A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts.

Static and dynamic analysis of cerebral blood flow in fifty-six large arterial vessel networks.

OBJECTIVE: The cerebral vasculature is formed of an intricate network of blood vessels over many different length scales. Changes in their structure and connection are implicated in multiple cerebrovascular and neurological disorders. In this study, we present a novel approach to the quantitative analysis of the cerebral macrovasculature using computational and mathematical tools in a large dataset. Approach. We analysed a publicly available vessel dataset from a cohort of 56 (32/24 F/M) healthy subjects. This dataset includes digital reconstructions of human brain macrovasculatures. We then propose a new mathematical model to compute blood flow dynamics and pressure distributions within these 56-representative cerebral macrovasculatures and quantify the results across this cohort. Main results. Statistical analysis showed that the steady state level of cerebrovascular resistance (CVR) gradually increases with age in both men and women. These age-related changes in CVR are in good agreement with previously reported values. All subjects were found to have only small phase angles (< 6°) between blood pressure and blood flow at the cardiac frequency. Significance. These results showed that the dynamic component of blood flow adds very little phase shift at the cardiac frequency, which implies that the cerebral macrocirculation can be regarded as close to steady state in its behaviour, at least in healthy populations, irrespective of age or sex. This implies that the phase shift observed in measurements of blood flow in cerebral vessels is caused by behaviour further down the vascular bed. This behaviour is important for future statistical models of the dynamic maintenance of oxygen and nutrient supply to the brain.

Predictability of B cell clonal persistence and immunosurveillance in breast cancer.

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

A simplified algorithm to evaluate the risk of submucosal invasive cancer in large (≥20 mm) nonpedunculated colonic polyps.

BACKGROUND: Recognition of submucosal invasive cancer (SMIC) in large (≥20 mm) nonpedunculated colonic polyps (LNPCPs) informs selection of the optimal resection strategy. LNPCP location, morphology, and size influence the risk of SMIC; however, currently no meaningful application of this information has simplified the process to make it accessible and broadly applicable. We developed a decision-making algorithm to simplify the identification of LNPCP subtypes with increased risk of potential SMIC. METHODS: Patients referred for LNPCP resection from September 2008 to November 2022 were enrolled. LNPCPs with SMIC were identified from endoscopic resection specimens, lesion biopsies, or surgical outcomes. Decision tree analysis of lesion characteristics identified in multivariable analysis was used to create a hierarchical classification of SMIC prevalence. RESULTS: 2451 LNPCPs were analyzed: 1289 (52.6%) were flat, 1043 (42.6%) nodular, and 118 (4.8%) depressed. SMIC was confirmed in 273 of the LNPCPs (11.1%). It was associated with depressed and nodular vs. flat morphology (odds ratios [ORs] 35.7 [95%CI 22.6-56.5] and 3.5 [95%CI 2.6-4.9], respectively; P<0.001); rectosigmoid vs. proximal location (OR 3.2 [95%CI 2.5-4.1]; P<0.001); nongranular vs. granular appearance (OR 2.4 [95%CI 1.9-3.1]; P<0.001); and size (OR 1.12 per 10-mm increase [95%CI 1.05-1.19]; P<0.001). Decision tree analysis targeting SMIC identified eight terminal nodes: SMIC prevalence was 62% in depressed LNPCPs, 19% in nodular rectosigmoid LNPCPs, and 20% in nodular proximal colon nongranular LNPCPs. CONCLUSIONS: This decision-making algorithm simplifies identification of LNPCPs with an increased risk of potential SMIC. When combined with surface optical evaluation, it facilitates accurate lesion characterization and resection choices.

Effect of Pre-, Pro-, and Synbiotics on Biomarkers of Systemic Inflammation in Children: A Scoping Review.

