PlantMine: A Machine-Learning Framework to Detect Core SNPs in Rice Genomics

As a fundamental global staple crop, rice plays a pivotal role in human nutrition and agricultural production systems. However, its complex genetic architecture and extensive trait variability pose challenges for breeders and researchers in optimizing yield and quality. Particularly to expedite breeding methods like genomic selection, isolating core SNPs related to target traits from genome-wide data reduces irrelevant mutation noise, enhancing computational precision and efficiency. Thus, exploring efficient computational approaches to mine core SNPs is of great importance. This study introduces PlantMine, an innovative computational framework that integrates feature selection and machine learning techniques to effectively identify core SNPs critical for the improvement of rice traits. Utilizing the dataset from the 3000 Rice Genomes Project, we applied different algorithms for analysis. The findings underscore the effectiveness of combining feature selection with machine learning in accurately identifying core SNPs, offering a promising avenue to expedite rice breeding efforts and improve crop productivity and resilience to stress.

Progress in Rice Breeding Based on Genomic Research

The role of rice genomics in breeding progress is becoming increasingly important. Deeper research into the rice genome will contribute to the identification and utilization of outstanding functional genes, enriching the diversity and genetic basis of breeding materials and meeting the diverse demands for various improvements. Here, we review the significant contributions of rice genomics research to breeding progress over the last 25 years, discussing the profound impact of genomics on rice genome sequencing, functional gene exploration, and novel breeding methods, and we provide valuable insights for future research and breeding practices.

Fates and models for exposure pathways of pyrethroid pesticide residues: A review

Pyrethroids (PYs) are widely applied pesticides whose residues pose potential health risks. This review describes current knowledge on PY chemical properties, usage patterns, environmental and food contamination, and human exposure models. It evaluates life cycle assessment (LCA), chemical alternatives assessment (CAA), and high-throughput screening (HTS) as tools for pesticide policy. Despite efforts to mitigate PY presence, their pervasive residues in the environment and food persist. And the highest concentrations ranged from 54,360 to 80,500 ng/L in water samples from agricultural fields. Food processing techniques variably reduce PY levels, yet no method guarantees complete elimination. This review provides insights into the fates and exposure pathways of PY residues in agriculture and food, and highlights the necessity for improved PY management and alternative practices to safeguard health and environment.

Sampling complex topology structures for spiking neural networks

Spiking Neural Networks (SNNs) have been considered a potential competitor to Artificial Neural Networks (ANNs) due to their high biological plausibility and energy efficiency. However, the architecture design of SNN has not been well studied. Previous studies either use ANN architectures or directly search for SNN architectures under a highly constrained search space. In this paper, we aim to introduce much more complex connection topologies to SNNs to further exploit the potential of SNN architectures. To this end, we propose the topology-aware search space, which is the first search space that enables a more diverse and flexible design for both the spatial and temporal topology of the SNN architecture. Then, to efficiently obtain architecture from our search space, we propose the spatio-temporal topology sampling (STTS) algorithm. By leveraging the benefits of random sampling, STTS can yield powerful architecture without the need for an exhaustive search process, making it significantly more efficient than alternative search strategies. Extensive experiments on CIFAR-10, CIFAR-100, and ImageNet demonstrate the effectiveness of our method. Notably, we obtain 70.79% top-1 accuracy on ImageNet with only 4 time steps, 1.79% higher than the second best model. Our code is available under https://github.com/stiger1000/Random-Sampling-SNN.

Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13  TeV and corresponding to an integrated luminosity of 137  fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst)  pb.

[Incidence of postoperative complications in Chinese patients with gastric or colorectal cancer based on a national, multicenter, prospective, cohort study]

Objective: To investigate the incidence of postoperative complications in Chinese patients with gastric or colorectal cancer, and to evaluate the risk factors for postoperative complications. Methods: This was a national, multicenter, prospective, registry-based, cohort study of data obtained from the database of the Prevalence of Abdominal Complications After Gastro- enterological Surgery (PACAGE) study sponsored by the China Gastrointestinal Cancer Surgical Union. The PACAGE database prospectively collected general demographic characteristics, protocols for perioperative treatment, and variables associated with postoperative complications in patients treated for gastric or colorectal cancer in 20 medical centers from December 2018 to December 2020. The patients were grouped according to the presence or absence of postoperative complications. Postoperative complications were categorized and graded in accordance with the expert consensus on postoperative complications in gastrointestinal oncology surgery and Clavien-Dindo grading criteria. The incidence of postoperative complications of different grades are presented as bar charts. Independent risk factors for occurrence of postoperative complications were identified by multifactorial unconditional logistic regression. Results: The study cohort comprised 3926 patients with gastric or colorectal cancer, 657 (16.7%) of whom had a total of 876 postoperative complications. Serious complications (Grade III and above) occurred in 4.0% of patients (156/3926). The rate of Grade V complications was 0.2% (7/3926). The cohort included 2271 patients with gastric cancer with a postoperative complication rate of 18.1% (412/2271) and serious complication rate of 4.7% (106/2271); and 1655 with colorectal cancer, with a postoperative complication rate of 14.8% (245/1655) and serious complication rate of 3.0% (50/1655). The incidences of anastomotic leakage in patients with gastric and colorectal cancer were 3.3% (74/2271) and 3.4% (56/1655), respectively. Abdominal infection was the most frequently occurring complication, accounting for 28.7% (164/572) and 39.5% (120/304) of postoperative complications in patients with gastric and colorectal cancer, respectively. The most frequently occurring grade of postoperative complication was Grade II, accounting for 65.4% (374/572) and 56.6% (172/304) of complications in patients with gastric and colorectal cancers, respectively. Multifactorial analysis identified (1) the following independent risk factors for postoperative complications in patients in the gastric cancer group: preoperative comorbidities (OR=2.54, 95%CI: 1.51-4.28, P<0.001), neoadjuvant therapy (OR=1.42, 95%CI:1.06-1.89, P=0.020), high American Society of Anesthesiologists (ASA) scores (ASA score 2 points:OR=1.60, 95% CI: 1.23-2.07, P<0.001, ASA score ≥3 points:OR=0.43, 95% CI: 0.25-0.73, P=0.002), operative time >180 minutes (OR=1.81, 95% CI: 1.42-2.31, P<0.001), intraoperative bleeding >50 mL (OR=1.29,95%CI: 1.01-1.63, P=0.038), and distal gastrectomy compared with total gastrectomy (OR=0.65,95%CI: 0.51-0.83, P<0.001); and (2) the following independent risk factors for postoperative complications in patients in the colorectal cancer group: female (OR=0.60, 95%CI: 0.44-0.80, P<0.001), preoperative comorbidities (OR=2.73, 95%CI: 1.25-5.99, P=0.030), neoadjuvant therapy (OR=1.83, 95%CI:1.23-2.72, P=0.008), laparoscopic surgery (OR=0.47, 95%CI: 0.30-0.72, P=0.022), and abdominoperineal resection compared with low anterior resection (OR=2.74, 95%CI: 1.71-4.41, P<0.001). Conclusion: Postoperative complications associated with various types of infection were the most frequent complications in patients with gastric or colorectal cancer. Although the risk factors for postoperative complications differed between patients with gastric cancer and those with colorectal cancer, the presence of preoperative comorbidities, administration of neoadjuvant therapy, and extent of surgical resection, were the commonest factors associated with postoperative complications in patients of both categories.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13 TeV with the ATLAS Detector

