Inflammatory shift alterations of proinflammatory and anti-inflammatory cytokines in unexplained recurrent miscarriage patients.

This study aimed to investigate the pro-inflammatory and anti-inflammatory cytokines status in the peripheral blood of uRM patients. The plasma pro-inflammatory (IFN-γ, IL-6, IL-1ß, and TNF-α) and anti-inflammatory (TGF-ß1, IL-10, and IL-4) cytokines of 25 patients with uRM were compared to 33 women with a successful pregnancy. It was concluded that patients with uRM have an excess pro-inflammatory cytokines status.

BpAFP, a Broussonetia papyrifera latex chitinase, exhibits a dual role in resisting to both Verticillium wilt disease and lepidopterous pests, Plutella xylostella and Prodenia litura.

Paper mulberry (Broussonetia papyrifera) is a fast-growing tree known for its tolerance to diverse biotic and abiotic stresses. To explore genes combating Verticillium wilt, a devasting and formidable disease damage to cotton and many economically significant crops, we purified an antifungal protein, named BpAFP, from the latex of paper mulberry. Based on peptide fingerprint, we cloned the full cDNA sequence of BpAFP and revealed that BpAFP belongs to Class I chitinases, sharing 74% identity with B. papyrifera leaf chitinase, PMAPII. We further introduced BpAFP into Arabidopsis, tobacco, and cotton. Transgenic plants exhibited significant resistance to Verticillium wilt. Importantly, BpAFP also demonstrated insecticidal activity against herbivorous pests, Plutella xylostella, and Prodenia litura, when feeding the larvae with transgenic leaves. Our finding unveils a dual role of BpAFP in conferring resistance to both plant diseases and lepidopterous pests.

CoF-DResNet: Cancer Metastasis Recognition Network based on Dynamic Coordinated Metabolic Attention and Structural Attention.

BACKGROUND: Cancer metastasis usually means that cancer cells spread to other tissues or organs, and the condition worsens. Identifying whether cancer has metastasized can help doctors infer the progression of a patient's condition and is an essential prerequisite for devising treatment plans. Fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography ( 18F -FDG PET/CT) is an advanced cancer diagnostic imaging technique that provides both metabolic and structural information. METHOD: In cancer metastasis recognition tasks, effectively integrating metabolic and structural information stands as a key technology to enhance feature representation and recognition performance. This paper proposes a cancer metastasis identification network based on dynamic coordinated metabolic attention and structural attention to address these challenges. Specifically, metabolic and structural features are extracted by incorporating a dynamic coordinated attention module (DCAM) into two branches of ResNet networks, thereby amalgamating high metabolic spatial information from PET images with texture structure information from CT images, and dynamically adjusting this process through iterations. DISCUSSION: Next, to improve the efficacy of feature expression, a multi-receptive field feature fusion module (MRFM) is included in order to execute multi-receptive field fusion of semantic features. RESULT: To validate the effectiveness of our proposed model, experiments were conducted on both a private lung lymph nodes dataset and a public soft tissue sarcomas dataset. CONCLUSION: The accuracy of our method reached 76.0% and 75.1% for the two datasets, respectively, demonstrating an improvement of 6.8% and 5.6% compared to ResNet, thus affirming the efficacy of our method.

Associations of Urinary Heavy Metal Mixtures with High Remnant Cholesterol among US Adults: Evidence from the National Health and Nutrition Examination Survey (1998-2018).

