A Computer Vision Algorithm to Predict Superior Mesenteric Artery Margin Status for Patients with Pancreatic Ductal Adenocarcinoma.

OBJECTIVE: To evaluate the feasibility of developing a computer vision algorithm that uses preoperative computed tomography (CT) scans to predict superior mesenteric artery (SMA) margin status in patients undergoing Whipple for pancreatic ductal adenocarcinoma (PDAC), and to compare algorithm performance to that of expert abdominal radiologists and surgical oncologists. SUMMARY BACKGROUND DATA: Complete surgical resection is the only chance to achieve a cure for PDAC; however, current modalities to predict vascular invasion have limited accuracy. METHODS: Adult patients with PDAC who underwent Whipple and had preoperative contrast-enhanced CT scans were included (2010-2022). The SMA was manually annotated on the CT scans, and we trained a U-Net algorithm for SMA segmentation and a ResNet50 algorithm for predicting SMA margin status. Radiologists and surgeons reviewed the scans in a blinded fashion. SMA margin status per pathology reports was the reference. RESULTS: Two hundred patients were included. Forty patients (20%) had a positive SMA margin. For the segmentation task, the U-Net model achieved a Dice Similarity Coefficient of 0.90. For the classification task, all readers demonstrated limited sensitivity, although the algorithm had the highest sensitivity at 0.43 (versus 0.23 and 0.36 for the radiologists and surgeons, respectively). Specificity was universally excellent, with the radiologist and algorithm demonstrating the highest specificity at 0.94. Finally, the accuracy of the algorithm was 0.85 versus 0.80 and 0.76 for the radiologists and surgeons, respectively. CONCLUSIONS: We demonstrated the feasibility of developing a computer vision algorithm to predict SMA margin status using preoperative CT scans, highlighting its potential to augment the prediction of vascular involvement.

A machine learning approach for predicting textbook outcome after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

INTRODUCTION: Peritoneal carcinomatosis is considered a late-stage manifestation of neoplastic diseases. Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) can be an effective treatment for these patients. However, the procedure is associated with significant morbidity. Our aim was to develop a machine learning model to predict the probability of achieving textbook outcome (TO) after CRS-HIPEC using only preoperatively known variables. METHODS: Adult patients with peritoneal carcinomatosis and who underwent CRS-HIPEC were included from a large, single-center, prospectively maintained dataset (2001-2020). TO was defined as a hospital length of stay ≤14 days and no postoperative adverse events including any complications, reoperation, readmission, and mortality within 90 days. Four models (logistic regression, neural network, random forest, and XGBoost) were trained, validated, and a user-friendly risk calculator was then developed. RESULTS: A total of 1954 CRS-HIPEC procedures for peritoneal carcinomatosis were included. Overall, 13% (n = 258) achieved TO following CRS-HIPEC procedure. XGBoost and logistic regression had the highest area under the curve (AUC) (0.76) after model optimization, followed by random forest (AUC 0.75) and neural network (AUC 0.74). The top preoperative variables associated with achieving a TO were lower peritoneal cancer index scores, not undergoing proctectomy, splenectomy, or partial colectomy and being asymptomatic from peritoneal metastases prior to surgery. CONCLUSION: This is a data-driven study to predict the probability of achieving TO after CRS-HIPEC. The proposed pipeline has the potential to not only identify patients for whom surgery is not associated with prohibitive risk, but also aid surgeons in communicating this risk to patients.

