Citations

Abstract Solid tumors develop within a complex environment called the tumor microenvironment (TME), which is sculpted by the presence of other cells, such as cancer‐associated fibroblasts (CAFs) and immune cells like macrophages (Mφs). Despite the presence of immune cells, tumor cells orchestrate a tumor‐supportive environment through intricate interaction with the components of the TME. However, the specific mechanism by which this intercellular dialogue is regulated is not fully understood. To that end, the development of an organotypic 3D breast TME‐on‐a‐chip (TMEC) model, integrated with single‐cell RNA sequencing analysis, is reported to mechanistically evaluate the progression of triple‐negative breast cancer (TNBC) cells in the presence of patient‐derived CAFs and Mφs. Extensive functional assays, including invasion and morphometric characterization, reveal the synergistic influence of CAFs and Mφs on tumor cells. Furthermore, gene expression and pathway enrichment analyses identify the involvement of the KYNU gene, suggesting a potential immune evasion mechanism through the kynurenine pathway. Lastly, the pharmacological targeting of the identified pathway is investigated.

Abstract Purpose Developing large‐scale, standardized radiographic registries for anterior cruciate ligament (ACL) injuries with artificial intelligence (AI) tools can enhance personalized orthopaedics. We propose deploying Artificial Intelligence for Knee Imaging Registration and Analysis (AKIRA), a trio of deep learning (DL) algorithms, to automatically classify and annotate radiographs. We hypothesize that algorithms can efficiently organize radiographs based on laterality, projection, identify implants and classify osteoarthritis (OA) grade. Methods A collection of 20,836 knee radiographs from all time points of treatment (mean orthopaedic follow‐up 70.7 months; interquartile range [IQR]: 6.8–172 months) were aggregated from 1628 ACL‐injured patients (median age 26 years [IQR: 19–42], 57% male). Three DL algorithms (EfficientNet, YOLO [You Only Look Once] and Residual Network) were employed. Radiograph laterality and projection (anterior‐posterior [AP], lateral, sunrise, posterior‐anterior, hip–knee–ankle and Camp‐Coventry intercondylar [notch]) were labelled by a DL model. Manually provided labels of metal fixation implants were used to develop a DL object detection algorithm. The degree of OA, both as measured by specific Kellgren–Lawrence (KL) grades, as well as based on a binarized label of OA (defined as KL Grade ≥2), on standing AP radiographs were classified using a DL algorithm. Individual model performances were evaluated on a subset of images prior to the deployment of AKIRA to registry construction using all ACL radiographs. Results The classification algorithms showed excellent performance in classifying radiographic laterality (F1 score: 0.962–0.975) and projection (F1 score: 0.941–1.0). The object detection algorithm achieved high precision–recall (area under the precision‐recall curve: 0.695–0.992) for identifying various metal fixations. The KL classifier reached concordances of 0.39–0.40, improving to 0.81–0.82 for binary OA labels. Sequential deployment of AKIRA following internal validation processed and labelled all 20,836 images with the appropriate views, implants, and the presence of OA within 88 min. Conclusion AKIRA effectively automated the classification and object detection in a large radiograph cohort of ACL injuries, creating an AI‐enabled radiographic registry with comprehensive details on laterality, projection, implants and OA. Study Design Cross‐sectional study. Level of Evidence Level IV.

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disease and the most prevalent form of late‐life dementia. The ε2 allele of the APOE gene encoding apolipoprotein E (APOE2) is associated with lower susceptibility to AD among the three genotypes (ε2, ε3, ε4), while APOE4 is the strongest genetic risk factor for late‐onset AD. APOE plays a critical role in maintaining synaptic plasticity and neuronal function by controlling lipid homeostasis, with APOE2 having a superior function. Gene therapy that increases APOE2 levels in the brain has, therefore, emerged as a potential therapeutic strategy to treat AD.MethodWe conjugated PEGylated liposomes with transferrin and Penetratin, a cell‐penetrating peptide, sufficiently deliver chitosan‐APOE2 cDNA plasmid complex into amyloid model AppNL‐G‐F knockin mice at 12‐month‐old. Biochemical studies and brain transcriptome analysis were employed to investigate how brain‐targeting liposome‐based APOE2 gene delivery influences amyloid‐β (Aβ)‐related pathologies in AppNL‐G‐F knockin mice.ResultOne month after APOE2 gene therapy, there was a trend of reduced insoluble Aβ levels in the mouse cortices. Furthermore, in the AppNL‐G‐F knockin mice that received the APOE2 gene therapy, brain transcriptome analysis through RNA‐sequencing identified the upregulation of genes/pathways related to neuronal development. This was supported by increases of Dlg4 and Syp mRNAs coding synaptic proteins in the experimental group. On the other hand, we found that APOE2 gene delivery increased soluble Aβ levels, including oligomers, as well as exacerbated neurite dystrophy and decreased synaptophysin.ConclusionOur results suggest that brain‐targeting liposome‐based APOE2 gene therapy is potentially beneficial for synaptic formation at the transcriptional level. Forced APOE2 expressions, however, may exacerbate Aβ toxicity by increasing the dissociation of Aβ oligomers from aggregates in the presence of considerable amyloid burden.