Systemic inflammation plays a central role in many diseases and is, therefore, an important therapeutic target. In a scoping review, we assessed the evidence base for the anti-inflammatory effects of pre-, pro-, and synbiotics in children. Of the 1254 clinical trials published in English in Ovid Medline and Cochrane Library PubMed from January 2003 to September 2022, 29 were included in the review. In six studies of healthy children (n = 1552), one reported that fructo-oligosaccharides added to infant formula significantly reduced pro-inflammatory biomarkers, and one study of a single-strain probiotic reported both anti- and pro-inflammatory effects. No effects were seen in the remaining two single-strain studies, one multi-strain probiotic, and one synbiotic study. In 23 studies of children with diseases (n = 1550), prebiotics were tested in 3, single-strain in 16, multi-strain probiotics in 6, and synbiotics in 2 studies. Significantly reduced inflammatory biomarkers were reported in 7/10 studies of atopic/allergic conditions, 3/5 studies of autoimmune diseases, 1/2 studies of preterm infants, 1 study of overweight/obesity, 2/2 studies of severe illness, and 2/3 studies of other diseases. However, only one or two of several biomarkers were often improved; increased pro-inflammatory biomarkers occurred in five of these studies, and a probiotic increased inflammatory biomarkers in a study of newborns with congenital heart disease. The evidence base for the effects of pre-, pro-, and synbiotics on systemic inflammation in children is weak. Further research is needed to determine if anti-inflammatory effects depend on the specific pre-, pro-, and synbiotic preparations, health status, and biomarkers studied.

Effect of Coffee and Chocolate Ingestion on Clozapine Dose and on Plasma Clozapine and Norclozapine Concentrations in Clinical Practice.

BACKGROUND: Some reports point to dietary caffeine intake as a cause of increased plasma clozapine concentrations in certain patients. METHODS: We compared clozapine dose and plasma clozapine and N-desmethylclozapine (norclozapine) concentrations in male and female smokers and nonsmokers in relation to reported (i) coffee (caffeine) and (ii) chocolate (caffeine and theobromine) intake in samples submitted for clozapine therapeutic drug monitoring, 1993-2017. RESULTS: There was information on coffee ingestion for 16,558 samples (8833 patients) from males and 5886 samples (3433 patients) from females and on chocolate ingestion for 12,616 samples (7568 patients) from males and 4677 samples (2939 patients) from females. When smoking was considered, there was no discernible effect of either coffee or chocolate ingestion either on the median dose of clozapine or on the median plasma clozapine and norclozapine concentrations in men and in women. However, cigarette smoking was associated with higher coffee and chocolate consumption. Although male nonsmokers who reported drinking 3 or more cups of coffee daily had significantly higher median plasma clozapine and norclozapine concentrations than those who drank less coffee, they were also prescribed a significantly higher clozapine dose. There was no clear effect of coffee ingestion on plasma clozapine and norclozapine in female nonsmokers. IMPLICATIONS: Inhibition of clozapine metabolism by caffeine at the doses of caffeine normally encountered in those treated with clozapine is unlikely even in male nonsmokers. Measurement of plasma caffeine in an appropriate sample should be considered in any future investigation into a presumed clozapine-caffeine interaction.

The role of 18F-FDG PET in minimizing variability in gross tumor volume delineation of soft tissue sarcomas.

BACKGROUND: Accurate gross tumor volume (GTV) delineation is a critical step in radiation therapy treatment planning. However, it is reader dependent and thus susceptible to intra- and inter-reader variability. GTV delineation of soft tissue sarcoma (STS) often relies on CT and MR images. PURPOSE: This study investigates the potential role of 18F-FDG PET in reducing intra- and inter-reader variability thereby improving reproducibility of GTV delineation in STS, without incurring additional costs or radiation exposure. MATERIALS AND METHODS: Three readers performed independent GTV delineation of 61 patients with STS using first CT and MR followed by CT, MR, and 18F-FDG PET images. Each reader performed a total of six delineation trials, three trials per imaging modality group. Dice Similarity Coefficient (DSC) score and Hausdorff distance (HD) were used to assess both intra- and inter-reader variability using generated simultaneous truth and performance level estimation (STAPLE) GTVs as ground truth. Statistical analysis was performed using a Wilcoxon signed-ranked test. RESULTS: There was a statistically significant decrease in both intra- and inter-reader variability in GTV delineation using CT, MR 18F-FDG PET images vs. CT and MR images. This was translated by an increase in the DSC score and a decrease in the HD for GTVs drawn from CT, MR and 18F-FDG PET images vs. GTVs drawn from CT and MR for all readers and across all three trials. CONCLUSION: Incorporation of 18F-FDG PET into CT and MR images decreased intra- and inter-reader variability and subsequently increased reproducibility of GTV delineation in STS.

Increasing prevalence of cirrhosis among insured adults in the United States, 2012-2018.