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140  fb^{-1} of pp collisions at sqrt[s]=13  TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

KASP-IEva: an intelligent typing evaluation model for KASP primers

KASP marker technology has been used in molecular marker-assisted breeding because of its high efficiency and flexibility, and an intelligent evaluation model of KASP marker primer typing results is essential to improve the efficiency of marker development on a large scale. To this end, this paper proposes a gene population delineation method based on NTC identification module and data distribution judgment module to improve the accuracy of K-Means clustering, and introduces a decision tree to construct the KASP-IEva primer typing evaluation model. The model firstly designs the NTC identification module and data distribution judgment module to extract four types of data, grouping and categorizing to achieve the improvement of the distinguishability of amplification product signals; secondly, the K-Means algorithm is used to aggregate and classify the data, to visualize the five aggregated clusters and to obtain the morphology location eigenvalues; lastly, the evaluation criteria for the typing effect level are constructed, and the logical decision tree is used to make conditional discrimination on the eigenvalues in order to realize the score prediction. The performance of the model was tested by the KASP marker typing test results of 2519 groups of cotton varieties, and the following conclusions were obtained: the model is able to visualize the aggregation and classification effects of the amplification products of NTC, pure genotypes, heterozygous genotypes, and untyped genotypes, enabling rapid and accurate KASP marker typing evaluation. Comparing and analyzing the model evaluation results with the expert evaluation results, the average accuracy rate of the four grades evaluated by the model was 87%, and the overall evaluation results showed an uneven distribution of the grades with significant differential characteristics. When evaluating 2519 KASP fractal maps, the expert evaluation consumes 15 hours, and the model evaluation only uses 8min27.45s, which makes the model intelligent evaluation significantly better than the expert evaluation from the perspective of time. The establishment of the model will further enhance the application of KASP markers in molecular marker-assisted breeding and provide technical support for the large-scale screening and identification of excellent genotypes.

GINv2.0: a comprehensive topological network integrating molecular interactions from multiple knowledge bases

Knowledge bases have been instrumental in advancing biological research, facilitating pathway analysis and data visualization, which are now widely employed in the scientific community. Despite the establishment of several prominent knowledge bases focusing on signaling, metabolic networks, or both, integrating these networks into a unified topological network has proven to be challenging. The intricacy of molecular interactions and the diverse formats employed to store and display them contribute to the complexity of this task. In a prior study, we addressed this challenge by introducing a "meta-pathway" structure that integrated the advantages of the Simple Interaction Format (SIF) while accommodating reaction information. Nevertheless, the earlier Global Integrative Network (GIN) was limited to reliance on KEGG alone. Here, we present GIN version 2.0, which incorporates human molecular interaction data from ten distinct knowledge bases, including KEGG, Reactome, and HumanCyc, among others. We standardized the data structure, gene IDs, and chemical IDs, and conducted a comprehensive analysis of the consistency among the ten knowledge bases before combining all unified interactions into GINv2.0. Utilizing GINv2.0, we investigated the glycolysis process and its regulatory proteins, revealing coordinated regulations on glycolysis and autophagy, particularly under glucose starvation. The expanded scope and enhanced capabilities of GINv2.0 provide a valuable resource for comprehensive systems-level analyses in the field of biological research. GINv2.0 can be accessed at: https://github.com/BIGchix/GINv2.0 .

Observation of WZγ Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

This Letter reports the observation of WZγ production and a measurement of its cross section using 140.1±1.2  fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The WZγ production cross section, with both the W and Z bosons decaying leptonically, pp→WZγ→ℓ^{'}^{±}νℓ^{+}ℓ^{-}γ (ℓ^{(^{'})}=e, μ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01±0.30(stat)±0.16(syst)  fb. The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50±0.06  fb. The observed significance of the WZγ signal is 6.3σ, compared with an expected significance of 5.0σ.

Combined Measurement of the Higgs Boson Mass from the H→γγ and H→ZZ^{*}→4ℓ Decay Channels with the ATLAS Detector Using sqrt[s]=7, 8, and 13 TeV pp Collision Data

A measurement of the mass of the Higgs boson combining the H→ZZ^{*}→4ℓ and H→γγ decay channels is presented. The result is based on 140  fb^{-1} of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11±0.09(stat)±0.06(syst)=125.11±0.11  GeV. This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics.

Search for Dark Photons in Rare Z Boson Decays with the ATLAS Detector

A search for events with a dark photon produced in association with a dark Higgs boson via rare decays of the standard model Z boson is presented, using 139  fb^{-1} of sqrt[s]=13  TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The dark boson decays into a pair of dark photons, and at least two of the three dark photons must each decay into a pair of electrons or muons, resulting in at least two same-flavor opposite-charge lepton pairs in the final state. The data are found to be consistent with the background prediction, and upper limits are set on the dark photon's coupling to the dark Higgs boson times the kinetic mixing between the standard model photon and the dark photon, α_{D}ϵ^{2}, in the dark photon mass range of [5, 40] GeV except for the ϒ mass window [8.8, 11.1] GeV. This search explores new parameter space not previously excluded by other experiments.

Molecular Ionization Dissociation Induced by Interatomic Coulombic Decay in an ArCH_{4}-Electron Collision System

Interatomic Coulombic decay (ICD) is a significant fragmentation mechanism observed in weakly bound systems. It has been widely accepted that ICD-induced molecular fragmentation occurs through a two-step process, involving ICD as the first step and dissociative-electron attachment (DEA) as the second step. In this study, we conducted a fragmentation experiment of ArCH_{4} by electron impact, utilizing the coincident detection of one electron and two ions. In addition to the well-known decay pathway that induces pure ionization of CH_{4}, we observed a new channel where ICD triggers the ionization dissociation of CH_{4}, resulting in the cleavage of the C-H bond and the formation of the CH_{3}^{+} and H ion pair. The high efficiency of this channel, as indicated by the relative yield of the Ar^{+}/CH_{3}^{+} ion pair, agrees with the theoretical prediction [L. S. Cederbaum, J. Phys. Chem. Lett. 11, 8964 (2020).JPCLCD1948-718510.1021/acs.jpclett.0c02259; Y. C. Chiang et al., Phys. Rev. A 100, 052701 (2019).PLRAAN2469-992610.1103/PhysRevA.100.052701]. These results suggest that ICD can directly break covalent bonds with high efficiency, bypassing the need for DEA. This finding introduces a novel approach to enhance the fragmentation efficiency of molecules containing covalent bonds, such as DNA backbone.

