Leveraging diverse cellular stress patterns for predicting clinical outcomes and therapeutic responses in patients with multiple myeloma.

Tumour microenvironment harbours diverse stress factors that affect the progression of multiple myeloma (MM), and the survival of MM cells heavily relies on crucial stress pathways. However, the impact of cellular stress on clinical prognosis of MM patients remains largely unknown. This study aimed to provide a cell stress-related model for survival and treatment prediction in MM. We incorporated five cell stress patterns including heat, oxidative, hypoxic, genotoxic, and endoplasmic reticulum stresses, to develop a comprehensive cellular stress index (CSI). Then we systematically analysed the effects of CSI on survival outcomes, clinical characteristics, immune microenvironment, and treatment sensitivity in MM. Molecular subtypes were identified using consensus clustering analysis based on CSI gene profiles. Moreover, a prognostic nomogram incorporating CSI was constructed and validated to aid in personalised risk stratification. After screening from five stress models, a CSI signature containing nine genes was established by Cox regression analyses and validated in three independent datasets. High CSI was significantly correlated with cell division pathways and poor clinical prognosis. Two distinct MM subtypes were identified through unsupervised clustering, showing significant differences in prognostic outcomes. The nomogram that combined CSI with clinical features exhibited good predictive performances in both training and validation cohorts. Meanwhile, CSI was closely associated with immune cell infiltration level and immune checkpoint gene expression. Therapeutically, patients with high CSI were more sensitive to bortezomib and antimitotic agents, while their response to immunotherapy was less favourable. Furthermore, in vitro experiments using cell lines and clinical samples verified the expression and function of key genes from CSI. The CSI signature could be a clinically applicable indicator of disease evaluation, demonstrating potential in predicting prognosis and guiding therapy for patients with MM.

Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impact on hospitalizations, morbidity, and mortality of patients. This study aimed to develop a model for predicting acute exacerbation in COPD patients (AECOPD) based on deep-learning (DL) features. METHODS: We performed a retrospective study on 219 patients with COPD who underwent inspiratory and expiratory HRCT scans. By recording the acute respiratory events of the previous year, these patients were further divided into non-AECOPD group and AECOPD group according to the presence of acute exacerbation events. Sixty-nine quantitative CT (QCT) parameters of emphysema and airway were calculated by NeuLungCARE software, and 2,000 DL features were extracted by VGG-16 method. The logistic regression method was employed to identify AECOPD patients, and 29 patients of external validation cohort were used to access the robustness of the results. RESULTS: The model 3-B achieved an area under the receiver operating characteristic curve (AUC) of 0.933 and 0.865 in the testing cohort and external validation cohort, respectively. Model 3-I obtained AUC of 0.895 in the testing cohort and AUC of 0.774 in the external validation cohort. Model 7-B combined clinical characteristics, QCT parameters, and DL features achieved the best performance with an AUC of 0.979 in the testing cohort and demonstrating robust predictability with an AUC of 0.932 in the external validation cohort. Likewise, model 7-I achieved an AUC of 0.938 and 0.872 in the testing cohort and external validation cohort, respectively. CONCLUSIONS: DL features extracted from HRCT scans can effectively predict acute exacerbation phenotype in COPD patients.

Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a prevalent and debilitating respiratory condition that imposes a significant healthcare burden worldwide. Accurate staging of COPD severity is crucial for patient management and treatment planning. METHODS: The retrospective study included 530 hospital patients. A lobe-based radiomics method was proposed to classify COPD severity using computed tomography (CT) images. First, we segmented the lung lobes with a convolutional neural network model. Secondly, the radiomic features of each lung lobe are extracted from CT images, the features of the five lung lobes are merged, and the selection of features is accomplished through the utilization of a variance threshold, t-Test, least absolute shrinkage and selection operator (LASSO). Finally, the COPD severity was classified by a support vector machine (SVM) classifier. RESULTS: 104 features were selected for staging COPD according to the Global initiative for chronic Obstructive Lung Disease (GOLD). The SVM classifier showed remarkable performance with an accuracy of 0.63. Moreover, an additional set of 132 features were selected to distinguish between milder (GOLD I + GOLD II) and more severe instances (GOLD III + GOLD IV) of COPD. The accuracy for SVM stood at 0.87. CONCLUSIONS: The proposed method proved that the novel lobe-based radiomics method can significantly contribute to the refinement of COPD severity staging. By combining radiomic features from each lung lobe, it can obtain a more comprehensive and rich set of features and better capture the CT radiomic features of the lung than simply observing the lung as a whole.

