Surface- and Spatial-Regulated Cd-Free Quantum Dots for Efficient, Mechanically Stable, and Full-Color Flexible Light-Emitting Diodes.

Flexible light-emitting diodes utilizing environmentally friendly cadmium (Cd)-free quantum dots (QDs) hold immense potential for next-generation wearable integrated displays. However, their overall performance lags behind Cd-based counterparts, and less research focuses on the suitability of QD layers in flexible devices. Herein, it is observed that the traditional surface oleate ligands on QDs readily detach under device operation after cycling bending, leading to increased surface defects and accumulated tensile stress in QDs layers, further diminishing their photoluminescence and electroluminescence performance.

Homogeneous ZnSeTeS quantum dots for efficient and stable pure-blue LEDs.

The electroluminescence performance of heavy-metal-free blue quantum dot (QD) light-emitting diodes (QLEDs) is much lower than that of state-of-the-art cadmium-based counterparts. Ecofriendly ZnSeTe QDs are an ideal alternative to cadmium-based blue QDs, but face issues with colour impurity and inferior stability caused by the aggregated tellurium (Te) that dominates compositional inhomogeneity. Here we developed an isoelectronic control strategy using congeneric sulfur coordinated with triphenyl phosphite (TPP-S) to construct homogeneous ZnSeTeS QDs with pure-blue emissions and near-unity photoluminescence quantum yield.

Neural Orthodontic Staging: Predicting Teeth Movements with a Transformer.

We present a novel learning-based method for predicting tooth movements in orthodontic treatment path planning (orthodontic staging). Recognizing the multi-solution nature of orthodontic staging, our approach involves generating the staging sequence progressively with a dedicated Transformer model. This model predicts teeth movements within a predefined number of steps (e.

The efficacy of adjuvant chemotherapy for curative resected biliary tract cancers: a systematic review and network meta-analysis of randomized clinical trials.

Background: Despite complete resection, the recurrence rate of biliary tract cancer (BTC) remains high, leading to poor prognosis. Postoperative adjuvant chemotherapy (ACT) following radical resection may substantially reduce the recurrence risk by eradicating micrometastatic lesions. However, the benefits of postoperative ACT and the optimal ACT strategy are still unclear for BTC.

Improved Efficiency and Stability in Pure-Red CdSe Nanoplatelet LEDs Enabled by Gradient Alloyed CdSeS/CdZnS Crown/Shell.

Anisotropic nanoplatelets (NPLs) possess strong in-plane transition dipole moments and out-of-plane emission, which enable a maximum photon out-coupling efficiency of 40% and a high gain coefficient, making them ideal candidates for light-emitting diodes (LEDs) and lasers. However, the unbalanced surface energy between the side and top facets of NPLs results in poor thermal stability and high susceptibility to ripening at elevated temperatures, which complicates the growth of the shell. To address this issue, a gradient crown (CdSeS) around the CdSe NPLs is designed to stabilize the high energy side facets.

Comparative evaluation of periodontally accelerated osteogenic orthodontics (PAOO) versus traditional camouflage orthodontic treatment in adult patients with skeletal class III malocclusion.

Background: Existing literature supports the efficacy of PAOO in augmenting alveolar bone volume and facilitating orthodontic tooth movement. However, there is a paucity of literature addressing its application in the treatment of adults with skeletal Class III malocclusion. This retrospective clinical study aimed to compare the clinical efficacy of camouflage orthodontic treatment combined with and without PAOO in adult patients presenting with skeletal Class III malocclusion.

Research on Sleep Staging Based on Support Vector Machine and Extreme Gradient Boosting Algorithm.

Purpose: To develop a sleep-staging algorithm based on support vector machine (SVM) and extreme gradient boosting model (XB Boost) and evaluate its performance.

Methods: In this study, data features were extracted based on physiological significance, feature dimension reduction was performed through appropriate methods, and XG Boost classifier and SVM were used for classification. One hundred and twenty training sets and 80 test sets were randomly composed of the first 200 groups of data from the SHH1 database.

Development and validation of a radiomics-based nomogram for the prediction of postoperative malnutrition in stage IB1-IIA2 cervical carcinoma.

Objective: In individuals with stage IB1-IIA2 cervical cancer (CC) who received postoperative radiotherapy ± chemotherapy (PORT/CRT), the interaction between sarcopenia and malnutrition remains elusive, let alone employing a nomogram model based on radiomic features of psoas extracted at the level of the third lumbar vertebra (L3). This study was set to develop a radiomics-based nomogram model to predict malnutrition as per the Patient-Generated Subjective Global Assessment (PG-SGA) for individuals with CC.

Methods: In total, 120 individuals with CC underwent computed tomography (CT) scans before PORT/CRT.

A 5-year survival status prognosis of nonmetastatic cervical cancer patients through machine learning algorithms.

Background: Prediction models with high accuracy rates for nonmetastatic cervical cancer (CC) patients are limited. This study aimed to construct and compare predictive models on the basis of machine learning (ML) algorithms for predicting the 5-year survival status of CC patients through using the Surveillance, Epidemiology, and End Results public database of the National Cancer Institute.

