DECIDE: A decoupled semantic and boundary learning network for precise osteosarcoma segmentation by integrating multi-modality MRI

Automated Osteosarcoma Segmentation in Multi-modality MRI (AOSMM) holds clinical significance for effective tumor evaluation and treatment planning. However, the precision of AOSMM is challenged by the diverse characteristics of multi-modality MRI and the inherent heterogeneity and boundary ambiguity of osteosarcoma. While numerous methods have made significant strides in automated osteosarcoma segmentation, they primarily focused on the use of a single MRI modality and overlooked the potential benefits of integrating complementary information from other MRI modalities. Furthermore, they did not adequately model the long-range dependencies of complex tumor features, which may lead to insufficiently discriminative feature representations. To this end, we propose a decoupled semantic and boundary learning network (DECIDE) to achieve precise AOSMM with three functional modules. The Multi-modality Feature Fusion and Recalibration (MFR) module adaptively fuses and recalibrates multi-modality features by exploiting their channel-wise dependencies to compute low-rank attention weights for effectively aggregating useful information from different MRI modalities, which promotes complementary learning between multi-modality MRI and enables a more comprehensive tumor characterization. The Lesion Attention Enhancement (LAE) module employs spatial and channel attention mechanisms to capture global contextual dependencies over local features, significantly enhancing the discriminability and representational capacity of intricate tumor features. The Boundary Context Aggregation (BCA) module further enhances semantic representations by utilizing boundary information for effective context aggregation while also ensuring intra-class consistency in cases of boundary ambiguity. Substantial experiments demonstrate that DECIDE achieves exceptional performance in osteosarcoma segmentation, surpassing state-of-the-art methods in terms of accuracy and stability.

Cardiac MRI feature-tracking-derived torsion mechanics in systolic and diastolic dysfunction in systemic light-chain cardiac amyloidosis

AIM

To describe the myocardial torsion mechanics in cardiac amyloidosis (CA), and evaluate the correlations between left ventricle (LV) torsion mechanics and conventional parameters using cardiac magnetic resonance imaging feature tracking (CMR-FT).

MATERIALS AND METHODS

One hundred and thirty-nine patients with light-chain CA (AL-CA) were divided into three groups: group 1 with preserved systolic function (LV ejection fraction [LVEF] ≥50%, n=55), group 2 with mildly reduced systolic function (40% ≤ LVEF <50%, n=51), and group 3 with reduced systolic function (LVEF <40%, n=33), and compared with age- and gender-matched healthy controls (n=26). All patients underwent cine imaging and late gadolinium-enhancement (LGE). Cine images were analysed offline using CMR-FT to estimate torsion parameters.

RESULTS

Global torsion, base-mid torsion, and peak diastolic torsion rate (diasTR) were significantly impaired in patients with preserved systolic function (p<0.05 for all), whereas mid-apex torsion and peak systolic torsion rate (sysTR) were preserved (p>0.05 for both) compared with healthy controls. In patients with mildly reduced systolic function, global torsion and base-mid torsion were lower compared to those with preserved systolic function (p<0.05 for both), while mid-apex torsion, sysTR, and diasTR were preserved (p>0.05 for all). In patients with reduced systolic function, only sysTR was significantly worse compared with mildly reduced systolic function (p<0.05). At multivariable analysis, right ventricle (RV) end-systolic volume RVESV index and NYHA class were independently related to global torsion, whereas LVEF was independently related to sysTR. RV ejection fraction (RVEF) was independently related to diasTR. LV global torsion performed well (AUC 0.71; 95% confidence interval [CI]: 0.61, 0.77) in discriminating transmural from non-transmural LGE in AL-CA patients.

CONCLUSION

LV torsion mechanics derived by CMR-FT could help to monitor LV systolic and diastolic function in AL-CA patients and function as a new imaging marker for LV dysfunction and LGE transmurality.

Hybrid Moiré Excitons and Trions in Twisted MoTe2-MoSe2 Heterobilayers

We report experimental and theoretical studies of MoTe2-MoSe2 heterobilayers with rigid moiré superlattices controlled by the twist angle. Using an effective continuum model that combines resonant interlayer electron tunneling with stacking-dependent moiré potentials, we identify the nature of moiré excitons and the dependence of their energies, oscillator strengths, and Landé g-factors on the twist angle. Within the same framework, we interpret distinct signatures of bound complexes among electrons and moiré excitons in nearly collinear heterostacks. Our work provides a fundamental understanding of hybrid moiré excitons and trions in MoTe2-MoSe2 heterobilayers and establishes the material system as a prime candidate for optical studies of correlated phenomena in moiré lattices.

Automatic artery/vein classification methods for retinal blood vessel: A review

Automatic retinal arteriovenous classification can assist ophthalmologists in disease early diagnosis. Deep learning-based methods and topological graph-based methods have become the main solutions for retinal arteriovenous classification in recent years. This paper reviews the automatic retinal arteriovenous classification methods from 2003 to 2022. Firstly, we compare different methods and provide comparison tables of the summary results. Secondly, we complete the classification of the public arteriovenous classification datasets and provide the annotation development tables of different datasets. Finally, we sort out the challenges of evaluation methods and provide a comprehensive evaluation system. Quantitative and qualitative analysis shows the changes in research hotspots over time, Quantitative and qualitative analyses reveal the evolution of research hotspots over time, highlighting the significance of exploring the integration of deep learning with topological information in future research.

Clinical features and prognostic factors of nasopharyngeal carcinoma with brain metastases

BACKGROUND

Brain metastasis in nasopharyngeal carcinoma is a rare occurrence, and the characteristics of patients in this subgroup remain poorly defined. This study aims to delineate the clinical features, treatment modalities, prognostic factors, and survival of nasopharyngeal carcinoma patients with brain metastasis.

METHODOLOGY

A retrospective analysis was conducted on patients diagnosed with nasopharyngeal carcinoma who developed brain metastasis and were treated at the Sun Yat-sen University Cancer Center between July 2000 and July 2023. Clinical data from patients were collected and used to assess their survival after brain metastases and prognostic factors.

RESULTS

Among 82,434 nasopharyngeal carcinoma patients, 40 (0.06 %) developed Brain metastasis with a median follow-up of 5.1 years. The predominant histological subtype was non-keratinizing squamous cell carcinoma (85 %). The median post-BM survival was 25 months. The age, the Eastern Cooperative Oncology Group (ECOG), and the procedural treatment of BM were prognostic factors. Notably, patients receiving local treatments had significantly prolonged post-BM survival compared to those receiving systemic therapy alone (median, 47.00 vs. 11.00 months; p = 0.011).

CONCLUSIONS

This is the largest cohort of brain metastasis in nasopharyngeal carcinoma to date. Local therapeutic measures after brain metastasis can significantly enhance the prognosis of these patients, particularly when radiotherapy is applied.

Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities

Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches.

Precision-controlled ultrafast electron microscope platforms. A case study: Multiple-order coherent phonon dynamics in 1T-TaSe2 probed at 50 fs-10 fm scales

We report on the first detailed beam tests attesting the fundamental principle behind the development of high-current-efficiency ultrafast electron microscope systems where a radio frequency (RF) cavity is incorporated as a condenser lens in the beam delivery system. To allow for the experiment to be carried out with a sufficient resolution to probe the performance at the emittance floor, a new cascade loop RF controller system is developed to reduce the RF noise floor. Temporal resolution at 50 fs in full-width-at-half-maximum and detection sensitivity better than 1% are demonstrated on exfoliated 1T-TaSe2 system under a moderate repetition rate. To benchmark the performance, multi-terahertz edge-mode coherent phonon excitation is employed as the standard candle. The high temporal resolution and the significant visibility to very low dynamical contrast in diffraction signals via high-precision phase-space manipulation give strong support to the working principle for the new high-brightness femtosecond electron microscope systems.

Intracranial response pattern, tolerability and biomarkers associated with brain metastases in non-small cell lung cancer treated by tislelizumab plus chemotherapy

Background

Programmed cell death protein-1/programmed cell death protein-ligand 1 (PD-1/PD-L1) inhibitor and chemotherapy are the standard treatment for advanced non-small cell lung cancer (NSCLC) without sensitizing mutations. However, patients with untreated, symptomatic or recently-irradiated brain metastases (BMs) are mostly excluded from immunochemotherapy trials. This study aims to evaluate the intracranial response pattern, tolerability and biomarkers of tislelizumab plus chemotherapy in NSCLC with untreated, symptomatic or recently-irradiated BM.

Methods

This multicenter, single-arm, phase 2 trial enrolled patients with treatment-naïve, brain-metastasized NSCLC. BM could be untreated or irradiated. Symptomatic or recently-irradiated BMs that were deemed clinically stable were allowed. Patients received tislelizumab (200 mg) plus pemetrexed (500 mg/m2) and carboplatin (AUC =5) on day 1 every 3 weeks for 4 cycles, followed by maintenance with tislelizumab plus pemetrexed. Primary endpoint was 1-year progression-free survival (PFS) rate. Secondary endpoints included intracranial efficacy and tolerability. PD-L1 expression, tumor mutational burden (TMB) and genomic alterations were evaluated as potential biomarkers.

