Green Fluorescent Carbon Dots with Critically Controlled Surface States: Make Silk Shine via Feeding Silkworms.

Feeding silkworms with functional materials as additives to produce naturally modified silk is a facile, diverse, controllable, and environmentally friendly method with a low cost of time and investment. Among various additives, carbon dots (CDs) show unique advantages due to their excellent biocompatibility and fluorescence stability. Here, a new type of green fluorescent carbon dots (G-CDs) is synthesized with a high oil-water partition ratio of 147, a low isoelectric point of 5.16, an absolute quantum yield of 71%, and critically controlled surface states. After feeding with G-CDs, the silkworms weave light yellow cocoons whose green fluorescence is visible to the naked eye under UV light. The luminous silk is sewn onto the cloth to create striking patterns with beautiful fluorescence. Such G-CDs have no adverse effect on the survival rate and the life cycle of silkworms and enable their whole bodies to glow under UV light. Based on the strong fluorescence, chemical stability, and biological safety, G-CDs are found in the digestive tracts, silk glands, feces, cocoons, and even moth bodies. G-CDs accumulate in the posterior silk glands where fibroin protein is secreted, indicating its stronger combination with fibroin than sericin, which meets the requirements for practical applications.

Natalizumab reduces loss of gray matter and thalamic volume in patients with relapsing-remitting multiple sclerosis: A post hoc analysis from the randomized, placebo-controlled AFFIRM trial.

BACKGROUND: Loss of brain gray matter fractional volume predicts multiple sclerosis (MS) progression and is associated with worsening physical and cognitive symptoms. Within deep gray matter, thalamic damage is evident in early stages of MS and correlates with physical and cognitive impairment. Natalizumab is a highly effective treatment that reduces disease progression and the number of inflammatory lesions in patients with relapsing-remitting MS (RRMS). OBJECTIVE: To evaluate the effect of natalizumab on gray matter and thalamic atrophy. METHODS: A combination of deep learning-based image segmentation and data augmentation was applied to MRI data from the AFFIRM trial. RESULTS: This post hoc analysis identified a reduction of 64.3% (p = 0.0044) and 64.3% (p = 0.0030) in mean percentage gray matter volume loss from baseline at treatment years 1 and 2, respectively, in patients treated with natalizumab versus placebo. The reduction in thalamic fraction volume loss from baseline with natalizumab versus placebo was 57.0% at year 2 (p < 0.0001) and 41.2% at year 1 (p = 0.0147). Similar findings resulted from analyses of absolute gray matter and thalamic fraction volume loss. CONCLUSION: These analyses represent the first placebo-controlled evidence supporting a role for natalizumab treatment in mitigating gray matter and thalamic fraction atrophy among patients with RRMS. CLINICALTRIALS.GOV IDENTIFIER: NCT00027300URL: https://clinicaltrials.gov/ct2/show/NCT00027300.

Konectom™ cognitive processing speed test enables reliable remote, unsupervised cognitive assessment in people with multiple sclerosis: Exploring the use of substitution time as a novel digital outcome measure.

BACKGROUND: The Konectom™ smartphone-based cognitive processing speed (CPS) test is designed to assess processing speed and account for impact of visuomotor function on performance. OBJECTIVE: Evaluate reliability and validity of Konectom CPS Test, performed in clinic and remotely. METHODS: Data were collected from people with multiple sclerosis (PwMS) aged 18-64 years and healthy control participants (HC) matched for age, sex, and education. Remote test-retest reliability (intraclass correlation coefficients, ICC); correlation with established clinical measures (Spearman correlation coefficients); group analyses between cognitively impaired/unimpaired PwMS; and influence of age, sex, education, and upper limb motor function on CPS Test measures were assessed. RESULTS: Eighty PwMS and 66 HC participated. CPS Test measures from remote tests had good test-retest reliability (ICC of 0.67-0.87) and correlated with symbol digit modalities test (highest |ρ| = 0.80, p < 0.0001). Remote measures were stable (change from baseline < 5%) and correlated with MS disability (highest |ρ| = 0.39, p = 0.0004) measured by Expanded Disability Status Scale. CPS Test measures displayed sensitivity to cognitive impairment (highest d = 1.47). Demographics and motor function had the lowest impact on CPS Test substitution time, a measure accounting for visuomotor function. CONCLUSION: Konectom CPS Test measures provide valid, reliable remote measurements of cognitive processing speed in PwMS.

Immune cholangitis related to anti-programmed cell death and programmed cell death ligand agents for the treatment of intrahepatic cholangiocarcinoma.

Anti-programmed cell death (anti-PD1) and anti-programmed cell death ligand (anti-PDL1) agents represent a burgeoning field of immunotherapy with an expanding array of indications. In this report, we present the observation of a patient with intrahepatic cholangiocarcinoma exhibiting features of immune-related cholangitis.

Study on AEMs with Excellent Comprehensive Performance Prepared by Covalently Cross-Linked p-Triphenyl with SEBS Remotely Grafted Piperidine Cations.

