A genetic switch for male UV iridescence in an incipient species pair of sulphur butterflies.

Mating cues evolve rapidly and can contribute to species formation and maintenance. However, little is known about how sexual signals diverge and how this variation integrates with other barrier loci to shape the genomic landscape of reproductive isolation. Here, we elucidate the genetic basis of ultraviolet (UV) iridescence, a courtship signal that differentiates the males of Colias eurytheme butterflies from a sister species, allowing females to avoid costly heterospecific matings. Anthropogenic range expansion of the two incipient species established a large zone of secondary contact across the eastern United States with strong signatures of genomic admixtures spanning all autosomes. In contrast, Z chromosomes are highly differentiated between the two species, supporting a disproportionate role of sex chromosomes in speciation known as the large-X (or large-Z) effect. Within this chromosome-wide reproductive barrier, linkage mapping indicates that cis-regulatory variation of bric a brac (bab) underlies the male UV-iridescence polymorphism between the two species. Bab is expressed in all non-UV scales, and butterflies of either species or sex acquire widespread ectopic iridescence following its CRISPR knockout, demonstrating that Bab functions as a suppressor of UV-scale differentiation that potentiates mating cue divergence. These results highlight how a genetic switch can regulate a premating signal and integrate with other reproductive barriers during intermediate phases of speciation.

Improved patient reported outcomes with the direct anterior approach versus the posterior approach for total hip arthroplasty in the early post-operative period.

BACKGROUND: Patients undergoing total hip arthroplasty (THA) with the direct anterior approach (DAA) may experience faster recovery but may also have better baseline health than those who undergo THA with the posterior approach (PA). This study aimed to compare patient-reported outcome measures (PROMs) between the DAA and PA while controlling for baseline factors. METHODS: This is a secondary data analysis from a prospective cohort study of patients utilizing a smartphone-based care management platform following THA. The primary outcomes were HOOS JR and EQ-5D-5L through 1 year and change from baseline. Longitudinal regression models were created to control for baseline characteristics and investigate the impact of surgical approach on PROMs. RESULTS: Of 1364 THAs evaluated, 731 (53.6%) were female, and 840 (61.6%) used the PA. Patients in the PA group were of similar age but had higher body mass index and comorbidity scores. Pre-operative HOOS JR and EQ-5D-5L were comparable, but higher post-operatively in the DAA group through 6 months (p = 0.03 and p = 0.005). At 1 year post-operatively, HOOS JR and EQ-5D-5L did not vary between groups (p = 0.48 and p = 0.56), nor did changes from baseline (p = 0.47 and p = 0.11). After controlling baseline characteristics, DAA was significantly associated with higher average HOOS JR through 6 months (p = 0.03) and EQ-5D-5L through 3 months (p = 0.005), but not at 12 months (p = 0.89 and p = 0.56). CONCLUSION: THA patients undergoing DAA demonstrate earlier improvements in HOOS JR and EQ-5D-5L. However, these differences may not be clinically significant and are not evident at 1-year post-operative. Patient selection and surgeon training may continue to affect outcomes by surgical approach.

Retention of titanium copings to implant-supported fixed dental prostheses.

