Rapid detection of colored and colorless macro- and micro-plastics in complex environment via near-infrared spectroscopy and machine learning.

To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focused only on colored plastic fragments, ignoring colorless plastic fragments and the effects of different environmental media (backgrounds), thus underestimating their abundance. To address this issue, the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis (PLS-DA), extreme gradient boost, support vector machine and random forest classifier. The effects of polymer color, type, thickness, and background on the plastic fragments classification were evaluated. PLS-DA presented the best and most stable outcome, with higher robustness and lower misclassification rate. All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm. A two-stage modeling method, which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background, was proposed. The method presented an accuracy higher than 99% in different backgrounds. In summary, this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.

Efficient Permeable Monolithic Hybrid Tribo-Piezo-Electromagnetic Nanogenerator Based on Topological-Insulator-Composite.

Escalating energy demands of self-independent on-skin/wearable electronics impose challenges on corresponding power sources to offer greater power density, permeability, and stretchability. Here, a high-efficient breathable and stretchable monolithic hybrid triboelectric-piezoelectric-electromagnetic nanogenerator-based electronic skin (TPEG-skin) is reported via sandwiching a liquid metal mesh with two-layer topological insulator-piezoelectric polymer composite nanofibers. TPEG-skin concurrently extracts biomechanical energy (from body motions) and electromagnetic radiations (from adjacent appliances), operating as epidermal power sources and whole-body self-powered sensors. Topological insulators with conductive surface states supply notably enhanced triboelectric and piezoelectric effects, endowing TPEG-skin with a 288 V output voltage (10 N, 4 Hz), ∼3 times that of state-of-the-art devices. Liquid metal meshes serve as breathable electrodes and extract ambient electromagnetic pollution (±60 V, ±1.6 µA cm-2). TPEG-skin implements self-powered physiological and body motion monitoring and system-level human-machine interactions. This study provides compatible energy strategies for on-skin/wearable electronics with high power density, monolithic device integration, and multifunctionality.

Pipeline multi-type high consequence area identification based on mask R-CNN with fused attention mechanisms.

Identification of high consequence areas is an important task in pipeline integrity management. However, traditional identification methods are generally characterized by low efficiency, high cost and low accuracy. For this reason, this paper proposes a recognition method based on the improved algorithm Mask Region-based Convolutional Neural Network. Coordinate attention mechanism module is introduced into the traditional Mask R-CNN algorithm to improve the recognition accuracy and reduce the training time. For the identification results, GIS tools are utilized to establish high consequence zones along both sides of the pipeline, and the grade and scope of the high consequence zones are determined according to relevant specifications.In this paper, this method is used to identify the high-consequence area of a pipeline section in Guangdong Province, the results show that: 1, the improved algorithm in the identification of densely populated, geologic hazards, flammable and explosive high consequence zones of the average accuracy of the identification of 1.7%, 3.4%, 3.9%. 2, The method in this paper identifies 8 more building elements and 0.311 more kilometers of pipeline mileage compared to traditional identification methods. The method of this paper can provide a reference for the early identification of high consequence areas of pipelines.

Trajectories of hepatic steatosis and incidence of cardiovascular disease over a 29-year follow-up.

