Connectome-based predictive modeling of Internet addiction symptomatology

Internet addiction symptomatology (IAS) is characterized by persistent and involuntary patterns of compulsive Internet use, leading to significant impairments in both physical and mental well-being. Here, a connectome-based predictive modeling approach was applied to decode IAS from whole-brain resting-state functional connectivity in healthy population. The findings showed that IAS could be predicted by the functional connectivity between prefrontal cortex with the cerebellum and limbic lobe and connections of the occipital lobe with the limbic lobe and insula lobe. The identified edges associated with IAS exhibit generalizability in predicting IAS within an independent sample. Furthermore, we found that the unique contributing network, which predicted IAS in contrast to the prediction networks of alcohol use disorder symptomatology (the range of symptoms and behaviors associated with alcohol use disorder), prominently comprised connections involving the occipital lobe and other lobes. The current data-driven approach provides the first evidence of the predictive brain features of IAS based on the organization of intrinsic brain networks, thus advancing our understanding of the neurobiological basis of Internet addiction disorder (IAD) susceptibility, and may have implications for the timely intervention of people potentially at risk of IAD.

Saturation of Fishbone Instability by Self-Generated Zonal Flows in Tokamak Plasmas

Gyrokinetic simulations of the fishbone instability in DIII-D tokamak plasmas find that self-generated zonal flows can dominate the nonlinear saturation by preventing coherent structures from persisting or drifting in the energetic particle phase space when the mode frequency down-chirps. Results from the simulation with zonal flows agree quantitatively, for the first time, with experimental measurements of the fishbone saturation amplitude and energetic particle transport. Moreover, the fishbone-induced zonal flows are likely responsible for the formation of an internal transport barrier that was observed after fishbone bursts in this DIII-D experiment. Finally, gyrokinetic simulations of a related ITER baseline scenario show that the fishbone induces insignificant energetic particle redistribution and may enable high performance scenarios in ITER burning plasma experiments.

Sustainable digital transformation path for manufacturing outwards foreign direct investment firms: Gradual or leapfrogging

Digital transformation plays an important role in improving the efficiency of production of enterprises and can provide strong support for green and sustainable development. Compared with domestic enterprises, outward foreign direct investment (OFDI) enterprises have greater access to advanced digital technology. This paper aims to analyze the path selection of green and sustainable production for the digital transformation of manufacturing outward foreign direct investment (OFDI) companies, whether gradual or leapfrogging. However, there is a lack of systemic game mechanisms and numerical simulation methods for heterogeneous enterprises. Based on the analysis of reverse technology spillover intensity of outward foreign direct investment (OFDI) and differences in the absorptive capacity of enterprises, we have proposed the evolutionary game model for different path selection of digital transformation of manufacturing enterprises, due to heterogeneous enterprises under different spillover degrees with numerical analysis methods. The research results show that: (i) Under low reverse technology spillover intensity, all enterprises evolve to a gradual transformation path, and enterprises with weaker absorptive capacity converge faster; (ii) There is a certain threshold for reverse technology spillover. When reverse technology spillover intensity exceeds the threshold, enterprises with stronger absorptive capacity converge to a leapfrog transformation path, but enterprises with weak absorptive capacity converge to a gradual transformation path; (iii) With high reverse technology spillover intensity, all enterprises evolve toward a leapfrog transformation path, and faster convergence happens to enterprises with higher absorptive capacity. The evolutionary game path of digital transformation in manufacturing enterprises is illustrated in Fig. 1.

Asymmetric Triphenylethylene-Based Hole Transporting Materials for Highly Efficient Perovskite Solar Cells

Molecular hole-transporting materials (HTMs) having triphenylethylene central core were designed, synthesized, and employed in perovskite solar cell (PSC) devices. The synthesized HTM derivatives were obtained in a two- or three-step synthetic procedure, and their characteristics were analyzed by various thermoanalytical, optical, photophysical, and photovoltaic techniques. The most efficient PSC device recorded a 23.43% power conversion efficiency. Furthermore, the longevity of the device employing V1509 HTM surpassed that of PSC with state-of-art spiro-OMeTAD as the reference HTM.

