A Cost-Effective Model for Predicting Recurrent Gastric Cancer Using Clinical Features.

This study used artificial intelligence techniques to identify clinical cancer biomarkers for recurrent gastric cancer survivors. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random Forest using MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged the synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive exPlanations (SHAPs) for feature importance analysis in this study. Our proposed Random Forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86%, and an F1 of 88.2% on the recurrent category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI (body mass index), and gender; these features significantly affect the prediction model's output and are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

Urban-Rural Disparities in the Association Between Home- and Community-Based Service Utilization and Levels of Disability Among Chinese Older Adults With Disabilities.

Home- and community-based services (HCBS) are optimal ways to deal with disability problems among older adults. This study aims to analyze urban-rural disparities in the relationship between HCBS utilization and levels of disability among Chinese older adults with disabilities, so as to meet the long-term care needs of them. In applying the Andersen Behavioral Model, bivariate analysis and multivariate regression models were employed using data from 843 older adults with disabilities from the 2018 China Longitudinal Aging Social Survey (CLASS). After adjusting covariates, disability levels among Chinese older adults with disabilities were significantly correlated with HCBS utilization in urban areas but not in rural areas. The urban-rural disparities may be due to the low utilization of HCBS in rural areas (only 11.2%) among older adults with disabilities compared with their urban counterparts (22.7%).

Differences in inpatient performance of public general hospitals following implementation of a points-counting payment based on diagnosis-related group: a robust multiple interrupted time series study in Wenzhou, China.

OBJECTIVES: This study measures the differences in inpatient performance after a points-counting payment policy based on diagnosis-related group (DRG) was implemented. The point value is dynamic; its change depends on the annual DRGs' cost settlements and points of the current year, which are calculated at the beginning of the following year. DESIGN: A longitudinal study using a robust multiple interrupted time series model to evaluate service performance following policy implementation. SETTING: Twenty-two public general hospitals (8 tertiary institutions and 14 secondary institutions) in Wenzhou, China. INTERVENTION: The intervention was implemented in January 2020. OUTCOME MEASURES: The indicators were case mix index (CMI), cost per hospitalisation (CPH), average length of stay (ALOS), cost efficiency index (CEI) and time efficiency index (TEI). The study employed the means of these indicators. RESULTS: The impact of COVID-19, which reached Zhejiang Province at the end of January 2020, was temporary given rapid containment following strict control measures. After the intervention, except for the ALOS mean, the change-points for the other outcomes (p<0.05) in tertiary and secondary institutions were inconsistent. The CMI mean turned to uptrend in tertiary (p<0.01) and secondary (p<0.0001) institutions compared with before. Although the slope of the CPH mean did not change (p>0.05), the uptrend of the CEI mean in tertiary institutions alleviated (p<0.05) and further increased (p<0.05) in secondary institutions. The slopes of the ALOS and TEI mean in secondary institutions changed (p<0.05), but not in tertiary institutions (p>0.05). CONCLUSIONS: This study showed a positive effect of the DRG policy in Wenzhou, even during COVID-19. The policy can motivate public general hospitals to improve their comprehensive capacity and mitigate discrepancies in treatment expenses efficiency for similar diseases. Policymakers are interested in whether the reform successfully motivates hospitals to strengthen their internal impetus and improve their performance, and this is supported by this study.

Enhancing the effectiveness of bioaerosol disinfection in indoor environments by optimizing far-UVC lamp locations based on Markov chain model.

Far-ultraviolet C (far-UVC) light is an effective and safe disinfection method for bioaerosol control in occupied indoor environments. The installation location of a far-UVC lamp strongly influences the spatial distribution of far-UVC irradiance, and thus the effectiveness of bioaerosol disinfection. To assist the design process, this study developed a fast prediction approach based on the Markov chain model for optimizing the installation locations of far-UVC lamps in order to enhance the disinfection effectiveness for indoor bioaerosol control. Experiments were conducted in an environmental chamber to validate the proposed simulation-based optimization approach. The results show that the proposed method can correctly predict the disinfection efficiency when compared with experimental data, and optimizing the installation location of the far-UVC lamp increased the disinfection efficiency by 54 % compared with the worst location. As an application, the validated method was then used to design the installation location of a far-UVC lamp in a real conference room. The results show that installing the far-UVC lamp in the optimal location can increase the disinfection efficiency by 48 % compared with the worst installation location. Therefore, optimizing the far-UVC lamp location using the proposed Markov chain model can enhance the effectiveness of bioaerosol disinfection in indoor environments.

