Global intracranial arterial tortuosity is associated with intracranial atherosclerotic burden.

The effect of arterial tortuosity on intracranial atherosclerosis (ICAS) is not well understood. This study aimed to evaluate the effect of global intracranial arterial tortuosity on intracranial atherosclerotic burden in patients with ischemic stroke. We included patients with acute ischemic stroke who underwent magnetic resonance angiography (MRA) and classified them into three groups according to the ICAS burden. Global tortuosity index (GTI) was defined as the standardized mean curvature of the entire intracranial arteries, measured by in-house vessel analysis software. Of the 516 patients included, 274 patients had no ICAS, 140 patients had a low ICAS burden, and 102 patients had a high ICAS burden. GTI increased with higher ICAS burden. After adjustment for age, sex, vascular risk factors, and standardized mean arterial area, GTI was independently associated with ICAS burden (adjusted odds ratio [adjusted OR] 1.33; 95% confidence interval [CI] 1.09-1.62). The degree of association increased when the arterial tortuosity was analyzed limited to the basal arteries (adjusted OR 1.48; 95% CI 1.22-1.81). We demonstrated that GTI is associated with ICAS burden in patients with ischemic stroke, suggesting a role for global arterial tortuosity in ICAS.

Histopathologic image-based deep learning classifier for predicting platinum-based treatment responses in high-grade serous ovarian cancer.

Platinum-based chemotherapy is the cornerstone treatment for female high-grade serous ovarian carcinoma (HGSOC), but choosing an appropriate treatment for patients hinges on their responsiveness to it. Currently, no available biomarkers can promptly predict responses to platinum-based treatment. Therefore, we developed the Pathologic Risk Classifier for HGSOC (PathoRiCH), a histopathologic image-based classifier. PathoRiCH was trained on an in-house cohort (n = 394) and validated on two independent external cohorts (n = 284 and n = 136). The PathoRiCH-predicted favorable and poor response groups show significantly different platinum-free intervals in all three cohorts. Combining PathoRiCH with molecular biomarkers provides an even more powerful tool for the risk stratification of patients. The decisions of PathoRiCH are explained through visualization and a transcriptomic analysis, which bolster the reliability of our model's decisions. PathoRiCH exhibits better predictive performance than current molecular biomarkers. PathoRiCH will provide a solid foundation for developing an innovative tool to transform the current diagnostic pipeline for HGSOC.

Controlling Fluorination Density of Soluble Polyimide Gate Dielectrics and its Influence on Organic Crystal Growth and Device Operational Stability.

Fluorinated polyimides (PIs) are among the most promising candidates for gate dielectric materials in organic electronic devices because of their solution processability and outstanding chemical, mechanical, and thermal stabilities. Additionally, fluorine (F) substitution improves the electrical properties of PI thin films, such as enhanced dielectric properties and reduced surface trap densities. However, the relationship between the fluorination density of PIs and crystal growth modes of vacuum-deposited conjugated molecules on PI thin films, which is directly related to the lateral charge transport along the PI-organic semiconductor interface, has not been systematically studied. Herein, five different soluble PIs with different F densities were synthesized, and the correlation between fluorination and thin-film properties was systematically investigated. Not only were their dielectric properties modulated, but the growth modes of the organic molecules deposited on the PI thin films also changed with increasing surface F density. This phenomenon was observed by both surface and crystallographic analyses, which resulted in extremely high operational stability of field-effect transistors and the successful fabrication of organic complementary circuits. We believe that the correlation between PI backbone fluorination and its thin-film properties will provide practical insights into the material design based on controlled molecular directed surface assembly on fluorinated polymer dielectrics.

GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox.

Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

Implantation of hUCB-MSCs generates greater hyaline-type cartilage than microdrilling combined with high tibial osteotomy.

