The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings.

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant cardiomyopathy (CM). Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry and simulate the impact of including future cohorts. This dataset reports penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some individuals with highly penetrant variants may benefit from SFs.

Galectin-7 Induction by EHMT2 Inhibition Enhances Immunity in Microsatellite Stability Colorectal Cancer.

BACKGROUND & AIMS: Although immunotherapy shows substantial advancement in colorectal cancer (CRC) with microsatellite instability high, it has limited efficacy for CRC with microsatellite stability (MSS). Identifying combinations that reverse immune suppression and prime MSS tumors for current immunotherapy approaches remains an urgent need. METHODS: An in vitro CRISPR screen was performed using coculture models of primary tumor cells and autologous immune cells from MSS CRC patients to identify epigenetic targets that could enhance immunotherapy efficacy in MSS tumors. RESULTS: We revealed EHMT2, a histone methyltransferase, as a potential target for MSS CRC. EHMT2 inhibition transformed the immunosuppressive microenvironment of MSS tumors into an immunomodulatory one by altering cytokine expression, leading to T-cell-mediated cytotoxicity activation and improved responsiveness to anti-PD1 treatment. We observed galectin-7 up-regulation upon EHMT2 inhibition, which converted a "cold" MSS tumor environment into a T-cell-inflamed one. Mechanistically, CHD4 repressed galectin-7 expression by recruiting EHMT2 to form a cotranscriptional silencing complex. Galectin-7 administration enhanced anti-PD1 efficacy in MSS CRC, serving as a potent adjunct cytokine therapy. CONCLUSIONS: Our findings suggest that targeting the EHMT2/galectin-7 axis could provide a novel combination strategy for immunotherapy in MSS CRC.

Sex-biased effects on hippocampal circuit development by perinatal SERT expression in CA3 pyramidal neurons.

Neurodevelopmental disorders ranging from autism to intellectual disability display sex-biased prevalence and phenotypical presentations. Despite increasing knowledge about temporospatial cortical map development and genetic variants linked to neurodevelopmental disorders, when and how sex-biased neural circuit derailment may arise in diseased brain remain unknown. Here, we identify in mice that serotonin uptake transporter (SERT) in non-serotonergic neurons - hippocampal and prefrontal pyramidal neurons - confers sex-biased effects specifically during neural circuit development. A set of gradient-patterned CA3 pyramidal neurons transiently express SERT to clear extracellular serotonin, coinciding with hippocampal synaptic circuit establishment. Ablating pyramidal neuron SERT (SERTPyramidΔ) alters dendritic spine developmental trajectory in the hippocampus, and precipitates sex-biased impairments in long-term activity-dependent hippocampal synaptic plasticity and cognitive behaviors. Transcriptomic analyses identify sex-biased alterations in gene sets associated with autism, dendritic spine structure, synaptic function and male-specific enrichment of dysregulated genes in glial cells in early postnatal SERTPyramidΔ hippocampus. Our data suggest that SERT function in these pyramidal neurons underscores a temporal- and brain region-specific regulation of normal sex-dimorphic circuit development and a source for sex-biased vulnerability to cognitive and behavioral impairments. This article has an associated 'The people behind the papers' interview.

The Mutual Regulatory Role of Ferroptosis and Immunotherapy in Anti-tumor Therapy.

Ferroptosis is a form of cell death that is triggered by the presence of ferrous ions and is characterized by lipid peroxidation induced by these ions. The mechanism exhibits distinct morphological characteristics compared to apoptosis, autophagy, and necrosis. A notable aspect of ferroptosis is its ability to inhibit uncontrolled tumor replication and immortalization, especially in malignant, drug-resistant, and metastatic tumors. Additionally, immunotherapy, a novel therapeutic approach for tumors, has been found to have a reciprocal regulatory relationship with ferroptosis in the context of anti-tumor therapy. A comprehensive analysis of ferroptosis and immunotherapy in tumor therapy is presented in this paper, highlighting the potential for mutual adjuvant effects. Specifically, we discuss the mechanisms underlying ferroptosis and immunotherapy, emphasizing their ability to improve the tumor immune microenvironment and enhance immunotherapeutic effects. Furthermore, we investigate how immunotherapeutic factors may increase the sensitivity of tumor cells to ferroptosis. We aim to provide a prospective view of the promising value of combined ferroptosis and immunotherapy in anticancer therapy by elucidating the mutual regulatory network between each.

RNA m6 A methylation regulates sorafenib resistance in liver cancer through FOXO3-mediated autophagy.