Home indoor air quality and cognitive function over one year for people working remotely during COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic triggered an increase in remote work-from-home for office workers. Given that many homes now function as offices despite not being designed to support office work, it is critical to research the impact of indoor air quality (IAQ) in homes on the cognitive performance of people working from home. In this study, we followed 206 office workers across the U.S. over one year under remote or hybrid-remote settings during 2021-2022. Participants placed two real-time, consumer-grade indoor environmental monitors in their home workstation area and bedroom. Using a custom smartphone application geofenced to their residential address, participants responded to surveys and periodic cognitive function tests, including the Stroop color-word interference test, Arithmetic two-digit addition/subtraction test, and Compound Remote Associates Task (cRAT). Exposures assessed included carbon dioxide (CO2) and thermal conditions (indoor heat index: a combination of temperature and relative humidity) averaged over 30 minutes prior to each cognitive test. In fully adjusted longitudinal mixed models (n≤121), we found that indoor thermal conditions at home were associated with cognitive function outcomes non-linearly (p<0.05), with poorer cognitive performance on the Stroop test and poorer creative problem-solving on the cRAT when conditions were either too warm or too cool. Most indoor CO2 levels were <640 ppm, but there was still a slight association between higher CO2 and poorer cognitive performance on Stroop (p=0.09). Our findings highlight the need to enhance home indoor environmental quality for optimal cognitive function during remote work, with benefits for both employees and employers.

Efficacy and safety of rivaroxaban for the treatment of PICC-related upper extremity deep vein thrombosis in cancer patients: a retrospective study.

BACKGROUND: The optimal duration and choice of anticoagulant for the treatment of Peripherally inserted central catheters (PICC)-related upper extremity deep vein thrombosis (UEDVT) in cancer patients are still undetermined. OBJECTIVES: The aim of this study was to assess the efficacy and safety of rivaroxaban for the treatment of PICC-related UEDVT in cancer patients. METHODS: We conducted a retrospective cohort study including consecutive cancer patients for the management of acute symptomatic PICC-related UEDVT. The efficacy outcome of the study was the 180-day recurrence of any venous thromboembolism (VTE), while the safety outcome was the 180-day incidence of all bleeding events. The Kaplan‒Meier method was used to estimate the overall incidence. Hazard ratios (HRs) were obtained with a Cox proportional hazards model to estimate the risk of the outcome events. RESULTS: A total of 217 patients were included in the final analysis with a median age of 56 years old, 41.5% of whom had metastases. After the initial 3-5 days of nadroparin, patients received sequential anticoagulation, either with nadroparin (118 patients) or with rivaroxaban (99 patients). Four patients with recurrent VTE were observed (nadroparin, n = 2; rivaroxaban, n = 2). The 180-day cumulative VTE recurrence rates were 1.7% and 2.0% (p = 0.777) in patients receiving nadroparin and rivaroxaban, respectively. The overall bleeding rate at 180 days was 8.8%. Although no major bleeding events were observed, nineteen patients with clinically relevant nonmajor bleeding (CRNMB) were observed. The 180-day cumulative rate of CRNMB was 5.1% for nadroparin and 13.1% for rivaroxaban (HR = 3.303, 95% CI 1.149-9.497, p = 0.027). CONCLUSION: Our study supported the efficacy of rivaroxaban for treating PICC-related UEDVT in cancer patients. However, data on anticoagulation therapy for PICC-related UEDVT presented with a low risk of VTE recurrence and a relatively high risk of CRNMB bleeding events. Considering the risk-benefit ratio, further well-designed trials are required to optimize the drug selection and duration for the treatment of PICC-related UEDVT in cancer patients.

