Health economic evaluation of an artificial intelligence (AI)-based rapid nutritional diagnostic system for hospitalised patients: A multicentre, randomised controlled trial.

BACKGROUND & AIMS: Malnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of using an artificial intelligence (AI)-based rapid nutritional diagnostic system for routine nutritional screening of hospitalised patients. METHODS: A nationwide multicentre randomised controlled trial was conducted at 11 centres in 10 provinces. Hospitalised patients were randomised to either receive an assessment using an AI-based rapid nutritional diagnostic system as part of routine care (experimental group), or not (control group). The overall medical resource costs were calculated for each participant and a decision-tree was generated based on an intention-to-treat analysis to analyse the cost-effectiveness of various treatment modalities. Subgroup analyses were performed according to clinical characteristics and a probabilistic sensitivity analysis was performed to evaluate the influence of parameter variations on the incremental cost-effectiveness ratio (ICER). RESULTS: In total, 5763 patients participated in the study, 2830 in the experimental arm and 2933 in the control arm. The experimental arm had a significantly higher cure rate than the control arm (23.24% versus 20.18%; p = 0.005). The experimental arm incurred an incremental cost of 276.52 CNY, leading to an additional 3.06 cures, yielding an ICER of 90.37 CNY. Sensitivity analysis revealed that the decision-tree model was relatively stable. CONCLUSION: The integration of the AI-based rapid nutritional diagnostic system into routine inpatient care substantially enhanced the cure rate among hospitalised patients and was cost-effective. REGISTRATION: NCT04776070 (https://clinicaltrials.gov/study/NCT04776070).

l-Carnitine relieves cachexia-related skeletal muscle fibrosis by inducing deltex E3 ubiquitin ligase 3L to negatively regulate the Runx2/COL1A1 axis.

BACKGROUND: Cancer cachexia-induced skeletal muscle fibrosis (SMF) impairs muscle regeneration, alters the muscle structure and function, reduces the efficacy of anticancer drugs, diminishes the patient's quality of life and shortens overall survival. RUNX family transcription factor 2 (Runx2), a transcription factor, and collagen type I alpha 1 chain (COL1A1), the principal constituent of SMF, have been linked previously, with Runx2 shown to directly modulate COL1A1 mRNA levels. l-Carnitine, a marker of cancer cachexia, can alleviate fibrosis in liver and kidney models; however, its role in cancer cachexia-associated fibrosis and the involvement of Runx2 in the process remain unexplored. METHODS: Female C57 mice (48 weeks old) were inoculated subcutaneously with MC38 cells to establish a cancer cachexia model. A 5 mg/kg dose of l-carnitine or an equivalent volume of water was administered for 14 days via oral gavage, followed by assessments of muscle function (grip strength) and fibrosis. To elucidate the interplay between the deltex E3 ubiquitin ligase 3L(DTX3L)/Runx2/COL1A1 axis and fibrosis in transforming growth factor beta 1-stimulated NIH/3T3 cells, a suite of molecular techniques, including quantitative real-time PCR, western blot analysis, co-immunoprecipitation, molecular docking, immunofluorescence and Duolink assays, were used. The relevance of the DTX3L/Runx2/COL1A1 axis in the gastrocnemius was also explored in the in vivo model. RESULTS: l-Carnitine supplementation reduced cancer cachexia-induced declines in grip strength (>88.2%, P < 0.05) and the collagen fibre area within the gastrocnemius (>57.9%, P < 0.05). At the 5 mg/kg dose, l-carnitine also suppressed COL1A1 and alpha-smooth muscle actin (α-SMA) protein expression, which are markers of SMF and myofibroblasts. Analyses of the TRRUST database indicated that Runx2 regulates both COL1A1 and COL1A2. In vitro, l-carnitine diminished Runx2 protein levels and promoted its ubiquitination. Overexpression of Runx2 abolished the effects of l-carnitine on COL1A1 and α-SMA. Co-immunoprecipitation, molecular docking, immunofluorescence and Duolink assays confirmed an interaction between DTX3L and Runx2, with l-carnitine enhancing this interaction to promote Runx2 ubiquitination. l-Carnitine supplementation restored DTX3L levels to those observed under non-cachectic conditions, both in vitro and in vivo. Knockdown of DTX3L abolished the effects of l-carnitine on Runx2, COL1A1 and α-SMA in vitro. The expression of DTX3L was negatively correlated with the levels of Runx2 and COL1A1 in untreated NIH/3T3 cells. CONCLUSIONS: This study revealed a previously unrecognized link between Runx2 and DTX3L in SMF and demonstrated that l-carnitine exerted a significant therapeutic impact on cancer cachexia-associated SMF, potentially through the upregulation of DTX3L.