BACKGROUND: Liver cirrhosis is a chronic disease that is known as a "silent killer" and its true prevalence is difficult to describe. It is imperative to accurately characterize the prevalence of cirrhosis because of its increasing healthcare burden. METHODS: In this retrospective cohort study, trends in cirrhosis prevalence were evaluated using administrative data from one of the largest national health insurance providers in the US. (2011-2018). Enrolled adult (≥18-years-old) patients with cirrhosis defined by ICD-9 and ICD-10 were included in the study. The primary outcome measured in the study was the prevalence of cirrhosis 2011-2018. RESULTS: Among the 371,482 patients with cirrhosis, the mean age was 62.2 (±13.7) years; 53.3% had commercial insurance and 46.4% had Medicare Advantage. The most frequent cirrhosis etiologies were alcohol-related (26.0%), NASH (20.9%) and HCV (20.0%). Mean time of follow-up was 725 (±732.3) days. The observed cirrhosis prevalence was 0.71% in 2018, a 2-fold increase from 2012 (0.34%). The highest prevalence observed was among patients with Medicare Advantage insurance (1.67%) in 2018. Prevalence increased in each US. state, with Southern states having the most rapid rise (2.3-fold). The most significant increases were observed in patients with NASH (3.9-fold) and alcohol-related (2-fold) cirrhosis. CONCLUSION: Between 2012-2018, the prevalence of liver cirrhosis doubled among insured patients. Alcohol-related and NASH cirrhosis were the most significant contributors to this increase. Patients living in the South, and those insured by Medicare Advantage also have disproportionately higher prevalence of cirrhosis. Public health interventions are important to mitigate this concerning trajectory of strain to the health system.

Neurological intervention transition model for dynamic prediction of good outcome in spontaneous subarachnoid haemorrhage.

Deterioration of neurovascular conditions can be rapid in patients with spontaneous subarachnoid haemorrhage (SAH) and often lead to poor clinical outcomes. Therefore, it is crucial to promptly assess and continually track the progression of the disease. This study incorporated baseline clinical conditions, repeatedly measured neurological grades and haematological biomarkers for dynamic outcome prediction in patients with spontaneous SAH. Neurological intervention, mainly aneurysm clipping and endovascular embolisation, was also incorporated as an intermediate event in developing a neurological intervention transition (NIT) joint model. A retrospective cohort study was performed on 701 patients in spontaneous SAH with a study period of 14 days from the MIMIC-IV dataset. A dynamic prognostic model predicting outcome of patients was developed based on combination of Cox model and piecewise linear mixed-effect models to incorporate different types of prognostic information. Clinical baseline covariates, including cerebral oedema, cerebral infarction, respiratory failure, hydrocephalus and vasospasm, as well as repeated measured Glasgow Coma Scale (GCS), glucose and white blood cell (WBC) levels were covariates contributing to the optimal model. Incorporation of neurological intervention as an intermediate event increases the prediction performance compared with baseline joint modelling approach. The average AUC of the optimal model proposed in this study is 0.7783 across different starting points of prediction and prediction intervals. The model proposed in this study can provide dynamic prognosis for spontaneous SAH patients and significant potential benefits in critical care management.

Safety and efficacy of physician-administered balanced-sedation for the endoscopic mucosal resection of large non-pedunculated colorectal polyps.

Background and study aims Because of concerns about peri-procedural adverse events (AEs), guidelines recommend anesthetist-managed sedation (AMS) for long and complex endoscopic procedures. The safety and efficacy of physician-administered balanced sedation (PA-BS) for endoscopic mucosal resection (EMR) of large non-pedunculated colorectal polyps (LNPCPs) ≥20 mm is unknown. Patients and methods We compared PA-BS with AMS in a retrospective study of prospectively collected data from consecutive patients referred for management of LNPCPs (NCT01368289; NCT02000141). A per-patient propensity analysis was performed following a 1:2 nearest-neighbor (Greedy-type) match, based on age, gender, Charlson comorbidity index, and lesion size. The primary outcome was any peri-procedural AE, which included hypotension, hypertension, tachycardia, bradycardia, hypoxia, and new arrhythmia. Secondary outcomes were unplanned admissions, 28-day re-presentation, technical success, and recurrence. Results Between January 2016 and June 2020, 700 patients underwent EMR for LNPCPs, of whom 638 received PA-BS. Among them, the median age was 70 years (interquartile range [IQR] 62-76 years), size 35 mm (IQR 25-45 mm), and duration 35 minutes (IQR 25-60 minutes). Peri-procedural AEs occurred in 149 (23.4%), most commonly bradycardia (116; 18.2%). Only five (0.8%) required an unplanned sedation-related admission due to AEs (2 hypotension, 1 arrhythmia, 1 bradycardia, 1 hypoxia), with a median inpatient stay of 1 day (IQR 1-3 days). After propensity-score matching, there were no differences between PA-BS and AMS in peri-procedural AEs, unplanned admissions, 28-day re-presentation rates, technical success or recurrence. Conclusions Physician-administered balanced sedation for the EMR of LNPCPs is safe. Peri-procedural AEs are infrequent, transient, rarely require admission (<1%), and are experienced in similar frequencies to those receiving anesthetist-managed sedation.

