The CNS Relapse in T-Cell Lymphoma Index Predicts CNS Relapse in Patients with T- and NK-Cell Lymphomas.

Little is known about risk factors for central nervous system (CNS) relapse in mature T- and NK-cell neoplasms (MTNKN). We aimed to describe the clinical epidemiology of CNS relapse in patients with MTNKN and developed the CNS relapse In T-cell lymphoma Index (CITI) to predict patients at highest risk of CNS relapse. We reviewed data from 135 patients with MTNKN and CNS relapse from 19 North American institutions. After exclusion of leukemic and most cutaneous forms of MTNKN, patients were pooled with non-CNS relapse control patients from a single institution to create a CNS relapse-enriched training set. Using a complete case analysis (N=182), of whom 91 had CNS relapse, we applied a LASSO Cox regression model to select weighted clinicopathologic variables for the CITI score, which we validated in an external cohort from the Swedish Lymphoma Registry (N=566). CNS relapse was most frequently observed in patients with PTCL, NOS (25%). Median time to CNS relapse and median overall survival after CNS relapse was 8.0 months and 4.7 months, respectively. We calculated unique CITI risk scores for individual training set patients and stratified them into risk terciles. Validation set patients with low-risk (N=158) and high-risk (N=188) CITI scores had a 10-year cumulative risk of CNS relapse of 2.2% and 13.4%, respectively (HR 5.24, 95%CI 1.50-18.26, P=0.018). We developed an open-access web-based CITI calculator (https://redcap.link/citicalc) to provide an easy tool for clinical practice. The CITI score is a validated model to predict patients with MTNKN at highest risk of developing CNS relapse.

The Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan.

INTRODUCTION: Multimorbidity rates are both increasing in prevalence across age ranges, and also increasing in diagnostic importance within and outside the family medicine clinic. Here we aim to describe the course of multimorbidity across the lifespan. METHODS: This was a retrospective cohort study across 211,953 patients from a large northeastern health care system. Past medical histories were collected in the form of ICD-10 diagnostic codes. Rates of multimorbidity were calculated from comorbid diagnoses defined from the ICD10 codes identified in the past medical histories. RESULTS: We identify 4 main age groups of diagnosis and multimorbidity. Ages 0 to 10 contain diagnoses which are infectious or respiratory, whereas ages 10 to 40 are related to mental health. From ages 40 to 70 there is an emergence of alcohol use disorders and cardiometabolic disorders. And ages 70 to 90 are predominantly long-term sequelae of the most common cardiometabolic disorders. The mortality of the whole population over the study period was 5.7%, whereas the multimorbidity with the highest mortality across the study period was Circulatory Disorders-Circulatory Disorders at 23.1%. CONCLUSION: The results from this study provide a comparison for the presence of multimorbidity within age cohorts longitudinally across the population. These patterns of comorbidity can assist in the allocation to practice resources that will best support the common conditions that patients need assistance with, especially as the patients transition between pediatric, adult, and geriatric care. Future work examining and comparing multimorbidity indices is warranted.

Natural course of metastatic castration-resistant prostate cancer in the era of intensified androgen deprivation therapy in the hormone-sensitive setting.

BACKGROUND: Androgen deprivation therapy (ADT) intensification (ADTi) (i.e., ADT with androgen receptor pathway inhibitor or docetaxel, or both) has significantly improved survival outcomes of patients with metastatic hormone-sensitive prostate cancer (mHSPC). However, the impact of prior ADTi in the mHSPC setting on the disease presentation and survival outcomes in metastatic castration-resistant prostate cancer (mCRPC) is not well characterized. In this study, our objective was to compare the disease characteristics and survival outcomes of patients with new mCRPC with respect to receipt of intensified or nonintensified ADT in the mHSPC setting. METHODS: In this institutional review board-approved retrospective study, eligibility criteria were as follows: patients diagnosed with mCRPC, treated with an approved first-line mCRPC therapy, and who received either intensified or nonintensified ADT in the mHSPC setting. Progression-free survival (PFS) was defined from the start of first-line therapy for mCRPC to progression per Prostate Cancer Working Group 2 criteria or death, and overall survival (OS) was defined from the start of first-line therapy for mCRPC to death or censored at the last follow-up. A multivariable analysis using the Cox proportional hazards model was used, adjusting for potential confounders. RESULTS: Patients (n = 387) treated between March 20, 2008, and August 18, 2022, were eligible and included: 283 received nonintensified ADT, whereas 104 were treated with ADTi. At mCRPC diagnosis, patients in the ADTi group were significantly younger, had more visceral metastasis, lower baseline prostate-specific antigen (all p < 0.01), and lower hemoglobin (p = 0.027). Furthermore, they had significantly shorter PFS (median 4.8 vs. 8.4 months, adjusted hazard ratio [HR]: 1.46, 95% confidence interval [95% CI]: 1.07-2, p = 0.017) and OS (median 21.3 vs. 33.1 months, adjusted HR: 1.53, 95% CI: 1.06-2.21, p = 0.022) compared to patients in the nonintensified ADT group. CONCLUSION: Patients treated with ADTi in the mHSPC setting and experiencing disease progression to mCRPC had more aggressive disease features of mCRPC (characterized by a higher number of poor prognostic factors at mCRPC presentation). They also had shorter PFS on first-line mCRPC treatment and shorter OS after the onset of mCRPC compared to those not receiving ADTi in the mHSPC setting. Upon external validation, these findings may impact patient counseling, prognostication, treatment selection, and design of future clinical trials in the mCRPC setting. There remains an unmet need to develop novel life-prolonging therapies with new mechanisms of action to improve mCRPC prognosis in the current era.

