Acetylation-dependent regulation of core spliceosome modulates hepatocellular carcinoma cassette exons and sensitivity to PARP inhibitors.

Despite the importance of spliceosome core components in cellular processes, their roles in cancer development, including hepatocellular carcinoma (HCC), remain poorly understood. In this study, we uncover a critical role for SmD2, a core component of the spliceosome machinery, in modulating DNA damage in HCC through its impact on BRCA1/FANC cassette exons and expression. Our findings reveal that SmD2 depletion sensitizes HCC cells to PARP inhibitors, expanding the potential therapeutic targets. We also demonstrate that SmD2 acetylation by p300 leads to its degradation, while HDAC2-mediated deacetylation stabilizes SmD2. Importantly, we show that the combination of Romidepsin and Olaparib exhibits significant therapeutic potential in multiple HCC models, highlighting the promise of targeting SmD2 acetylation and HDAC2 inhibition alongside PARP inhibitors for HCC treatment.

Study on the photosynthetic growth characters in Cimicifuga dahurica (Turcz.) Maxim under different supplemental light environments.

Cimicifuga dahurica (C. dahurica) is an important medicinal plant in the northern region of China. The best supplemental light environment helps plant growth, development, and metabolism. In this study, we used two-year-old seedlings as experimental materials. The white light as the control (CK). The different ratios of red (R) and blue (B) combined light were supplemented (T1, 2R: 1B, 255.37 µmol m-2·s-1; T2, 3R: 1B, 279.69 µmol m-2·s-1; T3, 7R: 1B, 211.16 µmol m-2·s-1). The growth characteristics, photosynthetic pigment content, photosynthesis and chlorophyll fluorescence parameters, and primary metabolite content were studied in seedlings. The results showed that: 1) The fresh weight from shoot, root, and total fresh weight were significantly (P < 0.05) increased under T2 and T3 treatment. 2) The contents of chlorophyll a (Chl a), chlorophyll b (Chl b), and total chlorophyll (Chl) were significantly (P < 0.05) increased under T2 treatment, and carotenoid (car) content was reduced. 3) The photochemical quenching (qP), the actual photosynthetic efficiency of PSII (Y(II)), and the photosynthetic electron transfer rate (ETR) from leaves were significantly (P < 0.05) increased under T1 treatment. The Net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO2 concentration (Ci), and transpiration rate (Tr) were significantly (P < 0.05) increased under T2 and T3 treatments. 4) A total of 52 primary metabolites were detected in C. dahurica leaves. Compared with CK, 14, 15, and 18 differential metabolites were screened under T1, T2, and T3 treatments. In addition, D-xylose, D-glucose, glycerol, glycolic acid, and succinic acid were significantly (P < 0.05) accumulated under the T2 treatment, which could regulate the TCA cycle metabolism pathway. The correlation analysis suggested that plant growth was promoted by regulating the change of D-mannose content in galactinol metabolism and amino sugar and nucleotide sugar metabolism. In summary, the growth of C. dahurica was improved under T2 treatment.

Simultaneous production of biosurfactant and extracellular unspecific peroxygenases by Moesziomyces aphidis XM01 enables an efficient strategy for crude oil degradation.

Crude oil is a hazardous pollutant that poses significant and lasting harm to human health and ecosystems. In this study, Moesziomyces aphidis XM01, a biosurfactant mannosylerythritol lipids (MELs)-producing yeast, was utilized for crude oil degradation. Unlike most microorganisms relying on cytochrome P450, XM01 employed two extracellular unspecific peroxygenases, MaUPO.1 and MaUPO.2, with preference for polycyclic aromatic hydrocarbons (PAHs) and n-alkanes respectively, thus facilitating efficient crude oil degradation. The MELs produced by XM01 exhibited a significant emulsification activity of 65.9% for crude oil and were consequently supplemented in an "exogenous MELs addition" strategy to boost crude oil degradation, resulting in an optimal degradation ratio of 72.3%. Furthermore, a new and simple "pre-MELs production" strategy was implemented, achieving a maximum degradation ratio of 95.9%. During this process, the synergistic up-regulation of MaUPO.1, MaUPO.1 and the key MELs synthesis genes contributed to the efficient degradation of crude oil. Additionally, the phylogenetic and geographic distribution analysis of MaUPO.1 and MaUPO.1 revealed their wide occurrence among fungi in Basidiomycota and Ascomycota, with high transcription levels across global ocean, highlighting their important role in biodegradation of crude oil. In conclusion, M. aphidis XM01 emerges as a novel yeast for efficient and eco-friendly crude oil degradation.