Background: Anterior cruciate ligament (ACL) reconstruction (ACLR) can be successful in restoring knee stability. However, secondary ACL injury, either through graft failure or contralateral injury, is a known complication and can significantly impact the ability of a patient to return successfully to previous activities. Purpose: To develop and internally validate an interpretable machine learning model to quantify the risk of graft failure and contralateral ACL injury in a longitudinal cohort treated with ACLR. Study Design: Case-control study; Level of evidence, 3. Methods: An established geographic database of >600,000 patients was used to identify patients with a diagnosis of ACL rupture between 1990 and 2016 with a minimum 2-year follow-up. Medical records were reviewed for relevant patient information and 4 candidate machine learning algorithms were evaluated for prediction of graft failure and contralateral ACL injury in patients after ACLR as identified either on magnetic resonance imaging or via arthroscopy. Performance of the algorithms was assessed through discrimination, calibration, and decision curve analysis. Model interpretability was enhanced utilizing global variable importance plots and partial dependence curves. Results: A total of 1497 patients met inclusion criteria. Among them, 140 (9.4%) had graft failure and 128 (8.6%) had a contralateral ACL injury after index surgery at a median follow-up of 140.7 months (interquartile range, 77.2-219.2 months). The best performing models achieved an area under the receiver operating characteristics curve of 0.70 for prediction of graft failure and 0.67 for prediction of contralateral ACL injury, outperforming a logistic regression fitted on the identical feature set. Notable predictors for increased risk of graft failure included younger age at injury, body mass index (BMI) <30, return to sports <13 months, initial time to surgery >75 days, utilization of allograft, femoral/tibial fixation with suspension/expansion devices, concomitant collateral ligament injury, and active or former smoking history. Predictors of contralateral ACL injury included greater preoperative pain, younger age at initial injury, BMI <30, active smoking history, initial time to surgery >75 days, history of contralateral knee arthroscopies, and involvement in contact sports. Conclusion: Less than 18% of all patients who undergo ACLR should be expected to sustain either a graft failure or contralateral ACL injury. Machine learning models outperformed logistic regression and identified greater preoperative pain, younger age, BMI <30, earlier return to higher activity, and time to surgical intervention >75 days as common risk factors for both graft failure as well as contralateral ACL injury after ACLR. Surgeon-modifiable risk factors for graft failure included allograft and femoral/tibial fixation with a suspension/expansion combination.

Background: Arthroscopic diagnosis and treatment of femoroacetabular pathology has experienced significant growth in the last 30 years; nevertheless, reduced utilization of orthopaedic procedures has been observed among the underrepresented population. Purpose/Hypothesis: The purpose of this study was to examine racial differences in case incidence rates, outcomes, and complications in patients undergoing hip arthroscopy. It was hypothesized that racial and ethnic minority patients would undergo hip arthroscopy at a decreased rate compared with their White counterparts but that there would be no differences in clinical outcomes. Study Design: Cross-sectional study. Methods: The State Ambulatory Surgery and Services Database and the State Emergency Department Database of New York were queried for patients undergoing hip arthroscopy between 2011 and 2017. Patients were stratified into White and racial and ethnic minority races, and intergroup comparisons were performed for utilization over time, total charges billed per encounter, 90-day emergency department (ED) visits, and revision hip arthroscopy. Temporal trends in the utilization of hip arthroscopy were identified, and racial differences in secondary outcomes were analyzed with a semiparametric method known as targeted maximum likelihood estimation (TMLE) backed by a library of machine learning algorithms. Results: A total of 9745 patients underwent hip arthroscopy during the study period, with 1081 patients of minority race (11.1%). White patients underwent hip arthroscopy at 5.68 (95% CI, 4.98-6.48) times the incidence rate of racial and ethnic minority patients; these incidence rates grew annually at a ratio of 1.11 in White patients compared with 1.03 in racial and ethnic minority patients ( P < .001). Based on the TMLE, racial and ethnic minority patients were significantly more likely to incur higher costs ( P < .001) and visit the ED within 90 days ( P = .049) but had negligible differences in reoperation rates at a 2-year follow-up ( P = .53). Subgroup analysis identified that higher likelihood for 90-day ED admissions among racial and ethnic minority patients compared with White patients was associated with Medicare insurance ( P = .002), median income in the lowest quartile ( P = .012), and residence in low-income neighborhoods ( P = .006). Conclusion: Irrespective of insurance status, racial and ethnic minority patients undergo hip arthroscopy at a lower incidence and incur higher costs per surgical encounter.

