Advancing youth transportation safety in North Carolina through addressing alcohol-related motor vehicle collisions.

The aim of this work is to analyze trends in youth transportation fatalities and injuries in North Carolina (NC), assess the implementation of ignition interlock devices (IIDs) in the United States and abroad, discuss policy implications for IIDs, and highlight health equity considerations related to motor vehicle collisions (MVCs). MVCs cause the highest number of unintentional injury-related deaths for children and teenagers in NC, and policymakers should pay special attention to MVCs related to alcohol consumption. IIDs are effective in reducing collision rates and recidivism for driving under the influence of alcohol (DUI). Ignition interlock device requirements have been increasingly implemented globally over the past three decades. However, the adoption of stricter IID policies after first-time DUI offenses in NC and across the U.S. is a prudent public health measure to enhance transportation safety for both adults and children. Evidence-based interventions such as IIDs must also strive to address inequities in transportation safety, and the framing of proposed policies should reflect the tenets of cultural humility.

Long acting delivery and therapies for neovascular age-related macular degeneration.

INTRODUCTION: Neovascular age-related macular degeneration (nAMD) represents a leading cause of severe visual impairment in individuals over 50 years of age in developed nations. Intravitreal anti-vascular endothelial growth factor (VEGF) injections have become the standard of care for treating nAMD; however, monthly or bimonthly dosing represents significant time and cost burden due to the disease's chronic nature and limited medication half-life. AREAS COVERED: This review summarizes innovative therapeutics and delivery methods for nAMD. Emerging methods for extended drug delivery include high molar concentration anti-VEGF drugs, intravitreal sustained release devices, reservoirs for intravitreal delivery, and gene therapy biofactories. In addition to VEGF-A, therapies targeting inhibition of VEGF-C and D, the angiopoetin-2 (Ang-2)/Tie-2 pathway, tyrosine kinases, and integrins are reviewed. EXPERT OPINION: The evolving therapeutic landscape of nAMD is rapidly expanding our toolkit for effective and durable treatment. Recent FDA approvals of faricimab (Vabysmo) and high dose aflibercept (Eylea HD) for nAMD with potential extension of injection intervals up to four months have been promising developments for patients and providers alike. Further research and innovation, including novel delivery techniques and pharmacologic targets, is necessary to validate the efficacy of developing therapeutics and characterize real-world outcomes. demonstrating promise in expanding treatment durability.

Alleviating tiling effect by random walk sliding window in high-resolution histological whole slide image synthesis.

Multiplex immunofluorescence (MxIF) is an advanced molecular imaging technique that can simultaneously provide biologists with multiple (i.e., more than 20) molecular markers on a single histological tissue section. Unfortunately, due to imaging restrictions, the more routinely used hematoxylin and eosin (H&E) stain is typically unavailable with MxIF on the same tissue section. As biological H&E staining is not feasible, previous efforts have been made to obtain H&E whole slide image (WSI) from MxIF via deep learning empowered virtual staining. However, the tiling effect is a long-lasting problem in high-resolution WSI-wise synthesis. The MxIF to H&E synthesis is no exception. Limited by computational resources, the cross-stain image synthesis is typically performed at the patch-level. Thus, discontinuous intensities might be visually identified along with the patch boundaries assembling all individual patches back to a WSI. In this work, we propose a deep learning based unpaired high-resolution image synthesis method to obtain virtual H&E WSIs from MxIF WSIs (each with 27 markers/stains) with reduced tiling effects. Briefly, we first extend the CycleGAN framework by adding simultaneous nuclei and mucin segmentation supervision as spatial constraints. Then, we introduce a random walk sliding window shifting strategy during the optimized inference stage, to alleviate the tiling effects. The validation results show that our spatially constrained synthesis method achieves a 56% performance gain for the downstream cell segmentation task. The proposed inference method reduces the tiling effects by using 50% fewer computation resources without compromising performance. The proposed random sliding window inference method is a plug-and-play module, which can be generalized for other high-resolution WSI image synthesis applications. The source code with our proposed model are available at https://github.com/MASILab/RandomWalkSlidingWindow.git.