Association of Late Radiographic Assessment of Lung Edema Score with Clinical Outcome in Patients with Influenza-Associated Acute Respiratory Distress Syndrome.

Background: Influenza virus infection leads to acute pulmonary injury and acute respiratory distress syndrome (ARDS). The Radiographic Assessment of Lung Edema (RALE) score has been proposed as a reliable tool for the evaluation of the opacity of chest X-rays (CXRs). This study aimed to examine the RALE scores and outcomes in patients with influenza-associated ARDS. Methods: Patients who were newly diagnosed with influenza-associated ARDS from December 2015 to March 2016 were enrolled. Two independent reviewers scored the CXRs obtained on the day of ICU admission and on days 2 and 7 after intensive care unit (ICU) admission. Results: During the study, 47 patients had influenza-associated ARDS. Five died within 7 days of ICU admission. Of the remaining 42, non-survivors (N = 12) had higher Sequential Organ Failure Assessment scores (SOFA) at ICU admission and higher day 7 RALE scores than survivors (N = 30). The day 7 RALE score independently related to late in-hospital mortality (aOR = 1.121, 95% CI: 1.014-1.240, p = 0.025). Conclusions: The RALE score for the evaluation of opacity on CXRs is a highly reproducible tool. Moreover, RALE score on day 7 was an independent predictor of late in-hospital mortality in patients with influenza-associated ARDS.

An observational study on salivary conductivity for fluid status assessment and clinical relevance in acute ischemic stroke during intravenous fluid hydration.

The body fluid status in acute stroke is a crucial determinant in early stroke recovery but a real-time method to monitor body fluid status is not available. This study aims to evaluate the relationship between salivary conductivity and body fluid status during the period of intravenous fluid hydration. Between June 2020 to August 2022, patients presenting with clinical signs of stroke at the emergency department were enrolled. Salivary conductivities were measured before and 3 h after intravenous hydration. Patients were considered responsive if their salivary conductivities at 3 h decreased by more than 20% compared to their baseline values. Stroke severity was assessed using the National Institutes of Health Stroke Scale, and early neurological improvement was defined as a decrease of ≥ 2 points within 72 h of admission. Among 108 recruited patients, there were 35 of stroke mimics, 6 of transient ischemic attack and 67 of acute ischemic stroke. Salivary conductivity was significantly decreased after hydration in all patients (9008 versus 8118 µs/cm, p = 0.030). Among patients with acute ischemic stroke, the responsive group, showed a higher rate of early neurological improvement within 3 days compared to the non-responsive group (37% versus 10%, p = 0.009). In a multivariate logistic regression model, a decrease in salivary conductivity of 20% or more was found to be an independent factor associated with early neurological improvement (odds ratio 5.42, 95% confidence interval 1.31-22.5, p = 0.020). Real-time salivary conductivity might be a potential indicator of hydration status of the patient with acute ischemic stroke.

Demand prediction of medical services in home and community-based services for older adults in China using machine learning.

Background: Home and community-based services are considered an appropriate and crucial caring method for older adults in China. However, the research examining demand for medical services in HCBS through machine learning techniques and national representative data has not yet been carried out. This study aimed to address the absence of a complete and unified demand assessment system for home and community-based services. Methods: This was a cross-sectional study conducted on 15,312 older adults based on the Chinese Longitudinal Healthy Longevity Survey 2018. Models predicting demand were constructed using five machine-learning methods: Logistic regression, Logistic regression with LASSO regularization, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGboost), and based on Andersen's behavioral model of health services use. Methods utilized 60% of older adults to develop the model, 20% of the samples to examine the performance of models, and the remaining 20% of cases to evaluate the robustness of the models. To investigate demand for medical services in HCBS, individual characteristics such as predisposing, enabling, need, and behavior factors constituted four combinations to determine the best model. Results: Random Forest and XGboost models produced the best results, in which both models were over 80% at specificity and produced robust results in the validation set. Andersen's behavioral model allowed for combining odds ratio and estimating the contribution of each variable of Random Forest and XGboost models. The three most critical features that affected older adults required medical services in HCBS were self-rated health, exercise, and education. Conclusion: Andersen's behavioral model combined with machine learning techniques successfully constructed a model with reasonable predictors to predict older adults who may have a higher demand for medical services in HCBS. Furthermore, the model captured their critical characteristics. This method predicting demands could be valuable for the community and managers in arranging limited primary medical resources to promote healthy aging.