A series of SEBS-C6-PIP-yPTP (y = 0-15%) AEMs with good mechanical and chemical stability were prepared by combining the strong rigidity of p-triphenyl, good toughness of SEBS, and excellent stability of PIP cations. After the introduction of a p-triphenyl polymer into the main chain, a clear hydrophilic-hydrophobic phase separation structure was constructed within the membrane, forming a continuous and interconnected ion transport channel to improve ion transport efficiency. Moreover, the molecular chains of the cross-linked AEMs change from chain-like to network-like, and the tighter binding between each molecule increases the tensile strength. The special structure of the six-membered ring makes PIP have a significant constraint effect; when nucleophilic substitution and Hoffman elimination occur at the α and ß positions, the required transition state potential energy increases, making the reaction difficult to occur and improving the alkaline stability of the polymer membrane. The SEBS-C6-PIP-15%PTP membrane has the best mechanical properties (Ts = 38.79 MPa, Eb = 183.09% at 80 °C, 100% RH), the highest ion conductivity (102.02 mS. cm-1 at 80 °C), and the best alkaline stability (6.23% degradation at 80 °C in a 2 M NaOH solution for 1400 h). It can be seen that organic-organic covalent cross-linking is an effective means to improve the comprehensive performance of AEMs.

A poor prognostic male choriocarcinoma with multiple systemic metastases: a case report and the literature review.

Background: Non-gestational choriocarcinoma, also known as primary choriocarcinoma, is extremely rare in men, manifesting with specific signs such as breast feminization, testicular atrophy, and loss of libido. The presentation typically includes elevated serum ß-hCG levels, widespread metastatic disease, and a rapid progression of the condition. Case report: We present a rare case of a 41-year-old man diagnosed with choriocarcinoma, exhibiting a unique combination of multiple metastases, including lung, brain, bone, and retroperitoneal lymph node metastases, as confirmed by 18F-FDG PET/CT imaging. The patient was treated with aggressive chemotherapy and pembrolizumab, and the prognosis remained poor. The patient's overall survival was a mere 5 months following diagnosis. Conclusion: Non-gestational choriocarcinoma represents a rare entity in clinical practice and should be considered in young men presenting with gynaecomastia and elevated ß-hCG levels alongside normal gonads. Thus, we advocate for a more comprehensive inquiry into medical history and a systematic examination. The 18F-FDG PET/CT examination not only visually delineates the lesion's location and extent but also serves as a cornerstone for clinical tumor staging, providing valuable support for treatment monitoring and subsequent follow-up.

Large-scale screening of clinical assessments to distinguish between states in the Integrated HD Progression Model (IHDPM).

Background: Understanding the sensitivity and utility of clinical assessments across different HD stages is important for study/trial endpoint selection and clinical assessment development. The Integrated HD Progression Model (IHDPM) characterizes the complex symptom progression of HD and separates the disease into nine ordered disease states. Objective: To generate a temporal map of discriminatory clinical measures across the IHDPM states. Methods: We applied the IHDPM to all HD individuals in an integrated longitudinal HD dataset derived from four observational studies, obtaining disease state assignment for each study visit. Using large-scale screening, we estimated Cohen's effect sizes to rank the discriminative power of 2,472 clinical measures for separating observations in disease state pairs. Individual trajectories through IHDPM states were examined. Discriminative analyses were limited to individuals with observations in both states of the pairs compared (N = 3,790). Results: Discriminative clinical measures were heterogeneous across the HD life course. UHDRS items were frequently identified as the best state pair discriminators, with UHDRS Motor items - most notably TMS - showing the highest discriminatory power between the early-disease states and early post-transition period states. UHDRS functional items emerged as strong discriminators from the transition period and on. Cognitive assessments showed good discriminative power between all state pairs examined, excepting state 1 vs. 2. Several non-UHDRS assessments were also flagged as excellent state discriminators for specific disease phases (e.g., SF-12). For certain state pairs, single assessment items other than total/summary scores were highlighted as having excellent discriminative power. Conclusion: By providing ranked quantitative scores indicating discriminatory ability of thousands of clinical measures between specific pairs of IHDPM states, our results will aid clinical trial designers select the most effective outcome measures tailored to their study cohort. Our observations may also assist in the development of end points targeting specific phases in the disease life course, through providing specific conceptual foci.

Using an artificial intelligence model to detect and localize visible clinically significant prostate cancer in prostate magnetic resonance imaging: a multicenter external validation study.

Background: An increasing number of patients with suspected clinically significant prostate cancer (csPCa) are undergoing prostate multiparametric magnetic resonance imaging (mpMRI). The role of artificial intelligence (AI) algorithms in interpreting prostate mpMRI needs to be tested with multicenter external data. This study aimed to investigate the diagnostic efficacy of an AI model in detecting and localizing visible csPCa on mpMRI a multicenter external data set. Methods: The data of 2,105 patients suspected of having prostate cancer from four hospitals were retrospectively collected to develop an AI model to detect and localize suspicious csPCa. The lesions were annotated based on pathology records by two radiologists. Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values were used as the input for the three-dimensional U-Net framework. Subsequently, the model was validated using an external data set comprising the data of 557 patients from three hospitals. Sensitivity, specificity, and accuracy were employed to evaluate the diagnostic efficacy of the model. Results: At the lesion level, the model had a sensitivity of 0.654. At the overall sextant level, the model had a sensitivity, specificity, and accuracy of 0.846, 0.884, and 0.874, respectively. At the patient level, the model had a sensitivity, specificity, and accuracy of 0.943, 0.776, and 0.849, respectively. The AI-predicted accuracy for the csPCa patients (231/245, 0.943) was significantly higher than that for the non-csPCa patients (242/312, 0.776) (P<0.001). The lesion number and tumor volume were greater in the correctly diagnosed patients than the incorrectly diagnosed patients (both P<0.001). Among the positive patients, those with lower average ADC values had a higher rate of correct diagnosis than those with higher average ADC values (P=0.01). Conclusions: The AI model exhibited acceptable accuracy in detecting and localizing visible csPCa at the patient and sextant levels. However, further improvements need to be made to enhance the sensitivity of the model at the lesion level.