N6-methyladenosine (m6 A) is an abundant nucleotide modification in mRNA, known to regulate mRNA stability, splicing, and translation, but it is unclear whether it is also has a physiological role in the intratumoral microenvironment and cancer drug resistance. Here, we find that METTL3, a primary m6 A methyltransferase, is significantly down-regulated in human sorafenib-resistant hepatocellular carcinoma (HCC). Depletion of METTL3 under hypoxia promotes sorafenib resistance and expression of angiogenesis genes in cultured HCC cells and activates autophagy-associated pathways. Mechanistically, we have identified FOXO3 as a key downstream target of METTL3, with m6 A modification of the FOXO3 mRNA 3'-untranslated region increasing its stability through a YTHDF1-dependent mechanism. Analysis of clinical samples furthermore showed that METTL3 and FOXO3 levels are tightly correlated in HCC patients. In mouse xenograft models, METTL3 depletion significantly enhances sorafenib resistance of HCC by abolishing the identified METTL3-mediated FOXO3 mRNA stabilization, and overexpression of FOXO3 restores m6 A-dependent sorafenib sensitivity. Collectively, our work reveals a critical function for METTL3-mediated m6 A modification in the hypoxic tumor microenvironment and identifies FOXO3 as an important target of m6 A modification in the resistance of HCC to sorafenib therapy.

Metformin inactivates the cGAS-STING pathway through autophagy and suppresses senescence in nucleus pulposus cells.

Intervertebral disc degeneration (IVDD) is a complex process involving many factors, among which excessive senescence of nucleus pulposus cells is considered to be the main factor. Our previous study found that metformin can inhibit senescence in nucleus pulposus cells; however, the mechanism of such an action was still largely unknown. In the current study, we found that metformin inactivates the cGAS-STING pathway during oxidative stress. Furthermore, knockdown of STING (also known as STING1) suppresses senescence, indicating that metformin might exert its effect through the cGAS-STING pathway. Damaged DNA is a major inducer of the activation of the cGAS-STING pathway. Mechanistically, our study showed that DNA damage was reduced during metformin treatment; however, suppression of autophagy by 3-methyladenine (3-MA) treatment compromised the effect of metformin on DNA damage. In vivo studies also showed that 3-MA might diminish the therapeutic effect of metformin on IVDD. Taken together, our results reveal that metformin may suppress senescence via inactivating the cGAS-STING pathway through autophagy, implying a new application for metformin in cGAS-STING pathway-related diseases.

High quantum efficiency of hydrogen production from methanol aqueous solution with PtCu-TiO2 photocatalysts.

Methanol with 12.5 wt% H2 content is widely considered a liquid hydrogen medium. Taking into account water with 11.1 wt% H2 content, H2 synthesis from the mixture of water and methanol is a promising method for on-demand hydrogen production. We demonstrate an atomic-level catalyst design strategy using the synergy between single atoms and nanodots for H2 production. The PtCu-TiO2 sandwich photocatalyst achieves a remarkable H2 formation rate (2,383.9 µmol h-1) with a high apparent quantum efficiency (99.2%). Furthermore, the oxidation product is a high-value chemical formaldehyde with 98.6% selectivity instead of CO2, leading to a nearly zero-carbon-emission process. Detailed investigations indicate a dual role of the copper atoms: an electron acceptor to facilitate photoelectron transfer to Pt, and a hole acceptor for the selective oxidation of methanol to formaldehyde, thus avoiding over-oxidation to CO2. The synergy between Pt nanodots and Cu single atoms together reduces the activation energy of this process to 13.2 kJ mol-1.

High-Performance Anode Material Based on Zinc Naphthalocyanine/Graphene Composite.

Transition metal oxides are a potential anode material owing to their high theoretical capacity. Nonetheless, their large volume changes and low electrical conductivities lead to poor cycling performance and rate capabilities. In this article, an effective strategy is proposed and developed for preparing a ZnO/N-doped graphene composite (ZnNc/GO-5). The key point of this strategy is to use zinc tetra tert-butyl-naphthalocyanine (ZnNc) as a codoped source of N atoms and zinc ions, and graphene oxide (GO) which is combined with ZnNc by π-π deposition as a carbon matrix. After calcination, ZnO microcrystals coated with N-doped graphene are obtained. The unique features of the composite and synergistic effect between N-doped reduced graphene oxide and ZnO microcrystals enable good electrochemical performance by the composites when used in lithium-ion batteries. As an anode material, the as-synthesized ZnNc/GO-5 composite delivers a high first capacity of 1942.9 mAh g-1 and excellent cyclic stability of 861.4 mAh g-1 after 150 cycles at 100 mA g-1. This strategy may offer a new method of designing the anode materials of lithium-ion batteries and promote the practical use of organic molecules in next-generation lithium-ion batteries.