The main objective of our study is to explore the associations between combined exposure to urinary heavy metals and high remnant cholesterol (HRC), a known cardiovascular risk factor. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we conducted a cross-sectional analysis of 5690 participants, assessing urinary concentrations of ten heavy metals. Ten heavy metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Fasting residual cholesterol ≥0.8 mmol/L was defined as HRC (using blood samples). Statistical analyses included weighted multivariable logistic regression, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the associations of heavy metal exposure with HRC. Stratified analyses based on individual characteristics were also conducted. Multivariable logistic regression found that the four metals (OR Q4 vs. Q1: 1.33, 95% CI: 1.01-1.75 for barium (Ba); OR Q4 vs. Q1: 1.50, 95% CI: 1.16-1.94 for cadmium (Cd); OR Q4 vs. Q1: 1.52, 95% CI: 1.15-2.01 for mercury (Hg); OR Q4 vs. Q1: 1.35, 95% CI: 1.06-1.73 for lead (Pb)) were positively correlated with the elevated risk of HRC after adjusting for covariates. In addition, all three mixed models, including WQS (OR: 1.25; 95% CI: 1.07-1.46), qgcomp (OR: 1.17; 95% CI: 1.03-1.34), and BKMR, consistently showed a significant positive correlation between co-exposure to heavy metal mixtures and HRC, with Ba and Cd being the main contributors within the mixture. These associations were more pronounced in younger adults (20 to 59 years), males, and those with a higher body mass index status (≥25 kg/m2). Our findings reveal a significant relationship between exposure to the mixture of heavy metals and HRC among US adults, with Ba and Cd being the major contributors to the mixture's overall effect. Public health efforts aimed at reducing heavy metal exposure can help prevent HRC and, in turn, cardiovascular disease.

Numerical investigation on the impact of different coronary aneurysms morphologies on thrombus formation and hemodynamics: a comparative study.

Coronary artery aneurysms (CAAs) are morphologically classified as saccular and fusiform. There is still a great deal of clinical controversy as to which types of CAA are more likely to cause thrombosis. Therefore, the main objective of this study was to evaluate the trend of thrombus growth in CAAs with different morphologies and to assess the risk of possible long-term complications based on hemodynamic parameters. Utilizing computed tomography angiography (CTA) data from eight healthy coronary arteries, two distinct morphologies of coronary artery aneurysms (CAAs) were reconstructed. Distribution of four wall shear stress (WSS)-based indicators and three helicity indicators was analyzed in this study. Meanwhile, a thrombus growth model was introduced to analyze the thrombus formation in CAAs with different morphologies. The research results showed the distribution of most WSS indicators between saccular and fusiform CAAs was not statistically significant. However, due to the presence of a more pronounced helical flow pattern, irregular helical flow structure and longer time of flow stagnation in saccular CAAs during the cardiac cycle, the mean and maximum relative residence time (RRT) were significantly higher in saccular CAAs than in fusiform CAAs (P < 0.05). This may increase the risk of saccular coronary arteries leading to aneurysmal dilatation or even rupture. Although the two CAAs had similar rates of thrombosis, fusiform CAAs may more early cause obstruction of the main coronary flow channel where the aneurysm is located due to thrombosis growth. Thus, the risk of thrombosis in fusiform coronary aneurysms may warrant greater clinical concern.

Unraveling the genetic basis of the causal association between inflammatory cytokines and osteonecrosis.

Background: Previous studies have reported that the occurrence and development of osteonecrosis is closely associated with immune-inflammatory responses. Mendelian randomization was performed to further assess the causal correlation between 41 inflammatory cytokines and osteonecrosis. Methods: Two-sample Mendelian randomization utilized genetic variants for osteonecrosis from a large genome-wide association study (GWAS) with 606 cases and 209,575 controls of European ancestry. Another analysis included drug-induced osteonecrosis with 101 cases and 218,691 controls of European ancestry. Inflammatory cytokines were sourced from a GWAS abstract involving 8,293 healthy participants. The causal relationship between exposure and outcome was primarily explored using an inverse variance weighting approach. Multiple sensitivity analyses, including MR-Egger, weighted median, simple model, weighted model, and MR-PRESSO, were concurrently applied to bolster the final results. Results: The results showed that bFGF, IL-2 and IL2-RA were clinically causally associated with the risk of osteonecrosis (OR=1.942, 95% CI=1.13-3.35, p=0.017; OR=0.688, 95% CI=0.50-0.94, p=0.021; OR=1.386, 95% CI=1.04-1.85, p = 0.026). there was a causal relationship between SCF and drug-related osteonecrosis (OR=3.356, 95% CI=1.09-10.30, p=0.034). Conclusion: This pioneering Mendelian randomization study is the first to explore the causal link between osteonecrosis and 41 inflammatory cytokines. It conclusively establishes a causal association between osteonecrosis and bFGF, IL-2, and IL-2RA. These findings offer valuable insights into osteonecrosis pathogenesis, paving the way for effective clinical management. The study suggests bFGF, IL-2, and IL-2RA as potential therapeutic targets for osteonecrosis treatment.