[Effect of recombinant human thrombin for hemostasis in liver resection: a randomized controlled phase Ⅲ clinical trial]

Objective: To evaluate the hemostatic efficacy, safety and immunogenicity of recombinant human thrombin in the treatment of liver wounds that still ooze after conventional surgical hemostasis. Methods: A multicenter, stratified randomized, double-blind, placebo-controlled phase Ⅲ trial with a planned enrollment of 510 subjects at 33 centers, with a 2∶1 randomization to the thrombin group versus the placebo group. An interim analysis will be conducted after approximately 70% of the subjects have completed the observation period. The primary efficacy endpoint was the rate of hemostasis within 6 minutes at the point of bleeding that could be evaluated. Safety analysis was performed one month after surgery, and the positive rates of anti-drug antibody (ADA) and neutralizing antibody were evaluated. Results: At the interim analysis, a total of 348 subjects had been randomized and received the study drug (215 were male and 133 were female). They were aged 19-69 (52.9±10.9)years. Among them, 232 were in the thrombin group and 116 were in the placebo group, with balanced and comparable demographics and baseline characteristics between the two groups. The hemostasis rate at 6 minutes was 71.6% (95%CI:65.75%-77.36%) in the thrombin group and 44.0% (95%CI: 34.93%-53.00%) in the placebo group, respectively (P<0.001). No grade≥3 drug-related adverse events and no drug-related deaths were reported from the study.No recombinant human thrombin-induced immunologically-enhanced ADA or immunologically-induced ADA was detected after topical use in subjects. Conclusion: Recombinant human thrombin has shown significant hemostatic efficacy and good safety in controlling bleeding during liver resection surgery, while also demonstrating low immunogenicity characteristics.

Surface Phonon Polariton-Mediated Near-Field Radiative Heat Transfer at Cryogenic Temperatures

Recent experiments, at room temperature, have shown that near-field radiative heat transfer (NFRHT) via surface phonon polaritons (SPhPs) exceeds the blackbody limit by several orders of magnitude. Yet, SPhP-mediated NFRHT at cryogenic temperatures remains experimentally unexplored. Here, we probe thermal transport in nanoscale gaps between a silica sphere and a planar silica surface from 77-300 K. These experiments reveal that cryogenic NFRHT has strong contributions from SPhPs and does not follow the T^{3} temperature (T) dependence of far-field thermal radiation. Our modeling based on fluctuational electrodynamics shows that the temperature dependence of NFRHT can be related to the confinement of heat transfer to two narrow frequency ranges and is well accounted for by a simple analytical model. These advances enable detailed NFRHT studies at cryogenic temperatures that are relevant to thermal management and solid-state cooling applications.

NRTPredictor: identifying rice root cell state in single-cell RNA-seq via ensemble learning

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) measurements of gene expression show great promise for studying the cellular heterogeneity of rice roots. How precisely annotating cell identity is a major unresolved problem in plant scRNA-seq analysis due to the inherent high dimensionality and sparsity.

RESULTS

To address this challenge, we present NRTPredictor, an ensemble-learning system, to predict rice root cell stage and mine biomarkers through complete model interpretability. The performance of NRTPredictor was evaluated using a test dataset, with 98.01% accuracy and 95.45% recall. With the power of interpretability provided by NRTPredictor, our model recognizes 110 marker genes partially involved in phenylpropanoid biosynthesis. Expression patterns of rice root could be mapped by the above-mentioned candidate genes, showing the superiority of NRTPredictor. Integrated analysis of scRNA and bulk RNA-seq data revealed aberrant expression of Epidermis cell subpopulations in flooding, Pi, and salt stresses.

CONCLUSION

Taken together, our results demonstrate that NRTPredictor is a useful tool for automated prediction of rice root cell stage and provides a valuable resource for deciphering the rice root cellular heterogeneity and the molecular mechanisms of flooding, Pi, and salt stresses. Based on the proposed model, a free webserver has been established, which is available at https://www.cgris.net/nrtp .

Observation of Single-Top-Quark Production in Association with a Photon Using the ATLAS Detector

This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139  fb^{-1} of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688±23(stat) _{-71}^{+75}(syst)  fb, to be compared with the standard model prediction of 515_{-42}^{+36}  fb at next-to-leading order in QCD.

Electrical Conductance and Thermopower of β-Substituted Porphyrin Molecular Junctions─Synthesis and Transport

Molecular junctions offer significant potential for enhancing thermoelectric power generation. Quantum interference effects and associated sharp features in electron transmission are expected to enable the tuning and enhancement of thermoelectric properties in molecular junctions. To systematically explore the effect of quantum interferences, we designed and synthesized two new classes of porphyrins, P1 and P2, with two methylthio anchoring groups in the 2,13- and 2,12-positions, respectively, and their Zn complexes, Zn-P1 and Zn-P2. Past theory suggests that P1 and Zn-P1 feature destructive quantum interference in single-molecule junctions with gold electrodes and may thus show high thermopower, while P2 and Zn-P2 do not. Our detailed experimental single-molecule break-junction studies of conductance and thermopower, the latter being the first ever performed on porphyrin molecular junctions, revealed that the electrical conductance of the P1 and Zn-P1 junctions is relatively close, and the same holds for P2 and Zn-P2, while there is a 6 times reduction in the electrical conductance between P1 and P2 type junctions. Further, we observed that the thermopower of P1 junctions is slightly larger than for P2 junctions, while Zn-P1 junctions show the largest thermopower and Zn-P2 junctions show the lowest. We relate the experimental results to quantum transport theory using first-principles approaches. While the conductance of P1 and Zn-P1 junctions is robustly predicted to be larger than those of P2 and Zn-P2, computed thermopowers depend sensitively on the level of theory and the single-molecule junction geometry. However, the predicted large difference in conductance and thermopower values between Zn-P1 and Zn-P2 derivatives, suggested in previous model calculations, is not supported by our experimental and theoretical findings.

