Consumption Patterns and Willingness to Pay for Sustainable Aquatic Food in China.

China, as the world's largest producer, trader, and consumer of aquatic foods, lacks comprehensive research on consumption patterns and willingness to pay for sustainable aquatic food. This study addressed this gap through an online survey of 3403 participants across Chinese provinces. A majority of consumers (34.7% of the participants) consume aquatic food twice or more per week, mainly from traditional markets (26%). Most prefer fresh or live products (76%), with 42% seeing no difference between farmed and wild options. Consumption is higher among older, affluent, urban, and coastal residents. Crustaceans, especially shrimp, are frequently consumed species, with growing interest in luxury species like salmon and abalone. Taste and quality emerge as the primary factors motivating consumer choices in aquatic food purchases. Food safety is the primary concern, followed by environmental impact. Notably, 92.4% of participants would pay extra for certified products. Factors influencing a higher willingness to pay include higher income, inland residence, price sensitivity, origin consciousness, and concerns about food safety and the environment. The findings highlight that China's aquatic food industry and consumption can become more sustainable by aligning with consumer preferences for high-quality and diverse aquatic food through both production and import, while also addressing concerns related to food safety and environmental impact. This research provides valuable insights into China's rapidly transforming aquatic food market landscape, offering implications for industry innovation and the promotion of sustainable consumption patterns.

Automatic cardiothoracic ratio calculation based on lung fields abstracted from chest X-ray images without heart segmentation.

Introduction: The cardiothoracic ratio (CTR) based on postero-anterior chest X-rays (P-A CXR) images is one of the most commonly used cardiac measurement methods and an indicator for initially evaluating cardiac diseases. However, the hearts are not readily observable on P-A CXR images compared to the lung fields. Therefore, radiologists often manually determine the CTR's right and left heart border points of the adjacent left and right lung fields to the heart based on P-A CXR images. Meanwhile, manual CTR measurement based on the P-A CXR image requires experienced radiologists and is time-consuming and laborious. Methods: Based on the above, this article proposes a novel, fully automatic CTR calculation method based on lung fields abstracted from the P-A CXR images using convolutional neural networks (CNNs), overcoming the limitations to heart segmentation and avoiding errors in heart segmentation. First, the lung field mask images are abstracted from the P-A CXR images based on the pre-trained CNNs. Second, a novel localization method of the heart's right and left border points is proposed based on the two-dimensional projection morphology of the lung field mask images using graphics. Results: The results show that the mean distance errors at the x-axis direction of the CTR's four key points in the test sets T1 (21 × 512 × 512 static P-A CXR images) and T2 (13 × 512 × 512 dynamic P-A CXR images) based on various pre-trained CNNs are 4.1161 and 3.2116 pixels, respectively. In addition, the mean CTR errors on the test sets T1 and T2 based on four proposed models are 0.0208 and 0.0180, respectively. Discussion: Our proposed model achieves the equivalent performance of CTR calculation as the previous CardioNet model, overcomes heart segmentation, and takes less time. Therefore, our proposed method is practical and feasible and may become an effective tool for initially evaluating cardiac diseases.

Adsorption-desorption and leaching behavior of benzovindiflupyr in different soil types.

Benzovindiflupyr is a succinate dehydrogenase inhibitor fungicide that targets mitochondrial function for disease control. In this study, we investigated the adsorption-desorption and leaching behavior of benzovindiflupyr in eight soil types using the batch equilibrium method and the soil column leaching method. A Freundlich model (r2 > 0.9959) was used to better characterize the adsorption-desorption process in eight soil types, with adsorption coefficients (KF-ads) ranging from 2.303 to 17.886. KF-ads was significantly and positively correlated (p < 0.05) with the organic carbon content. High temperatures and increased initial pH of aqueous solutions led to a decrease in benzovindiflupyr adsorption in the soil. The adsorption was also influenced by factors such as ionic strength, humic acid, surfactant type, microplastic type, and particle size and concentration. Moreover, benzovindiflupyr exhibited low leachability in all four soils selected, but different leaching solutions affected the risk of benzovindiflupyr migration to groundwater. Overall, this study provides insights into the adsorption characteristics of benzovindiflupyr in different soils and provides key information for environmental risk assessment.

