Search

The solid–liquid interfacial energy was optimized based on the nucleation potential model, aligning it more closely with the actual crystallization process. The solubility, induction time, and metastable zone width (MSZW) were determined using the favipiravir-acetonitrile system. The excellence of the nucleation potential model (N-model) and the optimization model (N(T)-model and n(T)-model) was evaluated by comparing the model-predicted MSZWs with the experimental MSZWs. The results indicated that the optimized model accuracy was enhanced by 4–7% compared to the nucleation potential model (N-model). Additionally, three systems were compared, including dicyandiamide in water (narrow MSZW), butyl paraben in ethanol (narrow MSZW), and l-ascorbic acid in water (wide MSZW). The optimized model accuracy was enhanced by 23–29, 23–29, and 51–52%, respectively. The results show that the N(T)-model and the n(T)-model have some prediction accuracy improvement for the narrow MSZW system. In addition, for the wide MSZW system, the model has significant accuracy improvement.

Dissecting and understanding the cancer ecosystem, especially that around the tumor margins, which have strong implications for tumor cell infiltration and invasion, are essential for exploring the mechanisms of tumor metastasis and developing effective new treatments. Using a novel tumor border scanning and digitization model enabled by nanoscale resolution-SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we identified a 500 µm-wide zone centered around the tumor border in patients with liver cancer, referred to as “the invasive zone”. We detected strong immunosuppression, metabolic reprogramming, and severely damaged hepatocytes in this zone. We also identified a subpopulation of damaged hepatocytes with increased expression of serum amyloid A1 and A2 (referred to collectively as SAAs) located close to the border on the paratumor side. Overexpression of CXCL6 in adjacent malignant cells could induce activation of the JAK-STAT3 pathway in nearby hepatocytes, which subsequently caused SAAs’ overexpression in these hepatocytes. Furthermore, overexpression and secretion of SAAs by hepatocytes in the invasive zone could lead to the recruitment of macrophages and M2 polarization, further promoting local immunosuppression, potentially resulting in tumor progression. Clinical association analysis in additional five independent cohorts of patients with primary and secondary liver cancer (n= 423) showed that patients with overexpression of SAAs in the invasive zone had a worse prognosis. Further in vivo experiments using mouse liver tumor models in situ confirmed that the knockdown of genes encoding SAAs in hepatocytes decreased macrophage accumulation around the tumor border and delayed tumor growth. The identification and characterization of a novel invasive zone in human cancer patients not only add an important layer of understanding regarding the mechanisms of tumor invasion and metastasis, but may also pave the way for developing novel therapeutic strategies for advanced liver cancer and other solid tumors.

The induction times at supersaturations of 1.15–1.24 and the metastable zone widths (MSZWs) with cooling rates of 6.0–30.0 K/h have been determined in the system of dicyandiamide and water. A model based on the accumulation of nucleation potential, derived from the classical nucleation theory, has been applied to estimate the critical nucleation potential and pre-exponential factor. The estimated values based on the experimental induction times or based on the experimental MSZWs were fairly consistent with each other. The pre-exponential factor was assumed to be constant in the model, while the modifications of the pre-exponential factor, dependent on the supersaturation, have been introduced to the model for more consistent between the estimations based on the induction time and the MSZW.

Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm. Using the features in the BFM associated with cardiometabolic health, carotid plaques can be predicted accurately in an independent dataset. We developed a model by comparing individual data with the health baseline in BFMsto assess health status (BFM-ash). Then we apply the model to chronic patients and modify the BFM-ash model to assess the effects of consuming grape seed extract as a dietary supplement. Finally, anomalous BFMs are identified for each subject. Our BFMs and BFM-ash model have huge prospects for application in precision health assessment.

A new approach to measure the 3D profile of a texture object is proposed utilizing light field imaging, in which three key steps are required: a disparity map is first obtained by detecting the slopes in the epipolar plane image with the multilabel technique; the intrinsic parameters of the light field camera are then extracted by camera calibration; at last, the relationship between disparity values and real distances is built up by depth calibration. In the last step, a linear calibration method is proposed to achieve accurate results. Furthermore, the depth error is also investigated and compensated for by reusing the checkerboard pattern. The experimental results are in good agreement with the 3D models, and also indicate that the light field imaging is a promising 3D measurement technique.

Biological age (BA) has been proposed to evaluate the aging status instead of chronological age (CA). Our study shows evidence that there might be multiple “clocks” within the whole-body system: systemic aging drivers/clocks overlaid with organ/tissue-specific counterparts. We utilize multi-omics data, including clinical tests, immune repertoire, targeted metabolomic molecules, gut microbiomes, physical fitness examinations, and facial skin examinations, to estimate the BA of different organs (e.g., liver, kidney) and systems (immune and metabolic system). The aging rates of organs/systems are diverse. People’s aging patterns are different. We also demonstrate several applications of organs/systems BA in two independent datasets. Mortality predictions are compared among organs' BA in the dataset of the United States National Health and Nutrition Examination Survey. Polygenic risk score of BAs constructed in the Chinese Longitudinal Healthy Longevity Survey cohort can predict the possibility of becoming centenarian.

Experimental large-scale screens for drug repositioning are limited by restriction to in vitroconditions and lack of applicability to real human conditions. Here, we developed an in silicoscreen in human in vivoconditions using a reference of single gene mutations’ non-tissue-specific “core transcriptome signatures” (CSs) of 8,476 genes generated from the TCGA database. We developed the core-signature drug-to-gene (csD2G) software to scan 3,546 drug treatment profiles against the reference signatures. csD2G significantly outperformed conventional cell line-based gene perturbation signatures and existing drug-repositioning methods in both coverage and specificity. We highlight this with 3 demonstrated applications: (1) repositioned category of psychiatric drugs to inhibit the TGF-β pathway; (2) antihypertensive calcium channel blockers predicted to activate AMPK and inhibit AKT pathways, and validated by clinical electronic medical records; and (3) 7 drugs predicted and validated to selectively target the AKT-FOXO and AMPK pathways and thus regulate worm lifespan.