Differences in Kondo Splitting of Surface Quantum Systems Induced by Two Distinct Magnetic Tips: A Joint Method of DFT and HEOM.

The interactions between a magnetic tip and local spin impurities initiate unconventional Kondo phenomena, such as asymmetric suppression or even splitting of the Kondo peak. However, a lack of realistic theoretical models and comprehensive explanations for this phenomenon persists due to the complexity of the interactions. This research employs a joint method of density functional theory (DFT) and hierarchical equation of motion (HEOM) to simulate and contrast the modulation of the spin state and Kondo behavior in the Fe/Cu(100) system with two distinct magnetic tips. A cobalt tip, possessing a larger magnetic moment, incites greater atomic displacement of the iron atom, more notable alterations in electronic structure, and enhanced charge transfer with the environment compared with the control process utilizing a nickel tip. Furthermore, the Kondo resonance undergoes asymmetric splitting as a result of the ferromagnetic correlation between the iron atom and the magnetic tip. The Co tip's higher spin polarization results in a wider spacing between the splitting peaks. This investigation underscores the precision of the DFT + HEOM approach in predicting complex quantum phenomena and explaining the underlying physical principles. This provides valuable theoretical support for developing more sophisticated quantum regulation experiments.

Paraptosis: a non-classical paradigm of cell death for cancer therapy.

Due to the sustained proliferative potential of cancer cells, inducing cell death is a potential strategy for cancer therapy. Paraptosis is a mode of cell death characterized by endoplasmic reticulum (ER) and/or mitochondrial swelling and cytoplasmic vacuolization, which is less investigated. Considerable evidence shows that paraptosis can be triggered by various chemical compounds, particularly in cancer cells, thus highlighting the potential application of this non-classical mode of cell death in cancer therapy. Despite these findings, there remain significant gaps in our understanding of the role of paraptosis in cancer. In this review, we summarize the current knowledge on chemical compound-induced paraptosis. The ER and mitochondria are the two major responding organelles in chemical compound-induced paraptosis, which can be triggered by the reduction of protein degradation, disruption of sulfhydryl homeostasis, overload of mitochondrial Ca2+, and increased generation of reactive oxygen species. We also discuss the stumbling blocks to the development of this field and the direction for further research. The rational use of paraptosis might help us develop a new paradigm for cancer therapy.

Novel STAT3 oligonucleotide compounds suppress tumor growth and overcome the acquired resistance to sorafenib in hepatocellular carcinoma.

Signal transducer and activator of transcription 3 (STAT3) plays an important role in the occurrence and progression of tumors, leading to resistance and poor prognosis. Activation of STAT3 signaling is frequently detected in hepatocellular carcinoma (HCC), but potent and less toxic STAT3 inhibitors have not been discovered. Here, based on antisense technology, we designed a series of stabilized modified antisense oligonucleotides targeting STAT3 mRNA (STAT3 ASOs). Treatment with STAT3 ASOs decreased the STAT3 mRNA and protein levels in HCC cells. STAT3 ASOs significantly inhibited the proliferation, survival, migration, and invasion of cancer cells by specifically perturbing STAT3 signaling. Treatment with STAT3 ASOs decreased the tumor burden in an HCC xenograft model. Moreover, aberrant STAT3 signaling activation is one of multiple signaling pathways involved in sorafenib resistance in HCC. STAT3 ASOs effectively sensitized resistant HCC cell lines to sorafenib in vitro and improved the inhibitory potency of sorafenib in a resistant HCC xenograft model. The developed STAT3 ASOs enrich the tools capable of targeting STAT3 and modulating STAT3 activity, serve as a promising strategy for treating HCC and other STAT3-addicted tumors, and alleviate the acquired resistance to sorafenib in HCC patients. A series of novel STAT3 antisense oligonucleotide were designed and showed potent anti-cancer efficacy in hepatocellular carcinoma in vitro and in vivo by targeting STAT3 signaling. Moreover, the selected STAT3 ASOs enhance sorafenib sensitivity in resistant cell model and xenograft model.

Elevated insulin growth factor-1 in dentate gyrus induces cognitive deficits in pre-term newborns.