Reclaiming Selenium from Water Using Aluminum-Modified Biochar: Adsorption Behaviors, Mechanisms, and Effects on Growth of Wheat Seedlings.

Although selenium is an essential nutrient, its contamination in water poses serious risks to human health and ecosystems. In this study, aluminum-modified bamboo biochar (Al-BC) was developed to reclaim Se(VI) from water. Compared to pristine biochar (BC), Al-BC had a larger specific surface area (176 m2/g) and pore volume (0.180 cm³/g). The modification, achieved by loading AlOOH and Al2O3 particles onto the surface, enabled Al-BC to achieve a maximum adsorption capacity of 37.6 mg/g for Se(VI) within 2 hours and remove 99.6% of Se(VI) across a pH range of 3-10. The main adsorption mechanism of Se(VI) involved electrostatic attraction, forming outer-sphere complexes between Se(VI) and AlOOH sites on the biochar. The bioavailability of Se sorbed on the spent biochar (Al-BC-Se) was thus evaluated. It was discovered that Al-BC-Se successfully released Se(VI), which impacted the growth of wheat seedlings. The Se content reached 134 µg/g dry weight (DW) in wheat shoots and 638 µg/g DW in roots, significantly exceeding normal selenium content (<40 µg/g DW). By successfully applying the modified biochar to capture selenium from water through adsorption and then reusing it as an essential nutrient in soil, this study suggests the promising feasibility of the "removal-collection-reuse" approach for the circular economy of selenium in wastewater.

In situ formed reactive oxygen species-responsive dipyridamole prodrug hydrogel: Spatiotemporal drug delivery for chemoimmunotherapy.

In the realm of combined cancer immunotherapy, the strategic combination of therapeutics targeting both cancer cells and macrophages holds immense potential. However, the major challenges remain on how to achieve facile spatiotemporal delivery of these therapies, allowing ease of manipulation and ensuring differential drug release for enhanced synergistic therapeutic effects. In the present study, we introduced a tumor microenvironment (TME)-adapted hydrogel with the phenylboronic acid-modified dipyridamole prodrug (DIPP) as a crosslinker. This prodrug hydrogel scaffold, 3BP@DIPPGel, could be formed in situ by a simple mixture of DIPP and poly(vinyl alcohol) (PVA), and loaded with a high ratio of 3-bromopyruvic acid (3BP). The 3BP@DIPPGel enables spatiotemporal localized delivery of dipyridamole (DIP) and 3BP with distinct release kinetics that effectively reshape the immunosuppressive TME. Upon reactive oxygen species (ROS) stimulation, 3BP@DIPPGel preferentially released 3BP, inducing tumor-specific pyroptosis via the ROS/BAX/caspase-3/GSDME signaling pathway and decreasing the secretion of chemokines such as CCL8 to counteract macrophage recruitment. Subsequently, the crosslinked DIP is released, triggering the tumor-associated macrophages (TAMs) polarization towards the immunostimulatory M1 phenotype via the CCR2/JAK2/STAT3 cascade signaling pathway. This dual action from 3BP@DIPPGel leads to the restoration of tumor cell immunogenicity with high efficacy and activation of immune cells. Furthermore, the 3BP@DIPPGel-based chemoimmunotherapy upregulates the expression of sialic-acid-binding Ig-like lectin 10 and hence sensitizing tumors to anti-CD24 therapy in the tumor-bearing mice. Therefore, this strategy can have significant potential in the prevention of tumor metastases and recurrence. To the best of our understanding, this study represents a pioneering showcase of tumor pyroptosis, induced by glycolytic inhibitors, which can be effectively coordinated with DIP-mediated TAM polarization for immune activation, offering a new paradigm for differentially sustained drug delivery to foster cancer immunotherapy.

Correction: Jabbar et al. Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images. Brain Sci. 2022, 12, 535.