Gene Therapy for Non-Hereditary Retinal Disease: Age-Related Macular Degeneration, Diabetic Retinopathy, and Beyond.

Gene therapy holds promise as a transformative approach in the treatment landscape of age-related macular degeneration (AMD), diabetic retinopathy (DR), and diabetic macular edema (DME), aiming to address the challenges of frequent intravitreal anti-vascular endothelial growth factor (VEGF) injections. This manuscript reviews ongoing gene therapy clinical trials for these disorders, including ABBV-RGX-314, ixoberogene soroparvovec (ixo-vec), and 4D-150. ABBV-RGX-314 utilizes an adeno-associated virus (AAV) vector to deliver a transgene encoding a ranibizumab-like anti-VEGF antibody fragment, demonstrating promising results in Phase 1/2a and ongoing Phase 2b/3 trials. Ixo-vec employs an AAV2.7m8 capsid for intravitreal delivery of a transgene expressing aflibercept, showing encouraging outcomes in Phase 1 and ongoing Phase 2 trials. 4D-150 utilizes an evolved vector to express both aflibercept and a VEGF-C inhibitory RNAi, exhibiting positive interim results in Phase 1/2 studies. Other therapies reviewed include EXG102-031, FT-003, KH631, OLX10212, JNJ-1887, 4D-175, and OCU410. These therapies offer potential advantages of reduced treatment frequency and enhanced safety profiles, representing a paradigm shift in management towards durable and efficacious cellular-based biofactories. These advancements in gene therapy hold promise for improving outcomes in AMD and addressing the complex challenges of DME and DR, providing new avenues for the treatment of diabetic eye diseases.

B-cell immune deficiency in twin sisters expands the phenotype of MOPDI.

Microcephalic osteodysplastic primordial dwarfism type I (MOPDI) is a very rare and severe autosomal recessive disorder characterized by marked intrauterine growth retardation, skeletal dysplasia, microcephaly and brain malformations. MOPDI is caused by biallelic mutations in RNU4ATAC, a non-coding gene involved in U12-type splicing of 1% of the introns in the genome, which are recognized by their specific splicing consensus sequences. Here, we describe a unique observation of immunodeficiency in twin sisters with mild MOPDI, who harbor a novel n.108_126del mutation, encompassing part of the U4atac snRNA 3' stem-loop and Sm protein binding site, and the previously reported n.111G>A mutation. Interestingly, both twin sisters show mild B-cell anomalies, including low naive B-cell counts and increased memory B-cell and plasmablasts counts, suggesting partial and transitory blockage of B-cell maturation and/or excessive activation of naive B-cells. Hence, the localization of a mutation in stem II of U4atac snRNA, as observed in another RNU4ATAC-opathy with immunodeficiency, that is, Roifman syndrome (RFMN), is not required for the occurrence of an immune deficiency. Finally, we emphasize the importance of considering immunodeficiency in MOPDI management to reduce the risk of serious infectious episodes.

Outpatient and Ambulatory Extended Recovery Robotic Hepatectomy: Multinational Study of 307 Cases.

BACKGROUND: For open minor hepatectomy, morbidity and recovery are dominated by the incision. The robotic approach may transform this "incision dominant procedure" into a safe outpatient procedure. STUDY DESIGN: We audited outpatient (less than 2 midnights) robotic hepatectomy at 6 hepatobiliary centers in 2 nations to test the hypothesis that the robotic approach can be a safe and effective short-stay procedure. Establishing early recovery after surgery programs were active at all sites, and home digital monitoring was available at 1 of the institutions. RESULTS: A total of 307 outpatient (26 same-day and 281 next-day discharge) robotic hepatectomies were identified (2013 to 2023). Most were minor hepatectomies (194 single segments, 90 bi-segmentectomies, 14 three segments, and 8 four segments). Thirty-nine (13%) were for benign histology, whereas 268 were for cancer (33 hepatocellular carcinoma, 27 biliary, and 208 metastatic disease). Patient characteristics were a median age of 60 years (18 to 93 years), 55% male, and a median BMI of 26 kg/m 2 (14 to 63 kg/m 2 ). Thirty (10%) patients had cirrhosis. One hundred eighty-seven (61%) had previous abdominal operation. Median operative time was 163 minutes (30 to 433 minutes), with a median blood loss of 50 mL (10 to 900 mL). There were no deaths and 6 complications (2%): 2 wound infections, 1 failure to thrive, and 3 perihepatic abscesses. Readmission was required in 5 (1.6%) patients. Of the 268 malignancy cases, 25 (9%) were R1 resections. Of the 128 with superior segment resections (segments 7, 8, 4A, 2, and 1), there were 12 positive margins (9%) and 2 readmissions for abscess. CONCLUSIONS: Outpatient robotic hepatectomy in well-selected cases is safe (0 mortality, 2% complication, and 1.6% readmission), including resection in the superior or posterior portions of the liver that is challenging with nonarticulating laparoscopic instruments.