Purpose To compile and analyze structural and clinical outcomes after meniscus root tear treatment as currently described in the literature. Methods A review was conducted to identify studies published since 2011 on efficacy of repair, meniscectomy, and nonoperative management in the treatment of meniscus root tears. Patient cohorts were grouped into treatment categories, with medial and lateral root tears analyzed separately; data were collected on patient demographics, structural outcomes including joint space width, degree of medial meniscal extrusion, progression to total knee arthroplasty, and patient‐reported outcome measures. Risk of bias was assessed using the MINORS (methodological index for non‐randomized studies) criteria. Heterogeneity was measured using the I‐statistic, and outcomes were summarized using forest plots without pooled means. Results The 56 included studies comprised a total of 3,191 patients. Mean age among the included studies ranged from 24.6 to 65.6 years, whereas mean follow‐up ranged from 12 to 125.9 months. Heterogeneity analysis identified significant differences between studies. Change in joint space width ranged from –2.4 to –0.6 mm (i.e., decreased space) after meniscectomy (n = 186) and –0.9 to –0.1 mm after root repair (n = 209); change in medial meniscal extrusion ranged from –0.6 to 6.5 mm after root repair (n = 521) and 0.2 to 4.2 mm after meniscectomy (n = 66); and event rate for total knee arthroplasty ranged from 0.00 to 0.22 after root repair (n = 205), 0.35 to 0.60 after meniscectomy (n = 53), and 0.27 to 0.35 after nonoperative treatment (n = 93). Root repair produced the greatest numerical increase in International Knee Documentation Committee and Lysholm scores of the 3 treatment arms. In addition, root repair improvements in Knee Injury and Osteoarthritis Outcome Score Pain (range: 22‐32), Sports and Recreational Activities (range: 23‐36), Quality of Life (range: 22‐42), and Symptoms subscales (range: 10‐19), in studies with low risk of bias. Conclusions The literature reporting on the treatment of meniscus root tears is heterogenous and largely limited to Level III and IV studies. Current evidence suggests root repair may be the most effective treatment strategy in lessening joint space narrowing of the knee and producing improvements in patient‐reported outcomes. Level of Evidence Level IV, systematic review of Level II‐IV studies.

Purpose To examine changes in obesity prevalence among US adults after the COVID-19 pandemic by level of stay-at-home order and sociodemographic characteristics. Design Quasi-experimental study using repeated cross-sectional data. Setting Behavioral Risk Factor Surveillance System (BRFSS). Sample Pooled data for US adults ages ≥26 years (n = 1,107,673) from BRFSS (2018-2021). Measures States/territories were classified into three levels of stay-at-home order: none, advisory/only for persons at risk, or mandatory for all. Individual-level sociodemographic characteristics were self-reported. Analysis The difference-in-differences method was conducted with weighted multiple logistic regression analysis to examine obesity (body mass index ≥30 kg/m 2 ) prevalence by stay-at-home order level and sociodemographic characteristics before/after the COVID-19 pandemic (January 2018-February 2020 vs March 2020-February 2022). Results After adjusting for a secular trend and multiple covariates, adults in states/territories with mandatory stay-at-home orders experienced a larger increase in obesity prevalence (adjusted odds ratio: 1.05; 95% confidence interval: 1.01, 1.11) than adults in states/territories with no stay-at-home order. Younger adults (vs ≥65 years) and individuals with <high school education (vs ≥4-year college) experienced larger increases in obesity prevalence. Conclusion Increases in obesity prevalence were perpetuated 2 years after implementation of stay-at-home orders, indicating that longer-term health implications are co-occurring during the pandemic recovery period. Future research should focus on successful methods for staying active and healthy during social distancing and beyond.