Invasiveness assessment by artificial intelligence against intraoperative frozen section for pulmonary nodules ≤ 3 cm.

PURPOSE: To investigate the performance of an artificial intelligence (AI) algorithm for assessing the malignancy and invasiveness of pulmonary nodules in a multicenter cohort. METHODS: A previously developed deep learning system based on a 3D convolutional neural network was used to predict tumor malignancy and invasiveness. Dataset of pulmonary nodules no more than 3 cm was integrated with CT images and pathologic information. Receiver operating characteristic curve analysis was used to evaluate the performance of the system. RESULTS: A total of 466 resected pulmonary nodules were included in this study. The areas under the curves (AUCs) of the deep learning system in the prediction of malignancy as compared with pathological reports were 0.80, 0.80, and 0.75 for all, subcentimeter, and solid nodules, respectively. Additionally, the AUC in the AI-assisted prediction of invasive adenocarcinoma (IA) among subsolid lesions (n = 184) was 0.88. Most malignancies that were misdiagnosed by the AI system as benign diseases with a diameter measuring greater than 1 cm (26/250, 10.4%) presented as solid nodules (19/26, 73.1%) on CT. In an exploratory analysis involving nodules underwent intraoperative pathologic examination, the concordance rate in identifying IA between the AI model and frozen section examination was 0.69, with a sensitivity of 0.50 and specificity of 0.97. CONCLUSION: The deep learning system can discriminate malignant diseases for pulmonary nodules measuring no more than 3 cm. The AI model has a high positive predictive value for invasive adenocarcinoma with respect to intraoperative frozen section examination, which might help determine the individualized surgical strategy.

Efficacy assessment of laser Doppler imager in diagnosing the pulp vitality after dental trauma.

Background/purpose: This is the first paper evaluating the efficacy of laser Doppler imager in diagnosis of pulpal vitality. The purpose of this study was to evaluate and compare the diagnostic benefits of laser Doppler imaging and electric pulp test (EPT) in dental trauma. Materials and methods: Seven patients were selected for pulp vitality evaluation in Kaohsiung Medical University Hospital between 2018 and 2019. EPT and laser Doppler imager evaluation were performed for patients with traumatic injury to teeth. Statistical methods included the Kappa consistency test and the chi-square test. In addition, the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) were used. Results: There was a significant difference in Doppler flow values between the severe trauma group and the mild trauma group, regardless of patient self-reported symptoms (P = 0.043) or physicians' diagnostic classification (P = 0.018). For an EPT instrument, the Kappa coefficient was 0.67 and 1-year pulpal status findings were highly consistent (P < 0.001). Using a Doppler instrument, the Kappa coefficient was 0.85. According to the ROC curve, the AUC for EPT was 0.94, the AUC for Doppler was 1, and the optimal cut-off value was 31.55, indicating that both were superior diagnostic tools. Conclusion: Both laser Doppler imager and EPT can be used as tools for diagnosing traumatic pulp necrosis. Doppler imaging instruments allow for a more timely and accurate assessment of pulp vitality in dental trauma. In the future, ongoing research and related training are necessary for interpretation of Doppler data.

Aspergillus oryzae Fermentation Extract Alleviates Inflammation in Mycoplasma pneumoniae Pneumonia.