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to perform a systematic review and meta-analysis to compare the performance of ML vs LR models in predicting postoperative outcomes for patients undergoing gastrointestinal (GI) surgery. METHODS: A systematic search of Embase, MEDLINE, Cochrane, Web of Science, and Google Scholar was performed through December 2022. The primary outcome was the discriminatory performance of ML vs LR models as measured by the area under the receiver operating characteristic curve (AUC). A meta-analysis was then performed using a random effects model. RESULTS: A total of 62 LR models and 143 ML models were included across 38 studies. On average, the best-performing ML models had a significantly higher AUC than the LR models (ΔAUC, 0.07; 95% CI, 0.04-0.09; P < .001). Similarly, on average, the best-performing ML models had a significantly higher logit (AUC) than the LR models (Δlogit [AUC], 0.41; 95% CI, 0.23-0.58; P < .001). Approximately half of studies (44%) were found to have a low risk of bias. Upon a subset analysis of only low-risk studies, the difference in logit (AUC) remained significant (ML vs LR, Δlogit [AUC], 0.40; 95% CI, 0.14-0.66; P = .009). CONCLUSION: We found a significant improvement in discriminatory ability when using ML over LR algorithms in predicting postoperative outcomes for patients undergoing GI surgery. Subsequent efforts should establish standardized protocols for both developing and reporting studies using ML models and explore the practical implementation of these models.

A Novel Machine Learning Approach to Predict Textbook Outcome in Colectomy.

BACKGROUND: Several calculators exist to predict risk of postoperative complications. However, in low-risk procedures such as colectomy, a tool to determine the probability of achieving the ideal outcome could better aid clinical decision-making, especially for high-risk patients. A textbook outcome is a composite measure that serves as a surrogate for the ideal surgical outcome. OBJECTIVE: To identify the most important factors for predicting textbook outcomes in patients with nonmetastatic colon cancer undergoing colectomy and to create a textbook outcome decision support tool using machine learning algorithms. DESIGN: This was a retrospective analysis study. SETTINGS: Data were collected from the American College of Surgeons National Surgical Quality Improvement Program database. PATIENTS: Adult patients undergoing elective colectomy for nonmetastatic colon cancer (2014-2020) were included. MAIN OUTCOME MEASURES: Textbook outcome was the main outcome, defined as no mortality, no 30-day readmission, no postoperative complications, no 30-day reinterventions, and a hospital length of stay of ≤5 days. Four models (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting) were trained and validated. Ultimately, a web-based calculator was developed as proof of concept for clinical application. RESULTS: A total of 20,498 patients who underwent colectomy for nonmetastatic colon cancer were included. Overall, textbook outcome was achieved in 66% of patients. Textbook outcome was more frequently achieved after robotic colectomy (77%), followed by laparoscopic colectomy (68%) and open colectomy (39%, p < 0.001). eXtreme Gradient Boosting was the best performing model (area under the curve = 0.72). The top 5 preoperative variables to predict textbook outcome were surgical approach, patient age, preoperative hematocrit, preoperative oral antibiotic bowel preparation, and patient sex. LIMITATIONS: This study was limited by its retrospective nature of the analysis. CONCLUSIONS: Using textbook outcome as the preferred outcome may be a useful tool in relatively low-risk procedures such as colectomy, and the proposed web-based calculator may aid surgeons in preoperative evaluation and counseling, especially for high-risk patients. See Video Abstract . UN NUEVO ENFOQUE DE APRENDIZAJE AUTOMTICO PARA PREDECIR EL RESULTADO DE LOS LIBROS DE TEXTO EN COLECTOMA: ANTECEDENTES:Existen varias calculadoras para predecir el riesgo de complicaciones posoperatorias. Sin embargo, en procedimientos de bajo riesgo como la colectomía, una herramienta para determinar la probabilidad de lograr el resultado ideal podría ayudar mejor a la toma de decisiones clínicas, especialmente para pacientes de alto riesgo. Un resultado de libro de texto es una medida compuesta que sirve como sustituto del resultado quirúrgico ideal.OBJETIVO:Identificar los factores más importantes para predecir el resultado de los libros de texto en pacientes con cáncer de colon no metastásico sometidos a colectomía y crear una herramienta de apoyo a la toma de decisiones sobre los resultados de los libros de texto utilizando algoritmos de aprendizaje automático.DISEÑO:Este fue un estudio de análisis retrospectivo.AJUSTES:Los datos se obtuvieron de la base de datos del Programa Nacional de Mejora de la Calidad del Colegio Americano de Cirujanos.PACIENTES:Se incluyeron pacientes adultos sometidos a colectomía electiva por cáncer de colon no metastásico (2014-2020).MEDIDAS PRINCIPALES DE RESULTADO:El resultado de los libros de texto fue el resultado principal, definido como ausencia de mortalidad, reingreso a los 30 días, complicaciones posoperatorias, reintervenciones a los 30 días y una estancia hospitalaria ≤5 días. Se entrenaron y validaron cuatro modelos (regresión logística, árbol de decisión, bosque aleatorio y XGBoost). Finalmente, se desarrolló una calculadora basada en la web como prueba de concepto para su aplicación clínica.RESULTADOS:Se incluyeron un total de 20.498 pacientes sometidos a colectomía por cáncer de colon no metastásico. En general, el resultado de los libros de texto se logró en el 66% de los pacientes. Los resultados de los libros de texto se lograron con mayor frecuencia después de la colectomía robótica (77%), seguida de la colectomía laparoscópica (68%) y la colectomía abierta (39%) (p<0,001). XGBoost fue el modelo con mejor rendimiento (AUC=0,72). Los cinco principales variables preoperatorias para predecir el resultado en los libros de texto fueron el abordaje quirúrgico, la edad del paciente, el hematocrito preoperatorio, la preparación intestinal con antibióticos orales preoperatorios y el sexo femenino.LIMITACIONES:Este estudio estuvo limitado por la naturaleza retrospectiva del análisis.CONCLUSIONES:El uso de los resultados de los libros de texto como resultado preferido puede ser una herramienta útil en procedimientos de riesgo relativamente bajo, como la colectomía, y la calculadora basada en la web propuesta puede ayudar a los cirujanos en la evaluación y el asesoramiento preoperatorios, especialmente para pacientes de alto riesgo. (Traducción-Yesenia Rojas-Khalil ).

