eccDNA Atlas: a comprehensive resource of eccDNA catalog.

Extrachromosomal circular DNA (eccDNA) represents a large category of non-mitochondrial and non-plasmid circular extrachromosomal DNA, playing an indispensable role in various aspects such as tumorigenesis, immune responses. However, the information of characteristics and functions about eccDNA is fragmented, hiding behind abundant literatures and massive whole-genome sequencing (WGS) data, which has not been sufficiently used for the identification of eccDNAs. Therefore, establishing an integrated repository portal is essential for identifying and analyzing eccDNAs. Here, we developed eccDNA Atlas (http://lcbb.swjtu.edu.cn/eccDNAatlas), a user-friendly database of eccDNAs that aims to provide a high-quality and integrated resource for browsing, searching and analyzing eccDNAs from multiple species. eccDNA Atlas currently contains 629 987 eccDNAs and 8221 ecDNAs manually curated from literatures and 1105 ecDNAs predicted by AmpliconArchitect based on WGS data involved in 66 diseases, 57 tissues and 319 cell lines. The content of each eccDNA entry includes multiple aspects such as sequence, disease, function, characteristic, validation strategies. Furthermore, abundant annotations and analyzing utilities were provided to explore existing eccDNAs in eccDNA Atlas or user-defined eccDNAs including oncogenes, typical enhancers, super enhancers, CTCF-binding sites, SNPs, chromatin accessibility, eQTLs, gene expression, survival and genome visualization. Overall, eccDNA Atlas provides an integrated eccDNA data warehouse and serves as an important tool for future research.

Novel TFG mutation causes autosomal-dominant spastic paraplegia and defects in autophagy.

BACKGROUND: Mutations in the tropomyosin receptor kinase fused (TFG) gene are associated with various neurological disorders, including autosomal recessive hereditary spastic paraplegia (HSP), autosomal dominant hereditary motor and sensory neuropathy with proximal dominant involvement (HMSN-P) and autosomal dominant type of Charcot-Marie-Tooth disease type 2. METHODS: Whole genome sequencing and whole-exome sequencing were used, followed by Sanger sequencing for validation. Haplotype analysis was performed to confirm the inheritance mode of the novel TFG mutation in a large Chinese family with HSP. Additionally, another family diagnosed with HMSN-P and carrying the reported TFG mutation was studied. Clinical data and muscle pathology comparisons were drawn between patients with HSP and patients with HMSN-P. Furthermore, functional studies using skin fibroblasts derived from patients with HSP and patients with HMSN-P were conducted to investigate the pathomechanisms of TFG mutations. RESULTS: A novel heterozygous TFG variant (NM_006070.6: c.125G>A (p.R42Q)) was identified and caused pure HSP. We further confirmed that the well-documented recessively inherited spastic paraplegia, caused by homozygous TFG mutations, exists in a dominantly inherited form. Although the clinical features and muscle pathology between patients with HSP and patients with HMSN-P were distinct, skin fibroblasts derived from both patient groups exhibited reduced levels of autophagy-related proteins and the presence of TFG-positive puncta. CONCLUSIONS: Our findings suggest that autophagy impairment may serve as a common pathomechanism among different clinical phenotypes caused by TFG mutations. Consequently, targeting autophagy may facilitate the development of a uniform treatment for TFG-related neurological disorders.

Y-Shaped Backbone-Rigidified DNA Tiles for the Construction of Supersized Nondeformable Tetrahedrons for Precise Cancer Therapies.

While engineered DNA nanoframeworks have been extensively exploited for delivery of diagnostic and therapeutic regents, DNA tiling-based DNA frameworks amenable to applications in living systems lag much behind. In this contribution, by developing a Y-shaped backbone-based DNA tiling technique, we assemble Y-shaped backbone-rigidified supersized DNA tetrahedrons (RDT) with 100% efficiency for precisely targeted tumor therapy. RDT displays unparalleled rigidness and unmatched resistance to nuclease degradation so that it almost does not deform under the force exerted by the atomic force microscopy tip, and the residual amount is not less than 90% upon incubating in biological media for 24 h, displaying at least 11.6 times enhanced degradation resistance. Without any targeting ligand, RDT enters the cancer cell in a targeted manner, and internalization specificity is up to 15.8. Moreover, 77% of RDT objects remain intact within living cells for 14 h. The drug loading content of RDT is improved by 4-8 times, and RDT almost 100% eliminates the unintended drug leakage in a stimulated physiological medium. Once systemically administrated into HeLa tumor-bearing mouse models, doxorubicin-loaded RDTs preferentially accumulate in tumor sites and efficiently suppress tumor growth without detectable off-target toxicity. The Y-DNA tiling technique offers invaluable insights into the development of structural DNA nanotechnology for precise medicine.