Results

A total of 36 patients were enrolled, 19.2% had prior brain radiotherapy, 8.3% had symptomatic BMs that required corticosteroids ≤10 mg/d or antiepileptics. Confirmed systemic and intracranial ORR (iORR) was 43.8% and 46.7%, respectively. One-year systematic PFS rate and One-year iPFS rate was 36.8% and 55.8%, respectively. About 41.7% patients had neurological adverse events, 90% patients had concordant intracranial-extracranial responses. No intracranial pseudoprogression or hyperprogression occurred. Patients with prior brain radiation trended towards higher systemic (83.3% vs. 34.6%) and iORR (75.0% vs. 42.3%). Similar intracranial efficacy was observed in tumors with different PD-L1 and TMB levels, while alterations in cytokine receptors pathway predicted higher iORR (P=0.081), prolonged systematic PFS [hazard ratio (HR) =0.16, P=0.021] and overall survival (OS) (HR =0.71, P=0.029).

Conclusions

Untreated or irradiated BMs in NSCLC follows a conventional response and progression pattern under immunochemotherapy with altered cytokine receptors pathway being a potential biomarker for systemic and intracranial outcomes.

BAP31 Promotes Adhesion Between Endothelial Cells and Macrophages Through the NF-κB Signaling Pathway in Sepsis

Purpose

To investigate the role of B cell receptor associated protein 31 (BAP31) in the pathogenesis of sepsis.

Methods

Cecal ligation and puncture (CLP)-induced C57BL/6J mice, and LPS-challenged endothelial cells (HUVECs) were established to mimic a sepsis animal model and a sepsis cell model, respectively. Cre/LoxP and shRNA methods were used for BAP31 knockdown in vivo and in vitro respectively. Neutrophils/macrophages-endothelial cocultures were used to evaluate neutrophils or macrophages infiltration and adhesion to endothelial cells. Cox proportional hazards model was used to evaluate the survival time of mice. Western blotting (WB) and Quantitative real-time polymerase chain reaction (qRT-PCR) were used to detect toll-like receptor (TLR) signaling pathway, transforming growth factor β activated kinase 1 (TAK1) signaling pathway and phosphoinositide-3 kinases-protein kinase B (PI3K/AKT) signaling pathway.

Results

Deletion of BAP31 reduced CLP-induced mortality of mice, histological damage with less interstitial edema, and neutrophils and macrophages infiltration. IHC and IF showed that BAP31 knockdown significantly decreases the expressions of ICAM1 and VCAM1 both in vivo and in vitro. Coculture showed that LPS-induced neutrophils or macrophages adhesion to endothelial cells was significantly weakened in BAP31 knockdown cells. In addition, BAP31 knockdown of endothelial cells decreased the expression of CD80 and CD86 on the surface of macrophages as well as interleukin 1β (IL-1β) and tumor necrosis factor α (TNF-α) during sepsis. Mechanistically, LPS-induced the activation of TLR4, MyD88 and TRAF6, and the phosphorylation of TAK1, PI3K, AKT, IκBα and IKKα/β, resulting in activation of nuclear factor kappa B (NF-κB) p65 in endothelial cells. However, BAP31 knockdown significantly reversed the expressions of associated proteins.

Conclusion

BAP31 up-regulated the expressions of ICAM1 and VCAM1 in endothelial cells leading to sepsis-associated organ injury. This may be involved in activation of TLR signaling pathway, TAK1 pathway, and PI3K-AKT signaling pathway.

Hierarchical Porous Nonprecious High-entropy Alloys for Ultralow Overpotential in Hydrogen Evolution Reaction

Water electrolysis is considered the cleanest method for hydrogen production. However, the widespread popularization of water splitting is limited by the high cost and scarce resources of efficient platinum group metals. Hence, it is imperative to develop an economical and high-performance electrocatalyst to improve the efficiency of hydrogen evolution reaction (HER). In this study, a hierarchical porous sandwich structure is fabricated through dealloying FeCoNiCuAl2 Mn high-entropy alloy (HEA). This free-standing electrocatalyst shows outstanding HER performance with a very small overpotential of 9.7 mV at 10 mA cm-2 and a low Tafel slope of 56.9 mV dec-1 in 1 M KOH solution, outperforming commercial Pt/C. Furthermore, this electrocatalytic system recorded excellent reaction stability over 100 h with a constant current density of 100 mA cm-2 . The enhanced electrochemical activity in high-entropy alloys results from the cocktail effect, which is detected by density functional theory (DFT) calculation. Additionally, micron- and nano-sized pores formed during etching boost mass transfer, ensuring sustained electrocatalyst performance even at high current densities. This work provides a new insight for development in the commercial electrocatalysts for water splitting.

Phase I trial of apatinib and paclitaxel+oxaliplatin+5-FU/levoleucovorin for treatment-naïve advanced gastric cancer

Chinese guidelines recommend POF (paclitaxel, oxaliplatin, and 5-FU/levoleucovorin) as first-line treatment for advanced gastric cancer (AGC). Apatinib can augment the antitumor effect of paclitaxel, oxaliplatin, or fluorouracil in preclinical studies of AGC. A phase I clinical trial was conducted to evaluate the anticancer activity and maximum tolerated dose (MTD) of apatinib plus POF in treatment-naïve patients with AGC and to establish a recommended phase II dose. Participants received escalating doses of daily oral apatinib (250, 375, 500, 625, 750, and 850 mg) plus POF every 2 weeks using a conventional "3 + 3" study design. Among 21 treated patients, one experienced a dose-limiting toxicity (grade 3 skin ulceration at 850 mg). No MTD was reached. Apatinib 750 mg plus POF was recommended for phase II study. The most common grade 3-4 adverse events (AEs) were neutropenia (33.3%), mucositis (14.3%), and hand-foot syndrome (14.3%). Median progression-free and overall survival were 10.4 months (95% CI: 6.3, 14.6) and 18.4 months (95% CI: 9.8, 28.2), respectively. Apatinib up to 850 mg coadministered with POF was well tolerated with manageable AEs. The safety and anticancer activity of this regimen warrants its further investigation as first-line treatment for AGC in a larger study.

Estimating Addiction-Related Brain Connectivity by Prior-Embedding Graph Generative Adversarial Networks

The study of nicotine addiction mechanism is of great significance in both nicotine withdrawal and brain science. The detection of addiction-related brain connectivity using functional magnetic resonance imaging (fMRI) is a critical step in study of this mechanism. However, it is challenging to accurately estimate addiction-related brain connectivity due to the low-signal-to-noise ratio of fMRI and the issue of small sample size. In this work, a prior-embedding graph generative adversarial network (PG-GAN) is proposed to capture addiction-related brain connectivity accurately. By designing a dual-generator-based scheme, the addiction-related connectivity generator is employed to learn the feature map of addiction connection, while the reconstruction generator is used for sample reconstruction. Moreover, a bidirectional mapping mechanism is designed to maintain the consistency of sample distribution in the latent space so that addiction-related brain connectivity can be estimated more accurately. The proposed model utilizes prior knowledge embeddings to reduce the search space so that the model can better understand the latent distribution for the issue of small sample size. Experimental results demonstrate the effectiveness of the proposed PG-GAN.

Ningetinib plus gefitinib in EGFR-mutant non-small-cell lung cancer with MET and AXL dysregulations: A phase 1b clinical trial and biomarker analysis

BACKGROUND

MET and AXL dysregulations are implicated in acquired resistance to EGFR-TKIs in NSCLC. But consensus on the optimal definition for MET/AXL dysregulations in EGFR-mutant NSCLC is lacking. Here, we investigated the efficacy and tolerability of ningetinib (a MET/AXL inhibitor) plus gefitinib in EGFR-mutant NSCLC, and evaluated the clinical relevance of MET/AXL dysregulations by different definitions.

METHODS

Patients in this phase 1b dose-escalation/dose-expansion trial received ningetinib 30 mg/40 mg/60 mg plus gefitinib 250 mg once daily. Primary endpoints were tolerability (dose-escalation) and objective response rate (dose-expansion). MET/AXL status were analyzed using FISH and IHC.

RESULTS

Between March 2017 and January 2021, 108 patients were enrolled. The proportion of MET focal amplification, MET polysomy, MET overexpression, AXL amplification and AXL overexpression is 18.1 %, 5.6 %, 55.8 %, 8.1 % and 45.3 %, respectively. 6.8 % patients have concurrent MET amplification and AXL overexpression. ORR is 30.8 % for tumors with MET amplification, 0 % for MET polysomy, 24.1 % for MET overexpression, 20 % for AXL amplification and 27.6 % for AXL overexpression. For patients with concurrent MET amplification and AXL overexpression, ningetinib plus gefitinib provides an ORR of 80 %, DCR of 100 % and median PFS of 4.7 months. Tumors with higher MET copy number and AXL expression tend to have higher likelihood of response. Biomarker analyses show that MET focal amplification and overexpression are complementary in predicting clinical benefit from MET inhibition, while AXL dysregulations defined by an arbitrary level may dilute the efficacy of AXL blockade.

