Value Of Features Research Articles

How the single-family residence housing market capitalizes green property upgraded features: evidence from city of Austin

Purpose By comparing regression models, this study aims to analyze the added home value of green sustainability features and green efficiency characteristics, rather than green certifications, in the city of Austin. Design/methodology/approach The adoption of home green energy efficiency upgrades has emerged as a new trend in the real estate industry, offering several benefits to builders and home buyers. These include tax reductions, health improvements and energy savings. Previous studies have shown that energy-certified single-family homes command a premium in the marketplace. However, the literature is limited in its analysis of the effects of green upgrades and certification on different types of single-family homes. To address this gap, this research collected data from 21,292 multiple listing services (MLS) closed home-selling listings in Austin, Texas, over a period of 35 months. Findings The analysis results showed that green efficiency features could generally increase single-family housing prices by 11.9%, whereas green sustainability upgrades can potentially bring a 11.7% higher selling price. Although green housing certification did not have significant effects on most housing groups, it did increase closing prices by 13.2% for single-family residences sold at the medium price range, which is higher than the impacts from simply listing the green features on MLS. Originality/value The study contributes to the body of knowledge by examining the market value of broadly defined energy efficiency and sustainability features in the residential housing market. The findings can help policymakers, brokerage firms, home builders and owners adjust their policies and strategies related to single-family home sales and mortgage approvals. The research also highlights the potential benefits of capitalizing on green housing features other than certifications.

Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma

BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults. Standard treatment includes chemoimmunotherapy with R-CHOP or similar regimens. Despite treatment advancements, many patients with DLBCL experience refractory disease or relapse. While baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) parameters have shown promise in predicting survival, they may not fully capture lesion heterogeneity. This study aimed to assess the prognostic value of baseline 18F-FDG PET radiomics features in comparison with clinical factors and metabolic parameters for assessing 2-year progression-free survival (PFS) and 5-year overall survival (OS) in patients with DLBCL.ResultsA total of 201 patients with DLBCL were enrolled in this study, and 1328 radiomics features were extracted. The radiomics signatures, clinical factors, and metabolic parameters showed significant prognostic value for individualized prognosis prediction in patients with DLBCL. Radiomics signatures showed the lowest Akaike information criterion (AIC) value and highest Harrell’s concordance index (C-index) value in comparison with clinical factors and metabolic parameters for both PFS (AIC: 571.688 vs. 596.040 vs. 576.481; C-index: 0.732 vs. 0.658 vs. 0.702, respectively) and OS (AIC: 339.843 vs. 363.671 vs. 358.412; C-index: 0.759 vs. 0.667 vs. 0.659, respectively). Statistically significant differences were observed in the area under the curve (AUC) values between the radiomics signatures and clinical factors for both PFS (AUC: 0.768 vs. 0.681, P = 0.017) and OS (AUC: 0.767 vs. 0.667, P = 0.023). For OS, the AUC of the radiomics signatures were significantly higher than those of metabolic parameters (AUC: 0.767 vs. 0.688, P = 0.007). However, for PFS, no significant difference was observed between the radiomics signatures and metabolic parameters (AUC: 0.768 vs. 0.756, P = 0.654). The combined model and the best-performing individual model (radiomics signatures) alone showed no significant difference for both PFS (AUC: 0.784 vs. 0.768, P = 0.163) or OS (AUC: 0.772 vs. 0.767, P = 0.403).ConclusionsRadiomics signatures derived from PET images showed the high predictive power for progression in patients with DLBCL. The combination of radiomics signatures, clinical factors, and metabolic parameters may not significantly improve predictive value beyond that of radiomics signatures alone.

