Explainable breast cancer molecular expression prediction using multi-task deep-learning based on 3D whole breast ultrasound.

OBJECTIVES: To noninvasively estimate three breast cancer biomarkers, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) and enhance performance and interpretability via multi-task deep learning. METHODS: The study included 388 breast cancer patients who received the 3D whole breast ultrasound system (3DWBUS) examinations at Xijing Hospital between October 2020 and September 2021. Two predictive models, a single-task and a multi-task, were developed; the former predicts biomarker expression, while the latter combines tumor segmentation with biomarker prediction to enhance interpretability. Performance evaluation included individual and overall prediction metrics, and Delong's test was used for performance comparison. The models' attention regions were visualized using Grad-CAM + + technology. RESULTS: All patients were randomly split into a training set (n = 240, 62%), a validation set (n = 60, 15%), and a test set (n = 88, 23%). In the individual evaluation of ER, PR, and HER2 expression prediction, the single-task and multi-task models achieved respective AUCs of 0.809 and 0.735 for ER, 0.688 and 0.767 for PR, and 0.626 and 0.697 for HER2, as observed in the test set. In the overall evaluation, the multi-task model demonstrated superior performance in the test set, achieving a higher macro AUC of 0.733, in contrast to 0.708 for the single-task model. The Grad-CAM + + method revealed that the multi-task model exhibited a stronger focus on diseased tissue areas, improving the interpretability of how the model worked. CONCLUSION: Both models demonstrated impressive performance, with the multi-task model excelling in accuracy and offering improved interpretability on noninvasive 3DWBUS images using Grad-CAM + + technology. CRITICAL RELEVANCE STATEMENT: The multi-task deep learning model exhibits effective prediction for breast cancer biomarkers, offering direct biomarker identification and improved clinical interpretability, potentially boosting the efficiency of targeted drug screening. KEY POINTS: Tumoral biomarkers are paramount for determining breast cancer treatment. The multi-task model can improve prediction performance, and improve interpretability in clinical practice. The 3D whole breast ultrasound system-based deep learning models excelled in predicting breast cancer biomarkers.

Proteomics reveals dynamic metabolic changes in human hematopoietic stem progenitor cells from fetal to adulthood.

BACKGROUND: Hematopoietic stem progenitor cells (HSPCs) undergo phenotypical and functional changes during their emergence and development. Although the molecular programs governing the development of human hematopoietic stem cells (HSCs) have been investigated broadly, the relationships between dynamic metabolic alterations and their functions remain poorly characterized. METHODS: In this study, we comprehensively described the proteomics of HSPCs in the human fetal liver (FL), umbilical cord blood (UCB), and adult bone marrow (aBM). The metabolic state of human HSPCs was assessed via a Seahorse assay, RT‒PCR, and flow cytometry-based metabolic-related analysis. To investigate whether perturbing glutathione metabolism affects reactive oxygen species (ROS) production, the metabolic state, and the expansion of human HSPCs, HSPCs were treated with buthionine sulfoximine (BSO), an inhibitor of glutathione synthetase, and N-acetyl-L-cysteine (NAC). RESULTS: We investigated the metabolomic landscape of human HSPCs from the fetal, perinatal, and adult developmental stages by in-depth quantitative proteomics and predicted a metabolic switch from the oxidative state to the glycolytic state during human HSPC development. Seahorse assays, mitochondrial activity, ROS level, glucose uptake, and protein synthesis rate analysis supported our findings. In addition, immune-related pathways and antigen presentation were upregulated in UCB or aBM HSPCs, indicating their functional maturation upon development. Glutathione-related metabolic perturbations resulted in distinct responses in human HSPCs and progenitors. Furthermore, the molecular and immunophenotypic differences between human HSPCs at different developmental stages were revealed at the protein level for the first time. CONCLUSION: The metabolic landscape of human HSPCs at three developmental stages (FL, UCB, and aBM), combined with proteomics and functional validations, substantially extends our understanding of HSC metabolic regulation. These findings provide valuable resources for understanding human HSC function and development during fetal and adult life.

Generation of CRISPR/Cas9-edited human iPSC lines carrying homozygous and heterozygous SAMD9 p.I983S mutations.

