A data-driven intravoxel mean diffusivities distribution approach for molecular classifications and MIB-1 prediction of gliomas.

BACKGROUND: Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes. PURPOSE: We developed a data-driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB-1 labeling index (LI) levels and molecular status of gliomas. METHODS: An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR ∈ [ 30 , 300 ] $ \in [ {30,\ 300} ]$ . Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years ± $ \pm $ 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo-echo planar imaging (SE-EPI) diffusion-weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C-means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions ( f n , n = 1 - 6 ${{f}_n},\ n = 1 -6$ ) and diffusivities of the maximum peaks ( D p e a k ${{D}_{peak}}$ ). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann-Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation. RESULTS: The simulation results showed that the FCN-based MDD approach (FCN-MDD) achieved higher CSS than non-negative least squares-based MDD (NNLS-MDD). For in vivo data, the spectra of ET and NET obtained by FCN-MDD are more distinguishable than NNLS-MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non-enhancing tumor, edema, and necrosis). f 3 , f 4 , D p e a k ${{f}_3},\ {{f}_4},{{D}_{peak}}$ showed a positive and negative correlation with MIB-1 respectively ( r = 0.568 , r = - 0.521 , r = - 0.654 $r = 0.568,\ r = - 0.521,\ r = - 0.654$ , all p < 0.001 $p < 0.001$ ). The AUC of D p e a k ${{D}_{peak}}$ for predicting MIB-1 LI levels was 0.900 (95% CI, 0.826-0.974), versus 0.781 (0.677-0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model ( f 1 + f 3 ${{f}_1} + {{f}_3}$ ) was 0.873 (95% CI, 0.802-0.944). CONCLUSION: The proposed FCN-MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS-MDD method. FCN-MDD also enabled qualitative and quantitative evaluation of the composition of gliomas.

Efficacy and safety analysis of combination therapy based on mitoxantrone hydrochloride liposome injection (Lipo-MIT) in relapsed/refractory NK/T-cell lymphoma.

Background: Currently, there is no standard treatment for relapsed/refractory NK/T-cell lymphoma (NKTCL). Liposomal mitoxantrone (Lipo-MIT) showed good anti-tumor effect in patients with NKTCL, breaking the limitation of natural resistance of NKTCL to anthracyclines. To further improve the efficacy, we tried a combination therapy based on Lipo-MIT in patients with relapsed/refractory NKTCL. Methods: 12 patients with relapsed/refractory NKTCL were enrolled in this retrospective study, all of whom had previously received pegaspargase-based treatments. The salvage treatment was a combination regimen based on Lipo-MIT. The efficacy was evaluated after every two cycles. Results: 11 patients had stage IV NKTCL, and all but one patients had an NRI score of ≥3. The median previous lines of treatment was two (range, 1-4), and five patients were refractory to their last line of treatment. The best response rates were as follows: complete response (CR) in five (41.7%) patients, partial response in five (41.7%) patients, stable disease in one (8.3%) patient, and progressive disease in one (8.3%) patient. At a median follow-up of four months (range, 2-14), seven patients died, with a median PFS of five months and a median OS of seven months. The six-month PFS and OS rate was 44.4% and 52.1%, respectively. All patients had suffered from side effects, among which myelosuppression was most reported. Nine patients had grade three or more myelosuppression, and the median recovery time from myelosuppression was 14 days (2-35 days). Five patients had obvious skin hyperpigmentation, and the CR rate was significantly higher compared with those without skin hyperpigmentation (80% vs. 14.3%, p=0.023). Other side effects included liver insufficiency (N=4), coagulation dysfunction (N=4), acute pancreatitis (N=2), and immunotherapy-related adverse effects (irAEs, N=2). Conclusion: Combination therapy based on Lipo-MIT has a high remission rate for relapsed/refractory NKTCL, but the duration of remission needs to be further extended. Lipo-MIT has obvious myelosuppression toxicity, and active supportive therapy should be given when combined with other cytotoxic drugs.

Relationships Between Chemotherapy-Related Cognitive Impairment, Self-Care Ability, and Quality of Life in Breast Cancer Survivors: A Cross-Sectional Study.