Prematurely born infants are deprived of maternal hormones and cared for in the stressful environment of Neonatal Intensive Care Units (NICUs). They suffer from long-lasting deficits in learning and memory. Here, we show that prematurity and associated neonatal stress disrupt dentate gyrus (DG) development and induce long-term cognitive deficits and that these effects are mediated by insulin growth factor-1 (IGF1). Nonmaternal care of premature rabbits increased the number of granule cells and interneurons and reduced neurogenesis, suggesting accelerated premature maturation of DG. However, the density of glutamatergic synapses, mature dendritic spines, and synaptic transmission were reduced in preterm kits compared with full-term controls, indicating that premature synaptic maturation was abnormal. These findings were consistent with cognitive deficits observed in premature rabbits and appeared to be driven by transcriptomic changes in the granule cells. Preterm kits displayed reduced weight, elevated serum cortisol and growth hormone, and higher IGF1 expression in the liver and DG relative to full-term controls. Importantly, blocking IGF-1 receptor in premature kits restored cognitive deficits, increased the density of glutamatergic puncta, and rescued NR2B and PSD95 levels in the DG. Hence, IGF1 inhibition alleviates prematurity-induced cognitive dysfunction and synaptic changes in the DG through modulation of NR2B and PSD95. The study identifies a novel strategy to potentially rescue DG maldevelopment and cognitive dysfunction in premature infants under stress in NICUs.

Rapid static feeding combined with Fe2+ addition for improving the formation and stability of aerobic granular sludge in low-strength wastewater.

Aerobic granular sludge (AGS) needs a long start-up time and always shows unstable performance when it is used to treat low-strength wastewater. In this study, a rapid static feeding combined with Fe2+ addition as a novel strategy was employed to improve the formation and stability of AGS in treating low-strength wastewater. Fe-AGS was formed within only 7 days and showed favorable pollutant removal capability and settling performance. The ammonia nitrogen (NH4+-N) and chemical oxygen demand (COD) concentration in the effluent were lower than 5 mg/L and 50 mg/L after day 23, respectively. The sludge volume index (SVI) and mixed liquid suspended solids (MLSS) was 37 mL/g and 2.15 g/L on day 50, respectively. Rapid static feeding can accelerate granules formation by promoting the growth of heterotrophic bacteria, but the granules are unstable due to filamentous bacteria overgrowth. Fe2+ addition can inhibit the growth of filamentous bacteria and promote the aggregation of functional bacteria (eg. Nitrosomonas, Nitrolancea, Paracoccus, Diaphorobacter) by enhancing the secretion of extracellular polymeric substances (EPS). This study provides a new way for AGS application in low-strength wastewater treatment.

N6-methyladenosine demethylase FTO enhances chemo-resistance in colorectal cancer through SIVA1-mediated apoptosis.

N6-methyladenosine (m6A) is the most pervasive RNA modification and is recognized as a novel epigenetic regulation in RNA metabolism. Although the m6A modification involves various physiological processes, its roles in drug resistance in colorectal cancer (CRC) still remain unknown. We analyzed the RNA expression profile of m6A/A (%) with MRM mass spectrometry in human 5-fluorouracil (5-FU)-resistant CRC tissues, and used the m6A RNA immunoprecipitation assay to validate the m6A-regulated target. Our results have shown that the m6A demethylase FTO was up-regulated in human primary and 5-FU-resistant CRC. Depletion of FTO decreased cell growth, colony formation and metastasis in 5-FU-resistant CRC cells in vitro and in vivo. Mechanistically, we identified SIVA1, a critical apoptotic gene, as a key downstream target of the FTO-mediated m6A demethylation. The m6A demethylation of SIVA1 at the CDS region induced its mRNA degradation via a YTHDF2-dependent mechanism. The SIVA1 levels were negatively correlated with the FTO levels in clinical CRC tissues. Notably, inhibition of FTO significantly reduced the tolerance of 5-FU in 5-FU-resistant CRC cells via the FTO-SIVA1 axis, whereas SIVA1-depletion could restore the m6A-dependent 5-FU sensitivity in CRC cells. In summary, our findings demonstrate a critical role of FTO as an m6A demethylase enhancing chemo-resistance in CRC cells, and suggest that FTO inhibition may restore the sensitivity of chemo-resistant CRC cells to 5-FU.

Ophthalmic Artery Morphology and Hemodynamics Associated with White Matter Hyperintensity.