CONCLUSIONS

This study demonstrates that combined blockade of MET, AXL and EGFR is a feasible strategy for a subset of EGFR-mutant NSCLC.

TRIAL REGISTRATION

Chinadrugtrials.org.cn, CTR20160875.

Vegetation-fire feedbacks increase subtropical wildfire risk in scrubland and reduce it in forests

Climate dictates wildfire activity around the world. But East and Southeast Asia are an apparent exception as fire-activity variation there is unrelated to climatic variables. In subtropical China, fire activity decreased by 80% between 2003 and 2020 amid increased fire risks globally. Here, we assessed the fire regime, vegetation structure, fuel flammability and their interactions across subtropical Hubei, China. We show that tree basal area (TBA) and fuel flammability explained 60% of fire-frequency variance. Fire frequency and fuel flammability, in turn, explained 90% of TBA variance. These results reveal a novel system of scrubland-forest stabilized by vegetation-fire feedbacks. Frequent fires promote the persistence of derelict scrubland through positive vegetation-fire feedbacks; in forest, vegetation-fire feedbacks are negative and suppress fire. Thus, we attribute the decrease in wildfire activity to reforestation programs that concurrently increase forest coverage and foster negative vegetation-fire feedbacks that suppress wildfire.

ZNF689 deficiency promotes intratumor heterogeneity and immunotherapy resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive disease characterized by remarkable intratumor heterogeneity (ITH), which poses therapeutic challenges. However, the clinical relevance and key determinant of ITH in TNBC are poorly understood. Here, we comprehensively characterized ITH levels using multi-omics data across our center's cohort (n = 260), The Cancer Genome Atlas cohort (n = 134), and four immunotherapy-treated cohorts (n = 109). Our results revealed that high ITH was associated with poor patient survival and immunotherapy resistance. Importantly, we identified zinc finger protein 689 (ZNF689) deficiency as a crucial determinant of ITH formation. Mechanistically, the ZNF689-TRIM28 complex was found to directly bind to the promoter of long interspersed element-1 (LINE-1), inducing H3K9me3-mediated transcriptional silencing. ZNF689 deficiency reactivated LINE-1 retrotransposition to exacerbate genomic instability, which fostered ITH. Single-cell RNA sequencing, spatially resolved transcriptomics and flow cytometry analysis confirmed that ZNF689 deficiency-induced ITH inhibited antigen presentation and T-cell activation, conferring immunotherapy resistance. Pharmacological inhibition of LINE-1 significantly reduced ITH, enhanced antitumor immunity, and eventually sensitized ZNF689-deficient tumors to immunotherapy in vivo. Consistently, ZNF689 expression positively correlated with favorable prognosis and immunotherapy response in clinical samples. Altogether, our study uncovers a previously unrecognized mechanism underlying ZNF689 deficiency-induced ITH and suggests LINE-1 inhibition combined with immunotherapy as a novel treatment strategy for TNBC.

Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs

The accurate and efficient prediction of chlorophyll-a (Chl-a) concentration is crucial for the early detection of algal blooms in reservoirs. Nevertheless, predicting Chl-a concentration in multivariate time series poses a significant challenge due to the complex interrelationships within the aquatic environment and the discrete and non-stationary nature of online monitoring of water quality data. To address the aforementioned issue, this paper proposes a novel prediction model named SGMD-KPCA-BiLSTM (SKB) for predicting Chl-a concentration. The model combines two-stage data processing and machine learning (ML). To capture nonlinear relationships in multivariate time series data, the optimal data subset is determined by combining symplectic geometry mode decomposition (SGMD) and kernel principal component analysis (KPCA). This subset is then input into a bidirectional long short-term memory (BiLSTM) model, and the model's hyperparameters are optimized using the sparrow search algorithm (SSA) to improve the accuracy of predictions. The performance of the model was evaluated at Qiaodian Reservoir in Shandong, China. To assess its superiority, the evaluation criteria included the root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), coefficient of determination (R2), frequency histograms of the prediction error, and the Taylor diagram. The prediction performance of five single models, namely the back-propagation (BP) neural network, support vector regression (SVR), long short-term memory (LSTM), convolutional neural network with long short-term memory (CNN-LSTM), and BiLSTM, as well as three hybrid models, namely SGMD-LSTM, SGMD-KPCA-LSTM, and SGMD-BiLSTM, were compared against the SKB model. The results demonstrated that the SKB model performs best in predicting Chl-a concentration (R2 = 96.19%, RMSE = 1.05, MAE = 0.65, MAPE = 0.08). It significantly reduced the prediction error compared to other models for comparison. Furthermore, the multi-step predictive capabilities of the SKB model are also discussed. The analysis shows a decline in predictive performance with larger prediction time steps, and the SKB model exhibits slightly superior performance compared to the other model at corresponding prediction intervals. The model has significant advantages in terms of its ability to accurately predict the non-smooth and nonlinear Chl-a sequences observed by the online monitoring system. This study presents a potential solution for controlling and preventing reservoir eutrophication, as well as an innovative approach for predicting water quality.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Myokines and Biomarkers of Frailty in Older Inpatients with Undernutrition: A Prospective Study

BACKGROUND

Population aging might increase the prevalence of undernutrition in older people, which increases the risk of frailty. Numerous studies have indicated that myokines are released by skeletal myocytes in response to muscular contractions and might be associated with frailty. This study aimed to evaluate whether myokines are biomarkers of frailty in older inpatients with undernutrition.

METHODS

The frailty biomarkers were extracted from the Gene Expression Omnibus and Genecards datasets. Relevant myokines and health-related variables were assessed in 55 inpatients aged ≥ 65 years from the Peking Union Medical College Hospital prospective longitudinal frailty study. Serum was prepared for enzyme-linked immunosorbent assay using the appropriate kits. Correlations between biomarkers and frailty status were calculated by Spearman's correlation analysis. Multiple linear regression was performed to investigate the association between factors and frailty scores.

RESULTS

The prevalence of frailty was 13.21%. The bioinformatics analysis indicated that leptin, adenosine 5'-monophosphate-activated protein kinase (AMPK), irisin, decorin, and myostatin were potential biomarkers of frailty. The frailty group had significantly higher concentrations of leptin, AMPK, and MSTN than the robust group (p < 0.05). AMPK was significantly positively correlated with frailty (p < 0.05). The pre-frailty and frailty groups had significantly lower concentrations of irisin than the robust group (p < 0.05), whereas the DCN concentration did not differ among the groups. Multiple linear regression suggested that the 15 factors influencing the coefficients of association, the top 50% were the ADL score, MNA-SF score, serum albumin concentration, urination function, hearing function, leptin concentration, GDS-15 score, and MSTN concentration.

CONCLUSIONS

Proinflammatory myokines, particularly leptin, myostatin, and AMPK, negatively affect muscle mass and strength in older adults. ADL and nutritional status play major roles in the development of frailty. Our results confirm that identification of frailty relies upon clinical variables, myokine concentrations, and functional parameters, which might enable the identification and monitoring of frailty.

An established abdominal wall multidisciplinary team improves patient care and aids surgical decision making with complex ventral hernia patients

INTRODUCTION

Abdominal wall reconstruction (AWR) is an emerging subspecialty within general surgery. The practice of multidisciplinary team (MDT) meetings to aid decision making and improve patient care has been demonstrated, with widespread acceptance. This study presents our initial experience of over 150 cases of complex hernia patients discussed in a newly established MDT setting.

METHODS

From February 2020 to July 2022 (30-month period), abdominal wall MDTs were held bimonthly. Key stakeholders included upper and lower gastrointestinal surgeons, a gastrointestinal specialist radiologist, a plastic surgeon, a high-risk anaesthetist and two junior doctors integrated into the AWR clinical team. Meetings were held online, where patient history, past medical and surgical history, hernia characteristics and up-to-date computed tomography scans were discussed.

RESULTS

Some 156 patients were discussed over 18 meetings within the above period. Ninety-five (61%) patients were recommended for surgery, and 61 (39%) patients were recommended for conservative management or referred elsewhere. Seventy-eight (82%) patients were directly waitlisted, whereas seventeen (18%) required preoperative optimisation: three (18%) for smoking cessation, eleven (65%) for weight-loss management and three (18%) for specialist diabetic assessment and management. In total, 92 (59%) patients (including operative and nonoperative management) have been discharged to primary care.

DISCUSSION

A multidisciplinary forum for complex abdominal wall patients is a safe process that facilitates decision making, promotes education and improves patient care. As the AWR subspecialty evolves, our view is that the "complex hernia MDT" will become commonplace. We present our experience and share advice for others planning to establish an AWR centre.