Low human beta-defensin-2 levels in the sputum of COPD patients are associated with the risk of exacerbations.

RATIONALE: Chronic obstructive pulmonary disease (COPD) is a complicated chronic inflammatory disease. It is important to investigate the characteristics of acute exacerbation of COPD to develop new therapeutic strategies. OBJECTIVE: This study aimed to determine the relationship between the human beta-defensin-2 (hBD-2) levels and aggravation of COPD. METHODS: We detected the sputum hBD-2 level of 254 patients from Guangzhou, China, for 2 years. The study participants were categorized into the COPD group (n = 203, GOLD 0-4) and the control group (n = 51, 40-79 years old). At baseline, 12th month, and 24th month, we detected the sputum hBD-2 level and levels of cytokines, such as CXCL10, CXCL11, and IFN. RESULTS: At baseline, there were no significant differences in the sputum and serum hBD-2 levels between the patients and the controls. However, the sputum hBD-2 levels of patients who had at least one symptom aggravation over the next 2 years were significantly lower than those of patients without any exacerbations (1130.9 ± 858.4 pg/mL vs. 2103.7 ± 1294.2 pg/mL, respectively; p = 0.001). Nevertheless, there were no statistically significant differences in the sputum hBD-2 levels between patients (no aggravation history) and controls (2084.9 ± 1317.6 pg/mL vs. 2152.5 ± 1251.6 pg/mL, respectively; p = 0.626). We used a logistic regression model to assess the relationship between aggravation and sputum hBD-2 levels. Interestingly, we found that low hBD-2 level (< 1000 pg/mL) was significantly associated with exacerbations. Specifically, patients with low hBD-2 levels were more likely to experience exacerbations in the next 12 months (0.333 vs. 0.117; p = 0.001). Moreover, we compared the hBD-2 levels between controls and patients with GOLD 3-4 and found that participants with bacteria (+) and/or viruses (+) had an association between hBD-2 level and disease severity (p = 0.02). CONCLUSION: Patients at risk of exacerbations are more likely to have lower sputum hBD-2 levels. These results have important implications for future therapies for COPD.

A meta-analysis of the effect and safety of platinum-based neoadjuvant chemotherapy in treatment of resectable triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive and fatal subtype of breast cancer. The effectiveness of platinum-based neoadjuvant chemotherapy in treatment of cancer has many divergent opinions. A search was conducted in the PubMed, EBSCO, Web of Science and Cochrane Library databases for relevant studies published before August 2020. The primary endpoint was pathological complete response (pCR) while the secondary endpoints were objective response rate (ORR), overall survival (OS) and progression-free survival (PFS). Nine randomized controlled trials comprised of 1873 patients were included in this meta-analysis. Platinum-based neoadjuvant chemotherapy showed significant improvements in pCR (RR = 1.51, 95% CI, 1.25-1.82, P < 0.001), ORR (RR = 1.20, 95% CI, 1.07-1.34, P = 0.001), OS (HR=0.56; 95% CI, 0.15-0.96, P < 0.001) and PFS (HR = 0.48, 95% CI, 0.22-0.73, P < 0.001) compared to nonplatinum neoadjuvant chemotherapy. Moreover, addition of platinum compounds did not significantly increase the side effects of any grade. However, there was an increase in blood toxicity of grade 3 patients which meant that it was mainly confined to the bone marrow/blood system. Platinum-based neoadjuvant chemotherapy can safely improve short-term and long-term outcomes in resectable TNBC patients.

Divergence-Based Locally Weighted Ensemble Clustering with Dictionary Learning and L2,1-Norm.