Induced pluripotent stem cells (iPSCs) harboring patient derived SAMD9 mutation offer a unique platform to study the multi-organ involvement observed in this rare disease, referred to as myelodysplasia, infections, restriction of growth, adrenal hypoplasia, genital phenotypes, and enteropathy (MIRAGE) syndrome. The pluripotent nature of iPSCs allows in vitro differentiation into various somatic cell types representing multiple organ systems affected in SAMD9-mutated patients. Hence, in this paper, we present a CRISPR/Cas9-engineered iPSC model carrying SAMD9 c.2948T>G, p.I983S mutation previously reported in two patients with severe MIRAGE syndrome.

Novel mutation in the IGHMBP2 gene in spinal muscular atrophy with respiratory distress type 1: A case report.

Background: Spinal muscular atrophy with respiratory distress type 1 (SMARD1) is a rare autosomal recessive hereditary disease. Immunoglobulin µ-binding protein 2 (IGHMBP2) gene mutations are the main cause of SMARD1. Case presentation: Here we describe a female infant with SMARD1 carrying heterozygous mutations in IGHMBP2 genes, c.1334A > C(p.His445Pro) and c.1666C > G(p.His556Asp), which were inherited from both parents. Clinical presentations included frequent respiratory infections, respiratory failure, distal limb muscle weakness, and fat pad found at the distal toe. Conclusions: c.1666C > G(p.His556Asp) is a novel site mutation in IGHMBP2. This case expanded knowledge on the genetic profile of SMARD1 and it provides a basis for genetic testing of parents and for genetic counseling to assess the risk of fetal disease.

Injectable citrate-based polyurethane-urea as a tug-of-war-inspired bioactive self-expansive and planar-fixing screw augmented bone-tendon healing.

Inspired by tug-of-war, a game-changing bone-tendon fixation paradigm was developed. Specifically, injectable citrate-based bioactive self-expansive and planar-fixing screw (iCSP-Scr) consisting of reactive isocyanate (NCO) terminalized citrate-based polyurethane, proanthocyanidin modified hydroxyapatite (HAp) and water (with/without porogen) was developed and administrated in the bone-tendon gap. Instead of the "point to point" tendon fixation by traditional interface screws, along with the moisture-induced crosslinking and expansion of iCSP-Scr within the confined space of the irregularly shaped bone-tendon gap, the tendon graft was evenly squeezed into the bone tunnel in a "surface to surface" manner to realize strong and stable bone-tendon fixation via physical expansion, mechanical interlocking and chemical bonding (between -NCO and the -NH2, -SH groups on bone matrix). The optimized iCSP-Scr exhibited rapid crosslinking, moderate expansion rate, high porosity after crosslinking, as well as tunable elasticity and toughness. The iCSP-Scr possessed favorable biodegradability, biocompatibility, and osteoinductivity derived from citrate, PC and HAp, it was able to promote osteogenesis and new bone growth inward of bone tunnel thus further enhanced the bone/iCSP-Scr mechanical interlock, ultimately leading to stronger tendon fixation (pull-out force 106.15 ± 23.15 N) comparing to titanium screws (93.76 ± 17.89 N) after 14 weeks' ACL reconstruction in a rabbit model. The iCSP-Scr not only can be used as a self-expansive screw facilitating bone-tendon healing, but also can be expanded into other osteogenic application scenarios.

Investigating distinct clinical features and constructing a nomogram model for survival probability in adults with cerebellar high-grade gliomas.

