Inactive PARP1 causes embryonic lethality and genome instability in a dominant-negative manner.

PARP1 (poly-ADP ribose polymerase 1) is recruited and activated by DNA strand breaks, catalyzing the generation of poly-ADP-ribose (PAR) chains from NAD+. PAR relaxes chromatin and recruits other DNA repair factors, including XRCC1 and DNA Ligase 3, to maintain genomic stability. Here we show that, in contrast to the normal development of Parp1-null mice, heterozygous expression of catalytically inactive Parp1 (E988A, Parp1+/A) acts in a dominant-negative manner to disrupt murine embryogenesis. As such, all the surviving F1 Parp1+/A mice are chimeras with mixed Parp1+/AN (neoR retention) cells that act similarly to Parp1+/-. Pure F2 Parp1+/A embryos were found at Mendelian ratios at the E3.5 blastocyst stage but died before E9.5. Compared to Parp1-/- cells, genotype and expression-validated pure Parp1+/A cells retain significant ADP-ribosylation and PARylation activities but accumulate markedly higher levels of sister chromatid exchange and mitotic bridges. Despite proficiency for homologous recombination and nonhomologous end-joining measured by reporter assays and supported by normal lymphocyte and germ cell development, Parp1+/A cells are hypersensitive to base damages, radiation, and Topoisomerase I and II inhibition. The sensitivity of Parp1+/A cells to base damages and Topo inhibitors exceed Parp1-/- controls. The findings show that the enzymatically inactive PARP1 dominant negatively blocks DNA repair in selective pathways beyond wild-type PARP1 and establishes a crucial physiological difference between PARP1 inactivation vs. deletion. As a result, the expression of enzymatically inactive PARP1 from one allele is sufficient to abrogate murine embryonic development, providing a mechanism for the on-target side effect of PARP inhibitors used for cancer therapy.

Identifying the potential miRNA biomarkers based on multi-view networks and reinforcement learning for diseases.

MicroRNAs (miRNAs) play important roles in the occurrence and development of diseases. However, it is still challenging to identify the effective miRNA biomarkers for improving the disease diagnosis and prognosis. In this study, we proposed the miRNA data analysis method based on multi-view miRNA networks and reinforcement learning, miRMarker, to define the potential miRNA disease biomarkers. miRMarker constructs the cooperative regulation network and functional similarity network based on the expression data and known miRNA-disease relations, respectively. The cooperative regulation of miRNAs was evaluated by measuring the changes of relative expression. Natural language processing was introduced for calculating the miRNA functional similarity. Then, miRMarker integrates the multi-view miRNA networks and defines the informative miRNA modules through a reinforcement learning strategy. We compared miRMarker with eight efficient data analysis methods on nine transcriptomics datasets to show its superiority in disease sample discrimination. The comparison results suggested that miRMarker outperformed other data analysis methods in receiver operating characteristic analysis. Furthermore, the defined miRNA modules of miRMarker on colorectal cancer data not only show the excellent performance of cancer sample discrimination but also play significant roles in the cancer-related pathway disturbances. The experimental results indicate that miRMarker can build the robust miRNA interaction network by integrating the multi-view networks. Besides, exploring the miRNA interaction network using reinforcement learning favors defining the important miRNA modules. In summary, miRMarker can be a hopeful tool in biomarker identification for human diseases.

Early detection and stratification of colorectal cancer using plasma cell-free DNA fragmentomic profiling.

Timely accurate and cost-efficient detection of colorectal cancer (CRC) is of great clinical importance. This study aims to establish prediction models for detecting CRC using plasma cell-free DNA (cfDNA) fragmentomic features. Whole-genome sequencing (WGS) was performed on cfDNA from 620 participants, including healthy individuals, patients with benign colorectal diseases and CRC patients. Using WGS data, three machine learning methods were compared to build prediction models for the stratification of CRC patients. The optimal model to discriminate CRC patients of all stages from healthy individuals achieved a sensitivity of 92.31% and a specificity of 91.14%, while the model to separate early-stage CRC patients (stage 0-II) from healthy individuals achieved a sensitivity of 88.8% and a specificity of 96.2%. Additionally, the cfDNA fragmentation profiles reflected disease-specific genomic alterations in CRC. Overall, this study suggests that cfDNA fragmentation profiles may potentially become a noninvasive approach for the detection and stratification of CRC.