Inadequate Lymph Node Yield: An Inadequate Indication for Adjuvant Chemotherapy in Stage II Colon Cancer.

Background: Optimal therapy for stage II colon cancer remains unclear, and national guidelines recommend "consideration" of adjuvant chemotherapy (ACT) in the presence of high-risk features, including inadequate lymph node yield (LNY, <12 nodes). This study aims to determine whether the survival benefit of ACT in stage II disease varies based on the adequacy of LNY. Methods: We used the National Cancer Database (NCDB) to identify adults who underwent resection for a single primary T3 or T4 colon cancer between 2006 and 2018. Multivariable logistic regression tested for associations between ACT and prespecified demographic and clinical characteristics, including the adequacy of LNY. We used Cox proportional hazards models to assess overall survival and restricted cubic splines to estimate the optimal LNY threshold to dichotomize patients based on overall survival. Results: Unadjusted 5- and 10-year survival rates were 84% and 75%, respectively, among patients who received ACT and 70% and 50% among patients who did not (log-rank P < 0.01). Inadequate LNY was independently associated with both receipt of ACT (odds ratios, 1.50; P < 0.01) and decreased overall survival [hazard ratio (HR), 1.56; P < 0.01]. ACT was independently associated with improved survival (HR, 0.67; P < 0.01); this effect size did not change based on the adequacy of LNY (interaction P = 0.41). Results were robust to re-analysis with our cohort-optimized threshold of 18 lymph nodes. Conclusions: Consistent with contemporary guidelines, patients with inadequate LNY are more likely to receive ACT. LNY adequacy is an independent prognostic factor but, in isolation, should not dictate whether patients receive ACT.

A Machine Learning Approach to Predict Postoperative Pancreatic Fistula After Pancreaticoduodenectomy Using Only Preoperatively Known Data.