GhMYB52 Like: A Key Factor That Enhances Lint Yield by Negatively Regulating the Lignin Biosynthesis Pathway in Fibers of Upland Cotton (Gossypium hirsutum L.).

In the context of sustainable agriculture and biomaterial development, understanding and enhancing plant secondary cell wall formation are crucial for improving crop fiber quality and biomass conversion efficiency. This is especially critical for economically important crops like upland cotton (Gossypium hirsutum L.), for which fiber quality and its processing properties are essential. Through comprehensive genome-wide screening and analysis of expression patterns, we identified a particularly high expression of an R2R3 MYB transcription factor, GhMYB52 Like, in the development of the secondary cell wall in cotton fiber cells. Utilizing gene-editing technology to generate a loss-of-function mutant to clarify the role of GhMYB52 Like, we revealed that GhMYB52 Like does not directly contribute to cellulose synthesis in cotton fibers but instead represses a subset of lignin biosynthesis genes, establishing it as a lignin biosynthesis inhibitor. Concurrently, a substantial decrease in the lint index, a critical measure of cotton yield, was noted in parallel with an elevation in lignin levels. This study not only deepens our understanding of the molecular mechanisms underlying cotton fiber development but also offers new perspectives for the molecular improvement of other economically important crops and the enhancement of biomass energy utilization.

Litoamentenes A-K, eleven undescribed cembranoids with cytotoxicity from the South China Sea soft coral Litophyton amentaceum.

Eleven undescribed cembrane-type diterpenoids, named litoamentenes A-K (1-11), were isolated from the soft coral Litophyton amentaceum collected from the South China Sea. Their structures were elucidated by extensive analysis of spectroscopic data, comparison with the literature data, single crystal X-ray diffraction, quantum chemical calculations and TDDFT-ECD calculations. This is the first systematic investigation of L. amentaceum. In particular, compounds 1-3 are cembrane-type norditerpenoids that lack isopropyl side chains. Compound 6 is a cembrane-type norditerpenoid without a methyl group at C-4, the first natural product identified with this carbon skeleton. Compounds 6, 9 and 10 showed modest cytotoxicity against several human cancer cell lines with IC50 values ranging from 3.99 to 14.56 µM.

[Study on mitigating effect and mechanism of Cichorium glandulosum n-butanol extraction site on CCl_4-induced chronic liver injury in rats].

This study aims to investigate the mitigating effect and mechanism of Cichorium glandulosum n-butanol extraction site(CGE) on the disease in carbon tetrachloride(CCl_4)-induced chronic liver injury model in rats. A chronic liver injury model was constructed by subcutaneous injection of CCl_4 olive oil solution, and after four weeks of CGE treatment, serum levels of aspartate aminotransferase(AST), alanine aminotransferase(ALT), alkaline phosphatase(AKP), hydroxyproline(HYP), interleukin-4(IL-4), interleukin-6(IL-6), malondialdehyde(MDA), superoxide dismutase(SOD), and tumor necrosis factor-α(TNF-α) were detected. Liver tissue was processed by hematoxylin-eosin(HE) staining and Masson staining to observe the structure of the rat liver. qPCR and Western blot were used to examine the expression of transforming growth factor-ß1(TGF-ß1)/small mothers against decapentaplegic(Smad), Toll-like receptor 4(TLR4), α-smooth muscle actin(α-SMA), and fibronectin(Fn) in rat liver tissue and hepatic stellate-T6(HSC-T6) and evaluate the inhibitory effect of CGE on HSC activation. The results showed that CGE could significantly reduce the serum levels of AST, ALT, AKP, HYP, and affect the levels of related inflammatory indexes including IL-4, IL-6, and TNF-α, and MDA in CCl_4-induced chronic liver injury in rats and had no effect on SOD activity, which could delay the process of liver injury, alleviate the hepatic collagen deposition and inflammatory infiltration, and had significant efficacy in mitigating chronic liver injury in rats. CGE could inhibit α-SMA and TLR4 protein expression in the liver tissue and reverse the increased TGF-ß1/Smad, Fn, and TLR4-related expression in HSC-T6 in vitro. The above results indicated that CGE exerted hepatoprotective effects in rats by inhibiting HSC activation and alleviated CCl_4-induced chronic liver injury in rats and could ameliorate inflammatory response and slight liver fibrosis in rat liver tissue. Its pharmacodynamic mechanism might be related to TGF-ß1/Smad and TLR4-related expression.