Epitaxial Growth of Two-Dimensional MoO2-MoSe2 Metal-Semiconductor Heterostructures for Schottky Diodes.

The metal-semiconductor interface fabricated by conventional methods often suffers from contamination, degrading transport performance. Herein, we propose a one-pot chemical vapor deposition (CVD) process to create a two-dimensional (2D) MoO2-MoSe2 heterostructure by growing MoO2 seeds under a hydrogen environment, followed by depositing MoSe2 on the surface and periphery. The ultraclean interface is verified by cross-sectional scanning transmission electron microscopy and photoluminescence. Along with the high work function of semimetallic MoO2 (Ef = -5.6 eV), a high-rectification Schottky diode is fabricated based on this heterostructure. Furthermore, the Schottky diode exhibits an excellent photovoltaic effect with a high open-circuit voltage of 0.26 eV and ultrafast photoresponse, owing to the naturally formed metal-semiconductor contact with suppressed pinning effect. Our method paves the way for the fabrication of an ultraclean 2D metal-semiconductor interface, without defects or contamination, offering promising prospects for future nanoelectronics.

Diagnostic Performance of Carotid Ring Sign on CT-Angiography in Internal Carotid True Occlusion.

BACKGROUND: To differentiate between pseudo occlusion (PO) and true occlusion (TO) of internal carotid artery (ICA) is important in thrombectomy treatment planning for patients with acute ischemic stroke. Although delayed contrast filling has been differentiated carotid PO from TO, its application has been limited by the implementations of multiphasic computed tomography angiography. In this study, we hypothesized that carotid ring sign, which is readily acquired from single-phasic CTA, can sufficiently differentiate carotid TO from PO. METHODS: One thousand four hundred and twenty patients with anterior circulation stroke receiving endovascular therapy were consecutively recruited through a hospital- and web-based registry. Two hundred patients with nonvisualization of the proximal ICA were included in the analysis after a retrospective screening. Diagnosis of PO or TO of the cervical segment of ICA was made based on digital subtraction angiography. Diagnostic performances of carotid ring sign on arterial-phasic CTA and delayed contrast filling on multiphasic computed tomography angiography were evaluated and compared. RESULTS: One-hundred twelve patients had ICA PO and 88 had TO. Carotid ring sign was more common in patients with TO (70.5% versus 6.3%; P<0.001), whereas delayed contrast filling was more common in PO (94.9% versus 7.7%; P<0.001). The sensitivity and specificity of carotid ring sign in diagnosing carotid TO were 0.70 and 0.94, respectively, whereas sensitivity and specificity of delayed contrast filling was 0.95 and 0.92 in judging carotid PO. CONCLUSIONS: Carotid ring sign is a potent imaging marker in diagnosing ICA TO. Carotid ring sign could be complementary to delayed contrast filling sign in differentiating TO from PO, in particular in centers with only single-phasic CTA.

Ultrasensitive and Highly Selective Detection of Staphylococcus aureus at the Single-Cell Level Using Bacteria-Imprinted Polymer and Vancomycin-Conjugated MnO2 Nanozyme.