Background: An increased posterior tibial slope (PTS) corresponds with an increased risk of graft failure after anterior cruciate ligament (ACL) reconstruction (ACLR). Validated methods of manual PTS measurements are subject to potential interobserver variability and can be inefficient on large datasets. Purpose/Hypothesis: To develop a deep learning artificial intelligence technique for automated PTS measurement from standard lateral knee radiographs. It was hypothesized that this deep learning tool would be able to measure the PTS on a high volume of radiographs expeditiously and that these measurements would be similar to previously validated manual measurements. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: A deep learning U-Net model was developed on a cohort of 300 postoperative short-leg lateral radiographs from patients who underwent ACLR to segment the tibial shaft, tibial joint surface, and tibial tuberosity. The model was trained via a random split after an 80 to 20 train-validation scheme. Masks for training images were manually segmented, and the model was trained for 400 epochs. An image processing pipeline was then deployed to annotate and measure the PTS using the predicted segmentation masks. Finally, the performance of this combined pipeline was compared with human measurements performed by 2 study personnel using a previously validated manual technique for measuring the PTS on short-leg lateral radiographs on an independent test set consisting of both pre- and postoperative images. Results: The U-Net semantic segmentation model achieved a mean Dice similarity coefficient of 0.885 on the validation cohort. The mean difference between the human-made and computer-vision measurements was 1.92° (σ = 2.81° [ P = .24]). Extreme disagreements between the human and machine measurements, as defined by ≥5° differences, occurred <5% of the time. The model was incorporated into a web-based digital application front-end for demonstration purposes, which can measure a single uploaded image in Portable Network Graphics format in a mean time of 5 seconds. Conclusion: We developed an efficient and reliable deep learning computer vision algorithm to automate the PTS measurement on short-leg lateral knee radiographs. This tool, which demonstrated good agreement with human annotations, represents an effective clinical adjunct for measuring the PTS as part of the preoperative assessment of patients with ACL injuries.