Performance of baseline FDG-PET/CT radiomics for prediction of bone marrow minimal residual disease status in the LyMa-101 trial

The prognostic value of 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) at baseline or the predictive value of minimal residual disease (MRD) detection appear as potential tools to improve mantle cell lymphoma (MCL) patients’ management. The LyMa-101, a phase 2 trial of the LYSA group (ClinicalTrials.gov:NCT02896582) reported induction therapy with obinutuzumab, a CD20 monoclonal antibody. Herein, we investigated the added prognostic value of radiomic features (RF) derived from FDG-PET/CT at diagnosis for MRD value prediction. FDG-PET/CT of 59 MCL patients included in the LyMa-101 trial have been independently, blindly and centrally reviewed. RF were extracted from the disease area with the highest uptake and from the total metabolic tumor volume (TMTV). Two models of machine learning were used to compare several combinations for prediction of MRD before autologous stem cell transplant consolidation (ASCT). Each algorithm was generated with or without constrained feature selections for clinical and laboratory parameters. Both algorithms showed better discrimination performances for negative vs positive MRD in the lesion with the highest uptake than in the TMTV. The constrained use of clinical and biological features showed a clear loss in sensitivity for the prediction of MRD status before ASCT, regardless of the machine learning model. These data plead for the importance of FDG-PET/CT RF compared to clinical and laboratory parameters and also reinforced the previously made hypothesis that the prognosis of the disease in MCL patients is linked to the most aggressive contingent, within the lesion with the highest uptake.

Prognostic MRI features to predict postresection survivals for very early to intermediate stage hepatocellular carcinoma

ObjectivesContrast-enhanced MRI can provide individualized prognostic information for hepatocellular carcinoma (HCC). We aimed to investigate the value of MRI features to predict early (≤ 2 years)/late (> 2 years) recurrence-free survival (E-RFS and L-RFS, respectively) and overall survival (OS).Materials and methodsConsecutive adult patients at a tertiary academic center who received curative-intent liver resection for very early to intermediate stage HCC and underwent preoperative contrast-enhanced MRI were retrospectively enrolled from March 2011 to April 2021. Three masked radiologists independently assessed 54 MRI features. Uni- and multivariable Cox regression analyses were conducted to investigate the associations of imaging features with E-RFS, L-RFS, and OS.ResultsThis study included 600 patients (median age, 53 years; 526 men). During a median follow-up of 55.3 months, 51% of patients experienced recurrence (early recurrence: 66%; late recurrence: 34%), and 17% died. Tumor size, multiple tumors, rim arterial phase hyperenhancement, iron sparing in solid mass, tumor growth pattern, and gastroesophageal varices were associated with E-RFS and OS (largest p = .02). Nonperipheral washout (p = .006), markedly low apparent diffusion coefficient value (p = .02), intratumoral arteries (p = .01), and width of the main portal vein (p = .03) were associated with E-RFS but not with L-RFS or OS, while the VICT2 trait was specifically associated with OS (p = .02). Multiple tumors (p = .048) and radiologically-evident cirrhosis (p < .001) were the only predictors for L-RFS.ConclusionTwelve visually-assessed MRI features predicted postoperative E-RFS (≤ 2 years), L-RFS (> 2 years), and OS for very early to intermediate-stage HCCs.Clinical relevance statementThe prognostic MRI features may help inform personalized surgical planning, neoadjuvant/adjuvant therapies, and postoperative surveillance, thus may be included in future prognostic models.Key Points• Tumor size, multiple tumors, rim arterial phase hyperenhancement, iron sparing, tumor growth pattern, and gastroesophageal varices predicted both recurrence-free survival within 2 years and overall survival.• Nonperipheral washout, markedly low apparent diffusion coefficient value, intratumoral arteries, and width of the main portal vein specifically predicted recurrence-free survival within 2 years, while the VICT2 trait specifically predicted overall survival.• Multiple tumors and radiologically-evident cirrhosis were the only predictors for recurrence-free survival beyond 2 years.Graphical

COVID-19 effects on travel choices under climate risks

This article analyses the impact of COVID-19 on travel behaviour by measuring changes in the utility of visiting destinations threatened by climate change. A choice experiment was conducted before and after the outbreak. The model was empirically investigated with 6900 individuals interviewed at origin countries as potential travellers to 11 destinations with different levels of damage. Data from the two waves of surveys show a shift in preferences toward travelling at lower prices, greater sensitivity to new infectious disease episodes and forest fires, and a downward effect on the value of other environmental features that may be more affected after the pandemic. The results support the ‘finite-pool-of-worry’ hypothesis over the alternative ‘affect-generalisation’ hypothesis. The implications of the shift in travellers' environmental sensitivities are discussed.