Pathogenic bacterial infections, even at extremely low concentrations, pose significant threats to human health. However, the challenge persists in achieving high-sensitivity bacterial detection, particularly in complex samples. Herein, we present a novel sandwich-type electrochemical sensor utilizing bacteria-imprinted polymer (BIP) coupled with vancomycin-conjugated MnO2 nanozyme (Van@BSA-MnO2) for the ultrasensitive detection of pathogenic bacteria, exemplified by Staphylococcus aureus (S. aureus). The BIP, in situ prepared on the electrode surface, acts as a highly specific capture probe by replicating the surface features of S. aureus. Vancomycin (Van), known for its affinity to bacterial cell walls, is conjugated with a Bovine serum albumin (BSA)-templated MnO2 nanozyme through EDC/NHS chemistry. The resulting Van@BSA-MnO2 complex, serving as a detection probe, provides an efficient catalytic platform for signal amplification. Upon binding with the captured S. aureus, the Van@BSA-MnO2 complex catalyzes a substrate reaction, generating a current signal proportional to the target bacterial concentration. The sensor displays remarkable sensitivity, capable of detecting a single bacterial cell in a phosphate buffer solution. Even in complex milk matrices, it maintains outstanding performance, identifying S. aureus at concentrations as low as 10 CFU mL-1 without requiring intricate sample pretreatment. Moreover, the sensor demonstrates excellent selectivity, particularly in distinguishing target S. aureus from interfering bacteria of the same genus at concentrations 100-fold higher. This innovative method, employing entirely synthetic materials, provides a versatile and low-cost detection platform for Gram-positive bacteria. In comparison to existing nanozyme-based bacterial sensors with biological recognition materials, our assay offers distinct advantages, including enhanced sensitivity, ease of preparation, and cost-effectiveness, thereby holding significant promise for applications in food safety and environmental monitoring.

Low Temperature Synthesis of 2D p-Type α-In2Te3 with Fast and Broadband Photodetection.

2D A 2 III B 3 VI ${\mathrm{A}}_2^{{\mathrm{III}}}{\mathrm{B}}_3^{{\mathrm{VI}}}$ compounds (A = Al, Ga, In, and B = S, Se, and Te) with intrinsic structural defects offer significant opportunities for high-performance and functional devices. However, obtaining 2D atomic-thin nanoplates with non-layered structure on SiO2/Si substrate at low temperatures is rare, which hinders the study of their properties and applications at atomic-thin thickness limits. In this study, the synthesis of ultrathin, non-layered α-In2Te3 nanoplates is demonstrated using a BiOCl-assisted chemical vapor deposition method at a temperature below 350 °C on SiO2/Si substrate. Comprehensive characterization results confirm the high-quality single crystal is the low-temperature cubic phase α-In2Te3 , possessing a noncentrosymmetric defected ZnS structure with good second harmonic generation. Moreover, α-In2Te3 is revealed to be a p-type semiconductor with a direct and narrow bandgap value of 0.76 eV. The field effect transistor exhibits a high mobility of 18 cm2 V-1 s-1, and the photodetector demonstrates stable photoswitching behavior within a broadband photoresponse from 405 to 1064 nm, with a satisfactory response time of τrise = 1 ms. Notably, the α-In2Te3 nanoplates exhibit good stability against ambient environments. Together, these findings establish α-In2Te3 nanoplates as promising candidates for next-generation high-performance photonics and electronics.

Aberrant functional connectivity of the globus pallidus in the modulation of the relationship between childhood trauma and major depressive disorder.

BACKGROUND: Childhood trauma plays a crucial role in the dysfunctional reward circuitry in major depressive disorder (MDD). We sought to explore the effect of abnormalities in the globus pallidus (GP)-centric reward circuitry on the relationship between childhood trauma and MDD. METHODS: We conducted seed-based dynamic functional connectivity (dFC) analysis among people with or without MDD and with or without childhood trauma. We explored the relationship between abnormal reward circuitry, childhood trauma, and MDD. RESULTS: We included 48 people with MDD and childhood trauma, 30 people with MDD without childhood trauma, 57 controls with childhood trauma, and 46 controls without childhood trauma. We found that GP subregions exhibited abnormal dFC with several regions, including the inferior parietal lobe, thalamus, superior frontal gyrus (SFG), and precuneus. Abnormal dFC in these GP subregions showed a significant correlation with childhood trauma. Moderation analysis revealed that the dFC between the anterior GP and SFG, as well as between the anterior GP and the precentral gyrus, modulated the relationship between childhood abuse and MDD severity. We observed a negative correlation between childhood trauma and MDD severity among patients with lower dFC between the anterior GP and SFG, as well as higher dFC between the anterior GP and precentral gyrus. This suggests that reduced dFC between the anterior GP and SFG, along with increased dFC between the anterior GP and precentral gyrus, may attenuate the effect of childhood trauma on MDD severity. LIMITATIONS: Cross-sectional designs cannot be used to infer causality. CONCLUSION: Our findings underscore the pivotal role of reward circuitry abnormalities in MDD with childhood trauma. These abnormalities involve various brain regions, including the postcentral gyrus, precentral gyrus, inferior parietal lobe, precuneus, superior frontal gyrus, thalamus, and middle frontal gyrus. CLINICAL TRIAL REGISTRATION: ChiCTR2300078193.