Polyurethane with β-Selenocarbonyl Structure Enabling the Combination of Plastic Degradation and Waste Upcycling

Degradable polymers offer a promising solution to mitigate global plastic pollution, but the degraded products often suffer from diminished value. Upcycling is a more sustainable approach to upgrade polymer waste into value-added products. Herein, we report a β-selenocarbonyl-containing polyurethane (SePU), which can be directly degraded under mild conditions into valuable selenium fertilizers for selenium-rich vegetable cultivation globally, enabling both plastic degradation and waste upcycling. Under oxidation condition, this polymer can be easily and selectively degraded via selenoxide elimination reaction from mixed plastic waste. The degraded product can serve as effective selenium fertilizers to increase selenium content in radish and pak choi. The SePU exhibits excellent mechanical properties. Additionally, we observed the formation of spherulites-like selenium particles within the materials during degradation for the first time. Our research offers a successful application of selenoxide elimination reaction in the field of plastic degradation for the first time, endowing plastics with both degradability and high reusable value. This strategy provides a promising solution to reduce pollution and improve economy and sustainability of plastics.

Search for Scalar Leptoquarks Produced via τ-Lepton-Quark Scattering in pp Collisions at sqrt[s]=13 TeV

The first search for scalar leptoquarks produced in τ-lepton-quark collisions is presented. It is based on a set of proton-proton collision data recorded with the CMS detector at the LHC at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138  fb^{-1}. The reconstructed final state consists of a jet, significant missing transverse momentum, and a τ lepton reconstructed through its hadronic or leptonic decays. Limits are set on the product of the leptoquark production cross section and branching fraction and interpreted as exclusions in the plane of the leptoquark mass and the leptoquark-τ-quark coupling strength.

A dual-receptor T-cell platform with Ab-TCR and costimulatory receptor achieves specificity and potency against AML

ABSTRACT

Chimeric antigen receptor T-cell (CAR T) therapy has produced remarkable clinical responses in B-cell neoplasms. However, many challenges limit this class of agents for the treatment of other cancer types, in particular the lack of tumor-selective antigens for solid tumors and other hematological malignancies, such as acute myeloid leukemia (AML), which may be addressed without significant risk of severe toxicities while providing sufficient abundance for efficient tumor suppression. One approach to overcome this hurdle is dual targeting by an antibody-T-cell receptor (AbTCR) and a chimeric costimulatory signaling receptor (CSR) to 2 different antigens, in which both antigens are found together on the cancer cells but not together on normal cells. To explore this proof of concept in AML, we engineered a new T-cell format targeting Wilms tumor 1 protein (WT1) and CD33; both are highly expressed on most AML cells. Using an AbTCR comprising a newly developed TCR-mimic monoclonal antibody against the WT1 RMFPNAPYL (RMF) epitope/HLA-A2 complex, ESK2, and a secondary CSR comprising a single-chain variable fragment directed to CD33 linked to a truncated CD28 costimulatory fragment, this unique platform confers specific T-cell cytotoxicity to the AML cells while sparing healthy hematopoietic cells, including CD33+ myelomonocytic normal cells. These data suggest that this new platform, named AbTCR-CSR, through the combination of a AbTCR CAR and CSR could be an effective strategy to reduce toxicity and improve specificity and clinical outcomes in adoptive T-cell therapy in AML.

UHPLC-MS/MS Assay for Quantification of Legubicin, a Novel Doxorubicin-Based Legumain-Activated Prodrug, and Its Application to Pharmacokinetic and Tissue Distribution Studies

Legubicin, a novel prodrug based on doxorubicin, has both albumin-binding and legumain-activating properties. The aim of this study was to develop and validate a UHPLC-MS/MS method for investigating the in vivo pharmacokinetics and tissue distribution profiles of legubicin in rats and tumor-bearing mice following intravenous administration, and to compare this prodrug with the positive control drug doxorubicin. The study employed a UHLC-MS/MS method to determine the levels of albumin-bound of legubicin and two metabolites (free Leu-DOX and DOX) in plasma, tumor, and tissue samples. This method was validated for good selectivity, high sensitivity, excellent extraction recovery, and short run time. The results showed that legubicin was present in the circulation in vivo mainly in a protein-bound form with larger AUC values and lower clearance and distribution, and essentially released small amounts of doxorubicin. Compared to administration of equimolar doses of doxorubicin, legubicin showed increased exposure of the active drug in the tumor and decreased the level of the active drug in the heart and kidney. This study provides valuable information on the pharmacokinetics and tissue distribution of legubicin, implicating its potential as a novel and effective drug candidate for anti-cancer therapies.