The filamentous fungus Aspergillus oryzae, also known as koji mold, has been used for centuries in the production of fermented foods in East Asia. A. oryzae fermentation can produce enzymes and metabolites with various bioactivities. In this study, we investigated whether A. oryzae fermentation extract (AOFE) has any effect on Mycoplasma pneumoniae (Mp) pneumonia. We performed solid-state fermentation of A. oryzae and obtained the ethanol extract. AOFE was analyzed by HPLC, and the major component was identified to be kojic acid. In vitro, AOFE suppressed Mp growth and invasion into A549 lung epithelial cells as determined by the gentamicin protection assay. AOFE treatment also suppressed Mp-stimulated production of tumor necrosis factor (TNF)-α and interleukin (IL)-6 at mRNA and protein levels in murine MH-S alveolar macrophages. In a mouse model of Mp pneumonia, Mp infection induced a marked pulmonary infiltration of neutrophils, which was significantly reduced in mice pre-treated orally with AOFE. AOFE administration also suppressed the production of proinflammatory cytokines and chemokines in the lungs. Collectively, our results show that AOFE has the potential to be developed into a preventive/therapeutic agent for Mp pneumonia.

Developing a Capsule Clinic-A 24-Hour Institution for Improving Primary Health Care Accessibility: Evidence From China.

Telehealth is an effective combination of medical service and intelligent technology. It can improve the problem of remote access to medical care. However, an imbalance in the allocation of health resources still occurs. People spend more time and money to access higher-quality services, which results in inequitable access to primary health care (PHC). At the same time, patients' usage of telehealth services is limited by the equipment and their own knowledge, and the PHC service suffers from low usage efficiency and lack of service supply. Therefore, improving PHC accessibility is crucial to narrowing the global health care coverage gap and maintaining health equity. In recent years, China has explored several new approaches to improve PHC accessibility. One such approach is the capsule clinic, an emerging institution that represents an upgraded version of the internet hospital. In coordination with the United Nations, the Yinzhou district of Ningbo city in Zhejiang, China, has been testing this new model since 2020. As of October 2022, the number of applications in Ningbo was 15, and the number of users reached 12,219. Unlike internet hospitals, the entire process-from diagnosis to prescription services-can be completed at the capsule clinic. The 24-hour telehealth service could also solve transportation problems and save time for users. Big data analysis can accurately identify regional populations' PHC service needs and improve efficiency in health resource allocation. The user-friendly, low-cost, and easily accessible telehealth model is of great significance. Installation of capsule clinics would improve PHC accessibility and resolve the uneven distribution of health resources to promote health equity.

Macroalgal biomass as a potential resource for lactic acid fermentation.

Lactic acid is an essential platform chemical with various applications in the chemicals, food, pharmaceutical, and cosmetic industries. Currently, the demand for lactic acid is driven by the role of lactic acid as the starting material for the production of bioplastic polylactide. Microbial fermentation for lactic acid production is favored due to the production of enantiomerically pure lactic acid required for polylactide synthesis, as opposed to the racemic mixture obtained via chemical synthesis. The utilization of first-generation feedstock for commercial lactic acid production is challenged by feedstock costs and sustainability issues. Macroalgae are photosynthetic benthic aquatic plants that contribute tremendously towards carbon capture with subsequent carbon-rich biomass production. Macroalgae are commercially cultivated to extract hydrocolloids, and recent studies have focused on applying biomass as a fermentation feedstock. This review provides comprehensive information on the design and development of sustainable and cost-effective, algae-based lactic acid production. The central carbon regulation in lactic acid bacteria and the metabolism of seaweed-derived sugars are described. An exhaustive compilation of lactic acid fermentation of macroalgae hydrolysates revealed that lactic acid bacteria can effectively ferment the mixture of sugars present in the hydrolysate with comparable yields. The environmental impacts and economic prospects of macroalgal lactic acid are analyzed. Valorization of the vast amounts of spent macroalgal biomass residue post hydrocolloid extraction in a biorefinery is a viable strategy for cost-effective lactic acid production.

Safety assessment of Mpp75Aa1.1, a new ETX_MTX2 protein from Brevibacillus laterosporus that controls western corn rootworm.