Accurate clustering is a challenging task with unlabeled data. Ensemble clustering aims to combine sets of base clusterings to obtain a better and more stable clustering and has shown its ability to improve clustering accuracy. Dense representation ensemble clustering (DREC) and entropy-based locally weighted ensemble clustering (ELWEC) are two typical methods for ensemble clustering. However, DREC treats each microcluster equally and hence, ignores the differences between each microcluster, while ELWEC conducts clustering on clusters rather than microclusters and ignores the sample-cluster relationship. To address these issues, a divergence-based locally weighted ensemble clustering with dictionary learning (DLWECDL) is proposed in this paper. Specifically, the DLWECDL consists of four phases. First, the clusters from the base clustering are used to generate microclusters. Second, a Kullback-Leibler divergence-based ensemble-driven cluster index is used to measure the weight of each microcluster. With these weights, an ensemble clustering algorithm with dictionary learning and the L2,1-norm is employed in the third phase. Meanwhile, the objective function is resolved by optimizing four subproblems and a similarity matrix is learned. Finally, a normalized cut (Ncut) is used to partition the similarity matrix and the ensemble clustering results are obtained. In this study, the proposed DLWECDL was validated on 20 widely used datasets and compared to some other state-of-the-art ensemble clustering methods. The experimental results demonstrated that the proposed DLWECDL is a very promising method for ensemble clustering.

The relationship between dairy products intake and breast cancer incidence: a meta-analysis of observational studies.

BACKGROUND: The effect of dairy products intake on breast cancer (BC) is highly controversial. This study aims to investigate the relationship between dairy intake and BC incidence. METHODS: A search was carried out in PubMed, EBSCO, Web of Science, and Cochrane Library databases before January 2021. The primary objective was the risk of BC and intake of dairy products were exposure variables. RESULTS: The meta-analysis comprised 36 articles with 1,019,232 participants. Total dairy products have a protective effect on female population (hazard ratio (HR) =0.95, 95% confidence interval (CI) =0.91-0.99, p = 0.019), especially for estrogen receptor-positive (ER+) (HR = 0.79, p = 0.002) and progesterone receptor-positive (PR+) BC (HR = 0.75, p = 0.027). For ER+/PR+ BC, there is a trend of protection, but it has not reached statistical significance (HR = 0.92, p = 0.075). Fermented dairy products can reduce BC risk in postmenopausal population (HR = 0.96, 95%CI = 0.93-0.99, p = 0.021), but have no protective effect on premenopausal population (HR = 0.98, 95%CI = 0.94-1.03, p = 0.52). Non-fermented dairy products have no significant effect on BC occurrence (p > 0.05). High-fat dairy products are harmful to women, without statistical difference (HR = 1.06, 95%CI = 1.00-1.13, p = 0.066). On the contrary, low-fat dairy products can protect the premenopausal population (HR = 0.94, 95%CI = 0.89-1.00, p = 0.048). CONCLUSION: The intake of dairy products can overall reduce BC risk in the female population, but different dairy products have varying effects on different BC subtypes and menopausal status.

The Role of Hepatic Arterial Infusion Chemotherapy in the Treatment of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.

BACKGROUND: The main aim of this study was to investigate comprehensively the clinical effect of hepatic arterial infusion chemotherapy (HAIC) on patients suffering from hepatocellular carcinoma (HCC). METHODS: The following electronic databases were searched for eligible articles published from inception to July 2020: PubMed, Web of Science, Embase, and Cochrane Library. The main final indicators were overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS). RESULTS: A total of 26 studies entailing 4,506 cases were included for a meta-analysis. The results showed that HAIC could improve advanced HCC patients' OS (HR, 0.49; 95% CI: 0.37-0.61) and PFS (HR, 0.52; 95% CI: 0.36-0.68). Remarkably, compared with Japan (HR, 0.58) and Korea (HR, 0.54), for the unresectable HCC patients, the HAIC group achieved higher efficacy on OS than the control group in China (HR, 0.24). The resectable HCC patients, who received HAIC adjuvant chemotherapy, exhibited favorable prognosis for OS (HR, 0.58; 95% CI: 0.27-0.88) and DFS (HR, 0.49; 95% CI: 0.31-0.68). CONCLUSION: HAIC improved long-term survival for both resectable and unresectable HCC patients in comparison with other therapies. However, the clinical effect of HAIC needs to be ascertained by large-scale well-designed studies.