Methods: The data registered from 2004 to 2016 were extracted and randomly divided into training and validation cohorts (8:2).

The Influence of Demographics and Vascular Risk Factors on Glymphatic Function Measured by Diffusion Along Perivascular Space.

Assessing glymphatic function using in-vivo imaging method is of great value for understanding its contribution to major brain diseases. In the present study, we aim to validate the association between a variety of risk factors and a potential index of glymphatic function-Diffusion Tensor Image Analysis Along the Perivascular Space (ALPS index). We enrolled 142 subjects from communities and performed multi-modality magnetic resonance imaging scans.

A Nomogram-Based Risk Classification System Predicting the Overall Survival of Patients With Newly Diagnosed Stage IVB Cervix Uteri Carcinoma.

This study constructed and demonstrated a model to predict the overall survival (OS) of newly diagnosed distant metastatic cervical cancer (mCC) patients. The SEER (Surveillance, Epidemiology, and End Results) database was used to collect the eligible data, which from 2010 to 2016. Then these data were separated into training and validation cohorts (7:3) randomly.

Characterization of Lenticulostriate Arteries and Its Associations With Vascular Risk Factors in Community-Dwelling Elderly.

Lenticulostriate arteries (LSAs) supply blood to important subcortical areas and are, therefore, essential for maintaining the optimal functioning of the brain's most metabolically active nuclei. Past studies have demonstrated the potential for quantifying the morphology of LSAs as biomarkers of vascular fragility or underlying arteriopathies. Thus, the current study aims to evaluate the morphological features of LSAs, their potential value in cerebrovascular risk stratification, and their concordance with other vascular risk factors in community-dwelling elderly people.

Quantity and Morphology of Perivascular Spaces: Associations With Vascular Risk Factors and Cerebral Small Vessel Disease.

Background: Perivascular spaces (PVSs) are important component of the brain glymphatic system. While visual rating has been widely used to assess PVS, computational measures may have higher sensitivity for capturing PVS characteristics under disease conditions.

Purpose: To compute quantitative and morphological PVS features and to assess their associations with vascular risk factors and cerebral small vessel disease (CSVD).

Factors Associated With the Dilation of Perivascular Space in Healthy Elderly Subjects.

The dilation of perivascular space (PVS) has been widely used to reflect brain degeneration in clinical brain imaging studies. However, PVS characteristics exhibit large differences in healthy subjects. Such variations need to be better addressed before PVS can be used to reflect pathological changes.

Deep white matter hyperintensity is associated with the dilation of perivascular space.

Understanding the pathophysiology of white matter hyperintensity (WMH) is necessary to reduce its harmfulness. Dilated perivascular space (PVS) had been found related to WMH. In the present study, we aimed to examine the topological connections between WMH and PVS, and to investigate whether increased interstitial fluid mediates the correlation between PVS and WMH volumes.

White Matter Free Water is a Composite Marker of Cerebral Small Vessel Degeneration.

To investigate the association between white matter free water (FW) and common imaging markers of cerebral small vessel diseases (CSVD) in two groups of subjects with different clinical status. One hundred and forty-four community subjects (mean age 60.5) and 84 CSVD subjects (mean age 61.

Disentangling the pathologies linking white matter hyperintensity and geriatric depressive symptoms in subjects with different degrees of vascular impairment.

Background: White matter hyperintensity (WMH) is closely associated with geriatric depressive symptoms, but its underlying neural mechanism is unclear. We aim to disentangle the contribution of vascular degeneration and fiber disruption to depressive symptoms in elderly subjects at different clinical status.

Methods: One hundred and thirty-three normal elderly subjects, as well as 43 patients with cerebral small vessel disease (CSVD) were included.

Pretreatment nutritional risk scores and performance status are prognostic factors in esophageal cancer patients treated with definitive chemoradiotherapy.

This study evaluated the prognostic effects of nutritional risk scores and performance status (PS) on unresectable locally advanced esophageal cancer (LAEC) patients who were treated with definitive concurrent chemoradiotherapy (dCRT). A total of 202 LAEC patients from four different cancer centers were retrospectively reviewed. Nutritional risk and PS were measured using the Nutritional Risk Screening 2002 (NRS-2002) scores and Eastern Cooperative Oncology Group (ECOG) scales.

BMP-2 plasmid DNA-loaded chitosan films - A new strategy for bone engineering.

Objectives: Bone defects are common in every area of medicine and remain a clinical challenge. Tissue engineering has led to promising new strategies in accelerating bone repair. Bone morphogenetic proteins (BMPs) play crucial roles in bone regeneration, but are required in supra-physiological doses, which are expensive and produce severe side effects.

Enhancing bone regeneration by combining mesenchymal stem cell sheets with β-TCP/COL-I scaffolds.

The combination of bone marrow-derived mesenchymal stem cells (BMSCs) and biological scaffolds has been demonstrated to be a promising strategy for bone regeneration. However, this method does not result in satisfactory bone regeneration, because the BMSCs are dispersed in the biological scaffolds. The current study developed a new bone regeneration system, which combines synthetic porous three-dimensional scaffolds of β-TCP/COL-I composite with cultured osteogenic sheets of BMSCs.