pathways in Drosophila.

Nirmatrelvir/Ritonavir Use and Hospitalizations or Death in a Previously Uninfected Nonhospitalized High-Risk Population With COVID-19: A Matched Cohort Study.

OBJECTIVE: To determine the association of nirmatrelvir/ritonavir (NMV/r) with hospitalization or death within 30 days as compared with untreated controls previously uninfected and nonhospitalized. METHODS: We used a matched cohort design using inverse probability of treatment weight (IPTW). Individuals prescribed NMV/r within 3 days of COVID-19 diagnosis were compared with IPTW-based untreated controls. Variables for IPTW included age, race, sex, body mass index, geographic location, vaccination status, and multiple comorbidities. Additional analyses were conducted on NMV/r-treated and propensity score-matched untreated controls. RESULTS: Among 7615 individuals prescribed NMV/r and 62 077 controls identified between 1 January 2022 and 25 February 2023, the risk of hospitalization/death was lower among NMV/r-treated persons vs untreated controls (243 vs 3468 events; absolute risk difference [ARD], -2.36 [95% CI, -2.57 to -2.14]). The difference was significant for those >60 and ≤60 years old (ARD, -3.86 [95% CI, -4.19 to -3.54] vs -0.27 [95% CI, -0.51 to -0.03]) and for persons asymptomatic and symptomatic (ARD, -7.09 [95% CI, -7.62 to -6.55] vs -1.46 [95% CI, -1.66 to -1.25]). Significant benefit was observed among individuals unvaccinated and vaccinated, with or without a booster dose. CONCLUSIONS: NMV/r is associated with a significant reduction in 30-day hospitalization or death among individuals previously uninfected and nonhospitalized.

Detection and evaluation of parameters influencing the identification of heterozygous-enriched regions in Holstein cattle based on SNP chip or whole-genome sequence data.

BACKGROUND: A heterozygous-enriched region (HER) is a genomic region with high variability generated by factors such as balancing selection, introgression, and admixture processes. In this study, we evaluated the genomic background of HERs and the impact of different parameters (i.e., minimum number of SNPs in a HER, maximum distance between two consecutive SNPs, minimum length of a HER, maximum number of homozygous allowed in a HER) and scenarios [i.e., different SNP panel densities and whole-genome sequence (WGS)] on the detection of HERs. We also compared HERs characterized in Holstein cattle with those identified in Angus, Jersey, and Norwegian Red cattle using WGS data. RESULTS: The parameters used for the identification of HERs significantly impact their detection. The maximum distance between two consecutive SNPs did not impact HERs detection as the same average of HERs (269.31 ± 787.00) was observed across scenarios. However, the minimum number of markers, maximum homozygous markers allowed inside a HER, and the minimum length size impacted HERs detection. For the minimum length size, the 10 Kb scenario showed the highest average number of HERs (1,364.69 ± 1,483.64). The number of HERs decreased as the minimum number of markers increased (621.31 ± 1,271.83 to 6.08 ± 21.94), and an opposite pattern was observed for the maximum homozygous markers allowed inside a HER (54.47 ± 195.51 to 494.89 ± 1,169.35). Forty-five HER islands located in 23 chromosomes with high Tajima's D values and differential among the observed and estimated heterozygosity were detected in all evaluated scenarios, indicating their ability to potentially detect regions under balancing selection. In total, 3,440 markers and 28 genes previously related to fertility (e.g., TP63, ZSCAN23, NEK5, ARHGAP44), immunity (e.g., TP63, IGC, ARHGAP44), residual feed intake (e.g., MAYO9A), stress sensitivity (e.g., SERPINA6), and milk fat percentage (e.g., NOL4) were identified. When comparing HER islands among breeds, there were substantial overlaps between Holstein with Angus (95.3%), Jersey (94.3%), and Norwegian Red cattle (97.1%), indicating conserved HER across taurine breeds. CONCLUSIONS: The detection of HERs varied according to the parameters used, but some HERs were consistently identified across all scenarios. Heterozygous genotypes observed across generations and breeds appear to be conserved in HERs. The results presented could serve as a guide for defining HERs detection parameters and further investigating their biological roles in future studies.

Gain-of-function mutations in RPA1 cause a syndrome with short telomeres and somatic genetic rescue.