Bioleaching of metals from spent fluid catalytic cracking catalyst using adapted Acidithiobacillus caldus

In this study, an adapted bioleaching strain of Acidithiobacillus caldus UVS10 was successfully developed. Batch tests and tests in bioreactor were conducted to evaluate the metals bioleaching performance of A. caldus UVS10 to spent FCC catalyst (SFCCC). Results of batch experiments showed the bioleaching efficiency of Ni, V, La, and Ce in SFCCC reached 19.40%, 22.06%, 53.75%, and 59.56%, respectively. High SFCCC pulp density inhibited the leaching of metals. Sb leaching was inhibited in acidic environment caused by A. caldus UVS10. Contents of Ni, V, La, and Ce in extracellular polymeric substances (EPS) were significantly higher than those intracellular. Accumulation of metal in EPS and cytosol increased with the increase of SFCCC pulp density. V was less intercepted by EPS than Ni, La, and Ce, because of lower toxicity. Experimental results in bioreactor showed that Ni, V, La, and Ce could be effectively leached by A. caldus UVS10 under 10% pulp density. The aeration and stirring operating environment in bioreactor improved the leaching efficiency of metals in SFCCC. After bioleached in bioreactor, the available fraction content of four metals in SFCCC decreased significantly. Ecological risk analysis demonstrated the environmental risks of bioleached SFCCC were significantly lower than raw SFCCC. Different reaction kinetic models were used to represent metals leaching behavior under bioleaching of A. caldus UVS10, leaching of La and Ce showed good agreement with the product layer diffusion model, while Ni and V leaching kinetics fit well with the surface chemical reaction models.

[Primary hepatic angiosarcoma: a clinicopathological analysis of nine cases]

Objective: To investigate the clinical manifestations, histomorphology, and differential diagnosis of primary hepatic angiosarcoma. Methods: Nine cases of primary hepatic angiosarcoma diagnosed in the Department of Pathology, the First Affiliated Hospital of Nanjing Medical University from January 2014 to December 2021 were collected, including biopsy and surgical specimens. The histomorphology, clinical, and radiologic findings were analyzed. The relevant literature was also reviewed. Results: There were six males and three females, aged 30 to 73 years (mean 57 years). Grossly, the growth pattern of the tumor was classified as either mass formation or non-mass formation (sinusoidal). Microscopically, the mass-forming primary hepatic angiosarcoma were further subdivided into vasoformative or non-vasoformative growth patterns; and those non-vasoformative tumors had either epithelioid, spindled, or undifferentiated sarcomatoid features. Sinusoidal primary hepatic angiosarcoma on the other hand presented with markedly dilated and congested blood vessels of varying sizes, with mild to moderately atypical endothelial cells. Follow-up in all nine cases revealed 8 mortality ranging from 1 to 18 months (mean 5 months) from initial diagnosis. One patient was alive with disease within a period of 48 months. Conclusions: Primary hepatic angiosarcoma is a rare entity with a wide spectrum of histomorphology, and often misdiagnosed. It should be considered when there are dilated and congested sinusoids, with overt nuclear atypia. The overall biological behavior is aggressive, and the prognosis is worse.

Design and Rationale for a Phase II/III, Randomized, Double-Blind, Placebo-Controlled Study of Sugemalimab as Consolidation Therapy in Patients With Limited-Stage Small-Cell Lung Cancer Who Have Not Progressed Following Concurrent or Sequential Chemoradiotherapy: The SURPASS Study

BACKGROUND

There is still a substantial need of more treatment options for patients with limited-stage small cell lung cancer (LS-SCLC). The standard therapy for LS-SCLC is platinum-based doublet chemotherapy administered concurrently with thoracic radiotherapy (cCRT). In China, sequential chemoradiotherapy (sCRT) is also a common practice. However, the disease inevitably progresses in most patients despite the curative intent and initial response.

MATERIALS AND METHODS

Sugemalimab is an anti-programmed death ligand-1 (PD-L1) antibody that improved clinical outcomes for patients with stage III non-small cell lung cancer after cCRT or sCRT. The SUPPASS study is a phase II/III, randomized, double-blind, placebo-controlled, multicenter study (NCT05623267) that aims to investigate the efficacy and tolerability of sugemalimab as consolidation therapy in patients with LS-SCLC who have no progression following cCRT or sCRT. Approximately 346 patients will be randomized in a 1:1 ratio to receive sugemalimab 1200 mg or placebo every 3 weeks for up to 12 months. The primary endpoint is progression-free survival (PFS). Key secondary endpoints include overall survival (OS), landmark PFS rate, landmark OS rate, objective response rate and safety. Longitudinal molecular residual disease (MRD) testing will be performed as preplanned exploratory analysis.

CONCLUSION

Study results will help demonstrate the efficacy and tolerability of anti-PD-L1 antibody consolidation therapy in LS-SCLC patients who have not progressed following cCRT or sCRT, and help determine the clinical implications of MRD in LS-SCLC.

Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer

Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.

Maximum Likelihood Estimation in Mixed Integer Linear Models

We consider the maximum likelihood (ML) parameter estimation problem for mixed integer linear models with arbitrary noise covariance. This problem appears in applications such as single frequency estimation, phase contrast imaging, and direction of arrival (DoA) estimation. Parameter estimates are found by solving a closest lattice point problem, which requires a lattice basis. In this letter, we present a lattice basis construction for ML parameter estimation and conclude with simulated results from DoA estimation and phase contrast imaging.

Recent advances in genetic etiology of non-syndromic deafness in children

Congenital auditory impairment is a prevalent anomaly observed in approximately 2-3 per 1,000 infants. The consequences associated with hearing loss among children encompass the decline of verbal communication, linguistic skills, educational progress, social integration, cognitive aptitude, and overall well-being. Approaches to reversing or preventing genetic hearing loss are limited. Patients with mild and moderate hearing loss can only use hearing aids, while those with severe hearing loss can only acquire speech and language through cochlear implants. Both environmental and genetic factors contribute to the occurrence of congenital hearing loss, and advancements in our understanding of the pathophysiology and molecular mechanisms underlying hearing loss, coupled with recent progress in genetic testing techniques, will facilitate the development of innovative approaches for treatment and screening. In this paper, the latest research progress in genetic etiology of non-syndromic deafness in children with the highest incidence is summarized in order to provide help for personalized diagnosis and treatment of deafness in children.

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast-enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.

Sarcopenia as a Predictor of Neoadjuvant Therapy-Related Toxicity in Esophageal Squamous Cell Carcinoma Patients

PURPOSE/OBJECTIVE(S)

Sarcopenia, characterized by loss of muscle mass, plays a critical role in patients with esophageal squamous cell cancer (ESCC). Preoperative chemoradiotherapy and immunotherapy in ESCC patients has been reported to improve survival. Therefore, we sought to evaluate the predictive value of preoperative sarcopenia for toxicity and pathological tumor response to neoadjuvant therapy (NAT) in ESCC patients.

MATERIALS/METHODS

A retrospective analysis was performed using a prospectively collected patient cohort of an academic cancer center diagnosed with cT2-4N0-3M0 ESCC between 2019-2022 and treated with neoadjuvant chemoradiotherapy ± pembrolizumab. Sarcopenia was assessed by skeletal muscle index at the third lumbar vertebra in computed tomography scans before NAT (men: 43cm²/m² for body mass index (BMI) < 25kg/m², 53cm²/m² for BMI≥25 kg/m²; women: 41cm²/m²). Logistic regression was performed to assess the association between sarcopenia and preoperative therapy-related toxicity and tumor response.

RESULTS

The study included 59 locally advanced ESCC patients (53 male and 6 female), 48 (81.4%) in the non-sarcopenia group, and 11 (18.6%) in the sarcopenia group. Mean age at diagnosis was 62±8 years. Mean BMI at diagnosis was 22.13±2.85 kg/m². 19 patients (32.2%) were stage ⅢA, 25 patients (42.4%) were ⅢB, 15 patients (25.4%) were ⅣA. No significant differences were found between both groups regarding sex, age, BMI, and clinical stage. Acute grade ≥3 toxicity occurred significantly more frequently in the sarcopenia group (54.5% vs. 22.9%, p = 0.045), which mainly included leukopenia, neutropenia, anemia and thrombocytopenia. The discontinuation of NAT owing to toxicity occurred in 8 patients (13.5%), which was significantly associated with sarcopenia (p = 0.003). All patients proceeded to surgery and 33 patients (55.9%) had a pathological complete response (pCR). Univariate analysis revealed no significant association between sarcopenia and pCR (p = 0.071).

CONCLUSION

Among patients with locally advanced EC, sarcopenia is not a predictor of poor NAT response, but it is strongly associated with discontinuation of NAT due to toxicity.