Bortezomib Inhibits Open Configurations of the 20S Proteasome.

Bortezomib, a small dipeptide-like molecule, is a proteasome inhibitor used widely in the treatment of myeloma and lymphoma. This molecule reacts with threonine side chains near the center of the 20S proteasome and disrupts proteostasis by blocking enzymatic sites that are responsible for protein degradation. In this work, we use novel mass-spectrometry-based techniques to examine the influence of bortezomib on the structures and stabilities of the 20S core particle. These studies indicate that bortezomib binding dramatically favors compact 20S structures (in which the axial gate is closed) over larger structures (in which the axial gate is open)─suppressing gate opening by factors of at least ∼400 to 1300 over the temperature range that is studied. Thus, bortezomib may also restrict degradation in the 20S proteasome by preventing substrates from entering the catalytic pore. That bortezomib influences structures at the entrance region of the pore at such a long distance (∼65 to 75 Å) from its binding sites raises a number of interesting biophysical issues.

Grazing exclusion-induced changes in soil fungal communities in a highly desertified Brazilian dryland.

Soil desertification poses a critical ecological challenge in arid and semiarid climates worldwide, leading to decreased soil productivity due to the disruption of essential microbial community processes. Fungi, as one of the most important soil microbial communities, play a crucial role in enhancing nutrient and water uptake by plants through mycorrhizal associations. However, the impact of overgrazing-induced desertification on fungal community structure, particularly in the Caatinga biome of semiarid regions, remains unclear. In this study, we assessed the changes in both the total fungal community and the arbuscular mycorrhizal fungal community (AMF) across 1. Natural vegetation (native), 2. Grazing exclusion (20 years) (restored), and 3. affected by overgrazing-induced degradation (degraded) scenarios. Our assessment, conducted during both the dry and rainy seasons in Irauçuba, Ceará, utilized Internal Transcribed Spacer (ITS) gene sequencing via Illumina® platform. Our findings highlighted the significant roles of the AMF families Glomeraceae (∼71% of the total sequences) and Acaulosporaceae (∼14% of the total sequences) as potential key taxa in mitigating climate change within dryland areas. Moreover, we identified the orders Pleosporales (∼35% of the total sequences) and Capnodiales (∼21% of the total sequences) as the most abundant soil fungal communities in the Caatinga biome. The structure of the total fungal community differed when comparing native and restored areas to degraded areas. Total fungal communities from native and restored areas clustered together, suggesting that grazing exclusion has the potential to improve soil properties and recover fungal community structure amid global climate change challenges.

m6A Reader YTHDC1 Impairs Respiratory Syncytial Virus Infection by Downregulating Membrane CX3CR1 Expression.

