Octogenarians unable to return home by postoperative-day 30.

BACKGROUND: For older adults undergoing surgery, returning home is instrumental for functional independence. We quantified octogenarians unable to return home by POD-30, assessed geriatric factors in a predictive model, and identified risk factors to inform decision-making and quality improvement. METHODS: This retrospective cohort study examined patients ≥80 years old from the ACS NSQIP Geriatric Surgery Pilot, using sequential logistic regression modelling. The primary outcome was non-home living location at POD-30. RESULTS: Of 4946 patients, 19.8 â€‹% lived in non-home facilities at POD-30. Increased odds of non-home living location were seen in patients with preoperative fall history (OR 2.92, 95%CI 2.06-4.14) and new postoperative pressure ulcer (OR 2.66, 95%CI 1.50-4.71) Other significant geriatric-specific risk factors included mobility aid use, surrogate-signed consent, and postoperative delirium, with odds ratios ranging from 1.42 (1.19-1.68) to 1.97 (1.53-2.53). CONCLUSIONS: These geriatric-specific risk factors highlight the importance of preoperative vulnerability screening and intervention to inform surgical decision-making.

Within-hospital Temporal Clustering of Postoperative Complications and Implications for Safety Monitoring and Benchmarking Using ACS-NSQIP Data.

Objective: To determine the extent to which within-hospital temporal clustering of postoperative complications is observed in the American College of Surgeons, National Surgical Quality Improvement Program (ACS-NSQIP). Background: ACS-NSQIP relies on periodic and on-demand reports for quality benchmarking. However, if rapid increases in postoperative complication rates (clusters) are common, other reporting methods might be valuable additions to the program. This article focuses on estimating the incidence of within-hospital temporal clusters. Methods: ACS-NSQIP data from 1,547,440 patients, in 425 hospitals, over a 2-year period was examined. Hospital-specific Cox proportional hazards regression was used to estimate the incidence of mortality, morbidity, and surgical site infection (SSI) over a 30-day postoperative period, with risk adjustment for patient and procedure and with additional adjustments for linear trend, day-of-week, and season. Clusters were identified using scan statistics, and cluster counts were compared, using unpaired and paired t tests, for different levels of adjustment and when randomization of cases across time eliminated all temporal influences. Results: Temporal clusters were rarely observed. When clustering was adjusted only for patient and procedure risk, an annual average of 0.31, 0.85, and 0.51 clusters were observed per hospital for mortality, morbidity, and SSI, respectively. The number of clusters dropped after adjustment for linear trend, day-of-week, and season (0.31-0.24; P = 0.012; 0.85-0.80; P = 0.034; and 0.51-0.36; P < 0.001; using paired t tests) for mortality, morbidity, and SSI, respectively. There was 1 significant difference in the number of clusters when comparing data with all adjustments and after data were randomized (0.24 and 0.25 for mortality; P = 0.853; 0.80 and 0.82 for morbidity; P = 0.529; and 0.36 and 0.46 [randomized data had more clusters] for SSI; P = 0.001; using paired t tests) for mortality, morbidity, and SSI, respectively. Conclusions: Temporal clusters of postoperative complications were rarely observed in ACS-NSQIP data. The described methodology may be useful in assessing clustering in other surgical arenas.

Targeting ALDOA to modulate tumorigenesis and energy metabolism in retinoblastoma.

This study aims to elucidate the pivotal role of aldolase A (ALDOA) in retinoblastoma (RB) and evaluate the potential of the ALDOA inhibitor itaconate in impeding RB progression. Utilizing single-cell RNA sequencing, ALDOA consistently exhibits overexpression across diverse cell types, particularly in cone precursor cells, retinoma-like cells, and retinoblastoma-like cells. This heightened expression is validated in RB tissues and cell lines. ALDOA knockdown significantly diminishes RB cell viability, impedes colony formation, and induces notable metabolic alterations. RNA-seq analysis identifies SUSD2, ARHGAP27, and CLK2 as downstream genes associated with ALDOA. The application of itaconate demonstrates efficacy in inhibiting RB cell proliferation, validated through in vitro and in vivo models. This study emphasizes ALDOA as a promising target for innovative RB therapies, with potential implications for altering tumor energy metabolism.