Human telomere biology disorders (TBD)/short telomere syndromes (STS) are heterogeneous disorders caused by inherited loss-of-function mutations in telomere-associated genes. Here, we identify 3 germline heterozygous missense variants in the RPA1 gene in 4 unrelated probands presenting with short telomeres and varying clinical features of TBD/STS, including bone marrow failure, myelodysplastic syndrome, T- and B-cell lymphopenia, pulmonary fibrosis, or skin manifestations. All variants cluster to DNA-binding domain A of RPA1 protein. RPA1 is a single-strand DNA-binding protein required for DNA replication and repair and involved in telomere maintenance. We showed that RPA1E240K and RPA1V227A proteins exhibit increased binding to single-strand and telomeric DNA, implying a gain in DNA-binding function, whereas RPA1T270A has binding properties similar to wild-type protein. To study the mutational effect in a cellular system, CRISPR/Cas9 was used to knock-in the RPA1E240K mutation into healthy inducible pluripotent stem cells. This resulted in severe telomere shortening and impaired hematopoietic differentiation. Furthermore, in patients with RPA1E240K, we discovered somatic genetic rescue in hematopoietic cells due to an acquired truncating cis RPA1 mutation or a uniparental isodisomy 17p with loss of mutant allele, coinciding with stabilized blood counts. Using single-cell sequencing, the 2 somatic genetic rescue events were proven to be independently acquired in hematopoietic stem cells. In summary, we describe the first human disease caused by germline RPA1 variants in individuals with TBD/STS.

Molecular Advances of Bud Dormancy in Trees.

Seasonal bud dormancy in perennial woody plants is a crucial and intricate process that is vital for the survival and development of plants. Over the past few decades, significant advancements have been made in understanding many features of bud dormancy, particularly in model species, where certain molecular mechanisms underlying this process have been elucidated. In this review, we provide an overview of recent molecular progress in understanding bud dormancy in trees, with a specific emphasis on the integration of common signaling and molecular mechanisms identified across different tree species. Additionally, we address some challenges that have emerged in the in-depth understanding of bud dormancy and offer insights for future studies.

Divergent and Nucleophile-Assisted Rearrangement in the Construction of Pyrrolo[2,1-b][3]benzazepine and Pyrido[2,1-a]isoquinoline Scaffolds.

Under microwave (MW) irradiation at 150 °C in toluene and in the presence of nucleophiles (DMAP, triphenylphosphine and tetrahydrothiophene) 1-substituted 1-ethynyl-2-vinyldi- and tetrahydroisoquinolines undergo [3,3]-sigmatropic rearrangement providing pyrrolo[2,1-b][3]benzazepines in good yields. The replacement of toluene with acetonitrile directs the rearrangement towards the formation of 7,11b-dihydro-6H-pyrido[2,1-a]isoquinolines.

Quantitative 1H Magnetic Resonance Imaging on Normal and Pathologic Rat Bones by Solid-State 1H ZTE Sequence with Water and Fat Suppression.

BACKGROUND: Osteoporosis (OP) and osteomalacia (OM) are metabolic bone diseases characterized by mineral and matrix density changes. Quantitative bone matrix density differentiates OM from OP. MRI is a noninvasive and nonionizing imaging technique that can measure bone matrix density quantitatively in ex vivo and in vivo. PURPOSE: To demonstrate water + fat suppressed 1H MRI to compute bone matrix density in ex vivo rat femurs in the preclinical model. STUDY TYPE: Prospective. ANIMAL MODEL: Fifteen skeletally mature female Sprague-Dawley rats, five per group (normal, ovariectomized (OVX), partially nephrectomized/vitamin D (Vit-D) deficient), 250-275 g, ∼15 weeks old. FIELD STRENGTH/SEQUENCE: 7T, zero echo time sequence with water + fat (VAPOR) suppression capability, µCT imaging, and gravimetric measurements. ASSESSMENT: Cortical and trabecular bone segments from normal and disease models were scanned in the same coil along with a dual calibration phantom for quantitative assessment of bone matrix density. STATISTICAL TESTS: ANOVA and linear regression were used for data analysis, with P-values <0.05 statistically significant. RESULTS: The MRI-derived three-density PEG pellet densities have a strong linear relationship with physical density measures (r2 = 0.99). The Vit-D group had the lowest bone matrix density for cortical bone (0.47 ± 0.16 g cm-3), whereas the OVX had the lowest bone matrix density for trabecular bone (0.26 ± 0.04 g cm-3). Gravimetry results confirmed these MRI-based observations for Vit-D cortical (0.51 ± 0.07 g cm-3) and OVX trabecular (0.26 ± 0.03 g cm-3) bone groups. DATA CONCLUSION: Rat femur images were obtained using a modified pulse sequence and a custom-designed double-tuned (1H/31P) transmit-receive solenoid-coil on a 7T preclinical MRI scanner. Phantom experiments confirmed a strong linear relation between MRI-derived and physical density measures and quantitative bone matrix densities in rat femurs from normal, OVX, and Vit-D deficient/partially nephrectomized animals were computed. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Bayesian response adaptive randomization design with a composite endpoint of mortality and morbidity.