Respiratory syncytial virus (RSV) is the most prevalent cause of acute lower respiratory infection in young children. Currently, the first RSV vaccines are approved by the FDA. Recently, N6-methyladenosine (m6A) RNA methylation has been implicated in the regulation of the viral life cycle and replication of many viruses, including RSV. m6A methylation of RSV RNA has been demonstrated to promote replication and prevent anti-viral immune responses by the host. Whether m6A is also involved in viral entry and whether m6A can also affect RSV infection via different mechanisms than methylation of viral RNA is poorly understood. Here, we identify m6A reader YTH domain-containing protein 1 (YTHDC1) as a novel negative regulator of RSV infection. We demonstrate that YTHDC1 abrogates RSV infection by reducing the expression of RSV entry receptor CX3C motif chemokine receptor 1 (CX3CR1) on the cell surface of lung epithelial cells. Altogether, these data reveal a novel role for m6A methylation and YTHDC1 in the viral entry of RSV. These findings may contribute to the development of novel treatment options to control RSV infection.

Diverse material properties and morphology of moth proboscises relates to the feeding habits of some macromoth and other lepidopteran lineages.

Insects have evolved unique structures that host a diversity of material and mechanical properties, and the mouthparts (proboscis) of butterflies and moths (Lepidoptera) are no exception. Here, we examined proboscis morphology and material properties from several previously unstudied moth lineages to determine if they relate to flower visiting and non-flower visiting feeding habits. Scanning electron microscopy and three-dimensional imaging were used to study proboscis morphology and assess surface roughness patterns on the galeal surface, respectively. Confocal laser scanning microscopy was used to study patterns of cuticular autofluorescence, which was quantified with colour analysis software. We found that moth proboscises display similar autofluorescent signals and morphological patterns in relation to feeding habits to those previously described for flower and non-flower visiting butterflies. The distal region of proboscises of non-flower visitors is brush-like for augmented capillarity and exhibited blue autofluorescence, indicating the possible presence of resilin and increased flexibility. Flower visitors have smoother proboscises and show red autofluorescence, an indicator of high sclerotization, which is adaptive for floral tube entry. We propose the lepidopteran proboscis as a model structure for understanding how insects have evolved a suite of morphological and material adaptations to overcome the challenges of acquiring fluids from diverse sources.

N6-Methyladenosine Promotes TNF mRNA Degradation In CD4+ T Lymphocytes.

N6-methyladenosine (m6A) is a RNA modification that can regulate post-transcriptional processes including RNA stability, translation, splicing and nuclear export. In CD4+ lymphocytes, m6A modifications have been demonstrated to play a role in early differentiation processes. The role of m6A in CD4+ T cell activation and effector function remains incompletely understood. To assess the role of m6A in CD4+ T lymphocyte activation and function, we assessed the transcriptome-wide m6A landscape of human primary CD4+ T cells by methylated RNA immunoprecipitation (meRIP) sequencing. Stimulation of the T cells impacted the m6A pattern of hundreds of transcripts including tumor necrosis factor (TNF). m6A methylation was increased on TNF mRNA after activation, predominantly in the 3' untranslated region (UTR) of the transcript. Manipulation of m6A levels in primary human T cells, the directly affected the expression of TNF. Furthermore, we identified that the m6A reader protein YT521-B homology domain family-2 (YTHDF2) binds m6A-methylated TNF mRNA, and promotes its degradation. Taken together, this study demonstrates that TNF expression in CD4+ T lymphocytes is regulated via m6A and YTHDF2, thereby providing novel insight into the regulation of T cell effector functions.

T helper cells are immune cells of the adaptive immune system. These cells are activated by antigen presenting cells that have engulfed invading pathogens. When the T helper cell is activated, it will produce and excrete signaling molecules (cytokines) that activate other immune cells in order to eradicate these pathogens. Cytokines are formed after translation of RNA molecules that encode for these cytokines. In this study it was found that a modification (m6A) on RNA molecules is involved in the regulation of the life cycle of these RNA molecules. It was found that the degradation of RNA encoding for cytokine TNF was mediated through m6A and its 'reader' protein YTHDF2 in activated T helper cells. As TNF promotes inflammation, reduction of TNF production through this mechanism dampens the immune response and therefore prevents chronic inflammation.

Does psychological distress predict risk of orthopaedic surgery and postoperative opioid prescribing in patients with hip pain? A retrospective study.