OBJECTIVES: It is not clear how chemotherapy-related cognitive impairment and self-care ability affect the quality of life of women with breast cancer. The purpose of this study was to explore the relationships between chemotherapy-related cognitive impairment, self-care ability, and quality of life in breast cancer patients, and test whether self-care ability plays a mediating role in the association between cognitive impairment and quality of life. METHODS: This study was a cross-sectional study, conducted in China in 2022. Self-reported scales were used to assess cognitive function, self-care ability, and quality of life. Data were analyzed using descriptive statistics, spearman correlation analysis and hierarchical multiple regression analyses, the SPSS Process program was used to explore the mediating effect of self-care ability. RESULTS: A total of 218 participants were investigated, and approximately 79.3% of patients experienced mild chemotherapy-related cognitive impairment, the mean quality of life score was 59.96 ± 14.15, and the mean self-care ability score was 107.4 ± 24.09. Significant correlations among cognitive impairment, self-care ability, and quality of life were observed (P < .05). Additionally, self-care ability played a partial mediating role between cognitive impairment and quality of life (P < .05), accounting for 24.3% and 22.3%, respectively. CONCLUSIONS: Chemotherapy-related cognitive impairment and self-care ability are factors affecting the quality of life of breast cancer survivors. Self-care ability mediates the relationship between cognitive impairment and quality of life. Enhancing patients' self-care ability can improve the quality of life of patients with cognitive impairment. IMPLICATIONS FOR NURSING PRACTICE: In the future, oncology nurses should not only pay attention to the severity of cognitive impairment, but also assess the level of patients' self-care ability, provide relevant medical and healthcare guidance, train self-management behavior and strengthen self-care ability by integrating multidisciplinary forces to improve the quality of life of breast cancer patients effectively.

Assessing the quality of life in patients with drug-resistant tuberculosis: a cross-sectional study.

BACKGROUND: This study investigated the current status of the quality of life (QOL) of drug-resistant tuberculosis (DR-TB) patients in Nanjing, China, and analyzed the influencing factors. METHODS: The survey was conducted among patients with DR-TB who were hospitalized in the tuberculosis department of the Second Hospital of Nanjing (Nanjing Public Health Medical Center) from July 2022 to May 2023. The Chinese version of the World Health Organization Quality of Life (WHOQOL-BREF) questionnaire was used to investigate the QOL levels of patients with DR-TB, and a multiple linear regression model was used to analyze the QOL influencing factors. RESULTS: A total of 135 patients participated in the study; 69.6% were male, the average age was 46.30 ± 17.98 years, 13.33% had an education level of elementary school or below, and 75.56% were married. The QOL scores were 51.35 ± 17.24, 47.04 ± 20.28, 43.89 ± 17.96, and 35.00 ± 11.57 in the physiological, psychological, social, and environmental domains, respectively. The differences between the four domain scores and the Chinese normative results were statistically significant (P < 0.05). The results of multiple linear regression analysis showed that the factors related to the physiological domain included residence, family per-capita monthly income, payment method, adverse drug reactions (ADRs), and comorbidities; psychological domain correlates included educational level, family per-capita monthly income, course of the disease, and caregivers; social domain correlates included age and comorbidities; and factors related to the environmental domain included age, education level, and comorbidities. CONCLUSIONS: In Nanjing, China, patients with younger age, higher education level, living in urban areas, high family per-capita monthly income, no adverse drug reactions, no comorbidities, and having caregivers have better quality of life. Future interventions to improve the quality of life of patients with drug-resistant tuberculosis could be tailored to a specific factor.

CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality. The limited temporal resolution also causes patient discomfort and introduces artifacts in the images, further diminishing their overall quality and diagnostic value. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have so far not been made publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. The 'CMRxRecon' dataset contains raw k-space data and auto-calibration lines. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community.

Discovery of Ureido-Substituted 4-Phenylthiazole Derivatives as IGF1R Inhibitors with Potent Antiproliferative Properties.