BACKGROUND: The clinical features of cerebellar high-grade gliomas (cHGGs) in adults have not been thoroughly explored. This large-scale, population-based study aimed to comprehensively outline these traits and construct a predictive model. METHODS: Patient records diagnosed with gliomas were collected from various cohorts and analyzed to compare the features of cHGGs and supratentorial HGGs (sHGGs). Cox regression analyses were employed to identify prognostic factors for overall survival and to develop a nomogram for predicting survival probabilities in patients with cHGGs. Multiple machine learning methods were applied to evaluate the efficacy of the predictive model. RESULTS: There were significant differences in prognosis, with SEER-cHGGs showing a median survival of 7.5 months and sHGGs 14.9 months (p < 0.001). Multivariate Cox regression analyses revealed that race, WHO grade, surgical procedures, radiotherapy, and chemotherapy were independent prognostic factors for cHGGs. Based on these factors, a nomogram was developed to predict 1-, 3-, and 5-year survival probabilities, with AUC of 0.860, 0.837, and 0.810, respectively. The model's accuracy was validated by machine learning approaches, demonstrating consistent predictive effectiveness. CONCLUSIONS: Adult cHGGs are distinguished by distinctive clinical features different from those of sHGGs and are associated with an inferior prognosis. Based on these risk factors affecting cHGGs prognosis, the nomogram prediction model serves as a crucial tool for clinical decision-making in patient care.

Assessing Diagnostic Performance Using the Transverse Plane Plus Coronal Plane Compared With the Transverse Plane Alone in Screening Automated Breast Ultrasound.

OBJECTIVES: The coronal plane is the unique display mode of automated breast (AB) ultrasound (US), which has valuable features of showing the entire breast anatomy and providing additional diagnostic value for breast lesions. However, whether adding the coronal plane could improve the diagnostic performance in screening breast cancer remains uncertain. This study aimed to evaluate the value of adding the coronal plane in interpretation for AB US screening. METHODS: In this retrospective study, AB US images from 644 women (396 in the no-finding group, 143 with benign lesions, and 105 with malignant lesions) aged 40-70 years were collected between January 2016 and October 2020. Four novice radiologists (with 1-5 years of experience with breast US) and four experienced radiologists (with >5 years of experience with breast US) were assigned to read all AB US images in the transverse plane plus coronal plane (T + C planes) and transverse plane (T plane) alone in separate reading sessions. Diagnostic performance, lesion conspicuity, and reading time were compared using analysis of variance. RESULTS: The mean reading time of all radiologists was significantly shorter in the T + C planes reading mode than in the T plane alone (115 ± 32 vs 128 ± 31 s, respectively; P < .05), and cancers had a higher conspicuity (odds ratio, 1.76; 95% confidence interval [CI], 1.00-3.08; P = .04). No significant differences were noted in the two reading modes (T + C planes vs T plane) in the sensitivity (82% [95% CI, 74-89%] vs 81% [95% CI, 74-88%], respectively; P = .68) and specificity (68% [95% CI, 62-75%] vs 70% [95% CI, 64-75%], respectively; P = .39) when Breast Imaging-Reporting and Data System (BI-RADS) 3 was set as the threshold. There were also no significant differences in the two reading modes (T + C planes vs T plane) in the sensitivity (70% [95% CI, 64-76%] vs 69% [95% CI, 63-75%], respectively; P = .39) and specificity (91% [95% CI, 87-96%] vs 91% [95% CI, 88-95%], respectively; P = .90) when BI-RADS 4 was set as the threshold. In addition, the mean areas under the receiver operating characteristic curves of all radiologists in the two reading modes (T + C planes vs T plane) were not significantly different (0.84 [95% CI, 0.79-0.89] vs 0.83 [95% CI, 0.78-0.89], respectively; P = .61). CONCLUSIONS: Adding a coronal plane in the AB US screening setting saved the reading time and improved the conspicuity of breast cancers but not the diagnostic performance.

Modulation of Cerebrospinal Fluid Dysregulation via a SPAK and OSR1 Targeted Framework Nucleic Acid in Hydrocephalus.

Hydrocephalus is one of the most common brain disorders and a life-long incurable condition. An empirical "one-size-fits-all" approach of cerebrospinal fluid (CSF) shunting remains the mainstay of hydrocephalus treatment and effective pharmacotherapy options are currently lacking. Macrophage-mediated ChP inflammation and CSF hypersecretion have recently been identified as a significant discovery in the pathogenesis of hydrocephalus. In this study, a pioneering DNA nano-drug (TSOs) is developed by modifying S2 ssDNA and S4 ssDNA with SPAK ASO and OSR1 ASO in tetrahedral framework nucleic acids (tFNAs) and synthesis via a one-pot annealing procedure. This construct can significantly knockdown the expression of SPAK and OSR1, along with their downstream ion channel proteins in ChP epithelial cells, thereby leading to a decrease in CSF secretion. Moreover, these findings indicate that TSOs effectively inhibit the M0 to M1 phenotypic switch of ChP macrophages via the MAPK pathways, thus mitigating the cytokine storm. In in vivo post-hemorrhagic hydrocephalus (PHH) models, TSOs significantly reduce CSF secretion rates, alleviate ChP inflammation, and prevent the onset of hydrocephalus. These compelling results highlight the potential of TSOs as a promising therapeutic option for managing hydrocephalus, with significant applications in the future.