Assessing the impact of tear direction in coronary artery dissection on thrombosis development: A hemodynamic computational study.

OBJECTIVE: Iatrogenic coronary artery dissection is a complication of coronary intimal injury and dissection due to improper catheter manipulation. The impact of tear direction on the prognosis of coronary artery dissection (CAD) remains unclear. This study examines the hemodynamic effects of different tear directions (transverse and longitudinal) of CAD and evaluates the risk of thrombosis, rupture and further dilatation of CAD. METHODS: Two types of CAD models (Type I: transverse tear, Type II: longitudinal tear) were reconstructed from the aorto-coronary CTA dataset of 8 healthy cases. Four WSS-based indicators were analyzed, including time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and cross flow index (CFI). A thrombus growth model was also introduced to predict the trend of thrombus growth in CAD with two different tear directions. RESULTS: For most of the WSS-based indicators, including TAWSS, RRT, and CFI, no statistically significant differences were observed across the CAD models with varying tear directions, except for OSI, where a significant difference was noted (p < 0.05). Meanwhile, in terms of thrombus growth, the thrombus growing at the tear of the Type I (transverse tear) CAD model extended into the true lumen earlier than that of the Type II (longitudinal tear) model. CONCLUSIONS: Numerical simulations suggest that: (1) The CAD with transverse tear have a high risk of further tearing of the dissection at the distal end of the tear. (2) The CAD with longitudinal tear create a hemodynamic environment characterized by low TAWSS and high OSI in the false lumen, which may additionally increase the risk of vessel wall injury. (3) The CAD with transverse tear may have a higher risk of thrombosis and coronary obstruction and myocardial ischemia in the early phase of the dissection.

Effects of Ultrasonic Treatment on Physical Stability of Lily Juice: Rheological Behavior, Particle Size, and Microstructure.

The aim of this study was to investigate the rheological properties, particle size distribution, color change, and stability of lily juice under different ultrasonic treatment conditions (152 W, 304 W, 456 W, 608 W, and 760 W). The results showed that the lily juice exhibited non-Newtonian shear thinning behavior, and the viscosity decreased with the increase in ultrasonic power. Under ultrasonic treatment conditions, there was no significant change in the pH value and zeta potential value of the samples. The content of cloudy value and total soluble solids (TSS) increased gradually. However, both the sedimentation components and centrifugal sedimentation rate showed a downward trend and an asymptotic behavior. In addition, high-power ultrasound changed the color index (L* value decreased, a* value increased), tissue structure, and particle distribution of the sample, and small particles increased significantly. To sum up, ultrasonic treatment has great potential in improving the physical properties and suspension stability of lily juice.

Interface-induced dual-pinning mechanism enhances low-frequency electromagnetic wave loss.