BACKGROUND: Clinically-relevant postoperative pancreatic fistula (CR-POPF) following pancreaticoduodenectomy (PD) is a major postoperative complication and the primary determinant of surgical outcomes. However, the majority of current risk calculators utilize intraoperative and postoperative variables, limiting their utility in the preoperative setting. Therefore, we aimed to develop a user-friendly risk calculator to predict CR-POPF following PD using state-of-the-art machine learning (ML) algorithms and only preoperatively known variables. METHODS: Adult patients undergoing elective PD for non-metastatic pancreatic cancer were identified from the ACS-NSQIP targeted pancreatectomy dataset (2014-2019). The primary endpoint was development of CR-POPF (grade B or C). Secondary endpoints included discharge to facility, 30-day mortality, and a composite of overall and significant complications. Four models (logistic regression, neural network, random forest, and XGBoost) were trained, validated and a user-friendly risk calculator was then developed. RESULTS: Of the 8666 patients who underwent elective PD, 13% (n = 1160) developed CR-POPF. XGBoost was the best performing model (AUC = 0.72), and the top five preoperative variables associated with CR-POPF were non-adenocarcinoma histology, lack of neoadjuvant chemotherapy, pancreatic duct size less than 3 mm, higher BMI, and higher preoperative serum creatinine. Model performance for 30-day mortality, discharge to a facility, and overall and significant complications ranged from AUC 0.62-0.78. CONCLUSIONS: In this study, we developed and validated an ML model using only preoperatively known variables to predict CR-POPF following PD. The risk calculator can be used in the preoperative setting to inform clinical decision-making and patient counseling.

Development and Validation of Prediction Models and Risk Calculators for Posthepatectomy Liver Failure and Postoperative Complications Using a Diverse International Cohort of Major Hepatectomies.

OBJECTIVE: The study aim was to develop and validate models to predict clinically significant posthepatectomy liver failure (PHLF) and serious complications [a Comprehensive Complication Index (CCI)>40] using preoperative and intraoperative variables. BACKGROUND: PHLF is a serious complication after major hepatectomy but does not comprehensively capture a patient's postoperative course. Adding the CCI as an additional metric can account for complications unrelated to liver function. METHODS: The cohort included adult patients who underwent major hepatectomies at 12 international centers (2010-2020). After splitting the data into training and validation sets (70:30), models for PHLF and a CCI>40 were fit using logistic regression with a lasso penalty on the training cohort. The models were then evaluated on the validation data set. RESULTS: Among 2192 patients, 185 (8.4%) had clinically significant PHLF and 160 (7.3%) had a CCI>40. The PHLF model had an area under the curve (AUC) of 0.80, calibration slope of 0.95, and calibration-in-the-large of -0.09, while the CCI model had an AUC of 0.76, calibration slope of 0.88, and calibration-in-the-large of 0.02. When the models were provided only preoperative variables to predict PHLF and a CCI>40, this resulted in similar AUCs of 0.78 and 0.71, respectively. Both models were used to build 2 risk calculators with the option to include or exclude intraoperative variables ( PHLF Risk Calculator; CCI>40 Risk Calculator ). CONCLUSIONS: Using an international cohort of major hepatectomy patients, we used preoperative and intraoperative variables to develop and internally validate multivariable models to predict clinically significant PHLF and a CCI>40 with good discrimination and calibration.

Immediate Breast Reconstruction Using the Autologous Dermal Flap.

