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.