Association of serum uric acid with all-cause and cardiovascular mortality in obstructive sleep apnea

The study investigated the association between Serum Uric Acid (SUA) levels and all-cause as well as cardiovascular mortality in patients with Obstructive Sleep Apnea (OSA). This prospective cohort study enrolled participants with OSA from four cycles of the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2008, and 2015-2018. A weighted Cox proportional hazards model was used to assess adjusted hazard ratios (aHRs) and their corresponding 95% confidence intervals (CI) for all-cause and cardiovascular mortality. Additionally, multivariable logistic regression and restricted cubic splines (RCS) models were employed to examine nonlinear relationships between SUA and all-cause and cardiovascular mortality. Among the 5,584 OSA participants included in the study, covering the four NHANES cycles and with a median follow-up of 4.333 years, a total of 537 deaths were observed, including 108 deaths attributed to cardiovascular disease. Comparing the fourth quartile (Q4) of uric acid levels, both the fifth quartile (Q5) (aHRs = 1.51, 95% CI [1.08, 2.12]) and the second quartile (Q2) (aHRs = 1.53, 95% CI [1.04, 2.25]) of uric acid levels were independently associated with an increased risk of all-cause mortality. Furthermore, comparing the fourth quartile (Q4) of uric acid levels, the second quartile (Q2) (aHRs = 2.40, 95% CI [1.08, 5.35]) of uric acid levels were independently associated with an increased risk of cardiovascular mortality. The RCS model demonstrated a U-shaped pattern in the association between SUA and all-cause mortality in OSA, with an inflection point observed at 5.83 mg/dl. The findings of this study suggest a U-shaped association between serum SUA levels and all-cause mortality and nonlinearity association between serum SUA levels and all-cause mortality. Further studies are warranted to determine the causal relationship between SUA levels and all-cause and cardiovascular mortality.

Distinct spin and orbital dynamics in Sr2RuO4

The unconventional superconductor Sr2RuO4 has long served as a benchmark for theories of correlated-electron materials. The determination of the superconducting pairing mechanism requires detailed experimental information on collective bosonic excitations as potential mediators of Cooper pairing. We have used Ru L3-edge resonant inelastic x-ray scattering to obtain comprehensive maps of the electronic excitations of Sr2RuO4 over the entire Brillouin zone. We observe multiple branches of dispersive spin and orbital excitations associated with distinctly different energy scales. The spin and orbital dynamical response functions calculated within the dynamical mean-field theory are in excellent agreement with the experimental data. Our results highlight the Hund metal nature of Sr2RuO4 and provide key information for the understanding of its unconventional superconductivity.

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.

Phalloplasty With a Free Scapular Flap Improves Postoperative Sensation in Penile Reconstruction

Objective We aimed to evaluate both the long-term surgical outcomes and patient-reported outcomes of free scapular flap (FSF) phalloplasty. Method The same surgical team performed phalloplasty in 66 patients using a FSF between March 2000 and September 2018. All patients had at least 24 months of follow-up. The surgical techniques used, complications observed, and surgical and patient-reported outcomes were retrospectively described. Results A total of 66 patients with indications of penile trauma (n = 19), micropenis (n = 42), and self-amputation (n = 5) underwent FSF phalloplasty. Two patients (3%) had total flap necrosis and 1 (1.5%) had partial flap necrosis. The urethral complication rate was 18.2% (12/66 patients). All patients were able to void while standing after revision procedures or urethroplasty. We found that an FSF is a reliable donor site for penile reconstruction. Conclusion The FSF phalloplasty creates an esthetically pleasing penis and allows voiding while standing. Most patients can engage in sexual activity. The main drawbacks of using this method are that patients experience different degrees of sensory recovery, and patients undergoing surgery with the "tube-in-tube" technique may find they are be limited by the thickness of the flap. However, by making full use of residual tissue, such as the micropenis glans or scrotal skin, patients can obtain good tactile and erogenous sensation. We believe that using an FSF complements the existing phalloplasty techniques.

Phase I dose escalation and expansion study of golidocitinib, a highly selective JAK1 inhibitor, in relapsed or refractory peripheral T-cell lymphomas

BACKGROUND

Relapsed or refractory peripheral T-cell lymphomas (r/r PTCLs) are a group of rare and aggressive diseases that lack effective therapies. Constitutive activation of the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway is reported to be associated with PTCLs. Golidocitinib is an oral, potent JAK1 selective inhibitor evaluated in a phase I/II multinational study in patients with r/r PTCLs.

PATIENTS AND METHODS

Patients with r/r PTCLs were eligible. The primary objectives were to assess safety and tolerability of golidocitinib and to define its recommended phase II dose (RP2D). The secondary objectives were to evaluate its antitumor activity and pharmacokinetics (PK).

RESULTS

A total of 51 patients were enrolled and received golidocitinib treatment at 150 or 250 mg once daily (QD). The median prior lines of therapies were 2 (range: 1-8). Golidocitinib was tolerated at both doses tested, while a higher incidence of serious adverse events and dose modifications at 250 mg were observed. The most common grade ≥3 drug-related treatment-emergent adverse events were neutropenia (27.5%) and thrombocytopenia (11.8%). An objective response rate of 39.2% and a complete response rate of 21.6% were observed. With median follow-up time of 14.7 and 15.9 months, the median duration of response (DoR) and progression-free survival were 8.0 and 3.3 months, respectively. Based on these data, 150 mg QD was defined as the RP2D. Golidocitinib demonstrated a favorable PK profile as an oral agent. Biomarker analysis suggested a potential correlation between JAK/STAT pathway aberrations and clinical activity of golidocitinib.

CONCLUSIONS

In this phase I study, golidocitinib demonstrated an acceptable safety profile and encouraging antitumor efficacy in heavily pretreated patients with r/r PTCLs. These results support the initiation of the multinational pivotal study in patients with r/r PTCLs.

Stacking Arrangement and Orientation of Aromatic Cations Tune Bandgap and Charge Transport of 2D Organic-Inorganic Hybrid Perovskites

Chemical modifications on aromatic spacers of 2D perovskites have been demonstrated to be an effective strategy to simultaneously improve optoelectronic properties and stability. However, its underlying mechanism is poorly understood. By using 2D phenyl-based perovskites ([C6 H5 (CH2 )m NH3 ]2 PbI4 ) as models, the authors have revealed how the chemical nature of aromatic cations tunes the bandgap and charge transport of 2D perovskites by utilizing sum-frequency generation vibrational spectroscopy to determine the stacking arrangement and orientation of aromatic cations. It is found that the antiparallel slip-stack arrangement of phenyl rings between adjacent layers induces an indirect band gap, resulting in anomalous carrier dynamics. Incorporation of the CH2 moiety causes stacking rearrangement of the phenyl ring and thus promotes an indirect to direct bandgap transition. In direct-bandgap perovskites, higher carrier mobility correlates with a larger orientation angle of the phenyl ring. Further optimizing the orientation angle by introducing a para-substituted element in a phenyl ring, higher carrier mobility is obtained. This work highlights the importance of leveraging stacking arrangement and orientation of the aromatic cations to tune the photophysical properties, which opens up an avenue for advancing high-performance 2D perovskites optoelectronics via molecular engineering.

Current status and future challenges of chlorobenzenes pollution in soil and groundwater (CBsPSG) in the twenty-first century: a bibliometric analysis

The global industrial structure had undertaken significant changes since the twenty-first century, making a severe problem of chlorobenzene pollution in soil and groundwater (CBsPSG). CBsPSG receives increasing attention due to the high toxicity, persistence, and bioaccumulation of chlorobenzenes. To date, despite the gravity of this issue, no bibliometric analysis (BA) of CBsPSG does exist. This study fills up the gap by conducting a BA of 395 articles related to CBsPSG from the Web of Science Core Collection database using CiteSpace. Based on a comprehensive analysis of various aspects, including time-related, related disciplines, keywords, journal contribution, author productivity, and institute and country distribution, the status, development, and hotspots of research in the field were shown visually and statistically. Moreover, this study has also delved into the environmental behavior and remediation techniques of CBsPSG. In addition, four challenges (unequal research development, insufficient cooperation, deeply mechanism research, and developing new technologies) have been identified, and corresponding suggestions have been proposed for the future development of research in the field. Afterwards, the limitations of BA were discussed. This work provides a powerful insight into CBsPSG, enabling to quickly identify the hotspot and direction of future studies by relevant researchers.