Dual-Mode Separation and SERS Detection of Carbaryl with PA-6/AuNRs@ZIF-8 Films

Appropriate separation and enrichment steps can enhance the performance of SERS assays. For rapid, in-situ detection of carbaryl, a novel PA-6/AuNRs@ZIF-8 film that can be applied to dual-mode separation and SERS detection, has been developed. In the film, PA-6 was used as a TLC substrate for the initial separation of the substance to be measured. ZIF-8 provides chemical enhancement in SERS as well as enrichment and secondary separation of the analytes. Utilizing this film, we have successfully implemented a TLC-SERS rapid detection scheme, resulting in a detection limit for carbaryl as low as 1 × 10-9 M in lake water in 15 min, which is significantly lower than existing standards. Additionally, the manufacturing cost of one PA-6/AuNRs@ZIF-8 film can be kept within the range of $0.20-$0.40 economically, presenting substantial financial advantages. The method is highly promising for pesticide detection as well as forensic in-situ testing.

The Application of CT Radiomics in the Diagnosis of Vein Wall Invasion in Patients With Renal Cell Carcinoma Combined With Tumor Thrombus

OBJECTIVE

The objective of this study was to explore the application of radiomics combined with machine learning to establish different models to assist in the diagnosis of venous wall invasion in patients with renal cell carcinoma and venous tumor thrombus and to evaluate the diagnostic efficacy.

MATERIALS AND METHODS

We retrospectively reviewed the data of 169 patients in Peking University Third Hospital from March 2015 to January 21, who was diagnosed as renal mass with venous invasion. According to the intraoperative findings, 111 patients were classified to the venous wall invasion group and 58 cases in the non-invasion group. ITK-snap was used for tumor segmentation and PyRadiomics 3.0.1 package was used for feature extraction. A total of 1598 features could be extracted from each CT image. The patients were divided into training set and testing set by time. The elastic-net regression with 4-fold cross-validation was used as a dimension-reduction method. After feature selection, a support vector machines (SVM) model, a logistic regression (LR) model, and an extra trees (ET) model were established. Then the sensitivity, specificity, accuracy, and the area under the curve (AUC) were calculated to evaluate the diagnostic performance of each model on the testing set.

RESULTS

Patients before September 2019 were divided into the training set, of which 88 patients were in the invasion group and 42 patients were in the non-invasion group. The others were in the testing set, of which 32 patients were in the invasion group and 16 patients were in the non-invasion group. A total of 34 radiomics features were obtained by the elastic-net regression. The SVM model had an AUC value of 0.641 (95% CI, 0.463-0.769), a sensitivity of 1.000, and a specificity of 0.062. The LR model had an AUC value of 0.769 (95% CI, 0.620-0.877), a sensitivity of 0.913, and a specificity of 0.312. The ET model had an AUC value of 0.853 (95% CI, 0.734-0.948), a sensitivity of 0.783, and a specificity of 0.812. Among the 3 models, the ET model had the best diagnostic effect, with a good balance of sensitivity and specificity. And the higher the tumor thrombus grade, the better the diagnostic efficacy of the ET model. In inferior vena cava tumor thrombus, the sensitivity, specificity, accuracy, and AUC of ET model can be improved to 0.889, 0.800, 0.857, 0.878 (95% CI, 0.745-1.000).

CONCLUSION

Machine learning combined with radiomics method can effectively identify whether venous wall was invaded by tumor thrombus and has high diagnostic efficacy with an AUC of 0.853 (95% CI, 0.734-0.948).

Elevated CO2 increases soil redox potential by promoting root radial oxygen loss in paddy field