In the original publication [...].

Development and validation of a diagnostic nomogram for frailty in cancer patients.

BACKGROUND: The presence of frailty decreases the overall survival of cancer patients. An accurate and operational diagnostic method is needed to help clinicians choose the most appropriate treatment to improve patient outcomes. METHODS: Data were collected from 10 649 cancer patients who were prospectively enrolled in the Investigation on Nutritional Status and its Clinical Outcomes of Common Cancers (INSCOC) project in China from July 2013 to August 2022. The training cohort and validation cohort were randomly divided at a ratio of 7:3. The multivariable logistic regression analysis, multivariate Cox regression analyses, and the least absolute shrinkage and selection operator (LASSO) method were used to develop the nomogram. The concordance index and calibration curve were used to assess the diagnostic utility of the nomogram model. RESULTS: The 10 risk factors associated with frailty in cancer patients were age, AJCC stage, liver cancer, hemoglobin, radiotherapy, surgery, hand grip strength (HGS), calf circumference (CC), PG-SGA score and QOL from the QLQ-C30. The diagnostic nomogram model achieved a good C index of 0.847 (95% CI, 0.832-0.862, P < 0.001) in the training cohort and 0.853 (95% CI, 0.83-0.876, P < 0.001) in the validation cohort. The prediction nomogram showed 1-, 3-, and 5-year mortality C indices in the training cohort of 0.708 (95% CI, 0.686-0.731), 0.655 (95% CI, 0.627-0.683), and 0.623 (95% CI, 0.568-0.678). The 1-, 3-, and 5-year C indices in the validation cohort were similarly 0.743 (95% CI, 0.711-0.777), 0.680 (95% CI, 0.639-0.722), and 0.629 (95% CI, 0.558-0.700). In addition, the calibration curves and decision curve analysis (DCA) were well-fitted for both the diagnostic model and prediction model. CONCLUSIONS: The nomogram model provides an accurate method to diagnose frailty in cancer patients. Using this model could lead to the selection of more appropriate therapy and a better prognosis for cancer patients.

The combination of handgrip strength and CONUT predicts overall survival in patients with gastrointestinal cancer: A multicenter cohort study.

BACKGROUND: The controlled nutritional status score (CONUT) and handgrip strength (HGS) were both predictive indexes for the prognosis of cancers. However, the combination of CONUT and HGS for predicting the prognosis of gastrointestinal cancer had not been developed. This study aimed to explore the combination of CONUT and HGS as the potential predictive prognosis in patients with gastric and colorectal cancer. METHODS: A cohort study was conducted with gastric and colorectal cancer patients in multicenter in China. Based on the optimal HGS cutoff value for different sex, the HGS cutoff value was determined. The patients were divided into high and low HGS groups based on their HGS scores. A CONUT score of 4 or less was defined as a low CONUT, whereas scores higher than 4 were defined as high CONUT. The Kaplan-Meier method was used to create survival curves, and the log-rank test was used to compare time-event relationships between groups. A Cox proportional hazard regression model was used to determine independent risk factors for overall survival (OS). RESULTS: A total 2177 gastric and colorectal patients were enrolled in this study, in which 1391 (63.9%) were men (mean [SD] age, 66.11 [11.60] years). Multivariate analysis revealed that patients with high HGS had a lower risk of death than those with low HGS (hazard ratio [HR],0.87; 95% confidence interval [CI], 0.753-1.006, P = 0.06), while high CONUT had a higher risk of death than those with low CONUT (HR, 1.476; 95% CI, 1.227-1.777, P < 0.001). Patients with both low HGS and high CONUT had 1.712 fold increased risk of death (HR, 1.712; 95% CI, 1.364-2.15, P < 0.001). Moreover, cancer type and sex were stratified and found that patients with high CONUT and low HGS had lower survival rate than those with low CONUT and high HGS in both gastric or colorectal cancer, and both male and female. CONCLUSION: A combination of low HGS and high CONUT was associated with poor prognosis in patients with gastrointestinal cancer, which could probably predict the prognosis of gastrointestinal cancer more accurate than HGS or CONUT alone.

Retrosynthesis prediction with an iterative string editing model.

