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Abstract Background There is a growing demand for colonoscopy, worldwide, resulting in increased rate of inappropriate referrals. This “overuse” of colonoscopies has become a major burden for health care. Objectives to assess the appropriateness of colonoscopies performed at the endoscopy unit of the university hospital of Sousse and to compare these results of appropriateness according to the European Panel of Appropriateness of Gastrointestinal Endoscopy (EPAGE) I and EPAGE II criteria. Patients and methods this cross-sectional study included all consecutive patients referred for a diagnostic colonoscopy, between January 2017 and December 2018. Patients referred for exclusively therapeutic indications, those with incomplete colonoscopies were not included. Patients with poor bowel preparation or missing data were also excluded. Indications were assessed using the EPAGE I and EPAGE II criteria. Results From 1972 consecutive patients, 1307 were included. Overall, 986 (75.4%) of all referrals were for out-patients. The majority of patients were referred by gastroenterologists (n = 1026 patients; 78.5%), followed by general surgeons (n = 85; 6.5%). The commonest indications were lower abdominal symptoms (275; 21%) followed by uncomplicated diarrhea (152; 11.6%). Relevant findings were present in 363 patients (27.7%). Neoplastic lesions were the dominant finding in 221 patients (16.9%). EPAGE I and EPAGE II criteria were applicable for 1237 (88.8%) and 1276 (97.7%) patients respectively. Hematochezia and abdominal pain recorded the highest inappropriate rates with both sets of criteria. Appropriate colonoscopies increased to 76.4% when EPAGE II criteria were applied; whereas uncertain and inappropriate procedures decreased to 10.3% and 10.9% respectively Appropriateness of indication was significantly higher in hospitalized patients. For the EPAGE II criteria, the specialty of the referring physician was also significantly associated to the appropriate use. The agreement between EPAGE I and EPAGE II criteria was slight using the weighted version of k (k = 0.153). Conclusions The updated and improved EPAGE II guidelines are a simple and valid tool for assessing the appropriateness of colonoscopies. They decreased the inappropriate rate and the possibility of missing potentially severe diagnoses.

Introduction Actinomycosis is an uncommon inflammatory bacterial disease caused by Actinomyces species, especially Actinomyces Israeli. Abdominopelvic forms are relatively rare and may involve the colon as a solid mass, mimicking a malignant tumor. Case presentation A 68-year-old Tunisian man, with a history of diabetes, hypertension, penicillin allergy, and renal failure, presented to the emergency department with abdominal pain, vomiting, and bowel obstruction. CT scan showed an acute intestinal obstruction upstream with obstructive tissular mass at the sigmoid colon. Emergency surgery revealed a sigmoid mass and a pre-perforative cecum. Subtotal colectomy was performed, with ileostomy and distal end closure. Histological examination confirmed Actinomyces infection. The patient was then placed on long-term doxycycline and Bactrim, with no recurrence over a 9-month follow-up period. Conclusion Abdominal actinomycosis, though rare, presents diagnostic challenges. It can be mistaken for malignancy, leading to unnecessary surgery in non-complicated cases, since it is effectively treated by antibiotics. In complicated cases, a combined approach involving both surgery and antibiotic therapy is necessary until the infection is completely eradicated.

Introduction Actinomycosis is an uncommon inflammatory bacterial disease caused by Actinomyces species, especially Actinomyces Israeli. Abdominopelvic forms are relatively rare and may involve the colon as a solid mass, mimicking a malignant tumor. Case presentation A 68-year-old Tunisian man, with a history of diabetes, hypertension, penicillin allergy, and renal failure, presented to the emergency department with abdominal pain, vomiting, and bowel obstruction. CT scan showed an acute intestinal obstruction upstream with obstructive tissular mass at the sigmoid colon. Emergency surgery revealed a sigmoid mass and a pre-perforative cecum. Total colectomy was performed, with ileostomy and distal end closure. Histological examination confirmed Actinomyces infection. The patient was then placed on long-term doxycycline and Bactrim, with no recurrence over a 9-month follow-up period. Conclusion Abdominal actinomycosis, though rare, presents diagnostic challenges. It can be mistaken for malignancy, leading to unnecessary surgery in non-complicated cases, since it is effectively treated by antibiotics. In complicated cases, a combined approach involving both surgery and antibiotic therapy is necessary until the infection is completely eradicated.