Development of a sensitive immunochromatographic method using lanthanide fluorescent microsphere for rapid test for PPRV antibody

Peste des petits ruminants virus (PPRV) causes a very devastating disease in sheep and goats. Rapid diagnosis and immunisation have been identified as key strategies for successful prevention of the disease. Therefore, a sensitive fluorescent microsphere immunochromatography test strips (FM-ICTS) was developed for rapid detection of special antibodies of PPRV in goats and sheep serum. The FM-ICTS were successfully prepared by fluorescent microspheres (FM) as tracer, which were covalently coupled to PPRV nucleocapsid protein (NP). The NP and monoclonal antibody of NP were separately dispensed onto a nitrocellulose membrane as test and quality control lines, respectively. The critical threshold for determining negative or positive through the ratio of the fluorescent signal of the test line and the control line (T/C) is 0.050. The repeatability of the FM-ICTS was excellent, with an overall average CV of 3.17 %. The detection limit of this assay was 1:5120. Additionally, the FM-ICTS no cross reaction with the sera of other related diseases was observed, only reacting with anti-PPRV serum. 70 serum samples were tested by FM-ICTS and commercial ELISA kit, and the results showed good agreement. Overall, a promising pen-side diagnostic tool was developed for the rapid qualitatively/semi-quantitatively detection of PPRV antibodies within 15 min.

A radiomics-clinical combined nomogram-based on non-enhanced CT for discriminating the risk stratification in GISTs

PURPOSE

To discriminate the risk stratification in gastrointestinal stromal tumors (GISTs) by preoperatively constructing a model of nonenhanced computed tomography (NECT).

METHODS

A total of 111 GISTs patients (77 in the training group and 34 in the validation Group) from two hospitals between 2015 and 2022 were collected retrospectively. One thousand and thirty-seven radiomics features were extracted from non-contract CT images, and the optimal radiomics signature was determined by univariate analysis and LASSO regression. The radiomics model was developed and validated from the ten optimal radiomics features by three methods. Covariates (clinical features, CT findings, and immunohistochemical characteristics) were collected to establish the clinical model, and both the radiomics features and the covariates were used to build the combined model. The effectiveness of the three models was evaluated by the Delong test.

RESULTS

The experimental results showed that the clinical models (75.3%, 70.6%), the radiomics models (79.2%, 79.4%) and the combined models (81.8%, 82.4%) all had high accuracy in predicting the pathological risk of GIST in both training and validation groups. The AUC values of the combined models were significantly higher in both the training groups (0.921 vs 0.822, p= 0.032) and the validation groups (0.913 vs 0.792, p= 0.019) than that of the clinical models. According to the calibration curve, the combined model nomogram is clinically useful.

CONCLUSIONS

The clinical-radiomics combined model and based on NECT performed well in discriminating the risk stratification in GISTs. As a quantitative technique, radiomics is capable of predicting the malignant potential and guiding treatment preoperatively.

Observation of New Baryons in the Ξ_{b}^{-}π^{+}π^{-} and Ξ_{b}^{0}π^{+}π^{-} Systems

The first observation and study of two new baryonic structures in the final state Ξ_{b}^{0}π^{+}π^{-} and the confirmation of the Ξ_{b}(6100)^{-} state in the Ξ_{b}^{-}π^{+}π^{-} decay mode are reported using proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9  fb^{-1}. In addition, the properties of the known Ξ_{b}^{*0}, Ξ_{b}^{'-} and Ξ_{b}^{*-} resonances are measured with improved precision. The new decay mode of the Ξ_{b}^{0} baryon to the Ξ_{c}^{+} π^{-} π^{+} π^{-} final state is observed and exploited for the first time in these measurements.

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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Precision Measurement of CP Violation in the Penguin-Mediated Decay B_{s}^{0}→ϕϕ

A flavor-tagged time-dependent angular analysis of the decay B_{s}^{0}→ϕϕ is performed using pp collision data collected by the LHCb experiment at the center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6  fb^{-1}. The CP-violating phase and direct CP-violation parameter are measured to be ϕ_{s}^{ss[over ¯]s}=-0.042±0.075±0.009  rad and |λ|=1.004±0.030±0.009, respectively, assuming the same values for all polarization states of the ϕϕ system. In these results, the first uncertainties are statistical and the second systematic. These parameters are also determined separately for each polarization state, showing no evidence for polarization dependence. The results are combined with previous LHCb measurements using pp collisions at center-of-mass energies of 7 and 8 TeV, yielding ϕ_{s}^{ss[over ¯]s}=-0.074±0.069  rad and |λ|=1.009±0.030. This is the most precise study of time-dependent CP violation in a penguin-dominated B meson decay. The results are consistent with CP symmetry and with the standard model predictions.

Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning

BACKGROUND

Disulfidptosis is a recently discovered programmed cell death pathway. However, the exact molecular mechanism of disulfidptosis in cutaneous melanoma remains unclear.

METHODS

In this study, clustering analysis was performed using data from public databases to construct a prognostic model, which was subsequently externally validated. The biological functions of the model genes were then investigated through various experimental techniques, including qRT-PCR, Western blotting, CCK-8 assay, wound healing assay, and Transwell assay.

RESULTS

We constructed a signature using cutaneous melanoma (CM) data, which accurately predicts the overall survival (OS) of patients. The predictive value of this signature for prognosis and immune therapy response was validated using multiple external datasets. High-risk CM subgroups may exhibit decreased survival rates, alterations in the tumor microenvironment (TME), and increased tumor mutation burden. We initially verified the expression levels of five optimum disulfidptosis-related genes (ODRGs) in normal tissues and CM. The expression levels of these genes were further confirmed in HaCaT cells and three melanoma cell lines using qPCR and protein blotting analysis. HLA-DQA1 emerged as the gene with the highest regression coefficient in our risk model, highlighting its role in CM. Mechanistically, HLA-DQA1 demonstrated the ability to suppress CM cell growth, proliferation, and migration.

CONCLUSION

In this study, a novel signature related to disulfidptosis was constructed, which accurately predicts the survival rate and treatment sensitivity of CM patients. Additionally, HLA-DQA1 is expected to be a feasible therapeutic target for effective clinical treatment of CM.

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.

STK4 is a prognostic biomarker correlated with immune infiltrates in clear cell renal cell carcinoma

BACKGROUND

Mammalian STE20-like kinase 1 (MST1/STK4/KRS2) is a highly conserved serine/threonine kinase and a central member of the Hippo signaling pathway. STK4 has been reported to play important roles in various tumors, but a systematic and comprehensive study of its function in clear cell renal cell carcinoma (ccRCC) has not been conducted.

METHODS

In this study, we used immunohistochemistry (IHC), western blot (WB), quantitative real-time PCR (qPCR) experiments, and bioinformatics analysis to comprehensively analyze the expression, prognostic value, and immune infiltration of STK4 in ccRCC.

RESULTS

Analysis of the TCGA database showed that the expression level of the STK4 gene in ccRCC patients depended on tumor stage, grade, and distant lymphatic metastasis. This was further confirmed by the results of IHC, WB, and qPCR. In addition, we used the receiver operating characteristic curve (ROC curve) to elucidate the diagnostic value of STK4 in ccRCC patients. According to the findings of the TIMER database, the high expression of STK4 is significantly associated with the survival of kidney cancer (including ccRCC) patients (p < 0.001), suggesting that STK4 is a reliable prognostic predictor. We then used gene set enrichment analysis (GSEA) to explore the mechanisms behind STK4 function in ccRCC. We found that STK4 may play a role in immune regulation interactions. Subsequently, we performed immune infiltration analysis of STK4. The results showed that STK4 may regulate the development of ccRCC by affecting the immune infiltration of NK and pDC cells.

CONCLUSIONS

STK4 may be a prognostic marker for ccRCC and may help identify new strategies for treating ccRCC patients.

Niclosamide improves cancer immunotherapy by modulating RNA-binding protein HuR-mediated PD-L1 signaling

BACKGROUND

Immune checkpoint blockade (ICB) represents a revolutionary advance in cancer treatment but remains limited success in triple-negative breast cancer (TNBC). Here we aim to explore the mechanism of RNA-binding protein (RBP) HuR in cancer immune evasion by post-transcriptionally regulating PD-L1 and evaluate the potential of HuR inhibition to improve immune response.

METHODS

The binding between HuR and PD-L1 mRNA was determined by ribonucleoprotein immunoprecipitation and RNA pull-down assays. The HuR knockout clones were established by CRISPR/Cas9 technology. The protein levels were assessed by Western blot, immunohistochemistry, and immunocytochemistry. The function and molecular mechanism of HuR-PD-L1 were determined by in vitro T cell activation and killing assay and in vivo efficacy assay.

