Editorial Commentary: Cadaveric Biomechanical Orthopaedic Research Is Essential and Requires Quality and Validity Metrics.

Evidence-based medicine is the commanding philosophy of patient care in the field of orthopaedic surgery, and analysis of clinical research is facilitated by instruments and scales developed for assessing methodologic quality and validity of conclusions. In contrast, little consideration has been given to developing metrics to assess the quality and validity of orthopaedic ex vivo and laboratory research. This is easier said than done because these studies may be heterogeneous and complex in design, and methodologic details may not be intuitive to (non-engineer) readers. The recently described Biomechanics Objective Basic Science Quality Assessment Tool (BOBQAT) represents a reliable means to assess cadaveric biomechanical studies. The BOBQAT emphasizes essential study elements including a clinically relevant, answerable purpose; detailed description of the specimens studied; thorough description of surgical technique; and careful consideration of loading conditions including clinically relevant cyclic loading. The BOBQAT provides a logical recipe for the design of future studies, a mechanism of quality assessment for systematic reviews, and a framework for readers to assess biomechanical research consistent with the ethos of evidence-based medicine.

Editorial Commentary: Bone Marrow Stimulation for Osteochondral Lesions of the Tibial Plafond Shows Generally Favorable Results.

Osteochondral lesions of the ankle are common, but only a small proportion of these lesions are found on the tibial plafond (osteochondral lesions of the tibial plafond, ie, OLTP). By and large, surgical treatment strategies for OLTP have been derived from techniques employed for those of the talus (ie, osteochondral lesion of the talus). Despite the clinical success of surgical treatments for osteochondral lesion of the talus, namely bone marrow stimulation, it is quite possible that OLTP may not respond similarly, given the unique anatomy and biomechanical properties of the tibia. To this end, the literature surrounding OLTP is relatively sparse, and studies evaluating the clinical and radiographic outcomes of treatments specific to OLTP are necessary. Still, if it works for the talus, it seems sensible that it could work for the plafond. Pending future research, there is no need to reinvent the wheel.

Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS.

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suite of computational tools that implement NMF and provide methods for accurate and clear biological interpretation and analysis. A generalized discussion of NMF covering its benefits, limitations and open questions is followed by four procedures for the Bayesian NMF algorithm Coordinated Gene Activity across Pattern Subsets (CoGAPS). Each procedure will demonstrate NMF analysis to quantify cell state transitions in a public domain single-cell RNA-sequencing dataset. The first demonstrates PyCoGAPS, our new Python implementation that enhances runtime for large datasets, and the second allows its deployment in Docker. The third procedure steps through the same single-cell NMF analysis using our R CoGAPS interface. The fourth introduces a beginner-friendly CoGAPS platform using GenePattern Notebook, aimed at users with a working conceptual knowledge of data analysis but without a basic proficiency in the R or Python programming language. We also constructed a user-facing website to serve as a central repository for information and instructional materials about CoGAPS and its application programming interfaces. The expected timing to setup the packages and conduct a test run is around 15 min, and an additional 30 min to conduct analyses on a precomputed result. The expected runtime on the user's desired dataset can vary from hours to days depending on factors such as dataset size or input parameters.

Quantifying the Impact of the COVID-19 Pandemic on Passenger Vehicle Drivers' Willingness to Pay for Travel Time Savings and Reliability.

The COVID-19 pandemic has fundamentally disrupted travel behavior and consumer preferences. To slow the spread of the virus, public health officials and state and local governments issued stay-at-home orders and, among other actions, closed nonessential businesses and educational facilities. The resulting recessionary effects have been particularly acute for U.S. toll roads, with an observed year-over-year decline in traffic and revenue of 50% to 90% in April and May 2020. These disruptions have also led to changes in the types of trip that travelers make and their frequency, their choice of travel mode, and their willingness to pay tolls for travel time savings and travel time reliability. This paper describes the results of travel behavior research conducted on behalf of the Virginia Department of Transportation before and during the COVID-19 pandemic in the National Capital Region of Washington, D.C., Maryland, and Northern Virginia. The research included a stated preference survey to estimate travelers' willingness to pay for travel time savings and travel time reliability, to support forecasts of traffic and revenue for existing and proposed toll corridors. The survey collected data between December 2019 and June 2020. A comparison of the data collected before and during the pandemic shows widespread changes in travel behavior and a reduction in willingness to pay for travel time savings and travel time reliability across all traveler types, particularly for drivers making trips to or from work. These findings have significant implications for the return of travelers to toll corridors in the region and future forecasts of traffic and revenue.

