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BACKGROUND: The intricate balance between the advantages and risks of low-dose computed tomography (LDCT) impedes the utilization of lung cancer screening (LCS). Guiding shared decision-making (SDM) for well-informed choices regarding LCS is pivotal. There has been a notable increase in research related to SDM. However, these studies possess limitations. For example, they may ignore the identification of decision support and needs from the perspective of health care providers and high-risk groups. Additionally, these studies have not adequately addressed the complete SDM process, including pre-decisional needs, the decision-making process, and post-decision experiences. Furthermore, the East-West divide of SDM has been largely ignored. This study aimed to explore the decisional needs and support for shared decision-making for LCS among health care providers and high-risk groups in China. METHODS: Informed by the Ottawa Decision-Support Framework, we conducted qualitative, face-to-face in-depth interviews to explore shared decision-making among 30 lung cancer high-risk individuals and 9 health care providers. Content analysis was used for data analysis. RESULTS: We identified 4 decisional needs that impair shared decision-making: (1) LCS knowledge deficit; (2) inadequate supportive resources; (3) shared decision-making conceptual bias; and (4) delicate doctor-patient bonds. We identified 3 decision supports: (1) providing information throughout the LCS process; (2) providing shared decision-making decision coaching; and (3) providing decision tools. CONCLUSIONS: This study offers valuable insights into the decisional needs and support required to undergo LCS among high-risk individuals and perspectives from health care providers. Future studies should aim to design interventions that enhance the quality of shared decision-making by offering LCS information, decision tools for LCS, and decision coaching for shared decision-making (e.g., through community nurses). Simultaneously, it is crucial to assess individuals needs for effective deliberation to prevent conflicts and regrets after arriving at a decision.

BackgroundThe diverse risk factors for kidney impairments suggest that kidney function decline is more likely to occur in individuals with a broadly constituted health deficit. Here we conducted a longitudinal cohort study to evaluate the association of baseline frailty status with the risk of estimated glomerular filtration rate (eGFR) decline.MethodsOverall, 1269 participants aged 70-84 years from Rugao Longevity and Ageing cohort with 3-year follow-up were included. Frailty was measured using a modified Fried frailty assessment. GFR was estimated using the Chronic Kidney Disease Epidemiology Collaboration equation. Associations between baseline frailty status and rapid eGFR decline were examined by multinomial logistic analysis. A linear mixed-effect model was used to determine eGFR decline in mL/min/1.73 m2 over the study period comparing those with frail or prefrail at baseline versus those with robust status.ResultsThe mean (± standard deviation) age of participants was 75.1 ± 3.8 years. A total of 144 (11%) participants had rapid eGFR decline by at least 10% during the 3-year follow-up. Compared with robust status, baseline frail status was associated with a 2.48-fold [95% confidence interval (CI) 1.24-4.95] increased risk of rapid eGFR decline after multiple adjustments. In multivariate linear mixed model analysis, subjects with frail status but not prefrail status at baseline had a significant coefficient of -1.70 (95% CI -3.35 to -0.04) for the frail × visit term, which indicates an accelerated eGFR decline compared with robust subjects over the study period (P = 0.044).ConclusionsFrailty may serve as an independent biomarker to predict the decline of kidney function.