Predictors of 1-year mortality in patients on prolonged mechanical ventilation after surgery in intensive care unit: a multicenter, retrospective cohort study.

OBJECTIVES: The requirement of prolonged mechanical ventilation (PMV) is associated with increased medical care demand and expenses, high early and long-term mortality, and worse life quality. However, no study has assessed the prognostic factors associated with 1-year mortality among PMV patients, not less than 21 days after surgery. This study analyzed the predictors of 1-year mortality in patients requiring PMV in intensive care units (ICUs) after surgery. METHODS: In this multicenter, respective cohort study, 124 patients who required PMV after surgery in the ICUs of five tertiary hospitals in Beijing between January 2007 and June 2016 were enrolled. The primary outcome was the duration of survival within 1 year. Predictors of 1-year mortality were identified with a multivariable Cox proportional hazard model. The predictive effect of the ProVent score was also validated. RESULTS: Of the 124 patients enrolled, the cumulative 1-year mortality was 74.2% (92/124). From the multivariable Cox proportional hazard analysis, cancer diagnosis (hazard ratio [HR] 2.14, 95% confidence interval [CI] 1.37-3.35; P < 0.01), no tracheostomy (HR 2.01, 95% CI 1.22-3.30; P < 0.01), enteral nutrition intolerance (HR 1.88, 95% CI 1.19-2.97; P = 0.01), blood platelet count ≤150 × 109/L (HR 1.77, 95% CI 1.14-2.75; P = 0.01), requirement of vasopressors (HR 1.78, 95% CI 1.13-2.80; P = 0.02), and renal replacement therapy (HR 1.71, 95% CI 1.01-2.91; P = 0.047) on the 21st day of mechanical ventilation (MV) were associated with shortened 1-year survival. CONCLUSIONS: For patients who required PMV after surgery, cancer diagnosis, no tracheostomy, enteral nutrition intolerance, blood platelet count ≤150 × 109/L, vasopressor requirement, and renal replacement therapy on the 21st day of MV were associated with shortened 1-year survival. The prognosis in PMV patients in ICUs can facilitate the decision-making process of physicians and patients' family members on treatment schedule.

Incidence and risk assessment of venous thromboembolism in cancer patients admitted to intensive care unit for postoperative care.

PURPOSE: The occurrence of venous thromboembolism (VTE) in Chinese cancer patients admitted to intensive care unit (ICU) for postoperative care is poorly characterized. This study was designed to investigate the incidence of VTE in this polulation and to evaluate the utility of the Caprini score in risk stratification. METHODS: We conducted a retrospective cohort study of 2127 consecutive adult patients admitted to a 10-bed surgical ICU in a tertiary care academic hospital during a 4-year period (January 1,2013 to December 31,2016). Demographic and VTE data were collected. Data for the Caprini risk assessment model (RAM) was used to stratify patients on their risk of VTE. RESULTS: Of the 2127 patients admitted to ICU after cancer surgery, 66 (3.1%) developed symptomatic VTE. There were a total of 32 patients with pulmonary embolism (PE), 51 patients with deep vein thrombosis (DVT), and 17 patients with both conditions. Based on the original Caprini RAM, 99.5% of the patients scored in the "highest risk" category (score≥5), all patients with VTE were in the "highest risk" category. Further substratification in the "highest risk" category showed the risk of developing VTE events were significantly higher among patients with Caprini score >10 ,as compared with patients with Caprini score of 5 to 6 (OR 5.63; 95%CI 1.27-24.94), 7 to 8 (OR 2.36; 95% CI 1.23-4.52 ) or 9 to 10 (OR 2.28; 95%CI 1.17-4.44). The percentage of patients receiving double prophylaxis was 16.8% (358/2127), 20 of the 66 VTE patients (30.3%) received double prophylaxis before VTE was diagnosed. Patients with higher Caprini score were more likely to receive double thromboprophylaxis than patients with lower Caprini score (23.4% of patients with Caprini score>10 vs 10.8% with Caprini score 5-6). CONCLUSIONS: Though accompanying with the sub-utilizing of chemoprophylaxis, the overall incidence of VTE was relatively low in Chinese cancer patients admitted to ICU for postoperative care. In contrast, the Caprini score was high in this population. The original Caprini RAM was limited to stratify this population, but further substratification of "highest risk" category demonstrated the risk of developing VTE events was significantly higher in patients with Caprini score >10. Future research with high quality evidence should be performed targeting on the accurate risk stratification and optimizing VTE prophylaxis for this population.