Secondary pigmentary glaucoma following cosmetic laser treatment to alter iris colour.

Cosmetic alteration of iris colour with implants, along with its secondary complications, is already well described in the literature. However the use of cosmetic iris laser is relatively novel. We report on a rare case of bilateral secondary pigmentary glaucoma, in a young patient who underwent such a treatment to cause a change in iris pigmentation. Data on the safety of such procedures are lacking. Ophthalmic healthcare professionals should be aware of the potentially devastating consequences and encourage caution in patients seeking this novel treatment.

Phacoemulsification combined with micropulse cyclodiode laser in glaucoma patients: efficacy and safety.

OBJECTIVE: To evaluate the safety and efficacy of phacoemulsification combined with Micropulse transscleral cyclophotocoagulation (MP-TSCPC) in glaucoma patients. METHODS: This is a retrospective case-note review. The participants were adult patients with diagnoses of glaucoma and cataract who required a further reduction in IOP or a reduction in the number of glaucoma drops. All consecutive patients who underwent cataract surgery (CS) combined with MP-TSCPC laser between October 2018 and July 2019 were included in the study. The effect on visual acuity (VA), intraocular pressure (IOP) and number of anti-glaucoma drops were evaluated at 6 and 12 months in addition to any complications that occurred during any time point of the study. RESULTS: 42 eyes were included in the study. Mean IOP was reduced from 19.5 ± 5.4 mmHg by 22.5% to 15.1 ± 4.6 at 6 months post-operatively and by 19.5% to 15 ± 6.6 mm Hg at 12 months (p < 0.001 at both time points). The number of anti-glaucoma medications also reduced significantly from 2.8 ± 1.3 to 1.6 ± 1.2 at 6 months and to 2.2 ± 1.3 at 12 months (p < 0.001 at both time points). The success rate was 56% at 6 months and 54% at 12 months. 54.7% of our patients who completed 12 months follow up had an improvement or unchanged vision at the last visits. CONCLUSION: This is the first study evaluating the effect of cataract surgery combined with MP-TSCPC in glaucoma patients. We demonstrated that this led to a reduction in IOP and the number of anti-glaucoma medications at 6 and 12-month postoperatively. The majority of patients had either stable or better vision at 12 months follow-up.

A review of spatial Markov models for predicting pre-asymptotic and anomalous transport in porous and fractured media.

Heterogeneity across a broad range of scales in geologic porous media often manifests in observations of non-Fickian or anomalous transport. While traditional anomalous transport models can successfully make predictions in certain geological systems, increasing evidence suggests that assumptions relating to independent and identically distributed increments constrain where and when they can be reliably applied. A relatively novel model, the Spatial Markov model (SMM), relaxes the assumption of independence. The SMM belongs to the family of correlated continuous time random walks and has shown promise across a wide range of transport problems relevant to natural porous media. It has been successfully used to model conservative as well as more recently reactive transport in highly complex flows ranging from pore scales to much larger scales of interest in geology and subsurface hydrology. In this review paper we summarize its original development and provide a comprehensive review of its advances and applications as well as lay out a vision for its future development.

Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model.

In an effort to better represent aerosol transport in mesoscale and global-scale models, large eddy simulations (LES) from the National Center for Atmospheric Research (NCAR) Turbulence with Particles (NTLP) code are used to develop a Markov chain random walk model that predicts aerosol particle profiles in a cloud-free marine atmospheric boundary layer (MABL). The evolution of vertical concentration profiles are simulated for a range of aerosol particle sizes and in a neutral and an unstable boundary layer. For the neutral boundary layer we find, based on the LES statistics and a specific model time step, that there exist significant correlation for particle positions, meaning that particles near the bottom of the boundary are more likely to remain near the bottom of the boundary layer than being abruptly transported to the top, and vice versa. For the unstable boundary layer, a similar time interval exhibits a weaker tendency for an aerosol particle to remain close to its current location compared to the neutral case due to the strong nonlocal convective motions. In the limit of a large time interval, particles have been mixed throughout the MABL and virtually no temporal correlation exists. We leverage this information to parameterize a Markov chain random walk model that accurately predicts the evolution of vertical concentration profiles. The new methodology has significant potential to be applied at the subgrid level for coarser-scale weather and climate models, the utility of which is shown by comparison to airborne field data and global aerosol models.

CoGAPS 3: Bayesian non-negative matrix factorization for single-cell analysis with asynchronous updates and sparse data structures.