PURPOSE: To compare the outcomes of treating large cartilage defects in knee osteoarthritis using human allogeneic umbilical cord blood-derived mesenchymal stem cell (hUCB-MSC) implantation or arthroscopic microdrilling as a supplementary cartilage regenerative procedure combined with high tibial osteotomy (HTO). METHODS: This 1-year prospective comparative study included 25 patients with large, near full-thickness cartilage defects (International Cartilage Repair Society grade ≥ IIIB) in the medial femoral condyles and varus malalignment. Defects were treated with hUCB-MSC implantation or arthroscopic microdrilling combined with HTO. The primary outcomes were pain visual analogue scale and International Knee Documentation Committee subjective scores at 12, 24 and 48 weeks. Secondary outcomes included arthroscopic, histological and magnetic resonance imaging assessments at 1 year. RESULTS: Fifteen and 10 patients were treated via hUCB-MSC implantation and microdrilling, respectively. Baseline demographics, limb alignment and clinical outcomes did not significantly differ between the groups. Cartilage defects and total restored areas were significantly larger in the hUCB-MSC group (7.2 ± 1.9 vs. 5.2 ± 2.1 cm2, p = 0.023; 4.5 ± 1.4 vs. 3.0 ± 1.6 cm2, p = 0.035). The proportion of moderate-to-strong positive type II collagen staining was significantly higher in the hUCB-MSC group compared to that in the microdrilled group (93.3% vs. 60%, respectively). Rigidity upon probing resembled that of normal cartilage tissue more in the hUCB-MSC group (86.7% vs. 50.0%, p = 0.075). Histological findings revealed a higher proportion of hyaline cartilage in the group with implanted hUCB-MSC (p = 0.041). CONCLUSION: hUCB-MSC implantation showed comparable clinical outcomes to those of microdrilling as supplementary cartilage procedures combined with HTO in the short term, despite the significantly larger cartilage defect in the hUCB-MSC group. The repaired cartilage after hUCB-MSC implantation showed greater hyaline-type cartilage with rigidity than that after microdrilling. LEVEL OF EVIDENCE: Level II, Prospective Comparative Cohort Study.

Comparative analysis of malt quality and starch characteristics of three South Korean barley cultivars.

In this study, malt was produced in pilot-scale facilities and conditioned using three barley (Hordeum vulgare L.) cultivars in South Korea (Heugho, Hopum, and Kwangmaeg). Quality and starch characteristics were compared. The starch content was considerably reduced in all malts. Coleoptile elongation was higher in Heugho (HHM; 85.7% ± 12.6%) and Hopum (HPM; 83.9% ± 10.7%) than in Kwangmaeg (KMM; 78.1% ± 9.9%) malt. Malt yield ranged from 81.8 to 84.9%, with no significant difference. All samples presented type A crystallinity, and granules showed discoid shapes. After malting, the mono- and di-saccharide contents (not including sucrose) were increased. The fermentable sugar level was the highest in HHM, whereas non-fermentable sugar was the highest in KMM. These results suggest that HPM enables efficient scarification based on the rapid degradation of starch, while Heugho barley and HHM have a high potential for beer and malt production, respectively. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01419-6.

Density Functional Theory-Based Approach For Dielectric Constant Estimation of Soluble Polyimide Insulators.

Evaluation of the insulating properties of polymers, such as the dielectric constant and dissipation factor, is crucial in electronic devices, including field-effect transistors and wireless communication applications. This study applies density functional theory (DFT) to predict the dielectric constant of soluble polyimides (SPIs). Various SPIs containing trifluoromethyl groups in the backbone with different pendant types, numbers, and symmetries are successfully synthesized, and their dielectric constants are evaluated and compared with the DFT-estimated values. Two types of DFT-optimized SPIs, single-chain and stacked-chain models, are used to describe the local geometries of the SPIs. In addition, to reveal the relationship between the molecular structure and dielectric constant, further investigations are conducted by considering the dielectric constant of composing ionic and electronic components. The DFT-estimated static dielectric constant of the single-chain model accurately reproduces the corresponding experimental value with at least 80% accuracy. Our approach provides a rational and accelerated strategy to evaluate polymer insulators for electronic devices based on cost-effective DFT calculations.

Combined radiomics-clinical model to predict platinum-sensitivity in advanced high-grade serous ovarian carcinoma using multimodal MRI.

Introduction: We aimed to predict platinum sensitivity using routine baseline multimodal magnetic resonance imaging (MRI) and established clinical data in a radiomics framework. Methods: We evaluated 96 patients with ovarian cancer who underwent multimodal MRI and routine laboratory tests between January 2016 and December 2020. The patients underwent diffusion-weighted, contrast-enhanced T1-weighted, and T2-weighted MRI. Subsequently, 293 radiomic features were extracted by manually identifying tumor regions of interest. The features were subjected to the least absolute shrinkage and selection operators, leaving only a few selected features. We built the first prediction model with a tree-based classifier using selected radiomics features. A second prediction model was built by combining the selected radiomic features with four established clinical factors: age, disease stage, initial tumor marker level, and treatment course. Both models were built and tested using a five-fold cross-validation. Results: Our radiomics model predicted platinum sensitivity with an AUC of 0.65 using a few radiomics features related to heterogeneity. The second combined model had an AUC of 0.77, confirming the incremental benefits of the radiomics model in addition to models using established clinical factors. Conclusion: Our combined radiomics-clinical data model was effective in predicting platinum sensitivity in patients with advanced ovarian cancer.