AIM: To examine the dynamic change in hepatic steatosis status during repeated assessments over time, and its potential impact on the risk of developing cardiovascular disease (CVD). METHODS: We assessed trajectories of hepatic steatosis and other metabolic disorders in 3134 middle-aged adults undergoing longitudinal assessment of ultrasonography during a pre-baseline period (1993-2009) in a population-based cohort study of liver health. Subsequently, we determined the association of hepatic steatosis trajectories with the incidence of CVD among 2185 CVD-free individuals, followed until 2021. Metabolic risk factors and cardiovascular events (including coronary heart disease and stroke) were determined through medical examination and linkage with nationwide health databases. RESULTS: We identified three discrete trajectories of hepatic steatosis according to changing pattern over time through group-based trajectory modeling: "stable, non-steatosis" (n = 1298), "intermittent" (n = 921), and "persistent steatosis" (n = 915). During the pre-baseline period, hepatic steatosis trajectories were associated with trajectories of developing diabetes and hypertension, and persistent steatosis (vs. other trajectories) was associated with higher risks and rapidly progressive disease patterns. At a median 13.6 years of follow-up, 629 CVD events occurred. A persistent (vs. non-steatosis: HR 1.44, 95% CI 1.17-1.76), but not intermittent, steatosis pattern predicted the future risk of CVD, after adjustment for age, sex, smoking, and obesity. This association was independent of genetic background, and remained after accounting for pre-baseline body-mass index, other cardiometabolic risk factors, Framingham risk score, medications, and hepatic fibrosis score. CONCLUSIONS: The persistence of hepatic steatosis is associated with trajectories of metabolic disorder development and increased risk of CVD. These data have important implications for practice and further research.

Enhancing Oxygen Activation Ability by Composite Interface Construction over a 2D Co3O4-Based Monolithic Catalyst for Toluene Oxidation.

Developing robust metal-based monolithic catalysts with efficient oxygen activation capacity is crucial for thermal catalytic treatment of volatile organic compound (VOC) pollution. Two-dimensional (2D) metal oxides are alternative thermal catalysts, but their traditional loading strategies on carriers still face challenges in practical applications. Herein, we propose a novel in situ molten salt-loading strategy that synchronously enables the construction of 2D Co3O4 and its growth on Fe foam for the first time to yield a unique monolithic catalyst named Co3O4/Fe-S. Compared to the Co3O4 nanocube-loaded Fe foam, Co3O4/Fe-S exhibits a significantly improved catalytic performance with a temperature reduction of 44 °C at 90% toluene conversion. Aberration-corrected scanning transmission electron microscopy and theoretical calculation suggest that Co3O4/Fe-S possesses abundant 2D Co3O4/Fe3O4 composite interfaces, which promote the construction of active sites (oxygen vacancy and Co3+) to boost oxygen activation and toluene chemisorption, thereby accelerating the transformation of reaction intermediates through Langmuir-Hinshelwood (L-H) and Mars-van Krevelen (MvK) mechanisms. Moreover, the growth mechanism reveals that 2D Co3O4/Fe3O4 composite interfaces are generated in situ in molten salt, inducing the growth of 2D Co3O4 onto the surface lattice of 2D Fe3O4. This study provides new insights into enhancing oxygen activation and opens an unprecedented avenue in preparing efficient monolithic catalysts for VOC oxidation.

Hounsfield units in assessing bone mineral density in ankylosing spondylitis patients with cervical fracture-dislocation.

BACKGROUND: Cervical spine fracture-dislocations in patients with ankylosing spondylitis (AS) are mostly unstable and require surgery. However, osteoporosis, one of the comorbidities for AS, could lead to detrimental prognoses. There are few accurate assessments of bone mineral density in AS patients. AIM: To analyze Hounsfield units (HUs) for assessing bone mineral density in AS patients with cervical fracture-dislocation. METHODS: The HUs from C2 to C7 of 51 patients obtained from computed tomography (CT) scans and three-dimensional reconstruction of the cervical spine were independently assessed by two trained spinal surgeons and statistically analyzed. Inter-reader reliability and agreement were assessed by interclass correlation coefficient. RESULTS: The HUs decreased gradually from C2 to C7. The mean values of the left and right levels were significantly higher than those in the middle. Among the 51 patients, 25 patients (49.02%) may be diagnosed with osteoporosis, and 16 patients (31.37%) may be diagnosed with osteopenia. CONCLUSION: The HUs obtained by cervical spine CT are feasible for assessing bone mineral density with excellent agreement in AS patients with cervical fracture-dislocation.