The recently discovered insecticidal protein Mpp75Aa1.1 from Brevibacillus laterosporus is a member of the ETX_MTX family of beta-pore forming proteins (ß-PFPs) expressed in genetically modified (GM) maize to control western corn rootworm (WCR; Diabrotica virgifera virgifera LeConte). In this manuscript, bioinformatic analysis establishes that although Mpp75Aa1.1 shares varying degrees of similarity to members of the ETX_MTX2 protein family, it is unlikely to have any allergenic, toxic, or otherwise adverse biological effects. The safety of Mpp75Aa1.1 is further supported by a weight of evidence approach including evaluation of the history of safe use (HOSU) of ETX_MTX2 proteins and Breviballus laterosporus. Comparisons between purified Mpp75Aa1.1 protein and a poly-histidine-tagged (His-tagged) variant of the Mpp75Aa1.1 protein demonstrate that both forms of the protein are heat labile at temperatures at or above 55°C, degraded by gastrointestinal proteases within 0.5 min, and have no adverse effects in acute mouse oral toxicity studies at a dose level of 1920 or 2120 mg/kg body weight. These results support the use of His-tagged proteins as suitable surrogates for assessing the safety of their non-tagged parent proteins. Taken together, we report that Mpp75Aa1.1 is the first ETX-MTX2 insecticidal protein from B. laterosporus and displays a similar safety profile as typical Cry proteins from Bacillus thuringiensis.

Efficacy and Safety of High-Dose Intracoronary Adenosine Injection in Fractional Flow Reserve Assessment.

Background: The recommended dosage of intracoronary adenosine in fractional flow reserve (FFR) assessment is controversial. High-dose adenosine may overcome the biological variability of adenosine response in hyperemia. Objectives: We aimed to test the efficacy and safety of a high-dose escalation protocol at our institute. Methods: Using the adenosine dose escalation protocol, the percentages of FFR ≤ 0.75 and 0.80 after high-dose escalation were compared with those at conventional doses. The chi-squared test was used to evaluate the accuracy of FFR values with the tested doses by comparing them with the results of a non-invasive pretest. Results: A total of 87 patients (130 vessels) were included, and protocol adherence was 93.1%. High-dose intracoronary adenosine was injected in 78.5% of the vessels. The dose escalation strategy was well-tolerated without serious complications. The positive rate increased significantly after conducting the protocol compared to that with a conventional dose (28.2% vs. 23.6% with an FFR threshold of 0.75, and 48.7% vs. 42.5% with a threshold of 0.80, both p < 0.05). In the validation cohort, only FFR ≤ 0.75 was associated with the binary result of the non-invasive pretest (p < 0.01 vs. p = 0.37). The high-dose adenosine escalation strategy did not increase the accuracy of FFR (77.8% vs. 75.6% in conventional dose and high-dose adenosine, respectively). Conclusions: The use of a high-dose escalation strategy increased the positive rate in FFR assessments.

Safety of Special Waveform of Transcranial Electrical Stimulation (TES): In Vivo Assessment.

Intermittent theta burst (iTBS) powered by direct current stimulation (DCS) can safely be applied transcranially to induce neuroplasticity in the human and animal brain cortex. tDCS-iTBS is a special waveform that is used by very few studies, and its safety needs to be confirmed. Therefore, we aimed to evaluate the safety of tDCS-iTBS in an animal model after brain stimulations for 1 h and 4 weeks. Thirty-one Sprague Dawley rats were divided into two groups: (1) short-term stimulation for 1 h/session (sham, low, and high) and (2) long-term for 30 min, 3 sessions/week for 4 weeks (sham and high). The anodal stimulation applied over the primary motor cortex ranged from 2.5 to 4.5 mA/cm2. The brain biomarkers and scalp tissues were assessed using ELISA and histological analysis (H&E staining) after stimulations. The caspase-3 activity, cortical myelin basic protein (MBP) expression, and cortical interleukin (IL-6) levels increased slightly in both groups compared to sham. The serum MBP, cortical neuron-specific enolase (NSE), and serum IL-6 slightly changed from sham after stimulations. There was no obvious edema or cell necrosis seen in cortical histology after the intervention. The short- and long-term stimulations did not induce significant adverse effects on brain and scalp tissues upon assessing biomarkers and conducting histological analysis.

Are ESG-committed hotels financially resilient to the COVID-19 pandemic? An autoregressive jump intensity trend model.