Hemi-diaphragm detection of chest X-ray images based on convolutional neural network and graphics.

BACKGROUND: Chest X-rays (CXR) are widely used to facilitate the diagnosis and treatment of critically ill and emergency patients in clinical practice. Accurate hemi-diaphragm detection based on postero-anterior (P-A) CXR images is crucial for the diaphragm function assessment of critically ill and emergency patients to provide precision healthcare for these vulnerable populations. OBJECTIVE: Therefore, an effective and accurate hemi-diaphragm detection method for P-A CXR images is urgently developed to assess these vulnerable populations' diaphragm function. METHODS: Based on the above, this paper proposes an effective hemi-diaphragm detection method for P-A CXR images based on the convolutional neural network (CNN) and graphics. First, we develop a robust and standard CNN model of pathological lungs trained by human P-A CXR images of normal and abnormal cases with multiple lung diseases to extract lung fields from P-A CXR images. Second, we propose a novel localization method of the cardiophrenic angle based on the two-dimensional projection morphology of the left and right lungs by graphics for detecting the hemi-diaphragm. RESULTS: The mean errors of the four key hemi-diaphragm points in the lung field mask images abstracted from static P-A CXR images based on five different segmentation models are 9.05, 7.19, 7.92, 7.27, and 6.73 pixels, respectively. Besides, the results also show that the mean errors of these four key hemi-diaphragm points in the lung field mask images abstracted from dynamic P-A CXR images based on these segmentation models are 5.50, 7.07, 4.43, 4.74, and 6.24 pixels,respectively. CONCLUSION: Our proposed hemi-diaphragm detection method can effectively perform hemi-diaphragm detection and may become an effective tool to assess these vulnerable populations' diaphragm function for precision healthcare.

Temporal and spatial evolution of net primary productivity in the Three-River Headwaters Region under phenological changes and anthropogenic influence.

Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 g C m - 2 yr - 1 , which is 0.132 times the average annual NPPC over the past 21 years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 g C m - 2 yr - 1 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1 year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21 years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.

MiR-34a-5p suppresses cutaneous squamous cell carcinoma progression by targeting SIRT6.

Cutaneous squamous cell carcinoma (cSCC) is a malignant tumor originating from epidermal or appendageal keratinocytes, with a rising incidence in recent years. Understanding the molecular mechanism driving its development is crucial. This study aims to investigate whether miR-34a-5p is involved in the pathogenesis of cSCC by targeting Sirtuin 6 (SIRT6).The expression levels of miR-34a-5p and SIRT6 were determined in 15 cSCC tissue specimens, 15 normal tissue specimens and cultured cells via real-time polymerase chain reaction (RT-qPCR). Pearson's correlation analysis was conducted to evaluate the relationship between miR-34a-5p and SIRT6 expression levels in cSCC tissues. A431 and SCL-1 cells were transfected with miR-34a-5p mimic, negative control or miR-34a-5p mimic together with recombinant plasmids containing SIRT6 gene. Cell counting kit-8, clone formation assay, wound healing assay, and flow cytometry were employed to assess the effects of these transfections on proliferation, migration, and apoptosis, respectively. The interaction between miR-34a-5p and SIRT6 was characterized using a dual-luciferase reporter assay.MiR-34a-5p expression was down-regulated in cSCC tissues significantly, while the SIRT6 expression was the opposite. A negative correlation was observed between the expression of miR-34a-5p and SIRT6 in cSCC tissues. Furthermore, overexpression of miR-34a-5p led to a significant reduction in the proliferation and migration abilities of A431 and SCL-1 cells, accompanied by an increase in apoptosis levels and a decrease in SIRT6 expression levels. MiR-34a-5p was identified as a direct target of SIRT6. Importantly, overexpression of SIRT6 effectively counteracted the inhibitory effect mediated by miR-34a-5p in cSCC cells.Our findings suggest that miR-34a-5p functions as a tumor suppressor in cSCC cells by targeting SIRT6.