Interpreting runoff forecasting of long short-term memory network: An investigation using the integrated gradient method on runoff data from the Han River Basin

Study regionHan River Basin, Shaanxi Province, China Study focusMachine Learning (ML) has emerged as a promising panacea for precise runoff forecasting. However, the dearth of interpretability in ML models engenders apprehensions regarding their veracity and credibility. The advent of Explainable Artificial Intelligence (XAI) has bestowed researchers with the ability to understand a deeper comprehension of their inner workings and ensuring the utmost transparency and reliability of predictions. In this pursuit, the Integrated Gradient (IG) method has been employed to conduct a interpretation analysis on the long short-term memory (LSTM) model, encompassing flood events and entire runoff forecasting. Lastly, we delve into an in-depth study of the uncertainty surrounding the interpretation results, analyzing it from three key dimensions: the method, the model, and the input features. New hydrological insights for the regionThe results show that: (1) the mechanism of runoff formation belongs to the recent rainfall, and the dominant cause of prediction results varies under different flood events; (2) the change in contribution value of input features is related to feature values, and the joint effect of two features will affect the contribution value; (3) different interpretation methods will have quantitative differences in interpretation results, and the interpretation method is affected by model parameters and important feature inputs.

Emotion dysregulation and affective temperaments in opioid use disorder: a 1-year follow-up study

Background Opioid use disorder (OUD) remains a significant public health challenge with high recurrence rates and varied long-term outcomes. Affective temperament and emotion regulation have been identified as influencing addictive behaviors and treatment outcomes in OUD. However, limited research has explored their association with reversion over an extended period. Objectives The EDATOUD (Emotion Dysregulation and Affective Temperaments in Opioid Use Disorder) study aimed to evaluate the effects of affective temperament and emotion regulation characteristics on recurrence over a 1-year follow-up period. The study aimed to compare the baseline characteristics of patients who achieved remission versus those who did not and identify potential predictors of recurrence risk. Methods The study included 63 patients with OUD who were assessed monthly for return-to-use through self-report, psychiatric examination, and urine analysis. Sociodemographic data, affective temperament, difficulties in emotion regulation, anxiety, and depression were measured at baseline. Statistical analyses were performed to compare the recurrent and remission groups and determine the predictive value of these clinical features on recurrence. Results Within the one-year, 77.8% of patients returned to use. Affective temperament characteristics did not differ between the groups. However, the recurrent group patients exhibited significantly more difficulties in emotion regulation. Conclusions Difficulties in emotion regulation are associated with an increased risk of recurrence in patients with OUD. Understanding these factors can inform the development of tailored treatment strategies to improve long-term outcomes. Further research is needed to explore additional factors contributing to reversion and enhance intervention and support systems for sustained recovery in OUD.

Prognostic value of baseline MRI features in patients treated with thermal ablation for hepatocellular carcinoma

PurposeTo investigate prognostic value of baseline MRI features for time-to-recurrence (TTR) and local recurrence in patients with early hepatocellular carcinoma (HCC). MethodBaseline and follow-up images of 88 patients treated with thermal ablation followed by adjuvant sorafenib or matching placebo due to HCC within the phase II prospective randomized trial (SORAMIC) were included. Baseline MRI images were evaluated in terms of atypical enhancement (lack of wash-in or wash-out), lesion diameter, tumor capsule, peritumoral enhancement on arterial phase, intratumoral fat, irregular margin, satellite lesions, and peritumoral hypointensity on hepatobiliary phase. Prognostic value of these features for TTR and local recurrence were assessed with univariable and multivariable Cox proportional hazard models. ResultsRecurrence at any location was diagnosed during follow-up in 30 patients, and the median TTR was 16.4 (95% CI, 15 – NA) months. The presence of more than one lesion (p = 0.028) and peritumoral hypointensity on hepatobiliary phase images (p = 0.012) at baseline were significantly associated with shorter TTR in univariable analysis. AFP > 15 mg/dL (p = 0.084), and history of cirrhosis (p = 0.099) were marginally non-significant. Peritumoral hypointensity on hepatobiliary phase images was the only significant risk factor for recurrence in multivariable analysis (p = 0.003).Local recurrence (adjacent to thermal scar) was diagnosed in eleven (8.3%) out of 132 lesions that underwent thermal ablation. The only significant risk factor for local recurrence was a lesion diameter larger than 3 cm (22.2% vs. 4.5%, p = 0.007). ConclusionsPeritumoral hypointensity on hepatobiliary phase can serve as imaging biomarker to identify increased recurrence risk in patients undergoing thermal ablation for early-stage HCC.