Low-Dose Fractionated Radiotherapy Combined with Neoadjuvant Chemotherapy for T3-4 Nasopharyngeal Carcinoma Patients: The Preliminary Results of a Phase II Randomized Controlled Trial

PURPOSE/OBJECTIVE(S)

Over 70% of NPC patients were local advanced NPC (LANPC). The 5-year local recurrence-free survival rate is only 70% in T3-4 patients. Neoadjuvant chemotherapy (NACT) followed with concurrent chemoradiotherapy (CCRT) was recommended for LANPC patients. Low-dose fractionated radiotherapy (LDFRT), which is <100cGy, induces enhanced cell killing by the hyper-radiation sensitivity phenomenon and potentiates effects of chemotherapy. The synergy of LDFRT and NACT has not been used in the clinical practice and few studies focused on it. A single arm study found the ORR of primary site was improved to 90% for head and neck squamous carcinoma patients treated with LDFRT and NACT. Our previous study found the ORR of lymph nodes was higher in LDFRT group for high-risk LANPC patients. However, another study showed there was no significant difference between LDFRT and control group for LANPC patients. So, we aimed to investigate the potential efficacy of this novel neoadjuvant therapy for T3-4 NPC patients.

MATERIALS/METHODS

A total of 60 pathological confirmed T3-4 (UICC/AJCC8th) NPC patients were prospectively enrolled in our study. They were randomly assigned to two groups. For the LDFRT group, the patients received 3 cycles of NACT (docetaxel 75mg/m2 D1, cisplatin 80mg/m2 D1) with LDFRT, and followed with CCRT. LDFRT was delivered as 50cGy per fraction twice a day to primary site on D1,2 for each cycle of NACT. The patients in the control group only received NACT and followed with CCRT. All the patients underwent IGRT. RECIST criteria and CTCAE 5.0 was used to evaluate the ORR and toxicity at post-NACT and the completion of CCRT.

RESULTS

From February 2022 to December 2022, 60 T3-4 NPC patients were included, and 30 patients for each group. For the primary site, the median volume reduction rate and the ORR after NACT was significantly improved in LDFRT group (69.27% vs 40.10%, p<0.001;93.33% vs 73.33%, p = 0.038). For the median volume reduction rate of primary site and lymph node, it was also obviously improved in LDFRT group (86.59% vs 55.43%, p<0.001). Though there was a tendency of ORR improvement in LDFRT group, but no significant difference (96.67% vs 83.33%, p = 0.195). After the completion of CCRT, the median volume reduction rate of primary site had an increased tendency in LDFRT group (96.16% vs 88.3%, p = 0.065), but the ORR had no statistical significance (LDFRT group: CR 45.8%, PR 54.2%; control group: CR 37.5%, PR 62.5%). For the toxicity, the incidence of grade 3-4 adverse events had no difference between two groups (p = 0.786). No grade 5 adverse events occurred.

CONCLUSION

LDFRT combined with NACT could obviously improve the median volume reduction rate and ORR of primary tumor for T3-4 NPC patients, and the toxicity was similar and tolerable. This novel treatment could be a promising strategy to improve treatment response and needed to be confirmed further.

Long-Term Survival Outcome for Metastatic Nasopharyngeal Carcinoma Patients Receiving Radiation to Primary and Metastatic Sites with Palliative Chemotherapy

PURPOSE/OBJECTIVE(S)

A total of 6% - 8% of NPC patients were initial diagnosed as distant metastatic disease. The median overall survival (OS) is only 10-15 months with palliative chemotherapy for these patients. A phase III study showed that palliative chemotherapy combined with radical radiotherapy to primary site could be a newly effective treatment method for metastatic NPC. Another phase 2, RCT found that the patients who had the solid tumors with 1-5 metastases received standard palliative care plus stereotactic body radiation therapy (SABR), and the 5-year OS were improved to 42.3%. Nevertheless, there was few studies focus on the radiation to both primary site and metastatic lesions. Therefore, we aimed to investigate the potential clinical benefits for initial diagnosed metastatic NPC patients with radiation to both primary site and distant metastatic lesions plus palliative chemotherapy.

MATERIALS/METHODS

Metastatic NPC patients treated with radiation to both primary site and distant metastatic lesions plus palliative chemotherapy were retrospectively collected in our hospital from May 2008 to May 2022. For treatment group, all patients underwent IGRT according to ICRU reports 50 and 62. The prescribed dose for primary site: GTVT: ≥66Gy, GTVn: ≥66Gy, CTV1: 60-66Gy, CTV2 54-60Gy, CTVln 50-54Gy. And the prescribed dose for distant metastatic lesions was more than 30Gy. For the control group, the patients treated with palliative chemotherapy were selected by propensity score matching from our hospital. The regimen for palliative chemotherapy was cisplatin-based chemotherapy every three weeks (100mg/m2 D1) for both groups. Kaplan-Meier method was used to analyze the OS. Cox regression model was used for multivariate analysis.

RESULTS

A total of 54 metastatic NPC patients with radiation to both primary site and distant metastatic lesions were retrospectively included in the treatment group, and another 54 patients were selected as the control group. The median follow-up time was 52 months. In the treatment group, the median age was 52 years (37-82), male (68%), female (32%), the main metastatic sites were bone (36 cases, 66%), lung (18 cases, 33%) and liver (10 cases, 18%). There were 23 oligometastasis cases and 31 cases. 3-year and 5-year OS in the treatment group were both dramatically improved than control group (63.2% vs 50.6%, p<0.05; 49.6% vs 38.9%, p<0.05). Multivariate analysis showed that T stage, liver metastatic lesion and oligometastases were the independent prognostic factors for them.

CONCLUSION

Palliative chemotherapy combined with radiation to primary sites and distant metastatic lesions might improve the OS for initial diagnosed distant metastatic NPC patients. More prospective clinical trials were needed to confirm it further.

Prediction of Response to Neoadjuvant Chemoradiotherapy Combined with Pembrolizumab in Esophageal Squamous Cell Carcinoma with CT/FDG PET Radiomic Signatures Based on Machine Learning Classification

PURPOSE/OBJECTIVE(S)

PALACE-1 trial has confirm that the addition of pembrolizumab to neoadjuvant chemoradiotherapy (NCRT) improves the pathological complete response(pCR) for esophageal squamous cell carcinoma (ESCC), which might be a novel treatment strategy for ESCC. In the present study, we aim to establish a machine learning model to predict the local response to NCRT+ pembrolizumab for ESCC by using pretreatment 18-fluorodeoxyglucose positron emission tomography (FDG PET) and contrast-enhanced plan CT images.

MATERIALS/METHODS

A total of 65 cases treated with NCRT+ pembrolizumab followed by surgery were prospectively enrolled for analysis from 2019-2022. Each patient contains a contrast-enhanced plan CT and FDG PET images. 52 patients were randomly divided into training set and 13 patients were used as test set. The Extraction of radiomics features was performed using an open-source Python library PyRadiomics automatically. Features were computed according to the radiologist-drawn ROIs on both CT and PET images. In the feature selection stage least absolute shrinkage and selection operator (LASSO) was utilized on CT features and PET features separately. Four different machine learning models were implemented: Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF) and XGBoost (XGB). The features selected by LASSO regression were used as model input and the output of the model is "pCR" or "non-pCR". To find the optimal parameter, the 5-fold cross-validation method was used in the training stage. In this study, we use accuracy, sensitivity and specificity as the metrics to evaluate the performance of the model on the testing cohort. The predictive performance of the model was assessed using the area under curve (AUC) of the receiver operating characteristics curve (ROC).

RESULTS

Of the 65 cases treated with NCRT+pembrolizumab, 35 patients archived pCR (53.8%), and 30 archived non-pCR. 1684 radiomics features were extracted from each case, and half of them (842 features) were from CT and others were from PET. Among the machine learning models mentioned above SVM achieves the most promising performance on the evaluation metrics. Accuracy, sensitivity, specificity and AUC score on test set were 0.692, 0.833, 0.571 and 0.786 for CT features and 0.615, 0.667, 0.571 and 0.762 for PET features, respectively. For CT+FDG PET fused features accuracy, sensitivity, specificity and AUC score on test set were 0.769, 0.667, 0.857 and 0.833.

CONCLUSION

In this study, we performed several different machine learning models to predict the response to NCRT+ pembrolizumab among ESCC based on the extracted radiomics features from CT and FDG PET images. The best-performing model based on radiomics features of CT and PET images could identify non-pCR to NCRT + pembrolizumab in EC patients.