Design and construction of chemical-biological module clusters for degradation and assimilation of poly(ethylene terephthalate) waste.

The rising accumulation of poly(ethylene terephthalate) (PET) waste presents an urgent ecological challenge, necessitating an efficient and economical treatment technology. Here, we developed chemical-biological module clusters that perform chemical pretreatment, enzymatic degradation, and microbial assimilation for the large-scale treatment of PET waste. This module cluster included (i) a chemical pretreatment that involves incorporating polycaprolactone (PCL) at a weight ratio of 2% (PET:PCL = 98:2) into PET via mechanical blending, which effectively reduces the crystallinity and enhances degradation; (ii) enzymatic degradation using Thermobifida fusca cutinase variant (4Mz), that achieves complete degradation of pretreated PET at 300 g/L PET, with an enzymatic loading of 1 mg protein per gram of PET; and (iii) microbial assimilation, where Rhodococcus jostii RHA1 metabolizes the degradation products, assimilating each monomer at a rate above 90%. A comparative life cycle assessment demonstrated that the carbon emissions from our module clusters (0.25 kg CO2-eq/kg PET) are lower than those from other established approaches. This study pioneers a closed-loop system that seamlessly incorporates pretreatment, degradation, and assimilation processes, thus mitigating the environmental impacts of PET waste and propelling the development of a circular PET economy.

A Single-Cell Landscape of Spermioteleosis in Mice and Pigs.

(1) Background: Spermatozoa acquired motility and matured in epididymis after production in the testis. However, there is still limited understanding of the specific characteristics of sperm development across different species. In this study, we employed a comprehensive approach to analyze cell compositions in both testicular and epididymal tissues, providing valuable insights into the changes occurring during meiosis and spermiogenesis in mouse and pig models. Additionally, we identified distinct gene expression signatures associated with various spermatogenic cell types. (2) Methods: To investigate the differences in spermatogenesis between mice and pigs, we constructed a single-cell RNA dataset. (3) Results: Our findings revealed notable differences in testicular cell clusters between these two species. Furthermore, distinct gene expression patterns were observed among epithelial cells from different regions of the epididymis. Interestingly, regional gene expression patterns were also identified within principal cell clusters of the mouse epididymis. Moreover, through analysing differentially expressed genes related to the epididymis in both mouse and pig models, we successfully identified potential marker genes associated with sperm development and maturation for each species studied. (4) Conclusions: This research presented a comprehensive single-cell landscape analysis of both testicular and epididymal tissues, shedding light on the intricate processes involved in spermatogenesis and sperm maturation, specifically within mouse and pig models.

Transformer based Pluralistic Image Completion with Reduced Information Loss.

