Elephants and algorithms: a review of the current and future role of AI in elephant monitoring.

Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to enhance our understanding of animal behaviour and conservation strategies. Using elephants, a crucial species in Africa and Asia's protected areas, as our focal point, we delve into the role of AI and ML in their conservation. Given the increasing amounts of data gathered from a variety of sensors like cameras, microphones, geophones, drones and satellites, the challenge lies in managing and interpreting this vast data. New AI and ML techniques offer solutions to streamline this process, helping us extract vital information that might otherwise be overlooked. This paper focuses on the different AI-driven monitoring methods and their potential for improving elephant conservation. Collaborative efforts between AI experts and ecological researchers are essential in leveraging these innovative technologies for enhanced wildlife conservation, setting a precedent for numerous other species.

What factors drive polyethylene wear in total knee arthroplasty? : results of a large retrieval series.

AIMS: Wear of the polyethylene (PE) tibial insert of total knee arthroplasty (TKA) increases the risk of revision surgery with a significant cost burden on the healthcare system. This study quantifies wear performance of tibial inserts in a large and diverse series of retrieved TKAs to evaluate the effect of factors related to the patient, knee design, and bearing material on tibial insert wear performance. METHODS: An institutional review board-approved retrieval archive was surveyed for modular PE tibial inserts over a range of in vivo duration (mean 58 months (0 to 290)). Five knee designs, totalling 1,585 devices, were studied. Insert wear was estimated from measured thickness change using a previously published method. Linear regression statistical analyses were used to test association of 12 patient and implant design variables with calculated wear rate. RESULTS: Five patient-specific variables and seven implant-specific variables were evaluated for significant association with lower insert wear rate. Six were significant when controlling for other factors: greater patient age, female sex, shorter duration in vivo, polished tray, highly cross-linked PE (HXLPE), and constrained knee design. CONCLUSION: This study confirmed that knee wear rate increased with duration in vivo. Older patients and females had significantly lower wear rates. Polished modular tibial tray surfaces, HXLPE, and constrained TKA designs were device design factors associated with significantly reduced wear rate. Cite this article: Bone Joint J 2021;103-B(11):1695-1701.

Certified Registered Nurse Anesthetists' Management of the Perioperative Do-Not-Resuscitate Order: Evaluating Trends in Required Reconsideration.

Required reconsideration or review of do-not-resuscitate (DNR) orders perioperatively is recommended by the American Association of Nurse Anesthesiology and other organizations instead of automatic suspension of the DNR. A survey on perioperative DNR orders developed for a 2000 study by Coopmans and Gries was amended, reviewed by an expert panel, reformatted for web-based layout, and emailed to a random sample of 3,000 practicing Certified Registered Nurse Anesthetists (CRNAs) in the United States. From 207 returned responses, most CRNAs (63.5%) initially reported unfamiliarity with required reconsideration. After receiving a definition of the term, more CRNAs reported familiarity and past education on the concept. Chi-square analyses showed that familiarity with required reconsideration was associated with potential refusal to care for patients with active DNR orders (P=.004). CRNAs reported education or training on required reconsideration as uncommon and often informal. The survey found significant changes in reported perioperative DNR orders at practice institutions between the original survey by Coopmans and Gries and the present study. CRNAs' responses from the present survey indicate significant increases in policies of required review with patient involvement and policies of informed routine suspension (P<.001). Findings also revealed a significant decrease in reported policies of uninformed routine suspension (P<.001).

MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks.

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep-learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules-such as gene promoter context, CpG island relationship, or user-defined groupings-and relate them to diagnostic and prognostic outcomes. We demonstrate these models' utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep-learning analyses' interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

Enrichment of CpG island shore region hypermethylation in epigenetic breast field cancerization.