Attractive deep morphology-aware active contour network for vertebral body contour extraction with extensions to heterogeneous and semi-supervised scenarios

Automatic vertebral body contour extraction (AVBCE) from heterogeneous spinal MRI is indispensable for the comprehensive diagnosis and treatment of spinal diseases. However, AVBCE is challenging due to data heterogeneity, image characteristics complexity, and vertebral body morphology variations, which may cause morphology errors in semantic segmentation. Deep active contour-based (deep ACM-based) methods provide a promising complement for tackling morphology errors by directly parameterizing the contour coordinates. Extending the target contours' capture range and providing morphology-aware parameter maps are crucial for deep ACM-based methods. For this purpose, we propose a novel Attractive Deep Morphology-aware actIve contouR nEtwork (ADMIRE) that embeds an elaborated contour attraction term (CAT) and a comprehensive contour quality (CCQ) loss into the deep ACM-based framework. The CAT adaptively extends the target contours' capture range by designing an all-to-all force field to enable the target contours' energy to contribute to farther locations. Furthermore, the CCQ loss is carefully designed to generate morphology-aware active contour parameters by simultaneously supervising the contour shape, tension, and smoothness. These designs, in cooperation with the deep ACM-based framework, enable robustness to data heterogeneity, image characteristics complexity, and target contour morphology variations. Furthermore, the deep ACM-based ADMIRE is able to cooperate well with semi-supervised strategies such as mean teacher, which enables its function in semi-supervised scenarios. ADMIRE is trained and evaluated on four challenging datasets, including three spinal datasets with more than 1000 heterogeneous images and more than 10000 vertebrae bodies, as well as a cardiac dataset with both normal and pathological cases. Results show ADMIRE achieves state-of-the-art performance on all datasets, which proves ADMIRE's accuracy, robustness, and generalization ability.

Molecular classification of hormone receptor-positive HER2-negative breast cancer

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most prevalent type of breast cancer, in which endocrine therapy resistance and distant relapse remain unmet challenges. Accurate molecular classification is urgently required for guiding precision treatment. We established a large-scale multi-omics cohort of 579 patients with HR+/HER2- breast cancer and identified the following four molecular subtypes: canonical luminal, immunogenic, proliferative and receptor tyrosine kinase (RTK)-driven. Tumors of these four subtypes showed distinct biological and clinical features, suggesting subtype-specific therapeutic strategies. The RTK-driven subtype was characterized by the activation of the RTK pathways and associated with poor outcomes. The immunogenic subtype had enriched immune cells and could benefit from immune checkpoint therapy. In addition, we developed convolutional neural network models to discriminate these subtypes based on digital pathology for potential clinical translation. The molecular classification provides insights into molecular heterogeneity and highlights the potential for precision treatment of HR+/HER2- breast cancer.

Improving Interfraction Robustness for IMPT Treatment Planning for Lung Cancer Using Multiple-CT Incorporated Robust Optimization

PURPOSE/OBJECTIVE(S)

Dose deterioration due to motion-induced density variation is a major concern in intensity-modulated proton therapy (IMPT) for lung cancer. Robust optimization is capable to address the intrafraction motion issue but not the interfraction variation. This study aims to investigate the potential of a new robust optimization technique of IMPT in mitigating the interfraction variation of lung cancer patients.

MATERIALS/METHODS

Two optimization techniques were used to create an IMPT plan for a lung cancer case, one was conventional robust optimization (ROcon) considering the perturbation of 3 mm setup uncertainty and 3.5% range uncertainty, and the other was multiple-CT incorporated robust optimization (ROmul) considering one more perturbation quantified using the end-of-inhalation-phase (T0) and end-of-exhalation-phase (T50) CTs. The ROcon plan was optimized on the average-intensity-projection (AIP) planning CT (pCT), and the ROmul plan was optimized on the AIP, T0, and T50 pCTs. The dose prescription was 40 Gy (RBE) in 5 fractions. The patient underwent a verification 4DCT (vCT) scan on six successive days. Both plans were recalculated on the T0 pCT, T50 pCT, and AIP vCT. The dose to the target and organ at risk of the ROcon and ROmul plans on pCT and vCT were compared.

RESULTS

Compared with the ROcon plan, the ROmul plan reduced the deviation of target coverage by greater than 50% in presence of intrafraction motion (ROmul:0.38-0.88%, ROcon:1.90-2.23%) and interfraction variation (ROmul: 0.62-1.63% vs ROcon:0.50-2.75%) while meeting the dose criteria on the planning AIP CT. As for the dose to the organ at risk, the ROmul plan had a slightly high lung V20 (0.3%) than did the ROcon plan on the AIP pCT. The deviations in lung V20 of the ROmul plan (mean 0.15%) on the vCTs were similar to that of the ROcon plan (mean 0.17%).

CONCLUSION

This study indicates that dose variation of an IMPT plan can be reduced in presence of interfraction variation along the treatment course by combining conventional robust optimization and novel multiple-CT optimization using only the planning CT.

[Y-shaped osteotomy in the apical vertebra for treating congenital complex rigid scoliosis:at least 2-year follow-up]

Objective: To investigate the clinical outcome of the coronal Y-shaped osteotomy in the apical vertebra for treating congenital complex rigid scoliosis. Methods: A retrospective analysis was conducted on 66 cases who underwent Y-shaped osteotomy treatment for congenital complex rigid scoliosis in the uppermost vertebra at the Department of Orthopedics,the Second Hospital of Shanxi Medical University from June 2007 to August 2020. There were 19 males and 47 females,with an age of (13.1±5.3) years(range:2 to 30 years).Classification of congenital scoliosis:25 cases (37.9%) were incomplete,13 cases (19.7%) were dysarthritic,and 28 cases (42.4%) were mixed. There were 25 cases (37.9%) with thoracic or rib malformations. 45 cases (68.2%) were complicated with spinal cord malformation.The main radiological indicators included Cobb angle of the curvature,Cobb angle of the local bend,apical vertebral translation (AVT),trunk shift (TS),thoracic trunk shift (TTS),radiographic shoulder height (RSH),coronal balance and sagittal vertebral axis. The preoperative,postoperative immediate,and last follow-up radiological indicators were collected and the operation time,blood loss,hospitalization time,and operation-related complications were recorded. Data were compared by repeated measure ANOVA and paired-t test. Results: All patients underwent surgery successfully. The duration of the first surgery was (221.4±52.8) minutes,and the blood loss during the first surgery was (273.2±41.8) ml. The length of the first hospital stay was (8.8±1.7) days.Unilateral fixation was performed in 19 cases (28.8%),while bilateral fixation was performed in 47 cases (71.2%). The fused segments were 7.5±2.9,and the vertebral pedicle screw density was (68.5±20.6)%. The follow-up time for the 66 patients was (36.7±17.0) months(range:24 to 102 months).The main curve Cobb Angle was improved from (58.5±18.9)°before surgery to (21.1±11.8)°after surgery,and was (23.6±15.3) ° at the last follow-up(F=273.957,P<0.01),with a correction rate of 66.2%. Segmental curve Cobb Angle was improved from (47.9±18.0)° to (16.0±11.3)° after surgery,and was (16.8±12.8) °at the last follow-up (F=270.483,P<0.01)with a correction rate of 69.2%. The AVT,TS,TTS and RSH values improved significantly at the final follow-up (all P<0.05),while coronal balance and sagittal vertical axis were maintained without significant differences between pre-operation and post-operation(both P>0.05). A total of 5 patients underwent staged operation,all of which were residual scoliosis aggravated after the first stage of orthosis operation and had good prognosis after the second stage of operation. Conclusions: Y-shaped osteotomy for the treatment of congenital rigid scoliosis results in good clinical and radiological outcomes without serious complications. This procedure can be considered as an option for the treatment of congenital complex rigid scoliosis.

Sequence based local-global information fusion framework for vertebrae detection under pathological and FOV variation challenges

Automated vertebrae detection (identification and localization) aims to identify vertebrae and locate their centroids in medical images, which is a critical step of spinal computer-aided systems. However, due to unpredictable field-of-view and various pathology cases, the image content is diverse and the vertebral morphology can be abnormal in a variety of ways, which challenges the designed systems. In this paper, we propose an effective sequence-based framework robust to various tough cases for accurate vertebrae identification and localization. Our method consists of three sub-modules: (1) Local Feature Extraction (LFE) module designs a shape-compatible category-balanced sampler to collect patches to train a convolution neural network, which extracts representative local features and generates score maps. (2) Discriminative Sequential Image Description (DSID) module proposes a node screening strategy for reliable vertebral feature sequence construction based on feature maps and score maps. This effectively prevents false positives and false negatives in light-weighted dense prediction schemes and fuses local features into a hierarchical discriminative description of given images. (3) Spinal Pattern Exploitation (SPE) module designs an end-balanced relative position learning scheme to fuse hierarchical local-global information for comprehensively exploiting spinal patterns to overcome the FOV and pathological variation challenges in vertebrae detection. Extensive experiments on a challenging dataset consisting of 450 spinal MRIs show that the identification rate of FSDF reaches 0.974 ±0.025 and the localization error is only 4.742 ±2.928 pixels, which demonstrates the effectiveness of our method with pathological and field-of-view variations and its superiority over other state-of-the-art methods.

TNF inhibitors associated with cardiovascular diseases and cardiometabolic risk factors: a Mendelian randomization study

OBJECTIVE

There is still disagreement about whether anti-tumor necrosis factor (TNF) therapy is beneficial or detrimental to cardiovascular conditions. This two-sample Mendelian randomization (MR) study aimed to evaluate the effects of long-term tumor necrosis factor (TNF) inhibition on cardiovascular diseases (CVDs) and cardiometabolic risk factors via genetically proxied inhibition of tumor necrosis factor receptor 1 (TNFR1) and TNF.