Retrosynthesis is a crucial task in drug discovery and organic synthesis, where artificial intelligence (AI) is increasingly employed to expedite the process. However, existing approaches employ token-by-token decoding methods to translate target molecule strings into corresponding precursors, exhibiting unsatisfactory performance and limited diversity. As chemical reactions typically induce local molecular changes, reactants and products often overlap significantly. Inspired by this fact, we propose reframing single-step retrosynthesis prediction as a molecular string editing task, iteratively refining target molecule strings to generate precursor compounds. Our proposed approach involves a fragment-based generative editing model that uses explicit sequence editing operations. Additionally, we design an inference module with reposition sampling and sequence augmentation to enhance both prediction accuracy and diversity. Extensive experiments demonstrate that our model generates high-quality and diverse results, achieving superior performance with a promising top-1 accuracy of 60.8% on the standard benchmark dataset USPTO-50 K.

Effect of Acupuncture for Methadone Reduction : A Randomized Clinical Trial.

BACKGROUND: Methadone maintenance treatment (MMT) is effective for managing opioid use disorder, but adverse effects mean that optimal therapy occurs with the lowest dose that controls opioid craving. OBJECTIVE: To assess the efficacy of acupuncture versus sham acupuncture on methadone dose reduction. DESIGN: Multicenter, 2-group, randomized, sham-controlled trial. (Chinese Clinical Trial Registry: ChiCTR2200058123). SETTING: 6 MMT clinics in China. PARTICIPANTS: Adults aged 65 years or younger with opioid use disorder who attended clinic daily and had been using MMT for at least 6 weeks. INTERVENTION: Acupuncture or sham acupuncture 3 times a week for 8 weeks. MEASUREMENTS: The 2 primary outcomes were the proportion of participants who achieved a reduction in methadone dose of 20% or more compared with baseline and opioid craving, which was measured by the change from baseline on a 100-mm visual analogue scale (VAS). RESULTS: Of 118 eligible participants, 60 were randomly assigned to acupuncture and 58 were randomly assigned to sham acupuncture (2 did not receive acupuncture). At week 8, more patients reduced their methadone dose 20% or more with acupuncture than with sham acupuncture (37 [62%] vs. 16 [29%]; risk difference, 32% [97.5% CI, 13% to 52%]; P < 0.001). In addition, acupuncture was more effective in decreasing opioid craving than sham acupuncture with a mean difference of -11.7 mm VAS (CI, -18.7 to -4.8 mm; P < 0.001). No serious adverse events occurred. There were no notable differences between study groups when participants were asked which type of acupuncture they received. LIMITATION: Fixed acupuncture protocol limited personalization and only 12 weeks of follow-up after stopping acupuncture. CONCLUSION: Eight weeks of acupuncture were superior to sham acupuncture in reducing methadone dose and decreasing opioid craving. PRIMARY FUNDING SOURCE: National Natural Science Foundation of China.

Development and validation of an inflammatory biomarkers model to predict gastric cancer prognosis: a multi-center cohort study in China.

BACKGROUND: Inflammatory factors have increasingly become a more cost-effective prognostic indicator for gastric cancer (GC). The goal of this study was to develop a prognostic score system for gastric cancer patients based on inflammatory indicators. METHODS: Patients' baseline characteristics and anthropometric measures were used as predictors, and independently screened by multiple machine learning(ML) algorithms. We constructed risk scores to predict overall survival in the training cohort and tested risk scores in the validation. The predictors selected by the model were used in multivariate Cox regression analysis and developed a nomogram to predict the individual survival of GC patients. RESULTS: A 13-variable adaptive boost machine (ADA) model mainly comprising tumor stage and inflammation indices was selected in a wide variety of machine learning models. The ADA model performed well in predicting survival in the validation set (AUC = 0.751; 95% CI: 0.698, 0.803). Patients in the study were split into two sets - "high-risk" and "low-risk" based on 0.42, the cut-off value of the risk score. We plotted the survival curves using Kaplan-Meier analysis. CONCLUSION: The proposed model performed well in predicting the prognosis of GC patients and could help clinicians apply management strategies for better prognostic outcomes for patients.

Three-year field study on the temporal response of soil microbial communities and functions to PFOA exposure.

