The mesenteric entry site as a potential weak point in gastrointestinal anastomoses - findings from an ex-vivo biomechanical analysis.

PURPOSE: Gastrointestinal disorders frequently necessitate surgery involving intestinal resection and anastomosis formation, potentially leading to severe complications like anastomotic leakage (AL) which is associated with increased morbidity, mortality, and adverse oncologic outcomes. While extensive research has explored the biology of anastomotic healing, there is limited understanding of the biomechanical properties of gastrointestinal anastomoses, which was aimed to be unraveled in this study. METHODS: An ex-vivo model was developed for the biomechanical analysis of 32 handsewn porcine end-to-end anastomoses, using interrupted and continuous suture techniques subjected to different flow models. While multiple cameras captured different angles of the anastomosis, comprehensive data recording of pressure, time, and temperature was performed simultaneously. Special focus was laid on monitoring time, location and pressure of anastomotic leakage (LP) and bursting pressures (BP) depending on suture techniques and flow models. RESULTS: Significant differences in LP, BP, and time intervals were observed based on the flow model but not on the suture techniques applied. Interestingly, anastomoses at the insertion site of the mesentery exhibited significantly higher rates of leakage and bursting compared to other sections of the anastomosis. CONCLUSION: The developed ex-vivo model facilitated comparable, reproducible, and user-independent biomechanical analyses. Assessing biomechanical properties of anastomoses offers an advantage in identifying technical weak points to refine surgical techniques, potentially reducing complications like AL. The results indicate that mesenteric insertion serves as a potential weak spot for AL, warranting further investigations and refinements in surgical techniques to optimize outcomes in this critical area of anastomotic procedures.

Fractal analysis of extracellular matrix for observer-independent quantification of intestinal fibrosis in Crohn's disease.

Prevention of intestinal fibrosis remains an unresolved problem in the treatment of Crohn's disease (CD), as specific antifibrotic therapies are not yet available. Appropriate analysis of fibrosis severity is essential for assessing the therapeutic efficacy of potential antifibrotic drugs. The aim of this study was to develop an observer-independent method to quantify intestinal fibrosis in surgical specimens from patients with CD using structural analysis of the extracellular matrix (ECM). We performed fractal analysis in fibrotic and control histological sections of patients with surgery for CD (n = 28). To specifically assess the structure of the collagen matrix, polarized light microscopy was used. A score to quantify collagen fiber alignment and the color of the polarized light was established. Fractal dimension as a measure for the structural complexity correlated significantly with the histological fibrosis score whereas lacunarity as a measure for the compactness of the ECM showed a negative correlation. Polarized light microscopy to visualize the collagen network underlined the structural changes in the ECM network in advanced fibrosis. In conclusion, observer-independent quantification of the structural complexity of the ECM by fractal analysis is a suitable method to quantify the degree of intestinal fibrosis in histological samples from patients with CD.

Development of an image-based Random Forest classifier for prediction of surgery duration of laparoscopic sigmoid resections.

PURPOSE: Sigmoid diverticulitis is a disease with a high socioeconomic burden, accounting for a high number of left-sided colonic resections worldwide. Modern surgical scheduling relies on accurate prediction of operation times to enhance patient care and optimize healthcare resources. This study aims to develop a predictive model for surgery duration in laparoscopic sigmoid resections, based on preoperative CT biometric and demographic patient data. METHODS: This retrospective single-center cohort study included 85 patients who underwent laparoscopic sigmoid resection for diverticular disease. Potentially relevant procedure-specific anatomical parameters recommended by a surgical expert were measured in preoperative CT imaging. After random split into training and test set (75% / 25%) multiclass logistic regression was performed and a Random Forest classifier was trained on CT imaging parameters, patient age, and sex in the training cohort to predict categorized surgery duration. The models were evaluated in the test cohort using established performance metrics including receiver operating characteristics area under the curve (AUROC). RESULTS: The Random Forest model achieved a good average AUROC of 0.78. It allowed a very good prediction of long (AUROC = 0.89; specificity 0.71; sensitivity 1.0) and short (AUROC = 0.81; specificity 0.77; sensitivity 0.56) procedures. It clearly outperformed the multiclass logistic regression model (AUROC: average = 0.33; short = 0.31; long = 0.22). CONCLUSION: A Random Forest classifier trained on demographic and CT imaging biometric patient data could predict procedure duration outliers of laparoscopic sigmoid resections. Pending validation in a multicenter study, this approach could potentially improve procedure scheduling in visceral surgery and be scaled to other procedures.