Nearly 50 years after the ground-breaking isolation of the primary Comptonia peregrina microsymbiont under axenic conditions, efforts to isolate a substantial number of Protofrankia and Frankia strains continue with enduring challenges and complexities. This study aimed to streamline genomic insights through comparative and predictive tools to extract traits crucial for isolating specific Frankia in axenic conditions. Pangenome analysis unveiled significant genetic diversity, suggesting untapped potential for cultivation strategies. Shared metabolic strategies in cellular components, central metabolic pathways, and resource acquisition traits offered promising avenues for cultivation. Ecological trait extraction indicated that most uncultured strains exhibit no apparent barriers to axenic growth. Despite ongoing challenges, potential caveats, and errors that could bias predictive analyses, this study provides a nuanced perspective. It highlights potential breakthroughs and guides refined cultivation strategies for these yet-uncultured strains. We advocate for tailored media formulations enriched with simple carbon sources in aerobic environments, with atmospheric nitrogen optionally sufficient to minimize contamination risks. Temperature adjustments should align with strain preferences—28–29°C for Frankia and 32–35°C for Protofrankia—while maintaining an alkaline pH. Given potential extended incubation periods (predicted doubling times ranging from 3.26 to 9.60 days, possibly up to 21.98 days), patience and rigorous contamination monitoring are crucial for optimizing cultivation conditions.

Introduction Actinomycosis is an uncommon inflammatory bacterial disease caused by Actinomyces species, especially Actinomyces Israeli. Abdominopelvic forms are relatively rare and may involve the colon as a solid mass, mimicking a malignant tumor. Case presentation A 68-year-old Tunisian man, with a history of diabetes, hypertension, penicillin allergy, and renal failure, presented to the emergency department with abdominal pain, vomiting, and bowel obstruction. CT scan showed an acute intestinal obstruction upstream with obstructive tissular mass at the sigmoid colon. Emergency surgery revealed a sigmoid mass and a pre-perforative cecum. Subtotal colectomy was performed, with ileostomy and distal end closure. Histological examination confirmed Actinomyces infection. The patient was then placed on long-term doxycycline and Bactrim, with no recurrence over a 9-month follow-up period. Conclusion Abdominal actinomycosis, though rare, presents diagnostic challenges. It can be mistaken for malignancy, leading to unnecessary surgery in non-complicated cases, since it is effectively treated by antibiotics. In complicated cases, a combined approach involving both surgery and antibiotic therapy is necessary until the infection is completely eradicated.

Peer-to-peer energy trading is an innovative idea that overcomes several technological and industrial hurdles. It allows industries and consumers, including knowledgeable prosumers, to trade excess energy with distributed generation sources, such as solar, wind, and electric vehicles, thus promoting a significant reduction in overall energy consumption. Real-Time Pricing (RTP) is increasingly essential in integrating smart home device Demand Response (DR) strategies. RTP improves energy management and enables customers to respond intelligently to price fluctuations. In this vein, this paper proves how DR and peer-to-peer (P2P) energy trading could affect energy prices by allowing producers (consumers) and smart home users to interact directly rather than through the traditional grid. The two-pronged planning approach substantially contributes to the reduction of electricity costs. DR enables P2P energy trading, while deep learning algorithms adapt smart home devices to RTP dynamics. Simulation results show that using P2P energy trading and DR in smart homes can significantly eliminate costs. This hybrid approach increases the energy efficiency of Smart Grid (SG) 2.0 technology and makes it more adaptable and cost-effective.

This paper aims to reveal how the refining industry's inputs in Saudi Arabia affect its output and to forecast refining industry dynamics. The variables used in this paper are the refined petroleum products representing the dependent variable, with natural gas liquids, crude oil, labor, and capital acting as explanatory variables covering the period 1990–2020. The long run cointegration of the variables was observed. An error correction model utilizing the Cobb–Douglas production function framework was performed. Furthermore, this study applied the vector autoregressive model (VAR) and its diagnosis tests, including forecast-error variance decomposition (FEVD) and impulse response functions (IRFs).The results indicate that natural gas liquids and crude oil have a significant influence on the refining industry's output. Although capital and labor are significant determinants of output, they do not contribute significantly to output creation in the refining industry. This might be related to some parts of the capital and human resources being directed toward supporting activities, such as administration, technical support, maintenance, transportation, logistics and assigning third-party contractors to perform the main duties related to the production process. Additionally, the petroleum refining industry requires substantial capital resources for construction and maintenance. Thus, the actual measurement of capital input's influence on output was observed in the long run. The results reveal that the refining industry's variation is influenced by both its own characteristics and that natural gas liquid, crude oil, capital, and labor factors have a significant impact on the accuracy of industry forecasts.This study concludes that Saudi Arabia's petroleum refining industry operates under decreasing returns to scale, while the shocks in the refining industry are influenced and caused by external factors.