Deciphering metabolic heterogeneity in retinoblastoma unravels the role of monocarboxylate transporter 1 in tumor progression.

BACKGROUND: Tumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited. METHODS: The metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion. RESULTS: Distinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications. CONCLUSIONS: This study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.

Identifying Population-Level and Within-Hospital Disparities in Surgical Care.

BACKGROUND: The lack of consensus on equity measurement and its incorporation into quality-assessment programs at the hospital and system levels may be a barrier to addressing disparities in surgical care. This study aimed to identify population-level and within-hospital differences in the quality of surgical care provision. STUDY DESIGN: The analysis included 657 NSQIP participating hospitals with more than 4 million patients (2014 to 2018). Multilevel random slope, random intercept modeling was used to examine for population-level and in-hospital disparities. Disparities in surgical care by Area Deprivation Index (ADI), race, and ethnicity were analyzed for 5 measures: all-case inpatient mortality, all-case urgent readmission, all-case postoperative surgical site infection, colectomy mortality, and spine surgery complications. RESULTS: Population-level disparities were identified across all measures by ADI, 2 measures for Black race (all-case readmissions and spine surgery complications), and none for Hispanic ethnicity. Disparities remained significant in the adjusted models. Before risk adjustment, in all measures examined, within-hospital disparities were detected in: 25.8% to 99.8% of hospitals for ADI, 0% to 6.1% of hospitals for Black race, and 0% to 0.8% of hospitals for Hispanic ethnicity. After risk adjustment, in all measures examined, less than 1.1% of hospitals demonstrated disparities by ADI, race, or ethnicity. CONCLUSIONS: After risk adjustment, very few hospitals demonstrated significant disparities in care. Disparities were more frequently detected by ADI than by race and ethnicity. The lack of substantial in-hospital disparities may be due to the use of postoperative metrics, small sample sizes, the risk adjustment methodology, and healthcare segregation. Further work should examine surgical access and healthcare segregation.

Magnetic Phase Transition-Induced Modulation of Ferroelectric Properties in Hexagonal RFeO3 (R = Tb and Ho).

Hexagonal rare-earth iron oxides (h-RFeO3) exhibit spontaneous magnetization and room-temperature ferroelectricity simultaneously. However, achieving a large magnetoelectric coupling necessitates further exploration. Herein, we report the impact of the magnetic phase transition on the ferroelectric properties of epitaxial h-RFeO3 (R = Tb and Ho) films prepared by pulsed laser deposition. The metastable h-RFeO3 phase is successfully stabilized with high crystallinity and low leakage current due to the ITO buffer layer, making it possible to investigate the ferroelectric properties. The h-TbFeO3 film exhibits a magnetic-field-induced transition from antiferromagnetic (AFM) to weak ferromagnetic (wFM) phases below 30 K, while also exhibiting ferroelectricity at 300 K. The dielectric constants change with the magnetic phase transition, demonstrating hysteresis in the magnetocapacitance. In contrast, the h-HoFeO3 film exhibits antiferroelectric-like behavior and an AFM-wFM phase transition. Notably, the h-HoFeO3 film shows a rapid increase in the remnant polarization during the AFM-wFM phase transition accompanied by an increase in the ferroelectric component. Considering the strong connection between the antiferroelectric behavior in the h-RFeO3 system and the ferroelectric domain wall motion, this considerable modification of ferroelectric properties during the magnetic phase transition is probably due to the faster movement of the ferroelectric domain walls in the wFM phase induced by the clamping effect. Our findings indicate the effectiveness of magnetic phase transitions in enhancing the magnetoelectric coupling, particularly when utilizing domain wall clamping properties.

Heterogeneous Expression Patterns of the Minichromosome Maintenance Complex Members in Retinoblastoma Unveil Its Clinical Significance.