Rehabilitation Outcomes in Multiple Sclerosis Patients on Ocrelizumab Diagnosed With West Nile Virus Encephalitis.

Multiple sclerosis (MS) has a global prevalence exceeding two million people and is a leading cause of non-traumatic physical disability. MS can be treated with ocrelizumab, an anti-CD20 monoclonal antibody. West Nile virus (WNV) is the most common cause of mosquito-borne viral encephalitis in North America. It can lead to neuroinvasive WNV disease (WNND) affecting the brain and peripheral nervous system, especially in immunocompromised patients, such as those being treated with ocrelizumab for MS. WNND is exceedingly rare and reported in less than 1% of cases of WNV. It has been established that inpatient rehabilitation improves functional outcomes in patients with MS and those with WNND. However, the inpatient rehabilitation outcomes in patients diagnosed with both WNND and MS have not been reported. In this study, we aimed to examine the rehabilitation outcomes of MS patients on ocrelizumab diagnosed with WNND. We performed a retrospective chart review of patients with MS treated with ocrelizumab, who were diagnosed with WNND and admitted to a single facility. Rehabilitation outcomes were assessed using functional independence measure (FIM) scores on admission and discharge. Three patients met the inclusion criteria; two in acute rehab, and one in the long-term acute care hospital (LTACH). Both patients admitted to acute inpatient rehabilitation showed an improvement in FIM scores from admission to discharge, one patient from 9 to 16 and the other from 14 to 54. However, the patient admitted to the LTACH had no improvement in FIM score from admission to discharge. Patients admitted to acute rehab were ultimately discharged home, while the patient admitted to the LTACH required discharge to a subacute rehabilitation facility. Based on our findings, intense and prolonged comprehensive inpatient rehabilitation is associated with improved functional outcomes and increased likelihood of discharge to home in this population suffering from both central and peripheral nervous system involvement due to MS and WNND.

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research.

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

Management dilemmas in pediatric nephrology: moving from friction to flourishing in "challenging" cases.

BACKGROUND: The circumstances surrounding chronic kidney disease and its impact on families can be complex and difficult to navigate, leading to these cases being labeled "challenging." CASE PRESENTATION: We present the case of an adolescent with kidney failure due to unremitting systemic illness and multiple complications ultimately resulting in the family's request to forgo dialysis. Medical team members wrestled with meeting the family's needs among internal and external constraints. CONCLUSION: Past experiences, systemic inequities, differing perspectives, and consequential decision-making within individual belief systems can lead to friction between and among medical team members and families. As pediatric nephrologists, we must shift our focus from the "challenging" patient or family to addressing what is challenging their ability to flourishing.

Validation of actigraphy sleep metrics in children aged 8 to 16 years: considerations for device type, placement and algorithms.