PURPOSE: The aim of this in vitro study was to assess the effects of using different cements and titanium copings designs on the retention of implant-supported fixed dental prostheses (IFDPs) using a pull-out test. MATERIALS AND METHODS: Fifty zirconia (ZirCAD; Ivoclar Vivadent) and 20 prepolymerized denture acrylic resin (AvaDent) rectangular (36 mm × 12 mm × 8 mm) specimens were milled to mimic the lower left segmental portion of the All-on-Four IFDPs. Cylindrical titanium copings (Variobase; Straumann) (V) were used in 2 prepolymerized denture acrylic resin groups (n = 10) while conical titanium copings (Straumann) (C) were used as a control group for zirconia with 4 groups using cylindrical titanium copings. Before cementation, the outer surfaces of all titanium copings and the intaglio bonding surface of prosthetic specimens were airborne-particle abraded. All specimens were cemented following the manufacturer's recommendations and instructions according to the experimental design. After artificial aging (5000 cycles of 5°C 55°C, dwelling time 20 s; 150 N, 1.5 Hz in a 37°C water bath), all specimens were subjected to retention force testing using a pull-out test using a universal testing machine and a custom fixture with a crosshead speed 5 mm/min. Modes of failure were classified as Type 1, 2, or 3. Retention force values were analyzed by the t-test for the prepolymerized denture acrylic resin specimen groups, and 1-way ANOVA and the Tukey test for the zirconia groups at α = 0.05. RESULTS: Mean and standard deviation retention force values varied from 101.1 ± 67.1 to 509.0 ± 65.2 N for the prepolymerized denture acrylic resin specimen groups. The zirconia groups ranged from 572.8 ± 274.7 to 1416.1 ± 258.0 N. There is no statistically significant difference in retention force values between V and C specimens cementing to zirconia with Panavia SA cement (Kuraray Noritake) (p = 0.587). The retention forces and failure modes were influenced by the cement used (p < 0.05). Modes of failure were predominantly Type 2 (mixed failure) and Type 1 (adhesive fracture from prosthetic materials) except for the quick-set resin group (Type 3, adhesive failure from coping). CONCLUSIONS: When bonding IFDPs onto titanium copings, quick-set resin provided significantly higher retention force for prepolymerized denture acrylic resin prostheses. Conical and cylindrical titanium copings performed similarly when cemented to zirconia with Panavia SA cement under the same protocol. The stability of the bonded interface and retention forces between zirconia prostheses and titanium copings varied from the cement used.

Stepping Beyond Counts in Recovery of Total Hip Arthroplasty: A Prospective Study on Passively Collected Gait Metrics.

Gait quality parameters have been used to measure recovery from total hip arthroplasty (THA) but are time-intensive and previously could only be performed in a lab. Smartphone sensor data and algorithmic advances presently allow for the passive collection of qualitative gait metrics. The purpose of this prospective study was to observe the recovery of physical function following THA by assessing passively collected pre- and post-operative gait quality metrics. This was a multicenter, prospective cohort study. From six weeks pre-operative through to a minimum 24 weeks post-operative, 612 patients used a digital care management application that collected gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-sample t-test. Recovery was defined as the post-operative week when the respective gait metric was no longer statistically inferior to the pre-operative value. To control for multiple comparison error, significance was set at p < 0.002. Walking speeds and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-post-operative (p < 0.001). Walking speed (1.00 ± 0.14 m/s, p = 0.04), step length (0.58 ± 0.06 m/s, p = 0.02), asymmetry (14.5 ± 19.4%, p = 0.046), and double support percentage (31.6 ± 1.5%, p = 0.0089) recovered at 9, 8, 7, and 10 weeks post-operative, respectively. Walking speed, step length, asymmetry, and double support all recovered beyond pre-operative values at 13, 17, 10, and 18 weeks, respectively (p < 0.002). Functional recovery following THA can be measured via passively collected gait quality metrics using a digital care management platform. The data suggest that metrics of gait quality are most negatively affected two weeks post-operative; recovery to pre-operative levels occurs at approximately 10 weeks following primary THA, and follows a slower trajectory compared to previously reported step count recovery trajectories.

Stepping beyond Counts in Recovery of Total Knee Arthroplasty: A Prospective Study on Passively Collected Gait Metrics.

Advances in algorithms developed from sensor-based technology data allow for the passive collection of qualitative gait metrics beyond step counts. The purpose of this study was to evaluate pre- and post-operative gait quality data to assess recovery following primary total knee arthroplasty. This was a multicenter, prospective cohort study. From 6 weeks pre-operative through to 24 weeks post-operative, 686 patients used a digital care management application to collect gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-samples t-test. Recovery was operationally defined as when the respective weekly average gait metric was no longer statistically different than pre-operative. Walking speed and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-operative (p < 0.0001). Walking speed recovered at 21 weeks (1.00 m/s, p = 0.063) and double support percentage recovered at week 24 (32%, p = 0.089). Asymmetry percentage was recovered at 13 weeks (14.0%, p = 0.23) and was consistently superior to pre-operative values at week 19 (11.1% vs. 12.5%, p < 0.001). Step length did not recover during the 24-week period (0.60 m vs. 0.59 m, p = 0.004); however, this difference is not likely clinically relevant. The data suggests that gait quality metrics are most negatively affected two weeks post-operatively, recover within the first 24-weeks following TKA, and follow a slower trajectory compared to previously reported step count recoveries. The ability to capture new objective measures of recovery is evident. As more gait quality data is accrued, physicians may be able to use passively collected gait quality data to help direct post-operative recovery using sensor-based care pathways.