Combined strategies with PARP inhibitors for the treatment of BRCA wide type cancer.

Genomic instability stands out as a pivotal hallmark of cancer, and PARP inhibitors (PARPi) emerging as a groundbreaking class of targeted therapy drugs meticulously crafted to inhibit the repair of DNA single-strand breaks(SSB) in tumor cells. Currently, PARPi have been approved for the treatment of ovarian cancer, pancreatic cancer, breast cancer, and prostate cancer characterized by homologous recombination(HR) repair deficiencies due to mutations in BRCA1/2 or other DNA repair associated genes and acquiring the designation of breakthrough therapy. Nonetheless, PARPi exhibit limited efficacy in the majority of HR-proficient BRCA1/2 wild-type cancers. At present, the synergistic approach of combining PARPi with agents that induce HR defects, or with chemotherapy and radiotherapy to induce substantial DNA damage, significantly enhances the efficacy of PARPi in BRCA wild-type or HR-proficient patients, supporting extension the use of PARPi in HR proficient patients. Therefore, we have summarized the effects and mechanisms of the combined use of drugs with PARPi, including the combination of PARPi with HR defect-inducing drugs such as ATRi, CHKi, HR indirectly inducing drugs like VEGFRi, CDKi, immune checkpoint inhibitors and drugs instigating DNA damage such as chemotherapy or radiotherapy. In addition, this review discusses several ongoing clinical trials aimed at analyzing the clinical application potential of these combined treatment strategies.

Sensitivity enhancement of an all-solid FPE sensor via a programmable Vernier effect.

All-solid, open-cavity fiber optic Fabry-Perot etalon (FPE) sensors possess a wide static pressure detection range, yet their low sensitivity significantly restricts their application. This study proposes a programmable Vernier effect to improve the gas pressure sensitivity of FPE sensors substantially. By effectively modulating the emission spectrum of a widely tunable laser using a variable optical attenuator (VOA), the emission spectrum at different modulation lengths is expected to produce an optical beating in conjunction with the transmission spectrum of the FPE sensor, thereby realizing the Vernier effect. Experimental results indicate that by utilizing the proposed programmable Vernier effect, the pressure sensitivity of the FPE sensor has increased to -612.21 pm/kPa, demonstrating an amplification in sensitivity of approximately -153 times, consistent with the theoretical results. Owing to the programmable Vernier effect, which flexibly enhances the sensitivity of the FPE sensor, this sensor demonstrates considerable potential for gas pressure monitoring under various extreme conditions.

Single-bundle ACL combined with ALL reconstruction yields comparable outcomes in patients with varied anatomical risk factors for ACL graft failure.

BACKGROUND: Anterior cruciate ligament (ACL) graft failure is influenced by factors such as meniscal tears and tibial plateau slope. Combined anterior cruciate ligament (ACL) and anterolateral ligament (ALL) reconstruction has reduced failure rates; however, its efficacy in high-risk patients remains unclear. This study hypothesized that combined ACL and ALL reconstruction would yield similar clinical outcomes in patients with varying risks of ACL failure. PATIENTS AND METHODS: A total of 76 patients who underwent primary single-bundle ACL reconstruction combined with ALL reconstruction between June 2018 and June 2021 were included. The medial tibial slope (MTS), lateral tibial slope (LTS), and anterior tibial translation (ATT) were measured using magnetic resonance imaging and plain radiography of the knee joint. The meniscal lesions were assessed during surgery. Preoperative clinical assessments and final follow-up were conducted using patient-reported outcome measurements (PROMs), including the International Knee Documentation Committee (IKDC) evaluation, Lysholm knee scoring scale, and Tegner Activity scale. PROMs were collected at least two years postoperatively. RESULTS: The average follow-up was 32.5 ± 7.4 months. There were no significant differences in postoperative IKDC score, Lysholm score, or Tegner activity score between patients with or without medial meniscus injury (p = 0.155, 0.914, and 0.042, respectively), with or without lateral meniscus injury (p = 0.737, 0.569, and 0.942, respectively), medial tibial slope > 12° or ≤ 12° (p = 0.290, 0.496, and 0.988, respectively), or lateral tibial slope > 7.4° or ≤ 7.4° (p = 0.213, 0.625, and 0.922, respectively). No significant correlations were found between anterior tibial translation and postoperative IKDC (R = -0.058, p = 0.365), Lysholm (R = -0.017, p = 0.459), or Tegner activity scores (R = -0.147, p = 0.189). CONCLUSION: Our study demonstrates that single-bundle ACL reconstruction combined with ALL reconstruction provides reliable and comparable clinical outcomes in patients with high-risk factors for ACL graft failure, such as increased tibial slope or meniscal injury. Our results suggest that the indications for ALL reconstruction may be expanded to include patients with a high tibial slope or meniscal injury, because these factors have been shown to contribute to increased rotational instability and high rates of ACL graft failure. Future prospective randomized controlled trials with large patient cohorts and long follow-up periods are needed to validate these findings and establish clear guidelines for patient selection and surgical decision-making. LEVEL OF EVIDENCE: Level 3.