Morphology-based molecular classification of spinal cord ependymomas using deep neural networks.

Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

B cell-mediated CD4 T-cell costimulation via CD86 exacerbates pro-inflammatory cytokine production during autoimmune intestinal inflammation.

Dysregulated B cell responses have been described in inflammatory bowel disease (IBD) patients; however, the role of B cells in IBD pathology remained incompletely understood. We here provide evidence for the detrimental role of activated B cells during the onset of autoimmune intestinal inflammation. Using Wiskott-Aldrich Syndrome interacting protein deficient (Wipf1-/-) mice as a mouse model of chronic colitis, we identified clusters of differentiation (CD)86 expression on activated B cells as a crucial factor exacerbating pro-inflammatory cytokine production of intestinal CD4 T cells. Depleting B cells through anti-CD20 antibody treatment or blocking costimulatory signals mediated by CD86 through cytotoxic T lymphocyte antigen-4-immunoglobulin (CTLA-4-Ig) diminished intestinal inflammation in our mouse model of chronic IBD at the onset of disease. This was due to a reduction in aberrant humoral immune responses and reduced CD4 T cell pro-inflammatory cytokine production, especially interferon-g (IFN-g) and granulocyte-macrophage colony-stimulating factor (GM-CSF). Interestingly, in addition to B cells isolated from the inflamed colon of Wipf1-/- mice, we also found CD86 mRNA and protein expression upregulated on activated B cells isolated from inflamed tissue of human patients with IBD. B cell activation and CD86 expression were boosted by soluble CD40L in vitro, which we found in the serum of mice and human patients with IBD. In summary, our data provides detailed insight into the contribution of B cells to intestinal inflammation, with implications for the treatment of IBD.

CT Attenuation of Hepatic Pancreatic Cancer Metastases Correlates with Prognostically Detrimental Metastatic Necrosis.

Percutaneous CT-guided biopsy is a frequently performed procedure for the confirmation and molecular workup of hepatic metastases of pancreatic ductal adenocarcinoma (PDAC). Tumor necrosis of primary PDAC has shown a negative prognostic impact in recent studies. This study aims to examine predictability in CT scans and the prognostic impact of necrosis in hepatic metastases of PDAC. In this tertiary-center retrospective cohort study, we included 36 patients with hepatic metastases of PDAC who underwent CT-guided hepatic biopsies. Normalized attenuation of the biopsied metastasis was determined in venous phase contrast-enhanced planning scans obtained prior to biopsy by automatic, threshold-based 3D segmentation and manual, blinded 2D segmentation. A board-certified pathologist specialized in hepatic pathology histologically quantified the tumor necrosis and cellularity of the biopsy cylinders. We found a significant inverse-linear correlation between normalized attenuation and the fraction of necrosis (Pearson's r = 0.51, p < 0.001 for automatic 3D segmentation or Pearson's r = 0.52, p < 0.001 for manual 2D segmentation), whereas no correlation was found with tumor cellularity. Additionally, we discovered that patients with a fraction of necrosis ≥ 20% in metastases had a significantly shorter overall survival (p < 0.035). In summary, tumor necrosis of PDAC metastases can be estimated from contrast-enhanced CT scans, which could help to improve biopsy sample pattern planning. In addition, liver metastatic necrosis may serve as a prognostic biomarker in PDAC.

Crohn's Disease as a Possible Risk Factor for Failed Healing in Ileocolic Anastomoses.