Endosome mediated nucleocytoplasmic trafficking and endomembrane allocation is crucial to polyglutamine toxicity.

Aggregation of aberrant proteins is a common pathological hallmark in neurodegeneration such as polyglutamine (polyQ) and other repeat-expansion diseases. Here through overexpression of ataxin3 C-terminal polyQ expansion in Drosophila gut enterocytes, we generated an intestinal obstruction model of spinocerebellar ataxia type3 (SCA3) and reported a new role of nuclear-associated endosomes (NAEs)-the delivery of polyQ to the nucleoplasm. In this model, accompanied by the prominently increased RAB5-positive NAEs are abundant nucleoplasmic reticulum enriched with polyQ, abnormal nuclear envelope invagination, significantly reduced endoplasmic reticulum, indicating dysfunctional nucleocytoplasmic trafficking and impaired endomembrane organization. Consistently, Rab5 but not Rab7 RNAi further decreased polyQ-related NAEs, inhibited endomembrane disorganization, and alleviated disease model. Interestingly, autophagic proteins were enriched in polyQ-related NAEs and played non-canonical autophagic roles as genetic manipulation of autophagic molecules exhibited differential impacts on NAEs and SCA3 toxicity. Namely, the down-regulation of Atg1 or Atg12 mitigated while Atg5 RNAi aggravated the disease phenotypes both in Drosophila intestines and compound eyes. Our findings, therefore, provide new mechanistic insights and underscore the fundamental roles of endosome-centered nucleocytoplasmic trafficking and homeostatic endomembrane allocation in the pathogenesis of polyQ diseases.

PARP inhibitors trap PARP2 and alter the mode of recruitment of PARP2 at DNA damage sites.

Dual-inhibitors of PARP1 and PARP2 are promising anti-cancer drugs. In addition to blocking PARP1&2 enzymatic activity, PARP inhibitors also extend the lifetime of DNA damage-induced PARP1&2 foci, termed trapping. Trapping is important for the therapeutic effects of PARP inhibitors. Using live-cell imaging, we found that PARP inhibitors cause persistent PARP2 foci by switching the mode of PARP2 recruitment from a predominantly PARP1- and PAR-dependent rapid exchange to a WGR domain-mediated stalling of PARP2 on DNA. Specifically, PARP1-deletion markedly reduces but does not abolish PARP2 foci. The residual PARP2 foci in PARP1-deficient cells are DNA-dependent and abrogated by the R140A mutation in the WGR domain. Yet, PARP2-R140A forms normal foci in PARP1-proficient cells. In PARP1-deficient cells, PARP inhibitors - niraparib, talazoparib, and, to a lesser extent, olaparib - enhance PARP2 foci by preventing PARP2 exchange. This trapping of PARP2 is independent of auto-PARylation and is abolished by the R140A mutation in the WGR domain and the H415A mutation in the catalytic domain. Taken together, we found that PARP inhibitors trap PARP2 by physically stalling PARP2 on DNA via the WGR-DNA interaction while suppressing the PARP1- and PAR-dependent rapid exchange of PARP2.

Dual Synthetic Receptor-Based Sandwich Electrochemical Sensor for Highly Selective and Ultrasensitive Detection of Pathogenic Bacteria at the Single-Cell Level.