Improving the absorption of electromagnetic waves at low-frequency bands (2-8 GHz) is crucial for the increasing electromagnetic (EM) pollution brought about by the innovation of the fifth generation (5G) communication technology. However, the poor impedance matching and intrinsic attenuation of material in low-frequency bands hinders the development of low-frequency electromagnetic wave absorbing (EMWA) materials. Here we propose an interface-induced dual-pinning mechanism and establish a magnetoelectric bias interface by constructing bilayer core-shell structures of NiFe2O4 (NFO)@BiFeO3 (BFO)@polypyrrole (PPy). Such heterogeneous interface could induce distinct magnetic pinning of the magnetic moment in the ferromagnetic NFO and dielectric pinning of the dipole rotation in PPy. The establishment of the dual-pinning effect resulted in optimized impedance and enhanced attenuation at low-frequency bands, leading to better EMWA performance. The minimum reflection loss (RLmin) at thickness of 4.43 mm reaches -65.30 dB (the optimal absorption efficiency of 99.99997%), and the effective absorption bandwidth (EAB) can almost cover C-band (4.72 ~ 7.04 GHz) with low filling of 15.0 wt.%. This work proposes a mechanism to optimize low-frequency impedance matching with electromagnetic wave (EMW) loss and pave an avenue for the research of high-performance low-frequency absorbers.

E93 is indispensable for reproduction in ametabolous and hemimetabolous insects.

Ecdysone-induced protein 93 (E93), known as the 'adult-specifier' transcription factor in insects, triggers metamorphosis in both hemimetabolous and holometabolous insects. Although E93 is conserved in ametabolous insects, its spatiotemporal expression and physiological function remain poorly understood. In this study, we first discover that, in the ametabolous firebrat Thermobia domestica, the previtellogenic ovary exhibits cyclically high E93 expression, and E93 mRNA is broadly distributed in previtellogenic ovarioles. E93 homozygous mutant females of T. domestica exhibit severe fecundity deficiency due to impaired previtellogenic development of the ovarian follicles, likely because E93 induces the expression of genes involved in ECM (extracellular matrix)-receptor interactions during previtellogenesis. Moreover, we reveal that in the hemimetabolous cockroach Blattella germanica, E93 similarly promotes previtellogenic ovarian development. In addition, E93 is also essential for vitellogenesis that is necessary to guarantee ovarian maturation and promotes the vitellogenesis-previtellogenesis switch in the fat body of adult female cockroaches. Our findings deepen the understanding of the roles of E93 in controlling reproduction in insects, and of E93 expression and functional evolution, which are proposed to have made crucial contributions to the origin of insect metamorphosis.

Multi-omics analysis provides new insights into the changes of important nutrients and fructose metabolism in loquat bud sport mutant.

Bud sport is a common and stable somatic variation in perennial fruit trees, and often leads to significant modification of fruit traits and affects the breeding value. To investigate the impact of bud sport on the main metabolites in the fruit of white-fleshed loquat, we conducted a multi-omics analysis of loquat fruits at different developmental stages of a white-fleshed bud sport mutant of Dongting loquat (TBW) and its wild type (TBY). The findings from the detection of main fruit quality indices and metabolites suggested that bud sport resulted in a reduction in the accumulation of carotenoids, fructose, titratable acid and terpenoids at the mature stage of TBW, while leading to the accumulation of flavonoids, phenolic acids, amino acids and lipids. The comparably low content of titratable acid further enhances the balanced and pleasent taste profile of TBW. Expression patterns of differentially expressed genes involved in fructose metabolism exhibited a significant increase in the expression level of S6PDH (EVM0006243, EVM0044405) prior to fruit maturation. The comparison of protein sequences and promoter region of S6PDH between TBY and TBW revealed no structural variations that would impact gene function or expression, indicating that transcription factors may be responsible for the rapid up-regulation of S6PDH before maturation. Furthermore, correlation analysis helped to construct a comprehensive regulatory network of fructose metabolism in loquat, including 23 transcription factors, six structural genes, and nine saccharides. Based on the regulatory network and existing studies, it could be inferred that transcription factors such as ERF, NAC, MYB, GRAS, and bZIP may promote fructose accumulation in loquat flesh by positively regulating S6PDH. These findings improve our understanding of the nutritional value and breeding potential of white-fleshed loquat bud sport mutant, as well as serve as a foundation for exploring the genes and transcription factors that regulate fructose metabolism in loquat.

A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis.

Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physicians in rendering more evidence-based decisions, thus presenting a pioneering solution for clinical practice. Traditionally, the amalgamation of diverse medical data modalities (e.g., image, text, speech, genetic data, physiological signals) is imperative to facilitate a comprehensive disease analysis, a topic of burgeoning interest among both researchers and clinicians in recent times. Hence, there exists a pressing need to synthesize the latest strides in multi-modal data and AI technologies in the realm of medical diagnosis. In this paper, we narrow our focus to five specific disorders (Alzheimer's disease, breast cancer, depression, heart disease, epilepsy), elucidating advanced endeavors in their diagnosis and treatment through the lens of artificial intelligence. Our survey not only delineates detailed diagnostic methodologies across varying modalities but also underscores commonly utilized public datasets, the intricacies of feature engineering, prevalent classification models, and envisaged challenges for future endeavors. In essence, our research endeavors to contribute to the advancement of diagnostic methodologies, furnishing invaluable insights for clinical decision making.

Tailored Exfoliation of Polymeric Carbon Nitride for Photocatalytic H2O2 Production and CH4 Valorization Mediated by O2 Activation.

The exfoliation of bulk C3N4 (BCN) into ultrathin layered structure is an effective strategy to boost photocatalytic efficiency by exposing interior active sites and accelerating charge separation and transportation. Herein, we report a novel nitrate anion intercalation-decomposition (NID) strategy that is effective in peeling off BCN into few-layer C3N4 (fl-CN) with tailored thickness down to bi-layer. This strategy only involves hydrothermal treatment of BCN in diluted HNO3 aqueous solution, followed by pyrolysis at various temperatures. The decomposition of the nitrate anions not only exfoliates BCN and changes the band structure, but also incorporates oxygen species onto fl-CN, which is conducive to O2 adsorption and hence relevant chemical processes. In photocatalytic O2 reduction under visible light irradiation, the H2O2 production rate over the optimal fl-CN-530 catalyst is 952 µmol g-1 h-1, which is 8.8 times that over BCN. More importantly, under full arc irradiation and in the absence of hole scavenger, CH4 can be photocatalytically oxidized by on-site formed H2O2 and active oxygen species to generate value-added C1 oxygenates with high selectivity of 99.2 % and record-high production rate of 1893 µmol g-1 h-1 among the metal-free C3N4-based photocatalysts.

DTP-Net: Learning to Reconstruct EEG Signals in Time-Frequency Domain by Multi-Scale Feature Reuse.

Electroencephalography (EEG) signals are prone to contamination by noise, such as ocular and muscle artifacts. Minimizing these artifacts is crucial for EEG-based downstream applications like disease diagnosis and brain-computer interface (BCI). This paper presents a new EEG denoising model, DTP-Net. It is a fully convolutional neural network comprising Densely-connected Temporal Pyramids (DTPs) placed between two learnable time-frequency transformations. In the time-frequency domain, DTPs facilitate efficient propagation of multi-scale features extracted from EEG signals of any length, leading to effective noise reduction. Comprehensive experiments on two public semi-simulated datasets demonstrate that the proposed DTP-Net consistently outperforms existing state-of-the-art methods on metrics including relative root mean square error (RRMSE) and signal-to-noise ratio improvement ( ∆SNR). Moreover, the proposed DTP-Net is applied to a BCI classification task, yielding an improvement of up to 5.55% in accuracy. This confirms the potential of DTP-Net for applications in the fields of EEG-based neuroscience and neuro-engineering. An in-depth analysis further illustrates the representation learning behavior of each module in DTP-Net, demonstrating its robustness and reliability.

CCDC88C variants are associated with focal epilepsy and genotype-phenotype correlation.