RESULTS

We found that HuR directly bound to and stabilized PD-L1 mRNA. Knocking out HuR reduced PD-L1 levels and promoted T cell activation. We discovered that niclosamide reduced PD-L1 by inhibiting HuR cytoplasmic translocation, and diminished glycosylation of PD-L1. Niclosamide enhanced T cell-mediated killing of cancer cells and significantly improved the efficacy of anti-PD-1 immunotherapy in two syngeneic animal tumor models.

CONCLUSION

We identified HuR as a novel posttranscriptional regulator of PD-L1, which plays an important role in tumor immune evasion. Niclosamide might be a promising repurposed drug to improve the patient response to immunotherapy by targeting HuR-PD-L1 axis. Our study demonstrates a novel strategy for targeting HuR/PD-L1 and provides the first proof-of-principle for repurposing niclosamide as a HuR inhibitor to overcome cancer immune evasion and improve response to ICB immunotherapy.

Enhancing the removal of organic micropollutants by nanofiltration membrane with Fe (III)-tannic acid interlayer: Mechanisms and environmental implications

Nanofiltration technology has been applied in a variety of water treatment scenarios. However, conventional thin-film composite (TFC) membranes fail to remove emerging organic micropollutants (OMPs) efficiently. Here we applied thin-film nanocomposite membrane with an interlayer (TFNi) of Fe (III)-tannic acid to remove various types of OMPs, such as endocrine disrupting chemicals (EDCs), pharmaceutically active compounds (PhACs), and perfluoroalkyl substances (PFASs). Compared to the pristine TFC membrane, TFNi membrane exhibited crumpled morphology and its rejection layer was denser, better cross-linked and possessed smaller average pore size with narrower distribution. Significant enhancement in water-OMPs selectivity of PhACs and PFASs was observed. The mechanism lies in the effects of interlayer in improving the membrane permeance to water and meanwhile reducing the permeance to some OMPs by enhancing size exclusion effects. This work confirms the effectiveness of using TFNi membrane to simultaneously enhance the OMPs rejection and water permeance. The unraveled mechanism might inspire the future development of high-performance nanofiltration membranes targeting OMPs removal.

Measurement of the Λ_{b}^{0}→Λ(1520)μ^{+}μ^{-} Differential Branching Fraction

The branching fraction of the rare decay Λ_{b}^{0}→Λ(1520)μ^{+}μ^{-} is measured for the first time, in the squared dimuon mass intervals q^{2}, excluding the J/ψ and ψ(2S) regions. The data sample analyzed was collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV, corresponding to a total integrated luminosity of 9  fb^{-1}. The result in the highest q^{2} interval, q^{2}>15.0  GeV^{2}/c^{4}, where theoretical predictions have the smallest model dependence, agrees with the predictions.

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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[Bioinformatics analysis of the RNA binding protein DDX39 of Toxoplasma gondii]

OBJECTIVE

To analyze the RNA binding protein of Toxoplasma gondii (TgDDX39) using bioinformatics technology, and to evaluate the immunogenicity of TgDDX39, so as to provide insights into development of toxoplasmosis vaccines.

METHODS

The amino acid sequences of TgDDX39 were retrieved from the ToxoDB database, and the physicochemical properties, transmembrane structure domain, signal peptide sites, post-translational modification sites, coils, secondary and tertiary structures, hydrophobicity, and antigenic epitopes of the TgDDX39 protein were predicted using online bioinformatics tools, incluiding ProtParam, TMHMM 2.0, SignalP 5.0, NetPhos 3.1, COILS, SOPMA, Phyre2, ProtScale, ABCpred, SYFPEITHI and DNA-STAR.

RESULTS

TgDDX39 protein was predicted to be an unstable hydrophilic protein with the molecular formula of C2173H3458N598O661S18, which contained 434 amino acids and had an estimated molecular weight of 49.1 kDa and a theoretical isoelectric point of 5.55. The protein was predicted to have an extremely low possibility of signal peptides, without transmembrane regions, and contain 27 phosphorylation sites. The β turn and random coils accounted for 39.63% of the secondary structure of the TgDDX39 protein, and a coiled helix tended to produce in one site. In addition, the TgDDX39 protein contained multiple B and T cell antigenic epitopes.

CONCLUSIONS

Bioinformatics analyses predict that TgDDX39 protein has high immunogenicity and contains multiple antigenic epitopes. TgDDX39 protein is a potential candidate antigen for vaccine development.

A 20-Year Experience with Tissue Expansion for Large Cervical Fascial Defects: An Algorithm Based on Different Clinical Flap Designs

Over the past 20 years, we have designed various types of expanded cervical flaps for large facial defects and achieved excellent tissue matching. This study was performed to propose a treatment strategy for flap selection for the reconstruction of different facial units. The authors retrospectively reviewed the application of cervical expanded flaps for facial rehabilitation in our department between January 2003 and January 2023. The study included 122 patients with unilateral (62.3%) and bilateral (37.7%) facial deformities ranging from the zygomatic arch to the chin. The median area of the tissue defect was 15.2 × 8.5 cm2 (ranging from 6 × 4 cm2 to 27 × 12 cm2). The expansion period ranged from 61 to 175 days (mean: 86.5 days). Maximum and minimum sizes of pre-expanded cervical flaps were 30 × 13 cm2 to 7 × 5 cm2. All the flaps could be summarized into type 1, an advanced expanded cervical flap; type 2, a wing-shaped expanded cervical flap with overlapping tissue expansion; and type 3, an expanded single-lobed transposition flap rotated based on the anterior neck. Cervical flaps reliably meet the reconstructive requirements for different facial units, especially for large cutaneous defects in the clinic. The selection of these flaps can be planned preoperatively according to the location and size of the defect or lesion.

Protein-coated cobalt oxide-hydroxide nanospheres deliver photosensitizer IR780 iodide for near-infrared light-triggered photodynamic/photothermal/chemodynamic therapy against colon cancer

Phototherapy has garnered worldwide attention for its minimal invasiveness, controllability, and spatial selectivity in treating cancer. One promising approach involves the use of near-infrared dye IR780, which demonstrates both photodynamic therapy (PDT) and photothermal therapy (PTT) effects under 808 nm laser irradiation. However, this hydrophobic dye's toxicity and limited tumor targeting ability severely hamper its suitability for cancer applications. Herein, a biocompatible nanoplatform CoOOH-IR780@BSA (CoIRB) is developed to efficiently deliver IR780 and provide multi-mode treatments for colon tumors. Due to the nanocarrier coating, CoIRB nanoparticles demonstrated reliable dispersion and stability, and their biotoxicity was substantially reduced for safer blood circulation, which overcame the biological barrier of IR780. The nanoplatform has also shown considerable results in phototherapy in vivo and in vitro experiments, with successful inhibition of MC38 tumor growth through intravenous administration. Additionally, the introduction of cobalt ions could induce Fenton-like reactions to activate the production of toxic hydroxyl radicals (˙OH), exerting an assisted chemodynamic therapy (CDT) effect. Notably, these nanodrugs also exhibited potential as scavengers of reductive glutathione (GSH) and hydrogen sulfide (H2S), leading to amplifying oxidative damage of reactive oxygen species (ROS). Overall, the versatile therapeutic platform, CoIRB, has opened up considerable prospects as a biotherapeutic option for combining PDT/PTT/CDT against colon cancer.

Nonverbal behavioral patterns predict social rejection elicited aggression

Aggression elicited by social rejection is costly, prevalent, and often lethal. Attempts to predict rejection-elicited aggression using trait-based data have had little success. This may be because in-the-moment aggression is a complex process influenced by current states of attention, arousal, and affect which are poorly predicted by trait-level characteristics. In a study of young adults (N = 89; 18-25 years), machine learning tested the extent to which nonverbal behavioral indices of attention (eye gaze), arousal (pupillary reactivity), and affect (facial expressions) during a novel social interaction paradigm predicted subsequent aggression towards rejecting and accepting peers. Eye gaze and pupillary reactivity predicted aggressive behavior; predictions were more successful than measures of trait-based aggression and harsh parenting. These preliminary results suggest that nonverbal behavior may elucidate underlying mechanisms of in-the-moment aggression.