Coregulation of Li/Li+ Spatial Distribution by Electric Field Gradient with Homogenized Li-Ion Flux for Dendrite-Free Li Metal Anodes.

Lithium (Li) metal batteries are highly sought after for their exceptional energy density. However, their practical implementation is impeded by the formation of dendrites and significant volume fluctuations in Li, which stem from the uneven distribution of Li-ions and uncontrolled deposition of Li on the current collector. Here, an amino-functionalized reduced graphene oxide covered with polyacrylonitrile (PrGN) film with an electric field gradient structure is prepared to deal with such difficulties. This novel current collector serves to stabilize Li-metal anodes by regulating Li-ion flux through vertically aligned channels formed by porous polyacrylonitrile (PAN). Moreover, the amino-functionalized reduced graphene oxide (rGN) acts as a three-dimensional (3D) host, reducing nucleation overpotential and accommodating volume expansion during cycling. The combination of the insulating PAN and conducting rGN creates an electric field gradient that promotes a bottom-up mode of Li electrodeposition and safeguards the anode from interfacial parasitic reactions. Consequently, the electrodes exhibit exceptional cycle life with stable voltage profiles and minimal hysteresis under high current densities and large areal capacities.

APC/C-regulated CPT1C promotes tumor progression by upregulating the energy supply and accelerating the G1/S transition.

BACKGROUND: In addition to functioning as a precise monitoring mechanism in cell cycle, the anaphase-promoting complex/cyclosome (APC/C) is reported to be involved in regulating multiple metabolic processes by facilitating the ubiquitin-mediated degradation of key enzymes. Fatty acid oxidation is a metabolic pathway utilized by tumor cells that is crucial for malignant progression; however, its association with APC/C remains to be explored. METHODS: Cell cycle synchronization, immunoblotting, and propidium iodide staining were performed to investigate the carnitine palmitoyltransferase 1 C (CPT1C) expression manner. Proximity ligation assay and co-immunoprecipitation were performed to detect interactions between CPT1C and APC/C. Flow cytometry, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2 H-tetrazolium, inner salt (MTS) assays, cell-scratch assays, and transwell assays and xenograft transplantation assays were performed to investigate the role of CPT1C in tumor progression in vitro and in vivo. Immunohistochemistry was performed on tumor tissue microarray to evaluate the expression levels of CPT1C and explore its potential clinical value. RESULTS: We identified CPT1C as a novel APC/C substrate. CPT1C protein levels exhibited cell cycle-dependent fluctuations, peaking at the G1/S boundary. Elevated CPT1C accelerated the G1/S transition, facilitating tumor cell proliferation in vitro and in vivo. Furthermore, CPT1C enhanced fatty acid utilization, upregulated ATP levels, and decreased reactive oxygen species levels, thereby favoring cell survival in a harsh metabolic environment. Clinically, high CPT1C expression correlated with poor survival in patients with esophageal squamous cell carcinoma. CONCLUSIONS: Overall, our results revealed a novel interplay between fatty acid utilization and cell cycle machinery in tumor cells. Additionally, CPT1C promoted tumor cell proliferation and survival by augmenting cellular ATP levels and preserving redox homeostasis, particularly under metabolic stress. Therefore, CPT1C could be an independent prognostic indicator in esophageal squamous cell carcinoma.

Adversarial Robustness Enhancement for Deep Learning-Based Soft Sensors: An Adversarial Training Strategy Using Historical Gradients and Domain Adaptation.