BACKGROUND: Bayesian factorization methods, including Coordinated Gene Activity in Pattern Sets (CoGAPS), are emerging as powerful analysis tools for single cell data. However, these methods have greater computational costs than their gradient-based counterparts. These costs are often prohibitive for analysis of large single-cell datasets. Many such methods can be run in parallel which enables this limitation to be overcome by running on more powerful hardware. However, the constraints imposed by the prior distributions in CoGAPS limit the applicability of parallelization methods to enhance computational efficiency for single-cell analysis. RESULTS: We developed a new software framework for parallel matrix factorization in Version 3 of the CoGAPS R/Bioconductor package to overcome the computational limitations of Bayesian matrix factorization for single cell data analysis. This parallelization framework provides asynchronous updates for sequential updating steps of the algorithm to enhance computational efficiency. These algorithmic advances were coupled with new software architecture and sparse data structures to reduce the memory overhead for single-cell data. CONCLUSIONS: Altogether our new software enhance the efficiency of the CoGAPS Bayesian matrix factorization algorithm so that it can analyze 1000 times more cells, enabling factorization of large single-cell data sets.

Editorial Commentary: Optimizing Surgical Management of Ankle Fractures: Is Arthroscopy the Answer?

The surgical management of ankle fractures can be an unforgiving endeavor. Subtle malreductions in fracture fragments lead to significant deviations in joint reactive forces and, consequently, accelerated arthritis. The diagnosis of associated ligamentous pathology, such as deltoid and syndesmotic injuries, is often difficult and ideal surgical management is debated. Ankle fractures that are seemingly optimally managed using traditional surgical techniques may remain persistently painful and function poorly-a scenario that begs the question, was there more to the injury than met the eye (or radiographs)? Here, unrecognized concomitant intra-articular injuries and subtle surgical malreductions have been implicated. In my practice, concurrent ankle arthroscopy at the time of definitive acute ankle fracture reduction and fixation results in improved accuracy of reduction, evaluation and management of concomitant syndesmotic and ligamentous injuries, assessment and treatment of occult intra-articular injuries, options for less-invasive fixation techniques through arthroscopic reduction, and a means to provide prognostic patient information. I typically reserve its use for fracture patterns that have been more closely associated with intra-articular injuries: high-energy mechanism injuries, Weber B and C fibula fractures, and those with a high likelihood of syndesmotic disruption based on preoperative imaging. Despite these intuitive advantages, concurrent ankle arthroscopy for acute fracture fixation is not routinely performed by most orthopedic surgeons, and a relative dearth of literature regarding its use and clinical impact remains.

Single-Cell Analysis of Human Retina Identifies Evolutionarily Conserved and Species-Specific Mechanisms Controlling Development.

The development of single-cell RNA sequencing (scRNA-seq) has allowed high-resolution analysis of cell-type diversity and transcriptional networks controlling cell-fate specification. To identify the transcriptional networks governing human retinal development, we performed scRNA-seq analysis on 16 time points from developing retina as well as four early stages of retinal organoid differentiation. We identified evolutionarily conserved patterns of gene expression during retinal progenitor maturation and specification of all seven major retinal cell types. Furthermore, we identified gene-expression differences between developing macula and periphery and between distinct populations of horizontal cells. We also identified species-specific patterns of gene expression during human and mouse retinal development. Finally, we identified an unexpected role for ATOH7 expression in regulation of photoreceptor specification during late retinogenesis. These results provide a roadmap to future studies of human retinal development and may help guide the design of cell-based therapies for treating retinal dystrophies.

Differential Variation Analysis Enables Detection of Tumor Heterogeneity Using Single-Cell RNA-Sequencing Data.

Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Single-cell RNA-sequencing (scRNA-seq) technologies have revealed the prevalence of intratumor and intertumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intratumor and intertumor molecular heterogeneity. In this study, we adapted our algorithm for pathway dysregulation, Expression Variation Analysis (EVA), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq. EVA has high sensitivity and specificity to detect pathways with true differential heterogeneity in simulated data. EVA was applied to several public domain scRNA-seq tumor datasets to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics such as immunogenicity, metastasis, and cancer subtypes. Immune pathway heterogeneity of hematopoietic cell populations in breast tumors corresponded to the amount of diversity present in the T-cell repertoire of each individual. Cells from head and neck squamous cell carcinoma (HNSCC) primary tumors had significantly more heterogeneity across pathways than cells from metastases, consistent with a model of clonal outgrowth. Moreover, there were dramatic differences in pathway dysregulation across HNSCC basal primary tumors. Within the basal primary tumors, there was increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. These results demonstrate the broad utility of EVA to quantify intertumor and intratumor heterogeneity from scRNA-seq data without reliance on low-dimensional visualization. SIGNIFICANCE: This study presents a robust statistical algorithm for evaluating gene expression heterogeneity within pathways or gene sets in single-cell RNA-seq data.

