Radically Accessing D–A Type Ambipolar Copolymeric Materials with Intrinsic Electrical Conductivity and Visible–Near Infrared Absorption Via Electro‐Copolymerization

Thienothiadiazole‐bisthiophene (TTDT₂) and diketopyrrolo–pyrrole–bisthiophene (DPPT₂) are successfully electro‐copolymerized with terthiophene (T₃) as an initiator and linker at low oxidative potentials. AC impedance analysis, absorption spectroscopy, and elemental composition via SEM‐EDX support the formation of donor–acceptor (D–A) type alternating block copolymers, poly(T₃‐TTDT₂), and poly(T₃‐DPPT₂). Unique optical properties that span into the near infrared‐II(>1000 nm) region and inherent electrical conductivity at the p‐type regime, n‐type regime, and in between the two regimes (i.e., typical insulator region) are observed. This study showcases the advantages of electro‐polymerization toward tailoring of next generation opto‐electronic materials.     

Robotic-assisted vs. open radical prostatectomy: A machine learning framework for intelligent analysis of patient-reported outcomes from online cancer support groups

Background

The advantages of Robot-assisted laparoscopic prostatectomy (RARP) over open radical prostatectomy (ORP) in Prostate cancer perioperatively are well-established, but quality of life is more contentious. Increasingly, patients are utilising online cancer support groups (OCSG) to express themselves. Currently there is no method of analysis of these sophisticated data sources. We have used the PRIME-2 (Patient Reported Information Multidimensional Exploration version 2) framework for automated identification and intelligent analysis of decision-making, functional and emotional outcomes in men undergoing ORP vs. RARP from OCSG discussions.

Visual Field Sensitivity Prediction Using Optical Coherence Tomography Analysis in Hydroxychloroquine Toxicity

PurposeThis study investigates the association between local retina structure and visual function in a cohort with long-term hydroxychloroquine (HCQ) use.MethodsThe study included 84 participants (54 participants without toxicity and 30 participants with toxicity) with history of chronic HCQ use (14.5 ± 7.4 years) who had testing with spectral-domain optical coherence tomography (SD-OCT) imaging and Humphrey 10-2 visual fields. Optical coherence tomography (OCT) metrics (total and outer retina thickness [TRT and ORT], minimum intensity [MinI], and ellipsoid zone [EZ] loss) were sampled in regions corresponding to visual field test locations. Univariate linear correlations were investigated and a multivariate random forest regression using a combination of OCT metrics was used to predict visual field sensitivity by locus using a leave-one-out cross-validation strategy.ResultsIn univariate linear regression, EZ loss demonstrated the strongest relationship with visual field sensitivities in the parafoveal ring with R² = 0.58. TRT and ORT revealed positive correlations with visual field sensitivity (R² = 0.57 and 0.40, respectively), whereas total and outer retinal MinI yielded negative correlations (R² = 0.10 and 0.22). The multivariate model improved correlations (R² = 0.66) yielding a root mean squared error of 3.8 decibel (dB). Feature importance analysis identified EZ loss as the most relevant predictor of function.ConclusionsMultiple OCT-derived quantitative metrics used in combination can provide information to predict local sensitivities. The results indicate a strong relationship between retinal function and OCT measures, which contribute to the understanding of the retinal toxicity caused by HCQ as well as being applicable to outcome development for other degenerative diseases of the outer retina.     

Screening of Neonatal UK Dried Blood Spots Using a Duplex TREC Screening Assay

Purpose

Severe Combined Immunodeficiency (SCID) is considered to be a paediatric emergency and unless identified promptly can be life-threatening. Frequently, infants are not diagnosed with SCID until they have become seriously ill with infection leading to treatment complications and a poorer prognosis. We aimed to test a newly available commercial duplex assay to measure T cell receptor excision circles (TRECs) to establish if this would be suitable for newborn screening for SCID in the UK.

Methods

Over 5000 anonymous retrospective dried blood spots (DBS) were used alongside 18 confirmed SCID positive DBS with a newly available duplex assay to measure TRECs levels and control gene levels. We also included testing of premature babies and babies from neonatal intensive care units (NICU) as these have been shown to have high false positive rates in other TREC screening assays.

Results

All 18 SCID DBS samples were successfully identified as SCID positives in the study. The number of presumptive positives detected was dependent on the TREC cut-off threshold settings. When analysed with five different TRECs cut-off values (20, 25, 30, 35 and 40 TREC copies/μl blood) the presumptive positive rate ranged from 0.04 to 1.00 % of samples tested. Premature infants and neonates from NICU did not show high presumed false positive rates in this assay.

Conclusions

The study demonstrated that this duplex assay kit will identify all newborns with SCID as presumptive positives. The data also shows that with suitable TREC cut-off settings the number of presumptive positives from non-SCID newborns will be manageable in the context of a national screening service.     