Sensitive and rapid detection of pathogenic bacteria is essential for effective source control and prevention of microbial infectious diseases. However, it remains a substantial challenge to rapidly detect bacteria at the single-cell level. Herein, we present an electrochemical sandwich sensor for highly selective and ultrasensitive detection of a single bacterial cell based on dual recognition by the bacteria-imprinted polymer film (BIF) and aptamer. The BIF was used as the capture probe, which was in situ fabricated on the electrode surface within 15 min via electropolymerization. The aptamer and electroactive 6-(Ferrocenyl)hexanethiol cofunctionalized gold nanoparticles (Au@Fc-Apt) were employed as the signal probe. Once the target bacteria were anchored on the BIF-modified electrode, the Au@Fc-Apt was further specifically bound to the bacteria, generating enhanced current signals for ultrasensitive detection of Staphylococcus aureus down to a single cell in phosphate buffer solution. Even in the complex milk samples, the sensor could detect as low as 10 CFU mL-1 of S. aureus without any complicated pretreatment except for 10-fold dilution. Moreover, the current response to the target bacteria was hardly affected by the coexisting multiple interfering bacteria, whose number is 30 times higher than the target, demonstrating the excellent selectivity of the sensor. Compared with most reported sandwich-type electrochemical sensors, this assay is more sensitive and more rapid, requiring less time (1.5 h) for the sensing interface construction. By virtue of its sensitivity, rapidity, selectivity, and cost-effectiveness, the sensor can serve as a universal detection platform for monitoring pathogenic bacteria in fields of food/public safety.

A Structure-Guided Molecular Network Strategy for Global Untargeted Metabolomics Data Annotation.

Large-scale metabolite annotation is a bottleneck in untargeted metabolomics. Here, we present a structure-guided molecular network strategy (SGMNS) for deep annotation of untargeted ultra-performance liquid chromatography-high resolution mass spectrometry (MS) metabolomics data. Different from the current network-based metabolite annotation method, SGMNS is based on a global connectivity molecular network (GCMN), which was constructed by molecular fingerprint similarity of chemical structures in metabolome databases. Neighbor metabolites with similar structures in GCMN are expected to produce similar spectra. Network annotation propagation of SGMNS is performed using known metabolites as seeds. The experimental MS/MS spectra of seeds are assigned to corresponding neighbor metabolites in GCMN as their "pseudo" spectra; the propagation is done by searching predicted retention times, MS1, and "pseudo" spectra against metabolite features in untargeted metabolomics data. Then, the annotated metabolite features were used as new seeds for annotation propagation again. Performance evaluation of SGMNS showed its unique advantages for metabolome annotation. The developed method was applied to annotate six typical biological samples; a total of 701, 1557, 1147, 1095, 1237, and 2041 metabolites were annotated from the cell, feces, plasma (NIST SRM 1950), tissue, urine, and their pooled sample, respectively, and the annotation accuracy was >83% with RSD <2%. The results show that SGMNS fully exploits the chemical space of the existing metabolomes for metabolite deep annotation and overcomes the shortcoming of insufficient reference MS/MS spectra.

Centimeter-Scale PdS2 Ultrathin Films with High Mobility and Broadband Photoresponse.

2D materials with mixed crystal phase will lead to the nonuniformity of performance and go against the practical application. Therefore, it is of great significance to develop a valid method to synthesize 2D materials with typical stoichiometry. Here, 2D palladium sulfides with centimeter scale and uniform stoichiometric ratio are synthesized via controlling the sulfurization temperature of palladium thin films. The relationship between sulfurization temperature and products is investigated in depth. Besides, the high-quality 2D PdS2 films are synthesized via sulfurization at the temperature of 450-550 °C, which would be compatible with back-end-of-line processes in semiconductor industry with considering of process temperature. The PdS2 films show an n-type semiconducting behavior with high mobility of 10.4 cm2 V-1 s-1 . The PdS2 photodetector presents a broadband photoresponse from 450 to 1550 nm. These findings provide a reliable way to synthesizing high-quality and large-area 2D materials with uniform crystal phase. The result suggests that 2D PdS2 has significant potential in future nanoelectronics and optoelectronic applications.

FATC Domain Deletion Compromises ATM Protein Stability, Blocks Lymphocyte Development, and Promotes Lymphomagenesis.