Transformer based methods have achieved great success in image inpainting recently. However, we find that these solutions regard each pixel as a token, thus suffering from an information loss issue from two aspects: 1) They downsample the input image into much lower resolutions for efficiency consideration. 2) They quantize 2563 RGB values to a small number (such as 512) of quantized color values. The indices of quantized pixels are used as tokens for the inputs and prediction targets of the transformer. To mitigate these issues, we propose a new transformer based framework called "PUT". Specifically, to avoid input downsampling while maintaining computation efficiency, we design a patch-based auto-encoder P-VQVAE. The encoder converts the masked image into non-overlapped patch tokens and the decoder recovers the masked regions from the inpainted tokens while keeping the unmasked regions unchanged. To eliminate the information loss caused by input quantization, an Un-quantized Transformer is applied. It directly takes features from the P-VQVAE encoder as input without any quantization and only regards the quantized tokens as prediction targets.Furthermore, to make the inpainting process more controllable, we introduce semantic and structural conditions as extra guidance. Extensive experiments show that our method greatly outperforms existing transformer based methods on image fidelity and achieves much higher diversity and better fidelity than state-of-the-art pluralistic inpainting methods on complex large-scale datasets (e.g., ImageNet). Codes are available at https://github.com/liuqk3/PUT.

Effects of flaxseed oil supplementation on metaphase II oocyte rates in IVF cycles with decreased ovarian reserve: a randomized controlled trial.

Background: This study was designed to explore the effects of flaxseed oil on the metaphase II (MII) oocyte rates in women with decreased ovarian reserve (DOR). Methods: The women with DOR were divided into a study group (n = 108, flaxseed oil treatment) and a control group (n = 110, no treatment). All patients were treated with assisted reproductive technology (ART). Subsequently, the ART stimulation cycle parameters, embryo transfer (ET) results, and clinical reproductive outcomes were recorded. The influencing factors affecting the MII oocyte rate were analyzed using univariate analysis and multivariate analysis. Results: Flaxseed oil reduced the recombinant human follicle-stimulating hormone (r-hFSH) dosage and stimulation time and increased the peak estradiol (E2) concentration in DOR women during ART treatment. The MII oocyte rate, fertilization rate, cleavage rate, high-quality embryo rate, and blastocyst formation rate were increased after flaxseed oil intervention. The embryo implantation rate of the study group was higher than that of the control group (p = 0.05). Additionally, the female age [odds ratio (OR): 0.609, 95% confidence interval (CI): 0.52-0.72, p < 0.01] was the hindering factor of MII oocyte rate, while anti-Müllerian hormone (AMH; OR: 100, 95% CI: 20.31-495, p < 0.01), peak E2 concentration (OR: 1.00, 95% CI: 1.00-1.00, p = 0.01), and the intake of flaxseed oil (OR: 2.51, 95% CI: 1.06-5.93, p = 0.04) were the promoting factors for MII oocyte rate. Conclusion: Flaxseed oil improved ovarian response and the quality of oocytes and embryos, thereby increasing the fertilization rate and high-quality embryo rate in DOR patients. The use of flaxseed oil was positively correlated with MII oocyte rate in women with DOR. Clinical trial number: https://www.chictr.org.cn/, identifier ChiCTR2300073785.

Exploring the Application of Large-Scale Pre-Trained Models on Adverse Weather Removal.

Image restoration under adverse weather conditions (e.g., rain, snow, and haze) is a fundamental computer vision problem that has important implications for various downstream applications. Distinct from early methods that are specially designed for specific types of weather, recent works tend to simultaneously remove various adverse weather effects based on either spatial feature representation learning or semantic information embedding. Inspired by various successful applications incorporating large-scale pre-trained models (e.g., CLIP), in this paper, we explore their potential benefits for leveraging large-scale pre-trained models in this task based on both spatial feature representation learning and semantic information embedding aspects: 1) spatial feature representation learning, we design a Spatially Adaptive Residual (SAR) encoder to adaptively extract degraded areas. To facilitate training of this model, we propose a Soft Residual Distillation (CLIP-SRD) strategy to transfer spatial knowledge from CLIP between clean and adverse weather images; 2) semantic information embedding, we propose a CLIP Weather Prior (CWP) embedding module to enable the network to adaptively respond to different weather conditions. This module integrates the sample-specific weather priors extracted by the CLIP image encoder with the distribution-specific information (as learned by a set of parameters) and embeds these elements using a cross-attention mechanism. Extensive experiments demonstrate that our proposed method can achieve state-of-the-art performance under various and severe adverse weather conditions. The code will be made available.

