BioMedGraphica: An All-in-One Platform for Biomedical Prior Knowledge and Omic Signaling Graph Generation.

Artificial intelligence (AI) is revolutionizing scientific discovery because of its super capability, following the neural scaling laws, to integrate and analyze large-scale datasets to mine knowledge. Foundation models, large language models (LLMs) and large vision models (LVMs), are among the most important foundations paving the way for general AI by pre-training on massive domain-specific datasets. Different from the well annotated, formatted and integrated large textual and image datasets for LLMs and LVMs, biomedical knowledge and datasets are fragmented with data scattered across publications and inconsistent databases that often use diverse nomenclature systems in the field of AI for Precision Health and Medicine (AI4PHM).

Anti-Inflammatory Effects of Cs-HK1 Fungus Exopolysaccharide on Lipopolysaccharide-Stimulated Macrophages via the TLR4/MyD88/NF-κB Pathway.

Chronic inflammation is a common factor in the pathological processes of multiple human diseases. EPS-LM, an exopolysaccharide (EPS) from the Cordyceps sinensis fungus Cs-HK1, has shown notable anti-inflammatory activities in previous studies. This study aimed to investigate the major signaling events mediating the anti-inflammatory effects of EPS-LM in lipopolysaccharide (LPS)-stimulated RAW 264.

An efficient leakage power optimization framework based on reinforcement learning with graph neural network.

Threshold voltage ( ) assignment is convenient for leakage optimization due to the exponential relation between leakage power and by swapping logic cells without routing effort. However, it poses great challenge in large scale circuit design as an NP-hard problem. Machine learning-based approaches have been proposed to solve this problem, aiming to achieve well tradeoff between leakage power reduction and runtime speed up without new induced timing violation.

Revealing the link between gut microbiota and brain tumor risk: a new perspective from Mendelian randomization.

Background: Recent studies have shown that gut microbiota may be related to the occurrence of brain tumors, but direct evidence is lacking. This study used the Mendelian randomization study (MR) method to explore the potential causal link between gut microbiota and brain tumors.

Method: We analyzed the genome-wide association data between 211 gut microbiota taxa and brain tumors, using the largest existing gut microbiota Genome-Wide Association Studies meta-analysis data (n=13266) and combining it with brain tumor data in the IEU OpenGWAS database.

Virus-Mimetic Extracellular-Vesicle Vaccine Boosts Systemic and Mucosal Immunity via Immune Recruitment.

Mucosal vaccines can prevent viruses from infecting the respiratory mucosa, rather than only curtailing infection and protecting against the development of disease symptoms. The SARS-CoV-2 spike receptor-binding domain (RBD) is a compelling vaccine target but is undermined by suboptimal mucosal immunogenicity. Here, we report a SARS-CoV-2-mimetic extracellular-vesicle vaccine developed using genetic engineering and dendritic cell membrane budding.

Immunogenicity and safety of a self-assembling ZIKV nanoparticle vaccine in mice.

Zika virus (ZIKV) is a mosquito-borne flavivirus that highly susceptibly causes Guillain-Barré syndrome and microcephaly in newborns. Vaccination is one of the most effective measures for preventing infectious diseases. However, there is currently no approved vaccine to prevent ZIKV infection.

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading.

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data.

[Expression of SCD1 in TFE3-rRCC and its effect on proliferation and migration].

Objective: To investigate the expression of SCD1 in TFE3-rRCC and its effect on the proliferation and migration of TFE3-rRCC cells.

Methods: GEPIA database was used to analyze the expression level of SCD1 in different tumors and its effect on the prognosis of patients. The expression levels of SCD1 in TFE3-rRCC patients and cell lines UOK109 and UOK120 were detected by QPCR and Western blot.

The combined effect of MTHFR C677T and A1298C polymorphisms on the risk of digestive system cancer among a hypertensive population.

Background And Purpose: The enzyme methylenetetrahydrofolate reductase (MTHFR) plays a crucial role in directing folate species towards nucleotide synthesis or DNA methylation. The MTHFR polymorphisms C677T and A1298C have been linked to cancer susceptibility, but the evidence supporting this association has been equivocal. To investigate the individual and joint associations between MTHFR C677T, A1298C, and digestive system cancer in a Chinese hypertensive population, we conducted a population-based case-control study involving 751 digestive system cancer cases and one-to-one matched controls from the China H-type Hypertension Registry Study (CHHRS).

Direct and Continuous Monitoring of Multicomponent Antibiotic Gentamicin in Blood at Single-Molecule Resolution.

Point-of-care monitoring of small molecules in biofluids is crucial for clinical diagnosis and treatment. However, the inherent low degree of recognition of small molecules and the complex composition of biofluids present significant obstacles for current detection technologies. Although nanopore sensing excels in the analysis of small molecules, the direct detection of small molecules in complex biofluids remains a challenge.

