Spinal Motion and Muscle Activity during Active Trunk Movements – Comparing Sheep and Humans Adopting Upright and Quadrupedal Postures

Sheep are used as models for the human spine, yet comparative in vivo data necessary for validation is limited. The purpose of this study was therefore to compare spinal motion and trunk muscle activity during active trunk movements in sheep and humans. Three-dimensional kinematic data as well as surface electromyography (sEMG) of spinal flexion and extension was compared in twenty-four humans in upright (UR) and 4-point kneeling (KN) postures and in 17 Austrian mountain sheep. Kinematic markers were attached over the sacrum, posterior iliac spines, and spinous and transverse processes of T5, T8, T11, L2 and L5 in humans and over the sacrum, tuber sacrale, T5, T8, T12, L3 and L7 in sheep. The activity of erector spinae (ES), rectus abdominis (RA), obliquus externus (OE), and obliquus internus (OI) were collected. Maximum sEMG (MOE) was identified for each muscle and trial, and reported as a percentage (MOE%) of the overall maximally observed sEMG from all trials. Spinal range of motion was significantly smaller in sheep compared to humans (UR / KN) during flexion (sheep: 6–11°; humans 12–34°) and extension (sheep: 4°; humans: 11–17°). During extension, MOE% of ES was greater in sheep (median: 77.37%) than UR humans (24.89%), and MOE% of OE and OI was greater in sheep (OE 76.20%; OI 67.31%) than KN humans (OE 21.45%; OI 19.34%), while MOE% of RA was lower in sheep (21.71%) than UR humans (82.69%). During flexion, MOE% of RA was greater in sheep (83.09%) than humans (KN 47.42%; UR 41.38%), and MOE% of ES in sheep (45.73%) was greater than KN humans (14.45%), but smaller than UR humans (72.36%). The differences in human and sheep spinal motion and muscle activity suggest that caution is warranted when ovine data are used to infer human spine biomechanics.     

Pore-forming Activity of the Escherichia coli Type III Secretion System Protein EspD

Enterohemorrhagic Escherichia coli is a causative agent of gastrointestinal and diarrheal diseases. Pathogenesis associated with enterohemorrhagic E. coli involves direct delivery of virulence factors from the bacteria into epithelial cell cytosol via a syringe-like organelle known as the type III secretion system. The type III secretion system protein EspD is a critical factor required for formation of a translocation pore on the host cell membrane. Here, we show that recombinant EspD spontaneously integrates into large unilamellar vesicle (LUV) lipid bilayers; however, pore formation required incorporation of anionic phospholipids such as phosphatidylserine and an acidic pH. Leakage assays performed with fluorescent dextrans confirmed that EspD formed a structure with an inner diameter of ∼2.5 nm. Protease mapping indicated that the two transmembrane helical hairpin of EspD penetrated the lipid layer positioning the N- and C-terminal domains on the extralumenal surface of LUVs. Finally, a combination of glutaraldehyde cross-linking and rate zonal centrifugation suggested that EspD in LUV membranes forms an ∼280–320-kDa oligomeric structure consisting of ∼6–7 subunits.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Die Blüten der Bennettitalen

Ohne Zusammenfassung     

Climatic sensitivity of species’ vegetative and reproductive phenology in a Hawaiian montane wet forest

Understanding how tropical tree phenology (i.e., the timing and amount of seed and leaf production) responds to climate is vital for predicting how climate change may alter ecological functioning of tropical forests. We examined the effects of temperature, rainfall, and photosynthetically active radiation (PAR) on seed phenology of four dominant species and community-level leaf phenology in a montane wet forest on the island of Hawaiʻi using monthly data collected over ~ 6 years. We expected that species phenologies would be better explained by variation in temperature and PAR than rainfall because rainfall at this site is not limiting. The best-fit model for all four species included temperature, rainfall, and PAR. For three species, including two foundational species of Hawaiian forests (Acacia koa and Metrosideros polymorpha), seed production declined with increasing maximum temperatures and increased with rainfall. Relationships with PAR were the most variable across all four species. Community-level leaf litterfall decreased with minimum temperatures, increased with rainfall, and showed a peak at PAR of ~ 400 μmol/m²s⁻¹. There was considerable variation in monthly seed and leaf production not explained by climatic factors, and there was some evidence for a mediating effect of daylength. Thus, the impact of future climate change on this forest will depend on how climate change interacts with other factors such as daylength, biotic, and/or evolutionary constraints. Our results nonetheless provide insight into how climate change may affect different species in unique ways with potential consequences for shifts in species distributions and community composition.