The existing kinase inhibitors for hepatocellular carcinoma (HCC) have conferred survival benefits but are hampered by adverse effects and drug resistance, necessitating the development of novel agents targeting distinct pathways. To discover potent new anti-HCC compounds, we leveraged scaffold hopping from Sorafenib and introduced morpholine/piperidine moieties to develop ureido-substituted 4-phenylthiazole analogs with optimized physicochemical properties and binding interactions. Notably, compound 27 exhibited potent cytotoxicity against HepG2 cells (IC50 = 0.62 ± 0.34 µM), significantly exceeding Sorafenib (IC50 = 1.62 ± 0.27 µM). Mechanistic investigations revealed that compound 27 potently inhibited HCC cell migration and colony formation, and it induced G2/M arrest and early-stage apoptosis. Kinase profiling revealed IGF1R as a key target, which compound 27 potently inhibited (76.84% at 10 µM). Molecular modeling substantiated compound 27's strong binding to IGF1R via multiple hydrogen bonds. Computational predictions indicate favorable drug-like properties for compound 27. These findings provide a promising drug candidate for the treatment of HCC patients.

TEX19 increases the levels of CDK4 and promotes breast cancer by disrupting SKP2-mediated CDK4 ubiquitination.

BACKGROUND: Globally, breast cancer in women is the fifth leading cause of cancer death. There is an urgent need to explore the molecular mechanism of breast cancer proliferation and metastasis. METHOD: TCGA database analysis was used to analyze genes expression in breast cancer and normal samples and the association between gene expression and prognosis. Immunohistochemical staining, qPCR and western blotting was sued to detected gene expression. The cell function tests were conducted to investigate the effects of TEX19 and CDK4 with abnormal expression on cell proliferation, migration, apoptosis, cell cycle, and colony formation. Bioinformatics analysis methods combined with CHX tracking experiment and Co-IP experiment were performed to screen and verify the downstream molecule and regulatory mechanism of TEX19. Besides, subcutaneous tumorigenesis model in nude mice was constructed. RESULTS: TEX19 was significantly upregulated in breast cancer, and the TEX19 level was related to tumor invasion and prognosis. TEX19 knockdown inhibited the proliferation and migration of breast cancer cells, increased cell apoptosis, and blocked the cell cycle in the G2 phase. Besides, TEX19 suppressed the growth of tumors in the body. Mechanically, TEX19 upregulated the level of CDK4 protein, which depended on the E3 ubiquitin ligase SKP2. Specifically, TEX19 knockdown and SKP2 protein overexpression destroyed the stability of CDK4 protein and enhanced the ubiquitination of CDK4 protein. Additionally, CDK4 knockdown inhibited the proliferation, migration, and colony formation of breast cancer cells, and alleviated the promotion of TEX19 overexpression on the proliferation and migration of breast cancer cell. CONCLUSION: TEX19 and CDK4 were upregulated in breast cancer, and TEX19 increased the level of CDK4 protein by influencing SKP2-mediated ubiquitination of CDK4, thereby promoting the progression of breast cancer.

Pulmonary granulomas and Mendelson syndrome in an immunocompromised patient.

Granuloma formation is generally correlated with infection. Pulmonary granulomas caused by foreign bodies aspiration are uncommon. The clinical and radiologic features of such cases often lack specificity, which makes it difficult to distinguish from malignancy. Aspiration is usually not considered in the differential diagnosis of patients presenting with mass-like abnormalities on chest imaging. Occult aspiration history, diverse clinical manifestations, atypical imaging findings, and limited availability of pathogen detection techniques make the precise diagnosis a substantial challenge. Herein, we describe an older patient presenting with chest pain and worrisome lung masses/nodules that proved to be pulmonary granulomas caused by foreign matters aspiration. In addition, the patient developed Mendelson syndrome due to acute macroaspiration. Lung tissue metagenomics next-generation sequencing (mNGS) revealed Streptococcus intermedius, a normal flora of the oropharynx. The aim of this case was to underscore the importance of considering aspiration as a potential differential diagnosis of patients presenting with pulmonary granulomas, especially in patients with recurrent pneumonia or predisposing factors. In addition, mNGS act as a potential, rapid, and effective technique for diagnosing aspiration-related syndrome, showing satisfactory performance in identifying pathogens.