Analytical evaluation of the automated genotyping system (GenPlex) compared to a traditional real-time PCR assay for the detection of high-risk human papillomaviruses.

The detection of high-risk human papillomaviruses (HPVs) is crucial for early screening and preventing cervical cancer. However, the substantial workload in high-level hospitals or the limited resources in primary-level hospitals hinder widespread testing. To address this issue, we explored a sample-to-answer genotyping system and assessed its performance by comparing it with the traditional real-time polymerase chain reaction (PCR) method conducted manually. Samples randomly selected from those undergoing routine real-time PCR detection were re-analyzed using the fully automatic GenPlex® system. This system identifies 24 types of HPV through a combination of ordinary PCR and microarray-based reverse hybridization. Inconsistent results were confirmed by repeated testing with both methods, and the κ concordance test was employed to evaluate differences between the two methods. A total of 365 samples were randomly selected from 7259 women. According to real-time PCR results, 76 were high-risk HPV negative, and 289 were positive. The GenPlex® system achieved a κ value greater than 0.9 (ranging from 0.920 to 1.000, p < 0.0001) for 14 types of high-risk HPV, except HPV 51 (κ = 0.697, p < 0.0001). However, the inconsistent results in high-risk HPV 51 were revealed to be false positive in real-time PCR by other method. When counting by samples without discriminating the high-risk HPV type, the results of both methods were entirely consistent (κ = 1.000, p < 0.0001). Notably, the GenPlex® system identified more positive cases, with 73 having an HPV type not covered by real-time PCR, and 20 potentially due to low DNA concentration undetectable by the latter. Compared with the routinely used real-time PCR assay, the GenPlex® system demonstrated high consistency. Importantly, the system's advantages in automatic operation and a sealed lab-on-chip format respectively reduce manual work and prevent aerosol pollution. For widespread use of GenPlex® system, formal clinical validation following international criteria should be warranted.

Exploring the relationship between malnutrition and the systemic immune-inflammation index in older inpatients: a study based on comprehensive geriatric assessment.

BACKGROUND: Malnutrition is a prevalent and major challenge among senior citizens, possibly due to the continual low-grade inflammatory state of the body. A novel inflammatory parameter, the systemic immune-inflammation index (SII), is highly valuable in evaluating and predicting the prognosis of a wide range of diseases. This study aims to explore the significance of the SII in assessing malnutrition in older inpatients. METHODS: This retrospective study included 500 senior hospitalized patients who met the inclusion and exclusion criteria from the Comprehensive Geriatric Assessment database of the First Hospital of Jilin University. The Mini-Nutritional Assessment (MNA) questionnaire was used to evaluate the nutritional status of patients. The SII was calculated using complete blood counts, and we performed natural logarithm transformation of the SII [ln(SII)]. Multivariable logistic regression analysis was used to identify the association between ln(SII) and malnutrition. To ensure the stability of the findings, a sensitivity analysis was conducted. RESULTS: The 500 patients had a mean age of 77.29 ± 9.85 years, and 68.6% were male. In accordance with the MNA, 30.4% of the patients were malnourished or at risk of malnutrition, and patients in this group had considerably greater levels of ln(SII) than patients with adequate nutrition (P < 0.001). The optimum ln(SII) cutoff value for patients with malnutrition or at risk of malnutrition was 6.46 (SII = 635.87) with 46.7% sensitivity and 80.2% specificity [95% CI: 0.613-0.721, AUC: 0.667, P < 0.001]. Multivariable logistic regression demonstrated that ln(SII) was an independent risk factor for the risk of malnutrition or malnutrition in older individuals (OR 3.984, 95% CI: 2.426-6.543, P < 0.001). Other metrics from the geriatric comprehensive assessment, including body mass index, calf circumference, fat ratio, activities of daily living and instrumental activities of daily living, and geriatric depression scale scores, were also independently correlated with nutritional status. CONCLUSIONS: According to our research, a high SII is an independent predictor of older inpatient malnutrition, and the SII aids in screening for malnutrition and may be a potential target for intervention. Comprehensive geriatric assessment parameters such as BMI, calf circumference, fat ratio, activities of daily living and depression were also linked to malnutrition.