Alterations in white matter fiber tracts and their correlation with flying cadet behavior.

An increasing number of studies have shown that flight training alters the human brain structure; however, most studies have focused on gray matter, and the exploration of white matter structure has been largely neglected. This study aimed to investigate the changes in white matter structure induced by flight training and estimate the correlation between such changes and psychomotor and flight performance. Diffusion tensor imaging data were obtained from 25 flying cadets and 24 general college students. Data were collected in 2019 and 2022 and analyzed using automated fiber quantification. This study found no significant changes in the flight group in 2019. However, in 2022, the flight group exhibited significant alterations in the diffusion tensor imaging of the right anterior thalamic radiation, left cingulum cingulate, bilateral superior longitudinal fasciculus, and left arcuate fasciculus. These changes occurred within local nodes of the fiber tracts. In addition, we found that changes in fiber tracts in the 2022 flight group were correlated with the reaction time of the psychomotor test task and flight duration. These findings may help improve flight training programs and provide new ideas for the selection of excellent pilots.

Complete degradation of PET waste using a thermophilic microbe-enzyme system.

Enzymatic degradation has been proposed as a suitable solution for addressing PET pollution, but approximately 10 % of PET is left as nonbiodegradable. Microbes can completely degrade PET at the gram level per year. Based on the complementary benefits of microbes and enzymes, a microbe-enzyme system was created to completely degrade PET. Here, a thermophilic microbe-enzyme (TME) system composed of Bacillus thermoamylovorans JQ3 and leaf-branch compost cutinase variant (ICCG) was used to demonstrate the synergistic degradation of PET, enabling 100 % degradation of PET waste at a high PET loading level (360 g/L). Six endogenous PET hydrolases of strain JQ3 were discovered by employing an ester bond hydrolysis function-first genome mining (EGM) strategy and first successfully expressed in E. coli. These hydrolases could release TPA as the final product from PET and preferentially degraded BHET instead of MHET. Of these, carboxylesterase 39_5 and ICCG could degrade PET in a synergistic manner to generate 50 µM of TPA, which was greater than the sum of the individual treatments. Finally, the degradation pathway of the TME system was speculated to include biofilm formation, PET degradation and utilization. The successful implementation of this study rendered a scale-up degradation feasible of PET at a lower cost.

Suppression of LPS-activated inflammatory responses and chromosomal histone modifications in macrophages by micropattern-induced nuclear deformation.

Macrophages are important immune effector cells which participate various physiological and pathological conditions. Numerous studies have demonstrated the regulation of macrophage phenotype by micropatterns. It is well accepted that micropatterns affect cellular behaviors through changing cell shape and modulating the associated mechanical sensors on the plasma membrane and cytoskeleton. However, the role of nucleus, which serves as a critical physical sensing device, is often ignored. Herein, we found the nuclear deformation and the subsequently increased chromosomal histone methylation (H3K36me2) may contribute to the micropattern-induced suppression of macrophage inflammatory responses. Specifically, macrophages on micropatterned surfaces expressed lower levels of key inflammatory genes, compared with those on flat surfaces. Further investigation on macrophage nuclei showed that micropatterned surfaces cause shrinkage of nucleus volume and compaction of chromatin. Moreover, micropatterned surfaces elevated the methylation level of H3K36me2 in macrophages, while decreased the methylation level of H3K4me3. Our study provides new mechanistic insight into how micropatterns affect macrophage phenotype and highlights the importance of nuclear shape and chromatin histone modification in mediating micropattern-induced change in cell behaviors.

Investigation of Altered Spontaneous Brain Activity Patterns in Herpes Zoster Keratitis Using the Percent Amplitude of Fluctuation Method: A Resting-State Functional Magnetic Resonance Imaging Study.

