Graphene-analogues boron nitride nanosheets confining ionic liquids: a high-performance quasi-liquid solid electrolyte

Solid electrolytes are one of the most promising electrolyte systems for safe lithium batteries, but the low ionic conductivity of these electrolytes seriously hinders the development of efficient lithium batteries. Here, a novel class of graphene-analogues boron nitride (g-BN) nanosheets confining an ultrahigh concentration of ionic liquids (ILs) in an interlayer and out-of-layer chamber to give rise to a quasi-liquid solid electrolyte (QLSE) is reported. The electron-insulated g-BN nanosheet host with a large specific surface area can confine ILs as much as 10 times of the host's weight to afford high ionic conductivity (3.85 × 10−3 S cm−1 at 25 °C, even 2.32 × 10−4 S cm−1 at −20 °C), which is close to that of the corresponding bulk IL electrolytes. The high ionic conductivity of QLSE is attributed to the enormous absorption for ILs and the confining effect of g-BN to form the ordered lithium ion transport channels in an interlayer and out-of-layer of g-BN. Furthermore, the electrolyte displays outstanding electrochemical properties and battery performance. In principle, this work enables a wider tunability, further opening up a new field for the fabrication of the next-generation QLSE based on layered nanomaterials in energy conversion devices

Related-Tweakey Impossible Differential Attack on Reduced-Round SKINNY-AEAD M1/M3

SKINNY-AEAD is one of the second-round candidates of the Lightweight Cryptography Standardization project held by NIST. SKINNY-AEAD M1 is the primary member of six SKINNY-AEAD schemes, while SKINNY-AEAD M3 is another member with a small tag. In the design document, only security analyses of their underlying primitive SKINNY-128-384 are provided. Besides, there are no valid third-party analyses on SKINNY-AEAD M1/M3 according to our knowledge. Therefore, this paper focuses on constructing the first third-party security analyses on them under a nonce-respecting scenario. By taking the encryption mode of SKINNY-AEAD into consideration and exploiting several properties of SKINNY, we can deduce some necessary constraints on the input and tweakey differences of related-tweakey impossible differential distinguishers. Under these constraints, we can find distinguishers suitable for mounting powerful tweakey recovery attacks. With the help of the automatic searching algorithms based on STP, we find some 14-round distinguishers. Based on one of these distinguishers, we mount a 20-round and an 18-round tweakey recovery attack on SKINNY-AEAD M1/M3. To the best of our knowledge, all these attacks are the best ones so far

Downregulation of TLX induces TET3 expression and inhibits glioblastoma stem cell self-renewal and tumorigenesis

International audienceGlioblastomas have been proposed to be maintained by highly tumorigenic glioblastoma stem cells (GSCs) that are resistant to current therapy. Therefore, targeting GSCs is critical for developing effective therapies for glioblastoma. In this study, we identify the regulatory cascade of the nuclear receptor TLX and the DNA hydroxylase Ten eleven translocation 3 (TET3) as a target for human GSCs. We show that knockdown of TLX expression inhibits human GSC tumorigenicity in mice. Treatment of human GSC-grafted mice with viral vector-delivered TLX shRNA or nanovector-delivered TLX siRNA inhibits tumour development and prolongs survival. Moreover, we identify TET3 as a potent tumour suppressor downstream of TLX to regulate the growth and self-renewal in GSCs. This study identifies the TLX-TET3 axis as a potential therapeutic target for glioblastoma

