Bilateral meibomian gland morphological alterations in unilateral herpes simplex keratitis based on artificial intelligence analysis.

Aim: To explore whether unilateral herpes simplex keratitis (HSK) can cause morphological changes of bilateral meibomian glands (MGs) based on artificial intelligence (AI) analytical system.

Methods: In the retrospective study, 29 patients with unilateral HSK and 29 participants matched in terms of age and sex were included as control group. Meibographic images of the upper eyelid using Keratograph 5M and assessed ocular surface parameters including tear meniscus height and tear break-up time.

Structural-color meta-nanoprinting embedding multi-domain spatial light field information.

Recently, multifunctional metasurface has showcased its powerful functionality to integrate nanoprinting and holography, and display ultracompact meta-images in near- and far-field simultaneously. Herein, we propose a tri-channel metasurface which can further extend the meta-imaging ranges, with three independent images located at the interface, Fresnel and Fourier domains, respectively. Specifically, a structural-color nanoprinting image is decoded right at the interface of the metasurface, enabled by varying the dimensions of nanostructures; a Fresnel holographic image and another Fourier holographic image are present at the Fresnel and Fourier (far-field) domains, respectively, enabled by geometric phase.

Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory.

Land use in urban agglomerations is the main source of carbon emissions, and reducing them and improving land use efficiency are the keys to achieving sustainable development goals (SDGs). To advance the literature on densely populated cities and highly commercialized regions, this research evaluates the total-factor carbon emission efficiency index (TCEI) of 27 cities in China's Yangtze River Delta (YRD) urban agglomeration at different stages from 2011 to 2020 using two-stage dynamic data envelopment analysis (DEA). The study carries out regression analysis and a long-short-term memory model (LSTM) to respectively filter out the factors and predict TCEI.

Roles of Necroptosis, Apoptosis, and Inflammation in Colorectal Carcinogenesis: A Longitudinal Human Study.

Necroptosis triggers an inflammatory cascade associated with antimicrobial defense. No prospective human study has yet explored the role of necroptosis in colorectal cancer (CRC) development. We conducted quantitative analysis of biomarkers for necroptosis (transient receptor potential melastatin 7 (TRPM7) and phosphorylated mixed lineage kinase-like protein (pMLKL)), inflammation (cyclooxygenase-2, COX-2), apoptosis (BAX and TUNEL), and cell proliferation (Ki67).

Tri-channel metasurface fusion of continuously varying gray levels for nanoprinting and holographic displays.

Metasurfaces are extensively utilized in nanoprinting and hologram fusion displays due to their superior wavefront shaping capabilities. However, the creation of continuously varying grayscale images based on conventional Malus's law necessitates the use of at least one polarizer for observation, which compromises the metasurface's integration. In this study, inspired by the Jacobi-Anger expansion, we propose a tri-channel metasurface to establish three independent information channels for simultaneous grayscale nanoprinting and polarization multiplexed holography.

Comparative analysis of circadian lighting models: melanopic illuminance vs. circadian stimulus.

The influence of light exposure on human circadian rhythms has been widely recognized. This effect is mediated by a phototransduction process projected by the intrinsically photosensitive retinal ganglion cells (ipRGCs). The process also involves signal inputs from visual photoreceptors.

CRBPSA: CircRNA-RBP interaction sites identification using sequence structural attention model.

Background: Due to the ability of circRNA to bind with corresponding RBPs and play a critical role in gene regulation and disease prevention, numerous identification algorithms have been developed. Nevertheless, most of the current mainstream methods primarily capture one-dimensional sequence features through various descriptors, while neglecting the effective extraction of secondary structure features. Moreover, as the number of introduced descriptors increases, the issues of sparsity and ineffective representation also rise, causing a significant burden on computational models and leaving room for improvement in predictive performance.

Precision DNA methylation typing via hierarchical clustering of Nanopore current signals and attention-based neural network.

Decoding DNA methylation sites through nanopore sequencing has emerged as a cutting-edge technology in the field of DNA methylation research, as it enables direct sequencing of native DNA molecules without the need for prior enzymatic or chemical treatments. During nanopore sequencing, methylation modifications on DNA bases cause changes in electrical current intensity. Therefore, constructing deep neural network models to decode the electrical signals of nanopore sequencing has become a crucial step in methylation site identification.

Adversarial regularized autoencoder graph neural network for microbe-disease associations prediction.

Background: Microorganisms inhabit various regions of the human body and significantly contribute to numerous diseases. Predicting the associations between microbes and diseases is crucial for understanding pathogenic mechanisms and informing prevention and treatment strategies. Biological experiments to determine these associations are time-consuming and costly.

GBMPhos: A Gating Mechanism and Bi-GRU-Based Method for Identifying Phosphorylation Sites of SARS-CoV-2 Infection.

Phosphorylation, a reversible and widespread post-translational modification of proteins, is essential for numerous cellular processes. However, due to technical limitations, large-scale detection of phosphorylation sites, especially those infected by SARS-CoV-2, remains a challenging task. To address this gap, we propose a method called GBMPhos, a novel method that combines convolutional neural networks (CNNs) for extracting local features, gating mechanisms to selectively focus on relevant information, and a bi-directional gated recurrent unit (Bi-GRU) to capture long-range dependencies within protein sequences.

Peptide-functionalized gold nanoparticles for boron neutron capture therapy with the potential to use in Glioblastoma treatment.