scPriorGraph: constructing biosemantic cell-cell graphs with prior gene set selection for cell type identification from scRNA-seq data.

Cell type identification is an indispensable analytical step in single-cell data analyses. To address the high noise stemming from gene expression data, existing computational methods often overlook the biologically meaningful relationships between genes, opting to reduce all genes to a unified data space. We assume that such relationships can aid in characterizing cell type features and improving cell type recognition accuracy. To this end, we introduce scPriorGraph, a dual-channel graph neural network that integrates multi-level gene biosemantics. Experimental results demonstrate that scPriorGraph effectively aggregates feature values of similar cells using high-quality graphs, achieving state-of-the-art performance in cell type identification.

Glucocorticoid therapy in pancreatic portal hypertension associated with autoimmune pancreatitis: A case report.

BACKGROUND: Autoimmune pancreatitis (AIP) is a chronic form of pancreatitis characterized by diffused enlargement of the pancreas and irregular stenosis of the main pancreatic duct. Some studies have reported that AIP can cause hemorrhage of gastric varices (GV) related to portal hypertension (PH). However, such cases are rare. In addition, the association of PH with AIP is unclear. At the same time, the efficacy and duration of glucocorticoid therapy is also controversial. CASE SUMMARY: In this case, we reported a case of GV in pancreatic PH associated with AIP. Enhanced abdominal computed tomography (CT) suggested splenic vein (SV) and superior mesenteric vein (SMV) thromboses. The patient received a long-term glucocorticoid therapy, that the initial dose of 40 mg is reduced weekly by 5 mg, and then reduced to 5 mg for long-term maintenance. CT and gastroscopic examination after 8 mo of treatment indicated that SV and SMV were recanalized, pancreatic stiffness and swelling were ameliorated, and the GV almost completely disappeared. CONCLUSION: Long-term glucocorticoid therapy can alleviate the development of GV in patients with AIP and has potential reversibility.

Circular RNAs in tumor immunity and immunotherapy.

Circular RNAs (circRNAs) are unique noncoding RNAs that have a closed and stable loop structure generated through backsplicing. Due to their conservation, stability and tissue specificity, circRNAs can potentially be used as diagnostic indicators and therapeutic targets for certain tumors. Many studies have shown that circRNAs can act as microRNA (miRNA) sponges, and engage in interactions with proteins and translation templates to regulate gene expression and signal transduction, thereby participating in the occurrence and development of a variety of malignant tumors. Immunotherapy has revolutionized the treatment of cancer. Early researches have indicated that circRNAs are involved in regulating tumor immune microenvironment and antitumor immunity. CircRNAs may have the potential to be important targets for increasing sensitivity to immunotherapy and expanding the population of patients who benefit from cancer immunotherapy. However, few studies have investigated the correlation between circRNAs and tumor immunity. In this review, we summarize the current researches on circRNAs involved in antitumor immune regulation through different mechanisms and their potential value in increasing immunotherapy efficacy with the goal of providing new targets for cancer immunotherapy.