While changes in DNA methylation are known to occur early in breast carcinogenesis and the landscape of breast tumour DNA methylation is profoundly altered compared with normal tissue, there have been limited efforts to identify DNA methylation field cancerization effects in histologically normal breast tissue adjacent to tumour. Matched tumour, histologically normal tissue of the ipsilateral breast (ipsilateral-normal), and histologically normal tissue of the contralateral breast (contralateral-normal) were obtained from nine women undergoing bilateral mastectomy. Laser capture microdissection was used to select epithelial cells from normal tissue, and neoplastic cells from tumour for genome-scale measures of DNA methylation with the Illumina HumanMethylationEPIC array. We identified substantially more CpG loci that were differentially methylated between contralateral-normal and tumour (63,271 CpG loci q < 0.01), than between ipsilateral-normal and tumour (38,346 CpG loci q < 0.01). We identified differential methylation in ipsilateral-normal relative to contralateral-normal tissue (9,562 CpG loci p < 0.01). In this comparison, hypomethylated loci were significantly enriched for breast cancer-relevant transcription factor binding sites including those for ESR1, FoxA1, and GATA3 and hypermethylated loci were significantly enriched for CpG island shore regions. In addition, progression of shore hypermethylation was observed in tumours compared to matched ipsilateral normal tissue, and these alterations tracked to several well-established tumour suppressor genes. Our results indicate an epigenetic field effect in surrounding histologically normal tissue. This work offers an opportunity to focus investigations of early DNA methylation alterations in breast carcinogenesis and potentially develop epigenetic biomarkers of disease risk. ABBREVIATIONS: DCIS: ductal carcinoma in situ; GO: gene ontology; OR: odds ratio; CI: confidence interval; TFBS: transcription factor binding site; LOLA: Locus Overlap Analysis.

MethylNet: an automated and modular deep learning approach for DNA methylation analysis.

BACKGROUND: DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease heterogeneity. DNAm deep learning approaches have not yet been formalized into user-friendly frameworks for execution, training, and interpreting models. Here, we describe MethylNet, a DNAm deep learning method that can construct embeddings, make predictions, generate new data, and uncover unknown heterogeneity with minimal user supervision. RESULTS: The results of our experiments indicate that MethylNet can study cellular differences, grasp higher order information of cancer sub-types, estimate age and capture factors associated with smoking in concordance with known differences. CONCLUSION: The ability of MethylNet to capture nonlinear interactions presents an opportunity for further study of unknown disease, cellular heterogeneity and aging processes.

Effectiveness of local anesthetic injection in geriatric patients following operative management of proximal and diaphyseal femur fracture.

INTRODUCTION: Geriatric fracture patients are at risk for poorly controlled pain and side effects of opioid medications. The arthroplasty literature has demonstrated that infiltration of long-acting local anesthetic or anesthetic cocktails improves pain control and reduces post-operative opioid use resulting in better postoperative mobility without the deleterious effects of narcotics. Despite having a higher risk for adverse events, there is limited data among geriatric trauma patients. The aim this study was to evaluate whether local anesthetic infiltration (LAI) into the soft tissues surrounding the surgical field reduces narcotic use or pain scores in patients undergoing surgical management of proximal and diaphyseal femur fractures. MATERIALS AND METHODS: A retrospective review was performed of patients age >65 undergoing operative intervention for proximal and diaphyseal femur fracture. The electronic record was utilized to determine if local anesthetic was injected into the surgical wound, the amount of narcotics administered over 48 h in four-hour intervals, and to obtain visual analog scale (VAS) pain scores associated with patients post-operative course in four-hour intervals. The amount of narcotics was converted to morphine milligram equivalents (MME). RESULTS: Among 477 patients with femur fracture, 358 did not receive LAI and 119 patients received LAI. Baseline demographics, fracture types, and surgical procedure were equivalent between the groups. In the first 28 h following surgery, compared with those who did not receive LAI, those who did required significantly less opioid (57.8 MME versus 94.3 MME, p = 0.034) and despite decreased narcotics, had equal pain scores (mean difference 0.37, p = 0.22). There was no difference in rates of post-operative complications. CONCLUSION: LAI is associated with a reduction in opioid consumption in geriatric fracture patients with equivalent pain scores. Optimizing pain control is a critical issue in caring for geriatric fracture patients since both under-treated pain and opioid medications are implicated in postoperative delirium, complications, and ability to mobilize early. More research is needed to identify effective ways to optimize pain management in this at-risk patient population.

PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.

SUMMARY: Performing highly parallelized preprocessing of methylation array data using Python can accelerate data preparation for downstream methylation analyses, including large scale production-ready machine learning pipelines. We present a highly reproducible, scalable pipeline (PyMethylProcess) that can be quickly set-up and deployed through Docker and PIP. AVAILABILITY AND IMPLEMENTATION: Project Home Page: https://github.com/Christensen-Lab-Dartmouth/PyMethylProcess. Available on PyPI (pymethylprocess), Docker (joshualevy44/pymethylprocess). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Duration of military service is associated with decision quality in Veterans considering total knee replacement: case series.