Br doping-induced evolution of the electronic band structure in dimorphic and hexagonal SnSe2 thermoelectric materials.

SnSe2 with its layered structure is a promising thermoelectric material with intrinsically low lattice thermal conductivity. However, its poor electronic transport properties have motivated extensive doping studies. Br doping effectively improves the power factor and converts the dimorphic SnSe2 to a fully hexagonal structure. To understand the mechanisms underlying the power factor improvement of Br-doped SnSe2, the electronic band parameters of Br-doped dimorphic and hexagonal SnSe2 should be evaluated separately. Using the single parabolic band model, we estimate the intrinsic mobility and effective mass of the Br-doped dimorphic and hexagonal SnSe2. While Br doping significantly improves the mobility of dimorphic SnSe2 (with the dominant hexagonal phase), it results in a combination of band convergence and band flattening in fully hexagonal SnSe2. Br-doped dimorphic SnSe2 is predicted to exhibit higher thermoelectric performance (zT ∼0.23 at 300 K) than Br-doped fully hexagonal SnSe2 (zT ∼0.19 at 300 K). Characterisation of the other, currently unidentified, structural phases of dimorphic SnSe2 will enable us to tailor the thermoelectric properties of Br-doped SnSe2.

Distinct spatiotemporal patterns of cortical thinning in Alzheimer's disease-type cognitive impairment and subcortical vascular cognitive impairment.

Previous studies on Alzheimer's disease-type cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI) has rarely explored spatiotemporal heterogeneity. This study aims to identify distinct spatiotemporal cortical atrophy patterns in ADCI and SVCI. 1,338 participants (713 ADCI, 208 SVCI, and 417 cognitively unimpaired elders) underwent brain magnetic resonance imaging (MRI), amyloid positron emission tomography, and neuropsychological tests. Using MRI, this study measures cortical thickness in five brain regions (medial temporal, inferior temporal, posterior medial parietal, lateral parietal, and frontal areas) and utilizes the Subtype and Stage Inference (SuStaIn) model to predict the most probable subtype and stage for each participant. SuStaIn identifies two distinct cortical thinning patterns in ADCI (medial temporal: 65.8%, diffuse: 34.2%) and SVCI (frontotemporal: 47.1%, parietal: 52.9%) patients. The medial temporal subtype of ADCI shows a faster decline in attention, visuospatial, visual memory, and frontal/executive domains than the diffuse subtype (p-value < 0.01). However, there are no significant differences in longitudinal cognitive outcomes between the two subtypes of SVCI. Our study provides valuable insights into the distinct spatiotemporal patterns of cortical thinning in patients with ADCI and SVCI, suggesting the potential for individualized therapeutic and preventive strategies to improve clinical outcomes.

Whole-brain structural connectome asymmetry in autism.

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA.

The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to affect the risk, severity, and clinical outcome of serious neuro-vascular diseases. However, characterizing the highly variable CoW anatomy is still a manual and time-consuming expert task. The CoW is usually imaged by two angiographic imaging modalities, magnetic resonance angiography (MRA) and computed tomography angiography (CTA), but there exist limited public datasets with annotations on CoW anatomy, especially for CTA. Therefore we organized the TopCoW Challenge in 2023 with the release of an annotated CoW dataset. The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology. It was also the first large dataset with paired MRA and CTA from the same patients. TopCoW challenge formalized the CoW characterization problem as a multiclass anatomical segmentation task with an emphasis on topological metrics. We invited submissions worldwide for the CoW segmentation task, which attracted over 140 registered participants from four continents. The top performing teams managed to segment many CoW components to Dice scores around 90%, but with lower scores for communicating arteries and rare variants. There were also topological mistakes for predictions with high Dice scores. Additional topological analysis revealed further areas for improvement in detecting certain CoW components and matching CoW variant topology accurately. TopCoW represented a first attempt at benchmarking the CoW anatomical segmentation task for MRA and CTA, both morphologically and topologically.

Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning.