Measurement of Suppression of Large-Radius Jets and Its Dependence on Substructure in Pb+Pb Collisions at sqrt[s_{NN}]=5.02 TeV with the ATLAS Detector

This letter presents a measurement of the nuclear modification factor of large-radius jets in sqrt[s_{NN}]=5.02  TeV Pb+Pb collisions by the ATLAS experiment. The measurement is performed using 1.72  nb^{-1} and 257  pb^{-1} of Pb+Pb and pp data, respectively. The large-radius jets are reconstructed with the anti-k_{t} algorithm using a radius parameter of R=1.0, by reclustering anti-k_{t} R=0.2 jets, and are measured over the transverse momentum (p_{T}) kinematic range of 158 Collapse

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Measurement of the Sensitivity of Two-Particle Correlations in pp Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the "ridge"-i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities-and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at sqrt[s]=13  TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8  pb^{-1}, in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v_{2}, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

[Chinese expert guidance on overall application of lenvatinib in hepatocellular carcinoma]

Lenvatinib mesylate is an oral receptor tyrosine kinase inhibitor against targets of vascular endothelial growth factor receptors 1-3, fibroblast growth factor receptors 1-4, platelet-derived growth factor receptor α, stem cell growth factor receptor, and rearranged during transfection, et al. Lenvatinib has been approved by the National Medical Products Administration of China on September 4, 2018, for the first-line treatment of patients with unresectable hepatocellular carcinoma who have not received systematic treatment before. Up to February 2023, Lenvatinib has been listed in China for more than 4 years, accumulating a series of post-marketing clinical research evidences. Based on the clinical practice before and after the launch of lenvatinib and referring to the clinical experience of other anti-angiogenesis inhibitors, domestic multidisciplinary experts and scholars adopt the Delphi method to formulate the Chinese Expert Guidance on Overall Application of Lenvatinib in Hepatocellular Carcinoma after repeated discussions and revisions, in order to provide reference for reasonable and effective clinical application of lenvatinib for clinicians.

Observation of an Excess of Dicharmonium Events in the Four-Muon Final State with the ATLAS Detector

A search is made for potential ccc[over ¯]c[over ¯] tetraquarks decaying into a pair of charmonium states in the four muon final state using proton-proton collision data at sqrt[s]=13  TeV, corresponding to an integrated luminosity of 140  fb^{-1} recorded by the ATLAS experiment at LHC. Two decay channels, J/ψ+J/ψ→4μ and J/ψ+ψ(2S)→4μ, are studied. Backgrounds are estimated based on a hybrid approach involving Monte Carlo simulations and data-driven methods. Statistically significant excesses with respect to backgrounds dominated by the single parton scattering are seen in the di-J/ψ channel consistent with a narrow resonance at 6.9 GeV and a broader structure at lower mass. A statistically significant excess is also seen in the J/ψ+ψ(2S) channel. The fitted masses and decay widths of the structures are reported.

Observation of the γγ→ττ Process in Pb+Pb Collisions and Constraints on the τ-Lepton Anomalous Magnetic Moment with the ATLAS Detector

This Letter reports the observation of τ-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb(γγ→ττ)Pb and constraints on the τ-lepton anomalous magnetic moment a_{τ}. The dataset corresponds to an integrated luminosity of 1.44  nb^{-1} of LHC Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of μ_{ττ}=1.03_{-0.05}^{+0.06} assuming the standard model value for a_{τ}. To measure a_{τ}, a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→μμ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for a_{τ} is -0.057 Collapse

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Antibody-Free Fluorine-Assisted Metabolic Sequencing of RNA N4-Acetylcytidine

N4-Acetylcytidine (ac4C) has been found to affect a variety of cellular and biological processes. For a mechanistic understanding of the roles of ac4C in biology and disease, we present an antibody-free, fluorine-assisted metabolic sequencing method to detect RNA ac4C, called "FAM-seq". We successfully applied FAM-seq to profile ac4C landscapes in human 293T, HeLa, and MDA cell lines in parallel with the reported acRIP-seq method. By comparison with the classic ac4C antibody sequencing method, we found that FAM-seq is a convenient and reliable method for transcriptome-wide mapping of ac4C. Because this method holds promise for detecting nascent RNA ac4C modifications, we further investigated the role of ac4C in regulating chemotherapy drug resistance in chronic myeloid leukemia. The results indicated that drug development or combination therapy could be enhanced by appreciating the key role of ac4C modification in cancer therapy.

Radiation Induced Lung Injury in Rats after Pre-Oxygenation Radiotherapy

PURPOSE/OBJECTIVE(S)

Deep inspiratory breath holding (DIBH) has been widely used during the radiotherapy of thoracic tumors. The main disadvantage of voluntary DIBH is the short duration of each breath hold. The hypocapnia induced by hyperoxia (oxygen concentration > 50%) pre-oxygenation (PreO2) combined with mechanical hyperventilation has been reported to prolong the duration of single breath hold, but its safety remains controversial, especially the sensitivity of lung tissue to radiation damage under hyperoxia exposure has not been elucidated. In this study, we aim to investigate the changes of radiation induced lung injury in rats after PreO2 radiation.

MATERIALS/METHODS

We evaluated the lung tissue of rats at different time points (48h, 2w, 4w, 8w, 12w) after thoracic radiation (15Gy single fraction to the right lung), and sequenced the transcriptome of lung tissue at 48 hours after irradiation. Rat cohorts (n = 7/group): 1. Control (Con); 2. Radiation group (RT); 3. Pre-oxygenation (oxygen concentration > 90%) for 8 hours before thoracic radiation (PreO2).

RESULTS

The inflammatory exudation emerged in the pulmonary interstitium at 48 hours, and reached the most serious alveolitis after four weeks of irradiation (the comparison of alveolitis scores in RT4w vs Con4w and PreO2(4w) vs Con4w, P<0.001) on hematoxylin-eosin staining. While the alveolitis scores in RT group and PreO2 group were not statistically different at each time point. Masson staining showed that the pulmonary fibrosis in the RT group and the PreO2 group reached an obvious pathological change at 12 weeks after irradiation, but the difference between the two groups was not significant. Transcriptome sequencing showed that the number of differential genes in PreO2 vs Con was 559 (302 up-regulated genes and 257 down-regulated genes). The GO enrichment analysis indicated that chromosome segregation was the most significant functional item with P value in the comparative analysis, and the KEGG enrichment analysis suggested that cell division was the most significant enrichment pathway of these differential genes. While there was a small quantity of differential genes in PreO2 vs RT group (3 up-regulated genes and 12 down-regulated genes). Pentose and glucuronate conversions were the most significant enrichment pathway of these differential genes.

CONCLUSION

This study demonstrated that PreO2 radiotherapy did not increase the severity of radiation induced lung injury in rats compared to conventional radiotherapy. Further study should be conducted to confirm these results and to investigate the regulatory mechanism of pneumonia caused by PreO2 radiotherapy.

Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model.

MATERIALS/METHODS

We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance.

RESULTS

The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality.

CONCLUSION

We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.