PURPOSE: Due to the nature of military service, the patient-physician relationship in Veterans is unlike that seen in civilian life. The structure of the military is hypothesized to result in barriers to open patient-physician communication and patient participation in elective care decision-making. Decision quality is a measure of concordance between a chosen treatment and the aspects of medical care that matter most to an informed patient; high decision quality is synonymous with patient-centered care. While past research has examined how age and other demographic factors affect decision quality in Veterans, duration of military service, rank at discharge, and years since discharge have not been studied. PATIENTS AND METHODS: We enrolled 25 Veterans with knee osteoarthritis at a VA hospital. Enrollees completed a survey with demographic, military service, and decision-making preference questions and the Hip-Knee Decision Quality Instrument (HK-DQI), which measures patients' knowledge about their disease process, concordance of their treatment decision, and the considered elements in their decision-making process. RESULTS: The HK-DQI knowledge score had a significant, positive correlation with duration of military service (R2=0.36, p=0.004). Rank at discharge and years since discharge did not show a significant correlation with decision quality (p=0.500 and p=0.317, respectively). The concordance score did not show a statistically significant correlation with rank, duration of service, and years since discharge (p=0.640, p=0.486 and p=0.795, respectively). Additionally, decision process score was not significantly associated with rank, duration of military service, and years since discharge (p=0.380, p=0.885, and p=0.474, respectively). CONCLUSION: Decision quality in Veterans considering treatment for knee osteoarthritis appears to be correlated positively with duration of military service. These findings may present an opportunity for identification of Veterans at most risk of low decision quality and customization of shared decision-making methods for Veterans by characteristics of military service.

Relationship Between Food Insecurity and Functional Limitations in Older Adults from 2005-2014 NHANES.

Background: Food insecurity refers to the physical, social, and economic inability to access and secure sufficient, safe and nutritious food. Food insecurity has been found to be associated with poor health status, obesity, and chronic disease. To date, a relationship between food insecurity and functional limitations has not been described in of older adults. Methods: We examined 9309 adults ≥60 years old from the 2005-2014 National Health and Nutrition Examination Surveys (NHANES). Food security was categorized as full, marginal, low, and very low. Functional limitations were assessed as having difficulty in physical, basic or instrumental activities of daily living. Results: Of adults ≥60 years old (mean age: 70.5 ± 0.08, 51% female), the prevalence of full, marginal, low, or very low food insecurity was 7572 (81%), 717 (7%), 667 (8%), and 353 (4%), respectively. The prevalence of any functional limitations was 5895 (66.3%). The adjusted odds (OR [95%CI]) of having any functional limitation in marginal, low, and very low food security levels compared to full food security are: 1.08 [1.02-1.13], 1.16 [1.10-1.22], 1.14 [1.07-1.21], respectively. The association between levels of food insecurity and functional limitation is modified by race/ethnicity. Conclusions: Functional limitation is significantly associated with increasing food insecurity in older adults.

Varying Levels of Food Insecurity Associated with Clinically Relevant Depressive Symptoms in U.S. Adults Aged 60 Years and Over: Results from the 2005-2014 National Health and Nutrition Survey.

Food insecurity refers to restricted or uncertain access to and ineffective utilization of nutritious and safe foods. Although food insecurity is linked to poorer physical health consequences among older adults, national estimates are not well known on food insecurity and depression. Using the 2005-2014 National Health and Nutrition Examination Survey, this study examines the associations between varying food insecurity levels and clinically relevant depressive symptoms (defined by PHQ-9 ≥ 10) among adults ≥60 years old (n = 7969). Rates of clinically relevant depressive symptoms in marginal, low, and very low food security were 12.3, 16.3, and 25.2%, respectively. Marginal, low, and very low food security were significantly associated with clinically relevant depressive symptoms: odds ratio (OR) = 1.12 (95% confidence intervals [CI] 1.07-1.18), OR = 1.07 (95% CI 1.03-1.12), and OR = 1.24 (95% CI 1.16-1.32), respectively. Given the intersection of food insecurity and depression, geriatric health professionals should work to improve health and nutrition programs for older adults at risk for or experiencing both public health concerns.

Are Geriatric Patients Who Sustain High-Energy Traumatic Injury Likely to Return to Functional Independence?