INTRODUCTION: Despite the development of breast-conserving surgery in breast cancer treatment, there still remain indications for total mastectomy. Since mastectomy has a significant negative impact on the patients' quality of life, breast reconstruction is increasingly popular. However, for patients with large ptotic breasts who do not choose tissue-based reconstruction techniques and prefer implant-based breast reconstruction, there is no single-stage breast reconstruction technique other than the classic technique using Acellular Dermal Matrix (ADM). METHODS: This study presents a novel technique for Nipple-Sparing Mastectomy (NSM) and Immediate Breast reconstruction (IBR) in 11 operations (in seven patients) whose treatment decision-making was based on NCCN guidelines. In this technique, the implant/tissue expander is covered by the pectoral muscle in the upper part and an autologous dermal flap in the lower part, replacing an ADM. The dermal flap is created from the de-epithelialized lower mastectomy flap in these large ptotic breasts. Maintaining the nipple-areola complex (NAC) is possible by re-implanting a free nipple split-thickness graft from the NAC of the ipsilateral breast prepared at the beginning of the operation. RESULTS: All seven patients had large ptotic breasts ranging from C cup to double D in size and grade 2 and higher breast ptosis. The mean BMI of the patients was 28 (range: 26-33). No major complications occurred postoperatively. There were three minor complications, all managed conservatively. Surgical indications were risk reduction surgery in three patients with BRCA mutations and therapeutic in the remaining patients (three multifocal invasive ductal carcinomas and one diffused ductal carcinoma in situ). None of the patients had a previous reduction mammoplasty as preparation for NSM, and all the patients underwent a single operation. No breast tissue remained under the NAC, which is ideal with the NSM technique. CONCLUSIONS: The proposed technique is excellent for implant-based IBR in patients with large ptotic breasts. It eliminates the use of ADM mesh and reduces the cost and postoperative complication rate associated with ADM. Furthermore, using a free nipple graft technique can eliminate the need for a preparatory mastopexy. This technique can also theoretically reduce the risk of recurrence or new primary breast cancer as there are no remaining ducts beneath the nipple-areola complex.

Prototypic P2X7 Receptor Agonist, BzATP, Induced the Expression of Unfolded Protein Response Genes in Human M1 Macrophages.

Purinergic receptors stimulation by adenosine triphosphate (ATP) contributes significantly to macrophage activation, and also macrophage cell death. Upon the macrophage activation, the protein load of the endoplasmic reticulum is increased which is resulted in the activation of unfolded protein response (UPR). In the current study, we aimed to evaluate the connection between prototypic P2X7 receptor agonist, extracellular 2'(3')-O-(4-Benzoylbenzoyl)-ATP (BzATP), and the UPR pathway in macrophages. The monocyte-derived macrophages from blood samples of 14 healthy volunteers were skewed toward M1 macrophages after incubation with LPS and IFN-γ. M1 macrophages were treated with 200 µM BzATP. The expression levels of UPR genes, including CHOP, HERP, GADD34, XBP1, and ATF6 in macrophages before and after treatment were measured using real-time polymerase chain reaction. The results demonstrated that the expression of CHOP, HERP, and ATF6 is significantly decreased and the expression level of GADD34 and XBP1 is significantly increased after M1 polarization. BzATP not only significantly increased the expression levels of CHOP, GADD34, ATF6, and HERP but also significantly decreases the XBP1 expression level in M1 macrophages. The present study showed that BzATP induces cellular stress in M1 macrophages by elevating the expression levels of UPR genes including CHOP, GADD34, ATF6, and reducing cell viability.

Efficacy and safety of sulforaphane for treatment of mild to moderate depression in patients with history of cardiac interventions: A randomized, double-blind, placebo-controlled clinical trial.