Soil redox potential (Eh) plays an important role in the biogeochemical cycling of soil nutrients. Whereas its effect soil process and nutrients' availability under elevated atmospheric CO2 concentration and warming has seldom been investigated. Thus, in this study, a field experiment was used to elucidate the effect of elevated CO2 concentration and warming on soil Eh, redox-sensitive elements and root radial oxygen loss (ROL). We hypothesized elevated CO2 and warming could alter soil Eh by promoting or inhibiting ROL. We found that soil Eh in the rhizosphere was significantly higher than that of non-rhizosphere. Elevated CO2 enhanced soil Eh by 11.5%, which corresponded to a significant decrease in soil Fe2+ and Mn2+concentration. Under elevated CO2, the concentration of Fe2+ and Mn2+ decreased by 14.7% and 13.7%, respectively. We also found that elevated CO2 altered rice root aerenchyma structure and promoted rice root ROL. Under elevated CO2, rice root ROL increased by 79.5% and 112.2% for Yangdao 6 and Changyou 5, respectively. Warming had no effect on soil Eh and rice root ROL. While warming increased the concentration of Mn2+ and SO42- by 4.9% and 19.3%, respectively. There was a significant interaction between elevated CO2 and warming on Fe2+ and Mn2+. Under elevated CO2, warming had no effect on the concentration of Fe2+ but decreased Mn2+ concentration significantly. Our study demonstrated that elevated atmospheric CO2 in the future could increase soil Eh by promoting rice root ROL, which will alter some soil nutrients' availability, such as Fe2+ and Mn2+.

Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes

MOTIVATION

The human microbiome may impact the effectiveness of drugs by modulating their activities and toxicities. Predicting candidate microbes for drugs can facilitate the exploration of the therapeutic effects of drugs. Most recent methods concentrate on constructing of the prediction models based on graph reasoning. They fail to sufficiently exploit the topology and position information, the heterogeneity of multiple types of nodes and connections, and the long-distance correlations among nodes in microbe-drug heterogeneous graph.

RESULTS

We propose a new microbe-drug association prediction model, NGMDA, to encode the position and topological features of microbe (drug) nodes, and fuse the different types of features from neighbors and the whole heterogeneous graph. First, we formulate the position and topology features of microbe (drug) nodes by t-step random walks, and the features reveal the topological neighborhoods at multiple scales and the position of each node. Second, as the features of nodes are high-dimensional and sparse, we designed an embedding enhancement strategy based on supervised fully connected autoencoders to form the embeddings with representative features and the more discriminative node distributions. Third, we propose an adaptive neighbor feature fusion module, which fuses features of neighbors by the constructed position- and topology-sensitive heterogeneous graph neural networks. A novel self-attention mechanism is developed to estimate the importance of the position and topology of each neighbor to a target node. Finally, a heterogeneous graph feature fusion module is constructed to learn the long-distance correlations among the nodes in the whole heterogeneous graph by a relationship-aware graph transformer. Relationship-aware graph transformer contains the strategy for encoding the connection relationship types among the nodes, which is helpful for integrating the diverse semantics of these connections. The extensive comparison experimental results demonstrate NGMDA's superior performance over five state-of-the-art prediction methods. The ablation experiment shows the contributions of the multi-scale topology and position feature learning, the embedding enhancement strategy, the neighbor feature fusion, and the heterogeneous graph feature fusion. Case studies over three drugs further indicate that NGMDA has ability in discovering the potential drug-related microbes.

AVAILABILITY AND IMPLEMENTATION

Source codes and Supplementary Material are available at https://github.com/pingxuan-hlju/NGMDA.

Fabrication of CuFe2O4/Bi12O17Cl2 photocatalyst with intrinsic p-n junction for highly efficient bisphenol A degradation

The construction and application of novel highly efficient photocatalysts have been the focus in the field of environmental pollutant removal. In this work, a novel CuFe2O4/Bi12O17Cl2 photocatalysts were synthesized by simple hydrothermal and chemical precipitation method. The fabricated CuFe2O4/Bi12O17Cl2 composite exhibited much higher photocatalytic activity than pristine CuFe2O4 and Bi12O17Cl2 in the removal of bisphenol A (BPA) under visible-light illumination, which ascribed to the intrinsic p-n junction of CuFe2O4 and Bi12O17Cl2. The photocatalytic degradation rate of BPA on CuFe2O4/Bi12O17Cl2 with an optimized CuFe2O4 content (1.0 wt.%) reached 93.0% within 30 min. The capture experiments of active species confirmed that the hydroxyl radicals (•OH) and superoxide radicals (•O2-) played crucial roles in photocatalytic BPA degradation process. Furthermore, the possible degradation mechanism and pathways of BPA was proposed according to the detected intermediates in photocatalytic reaction process.