Smart Grid 2.0 (SG 2.0) implementation constitutes an additional challenge in the industry and research fields. Energy consumption decreases when producers exchange excess energy consumers, including intelligent consumers, Distributed Generation (DG), such as wind and solar, and Electric Vehicles (EVs). By utilizing Demand Response (DR) based on Real-Time Pricing (RTP), the operation of every device in a smart home can be scheduled. Allowing users to trade energy directly with other energy producers (prosumers) rather than exclusively relying on the grid, peer-to-peer (P2P) energy trading in smart homes lowers energy prices for users. This article focuses on how the DR P2P energy trading affects consumers. The study conducted utilizes a two-stage scheduling technique to reduce consumers' electricity expenses. The initial stage involves arranging each device in the smart home based on RTP employing a deep learning method. The P2P energy trading between consumers in the second phase is made more accessible by the DR and the simulation results exhibit that energy trading decreases electricity bills in smart homes. Utility companies can reduce load during peak hours using DR-based P2P energy trading.

One of the key advantages of Additive Manufacturing is the versatility in working with a wide range of materials. Among these materials, Nickel-based superalloys have drawn great attention of specialists. This study investigates the behavior of Inconel 625 and Inconel 718 during selective laser melting. While these alloys have many similarities, thus their distinct chemical compositions determine different responses to this new process, which the authors aimed to elucidate in this study. Numerical simulations using ANSYS Additive® software were conducted to compare the melt pool dimensions (depth and width) of Inconel 625 and Inconel 718. The results reveal that the material's thermal properties play a significant role in determining the melt pool geometry. The Inconel 718 consistently exhibited larger melt pool dimensions than Inconel 625. The findings highlight the importance of understanding the connection between the material properties and process parameters.

Given the global decline in adherence to the Mediterranean Diet (MD), even within its native region, it is key to identify the factors influencing this trend to mitigate the negative health outcomes associated with westernized diets. To this end, 4025 individuals (49.6% women, 42.6 ± 14.2 y/o) from Greece, Italy, Morocco, Slovenia, and Tunisia remotely completed a series of measures assessing motives, attitudes, and psychosocial factors related to MD adherence, which was evaluated using the MEDAS questionnaire. The results suggested medium-to-low adherence across all countries, with the highest adherence in Italy and Morocco and the lowest in Slovenia. Structural equation modeling revealed that positive attitudes toward the healthiness of food were the strongest predictors of adherence, whereas picky eating was a significant negative predictor in all countries except Greece. Adherence to the MD was positively influenced by health motivations in Morocco and weight control in Slovenia and Greece, while sensory appeal negatively influenced adherence in Italy. Additionally, price and convenience were significant barriers in Tunisia and Greece, whereas a preference for local and seasonal foods promoted adherence in Morocco and Greece. Overall, our findings underscore the need for country-specific interventions and policies that address distinct local factors and motivations to ease favorable shifts in dietary patterns toward MD principles.

Prostatic condyloma acuminata is a rarely encountered clinical manifestation primarily linked to low-risk subtypes of human papillomavirus (HPV), such as HPV-6 and HPV-11. Unlike the more common anogenital presentation, prostatic condyloma acuminata remains an infrequent phenomenon, necessitating a nuanced approach to diagnosis and management. We present a case report involving a 68-year-old patient with an intricate medical history, where the discovery of prostatic condyloma acuminata presented diagnostic challenges and clinical intricacies.