Sub-micrometer insights into the cytoskeletal dynamics and ultrastructural diversity of butterfly wing scales.

BACKGROUND: The color patterns that adorn lepidopteran wings are ideal for studying cell type diversity using a phenomics approach. Color patterns are made of chitinous scales that are each the product of a single precursor cell, offering a 2D system where phenotypic diversity can be studied cell by cell, both within and between species. Those scales reveal complex ultrastructures in the sub-micrometer range that are often connected to a photonic function, including iridescent blues and greens, highly reflective whites, or light-trapping blacks. RESULTS: We found that during scale development, Fascin immunostainings reveal punctate distributions consistent with a role in the control of actin patterning. We quantified the cytoskeleton regularity as well as its relationship to chitin deposition sites, and confirmed a role in the patterning of the ultrastructures of the adults scales. Then, in an attempt to characterize the range and variation in lepidopteran scale ultrastructures, we devised a high-throughput method to quickly derive multiple morphological measurements from fluorescence images and scanning electron micrographs. We imaged a multicolor eyespot element from the butterfly Vanessa cardui (V. cardui), taking approximately 200 000 individual measurements from 1161 scales. Principal component analyses revealed that scale structural features cluster by color type, and detected the divergence of non-reflective scales characterized by tighter cross-rib distances and increased orderedness. CONCLUSION: We developed descriptive methods that advance the potential of butterfly wing scales as a model system for studying how a single cell type can differentiate into a multifaceted spectrum of complex morphologies. Our data suggest that specific color scales undergo a tight regulation of their ultrastructures, and that this involves cytoskeletal dynamics during scale growth.

Using Patient Demographics and Statistical Modeling to Predict Knee Tibia Component Sizing in Total Knee Arthroplasty.

BACKGROUND: Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range. METHODS: With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration. RESULTS: The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set. CONCLUSION: The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable.

Multicenter, prospective cohort study: immediate postoperative gains in active range of motion following robotic-assisted total knee replacement compared to a propensity-matched control using manual instrumentation.

BACKGROUND: Range of motion (ROM) following total knee replacement (TKR) has been associated with patient satisfaction and knee function, and is also an early indicator of a successful procedure. Robotic-assisted TKR (raTKR) is considered to reproduce more precise resections, and, as a result, may be associated with improved early patient satisfaction compared to manual TKR (mTKR). The purpose of this study was to evaluate the early postoperative active ROM (aROM) between raTKR and mTKR. METHODS: A total of 216 mTKR patients were propensity-matched, in terms of age, gender, comorbidities, and BMI, to 216 raTKR cases. Intraoperative and immediate postoperative adverse events were collected. Knee flexion and extension aROM were measured preoperatively and at one- and three months after operation. RESULTS: Changes in flexion aROM were significantly greater in raTKR vs. mTKR at one- (6.9°, 95% CI: 3.5, 10.4°) and three months (4.9°, 95% CI: 2.1, 7.7°). Flexion aROM was greater at three postoperative months compared to preoperative aROM only in the raTKR group, and raTKR patients had higher odds of achieving ≥ 90° of flexion at one month after operation (OR: 2.15, 95% CI: 1.16, 3.99). There were no significant differences between groups in intraoperative (P > 0.999) or postoperative adverse events. CONCLUSIONS: Compared with mTKR, raTKR resulted  in less loss of aROM immediately after operation and a faster recovery of aROM within three months after operation. TRIAL REGISTRATION: Clinicaltrials.gov (NCT# 03737149).

Automated Mapping of Real-world Oncology Laboratory Data to LOINC.

In this study we seek to determine the efficacy of using automated mapping methods to reduce the manual mapping burden of laboratory data to LOINC(r) on a nationwide electronic health record derived oncology specific dataset. We developed novel encoding methodologies to vectorize free text lab data, and evaluated logistic regression, random forest, and knn machine learning classifiers. All machine learning models did significantly better than deterministic baseline algorithms. The best classifiers were random forest and were able to predict the correct LOINC code 94.5% of the time. Ensemble classifiers further increased accuracy, with the best ensemble classifier predicting the same code 80.5% of the time with an accuracy of 99%. We conclude that by using an automated laboratory mapping model we can both reduce manual mapping time, and increase quality of mappings, suggesting automated mapping is a viable tool in a real-world oncology dataset.

