Machine learning in prenatal MRI predicts postnatal ventricular abnormalities in fetuses with isolated ventriculomegaly.

Objectives: To evaluate the intracranial structures and brain parenchyma radiomics surrounding the occipital horn of the lateral ventricle in normal fetuses (NFs) and fetuses with ventriculomegaly (FVs), as well as to predict postnatally enlarged lateral ventricle alterations in FVs.

Methods: Between January 2014 and August 2023, 141 NFs and 101 FVs underwent 1.5 T balanced steady-state free precession (BSSFP), including 68 FVs with resolved lateral ventricles (FVM-resolved) and 33 FVs with stable lateral ventricles (FVM-stable).

Serum biomarkers in patients with drug-resistant epilepsy: a proteomics-based analysis.

Objective: To investigate the serum biomarkers in patients with drug-resistant epilepsy (DRE).

Methods: A total of 9 DRE patients and 9 controls were enrolled. Serum from DRE patients was prospectively collected and analyzed for potential serum biomarkers using TMT18-labeled proteomics.

Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI.

Objective: To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions.

Methods: Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis.

A tract-based spatial statistics study of white matter integrity in epilepsy.

Objective: To explore the changes of cerebral white matter diffusion tensor in epilepsy.

Methods: This study was a retrospective study based on diffusion tensor imaging (DTI). Twenty-six epileptic patients and 42 normal controls matched for sex, age and handedness were enrolled in our research.

RESOLVE-DWI-based deep learning nomogram for prediction of normal-sized lymph node metastasis in cervical cancer: a preliminary study.

Background: It is difficult to predict normal-sized lymph node metastasis (LNM) in cervical cancer clinically. We aimed to investigate the feasibility of using deep learning (DL) nomogram based on readout segmentation of long variable echo-trains diffusion weighted imaging (RESOLVE-DWI) and related patient information to preoperatively predict normal-sized LNM in patients with cervical cancer.

Methods: A dataset of MR images [RESOLVE-DWI and apparent diffusion coefficient (ADC)] and patient information (age, tumor size, International Federation of Gynecology and Obstetrics stage, ADC value and squamous cell carcinoma antigen level) of 169 patients with cervical cancer between November 2013 and January 2022 were retrospectively collected.

Functional Localized High-Concentration Ether-Based Electrolyte for Stabilizing High-Voltage Lithium-Metal Battery.

Localized high-concentration electrolytes have attracted much attention of researchers due to their low viscosity, low cost, and relatively higher electrochemical performance than their low-concentration counterparts. In our work, 1.5 M (mol L) locally concentrated ether-based electrolyte has been obtained by adding 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (HFE) into a 4 M LiFSI concentrated dimethoxyethane (DME)-based electrolyte.

The association between insulin therapy and depression in patients with type 2 diabetes mellitus: a meta-analysis.

Objectives: Several patients with type 2 diabetes mellitus (T2DM) have depressive disorders. Whether insulin treatment was associated with increased risk of depression remains controversial. We performed a meta-analysis to evaluate the association of insulin therapy and depression.

Two nanocage-based metal-organic frameworks with mixed-cluster SBUs and CO2 sorption selectivity.

Two nanocage-based metal-organic frameworks respectively built on two and three types of clusters with diisophthalate ligand were constructed, displaying unprecedented (3,4,6)-connected nets, unusual nanocages, and new bipaddle-wheel tetranuclear cluster, as well as highly selective CO2 capture.

Double-step CO2 sorption and guest-induced single-crystal-to-single-crystal transformation in a flexible porous framework.

A new 2D highly flexible and breathing porous framework [CuL(Me2NH)]·DMF·H2O () (H3L = 5-(4'-carboxylphenoxy)nicotinic acid) has been synthesized using a tritopic linker with a flexible joint. The desolvated framework, [CuL(Me2NH)] (), undergoes structural contraction, and exhibits selective and double-step hysteretic adsorption for CO2. Furthermore, on exposure to CH2Cl2 at room temperature, a unique single-crystal-to-single-crystal transformation occurred between and [Cu2L2(Me2NH)2(H2O)2]·5H2O ().