Multistate structures in a hydrogen-bonded polycatenation non-covalent organic framework with diverse resistive switching behaviors.

The inherent structural flexibility and reversibility of non-covalent organic frameworks have enabled them to exhibit switchable multistate structures under external stimuli, providing great potential in the field of resistive switching (RS), but not well explored yet. Herein, we report the 0D+1D hydrogen-bonded polycatenation non-covalent organic framework (HOF-FJU-52), exhibiting diverse and reversible RS behaviors with the high performance. Triggered by the external stimulus of electrical field E at room temperature, HOF-FJU-52 has excellent resistive random-access memory (RRAM) behaviors, comparable to the state-of-the-art materials. When cooling down below 200 K, it was transferred to write-once-read-many-times memory (WORM) behaviors. The two memory behaviors exhibit reversibility on a single crystal device through the temperature changes. The RS mechanism of this non-covalent organic framework has been deciphered at the atomic level by the detailed single-crystal X-ray diffraction analyses, demonstrating that the structural dual-flexibility both in the asymmetric hydrogen bonded dimers within the 0D loops and in the infinite π-π stacking column between the loops and chains contribute to reversible structure transformations between multi-states and thus to its dual RS behaviors.

Ivermectin as a potential therapeutic strategy for glioma.

Ivermectin (IVM), a semi-synthetic macrolide parasiticide, has demonstrated considerable effectiveness in combating internal and external parasites, particularly nematodes and arthropods. Its remarkable ability to control parasites has earned it significant recognition, culminating in Satoshi Omura and William C. Campbell's receipt of the 2015 Nobel Prize in Physiology or Medicine for their contributions to the development of IVM. In recent years, investigations have revealed that IVM possesses antitumor properties. It can suppress the growth of various cancer cells, including glioma, through a multitude of mechanisms such as selective targeting of tumor-specific proteins, inducing programmed cell death, and modulation of tumor-related signaling pathways. Hence, IVM holds tremendous potential as a novel anticancer drug. This review seeks to provide an overview of the underlying mechanisms that enable IVM's capacity to suppress glioma. Furthermore, it aims to elucidate the challenges and prospects associated with utilizing IVM as a new anticancer agent.

From Tea to Health: Exploring Abrus mollis for Liver Protection and Unraveling Its Potential Mechanisms.

Abrus mollis Hance is a characteristic medicinal herb which is used in Guangdong and Guangxi provinces of China for making soup, medicinal meals, and herbal tea to treat dampheat jaundice and rib discomfort. Current phytochemical study on A. mollis led to the isolation of four new flavones, mollisone A-D (1-4), and thirty two known compounds (5-36). Their structures were characterized by an extensive analysis of spectroscopic data including IR, UV, HR-ESI-MS, and 1D and 2D NMR, as well as electronic circular dichroism calculation. In addition, in order to initially understand their biological activities for traditional applications, in vitro antioxidant and hepatoprotective tests were carried out, whose results illustrated that 25 compounds had significant free radical scavenging ability, and compounds 13 and 16 exhibited protective activities on D-GalN-induced LO2 cell damage than the positive control. Moreover, network pharmacological analysis revealed that the hepatoprotective activity of A. mollis involved multitargets and multipathways such as PI3K/Akt, MAPK, and JAK-STAT pathways and various biological processes such as positive regulation of phosphorylation and regulation of kinase activity. These results suggested that this species could serve as a potential hepatoprotective agent for functional food or medicinal use.