Cortex cis-regulatory switches establish scale colour identity and pattern diversity in Heliconius.

In Heliconius butterflies, wing colour pattern diversity and scale types are controlled by a few genes of large effect that regulate colour pattern switches between morphs and species across a large mimetic radiation. One of these genes, cortex, has been repeatedly associated with colour pattern evolution in butterflies. Here we carried out CRISPR knockouts in multiple Heliconius species and show that cortex is a major determinant of scale cell identity. Chromatin accessibility profiling and introgression scans identified cis-regulatory regions associated with discrete phenotypic switches. CRISPR perturbation of these regions in black hindwing genotypes recreated a yellow bar, revealing their spatially limited activity. In the H. melpomene/timareta lineage, the candidate CRE from yellow-barred phenotype morphs is interrupted by a transposable element, suggesting that cis-regulatory structural variation underlies these mimetic adaptations. Our work shows that cortex functionally controls scale colour fate and that its cis-regulatory regions control a phenotypic switch in a modular and pattern-specific fashion.

Heliconius butterflies have bright patterns on their wings that tell potential predators that they are toxic. As a result, predators learn to avoid eating them. Over time, unrelated species of butterflies have evolved similar patterns to avoid predation through a process known as Müllerian mimicry. Worldwide, there are over 180,000 species of butterflies and moths, most of which have different wing patterns. How do genes create this pattern diversity? And do butterflies use similar genes to create similar wing patterns? One of the genes involved in creating wing patterns is called cortex. This gene has a large region of DNA around it that does not code for proteins, but instead, controls whether cortex is on or off in different parts of the wing. Changes in this non-coding region can act like switches, turning regions of the wing into different colours and creating complex patterns, but it is unclear how these switches have evolved. Butterfly wings get their colour from tiny structures called scales, which each have their own unique set of pigments. In Heliconius butterflies, there are three types of scales: yellow/white scales, black scales, and red/orange/brown scales. Livraghi et al. used a DNA editing technique called CRISPR to find out whether the cortex gene affects scale type. First, Livraghi et al. confirmed that deleting cortex turned black and red scales yellow. Next, they used the same technique to manipulate the non-coding DNA around the cortex gene to see the effect on the wing pattern. This manipulation turned a black-winged butterfly into a butterfly with a yellow wing band, a pattern that occurs naturally in Heliconius butterflies. The next step was to find the mutation responsible for the appearance of yellow wing bands in nature. It turns out that a bit of extra genetic code, derived from so-called 'jumping genes', had inserted itself into the non-coding DNA around the cortex gene, 'flipping' the switch and leading to the appearance of the yellow scales. Genetic information contains the instructions to generate shape and form in most organisms. These instructions evolve over millions of years, creating everything from bacteria to blue whales. Butterfly wings are visual evidence of evolution, but the way their genes create new patterns isn't specific to butterflies. Understanding wing patterns can help researchers to learn how genetic switches control diversity across other species too.

Truncated amelogenin and LRAP transgenes improve Amelx null mouse enamel.

Amelogenin is the most abundant enamel protein involved in enamel mineralization. Our goal was to determine whether all three regions of amelogenin (N-terminus, C-terminus, central core) are required for enamel formation. Amelogenin RNA is alternatively spliced, resulting in at least 16 different amelogenin isoforms in mice, with M180 and LRAP expressed most abundantly. Soon after secretion by ameloblasts, M180 is cleaved by MMP20 resulting in C-terminal truncated (CTRNC) amelogenin. We aimed to determine whether the 2 transgenes (Tg), LRAP and CTRNC together, can improve LRAPTg/Amelx-/- and CTRNCTg/Amelx-/- enamel thickness and prism organization, which were not rescued in Amelx-/- enamel. We generated CTRNCTg/LRAPTg/Amelx-/- mice and analyzed developing and mature incisor and molar enamel histologically, by microCT, SEM and microhardness testing. CTRNCTg and LRAPTg overexpression together significantly improved the enamel phenotype of LRAPTg/Amelx-/- and CTRNCTg/Amelx-/- mouse enamel, however enamel microhardness was recovered only when M180Tg was expressed, alone or with LRAPTg. We determined that both LRAP and CTRNC, which together express all three regions of the amelogenin protein (N-terminus, C-terminus and hydrophobic core) contribute to the final enamel thickness and prism organization in mice.