Anastomotic leakage (AL) after colorectal resections is a serious complication in abdominal surgery. Especially in patients with Crohn's disease (CD), devastating courses are observed. Various risk factors for the failure of anastomotic healing have been identified; however, whether CD itself is independently associated with anastomotic complications still remains to be validated. A retrospective analysis of a single-institution inflammatory bowel disease (IBD) database was conducted. Only patients with elective surgery and ileocolic anastomoses were included. Patients with emergency surgery, more than one anastomosis, or protective ileostomies were excluded. For the investigation of the effect of CD on AL 141, patients with CD-type L1, B1-3 were compared to 141 patients with ileocolic anastomoses for other indications. Univariate statistics and multivariate analysis with logistic regression and backward stepwise elimination were performed. CD patients had a non-significant higher percentage of AL compared to non-IBD patients (12% vs. 5%, p = 0.053); although, the two samples differed in terms of age, body mass index (BMI), Charlson comorbidity index (CCI), and other clinical variables. However, Akaike information criterion (AIC)-based stepwise logistic regression identified CD as a factor for impaired anastomotic healing (final model: p = 0.027, OR: 17.043, CI: 1.703-257.992). Additionally, a CCI ≥ 2 (p = 0.010) and abscesses (p = 0.038) increased the disease risk. The alternative point estimate for CD as a risk factor for AL based on propensity score weighting also resulted in an increased risk, albeit lower (p = 0.005, OR 7.36, CI 1.82-29.71). CD might bear a disease-specific risk for the impaired healing of ileocolic anastomoses. CD patients are prone to postoperative complications, even in absence of other risk factors, and might benefit from treatment in dedicated centers.

Robust classification using average correlations as features (ACF).

MOTIVATION: In single-cell transcriptomics and other omics technologies, large fractions of missing values commonly occur. Researchers often either consider only those features that were measured for each instance of their dataset, thereby accepting severe loss of information, or use imputation which can lead to erroneous results. Pairwise metrics allow for imputation-free classification with minimal loss of data. RESULTS: Using pairwise correlations as metric, state-of-the-art approaches to classification would include the K-nearest-neighbor- (KNN) and distribution-based-classification-classifier. Our novel method, termed average correlations as features (ACF), significantly outperforms those approaches by training tunable machine learning models on inter-class and intra-class correlations. Our approach is characterized in simulation studies and its classification performance is demonstrated on real-world datasets from single-cell RNA sequencing and bottom-up proteomics. Furthermore, we demonstrate that variants of our method offer superior flexibility and performance over KNN classifiers and can be used in conjunction with other machine learning methods. In summary, ACF is a flexible method that enables missing value tolerant classification with minimal loss of data.

Radio-Frequency Sweeps at Microtesla Fields for Parahydrogen-Induced Polarization of Biomolecules.

Magnetic resonance imaging of 13C-labeled metabolites enhanced by parahydrogen-induced polarization (PHIP) enables real-time monitoring of processes within the body. We introduce a robust, easily implementable technique for transferring parahydrogen-derived singlet order into 13C magnetization using adiabatic radio frequency sweeps at microtesla fields. We experimentally demonstrate the applicability of this technique to several molecules, including some molecules relevant for metabolic imaging, where we show significant improvements in the achievable polarization, in some cases reaching above 60% nuclear spin polarization. Furthermore, we introduce a site-selective deuteration scheme, where deuterium is included in the coupling network of a pyruvate ester to enhance the efficiency of the polarization transfer. These improvements are enabled by the fact that the transfer protocol avoids relaxation induced by strongly coupled quadrupolar nuclei.

A nationwide population-based study on the clinical and economic burden of anastomotic leakage in colorectal surgery.

AIM: Anastomotic leakage (AL) is one of the most dreaded complications in colorectal surgery. In 2013, the International Classification of Diseases code K91.83 for AL was introduced in Germany, allowing nationwide analysis of AL rates and associated parameters. The aim of this population-based study was to investigate the current incidence, risk factors, mortality, clinical management, and associated costs of AL in colorectal surgery. METHODS: A data query was performed based on diagnosis-related group data of all hospital cases of inpatients undergoing colon or sphincter-preserving rectal resections between 2013 and 2018 in Germany. RESULTS: A total number of 690,690 inpatient cases were included in this study. AL rates were 6.7% for colon resections and 9.2% for rectal resections in 2018. Regarding the treatment of AL, the application of endoluminal vacuum therapy increased during the studied period, while rates of relaparotomy, abdominal vacuum therapy, and terminal enterostomy remained stable. AL was associated with significantly increased in-house mortality (7.11% vs. 20.11% for colon resections and 3.52% vs. 11.33% for rectal resections in 2018) and higher socioeconomic costs (mean hospital reimbursement volume per case: 14,877€ (no AL) vs. 37,521€ (AL) for colon resections and 14,602€ (no AL) vs. 30,606€ (AL) for rectal resections in 2018). CONCLUSIONS: During the studied time period, AL rates did not decrease, and associated mortality remained at a high level. Our study provides updated population-based data on the clinical and economic burden of AL in Germany. Focused research in the field of AL is still urgently necessary to develop targeted strategies to prevent AL, improve patient care, and decrease socioeconomic costs.