Deep Learning for the Prediction of the Survival of Midline Diffuse Glioma with an H3K27M Alteration.

BACKGROUND: The prognosis of diffuse midline glioma (DMG) patients with H3K27M (H3K27M-DMG) alterations is poor; however, a model that encourages accurate prediction of prognosis for such lesions on an individual basis remains elusive. We aimed to construct an H3K27M-DMG survival model based on DeepSurv to predict patient prognosis. METHODS: Patients recruited from a single center were used for model training, and patients recruited from another center were used for external validation. Univariate and multivariate Cox regression analyses were used to select features. Four machine learning models were constructed, and the consistency index (C-index) and integrated Brier score (IBS) were calculated. We used the receiver operating characteristic curve (ROC) and area under the receiver operating characteristic (AUC) curve to assess the accuracy of predicting 6-month, 12-month, 18-month and 24-month survival rates. A heatmap of feature importance was used to explain the results of the four models. RESULTS: We recruited 113 patients in the training set and 23 patients in the test set. We included tumor size, tumor location, Karnofsky Performance Scale (KPS) score, enhancement, radiotherapy, and chemotherapy for model training. The accuracy of DeepSurv prediction is highest among the four models, with C-indexes of 0.862 and 0.811 in the training and external test sets, respectively. The DeepSurv model had the highest AUC values at 6 months, 12 months, 18 months and 24 months, which were 0.970 (0.919-1), 0.950 (0.877-1), 0.939 (0.845-1), and 0.875 (0.690-1), respectively. We designed an interactive interface to more intuitively display the survival probability prediction results provided by the DeepSurv model. CONCLUSION: The DeepSurv model outperforms traditional machine learning models in terms of prediction accuracy and robustness, and it can also provide personalized treatment recommendations for patients. The DeepSurv model may provide decision-making assistance for patients in formulating treatment plans in the future.

Effects of Table Grape Cultivars on Fruit Quality and Aroma Components.

The basic physical and chemical qualities, nutrition, aroma components, and sensory evaluation of 17 varieties of table grapes were studied. The quality evaluation system of different table grape varieties was preliminarily determined. Our results show that the soluble solid content in Ruby Seedless was 21.17%, which was higher than that of other varieties. The black varieties Aishenmeigui and Sweet Sapphire had the highest total phenol content. Aishenmeigui had high levels of tannin and vitamin C. In addition, the aroma contents in Meixiangbao, Ruby Seedless, and Shine-Muscat were higher than those in other varieties. Manicure Finger and Ruby Seedless had higher levels of C6 compounds. Moreover, the "Kyoho" series of grape Meixiangbao, Sunmmer Black, Jumeigui, Hutai 8 hao, and Black Beet were high in ester content, while Muscat varieties, including Zaoheibao, Aishenmeigui, Jumeigui, and Shine-Muscat were rich in terpene substances. Ruby Seedless, Shine-Muscat, and Heibaladuo had higher comprehensive scores in sensory evaluation. Hence, the comprehensive quality of Shine-Muscat, Ruby Seedless, and Aishenmeigui was better. These results may serve as references for determining the quality differences between table grape varieties.

Detecting rare thalassemia in children with anemia using third-generation sequencing.

BACKGROUND: In China, conventional genetic testing methods can only detect common thalassemia variants. Accurate detection of rare thalassemia is crucial for clinical diagnosis, especially for children that need long-term blood transfusion. This study aims to explore the application value of third-generation sequencing (TGS) in the diagnosis of rare thalassemia in children with anemia. METHODS: We enrolled 20 children with anemia, excluding from iron deficiency anemia (IDA). TGS was employed to identify both known and novel thalassemia genotypes, while sanger sequencing was used to confirm the novel mutation detected. RESULTS: Among the 20 samples, we identified 5 cases of rare thalassemia. These included ß-4.9 (hg38,Chr11:5226187-5231089) at HBB gene, α-91(HBA2:c.*91delT), αCD30(HBA2:c.91-93delGAG), Chinese Gγ+(Aγδß)0(NG_000007.3: g .48795-127698 del 78904) and delta - 77(T > C)(HBD:c.-127T>C). Notably, the -SEA/α-91α genotype associated with severe non-deletional hemoglobin H disease (HbH disease) has not been previously reported. Patients with genotypes ß654/ß-4.9 and -SEA/α-91α necessitate long-term blood transfusions, and those with the -SEA/αCD30α, Chinese Gγ+(Aγδß)0 and delta thalassemia demonstrate mild anemia. CONCLUSIONS: TGS demonstrates promising potential as a diagnostic tool for suspected cases of rare thalassemia in children, especially those suspected to have transfusion-dependent thalassemia (TDT).

