Driving a musculoskeletal model with inertial and magnetic measurement units

We developed and evaluated a new kinematic driver for musculoskeletal models using ambulatory inertial and magnetic measurement units (IMMUs). The new driver uses the orientation estimates based on sensor fusion of each individual IMMU and benefits from two important properties of musculoskeletal models. First, these models contain more complex, anatomical, kinematic models than those currently used for sensor fusion of multiple IMMUs and are continuously improved. Second, they allow movement between segment and measured sensor. For three different tasks, the new IMMU driver, (optical) marker drivers and a combination of both were used to reconstruct the motion. Maximal root mean square (RMS) joint angle differences with respect to the silver standard (combined IMMU/marker drivers) were found for the hip joint; 4°, 2° and 5° during squat, gait and slideboard tasks for IMMU-driven reconstructions, compared with 6°, 5° and 5° for marker-driven reconstructions, respectively. The measured angular velocities corresponded best to the IMMU-driven reconstructions, with a maximal RMS difference of 66°/s, compared with 108°/s and 91°/s for marker-driven reconstructions and silver standard. However, large oscillations in global accelerations occurred during IMMU-driven reconstructions resulting in a maximal RMS difference with respect to measured acceleration of 23 m/s², compared with 9 m/s² for reconstructions that included marker drivers. The new driver facilitates direct implementation of IMMU-based orientation estimates in currently available biomechanical models. As such, it can help in the rapid expansion of biomechanical analysis based on outdoor measurements.     

Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures

High-grade serous ovarian cancer (HG-SOC), a major histologic type of epithelial ovarian cancer (EOC), is a poorly-characterized, heterogeneous and lethal disease where somatic mutations of TP53 are common and inherited loss-of-function mutations in BRCA1/2 predispose to cancer in 9.5–13% of EOC patients. However, the overall burden of disease due to either inherited or sporadic mutations is not known.

We performed bioinformatics analyses of mutational and clinical data of 334 HG-SOC tumor samples from The Cancer Genome Atlas to identify novel tumor-driving mutations, survival-significant patient subgroups and tumor subtypes potentially driven by either hereditary or sporadic factors.

We identified a sub-cluster of high-frequency mutations in 22 patients and 58 genes associated with DNA damage repair, apoptosis and cell cycle. Mutations of CHEK2, observed with the highest intensity, were associated with poor therapy response and overall survival (OS) of these patients (P = 8.00e-05), possibly due to detrimental effect of mutations at the nuclear localization signal. A 21-gene mutational prognostic signature significantly stratifies patients into relatively low or high-risk subgroups with 5-y OS of 37% or 6%, respectively (P = 7.31e-08). Further analysis of these genes and high-risk subgroup revealed 2 distinct classes of tumors characterized by either germline mutations of genes such as CHEK2, RPS6KA2 and MLL4, or somatic mutations of other genes in the signature.

Our results could provide improvement in prediction and clinical management of HG-SOC, facilitate our understanding of this complex disease, guide the design of targeted therapeutics and improve screening efforts to identify women at high-risk of hereditary ovarian cancers distinct from those associated with BRCA1/2 mutations.     

Sleep and Sleepiness among Brazilian Shift-Working Bus Drivers

The aim of this study was to evaluate daytime and nighttime sleep, as well as daytime and nighttime sleepiness of professional shift-working bus drivers. Thirty-two licensed bus drivers were assessed by nocturnal and diurnal polysomnography (PSG) recording and multiple sleep latency testing (MSLT) sessions. Sleep length was shorter and sleep efficiency reduced during daytime sleep compared with nighttime sleep. Thirty-eight percent of the drivers had indices of obstructive apnea and hypopnea syndrome (>5/h sleep) during nighttime and daytime sleep; more drivers snored during daytime than nighttime sleep (50% vs. 35%, p < 0.05), and 38% of the drivers evidenced periodic leg movements. The MSLT revealed that 42 and 38% of the bus drivers met the criteria for sleepiness when the test was conducted during the day and night, respectively. The daytime as compared to nighttime sleep of shift-working bus drivers was shorter and more fragmented and was associated in many with evidence of excessive sleepiness. Respiratory disorder was a common finding among the professional shift-working bus drivers. All these sleep deficiencies may adversely affect on the job driving performance.     