Development and Validation of a Deep Learning Algorithm to Differentiate Colon Carcinoma From Acute Diverticulitis in Computed Tomography Images.

Importance: Differentiating between malignant and benign etiology in large-bowel wall thickening on computed tomography (CT) images can be a challenging task. Artificial intelligence (AI) support systems can improve the diagnostic accuracy of radiologists, as shown for a variety of imaging tasks. Improvements in diagnostic performance, in particular the reduction of false-negative findings, may be useful in patient care. Objective: To develop and evaluate a deep learning algorithm able to differentiate colon carcinoma (CC) and acute diverticulitis (AD) on CT images and analyze the impact of the AI-support system in a reader study. Design, Setting, and Participants: In this diagnostic study, patients who underwent surgery between July 1, 2005, and October 1, 2020, for CC or AD were included. Three-dimensional (3-D) bounding boxes including the diseased bowel segment and surrounding mesentery were manually delineated and used to develop a 3-D convolutional neural network (CNN). A reader study with 10 observers of different experience levels was conducted. Readers were asked to classify the testing cohort under reading room conditions, first without and then with algorithmic support. Main Outcomes and Measures: To evaluate the diagnostic performance, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for all readers and reader groups with and without AI support. Metrics were compared using the McNemar test and relative and absolute predictive value comparisons. Results: A total of 585 patients (AD: n = 267, CC: n = 318; mean [SD] age, 63.2 [13.4] years; 341 men [58.3%]) were included. The 3-D CNN reached a sensitivity of 83.3% (95% CI, 70.0%-96.6%) and specificity of 86.6% (95% CI, 74.5%-98.8%) for the test set, compared with the mean reader sensitivity of 77.6% (95% CI, 72.9%-82.3%) and specificity of 81.6% (95% CI, 77.2%-86.1%). The combined group of readers improved significantly with AI support from a sensitivity of 77.6% to 85.6% (95% CI, 81.3%-89.3%; P < .001) and a specificity of 81.6% to 91.3% (95% CI, 88.1%-94.5%; P < .001). Artificial intelligence support significantly reduced the number of false-negative and false-positive findings (NPV from 78.5% to 86.4% and PPV from 80.9% to 90.8%; P < .001). Conclusions and Relevance: The findings of this study suggest that a deep learning model able to distinguish CC and AD in CT images as a support system may significantly improve the diagnostic performance of radiologists, which may improve patient care.

Perioperative Low-Dose Prednisolone Treatment Has Beneficial Effects on Postoperative Recovery and Anastomotic Healing in a Murine Colitis Model.

BACKGROUND AND AIMS: High-dose glucocorticoid treatment has been identified as a risk factor for anastomotic leakage in patients with inflammatory bowel disease [IBD] undergoing bowel resection surgery. By contrast, active disease during surgery is also associated with elevated morbidity. Perioperative low-dose treatment might be beneficial regarding postoperative outcomes by controlling disease activity. The present study is the first to investigate the dose-dependent effect of perioperative prednisolone therapy in a murine IBD model combining dextran sodium sulphate [DSS] colitis with intestinal anastomosis surgery. METHODS: In 84 10-week-old wild-type mice, a colorectal anastomosis was performed using a microsurgical technique. Half the animals received induction of chemical colitis with 2% DSS via drinking water prior to surgery. In both groups, one-third of the animals received daily oral administration of high-dose [0.533 mg/kg] and one-third low-dose [0.133 mg/kg] prednisolone. Evaluation was performed on postoperative days 3 and 7. RESULTS: While high-dose prednisolone treatment led to an increased anastomotic leakage rate in mice under colitis, low-dose prednisolone treatment limited preoperative disease activity and did not influence the leakage rate. Histological examination showed a beneficial effect of low-dose prednisolone treatment on microscopic abscess formation at the anastomotic site in DSS mice as well as an increased anastomotic healing score. CONCLUSIONS: We demonstrate a beneficial effect of perioperative short-term low-dose prednisolone treatment on intestinal anastomotic healing in the context of colitis. Perioperative use of short-term low-dose prednisolone treatment might be beneficial in IBD patients who need to undergo surgery during active disease.