Malignant and Benign Peripheral Nerve Sheath Tumors in a Single Center: Value of Clinical and Ultrasound Features for the Diagnosis of Malignant Peripheral Nerve Sheath Tumor Compared With Magnetic Resonance Imaging.

This study aimed to investigate the combined use of ultrasonography and clinical features for the differentiation of malignant peripheral nerve sheath tumors (MPNST) from benign peripheral nerve sheath tumors (BPNST) and to compare the efficacy of ultrasonography with that of magnetic resonance imaging (MRI). This retrospective study included 28 MPNSTs and a control group of 57 BPNSTs. All patients underwent an ultrasound scan using the Logiq E9 (GE Health Care, Milwaukee, WI) or EPIQ7 equipment (Philips Medical System, Bothell, WA). A 3.0-T MRI machine (Ingenia; Philips Healthcare, Best, the Netherlands) was used for scanning, and conventional MRI was performed on different regions based on the patient's clinical situation. The following variables were evaluated: palpable mass, pain, nerve symptoms, maximum diameter, location, shape, boundary, encapsulation, echogenicity, echo homogeneity, presence of a cystic component, calcification, target sign, posterior echo, and intertumoral vascularity of the tumors. The diagnostic efficacy of ultrasonography and clinical factors was compared with that of MRI. Independent factors for predicting MPNST versus BPNST were also assessed. The parameters of location, shape, boundary, encapsulation, and vascularity were significantly different between MPNSTs and BPNSTs. Multiple logistic regression analysis showed that shape, boundary, and vascularity were independent predictors of MPNSTs. The sensitivity, specificity, and Youden index of the three clinical and ultrasound factors (shape, boundary, and vascularity) were 0.89, 0.81, and 0.69, respectively, whereas those of MRI were 0.71, 0.89, and 0.61, respectively. No significant differences in the area under the curve (AUC) of the three combined clinical and ultrasound factors and those of MRI were found (P > .05). MRI was useful in the differential diagnosis between MPNSTs and BPNSTs. However, the combination of clinical and ultrasound diagnoses can achieve the same effect as MRI, including shape, boundary, and vasculature.

Prognostic Value of Weekly Delta-Radiomics during MR-Linac Radiotherapy of Glioblastoma