Predicting short-term major postoperative complications in intestinal resection for Crohn's disease: A machine learning-based study.

BACKGROUND: Due to the complexity and numerous comorbidities associated with Crohn's disease (CD), the incidence of postoperative complications is high, significantly impacting the recovery and prognosis of patients. Consequently, additional studies are required to precisely predict short-term major complications following intestinal resection (IR), aiding surgical decision-making and optimizing patient care. AIM: To construct novel models based on machine learning (ML) to predict short-term major postoperative complications in patients with CD following IR. METHODS: A retrospective analysis was performed on clinical data derived from a patient cohort that underwent IR for CD from January 2017 to December 2022. The study participants were randomly allocated to either a training cohort or a validation cohort. The logistic regression and random forest (RF) were applied to construct models in the training cohort, with model discrimination evaluated using the area under the curves (AUC). The validation cohort assessed the performance of the constructed models. RESULTS: Out of the 259 patients encompassed in the study, 5.0% encountered major postoperative complications (Clavien-Dindo ≥ III) within 30 d following IR for CD. The AUC for the logistic model was 0.916, significantly lower than the AUC of 0.965 for the RF model. The logistic model incorporated a preoperative CD activity index (CDAI) of ≥ 220, a diminished preoperative serum albumin level, conversion to laparotomy surgery, and an extended operation time. A nomogram for the logistic model was plotted. Except for the surgical approach, the other three variables ranked among the top four important variables in the novel ML model. CONCLUSION: Both the nomogram and RF exhibited good performance in predicting short-term major postoperative complications in patients with CD, with the RF model showing more superiority. A preoperative CDAI of ≥ 220, a diminished preoperative serum albumin level, and an extended operation time might be the most crucial variables. The findings of this study can assist clinicians in identifying patients at a higher risk for complications and offering personalized perioperative management to enhance patient outcomes.

The role of the CXCR6/CXCL16 axis in the pathogenesis of fibrotic disease.

CXC chemokine receptor 6 (CXCR6), a seven-transmembrane domain G-protein-coupled receptor, plays a pivotal regulatory role in inflammation and tissue damage through its interaction with CXC chemokine ligand 16 (CXCL16). This axis is implicated in the pathogenesis of various fibrotic diseases and correlates with clinical parameters that indicate disease severity, activity, and prognosis in organ fibrosis, including afflictions of the liver, kidney, lung, cardiovascular system, skin, and intestines. Soluble CXCL16 (sCXCL16) serves as a chemokine, facilitating the migration and recruitment of CXCR6-expressing cells, while membrane-bound CXCL16 (mCXCL16) functions as a transmembrane protein with adhesion properties, facilitating intercellular interactions by binding to CXCR6. The CXCR6/CXCL16 axis is established to regulate the cycle of damage and repair during chronic inflammation, either through modulating immune cell-mediated intercellular communication or by independently influencing fibroblast homing, proliferation, and activation, with each pathway potentially culminating in the onset and progression of fibrotic diseases. However, clinically exploiting the targeting of the CXCR6/CXCL16 axis requires further elucidation of the intricate chemokine interactions within fibrosis pathogenesis. This review explores the biology of CXCR6/CXCL16, its multifaceted effects contributing to fibrosis in various organs, and the prospective clinical implications of these insights.

A correction method for radial distortion and nonlinear response of infrared cameras.