Phytic acid inhibits Cr(VI) reduction on Fe(II)-bearing clay minerals: Changing reduction sites and electron transfer pathways.

The presence of organic phosphorus may influence the characteristics of Cr(VI) reduction and immobilization on Fe(II)-bearing clay minerals under anoxic conditions, as the organic phosphorus tends to bind strongly to clay minerals in soil. Herein, reduced nontronite (rNAu-2) was used to reduction of Cr(VI) in the presence of phytic acid (IHP) at neutral pH. With IHP concentration from 0 to 500 µM, Cr(VI) reduction decreased obviously (17.8%) within first 5 min, and then preferred to stagnate during 4-12 h (≥50 µM). After that, Cr(VI) was reduced continuously at a slightly faster rate. Density functional theory (DFT) calculations revealed that IHP primarily absorbed at the edge sites of rNAu-2 to form Fe-IHP complexes. X-ray diffraction (XRD), scanning transmission electron microscopy (STEM), and Fourier transform infrared spectroscopy (FTIR) results demonstrated that IHP hindered the ingress of CrO42- into the interlayer space of rNAu-2 and impeded their reduction by trioctahedral Fe(II) and Al-Fe(II) at basal plane sites in the initial stage. Additionally, Fe(II) extraction results showed that IHP promoted the electron from interior transfer to near-edge, but hindered it further transfer to surface, resulting in the inhibition on Cr(VI) reduction at edge sites during the later stage. Consequently, IHP inhibits the reduction and immobilization of Cr(VI) by rNAu-2. Our study offers novel insights into electron transfer pathways during the Cr(VI) reduction by rNAu-2 with coexisting IHP, thereby improve the understanding of the geochemical processes of chromium within the iron cycle in soil.

Causal relationships between immune cells, inflammatory factors, serum metabolites, and hepatic cancer: A two-sample Mendelian randomization study.

Background: Observational studies and clinical trials suggest associations between immune cells, inflammatory factors, serum metabolites, and hepatic cancer. However, the causal relationships between these factors and hepatic cancer remain to be established. Objective: To explore the causal relationships between immune cells, inflammatory factors, serum metabolites, and hepatic cancer. Methods: This study employed comprehensive two-sample Mendelian randomization (MR) utilizing publicly available genetic data (GWAS) to analyze causal relationships between 731 immune cell traits, 91 inflammatory factors, 1400 serum metabolites, and hepatic cancer. The primary analysis used inverse variance-weighted (IVW) MR, with additional sensitivity tests to assess the validity of causal relationships. Results: After correction for heterogeneity and horizontal pleiotropy, in exploring the causal relationships between immune cell groups and hepatic cancer, we found that Terminally Differentiated CD4-CD8- T cell %T cell was negatively associated with hepatic cancer, serving as a protective factor, while Effector Memory CD4-CD8- T cell %CD4-CD8- T cell was positively associated with hepatic cancer, acting as a risk factor. In investigating the causal relationships between inflammatory factors and hepatic cancer, C-C motif chemokine 19 levels were positively associated with hepatic cancer, representing a risk factor, while Interleukin-10 levels were negatively associated with hepatic cancer, acting as a protective factor. Regarding the causal relationships between serum metabolites and hepatic cancer, (N(1) + N(8))-acetylspermidine levels were negatively associated with hepatic cancer, serving as a protective factor, while 1-(1-enyl-palmitoyl)-GPC (p-16:0) levels were positively associated with hepatic cancer, acting as a risk factor. Conclusion: Our MR analysis indicates causal relationships between immune cells, inflammatory factors, serum metabolites, and hepatic cancer. However, further validation is needed to assess the potential of these immune cells, inflammatory factors, and serum metabolites as preventive or therapeutic targets for hepatic cancer.