OBJECTIVES: To evaluate physical function and return to independence of geriatric trauma patients, to compare physical function outcomes of geriatric patients who sustained high-energy trauma with that of those who sustained low-energy trauma, and to identify predictors of physical function outcomes. DESIGN: Retrospective. SETTING: Urban Level I trauma center. PATIENTS: Study group of 216 patients with high-energy trauma and comparison group of 117 patients with low-energy trauma. INTERVENTION: Injury mechanism (high- vs. low-energy mechanism). MAIN OUTCOME MEASUREMENT: Patient-Reported Outcomes Measurement Information System Physical Function (PROMIS PF) patient-reported outcome measure, and change in living situation and mobility. RESULTS: Physical function outcomes and return to independence differed between patients with high-energy and low-energy injuries. High-energy geriatric trauma patients had significantly higher PROMIS PF scores compared with low-energy geriatric trauma patients (PROMIS PF score 42.2 ± 10.4 vs. 24.6 ± 10.4, P < 0.001). High-energy geriatric trauma patients were able to ambulate outdoors without an assistive device in 67% of cases and were living independently 74% of the time in comparison with 28% and 45% of low-energy geriatric trauma patients, respectively (P < 0.001, P < 0.001). Multivariate linear regression analysis demonstrated that low-energy mechanism injury was independently associated with a 13.2 point reduction in PROMIS PF score (P < 0.001). CONCLUSIONS: Geriatric patients greater than 1 year out from sustaining a high-energy traumatic injury seem to be functioning within the expected range for their age, whereas low-energy trauma patients seem to be functioning substantially worse than both age-adjusted norms and their high-energy cohorts. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

MicroRNA-Related Genetic Variants Associated with Survival of Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is commonly diagnosed at an advanced stage, and prognosis for such patients is poor. There remains a gap in our understanding of genetic variants related with HNSCC prognosis. miRNA-related single nucleotide polymorphisms (miR-SNPs) are a class of genetic variants with gene-regulatory potential. METHODS: We used a genome-scale approach and independent patient populations in a two-stage approach to test 40,286 common miR-SNPs for association with HNSCC survival in the discovery population (n = 847), and selected the strongest associations for replication in validation phase cases (n = 1,236). Furthermore, we leveraged miRNA interaction databases and miRNA expression data from The Cancer Genome Atlas, to provide functional insight for the identified and replicated associations. RESULTS: Joint population analyses identified novel miR-SNPs associated with overall survival in oral and laryngeal cancers. rs1816158, located within long noncoding RNA MIR100HG, was associated with overall survival in oral cavity cancer (HR, 1.56; 95% confidence interval (CI), 1.21-2.00). In addition, expression of MIR100HG-embedded miRNA, miR-100, was significantly associated with overall survival in an independent cohort of HNSCC cases (HR, 1.25; 95% CI, 1.06-1.49). A SNP in the 3'UTR of SH3BP4 (rs56161233) that overlaps predicted miRNA-binding sites and is predicted to disrupt several miRNA-mRNA interactions was associated with overall survival of laryngeal cancer (HR, 2.57; 95% CI, 1.71-3.86). CONCLUSIONS: This work reveals novel miR-SNPs associated with HNSCC survival, and utilizes miRNA-mRNA interaction and expression data to provide functional support for these associations. IMPACT: These findings extend our understanding of how genetic variation contributes to HNSCC survival, and may contribute to future prognostic models for improved risk stratification.

SIG-DB: Leveraging homomorphic encryption to securely interrogate privately held genomic databases.

Genomic data are becoming increasingly valuable as we develop methods to utilize the information at scale and gain a greater understanding of how genetic information relates to biological function. Advances in synthetic biology and the decreased cost of sequencing are increasing the amount of privately held genomic data. As the quantity and value of private genomic data grows, so does the incentive to acquire and protect such data, which creates a need to store and process these data securely. We present an algorithm for the Secure Interrogation of Genomic DataBases (SIG-DB). The SIG-DB algorithm enables databases of genomic sequences to be searched with an encrypted query sequence without revealing the query sequence to the Database Owner or any of the database sequences to the Querier. SIG-DB is the first application of its kind to take advantage of locality-sensitive hashing and homomorphic encryption to allow generalized sequence-to-sequence comparisons of genomic data.

Prevalence rates of arthritis among US older adults with varying degrees of depression: Findings from the 2011 to 2014 National Health and Nutrition Examination Survey.