Purpose: The purpose of this study was to use the percent amplitude of fluctuation (PerAF) to study the changes in brain activity and nerve function of herpes zoster keratitis (HZK) patients. Methods: We recruited 20 HZK patients and 20 healthy controls (HCs). Each of these groups included ten males and ten females and were matched in weight and age. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI). The percent amplitude of fluctuation (PerAF) method was used for analysis and detected differences between the two groups in the neurological function of brain areas. We also applied the receiver operating characteristic (ROC) curve to analyze the two groups and did a correlation analysis between the PerAF value, anxiety and depression score, and visual acuity. Results: The PerAF signal at the right putamen and right precentral gyrus was significantly higher in patients than in HCs. However, the PerAF value of the left inferior temporal was lower in patients than in HCs. In addition, the HZK patients' anxiety and depression score (HADS) and visual acuity (V.A.) Log MAR negatively correlated with the PerAF value at the left inferior temporal gyrus. Conclusion: HZK patients had some changes in brain regions, and the changes were also related to their mood and visual acuity. These findings might contribute to other studies on the potential pathological mechanism, disease development, prognosis, and brain function in HZK patients.

Optical noise characteristics of injection-locked epitaxial quantum dot lasers on silicon.

This work theoretically investigates the relative intensity noise (RIN) and spectral linewidth characteristics of epitaxial quantum dot (QD) lasers on silicon subject to optical injection. The results show that the RIN of QD lasers can be reduced by optical injection, hence a reduction of 10 dB is achieved which leads to a RIN as low as -167.5 dB/Hz in the stable injection-locked area. Furthermore, the spectral linewidth of the QD laser can be greatly improved through the optical injection locked scheme. It is reduced from 556.5 kHz to 9 kHz with injection ratio of -60 dB and can be further reduced down to 1.5 Hz with injection ratio of 0 dB. This work provides an effective method for designing low intensity noise and ultra-narrow linewidth QD laser sources for photonics integrated circuits on silicon.

Modulating Myofibroblastic Differentiation of Fibroblasts through Actin-MRTF Signaling Axis by Micropatterned Surfaces for Suppressed Implant-Induced Fibrosis.

Myofibroblasts, the primary effector cells for implant-induced fibrosis, contribute to this process by secreting excessive collagen-rich matrix and contracting. Thus, approaches that suppress myofibroblasts may achieve desirable suppression effects in the fibrotic process. As one of the important physical properties of materials, material topographical structures have been proven to affect various aspects of cell behaviors, so is it possible to manipulate the formation of myofibroblasts by tailoring the topographical properties of medical devices? In this study, polycaprolactone (PCL) surfaces with typical micropatterns (micro column and micro pit) were fabricated. The regulatory effects of surface micropatterns on the myofibroblastic differentiation of fibroblasts were investigated. Compared to the flat surfaces and surfaces with micro pit, surfaces with micro columns triggered the F- to G-actin transition, inhibiting the nuclear transfer of myocardin-related transcription factor-A. Subsequently, the downstream gene α-smooth muscle actin, which is a marker of myofibroblasts, was suppressed. Further in vivo investigation showed that PCL implants with micro-column-patterned surfaces inhibited the formation of peri-implant fibrotic capsules. Our results demonstrate that surface topographical properties are a potent regulator of fibroblast differentiation into myofibroblasts and highlight the antifibrotic potential of modifying surfaces with micro-column patterns.

Interface Design of 3D Flower-like Ag@ZnSe Composites: SERS and Photocatalytic Performance.