CCDC88C gene, which encodes coiled-coil domain containing 88C, is essential for cell communication during neural development. Variants in the CCDC88C caused congenital hydrocephalus, some accompanied by seizures. In patients with epilepsy without acquired etiologies, we performed whole-exome sequencing (trio-based). Two de novo and two biallelic CCDC88C variants were identified in four cases with focal (partial) epilepsy. These variants did not present or had low frequencies in the gnomAD populations and were predicted to be damaging by multiple computational algorithms. Patients with de novo variants presented with adult-onset epilepsy, whereas patients with biallelic variants displayed infant-onset epilepsy. They all responded well to anti-seizure medications and were seizure-free. Further analysis showed that de novo variants were located at crucial domains, whereas one paired biallelic variants were located outside the crucial domains, and the other paired variant had a non-classical splicing and a variant located at crucial domain, suggesting a sub-molecular effect. CCDC88C variants associated with congenital hydrocephalus were all truncated, whereas epilepsy-associated variants were mainly missense, the proportion of which was significantly higher than that of congenital hydrocephalus-associated variants. CCDC88C is potentially associated with focal epilepsy with favorable outcome. The underlying mechanisms of phenotypic variation may correlation between genotype and phenotype.

Macro CD5L+ deteriorates CD8+T cells exhaustion and impairs combination of Gemcitabine-Oxaliplatin-Lenvatinib-anti-PD1 therapy in intrahepatic cholangiocarcinoma.

Intratumoral immune status influences tumor therapeutic response, but it remains largely unclear how the status determines therapies for patients with intrahepatic cholangiocarcinoma. Here, we examine the single-cell transcriptional and TCR profiles of 18 tumor tissues pre- and post- therapy of gemcitabine plus oxaliplatin, in combination with lenvatinib and anti-PD1 antibody for intrahepatic cholangiocarcinoma. We find that high CD8 GZMB+ and CD8 proliferating proportions and a low Macro CD5L+ proportion predict good response to the therapy. In patients with a poor response, the CD8 GZMB+ and CD8 proliferating proportions are increased, but the CD8 GZMK+ proportion is decreased after the therapy. Transition of CD8 proliferating and CD8 GZMB+ to CD8 GZMK+ facilitates good response to the therapy, while Macro CD5L+-CD8 GZMB+ crosstalk impairs the response by increasing CTLA4 in CD8 GZMB+. Anti-CTLA4 antibody reverses resistance of the therapy in intrahepatic cholangiocarcinoma. Our data provide a resource for predicting response of the combination therapy and highlight the importance of CD8+T-cell status conversion and exhaustion induced by Macro CD5L+ in influencing the response, suggesting future avenues for cancer treatment optimization.

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography (CT) radiomics and clinicobiochemical characteristics associated with PA. MATERIALS AND METHODS: This study retrospectively enrolled 158 patients with PA who underwent AVS between January 2014 and March 2021. Neural network machine learning models were developed using a two-stage analysis of triple-phase abdominal CT and clinicobiochemical characteristics. In the first stage, the models were constructed to classify unilateral or bilateral PA; in the second stage, they were designed to determine the predominant side in patients with unilateral PA. The final proposed model combined the best-performing models from both stages. The model's performance was evaluated using repeated stratified five-fold cross-validation. We employed paired t-tests to compare its performance with the conventional imaging evaluations made by radiologists, which categorize patients as either having bilateral PA or unilateral PA on one side. RESULTS: In the first stage, the integrated model that combines CT radiomic and clinicobiochemical characteristics exhibited the highest performance, surpassing both the radiomic-alone and clinicobiochemical-alone models. It achieved an accuracy and F1 score of 80.6% ± 3.0% and 74.8% ± 5.2% (area under the receiver operating curve [AUC] = 0.778 ± 0.050). In the second stage, the accuracy and F1 score of the radiomic-based model were 88% ± 4.9% and 81.9% ± 6.2% (AUC=0.831 ± 0.087). The proposed model achieved an accuracy and F1 score of 77.5% ± 3.9% and 70.5% ± 7.1% (AUC=0.771 ± 0.046) in subtype diagnosis and lateralization, surpassing the accuracy and F1 score achieved by radiologists' evaluation (p < .05). CONCLUSION: The proposed machine learning model can predict the subtypes and lateralization of PA. It yields superior results compared to conventional imaging evaluation and has potential to supplement the diagnostic process in PA.