Purpose: To explore the expression patterns and clinical significance of minichromosome maintenance (MCM) complex members in retinoblastoma (RB). Methods: Single-cell RNA sequencing datasets from five normal retina, six intraocular, and five extraocular RB samples were integrated to characterize the expression patterns of MCM complex members at the single-cell level. Western blot and quantitative PCR were used to detect the expression of MCM complex members in RB cell lines. Immunohistochemistry was conducted to validate the expression of MCM complex members in RB patient samples and a RB mouse model. Results: The expression of MCM2-7 is increased in RB tissue, with MCM2/3/7 showing particularly higher levels in extraocular RB. MCM3/7 are abundantly detected in cell types associated with oncogenesis. Both mRNA and protein levels of MCM3/4/6/7 are increased in RB cell lines. Immunohistochemistry further confirmed the elevated expression of MCM3 in extraocular RB, with MCM6 being the most abundantly expressed MCM in RB. Conclusions: The distinct MCM expression patterns across various RB cell types suggest diverse functional roles, offering valuable insights for targeted therapeutic strategies. The upregulation of MCM3, MCM4, MCM6, and MCM7 in RB, with a specific emphasis on MCM6 as a notable marker, highlights their potential significance.

Single-cell transcriptomics enable the characterization of local extension in retinoblastoma.

Retinoblastoma (RB) is the most prevalent ocular tumor of childhood, and its extraocular invasion significantly increases the risk of metastasis. Nevertheless, a single-cell characterization of RB local extension has been lacking. Here, we perform single-cell RNA sequencing on four RB samples (two from intraocular and two from extraocular RB patients), and integrate public datasets of five normal retina samples, four intraocular samples, and three extraocular RB samples to characterize RB local extension at the single-cell level. A total of 128,454 qualified cells are obtained in nine major cell types. Copy number variation inference reveals chromosome 6p amplification in cells derived from extraocular RB samples. In cellular heterogeneity analysis, we identified 10, 8, and 7 cell subpopulations in cone precursor like cells, retinoma like cells, and MKI67+ photoreceptorness decreased (MKI67+ PhrD) cells, respectively. A high expression level of SOX4 was detected in cells from extraocular samples, especially in MKI67+ PhrD cells, which was verified in additional clinical RB samples. These results suggest that SOX4 might drive RB local extension. Our study presents a single-cell transcriptomic landscape of intraocular and extraocular RB samples, improving our understanding of RB local extension at the single-cell resolution and providing potential therapeutic targets for RB patients.

National Multi-Institutional Validation of a Surgical Transfusion Risk Prediction Model.

BACKGROUND: Accurate estimation of surgical transfusion risk is important for many aspects of surgical planning, yet few methods for estimating are available for estimating such risk. There is a need for reliable validated methods for transfusion risk stratification to support effective perioperative planning and resource stewardship. STUDY DESIGN: This study was conducted using the American College of Surgeons NSQIP datafile from 2019. S-PATH performance was evaluated at each contributing hospital, with and without hospital-specific model tuning. Linear regression was used to assess the relationship between hospital characteristics and area under the receiver operating characteristic (AUROC) curve. RESULTS: A total of 1,000,927 surgical cases from 414 hospitals were evaluated. Aggregate AUROC was 0.910 (95% CI 0.904 to 0.916) without model tuning and 0.925 (95% CI 0.919 to 0.931) with model tuning. AUROC varied across individual hospitals (median 0.900, interquartile range 0.849 to 0.944), but no statistically significant relationships were found between hospital-level characteristics studied and model AUROC. CONCLUSIONS: S-PATH demonstrated excellent discriminative performance, although there was variation across hospitals that was not well-explained by hospital-level characteristics. These results highlight the S-PATH's viability as a generalizable surgical transfusion risk prediction tool.

Surgical Outcomes of Standardized Endoscopical Deep Medial Orbital Decompression in Dysthyroid Optic Neuropathy.