Eating behavior is highly heterogeneous across individuals and cannot be fully explained using only the degree of obesity. We utilized unsupervised machine learning and functional connectivity measures to explore the heterogeneity of eating behaviors measured by a self-assessment instrument using 424 healthy adults (mean ± standard deviation [SD] age = 47.07 ± 18.89 years; 67% female). We generated low-dimensional representations of functional connectivity using resting-state functional magnetic resonance imaging and estimated latent features using the feature representation capabilities of an autoencoder by nonlinearly compressing the functional connectivity information. The clustering approaches applied to latent features identified three distinct subgroups. The subgroups exhibited different levels of hunger traits, while their body mass indices were comparable. The results were replicated in an independent dataset consisting of 212 participants (mean ± SD age = 38.97 ± 19.80 years; 35% female). The model interpretation technique of integrated gradients revealed that the between-group differences in the integrated gradient maps were associated with functional reorganization in heteromodal association and limbic cortices and reward-related subcortical structures such as the accumbens, amygdala, and caudate. The cognitive decoding analysis revealed that these systems are associated with reward- and emotion-related systems. Our findings provide insights into the macroscopic brain organization of eating behavior-related subgroups independent of obesity.

Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning.

Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy.

Does injecting small amounts of fillers prevent the development of secondary blindness?

INTRODUCTION: Inadvertent entry of filler products into the supratrochlear, supraorbital, or dorsal nasal arteries, among other branches of the ophthalmic artery, might result in an immediate and devastating loss of vision. We wanted to examine how much filler could block the ophthalmic artery. MATERIALS AND METHODS: Twenty-nine fresh cadavers were examined. We exposed the arterial supply to the opthalmic artery by dissecting the orbital area. Thereafter, 17 filler injections were introduced into the supratrochlear, supraorbital, and dorsal nasal arteries each. The amount of filler injection that completely blocked the ophthalmic artery was measured. Additionally, one of the head specimens was processed using phosphotungstic acid-based contrast enhancement micro-computed tomography to analyze each arteries to obstruct its whole ophthalmic artery. RESULTS: The supratrochlear, supraorbital, and dorsal nasal arteries had mean volumes in milliliter (mean ± standard deviation) of 0.0397 ± 0.010 mL, 0.0409 ± 0.00932 mL, and 0.0368 ± 0.00732 mL, respectively. However, the arteries did not differ significantly. CONCLUSION: Even a modest amount of filler injection can completely block the ophthalmic artery, resulting in visual loss.

Chlorophyll a and novel synthetic derivatives alleviate atopic dermatitis by suppressing Th2 cell differentiation via IL-4 receptor modulation.

Atopic dermatitis (AD) treatment has largely relied on non-specific broad immunosuppressants despite their long-term toxicities until the approval of dupilumab, which blocks IL-4 signaling to target Th2 cell responses. Here, we report the discovery of compound 4aa, a novel compound derived from the structure of chlorophyll a, and the efficacy of chlorophyll a to alleviate AD symptoms by oral administration in human AD patients. 4aa downregulated GATA3 and IL-4 in differentiating Th2 cells by potently blocking IL-4 receptor dimerization. In the murine model, oral administration of 4aa reduced the clinical severity of symptoms and scratching behavior by 76% and 72%, respectively. Notably, the elevated serum levels of Th2 cytokines reduced to levels similar to those in the normal group after oral administration of 4aa. Additionally, the toxicological studies showed favorable safety profiles and good tolerance. In conclusion, 4aa may be applied for novel therapeutic developments for patients with AD.

Paravertebral Nerve Block for Procedural Pain in Percutaneous Vertebroplasty.

OBJECTIVES: This study aimed to unidimensionally measure procedural pain at each percutaneous vertebroplasty (PVP) stage and evaluate the effectiveness of paravertebral nerve block (PVNB) in reducing procedural pain. METHODS: A retrospective study of prospectively collected data was conducted on 66 patients who underwent PVP for osteoporotic vertebral compression fractures. The patients were divided into 2 groups: group A (fluoroscopic-guided PVNB; 5 cm 3 of 0.75% ropivacaine on each side) and group B (local anesthesia). To investigate procedural pain associated with PVP, the visual analog scale score was assessed at each surgical stage: before the incision (stage 1), transpedicular approach (stage 2), and polymethylmethacrylate cement injection (stage 3). After the procedure, patients were asked about their surgical experience and satisfaction using the Iowa Satisfaction with Anesthesia Scale. Periprocedural complications were also recorded. RESULTS: A total of 63 patients (78.65 y of age) were finally enrolled: 30 from group A and 33 from group B. In both groups, a significant ≥2-point increase in procedural pain was observed during PVP compared with that during stage 1 ( P < 0.001). In stages 2 and 3, the pain intensity was significantly lower in group A ( P < 0.001). Upon discharge, the visual analog scale score improved in all groups; however, the Iowa Satisfaction with Anesthesia Scale score was significantly higher in group A ( P < 0.001). There was no difference in periprocedural complications between the two groups ( P = 0.743). CONCLUSION: PVP causes significant procedural pain, and PVNB is a potentially effective modality for enhancing patient satisfaction and reducing procedural pain.

