Exploring the therapeutic potential of psychedelics in treating substance use disorders.

Psychedelics, particularly psilocybin, have garnered significant attention as potential therapeutic tools for treating substance use disorders (SUDs), such as those related to alcohol, nicotine, heroin (an opioid), or cocaine. Traditional treatments often fall short, leading to high relapse rates and an urgent need for innovative approaches. This article explores the emerging role of psychedelics in SUDs therapy, highlighting their ability to disrupt maladaptive neural circuits, promote neuroplasticity, and facilitate profound psychological insights that address the root causes of SUDs.

The Effects of UV-LED Technology on the Quality of Ready-to-Eat Pomegranates: Epigenetic Indicators and Metabolomic Analysis.

Pomegranates are rich in nutrients and classified among ready-to-eat fruits and vegetables. Although this ready-to-eat produce offers convenience, it presents risks associated with pathogenic microorganisms, highlighting the need for pre-sale disinfection. Ultraviolet light-emitting diodes (UV-LEDs) constitute an innovative non-thermal processing technology for food products, offering reduced heat generation and lower energy consumption compared to traditional ultraviolet (UV) irradiation methods.

Advanced phase diversity method for RSA: wavefront detection and image fusion.

Rotating synthetic aperture (RSA) represents an emerging large-aperture imaging technology characterized by a rectangular aperture with a high aspect ratio. This configuration enables enhanced imaging resolution along the long-axis direction. During target observation, the aperture undergoes rotational maneuvers to acquire multi-angle imaging data, where subsequent fusion processing techniques facilitate high-quality image reconstruction.

Efficient capture and detoxification of gaseous arsenic trioxide from flue gas using silicomanganese alloy dust.

This study aims to develop efficient capture materials for gaseous arsenic trioxide (AsO(g)) that can prevent arsenic poisoning in selective catalytic reduction (SCR) systems and reduce atmospheric arsenic emissions from coal-fired power plants. One kind of metallurgical dust from a silicomanganese alloy plant (named as SiMnD) was found to be cost-effective and environmentally friendly for AsO(g) removal from flue gas for the first time. The sorbent showed excellent performance for gaseous arsenic trioxides capture with a good capacity of 13.

Quality Analysis of Peanut Oils and Peanut Diacylglycerol Edible Oils After Frying Using Raman Spectroscopy Combined with Oil Microscopy Method.

Background: The thermal stability and quality of fats change during oil-frying, directly impacting food safety and nutritional value; however, traditional analysis methods are time-consuming and complex.

Objective: This study aimed to develop a rapid monitoring protocol using a portable Raman spectrometer for peanut oils and peanut diacylglycerol (DAG) edible oils after frying zero to five times at 150°C.

Methods: Raman spectral data and the acid and peroxide values were determined for 48 oil test samples.

Clinical Characteristics of Postpartum Women With Hypoxia: A Retrospective Analysis of 92 Cases.

Purpose: Postpartum hypoxia is a significant concern among clinicians due to its association with fatal diseases such as amniotic fluid embolism. This study analyzed the clinical characteristics of patients with different etiologies of postpartum hypoxia.

Patients And Methods: Ninety-two postpartum cases with hypoxia, defined as oxygen saturation (SpO) < 95% within 48 h postpartum without supplemental oxygen inhalation, and 100 normal gravidas were enrolled.

Amidoxime-functionalized carboxymethylcellulose based porous hydrogels adsorbent fabricated from oyster shell stabilized Pickering emulsions for enhanced adsorption of Gd and Er.

Rare earth elements are strategic resources with diverse applications. However, during mining, wastewater rich in these elements is generated, leading to the loss of valuable rare-earth resources and poses a significant environmental threat. Therefore, a sustainable strategy for recycling rare earth elements from secondary sources is essential.

Utilizing Caenorhabditis Elegans as a Rapid and Precise Model for Assessing Amphetamine-Type Stimulants: A Novel Approach to Evaluating New Psychoactive Substances Activity and Mechanisms.

The surge of new psychoactive substances (NPS) poses significant public health challenges due to their unregulated status and diverse effects. However, existing in vivo models for evaluating their activities are limited. To address this gap, this study utilizes the model organism Caenorhabditis elegans (C.

Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking.

In order to address the issue of tracking errors of collision Caenorhabditis elegans, this research proposes an improved particle filter tracking method integrated with cultural algorithm. The particle filter algorithm is enhanced through the integration of the sine cosine algorithm, thereby facilitating uninterrupted tracking of the target C. elegans.

The Effects of Cold-Plasma Technology on the Quality Properties of Fresh-Cut Produce: A Review.

With improving economic conditions, consumer demand for fresh-cut produce is rising. The development of the fresh-cut industry has been hindered by pathogenic contamination and quality deterioration. Scientific communities have developed novel preservation technologies for fresh-cut produce.

Ion-Regulated Signal Amplification Optical Microfiber Interferometric DNA Sensor.