BACKGROUND: Actigraphy is often used to measure sleep in pediatric populations, despite little confirmatory evidence of the accuracy of existing sleep/wake algorithms. The aim of this study was to determine the performance of 11 sleep algorithms in relation to overnight polysomnography in children and adolescents. METHODS: One hundred thirty-seven participants aged 8-16 years wore two Actigraph wGT3X-BT (wrist, waist) and three Axivity AX3 (wrist, back, thigh) accelerometers over 24-h. Gold standard measures of sleep were obtained using polysomnography (PSG; Embletta MPRPG, ST + Proxy and TX Proxy) in the home environment, overnight. Epoch by epoch comparisons of the Sadeh (two algorithms), Cole-Kripke (three algorithms), Tudor-Locke (four algorithms), Count-Scaled (CS), and HDCZA algorithms were undertaken. Mean differences from PSG values were calculated for various sleep outcomes. RESULTS: Overall, sensitivities were high (mean ± SD: 91.8%, ± 5.6%) and specificities moderate (63.8% ± 13.8%), with the HDCZA algorithm performing the best overall in terms of specificity (87.5% ± 1.3%) and accuracy (86.4% ± 0.9%). Sleep outcome measures were more accurately measured by devices worn at the wrist than the hip, thigh or lower back, with the exception of sleep efficiency where the reverse was true. The CS algorithm provided consistently accurate measures of sleep onset: the mean (95%CI) difference at the wrist with Axivity was 2 min (-6; -14,) and the offset was 10 min (5, -19). Several algorithms provided accurate measures of sleep quantity at the wrist, showing differences with PSG of just 1-18 min a night for sleep period time and 5-22 min for total sleep time. Accuracy was generally higher for sleep efficiency than for frequency of night wakings or wake after sleep onset. The CS algorithm was more accurate at assessing sleep period time, with narrower 95% limits of agreement compared to the HDCZA (CS:-165 to 172 min; HDCZA: -212 to 250 min). CONCLUSION: Although the performance of existing count-based sleep algorithms varies markedly, wrist-worn devices provide more accurate measures of most sleep measures compared to other sites. Overall, the HDZCA algorithm showed the greatest accuracy, although the most appropriate algorithm depends on the sleep measure of focus.

Comparing changes in eating disorder psychopathology and comorbid symptoms over treatment in anorexia nervosa and atypical anorexia nervosa in a partial hospitalization program.

OBJECTIVE: The objective of this study is to compare treatment trajectories in anorexia nervosa (AN) and atypical AN. METHOD: Adolescents and adults with AN (n = 319) or atypical AN (n = 67) in a partial hospitalization program (PHP) completed diagnostic interviews and self-report questionnaires measuring eating disorder (ED), depression, and anxiety symptoms throughout treatment. RESULTS: Premorbid weight loss did not differ between diagnoses. Individuals with atypical AN had more comorbid diagnoses, but groups did not differ on specific diagnoses. ED psychopathology and comorbid symptoms of depression/anxiety did not differ at admission between groups nor did rate of change in ED psychopathology and comorbid symptoms of depression/anxiety from admission to 1-month. From admission to discharge, individuals with atypical AN had a faster reduction in ED psychopathology and comorbid symptoms of depression and anxiety (ps < 0.05; rs = 0.01-0.32); however, there were no group differences in ED psychopathology or depression symptoms at discharge (ps>.50; ds = .01-.30). Individuals with atypical AN had lower anxiety at discharge compared to individuals with AN (p = 0.05; d = .4). Length of stay did not differ between groups (p = 0.11; d = .21). DISCUSSION: Groups had similar ED treatment trajectories, suggesting more similarities than differences. PHP may also be effective for AAN. PUBLIC SIGNIFICANCE: This study supports previous research that individuals with AN and atypical AN have more similarities than differences. Results from this study indicate that individuals with AN and atypical AN have similar treatment outcomes for both ED psychopathology and depressive symptoms; however, individuals with atypical AN have lower anxiety symptoms at discharge compared to individuals with AN. AN and atypical AN also have more symptom similarity at admission and throughout treatment, which challenges their current designation as distinct disorders.

Peripheral Nerve Stimulation in Postoperative Analgesia: A Narrative Review.

PURPOSE OF REVIEW: Recent research has shown the effectiveness of peripheral nerve stimulators (PNS) in managing chronic pain conditions. Ongoing studies aim to explore its potential application in treating acute postoperative pain states. The purpose of this systematic review is to assess the role of PNS in providing relief for postoperative pain. RECENT FINDINGS: Clinical studies investigating the use of peripheral nerve stimulators (PNS) for analgesia following various surgeries, such as total knee arthroplasty, anterior cruciate ligament repair, ankle arthroplasty, rotator cuff repair, hallux valgus correction, and extremity amputation, have shown promising results. Lead placement locations include the brachial plexus, sciatic, femoral, tibial, genicular, perineal, sural, radial, median, and ulnar nerves. These studies consistently report clinically significant reductions in pain scores, and some even indicate a decrease in opioid consumption following PNS for postoperative pain. PNS involves the subcutaneous placement of electrode leads to target peripheral nerve(s) followed by delivery of an electric current via an external pulse generator. While the precise mechanism is not fully understood, the theory posits that PNS modulates electrical stimulation, hindering the signaling of nociceptive pain. PNS presents itself as an alternative to opioid therapy, holding promise to address the opioid epidemic by offering a nonpharmacologic approach for both acute and chronic pain states.

Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.

BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text such as electronic health record (EHR) notes. This opens the door to large-scale projects that rely on variables that are not typically recorded in a structured form, such as patient signs and symptoms. OBJECTIVES: This study is designed to acquaint the emergency medicine research community with the foundational elements of NLP, highlighting essential terminology, annotation methodologies, and the intricacies involved in training and evaluating NLP models. Symptom characterization is critical to urinary tract infection (UTI) diagnosis, but identification of symptoms from the EHR has historically been challenging, limiting large-scale research, public health surveillance, and EHR-based clinical decision support. We therefore developed and compared two NLP models to identify UTI symptoms from unstructured emergency department (ED) notes. METHODS: The study population consisted of patients aged ≥ 18 who presented to an ED in a northeastern U.S. health system between June 2013 and August 2021 and had a urinalysis performed. We annotated a random subset of 1250 ED clinician notes from these visits for a list of 17 UTI symptoms. We then developed two task-specific LLMs to perform the task of named entity recognition: a convolutional neural network-based model (SpaCy) and a transformer-based model designed to process longer documents (Clinical Longformer). Models were trained on 1000 notes and tested on a holdout set of 250 notes. We compared model performance (precision, recall, F1 measure) at identifying the presence or absence of UTI symptoms at the note level. RESULTS: A total of 8135 entities were identified in 1250 notes; 83.6% of notes included at least one entity. Overall F1 measure for note-level symptom identification weighted by entity frequency was 0.84 for the SpaCy model and 0.88 for the Longformer model. F1 measure for identifying presence or absence of any UTI symptom in a clinical note was 0.96 (232/250 correctly classified) for the SpaCy model and 0.98 (240/250 correctly classified) for the Longformer model. CONCLUSIONS: The study demonstrated the utility of LLMs and transformer-based models in particular for extracting UTI symptoms from unstructured ED clinical notes; models were highly accurate for detecting the presence or absence of any UTI symptom on the note level, with variable performance for individual symptoms.

Dynamic disability measures decrease the clinico-radiological gap in people with severely affected multiple sclerosis.

BACKGROUND: Expanded Disability Status Scale (EDSS) is limited when utilized in highly disabled people with multiple sclerosis (pwMS). OBJETIVE: To explore the relationship between disability measures and MRI outcomes in severely-affected pwMS. METHODS: PwMS recruited from The Boston Home (TBH), a specialized residential facility for severly-affected pwMS and University at Buffalo (UB) MS Center were assessed using EDSS, MS Severity Scale, age-related MSS, Scripps Neurological Rating Scale (SNRS) and Combinatorial Weight-Adjusted Disability Score (CombiWISE). In all scores except SNRS, higher score indicates greater disability. MRI measures of T1, T2-lesion volume (LV), whole brain, gray matter, medulla oblongata and thalamic volumes (WBV, GMV, MOV, TV) and thalamic dysconnectivity were obtained. RESULTS: Greatest disability differences between the TBH and UB pwMS were in SNRS (24.4 vs 71.9, p < 0.001, Cohen's d = 4.05) and CombiWISE (82.3 vs. 38.9, p < 0.001, Cohen's d = 4.02). In combined analysis of all pwMS, worse SNRS scores were correlated with worse MRI pathology in 8 out of 9 outcomes. EDSS only with 3 measures (GMV, MOV and TV). In severely-affected pwMS, SNRS was associated with T1-LV, T2-LV and WBV (not surviving false discovery rate (FDR) correction for multiple comparisons) whereas EDSS did not. CONCLUSION: Granular and dynamic disability measures may bridge the clinico-radiologcal gap present in severely affected pwMS.

Proximal Row Carpectomy with and without Capitate Resurfacing: A Preliminary Systematic Review and Meta-Analysis.