Despite their high prediction accuracy, deep learning-based soft sensor (DLSS) models face challenges related to adversarial robustness against malicious adversarial attacks, which hinder their widespread deployment and safe application. Although adversarial training is the primary method for enhancing adversarial robustness, existing adversarial-training-based defense methods often struggle with accurately estimating transfer gradients and avoiding adversarial robust overfitting. To address these issues, we propose a novel adversarial training approach, namely domain-adaptive adversarial training (DAAT). DAAT comprises two stages: historical gradient-based adversarial attack (HGAA) and domain-adaptive training. In the first stage, HGAA incorporates historical gradient information into the iterative process of generating adversarial samples. It considers gradient similarity between iterative steps to stabilize the updating direction, resulting in improved transfer gradient estimation and stronger adversarial samples. In the second stage, a soft sensor domain-adaptive training model is developed to learn common features from adversarial and original samples through domain-adaptive training, thereby avoiding excessive leaning toward either side and enhancing the adversarial robustness of DLSS without robust overfitting. To demonstrate the effectiveness of DAAT, a DLSS model for crystal quality variables in silicon single-crystal growth manufacturing processes is used as a case study. Through DAAT, the DLSS achieves a balance between defense against adversarial samples and prediction accuracy on normal samples to some extent, offering an effective approach for enhancing the adversarial robustness of DLSS.

Pseudopyrolysis of Metal-Organic Frameworks: A Synchronous Nucleation Mechanism to Synthesize Ultrafine Metal Compound Nanoparticles.

Metal-Organic frameworks (MOFs) are increasingly being investigated for the synthesis of carbon-supported metal-based ultrafine nanoparticles (UNPs). However, the collapse of the carbon framework and aggregation of metal particles in the pyrolysis process have severely hindered their stability and applications. Here, we report the synchronous nucleation pseudopyrolysis of MOFs to confine Fe/FeOx UNPs in intact porous carbon nanorods (IPCNs), revealed by in situ transmission electron microscopy experiments and ex situ structure analysis. The pseudopyrolysis mechanism enables strong physical and chemical confinement effects between UNPs and carbon by moderate thermal kinetics and abundant oxygen defects. Further, this strong confinement is greatly beneficial for subsequent chemical transformations to obtain different Fe-based UNPs and excellent electrochemical performance. As a proof of concept, the as-prepared FeSe UNPs in IPCNs show superior lithium storage performance with an ultrahigh and stable capacity of 815.1 mAh g-1 at 0.1 A g -1 and 379.7 mAh g-1 at 5 A g-1 for 1000 cycles.

Invasibility framework to predict the early colonization of alien Sonneratia in mangrove: Implications for coastal area management.

Invasibility, or an ecosystem's susceptibility to invasion, plays a critical role in managing biological invasions but is challenging to quantify due to its dependence on specific ecosystem variables. This limitation restricts the practical application of this concept in the control of alien species. This study aims to simplify invasibility into measurable components and develop an applicable framework to predict early colonization of alien plants within the coastal mangrove ecosystem. We used the unchanneled path length (UPL), a widely applied hydrological connectivity-related indicator, to assess the accessibility of the mangrove. The enhanced vegetation index (EVI), positively correlated with above-ground biomass, was used to evaluate the potential competitive intensity. Firstly, building on existing studies, we developed a four-quadrant concept model integrating the effects of EVI and UPL on the early colonization of the alien species Sonneratia apetala. Our results revealed significant differences in EVI and UPL values between colonized and uncolonized areas, with colonized regions displaying markedly lower values (P < 0.001). Additionally, logistic regression showed a significant negative association between the probability of successful colonization by S. apetala and both indicators (P < 0.001). These results validate the effectiveness of our conceptual model. Furtherly, we identified four key niche opportunities for exotic species in mangrove: mudflats outside the mangrove forest, tidal creeks, canopy gaps, and unmanaged abandoned aquaculture ponds. Overall, this study provides important insight into the ecological processes of alien S. apetala colonization and practical information for management of coastal areas susceptible to invasion. Additionally, it presents a case study on the practical application of the concept of invasibility in the management of alien species.

Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019.

Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01-2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30-0.60) and 0.46 (95%CI: 0.38-0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.