AIM: Depression has been recognized as one of the disorders associated with cardiac interventions such as percutaneous coronary intervention (PCI) or coronary artery bypass graft surgery (CABG). In the present study, we evaluated the efficacy and safety of sulforaphane in treatment of depression induced by cardiac interventions. METHODS: After initial screening, 66 patients with previous history of at least one cardiac intervention and current mild to moderate depression were randomly assigned to two parallel groups receiving either sulforaphane (n = 33) or placebo (n = 33) for six successive weeks. Efficacy was assessed using the Hamilton Rating Scale for Depression (HAM-D) at baseline and week 2, 4, and 6. Safety of the treatments was checked during the trial period. RESULTS: Sixty participants completed the clinical trial (n = 30 in each group). Baseline demographic and clinical parameters were all similar among groups. Repeated measures analysis indicated that the sulforaphane group exhibited greater improvement in HAM-D scores throughout the trial (P < 0.001). Response to treatment (≥50% reduction in the HAM-D score) rate was higher in the sulforaphane group at trial endpoint (30% vs 6.67%, P = 0.042). Remission (HAM-D score ≤ 7) rate was also higher in the sulforaphane group; however, the difference was not significant (23.33% vs 3.33%, P = 0.052). Finally, no significant difference was observed between the two groups in terms of frequency of side effects. CONCLUSIONS: Sulforaphane could safely improve depressive symptoms induced by cardiac interventions. Further clinical trials with larger sample sizes and longer follow-up periods are warranted to confirm our results.

Inhibition of phosphodiesterase IV enzyme improves locomotor and sensory complications of spinal cord injury via altering microglial activity: Introduction of Roflumilast as an alternative therapy.

Despite the great search for an effective approach to minimize secondary injury in spinal cord injury (SCI) setting, there have been limited advances. Roflumilast is a selective inhibitor of phosphodiesterase 4 with potent anti-inflammatory properties. Here, we sought to explore Roflumilast efficacy in the improvement of locomotor and sensory deficits of SCI. In an animal setting, 50 male rats were randomly assigned to five groups: an SCI group receiving Placebo, three SCI groups receiving Roflumilast at the doses of 0.25, 0.5, and 1 mg/kg prior to T9 vertebra laminectomy, and a sham-operated group. Locomotor, mechanical, and thermal activities were evaluated for 28 days. At the end of the study, spinal cord samples were taken to assess the relative ratio of microglial subtypes, including M1 and M2, histopathological changes, levels of pro-inflammatory (TNF-α and IL-1ß) and anti-inflammatory (IL-10) biomarkers, and cAMP level. Repeated measure analysis revealed significant effect for time-treatment interaction on locomotion [F (24, 270) = 280.7, p < 0.001], thermal sensitivity [F (16, 180) = 4.35, p < 0.001], and mechanical sensitivity [F (16, 180) = 7.96, p < 0.001]. As expected, Roflumilast significantly increased the expression of spinal cAMP. H&E staining exhibited lesser histopathological disruptions in Roflumilast-treated rodents. We also observed a significant reduction in the M1/M2 ratio (p values < 0.001) as well as in pro-inflammatory biomarkers following the administration of Roflumilast to the injured rats. Furthermore, IL-10 level was increased in rodents receiving 1 mg/kg of the reagent. In conclusion, the increased spinal cAMP following Roflumilast therapy might attenuate neuroinflammation via altering microglial activity; therefore, it could be considered as an alternative therapeutic agent for SCI complications.

The association between systemic inflammation and cognitive performance in healthy adults.

BACKGROUND: Several studies have indicated that mild systemic inflammation is associated with the risk of cognitive impairment. However, not every cognitive domain has been evaluated to have a correlation with peripheral inflammation in healthy individuals. Therefore, we aimed to investigate the association between C-reactive protein (CRP) as a marker of peripheral inflammation with various domains of cognition in healthy adults. METHOD: This study consisted of 216 healthy native German adults (138 males and 78 females, mean age: 39.12 ± 20.19 years) from "Leipzig Study for Mind-Body-Emotion Interactions" (LEMON) database. After the initial assessment and conducting the cognitive battery, a blood sample was collected and CRP level was evaluated. Patients were categorized into three groups based on their CRP level. Subsequently, demographic and cognitive features were compared across three groups and to confirm the association between CRP level and cognitive performance, general linear models (GLM) were applied. RESULTS: All California Verbal Learning Task (CVLT)-evaluated aspects of memory performance were inversely associated with CRP level, some of which remained significant after the adjustment for age, gender, education, smoking status and body mass index. Moreover, GLM analysis indicated that mean reaction time of the Test of Attentional Performance-Alertness (TAP-A) test (with and without signal) was also significantly associated with CRP level. CONCLUSION: The current study indicated that healthy subjects with higher levels of CRP exhibit poorer performance in verbal learning memory and general wakefulness domains of cognition.