BACKGROUND: In wrist salvage, proximal row carpectomy (PRC) has increasingly shown superior outcomes to four-corner fusion (4CF). Furthermore, PRC with resurfacing capitate pyrocarbon implants (PRC + RCPIs) provides a treatment option that may allow patients to avoid 4CF or wrist arthrodesis and help restore natural joint function and distribute loads evenly across the implant, though RCPI has yet to be evaluated on a large scale. We aimed to compare outcomes between PRC and PRC + RCPI for the treatment of scapholunate advanced collapse (SLAC) and scaphoid nonunion advanced collapse (SNAC) wrists. METHODS: A systematic review and meta-analysis was performed per Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed/MEDLINE, Embase, Web of Science, and Cochrane were queried for articles on PRC and PRC + RCPI performed for SLAC and SNAC wrist with minimum 12-month follow-up. Primary outcomes included wrist range of motion (ROM), grip strength, and outcome scores including Disabilities of Arm, Shoulder, and Hand (DASH) and QuickDASH scores, Patient-Rated Wrist and Hand Evaluation (PRWHE), and visual analog scale pain scores. RESULTS: Twenty-two studies reporting on 1,804 wrists were included (1,718 PRC alone, 86 PRC + RCPI). PRC + RCPI was associated with greater postoperative radial deviation, but poorer flexion. PRC + RCPI also had significantly lower postoperative QuickDASH (less disability and symptoms) and postoperative PRWHE (lower pain and disability) scores and an improvement in PRWHE compared with PRC. There was no significant difference in grip strength. CONCLUSION: PRC + RCPI demonstrated similar postoperative ROM to PRC alone. While PRC + RCPI was associated with more favorable outcome scores, further research is needed to confirm these findings and assess the incidence and profile of complications related to RCPIs. LEVEL OF EVIDENCE: Level IV. See Instructions for Authors for a complete description of levels of evidence.

The nociceptive activity of peripheral sensory neurons is modulated by the neuronal membrane proteasome.

Proteasomes are critical for peripheral nervous system (PNS) function. Here, we investigate mammalian PNS proteasomes and reveal the presence of the neuronal membrane proteasome (NMP). We show that specific inhibition of the NMP on distal nerve fibers innervating the mouse hind paw leads to reduction in mechanical and pain sensitivity. Through investigating PNS NMPs, we demonstrate their presence on the somata and proximal and distal axons of a subset of dorsal root ganglion (DRG) neurons. Single-cell RNA sequencing experiments reveal that the NMP-expressing DRGs are primarily MrgprA3+ and Cysltr2+. NMP inhibition in DRG cultures leads to cell-autonomous and non-cell-autonomous changes in Ca2+ signaling induced by KCl depolarization, αß-meATP, or the pruritogen histamine. Taken together, these data support a model whereby NMPs are expressed on a subset of somatosensory DRGs to modulate signaling between neurons of distinct sensory modalities and indicate the NMP as a potential target for controlling pain.

Shoulder terminal sensory articular nerve radiofrequency ablation for non-surgical refractory shoulder pain due to rotator cuff pathology and osteoarthritis: A technical note.

BACKGROUND: Given the high prevalence of chronic shoulder pain and encouraging early results of terminal sensory articular branch (TSAB) radiofrequency ablation to treat shoulder pain, research is warranted to refine the procedural technique based on updated neuroanatomical knowledge with the goal of further improving patient outcomes. OBJECTIVE: We describe an updated radiofrequency ablation protocol that accounts for varied locations of the TSABs of suprascapular, axillary, subscapular and lateral pectoral nerves within individual patients. DESIGN: Technical note. METHODS: Cadaveric studies delineating the sensory innervation of the shoulder joint were reviewed, and a more comprehensive radiofrequency ablation (RFA) protocol is proposed relative to historical descriptions. CONCLUSIONS: Based on neuroanatomical dissections of the shoulder joint, the proposed RFA protocol will provide a safe means of more complete sensory denervation and potentially improve clinical outcomes compared to historical descriptions, which must be confirmed in prospective studies.

Automated HEART score determination via ChatGPT: Honing a framework for iterative prompt development.