Healthcare is a topic of significant concern within the academic and business sectors. The COVID-19 pandemic has had a considerable effect on the health of people worldwide. The rapid increase in cases adversely affects a nation's economy, public health, and residents' social and personal well-being. Improving the precision of COVID-19 infection forecasts can aid in making informed decisions regarding interventions, given the pandemic's harmful impact on numerous aspects of human life, such as health and the economy. This study aims to predict the number of confirmed COVID-19 cases in Saudi Arabia using Bayesian optimization (BOA) and deep learning (DL) methods. Two methods were assessed for their efficacy in predicting the occurrence of positive cases of COVID-19. The research employed data from confirmed COVID-19 cases in Saudi Arabia (SA), the United Kingdom (UK), and Tunisia (TU) from 2020 to 2021. The findings from the BOA model indicate that accurately predicting the number of COVID-19 positive cases is difficult due to the BOA projections needing to align with the assumptions. Thus, a DL approach was utilized to enhance the precision of COVID-19 positive case prediction in South Africa. The DQN model performed better than the BOA model when assessing RMSE and MAPE values. The model operates on a local server infrastructure, where the trained policy is transmitted solely to DQN. DQN formulated a reward function to amplify the efficiency of the DQN algorithm. By examining the rate of change and duration of sleep in the test data, this function can enhance the DQN model's training. Based on simulation findings, it can decrease the DQN work cycle by roughly 28% and diminish data overhead by more than 50% on average.

The increase in demand due to scientific innovation and economic expansion raises challenges linked to environmental impact and sustainable market development. This study analyzes the role played by Peer-to-Peer (P2P) energy trading in system operation. Several case studies with four distinct prosumer models, each fitted with diverse Energy Storage Systems (ESS), photovoltaic (PV) systems, and responsive demand technologies such as Electric Vehicles (EV), are examined. An economic analysis is conducted using the developed interface. An energy management system establishes a dynamic market framework, enabling energy trading via P2P market operators and distribution system operators. The implemented trading platform is chosen depending on pricing variations across different time intervals for home models. The P2P energy trading system employs mathematical modeling via deep learning to achieve an optimal solution that minimizes costs. The study uses other domestic models and optimization techniques to explore the amount of energy traded across households and timeframes. Additionally, it investigates the accomplishment of two-way energy transfer in electric cars, the importance of energy storage and photovoltaic systems, and various housing scenarios concerning peer-to-peer energy trading. Additionally, the system's advantages are demonstrated to participants beforehand by validating and presenting data through an input and output system that accepts these instances.

Abstract Background Intraoperative iatrogenic ureteral injuries represent rare technical surgical complications with the potential for adverse patient outcomes, particularly when the diagnosis is delayed. Ideally, these technical complications are recognized and repaired intraoperatively. This study was designed to investigate the root causes and outcomes of missed intraoperative ureteral injuries at a tertiary urology referral centre in Tunisia. Methods This is a retrospective cohort study in a tertiary urology referral centre in Tunis from January 1st, 2015, to December 31st, 2020, including all patients with iatrogenic ureteral injury, not diagnosed intraoperatively. The factors associated with the success of endoscopic treatment and those associated with the unfavourable evolution were investigated. Results A total of 40 iatrogenic ureteral injuries were included. Gynaecological surgery was responsible for 85% of ureteral injuries, mainly during hysterectomies (55%). The symptoms were dominated by low back pain (37.5%) and pyelonephritis (25%). Endoscopic treatment was attempted in 22 cases, it was sufficient in 12 cases. Ureteral injury required surgical treatment in 24 cases, and ureteroneocystostomy was performed in 16 cases. Nephrectomy was performed in eight cases, representing 20% of injuries, including three cases as the first treatment for late-diagnosed cases with a destroyed kidney. In the analytical study, endoscopic treatment was sufficient in 50% in case of ureteral fistula versus 27% in case of ureteral stenosis (p = 0.04). Nephrectomy was performed in 10% of cases when ureteral injury was diagnosed within the first month postoperatively compared to 60% of cases when this delay exceeded one month (p = 0.004). Conclusion Iatrogenic ureteral injuries discovered postoperatively are mostly secondary to gynaecologic surgery. Although endoscopic treatment is usually performed as a first treatment, a more aggressive surgical is often necessary, with a nephrectomy rate of 20%.