Overall Survival Prediction in Stereotactic Radiosurgery Patients with Glioblastoma Via a Deep-Learning Approach

PURPOSE/OBJECTIVE(S)

Accurate and automated early survival prediction is critical for glioblastoma (GBM) patients as their poor prognosis requires timely treatment decision-making. We have developed a deep learning (DL)-based GBM overall survival (OS) prediction model based on a multi-institutional public dataset using only pre-operative basic structural multi-parametric magnetic resonance images (MRIs). The purpose of this study is to evaluate this DL-based OS prediction model with an institutional stereotactic radiosurgery (SRS) clinical trial dataset.

MATERIALS/METHODS

The task of this study is to classify GBM patients into 3 OS classes: long-survivors (>15 months), mid-survivors (between 10 and 15 months) and short-survivors (< 10 months). The proposed OS prediction model is an ensemble of a ResNet-based classifier and a K-NN classifier. The ResNet-based classifier is trained in a Siamese fashion to explore inter-class differences. During testing, training sample features are implemented with a K-NN classifier to ensemble with the ResNet-based classifier. A public dataset from Medical Image Computing and Computer Assisted Intervention (MICCAI) Brain Tumor Segmentation (BraTS) challenge 2020 (235 patients) were used for model establishing and initial validation. Then the validated model was evaluated on 19 GBM patients from an institutional SRS clinical trial. Each data entry consists of pre-operative basic structural multi-parametric MRIs and survival days, as well as patient ages for BraTS data and basic clinical characteristics for institutional data. GBM sub-regions, including contrast-enhancing tumor, peri-tumoral edema, and necrotic/non-enhancing tumor core, were segmented in the multi-parametric MRIs by an in-house DL model for both datasets. The OS prediction model was trained on 90% of the segmented BraTS data and validated on the rest 10%, then further evaluated on the institutional data. The model performance was assessed by prediction accuracy (ACC) and the area under the curve (AUC).

RESULTS

For this 3-class OS classification task, our DL-based prediction model achieved an ACC of 65.22% and an AUC of 0.81 on the BraTS dataset compared with the top-ranked result from the BraTS challenge 2020 (Rank 1st: ACC 61.7%), and an ACC of 52.63% and an AUC of 0.69 on the institutional dataset. Further analysis of the institutional dataset found that the predicted OS class had a statistically significant correlation with treatment volume (p = 0.012) and age (p = 0.006), which matches the analysis that the patients' ground truth OS class is statistical significantly correlated with treatment volume (p = 0.045).

CONCLUSION

Our DL-based OS prediction model for GBM using basic structural multi-parametric pre-operative MRIs has demonstrated promising performance in both public and institutional dataset with minimal manual processing requirements. This OS prediction model can be potentially applied to assist timely clinical decision-making.

Potential Predictive Value of Intravoxel Incoherent Motion Magnetic Resonance for Xerostomia of Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Xerostomia, caused by radiation-induced parotid damage, is the most commonly reported complications of radiotherapy (RT) to nasopharyngeal carcinoma (NPC). This study aimed to evaluate the value of IVIM MR in monitoring radiation parotid gland damage and predicting the risk of xerostomia.

MATERIALS/METHODS

A total of 54 patients were enrolled and underwent IVIM MR scans at before RT, after the fifth fraction, halfway through the course of RT, and at the end of radiotherapy. The parameters of IVIM MR include pseudo-diffusion coefficient (D*), perfusion fraction (f), and pure diffusion coefficient (D). The degree of xerostomia in NPC patients was assessed before each MR examination using the acute radiation morbidity scoring criteria proposed by the Radiation Therapy Oncology Group (RTOG). Concurrently, the time when the patient first reported suffering from xerostomia was recorded. The IVIM parameters trend throughout the RT, and the relationships between IVIM parameters and xerostomia, were analyzed.

RESULTS

All of the IVIM parameters increased from pre-RT to post-RT significantly (all p < 0.001). The increase rate of D from pre-RT to halfway through the RT was 32.61%, which was significantly higher than 15.64% from halfway to post-RT (p<0.001), indicating that cell necrosis in the first half of treatment is significantly higher than that in the second half. Both D* and F had significantly increased from pre-RT to halfway through the radiotherapy (p<0.001), with an increase rate of 19.58% and 29.38%, respectively. However, no significant increase was observed from Halfway to post-RT (p>0.05), with an increase rate of 4.10% and 8.30%, respectively. This may be due to radiation-induced vasculitic dilation that is significant in the first half of the radiotherapy but plateaus in the second half. Pre-D (OR = 23.85; 95% CI = 2.39, 237.82; p = .007) and pre-D* (OR = 0.75; 95% CI = 0.63, 0.91; p = 0.003) are independent influencing factors for xerostomia at 3 months after the completion of RT. D and F were significantly higher after the fifth fraction compared with Pre-RT (both p<0.05), respectively increased 31.25% and 25.16%. D* increase by 15% (p = 0.081). IVIM scans can assess parotid gland damage early. And the average time of parotid damage underwent IVIM scan was 5.99 ± 0.84 (day), much earlier than 11.84 ± 2.74 (day) according to RTOG.

CONCLUSION

Our study indicates that IVIM MR can dynamically monitor radiotherapy-induced parotid gland damage, and much earlier and objectively than RTOG.

SAA1 exacerbates pancreatic β-cell dysfunction through activation of NF-κB signaling in high-fat diet-induced type 2 diabetes mice

Insufficient decompensated insulin secretion and insulin resistance caused by pancreatic β-cell dysfunction are the pathological bases of type 2 diabetes mellitus (T2DM). Glucolipotoxicity in pancreatic β-cells is an important factor leading to their dysfunction, closely related to inflammatory signals, oxidative stress, mitochondrial dysfunction, and endoplasmic reticulum stress (ERs). However, there may be other unproven regulatory mechanisms that govern pancreatic β-cell dysfunction. Therefore, further elucidation of the underlying mechanisms that lead to pancreatic β-cells dysfunction will provide a sufficient theoretical basis for the more effective prevention and treatment of T2DM. As a stress protein with pro-inflammatory properties, Serum Amyloid 1 (SAA1) promotes the progression of metabolic syndrome-related diseases by activating immune cells and damaging endothelial cells. In the development of T2DM, the activation of nuclear factor-kappa B (NF-κB) signaling aggravates pancreatic β-cells dysfunction under the stimulation of free fatty acids (FFAs), inflammatory factors, and chemokines. Moreover, the facilitating effect of SAA1 on the activation of the NF-κB signaling pathway has been demonstrated in other studies. In the present study, we demonstrated that SAA1 inhibits insulin secretion and promotes apoptotic molecular expression in pancreatic cells and islets and that NF-κB signaling inhibitors could reduce this effect of SAA1. SAA1 deficiency improved high-fat diet (HFD)-induced pancreatic β-cell dysfunction and decreased expression of NF-κB signaling molecules. Our findings suggested that HFD-induced SAA1 might exacerbate T2DM by enhancing pancreatic β-cell dysfunction; such a function of SAA1 might depend on NF-κB signaling activation.

The Role of CT-Based Radiomics Nomogram in Differential Diagnosis of Immune Checkpoint Inhibitor-Related Pneumonitis from Radiation Pneumonitis for Patients with ESCC

PURPOSE/OBJECTIVE(S)

The combination of immunotherapy and chemoradiotherapy has widely used for patients with esophageal squamous cell carcinoma (ESCC) and induced treatment-related adverse effects, particularly immune checkpoint inhibitor-related pneumonitis (CIP) and radiation pneumonitis (RP). The aim of this study is to differentiate between CIP and RP by the CT radiomics and clinical or radiological parameters.

MATERIALS/METHODS

A total of 76 ESCC patients with pneumonitis were enrolled in this retrospective study and divided into training dataset (n = 53) and validation dataset (n = 23). A total of 837 radiomics features were extracted from regions of interest (ROIs) based on the lung parenchyma window of CT images. A radiomics signature was constructed on the basis of the predictive features by the least absolute shrinkage and selection operator (LASSO). A logistic regression was applied to develop radiomics nomogram. Receiver operating characteristics (ROC) curve and area under the curve (AUC) were applied to evaluate the performance of pneumonitis etiology identification.

RESULTS

No significant difference was detected between training dataset and validation dataset. The radiomics signature which was made up of four radiomics features shown a favorable performance on differentiating between CIP and RP with the α-binormal-based and empirical AUC = 0.831 and 0.843. Patients with RP had a close relationship with location (p = 0.003) and shape of lesions (p = 0.002). The nomogram that combined with radiomics signature and clinical factors improved the classifying performance on discrimination in the training dataset (AUCαbin = 0.963 and AUCemp = 0.964). The results were verified in the validation dataset with AUC = 0.967 and 0.964.