Lateral Transfer of the Flexor Digitorum Longus for Peroneal Tendinopathy.

BACKGROUND: Few studies have reported midterm outcomes after single-stage flexor digitorum longus (FDL) tendon transfer to the lateral foot for irreparable rupture of the peroneal tendons. METHODS: Over a 7-year period (2008-2015), 25 consecutive patients underwent transfer of the FDL to the fifth metatarsal for irreparable peroneal tendon tears. Of these, 15 patients were available for inclusion with a mean follow-up of 53.7 ± 23.3 months, mean age at surgery of 48.4 years, and mean body mass index (BMI) of 29.8 kg/m2. Patients completed the pain visual analog scale (VAS), Foot Function Index (FFI), Short Musculoskeletal Function Assessment (SMFA), and Foot and Ankle Ability Measure (FAAM) and participated in range of motion, peak force, and peak power testing. RESULTS: All 15 patients were satisfied with their surgery and reported a reduction in their pain level with a decreased VAS of 5.6 ± 2.5. The mean FFI was 12.8 ± 9.2, the SMFA Function Index was 12.4 ± 8, and the mean SMFA Bothersome Index was 11.5 ± 11. The mean FAAM was 86.4 ± 9.7. Patients had on average 58% less eversion and 28% less inversion compared with the nonoperative side. Isometric peak torque and isotonic peak velocity were 38.4% and 28.8% less compared with the contralateral side, respectively. The average power in the operative limb was diminished by 56% compared with the nonoperative limb. CONCLUSION: In this small case series with midterm follow-up, FDL transfer to the lateral foot for significant, irreparable peroneal tendinopathy was an effective and durable treatment option. LEVEL OF EVIDENCE: Level IV, retrospective case series.

Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species.

Analysis of gene expression in single cells allows for decomposition of cellular states as low-dimensional latent spaces. However, the interpretation and validation of these spaces remains a challenge. Here, we present scCoGAPS, which defines latent spaces from a source single-cell RNA-sequencing (scRNA-seq) dataset, and projectR, which evaluates these latent spaces in independent target datasets via transfer learning. Application of developing mouse retina to scRNA-Seq reveals intrinsic relationships across biological contexts and assays while avoiding batch effects and other technical features. We compare the dimensions learned in this source dataset to adult mouse retina, a time-course of human retinal development, select scRNA-seq datasets from developing brain, chromatin accessibility data, and a murine-cell type atlas to identify shared biological features. These tools lay the groundwork for exploratory analysis of scRNA-seq data via latent space representations, enabling a shift in how we compare and identify cells beyond reliance on marker genes or ensemble molecular identity.

Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification.

Precise temporal control of gene expression in neuronal progenitors is necessary for correct regulation of neurogenesis and cell fate specification. However, the cellular heterogeneity of the developing CNS has posed a major obstacle to identifying the gene regulatory networks that control these processes. To address this, we used single-cell RNA sequencing to profile ten developmental stages encompassing the full course of retinal neurogenesis. This allowed us to comprehensively characterize changes in gene expression that occur during initiation of neurogenesis, changes in developmental competence, and specification and differentiation of each major retinal cell type. We identify the NFI transcription factors (Nfia, Nfib, and Nfix) as selectively expressed in late retinal progenitor cells and show that they control bipolar interneuron and Müller glia cell fate specification and promote proliferative quiescence.

A spatial Markov model for upscaling transport of adsorbing-desorbing solutes.

The Spatial Markov Model (SMM) is an upscaled model with a strong track record in predicting upscaled behavior of conservative solute transport across hydrologic systems. Here we propose an SMM that can account for reactive linear adsorption and desorption processes and test it on a simple benchmark problem: flow and transport through an idealized periodic wavy channel. The methodology is built using trajectories that are obtained from a single high resolution random walk simulation of conservative transport across one periodic element. Our approach encodes information about where a particle starts at the inlet, where it leaves at the outlet, how long it takes to cross the domain and one additional piece of information, the number of times a particle strikes the boundary, with the objective of predicting large scale transport with arbitrary linear adsorption and desorption rates. Our benchmark problem demonstrates that predictions made with our proposed SMM agree favorably with results from direct numerical simulations, which resolve the full transport problem.