Ataxia-telangiectasia mutated (ATM) kinase is a master regulator of the DNA damage response, and loss of ATM leads to primary immunodeficiency and greatly increased risk for lymphoid malignancies. The FATC domain is conserved in phosphatidylinositol-3-kinase-related protein kinases (PIKKs). Truncation mutation in the FATC domain (R3047X) selectively compromised reactive oxygen species-induced ATM activation in cell-free assays. In this article, we show that in mouse models, knock-in ATM-R3057X mutation (Atm⁠ RX ⁠, corresponding to R3047X in human ATM) severely compromises ATM protein stability and causes T cell developmental defects, B cell Ig class-switch recombination defects, and infertility resembling ATM-null. The residual ATM-R3057X protein retains minimal yet functional measurable DNA damage-induced checkpoint activation and significantly delays lymphomagenesis in Atm⁠ RX/RX ⁠ mice compared with Atm⁠ -/- ⁠. Together, these results support a physiological role of the FATC domain in ATM protein stability and show that the presence of minimal residual ATM-R3057X protein can prevent growth retardation and delay tumorigenesis without restoring lymphocyte development and fertility.

An omics data analysis method based on feature linear relationship and graph convolutional network.

Biological networks are known to be highly modular, and the dysfunction of network modules may cause diseases. Defining the key modules from the omics data and establishing the classification model is helpful in promoting the research of disease diagnosis and prognosis. However, for applying modules in downstream analysis such as disease states discrimination, most methods only utilize the node information, and ignore the node interactions or topological information, which may lead to false positives and limit the model performance. In this study, we propose an omics data analysis method based on feature linear relationship and graph convolutional network (LCNet). In LCNet, we adopt a way of applying the difference of feature linear relationships during disease development to characterize physiological and pathological changes and construct the differential linear relation network, which is simple and interpretable from the perspective of feature linear relationship. A greedy strategy is developed for searching the highly interactive modules with a strong discrimination ability. To fully utilize the information of the detected modules, the personalized sub-graphs for each sample based on the modules are defined, and the graph convolutional network (GCN) classifiers are trained to predict the sample labels. The experimental results on public datasets show the superiority of LCNet in classification performance. For Breast Cancer metabolic data, the identified metabolites by LCNet involve important pathways. Thus, LCNet can identify the module biomarkers by feature linear relationship and a greedy strategy, and label samples by personalized sub-graphs and GCN. It provides a new manner of utilizing node (molecule) information and topological information in the defined modules for better disease classification.

Automatic mammographic breast density classification in Chinese women: clinical validation of a deep learning model.

BACKGROUND: High breast density is a strong risk factor for breast cancer. As such, high consistency and accuracy in breast density assessment is necessary. PURPOSE: To validate our proposed deep learning (DL) model and explore its impact on radiologists on density assessments. MATERIAL AND METHODS: A total of 3732 mammographic cases were collected as a validated set: 1686 cases before the implementation of the DL model and 2046 cases after the DL model. Five radiologists were divided into two groups (junior and senior groups) to assess all mammograms using either two- or four-category evaluation. Linear-weighted kappa (K) and intraclass correlation coefficient (ICC) statistics were used to analyze the consistency between radiologists before and after implementation of the DL model. RESULTS: The accuracy and clinical acceptance of the DL model for the junior group were 96.3% and 96.8% for two-category evaluation, and 85.6% and 89.6% for four-category evaluation, respectively. For the senior group, the accuracy and clinical acceptance were 95.5% and 98.0% for two-category evaluation, and 84.3% and 95.3% for four-category evaluation, respectively. The consistency within the junior group, the senior group, and among all radiologists improved with the help of the DL model. For two-category, their K and ICC values improved to 0.81, 0.81, and 0.80 from 0.73, 0.75, and 0.76. And for four-category, their K and ICC values improved to 0.81, 0.82, and 0.82 from 0.73, 0.79, and 0.78, respectively. CONCLUSION: The DL model showed high accuracy and clinical acceptance in breast density categories. It is helpful to improve radiologists' consistency.

Composition, functional properties and safety of honey: a review.

Honey has been used not only as a food source but also for medicinal purposes. Recent studies have indicated that honey exhibits antioxidant, hepatoprotective, hypolipidemic, hypoglycemic and anti-obesity properties, as well as anticancer, anti-atherosclerotic, hypotensive, neuroprotective and immunomodulatory activities. These health benefits of honey could be attributed to its wide range of nutritional components, including polysaccharides and polyphenols, which have been proven to possess various beneficial properties. It is notable that the composition of honey can also be affected by nectar, season, geography and storage condition. Moreover, the safety of honey requires caution to avoid any potential safety incidents. Therefore, this review aims to provide recent research regarding the chemical composition, biological activities and safety of honey, which might be attributed to comprehensive utilization of honey. © 2023 Society of Chemical Industry.