Multi‐modal meta‐analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor

Molecular and functional profiling of cancer cell lines is subject to laboratory‐specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer cell lines for reliable biological discoveries. Here, we carried out a systematic analysis of nine types of data modalities using meta‐analysis of 53 omics studies across 12 research laboratories for 2,018 cell lines. To account for a relatively low consistency observed for certain data modalities, we developed a robust data integration approach that identifies reproducible signals shared among multiple data modalities and studies. We demonstrated the power of the integrative analyses by identifying a novel driver gene, ECHDC1, with tumor suppressive role validated both in breast cancer cells and patient tumors. The multi‐modal meta‐analysis approach also identified synthetic lethal partners of cancer drivers, including a co‐dependency of PTEN deficient endometrial cancer cells on RNA helicases.     

Not all cancers are created equal: Tissue specificity in cancer genes and pathways

Tumors arise through waves of genetic alterations and clonal expansion that allow tumor cells to acquire cancer hallmarks, such as genome instability and immune evasion. Recent genomic analyses showed that the vast majority of cancer driver genes are mutated in a tissue-dependent manner, that is, are altered in some cancers but not others. Often the tumor type also affects the likelihood of therapy response. What is the origin of tissue specificity in cancer? Recent studies suggest that both cell-intrinsic and cell-extrinsic factors play a role. On one hand, cell type–specific wiring of the cell signaling network determines the outcome of cancer driver gene mutations. On the other hand, the tumor cells’ exposure to tissue-specific microenvironments (e.g. immune cells) also contributes to shape the tissue specificity of driver genes and of therapy response. In the future, a more complete understanding of tissue specificity in cancer may inform methods to better predict and improve therapeutic outcomes.     

The role of dominant prairie species ecotypes on plant diversity patterns of restored grasslands across a rainfall gradient in the US Great Plains

Questions

A robust ecosystem requires a functionally heterogeneous community of organisms with ecological traits that permit broad resource partitioning. Understanding community diversity patterns can help investigate drivers of community assembly and assess restoration success. Do biodiversity patterns differ among grassland communities sown with different ecotypes of dominant species during restoration along a rainfall gradient in the tallgrass prairie of the central US Great Plains?

Location

Four field sites across a rainfall gradient within the North American Great Plains: Colby, Kansas (39°23′17.8″N, 101°04′57.4″W), Hays, Kansas (38°51′13.2″N, 99°19′08.6″W), Manhattan, Kansas (39°08′22.3″N, 96°38′23.3″W), and Carbondale, Illinois (IL, 37°41′47.0″N, 89°14′19.2″W).

Methods

We applied linear mixed models to assess the effect of dominant species ecotype, year, and location on grassland taxonomic, phylogenetic, and functional diversity.

Results

The non-local grass ecotype (compared to the local ecotype) promoted species richness. In contrast, the effect of the dominant species ecotype on phylogenetic or functional diversity was site-specific over the 10-year restoration. Richness decreased across the rainfall gradient from dry to moist sites, and the wettest site had the highest phylogenetic and functional diversity.

Conclusions

Our results suggest that abiotic filtering by rainfall is a key assembly mechanism that could predict grassland changes in biodiversity in the early restoration phases. Given the community response across the tallgrass prairie, restoration practitioners should consider the impact of regional sources of dominant species used in restoration when biodiversity is a restoration goal. It is recommended for future grassland restoration to detect gaps and limitations in evolutionary and trait structure that will reveal which diversity components to evaluate.     

Co-survival of the fittest few: mosaic amplification of receptor tyrosine kinases in glioblastoma

Mosaic amplification of receptor tyrosine kinases in glioblastoma suggests that tumor cells with different progression driver mutations may coevolve rather than compete during clonal evolution.