MATERIALS AND METHODS

Two genetic instruments were examined to mimic the long-term effect of TNF inhibitors. The first were single-nucleotide polymorphisms (SNPs) within or nearby drug-target genes TNFRSF1A and TNF (encoding TNFR1 and TNF) associated with circulating CRP levels. The other instruments were the expression quantitative trait loci (eQTLs) near the genes. Inverse variance-weighted MR (IVW-MR) and summary-based MR (SMR) methods were employed to estimate causal effects.

RESULTS

In IVW-MR analysis, TNF-mediated circulating CRP levels were significantly associated with 4 out of 12 CVDs, including hypertension [odds ratio (OR) = 1.13; 95% CI, 1.09-1.18], coronary artery disease (OR = 3.18; 95% CI, 1.77-5.71), coronary atherosclerosis (OR = 1.05; 95% CI, 1.02-1.08) and type 2 diabetes (OR = 3.48; 95% CI, 1.98-6.10). These findings were also validated in the FinnGen study. Moreover, TNF inhibition was also associated with total cholesterol, triglycerides, apolipoprotein B, systolic blood pressure, serum cystatin C, height, weight, and body mass index.

CONCLUSIONS

In this study, the decrease in several CVDs and cardiometabolic risk factors has been found to be causally associated with genetically proxied TNF inhibitors.

The reinfection threshold, revisited

One mode by which infection-derived immunity fails is when recovery leads to a reduced but nonzero risk of reinfection. This type of partial protection is called leaky immunity with the degree of leakiness quantified by the relative probability a previously infected individual will get infected upon exposure compared to a naively susceptible individual. Previous authors have defined the reinfection threshold, which occurs when the basic reproduction number equals the inverse of the leakiness, however, there has been some debate about whether or not this is a real threshold. Here we show how the reinfection threshold relates to two important occurrences: (1) the point at which the endemic equilibrium changes from being a stable spiral to a stable node, and (2) the point at which the rate of change of the prevalence increases the most relative to leakiness. When the recovery period is short relative to the average lifetime then both occurrences are close to the reinfection threshold. We show how these results are related to the reinfection threshold found in other models of imperfect immunity. To further demonstrate the significance of this threshold in modeling, we conducted a simulation study to evaluate some of the consequences the reinfection threshold might have in parameter estimation and modeling. Using specific parameter values chosen to reflect an acute infection, we found that the basic reproduction number values larger than that of the reinfection threshold value were less identifiable than those below the threshold.

Alcanivorax borkumensis biofilms enhance oil degradation by interfacial tubulation

During the consumption of alkanes, Alcanivorax borkumensis will form a biofilm around an oil droplet, but the role this plays during degradation remains unclear. We identified a shift in biofilm morphology that depends on adaptation to oil consumption: Longer exposure leads to the appearance of dendritic biofilms optimized for oil consumption effected through tubulation of the interface. In situ microfluidic tracking enabled us to correlate tubulation to localized defects in the interfacial cell ordering. We demonstrate control over droplet deformation by using confinement to position defects, inducing dimpling in the droplets. We developed a model that elucidates biofilm morphology, linking tubulation to decreased interfacial tension and increased cell hydrophobicity.

Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC

INTRODUCTION

According to mechanisms of adaptive immune resistance, tumor immune microenvironment (TIME) is classified into four types: (1) programmed death-ligand 1 (PD-L1)-negative and tumor-infiltrating lymphocyte (TIL)-negative (type I); (2) PD-L1-positive and TIL-positive (type II); (3) PD-L1-negative and TIL-positive (type III); and (4) PD-L1-positive and TIL-negative (type IV). However, the relationship between the TIME classification model and immunotherapy efficacy has not been validated by any large-scale randomized controlled clinical trial among patients with advanced NSCLC.

METHODS

On the basis of RNA-sequencing and immunohistochemistry data from the ORIENT-11 study, we optimized the TIME classification model and evaluated its predictive value for the efficacy of immunotherapy plus chemotherapy.

RESULTS

PD-L1 mRNA expression and immune score calculated by the ESTIMATE method were the strongest predictors for the efficacy of immunotherapy plus chemotherapy. Therefore, they were determined as the optimized definition of the TIME classification system. When compared between combination therapy and chemotherapy alone, only the type II subpopulation with high immune score and high PD-L1 mRNA expression was significantly associated with improved progression-free survival (PFS) (hazard ratio = 0.12, 95% confidence interval: 0.06-0.25, p < 0.001) and overall survival (hazard ratio = 0.27, 95% confidence interval: 0.13-0.55, p < 0.001). In the combination group, the type II subpopulation had a much longer survival time, not even reaching the median PFS or overall survival, but the other three subpopulations were susceptible to having similar PFS. In the chemotherapy group, there was no marked association between survival outcomes and TIME subtypes.

CONCLUSIONS

Only patients with both high PD-L1 expression and high immune infiltration could benefit from chemotherapy plus immunotherapy in first-line treatment of advanced NSCLC. For patients lacking either PD-L1 expression or immune infiltration, chemotherapy alone might be a better treatment option to avoid unnecessary toxicities and financial burdens.

Visible-Light-Induced Intermolecular Trifluoromethyl Heteroarylation of Vinyl Ethers for the Syntheses of β-Trifluoromethyl Alkyl Thiochromones

Herein, we reported a transition-metal-free three-component trifluoromethyl heteroarylation of vinyl ethers under visible light irradiation. This protocol proceeded through a radical addition/cyclization sequence which hinged on the intrinsic nucleo/electrophilic reactivity of both the radicals, alkene, and alkynones, allowing β-trifluoromethyl alkyl thiochromones furnished with high efficiency and excellent functional group tolerance. By virtue of this procedure, three distinct chemical bonds including C(sp²)-C(sp³), C(sp³)-C(sp³), and C(sp²)-S have been successively forged in a single pot.

Immunolocalization of Enzymes/Membrane Transporters Related to Bone Mineralization in the Metaphyses of the Long Bones of Parathyroid-Hormone-Administered Mice

The present study aimed to demonstrate the immunolocalization and/or gene expressions of the enzymes and membrane transporters involved in bone mineralization after the intermittent administration of parathyroid hormone (PTH). The study especially focused on TNALP, ENPP1, and PHOSPHO1, which are involved in matrix vesicle-mediated mineralization, as well as PHEX and the SIBLING family, which regulate mineralization deep inside bone. Six-week-old male mice were subcutaneously injected with 20 μg/kg/day of human PTH (1-34) two times per day (n = 6) or four times per day (n = 6) for two weeks. Additionally, control mice (n = 6) received a vehicle. Consistently with an increase in the volume of the femoral trabeculae, the mineral appositional rate increased after PTH administration. The areas positive for PHOSPHO1, TNALP, and ENPP1 in the femoral metaphyses expanded, and the gene expressions assessed by real-time PCR were elevated in PTH-administered specimens when compared with the findings in control specimens. The immunoreactivity and/or gene expressions of PHEX and the SIBLING family (MEPE, osteopontin, and DMP1) significantly increased after PTH administration. For example, MEPE immunoreactivity was evident in some osteocytes in PTH-administered specimens but was hardly observed in control specimens. In contrast, mRNA encoding cathepsin B was significantly reduced. Therefore, the bone matrix deep inside might be further mineralized by PHEX/SIBLING family after PTH administration. In summary, it is likely that PTH accelerates mineralization to maintain a balance with elevated matrix synthesis, presumably by mediating TNALP/ENPP1 cooperation and stimulating PHEX/SIBLING family expression.

[Effects of in vivo targeted carboxylesterase 1f gene knockdown on the Kupffer cells polarization activity in mice with acute liver failure]