Novel Method for Comprehensive Annotation of Plant Glycosides Based on Untargeted LC-HRMS/MS Metabolomics.

Glycosides are a large family of secondary metabolites in plants, which play a critical role in plant growth and development. Due to the complexity and diversity in structures and the limited availability of authentic standards, comprehensive annotation of the glycosides remains a great challenge. In this study, using maize as an example, a deep annotation method of glycosides was proposed based on untargeted liquid chromatography-high-resolution tandem mass spectrometry metabolomics analysis. First, knowledge-based in silico aglycone and glycosyl/acyl-glycosyl libraries were built. A total of 1240 known and potential aglycones from databases and literature were recorded. Next, the MS parameters beneficial to aglycone ion-rich MS/MS were explored using 1782 high-resolution MS/MS spectra of glycosides from the MassBank of North America (MoNA) and confirmed by 52 authentic glycoside standards. Then, screening rules for aglycon ions in MS/MS were recommended. Glycoside candidates were further filtered by MS/MS-based chemical classification and MS/MS similarity of aglycon-glycoside pairs. Finally, the glycosylation sites of flavonoid mono-O-glycosides were recommended by characteristic fragmentation patterns. The developed method was validated using glycosides and nonglycosides from the MoNA library. The annotation accuracy rates were 96.8, 94.9, and 98.0% in negative ion mode (ESI-), positive ion mode (ESI+), and the combined ESI- & ESI+, respectively. The annotation specificity was 99.6% (ESI-), 99.6% (ESI+), and 99.2% (ESI- & ESI+). A total of 274 glycosides (including 34 acyl-glycosides) were tentatively annotated in maize by the developed method. The method enables effective and reliable annotation for plant glycosides.

Revisiting PARP2 and PARP1 trapping through quantitative live-cell imaging.

Poly (ADP-ribose) polymerase-1 (PARP1) and 2 (PARP2) are two DNA damage-induced poly (ADP-ribose) (PAR) polymerases in cells and are the targets of PARP inhibitors used for cancer therapy. Strand breaks recruit and activate PARP1 and 2, which rapidly generate PAR from NAD+. PAR promotes the recruitment of other repair factors, relaxes chromatin, and has a role in DNA repair, transcription regulation, and RNA biology. Four PARP1/2 dual inhibitors are currently used to treat BRCA-deficient breast, ovarian, prostate, and pancreatic cancers. In addition to blocking the enzymatic activity of PARP1 and 2, clinical PARP inhibitors extend the appearance of PARP1 and PARP2 on chromatin after damage, termed trapping. Loss of PARP1 confers resistance to PARP inhibitors, suggesting an essential role of trapping in cancer therapy. Yet, whether the persistent PARP1 and 2 foci at the DNA damage sites are caused by the retention of the same molecules or by the continual exchange of different molecules remains unknown. Here, we discuss recent results from quantitative live-cell imaging studies focusing on PARP1 and PARP2's distinct DNA substrate specificities and modes of recruitment and trapping with implications for cancer therapy and on-target toxicities of PARP inhibitors.

Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes.

Dehydration is one of the most widely used food processing techniques, which is sophisticated in nature. Rapid and accurate prediction of dehydration performance and its effects on product quality is still a difficult task. Traditional analytical methods for evaluating food dehydration processes are laborious, time-consuming and destructive, and they are not suitable for online applications. On the other hand, vibrational spectral techniques coupled with chemometrics have emerged as a rapid and noninvasive tool with excellent potential for online evaluation and control of the dehydration process to improve final dried food quality. In the current review, the fundamental of food dehydration and five types of vibrational spectral techniques, and spectral data processing methods are introduced. Critical overtones bands related to dehydration attributes in the near-infrared (NIR) region and the state-of-the-art applications of vibrational spectral analyses in evaluating food quality attributes as affected by dehydration processes are summarized. Research investigations since 2010 on using vibrational spectral technologies combined with chemometrics to continuously monitor food quality attributes during dehydration processes are also covered in this review.