Deep-learning based multi-modal retinal image registration for the longitudinal analysis of patients with age-related macular degeneration

This work reports a deep-learning based registration algorithm that aligns multi-modal retinal images collected from longitudinal clinical studies to achieve accuracy and robustness required for analysis of structural changes in large-scale clinical data. Deep-learning networks that mirror the architecture of conventional feature-point-based registration were evaluated with different networks that solved for registration affine parameters, image patch displacements, and patch displacements within the region of overlap. The ground truth images for deep learning-based approaches were derived from successful conventional feature-based registration. Cross-sectional and longitudinal affine registrations were performed across color fundus photography (CFP), fundus autofluorescence (FAF), and infrared reflectance (IR) image modalities. For mono-modality longitudinal registration, the conventional feature-based registration method achieved mean errors in the range of 39-53 µm (depending on the modality) whereas the deep learning method with region overlap prediction exhibited mean errors in the range 54-59 µm. For cross-sectional multi-modality registration, the conventional method exhibited gross failures with large errors in more than 50% of the cases while the proposed deep-learning method achieved robust performance with no gross failures and mean errors in the range 66-69 µm. Thus, the deep learning-based method achieved superior overall performance across all modalities. The accuracy and robustness reported in this work provide important advances that will facilitate clinical research and enable a detailed study of the progression of retinal diseases such as age-related macular degeneration.     

Is the copper T 380A device associated with an increased risk of removal due to bleeding and/or pain? An analysis

Previous studies have consistently shown that the family of the Copper T 380 devices is more effective in preventing accidental pregnancies than the inert, as well as most other, if not all, copper devices. However, a number of these studies also reported a higher removal rate due to bleeding and/or pain for the TCu 380A than for other devices. The programmatical importance of these findings prompted us to analyze the international multi-center randomized clinical trial datasets to examine this question on the new TCu 380A (ParaGard) recently marketed in the U.S. Our results, while confirming the inherent superior efficacy of the TCu 380A, did not reveal a significantly higher removal rate because of bleeding and/or pain among TCu 380A users than among users of the comparative devices, which included the Lippes Loop D, the TCu 200, the TCu 220 and the Multiload Cu 250 devices.     

Clinical Translation of the <Emphasis Type="Italic">LevelCheck</Emphasis> Decision Support Algorithm for Target Localization in Spine Surgery

Recent work has yielded a method for automatic labeling of vertebrae in intraoperative radiographs as an assistant to manual level counting. The method, called LevelCheck, previously demonstrated promise in phantom studies and retrospective studies. This study aims to: (#1) Analyze the effect of LevelCheck on accuracy and confidence of localization in two modes: (a) Independent Check (labels displayed after the surgeon’s decision) and (b) Active Assistant (labels presented before the surgeon’s decision). (#2) Assess the feasibility and utility of LevelCheck in the operating room. Two studies were conducted: a laboratory study investigating these two workflow implementations in a simulated operating environment with 5 surgeons, reviewing 62 cases selected from a dataset of radiographs exhibiting a challenge to vertebral localization; and a clinical study involving 20 patients undergoing spine surgery. In Study #1, the median localization error without assistance was 30.4% (IQR?=?5.2%) due to the challenging nature of the cases. LevelCheck reduced the median error to 2.4% for both the Independent Check and Active Assistant modes (p?<?0.01). Surgeons found LevelCheck to increase confidence in 91% of cases. Study #2 demonstrated accuracy in all cases. The algorithm runtime varied from 17 to 72 s in its current implementation. The algorithm was shown to be feasible, accurate, and to improve confidence during surgery.     

Implementing the donor–acceptor approach in electronically conducting copolymers via electropolymerization

Electropolymerization has become a convenient method for synthesizing and characterizing complex organic copolymers having intrinsic electronic conductivity, including the donor (D)–acceptor (A) class of electronically conducting polymers (ECPs). This review begins with an introduction to the electrosynthesis of common second-generation ECPs. The information obtainable from electroanalytical studies, charge carriers such as polarons (positive and negative) and bipolarons (positive and negative) and doping will be discussed. The evolutionary chain of ECPs is then presented. ECPs comprising electron-rich D and electron-deficient A moieties have been shown to possess intrinsic electronic conductivity and unique optical and electronic properties. They are third generation ECPs and electropolymerization of mixtures of D and A leads to stoichiometrically controlled block copolymers. These D–A type ECPs are discussed on the basis of selected representative materials. Since the discovery of electropolymerization as a powerful tool to synthesize copolymers of conjugated monomers with a pre-determined ratio of D and A repeat units present in the polymer, the field of D–A type ECPs has grown considerably and the literature available since 2004 to 2021 is summarized and tabulated. Electronic and optical properties of the materials determined by computational chemistry are presented. The data obtained from electrochemical and optical methods are compared with those obtained from computational methods and reasons for discrepancies are given. The literature on the concept of electropolymerization extended to synthesizing triblock and many-block copolymers is reviewed. Finally, applications of D–A polymers in optoelectronic devices (organic solar cells and field-effect transistors) and in bio-imaging are explained quoting appropriate examples.

Electropolymerization has become a convenient method for synthesizing and characterizing complex organic copolymers having intrinsic electronic conductivity, including the donor (D)–acceptor (A) class of electronically conducting polymers (ECPs).