Repurposing of CDK Inhibitors as Host Targeting Antivirals: A Mini-Review.

Most of the antiviral drugs in the market are designed to target viral proteins directly. They are generally considered safe for human use. However, they also suffer from several inherent limitations, in particular, narrow-spectrum antiviral profiles and liability to drug resistance. The other strategy for antiviral drug development is targeting host factors, which are highly involved at different stages in the viral life cycle. In contrast to direct-acting antiviral agents, host-targeting antiviral ones normally exhibit broad-spectrum antiviral properties along with a much higher genetic barrier to drug resistance. Cyclin-dependent kinases (CDKs) represent one such host factor. In this review, we summarized a number of CDK inhibitors (CDKIs) of varied chemical scaffolds with demonstrated antiviral activity. Challenges and issues associated with the repurposing of CDKIs as antiviral agents were also discussed.

Hyperspectral Imaging Technique to Characterize Digestate and Visualize Physical Impurities in Anaerobically Digested Biowaste.

Methods used to monitor anaerobic digestion (AD) indicators are commonly based on wet chemical analyses, which consume time and materials. In addition, physical disturbances, such as floating granules (FGs), must be monitored manually. In this study, we present an eco-friendly, high-throughput methodology that uses near-infrared hyperspectral imaging (NIR-HSI) to build a machine-learning model for characterizing the chemical composition of the digestate and a target detection algorithm for identifying FGs. A total of 732 digestate samples were used to develop and validate a model for calculating total nitrogen (TN), total organic carbon (TOC), total ammonia nitrogen (TAN), and chemical oxygen demand (COD), which are the chemical indicators of responses to disturbances in the AD process. Among these parameters, good model performance was obtained using the dried digestates data set, where the coefficient of determination (R2test) and the root-mean-square error (RMSEtest) were 0.82 and 1090 mg/L for TOC, and 0.86 and 690 mg/L for TN, respectively. Furthermore, the unique spectral features of the FGs in reactors with a lipid-rich substrate meant that they could also be identified by the HSI system. Based on these findings, developing NIR-HSI solutions to monitor the digestate properties in AD plants has great potential for industrial application.

Efficacy of selective serotonin reuptake inhibitors-related antidepressants in Alzheimer's disease: a meta-analysis.

OBJECTIVE: To study the effects of selective serotonin reuptake inhibitors (SSRIs) on cognitive functions, mental improvements, and adverse effects in patients with Alzheimer's disease (AD). METHODS: Registered in INPLASY (INPLASY202450004), five drugs (citalopram, s-citalopram, quetiapine, olanzapine, and sertraline) were selected as representatives. A comprehensive search was conducted in PubMed, EMBASE, Web of Science, and the Cochrane Library up to May 15, 2024. Search terms were combined using Boolean operators, specifically 'AND' between different categories (e.g., 'Alzheimer's Disease' AND 'SSRIs') and 'OR' within the same category (e.g., 'citalopram OR s-citalopram OR quetiapine OR olanzapine OR sertraline'), to ensure a thorough retrieval of relevant studies. The selection followed rigorous inclusion and exclusion criteria for meta-analysis. RESULTS: Fourteen articles from 1118 were selected for meta-analysis. The indicators, including Neuropsychiatric Inventory (NPI), Mini-Mental State Examination (MMSE), Brief Psychiatric Rating Scale (BPRS), and Cornell Scale for Depression in Dementia (CSDD), were used to assess the effects of the drugs on AD treatment. According to the results of NPI, CSDD, BPRS, MMSE, and security assessments, the five antidepressants have significant advantages in AD treatment compared with placebo, while the MMSE of the patient treated with the antidepressants did not show notable changes compared with patients treated only with placebo. Statistical analyses were conducted using Review Manager 5.3, employing random-effects models to account for study heterogeneity and sensitivity analyses to test the robustness of our findings. CONCLUSION: This study suggests that SSRI-related antidepressants have great potential values in AD treatment, and further research on the application of SSRI-related antidepressants in AD treatment is necessary.