Gastrectomy for cancer beyond life expectancy. A comprehensive analysis of oncological gastric surgery in Germany between 2008 and 2018.

Introduction: Major gastric surgery for distal esophageal and gastric cancer has a strong impact on the quality of life, morbidity, and mortality. Especially in elderly patients reaching their life expectancy, the responsible use and extent of gastrectomy are imperative to achieve a balance between harm and benefit. In the present study, the reimbursement database (German Diagnosis Related Groups (G-DRG) database) of the Statistical Office of the Federal Republic of Germany was queried to evaluate the morbidity and mortality of patients aged above or below 75 years following gastrectomy. Material and methods: All patients in Germany undergoing subtotal gastrectomy (ST), total gastrectomy (T), or gastrectomy combined with esophagectomy (TE) for gastric or distal esophageal cancer (International Statistical Classification of Diseases and Related Health Problems Version 10 (ICD-10) C15.2, C15.5, and C16.0-C16.9) between 2008 and 2018 were included. Intraoperative and postoperative complications as well as comorbidities, in-hospital mortality, and the extent of surgery were assessed by evaluating ICD-10 and operation and procedure key (Operationen- und Prozedurenschlüssel) codes. Results: A total of 67,389 patients underwent oncologic gastric resection in Germany between 2008 and 2018. In total, 21,794 patients received ST, 41,825 received T, and 3,466 received TE, respectively. In 304 cases, the combinations of these, in fact, mutually exclusive procedures were encoded. The proportion of patients aged 75 years or older was 51.4% (n = 11,207) for ST, 32.6% (n = 13,617) for T, and 28.1% (n = 973) for TE. The in-hospital mortality of elderly patients was significantly increased in all three groups. (p < 0.0001) General complications such as respiratory failure (p = 0.0054), acute renal failure (p < 0.0001), acute myocardial failure (p < 0.0001), and the need for resuscitation (ST/T: p < 0.0001/TE: p = 0.0218) were significantly increased after any kind of gastrectomy. Roux-en Y was the most commonly applied reconstruction technique in both young and elderly patients. Regarding lymphadenectomy, systematic D2 dissection was performed less frequently in older patients than in the younger collective in the case of ST and T as well as D3 dissection. Peritonectomy and hyperthermic intraperitoneal chemotherapy were uncommon in elderly patients alongside ST and T compared to younger patients (p < 0.0001). Conclusion: The clinical outcome of major oncological gastric surgery is highly dependent on a patient's age. The elderly show a tremendously increased likelihood of in-hospital mortality and morbidity.

The Effect of Anti-Tumor Necrosis Factor-Alpha Therapy within 12 Weeks Prior to Surgery on Postoperative Complications in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis.

The rate of abdominal surgical interventions and associated postoperative complications in inflammatory bowel disease (IBD) patients is still substantially high. There is an ongoing debate as to whether or not patients who undergo treatment with anti-tumor necrosis factor-alpha (TNF-α) agents may have an increased risk for general and surgical postoperative complications. Therefore, a systematic review and meta-analysis was conducted in order to assess the effect of anti-TNF-α treatment within 12 weeks (washout period) prior to abdominal surgery on 30-day postoperative complications in patients with IBD. The results of previously published meta-analyses examining the effect of preoperative anti-TNF-α treatment on postoperative complications reported conflicting findings which is why we specifically focus on the effect of anti-TNF-α treatment within 12 weeks prior to surgery. PubMed, Cochrane, Scopus, Web of Science, World Health Organization Trial Registry, ClinicalTrials.gov and reference lists were searched (June 1995−February 2022) to identify studies, investigating effects of anti-TNF-α treatment prior to abdominal surgery on postoperative complications in IBD patients. Pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated and subgroup analyses were performed. In this case, 55 cohort studies (22,714 patients) were included. Overall, postoperative complications (OR, 1.23; 95% CI, 1.04−1.45; p = 0.02), readmission (OR, 1.39; 95% CI, 1.11−1.73; p = 0.004), and intra-abdominal septic complications (OR, 1.89; 95% CI, 1.44−2.49; p < 0.00001) were significantly higher for anti-TNF-α-treated patients. Significantly higher intra-abdominal abscesses and readmission were found for anti-TNF-α-treated CD patients (p = 0.05; p = 0.002). Concomitant treatment with immunosuppressives in <50% of anti-TNF-α-treated patients was associated with significantly lower mortality rates (OR, 0.32; 95% CI, 0.12−0.83; p = 0.02). Anti-TNF-α treatment within 12 weeks prior to surgery is associated with higher short-term postoperative complication rates (general and surgical) for patients with IBD, especially CD.