An Integrated Strategy Based on 10-DAB Extraction and In Situ Whole-Cell Biotransformation of Renewable Taxus Needles to Produce Baccatin III.

Baccatin III is a crucial precursor in the biosynthesis pathway of paclitaxel. Its main sources are extraction from Taxus or chemical synthesis using 10-deacetylbaccatin III (10-DAB) as substrate. However, these preparation approaches exhibit serious limitations, including the low content of baccatin III in Taxus and the complicated steps of chemical synthesis. Heterologous expression of 10-deacetylbaccatin III-10-O-acetyltransferase (TcDBAT) in microbial strains for biotransformation of 10-DAB is a promising alternative strategy for baccatin III production. Here, the promotion effects of glycerol supply and slightly acidic conditions with a low-temperature on the catalysis of recombinant TcDBAT strain were clarified using 10-DAB as substrate. Taxus needles is renewable and the content of 10-DAB is relatively high, it can be used as an effective source of the catalytic substrate 10-DAB. Baccatin III was synthesized by integrating the extraction of 10-DAB from renewable Taxus needles and in situ whole-cell catalysis in this study. 40 g/L needles were converted into 20.66 mg/L baccatin III by optimizing and establishing a whole-cell catalytic bioprocess. The method used in this study can shorten the production process of Taxus extraction for baccatin III synthesis and provide a reliable strategy for the efficient production of baccatin III by recombinant strains and the improvement of resource utilization rate of Taxus needles.

Effects of modified Danggui Sini Decoction as adjuvant therapy for angina pectoris in coronary heart disease: a systematic review and meta-analysis based on randomised controlled trials.

Introduction: This systematic review evaluates the efficacy of the Chinese herbal formula modified Danggui Sini Decoction as an adjunctive treatment for angina pectoris in patients with coronary heart disease. Methods: We conducted a comprehensive search for randomized controlled trials that investigated the effects of modified Danggui Sini Decoction in combination with conventional Western medication on angina pectoris in coronary artery disease, published up to July 2023 across eight databases, including China Knowledge International Literature screening and data extraction were performed by two researchers following predefined inclusion and exclusion criteria. The quality of included studies was assessed using the Cochrane Handbook version 5.1, and meta-analysis was executed via RevMan 5.4 software. Results: Thirteen studies encompassing 1,232 participants were incorporated. The meta-analysis revealed that combining modified Danggui Sini Decoction with conventional Western medication significantly enhanced overall clinical efficacy, reduced the duration of angina attacks, decreased the Chinese medicine syndrome score, improved inflammatory markers and cardiac function, lowered serum NT-proBNP levels, and elevated the Seattle Angina Questionnaire scores compared to the control group. Conclusion: Modified Danggui Sini Decoction, when used alongside conventional Western medications, shows promise in treating coronary artery disease patients with angina pectoris and may serve as a beneficial adjunctive therapy in clinical settings. Nonetheless, due to the limited quantity and quality of the included studies, further high-caliber research is essential to substantiate these findings. Systematic Review Registration: https://inplasy.com/? s=202390078, identifier INPLASY 202390078.

Sorption characteristics of phosphorus on marine sediments in the presence of black carbon derived from fly ash.

The sorption behavior of phosphorus on marine sediments in the presence of black carbon derived from fly ash (FC) was studied. For both the FC and sediment samples, the kinetic curves could be described by a two-compartment first order equation, and the isotherms fit the Freundlich and Langmuir models well. The high specific surface area with abundant acidic functional groups of FC promoted the sorption and make this process more irreversible. The effects were more significant with higher amount of FC added. After sorption, more significant increase in Ex-P, Fe/Al-P and CaP was found in the sediment with FC added, while the organic groups in FC rarely react with phosphorus to form OP. The pH of medium influenced the sorption character, and FC promoted the process significantly at pH < pHPZNPC. The sorption was endothermic with an increase in randomness. The presence of FC had little effects on the thermodynamic parameters.