Effect of Particle Strength on SiCp/Al Composite Properties with Network Architecture Design

Recent works have experimentally proven that metal matrix composites (MMCs) with network architecture present improved strength-ductility match. It is envisaged that the performance of architecturally designed composites is particularly sensitive to reinforcement strength. Here, reinforcing particles with various fracture strengths were introduced in numerical models of composites with network particle distribution. The results revealed that a low particle strength (1 GPa) led to early-stage failure and brittle fracture. Nevertheless, a high particle strength (5 GPa) delayed the failure behavior and led to ductile fracture at the SiC/Al-Al macro-interface areas. Therefore, the ultimate tensile strengths (UTS) of the network SiC/Al composites increased from 290 to 385 MPa, with rising particle strength from 1 to 5 GPa. Based on the composite property, different particle fracture threshold strengths existed for homogeneous (~2.7 GPa) and network (~3.7 GPa) composites. The higher threshold strength in network composites was related to the increased stress concentration induced by network architecture. Unfortunately, the real fracture strength of the commercial SiC particle is 1-2 GPa, implying that it is possible to select a high-strength particle necessary for efficient network architecture design.

Search for Inelastic Dark Matter in Events with Two Displaced Muons and Missing Transverse Momentum in Proton-Proton Collisions at sqrt[s]=13 TeV

A search for dark matter in events with a displaced nonresonant muon pair and missing transverse momentum is presented. The analysis is performed using an integrated luminosity of 138  fb^{-1} of proton-proton (pp) collision data at a center-of-mass energy of 13 TeV produced by the LHC in 2016-2018. No significant excess over the predicted backgrounds is observed. Upper limits are set on the product of the inelastic dark matter production cross section σ(pp→A^{'}→χ_{1}χ_{2}) and the decay branching fraction B(χ_{2}→χ_{1}μ^{+}μ^{-}), where A^{'} is a dark photon and χ_{1} and χ_{2} are states in the dark sector with near mass degeneracy. This is the first dedicated collider search for inelastic dark matter.

Ku70 senses cytosolic DNA and assembles a tumor-suppressive signalosome

The innate immune response contributes to the development or attenuation of acute and chronic diseases, including cancer. Microbial DNA and mislocalized DNA from damaged host cells can activate different host responses that shape disease outcomes. Here, we show that mice and humans lacking a single allele of the DNA repair protein Ku70 had increased susceptibility to the development of intestinal cancer. Mechanistically, Ku70 translocates from the nucleus into the cytoplasm where it binds to cytosolic DNA and interacts with the GTPase Ras and the kinase Raf, forming a tripartite protein complex and docking at Rab5+Rab7+ early-late endosomes. This Ku70-Ras-Raf signalosome activates the MEK-ERK pathways, leading to impaired activation of cell cycle proteins Cdc25A and CDK1, reducing cell proliferation and tumorigenesis. We also identified the domains of Ku70, Ras, and Raf involved in activating the Ku70 signaling pathway. Therapeutics targeting components of the Ku70 signalosome could improve the treatment outcomes in cancer.

Evaluation and identification of powdery mildew-resistant genes in 137 wheat relatives

Powdery mildew is one of the most severe diseases affecting wheat yield and quality and is caused by Blumeria graminis f. sp. tritici (Bgt). Host resistance is the preferred strategy to prevent this disease. However, the narrow genetic basis of common wheat has increased the demand for diversified germplasm resources against powdery mildew. Wheat relatives, especially the secondary gene pool of common wheat, are important gene donors in the genetic improvement of common wheat because of its abundant genetic variation and close kinship with wheat. In this study, a series of 137 wheat relatives, including 53 Triticum monococcum L. (2n = 2x = 14, AA), 6 T. urartu Thumanjan ex Gandilyan (2n = 2x = 14, AA), 9 T. timopheevii Zhuk. (2n = 4x = 28, AAGG), 66 T. aestivum subsp. spelta (2n = 6x = 42, AABBDD), and 3 Aegilops speltoides (2n = 2x = 14, SS) were systematically evaluated for their powdery mildew resistance and composition of Pm genes. Out of 137 (60.58%) accessions, 83 were resistant to Bgt isolate E09 at the seedling stage, and 116 of 137 (84.67%) wheat relatives were resistant to the mixture of Bgt isolates at the adult stage. This indicates that these accessions show a high level of resistance to powdery mildew. Some 31 markers for 23 known Pm genes were used to test these 137 accessions, and, in the results, only Pm2, Pm4, Pm6, Pm58, and Pm68 were detected. Among them, three Pm4 alleles (Pm4a, Pm4b, and Pm4f) were identified in 4 T. subsp. spelta accessions. q-RT PCR further confirmed that Pm4 alleles played a role in disease resistance in these four accessions. The phylogenetic tree showed that the kinship of Pm4 was close to Pm24 and Sr62. This study not only provides reference information and valuable germplasm resources for breeding new wheat varieties with disease resistance but also lays a foundation for enriching the genetic basis of wheat resistance to powdery mildew.