In this work, we cosputtered Ag and ZnSe on a polystyrene template to form a three-dimensional (3D) Ag@ZnSe (x) structure. The 3D surface morphology and material composition that provided abundant "hot spots" were controlled by adjusting the sputtering power of the ZnSe, which was confirmed by finite-difference time-domain (FDTD) simulation. The introduction of ZnSe into the noble metal Ag also introduced a charge-transfer (CT) effect into the system, and the CT path was proven with the two-dimensional correlation spectroscopy (2D-COS)-surface-enhanced Raman scattering (SERS) technique. In addition, the substrate exhibited excellent catalytic activity due to the CT effect. The catalyzed degradation of malachite green (MG) was due to the CT effect in the system, and the catalytic process was successfully monitored by in situ SERS. Most importantly, the catalytic degradation by Ag@ZnSe (x) with different parameters was proportional to the degree of CT (ρCT). The SERS and catalytic mechanisms were analyzed in depth with the 2D-COS-SERS technique, which was also useful in verifying the CT process. The catalytic sites for MG were successfully monitored with the 2D-COS-SERS technique. This study provides a reference for studies of the synergistic effects of the electromagnetic mechanism and CT, as well as a new perspective on photocatalysis with dye molecules and monitoring of the catalytic processes.

Bayesian inference of heavy metals exposure in crayfish for assessing human non-carcinogenic health risk.

Contaminant concentrations often presented left censorship that below the limit of detection (LOD), which may contain true zero values because of no residue. In this study, we analyzed the concentrations of lead (Pb), cadmium (Cd), mercury (Hg), arsenic (As), and chromium (Cr) in 391 crayfish samples collected from 24 provinces of China, modelled the concentrations with two different models in a Bayesian framework, and evaluated health risk by estimating the target hazard quotient (THQ). The highest concentration was associated with Cr in Northwest China (0.1753 ± 0.1520 mg/kg w. w.), and the minimum concentration was Cd in Southwest China (0.0052 ± 0.0144 mg/kg w. w.), all heavy metal concentrations were below their safety limits. The posterior means of not detect rates P0 of Pb, Cd, Hg, As, and Cr obtained with two models were both nearly equal to the observed not detect rates (51.15%, 36.83%, 27.37%, 64.71%, and 43.73%, respectively). The posterior probabilistic density lines for Pb, Hg, and Cd concentrations obtained with two models were similar, and fitted the empirical distributions well. The posterior density lines of THQs showed that the non-carcinogenic risk of As and Hg were significant high. Moreover, Bayesian approach presented a better understanding of the percentage of population exposed to potential risk.

Controllable hot electron transfer in the Ag/MoO3 layer by layer system: Thickness-dependent MoO3 layer.

The Ag and MoO3 layer-by-layer sputtering method was employed to fabricate Ag/MoO3 coated on a polystyrene (PS) array (Ag/MoO3@PS), which exhibited excellent surface-enhanced Raman scattering (SERS) activity. The thickness of the MoO3 layer was controlled by changing the sputtering power. The SERS intensity of 4-aminothiophenol (PATP) on Ag/MoO3@PS with a 2 nm thickness of the MoO3 layer was comparable to that on pure Ag coated on the PS array (Ag@PS). This is possible because hot electrons were injected from Ag into the MoO3 layer to enhance the photocatalyst reaction; thus, the SERS spectra of coupled PATP were obtained. The transport of hot electrons rapidly decayed and was blocked with increasing thickness of the MoO3 layer from 2 nm to 9 nm. Thus, the SERS intensity decreased, and interestingly, the b2 mode of PATP decreased and nearly disappeared. This study provides new insight into the control of hot electron reduction for catalytic reduction process monitoring.

Comparison of the predictive value of anthropometric indicators for the risk of benign prostatic hyperplasia in southern China.