Contamination of per- and polyfluoroalkyl substances (PFAS) poses a significant threat to soil ecosystem health, yet there remains a lack of understanding regarding the responses of soil microbial communities to prolonged PFAS exposure in field conditions. This study involved a three-year field investigation to track changes in microbial communities and functions in soil subjected to the contamination of a primary PFAS, perfluorooctanoic acid (PFOA). Results showed that PFOA exposure altered soil bacterial and fungal communities in terms of diversity, composition, and structure. Notably, certain bacterial communities with a delayed reaction to PFOA contamination showed the most significant response after one year of exposure. Fungal communities were sensitive to PFOA in soil, exhibiting significant responses within just four months of exposure. After two years, the impact of PFOA on both bacterial and fungal communities was lessened, likely due to the long-term adaptation of microbial communities to PFOA. Moreover, PFOA exposure notably inhibited alkaline phosphatase activity and reduced certain phosphorus cycling-related functional genes after three years of exposure, suggesting potential disruptions in soil fertility. These new insights advance our understanding of the long-term effects of PFOA on soil microbial communities and functions at a field scale.

Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

BACKGROUND: Body weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. METHODS: This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight-related indicators and compared their prognostic performance using Harrell's C-index, integrated discrimination improvement, continuous net reclassification improvement and time-dependent C-index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan-Meier analysis and multivariable-adjusted Cox regression models. RESULTS: The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (PRWC < 0.001, Pnon-linear < 0.001). Univariate survival analysis showed that the peridiagnosis RWC groups could represent distinct mortality risk stratifications (P < 0.001). Multivariable survival analysis showed that, compared with the maintenance group (weight change < 5%), the significant (gain >10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5-10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5-10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. CONCLUSIONS: The prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Complete biodegradation of tetrabromobisphenol A through sequential anaerobic reductive dehalogenation and aerobic oxidation.

Tetrabromobisphenol A (TBBPA), a common brominated flame retardant and a notorious pollutant in anaerobic environments, resists aerobic degradation but can undergo reductive dehalogenation to produce bisphenol A (BPA), an endocrine disruptor. Conversely, BPA is resistant to anaerobic biodegradation but susceptible to aerobic degradation. Microbial degradation of TBBPA via anoxic/oxic processes is scarcely documented. We established an anaerobic microcosm for TBBPA dehalogenation to BPA facilitated by humin. Dehalobacter species increased with a growth yield of 1.5 × 108 cells per µmol Br- released, suggesting their role in TBBPA dehalogenation. We innovatively achieved complete and sustainable biodegradation of TBBPA in sand/soil columns columns, synergizing TBBPA reductive dehalogenation by anaerobic functional microbiota and BPA aerobic oxidation by Sphingomonas sp. strain TTNP3. Over 42 days, 95.11 % of the injected TBBPA in three batches was debrominated to BPA. Following injection of strain TTNP3 cells, 85.57 % of BPA was aerobically degraded. Aerobic BPA degradation column experiments also indicated that aeration and cell colonization significantly increased degradation rates. This treatment strategy provides valuable technical insights for complete TBBPA biodegradation and analogous contaminants.

The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information.

BACKGROUND & AIMS: The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weight loss information, and bias or even failure to recall patients' historical weight can cause misestimates of malnutrition. We aimed to compare the suitability of several screening tools in GLIM diagnosis, and establish machine learning (ML) models to predict malnutrition in CRC patients without weight loss information. METHODS: This multicenter cohort study enrolled 4487 CRC patients. The capability of GLIM diagnoses combined with four screening tools in predicting survival probability was compared by Kaplan-Meier curves, and the most accurate one was selected as the malnutrition reference standard. Participants were randomly assigned to a training cohort (n = 3365) and a validation cohort (n = 1122). Several ML approaches were adopted to establish models for predicting malnutrition without weight loss data. We estimated feature importance and reserved the top 30% of variables for retraining simplified models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess and compare model performance. RESULTS: NRS-2002 was the most suitable screening tool for GLIM diagnosis in CRC patients, with the highest hazard ratio (1.59; 95% CI, 1.43-1.77). A total of 2076 (46.3%) patients were malnourished diagnosed by GLIM combined with NRS-2002. The simplified random forest (RF) model outperformed other models with an AUC of 0.830 (95% CI, 0.805-0.854), and accuracy, sensitivity and specificity were 0.775, 0.835 and 0.742, respectively. We deployed an online application based on the simplified RF model to accurately estimate malnutrition probability in CRC patients without weight loss information (https://zzuwtt1998.shinyapps.io/dynnomapp/). CONCLUSIONS: Nutrition Risk Screening 2002 was the optimal initial nutritional risk screening tool in the GLIM process. The RF model outperformed other models, and an online prediction tool was developed to properly identify patients at high risk of malnutrition.

