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Derailed transmembrane receptor trafficking could be a hallmark of tumorigenesis and increased tumor invasiveness, but receptor dynamics have not been used to differentiate metastatic cancer cells from less invasive ones. Using single-particle tracking techniques, we  developed a phenotyping asssay named T ransmembrane Re ceptor D ynamics (TReD), studied the dynamics of epidermal growth factor receptor (EGFR) in seven breast epithelial cell lines and developed a phenotyping assay named T ransmembrane Re ceptor D ynamics (TReD). Here we show a clear evidence that increased EGFR diffusivity and enlarged EGFR confinement size in the plasma membrane (PM) are correlated with the enhanced metastatic potential in these cell lines. By comparing the TReD results with the gene expression profiles, we found a clear negative correlation between the EGFR diffusivities and the breast cancer luminal differentiation scores (r = −0.75). Upon the induction of epithelial-mesenchymal transition (EMT), EGFR diffusivity significantly increased for the non-tumorigenic MCF10A (99%) and the non-invasive MCF7 (56%) cells, but not for the highly metastatic MDA-MB-231 cell. We believe that the reorganization of actin filaments during EMT modified the PM structures, causing the receptor dynamics to change. TReD can thus serve as a new biophysical marker to probe the metastatic potential of cancer cells and even to monitor the transition of metastasis.

With many real-world applications of Natural Language Processing (NLP) comprising of long texts, there has been a rise in NLP benchmarks that measure the accuracy of models that can handle longer input sequences. However, these benchmarks do not consider the trade-offs between accuracy, speed, and power consumption as input sizes or model sizes are varied. In this work, we perform a systematic study of this accuracy vs. efficiency trade-off on two widely used long-sequence models - Longformer-Encoder-Decoder (LED) and Big Bird - during fine-tuning and inference on four datasets from the SCROLLS benchmark. To study how this trade-off differs across hyperparameter settings, we compare the models across four sequence lengths (1024, 2048, 3072, 4096) and two model sizes (base and large) under a fixed resource budget. We find that LED consistently achieves better accuracy at lower energy costs than Big Bird. For summarization, we find that increasing model size is more energy efficient than increasing sequence length for higher accuracy. However, this comes at the cost of a large drop in inference speed. For question answering, we find that smaller models are both more efficient and more accurate due to the larger training batch sizes possible under a fixed resource budget.

Background Pinch and grip strengths are vital indicators of upper limb function, musculoskeletal health, and general health. While most research has focused on older individuals, it is crucial to build normative data for younger populations. This cross-sectional study was conducted to determine the normative values for lateral pinch strength (LPS) and hand grip strength (HGS) in healthy adult Singaporeans. Methods The study recruited 500 healthy individuals without any serious general illnesses and upper limb pain, aged 21–80 years. LPS and HGS were measured using a standardized JAMAR hand dynamometer. Age, gender, hand dominance, and participant demographics were recorded. Normative values were then established for different age groups and hand dominance. A machine learning approach was employed to determine the most relevant variables for dominant LPS and HGS in our data, respectively. Results Our data showed that HGS and LPS peaked between 40–44 years of age in women. In men, average HGS peaked between 35–39 years and LPS peaked between 50–54 years. Compared to the non-dominant side, dominant HGS was 6.86% and 6.23% higher in women and men, respectively. The difference between dominant and non-dominant LPS in men and women was 6.96% and 9.18%, respectively. Age was strongly associated with hand strength for older participants, but not for younger ones. Height, weight, and age were important for predicting dominant HGS and LPS, and gait speed for HGS only. Conclusions Our data align with past results, but the normative values are comparatively lower than the consolidated Western norms. Compared to the non-dominant hand, the strength of the dominant hand is significantly higher. No statistical difference between the right- and left-handed participants in terms of dominant HGS and dominant LPS. The results can be valuable for researchers and healthcare providers working with young and older adults.

Assessment of human movement performance in activities of daily living (ADL) is a key component in clinical and rehabilitation settings. Motion capture technology is an effective method for objective assessment of human movement. Existing databases capture human movement and ADL performance primarily in the Western population, and there are no Asian databases to date. This is despite the fact that Asian anthropometrics influence movement kinematics and kinetics. This paper details the protocol in the first phase of the largest Asian normative human movement database. Data collection has commenced, and this paper reports 10 healthy participants. Twelve tasks were performed and data was collected using Qualisys motion capture system, force plates and instrumented table and chair. In phase two, human movement of individuals with stroke and knee osteoarthritis will be captured. This can have great potential for benchmarking with the normative human movement captured in phase one and predicting recovery and progression of movement for patients. With individualised progression, it will offer the development of personalised therapy protocols in rehabilitation.Measurement(s)voluntary movement behavior • grip strength measurement • Pinch StrengthTechnology Type(s)motion capture system • force plates • sensor • dynamometryFactor Type(s)gait • Timed Get Up and Go Test • balance • reaching • key turning • hand to mouth • hand to back • hand on head • cross obstacle • folding towel • step up and downSample Characteristic - OrganismHomo sapiensSample Characteristic - LocationAsiaMachine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12808187