Background In unfit patients (pts) with newly diagnosed (ND) AML, long-term survival remains short (mOS 14.7 months) despite improved responses (CR 37% and CR/CRi 66%) with azacitidine (AZA) and venetoclax (VEN) (VIALE-A, DiNardo NEJM 2020). In a pooled analysis of AZA-VEN in ND AML pts with poor risk cytogenetics the response rates were higher in TP53wt pts (CR/CRi 70%) compared with TP53mut pts (CR/CRi 41%) (Pollyea Clin Cancer Res 2022). The measurable residual disease (MRD)-negative rate was 41% in AZA-VEN treated pts in VIALE-A which was associated with improved survival (Pratz JCO 2022). Pivekimab sunirine (PVEK, IMGN632) is a first-in-class antibody-drug conjugate (ADC) comprising a high-affinity CD123 antibody, cleavable linker, and an indolinobenzodiazepine pseudodimer (IGN) payload. The novel IGN payload alkylates DNA and causes single strand breaks without crosslinking (Kovtun Blood Adv 2018). Methods This is an ongoing, open-label, multicenter, Phase 1b/2 study of PVEK in combination with AZA +VEN in adults with ND CD123-positive AML (any CD123+ expression by local flow cytometry or IHC). Pts received the recommended phase 2 dose of PVEK 0.045 mg/kg IV on D7 + AZA 75 mg/m 2 SC or IV daily on D1-7 + VEN up to 400 mg PO daily for 14 to 28 days (based on cohort assignment) in a 28-day cycle. Bone marrow assessment was performed at D14 (cohort 1) or D21 (cohort 2) of cycle 1 to determine VEN duration. The primary endpoints are composite CR rate (CCR [CR+CRh+CRp+CRi]), MRD rate (assessed centrally [Hematologics, Inc.] by flow cytometry; &lt;0.1% defined as negative) and duration of remission. Key secondary endpoints are safety, pharmacokinetics and immunogenicity. Responses were determined using ELN 2017 criteria (with the addition of CRh) and a 14-day post-marrow count recovery window. Results As of July 17, 2023, data is available for 50 ND pts (n=25 per cohort) treated with PVEK+AZA+VEN and are aggregately reported here. The median age was 74 years (range, 46-83), 42% were ≥ 75 years old, 26% had secondary AML, 64% were ELN 2017 adverse risk, and 38% had a TP53mut. The most common non-hematologic treatment-emergent adverse events (TEAE) (all grades [grade 3+]) seen in &gt; 20% of all pts were febrile neutropenia (44% [38%]), constipation (42% [2%]), peripheral edema (36% [4%]), diarrhea (36% [2%]), hypophosphatemia (32% [0%], nausea (28% [4%]), and hypokalemia (24% [2%]). No veno-occlusive disease (VOD) events were reported. In responders, the median time to achieve absolute neutrophil count ≥500/µL and platelet count ≥50,000/µL was 35.5 days (range, 20-55) and 22 days (range, 20-55), respectively. The median post-remission cycle delay (beyond cycle day 28) was 14 days. Two pts discontinued PVEK due to a TEAE (edema; marrow aplasia). The 60-day mortality was 4%. In the ITT population (N=50) the CR rate was 52% (26/50), and the CCR rate was 66% (33/50). In pts ≥ 75 years old, the CCR rate was 76% (16/21). In pts known to be TP53wt, both the CR and CCR rate was 88% (22/25). Additional response subsets in Table 1. Twenty-one pts received 9-14 days of VEN, 9 pts received 15-21 days of VEN and 20 pts received ≥ 22 days of VEN in cycle 1; of those who received ≤ 14 days of VEN the CR rate was 71% (15/21) and the CCR rate was 76% (16/21). Of the 26 pts who achieved CCR and had an MRD-evaluable sample, 73% (19/26) achieved MRD negativity (CCR MRD-, &lt;0.1% residual blasts); notably all had undetectable MRD levels (lower level of detection is 0.02%). MRD-negativity was achieved rapidly with a median of 1.7 months (range, 0.8-4.5). CCR MRD- rates were high across major molecular subsets, including FLT3 (ITD/TKD) at 100% (7/7), IDH1/2 at 89% (8/9), and NPM1 at 89% (8/9), as well as ELN risk groups (intermediate 80% [8/10]; adverse 64% [9/14]). Conclusion With a manageable safety profile in pts with ND AML, the PVEK+AZA+VEN triplet demonstrated anti-leukemia activity with robust CR rates and early MRD negative responses in a cohort enriched for adverse disease characteristics (64% ELN adverse risk; 38% TP53mut). Encouraging CCR MRD- rates were observed across cytogenetic/molecular subsets, and the majority of responding pts achieved early and deep remissions, which may translate to improved clinical outcomes. The regimen was well tolerated with no new safety signals, and the addition of PVEK to the AZA-VEN backbone did not appear to meaningfully prolong count recovery.

Purpose To compare 3 separate blood flow restriction (BFR) systems in their capacity to reduce repetitions to failure, impact perceptual responses, and cause adverse events during a low‐load free‐flow exercise. Methods The study included healthy subjects aged 18 years or older who presented to an ambulatory‐care sports medicine clinic. On day 1, participants’ demographic characteristics and anthropomorphic measurements were recorded. Each participant performed dumbbell biceps curl repetitions to failure using 20% of his or her 1‐repetition maximum weight with each arm. Participants were exposed to 3 different tourniquet systems for familiarization. On day 2, each participant’s arm was randomized to a cuff system, and the participant performed 2 sets of biceps curl repetitions to failure with the cuff inflated. Repetitions to failure, rating of perceived effort (RPE), rating of perceived discomfort, and pulse oxygenation levels were recorded after each set. On day 3, participants completed a survey of their perceived delayed‐onset muscle soreness. Results The final analysis was performed on 42 arms, with 14 limbs per system. The study population had a mean age of 28.7 ± 2.4 years and a mean body mass index of 24.9 ± 4.3. All 3 systems successfully reduced repetitions to failure compared with unrestricted low‐load exercise from baseline to BFR set 1 and from baseline to BFR set 2. There were no significant between‐group differences among BFR systems regarding the number of repetitions to failure performed at baseline versus BFR set 1 or BFR set 2. The Delfi Personalized Tourniquet System (PTS) cohort had the greatest reductions in repetitions to failure from BFR set 1 to BFR set 2 ( P = .002) and reported the highest RPE after set 2 ( P = .025). Conclusions The Delfi PTS, SmartCuffs Pro, and BStrong BFR systems were each safe and were able to significantly reduce repetitions to failure compared with a low‐load free‐flow condition when used in a BFR exercise protocol. The Delfi PTS system may produce a higher RPE with prolonged use in comparison to the other systems. Level of Evidence Level II, prospective cohort study.