INTRODUCTION: The aim of the study was to standardize the endoscopic deep medial orbital decompression surgery for better relief of optic nerve compression in dysthyroid optic neuropathy (DON). METHODS: A total of 128 eyes from patients received the standardized endoscopic deep medial orbital decompression surgery were recruited in this study. The efficacy of the procedure was assessed at a 1-month follow-up by the best-corrected visual acuity (VA), visual field (VF), and visual evoked potential (VEP). Clinical data were collected to explore the factors that affected visual recovery. Oxygen saturation of retinal blood vessels, retinal thickness, and vessel density were measured to demonstrate the potential recovery mechanisms. RESULTS: After surgery, the ratio of extraocular muscle volume in the orbital apex to orbital apex volume significantly decreased from 44.32 ± 22.31% to 36.82 ± 12.02% (p < 0.001). 96.87% of eyes' final VA improved; average VA improved from 0.93 ± 0.73 to 0.50 ± 0.60 at 1 week (p < 0.001) and 0.40 ± 0.53 at 1 month (p < 0.001). Postoperatively, VF and VEP also improved, the oxygen saturation of retinal arteries increased, and the retinal thickness was reduced. Preoperative VA, visual impairment duration, and clinical activity score evaluation were associated with visual recovery. CONCLUSION: In this study, we standardized the endoscopic deep medial orbital decompression, of which key point was to relieve pressure in the orbital apex and achieved satisfactory visual recovery in DON patients.

The Accuracy of the NSQIP Universal Surgical Risk Calculator Compared to Operation-Specific Calculators.

Objective: To compare the performance of the ACS NSQIP "universal" risk calculator (N-RC) to operation-specific RCs. Background: Resources have been directed toward building operation-specific RCs because of an implicit belief that they would provide more accurate risk estimates than the N-RC. However, operation-specific calculators may not provide sufficient improvements in accuracy to justify the costs in development, maintenance, and access. Methods: For the N-RC, a cohort of 5,020,713 NSQIP patient records were randomly divided into 80% for machine learning algorithm training and 20% for validation. Operation-specific risk calculators (OS-RC) and OS-RCs with operation-specific predictors (OSP-RC) were independently developed for each of 6 operative groups (colectomy, whipple pancreatectomy, thyroidectomy, abdominal aortic aneurysm (open), hysterectomy/myomectomy, and total knee arthroplasty) and 14 outcomes using the same 80%/20% rule applied to the appropriate subsets of the 5M records. Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), and Hosmer-Lemeshow (H-L) P values, for 13 binary outcomes, and mean squared error for the length of stay outcome. Results: The N-RC was found to have greater AUROC (P = 0.002) and greater AUPRC (P < 0.001) compared to the OS-RC. No other statistically significant differences in accuracy, across the 3 risk calculator types, were found. There was an inverse relationship between the operation group sample size and magnitude of the difference in AUROC (r = -0.278; P = 0.014) and in AUPRC (r = -0.425; P < 0.001) between N-RC and OS-RC. The smaller the sample size, the greater the superiority of the N-RC. Conclusions: While operation-specific RCs might be assumed to have advantages over a universal RC, their reliance on smaller datasets may reduce their ability to accurately estimate predictor effects. In the present study, this tradeoff between operation specificity and accuracy, in estimating the effects of predictor variables, favors the N-R, though the clinical impact is likely to be negligible.

A novel multi-functional fluorescent probe for dual-channel detection of SO2 and Hg2+ and dynamic visualization of SO2 fluctuations in vivo upon mercury exposure.