Happy people are always similar: The evidence from brain morphological and functional inter-subject correlations.

A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.

Integrated bioinformatics and validation reveal PTGS2 and its related molecules to alleviate TNF-α-induced endothelial senescence.

Accumulative evidences have indicated the interaction between cellular senescence and ferroptosis. This study intends to investigate the ferroptosis-related molecular markers in TNF-α-induced endothelial senescence. The microarray expression dataset (GSE195517) was used to identify the differently expressed ferroptosis-related genes (DEFRGs) through weighted gene co-expressed network analysis (WGCNA). GO and KEGG were performed to explore the biological function. Furthermore, hub genes were identified after protein-protein interaction (PPI) analysis and validated through real-time qPCR (RT-qPCR). Then, a drug-gene network was established to predict potential drugs for the hub genes. Seven DEFRGs were recognized in the TNF-α-induced HUVEC senescence. Moreover, four hub genes (PTGS2, TNFAIP3, CXCL2, and IL6 are upregulated) were identified by PPI analysis and validated by RT-qPCR. Further analysis exhibited that PTGS2 was subcellularly located in the plasma membrane. Furthermore, after aminosalicylic acid (ASA) was identified as ferroptosis inhibitor for targeting PTGS2 in senescent HUVECs, 5-ASA and 4-ASA were verified to alleviate TNF-α-induced HUVEC senescence through ferroptosis. PTGS2 might play a role in TNF-α-induced HUVEC senescence and ASA may be the potential drug for alleviating TNF-α-induced HUVEC senescence through ferroptosis.

Bulk T-cell receptor sequencing confirms clonality in obstetric antiphospholipid syndrome and may as a potential biomarker.

The heterogeneity of the T cell receptor (TCR) repertoire critically influences the autoimmune response in obstetric antiphospholipid syndrome (OAPS) and is intimately associated with the prophylaxis of autoimmune disorders. Investigating the TCR diversity patterns in patients with OAPS is thus of paramount clinical importance. This investigation procured peripheral blood specimens from 31 individuals with OAPS, 21 patients diagnosed with systemic lupus erythematosus (SLE), and 22 healthy controls (HC), proceeding with TCR repertoire sequencing. Concurrently, adverse pregnancy outcomes in the OAPS cohort were monitored and documented over an 18-month timeframe. We paid particular attention to disparities in V/J gene utilisation and the prevalence of shared clonotypes amongst OAPS patients and the comparative groups. When juxtaposed with observations from healthy controls and SLE patients, immune repertoire sequencing disclosed irregular T- and B-cell profiles and a contraction of diversity within the OAPS group. Marked variances were found in the genomic rearrangements of the V gene, J gene, and V/J combinations. Utilising a specialised TCRß repertoire, we crafted a predictive model for OAPS classification with robust discriminative capability (AUC = 0.852). Our research unveils alterations in the TCR repertoire among OAPS patients for the first time, positing potential covert autoimmune underpinnings. These findings nominate the TCR repertoire as a prospective peripheral blood biomarker for the clinical diagnosis of OAPS and may offer valuable insights for advancing the understanding of OAPS immunologic mechanisms and prognostic outcomes.

3.05 kW, 13.7 GHz linewidth fiber amplifier based on PRBS phase modulation for SBS suppression.

In this paper, we establish a multi-stage fiber amplifier with pseudo-random binary sequence (PRBS) phase modulation. The stimulated Brillouin gain spectra of the main amplifier with both the unmodulated and pseudo-random binary sequence phase modulated configuration are measured (with corresponding output power), and the stimulated Brillouin scattering (SBS) threshold is investigated experimentally and theoretically. The pseudo-random binary sequence phase modulation parameters are optimized by theoretical simulation. With a two-stage preamplifier chain and a counter-pumping main amplifier stage, a maximum 3.05 kW output power with a slope efficiency of 85.9% is obtained experimentally. The central wavelength of the fiber amplifier is 1050 nm, associated with a full-width at half-maximum linewidth of 13.7 GHz. The stimulated Brillouin scattering reflectivity is below 0.01% at 3.05 kW at 13.7 GHz, which indicates that stimulated Brillouin scattering can be suppressed efficiently at this power and linewidth level.