A population pharmacokinetic model to guide clozapine dose selection, based on age, sex, ethnicity, body weight and smoking status.

AIMS: Guidance on clozapine dosing in treatment-resistant schizophrenia is based largely on data from White young adult males. This study aimed to investigate the pharmacokinetic profiles of clozapine and N-desmethylclozapine (norclozapine) across the age range, accounting for sex, ethnicity, smoking status and body weight. METHODS: A population pharmacokinetic model, implemented in Monolix, that linked plasma clozapine and norclozapine via a metabolic rate constant, was used to analyse data from a clozapine therapeutic drug monitoring service, 1993-2017. RESULTS: There were 17 787 measurements from 5960 patients (4315 male) aged 18-86 years. The estimated clozapine plasma clearance was reduced from 20.2 to 12.0 L h-1 between 20 and 80 years. Model-based dose predictions to attain a predose plasma clozapine concentration of 0.35 mg L-1 was 275 (90% prediction interval 125, 625) mg day-1 in nonsmoking, White males weighing 70 kg and aged 40 years. The corresponding predicted dose was increased by 30% in smokers, decreased by 18% in females, and was 10% higher and 14% lower in otherwise analogous Afro-Caribbean and Asian patients, respectively. Overall, the predicted dose decreased by 56% between 20 and 80 years. CONCLUSION: The large sample size and wide age range of the patients studied allowed precise estimation of dose requirements to attain predose clozapine concentration of 0.35 mg L-1 . The analysis was, however, limited by the absence of data on clinical outcome and future studies are required to determine optimal predose concentrations specifically in those aged over 65 years.

An ultrastructural report of human articular cartilage resident cells in correlation with their phenotypic characteristics.

The recent discovery of progenitors based on their differential fibronectin-adhesion (FAA-CPs) and migratory-based (MCPs) assay has evoked interest due to their superiority in terms of their efficient chondrogenesis and reduced hypertrophic propensity. This study aims to isolate and enrich three articular cartilage subsets, chondrocytes, FAA-CPs, and MCPs, and compare their undifferentiated and chondrogenic differentiated status, using in-vitro phenotypical characterization in correlation with ultrastructural analysis using Transmission Electron Microscopy (TEM). Following informed consent, cartilage shavings were procured from a non-diseased human ankle joint and cultured to obtain the three subsets. Chondrocytes exhibited higher CD106 and lower CD49b and CD146 levels. Following chondrogenic differentiation, corroborative results were seen, with the MCP group showing the highest GAG/DNA ratio levels and uptake of extracellular matrix stain as compared to the FAA-CP group. TEM analysis of the chondrocytes revealed the presence of more autolytic cells with disintegrated cytoplasm and plasma membrane. The differentiated FAA-CPs and MCPs displayed higher collagen and rough endoplasmic reticulum. The results presented in this study provide novel information on the ultrastructural characteristics of cartilage resident cells, with the chondrocyte group displaying features of terminal differentiation. Both progenitor subtypes showed superiority in varied contexts, with greater collagen fibrils and greater GAG content in MCPs. The display of preferential and differentiation traits sheds insight on the necessity to enrich progenitors and coculturing them with the general pool of constituent cells to combine their advantages and reduce their drawbacks to achieve a regenerative tissue displaying genuine hyaline-like repair while limiting their terminal differentiation.

The measurement of fatigue in clinicians within hospital settings: A systematic review of measurement properties.