The key feature of non-contact temperature measurement provided by infrared (IR) cameras underpins their versatility. However, the accuracy of temperature measurements with IR cameras depends on imaging quality due to their non-contact nature, such as the lens, body temperature, and measurement environment. This paper addresses the correction of radial distortion and nonlinear response issues in IR cameras. To address radial distortion, we have designed a passive checkerboard calibration board specifically for infrared cameras. This board is used to calibrate the IR camera and derive the necessary camera parameters. Subsequently, these parameters are applied during the actual measurement process to rectify radial distortion effectively. Building on the radial distortion correction method mentioned above, we propose a multi-point segmented calibration approach that considers different temperature ranges and imaging regions. This method alleviates the issue of reduced temperature measurement accuracy due to variations in camera responses by computing gain and offset coefficient matrices for each temperature range. Experimental results demonstrate the effectiveness of the calibration board in correcting radial distortion in IR cameras, with a mean reprojection error of less than 0.16 pixels. Regarding the nonlinear response problem, the introduced method significantly reduces the relative error in temperature measurement. In the verification phase, spanning from 100 to 500 °C, the average relative error in temperature measurement decreases by 0.49% from 1.61% before and after correction, which highlights a substantial improvement in temperature measurement accuracy. This work gives a useful reference to improve the imaging quality and temperature measurement accuracy using infrared cameras.

Adsorption-desorption behavior of florpyrauxifen-benzyl on three microplastics in aqueous environment as well as its mechanism and various influencing factors.

Microplastics (MPs) and pesticides are two categories contaminants with proposed negative impacts to aqueous ecosystems, and adsorption of pesticides on MPs may result in their long-range transport and compound combination effects. Florpyrauxifen-benzyl, a novel pyridine-2-carboxylate auxin herbicide has been widely used to control weeds in paddy field, but the insights of which are extremely limited. Therefore, adsorption and desorption behaviors of florpyrauxifen-benzyl on polyvinyl chloride (PVC), polyethylene (PE) and disposable face masks (DFMs) in five water environment were investigated. The impacts of various environmental factors on adsorption capacity were evaluated, as well as adsorption mechanisms. The results revealed significant variations in adsorption capacity of florpyrauxifen-benzyl on three MPs, with approximately order of DFMs > PE > PVC. The discrepancy can be attributed to differences in structural and physicochemical properties, as evidenced by various characterization analysis. The kinetics and isotherm of florpyrauxifen-benzyl on three MPs were suitable for different models, wherein physical force predominantly governed adsorption process. Thermodynamic analysis revealed that both high and low temperatures weakened PE and DFMs adsorption, whereas temperature exhibited negligible impact on PVC adsorption. The adsorption capacity was significantly influenced by most environmental factors, particularly pH, cations and coexisting herbicide. This study provides valuable insights into the fate of florpyrauxifen-benzyl in presence of MPs, suggesting that PVC, PE and DFMs can serve as carriers of florpyrauxifen-benzyl in aquatic environment.

The relation between effortful control and executive function training in preschoolers.

In recent years, the question of whether executive function (EF) is malleable has been widely documented. Despite using the same training tasks, transfer effects remain uncertain. Researchers suggested that the inconsistency might be attributed to individual differences in temperamental traits. In the current study, we investigated how effortful control, a temperamental trait, would affect EF training outcomes in children. Based on parent rating, 79 6-year-old preschoolers were identified as having higher or lower effort control and were assigned to three conditions: working memory (WM) training, inhibitory control (IC) training, and a business-as-usual control group. Children completed assessments at baseline, 1 week after intervention (posttest), and 3 months after intervention (follow-up). As compared with the control group, the WM and IC training groups showed improvement in both trained tasks and nontrained measures. At baseline, children with higher effortful control scores showed greater WM capacity and better IC. Furthermore, effortful control was positively correlated with training gain in both training groups, with children with higher effortful control benefitting more through training. In the WM training group, effortful control was positively correlated with near transfer on WM outcomes both immediately and longitudinally. At posttest, the WM and IC training groups showed a positive correlation between effortful control and fluid intelligence performance. Our results underscore the importance of individual differences in training benefits, in particular the role of effortful control, and further illustrate the potential avenues for designing more effective individualized cognitive training programs to foster learning and optimize children's development.

Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15.

To enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3rd among 26 CASP15 server predictors and MULTICOM_human ranked 7th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

Transformation of colitis and colorectal cancer: a tale of gut microbiota.

Intestinal inflammation modifies host physiology to promote the occurrence of colorectal cancer (CRC), as seen in colitis-associated CRC. Gut microbiota is crucial in cancer progression, primarily by inducing intestinal chronic inflammatory microenvironment, leading to DNA damage, chromosomal mutation, and alterations in specific metabolite production. Therefore, there is an increasing interest in microbiota-based prevention and treatment strategies, such as probiotics, prebiotics, microbiota-derived metabolites, and fecal microbiota transplantation. This review aims to provide valuable insights into the potential correlations between gut microbiota and colitis-associated CRC, as well as the promising microbiota-based strategies for colitis-associated CRC.

Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15.

Since the 14th Critical Assessment of Techniques for Protein Structure Prediction (CASP14), AlphaFold2 has become the standard method for protein tertiary structure prediction. One remaining challenge is to further improve its prediction. We developed a new version of the MULTICOM system to sample diverse multiple sequence alignments (MSAs) and structural templates to improve the input for AlphaFold2 to generate structural models. The models are then ranked by both the pairwise model similarity and AlphaFold2 self-reported model quality score. The top ranked models are refined by a novel structure alignment-based refinement method powered by Foldseek. Moreover, for a monomer target that is a subunit of a protein assembly (complex), MULTICOM integrates tertiary and quaternary structure predictions to account for tertiary structural changes induced by protein-protein interaction. The system participated in the tertiary structure prediction in 2022 CASP15 experiment. Our server predictor MULTICOM_refine ranked 3rd among 47 CASP15 server predictors and our human predictor MULTICOM ranked 7th among all 132 human and server predictors. The average GDT-TS score and TM-score of the first structural models that MULTICOM_refine predicted for 94 CASP15 domains are ~0.80 and ~0.92, 9.6% and 8.2% higher than ~0.73 and 0.85 of the standard AlphaFold2 predictor respectively.

Hydrolysis of propyrisulfuron in water: Kinetics, influence of 34 environmental factors, transformation products identification, mechanisms and toxicities.

Propyrisulfuron is a novel sulfonylurea herbicide used for controlling annual grass and broad-leaved weeds in fields, but its fates and behaviors in environment are still unknown, which are of utmost importance for environmental protection. To reduce its potential environmental risks in agricultural production, the hydrolysis kinetics, influence of 34 environmental factors including 12 microplastics (MPs), disposable face masks (DFMs) and its different parts, 6 fertilizers, 5 ions, 3 surfactants, a co-existed herbicide of florpyrauxifen-benzy, humic acid and biochar, and the effect of MPs and DFMs on its hydrolysis mechanisms were systematically investigated. The main hydrolysis products (HPs), possible mechanisms, toxicities and potential risks to aquatic organisms were studied. Propyrisulfuron hydrolysis was an acid catalytic pyrolysis, endothermic and spontaneous process driven by the reduction of activation enthalpy, and followed the first-order kinetics. All environmental factors can accelerate propyrisulfuron hydrolysis to varying degrees except humic acid, and different hydrolysis mechanisms occurred in the presence of MPs and DFMs. In addition, 10 possible HPs and 7 possible mechanisms were identified and proposed. ECOSAR prediction and ecotoxicity testing showed that acute toxicity of propyrisulfuron and its HPs for aquatic organisms were low, but may have high chronic toxicity and pose a potential threat to aquatic ecosystems. The investigations are significantly important for elucidating the environmental fates and behaviors of propyrisulfuron, assessing the risks in environmental protection, and further providing guidance for scientific application in agro-ecosystem.