Glioblastoma is a highly aggressive glioma with limited treatment options. Boron neutron capture therapy (BNCT) offers a promising approach for refractory cancers, utilizing boron-10 (B) and thermal neutrons to generate cytotoxic particles. Effective BNCT depends on selective targeting and retention of B in tumors.

Self-Healing Hydrogel Resulting from the Noncovalent Interaction between Ropivacaine and Low-Molecular-Weight Gelator Sodium Deoxycholate Achieves Stable and Endurable Local Analgesia in Vivo.

Regional analgesia based on the local anesthetic ropivacaine plays a crucial role in postoperative pain management and recovery; however, the short duration of analgesia limits its clinical potential. Various drug delivery systems such as microparticles and lipid carriers have been used to prolong the analgesic effect, yet most of them are prone to abrupt release from the site of administration or have poor analgesic effects of less than 48 h, which fail to meet the needs of postoperative analgesia. In this study, a low-molecular-weight gelator sodium deoxycholate-based hydrogel loaded with ropivacaine (DC-ROP gel) was designed for long-acting analgesia.

Two novel compounds inhibit Flavivirus infection and by targeting lipid metabolism.

Unlabelled: Flavivirus infection capitalizes on cellular lipid metabolism to remodel the cellular intima, creating a specialized lipid environment conducive to viral replication, assembly, and release. The Japanese encephalitis virus (JEV), a member of the genus, is responsible for significant morbidity and mortality in both humans and animals. Currently, there are no effective antiviral drugs available to combat JEV infection.

Metabolic Labeling and Digital Microfluidic Single-Cell Sequencing for Single Bacterial Genotypic-Phenotypic Analysis.

Accurate assessment of phenotypic and genotypic characteristics of bacteria can facilitate comprehensive cataloguing of all the resistance factors for better understanding of antibiotic resistance. However, current methods primarily focus on individual phenotypic or genotypic profiles across different colonies. Here, a Digital microfluidic-based automated assay for whole-genome sequencing of single-antibiotic-resistant bacteria is reported, enabling Genotypic and Phenotypic Analysis of antibiotic-resistant strains (Digital-GPA).

[Advances in using artificial intelligence for predicting protein-ligand binding affinity].

The binding of proteins and ligands is a crucial aspect of life processes. The calculation of the protein-ligand binding affinity (PLBA) offers valuable insights into protein function, drug screening targets protein receptors, and enzyme modifications. In recent years, artificial intelligence (AI) has experienced rapid advancements, becoming widely used in PLBA prediction.

Nitrous oxide abuse in a 21-year-old female: a case report and review of literature.

The abuse of nitrous oxide (NO) poses a substantial public health challenge. In many countries, including China, regulations governing the utilization and accessibility to NO remain ambiguous, particularly within the food industry. Here, we report a case of a 21-year-old female who presented with symptoms of subacute combined degeneration (SCD) of the spinal cord due to NO abuse.

The Role of Occipitotemporal Network for Speed-Reading: An fMRI Study.

The activity of occipitotemporal regions involved in linguistic reading processes, such as the ventral occipitotemporal cortex (vOT), is believed to exhibit strong interactions during higher-order language processing, specifically in the connectivity between the occipital gyrus and the temporal gyrus. In this study, we utilized functional magnetic resonance imaging (fMRI) with psychophysiological interaction (PPI) and dynamic causal modeling (DCM) to investigate the functional and effective connectivity in the occipitotemporal network during speed reading. We conducted the experiment with native Japanese speakers who underwent and without speed-reading training and subsequently performed established reading tasks at different speeds (slow, medium, and fast) while undergoing 3-Tesla Siemens fMRI.

The efficacy of repetitive transcranial magnetic stimulation in postherpetic neuralgia: a meta-analysis of randomized controlled trials.

Purpose: This systematic review and meta-analysis aimed to evaluate the efficacy of repetitive transcranial magnetic stimulation (rTMS) in postherpetic neuralgia (PHN).

Methods: Through an extensive search in four databases until October 2023, we selected five randomized controlled trials adhering to our specific criteria, involving 257 patients in total. For continuous outcomes, the standardized mean difference (SMD) was calculated.

Quantitative Assessment of Lid Margin Vascularity Using Swept-Source Optical Coherence Tomography Angiography.

Purpose: To evaluate the ability of swept-source optical coherence tomography angiography (SS-OCTA) to assess lid margin vascularity.

Methods: This prospective, cross-sectional trial enrolled 125 participants, including 15 control subjects and 110 meibomian gland dysfunction (MGD) patients. Lid margin blood flow density (LMBFD) was obtained using SS-OCTA.

Associations between traditional Chinese medicine body constitution and obesity risk among US adults.

Background: Traditional Chinese medicine (TCM) body constitution (BC), primarily determined by physiological and clinical characteristics, is an important process for clinical diagnosis and treatment and play a critical role in precision medicine in TCM. The purpose of the study was to explore whether the distributions of BC types differed by obesity status.

Methods: We conducted a study to evaluate BC type in US population during 2012-2016.

LncARSR promotes glioma tumor growth by mediating glycolysis through the STAT3/HK2 axis.

Background: Glioma represents the predominant malignant brain tumor. This investigation endeavors to elucidate the impact and prospective mechanisms of glycolysis-related lncARSR on glioma.

Methods: LncARSR level was assessed in normal glial cells and glioma cells.