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Cheap AI chatbots transform medical diagnoses in places with limited care
Daily briefing: Bonobo’s tea party is first demonstration of pretend play in a non-human
Briefing Chat: 'External lungs' keep man alive for 48 hours until transplant
Genomic analysis of ST117, 155, 1011, 167, 744, and 17391 in poultry-associated multidrug resistant Escherichia coli isolates from India
Genomic clues to the origin of eukaryotic cells
Somatosensory evoked potentials and high-frequency oscillations after transcranial static magnetic stimulation over the primary somatosensory cortex
Abstract Transcranial static magnetic field stimulation (tSMS) is a non-invasive brain stimulation technique known to reduce cortical excitability. Although its effectiveness has been demonstrated in various cortical regions, it remains unclear whether somatosensory processing is influenced by this stimulation. The purpose of this study was to investigate whether tSMS over the primary somatosensory cortex (S1) modulates somatosensory evoked potentials (SEPs) and high-frequency oscillations superimposed on them (somatosensory HFOs). In a randomized crossover study, twenty healthy young adults received tSMS or sham stimulation over the left S1 (corresponding to C3 of the international 10–20 system) for 20 min. SEPs were recorded in response to right median nerve stimulation before, immediately after, and 20 min after stimulation. Somatosensory HFOs were extracted by applying a 400–800 Hz band-pass filter to SEP waveforms and separated into early and late components relative to the N20 peak latency. TSMS over the left S1 significantly reduced the amplitude of early HFOs 20 min after stimulation, whereas late HFOs remained unchanged. No effects of tSMS were observed on the N20 component of standard SEPs, which reflects neural activity in area 3b of the S1. Early and late HFOs are thought to reflect the action potentials of thalamocortical fibers and the activity of GABAergic interneurons, respectively. These findings therefore suggest that tSMS over the S1 selectively attenuates thalamocortical input while exerting no effect on GABAergic interneuron activity.
Association between osteoporosis and waitlist mortality in liver transplant candidates
Intramuscular neural distribution of the vastus lateralis informs effective and safe botulinum neurotoxin injection
Differences in AUTOS- and FTND-assessed dependence on various tobacco products among Chinese current tobacco/nicotine users
Biofluid biomarkers in Alzheimer’s disease and other neurodegenerative dementias
Integrative analyses of metastatic cancer transcriptome reveal clinically distinct cellular States and ecosystems
Abstract Determining the diverse cellular states and their organization into cellular ecosystems that make up metastatic tumor is vital for elucidating the biological and prognostic diversity of cancer. However, large-scale studies profiling the clinical relevance of these cellular states and ecotypes are still lacking in metastatic cancers. In this study, we used EcoTyper, a machine learning framework, to comprehensively analyze transcriptomes from 2822 metastatic cancer patient samples covering 25 cancer types, enabling characterization of the fundamental cellular states and tumor ecosystems integral to metastatic cancer. We identified 45 distinct cellular states across 12 cell types and validated their robustness in validation cohorts. We observed that they differed in functional and prognostic associations. Survival analysis revealed that the clinically relevant cellular states, highlighting their promise as predictors of clinical outcomes. Functional enrichment analysis exhibited that the marker genes of cellular states were significantly enriched in cancer hallmark and immune-related pathways. In addition, our analysis identified five ecotypes associated with different clinical outcomes. Transcription factor enrichment analysis revealed key transcription factors (i.e. SPIB, SRF, and NR1D1) that were significantly associated with patient clinical outcomes. In conclusion, this study provided a high-resolution landscape of cellular states and ecosystems in metastatic tumors, offering new potential targets for the development of cancer treatment strategies and prognostic assessment.
Measuring spin correlation between quarks during QCD confinement
NeuroAction: a neuroevolutionary approach to reinforcement learning for autonomous vehicles
Influence of dairy farms’ characteristics and technological level on attitude towards augmented reality
Association of sarcopenia with survival and treatment response in brain metastasis of non-small cell lung cancer
Abstract Brain metastases are common in non-small cell lung cancer (NSCLC) and affect prognosis and survival. While frailty and sarcopenia are associated with the overall survival in NSCLC the impact on outcome and survival after surgery for brain metastasis is unknown. We therefore analyzed 179 patients (81 women) with NSCLC undergoing resection for brain metastasis between 2011 and 2020 retrospectively. Frailty was measured using the Clinical Frailty Scale (CFS). Temporal Muscle Volume (TMV) was assessed in preoperative T1w MRI. The median age was 63 years. Clinical frailty was present in about 20.6%. Mean follow-up was 11 months. Frailty correlated significantly with age ( r = 0.36, p < 0.001) and smaller TMV ( r =-0.24, p = 0.002). However, only measurement of TMV predicted impaired survival (median OS 34.5 vs. 10.3 months, p < 0.001). Physical performance after surgery was negatively affected by frailty ( r =-0.72, p < 0.001) and positively by TMV ( r = 0.2, p = 0.038). Major postoperative complications were more strongly associated with sarcopenia rather than frailty. Treatment response towards immunotherapy improved in the absence of sarcopenia (B = 2.48, p = 0.031). TMV is a predictor for survival after resection of brain metastasis and an indicator of treatment response to immunotherapy in patients with NSCLC. Accounting for sarcopenia in surgical decision making could improve patient selection for different treatment modalities.
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Sustainable high-performance concrete: harnessing recycled rubber and slag for strength and eco-friendliness
Group-specific effect of interannual water level fluctuation on consumers trophic niche area
Abstract The trophic niche area defines the consumer’s ability to utilize a range of food sources and their role in community. However, the trophic niche area might be influenced by a variety of biotic and abiotic factors. For instance, water level fluctuation might also affect the trophic niche area of all consumers inhabiting a given aquatic ecosystem. Thus, in this study we investigated the effect of water level fluctuation on the isotopic niche area of multiple consumers (macroinvertebrates and fish) belonging to different trophic guilds (i.e., predator, omnivore, and detritivore) over three years. The results showed that water level fluctuation strongly affects the isotopic niche area of all consumers. Nevertheless, the magnitude and direction were group specific. While predatory fish increased the isotopic niche area when the water level dropped, omnivorous fish experienced a decrease; these two trends continued even after the water level drop. In crayfish, the isotopic niche area was considerably larger during the year with water level drop. However, decreasing water levels resulted in a corresponding decrease in isotopic niche area in detritivores and predatory macrozoobenthos. Our study demonstrated the importance of water fluctuations on the isotopic niche area across different types of consumers.