Incidence and risk assessment of venous thromboembolism in cancer patients admitted to intensive care unit for postoperative care.

PURPOSE: Cancer patients undergoing surgery are at high risk of venous thromboembolism (VTE). The occurrence of VTE in Chinese cancer patients admitted to intensive care unit (ICU) for postoperative care is poorly characterized. This study was designed to investigate the incidence of VTE in this population and to evaluate the utility of the Caprini score in risk stratification. METHODS: 2127 consecutive adult patients admitted to a 10-bed surgical ICU (SICU) in a tertiary care academic hospital during a 4-year period (January 1, 2013 - December 31, 2016) were enrolled. Demographic and VTE data were collected. Data for the Caprini risk assessment model (RAM) was used to stratify patients on their risk of VTE. RESULTS: Of the 2127 patients admitted to ICU after cancer surgery, 66 (3.1%) developed symptomatic VTE. There were a total of 32 patients with pulmonary embolism (PE), 51 patients with deep vein thrombosis (DVT) and 17 patients with both conditions. Based on the original Caprini RAM, 99.5% of the patients scored in the "highest risk" category (score ≥5), all patients with VTE were in the "highest risk" category. Further substratification in the "highest risk" category showed the risk of developing VTE events was significantly higher among patients with Caprini score greater than 10, as compared with patients with Caprini score of 5 to 6 (OR 5.63;95%CI 1.27-24.94), 7 to 8 (OR 2.36;95%CI 1.23-4.52 ) or 9 to 10 (OR 2.28;95%CI 1.17-4.44). The percentage of patients receiving double prophylaxis was 16.8% (358/2127), 20 of the 66 VTE patients (30.3%) received double prophylaxis before VTE was diagnosed. Patients with higher Caprini score were more likely to receive double thromboprophylaxis than patients with lower Caprini score (23.4% of patients with Caprini score>10 vs 10.8% with Caprini score 5-6). CONCLUSIONS: Though accompanied with the subutilizing of chemoprophylaxis, the overall incidence of VTE was relatively low in Chinese cancer patients admitted to ICU for postoperative care. In contrast, the Caprini score was high in this population. The original Caprini RAM was limited to stratify this population, but further substratification of "highest risk" category demonstrated the risk of developing VTE events was significantly higher in patients with Caprini score greater than 10. Future research with high quality evidence should be performed targeting on the accurate risk stratification and optimizing VTE prophylaxis for this population.

Pulmonary embolism in non-brain tumor patients after surgery-a retrospective study in China.

BACKGROUND: The incidence rate of pulmonary emboli (PE) is high in tumor patients; however, the morbidity and mortality associated with the development of PE after tumor surgery are unknown. We studied the clinical profiles and outcomes of patients with PE after non-brain tumor surgery. METHODS: We retrospectively screened 55,967 patients who underwent non-brain tumor surgery at the Peking University Cancer Hospital from January 2008 to June 2015. Among them, 76 patients who were diagnosed with PE were enrolled in our study. Factors impacting the overall survival at 90 days were analyzed. A Kaplan-Meier curve was plotted for time to death or until day 90. Cox proportional hazard modeling was performed for univariate- and multivariate-adjusted factor analyses. RESULTS: The morbidity rate was approximately 135.8 per 100,000 non-brain tumor surgery patients (possibly underestimated). When treated, seven patients had major bleeding, and 14 patients had clinically relevant non-major bleeding, which represented 9.2 and 18.4% of all the patients, respectively. The 3-month overall mortality rate was 11.8% in our study. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score and platelet distribution width (PDW) were independent risk factors for the prognosis of PE after non-brain surgery (P values of 0.001 and 0.016, respectively). CONCLUSIONS: Treatment of PE in non-brain tumor surgical patients remained a challenge due to the high bleeding rate. The APACHE II score and PDW were independent prognostic factors of survival in patients with PE after non-brain tumor surgery; however, the study power was limited.