Value of the modified Patient-Generated Subjective Global Assessment in indicating the need for nutrition intervention and predicting overall survival in patients with malignant tumors in at least two organs.

BACKGROUND: Although the Patient-Generated Subjective Global Assessment (PG-SGA) is a reference standard used to assess a patient's nutrition status, it is cumbersome to administer. The aim of the present study was to estimate the value of a simpler and easier-to-use modified PG-SGA (mPG-SGA) to evaluate the nutrition status and need for intervention in patients with malignant tumors present in at least two organs. METHODS: A total of 591 patients (343 male and 248 female) were included from the INSCOC study. A Pearson correlation analysis was conducted to assess the correlation between the mPG-SGA and nutrition-related factors, with the optimal cut-off defined by a receiver operating characteristic curve (ROC). The consistency between the mPG-SGA and PG-SGA was compared in a concordance analysis. A survival analysis was used to determine the effects of nutritional intervention among different nutrition status groups. Univariable and multivariable Cox analyses were applied to evaluate the association of the mPG-SGA with the all-cause mortality. RESULTS: The mPG-SGA showed a negative association with nutrition-related factors. Individuals with an mPG-SGA ≥ 5 (rounded from 4.5) were considered to need nutritional intervention. Among the malnourished patients (mPG-SGA ≥ 5), the overall survival (OS) of those who received nutrition intervention was significantly higher than that of patients who did not. However, the OS was not significantly different in the better-nourished patients (mPG-SGA < 5). CONCLUSION: Our findings support that the mPG-SGA is a feasible tool that can be used to guide nutritional interventions and predict the survival of patients with malignant tumors affecting at least two organs.

Integrated neutrophil-to-lymphocyte ratio and handgrip strength better predict survival in patients with cancer cachexia.

OBJECTIVES: Systemic inflammation and skeletal muscle strength play crucial roles in the development and progression of cancer cachexia. In this study we aimed to evaluate the combined prognostic value of neutrophil-to-lymphocyte ratio (NLR) and handgrip strength (HGS) for survival in patients with cancer cachexia. METHODS: This multicenter cohort study involved 1826 patients with cancer cachexia. The NLR-HGS (NH) index was defined as the ratio of neutrophil-to-lymphocyte ratio to handgrip strength. Harrell's C index and receiver operating characteristic (ROC) curve analysis were used to assess the prognosis of NH. Kaplan-Meier analysis and Cox regression models were used to evaluate the association of NH with all-cause mortality. RESULTS: Based on the optimal stratification, 380 women (NH > 0.14) and 249 men (NH > 0.19) were classified as having high NH. NH has shown greater predictive value compared to other indicators in predicting the survival of patients with cancer cachexia according to the 1-, 3-, and 5-y ROC analysis and Harrell's C index calculation. Multivariate survival analysis showed that higher NH was independently associated with an increased risk of death (hazard ratio = 1.654, 95% confidence interval = 1.389-1.969). CONCLUSION: This study demonstrates that the NH index, in combination with NLR and HGS, is an effective predictor of the prognosis of patients with cancer cachexia. It can offer effective prognosis stratification and guidance for their treatment.

A rapid PCR-free next-generation sequencing method for comprehensive diagnosis of chromosome disease syndromes in prenatal samples.