Homeostatic Balance of Gut Microbiota in Head and Neck Squamous Cell Carcinoma Patients during Radiotherapy

PURPOSE/OBJECTIVE(S)

Radiotherapy is the major treatment for head and neck squamous cell carcinoma (HNSCC). Oral microbiota changes have been described before. However, gut microbiota changes in HNSCC patients who received local radiotherapy remain unclear. We aim to investigate the dynamic change of gut microbiota composition in HNSCC patients undergoing radiotherapy and to construct the radiotherapy related gut microbiota database in HNSCC patients.

MATERIALS/METHODS

We enrolled 47 HNSCC patients who scheduled with radiotherapy solely. Intensity-modulated radiotherapy (IMRT) was the standard radiotherapy technique for all the enrolled patients. The field was irradiated with a total dose of 60-66Gy in 30-33 fractions. Fecal pellets were collected at three time points. Bacterial genomic DNA was isolated using magnetic beads and then analyzed by the Illumina MiSeq Sequencing System based on the V3-V4 hypervariable regions of the 16S rRNA gene.

RESULTS

A total of 194 genera which belonged to 27 phyla were found in 141 samples. Increased abundance of microbiota in diversity and richness was observed in mid-radiotherapy group. Moreover, Bacteroides, Blautia, and Phascolarctobacterium were three main genera in all three groups and the mid-radiotherapy group had the highest relative abundance of Phascolarctobacterium. What's more, most significantly altered bacteria shared the same variation pattern which was increased in mid-radiotherapy while decreased to the almost same level of as pre-radiotherapy in post-radiotherapy group.

CONCLUSION

Local radiotherapy can affect the composition of the gut microbiota in HNSCC patients during the mid-term of radiotherapy. However, self-stabilized ability maintained the gut microbiota homeostasis in the end.

Anatomy-Guided Deep Learning Model for Accurate and Robust Gross Tumor Volume Segmentation in Lung Cancer Radiation Therapy

PURPOSE/OBJECTIVE(S)

In lung cancer radiation therapy, clinicians must outline the gross tumor volume (GTV) precisely on the planning computed tomography (pCT) for accurate radiation dose delivery. However, due to the limited contrast between tumor and normal tissues in lung parenchyma, accurate delineation of tumor boundaries is difficult leading to large inter-observer variation. In this study, we develop an anatomy-guided lung GTV deep segmentation model using a training cohort of multi-center datasets. The quantitative segmentation performance is evaluated on an independent dataset, where the inter-observer delineation variation is also assessed.

MATERIALS/METHODS

We collected and curated four publicly available lung datasets with GTV annotations (Lung-PET-CT-Dx, LIDC-IDRI, NSCLC-Radiogenomics and RIDER-CT) for deep learning model development. A total of 871 CT scans of patients, who were diagnosed with T1-T4 NSCLC, were available for training after data curation. The GTV annotations of primary tumor were examined and edited by two experienced radiation oncologists following the RTOG 1106 protocol. An anatomy-guided deep learning model was proposed, which consisted two deep networks. The first deep network used CT scan as input and segmented 4 anatomic organs (airway, heart, pulmonary artery and pulmonary vein), while the second deep network took both CT scan and these pre-segmented 4 organs as input and segmented the lung GTV. With the help of anatomic priors from 4 pre-segmented organs, the second deep network could more easily locate the GTV. We used nnUNet as the deep segmentation network. For evaluation, we used NSCLC-Radiomics as the testing dataset, which contains 20 CT scans each annotated by 5 radiation oncologists. The auto-segmented GTV were compared against each of the manual GTV reference. Inter-observer variation was also assessed using the 5 manual GTV references.

RESULTS

The proposed anatomic-guided lung GTV segmentation model achieved a mean Dice score of 82.4% and 95% Hausdorff distance (HD95) of 6.9mm when averaged cross 20 patients and 5 GTV references (Table 1), which outperformed the basic deep GTV segmentation model by markedly reducing 19.4% HD95 error. The performance of proposed model was also comparable to the inter-observer variation (Dice score: 82.4% vs. 81.9%, HD95 6.9 vs. 6.4mm), indicating that our model had similar reproducibility as human observers.

CONCLUSION

We developed and tested an anatomy-guided deep learning model for segmenting GTV in NSCLC patients. The model achieves high quantitative segmentation performance, which is comparable to the human observer variation. It can be potentially used in radiotherapy practice to improve GTV delineation consistency and reduce workloads of radiation oncologists.

Transcriptome-wide profiling of A-to-I RNA editing by Slic-seq

Adenosine-to-inosine (A-to-I) RNA editing is a post-transcriptional processing event involved in diversifying the transcriptome and is responsible for various biological processes. In this context, we developed a new method based on the highly selective cleavage activity of Endonuclease V against Inosine and the universal activity of sodium periodate against all RNAs to enrich the inosine-containing RNA and accurately identify the editing sites. We validated the reliability of our method in human brain in both Alu and non-Alu elements. The conserved sites of A-to-I editing in human cells (HEK293T, HeLa, HepG2, K562 and MCF-7) primarily occurs in the 3'UTR of the RNA, which are highly correlated with RNA binding and protein binding. Analysis of the editing sites between the human brain and mouse brain revealed that the editing of exons is more conserved than that in other regions. This method was applied to three neurological diseases (Alzheimer's, epilepsy and ageing) of mouse brain, reflecting that A-to-I editing sites significantly decreased in neuronal activity genes.

Strong Constraints on Jet Quenching in Centrality-Dependent p+Pb Collisions at 5.02 TeV from ATLAS

Jet quenching is the process of color-charged partons losing energy via interactions with quark-gluon plasma droplets created in heavy-ion collisions. The collective expansion of such droplets is well described by viscous hydrodynamics. Similar evidence of collectivity is consistently observed in smaller collision systems, including pp and p+Pb collisions. In contrast, while jet quenching is observed in Pb+Pb collisions, no evidence has been found in these small systems to date, raising fundamental questions about the nature of the system created in these collisions. The ATLAS experiment at the Large Hadron Collider has measured the yield of charged hadrons correlated with reconstructed jets in 0.36  nb^{-1} of p+Pb and 3.6  pb^{-1} of pp collisions at 5.02 TeV. The yields of charged hadrons with p_{T}^{ch}>0.5  GeV near and opposite in azimuth to jets with p_{T}^{jet}>30 or 60 GeV, and the ratios of these yields between p+Pb and pp collisions, I_{pPb}, are reported. The collision centrality of p+Pb events is categorized by the energy deposited by forward neutrons from the struck nucleus. The I_{pPb} values are consistent with unity within a few percent for hadrons with p_{T}^{ch}>4  GeV at all centralities. These data provide new, strong constraints that preclude almost any parton energy loss in central p+Pb collisions.