CONCLUSION

CT-based radiomics features have potential values for differentiating between patients with CIP and RP. Addition of bilateral changes and sharp border produced superior model performance on classifying, which could be a useful method to improve related clinical decision-making.

Equivalent Dose Estimation in FLASH Irradiation with a Deep Learning Approach

PURPOSE/OBJECTIVE(S)

Ultra-high dose rate (FLASH) irradiation has been reported to provide decreased normal tissue toxicity without compromising tumor control compared with conventional (CONV) irradiation. However, a comprehensive understanding of the FLASH biological effect requires precise quantification of radiobiology. The study is to explore whether deep learning (DL) can tackle the task. As a proof of concept, we investigate a DL model for estimating FLASH dose to its equivalent CONV dose.

MATERIALS/METHODS

Healthy C57Bl/6 female mice underwent FLASH (200Gy/s; n = 43) or CONV (0.12Gy/s; n = 41) whole abdominal irradiation using ∼16 MeV electron beams with a dose escalation scheme of 5 groups (n = 8 or 9) at 1Gy increments: 12-16Gy FLASH, 11-15Gy CONV. 4 days post-irradiation, 9 jejunum cross-sections per mouse were H&E stained for histological analysis. Each cross-section image was processed to remove lumen background and oversampled into multiple large-scale and small-scale patches along jejunal circumference. In CONV dataset, we randomly selected the data of 32 mice (80%) for model training and the rest (20%) for model validation. A ResNet101-based DL model, pre-trained with an unsupervised contrastive learning scheme, was retrained with only CONV training set to estimate corresponding CONV dose. For comparison, a crypt counting (CC) approach was implemented by manually counting the number of regenerating crypts on each cross-section image. An exponential function of dose vs crypt number was fitted with the CONV training set and used for dose estimation on the testing set. Mean squared error (MSE) was used to assess the accuracy of DL and CC approaches in estimating dose levels in CONV irradiation. The validated DL model was applied to the FLASH set to project FLASH dose into corresponding CONV dose that results in equivalent biological response.

RESULTS

The CONV dose estimated by DL and CC approaches and DL-estimated FLASH equivalent dose were summarized in Table 1. The DL model achieved an MSE of 0.21 Gy2 on CONV testing set compared with 0.32 Gy2 of the CC approach. FLASH equivalent dose estimated by DL model for 12, 13, 14, 15 and 16Gy were 12.16±0.40, 12.53±0.32, 12.72±0.24, 12.85±0.20 and 13.04±0.27 Sv, respectively.

CONCLUSION

Our proposed DL model can accurately estimate the CONV dose based on histological images. The DL predictions of FLASH dataset demonstrate that FLASH may reduce normal tissue toxicity with a lower equivalent dose, especially at high irradiated dose levels. Our study indicates that deep learning can be potentially used to assess the equivalent dose of FLASH irradiation to normal tissue.

Evaluating the Use of SGRT and Abdominal Compression Device for Improved Patient Positioning in Liver Cancer Radiotherapy

PURPOSE/OBJECTIVE(S)

To mitigate tumor displacement caused by respiratory movement and to enhance positioning accuracy in liver cancer patients during radiotherapy, abdominal compression fixation devices are commonly employed. However, the efficacy of using surface guided radiotherapy (SGRT) to further improve patient setup accuracy in combination with abdominal compression has not been fully established. Hence, we aimed to investigate this in our study.

MATERIALS/METHODS

In this study, we analyzed data from 11 patients with liver cancer. The patients were positioned using isocentric skin markers and the abdominal compression fixture was placed on an accurate scale reading based on the records from CT simulation. A cone-beam CT (CBCT) scan was performed to assess setup errors. These setup errors represent data for the control group - Skin marker group. The patients were then adjusted to the correct treatment position based on CBCT correction and the SGRT system was activated for monitoring. Care was taken for the region of interest drawn to avoid the abdominal compression device for all patients. The reference surface used for monitoring was the captured VRT surface rather than DICOM. The six degrees of freedom values detected by the SGRT system were recorded, representing data for the test group - SGRT group. Both sets of data were analyzed using statistical software. The errors were presented as median (interquartile range) and the differences between the two groups were tested using paired Wilcoxon rank sum test, with P < 0.05 considered as significant.

RESULTS

A total of 60 CBCT images were analyzed, the median values and interquartile ranges are presented in the Table. The results showed that the accuracy of the SGRT group in the x and y directions was significantly better than the skin marker group (P < 0.05). The median values for the x (transverse) direction were 0.25(0.09-0.43) cm and 0.09(0.05-0.19) cm for the skin marker and SGRT groups, respectively. The median values for the y (longitudinal) direction were 0.54 (0.29-0.79) cm and 0.14 (0.07-0.24) cm for the skin marker and SGRT groups, respectively. The results for the z (vertical) direction, Rz (rotation), Ry (roll) and Rx (pitch) rotation directions were also analyzed similarly.

CONCLUSION

The findings of this study suggest that compared to skin markers, SGRT can improve the accuracy of patient positioning in liver cancer radiotherapy with abdominal compression, potentially reducing unnecessary radiation exposure from CBCT imaging due to inaccurate positioning. Further multicenter prospective clinical trials are required to confirm these results.

Effects of energy restriction during growing phase on the productive performance of Hyline Brown laying hens aged 6 to 72 wk

The aim of this study was to assess the effects of energy-restricted feeding during growing phase on the productive performance of Hyline Brown laying hens aged 6 to 72 wk. A total of 720 six-week-old layer chicks were allocated equally to 3 groups with 6 replicates of 40 pullets each, and were fed 1 of 3 diets that were nutritionally similar except for the apparent metabolizable energy corrected for nitrogen (AMEn) content. At the age of 6 to 17 wk, the pullets in the control group were given diet with 2,850 kcal/kg AMEn, and were fed ad libitum. The levels of AMEn in diet of pullets in the experimental groups were 90% (2,565 [2,850 × 90%] kcal/kg) and 80% (2,280 [2,850 × 80%] kcal/kg) of that in control group, and the daily amount of feed was restricted to the absolute quantity of the diet consumed by pullets in control group. At the age of 18 to 72 wk, all the hens were fed with the same diets ad libitum. As energy restriction increased in the growing phase, body weight (BW) dropped at the ages of 12 and 15 to 23 wk (at 23 wk: P = 0.001; at other ages: P < 0.001), but it showed no significant difference at 24 wk (P = 0.071). At 20 wk, restricting energy induced a delay in the development of sexual organs, including the ovary stroma, oviduct, and small yellow follicle (P < 0.05), as well as a delay in sexual maturity (P < 0.05). Consequently, the laying rate in the first and second periods dropped linearly (P = 0.046, 0.030, and 0.038, P < 0.001, respectively). The coefficient of variation (CV) in the BW at 19, 20, and 21 wk (P = 0.040, 0.023, and 0.042, respectively), the CV of age at first egg (P < 0.001), and CV of individual egg number at age 18 to 72 wk (P < 0.001) decreased linearly. There was a linear increase in the laying rate of hens in the later periods (at age 32-72 wk, P < 0.05), as well as in the average total egg number per hen and average laying rate at the age of 18 to 72 wk (P = 0.006). The average egg mass also showed a linear increase with increasing levels of energy restriction (P < 0.001). In summary, although appropriate energy restriction during growing phase delayed sexual maturity and sexual organ development in early-laying Hyline Brown pullets, it improved uniformity of BW, age at first egg laying, and individual egg number, and increased egg number per hen, laying rate, average egg mass, and number of settable eggs from 18 to 72 wk of age.

Predicting Neurocognitive Decline in Multiple Brain Metastases Patients Undergoing Distributed Stereotactic Radiosurgery

PURPOSE/OBJECTIVE(S)

Stereotactic radiosurgery (SRS) is the standard of care for treating a limited number (<3) of brain metastasis (BMs), which offers reduced neurotoxicity compared to whole brain radiotherapy (WBRT). Contemporary advancements in SRS made it possible to also commonly treat multiple (>4) BMs (mBMs). Emphasizing the value of preserving quality of life (QoL) after SRS, there is an urgent need for a systematic study of potential neurocognitive decline in patients receiving SRS treatment for mBMs. The purpose of this study is to use routine MRIs to predict neurocognitive decline for patients treated with distributed SRS, allowing for timely and effective treatment strategy design.