Degradation of a New Herbicide Florpyrauxifen-Benzyl in Water: Kinetics, Various Influencing Factors and Its Reaction Mechanisms.

Florpyrauxifen-benzyl is a novel herbicide used to control weeds in paddy fields. To clarify and evaluate its hydrolytic behavior and safety in water environments, its hydrolytic characteristics were investigated under varying temperatures, pH values, initial mass concentrations and water types, as well as the effects of 40 environmental factors such as microplastics (MPs) and disposable face masks (DFMs). Meanwhile, hydrolytic products were identified by UPLC-QTOF-MS/MS, and its hydrolytic pathways were proposed. The effects of MPs and DFMs on hydrolytic products and pathways were also investigated. The results showed that hydrolysis of florpyrauxifen-benzyl was a spontaneous process driven by endothermic, base catalysis and activation entropy increase and conformed to the first-order kinetics. The temperature had an obvious effect on hydrolysis rate under alkaline condition, the hydrolysis reaction conformed to Arrhenius formula, and activation enthalpy, activation entropy, and Gibbs free energy were negatively correlated with temperature. Most of environmental factors promoted hydrolysis of florpyrauxifen-benzyl, especially the cetyltrimethyl ammonium bromide (CTAB). The hydrolysis mechanism was ester hydrolysis reaction with a main product of florpyrauxifen. The MPs and DFMs did not affect the hydrolytic mechanisms but the hydrolysis rate. The results are crucial for illustrating and assessing the environmental fate and risks of florpyrauxifen-benzyl.

Enhancing AlphaFold-Multimer-based Protein Complex Structure Prediction with MULTICOM in CASP15.

AlphaFold-Multimer has emerged as the state-of-the-art tool for predicting the quaternary structure of protein complexes (assemblies or multimers) since its release in 2021. To further enhance the AlphaFold-Multimer-based complex structure prediction, we developed a new quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine the outputs generated by AlphaFold2-Multimer. Specifically, MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural models by using both traditional sequence alignments and new Foldseek-based structure alignments, ranks structural models through multiple complementary metrics, and refines the structural models via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. Our server (MULTICOM_qa) ranked 3rd among 26 CASP15 server predictors and our human predictor (MULTICOM_human) ranked 7th among 87 CASP15 server and human predictors. The average TM-score of the first models predicted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 models predicted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the novel Foldseek Structure Alignment-based Model Generation (FSAMG) method based on AlphaFold-Multimer outperforms the widely used sequence alignment-based model generation. The source code of MULTICOM is available at: https://github.com/BioinfoMachineLearning/MULTICOM3.

How does digital infrastructure affect residents' healthcare expenditures? Evidence from Chinese microdata.

Healthcare expenditure is only one of the heavy burdens that families face in developing countries. Current research mainly focuses on analyzing the effects of financial policy. There is a lack of studies that examine the understanding and assessment of the impact of digital infrastructure on this issue. In this study, we used the Broadband China policy as a quasi-natural experiment to explore the impact of digital infrastructure on residents' healthcare expenditures in China. Using the differences-in-differences (DID) model and micro-survey data, we found that digital infrastructure has a positive impact on reducing the burden of healthcare expenditure in China. Our findings indicate that residents in cities can save up to 18.8% on healthcare expenses following large-scale digital infrastructure construction. Through mechanism analysis, we found that digital infrastructure reduces residents' healthcare expenditures by improving both commercial insurance availability and the healthcare efficiency of residents. In addition, the effects of digital infrastructure on reducing healthcare expenditure are more pronounced among middle-aged individuals, those with low levels of education, and those with low incomes, which indicates this digital construction wave helps bridge the social gap between the poor and the rich. This study provides compelling evidence of the positive impact of digital society construction on social health and wellbeing.