OBJECTIVE: Arthritis and depressive symptoms often interact and negatively influence one another to worsen mental and physical health outcomes. Better characterization of arthritis rates among older adults with different levels of depressive symptoms is an important step toward informing mental health professionals of the need to detect and respond to arthritis and related mental health complications. The primary objective is to determine arthritis rates among US older adults with varying degrees of depression. METHODS: Using National Health and Nutrition Examination Survey 2011 to 2014 data (N = 4792), we first identified participants aged ≥50 years. Measures screened for depressive symptoms and self-reported doctor-diagnosed arthritis. Weighted logistic regression models were conducted. RESULTS: Prevalence of arthritis was 55.0%, 62.9%, and 67.8% in participants with minor, moderate, and severe depression, respectively. In both unadjusted and adjusted regression models, a significant association between moderate depression and arthritis persisted. There were also significant associations between minor and severe depression with arthritis. CONCLUSIONS: Arthritis is commonly reported in participants with varying degrees of depression. This study highlights the importance of screening for and treating arthritis-related pain in older adults with depressive symptoms and the need for future geriatric psychiatry research on developing integrated biopsychosocial interventions for these common conditions.

Military Service and Decision Quality in the Management of Knee Osteoarthritis.

Background: Decision quality measures the degree to which care decisions are knowledge-based and value-aligned. Because military service emphasizes hierarchy, command, and mandates some healthcare decisions, military service may attenuate patient autonomy in healthcare decisions and lower decision quality. VA is the nation's largest provider of orthopedic care. We compared decision quality in a sample of VA and non-VA patients seeking care for knee osteoarthritis. Methods: Our study sample consisted of patients newly referred to our orthopedic clinic for the management of knee osteoarthritis. None of the study patients were exposed to a knee osteoarthritis decision aid. Consenting patients were administered the Hip/Knee Decision Quality Instrument (HK-DQI). In addition, they were surveyed about decision-making preferences and demographics. We compared results to a non-VA cohort from our academic institution's arthroplasty database. Results: The HK-DQI Knowledge Score was lower in the VA cohort (45%, SD = 22, n = 25) compared with the non-VA cohort (53%, SD = 21, n = 177) (p = 0.04). The Concordance Score was lower in the VA cohort (36%, SD = 49%) compared with the control cohort (70%, SD 46%) (p = 0.003). Non-VA patients were more likely to make a high-quality decision (p = 0.05). Non-VA patients were more likely to favor a shared decision-making process (p = 0.002). Conclusions: Decision quality is lower in Veterans with knee osteoarthritis compared with civilians, placing them at risk for lower treatment satisfaction and possibly unwarranted surgical utilization. Our future work will examine if this difference is from conditioned military service behaviors or confounding demographic factors, and if conventional shared decision-making techniques will correct this deficiency.

Mortality Risk Along the Frailty Spectrum: Data from the National Health and Nutrition Examination Survey 1999 to 2004.

OBJECTIVES: To determine the relationship between frailty and overall and cardiovascular mortality. DESIGN: Longitudinal mortality analysis. SETTING: National Health and Nutrition Examination Survey (NHANES) 1999-2004. PARTICIPANTS: Community-dwelling older adults aged 60 and older (N = 4,984; mean age 71.1 ± 0.19, 56% female). MEASUREMENTS: We used data from 1999-2004 cross-sectional NHANES and mortality data from the National Death Index, updated through December 2011. An adapted version of Fried's frailty criteria was used (low body mass index, slow walking speed, weakness, exhaustion, low physical activity). Frailty was defined as persons meeting 3 or more criteria, prefrailty as meeting 1 or 2 criteria, and robust (reference) as not meeting any criteria. The primary outcome was to evaluate the association between frailty and overall and cardiovascular mortality. Cox proportional hazard models were used to evaluate the association between risk of death and frailty category adjusted for age, sex, race, smoking, education, coronary artery disease, heart failure, nonskin cancer, diabetes, and arthritis. RESULTS: Half (50.4%) of participants were classified as robust, 40.3% as prefrail, and 9.2% as frail. Fully adjusted models demonstrated that prefrail (hazard ratio (HR) = 1.64, 95% confidence interval (CI) = 1.45-1.85) and frail (HR = 2.79, 95% CI = 2.35-3.30) participants had a greater risk of death and of cardiovascular death (prefrail: HR = 1.84, 95% CI = 1.45-2.34; frail: HR = 3.39, 95% CI = 2.45-4.70). CONCLUSION: Frailty and prefrailty are associated with increased risk of death. Demonstrating the association between prefrail status and mortality is the first step to identifying potential targets of intervention in future studies.

Cell-type deconvolution from DNA methylation: a review of recent applications.

Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).