Given that the United Nations views environmental, social, and governance (ESG) as a practical framework for anchoring responsible corporate behavior to achieve its sustainable development goals, this study constructs an autoregressive jump intensity trend (ARJI-trend) model to determine if ESG can improve future resilience and create crisis-resilient value for chained-brand hotel corporations from the effects of COVID-19. The findings indicate that the ARJI-trend model indeed captures both the permanent and transitory components of the hotel corporation's ESG performance related to stock return dynamics. When ESG rating is taken into account, the following conclusions emerge: 1) the transitory component of time-varying return variance decreases but the permanent component does not; 2) the hotel corporation portfolios with a lower transitory component experiences a higher return, implying that the hotel corporations with a higher ESG rating appear to be more defensiveness; and 3) with proper asset reallocation, a portfolio centered on strong ESG-conscious hotel corporations is a safe-haven asset during market turmoil.

Health risk assessment of PM2.5 heavy metals in county units of northern China based on Monte Carlo simulation and APCS-MLR.

The key areas of China's urbanization process have gradually shifted from urban areas to county-level units. Correspondingly, air pollution in county towns may be heavier than in urban areas, which has led to a lack of understanding of the pollution situation in such areas. In view of this, 236 PM2.5 filter samples were collected in Pingyao, north of the Fen-Wei Plain, one of the most polluted areas in China. Monte Carlo simulation was used to solve the serious uncertainties of traditional HRA, and the coupling technology of absolute principal component score-multiple linear regression (APCS-MLR) and health risk assessment (HRA) is used to quantitatively analyze the health risks of pollution sources. The results showed that PM2.5 concentration was highest in autumn, 3.73 times the 24 h guideline recommended by the World Health Organization (WHO). Children were more susceptible to heavy metals in the county-level unit, with high hazard quotient (HQ) values of Pb being the dominant factor leading to an increased non-carcinogenic risk. A significant carcinogenic risk was observed for all groups in autumn in Pingyao, with exposure to Ni in the outdoor environment being the main cause. Vehicle emissions and coal combustion were identified as two major sources of health threats. In short, China's county-level population, about one-tenth of the world's population, faces far more health risks than expected.

Cost-effectiveness of osimertinib versus placebo in resected EGFR-mutated non-small cell lung cancer in China.

PURPOSE: We aim to assess whether osimertinib postoperative adjuvant therapy, compared with placebo, is cost-effective in China. METHODS: We set up the Markov model that contains three health states over a 20-year period. Data were collected from the ADAURA trial that included transition probabilities and safety data. Through the analysis of literature and local charges, we explore both the cost and utility values. Sensitivity analyses were employed using TreeAge Pro software to access model stability. FINDINGS: Patients in the osimertinib group had 1.46 more Quality-adjusted Life Years (8.45 QALYs vs 6.99 QALYs) than the placebo group at an incremental cost of $14098.51($39962.99 vs $25864.48). Compared with the placebo group, the treatment strategy with osimertinib postoperative adjuvant therapy had an incremental cost-effectiveness ratio of $9661.97/QALY. The probability of the osimertinib-assisted therapy strategy being cost-effective will reach 100% if the threshold of willingness to pay is above $15,000/QALY. IMPLICATIONS: From the perspective of the Chinese Healthcare System, the treatment strategy with osimertinib postoperative adjuvant therapy is more cost-effective than the placebo strategy.

The causal link between circular economy and economic growth in EU-25.

Actively promoting circular economy (CE) is one of the key means of global sustainable development. The purpose of this study is to analyze the causal relationship between CE and economic growth using data from EU-25 countries from 2010 to 2018. The selected CE indicators included municipal waste recycling rate, CE-related investment, municipal waste generation per capita, circularity rate, and trade in recyclable raw materials. Panel cointegration techniques affirmed the long-term equilibrium relationship between CE indicators and GDP. Panel vector error correction model results confirmed that in terms of short-run causality, an increase in material recycling led to a decrease in waste generation, an increase in waste generation led to an increase in CE-related investment, and economic growth led to circular economy growth, but not vice versa. This implies that encouraging CE-related innovation investments and promoting material recycling to stimulate the secondary raw material market can help achieve zero waste goals. Looking at the long-term causality, the GDP and CE indicators constituted a causal loop, which implies that there is co-evolution between them, although the circular economy is still in its infancy. This co-evolutionary sustainable economic growth can bring welfare to future generations.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels.

PURPOSE: Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not. METHODS: Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship. RESULTS: As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants. CONCLUSION: Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.