Integration of Pre-trained Protein Language Models into Geometric Deep Learning Networks

Geometric deep learning has recently achieved great success in non-Euclidean domains, and learning on 3D structures of large biomolecules is emerging as a distinct research area. However, its efficacy is largely constrained due to the limited quantity of structural data. Meanwhile, protein language models trained on substantial 1D sequences have shown burgeoning capabilities with scale in a broad range of applications. Several previous studies consider combining these different protein modalities to promote the representation power of geometric neural networks, but fail to present a comprehensive understanding of their benefits. In this work, we integrate the knowledge learned by well-trained protein language models into several state-of-the-art geometric networks and evaluate a variety of protein representation learning benchmarks, including protein-protein interface prediction, model quality assessment, protein-protein rigid-body docking, and binding affinity prediction. Our findings show an overall improvement of 20% over baselines. Strong evidence indicates that the incorporation of protein language models' knowledge enhances geometric networks' capacity by a significant margin and can be generalized to complex tasks

Contactless Electrocardiogram Monitoring with Millimeter Wave Radar

The electrocardiogram (ECG) has always been an important biomedical test to diagnose cardiovascular diseases. Current approaches for ECG monitoring are based on body attached electrodes leading to uncomfortable user experience. Therefore, contactless ECG monitoring has drawn tremendous attention, which however remains unsolved. In fact, cardiac electrical-mechanical activities are coupling in a well-coordinated pattern. In this paper, we achieve contactless ECG monitoring by breaking the boundary between the cardiac mechanical and electrical activity. Specifically, we develop a millimeter-wave radar system to contactlessly measure cardiac mechanical activity and reconstruct ECG without any contact in. To measure the cardiac mechanical activity comprehensively, we propose a series of signal processing algorithms to extract 4D cardiac motions from radio frequency (RF) signals. Furthermore, we design a deep neural network to solve the cardiac related domain transformation problem and achieve end-to-end reconstruction mapping from RF input to the ECG output. The experimental results show that our contactless ECG measurements achieve timing accuracy of cardiac electrical events with median error below 14ms and morphology accuracy with median Pearson-Correlation of 90% and median Root-Mean-Square-Error of 0.081mv compared to the groudtruth ECG. These results indicate that the system enables the potential of contactless, continuous and accurate ECG monitoring

Oscillation of mineral compositions in Core SG-1b, western Qaidam Basin, NE Tibetan Plateau

Uplift of the Tibetan Plateau since the Late Miocene has greatly affected the nature of sediments deposited in the Qaidam Basin. However, due to the scarcity of continuously dated sediment records, we know little about how minerals responded to this uplift. In order to understand this response, we here present results from the high-resolution mineral profile from a borehole (7.3–1.6 Ma) in the Basin, which shows systematic oscillations of various evaporite and clay minerals that can be linked to the variation of regional climate and tectonic history. In particular, x-ray diffraction (XRD) analyses show that carbonate minerals consist mainly of calcite and aragonite, with minor ankerite and dolomite. Evaporates consist of gypsum, celesite and halite. Clay minerals are principally Fe-Mg illite, mixed layers of illite/smectite and chlorite, with minor kaolinite and smectite. Following implications can be drawn from the oscillations of these minerals phases: (a) the paleolake was brackish with high salinity after 7.3 Ma, while an abrupt change in the chemical composition of paleolake water (e.g. Mg/Ca ratio, SO4 2− concentration, salinity) occurred at 3.3 Ma; (b) the three changes at ~6.0 Ma, 4.5–4.1 Ma and 3.3 Ma were in response to rapid erosions/uplift of the basin; (c) pore water or fluid was Fe/Mg-rich in 7.3–6.0 Ma, Mg-rich in 6.0–4.5 Ma, and K-rich in 4.1–1.6 Ma; and (d) evaporation rates were high, but weaker than today’s

InstructBio: A Large-scale Semi-supervised Learning Paradigm for Biochemical Problems

In the field of artificial intelligence for science, it is consistently an essential challenge to face a limited amount of labeled data for real-world problems. The prevailing approach is to pretrain a powerful task-agnostic model on a large unlabeled corpus but may struggle to transfer knowledge to downstream tasks. In this study, we propose InstructMol, a semi-supervised learning algorithm, to take better advantage of unlabeled examples. It introduces an instructor model to provide the confidence ratios as the measurement of pseudo-labels' reliability. These confidence scores then guide the target model to pay distinct attention to different data points, avoiding the over-reliance on labeled data and the negative influence of incorrect pseudo-annotations. Comprehensive experiments show that InstructBio substantially improves the generalization ability of molecular models, in not only molecular property predictions but also activity cliff estimations, demonstrating the superiority of the proposed method. Furthermore, our evidence indicates that InstructBio can be equipped with cutting-edge pretraining methods and used to establish large-scale and task-specific pseudo-labeled molecular datasets, which reduces the predictive errors and shortens the training process. Our work provides strong evidence that semi-supervised learning can be a promising tool to overcome the data scarcity limitation and advance molecular representation learning

Effects of the stem extracts of Schisandra glaucescens Diels on collagen-induced arthritis in Balb/c mice