Allocating patients to treatment arms during a trial based on the observed responses accumulated up to the decision point, and sequential adaptation of this allocation, could minimize the expected number of failures or maximize total benefits to patients. In this study, we developed a Bayesian response-adaptive randomization (RAR) design targeting the endpoint of organ support-free days (OSFD) for patients admitted to the intensive care units. The OSFD is a mixture of mortality and morbidity assessed by the number of days of free of organ support within a predetermined post-randomization time-window. In the past, researchers treated OSFD as an ordinal outcome variable where the lowest category is death. We propose a novel RAR design for a composite endpoint of mortality and morbidity, for example, OSFD, by using a Bayesian mixture model with a Markov chain Monte Carlo sampling to estimate the posterior probability distribution of OSFD and determine treatment allocation ratios at each interim. Simulations were conducted to compare the performance of our proposed design under various randomization rules and different alpha spending functions. The results show that our RAR design using Bayesian inference allocated more patients to the better performing arm(s) compared to other existing adaptive rules while assuring adequate power and type I error rate control across a range of plausible clinical scenarios.

A Two-Stage Injection Technique and Dose-Ranging Study Using High-Dose AbobotulinumtoxinA for Treating Platysmal Bands.

BACKGROUND: AbobotulinumtoxinA (aboBoNT-A) is useful for the treatment of platysmal banding. This study evaluated the efficacy and safety of a standardized 2-staged injection technique using high doses of AboBoNT-A for treating platysmal banding. METHODS: This was a randomized, double-blinded, dose-ranging prospective study. Subjects included adults with moderate-to-severe platysmal bands (grade 3 or 4 on the validated 5-point photographic scale), who received either 120 U (Cohort 1) or 180 U (Cohort 2) of aboBoNT-A, followed by an optional 90 U touch-up. The relatively higher on-label concentration of aboBoNT-A was used (1.5 mL/300 units) to reduce the volume injected and the risk of spread to adjacent muscles. Subjects were followed for 5 months, with safety and efficacy endpoints evaluated by the Investigator Live Assessment (ILA) and Subject Live Assessment (SLA). RESULTS: Twenty women were included in the analysis. Cohort 1 and Cohort 2 had 100% and 90% responder rates (achieved grade 1 or 2) during maximal contraction at month 1 with ILA. Cohort 2 had more subjects with 2 or greater grade improvement at maximal contraction using both ILA and SLA. Cohort 2 also had longer time to loss of grade 1 or 2 at maximal contraction compared with Cohort 1. No major adverse reactions occurred, but 3 subjects experienced transient positional neck weakness. CONCLUSION: We demonstrate a standardized 2-stage injection technique using aboBoNT-A for effectively treating moderate-to-severe platysmal banding. We used relatively higher doses while maintaining a good safety profile by using the more concentrated on-label volume of reconstitution for aboBoNT-A and by including a touch-up. J Drugs Dermatol. 2024;23(1):1311-1318.     doi:10.36849/JDD.7537.

Do healthcare providers consider the social determinants of health? Results from a nationwide cross-sectional study in the United States.