MATERIALS/METHODS

This study uses data from an institutional phase I/II clinical trial to determine the neurocognitive decline in patients with (>6) mBMs treated with distributed SRS. In the first 12 months post-SRS, participants are followed and evaluated with routine MRIs and the Hopkins Verbal Learning Test-Revised (HVLT-R) at 2 to 3-month intervals. Changes in HVLT-Delayed Recall scores between two visits are used to define neurocognitive decline. For each visit, an in-house deep learning model segments 66 cortical and 55 subcortical brain regions of interest (ROIs) from the T1 structural MRI and extracts 253 ROI features, including the surface area and thickness of cortical ROIs, and the volume of all ROIS. The difference in ROI features between two visits, together with other clinical factors (e.g., prescription, number of BMs, etc.), is considered as one sample. The study included 22 subjects with 91 visits, resulting in 171 samples with neurocognitive decline labels. The entire sample set is split into 10 folds on patient level for cross validation. In each fold, feature engineering is conducted to remove redundancy and to select the most-important features. The top 20% most frequently selected features are applied with Support Vector Machine to predict the neurocognitive decline label of each sample.

RESULTS

As a preliminary result, the proposed method achieves an accuracy of 76%, with an area under the curve (AUC) of 0.75, sensitivity of 0.65 and specificity of 0.83 for predicting neurocognitive decline in mBMs SRS patients using only routine T1 MRIs. The volume of lateral occipital complex, the thickness of inferior parietal lobe and postcentral gyrus, and the surface area of lateral orbitofrontal cortex and pars triangularis are identified as the 5 most important features for this task.

CONCLUSION

Our method shows promising findings for post-SRS neurocognitive decline prediction solely based on routine baseline and follow-up MRIs. In addition, it can identify critical brain ROIs associated with the post-SRS cognitive function. This method has the potential to assist treatment planning strategy to help preserve patients' QoL.

A Comprehensive Deep Learning Framework for Automatic Target Volumes Segmentation in Post-Operative Stereotactic Partial Breast Irradiation (S-PBI)

PURPOSE/OBJECTIVE(S)

In S-PBI, accurate delineation of post-surgical tumor bed volume (TBV) and clinical target volume (CTV) are crucial tasks to achieve effective radiotherapy outcomes. However, manual contouring is labor intensive, time consuming, and largely relies on the experience of clinicians. We aimed to propose a deep learning (DL) approach which mimics physicians' contouring practice to accurately segment target volumes in post-operative breast CT images.

MATERIALS/METHODS

Our approach incorporated domain knowledge into a 3D U-Net based DL model for breast target volumes (TBV and CTV) delineation. Our TBV segmentation approach was inspired by the marker-guidance procedure in manual delineation, where the visual clues provided by the markers assist physicians in defining TBV. For this purpose, a distance-transformation coupled with a Gaussian filter was adopted to convert markers' locations on the CT images to saliency maps. Subsequently, the CT images and the corresponding saliency maps formed a two-channel input for the segmentation model. For CTV segmentation, TBV was incorporated as an input in addition to the CT images, guiding the model to encode the location-related image features. The architecture allowed the network to emulate the oncologist's manual delineation where CTV is derived from TBV via a margin expansion, followed by correcting the extensions for anatomical barriers of tumor invasion (e.g., skin, chest wall). We retrospectively collected 175 prone CT images from 35 post-operative breast cancer patients who received 5-fraction partial breast irradiation (PBI) regimen on a Co-60 prone based S-PBI unit. The 35 patients were randomly split into 25, 5, and 5 for model training, validation, and testing respectively.

RESULTS

We evaluated the performance of the developed DL model on the testing dataset by comparing the predicted volumes with the manually delineated contours (ground truth) using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), and average symmetric surface distance (ASD). For TBV segmentation, our model achieved mean (standard deviation) of 0.76 (±2.7), 6.76 (±1.83) mm, and 1.9 (±0.66) mm for DSC, HD95, and ASD respectively. For CTV segmentation, our model achieved 0.94 (±0.02), 2.46 (±0.5) mm, and 0.53 (±0.14) mm for DSC, HD95, and ASD respectively. The proposed auto-segmentation approach generated TBV and CTV masks in ∼11 seconds per CT volume, implying significantly improved efficiency compared to manual contouring.

CONCLUSION

We developed a comprehensive DL framework mimicking clinical contouring practice for auto-segmentation of target volumes in S-PBI. The results demonstrated high levels of agreement between the predicted contours and physicians' manual contours. The approach is promising for improving the efficiency and accuracy of the on-line treatment planning workflow, such as adaptive based S-PBI.

Stereotactic Radiotherapy or Whole Brain Radiotherapy Combined with Pyrotinib and Capecitabine in HER2-Positive Advanced Breast Cancer Patients with Brain Metastases (BROPTIMA): A Prospective, Phase Ib/II Single-Arm Clinical Study

PURPOSE/OBJECTIVE(S)

Approximately half of patients with advanced HER2-positive breast cancer (BC) will develop brain metastases (BM) over time. Local therapy including stereotactic radiotherapy (SRT) and whole brain radiotherapy (WBRT) is the main initial treatment in malignant tumor patients with BM. However, more than 50% patients after radiotherapy in one year suffered intracranial recurrence. Pyrotinib, a small molecule, irreversible, pan-ErbB receptor tyrosine kinase inhibitor (TKI), has a high potency for controlling BM and reducing the occurrence of brain metastases in advanced HER2-positive BC patients. We hypothesized that SRT or WBRT combined with pyrotinib and capecitabine could decrease intracranial progression in HER2 positive BC with newly diagnosed BM.

MATERIALS/METHODS

In this prospective single-arm phase Ib/II trial (NCT04582968), eligible patients were assigned to either fractionated stereotactic radiotherapy (FSRT) or whole-brain radiation therapy (WBRT), combined with pyrotinib and capecitabine. The primary endpoint was one-year CNS progression-free survival (PFS) rate. Secondary endpoints included intracranial objective response rate (IC-ORR) according to RANO-BM criteria, progression-free survival (PFS), overall survival (OS) and evaluation of safety and neurocognitive function.

RESULTS

From January 2020 to August 2022, 40 patients were enrolled. Twenty-nine patients were treated with FSRT in 8 Gy per fraction with 3 to 5 fractions and 11 were treated with WBRT in 3 Gy per fraction with 10 fractions, and then received chemotherapy in a time frame starting from 0 to 7 days after radiotherapy. At a median follow-up of 17.3 months, 1-year CNS-PFS rate was 74.9% (95% CI 61.9-90.7%) and median CNS-PFS was 18 months (95% CI, 15.5 to NA months). One-year PFS rate was 66.9% (53.1-84.2%) and median PFS time was 17.6 months (95% CI 12.8-34.1 months). The best intracranial response rate (IC-ORR: complete response and partial response) was 92.5% (37/40). The most common grade 3 or worse toxicity was diarrhea (7.5%) and asymptomatic radiation necrosis was detected in 4 of 67(6.0%) lesions treated with FSRT. No differences of neurocognitive function evaluated by MMSE (Mini-Mental State Exam) were observed between different groups at any time point.

CONCLUSION

Radiotherapy combined with pyrotinib and capecitabine resulted in a promising efficacy that crossed the pre-specified boundary in patients with HER2-positive advanced breast cancer with brain metastases. This is the first prospective study showing the efficacy and safety of CNS radiotherapy concurrent with pyrotinib and capecitabine in patients with BM from HER2-positive breast cancer. Further investigation in a randomized controlled study is warranted.

Expression of FOXO3 in the skin follicles of goose embryos during embryonic development

1. The Forkhead box O3 (FOXO3) transcription factor is a crucial regulator in controlling cell metabolism, proliferation, apoptosis, migration and response to oxidative stress. However, FOXO3 has not previously been studied much in the embryonic skin follicles of geese.2. This study used Zhedong white geese (Anser cygnoides), Jilin white geese (Anser cygnoides) and Hungarian white geese (Anser anser). The feather follicle structure in the dorsal skin during embryonic stages was examined with haematoxylin and eosin (HE) and Pollak staining. The FOXO3 protein content in the embryonic dorsal skin from feather follicles was detected using western blotting and quantitative real-time PCR.3. The mRNA expression level of FOXO3 in the dorsal skin of Jilin white geese was highly expressed on embryonic day 23 (E23; P < 0.01), while mRNA expression of FOXO3 was highly expressed in the feather follicle of Hungarian white geese at E28 (P < 0.01). The expression of FOXO3 protein mainly concentrated in the early embryonic phase among these goose breeds (P < 0.05). This suggested that FOXO3 plays a crucial role in the development and growth of embryonic dorsal skin of feather follicles. The location of the FOXO3 protein was determined using the IHC technique, which further verified the effect of FOXO3 in the dorsal skin for feather follicles during embryogenesis.4. The study demonstrated the differential expression and localisation of the FOXO3 gene among different goose species. It was speculated that the gene could potentially improve goose feather follicle development and feather-related traits and provide a basis for further understanding of FOXO3 function in the dorsal tissue of goose embryos.