Metal-Free Catalytic Formation of a Donor-Acceptor-Donor Molecule and Its Lewis Acid-Adduct Singlet Diradical with High-Efficient NIR-II Photothermal Conversion.

We have synthesized a quinone-incorporated bistriarylamine donor-acceptor-donor (D-A-D) semiconductor 1 by B(C6F5)3 (BCF) catalyzed C-H/C-H cross coupling via radical ion pair intermediates. Coordination of Lewis acids BCF and Al(ORF)3 (RF=C(CF3)3) to the semiconductor 1 afforded diradical zwitterions 2 and 3 by integer electron transfer. Upon binding to Lewis acids, the LUMO energy of 1 is significantly lowered and the band gap of the semiconductor is significantly narrowed from 1.93 eV (1) to 1.01 eV (2) and 1.06 eV (3). 2 and 3 are rare near-infrared (NIR) diradical dyes with broad absorption both centered around 1500 nm. By introducing a photo BCF generator, 2 can be generated by light-dependent control. Furthermore, the integer electron transfer process can also be reversibly regulated via the addition of CH3CN. In addition, the temperature of 2 sharply increased and reached as high as 110 °C in 10 s upon the irradiation of near-infrared-II (NIR-II) laser (1064 nm, 0.7 W cm-2), exhibiting a fast response to laser. It displays excellent photothermal stability with a photothermal (PT) conversion efficiency of 62.26 % and high-quality PT imaging.

3D-Printed Micro/Nano-Scaled Mechanical Metamaterials: Fundamentals, Technologies, Progress, Applications, and Challenges.

Micro/nano-scaled mechanical metamaterials have attracted extensive attention in various fields attributed to their superior properties benefiting from their rationally designed micro/nano-structures. As one of the most advanced technologies in the 21st century, additive manufacturing (3D printing) opens an easier and faster path for fabricating micro/nano-scaled mechanical metamaterials with complex structures. Here, the size effect of metamaterials at micro/nano scales is introduced first. Then, the additive manufacturing technologies to fabricate mechanical metamaterials at micro/nano scales are introduced. The latest research progress on micro/nano-scaled mechanical metamaterials is also reviewed according to the type of materials. In addition, the structural and functional applications of micro/nano-scaled mechanical metamaterials are further summarized. Finally, the challenges, including advanced 3D printing technologies, novel material development, and innovative structural design, for micro/nano-scaled mechanical metamaterials are discussed, and future perspectives are provided. The review aims to provide insight into the research and development of 3D-printed micro/nano-scaled mechanical metamaterials.

A Caenorhabditis elegans model of adenylosuccinate lyase deficiency reveals neuromuscular and reproductive phenotypes of distinct etiology.

Inborn errors of purine metabolism are rare syndromes with an array of complex phenotypes in humans. One such disorder, adenylosuccinate lyase deficiency (ASLD), is caused by a decrease in the activity of the bi-functional purine biosynthetic enzyme adenylosuccinate lyase (ADSL). Mutations in human ADSL cause epilepsy, muscle ataxia, and autistic-like symptoms. Although the genetic basis of ASLD is known, the molecular mechanisms driving phenotypic outcome are not. Here, we characterize neuromuscular and reproductive phenotypes associated with a deficiency of adsl-1 in Caenorhabditis elegans. We demonstrate that adsl-1 function contributes to regulation of spontaneous locomotion, that adsl-1 functions acutely for proper mobility, and that aspects of adsl-1-related dysfunction are reversible. Using pharmacological supplementation, we correlate phenotypes with distinct metabolic perturbations. The neuromuscular defect correlates with accumulation of a purine biosynthetic intermediate whereas reproductive deficiencies can be ameliorated by purine supplementation, indicating differing molecular mechanisms behind the phenotypes. Because purine metabolism is highly conserved in metazoans, we suggest that similar separable metabolic perturbations result in the varied symptoms in the human disorder and that a dual-approach therapeutic strategy may be beneficial.

Molecular mechanisms of glucocorticoid resistance.