Objectives: This study presents a design framework to enhance the accuracy by which large language models (LLMs), like ChatGPT can extract insights from clinical notes. We highlight this framework via prompt refinement for the automated determination of HEART (History, ECG, Age, Risk factors, Troponin risk algorithm) scores in chest pain evaluation. Methods: We developed a pipeline for LLM prompt testing, employing stochastic repeat testing and quantifying response errors relative to physician assessment. We evaluated the pipeline for automated HEART score determination across a limited set of 24 synthetic clinical notes representing four simulated patients. To assess whether iterative prompt design could improve the LLMs' ability to extract complex clinical concepts and apply rule-based logic to translate them to HEART subscores, we monitored diagnostic performance during prompt iteration. Results: Validation included three iterative rounds of prompt improvement for three HEART subscores with 25 repeat trials totaling 1200 queries each for GPT-3.5 and GPT-4. For both LLM models, from initial to final prompt design, there was a decrease in the rate of responses with erroneous, non-numerical subscore answers. Accuracy of numerical responses for HEART subscores (discrete 0-2 point scale) improved for GPT-4 from the initial to final prompt iteration, decreasing from a mean error of 0.16-0.10 (95% confidence interval: 0.07-0.14) points. Conclusion: We established a framework for iterative prompt design in the clinical space. Although the results indicate potential for integrating LLMs in structured clinical note analysis, translation to real, large-scale clinical data with appropriate data privacy safeguards is needed.

Identifying incarceration status in the electronic health record using large language models in emergency department settings.

Background: Incarceration is a significant social determinant of health, contributing to high morbidity, mortality, and racialized health inequities. However, incarceration status is largely invisible to health services research due to inadequate clinical electronic health record (EHR) capture. This study aims to develop, train, and validate natural language processing (NLP) techniques to more effectively identify incarceration status in the EHR. Methods: The study population consisted of adult patients (≥ 18 y.o.) who presented to the emergency department between June 2013 and August 2021. The EHR database was filtered for notes for specific incarceration-related terms, and then a random selection of 1,000 notes was annotated for incarceration and further stratified into specific statuses of prior history, recent, and current incarceration. For NLP model development, 80% of the notes were used to train the Longformer-based and RoBERTa algorithms. The remaining 20% of the notes underwent analysis with GPT-4. Results: There were 849 unique patients across 989 visits in the 1000 annotated notes. Manual annotation revealed that 559 of 1000 notes (55.9%) contained evidence of incarceration history. ICD-10 code (sensitivity: 4.8%, specificity: 99.1%, F1-score: 0.09) demonstrated inferior performance to RoBERTa NLP (sensitivity: 78.6%, specificity: 73.3%, F1-score: 0.79), Longformer NLP (sensitivity: 94.6%, specificity: 87.5%, F1-score: 0.93), and GPT-4 (sensitivity: 100%, specificity: 61.1%, F1-score: 0.86). Conclusions: Our advanced NLP models demonstrate a high degree of accuracy in identifying incarceration status from clinical notes. Further research is needed to explore their scaled implementation in population health initiatives and assess their potential to mitigate health disparities through tailored system interventions.

Ruminal Microbiome Differences in Angus Steers with Differing Feed Efficiencies during the Feedlot Finishing Phase.

The catabolic activity of the ruminal microbial community of cattle enables the conversion of low-quality feedstuffs into meat and milk. The rate at which this conversion occurs is termed feed efficiency, which is of crucial importance given that feed expenses account for up to 70% of the cost of animal production. The present study assessed the relationship between cattle feed efficiency and the composition of their ruminal microbial communities during the feedlot finishing period. Angus steers (n = 65) were fed a feedlot finishing diet for 82 days and their growth performance metrics were evaluated. These included the dry matter intake (DMI), average daily gain (ADG), and residual feed intake (RFI). Steers were rank-ordered based upon their RFI, and the five lowest RFI (most efficient) and five highest RFI (least efficient) steers were selected for evaluations. Ruminal fluid samples were collected on days 0 and 82 of the finishing period. Volatile fatty acids (VFA) were quantified, and microbial DNA was extracted and the 16S rRNA gene was sequenced. The results showed that the ADG was not different (p = 0.82) between efficiency groups during the 82-day feedlot period; however, the efficient steers had lower (p = 0.03) DMI and RFI (p = 0.003). Less-efficient (high RFI) steers developed higher (p = 0.01) ruminal Methanobrevibacter relative abundances (p = 0.01) and tended (p = 0.09) to have more Methanosphaera. In high-efficiency steers (low RFI), the relative abundances of Ruminococcaceae increased (p = 0.04) over the 82-day period. The molar proportions of VFA were not different between the two efficiency groups, but some changes in the concentration of specific VFA were observed over time. The results indicated that the ruminal microbial populations of the less-efficient steers contained a greater relative abundance of methanogens compared to the high-efficiency steers during the feedlot phase, likely resulting in more energetic waste in the form or methane and less dietary energy being harvested by the less-efficient animals.