Although there are many drugs used for the treatment of mercury poisoning, it is remains confused that pathological symptoms associated with Hg2+-induced oxidative stress. It is reported that SO2 can be generated as the anti-oxidant, and plays an important role in maintaining redox balance in cells. There has not yet been a study to precisely track the changes in SO2 during mercury ion poisoning. We developed a novel dual-response fluorescence probe (CY-SPH) for respective or successive determination of Hg2+ and SO2 in neutral aqueous media. The nucleophilic addition of HSO3- toward CY-SPH caused a significant fluorescence enhancement at 455 nm while the Hg2+ -triggered desulfurization of CY-SPH to the final phenolic product (CY-OH) elicited a markedly enhanced emission at 760 nm, allowing for two-color visualization of Hg2+ and SO2 with good selectivity (detection limit: 67.2 nM for Hg2+ and 34.7 nM for SO2). Moreover, CY-OH could undergo further nucleophilic addition reaction with HSO3- and resulted in a decrease in emission at 760 nm and an increase in emission at 438 nm, enabling the ratiometric determination of SO2 with better sensitivity (detection limit, 3.50 nM). Significantly, CY-SPH can monitor the endogenous SO2 fluctuations upon mercury exposure by means of confocal fluorescence imaging, which may prove valuable for deciphering the relationship between SO2 levels and the mercury induced oxidative stress. We anticipated that this research will promote to understand the functions of SO2 under the oxidative stress by Hg2+.

Integrated Transcriptome Analysis of Long Noncoding RNA and mRNA in Developing and Aging Mouse Retina.

Mice have emerged as a widely employed model for investigating various retinal diseases. However, the availability of comprehensive datasets capturing the entire developmental and aging stages of the mouse retina, particularly during the elderly period, encompassing integrated lncRNA and mRNA expression profiles, is limited. In this study, we assembled a total of 18 retina samples from mice across 6 distinct stages of development and aging (5 days, 3 weeks, 6 weeks, 10 weeks, 6 months, and 15 months) to conduct integrated lncRNA and mRNA sequencing analysis. This invaluable dataset offers a comprehensive transcriptomic resource of mRNA and lncRNA expression profiles during the natural progression of retinal development and aging. The discoveries stemming from this investigation will significantly contribute to the elucidation of the underlying molecular mechanisms associated with various retinal diseases, such as congenital retinal dysplasia and retinal degenerative diseases.

The Genetic, Pharmacogenomic, and Immune Landscapes Associated with Protein Expression across Human Cancers.

Proteomics is a powerful approach that can rapidly enhance our understanding of cancer development. Detailed characterization of the genetic, pharmacogenomic, and immune landscape in relation to protein expression in patients with cancer could provide new insights into the functional roles of proteins in cancer. By taking advantage of the genotype data from The Cancer Genome Atlas and protein expression data from The Cancer Proteome Atlas, we characterized the effects of genetic variants on protein expression across 31 cancer types and identified approximately 100,000 protein quantitative trait loci (pQTL). Among these, over 8000 pQTLs were associated with patient overall survival. Furthermore, characterization of the impact of protein expression on more than 350 imputed anticancer drug responses in patients revealed nearly 230,000 significant associations. In addition, approximately 21,000 significant associations were identified between protein expression and immune cell abundance. Finally, a user-friendly data portal, GPIP (https://hanlaboratory.com/GPIP), was developed featuring multiple modules that enable researchers to explore, visualize, and browse multidimensional data. This detailed analysis reveals the associations between the proteomic landscape and genetic variation, patient outcome, the immune microenvironment, and drug response across cancer types, providing a resource that may offer valuable clinical insights and encourage further functional investigations of proteins in cancer. SIGNIFICANCE: Comprehensive characterization of the relationship between protein expression and the genetic, pharmacogenomic, and immune landscape of tumors across cancer types provides a foundation for investigating the role of protein expression in cancer development and treatment.

An optimized TRIzol-based method for isolating RNA from adipose tissue.

High-quality RNA isolation from recalcitrant adipose tissue with high lipid content and low cell numbers is difficult. Many studies have made efforts to optimize methods for isolating RNA from adipose tissue through combinations of column-based kits and phenol-chloroform methods, or through in-house protocols. However, the considerable complexity of these protocols and the various kits/materials required hamper their wide use. Herein, we describe an optimized protocol based on TRIzol reagent, which is the most accessible ready-to-use reagent for nucleic acid and/or protein isolation in laboratories. This article provides a step-by-step protocol yielding sufficient and qualified RNA from lipid-rich specimens for downstream applications.