BACKGROUND: While the social determinants of health (SDOH) have a greater impact on individual health outcomes than the healthcare services a person receives, healthcare providers face barriers to addressing these factors in clinical settings. Previous studies have shown that providers often lack the necessary knowledge and resources to adequately screen for and otherwise assist patients with unmet social needs. This study explores the perceptions and behaviors related to SDOH among healthcare providers in the United States (US). METHODS: This cross-sectional study analyzed data from a 22-item online survey using Reaction Data's research platform of healthcare professionals in the US. Survey items included demographic questions as well as Likert scale questions about healthcare providers' perceptions and behaviors related to SDOH. Descriptive statistics were calculated, and further analyses were conducted using t-tests and analysis of variance. RESULTS: A total of 563 respondents completed the survey, with the majority being male (72.6%), White (81%), and located in urban areas (82.2%). In terms of perceptions, most providers agreed or strongly agreed that SDOH affect the health outcomes of all patients (68.5%), while only 24.1% agreed or strongly agreed that their healthcare setting was set up to address SDOH. In terms of behavior, fewer than half currently screened for SDOH (48.6%) or addressed (42.7%) SDOH in other ways. Most providers (55.7%) wanted additional resources to focus on SDOH. Statistical analyses showed significant differences by gender, with females being more likely than males to prioritize SDOH, and by specialty, with psychiatrists, pediatricians, and family/general medicine practitioners being more likely to prioritize SDOH. CONCLUSION: Most healthcare providers understand the connection between unmet social needs and their patients' health, but they also feel limited in their ability to address these issues. Ongoing efforts to improve medical education and shift the healthcare system to allow for payment and delivery of more holistic care that considers SDOH will likely provide new opportunities for healthcare providers. In addition to what they can do at the institutional and patient levels, providers have the potential to advocate for policy and system changes at the societal level that can better address the root causes of social issues.

Development of the intelligent knee osteoarthritis lifestyle app: a person-based approach.

BACKGROUND: Knee osteoarthritis is one of the most prevalent long term health conditions globally. Exercise and physical activity are now widely recognised to significantly reduce joint pain, improve physical function and quality of life in patients with knee osteoarthritis. However, prescribed exercise without regular contact with a healthcare professional often results in lower adherence and poorer health outcomes. Digital mobile health (mHealth) technologies offer great potential to support people with long-term conditions such as knee osteoarthritis more efficiently and effectively and with relatively lower cost than existing interventions. However, there are currently very few mHealth interventions for the self-management of knee osteoarthritis. The aim of the present study was to describe the development process of a mHealth app to extend the support for physical activity and musculoskeletal health beyond short-term, structured rehabilitation through self-management, personalised physical activity, education, and social support. METHODS: The development of the intelligent knee osteoarthritis lifestyle application intervention involved an iterative and interconnected process comprising intervention 'planning' and 'optimisation' informed by the person-based approach framework for the development of digital health interventions. The planning phase involved a literature review and collection of qualitative data obtained from focus groups with individuals with knee osteoarthritis (n = 26) and interviews with relevant physiotherapists (n = 5) to generate 'guiding principles' for the intervention. The optimisation phase involved usability testing (n = 7) and qualitative 'think aloud' sessions (n = 6) with potential beneficiaries to refine the development of the intervention. RESULTS: Key themes that emerged from the qualitative data included the need for educational material, modifying activities to suit individual abilities and preferences as well as the inclusion of key features such as rehabilitation exercises. Following a user-trial further changes were made to improve the usability of the application. CONCLUSIONS: Using a systematic person-based, development approach, we have developed the intelligent knee osteoarthritis lifestyle application to help people maintain physical activity behaviour. The app extends the support for physical activity and musculoskeletal health beyond short-term, structured rehabilitation through personalised physical activity guidance, education, and social support.

A comprehensive meta-analysis of genetic parameters for resilience and productivity indicator traits in Holstein cattle.

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices.

Unraveling the genomic background of resilience based on variability in milk yield and milk production levels in North American Holstein cattle through genome-wide association study and Mendelian randomization analyses.

Breeding more resilient animals will benefit the dairy cattle industry in the long term, especially as global climate changes become more severe. Previous studies have reported genetic parameters for various milk yield-based resilience indicators, but the underlying genomic background of these traits remain unknown. In this study, we conducted GWAS of 62,029 SNPs with 4 milk yield-based resilience indicators, including the weighted occurrence frequency (wfPert) and accumulated milk losses (dPert) of milk yield perturbations, and log-transformed variance (LnVar) and lag-1 autocorrelation (rauto) of daily yield residuals. These variables were previously derived from 5.6 million daily milk yield records from 21,350 lactations (parities 1-3) of 11,787 North American Holstein cows. The average daily milk yield (ADMY) throughout lactation was also included to compare the shared genetic background of resilience indicators with milk yield. The differential genetic background of these indicators was first revealed by the significant genomic regions identified and significantly enriched biological pathways of positional candidate genes, which confirmed the genetic difference among resilience indicators. Interestingly, the functional analyses of candidate genes suggested that the regulation of intestinal homeostasis is most likely affecting resilience derived based on variability in milk yield. Based on Mendelian randomization analyses of multiple instrumental SNPs, we further found an unfavorable causal association of ADMY with LnVar. In conclusion, the resilience indicators evaluated are genetically different traits, and there are causal associations of milk yield with some of the resilience indicators evaluated. In addition to providing biological insights into the molecular regulation mechanisms of resilience derived based on variability in milk yield, this study also indicates the need for developing selection indexes combining multiple indicator traits and taking into account their genetic relationship for breeding more resilient dairy cattle.