Background: Pathological response of liver metastases (LM) from colorectal carcinoma (CRC) to neoadjuvant therapy is one of the prognostic factors correlated with recurrence and survival. The aim of this study was to compare the performance of two prognostic scores in patients operated for colorectal cancer liver metastases (CRCLM) Methods: A study was performed of patients who underwent preoperative chemotherapy (CT), followed by resection of LM, from 2015-2021. Pathological response was evaluated according to Rubbia-Brandt tumor regression grade (TRG) and the Blazer scoring system. Then, we studied the performance of these two prognostic scores, based on homogeneity using the likelihood Ratio (LR+), monotonicity and discriminative ability using the area under the receiver operating characteristic (ROC) curve (AUC). Results: 70 cases were included in the study. Mean age was 56 years. The sex ratio was 2.2. Forty patients were stage IV (57%) with synchronous all CRCLMs. The overall survival, all stages combined, was 85.5% at 12 months, 41.7% at 24 months and 19.3% at 36 months. The mean survival was better in case of major response (TRG1/TRG2) evaluated at 40.1 and 41.1 months after diagnosis. In cases of partial response (TRG3), the mean survival was 32.1 months. In cases with no response (TRG4/TRG5), survival was estimated at 29.9 and 18.5 months. The Rubbia-Brandt TRG had the highest LR+ (10.95). The LR+ of the Rubbia-Brandt score was greater than 10, so it was a test with very strong contribution. The LR+ of the Blazer score was between 5 and 10, it was a test with strong contribution. The Rubbia-Brandt TRG had the highest linearity value (10.73). With a higher AUC of the ROC curve (0.8), the Rubbia-Brandt TRG was better at predicting survival than the Blazer score.

Salinity stress is among the key challenges for sustainable food production. It is continuously increasing against the backdrop of constant climate change and anthropogenic practices leading to a huge drop in soil, water, and cultivated crop quality and productivity. Halotolerant plants represent hot spots for endophytic bacteria which may have mechanisms to overcome salt stress. This research initiative aims to highlight the possible exploitation of bacterial endophytes as a microbial biotechnology tool in the productive success of plants exposed to saline stress. We started by solely studying the mechanisms of stress tolerance by plants and halotolerant bacteria. After that, we focused on the beneficial mechanisms of endophytic bacteria in salt stress mitigation. On one side, potent bacterium works by promoting plant performances by facilitating the plant’s nutrient uptake (P, K, Zn, N, and Fe) and by promoting the production of growth hormones (IAA and CKs). On the other side, they balance stress phytohormones (ABA, JA, GA, and ACC) produced by plants in case of soil salt augmentation. The selected potent endophytic bacteria could be exploited and applied to ameliorate the production and salt tolerance of food crops. Lastly, we elucidated deeper advanced technologies including (i) genomics unveiling the plant’s culture-dependent and culture-independent microbiomes, (ii) metabolomics focusing on genes’ metabolic pathways to discover novel secondary metabolites, (iii) transcriptomics studying gene expression, and (iv) proteomics delimiting proteins expressed in stress alleviation. These technologies have been used to understand the plant–bacterial mechanisms of interaction to combat salt stress.

With the price of green energy now more reasonable, users can now produce enough electricity to meet their needs and make a profit by selling the surplus on the underground P2P energy market. For households, energy trading and demand management can reduce electricity costs. However, consumers generally obtain market offers based on their expectations and the forecasts of other households. However, the P2P exchange system is not able to quantify the gap between these offers and the best market. The objective of this paper is to apply deep reinforcement learning techniques to optimal energy trading and demand response (DR) methods within a peer-to-peer (P2P) market. The main objective is to maximize cost reductions. The best approach to achieve this objective was investigated as part of this project. The complexity of domestic energy trading and energy recovery is formally characterized as a partially observable Markov decision process (POMDP). Through decentralized training and performance-based learning, the strategy maximizes policy and value functions. In order to identify the most effective proactive solutions, a comparative analysis is carried out between the two parties. Based on the simulation results, it was observed that implementing the recommended reinforcement learning strategy to optimize peer-to-peer (P2P) energy exchange can lead to a significant improvement in the average household reward. Specifically, the average household reward can be increased by 7.6% and 12.08% by employing the aforementioned approach.