LncRNA AOC4P impacts the differentiation of macrophages and T-lymphocyte by regulating the NF-κB pathways of KGN cells: Potential pathogenesis of polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is a multifactorial endocrine disease, which is an important cause of female infertility worldwide. PCOS patients are in a state of chronic low-grade inflammation, and immune imbalance is considered as a potential cause of its pathogenesis.

METHODS

The expression of AOC4P in PCOS and normal ovarian granulosa cells (GCs) was detected by real-time quantitative PCR. KGN cells were induced by dihydrotestosterone at 500 ng/mL to construct the PCOS model. After lentivirus-infected, KGN cells were constructed with AOC4P overexpression cell lines, the proliferation and apoptosis levels of KGN cells in AOC4P and NC groups were detected. Human monocyte cell line (THP-1)-derived macrophages and peripheral blood mononuclear cells (PBMC) were co-cultured with KGN cells for 48 h, respectively, and the differentiation of macrophages and CD4+ T cells were detected by flow cytometry.

RESULTS

Decreased AOC4P expression was found in PCOS patients. After constructing the PCOS cell model, we observed that overexpression of AOC4P promoted KGN cell proliferation and inhibited apoptosis. After co-culture with AOC4P overexpressed KGN cells, M1 macrophages decreased, M2 macrophages increased, T helper cells type 1 (Th1)/Th2 ratio increased, and regulatory T cell (Treg) cells increased. Finally, we found that AOC4P inhibited the activation of the nuclear factor κ B (NF-κB) pathway in KGN cells.

CONCLUSIONS

In this study, we found that AOC4P regulated the NF-κB signaling pathway by inhibiting the phosphorylation of P65, thereby affecting the proliferation and apoptosis of GCs, altering the differentiation of macrophages and T cells, thus contributing to the pathogenesis of PCOS.

Brachytherapy Dose Prediction Based on Monte Carlo Simulations Using Artificial Neural Networks

PURPOSE/OBJECTIVE(S)

The current brachytherapy dose calculation is still based on the oversimplified water kernel superposition algorithm recommended by AAPM TG43. Monte Carlo (MC) method provides high accuracy in dose calculation. However, the MC simulation is computationally intensive and too slow to use in the time-sensitive clinical workflow. This study aims to develop a fast neural network (SK-UNet) to predict 3D brachytherapy dose distribution calculated by the MC simulations.

MATERIALS/METHODS

We hypothesize that the tracks of Ir-192 inside applicators are essential in dose map prediction and the Selective Kernel Networks (SK) can be employed to emphasize the contribution of the applicator in training. We then included SK in UNet to select appropriate receptive field sizes as needed. The network inputs were CT images of patient anatomy, binary masks of HRCTV, bladder, rectum, and source tracks, and the output was the predicted dose map. Totally, 120 cases were used for training and 30 for testing. All clinically common applicators (e.g., vaginal, tandem and ovoid, multi-channel applicator, free needles, etc.) were involved in the study. Model performance was evaluated by the mean absolute error (MAE) of DVH dosimetric metrics and dose distribution metrics between ground truth (GT) and prediction. A smaller MAE indicated a more accurate dose prediction. Dose distribution metrics include the overdose volume index (ODI), target conformity (TC), dose homogeneity index (DHI), and conformal index (COIN). GT was dose calculated by MC simulations. 3D Gamma analysis was also involved.

RESULTS

As shown in Table 1, compared with GT, SK-Net showed comparable DVH dosimetric metrics with 0.28±0.19 deviation for HRCTV D90%, 0.21±0.16 deviation for bladder D2cc, and 0.25±0.22 deviation for rectum D2cc. In dose distribution metrics, the deviations between GT and prediction were TC = 0.04±0.02, ODI = 0.03±0.03, DHI = 0.02±0.02, and COIN = 0.02±0.03. The gamma passing rate was 93%±6%. The 3D dose map prediction for each patient takes about 6s on average in an NVIDIA GeForce RTX 3060 GPU compared to hours with MC simulations.

CONCLUSION

SK-Net demonstrated comparable performance to the MC simulation but with a significantly shorter execution time, taking only 6 seconds on average. It offered a solution to the trade-off between accuracy and speed and has the potential to serve as an alternative to the time-consuming MC simulation in brachytherapy. The developed technique is believed to have the potential for future application with other types of radiation sources and cancers.

A Radiogenomic Machine Learning Model for Glioblastoma Post-Resection Overall Survival Group Prediction

PURPOSE/OBJECTIVE(S)

Novel methods are needed to better predict outcomes and tailor personalized therapies for patients with glioblastoma (GBM). To improve post-resection survival prediction in GBM patients, we developed a machine learning model that utilized 1) radiomic computational biomarkers from pre-resection multi-parametric MRI (mp-MRI) images, and 2) clinical information including tumor molecular features and extent of surgical resection.

MATERIALS/METHODS

A cohort of 406 GBM patients treated with surgical resection was studied. Each patient received a pre-resection mp-MRI that included T1, contrast-enhanced T1 (T1-ce), T2, and FLAIR sequences. Three tumor subregions, i.e., enhanced tumor, tumor core, and whole tumor, were segmented with radiologists' correction. Based on survival outcomes in the literature, the cohort was categorized into three survival groups: group A (<9 mos, n = 148), B (9-21 mos, n = 181), and C (21+ mos, n = 77). We first extracted 88 radiomic features from each tumor subregion on each MR volume, and Z-score normalization was adopted. Three other patient-specific factors, including age, resection status (subtotal versus gross total), and IDH1 status, were concatenated with the radiomic features as a synthesized patient-specific feature vector. We then designed a two-step machine learning model: using the patient-specific feature vectors, the model 1) identified patients in group A with the shortest predicted survival using a balanced random forest (BRF) classifier, and 2) used a 2nd BRF classifier to segregate the remaining patients into groups B and C. For model training, a 7:3 training/test sample ratio was adopted, and 100 model versions were acquired through random validation sample assignments to study model robustness. Sensitivity, specificity, and accuracy results of each group were calculated, and an overall ROC was generated to represent the model's overall performance.

RESULTS

The model demonstrated acceptable prediction performance with an ROC AUC value at 0.68. Individually, the model achieved good prediction accuracies for short and long-term survival prediction (Groups A and C), though we observed relatively limited accuracy in medium survival prediction (Group B). Model sensitivity in group A was promising, but was limited in the remaining two groups. Feature weight analysis showed that radiomic features from the enhanced tumor subregion were the leading variables in the BRF classifier.

CONCLUSION

The developed radiogenomic machine learning model predicts GBM post-resection overall survival outcomes. Future work is necessary to further improve model sensitivity for patients with medium and long-term predicted survival.

A risk prognostic model for patients with esophageal squamous cell carcinoma basing on cuproptosis and ferroptosis

BACKGROUND

Cuproptosis, a form of copper-dependent programmed cell death recently presented by Tsvetkov et al., have been identified as a potential therapeutic target for refractory cancers and ferroptosis, a well-known form describing iron-dependent cell death. However, whether the crossing of cuproptosis-related genes and ferroptosis-related genes can introduce some new idea, thus being used as a novel clinical and therapeutic predictor in esophageal squamous cell carcinoma (ESCC) remains unknown.

METHODS

We collected ESCC patient data from the Gene Expression Omnibus and the Cancer Genome Atlas databases and used Gene Set Variation Analysis to score each sample based on cuproptosis and ferroptosis. We then performed weighted gene co-expression network analysis to identify cuproptosis and ferroptosis-related genes (CFRGs) and construct a ferroptosis and cuproptosis-related risk prognostic model, which we validated using a test group. We also investigated the relationship between the risk score and other molecular features, such as signaling pathways, immune infiltration, and mutation status.

RESULTS

Four CFRGs (MIDN, C15orf65, COMTD1 and RAP2B) were identified to construct our risk prognostic model. Patients were classified into low- and high-risk groups based on our risk prognostic model and the low-risk group showed significantly higher survival possibilities (P < 0.001). We used the "GO", "cibersort" and "ESTIMATE" methods to the above-mentioned genes to estimate the relationship among the risk score, correlated pathways, immune infiltration, and tumor purity.