Purpose: To investigate morphological and hemodynamic characteristics of the ophthalmic artery (OA) in patients with white matter hyperintensity (WMH), and the association of the presence and severity of WMH with OA characteristics. Methods: This cross-sectional study included 44 eyes of 25 patients with WMH and 38 eyes of 19 controls. The Fazekas scale was adopted as criteria for evaluating the severity of white matter hyperintensities. The morphological characteristics of the OA were measured on the basis of three-dimensional reconstruction. The hemodynamic parameters of the OA were calculated using computational fluid dynamics simulations. Results: Compared with the control group, the diameter (16.0±0.27 mm vs. 1.71±0.18 mm, P=0.029), median blood flow velocity (0.12 m/s vs. 0.22 m/s, P<0.001), mass flow ratio (2.16% vs. 3.94%, P=0.012) and wall shear stress (2.65 Pa vs. 9.31 Pa, P<0.001) of the OA in patients with WMH were significantly decreased. After adjusting for confounding factors, the diameter, blood flow velocity, wall shear stress, and mass flow ratio of the OA were significantly associated with the presence of WMH. Male sex and high low-density protein level were associated with moderate-to-severe total WMH, and smoking was associated with the moderate-to-severe periventricular WMH. Conclusions: The diameter, blood flow velocity, mass flow ratio, and wall shear stress of the OA were independently associated with the presence of WMH. Atherosclerosis might be involved in the common mechanism of the occurrence of WMH and the OA changes.

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep learning features to radiomics models for predicting 5-year OS status. METHODS: Two hundred twenty cases from The Cancer Imaging Archive public dataset were included in this study; 2212 radiomics features and 304 deep features were extracted from each case. The features were selected by univariate analysis and the least absolute shrinkage and selection operator, and then grouped into a radiomics model containing Positron Emission Tomography /Computed Tomography (PET/CT) radiomics features score, a deep model containing deep features score, and a combined model containing PET/CT radiomics features score +3D deep features score. TumorStage model was also constructed using initial patient tumor node metastasis stage to compare the performance of the combined model. A nomogram was constructed to analyze the influence of deep features on the performance of the model. The 10-fold cross-validation of the average area under the receiver operating characteristic curve and calibration curve were used to evaluate performance, and Shapley Additive exPlanations (SHAP) was developed for interpretation. RESULTS: The TumorStage model, radiomics model, deep model, and the combined model achieved areas under the receiver operating characteristic curve of 0.604, 0.851, 0.840, and 0.895 on the train set and 0.571, 0.849, 0.832, and 0.900 on the test set. The combined model showed better performance of predicting the 5-year OS status of HNC patients than the radiomics model and deep model. The combined model was shown to provide a favorable fit in calibration curves and be clinically useful in decision curve analysis. SHAP summary plot and SHAP The SHAP summary plot and SHAP force plot visually interpreted the influence of deep features and radiomics features on the model results. CONCLUSIONS: In predicting 5-year OS status in patients with HNC, 3D deep features could provide richer features for combined model, which showed outperformance compared with the radiomics model and deep model.

Deep learning in computed tomography to predict endotype in chronic rhinosinusitis with nasal polyps.

BACKGROUND: As treatment strategies differ according to endotype, rhinologists must accurately determine the endotype in patients affected by chronic rhinosinusitis with nasal polyps (CRSwNP) for the appropriate management. In this study, we aim to construct a novel deep learning model using paranasal sinus computed tomography (CT) to predict the endotype in patients with CRSwNP. METHODS: We included patients diagnosed with CRSwNP between January 1, 2020, and April 31, 2023. The endotype of patients with CRSwNP in this study was classified as eosinophilic or non-eosinophilic. Sinus CT images (29,993 images) were retrospectively collected, including the axial, coronal, and sagittal planes, and randomly divided into training, validation, and testing sets. A residual network-18 was used to construct the deep learning model based on these images. Loss functions, accuracy functions, confusion matrices, and receiver operating characteristic curves were used to assess the predictive performance of the model. Gradient-weighted class activation mapping was performed to visualize and interpret the operating principles of the model. RESULTS: Among 251 included patients, 86 and 165 had eosinophilic or non-eosinophilic CRSwNP, respectively. The median (interquartile range) patient age was 49 years (37-58 years), and 153 (61.0%) were male. The deep learning model showed good discriminative performance in the training and validation sets, with areas under the curves of 0.993 and 0.966, respectively. To confirm the model generalizability, the receiver operating characteristic curve in the testing set showed good discriminative performance, with an area under the curve of 0.963. The Kappa scores of the confusion matrices in the training, validation, and testing sets were 0.985, 0.928, and 0.922, respectively. Finally, the constructed deep learning model was used to predict the endotype of all patients, resulting in an area under the curve of 0.962. CONCLUSIONS: The deep learning model developed in this study may provide a novel noninvasive method for rhinologists to evaluate endotypes in patients with CRSwNP and help develop precise treatment strategies.