A quantitative analysis of municipal solid waste disposal charges in China.

Rapid industrialization and economic development have caused a tremendous increase in municipal solid waste (MSW) generation in China. China began implementing a policy of MSW disposal fees for household waste management at the end of last century. Three charging methods were implemented throughout the country: a fixed disposal fee, a potable water-based disposal fee, and a plastic bag-based disposal fee. To date, there has been little qualitative or quantitative analysis on the effectiveness of this relatively new policy. This paper provides a general overview of MSW fee policy in China, attempts to verify whether the policy is successful in reducing general waste collected, and proposes an improved charging system to address current problems. The paper presents an empirical statistical analysis of policy effectiveness derived from an environmental Kuznets curve (EKC) test on panel data of China. EKC tests on different kinds of MSW charge systems were then examined for individual provinces or cities. A comparison of existing charging systems was conducted using environmental and economic criteria. The results indicate the following: (1) the MSW policies implemented over the study period were effective in the reduction of waste generation, (2) the household waste discharge fee policy did not act as a strong driver in terms of waste prevention and reduction, and (3) the plastic bag-based disposal fee appeared to be performing well according to qualitative and quantitative analysis. Based on current situation of waste discharging management in China, a three-stage transitional charging scheme is proposed and both advantages and drawbacks discussed. Evidence suggests that a transition from a fixed disposal fee to a plastic bag-based disposal fee involving various stakeholders should be the next objective of waste reduction efforts.

Defect scattering can lead to enhanced phonon transport at nanoscale.

Defect scattering is well known to suppress thermal transport. In this study, however, we perform both molecular dynamics and Boltzmann transport equation calculations, to demonstrate that introducing defect scattering in nanoscale heating zone could surprisingly enhance thermal conductance of the system by up to 75%. We further reveal that the heating zone without defects yields directional nonequilibrium with overpopulated oblique-propagating phonons which suppress thermal transport, while introducing defects redirect phonons randomly to restore directional equilibrium, thereby enhancing thermal conductance. We demonstrate that defect scattering can enable such thermal transport enhancement in a wide range of temperatures, materials, and sizes, and offer an unconventional strategy for enhancing thermal transport via the manipulation of phonon directional nonequilibrium.

Development of a fluorescent DNA sensor for dual detection of heavy metal ions utilising DAPI in distinct buffers.

The DNA-based biosensor utilises a thymine/guanine(T/G)-rich ODN-4 scaffold with 4',6-diamidino-2-phenylindole(DAPI) as a fluorescent emissary to monitor mercury/lead(Hg(II)/Pb(II)) ions simultaneously. Key to its bifocal detection capability is the twin unbound cytosine(C) bases strategically bridging the G-quadruplex and T-rich sequences, enabling their synergistic interplay. It facilitates the recognition of Hg(II)/Pb(II) ions, characterised by high specificity, and effectively mitigates interference from silver(Ag(I)). The G-quadruplex, guided by the C bases, induces a conformational transition in T-Hg(II)-T complexes, resulting in intense fluorescence. Pb(II) causes a spatial shift in the G-quadruplex, relaxing the T-Hg(II)-T base pairs and attenuating the fluorescence signal. The ODN-4 exhibits a robust, linear correlation with Hg(II) concentration (4.09 nmol/L to 1000 nmol/L) and Pb(II) concentration (3.22 nmol/L to 5 µmol/L). Recovery rates in milk, tap water, and rice water specimens with both ions validate method accuracy (Hg(II): 95.19% to 104.68%, Pb(II): 98.20% to 103.46%). It holds promising prospects for practical food analysis.