American College of Surgeons NSQIP Risk Calculator Accuracy Using a Machine Learning Algorithm Compared with Regression.

BACKGROUND: The American College of Surgeons NSQIP risk calculator (RC) uses regression to make predictions for fourteen 30-day surgical outcomes. While this approach provides accurate (discrimination and calibration) risk estimates, they might be improved by machine learning (ML). To investigate this possibility, accuracy for regression-based risk estimates were compared to estimates from an extreme gradient boosting (XGB)-ML algorithm. STUDY DESIGN: A cohort of 5,020,713 million NSQIP patient records was randomly divided into 80% for model construction and 20% for validation. Risk predictions using regression and XGB-ML were made for 13 RC binary 30-day surgical complications and one continuous outcome (length of stay [LOS]). For the binary outcomes, discrimination was evaluated using the area under the receiver operating characteristic curve (AUROC) and area under the precision recall curve (AUPRC), and calibration was evaluated using Hosmer-Lemeshow statistics. Mean squared error and a calibration curve analog were evaluated for the continuous LOS outcome. RESULTS: For every binary outcome, discrimination (AUROC and AUPRC) was slightly greater for XGB-ML than for regression (mean [across the outcomes] AUROC was 0.8299 vs 0.8251, and mean AUPRC was 0.1558 vs 0.1476, for XGB-ML and regression, respectively). For each outcome, miscalibration was greater (larger Hosmer-Lemeshow values) with regression; there was statistically significant miscalibration for all regression-based estimates, but only for 4 of 13 when XGB-ML was used. For LOS, mean squared error was lower for XGB-ML. CONCLUSIONS: XGB-ML provided more accurate risk estimates than regression in terms of discrimination and calibration. Differences in calibration between regression and XGB-ML were of substantial magnitude and support transitioning the RC to XGB-ML.

Multi-omics characterization of autophagy-related molecular features for therapeutic targeting of autophagy.

Autophagy is a major contributor to anti-cancer therapy resistance. Many efforts have been made to understand and overcome autophagy-mediated therapy resistance, but these efforts have been unsuccessful in clinical applications. In this study, we establish an autophagy signature to estimate tumor autophagy status. We then classify approximately 10,000 tumor samples across 33 cancer types from The Cancer Genome Atlas into autophagy score-high and autophagy score-low groups. We characterize the associations between multi-dimensional molecular features and tumor autophagy, and further analyse the effects of autophagy status on drug response. In contrast to the conventional view that the induction of autophagy serves as a key resistance mechanism during cancer therapy, our analysis reveals that autophagy induction may also sensitize cancer cells to anti-cancer drugs. We further experimentally validate this phenomenon for several anti-cancer drugs in vitro and in vivo, and reveal that autophagy inducers potentially sensitizes tumor cells to etoposide through downregulating the expression level of DDIT4. Our study provides a comprehensive landscape of molecular alterations associated with tumor autophagy and highlights an opportunity to leverage multi-omics analysis to utilize multiple drug sensitivity induced by autophagy.

NSQIP Quality Benchmarking and Evaluation of Potential Bias Associated with Higher- or Lower-Risk Operation Case Mix.