Genetic parameters for calf feeding traits derived from automated milk feeding machines and number of bovine respiratory disease treatments in North American Holstein calves.

Precision livestock farming technologies, such as automatic milk feeding machines, have increased the availability of on-farm data collected from dairy operations. We analyzed feeding records from automatic milk feeding machines to evaluate the genetic background of milk feeding traits and bovine respiratory disease (BRD) in North American Holstein calves. Data from 10,076 preweaning female Holstein calves were collected daily over a period of 6 yr (3 yr included per-visit data), and daily milk consumption (DMC), per-visit milk consumption (PVMC), daily sum of drinking duration (DSDD), drinking duration per-visit, daily number of rewarded visits (DNRV), and total number of visits per day were recorded over a 60-d preweaning period. Additional traits were derived from these variables, including total consumption and duration variance (TCV and TDV), feeding interval, drinking speed (DS), and preweaning stayability. A single BRD-related trait was evaluated, which was the number of times a calf was treated for BRD (NTT). The NTT was determined by counting the number of BRD incidences before 60 d of age. All traits were analyzed using single-step genomic BLUP mixed-model equations and fitting either repeatability or random regression models in the BLUPF90+ suite of programs. A total of 10,076 calves with phenotypic records and genotypic information for 57,019 SNP after the quality control were included in the analyses. Feeding traits had low heritability estimates based on repeatability models (0.006 ± 0.0009 to 0.08 ± 0.004). However, total variance traits using an animal model had greater heritabilities of 0.21 ± 0.023 and 0.23 ± 0.024, for TCV and TDV, respectively. The heritability estimates increased with the repeatability model when using only the first 32 d preweaning (e.g., PVMC = 0.040 ± 0.003, DMC = 0.090 ± 0.009, DSDD = 0.100 ± 0.005, DS = 0.150 ± 0.007, DNRV = 0.020 ± 0.002). When fitting random regression models (RRM) using the full dataset (60-d period), greater heritability estimates were obtained (e.g., PVMC = 0.070 [range: 0.020, 0.110], DMC = 0.460 [range: 0.050, 0.680], DSDD = 0.180 [range: 0.010, 0.340], DS = 0.19 [range: 0.070, 0.430], DNRV = 0.120 [range: 0.030, 0.450]) for the majority of the traits, suggesting that RRM capture more genetic variability than the repeatability model with better fit being found for RRM. Moderate negative genetic correlations of -0.59 between DMC and NTT were observed, suggesting that automatic milk feeding machines records have the potential to be used for genetically improving disease resilience in Holstein calves. The results from this study provide key insights of the genetic background of early in-life traits in dairy cattle, which can be used for selecting animals with improved health outcomes and performance.

Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle.

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems have increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in a xyz plan, which can then be used to derive udder conformation traits. AMS generate a large amount of per milking visit data for individual cows, which contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multi-trait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 single nucleotide polymorphisms. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (±standard error, SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (±SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between the FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection sub-indexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.

Machine learning methods for genomic prediction of cow behavioral traits measured by automatic milking systems in North American Holstein cattle.