The aim of this study is to investigate the application performance of rapid copy number variation sequencing (rCNV-seq) technology for the detection of chromosomal abnormalities during prenatal diagnosis. Samples were collected from 424 pregnant women who were at high-risk for noninvasive prenatal screening in Kunming Maternal and Child Care Hospital from January 2018 to May 2022. rCNV-seq technique was used to detect fetal chromosome abnormalities and compare the results with that of chromosomal karyotype analysis. The Result showed that 330 (77.83%, 330/424) cases indicated chromosomal abnormalities among 424 high-risk pregnant women who underwent rCNV-seq. Moreover, 94 (22.17%, 94/424) cases were discovered to have copy number variations. Among the 330 fetuses with chromosomal abnormalities, common autosomal aneuploidy was observed in 203 cases (47.87%, 203/424) and sex chromosome aneuploidy was observed in 91 cases (21.46%, 91/424). Moreover, the abnormalities in multiple chromosomes were discovered in 33 cases (7.78%, 33/424), and the rare autosomal aneuploidy was observed in 3 cases (0.71%, 3/424). There were 63 fetuses (14.86%, 63/424) with pathogenic CNVs among the 94 fetuses with variable copy numbers. Of the 245 pregnant women who voluntarily selected G-band karyotyping, 1 fetus with copy number variation had normal karyotype results, and the remaining women were consistent with rCNV-seq. Our study revealed that rCNV-seq has higher accuracy in detecting common trisomy and can also detect chromosomal microdeletions or microduplications that cannot be detected by G-banding karyotype analysis. There is no effective treatment for chromosomal diseases, so it is particularly important to prevent chromosomal diseases through genetic counseling and prenatal diagnosis of chromosomal diseases.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study.

OBJECTIVES: The concept of possible sarcopenia (PS) was recently introduced to enable timely intervention in settings without the technologies required to make a full diagnosis of sarcopenia. This study aimed to investigate the association between PS and all-cause mortality in patients with solid cancer. DESIGN: Retrospective observational study. SETTING AND PARTICIPANTS: 13,736 patients with 16 types of solid cancer who were ≥18 years old. MEASUREMENTS: The presence of both a low calf circumference (men <34 cm or women <33 cm) and low handgrip strength (men <28 kg or women <18 kg) was considered to indicate PS. Harrell's C-index was used to assess prognostic value and the association of PS with mortality was estimated by calculating multivariable-adjusted hazard ratios (HRs). RESULTS: The study enrolled 7207 men and 6529 women (median age = 57.8 years). During a median follow-up of 43 months, 3150 deaths occurred. PS showed higher Harrell's C-index (0.549, 95%CI = [0.541, 0.557]) than the low calf circumference (0.541, 95%CI = [0.531, 0.551], P = 0.037) or low handgrip strength (0.542, 95%CI = [0.532, 0.552], P = 0.026). PS was associated with increased mortality risk in both univariate (HR = 1.587, 95%CI = [1.476, 1.708]) and multivariable-adjusted models (HR = 1.190, 95%CI = [1.094, 1.293]). Sensitivity analyses showed that the association of PS with mortality was robust in different covariate subgroups, which also held after excluding those patients who died within the first 3 months (HR = 1.162, 95%CI = [1.060, 1.273]), 6 months (HR = 1.150, 95%CI = [1.039, 1.274]) and 12 months (HR = 1.139, 95%CI = [1.002, 1.296]) after enrollment. CONCLUSION: PS could independently and robustly predict all-cause mortality in patients with solid cancer. These findings imply the importance of including PS assessment in routine cancer care to provide significant prognostic information to help mitigate sarcopenia-related premature deaths.

Degradation and mechanism of PFOA by peroxymonosulfate activated by nitrogen-doped carbon foam-anchored nZVI in aqueous solutions.

Perfluorooctanoic acid (PFOA) is an emerging pollutant that is non-biodegradable and presents severe environmental and human health risks. In this study, we present an effective and mild approach for PFOA degradation that involves the use of nitrogen-doped carbon foam anchored with nanoscale zero-valent iron (nZVI@NCF) to activate low concentration peroxymonosulfate (PMS) for the treatment. The nZVI@NCF/PMS system efficiently removed 84.4% of PFOA (2.4 µM). The active sites of nZVI@NCF including Fe0 (110) and graphitic nitrogen played crucial roles in the degradation. Electrochemical analyses and density functional theory calculations revealed that nZVI@NCF acted as an electronic donor, transferring electrons to both PMS and PFOA during the reaction. By further analyzing the electron paramagnetic resonance and byproducts, it was determined that electron transfer and singlet oxygen were responsible for PFOA degradation. Three degradation pathways involving decarboxylation and surface reduction of PFOA in the nZVI@NCF/PMS system were determined. Finding from this study indicate that nZVI@NCF/PMS systems are effective in degrading PFOA and thus present a promising persulfate-advanced oxidation process technology for PFAS treatment.