BACKGROUND: Clinicians and public health professionals have allocated resources to curb opioid over-prescription and address psychological needs among patients with musculoskeletal pain. However, associations between psychological distress, risk of surgery, and opioid prescribing among those with hip pathologies remain unclear. METHODS: Using a retrospective cohort study design, we identified patients that were evaluated for hip pain from January 13, 2020 to October 27, 2021. Patients' surgical histories and postoperative opioid prescriptions were extracted via chart review. Risk of hip surgery within one year of evaluation was analyzed using multivariable logistic regression. Multivariable linear regression was employed to predict average morphine milligram equivalents (MME) per day of opioid prescriptions within the first 30 days after surgery. Candidate predictors included age, gender, race, ethnicity, employment, insurance type, hip function and quality of life on the International Hip Outcome Tool (iHOT-12), and psychological distress phenotype using the OSPRO Yellow Flag (OSPRO-YF) Assessment Tool. RESULTS: Of the 672 patients, n = 350 (52.1%) underwent orthopaedic surgery for hip pain. In multivariable analysis, younger patients, those with TRICARE/other government insurance, and those with a high psychological distress phenotype had higher odds of surgery. After adding iHOT-12 scores, younger patients and lower iHOT-12 scores were associated with higher odds of surgery, while Black/African American patients had lower odds of surgery. In multivariable analysis of average MME, patients with periacetabular osteotomy (PAO) received opioid prescriptions with significantly higher average MME than those with other procedures, and surgery type was the only significant predictor. Post-hoc analysis excluding PAO found higher average MME for patients undergoing hip arthroscopy (compared to arthroplasty or other non-PAO procedures) and significantly lower average MME for patients with public insurance (Medicare/Medicaid) compared to those with private insurance. Among those only undergoing arthroscopy, older age and having public insurance were associated with opioid prescriptions with lower average MME. Neither iHOT-12 scores nor OSPRO-YF phenotype assignment were significant predictors of postoperative mean MME. CONCLUSIONS: Psychological distress characteristics are modifiable targets for rehabilitation programs, but their use as prognostic factors for risk of orthopaedic surgery and opioid prescribing in patients with hip pain appears limited when considered alongside other commonly collected clinical information such as age, insurance, type of surgery pursued, and iHOT-12 scores.

Cross-scale multi-instance learning for pathological image diagnosis.

Analyzing high resolution whole slide images (WSIs) with regard to information across multiple scales poses a significant challenge in digital pathology. Multi-instance learning (MIL) is a common solution for working with high resolution images by classifying bags of objects (i.e. sets of smaller image patches). However, such processing is typically performed at a single scale (e.g., 20× magnification) of WSIs, disregarding the vital inter-scale information that is key to diagnoses by human pathologists. In this study, we propose a novel cross-scale MIL algorithm to explicitly aggregate inter-scale relationships into a single MIL network for pathological image diagnosis. The contribution of this paper is three-fold: (1) A novel cross-scale MIL (CS-MIL) algorithm that integrates the multi-scale information and the inter-scale relationships is proposed; (2) A toy dataset with scale-specific morphological features is created and released to examine and visualize differential cross-scale attention; (3) Superior performance on both in-house and public datasets is demonstrated by our simple cross-scale MIL strategy. The official implementation is publicly available at https://github.com/hrlblab/CS-MIL.

Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

BACKGROUND: The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to substantial shifts in measurements unrelated to underlying anatomical structures. PURPOSE: In this study, we investigate kernel harmonization in a multi-vendor low-dose CT lung cancer screening cohort and evaluate our approach's validity in quantitative CT-based assessments. METHODS: Using the National Lung Screening Trial, we identified CT scan pairs of the same sessions with one reconstructed from a soft tissue kernel and one from a hard kernel. In total, 1000 pairs of five different paired kernel types (200 each) were identified. We adopt the pix2pix architecture to train models for kernel conversion. Each model was trained on 100 pairs and evaluated on 100 withheld pairs. A total of 10 models were implemented. We evaluated the efficacy of kernel conversion based on image similarity metrics including root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM) as well as the capability of the models to reduce measurement shifts in quantitative emphysema and body composition measurements. Additionally, we study the reproducibility of standard radiomic features for all kernel pairs before and after harmonization. RESULTS: Our approach effectively converts CT images from one kernel to another in all paired kernel types, as indicated by the reduction in RMSE (p < 0.05) and an increase in the PSNR (p < 0.05) and SSIM (p < 0.05) for both directions of conversion for all pair types. In addition, there is an increase in the agreement for percent emphysema, skeletal muscle area, and subcutaneous adipose tissue (SAT) area for both directions of conversion. Furthermore, radiomic features were reproducible when compared with the ground truth features. CONCLUSIONS: Kernel conversion using deep learning reduces measurement variation in percent emphysema, muscle area, and SAT area.