Atypical structural connectome asymmetry and associations with network communication in autism spectrum disorder.

Autism spectrum disorder is a common neurodevelopmental condition showing connectome disorganization in sensory and transmodal cortices. However, alterations in the inter-hemispheric asymmetry of structural connectome are remained to be investigated. Here, we studied structural connectome asymmetry in individuals with autism using dimensionality reduction techniques and assessed its topological underpinnings by associating with network communication measures. We found that the sensory and heteromodal association regions showed significant between-group differences in inter-hemispheric asymmetry between individuals with autism and neurotypical controls. In addition, the network communication ability was particularly altered between visual and limbic areas. Our findings provide insights for understanding structural connectome alteration in autism and its topological underpinnings.Clinical Relevance- This study provides insights into the understanding of atypical macroscale structural connectome organization in individuals with autism.

Metabolic complications of obesity in children and adolescents.

The global prevalence of childhood and adolescent obesity, exacerbated by the COVID-19 pandemic, is affecting not only school-aged children but also preschoolers. Early-onset obesity, along with a higher risk of metabolic complications, may contribute to a lower age of onset of cardiovascular disease (CVD). As metabolic diseases such as diabetes, dyslipidemia, and non-alcoholic fatty liver disease (NAFLD) observed in adulthood are increasingly recognized in the pediatric population, there is an emphasis on moving disease susceptibility assessment from adulthood to childhood for early detection. Unlike adults, there is a lack of consensus in the definition of metabolic diseases in children. In response to this, various indicators such as pediatric simple metabolic syndrome score (PsiMS), continuous metabolic syndrome score (cMetS), single point insulin sensitivity estimator (SPISE), and fatty liver index (FLI) have been proposed in several studies. These indicators may help explain and early detect metabolic complications associated with pediatric obesity, although more validity studies are needed. Meanwhile, obesity assessment is shifting its perspective from visual obesity to metabolic health and body composition considerations to fill the gap in health impact assessment. Sarcopenic obesity, defined as muscle-to-fat ratio (MFR), has been proposed in pediatric populations and has also been found to be associated with metabolic health in children and adolescents. The National health screening program for children in Korea has expanded but still faces limitations in laboratory testing. These tests facilitate timely intervention by identifying high-risk groups for metabolic complications. Early detection and intervention through comprehensive health screening are critical to mitigate long-term complications of childhood obesity.

Cancer risk based on alcohol consumption levels: a comprehensive systematic review and meta-analysis.

OBJECTIVES: Alcohol consumption is a well-established risk factor for cancer. Despite extensive research into the relationship between alcohol consumption and cancer risk, the effect of light alcohol consumption on cancer risk remains a topic of debate. To contribute to this discourse, we conducted a comprehensive systematic review and meta-analysis. METHODS: Our systematic review aimed to investigate the associations between different levels of alcohol consumption and the risk of several cancer types. We focused on analyzing prospective associations using data from 139 cohort studies. Among them, 106 studies were included in the meta-analysis after a quantitative synthesis. RESULTS: Our analysis did not find a significant association between light alcohol consumption and all-cause cancer risk (relative risk, 1.02; 95% confidence interval, 0.99 to 1.04), but we observed a dose-response relationship. Light alcohol consumption was significantly associated with higher risks of esophageal, colorectal, and breast cancers. Light to moderate drinking was associated with elevated risks of esophageal, colorectal, laryngeal, and breast cancers. Heavy drinking was also found to contribute to the risk of stomach, liver, pancreas, and prostate cancers, thereby increasing the risk of almost all types of cancer. Additionally, females generally had lower cancer risks compared to males. CONCLUSIONS: Our findings highlight that cancer risks extend beyond heavy alcohol consumption to include light alcohol consumption as well. These findings suggest that there is no safe level of alcohol consumption associated with cancer risk. Our results underscore the importance of public health interventions addressing alcohol consumption to mitigate cancer risks.