Discovery of Trifluorobutene Amide Derivatives as Potential Nematicides: Design, Synthesis, Nematicidal Activity Evaluation, SAR, and Mode of Action Study

Plant-parasitic nematodes are one of the major threats to crop protection. However, only limited nematicides are currently available and are confronted with a growing resistance problem, which necessitates the development of novel nematicides. In this study, a series of trifluorobutene amide derivatives was synthesized through the strategy of amide bond reversal, and their nematicidal activity against Meloidogyne incognita was evaluated. The bioassay showed that compounds C2, C10, and C18 and some analogues thereof exhibited good nematicidal activity. Among them, the derivatives of compound C2 containing a benzene ring [C26 (R = 2-CH3) and C33 (R = 2-Cl)] exhibited excellent bioactivity against M. incognita in vitro. The LC50/72h values reached 14.13 and 14.71 mg·L-1, respectively. Moreover, analogues of compounds C10 and C18 containing a thiophene ring [C43 (R = 5-CH3), C44 (R = 4-CH3), and C50 (R = 5-Cl)] exhibited significant bioactivity against M. incognita in vivo with inhibition rates of 68.8, 65.5, and 69.8% at 2.5 mg·L-1 in a matrix, respectively. Meanwhile, C44 and C50 also showed excellent control effects against M. incognita in both cups and microplots. The structure-activity relationship (SAR) of synthesized compounds was discussed in detail. Comparative molecular field analysis (CoMFA) was also conducted to develop the SAR profile. The preliminary mode of action investigation showed that compound C33 exhibited strong inhibition on egg hatching, motility, feeding behavior, and growth of Caenorhabditis elegans. At the same time, the impact of active compounds on biochemical indicators related to oxidative stress showed that compound C33 influenced the production of ROS (reactive oxygen species), and the accumulation of lipofuscin and lipids on C. elegans.

First Measurement of the Decay Asymmetry in the Pure W-Boson-Exchange Decay Λ_{c}^{+}→Ξ^{0}K^{+}

Based on 4.4  fb^{-1} of e^{+}e^{-} annihilation data collected at the center-of-mass energies between 4.60 and 4.70 GeV with the BESIII detector at the BEPCII collider, the pure W-boson-exchange decay Λ_{c}^{+}→Ξ^{0}K^{+} is studied with a full angular analysis. The corresponding decay asymmetry is measured for the first time to be α_{Ξ^{0}K^{+}}=0.01±0.16(stat)±0.03(syst). This result reflects the noninterference effect between the S- and P-wave amplitudes. The phase shift between S- and P-wave amplitudes has two solutions, which are δ_{p}-δ_{s}=-1.55±0.25(stat)±0.05(syst)  rad or 1.59±0.25(stat)±0.05(syst)  rad.

Deficiency of FRMD5 results in neurodevelopmental dysfunction and autistic-like behavior in mice

The pathophysiology of autism spectrum disorders (ASDs) is causally linked to postsynaptic scaffolding proteins, as evidenced by numerous large-scale genomic studies [1, 2] and in vitro and in vivo neurobiological studies of mutations in animal models [3, 4]. However, due to the distinct phenotypic and genetic heterogeneity observed in ASD patients, individual mutation genes account for only a small proportion (<2%) of cases [1, 5]. Recently, a human genetic study revealed a correlation between de novo variants in FERM domain-containing-5 (FRMD5) and neurodevelopmental abnormalities [6]. In this study, we demonstrate that deficiency of the scaffolding protein FRMD5 leads to neurodevelopmental dysfunction and ASD-like behavior in mice. FRMD5 deficiency results in morphological abnormalities in neurons and synaptic dysfunction in mice. Frmd5-deficient mice display learning and memory dysfunction, impaired social function, and increased repetitive stereotyped behavior. Mechanistically, tandem mass tag (TMT)-labeled quantitative proteomics revealed that FRMD5 deletion affects the distribution of synaptic proteins involved in the pathological process of ASD. Collectively, our findings delineate the critical role of FRMD5 in neurodevelopment and ASD pathophysiology, suggesting potential therapeutic implications for the treatment of ASD.