Direct single-molecule detection of CoA-SH and ATP by the membrane proteins TMEM120A and TMEM120B.

Membrane proteins are vital resources for developing biosensors. TMEM120A is a membrane protein associated with human pain transmission and lipid metabolism, and recent studies have demonstrated its ability to transport ions and bind to coenzyme A (COA-SH), indicating its potential to develop into a single-molecule sensor based on electrical methods. In this study, we investigated the ion transport properties of TMEM120A and its homolog TMEM120B on an artificial lipid bilayer using single-channel recording.

Increased serum SGLT2 and its potential diagnostic and prognostic value in patients with acute ischemic stroke.

Background: Recently acquired data suggests that sodium-glucose cotransporter-2 (SGLT2) may be a therapeutic target for cerebral ischemia. The specific impact of SGLT2 in acute ischemic stroke (AIS) remains unknown. We aimed to explore the levels of SGLT2 in AIS patients and its association with functional prognosis.

Correlation Between Oncostatin M and Acute Ischemic Stroke: A Case-Control Study.

Background: The expression of oncostatin M (OSM) has been studied in various diseases related to inflammatory response, but its implementation in acute ischemic stroke (AIS) remains to be explored.  Objective: The objective of this study is to assess the correlation between serum OSM expression and various aspects of AIS in a clinical setting.

Materials And Method: A single-centered case-control study was performed in the First Affiliate Hospital of Chongqing Medical University from October 2020 to March 2021.

Layered hybrid PAM-DMT for IM/DD OWC systems.

Traditional pulse-amplitude-modulated discrete multitone modulation (PAM-DMT) suffers from poor overall performance of spectral and power efficiencies in optical wireless communication (OWC) systems. We propose layered hybrid PAM-DMT (LHPAM-DMT) to utilize more subcarriers to improve the performance. The real part of frequency domain signal is divided into several layers and symmetry biases are added in time domain to generate real-valued and nonnegative signals for intensity modulation with direct detection (IM/DD) OWC systems.

LncRNA like NMRK2 mRNA functions as a key molecular scaffold to enhance mitochondrial respiration of NONO-TFE3 rearranged renal cell carcinoma in an NAD kinase-independent manner.

Background: NONO-TFE3 rearranged renal cell carcinoma (NONO-TFE3 rRCC) is one of a subtype of TFE3 rRCCs with high malignancy and poor prognosis. Compared with clear cell RCC, NONO-TFE3 rRCC shows a preference for mitochondrial respiration. We recently identified that the upregulation of nicotinamide ribokinase 2 (NMRK2) was associated with enhanced mitochondrial respiration and tumor progression in TFE3 rRCC.

Experimental study on underwater continuous-variable quantum key distribution with discrete modulation.

We experimentally demonstrated the feasibility of an underwater continuous-variable quantum key distribution (CV-QKD) system based on four-state protocol, which is promising to guarantee the unconditionally secure underwater wireless optical communication. CV-QKD parameter estimation is performed after transmitting quantum coherent signal from Alice to Bob through a water tank. The secure key rate under collective attack of the demonstrated CV-QKD system is estimated as 22.

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of recurrence is still high.

Fluorescent concentrator based MISO-NOMA for visible light communications.

The experimental realization of multiple-input single-output (MISO) in visible light communication (VLC) has always been difficult due to dynamic channels, complex alignment, and limited capacity. We designed a quantum dot (QD) fluorescent concentrator combined with power domain multiplexing of a non-orthogonal multiple access (NOMA) scheme to provide an estimation-free MISO system. The system supports a large detection area of over 4 cm and a sum rate up to 120 Mbps over 2.

Controlled growth factor delivery system with osteogenic-angiogenic coupling effect for bone regeneration.

Objective: Bone regeneration involves a coordinated cascade of events that are regulated by several cytokines and growth factors, among which bone morphogenic protein-2 (BMP-2), vascular endothelial growth factor (VEGF) and fibroblast growth factor-2 (FGF-2) play important roles. In this study, we investigated the effects of dual release of the three growth factors on bone regeneration in femur defects.

Methods: A composite consisting of Gelatin microparticles loaded with VEGF/FGF-2 and poly(lactic-co-glycolic acid)-poly(ethylene glycol)-carboxyl (PLGA-PEG-COOH) microparticles loaded with BMP-2 encapsulated in a nano hydroxyapatite-poly actic-co-glycolic acid (nHA-PLGA) scaffold was prepared for the dual release of the growth factors.

ZooME: Efficient Melanoma Detection Using Zoom-in Attention and Metadata Embedding Deep Neural Network.

Melanoma detection is a crucial yet hard task for both dermatologists and computer-aided diagnosis (CAD). Many traditional machine learning algorithms including deep learning-based methods are employed for melanoma classification. However, more and more complex network architectures do not harvest a leap in model performance.