Activation of adenosine A2A receptor induced interleukin-23 mRNA expression in macrophages of ankylosing spondylitis patients.

BACKGROUND: Ankylosing spondylitis (AS) is an auto-inflammatory debilitating disorder with a complex pathogenesis. The adenosinergic pathway is an immunologic regulating pathway with a potential role in AS pathophysiology. In the present study, we have aimed to investigate the influence of A2A adenosine receptor (A2AAR) activation on tumor necrosis factor-α (TNF-α) and interleukin-23 (IL-23) expression and secretion by monocyte-generated macrophages of AS patients. METHODS: Whole-blood separated monocytes were extracted from 14 AS patients and 14 healthy controls. Macrophages were differentiated by macrophage colony-stimulating factor (M-CSF), and surface markers were confirmed by flow cytometer. Cells were treated with CGS-21680 as a known agonist of A2AAR. Analysis of ADORA2A, TNFA, and IL23A gene expression was performed by SYBR green real-time PCR. The concentration of secreted cytokines was also measured by ELISA kits. RESULTS: Based on our analysis, CGS-21680 significantly decreased TNF-α secretion by monocyte-derived macrophages of AS patients. Moreover, A2AAR agonist increased the IL23A mRNA expression level in monocyte-derived macrophages of AS patients considerably. Whereas, CGS-21680 did not have any influence on macrophages of healthy individuals. CONCLUSION: According to our results, it appears that A2AAR activation can increase IL-23 secretion by monocyte-derived macrophages of AS patients. Although the TNF-α reducing effect of A2AAR agonists can be a potential target in AS treatment, robust increasing of IL-23 should be considered as the undesirable effect of these agents.

P2 receptors mRNA expression profiles in macrophages from ankylosing spondylitis patients and healthy individuals.

BACKGROUND: Ankylosing spondylitis (AS) is a multifactorial rheumatic disease which mainly involves the axial skeleton. Macrophages and extracellular nucleotides have been shown to contribute to the inflammation process in autoimmune diseases. Membrane-bound purinergic P2 receptors might be involved in the modulation of immune cells in AS. Therefore, we aimed to analyze the messenger RNA (mRNA) expression of P2 receptors in the macrophages of AS patients and healthy controls. METHODS: Twenty-three AS patients and 23 age- and sex-matched healthy individuals were included in our study. Whole blood-separated monocytes of study participants were stimulated by macrophage colony-stimulating factor for 7 days and differentiated to macrophages. Monocyte and macrophage markers were analyzed by flow cytometry. SYBR green real-time polymerase chain reaction was used to measure the relative expression levels of P2RX1 , P2RX2 , P2RX3 , P2RX4 , P2RX5 , P2RX6 , P2RX7 , P2RY1 , P2RY2 , P2RY4 , P2RY6 , P2RY11 , P2RY12 , P2RY13 , P2RY14 , and PANX1 genes. RESULTS: P2RY13 and P2RY6 genes had the highest expression levels in macrophages among P2RY genes. P2RY1 mRNA expression was significantly down-regulated (-1.75 fold) and P2RY14 was up-regulated (2.6 fold) in macrophages of AS patients compared to healthy individuals. P2RX4 gene had the highest expression in monocyte-derived macrophages, followed by P2RX7 and P2RX1  genes. There was no significant difference in P2X receptor mRNA expression level between macrophages of AS patients and healthy individuals. CONCLUSIONS: Our results indicate that AS patients show altered expression levels of P2 receptor genes. Moreover, these changes might be associated with disease activity and patients' status.