BACKGROUND: As a powerful anti-inflammatory, immunosuppressive, and antiproliferative drug, glucocorticoid (GC) plays an important role in the treatment of various diseases. However, some patients may experience glucocorticoid resistance (GCR) in clinical, and its molecular mechanism have not been determined. METHODS: The authors performed a review of the literature on GCR focusing on mutations in the NR3C1 gene and impaired glucocorticoid receptor (GR) signalling, using METSTR (2000 through May 2022) to identify original articles and reviews on this topic. The search terms included 'glucocorticoid resistance/insensitive', 'steroid resistance/insensitive', 'NR3C1', and 'glucocorticoid receptor'. RESULTS: Primary GCR is mainly caused by NR3C1 gene mutation, and 31 NR3C1 gene mutations have been reported so far. Secondary GCR is caused by impaired GC signalling pathways, including decreased expression of GR, impaired nuclear translocation of GR, and impaired binding of GR to GC and GR to target genes. However, the current research is more on the expression level of GR, and there are relatively few studies on other mechanisms. In addition, methods for improving GC sensitivity are rarely reported. CONCLUSION: The molecular mechanisms of GCR are complex and may differ in different diseases or different patients. In future studies, when exploring the mechanism of GCR, methods to improve GC sensitivity should also be investigated.

Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomas.

OBJECTIVES: To investigate whether radiomic features extracted from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) can improve the prediction of the molecular subtypes of adult diffuse gliomas, and to further develop and validate a multimodal radiomic model by integrating radiomic features from conventional and perfusion MRI. METHODS: We extracted 1197 radiomic features from each sequence of conventional MRI and DSC-PWI, respectively. The Boruta algorithm was used for feature selection and combination, and a three-class random forest method was applied to construct the models. We also constructed a combined model by integrating radiomic features and clinical metrics. The models' diagnostic performance for discriminating the molecular subtypes (IDH wild type [IDHwt], IDH mutant and 1p/19q-noncodeleted [IDHmut-noncodel], and IDH mutant and 1p/19q-codeleted [IDHmut-codel]) was compared using AUCs in the validation set. RESULTS: We included 272 patients (training set, n = 166; validation set, n = 106) with grade II-IV gliomas (mean age, 48.7 years; range, 19-77 years). The proportions of the molecular subtypes were 66.2% IDHwt, 15.1% IDHmut-noncodel, and 18.8% IDHmut-codel. Nineteen radiomic features (13 from conventional MRI and 6 from DSC-PWI) were selected to build the multimodal radiomic model. In the validation set, the multimodal radiomic model showed better performance than the conventional radiomic model did in predicting the IDHwt and IDHmut-codel subtypes, which was comparable to the conventional radiomic model in predicting the IDHmut-noncodel subtype. The multimodal radiomic model yielded similar performance as the combined model in predicting the three molecular subtypes. CONCLUSIONS: Adding DSC-PWI to conventional MRI can improve molecular subtype prediction in patients with diffuse gliomas. KEY POINTS: • The multimodal radiomic model outperformed conventional MRI when predicting both the IDH wild type and IDH mutant and 1p/19q-codeleted subtypes of gliomas. • The multimodal radiomic model showed comparable performance to the combined model in the prediction of the three molecular subtypes. • Radiomic features from T1-weighted gadolinium contrast-enhanced and relative cerebral blood volume images played an important role in the prediction of molecular subtypes.

Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center study.

OBJECTIVES: To develop and validate a deep learning imaging signature (DLIS) for risk stratification in patients with multiforme (GBM), and to investigate the biological pathways and genetic alterations underlying the DLIS. METHODS: The DLIS was developed from multi-parametric MRI based on a training set (n = 600) and validated on an internal validation set (n = 164), an external test set 1 (n = 100), an external test set 2 (n = 161), and a public TCIA set (n = 88). A co-profiling framework based on a radiogenomics analysis dataset (n = 127) using multiscale high-dimensional data, including imaging, transcriptome, and genome, was established to uncover the biological pathways and genetic alterations underpinning the DLIS. RESULTS: The DLIS was associated with survival (log-rank p < 0.001) and was an independent predictor (p < 0.001). The integrated nomogram incorporating the DLIS achieved improved C indices than the clinicomolecular nomogram (net reclassification improvement 0.39, p < 0.001). DLIS significantly correlated with core pathways of GBM (apoptosis and cell cycle-related P53 and RB pathways, and cell proliferation-related RTK pathway), as well as key genetic alterations (del_CDNK2A). The prognostic value of DLIS-correlated genes was externally confirmed on TCGA/CGGA sets (p < 0.01). CONCLUSIONS: Our study offers a biologically interpretable deep learning predictor of survival outcomes in patients with GBM, which is crucial for better understanding GBM patient's prognosis and guiding individualized treatment. KEY POINTS: • MRI-based deep learning imaging signature (DLIS) stratifies GBM into risk groups with distinct molecular characteristics. • DLIS is associated with P53, RB, and RTK pathways and del_CDNK2A mutation. • The prognostic value of DLIS-correlated pathway genes is externally demonstrated.