PurposePrevious research on incremental hemodialysis transition has mainly focused on one or two benefits or prognoses. We aimed to conduct a comprehensive analysis by investigating whether incremental hemodialysis was simultaneously associated with adequate dialysis therapy, stable complication indicators, long-lasting arteriovenous vascular access, and long-lasting preservation of residual kidney function (RKF) without increasing mortality or hospitalization.Patients and methodsIncident hemodialysis patients from Huashan Hospital in Shanghai, China, over the period of 2012 to 2019, were enrolled and followed every three months until death or the time of censoring. Changes in complication indicators from baseline to all post-baseline visits were analyzed by mixed-effects models. The outcomes of RKF loss, arteriovenous vascular access complications, and the composite of all-cause mortality and cardiovascular events were compared between incremental and conventional hemodialysis by Cox proportional hazards model.ResultsOf the 113 patients enrolled in the study, 45 underwent incremental and 68 conventional hemodialysis. There were no significant differences in the changes from baseline to post-baseline visits in complication indicators between the two groups. Incremental hemodialysis reduced the risks of RKF loss (HR, 0.33; 95% CI, 0.14-0.82), de novo arteriovenous access complication (HR, 0.26; 95% CI, 0.08-0.82), and recurrent arteriovenous access complications under the Andersen-Gill (AG) model (HR, 0.27; 95% CI, 0.10-0.74) and the Prentice, Williams and Peterson Total Time (PWP-TT) model (HR, 0.31; 95% CI, 0.12-0.80). There were no significant differences in all-cause hospitalization or the composite outcome between groups.ConclusionIncremental hemodialysis is an effective dialysis transition strategy that preserves RKF and arteriovenous access without affecting dialysis adequacy, patient stability, hospitalization risk and mortality risk. Randomized controlled trials are warranted.

Genome editing of human induced pluripotent stem cells (iPSCs) is instrumental for functional genomics, disease modeling, and regenerative medicine. However, low editing efficiency has hampered the applications of CRISPR-Cas9 technology in creating knockin (KI) or knockout (KO) iPSC lines, which is largely due to massive cell death after electroporation with editing plasmids. Here, we report that the transient delivery of BCL-XL increases iPSC survival by ∼10-fold after plasmid transfection, leading to a 20- to 100-fold increase in homology-directed repair (HDR) KI efficiency and a 5-fold increase in non-homologous end joining (NHEJ) KO efficiency. Treatment with a BCL inhibitor ABT-263 further improves HDR efficiency by 70% and KO efficiency by 40%. The increased genome editing efficiency is attributed to higher expressions of Cas9 and sgRNA in surviving cells after electroporation. HDR or NHEJ efficiency reaches 95% with dual editing followed by selection of cells with HDR insertion of a selective gene. Moreover, KO efficiency of 100% can be achieved in a bulk population of cells with biallelic HDR KO followed by double selection, abrogating the necessity for single cell cloning. Taken together, these simple yet highly efficient editing strategies provide useful tools for applications ranging from manipulating human iPSC genomes to creating gene-modified animal models.

Biochar is crucial for agricultural output and plays a significant role in effectively eliminating heavy metals (HMs) from the soil, which is essential for maintaining a soil–plant environment. This work aimed to assess machine learning models to analyze the impact of soil parameters on the transformation of HMs in biochar–soil–plant environments, considering the intricate non-linear relationships involved. A total of 211 datasets from pot or field experiments were evaluated. Fourteen factors were taken into account to assess the efficiency and bioavailability of HM–biochar amendment immobilization. Four predictive models, namely linear regression (LR), partial least squares (PLS), support vector regression (SVR), and random forest (RF), were compared to predict the immobilization efficiency of biochar-HM. The findings revealed that the RF model was created using 5-fold cross-validation, which exhibited a more reliable prediction performance. The results indicated that soil features accounted for 79.7% of the absorption of HM by crops, followed by biochar properties at 17.1% and crop properties at 3.2%. The main elements that influenced the result have been determined as the characteristics of the soil (including the presence of different HM species and the amount of clay) and the quantity and attributes of the biochar (such as the temperature at which it was produced by pyrolysis). Furthermore, the RF model was further developed to predict bioaccumulation factors (BAF) and variations in crop uptake (CCU). The R2 values were found to be 0.7338 and 0.6997, respectively. Thus, machine learning (ML) models could be useful in understanding the behavior of HMs in soil–plant ecosystems by employing biochar additions. [ABSTRACT FROM AUTHOR]