Background: The determination of area tumor presents the chief challenge in brain tumor therapy and assessment. Without ionizing radiation, the medical Magnetic Resonance Imaging (MRI) tool has appeared as an essential diagnostic technique for brain cancers. Using 2D MRI images, manual segmentation of brain tumor size is a slow, error-prone task which the performance is extremely depends on operator's experience. In that respect, a consistent totally automated segmentation approach for the brain tumor detection is effectively needed to get a proficient dimension of the tumor size. Results: In this paper, an effusively computerized scheme for brain tumor detection is proposed by the use of deep convolutional networks. The proposed method was appraised on Brain Tumor Image Segmentation (BRATS 2020) datasets, including 1352 affected by brain tumor. Conclusion: Cross-validation technique has revealed that our process can attain talented segmentation competently reaching higher accuracy compared to other previous studies.

Peer-to-Peer energy trading is becoming increasingly essential and attracting a significant centralized transient energy trading market, an optimization model interest from companies and academics. As a result, new methods of creation and implementation have been developed. The deployment of the consumer concept, which combines residential needs with photovoltaic and battery storage systems, has been proposed as a viable approach to promote the integration of renewable energies with neighboring energy consumers' distribution networks. Therefore, this paper presents an innovative group of grid-connected residential consumers and communities that uses an appropriate MILP method to share, organize and schedule surplus energy generated from distributed energy resources (DER) with neighboring energy consumers/deficit. The energy community investigated in this study consists of four consumers (a residential load and two consumers, a solar PV system and a battery storage system), an energy community manager, and an energy seller, all connected to a distribution network. The proposed market model aims to investigate the economic benefits of renewable energy sources participating in centralized transit energy trading. A centralized strategy is used in transit energy trading between 10 proactive consumers and the energy network, with the energy community manager overseeing trading operations in the energy community. In the centralized transient energy trading market, an optimization model is proposed to increase the financial benefits of rooftop solar PV/ESS systems.

This is a case report about a 44-year-old woman who sustained multiple stab wounds, resulting in an isolated right ureteral injury. Despite a precise diagnosis from an urgent CT scan showing contrast material extravasation, the patient's stable vital signs allowed for a thorough surgical exploration, leading to an accurate diagnosis. Immediate surgical repair of the right ureter using an end-to-end anastomosis following precise surgical principles achieved complete restoration of the initial injuries. The case highlights the accuracy of CT scan assessment, the unreliability of hematuria in diagnosing ureteral injuries, and the need for a high index of suspicion during surgical exploration to avoid overlooking such cases.

Key Clinical Message Currently, there is no consensus on the optimal management of nonmetastatic Ewing's sarcoma of the mobile spine. However, associated to chemotherapy, aggressive surgery with en bloc wide resection seems to improve local control and survival. Abstract Primary Ewing's sarcoma (EWS) of non‐sacral spine is extremely rare, especially in middle‐age. Therapeutic strategy aims: to large tumor resection, to provide spine stability and to avoid recurrence through chemo and radiotherapy. We report a case of thoracic spine EWS in an adult treated by combined approach en bloc vertebrectomy.

The Indoor Household Environment (IHE) has caught the attention of industry and academia due to the substantial amount of time that families spend indoors. Domestic air pollution imposes significant burdens on communities, although both indoor and outdoor sources of air pollution contribute to outdoor pollution. This article presents a precise approach for an Intelligent Home Energy Management System (IHEMS) that integrates Deep Reinforcement Learning (DRL) and Demand Response (DR) techniques. IHEMS employs Markov decision processes to handle problems and concerns efficiently. A novel approach has been developed to enhance the efficiency of deep reinforcement learning control, utilizing a double deep Q network and a restart strategy during a priority event. Unlike the HEMS technique, which uses a predictive control model, the optimal strategy resulted in a 20% decrease in monthly power consumption.

Keratinizing squamous metaplasia of the renal pelvis is a rare lesion of the upper urinary tract that can occur in the context of chronic aggression to the urothelium, potentially leading to a secondary pyeloureteral junction syndrome.We report the case of a 43-year-old patient discovered intraoperatively in relation to a renal pelvis stone causing a pyeloureteral junction syndrome. The extemporaneous histological examination ruled out a malignant process, and we performed a pyeloplasty according to KUSS-ANDERSON technique. This pathology should be recognized by the urologist for appropriate management. Treatment is conservative, with extended follow-up to detect recurrences or carcinomatous degenerations.