Method for trace determination of N-nitrosamines impurities in metronidazole benzoate using high-performance liquid chromatography coupled with atmospheric-pressure chemical ionization tandem mass spectrometry.

Genotoxic impurity control has been a great concern in the pharmaceutical industry since the recall of the large round of sartans worldwide in 2018. In these sartans, N-nitrosamines were the main contaminants in active pharmaceutical ingredients and formulations. Numerous analytical methods have been developed to detect N-nitrosamines in food, drugs, and environmental samples. In this study, a sensitive method is developed for the trace determination of N-nitrosamine impurities in metronidazole benzoate pharmaceuticals using high-performance liquid chromatography/atmospheric-pressure chemical ionization tandem mass spectrometry in the multiple reaction monitoring mode. The method was validated regarding system suitability, selectivity, linearity, accuracy, precision, sensitivity, solution stability, and robustness. The method showed good linearity with R2 ≥ 0.999 and FMandel  < Ftab(95%) ranging from 0.33 to 8.00 ng/ml. The low limits of detection of N-nitrosamines were in the range of 0.22-0.80 ng/ml (0.0014-0.0050 ppm). The low limits of quantification were in the range of 0.33-1.20 ng/ml (0.0021-0.0075 ppm), which were lower than the acceptable limits in metronidazole benzoate pharmaceuticals and indicated the high sensitivity of the method. The recoveries of N-nitrosamines ranged from 84% to 97%. Thus, this method exhibits good selectivity, sensitivity, and accuracy. Moreover, it is a simple, convenient, and scientific strategy for detecting N-nitrosamine impurities in pharmaceuticals to support the development of the pharmaceutical industry.

A Triply Negatively Charged Nanographene Bilayer with Spin Frustration.

We report on the largest open-shell graphenic bilayer and also the first example of triply negatively charged radical π-dimer. Upon three-electron reduction, bilayer nanographene fragment molecule (C96 H24 Ar6 )2 (Ar=2,6-dimethylphenyl) (12 ) was transformed to a triply negatively charged species 12 3.- , which has been characterized by single-crystal X-ray diffraction, electron paramagnetic resonance (EPR) spectroscopy and magnetic properties on a superconducting quantum interference device (SQUID). 12 3.- features a 96-center-3-electron (96c/3e) pancake bond with a doublet ground state, which can be thermally excited to a quartet state. It consists of 34 π-fused rings with 96 conjugated sp2 carbon atoms. Spin frustration is observed with the frustration parameter f>31.8 at low temperatures in 12 3.- , which indicates graphene upon reduction doping may behave as a quantum spin liquid.

Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study.

Determination of 1p/19q co-deletion status is important for the classification, prognostication, and personalized therapy in diffuse lower-grade gliomas (LGG). We developed and validated a deep learning imaging signature (DLIS) from preoperative magnetic resonance imaging (MRI) for predicting the 1p/19q status in patients with LGG. The DLIS was constructed on a training dataset (n = 330) and validated on both an internal validation dataset (n = 123) and a public TCIA dataset (n = 102). The receiver operating characteristic (ROC) analysis and precision recall curves (PRC) were used to measure the classification performance. The area under ROC curves (AUC) of the DLIS was 0.999 for training dataset, 0.986 for validation dataset, and 0.983 for testing dataset. The F1-score of the prediction model was 0.992 for training dataset, 0.940 for validation dataset, and 0.925 for testing dataset. Our data suggests that DLIS could be used to predict the 1p/19q status from preoperative imaging in patients with LGG. The imaging-based deep learning has the potential to be a noninvasive tool predictive of molecular markers in adult diffuse gliomas.