Antimicrobial resistance in the United States: Origins and future directions.

Antimicrobial resistance (AMR) remains a critical public health problem that pervades hospitals and health systems worldwide. The ongoing AMR crisis is not only concerning for patient care but also healthcare delivery and quality. This article outlines key components of the origins of AMR in the United States and how it presents across the American healthcare system. Numerous factors contributed to the crisis, including agricultural antibiotic use, wasteful prescribing practices in health care, conflicting behaviours among patients and clinicians, patient demand and satisfaction, and payment and reimbursement models that incentivize inappropriate antibiotic use. To combat AMR, clinicians, healthcare professionals, and legislators must continue to promote and implement innovative solutions, including antibiotic stewardship programmes (ASPs), hand hygiene protocols, ample supply of personal protective equipment (PPE), standardized treatment guidelines for antibiotic prescribing, clinician and patient educational programmes, and health policy initiatives. With the rising prevalence of multi-drug resistant bacterial infections, AMR must become a greater priority to policymakers and healthcare stakeholders.

Genetic disruption of the bacterial raiA motif noncoding RNA causes defects in sporulation and aggregation.

Several structured noncoding RNAs in bacteria are essential contributors to fundamental cellular processes. Thus, discoveries of additional ncRNA classes provide opportunities to uncover and explore biochemical mechanisms relevant to other major and potentially ancient processes. A candidate structured ncRNA named the "raiA motif" has been found via bioinformatic analyses in over 2,500 bacterial species. The gene coding for the RNA typically resides between the raiA and comFC genes of many species of Bacillota and Actinomycetota. Structural probing of the raiA motif RNA from the Gram-positive anaerobe Clostridium acetobutylicum confirms key features of its sophisticated secondary structure model. Expression analysis of raiA motif RNA reveals that the RNA is constitutively produced but reaches peak abundance during the transition from exponential growth to stationary phase. The raiA motif RNA becomes the fourth most abundant RNA in C. acetobutylicum, excluding ribosomal RNAs and transfer RNAs. Genetic disruption of the raiA motif RNA causes cells to exhibit substantially decreased spore formation and diminished ability to aggregate. Restoration of normal cellular function in this knock-out strain is achieved by expression of a raiA motif gene from a plasmid. These results demonstrate that raiA motif RNAs normally participate in major cell differentiation processes by operating as a trans-acting factor.

Identification of functional white matter networks in BOLD fMRI.

White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is growing evidence that these signals are indicative of brain activity. Understanding how these white matter signals capture function can provide insight into brain physiology. Moreover, functional signals could potentially be used as early markers for neurological changes, such as in Alzheimer's Disease. To investigate white matter brain networks, we leveraged the OASIS-3 dataset to extract white matter signals from resting state BOLD-FMRI data on 711 subjects. The imaging was longitudinal with a total of 2,026 images. Hierarchical clustering was performed to investigate clusters of voxel-level correlations on the timeseries data. The stability of clusters was measured with the average Dice coefficients on two different cross fold validations. The first validated the stability between scans, and the second validated the stability between subject populations. Functional clusters at hierarchical levels 4, 9, 13, 18, and 24 had local maximum stability, suggesting better clustered white matter. In comparison with JHU-DTI-SS Type-I Atlas defined regions, clusters at lower hierarchical levels identified well defined anatomical lobes. At higher hierarchical levels, functional clusters mapped motor and memory functional regions, identifying 50.00%, 20.00%, 27.27%, and 35.14% of the frontal, occipital, parietal, and temporal lobe regions respectively.

Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites.

Connectivity matrices derived from diffusion MRI (dMRI) provide an interpretable and generalizable way of understanding the human brain connectome. However, dMRI suffers from inter-site and between-scanner variation, which impedes analysis across datasets to improve robustness and reproducibility of results. To evaluate different harmonization approaches on connectivity matrices, we compared graph measures derived from these matrices before and after applying three harmonization techniques: mean shift, ComBat, and CycleGAN. The sample comprises 168 age-matched, sex-matched normal subjects from two studies: the Vanderbilt Memory and Aging Project (VMAP) and the Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD). First, we plotted the graph measures and used coefficient of variation (CoV) and the Mann-Whitney U test to evaluate different methods' effectiveness in removing site effects on the matrices and the derived graph measures. ComBat effectively eliminated site effects for global efficiency and modularity and outperformed the other two methods. However, all methods exhibited poor performance when harmonizing average betweenness centrality. Second, we tested whether our harmonization methods preserved correlations between age and graph measures. All methods except for CycleGAN in one direction improved correlations between age and global efficiency and between age and modularity from insignificant to significant with p-values less than 0.05.

Total Hip and Total Knee Arthroplasty Outpatient Case Volume During the 2020 COVID-19 Pandemic in New York and California.

BACKGROUND: Inpatient total hip and total knee arthroplasty were substantially impacted by the SARS-CoV-2 (COVID-19) pandemic. We sought to characterize the transition of total joint arthroplasty (TJA) to the outpatient setting in 2 large state health systems during this pandemic. METHODS: Adult patients who underwent primary elective TJA between January 1, 2016 and December 31, 2020 were retrospectively reviewed using the New York Statewide Planning and Research Cooperative System and California Department of Health Care Access and Information datasets. Yearly inpatient and outpatient case volumes and patient demographics, including age, sex, race, and payer coverage, were recorded. Continuous and categorical variables were compared using descriptive statistics. Significance was set at P < .05. RESULTS: In New York during 2020, TJA volume decreased 16% because 22,742 fewer inpatient TJAs were performed. Much of this lost volume (46.6%) was offset by a 166% increase in outpatient TJA. In California during 2020, TJA volume decreased 20% because 34,114 fewer inpatient TJAs were performed. Much of this lost volume (37%) was offset by a 47% increase in outpatient TJA. CONCLUSIONS: This present study demonstrates a marked increase in the proportion of TJA being performed on an outpatient basis in both California and New York. In both states, despite a decrease in overall TJA volume in 2020, outpatient TJA volume increased markedly. LEVEL OF EVIDENCE: Therapeutic Level IV, Retrospective Cohort Study.

Deconvoluting Nonlinear Catalyst-Substrate Effects in the Intramolecular Dirhodium-Catalyzed C-H Insertion of Donor/Donor Carbenes Using Data Science Tools.

Interactions between catalysts and substrates can be highly complex and dynamic, often complicating the development of models to either predict or understand such processes. A dirhodium(II)-catalyzed C-H insertion of donor/donor carbenes into 2-alkoxybenzophenone substrates to form benzodihydrofurans was selected as a model system to explore nonlinear methods to achieve a mechanistic understanding. We found that the application of traditional methods of multivariate linear regression (MLR) correlating DFT-derived descriptors of catalysts and substrates leads to poorly performing models. This inspired the introduction of nonlinear descriptor relationships into modeling by applying the sure independence screening and sparsifying operator (SISSO) algorithm. Based on SISSO-generated descriptors, a high-performing MLR model was identified that predicts external validation points well. Mechanistic interpretation was aided by the deconstruction of feature relationships using chemical space maps, decision trees, and linear descriptors. Substrates were found to have a strong dependence on steric effects for determining their innate cyclization selectivity preferences. Catalyst reactive site features can then be matched to product features to tune or override the resultant diastereoselectivity within the substrate-dictated ranges. This case study presents a method for understanding complex interactions often encountered in catalysis by using nonlinear modeling methods and linear deconvolution by pattern recognition.