Anastomotic Rings and Inflammation Values as Biomarkers for Leakage of Stapled Circular Colorectal Anastomoses.

Reliable markers to predict or diagnose anastomotic leakage (AL) of stapled circular anastomoses following colorectal resections are an important clinical need. Here, we aim to quantitatively investigate the morphology of anastomotic rings as an early available prognostic marker for AL and compare them to established inflammatory markers. We perform a prospective single-center cohort study, including patients undergoing stapled circular anastomosis between August 2020 and August 2021. The predictive value of the anastomotic ring configuration and the neutrophil-to-lymphocyte ratio (NLR) regarding anastomotic leakage is examined by ROC analyses and compared to the C-reactive protein (CRP) as an established marker. We included 204 patients, of which 19 suffered from anastomotic leakage (LEAK group), while in 185 patients the anastomoses healed well (HEAL group). The minimal height of the anastomotic rings as a binary classifier had a good ROC-AUC of 0.81 but was inferior to the NLR at postoperative day (POD) 5, with an excellent ROC-AUC of 0.93. Still, it was superior to the NLR at POD 3 (0.74) and the CRP at POD 3 (ROC-AUC 0.54) and 5 (ROC-AUC 0.70). The minimal height of the anastomotic rings as indicator for technically insufficient anastomoses is a good predictor of AL, while postoperatively the NLR was superior to the CRP in prediction of AL.

Outcome Quality After Colorectal Cancer Resection in Certified Colorectal Cancer Centers­Patient-Reported and Short-Term Clinical Outcomes.

BACKGROUND: In this observational study, patient-reported outcomes and short-term clinical outcome parameters in patients with colorectal cancer were studied 12 months after the start of treatment. Outcomes were also compared across German Certified Colorectal Cancer Centres. METHODS: Data were collected from 4239 patients with colorectal cancer who had undergone elective tumor resection in one of 102 colorectal cancer centers and had responded to a quality-of-life questionnaire before treatment (EORTC QLQ-C30 and -CR29). 3142 (74.1%) of these patients completed a post-treatment questionnaire 12 months later. Correlation analyses were calculated and case-mix adjusted comparisons across centers were made for selected patient-reported outcomes, anastomotic insufficiency, and 30-day-mortality. RESULTS: At 12 months, mild improvements were seen in mean quality-of-life scores (66 vs. 62 points), constipation (16 vs. 19), and abdominal pain (15 vs. 17). Worsening was seen in physical function (75 vs. 82) and pain (22 vs. 19). Better patient-reported outcomes at 12 months were associated with better scores before treatment. Better results in at least three of the five scores were associated with male sex, higher educational level, higher age, and private health insurance. Major worsening of fecal incontinence was seen among patients with rectal cancer without a stoma. The largest differences across centers were found with respect to physical function. Anastomotic insufficiency was found in 4.3% of colon cancer patients and 8.2% of rectal cancer patients. 1.9% of patients died within 30 days after their resection. CONCLUSION: Clinicians can use these findings to identify patients at higher risk for poorer patient-reported outcomes. The differences among cancer centers that were found imply that measures for quality improvement would be desirable.

Annexin A1 based inflammation resolving mediators and nanomedicines for inflammatory bowel disease therapy.