Ultrasensitive Electrochemical Detection of cancer-Related Point Mutations Based on Surface-Initiated Three-Dimensionally Self-Assembled DNA Nanostructures from Only Two Palindromic Probes.

Sensitive and selective detection of proto-oncogenes, especially recognition of point mutation, is of great importance in cancer diagnosis. Here, a ligation-mediated technique is demonstrated for the construction of an intertwined three-dimensional DNA nanosheet (3D SDN) on an electrode surface from only two palindromic hairpin probes (HP1 and HP2), creating a powerful electrochemical biosensor (E-biosensor) for the detection of the p53 gene. First, a capturing probe (CP) is immobilized on an electrode surface via Au-S chemistry, forming an electrochemical sensing interface. In the presence of the target p53 (T), the triggering probe is covalently linked to CP by a ligase. Moreover, target hybridization/ligation/dehybridization process is repeated, amplifying the target hybridization event and increasing the content of surface-confined triggering fragments. As a result, HP1 is opened and in turn interacts with HP2, forming intertwined 3D SDN where HP1 and HP2 are alternately arranged in parallel. Common hybridization and interaction between palindromic fragments are responsible for the assembly in the horizontal and vertical directions, respectively. An electrochemical indicator, methylene blue (MB), can be inserted into 3D SDN, generating a strong electrochemical signal. Utilizing the 3D SDN-based E-biosensor, the target DNA is detected down to 3 fM with a linear response range from 10 fM to 10 nM. Single point mutations are reliably identified even in fetal bovine serum and cellular homogenate. Because of the several advantages of simple design, good universality, inexpensive instrumentation, high assay specificity, and sensitivity, the 3D SDN-based E-biosensor is expected to provide a potential platform for screening point mutation required by early clinical diagnostics and medical research.

Role of exogenous abscisic acid in freezing tolerance of mangrove Kandelia obovata under natural frost condition at near 32°N.

BACKGROUND: Mangroves possess substantial ecological, social, and economic functions in tropical and subtropical coastal wetlands. Kandelia obovata is the most cold-resistance species among mangrove plants, with a widespread distribution in China that ranges from Sanya (18° 12' N) to Wenzhou (28° 20' N). Here, we explored the temporal variations in physiological status and transcriptome profiling of K. obovata under natural frost conditions at ~ 32oN, as well as the positive role of exogenous abscisic acid (ABA) in cold resistance. RESULTS: The soluble sugar (SS) and proline (Pro) functioned under freezing stress, of which SS was more important for K. obovata. Consistently, up-regulated DEGs responding to low temperature were significantly annotated to glycometabolism, such as starch and sucrose metabolism and amino sugar and nucleotide sugar metabolism. Notably, the top 2 pathways of KEGG enrichment were phenylpropanoid biosynthesis and flavonoid biosynthesis. For the antioxidant system, POD in conjunction with CAT removed hydrogen peroxide, and CAT appeared to be more important. The up-regulated DEGs responding to low temperature and ABA were also found to be enriched in arginine and proline metabolism, starch and sucrose metabolism, and peroxisome. Moreover, ABA triggered the expression of P5CS and P5CR, but inhibited the ProDH expression, which might contribute to Pro accumulation. Interestingly, there was no significant change in malondialdehyde (MDA) content during the cold event (P > 0.05), suggesting foliar application of ABA effectively alleviated the adverse effects of freezing stress on K. obovata by activating the antioxidant enzyme activity and increasing osmolytes accumulation, such as Pro, and the outcome was proportional to ABA concentration. CONCLUSIONS: This study deepened our understanding of the physiological characters and molecular mechanisms underlying the response of K. obovata to natural frost conditions and exogenous ABA at the field level, which could provide a sound theoretical foundation for expanding mangroves plantations in higher latitudes, as well as the development coastal landscape.