Three successive vegetable pot experiments were conducted to assess the effects on the long-term immobilization of heavy metals in soil and crop yield improvement after the addition of peanut shell biochar and an alkaline mineral to an acidic soil contaminated with lead and cadmium. Compared with the CK treatment, the change rates of biomass in the edible parts of the three types of vegetables treated with B0.3, B1, B3, B9, R0.2 and B1R0.2 were −15.43%~123.30%, 35.10%~269.09%, 40.77%~929.31%, −26.08%~711.99%, 44.14%~1067.12% and 53.09%~1139.06%, respectively. The cadmium contents in the edible parts of the three vegetables treated with these six additives reduced by 2.08%~13.21%, 9.56%~24.78%, 9.96%~35.61%, 41.96%~78.42%, −4.19%~57.07% and 12.43%~65.92%, respectively, while the lead contents in the edible parts reduced by −15.70%~59.47%, 6.55%~70.75%, 3.40%~80.10%, 55.26%~89.79%, 11.05%~70.15% and 50.35%~79.25%, respectively. Due to the increases in soil pH, soil cation-exchange capacity and soil organic carbon content, the accumulation of Cd and Pb in the vegetables was most notably reduced with a high dosage of 9% peanut shell biochar alone, followed by the addition of a low dosage of 1% peanut shell biochar blended with 0.2% alkaline mineral. Therefore, the addition of a low dosage of 1% peanut shell biochar blended with 0.2% alkaline mineral was the best additive in increasing the vegetable biomass, whereas the addition of 9% peanut shell biochar alone was the worst. Evidently, the addition of 0.2% alkaline mineral can significantly reduce the amount of peanut shell needed for passivating heavy metals in soil, while it also achieves the effect of increasing the vegetable yield. [ABSTRACT FROM AUTHOR]

Sorption is the most important process influencing the amount of herbicide retained in soils. The special properties of biochar could influence the soil retention of pollutants through adsorption. However, the detailed sorption mechanisms as influenced before and after applying biochar to soils with different properties are unclear. This study examined the sorption characteristics of metolachlor using soil samples collected from South China. Sorption experiments were conducted using a batch equilibration method. After comparing the metolachlor sorption constants observed for all soil samples, our results showed that the application of biochar significantly increased the capacity of metolachlor adsorption. Without biochar, sorption capacity (Kf) was positively related to soil organic matter and to a soil particle size of 0.002–0.02 mm in soils developed from granite, of 0.002–0.02 mm in soils developed from delta shockwaves, and of 0.002–0.02 mm, together with complex iron oxide and total iron content, in soils developed from arenaceous shale. Moreover, sorption capacity (Kf) with biochar was positively related to peroxidase in soils developed from granite and to dissociative iron oxide and total iron content in soils developed from arenaceous shale. Our results show that biochar greatly affects metolachlor sorption behavior, probably because of qualitative differences in the structural characteristics of soils with different developmental parent materials and properties. [ABSTRACT FROM AUTHOR]

Aims/Introduction: Gastric cancer, one of the most common malignant tumors worldwide, is affected by insulin resistance. The triglyceride glucose (TYG) index is considered a surrogate indicator of insulin resistance; however, its prognostic value in patients with gastric cancer remains obscure. This study aimed to determine whether the TYG index could predict the long‐term prognosis of patients with gastric cancer after radical resection gastrectomy. Materials and Methods: We retrospectively analyzed patients with gastric cancer who underwent radical resection gastrectomy. The preoperative TYG index was calculated using the patients' laboratory data. Patients were divided into two groups based on a high or low TYG index. We observed overall survival and evaluated the clinical application value of the index using Cox proportional hazards regression to calculate independent parameters. A prediction model was also established. Results: In total, 822 patients with gastric cancer were included. The high and low TYG index groups comprised 353 and 469 patients, respectively. The overall survival time was significantly longer in the high‐index group than in the low‐index group. In the multivariate analysis, TYG index, preoperative age, surgical procedure, tumor node metastasis (TNM) stage, N stage, and postoperative complications (all p < 0.01) were considered independent prognostic predictors. Based on the multivariate analysis, the riglyceride glucose (TYG) index hazard ratio was 0.70 (95% confidence interval, 0.54–0.89, p = 0.004). Conclusions: We established a model with a high clinical application value and clinical practice relevance to predict the prognosis of gastric cancer. In this model, TYG was an independent protective factor for gastric cancer prognosis. [ABSTRACT FROM AUTHOR]