MRI after chemoradiotherapy (chemoRT) shows areas of presumed tumor growth in ≤ 50% of glioblastoma (GBM) patients, which can be true progression (TP) - tumor growth with poor treatment response, or pseudoprogression (PP) - edema and tumor necrosis with favorable treatment response. Patients with TP have median overall survival (OS) of only 7 months, while patients with PP have median OS of 36 months. However, on imaging, TP and PP are usually not discernible during treatment, making it difficult to adapt radiation for poor responders. The purpose of this study was to investigate the prognostic value of delta radiomic features from MR-Linac for GBM. Using an IRB-approved prospective cohort of GBM patients undergoing 30 fractions of chemoRT to 60 Gy on a 0.35T MR-Linac, 2 regions of interest (ROI) were contoured on daily T2-weighted treatment set-up scans: 1) tumor/edema (lesion) and 2) post-surgical resection cavity (RC). The lesion ROI were used to calculate texture features: second order radiomics features based on the gray-level co-occurrence matrix (GLCM), gray-level size zone matrix (GLSZM), gray-level run length matrix (GLRLM), and neighborhood gray-tone difference matrix (NGTDM). Each of these describe the probability of spatial relationships of gray levels occurring within the ROI. Features from fraction 1 (pre-radiation) were subtracted from fractions 5, 10, 15, 25, and 30 to create delta features at 5 timepoints (D5-D30). Patient response was retrospectively defined as no progression (NP), TP, or PP. Supervised machine learning was utilized using a 500-tree random forest (RF) classification model with TP or PP as the outcome. Variable importance analysis was conducted by calculating the out-of-bag errors with multiple bootstrapped data sets. The most prognostic features were selected using the RF importance scores. Thirty-six patients were screened for inclusion: 9 were excluded due to no T2 lesion (RC ROI only). Of the remaining 27 patients: 10 had NP, 11 had TP, and 6 had PP. Thirty-nine texture features, plus lesion volume and mean lesion intensity (for a total of 41 variables per time point) were calculated and included in the model. Of the 10 most prognostic features, 6 were from D10, suggesting that prognostic changes in the underlying lesion microenvironment are occurring within the first 10 fractions of treatment. The model selected GLSZM high gray-level zone emphasis (HGZE) D10, IBSI code 5GN9, as the most prognostic feature. The receiver operator characteristic (ROC) area under the curve (AUC) for GLSZM HGZE D10 was 0.94 (95% CI = 0.81-1.00). Delta radiomic features extracted from MR-Linac imaging may predict between PP and TP in GBM patients during treatment, which is earlier than current methods. This could allow physicians to adapt/intensify treatment in real time for poorly responding patients. Future directions include analysis with a larger patient cohort and with additional MRI contrasts (MR-Linac multiparametric MRI).

Retracted: Value of CT Radiomics and Clinical Features in Predicting Bone Metastases in Patients with NSCLC.

[This retracts the article DOI: 10.1155/2022/7642511.].

Preoperative prediction of microvascular invasion in hepatocellular carcinoma using ultrasound features including elasticity.

Microvascular invasion (MVI) is an important predictor of poor prognosis in patients with hepatocellular carcinoma (HCC). Accurate preoperative prediction of MVI in HCC would provide useful information to guide the choice of therapeutic strategy. Shear wave elastography (SWE) plays an important role in hepatic imaging, but its value in the preoperative prediction of MVI in HCC has not yet been proven. To explore the value of conventional ultrasound features and SWE in the preoperative prediction of MVI in HCC. Patients with a postoperative pathological diagnosis of HCC and a definite diagnosis of MVI were enrolled in this study. Conventional ultrasound features and SWE features such as maximal elasticity (Emax) of HCCs and Emax of the periphery of HCCs were acquired before surgery. These features were compared between MVI-positive HCCs and MVI-negative HCCs and between mild MVI HCCs and severe MVI HCCs. This study included 86 MVI-negative HCCs and 102 MVI-positive HCCs, including 54 with mild MVI and 48 with severe MVI. Maximal tumor diameters, surrounding liver tissue, color Doppler flow, Emax of HCCs, and Emax of the periphery of HCCs were significantly different between MVI-positive HCCs and MVI-negative HCCs. In addition, Emax of the periphery of HCCs was significantly different between mild MVI HCCs and severe MVI HCCs. Higher Emax of the periphery of HCCs and larger maximal diameters were independent risk factors for MVI, with odds ratios of 2.820 and 1.021, respectively. HCC size and stiffness of the periphery of HCC are useful ultrasound criteria for predicting positive MVI. Preoperative ultrasound and SWE can provide useful information for the prediction of MVI in HCCs.

Radiomics Nomogram with Added Nodal Features Improves Treatment Response Prediction in Locally Advanced Esophageal Squamous Cell Carcinoma: A Multicenter Study.