A Representation Learning Approach for Predicting circRNA Back-Splicing Event via Sequence-Interaction-Aware Dual Encoder.

Circular RNAs (circRNAs) play a crucial role in gene regulation and association with diseases because of their unique closed continuous loop structure, which is more stable and conserved than ordinary linear RNAs. As fundamental work to clarify their functions, a large number of computational approaches for identifying circRNA formation have been proposed. However, these methods fail to fully utilize the important characteristics of back-splicing events, i.e., the positional information of the splice sites and the interaction features of its flanking sequences, for predicting circRNAs. To this end, we hereby propose a novel approach called SIDE for predicting circRNA back-splicing events using only raw RNA sequences. Technically, SIDE employs a dual encoder to capture global and interactive features of the RNA sequence, and then a decoder designed by the contrastive learning to fuse out discriminative features improving the prediction of circRNAs formation. Empirical results on three real-world datasets show the effectiveness of SIDE. Further analysis also reveals that the effectiveness of SIDE.

Material Removal Mechanism of SiC Ceramic by Porous Diamond Grinding Wheel Using Discrete Element Simulation.

SiC ceramics are typically hard and brittle materials. Serious surface/subsurface damage occurs during the grinding process due to the poor self-sharpening ability of monocrystalline diamond grits. Nevertheless, recent findings have demonstrated that porous diamond grits can achieve high-efficiency and low-damage machining. However, research on the removal mechanism of porous diamond grit while grinding SiC ceramic materials is still in the bottleneck stage. A discrete element simulation model of the porous diamond grit while grinding SiC ceramics was established to optimize the grinding parameters (e.g., grinding wheel speed, undeformed chip thickness) and pore parameters (e.g., cutting edge density) of the porous diamond grit. The influence of these above parameters on the removal and damage of SiC ceramics was explored from a microscopic perspective, comparing with monocrystalline diamond grit. The results show that porous diamond grits cause less damage to SiC ceramics and have better grinding performance than monocrystalline diamond grits. In addition, the optimal cutting edge density and undeformed chip thickness should be controlled at 1-3 and 1-2 um, respectively, and the grinding wheel speed should be greater than 80 m/s. The research results lay a scientific foundation for the efficient and low-damage grinding of hard and brittle materials represented by SiC ceramics, exhibiting theoretical significance and practical value.

Construction and validation of an 18F-FDG-PET/CT-based prognostic model to predict progression-free survival in newly diagnosed multiple myeloma patients.

OBJECTIVE: To investigate the relationship between 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) related parameters and the prognosis of multiple myeloma and to establish and validate a prediction model regarding the progression-free survival (PFS) of multiple myeloma. METHODS: A retrospective analysis of 126 newly diagnosed multiple myeloma patients who attended Nanjing Drum Tower Hospital from 2014-2021. All patients underwent PET/CT before treatment and were divided into a training cohort (n = 75) and a validation cohort (n = 51). Multivariate Cox proportional hazard regression analysis incorporated PET/CT-related parameters and clinical indicators. A nomogram was established to individually predict PFS in MM patients. The model was evaluated by calculating the C-index and calibration curve. RESULTS: Here, 4.2 was used as the cut-off value of SUVmax to divide patients into high and low groups. PFS significantly differed between patients in the high-SUVmax group and low-SUVmax group, and SUVmax was an independent predictor of PFS in newly diagnosed multiple myeloma (NDMM) patients. Univariate and multivariate cox regression analysis suggested that lactate dehydrogenase (LDH), bone marrow plasma cell (BMPC), and SUVmax affected PFS. These factors were incorporated to construct a nomogram model for predicting PFS at 1 and 2 years in NDMM patients. The C-index and calibration curves of the nomogram exhibited good accuracy and consistency, and the DCA curves suggested that the model had good clinical utility. CONCLUSION: The PET/CT parameter SUVmax is closely related to the prognosis of myeloma patients. The nomogram constructed in this study based on PET/CT-related parameters and clinical indicators individually predicts the PFS rate of NDMM patients and enables further risk stratification of NDMM patients.