This is a case report about a patient presenting with a urachal mass mimicking a urachus adenocarcinoma. Cystoscopy showed a vesicourachal patent diverticulum. Histological findings after the removal of the umbilicus, urachus, urachal tumor, as well as a bladder cuff, consisted of a nonspecific polymorphous suppurative inflammatory infiltrate. Urachal adenocarcinoma is an aggressive tumor with poor prognosis if not treated while it is still localized. Surgical excision is the only recommended treatment that offers the best chances of survival. As no preoperative procedure has been proven accurate enough to rule out the diagnosis of adenocarcinoma, surgery appears to be inevitable.

With about 110 cases reported in literature, juxtaglomerular cell tumors are rare. We report a 25 years old patient who was admitted in neurology for a hemorrhagic stroke secondary to a cerebral aneurysm rupture due to high blood pressure. Etiological investigations showed a solid mass of the left kidney. A radical nephrectomy was realized and pathological examination and immunohistochemical profile concluded to juxtaglomerular cell tumor. The originality of this observation is based on the mode of presentation of a rare renal tumor by a malignant high blood pressure.

Aim: We aimed in this study to evaluate the impact of inflammatory bowel disease (IBD) on patients’ professional life and to determine predictors of severe work productivity loss (WPL). Materials & methods: A cross sectional study including patients with a confirmed diagnosis of IBD. Work productivity was evaluated with the work productivity and activity impairment score. Results: Severe absenteeism and WPL were found in respectively 7 (5.1%) and 54 (39.1%) patients. In multivariate analysis, the following features were found to be independently associated with severe WPL: penetrating Crohn’s disease (p: 0.001, OR: 6), anemia (p: 0.031, OR: 3.23), diarrhea (p

IntroductionUnilateral primary aldosteronism (UPA) is the most frequent surgically curable form of endocrine hypertension. Adrenalectomy is the cornerstone of treatment for UPA, but outcomes after surgery are variable. The cause of resistant hypertension after surgery is still a matter of debate. Our aim was to investigate cure rates after surgery and to evaluate preoperative factors that might influence the surgical outcome.MethodsBetween 2000 and 2021, the charts of 71 Tunisian patients who underwent laparoscopic adrenalectomy for UPA were retrospectively reviewed. Preoperative medical records were collected and follow-up data (1-158 months) were registered. Antihypertensive medication doses were calculated using defined daily doses (DDD) and postoperative outcomes were assessed using the Primary Aldosteronism Surgical Outcome (PASO) criterion.ResultsOf 91 enrolled patients, 71 (59% women, mean age 46 years, median length of follow-up 21 months) were suitable for evaluation. Thirty-four patients (48%) had complete clinical success according to the PASO criteria. The most relevant factors associated with complete clinical success on univariate analysis were: absence of diabetes (p= 0.007), low body mass index (BMI) (p= 0.001), lower preoperative DDD (p= 0.01), preoperatively controlled blood pressure (p= 0.024), higher plasma aldosterone to renin ratio (ARR) (p= 0.001), adenoma subtyping (p 332 (OR: 4.554) and an ARS ≥ 3 (OR: 2.056).ConclusionComplete and partial clinical response rates were achieved in respectively 48 and 43% of cases. The main predictors of complete resolution of hypertension were absence of diabetes, low BMI, high plasma ARR and high ARS. Taking these factors into account may help identify patients at risk of persistent postoperative hypertension who may require long-term surveillance and medication.

Selective laser melting (SLM) presents significant assets for both industrial and academic fields. However, the process parameters selection is yet challenging. It presents tens of parameters to be carefully selected, including laser power and speed, bed thickness, hatching space, and other parameters, for the manufacturing of parts with high density. This paper provides a deeper understanding of the processing parameters’ effect on the evolution of the product’s density. A series of numerical simulations of porosity is achieved on Ansys Additive© software and it shows the evolution of the relative density at different laser powers and scan speeds. Numerical results show that low laser power and accelerated scan lead to the generation of a small melt pool, and consequently low density. In the opposite case, at high power and slow scan, the created melt pool is wide enough to avoid porosity and generate fully dense products. The product density is proportionally related to the melt pool size. Hence, it could be estimated through the correlation with the melt pool width, which enables the perfect selection of the hatching space for the selected set of parameters.