The Association between the Pulmonary Arterial Obstruction Index and Atrial Size in Patients with Acute Pulmonary Embolism.

PURPOSE: Pulmonary embolism (PE) is a common and potentially fatal form of venous thromboembolism. The aim of this study is to investigate the association between the pulmonary arterial obstruction index and atrial size in patients with acute pulmonary embolism. BASIC PROCEDURE: The study consisted of 86 patients with clinical symptoms of PE. Out of 86 individuals, 50 patients were diagnosed with PE and considered as the patient group. The others were considered as the control group. All patients were scanned by a multidetector CT scanner. Using the radiology workstation, an expert radiologist calculated the left atrium (LA) and right atrium (RA) areas from planimetric measurements obtained from free-hand delineation of the atrial boarders using an electronic pen. Quantitative volumetric measurements of LA and RA were obtained from original axial images. MAIN FINDINGS: There were 25 males and 25 females with PE, who had a mean age of 58 years. There was not a significant difference in the positive history of diabetes mellitus, hypertension, asthma, chronic obstructive pulmonary diseases, ischemic heart disease, and smoking between patients and control group. There was a significant negative correlation between almost all LA measurements and the PAOI. RA area and volume had the highest area under the curves for recognizing larger clot burden. PRINCIPAL CONCLUSIONS: A higher clot load is associated with a smaller LA size and increased RA/LA ratios, measured with CTPA. Atrial measurements are correlated with POAI, and they could be used as sensitive parameters in predicting heart failure in patients with PE.

A Novel Level I Oncoplastic Surgery Technique for Tumors Located in UIQ of the Breast Far from the Nipple: The "Cross" Technique.

Breast surgery was revolutionized with the use of oncoplastic reshaping techniques minimizing breast deformities and esthetic complications. However, the application of the current oncoplastic techniques becomes challenging in some situations such as small-size breasts and when the tumors are located in special locations of the breast, for example, upper inner quadrant. In this article, an optimized oncoplastic technique named the "Cross" technique is introduced to overcome the abovementioned problems in the surgery of breast tumors located in the upper inner quadrant far from the center of the breast. Nineteen oncoplastic surgeries were performed by the same breast surgeon. The mean diameter and weight of the excised specimens were 20 mm and 74 g. The mean age of the patients was 51 years. Clear surgical margins were obtained in all patients. There was no marked deformity in the breast after surgery. The optimized technique produced promising results in our hands when applied to a selected group of patients. Moreover, the technique was found to reduce the need for revision surgery in ptotic breasts, as the alteration in the shape of the breast undergoing surgery is not significant enough to introduce asymmetry to the breasts.

HBV reactivation in rheumatic diseases patients under therapy: A meta-analysis.

BACKGROUND: Hepatitis B is one of the most common infectious diseases worldwide. In patients undergoing immunosuppressive therapy such as rheumatic diseases, reactivation of hepatitis B virus (HBV) is considered clinically important. This systematic review and meta-analysis were performed to determine the prevalence rate of HBV reactivation in rheumatic patients from different parts of the world. METHODS: The authors performed a systematic literature review from several reliable databases including Scopus, ISI Web of Science and PubMed. Furthermore, the keywords of this research were "Hepatitis B virus", "Rheumatic diseases", "HBV reactivation", "Anti-TNF", "DMARDs" and "Biologic agents". RESULTS: The authors selected 30 studies out of 983 for the present review. The overall estimation of the prevalence of HBV reactivation was 1.4 (95% confidence interval (CI): 1.3-1.6). Also, the heterogeneity in estimating the pooled prevalence among the studies was shown; Cochran Q test, P < 0.001, I2 = 99.9%. It should be noted that max and min reactivation rate of HBV were in Italy and France respectively. CONCLUSIONS: Rheumatic disease patients with resolved hepatitis B should be tightly monitored for possible HBV reactivation by elevation of liver enzymes and HBV DNA levels.