Deep learning-based prediction of H3K27M alteration in diffuse midline gliomas based on whole-brain MRI.

BACKGROUND: H3K27M mutation status significantly affects the prognosis of patients with diffuse midline gliomas (DMGs), but this tumor presents a high risk of pathological acquisition. We aimed to construct a fully automated model for predicting the H3K27M alteration status of DMGs based on deep learning using whole-brain MRI. METHODS: DMG patients from West China Hospital of Sichuan University (WCHSU; n = 200) and Chengdu Shangjin Nanfu Hospital (CSNH; n = 35) who met the inclusion and exclusion criteria from February 2016 to April 2022 were enrolled as the training and external test sets, respectively. To adapt the model to the human head MRI scene, we use normal human head MR images to pretrain the model. The classification and tumor segmentation tasks are naturally related, so we conducted cotraining for the two tasks to enable information interaction between them and improve the accuracy of the classification task. RESULTS: The average classification accuracies of our model on the training and external test sets was 90.5% and 85.1%, respectively. Ablation experiments showed that pretraining and cotraining could improve the prediction accuracy and generalization performance of the model. In the training and external test sets, the average areas under the receiver operating characteristic curve (AUROCs) were 94.18% and 87.64%, and the average areas under the precision-recall curve (AUPRC) were 93.26% and 85.4%. CONCLUSIONS: The developed model achieved excellent performance in predicting the H3K27M alteration status in DMGs, and its good reproducibility and generalization were verified in the external dataset.

Photo Responsive Electron and Proton Conductivity within a Hydrogen-Bonded Organic Framework.

Rational design of crystalline porous materials with coupled proton-electron transfer has not yet been reported to date. Herein, we report a donor-acceptor (D-A) π-π stacking hydrogen-bonded organic framework (HOF; HOF-FJU-36) with zwitterionic 1,1'-bis(3-carboxybenzyl)-4,4'-bipyridinium (H2 L2+ ) as acceptor and 2,7-naphthalene disulfonate (NDS2- ) as donor to form a two-dimensional (2D) layer. Three water molecules were situated in the channels to connect with acidic species through hydrogen bonding interactions to give a 3D framework. The continuous π-π interactions along the a axis and the smooth H-bonding chain along the b axis provide the electron and proton transfer pathways, respectively. After 405 nm light irradiation, the photogenerated radicals could simultaneously endow HOF-FJU-36 with photoswitchable electron and proton conductivity due to coupled electron-proton transfer. By single-crystal X-ray diffraction (SCXRD) analyses, X-ray photoelectron spectroscopy (XPS), transient absorption spectra and density functional theory (DFT) calculations, the mechanism of the switchable conductivity upon irradiation has been demonstrated.

Three Undescribed Flavonoids and Amide from Abrus mollis Hance with Hepatoprotective Effects.

Through a phytochemical investigation of Abrus mollis Hance, a folk medicinal plant in China, we isolated and identified three undescribed compounds, including two flavonoids and one amides alkaloid, along with nine known from this plant. Their structures were elucidated by analyses of 1D, 2D NMR, HR-ESI-MS, ECD, and DP4+ analysis. Furthermore, we evaluated the hepatoprotective effects of all twelve compounds on D-GalN-induced Brl-3 A cells. According to the results, at a concentration of 25 µM, the cell survival rates were observed to be 71.92±0.34 %, 70.03±1.29 %, and 69.11±1.90 % for compound 2, 4, and 11, respectively. Further experimental studies showed that compound 2 (EC50 5.76±0.37 µM) showed more significant protective activity than the bicyclol.