Genetic information sensors play a pivotal role in the biomedical field. The detection of deoxyribonucleic acid (DNA) is achieved experimentally using an optical microfiber interferometric sensor, which operates based on an ion-regulation sensitivity enhancement mechanism. The optical microfiber is fabricated by drawing optical fiber into a diameter of less than 10 μm via the melting and tapering technique.

A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulation during fruit storage poses a significant challenge to the citrus industry. This study used Raman spectroscopy coupled with machine learning algorithms to rapidly, non-destructively, and precisely detect citrus granulation. The investigation analyzed 969 Raman spectral data points, comprising 714 non-granulated and 255 granulated citrus samples.

Advanced Spore Identification: Single-Cell Raman Spectroscopy Combined with Self-Attention Mechanism-Guided Deep Learning.

(Nb) has been considered a dangerous pathogen, which can spread rapidly through free spores. Nowadays, pebrine disease caused by Nb spores is a serious threat to silkworms, causing huge economic losses in both the silk industry and agriculture every year. Thus, how to accurately identify living Nb spores at a single-cell level is greatly demanded.

Identification of Alzheimer's disease and vascular dementia based on a Deep Forest and near-infrared spectroscopy analysis method.

Alzheimer's disease (AD) and vascular dementia (VaD) typically do not exhibit distinct differences in clinical manifestations and auxiliary examination results, which leads to a high misdiagnosis rate. However, significant differences in treatment approaches and prognosis between these two diseases underscore the critical need for an accurate diagnosis of AD and VaD. In this study, serum samples from 33 patients with AD patients, 37 patients with VaD, and 130 healthy individuals were collected, employing near-infrared aquaphotomics technology in combination with deep learning for differential diagnoses.

A novel technology for rapid identification of hemp fibers by terahertz spectroscopy.

A novel method for the rapid identification of hemp fibers is proposed in this paper, utilizing terahertz time-domain spectroscopy (THz-TDS) combined with the LargeVis (LV) dimensionality reduction technique. This approach takes advantage of the strengths of THz-TDS while enhancing classification accuracy through LV. To verify the efficacy of this method, terahertz absorption spectral data from three types of hemp fibers were processed.

A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.

Purpose: Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models are commonly used in early drug discovery to predict drug properties. However, basic PBPK models require a large number of molecule-specific inputs from in vitro experiments, which hinders the efficiency and accuracy of these models.

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics.

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation.

Insights into enhanced immobilization of uranyl carbonate from seawater by Fe-doped MXene.

Extracting uranium from seawater not only reduces radioactive contamination in seawater but also provides a source of uranium energy. However, due to the low concentration of uranium in seawater and the high salinity of seawater, extraction of uranium from seawater is challenging. In this work, we demonstrated a simple strategy to synthesize Fe-doped MXene (Fe@TiCT) via a hydrothermal method and applied for uranium enrichment in seawater.

Application scenario-oriented molecule generation platform developed for drug discovery.

Design of molecules for candidate compound selection is one of the central challenges in drug discovery due to the complexity of chemical space and requirement of multi-parameter optimization. Here we present an application scenario-oriented platform (ID4Idea) for molecule generation in different scenarios of drug discovery. This platform utilizes both library or rule based and generative based algorithms (VAE, RNN, GAN, etc.

Early osteoarthritis diagnosis based on near-infrared spectroscopy combined with aquaphotomics.

Osteoarthritis (OA) is the most common joint disease and the leading cause of disability in elderly individuals. Despite rapid advances in imaging techniques, early OA diagnosis remains a clinical challenge. In the present study, the feasibility of early OA diagnosis was explored via near-infrared spectroscopy (NIRS) combined with aquaphotomics.

Identification of mercury species in coal combustion by-products from power plants using thermal desorption-atomic fluorescence spectrometry on-line coupling system.

Along with the environmental protection policies becoming strict in China, the air pollution control devices (especially selective catalytic reduction (SCR)) are widely equipped in coal-fired power plants. The installation and run of these devices will inevitably affect mercury (Hg) species distribution in coal fired by-products such like fly ash (FA) and gypsum. In this work, a new on-line coupling system based on atomic fluorescence spectrometry (AFS) with a home-made chromatographic workstation was successfully developed to identify Hg species through thermal programmed desorption (TPD).

Non-small-molecule therapeutics for drug addiction: From pharmaco-kinetics modulating to synthetic biology.

Drug addiction is a pervasive problem worldwide. It not only affects the abuser's life, but also poses a serious threat to public health. Accordingly, there is a strong demand for the development of novel and effective therapies for drug addiction.

Rapid detection of hepatitis B virus DNA level based on interval-point data fusion of infrared spectra.

Hepatitis B is an infectious disease cause by the hepatitis B virus (HBV). In recent years, HBV-DNA level clinically gets more attention for its detailed information than other serological markers. Unfortunately, common clinical method for HBV-DNA level detection is limited for its hours consuming.