A multi-view fusion lightweight network for CRSwNPs prediction on CT images.

Accurate preoperative differentiation of the chronic rhinosinusitis (CRS) endotype between eosinophilic CRS (eCRS) and non-eosinophilic CRS (non-eCRS) is an important topic in predicting postoperative outcomes and administering personalized treatment. To this end, we have constructed a sinus CT dataset, which comprises CT scan data and pathological biopsy results from 192 patients of chronic rhinosinusitis with nasal polyps (CRSwNP), treated at the Second Affiliated Hospital of Shantou University Medical College between 2020 and 2022. To differentiate CRSwNP endotype on preoperative CT and improve efficiency at the same time, we developed a multi-view fusion model that contains a mini-architecture with each network of 10 layers by modifying the deep residual neural network. The proposed model is trained on a training set and evaluated on a test set. The multi-view deep learning fusion model achieved the area under the receiver-operating characteristics curve (AUC) of 0.991, accuracy of 0.965 and F1-Score of 0.970 in test set. We compared the performance of the mini-architecture with other lightweight networks on the same Sinus CT dataset. The experimental results demonstrate that the developed ResMini architecture contribute to competitive CRSwNP endotype identification modeling in terms of accuracy and parameter number.

The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers.

BACKGROUND: This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine learning models. MATERIALS AND METHODS: 135 CT images of Credence Cartridge Radiomic phantoms were collected and screened from three scanners manufactured by Siemens, Philips, and GE. 100 radiomic features were extracted and 20 radiomic features were screened according to the Lasso regression method. The radiomic features extracted from the rubber and resin-filled regions in the cartridges were labeled into different categories for evaluating the performance of the machine learning model. Radiomics features were divided into three groups based on the different scanner manufacturers. The radiomic features were randomly divided into training and test sets with a ratio of 8:2. Five machine learning models (lasso, logistic regression, random forest, support vector machine, neural network) were employed to evaluate the impact of Combat on radiomic features. The variability among radiomic features were assessed using analysis of variance (ANOVA) and principal component analysis (PCA). Accuracy, precision, recall, and area under the receiver curve (AUC) were used as evaluation metrics for model classification. RESULTS: The principal component and ANOVA analysis results show that the variability of different scanner manufacturers in radiomic features was removed (P˃0.05). After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. The performance of machine learning models for classification improved, with the Random Forest model showing the most significant enhancement. The AUC value increased from 0.88 to 0.92. CONCLUSIONS: The Combat algorithm has reduced variability in radiomic features from different scanners. In the phantom CT dataset, it appears that the machine learning model's classification performance may have improved after Combat harmonization. However, further investigation and validation are required to fully comprehend Combat's impact on radiomic features in medical imaging.

Association of the Verbal Rating Scale-Measured Dysmenorrhea with Nausea and Vomiting in Pregnancy: A Retrospective Cohort Study.

OBJECTIVES: Nausea and vomiting in pregnancy (NVP) is a common condition that reduces the quality of life by negatively affecting work and family life, physical and mental health, and economic well-being. However, its risk factors remain unclear. This study aimed to explore the association between NVP and verbal rating scale (VRS)-measured dysmenorrhea and to explore potential protective factors. METHODS: This retrospective cohort study was conducted from June 2018 to December 2020 at Tongji Hospital in Wuhan. Information on baseline characteristics, pregnancy-related history, periconceptional micronutrient supplementation, and obstetric outcomes were collected. The severity of dysmenorrhea was assessed using VRS. RESULTS: A total of 443 pregnant women were recruited and divided into the NVP group (n = 76) and the control group (n = 367). A significant association was observed between NVP and VRS-measured dysmenorrhea (c2=10.038, P = 0.007). After adjusting for covariates, the association between moderate/severe dysmenorrhea and NVP remained significant (OR 2.384; 95% CI 1.104-5.148, P = 0.004). First-trimester docosahexaenoic acid supplement (OR 0.443; 95% CI 0.205-0.960, P = 0.039) may be beneficial in reducing the risk of NVP. CONCLUSIONS: Women with moderate to severe dysmenorrhea have a higher risk of experiencing NVP during the first trimester. Periconceptional docosahexaenoic acid supplementation may play a protective role.