Rare deleterious germline variants and risk of lung cancer

Recent studies suggest that rare variants exhibit stronger effect sizes and might play a crucial role in the etiology of lung cancers (LC). Whole exome plus targeted sequencing of germline DNA was performed on 1045 LC cases and 885 controls in the discovery set. To unveil the inherited causal variants, we focused on rare and predicted deleterious variants and small indels enriched in cases or controls. Promising candidates were further validated in a series of 26,803 LCs and 555,107 controls. During discovery, we identified 25 rare deleterious variants associated with LC susceptibility, including 13 reported in ClinVar. Of the five validated candidates, we discovered two pathogenic variants in known LC susceptibility loci, ATM p.V2716A (Odds Ratio [OR] 19.55, 95%CI 5.04–75.6) and MPZL2 p.I24M frameshift deletion (OR 3.88, 95%CI 1.71–8.8); and three in novel LC susceptibility genes, POMC c.*28delT at 3′ UTR (OR 4.33, 95%CI 2.03–9.24), STAU2 p.N364M frameshift deletion (OR 4.48, 95%CI 1.73–11.55), and MLNR p.Q334V frameshift deletion (OR 2.69, 95%CI 1.33–5.43). The potential cancer-promoting role of selected candidate genes and variants was further supported by endogenous DNA damage assays. Our analyses led to the identification of new rare deleterious variants with LC susceptibility. However, in-depth mechanistic studies are still needed to evaluate the pathogenic effects of these specific alleles

Germline Polymorphisms in MGMT Associated With Temozolomide-Related Myelotoxicity Risk in Patients With Glioblastoma Treated on NRG Oncology/RTOG 0825

Background: We sought to identify clinical and genetic predictors of temozolomide-related myelotoxicity among patients receiving therapy for glioblastoma. Methods: Patients (n = 591) receiving therapy on NRG Oncology/RTOG 0825 were included in the analysis. Cases were patients with severe myelotoxicity (grade 3 and higher leukopenia, neutropenia, and/or thrombocytopenia); controls were patients without such toxicity. A risk-prediction model was built and cross-validated by logistic regression using only clinical variables and extended using polymorphisms associated with myelotoxicity. Results: 23% of patients developed myelotoxicity (n = 134). This toxicity was first reported during the concurrent phase of therapy for 56 patients; 30 stopped treatment due to toxicity. Among those who continued therapy (n = 26), 11 experienced myelotoxicity again. The final multivariable clinical factor model included treatment arm, gender, and anticonvulsant status and had low prediction accuracy (area under the curve [AUC] = 0.672). The final extended risk prediction model including four polymorphisms in MGMT had better prediction (AUC = 0.827). Receiving combination chemotherapy (OR, 1.82; 95% CI, 1.02-3.27) and being female (OR, 4.45; 95% CI, 2.45-8.08) significantly increased myelotoxicity risk. For each additional minor allele in the polymorphisms, the risk increased by 64% (OR, 1.64; 95% CI, 1.43-1.89). Conclusions: Myelotoxicity during concurrent chemoradiation with temozolomide is an uncommon but serious event, often leading to treatment cessation. Successful prediction of toxicity may lead to more cost-effective individualized monitoring of at-risk subjects. The addition of genetic factors greatly enhanced our ability to predict toxicity among a group of similarly treated glioblastoma patients

Aggregation-Induced Emission (AIE), Life and Health

Light has profoundly impacted modern medicine and healthcare, with numerous luminescent agents and imaging techniques currently being used to assess health and treat diseases. As an emerging concept in luminescence, aggregation-induced emission (AIE) has shown great potential in biological applications due to its advantages in terms of brightness, biocompatibility, photostability, and positive correlation with concentration. This review provides a comprehensive summary of AIE luminogens applied in imaging of biological structure and dynamic physiological processes, disease diagnosis and treatment, and detection and monitoring of specific analytes, followed by representative works. Discussions on critical issues and perspectives on future directions are also included. This review aims to stimulate the interest of researchers from different fields, including chemistry, biology, materials science, medicine, etc., thus promoting the development of AIE in the fields of life and health

Lung cancer in ever- and never-smokers: findings from multi-population GWAS studies.

BackgroundClinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer.MethodsWe conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including eQTL colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer.ResultsFive novel independent loci, GABRA4, inter-genic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P 20). Different risk patterns were observed for the variants among the different groups by smoking behavior.ConclusionsWe identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies.ImpactOur study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiological insights into the complicated genetic architecture of this deadly cancer