This study aimed to compare the predictive value of six selected anthropometric indicators for benign prostatic hyperplasia (BPH). Males over 50 years of age who underwent health examinations at the Health Management Center of the Second Xiangya Hospital, Central South University (Changsha, China) from June to December 2020 were enrolled in this study. The characteristic data were collected, including basic anthropometric indices, lipid parameters, six anthropometric indicators, prostate-specific antigen, and total prostate volume. The odds ratios (ORs) with 95% confidence intervals (95% CIs) for all anthropometric parameters and BPH were calculated using binary logistic regression. To assess the diagnostic capability of each indicator for BPH and identify the appropriate cutoff values, receiver operating characteristic (ROC) curves and the related areas under the curves (AUCs) were utilized. All six indicators had diagnostic value for BPH (all P ≤ 0.001). The visceral adiposity index (VAI; AUC: 0.797, 95% CI: 0.759-0.834) had the highest AUC and therefore the highest diagnostic value. This was followed by the cardiometabolic index (CMI; AUC: 0.792, 95% CI: 0.753-0.831), lipid accumulation product (LAP; AUC: 0.766, 95% CI: 0.723-0.809), waist-to-hip ratio (WHR; AUC: 0.660, 95% CI: 0.609-0.712), waist-to-height ratio (WHtR; AUC: 0.639, 95% CI: 0.587-0.691), and body mass index (BMI; AUC: 0.592, 95% CI: 0.540-0.643). The sensitivity of CMI was the highest (92.1%), and WHtR had the highest specificity of 94.1%. CMI consistently showed the highest OR in the binary logistic regression analysis. BMI, WHtR, WHR, VAI, CMI, and LAP all influence the occurrence of BPH in middle-aged and older men (all P ≤ 0.001), and CMI is the best predictor of BPH.

Concurrent external validation of bloodstream infection probability models.

OBJECTIVE: Accurately estimating the likelihood of bloodstream infection (BSI) can help clinicians make diagnostic and therapeutic decisions. Many multivariate models predicting BSI probability have been published. This study measured the performance of BSI probability models within the same patient sample. METHODS: We retrieved validated BSI probability models included in a recently published systematic review that returned a patient-level BSI probability for adults. Model applicability, discrimination, and accuracy was measured in a simple random sample of 4485 admitted adults having blood cultures ordered in the emergency department or the initial 48 hours of hospitalization. RESULTS: Ten models were included (publication years 1991-2015). Common methodological threats to model performance included overfitting and continuous variable categorization. Restrictive inclusion criteria caused seven models to apply to <15% of validation patients. Model discrimination was less than originally reported in derivation groups (median c-statistic 60%, range 48-69). The observed BSI risk frequently deviated from expected (median integrated calibration index 4.0%, range 0.8-12.4). Notable disagreement in expected BSI probabilities was seen between models (median (25th-75th percentile) relative difference between expected risks 68.0% (28.6-113.6%)). DISCUSSION: In a large randomly selected external validation population, many published BSI probability models had restricted applicability, limited discrimination and calibration, and extensive inter-model disagreement. Direct comparison of model performance is hampered by dissimilarities between model-specific validation groups.

Semantic Probability Distribution Modeling for Diverse Semantic Image Synthesis.

Semantic image synthesis, translating semantic layouts to photo-realistic images, is a one-to-many mapping problem. Though impressive progress has been recently made, diverse semantic synthesis that can efficiently produce semantic-level or even instance-level multimodal results, still remains a challenge. In this article, we propose a novel diverse semantic image synthesis framework from the perspective of semantic class distributions, which naturally supports diverse generation at both semantics and instance level. We achieve this by modeling class-level conditional modulation parameters as continuous probability distributions instead of discrete values, and sampling per-instance modulation parameters through instance-adaptive stochastic sampling that is consistent across the network. Moreover, we propose prior noise remapping, through linear perturbation parameters encoded from paired references, to facilitate supervised training and exemplar-based instance style control at test time. To further extend the user interaction function of the proposed method, we also introduce sketches into the network. In addition, specially designed generator modules, Progressive Growing Module and Multi-Scale Refinement Module, can be used as a general module to improve the performance of complex scene generation. Extensive experiments on multiple datasets show that our method can achieve superior diversity and comparable quality compared to state-of-the-art methods. Codes are available at https://github.com/tzt101/INADE.git.