Search for Heavy Neutral Leptons in Decays of W Bosons Using a Dilepton Displaced Vertex in sqrt[s]=13 TeV pp Collisions with the ATLAS Detector

A search for a long-lived, heavy neutral lepton (N) in 139  fb^{-1} of sqrt[s]=13  TeV pp collision data collected by the ATLAS detector at the Large Hadron Collider is reported. The N is produced via W→Nμ or W→Ne and decays into two charged leptons and a neutrino, forming a displaced vertex. The N mass is used to discriminate between signal and background. No signal is observed, and limits are set on the squared mixing parameters of the N with the left-handed neutrino states for the N mass range 3  GeV Collapse

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Test of CP Invariance in Higgs Boson Vector-Boson-Fusion Production Using the H→γγ Channel with the ATLAS Detector

A test of CP invariance in Higgs boson production via vector-boson fusion has been performed in the H→γγ channel using 139  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV collected by the ATLAS detector at the LHC. The optimal observable method is used to probe the CP structure of interactions between the Higgs boson and electroweak gauge bosons, as described by an effective field theory. No sign of CP violation is observed in the data. Constraints are set on the parameters describing the strength of the CP-odd component in the coupling between the Higgs boson and the electroweak gauge bosons in two effective field theory bases: d[over ˜] in the HISZ basis and c_{HW[over ˜]} in the Warsaw basis. The results presented are the most stringent constraints on CP violation in the coupling between Higgs and weak bosons. The 95% C.L. constraint on d[over ˜] is derived for the first time and the 95% C.L. constraint on c_{HW[over ˜]} has been improved by a factor of 5 compared to the previous measurement.

Randomized phase II adjuvant trial to compare two treatment durations of icotinib (2 years versus 1 year) for stage II-IIIA EGFR-positive lung adenocarcinoma patients (ICOMPARE study)

BACKGROUND

Despite the prolonged median disease-free survival (DFS) by adjuvant targeted therapy in non-small-cell lung cancer patients with epidermal growth factor receptor (EGFR) mutations, the relationship between the treatment duration and the survival benefits in patients remains unknown.

PATIENTS AND METHODS

In this multicenter, randomized, open-label, phase II trial, eligible patients aged 18-75 years with EGFR-mutant, stage II-IIIA lung adenocarcinoma and who had not received adjuvant chemotherapy after complete tumor resection were enrolled from eight centers in China. Patients were randomly assigned (1 : 1) to receive either 1-year or 2-year icotinib (125 mg thrice daily). The primary endpoint was DFS assessed by investigator. The secondary endpoints were overall survival (OS) and safety. This study was registered at ClinicalTrials.gov (NCT01929200).

RESULTS

Between September 2013 and October 2018, 109 patients were enrolled (1-year group, n = 55; 2-year group, n = 54). Median DFS was 48.9 months [95% confidence interval (CI) 33.1-70.1 months] in the 2-year group and 32.9 months (95% CI 26.6-44.8 months) in the 1-year group [hazard ratio (HR) 0.51; 95% CI 0.28-0.94; P = 0.0290]. Median OS for patients was 75.8 months [95% CI 64.4 months-not evaluable (NE)] in the 2-year group and NE (95% CI 66.3 months-NE) in the 1-year group (HR 0.34; 95% CI 0.13-0.95; P = 0.0317). Treatment-related adverse events (TRAEs) were observed in 41 of 55 (75%) patients in the 1-year group and in 36 of 54 (67%) patients in the 2-year group. Grade 3-4 TRAEs occurred in 4 of 55 (7%) patients in the 1-year group and in 3 of 54 (6%) patients in the 2-year group. No treatment-related deaths or interstitial lung disease was reported.

CONCLUSIONS

Two-year adjuvant icotinib was shown to significantly improve DFS and provide an OS benefit in EGFR-mutant, stage II-IIIA lung adenocarcinoma patients compared with 1-year treatment in this exploratory phase II study.

[Efficacy and safety of VRD regimen of autologous hematopoietic stem cell transplantation in patients with newly diagnosed multiple myeloma]

Objective: To explore the stem cell collection rate and efficacy and safety of patients aged 70 and below with newly diagnosed multiple myeloma (MM) treated with the VRD (bortezomib, lenalidomide and dexamethasone) regimen followed by autologous stem cell transplantation (ASCT). Methods: Retrospective case series study. The clinical data of 123 patients with newly diagnosed MM from August 1, 2018, to June 30, 2020, at the First Affiliated Hospital of Soochow University and Suzhou Hopes Hematology Hospital, who were eligible for VRD regimen sequential ASCT, were collected. The clinical characteristics, efficacy after induction therapy, mobilization regimen of autologous stem cells, autologous stem cell collection rate, and side effects and efficacy of ASCT were retrospectively analyzed. Results: Of the 123 patients, 67 were males. The median patient age was 56 (range: 31-70) years. Patients with IgG, IgA, IgD, and light-chain types accounted for 47.2% (58/123), 23.6% (29/123), 3.2% (4/123), and 26.0% (32/123) of patients, respectively. In addition, 25.2% (31/123) of patients had renal insufficiency (creatinine clearance rate<40 ml/min). Patients with Revised-International Staging System (R-ISS) Ⅲ accounted for 18.2% (22/121) of patients. After induction therapy, the rates of partial response and above, very-good partial response (VGPR) and above, and complete response (CR)+stringent CR were 82.1% (101/123), 75.6% (93/123), and 45.5% (56/123), respectively. Overall, 90.3% (84/93) of patients were mobilized with cyclophosphamide+granulocyte colony-stimulating factor (G-CSF) and 8 patients with G-CSF or G-CSF+plerixafor due to creatinine clearance rate<30 ml/min and one of them was mobilized with DECP (cisplatin, etoposide, cyclophosphamide and dexamethasone)+G-CSF for progressive disease. The rate of autologous stem cell collection (CD34⁺cells≥2×10⁶/kg) after four courses of VRD regimen was 89.1% (82/92), and the rate of collection (CD34⁺cells≥5×10⁶/kg) was 56.5% (52/92). Seventy-seven patients treated with the VRD regimen sequential ASCT. All patients had grade 4 neutropenia and thrombocytopenia. Among the nonhematologic adverse events during ASCT, the highest incidence was observed for gastrointestinal reactions (76.6%, 59/77), followed by oral mucositis (46.8%, 36/77), elevated aminotransferases (44.2%, 34/77), fever (37.7%, 29/77), infection (16.9%, 13/77) and heart-related adverse events (11.7%, 9/77). Among the adverse events, grade 3 adverse events included nausea (6.5%, 5/77), oral mucositis (5.2%, 4/77), vomiting (3.9%, 3/77), infection (2.6%, 2/77), elevated blood pressure after infusion (2.6%, 2/77), elevated alanine transaminase (1.3%, 1/77), and perianal mucositis (1.3%, 1/77); there were no grade 4 or above nonhematologic adverse events. The proportion of patients who achieved VGPR and above after VRD sequential ASCT was 100% (75/75), and the proportion of patients who were minimal residual disease-negative (<10^-4 level) was 82.7% (62/75). Conclusion: In patients aged 70 and below with newly diagnosed MM treated with VRD induction therapy, the collection rate of autologous stem cells was good, and good efficacy and tolerability were noted after follow-up ASCT.

