PROSTHETIC LEG DESIGN, FORCE PRODUCTION, AND CURVE SPRINT PERFORMANCE: A PILOT STUDY

We compared the use of a running specific prosthesis (RSP) with a solid or “split-toe“ design by athletes with a leg amputation on sprinting speed and stance-average centripetal ground reaction force (GRF) along a flat 400 m track curve, 200 m track curve, and straightaway. Three athletes with a right transtibial amputation performed maximal effort sprints along the curves (clockwise and counterclockwise) and straightaway of an indoor track using a traditional, solid RSP and an RSP with a split-toe design while we measured 3D GRFs and kinematics. Sprinting speed was significantly faster (p = 0.003) when using the split-toe RSP across curve conditions and directions compared to the solid RSP. However, there was no significant effect of RSP design on stance-average centripetal force (p = 0.180). Sprint speed was similar between RSP designs on the straightaway (p = 0.705)

The HIV-1 Subtype C Epidemic in South America Is Linked to the United Kingdom

Background: The global spread of HIV-1 has been accompanied by the emergence of genetically distinct viral strains. Over the past two decades subtype C viruses, which predominate in Southern and Eastern Africa, have spread rapidly throughout parts of South America. Phylogenetic studies indicate that subtype C viruses were introduced to South America through a single founder event that occurred in Southern Brazil. However, the external route via which subtype C viruses spread to the South American continent has remained unclear.Methodology/Principal Findings: We used automated genotyping to screen 8,309 HIV-1 subtype C pol gene sequences sampled within the UK for isolates genetically linked to the subtype C epidemic in South America. Maximum likelihood and Bayesian approaches were used to explore the phylogenetic relationships between 54 sequences identified in this screen, and a set of globally sampled subtype C reference sequences. Phylogenetic trees disclosed a robustly supported relationship between sequences from Brazil, the UK and East Africa. A monophyletic cluster comprised exclusively of sequences from the UK and Brazil was identified and dated to approximately the early 1980s using a Bayesian coalescent-based method. A sub-cluster of 27 sequences isolated from homosexual men of UK origin was also identified and dated to the early 1990s.Conclusions: Phylogenetic, demographic and temporal data support the conclusion that the UK was a crucial staging post in the spread of subtype C from East Africa to South America. This unexpected finding demonstrates the role of diffuse international networks in the global spread of HIV-1 infection, and the utility of globally sampled viral sequence data in revealing these networks. Additionally, we show that subtype C viruses are spreading within the UK amongst men who have sex with men

AAV-mediated direct in vivo CRISPR screen identifies functional suppressors in glioblastoma

A causative understanding of genetic factors that regulate glioblastoma pathogenesis is of central importance. Here we developed an adeno-associated virus-mediated, autochthonous genetic CRISPR screen in glioblastoma. Stereotaxic delivery of a virus library targeting genes commonly mutated in human cancers into the brains of conditional-Cas9 mice resulted in tumors that recapitulate human glioblastoma. Capture sequencing revealed diverse mutational profiles across tumors. The mutation frequencies in mice correlated with those in two independent patient cohorts. Co-mutation analysis identified co-occurring driver combinations such as B2m-Nf1, Mll3-Nf1 and Zc3h13-Rb1, which were subsequently validated using AAV minipools. Distinct from Nf1-mutant tumors, Rb1-mutant tumors are undifferentiated and aberrantly express homeobox gene clusters. The addition of Zc3h13 or Pten mutations altered the gene expression profiles of Rb1 mutants, rendering them more resistant to temozolomide. Our study provides a functional landscape of gliomagenesis suppressors in vivo

A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for narrowband radio signals over four observing sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ~11,680 stars and planetary systems in the ~9 arcminute beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. In this work, we also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense RFI are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ~15 times smaller at ~6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake Figure of Merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is detectable in our search (EIRP > 1e13 W). For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5e16 W) is at most 3e-4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al. (2023).Comment: 22 pages, 9 figures, submitted to AJ, revise

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Stroller running: Energetic and kinematic changes across pushing methods

<div><p>Objective</p><p>Running with a stroller provides an opportunity for parents to exercise near their child and counteract health declines experienced during early parenthood. Understanding biomechanical and physiological changes that occur when stroller running is needed to evaluate its health impact, yet the effects of stroller running have not been clearly presented. Here, three commonly used stroller pushing methods were investigated to detect potential changes in energetic cost and lower-limb kinematics.</p><p>Methods</p><p>Sixteen individuals (M/F: 10/6) ran at self-selected speeds for 800m under three stroller conditions (2-Hands, 1-Hand, and Push/Chase) and an independent running control.</p><p>Results</p><p>A significant decrease in speed (p = 0.001) and stride length (p<0.001) was observed between the control and stroller conditions, however no significant change in energetic cost (p = 0.080) or heart rate (p = 0.393) was observed. Additionally, pushing method had a significant effect on speed (p = 0.001) and stride length (p<0.001).</p><p>Conclusions</p><p>These findings suggest that pushing technique influences stroller running speed and kinematics. These findings suggest specific fitness effects may be achieved through the implementation of different pushing methods.</p></div

Review of prior studies investigating stroller running.

<p>Review of prior studies investigating stroller running.</p

Kinematic and energetic values across conditions (Mean ± SD).

<p>Kinematic and energetic values across conditions (Mean ± SD).</p

Predicting continuous ground reaction forces from accelerometers during uphill and downhill running: a recurrent neural network solution

Background Ground reaction forces (GRFs) are important for understanding human movement, but their measurement is generally limited to a laboratory environment. Previous studies have used neural networks to predict GRF waveforms during running from wearable device data, but these predictions are limited to the stance phase of level-ground running. A method of predicting the normal (perpendicular to running surface) GRF waveform using wearable devices across a range of running speeds and slopes could allow researchers and clinicians to predict kinetic and kinematic variables outside the laboratory environment. Purpose We sought to develop a recurrent neural network capable of predicting continuous normal (perpendicular to surface) GRFs across a range of running speeds and slopes from accelerometer data. Methods Nineteen subjects ran on a force-measuring treadmill at five slopes (0°, ±5°, ±10°) and three speeds (2.5, 3.33, 4.17 m/s) per slope with sacral- and shoe-mounted accelerometers. We then trained a recurrent neural network to predict normal GRF waveforms frame-by-frame. The predicted versus measured GRF waveforms had an average ± SD RMSE of 0.16 ± 0.04 BW and relative RMSE of 6.4 ± 1.5% across all conditions and subjects. Results The recurrent neural network predicted continuous normal GRF waveforms across a range of running speeds and slopes with greater accuracy than neural networks implemented in previous studies. This approach may facilitate predictions of biomechanical variables outside the laboratory in near real-time and improves the accuracy of quantifying and monitoring external forces experienced by the body when running