We aimed to develop and validate a radiomics nomogram and determine the value of radiomic features from lymph nodes (LNs) for predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced esophageal squamous cell carcinoma (ESCC). In this multicenter retrospective study, eligible participants who had undergone NCRT followed by radical esophagectomy were consecutively recruited. Three radiomics models (modelT, modelLN, and modelTLN) based on tumor and LN features, alone and combined, were developed in the training cohort. The radiomics nomogram was developed by incorporating the prediction value of the radiomics model and clinicoradiological risk factors using multivariate logistic regression, and was evaluated using the receiver operating characteristic curve, validated in two external validation cohorts. Between October 2011 and December 2018, 116 patients were included in the training cohort. Between June 2015 and October 2020, 51 and 27 patients from two independent hospitals were included in validation cohorts 1 and 2, respectively. The radiomics modelTLN performed better than the radiomics modelT for predicting pCR. The radiomics nomogram incorporating the predictive value of the radiomics modelTLN and heterogeneous after NCRT outperformed the clinicoradiological model, with an area under the curve (95% confidence interval) of 0.833 (0.765-0.894) versus 0.764 (0.686-0.833) [p = 0.088, DeLong test], 0.824 (0.718-0.909) versus 0.692 (0.554-0.809) [p = 0.012], and 0.902 (0.794-0.984) versus 0.696 (0.526-0.857) [p = 0.024] in all three cohorts. Radiomic features from LNs could provide additional value for predicting pCR in ESCC patients, and the radiomics nomogram provided an accurate prediction of pCR, which might aid treatment decision.

The monetary value of convenience and environmental features in residential heat energy consumption, in particular its social determinants

Environmental and comfort value of renewable energy sources is a less studied area. The article introduce the economic value of these characteristics, related to social determinants. The data basis is representative of the Hungarian population above 18 years of age, by gender, age and level of education. Our model estimation was developed by hybrid choice context in latent class modelling. In addition to the usual WTP (willingness to pay) calculation, we also used WTI (willingness to invest) calculations. The results show that the value of environmentally-friendly nature in Hungary exceeds the convenience factor. The latter cannot be significantly detected for the majority of the Hungarian population. This statement is supported by results for both fuels and boilers. Our findings show the strong attachment of the Hungarian average person to the use of firewood and natural gas, which are very typical in Hungarian heat consumption. Regarding socially selected consumer groups, strong correlation can be observed between social capital supply, income level, access to information and environmental awareness in Hungary. Regarding policy implications, our results in development of clusters may be useful for the establishment of a selective support policy and two clearly identifiable groups should be highlighted in the energy policy.

Prognostic Value of Metabolic Parameters and Textural Features in Pretreatment 18F-FDG PET/CT of Primary Lesions for Pediatric Patients with Neuroblastoma

Our study evaluated the prognostic value of the metabolic parameters and textural features in pretreatment 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) of primary lesions for pediatric patients with neuroblastoma. In total, 107 pediatric patients with neuroblastoma who underwent pretreatment 18F-FDG PET/CT were retrospectively included and analyzed. All patients were diagnosed by pathology, and baseline characteristics and clinical data were collected. The four metabolic parameters and 43 textural features of 18F-FDG PET/CT of the primary lesions were measured. The prognostic significance of metabolic parameters and other clinical variables was assessed using Cox proportional hazards regression models. Differences in progression-free survival (PFS) and overall survival (OS) in relation to parameters were examined using the Kaplan-Meier method. During a median follow-up period of 34.3 months, 45 patients (42.1%) experienced tumor recurrence or progression, and 21 patients (19.6%) died of cancer. In univariate Cox regression analysis, age, location of disease, International Neuroblastoma Risk Group Staging System (INRGSS) stage M, neuron-specific enolase (NSE), lactate dehydrogenase (LDH), four positron emission tomography (PET) metabolic parameters, and 33 textural features were significant predictors of PFS. In multivariate analysis, INRGSS stage M (hazard ratio [HR]=19.940, 95% confidence interval [CI]=2.733-145.491, P=0.003), skewness (＞0.173; PET first-order features; HR=2.938, 95% CI=1.389-6.215, P=0.005), coarseness (＞0.003; neighborhood gray-tone difference matrix; HR=0.253, 95% CI=0.132-0.484, P＜0.001), and variance (＞103.837; CT first-order gray histogram parameters; HR=2.810, 95% CI=1.160-6.807, P=0.022) were independent predictors of PFS. In univariate Cox regression analysis, gender, INRGSS stage M, MYCN amplification, NSE, LDH, two PET metabolic parameters, and five textural features were significant predictors of OS. In multivariate analysis, INRGSS stage M (HR=7.704, 95% CI=1.031-57.576, P=0.047), MYCN amplification (HR=3.011, 95% CI=1.164-7.786, P=0.023), and metabolic tumor volume (＞138.788; HR=3.930, 95% CI=1.317-11.727, P=0.014) were independent predictors of OS. The metabolic parameters and textural features in pretreatment 18F-FDG PET/CT of primary lesions are predictive of survival in pediatric patients with neuroblastoma.