Ethnopharmacological relevance Schisandra glaucescens Diels (SGD) is used in a subclass of traditional Chinese medicine known as “Tujia drugs”. It has been long used for the treatment of rheumatoid arthritis (RA), cough with dyspnea, spontaneous sweating, night sweating, chronic diarrhea, and neurasthenia. As a woody liana growing in mountain jungles at the altitudes of 750–1800 m, it is mainly distributed in Sichuan and Hubei Provinces of China. Aim of the study To evaluate the antiarthritic activity of acetate (EA) and n-butanol (Bu) fractions of SGD extract on a collagen-induced arthritis mice model. Materials and methods Acute toxicity of EA and Bu fractions of SGD extract was evaluated by gavage on normal mice. Pharmacological investigations were conducted on arthritis male Balb/c mice. The animal model was induced by immunization with type II bovine collagen (CII) on the 1st and the 14th day of the experimental schedule. EA fraction (104, 312, 936 mg/kg), Bu fraction (156, 469, 1407 mg/kg) of SGD extract was orally administered every two days since the 15th day for 3 weeks. Progression of edema in the paws was measured using a vernier caliper every 3 days since the 10th day. At the end of the experiment, the spleen index and histological changes of the hind knee joints were investigated. Additionally, to explore the possible antirheumatic mechanisms of the EA and Bu fractions, ELISA was carried out to analyze TNF-α, IL-10, IL-6 and IL-1β in the serum. Results The half lethal doses of both EA and Bu fractions were much higher than the dose administered in the pharmacological investigations. Oral administration of EA fraction and Bu fraction of SGD extract significantly and does-dependently inhibited type ІІ collagen induced arthritis (CIA) in mice, as indicated by the effects on paws swelling and spleen index. Histopathological examinations demonstrated that SGD effectively protected the bones and cartilages of knee joints from erosion, lesion and deformation. Besides, the serum concentrations of cytokines TNF-α, IL-1β and IL-6 were significantly lower than the ones from the vehicle control group. Respectively, while cytokine IL-10 was remarkably higher compare with the vehicle control group. Conclusions SGD might be a safe and effective candidate for the treatment of RA, and deserves further investigation on the chemical components in both EA and Bu fractions of SGD extract

What we know about grief intervention: a bibliometric analysis

BackgroundGrief is a natural and individualized response to different losses, but if grief persists or becomes pathological, professional interventions are required. Grief and corresponding interventions have received increasing attention, as the related concepts have been incorporated into the DSM-5 and ICD-11. Therefore, we conducted a bibliometric analysis to explore the developments in the field of grief intervention research.MethodsArticles on grief interventions were systematically searched and screened from the Web of Science Core Collection. The retrieved data were analyzed and visualized using VOSviewer and Bibliometrix software for journals, authors, institutions, countries, references, and keywords.ResultsA total of 9,754 articles were included. The number of articles on grief interventions has increased significantly each year since 1990. Death Studies was the journal that published the most articles in this field. We identified 25,140 authors contributed to this research area and these authors were from 123 countries and 6,630 institutions. Boelen PA secured the first position in article production, Columbia University emerged as the most productive affiliation and the United States was the foremost leading in grief intervention research. The prevalent keywords utilized in this field comprised bereavement, grief, death, depression, and palliative care.ConclusionThe quantity of publications regarding grief interventions is increasing. Although most prior studies have focused on mortality, grief, and health, emerging themes such as COVID-19, grief among workers, and disfranchised grief have drawn increasing attention in recent years. Future studies may focus on investigating the complexities and challenges of grief, including its underlying mechanisms and impact on mental well-being

Strategies in activating lymphatic system on symptom distress and health-related quality of life in patients with heart failure: secondary analysis of a pilot randomized controlled trial

BackgroundAbnormal interstitial fluid accumulation remains the major cause for patients with heart failure (HF) to endure a myriad of distressing symptoms and a decline in their health-related quality of life (HRQoL). The lymphatic system is essential in regulating fluid balance within the interstitial compartment and has recently been recognized as an important target for the prevention and mitigation of congestion. This study aimed to investigate the effects of exercises in activating lymphatic system on symptom distress and HRQoL among patients with HF.Methods and resultsThis was a pre-determined, secondary analysis of the TOLF-HF [The-Optimal-Lymph-Flow for Heart Failure (TOLF-HF)] study, a two-arm pilot randomized controlled trial evaluating the preliminary effects of the lymphatic exercise intervention in enhancing interstitial decongestion among patients with HF. Participants were randomized to receive either a four-week TOLF-HF program in addition to standard care or standard care alone. The Chinese version of the Minnesota Living with Heart Failure Questionnaire (MLHFQ) was employed to measure symptom distress and HRQoL before and after the intervention. Data analyses included descriptive statistics, the independent sample t-test, Pearson’s chi-square test, the Mann-Whitney U test, and covariance analysis. Of the 66 patients enrolled, 60 completed the study. The study results exhibited that the TOLF-HF intervention were effective in alleviating both physical and psychological symptom distress. The intervention group yielded significantly lower MLHFQ total scores in comparison to the control group. The odd ratio of achieving meaningful improvement in HRQoL in TOLF-HF group was 2.157 times higher than those in the control group.ConclusionsThe TOLF-HF program focusing on activating lymphatic system was effective in alleviating physical and psychological symptom distress as well as improving HRQoL for patients with HF. The tolerability, feasibility, and effectiveness of the TOLF-HF intervention make it a promising intervention for patients to manage HF.Clinical Trial Registrationhttp://www.chictr.org.cn/index.aspx, identifier (ChiCTR2000039121)