Objective: To investigate the effect of targeted carboxylesterase 1f (Ces1f) gene knockdown on the polarization activity of Kupffer cells (KC) induced by lipopolysaccharide/D-galactosamine (LPS/D-GalN) in mice with acute liver failure. Methods: The complex siRNA-EndoPorter formed by combining the small RNA (siRNA) carrying the Ces1f-targeting interference sequence and the polypeptide transport carrier (Endoporter) was wrapped in β-1, 3-D glucan shell to form complex particles (GeRPs). Thirty male C57BL/6 mice were randomly divided into a normal control group, a model group (LPS/D-GalN), a pretreatment group (GeRPs), a pretreatment model group (GeRPs+LPS/D-GalN), and an empty vector group (EndoPorter). Real-time fluorescent quantitative PCR and western blot were used to detect Ces1f mRNA and protein expression levels in the liver tissues of each mouse group. Real-time PCR was used to detect the expression levels of KC M1 polarization phenotypic differentiation cluster 86(CD86) mRNA and KC M2 polarization phenotypic differentiation cluster 163 (CD163) mRNA in each group. Immunofluorescence double staining technique was used to detect the expression of Ces1f protein and M1/M2 polarization phenotype CD86/CD163 protein in KC. Hematoxylin-eosin staining was used to observe the pathological damage to liver tissue. A one-way analysis of variance was used to compare the means among multiple groups, or an independent sample nonparametric rank sum test was used when the variances were uneven. Results: The relative expression levels of Ces1f mRNA/protein in liver tissue of the normal control group, model group, pretreatment group, and pretreatment model group were 1.00 ± 0.00, 0.80 ± 0.03/0.80 ± 0.14, 0.56 ± 0.08/0.52 ± 0.13, and 0.26 ± 0.05/0.29 ± 0.13, respectively, and the differences among the groups were statistically significant (F = 9.171/3.957, 20.740/9.315, 34.530/13.830, P < 0.01). The percentages of Ces1f-positive Kupffer cells in the normal control group, model group, pretreatment group, and pretreatment model group were 91.42%, ± 3.79%, 73.85% ± 7.03%, 48.70% ± 5.30%, and 25.68% ± 4.55%, respectively, and the differences between the groups were statistically significant (F = 6.333, 15.400, 23.700, P < 0.01). The relative expression levels of CD86 mRNA in the normal control group, model group, and pretreatment model group were 1.00 ± 0.00, 2.01 ± 0.04, and 4.17 ± 0.14, respectively, and the differences between the groups were statistically significant (F = 33.800, 106.500, P < 0.01). The relative expression levels of CD163 mRNA in the normal control group, the model group, and the pretreatment model group were 1.00 ± 0.00, 0.85 ± 0.01, and 0.65 ± 0.01, respectively, and the differences between the groups were statistically significant (F = 23.360, 55.350, P < 0.01). The percentages of (F4/80(+)CD86(+)) and (F4/80(+)CD163(+)) in the normal control group and model group and pretreatment model group were 10.67% ± 0.91% and 12.60% ± 1.67%, 20.02% ± 1.29% and 8.04% ± 0.76%, and 43.67% ± 2.71% and 5.43% ± 0.47%, respectively, and the differences among the groups were statistically significant (F = 11.130/8.379, 39.250/13.190, P < 0.01). The liver injury scores of the normal control group, the model group, and the pretreatment model group were 0.22 ± 0.08, 1.32 ± 0.36, and 2.17 ± 0.26, respectively, and the differences among the groups were statistically significant (F = 12.520 and 22.190, P < 0.01). Conclusion: Ces1f may be a hepatic inflammatory inhibitory molecule, and its inhibitory effect production may come from the molecule's maintenance of KC polarization phenotypic homeostasis.

Phase 1b trial of anti-EGFR antibody JMT101 and Osimertinib in EGFR exon 20 insertion-positive non-small-cell lung cancer

EGFR exon 20 insertion (20ins)-positive non-small-cell lung cancer (NSCLC) is an uncommon disease with limited therapeutic options and dismal prognosis. Here we report the activity, tolerability, potential mechanisms of response and resistance for dual targeting EGFR 20ins with JMT101 (anti-EGFR monoclonal antibody) plus osimertinib from preclinical models and an open label, multi-center phase 1b trial (NCT04448379). Primary endpoint of the trial is tolerability. Secondary endpoints include objective response rate, duration of response, disease control rate, progression free survival, overall survival, the pharmacokinetic profile of JMT101, occurrence of anti-drug antibodies and correlation between biomarkers and clinical outcomes. A total of 121 patients are enrolled to receive JMT101 plus osimertinib 160 mg. The most common adverse events are rash (76.9%) and diarrhea (63.6%). The confirmed objective response rate is 36.4%. Median progression-free survival is 8.2 months. Median duration of response is unreached. Subgroup analyses were performed by clinicopathological features and prior treatments. In patients with platinum-refractory diseases (n = 53), confirmed objective response rate is 34.0%, median progression-free survival is 9.2 months and median duration of response is 13.3 months. Responses are observed in distinct 20ins variants and intracranial lesions. Intracranial disease control rate is 87.5%. Confirmed intracranial objective response rate is 25%.

Excitons in mesoscopically reconstructed moiré heterostructures

Moiré effects in vertical stacks of two-dimensional crystals give rise to new quantum materials with rich transport and optical phenomena that originate from modulations of atomic registries within moiré supercells. Due to finite elasticity, however, the superlattices can transform from moiré-type to periodically reconstructed patterns. Here we expand the notion of such nanoscale lattice reconstruction to the mesoscopic scale of laterally extended samples and demonstrate rich consequences in optical studies of excitons in MoSe₂-WSe₂ heterostructures with parallel and antiparallel alignments. Our results provide a unified perspective on moiré excitons in near-commensurate semiconductor heterostructures with small twist angles by identifying domains with exciton properties of distinct effective dimensionality, and establish mesoscopic reconstruction as a compelling feature of real samples and devices with inherent finite size effects and disorder. Generalized to stacks of other two-dimensional materials, this notion of mesoscale domain formation with emergent topological defects and percolation networks will instructively expand the understanding of fundamental electronic, optical and magnetic properties of van der Waals heterostructures.

Machine-learning models for prediction of sepsis patients mortality

OBJECTIVES

Sepsis is an infection-caused syndrome, that leads to life-threatening organ damage. We aim to develop machine learning models with large-scale data to predict sepsis patients' mortality.

DESIGN

we extracted sepsis patients from two databases, Medical Information Mart for Intensive Care IV (MIMIC-IV) as a train set and Philips eICU Collaborative Research Database as a test set.

SETTING

ICUs in multicenter hospitals in the USA during 2012-2019.

PATIENTS OR PARTICIPANTS

A total of 21,680 sepsis-3 patients are included in the study, in which, 3771 patients were dead and 17,909 survived during hospitalization, respectively.

INTERVENTIONS

No interventions.

MAIN VARIABLES OF INTEREST

Basic information, examination items during hospitalization and some medication and treatment information are incorporated into analyzed. Seven different models were built with a Support vector machine, Decision Tree Classifier, Random Forest, Gradients Boosting, Multiple Layer Perception, Xgboost, light Gradients Boosting to predict dead or live during hospitalization.

RESULTS

Algorithms with an AUC value in the test set of the top three: light GBM, GBM, Xgboost. Considering the performance of the training set and the test set, the light GBM model performs best, and then the parameters of the model were adjusted, after that the AUC value was 0.99 in the train set, 0.96 in the test set, respectively.

CONCLUSIONS

Models built with light GBM algorithm from real-world sepsis patients from electronic health records accurately predict whether sepsis patients are dead and can be incorporated into clinical decision tools to enhance the prognosis of the patient and prevent adverse outcomes.

Prediction of clinicopathological features, multi-omics events and prognosis based on digital pathology and deep learning in HR+/HER2- breast cancer

Background

Breast cancer has the highest incidence and mortality rates among women worldwide. Hormone receptor (HR)⁺/human epidermal growth factor receptor 2 (HER2)^- breast cancer is the most common molecular subtype, accounting for 50-79% of breast cancers. Deep learning has been widely used in cancer image analysis, especially for predicting targets related to precise treatment and patient prognosis. However, studies focusing on therapeutic target and prognosis predicting in HR⁺/HER2^- breast cancer are lacking.

Methods

This study retrospectively collected hematoxylin and eosin (H&E)-stained slides of HR⁺/HER2^- breast cancer patients between January 2013 and December 2014 at Fudan University Shanghai Cancer Center (FUSCC) and scanned to generate whole-slide images (WSIs). Then, we built a deep-learning-based workflow to train and validate model to predict clinicopathological features, multi-omics molecular features and prognosis; the area under the curve (AUC) of the receiver operating characteristic (ROC) and the concordance index (C-index) of the test set were used to assess model effectiveness.

Results

A total of 421 HR⁺/HER2^- breast cancer patients were included in our study. Regarding clinicopathological features, grade III could be predicted with an AUC of 0.90 [95% confidence interval (CI): 0.84-0.97]. Regarding somatic mutations, TP53 and GATA3 mutation could be predicted with AUCs of 0.68 (95% CI: 0.56-0.81) and 0.68 (95% CI: 0.47-0.89), respectively. Regarding gene set enrichment analysis (GSEA) pathways, the G2-M checkpoint pathway was predicted with an AUC of 0.79 (95% CI: 0.69-0.90). Regarding markers of immunotherapy response, intratumoral tumor-infiltrating lymphocytes (iTILs), stromal tumor-infiltrating lymphocytes (sTILs), CD8A, and PDCD1 were predicted with AUCs of 0.78 (95% CI: 0.55-1.00), 0.76 (95% CI: 0.65-0.87), 0.71 (95% CI: 0.60-0.82), and 0.74 (95% CI: 0.63-0.85), respectively. In addition, we found that the integration of clinical prognostic variables and deep features of images can improve the stratification of patient prognosis.

Conclusions

Using a deep-learning-based workflow, we developed models to predict the clinicopathological features, multi-omics features and prognosis of patients with HR⁺/HER2^- breast cancer using pathological WSIs. This work may contribute to efficient patient stratification to promote the personalized management of HR⁺/HER2^- breast cancer.