Stable, narrow-linewidth laser system with a broad frequency tunability and a fast switching time

For a Rydberg atom-based sensor to change its sensing frequency, the wavelength of the Rydberg state excitation laser must be altered. The wavelength shifts required can be on the order of 10 nm. A fast-tunable narrow-linewidth laser with broadband tuning capability is required. Here, we present a demonstration of a laser system that can rapidly switch a coupling laser as much as 8 nm in less than 50 μs. The laser system comprises a frequency-stabilized continuous wave laser and an electro-optic frequency comb. A filter enables selection of individual comb lines. A high-speed electro-optic modulator is used to tune the selected comb line to a specific frequency, i.e., an atomic transition. Through Rydberg atom-based sensing experiments, we demonstrate frequency hopping between two Rydberg states and a fast switching time of 400 μs, which we show can be reduced to ∼50 μs with a ping-pong scheme. If updating the RF frequency is not required during frequency hopping, a 200 ns switching time can be achieved. These results showcase the potential of the laser system for advanced Rydberg atom-based radio frequency sensing applications, like communications and radar.

Suffering and adjustment: a grounded theory of the process of coping with financial toxicity among young women with breast cancer

PURPOSE

To explore the process of coping with financial toxicity among young women with breast cancer and formulate a grounded theory that serves as a foundation for creating intervention strategies aimed at supporting cancer survivors.

METHODS

A qualitative study using the Corbin and Strauss variant of grounded theory. A series of in-depth interviews were carried out with young women with breast cancer (n = 29) using the theoretical sampling method. We analyzed data by coding core categories in the patients' coping processes and developing theory around these categories. Data collection and analysis were performed simultaneously.

RESULTS

A substantial theory of the process of coping with financial toxicity among young female breast cancer survivors was constructed. Two core concepts, suffering and adjustment, were identified. Young women with breast cancer suffered from financial toxicity, which was related to risk factors, coping resources, and unmet needs. To overcome financial toxicity, young women with breast cancer adjusted by reshaping consumption concept, re-dividing of family functions, re-planning of occupation career, and rebuilding life confidence.

CONCLUSION

This qualitative study constructed a theory delineating the coping strategies employed by young women with breast cancer in response to financial toxicity, offering profound insights into the intricacies of cancer-related financial toxicity. Identifying risk factors, enhancing coping resources, and meeting unmet needs would be helpful to patients' adjustment to financial stress.

Luminosity determination using Z boson production at the CMS experiment

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton-proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13Te V . Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20pb - 1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z  bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.

Measurement of the production cross section for a W boson in association with a charm quark in proton-proton collisions at s=13TeV

The strange quark content of the proton is probed through the measurement of the production cross section for a W boson and a charm (c) quark in proton-proton collisions at a center-of-mass energy of 13Te V . The analysis uses a data sample corresponding to a total integrated luminosity of 138fb - 1 collected with the CMS detector at the LHC. The W bosons are identified through their leptonic decays to an electron or a muon, and a neutrino. Charm jets are tagged using the presence of a muon or a secondary vertex inside the jet. The W + c production cross section and the cross section ratio R c ± = σ ( W + + c ¯ ) / σ ( W - + c ) are measured inclusively and differentially as functions of the transverse momentum and the pseudorapidity of the lepton originating from the W boson decay. The precision of the measurements is improved with respect to previous studies, reaching 1% in R c ± = 0.950 ± 0.005 (stat) ± 0.010 (syst) . The measurements are compared with theoretical predictions up to next-to-next-to-leading order in perturbative quantum chromodynamics.

Establishment of a prognostic risk prediction model incorporating disulfidptosis-related lncRNA for patients with prostate cancer

PURPOSE

Prostate cancer (PCa) is one of the major tumor diseases that threaten men's health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two.

METHODS

Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted.

RESULTS

The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue.

CONCLUSIONS

A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.