CONCLUSION

We constructed a prognostic model using four CFRGs and demonstrated its potential clinical and therapeutic guidance value for ESCC patients.

Observation of New Ω_{c}^{0} States Decaying to the Ξ_{c}^{+}K^{-} Final State

Two new excited states, Ω_{c}(3185)^{0} and Ω_{c}(3327)^{0}, are observed in the Ξ_{c}^{+}K^{-} invariant-mass spectrum using proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9  fb^{-1}. Five previously observed excited Ω_{c}^{0} states are confirmed, namely Ω_{c}(3000)^{0}, Ω_{c}(3050)^{0}, Ω_{c}(3065)^{0}, Ω_{c}(3090)^{0}, and Ω_{c}(3119)^{0}. The masses and widths of these seven states are measured with the highest precision to date.

Evidence of a J/ψK_{S}^{0} Structure in B^{0}→J/ψϕK_{S}^{0} Decays

An amplitude analysis of B^{0}→J/ψϕK_{S}^{0} decays is performed using proton-proton collision data, corresponding to an integrated luminosity of 9  fb^{-1}, collected with the LHCb detector at center-of-mass energies of 7, 8, and 13 TeV. Evidence with a significance of 4.0 standard deviations of a structure in the J/ψK_{S}^{0} system, named T_{ψs1}^{θ}(4000)^{0}, is seen, with its mass and width measured to be 3991_{-10}^{+12} _{-17}^{+9}  MeV/c^{2} and 105_{-25}^{+29} _{-23}^{+17}  MeV, respectively, where the first uncertainty is statistical and the second systematic. The T_{ψs1}^{θ}(4000)^{0} state is likely to be the isospin partner of the T_{ψs1}^{θ}(4000)^{+} state, previously observed in the J/ψK^{+} system of the B^{+}→J/ψϕK^{+} decay. When isospin symmetry for the charged and neutral T_{ψs1}^{θ}(4000) states is assumed, the signal significance increases to 5.4 standard deviations.

Correction: Ding et al. Full-Right Full-Left Split Liver Transplantation for Two Adult Recipients: A Single-Center Experience in China. J. Clin. Med. 2023, 12, 3782

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Measurement of the Ratios of Branching Fractions R(D^{*}) and R(D^{0})

The ratios of branching fractions R(D^{*})≡B(B[over ¯]→D^{*}τ^{-}ν[over ¯]_{τ})/B(B[over ¯]→D^{*}μ^{-}ν[over ¯]_{μ}) and R(D^{0})≡B(B^{-}→D^{0}τ^{-}ν[over ¯]_{τ})/B(B^{-}→D^{0}μ^{-}ν[over ¯]_{μ}) are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0  fb^{-1} of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode τ^{-}→μ^{-}ν_{τ}ν[over ¯]_{μ}. The measured values are R(D^{*})=0.281±0.018±0.024 and R(D^{0})=0.441±0.060±0.066, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is ρ=-0.43. The results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the standard model.

Measurement of the Prompt D^{0} Nuclear Modification Factor in p-Pb Collisions at sqrt[s_{NN}]=8.16 TeV

The production of prompt D^{0} mesons in proton-lead collisions in both the forward and backward rapidity regions at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=8.16  TeV is measured by the LHCb experiment. The nuclear modification factor of prompt D^{0} mesons is determined as a function of the transverse momentum p_{T}, and the rapidity in the nucleon-nucleon center-of-mass frame y^{*}. In the forward rapidity region, significantly suppressed production with respect to pp collisions is measured, which provides significant constraints on models of nuclear parton distributions and hadron production down to the very low Bjorken-x region of ∼10^{-5}. In the backward rapidity region, a suppression with a significance of 2.0-3.8 standard deviations compared to parton distribution functions in a nuclear environment expectations is found in the kinematic region of p_{T}>6  GeV/c and -3.25 Collapse

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Measurement of the Time-Integrated CP Asymmetry in D^{0}→K^{-}K^{+} Decays

The time-integrated CP asymmetry in the Cabibbo-suppressed decay D^{0}→K^{-}K^{+} is measured using proton-proton collision data, corresponding to an integrated luminosity of 5.7  fb^{-1} collected at a center-of-mass energy of 13 TeV with the LHCb detector. The D^{0} mesons are required to originate from promptly produced D^{*+}→D^{0}π^{+} decays, and the charge of the companion pion is used to determine the flavor of the charm meson at production. The time-integrated CP asymmetry is measured to be A_{CP}(K^{-}K^{+})=[6.8±5.4±1.6]×10^{-4} where the first uncertainty is statistical and the second systematic. The direct CP asymmetries in D^{0}→K^{-}K^{+} and D^{0}→π^{-}π^{+} decays, a_{K^{-}K^{+}}^{d} and a_{π^{-}π^{+}}^{d}, are derived by combining A_{CP}(K^{-}K^{+}) with the time-integrated CP asymmetry difference, ΔA_{CP}=A_{CP}(K^{-}K^{+})-A_{CP}(π^{-}π^{+}), and other inputs, giving a_{K^{-}K^{+}}^{d}=(7.7±5.7)×10^{-4},a_{π^{-}π^{+}}^{d}=(23.2±6.1)×10^{-4},with a correlation coefficient corresponding to ρ=0.88. The compatibility of these results with CP symmetry is 1.4 and 3.8 standard deviations for D^{0}→K^{-}K^{+} and D^{0}→π^{-}π^{+} decays, respectively. This is the first evidence for direct CP violation in a specific D^{0} decay.

Measurement of the Branching Fractions B(B^{0}→pp[over ¯]pp[over ¯]) and B(B_{s}^{0}→pp[over ¯]pp[over ¯])

Searches for the rare hadronic decays B^{0}→pp[over ¯]pp[over ¯] and B_{s}^{0}→pp[over ¯]pp[over ¯] are performed using proton-proton collision data recorded by the LHCb experiment and corresponding to an integrated luminosity of 9  fb^{-1}. Significances of 9.3σ and 4.0σ, including statistical and systematic uncertainties, are obtained for the B^{0}→pp[over ¯]pp[over ¯] and B_{s}^{0}→pp[over ¯]pp[over ¯] signals, respectively. The branching fractions are measured relative to the topologically similar normalization decays B^{0}→J/ψ(→pp[over ¯])K^{*0}(→K^{+}π^{-}) and B_{s}^{0}→J/ψ(→pp[over ¯])⁢ϕ(→K^{+}K^{-}). The branching fractions are measured to be B(B^{0}→pp[over ¯]pp[over ¯])=(2.2±0.4±0.1±0.1)×10^{-8} and B(B_{s}^{0}→pp[over ¯]pp[over ¯])=(2.3±1.0±0.2±0.1)×10^{-8}. In these measurements, the first uncertainty is statistical, the second is systematic, and the third one is due to the external branching fraction of the normalization channel.

Controlling Surface Chemical Inhomogeneity of Ni2 P/MoNiP2 /MoP Heterostructure Electrocatalysts for Efficient Hydrogen Evolution Reaction

Crystalline/amorphous phase engineering is demonstrated as a powerful strategy for electrochemical performance optimization. However, it is still a considerable challenge to prepare transition metal-based crystalline/amorphous heterostructures because of the low redox potential of transition metal ions. Herein, a facile H2 -assisted method is developed to prepare ternary Ni2 P/MoNiP2 /MoP crystalline/amorphous heterostructure nanowires on the conductive substrate. The characterization results show that the content of the MoNiP2 phase and the crystallinity of the MoP phase can be tuned by simply controlling the H2 concentration. The obtained electrocatalyst exhibits a superior alkaline hydrogen evolution reaction performance, delivering overpotentials of 20 and 76 mV to reach current densities of 10 and 100 mA cm-2 with a Tafel slope of 30.6 mV dec-1 , respectively. The catalysts also reveal excellent stability under a constant 100 h operation, higher than most previously reported electrocatalysts. These striking performances are ascribed to the optimized hydrogen binding energy and favorable hydrogen adsorption/desorption kinetics. This work not only exhibits the potential application of ternary Ni2 P/MoNiP2 /MoP crystalline/amorphous heterostructure nanowires catalysts for practical electrochemical water splitting, but also paves the way to prepare non-noble transition metal-based electrocatalysts with optimized crystalline/amorphous heterostructures.

Erratum: Global Polarization of Ξ and Ω Hyperons in Au+Au Collisions at sqrt[s_{NN}]=200 GeV [Phys. Rev. Lett. 126, 162301 (2021)]

This corrects the article DOI: 10.1103/PhysRevLett.126.162301.