The relation between psychopathy factors and emotional states prior and during criminal behaviour in a Dutch sample

PurposeThe purpose of this study is to examine the predictive value of psychopathy features on crime-related emotional states in forensic male patients with offence histories who were mandated to Dutch clinical care.Design/methodology/approachThe study had a retrospective design in which psychopathy features were assessed using the Psychopathy Checklist-Revised. For each patient, information on the events leading up to the crime and a description of the crime itself were extracted from the hospital record to assess emotional states. These crime-related emotional states were assessed using the mode observation scale. The sample consisted of 175 patients with offence histories.FindingsMultiple regression analyses indicated that affective features of psychopathy were a negative predictor for feelings of vulnerability in the events leading up to the crime but not predictive of loneliness. The interpersonal features were predictive of deceit during criminal behaviour.Practical implicationsThis study leads to a better, more nuanced and substantiated understanding of which emotional states play a prominent role in criminal behaviour and how these states are affected by psychopathic traits. This knowledge can influence existing treatment programmes for patients with offence histories.Originality/valueSeveral studies have examined the relationship between emotional states and criminal behaviour and between psychopathy and emotions, but less is known about the predictive relationship between psychopathy features and crime-scene-related emotional states.

Angiography-based hemodynamic features predict recurrent ischemic events after angioplasty and stenting of intracranial vertebrobasilar atherosclerotic stenosis

ObjectivesTo assess the predictive value of hemodynamic features for stroke relapse in patients with intracranial vertebrobasilar atherosclerotic stenosis treated with percutaneous transluminal angioplasty and stenting (PTAS) using quantitative digital subtraction angiography (q-DSA).MethodsIn this retrospective longitudinal study, patients with intracranial vertebrobasilar atherosclerotic stenosis and who underwent PTAS treatment between January 2012 and May 2020 were enrolled. The q-DSA assessment was performed before and after PTAS. ROIs 1–4 were placed along the vertebral artery, proximal and distal basilar artery, and posterior cerebral artery; ROIs 5–8 were in 5 mm and 10 mm proximal and distal to the lesion, respectively. Relative time to peak (rTTP) was defined as the difference in TTP between ROIs. Cox regression analyses were performed to determine risk factors for recurrent stroke.ResultsA total of 137 patients (mean age, 62 years ± 10 [standard deviation], 83.2% males) were included, and 26 (19.0%) patients had stroke relapse during follow-up (median time of 42.6 months [interquartile range, 19.7–60.7]). Preprocedural rTTP4-1 (adjusted hazard ratio (HR) = 2.270; 95% CI 1.371–3.758; p = 0.001) and preprocedural rTTP8-5 (adjusted HR = 0.240; 95% CI 0.088–0.658; p = 0.006) were independently associated with the recurrent stroke. These hemodynamic parameters provided an incremental prognostic value for stroke relapse (AUC, 0.817 [0.704–0.931]; the net reclassification index, 0.431 [0.057–0.625]; and the integrated discrimination index, 0.140 [0.035–0.292]).ConclusionsIn patients with intracranial vertebrobasilar atherosclerosis treated with PTAS, preprocedural prolonged TTP of the target vessel and shortened trans-stenotic TTP difference were associated with stroke relapse. Q-DSA-defined hemodynamic parameters provided incremental predictive value over conventional parameters for stroke recurrence.Clinical relevance statementQuantitative DSA analysis enables intuitive observation and semi-quantitative evaluation of peri-therapeutic cerebral blood flow. More importantly, quantitative DSA–defined hemodynamic parameters have the potential for risk stratification of patients with intracranial atherosclerotic stenosis.Key PointsSemi-quantitative angiography-based parameters can reflect pre- and postprocedural subtle changes in blood flow in patients with intracranial atherosclerotic stenosis.Although angioplasty procedures can significantly improve blood flow status, patients with more restricted baseline blood flow still show a higher risk of stroke recurrence.Angiography-based hemodynamic features possess prognostic value and can serve as clinical markers to assess stroke risk of patients with intracranial atherosclerotic stenosis.

DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

DNA damage repair (DDR) is a critical process that maintains genomic integrity and plays essential roles at both the cellular and organismic levels. Here, we aimed to characterize the DDR profiling of esophageal squamous cell carcinoma (ESCC), investigate the prognostic value of DDR-related features, and explore their potential for guiding personalized treatment strategies. We analyzed bulk and single-cell transcriptomics data from 377 ESCC cases from our institution and other publicly available cohorts to identify major DDR subtypes. The heterogeneity in cellular and functional properties, tumor microenvironment (TME) characteristics, and prognostic significance of these DDR subtypes were investigated using immunogenomic analysis and invitro experiments. Additionally, we experimentally validated a combinatorial immunotherapy strategy using syngeneic mouse models of ESCC. DDR alteration profiling enabled us to identify two distinct DDR subtypes, DDRactive and DDRsilent, which exhibited independent prognostic values in locoregional ESCC but not in metastatic ESCC. The DDRsilent subtype was characterized by an inflamed but immune-suppressed microenvironment with relatively high immune cell infiltration, abnormal immune checkpoint expression, T-cell exhaustion, and enrichment of cancer-related pathways. Moreover, DDR subtyping indicates that BRCA1 and HFM1 are robust and independent prognostic factors in locoregional ESCC. Finally, we proposed and verified that the concomitant triggering of GITR or blockade of BTLA with PD-1 blockade or cisplatin chemotherapy represents effective combination strategies for high-risk locoregional ESCC tumors. Our discovery of DDR-based molecular subtypes will enhance our understanding of tumor heterogeneity and have significant clinical implications for the therapeutic and management strategies of locoregional ESCC. This study was supported by the National Key R&D Program of China (2021YFC2501000, 2022YFC3401003), National Natural Science Foundation of China (82172882), the Beijing Natural Science Foundation (7212085), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091), and the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310027).

Variation in spatial dependencies across the cortical mantle discriminates the functional behaviour of primary and association cortex

Recent theories of cortical organisation suggest features of function emerge from the spatial arrangement of brain regions. For example, association cortex is located furthest from systems involved in action and perception. Association cortex is also ‘interdigitated’ with adjacent regions having different patterns of functional connectivity. It is assumed that topographic properties, such as distance between regions, constrains their functions, however, we lack a formal description of how this occurs. Here we use variograms, a quantification of spatial autocorrelation, to profile how function changes with the distance between cortical regions. We find function changes with distance more gradually within sensory-motor cortex than association cortex. Importantly, systems within the same type of cortex (e.g., fronto-parietal and default mode networks) have similar profiles. Primary and association cortex, therefore, are differentiated by how function changes over space, emphasising the value of topographical features of a region when estimating its contribution to cognition and behaviour.

Extracting product design guidance from online reviews: An explainable neural network-based approach

With the development of data mining techniques, user-generated data has become a valuable resource in diverse research areas. In product design research, many studies have been utilizing user data to discover implications for new product design. However, previous works focused on analyzing existing features, whereas companies also need strategies for new features. Some studies discovered new feature ideas from user data but did not provide design implications. This paper addresses the above limitation by extracting comprehensive design implications for both features from user data. The method first defines the lists of existing/new features and collects spec data for these features. Then, it constructs customer choice sets based on the online review and spec data. Regarding spec values, this study presents a newness merit function that reflects the changing value of new features and applies it to the choice sets. The final stage trains a neural network model based on choice sets and conducts SHAP (SHapley Additive exPlanations) on the model. The method draws design implications by further analyzing the resultant SHAP values. The suggested methodology was tested on real-world datasets. The result provides design guidance, including strategies for new features and recommended spec ranges for existing features. This article validates the result by showing that the obtained design implications are consistent with previous market research for product features.