BACKGROUND: To ensure validity and acceptance of NSQIP risk-adjusted benchmarking, it is important that adjustments adequately control for hospitals that vary in their proportions of lower- or higher-risk operations (combined risk for procedure and patient). This issue was addressed in separate empirical and simulation studies. STUDY DESIGN: For the empirical study, potential miscalibration bias favoring hospitals that do lower-risk operations or disfavoring hospitals that do higher-risk operations was evaluated for 14 modeled outcomes using NSQIP data. A determination was also made as to whether there was a relationship between mean hospital operation risk and benchmarking results (log odds ratio). In the simulation study of the same 14 outcomes, hospital benchmarked performance was evaluated when sampled cases were reconstituted to include either a larger proportion of lower-risk operations or a larger proportion of higher-risk operations. RESULTS: Miscalibration favoring either lower- or higher-risk operations was absent, as were important associations between operative risk and hospital log odds ratios (most model R 2 less than 0.01). In the simulation, there were no substantial changes in log odds ratios when greater percentages of either lower- or higher-risk operations were included in a hospital's sample (nonsignificant p values and effect sizes less than 0.1). CONCLUSIONS: These results should enhance NSQIP participants' confidence in the adequacy of NSQIP patient and procedure risk-adjustment methods. NSQIP participants may rely on benchmarking findings, and implement quality improvement efforts based on them, without concern that they are biased by a preponderance of lower or higher risk operations.

Real-time imaging of intracellular cysteine level fluctuations during Cu2+ or H2O2 induced redox imbalance using a turn-on fluorescence sensor.

Redox balance is a necessary guarantee to maintain the normal physiological activities of organisms. Cysteine (Cys), a critical biological thiol, has the effect of maintaining redox balance in the body. The concentration of intracellular Cys is abnormal under redox imbalance, thereby resulting in multiple diseases. Additionally, studies have revealed that Cu2+ can stimulate the body to produce excess reactive oxygen species (ROS, similar to H2O2), and the generated ROS will consume reducing substances (such as Cys) in the body, leading to redox imbalance. Thus, finding a simple and effective method to monitor Cys under redox imbalance is pressing. Here, a turn on probe (DDNO) was proposed by connecting SBD-Cl to a red dye (HDM). The probe can specifically recognize Cys with rapid response (180 s) and low detection limit (0.61 µM) through substitution-rearrangement reaction between sulfhydryl and chlorine atom. Bioimaging experiments indicated that the probe has good biocompatibility and cell membrane permeability, which can be applied to monitor the fluctuation of Cys levels in live cells and zebrafish under the redox imbalance induced by Cu2+ or H2O2.

Association of antibiotic treatment with immune-related adverse events in patients with cancer receiving immunotherapy.

BACKGROUND: To determine whether antibiotic treatment is a risk factor for immune-related adverse events (irAEs) across different patients with cancer receiving anti-PD-1/PD-L1 therapies. METHODS: The retrospective analysis includes clinical information from 767 patients with cancer treated at Hunan Cancer Hospital from 2017 to 2020. The pharmacovigilance data analysis includes individual cases of 38,705 safety reports from the US Food and Drug Administration Adverse Event Reporting System (FAERS) from 2014 to 2020, and 25,122 cases of safety reports from the World Health Organization database VigiBase from 2014 to 2019. All cases that received anti-PD-1/PD-L1 treatment were included. Multiomics data from patients across 25 cancer types were download from The Cancer Genome Atlas. Logistic regression and propensity score algorithm was employed to calculate OR of irAEs. RESULTS: Retrospective analysis of in-house patients showed that irAE potential risks are higher in all cancer (OR 2.12, 95% CI 1.38 to 3.22, false discovery rate (FDR) adjusted-p=1.93×10-3) and patients with lung cancer (OR 3.16, 95% CI 1.67 to 5.95, FDR adjusted-p=1.93×10-3) when using antibiotics. Potential risk of irAEs in patients with lung cancer with antibiotic treatment is significantly higher in FAERS (OR 1.39, 95% CI 1.21 to 1.59; FDR adjusted-p=1.62×10-5) and VigiBase (OR 1.32, 95% CI 1.09 to 1.59, FDR adjusted-p=0.05). Mechanistically, decreased microbial diversity caused by antibiotics use may increase the irAE risk through mediating the irAE-related factors. CONCLUSIONS: Our study is the first to comprehensively demonstrate the associations of irAEs and antibiotic during anti-PD-1/PD-L1 therapy across a wide spectrum of cancers by analyzing multisource data. Administration of antibiotics should be carefully evaluated in patients with cancer treated by anti-PD-1/PD-L1 to avoid potentially increasing irAE risk.