Sampled Memory-Event-Triggered Fuzzy Load Frequency Control for Wind Power Systems Subject to Outliers and Transmission Delays

This study is devoted to event-triggered fuzzy load frequency control (LFC) for wind power systems (WPSs) with measurement outliers and transmission delays. Due to the integration of wind turbine (WT) with nonlinearity, the T-S fuzzy model of WPS is established for stability analysis and controller design. To mitigate the network burden, a new sampled memory-event-triggered mechanism (SMETM) related to historical system information is presented. It has the following two merits: 1) the utilization of continuous memory outputs over a given interval is useful to reduce the information loss in the period of samples and the redundant triggering events induced by disturbances and noises and 2) an extra upper constraint is added in the triggering condition to generate a new event only when the error signal belongs to a bounded range, thus, the false events caused by measurement outliers can be differentiated out and then be dropped. By representing the memory signal with transmission delay as a time-varying distributed delay term, a T-S fuzzy time-varying distributed delay system is built up to model the H_∞ LFC WPS. With the help of the Lyapunov method and the integral inequality relying on distributed delay, some criteria are derived to solve the triggering matrix and fuzzy controllers. Finally, the merits of the proposed SMETM are tested by simulation results.

Event-based formation control for multiple unmanned aerial vehicles under directed topology

This paper focuses on the problem of formation control for multiple unmanned aerial vehicles (UAV) subject to cyber attacks by a novel event-triggered communication scheme. An average method is introduced to design the triggering condition of this communication scheme, by which the amount of wrong triggering events caused by the sudden change of system states is greatly decreased, thereby saving a great deal of network bandwidth and reducing network congestion. Considering cyber attacks, a new event-based formation control strategy is developed for multi-UAV systems under directed topology by utilizing a control compensation approach. Sufficient conditions for the multi-UAV system to achieve the desired formation are acquired. Finally, a simulation example is undertaken to demonstrate the effectiveness of the theoretical results.

Utilizing Epigenetic Modification as a Reactive Handle To Regulate RNA Function and CRISPR-Based Gene Regulation

The current methods to control RNA functions in living conditions are limited. The new RNA-controlling strategy presented in this study involves utilizing 5-formylcytidine (f5C)-directed base manipulation. This study shows that malononitrile and pyridine boranes can effectively manipulate the folding, small molecule binding, and enzyme recognition of f5C-bearing RNAs. We further demonstrate the efficiency of f5C-directed reactions in controlling two different clustered regularly interspaced short palindromic repeat (CRISPR) systems. Although further studies are needed to optimize the efficiency of these reactions in vivo, this small molecule-based approach presents exciting new opportunities for regulating CRISPR-based gene expression and other applications.

[Clinical analysis of 226 cases of deviated nose with deviated nasal septum treated by endoscopic assisted functional rhinoplasty]

Objective: To explore the method and effect of endoscopic assisted functional rhinoplasty for patients with deviated nose and deviated nasal septum, which achieve correction of nasal morphology and ventilation dysfunction. Methods: The clinical data of 226 patients with deviated nose and deviated nasal septum from June 2009 to February 2022 who were treated by endoscopic assisted functional rhinoplasty in the Affiliated Hospital of Qingdao University were analyzed retrospectively. There were 174 males and 52 females, with the age ranging from 7 to 67 years old. The effect was evaluated by subjective and objective evaluation methods. SPSS 27.0 software was used for statistical analysis. Results: All patients were followed up for 6 to 24 months, 174 cases were cured (174/226, 76.99%), 52 cases were effective (52/226, 23.01%), and the total effective rate was 100% (226/226). The difference between preoperative and postoperative facial appearance deviation was statistically significant ((6.84±2.25)mm vs (1.82±1.05)mm, t=38.94, P<0.001), and the nasal ventilation function of all patients was improved. Conclusions: Endoscopic assisted functional rhinoplasty for the patients with deviated nose combined with deviated nasal septum has the advantages of clear surgical field, fewer complications, and good result. It can achieve the purpose of simultaneous correction of nasal and ventilation dysfunction, which is recommended for popularizing in clinical application.

High Electron Mobility Hot-Exciton Induced Delayed Fluorescent Organic Semiconductors

The development of high mobility emissive organic semiconductors is of great significance for the fabrication of miniaturized optoelectronic devices, such as organic light emitting transistors. However, great challenge exists in designing key materials, especially those who integrates triplet exciton utilization ability. Herein, dinaphthylanthracene diimides (DNADIs), with 2,6-extended anthracene donor, and 3'- or 4'-substituted naphthalene monoimide acceptors were designed and synthesized. By introducing acceptor-donor-acceptor structure, both materials show high electron mobility. Moreover, by fine-tuning of substitution sites, good integration with high solid state photoluminescence quantum yield of 26 %, high electron mobility of 0.02 cm²  V^-1  s^-1 , and the feature of hot-exciton induced delayed fluorescence were obtained in 4'-DNADI. This work opens a new avenue for developing high electron mobility emissive organic semiconductors with efficient utilization of triplet excitons.

Leveraging molecular structure and bioactivity with chemical language models for de novo drug design

Generative chemical language models (CLMs) can be used for de novo molecular structure generation by learning from a textual representation of molecules. Here, we show that hybrid CLMs can additionally leverage the bioactivity information available for the training compounds. To computationally design ligands of phosphoinositide 3-kinase gamma (PI3Kγ), a collection of virtual molecules was created with a generative CLM. This virtual compound library was refined using a CLM-based classifier for bioactivity prediction. This second hybrid CLM was pretrained with patented molecular structures and fine-tuned with known PI3Kγ ligands. Several of the computer-generated molecular designs were commercially available, enabling fast prescreening and preliminary experimental validation. A new PI3Kγ ligand with sub-micromolar activity was identified, highlighting the method's scaffold-hopping potential. Chemical synthesis and biochemical testing of two of the top-ranked de novo designed molecules and their derivatives corroborated the model's ability to generate PI3Kγ ligands with medium to low nanomolar activity for hit-to-lead expansion. The most potent compounds led to pronounced inhibition of PI3K-dependent Akt phosphorylation in a medulloblastoma cell model, demonstrating efficacy of PI3Kγ ligands in PI3K/Akt pathway repression in human tumor cells. The results positively advocate hybrid CLMs for virtual compound screening and activity-focused molecular design.