Multi-modal segmentation with missing image data for automatic delineation of gross tumor volumes in head and neck cancers.

BACKGROUND: Head and neck (HN) gross tumor volume (GTV) auto-segmentation is challenging due to the morphological complexity and low image contrast of targets. Multi-modality images, including computed tomography (CT) and positron emission tomography (PET), are used in the routine clinic to assist radiation oncologists for accurate GTV delineation. However, the availability of PET imaging may not always be guaranteed. PURPOSE: To develop a deep learning segmentation framework for automated GTV delineation of HN cancers using a combination of PET/CT images, while addressing the challenge of missing PET data. METHODS: Two datasets were included for this study: Dataset I: 524 (training) and 359 (testing) oropharyngeal cancer patients from different institutions with their PET/CT pairs provided by the HECKTOR Challenge; Dataset II: 90 HN patients(testing) from a local institution with their planning CT, PET/CT pairs. To handle potentially missing PET images, a model training strategy named the "Blank Channel" method was implemented. To simulate the absence of a PET image, a blank array with the same dimensions as the CT image was generated to meet the dual-channel input requirement of the deep learning model. During the model training process, the model was randomly presented with either a real PET/CT pair or a blank/CT pair. This allowed the model to learn the relationship between the CT image and the corresponding GTV delineation based on available modalities. As a result, our model had the ability to handle flexible inputs during prediction, making it suitable for cases where PET images are missing. To evaluate the performance of our proposed model, we trained it using training patients from Dataset I and tested it with Dataset II. We compared our model (Model 1) with two other models which were trained for specific modality segmentations: Model 2 trained with only CT images, and Model 3 trained with real PET/CT pairs. The performance of the models was evaluated using quantitative metrics, including Dice similarity coefficient (DSC), mean surface distance (MSD), and 95% Hausdorff Distance (HD95). In addition, we evaluated our Model 1 and Model 3 using the 359 test cases in Dataset I. RESULTS: Our proposed model(Model 1) achieved promising results for GTV auto-segmentation using PET/CT images, with the flexibility of missing PET images. Specifically, when assessed with only CT images in Dataset II, Model 1 achieved DSC of 0.56 ± 0.16, MSD of 3.4 ± 2.1 mm, and HD95 of 13.9 ± 7.6 mm. When the PET images were included, the performance of our model was improved to DSC of 0.62 ± 0.14, MSD of 2.8 ± 1.7 mm, and HD95 of 10.5 ± 6.5 mm. These results are comparable to those achieved by Model 2 and Model 3, illustrating Model 1's effectiveness in utilizing flexible input modalities. Further analysis using the test dataset from Dataset I showed that Model 1 achieved an average DSC of 0.77, surpassing the overall average DSC of 0.72 among all participants in the HECKTOR Challenge. CONCLUSIONS: We successfully refined a multi-modal segmentation tool for accurate GTV delineation for HN cancer. Our method addressed the issue of missing PET images by allowing flexible data input, thereby providing a practical solution for clinical settings where access to PET imaging may be limited.

Validation of the psychoactive substance refusal Self-Efficacy Questionnaire (PSRSEQ) in adolescent case-clients of social workers in Hong Kong.

BACKGROUND: Self-efficacy is a key concept in various behavioral theories. Refusal self-efficacy is important in understanding issues related to psychoactive substance use. To facilitate related research, this study translated and validated the Chinese version of the 14-item Psychoactive Substance Refusal Self-efficacy Questionnaire (PSRSEQ) among adolescents. There is a debate about whether such a refusal self-efficacy scale should be unidimensional or multidimensional. METHODS: A survey was conducted among 601 adolescent case-clients of social workers in Hong Kong from July 2021 to June 2022. Various psychometric properties were examined. RESULTS: The confirmatory factor analysis (CFA) supported the original 3-factor structure of the PSRSEQ (emotional relief, opportunistic, and social facilitation refusal self-efficacy), which showed satisfactory psychometric properties (internal consistency, convergent validity in terms of significant negative correlations with the intention of psychoactive substance use in the next year and psychoactive substance use behavior in the past six months, and the absence of floor effect) but ceiling effect was obvious. Notably, unacceptable discriminant validity of one subscale and strong correlations among the three subscales were observed. In another set of analyses using two split-half subsamples, the exploratory factor analysis identified a 1-factor 14-item structure, which was confirmed by CFA and showed satisfactory psychometric properties. CONCLUSIONS: The 1-factor PSRSEQ, instead of the one having a 3-factor structure, was preferred and recommended to assess psychoactive substance refusal self-efficacy among Chinese adolescents. It is warranted to validate the scale in other adolescent and age groups in future studies.

Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative. PURPOSE: To assess the diagnostic accuracy of histological grading and prognosis in STS patients when integrating clinical-imaging parameters with deep learning (DL) features from preoperative MR images. STUDY TYPE: Retrospective/prospective. POPULATION: 354 pathologically confirmed STS patients (226 low-grade, 128 high-grade) from three hospitals and the Cancer Imaging Archive (TCIA), divided into training (n = 185), external test (n = 125), and TCIA cohorts (n = 44). 12 patients (6 low-grade, 6 high-grade) were enrolled into prospective validation cohort. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/Unenhanced T1-weighted and fat-suppressed-T2-weighted. ASSESSMENT: DL features were extracted from MR images using a parallel ResNet-18 model to construct DL signature. Clinical-imaging characteristics included age, gender, tumor-node-metastasis stage and MRI semantic features (depth, number, heterogeneity at T1WI/FS-T2WI, necrosis, and peritumoral edema). Logistic regression analysis identified significant risk factors for the clinical model. A DL clinical-imaging signature (DLCS) was constructed by incorporating DL signature with risk factors, evaluated for risk stratification, and assessed for progression-free survival (PFS) in retrospective cohorts, with an average follow-up of 23 ± 22 months. STATISTICAL TESTS: Logistic regression, Cox regression, Kaplan-Meier curves, log-rank test, area under the receiver operating characteristic curve (AUC)，and decision curve analysis. A P-value <0.05 was considered significant. RESULTS: The AUC values for DLCS in the external test, TCIA, and prospective test cohorts (0.834, 0.838, 0.819) were superior to clinical model (0.662, 0.685, 0.694). Decision curve analysis showed that the DLCS model provided greater clinical net benefit over the DL and clinical models. Also, the DLCS model was able to risk-stratify patients and assess PFS. DATA CONCLUSION: The DLCS exhibited strong capabilities in histological grading and prognosis assessment for STS patients, and may have potential to aid in the formulation of personalized treatment plans. TECHNICAL EFFICACY: Stage 2.

Who takes the lead in consumer choices within romantic relationships: the evidence from electroencephalography hyperscanning and granger causality analysis.

In real-life scenarios, joint consumption is common, particularly influenced by social relationships such as romantic ones. However, how romantic relationships affect consumption decisions and determine dominance remains unclear. This study employs electroencephalography hyperscanning to examine the neural dynamics of couples during joint-consumption decisions. Results show that couples, compared to friends and strangers, prefer healthier foods, while friends have significantly faster reaction times when selecting food. Time-frequency analysis indicates that couples exhibit significantly higher theta power, reflecting deeper emotional and cognitive involvement. Strangers show greater beta1 power, indicating increased cognitive effort and alertness due to unfamiliarity. Friends demonstrate higher alpha2 power when choosing unhealthy foods, suggesting increased cognitive inhibition. Inter-brain phase synchrony analysis reveals that couples display significantly higher inter-brain phase synchrony in the beta1 and theta bands across the frontal-central, parietal, and occipital regions, indicating more coordinated cognitive processing and stronger emotional bonds. Females in couples may be more influenced by emotions during consumption decisions, with detailed sensory information processing, while males exhibit higher cognitive control and spatial integration. Granger-causality analysis shows a pattern of male dominance and female dependence in joint consumption within romantic relationships. This study highlights gender-related neural synchronous patterns during joint consumption among couples, providing insights for further research in consumer decision-making.