Identifying genome-enabled methods that provide more accurate genomic prediction is crucial when evaluating complex traits such as dairy cow behavior. In this study, we aimed to compare the predictive performance of traditional genomic prediction methods and deep learning algorithms for genomic prediction of milking refusals (MREF) and milking failures (MFAIL) in North American Holstein cows measured by automatic milking systems (milking robots). A total of 1,993,509 daily records from 4,511 genotyped Holstein cows were collected by 36 milking robot stations. After quality control, 57,600 SNPs were available for the analyses. Four genomic prediction methods were considered: Bayesian least absolute shrinkage and selection operator (LASSO), multiple layer perceptron (MLP), convolutional neural network (CNN), and GBLUP. We implemented the first 3 methods using the Keras and TensorFlow libraries in Python (v.3.9) but the GBLUP method was implemented using the BLUPF90+ family programs. The accuracy of genomic prediction (mean square error) for MREF and MFAIL was 0.34 (0.08) and 0.27 (0.08) based on LASSO, 0.36 (0.09) and 0.32 (0.09) for MLP, 0.37 (0.08) and 0.30 (0.09) for CNN, and 0.35 (0.09) and 0.31(0.09) based on GBLUP, respectively. Additionally, we observed a lower reranking of top selected individuals based on the MLP versus CNN methods compared with the other approaches for both MREF and MFAIL. Although the deep learning methods showed slightly higher accuracies than GBLUP, the results may not be sufficient to justify their use over traditional methods due to their higher computational demand and the difficulty of performing genomic prediction for nongenotyped individuals using deep learning procedures. Overall, this study provides insights into the potential feasibility of using deep learning methods to enhance genomic prediction accuracy for behavioral traits in livestock. Further research is needed to determine their practical applicability to large dairy cattle breeding programs.

Genome-wide association and functional genomic analyses for various hoof health traits in North American Holstein cattle.

Hoof diseases are a major welfare and economic issue in the global dairy cattle production industry, which can be minimized through improved management and breeding practices. Optimal genetic improvement of hoof health could benefit from a deep understanding of the genetic background and biological underpinning of indicators of hoof health. Therefore, the primary objectives of this study were to perform genome-wide association studies, using imputed high-density genetic markers data from North American Holstein cattle, for 8 hoof-related traits: digital dermatitis, sole ulcer, sole hemorrhage, white line lesion, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, and toe ulcer, and a hoof health index. De-regressed estimated breeding values from 25,580 Holstein animals were used as pseudo-phenotypes for the association analyses. The genomic quality control, genotype phasing, and genotype imputation were performed using the PLINK (version 1.9), Eagle (version 2.4.1), and Minimac4 software, respectively. The functional genomic analyses were performed using the GALLO R package and the DAVID platform. We identified 22, 34, 14, 22, 28, 33, 24, 43, and 15 significant markers for digital dermatitis, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, white line lesion disease, and the hoof health index, respectively. The significant markers were located across all autosomes, except BTA10, BTA12, BTA20, BTA26, BTA27, and BTA28. Moreover, the genomic regions identified overlap with various previously reported quantitative trait loci for exterior, health, meat and carcass, milk, production, and reproduction traits. The enrichment analyses identified 44 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously associated with bone development, metabolism, and infectious and immunological diseases. These findings indicate that hoof health traits are highly polygenic and influenced by a wide range of biological processes.

Evaluating post-rhinoplasty nasal obstruction treatment: The efficacy of VivAer radiofrequency ablation.

PURPOSE: Nasal obstruction is a prevalent issue affecting up to one-third of adults, often requiring surgical intervention. Low-temperature radiofrequency (RF) treatment, specifically VivAer, has emerged as a promising alternative, especially for the treatment of nasal valve collapse (NVC). However, its efficacy in patients with a history of rhinoplasty or nasal valve repair remains unexplored. METHODS: A single-center retrospective chart review was conducted on 37 patients with a history of rhinoplasty or nasal valve repair who underwent VivAer RF treatment. Treatment outcomes were assessed using the Nasal Obstruction Symptom Evaluation (NOSE) scale. The primary outcome was defined as a decrease in NOSE score by at least one severity category or a 20 % reduction in total NOSE score. RESULTS: The study found a statistically significant average reduction in NOSE score of 22.4 points or 36.6 %. Among patients with a positive treatment response (21 patients or 56.8 %), the average NOSE score reduction was 34.7 points or 55.6 %. Repeat RF treatment in non-responders resulted in a 50 % response rate. No significant difference was observed in treatment outcomes based on the type of prior rhinoplasty or NVC. CONCLUSIONS: Temperature-controlled RF treatment with VivAer can effectively alleviate nasal obstruction in patients with a history of rhinoplasty or nasal valve repair, offering a viable alternative to revision surgery. The study also highlights the potential benefit of repeat RF treatment in non-responders. Further research, including randomized controlled trials, is needed to validate these promising results and expand the treatment options for this complex patient population.