Medical staff fatigue leads to accidents and mistakes and puts patient safety at risk. A measure of fatigue in the workplace may help to quantify, predict, and manage fatigue. This review aimed to evaluate instruments used to measure fatigue in medical staff within hospitals. A systematic review following the JBI methodology was undertaken. A search for articles was conducted in 2021. Included articles (all validation studies) were assessed for methodological quality using the COSMIN checklist. Measurement property data was evaluated for Quality of Evidence using GRADE methodology. Ten studies representing five instruments were reviewed: Occupational Fatigue Exertion and Recovery scale (now superseded); Occupational Fatigue Exertion and Recovery scale (15-item); Multidimensional Fatigue Inventory; Need for Recovery Scale; and the Swedish Occupational Fatigue Inventory. Four instruments show promise for measuring fatigue in hospital medical staff, however, there is limited certainty in the measure property estimates. The Quality of Evidence for measurement properties for all instruments is insufficient. Further validation studies following the COSMIN standards are needed before recommendations for use can be made.

Effect of Cigarette Smoking on Clozapine Dose and on Plasma Clozapine and N-Desmethylclozapine (Norclozapine) Concentrations in Clinical Practice.

BACKGROUND: Cigarette smoking enhances plasma clozapine clearance and thus affects the clozapine dose requirement. METHODS: We compared clozapine daily dose and plasma clozapine and N-desmethylclozapine (norclozapine) concentrations in male and female smokers and nonsmokers in samples submitted for clozapine therapeutic drug monitoring (1996-2017). RESULTS: There were 105,316/60,792 and 34,290/31,309 samples with dose information from male and female smokers/nonsmokers, respectively. There was information on the number of cigarettes smoked daily for 12,842 samples (8409 patients) and 3948 samples (2753 patients) from men and women, respectively. Of these, 574 and 253 samples were from men and women, respectively, who reported smoking 1-9 cigarettes daily.In both sexes, the median clozapine doses in the nonsmokers were 75%-80% of those in the smokers, but the median plasma clozapine and norclozapine concentrations were 136% higher. The effect of smoking on the dose and on median plasma clozapine and norclozapine concentrations seemed maximal after 2-3, perhaps fewer, cigarettes daily in males. In females, the effect of smoking seemed to be near maximal after some 4-5 cigarettes per day. IMPLICATIONS: The optimum target range for predose plasma clozapine may be different in smokers (0.35-0.45 mg L-1) as opposed to nonsmokers (0.50-0.60 mg L-1). That changes in clozapine clearance are likely near maximal with cigarette smoking as low as 2-3 d-1 in males, perhaps slightly more in females, emphasizes that covert or passive smoking may be an important factor in seemingly random changes in plasma clozapine concentration at constant dose.

Prediction of cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin (H&E)-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an approach for predicting response to multiple targeted and immunotherapies from H&E-slides. In difference from existing approaches that aim to predict treatment response directly from the slides, ENLIGHT-DeepPT is an indirect two-step approach consisting of (1) DeepPT, a new deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response based on the DeepPT inferred expression values. DeepPT successfully predicts transcriptomics in all 16 TCGA cohorts tested and generalizes well to two independent datasets. Our key contribution is showing that ENLIGHT-DeepPT successfully predicts true responders in five independent patients' cohorts involving four different treatments spanning six cancer types with an overall odds ratio of 2.44, increasing the baseline response rate by 43.47% among predicted responders, without the need for any treatment data for training. Furthermore, its prediction accuracy on these datasets is comparable to a supervised approach predicting the response directly from the images, which needs to be trained and tested on the same cohort. ENLIGHT-DeepPT future application could provide clinicians with rapid treatment recommendations to an array of different therapies and importantly, may contribute to advancing precision oncology in developing countries.

Spatial distribution of meiofaunal and macrofaunal assemblages in the tidal flats of the southern Korean coast in relation to natural and anthropogenic impacts.

We investigated the spatial variability of macrofaunal and meiofaunal assemblages in intertidal flats on the southern coast of Korea. Abiotic and biotic samples were collected at five stations. The species richness, density, and composition of the assemblages differed significantly among stations. Nematoda and Annelida were the most dominant meiofaunal and macrofaunal taxa, respectively, although taxon dominance differed among stations. Distance-based linear models showed that sediment-related variables and heavy metals were the main environmental factors determining the spatial variability of the assemblages. Macrofauna had only sediment-related variables and heavy metals as major environmental factors, but meiofauna were also influenced by other environmental factors such as sea surface temperature, dissolved oxygen-related variables, and salinity. This study can provide basic ecological data for understanding the spatial distribution of macro-meiofaunal assemblages and aid in the development of marine environmental management strategies on the western south coast of Korea.