Designing Retirement Strategies for Coal-Fired Power Plants To Mitigate Air Pollution and Health Impacts.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system operations and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO2 emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and Rest of PJM, leading to scenario-varying changes in the plant-level release of air pollutants. Considering pollution transport and the size of the exposed population, these emissions changes, in turn, give rise to a reduction of 6-136 PM2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Among our designed scenarios, those that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, comparing across the six scenarios evaluated in this study, vulnerable populations─in both PA and Rest of PJM─benefit most in scenarios that prioritize plant closures near Environmental Justice Areas in PA. These results demonstrate the importance of considering cross-regional linkages and sociodemographics in designing equitable retirement strategies.

Metadata-conditioned generative models to synthesize anatomically-plausible 3D brain MRIs.

Recent advances in generative models have paved the way for enhanced generation of natural and medical images, including synthetic brain MRIs. However, the mainstay of current AI research focuses on optimizing synthetic MRIs with respect to visual quality (such as signal-to-noise ratio) while lacking insights into their relevance to neuroscience. To generate high-quality T1-weighted MRIs relevant for neuroscience discovery, we present a two-stage Diffusion Probabilistic Model (called BrainSynth) to synthesize high-resolution MRIs conditionally-dependent on metadata (such as age and sex). We then propose a novel procedure to assess the quality of BrainSynth according to how well its synthetic MRIs capture macrostructural properties of brain regions and how accurately they encode the effects of age and sex. Results indicate that more than half of the brain regions in our synthetic MRIs are anatomically plausible, i.e., the effect size between real and synthetic MRIs is small relative to biological factors such as age and sex. Moreover, the anatomical plausibility varies across cortical regions according to their geometric complexity. As is, the MRIs generated by BrainSynth significantly improve the training of a predictive model to identify accelerated aging effects in an independent study. These results indicate that our model accurately capture the brain's anatomical information and thus could enrich the data of underrepresented samples in a study. The code of BrainSynth will be released as part of the MONAI project at https://github.com/Project-MONAI/GenerativeModels.

Analysis of lumateperone data for patients with schizophrenia using related adverse events from the FDA adverse reporting system.

BACKGROUND: Our study utilized the U.S. Food and Drug Administration's Adverse Event Reporting System (FAERS) to analyze and study the adverse event (AEs) signals of second-generation antipsychotic drug lumateperone, providing a reference for clinical safety monitoring in the treatment of schizophrenia. METHODS: The International Dictionary of Medical Terminology (version 26.0) was used to standardize the preferred system organ category (SOC) and preferred terminology (PT) for adverse drug events (ADE) data related to lumateperone. ADE signals were classified and described using four algorithms: reporting odds ratios (ROR), proportional reporting ratios (PRR), Bayesian confidence-propagation neural network (BCPNN) and Multinomial gamma-poisson shrinkage (MGPS). RESULT: Among the 2542 case reports collected from the FAERS database, 1762 reports with lumateperone as a 'principal suspect(PS)' AEs were identified. Lumateperone-induced AEs occurred in 26 system organ categories (SOC). A total of 118 significant disproportionate preferred terms (PTs) meeting the requirements of 4 algorithms were retained, and unexpected major events, such as burning sensation, tremor, migraine etc. may also occur. The median time to onset of lumateperone-related adverse events was 9 days (interquartile range [IQR] 2-31.25 days), and most AEs occurred within the first 10 days and 1 month after initiation of lumateperone therapy. CONCLUSION: Our research may provide a better understanding of the potential adverse events that may be caused by lumateperone and those not recorded in the drug instructions, providing valuable signals for clinical use.