Study of the N=32 and N=34 Shell Gap for Ti and V by the First High-Precision Multireflection Time-of-Flight Mass Measurements at BigRIPS-SLOWRI

The atomic masses of ^{55}Sc, ^{56,58}Ti, and ^{56-59}V have been determined using the high-precision multireflection time-of-flight technique. The radioisotopes have been produced at RIKEN's Radioactive Isotope Beam Factory (RIBF) and delivered to the novel designed gas cell and multireflection system, which has been recently commissioned downstream of the ZeroDegree spectrometer following the BigRIPS separator. For ^{56,58}Ti and ^{56-59}V, the mass uncertainties have been reduced down to the order of 10 keV, shedding new light on the N=34 shell effect in Ti and V isotopes by the first high-precision mass measurements of the critical species ^{58}Ti and ^{59}V. With the new precision achieved, we reveal the nonexistence of the N=34 empirical two-neutron shell gaps for Ti and V, and the enhanced energy gap above the occupied νp_{3/2} orbit is identified as a feature unique to Ca. We perform new Monte Carlo shell model calculations including the νd_{5/2} and νg_{9/2} orbits and compare the results with conventional shell model calculations, which exclude the νg_{9/2} and the νd_{5/2} orbits. The comparison indicates that the shell gap reduction in Ti is related to a partial occupation of the higher orbitals for the outer two valence neutrons at N=34.

Biochar-amended composting of lincomycin fermentation dregs promoted microbial metabolism and reduced antibiotic resistance genes

Improper disposal of antibiotic fermentation dregs poses a risk of releasing antibiotics and antibiotic resistant bacteria to the environment. Therefore, this study evaluated the effects of biochar addition to lincomycin fermentation dregs (LFDs) composting. Biochar increased compost temperature and enhanced organic matter decomposition and residual antibiotics removal. Moreover, a 1.5- to 17.0-fold reduction in antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) was observed. Adding biochar also reduced the abundances of persistent ARGs hosts (e.g., Streptomyces, Pseudomonas) and ARG-related metabolic pathways and genes (e.g., ATP-binding cassette type-2 transport, signal transduction and multidrug efflux pump genes). By contrast, compost decomposition improved due to enhanced metabolism of carbohydrates and amino acids. Overall, adding biochar into LFDs compost reduced the proliferation of ARGs and enhanced microbial community metabolism. These results demonstrate that adding biochar to LFDs compost is a simple and efficient way to decrease risks associated with LFDs composting.

[Preliminary exploration of the metabolic profile and metabolic pathways in newly diagnosed multiple myeloma]

Objective: To explore the metabolite profile and metabolic pathways of newly diagnosed multiple myeloma (MM). Methods: Gas chromatography-mass spectrometry (GC-MS) was employed for the high-throughput detection and identification of serum samples from 55 patients with MM and 37 healthy controls matched for age and sex from 2016 to 2017 collected at the First Affiliated Hospital of Soochow University. The relative standard deviation (RSD) of quality control (QC) samples was employed to validate the reproducibility of GC-MS approach. The differential metabolites between patients with MM and healthy controls were detected by partial least squares discrimination analysis (PLS-DA), and t-test with false discovery rate (FDR) correction. Metabolomics pathway analysis (MetPA) was employed to construct metabolic pathways. Results: There were 55 MM patients, including 34 males and 21 females. The median age was 60 years old (42-73 years old). There were 30 cases of IgG type, 9 cases of IgA type, 1 case of IgM type, 2 cases of non-secreted type, 1 case of double clone type and 12 cases of light chain type, including 3 cases of kappa light chain type and 9 cases of lambda light chain type. The result of QC sample test showed that the proportion of compounds with the RSD of the relative content of metabolites < 15% was 70.21% obtained by the reproducibility of GC-MS experimental data, which implied that the experimental data were reliable. A total of 17 metabolites were screened differently with the healthy control group, including myristic acid, hydroxyproline, cysteine, palmitic acid, L-leucine, stearic acid, methionine, phenylalanine, glycerin, serine, isoleucine, tyrosine, valine, citric acid, inositol, threonine, and oxalic acid (VIP>1, P<0.05). Metabolic pathway analysis suggested that metabolic disorders in MM patients comprised mainly phenylalanine metabolism, glyoxylic acid and dicarboxylic acid metabolism, phosphoinositide metabolism, cysteine and methionine metabolism, glycerolipid metabolism, glycine, serine, and threonine metabolism. Conclusion: Compared with normal people, patients with newly diagnosed MM have obvious differences in metabolic profiles and metabolic pathways.

The molecular basis of the dichotomous functionality of MAP4K4 in proliferation and cell motility control in cancer

The finely tuned integration of intra- and extracellular cues by components of the mitogen-activated protein kinase (MAPK) signaling pathways controls the mutually exclusive phenotypic manifestations of uncontrolled growth and tumor cell dissemination. The Ser/Thr kinase MAP4K4 is an upstream integrator of extracellular cues involved in both proliferation and cell motility control. Initially identified as an activator of the c-Jun N-terminal kinase (JNK), the discovery of diverse functions and additional effectors of MAP4K4 beyond JNK signaling has considerably broadened our understanding of this complex kinase. The implication of MAP4K4 in the regulation of cytoskeleton dynamics and cell motility provided essential insights into its role as a pro-metastatic kinase in cancer. However, the more recently revealed role of MAP4K4 as an activator of the Hippo tumor suppressor pathway has complicated the understanding of MAP4K4 as an oncogenic driver kinase. To develop a better understanding of the diverse functions of MAP4K4 and their potential significance in oncogenesis and tumor progression, we have collected and assessed the current evidence of MAP4K4 implication in molecular mechanisms that control proliferation and promote cell motility. A better understanding of these mechanisms is particularly relevant in the brain, where MAP4K4 is highly expressed and under pathological conditions either drives neuronal cell death in neurodegenerative diseases or cell dissemination in malignant tumors. We review established effectors and present novel interactors of MAP4K4, which offer mechanistic insights into MAP4K4 function and may inspire novel intervention strategies. We discuss possible implications of novel interactors in tumor growth and dissemination and evaluate potential therapeutic strategies to selectively repress pro-oncogenic functions of MAP4K4.

A resource-aware control approach to vehicle platoons under false data injection attacks

Wireless vehicle-to-vehicle communication brings inevitable imperfections. This work simultaneously addresses the resource utilization and security issues for a vehicle platoon. Inspired by the modeling of denial of service attacks, a novel queuing model is constructed to depict false data injection attacks. A switched event-triggered mechanism is proposed to optimize network resources. The transmission rate can be actively reduced when the system is under malicious attacks. Then, a unified error system is established, where string stability is interpreted as global exponential stability. By using a proper Lyapunov function, a co-design approach is developed for closed-loop controllers and event-triggering parameters, with which the vehicle platoon can maintain a small safety distance and resist the negative impacts of cyber attacks. Finally, the proposed methods are verified by a virtual vehicle platoon.