Inflammatory bowel diseases (IBD) such as Crohn's Disease (CD) and Ulcerative Colitis (UC) are chronic, progressive, and relapsing disorders of the gastrointestinal tract (GIT), characterised by intestinal epithelial injury and inflammation. Current research shows that in addition to traditional anti-inflammatory therapy, resolution of inflammation and repair of the epithelial barrier are key biological requirements in combating IBD. Resolution mediators include endogenous lipids that are generated during inflammation, e.g., lipoxins, resolvins, protectins, maresins; and proteins such as Annexin A1 (ANXA1). Nanoparticles can specifically deliver these potent inflammation resolving mediators in a spatiotemporal manner to IBD lesions, effectively resolve inflammation, and promote a return to homoeostasis with minimal collateral damage. We discuss these exciting and timely concepts in this review.

Scalable and Tunable Diamond Nanostructuring Process for Nanoscale NMR Applications.

Nanostructuring of a bulk material is used to change its mechanical, optical, and electronic properties and to enable many new applications. We present a scalable fabrication technique that enables the creation of densely packed diamond nanopillars for quantum technology applications. The process yields tunable feature sizes without the employment of lithographic techniques. High-aspect-ratio pillars are created through oxygen-plasma etching of diamond with a dewetted palladium film as an etch mask. We demonstrate an iterative renewal of the palladium etch mask, by which the initial mask thickness is not the limiting factor for the etch depth. Following the process, 300-400 million densely packed 100 nm wide and 1 µm tall diamond pillars were created on a 3 × 3 mm2 diamond sample. The fabrication technique is tailored specifically to enable applications and research involving quantum coherent defect center spins in diamond, such as nitrogen-vacancy (NV) centers, which are widely used in quantum science and engineering. To demonstrate the compatibility of our technique with quantum sensing, NV centers are created in the nanopillar sidewalls and are used to sense 1H nuclei in liquid wetting the nanostructured surface. This nanostructuring process is an important element for enabling the wide-scale implementation of NV-driven magnetic resonance imaging or NV-driven NMR.

Coating of Intestinal Anastomoses for Prevention of Postoperative Leakage: A Systematic Review and Meta-Analysis.

Background: For several decades, scientific efforts have been taken to develop strategies and medical aids for the reduction of anastomotic complications after intestinal surgery. Still, anastomotic leakage (AL) represents a frequently occurring postoperative complication with serious consequences on health, quality of life, and economic aspects. Approaches using collagen and/or fibrin-based sealants to cover intestinal anastomoses have shown promising effects toward leak reduction; however, they have not reached routine use yet. To assess the effects of covering intestinal anastomoses with collagen and/or fibrin-based sealants on postoperative leakage, a systematic review and meta-analysis were conducted. Method: PubMed, Web of Science, Cochrane Library, and Scopus (01/01/1964 to 17/01/2022) were searched to identify studies investigating the effects of coating any intestinal anastomoses with collagen and/or fibrin-based sealants on postoperative AL, reoperation rates, Clavien-Dindo major complication, mortality, and hospitalization length. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: Overall, 15 studies (five randomized controlled trials, three nonrandomized intervention studies, six observational cohort studies) examining 1,387 patients in the intervention group and 2,243 in the control group were included. Using fixed-effects meta-analysis (I 2 < 50%), patients with coated intestinal anastomoses presented significantly lower AL rates (OR = 0.37; 95% CI 0.27-0.52; p < 0.00001), reoperation rates (OR, 0.21; 95% CI, 0.10-0.47; p = 0.0001), and Clavien-Dindo major complication rates (OR, 0.54; 95% CI, 0.35-0.84; p = 0.006) in comparison to controls, with results remaining stable in sensitivity and subgroup analyses (stratified by study design, age group, intervention used, location of anastomoses, and indication for surgery). The length of hospitalization was significantly shorter in the intervention group (weighted mean difference (WMD), -1.96; 95% CI, -3.21, -0.71; p = 0.002) using random-effects meta-analysis (I 2 ≥ 50%), especially for patients with surgery of upper gastrointestinal malignancy (WMD, -4.94; 95% CI, -7.98, -1.90; p = 0.001). Conclusion: The application of collagen-based laminar biomaterials or fibrin sealants on intestinal anastomoses can significantly reduce postoperative rates of AL and its sequelae. Coating of intestinal anastomoses could be a step toward effective and sustainable leak prevention. To assess the validity and robustness of these findings, further clinical studies need to be conducted.

HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values.

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods-ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences.