Integrative Approach to Risk Factors in Simple Chronic Obstructive Airway Diseases of the Lung or Associated with Metabolic Syndrome-Analysis and Prediction.

We conducted an epidemiological non-interventional cross-sectional and case-control study from 1 January 2023 until 26 May 2023 in Oltenia region, southwestern Romania. Throughout the research, 160 consecutive patients were included from two different clinical departments (1-Pneumology; 2-Diabetes and Nutritional Diseases). Subjects were voluntary adult individuals of any gender who expressed their written consent. The clinical data of the patients were correlated with the exposure to behavioral risk factors (diet, lifestyle, exposure to pollutants) to identify some negative implications that could be corrected to improve the quality of life of patients with simple chronic obstructive airway diseases of the lung or associated with metabolic syndrome (MS). In the first group of patients with respiratory diseases, there was a higher degree of exposure to toxic substances (43.75%) compared to the second group of patients with diabetes (18.75%); it is also noticeable that in the first group, there were noticeably fewer individuals who have never smoked (25%) compared to the second group (50%). Respiratory function impairment was observed to be more severe in overweight individuals. In the group of patients with known lung diseases, a positive correlation was noted between the presence of MS and respiratory dysfunctions of greater severity. Additionally, potential exacerbating factors affecting lung function, such as direct exposure to toxins and smoking, were considered. Potential secondary factors exacerbating respiratory dysfunction were considered by correlating biochemical parameters with dietary habits. These included reduced consumption of vegetables, inadequate hydration, and increased intake of sweets and products high in saturated or trans fats (commonly found in junk food), primarily due to their potential contribution to excess weight. Compared to patients without MS, the severity of the pulmonary function impairment correlated with the number of criteria met for MS and, independently, with an increase in weight.

Assessment of Behavioral Risk Factors in Chronic Obstructive Airway Diseases of the Lung Associated with Metabolic Syndrome.

BACKGROUND: Diet and lifestyle play important roles in preventing and improving chronic diseases, and evaluating behavioral risk factors in these pathologies allows for efficient management. METHODS: A clinical study by screening biochemical parameters and pulmonary function was carried out to evaluate behavioral risk factors in obstructive pulmonary disease associated with metabolic syndrome. RESULTS: Of the total of 70 patients included in the clinical study, 46 were men and 24 were women (χ2 = 3.9, p = 0.168). Forty-eight patients presented at least three met risk criteria associated with the metabolic syndrome (19 women and 29 men). Regarding the assessment of lung function, only 7 of the patients presented normal spirometry values (χ2 = 75.28, p < 0.001), and the other 63 patients presented with ventilatory dysfunction; most (over 80%) declared that they were smokers or had smoked in the past (χ2 = 5.185, p = 0.075). In terms of body weight, 45 of the patients are overweight or obese, most of them declaring that they do not consume enough vegetable products, they consume large amounts of foods of animal origin (meat, milk, eggs) but also super processed foods (food products type of junk food), do not hydrate properly, and are predominantly sedentary people (54 of the patients do no physical activity at all; χ2 = 2.12, p = 0.713). CONCLUSION: From the statistical processing of the data, it is noted that insufficient hydration, low consumption of vegetables, increased consumption of hyper-caloric food products rich in additives, sedentary lifestyle, and smoking are the main disruptive behavioral factors that worsen the health status in lung disease associated with the metabolic syndrome. An important conclusion emerging from the study is that the imbalances that aggravate obstructive lung diseases are generated by unhealthy food and an unbalanced lifestyle.

Diagnostic Performance of an Artificial Intelligence Model Based on Contrast-Enhanced Ultrasound in Patients with Liver Lesions: A Comparative Study with Clinicians.

Contrast-enhanced ultrasound (CEUS) is widely used in the characterization of liver tumors; however, the evaluation of perfusion patterns using CEUS has a subjective character. This study aims to evaluate the accuracy of an automated method based on CEUS for classifying liver lesions and to compare its performance with that of two experienced clinicians. The system used for automatic classification is based on artificial intelligence (AI) algorithms. For an interpretation close to the clinical setting, both clinicians knew which patients were at high risk for hepatocellular carcinoma (HCC), but only one was aware of all the clinical data. In total, 49 patients with 59 liver tumors were included. For the benign and malignant classification, the AI model outperformed both clinicians in terms of specificity (100% vs. 93.33%); still, the sensitivity was lower (74% vs. 93.18% vs. 90.91%). In the second stage of multiclass diagnosis, the automatic model achieved a diagnostic accuracy of 69.93% for HCC and 89.15% for liver metastases. Readers demonstrated greater diagnostic accuracy for HCC (83.05% and 79.66%) and liver metastases (94.92% and 96.61%) compared to the AI system; however, both were experienced sonographers. The AI model could potentially assist and guide less-experienced clinicians to discriminate malignant from benign liver tumors with high accuracy and specificity.

Preoperative Immunocyte-Derived Ratios Predict Postoperative Recovery of Gastrointestinal Motility after Colorectal Cancer Surgery.

The aim of this study was to assess the role of immunocyte-derived ratios (IDRs), such as the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR), as markers for the postoperative recovery of gastrointestinal function following colorectal cancer surgery. A retrospective analysis was conducted on a consecutive cohort of 260 patients who underwent radical colorectal cancer surgery within the timeframe spanning from January 2016 to December 2022. Data concerning the postoperative recovery of gastrointestinal function included the I-FEED score, time to pass flatus, toleration for liquids in the first 48 h, and the need for nasogastric tube reinsertion in the immediate postoperative period. A special emphasis was allocated towards the examination of IDRs and their interrelation with the postoperative gastrointestinal functional parameters. The I-FEED score exhibited a positive correlation with the NLR, SII, and PLR. The univariate analysis indicated that all IDRs, multiorgan resection, hemoglobin and protein levels, regional nodal extent of the tumor (N), and obesity significantly affected nasogastric tube reinsertion. The multivariate analysis showed that the SII and N1 stages were risk factors for nasogastric tube reinsertion after colorectal cancer surgery. The SII and multiorgan resection were the only classifiers that remained significant in the multivariable analysis for the toleration for liquids. In summation, certain preoperative IDRs, such as the SII, PLR, and NLR, may hold potential as predictive determinants for postoperative gastrointestinal functional recovery following colorectal cancer surgery.

An Automated Method for Classifying Liver Lesions in Contrast-Enhanced Ultrasound Imaging Based on Deep Learning Algorithms.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) is an important imaging modality in the diagnosis of liver tumors. By using contrast agent, a more detailed image is obtained. Time-intensity curves (TIC) can be extracted using a specialized software, and then the signal can be analyzed for further investigations. METHODS: The purpose of the study was to build an automated method for extracting TICs and classifying liver lesions in CEUS liver investigations. The cohort contained 50 anonymized video investigations from 49 patients. Besides the CEUS investigations, clinical data from the patients were provided. A method comprising three modules was proposed. The first module, a lesion segmentation deep learning (DL) model, handled the prediction of masks frame-by-frame (region of interest). The second module performed dilation on the mask, and after applying colormap to the image, it extracted the TIC and the parameters from the TIC (area under the curve, time to peak, mean transit time, and maximum intensity). The third module, a feed-forward neural network, predicted the final diagnosis. It was trained on the TIC parameters extracted by the second model, together with other data: gender, age, hepatitis history, and cirrhosis history. RESULTS: For the feed-forward classifier, five classes were chosen: hepatocarcinoma, metastasis, other malignant lesions, hemangioma, and other benign lesions. Being a multiclass classifier, appropriate performance metrics were observed: categorical accuracy, F1 micro, F1 macro, and Matthews correlation coefficient. The results showed that due to class imbalance, in some cases, the classifier was not able to predict with high accuracy a specific lesion from the minority classes. However, on the majority classes, the classifier can predict the lesion type with high accuracy. CONCLUSIONS: The main goal of the study was to develop an automated method of classifying liver lesions in CEUS video investigations. Being modular, the system can be a useful tool for gastroenterologists or medical students: either as a second opinion system or a tool to automatically extract TICs.

Genomic Profiling - A Need for Clinical Decision? -Case Reports.

Cancer is still an important health issue worldwide due to increased incidence and mortality. Personalized medicine is the future of cancer treatment. Development in technology improved technical skills in DNA/RNA sequencing. NGS technology in solid-tumor samples can describe DNA or RNA analysis by including the entire genome to detect clinical relevant mutations. Genetic results may be considered having a dynamic impact because of heterogenous molecular alterations depending of time and treatment influence. We conducted a retrospective study of all NGS tests made in the last five years for the patients from 'Sf. Nectarie' Oncology Center, Craiova, Romania. We selected three relevant clinical cases where NGS analysis was performed and the results changed the perspective of the clinical decision. Our aim is to evaluate the importance of NGS results in clinical approach. Although medicine known an important development during the last decades, only a few patients can benefit of advanced personalized treatments. It is still hard to identify the alterations or gene mutations because of genetic tests are not easily available and only a small proportion of patients carries genetic alterations.

Probe - Based Confocal Endomicroscopy and Endoscopy in NBI Module - The Role in Clinical Decision - Case Reports.

Cancer remains a significant global cause of mortality, irrespective of a country's level of development. Among all cancer types, gastrointestinal cancers claim the highest number of lives annually. This disease predominantly affects individuals in their 6th to 8th decades of life. Unfortunately, diagnoses often occur during advanced stages of the illness, rendering chemotherapy less effective and offering a reserved prognosis. Conventional endoscopy, however, struggles to differentiate lesions based on their histological composition. Consequently, the management of patients largely depends on histopathological examinations, which can be time-consuming. Biopsy results are sometimes delayed, with precious weeks passing, particularly critical for patients with malignant lesions. Moreover, biopsies may yield inconclusive results if not precisely targeted, leading to potential mismanagement, unnecessary resections and burdensome pathology services. This series of cases underscores, as previous studies have, the value of modern endoscopic techniques in determining the appropriate therapeutic approach for each patient, an approach that ensures the highest quality of life.

Deep Learning Algorithms in the Automatic Segmentation of Liver Lesions in Ultrasound Investigations.

BACKGROUND: The ultrasound is one of the most used medical imaging investigations worldwide. It is non-invasive and effective in assessing liver tumors or other types of parenchymal changes. METHODS: The aim of the study was to build a deep learning model for image segmentation in ultrasound video investigations. The dataset used in the study was provided by the University of Medicine and Pharmacy Craiova, Romania and contained 50 video examinations from 49 patients. The mean age of the patients in the cohort was 69.57. Regarding presence of a subjacent liver disease, 36.73% had liver cirrhosis and 16.32% had chronic viral hepatitis (5 patients: chronic hepatitis C and 3 patients: chronic hepatitis B). Frames were extracted and cropped from each examination and an expert gastroenterologist labelled the lesions in each frame. After labelling, the labels were exported as binary images. A deep learning segmentation model (U-Net) was trained with focal Tversky loss as a loss function. Two models were obtained with two different sets of parameters for the loss function. The performance metrics observed were intersection over union and recall and precision. RESULTS: Analyzing the intersection over union metric, the first segmentation model obtained performed better compared to the second model: 0.8392 (model 1) vs. 0.7990 (model 2). The inference time for both models was between 32.15 milliseconds and 77.59 milliseconds. CONCLUSIONS: Two segmentation models were obtained in the study. The models performed similarly during training and validation. However, one model was trained to focus on hard-to-predict labels. The proposed segmentation models can represent a first step in automatically extracting time-intensity curves from CEUS examinations.

Diagnosis of lung cancer by flexible fiberoptic bronchoscopy: a descriptive study.

Flexible fiberoptic bronchoscopy (FFB) remains the most important minimally invasive method for the diagnosis of lung cancer (LC). We performed a retrospective study to assess the main endoscopic findings of malignant lung tumors in the large airways in a cohort of Romanian patients. The group consisted of 32 (84.21%) men and six (15.78%) women, with an average age of 64.63±6.07 years. The bronchoscopic examination allowed the detection and biopsy of 36 malignant lung tumors, and in two other cases, due to malignant atelectasis, the patients were sent to a Department of Thoracic Surgery, to perform the biopsy following the surgery. Histopathological (HP) examination revealed the presence of squamous cell carcinoma (SCC) in 19 (50%) patients, adenocarcinoma (ADC) in 11 (28.94%) patients and small cell lung cancer (SCLC) in eight (21.05%) patients. The macroscopic and microscopic analysis of the lung tumors showed that infiltrative forms were found in most cases (58.33%), followed by exophytic (mass) endobronchial lesions (22.22%) and mixed forms (19.44%). If most infiltrative forms were SCC (66.66%), the exophytic and mixed lesions were most frequently ADC (50% and 57.14%). The tumor lesions caused both malignant bronchial stenosis (57.89%) and malignant atelectasis (42.1%). The main mechanisms involved in bronchial malignant obstruction were endoluminal (50%), mixed (31.57%) and extraluminal (18.42%) mechanisms. In conclusion, FFB remains the main method of diagnosing LC in the large airways. The most common macroscopic appearance of lung tumors revealed by bronchoscopy was the infiltrative appearance. In half of our patients, the malignant bronchial obstruction was achieved by endoluminal mechanism. The most common pathological form found in our patients was the SCC, as described in half of the investigated patients.

Resource Management through Artificial Intelligence in Screening Programs-Key for the Successful Elimination of Hepatitis C.

BACKGROUND: The elimination of the Hepatitis C virus (HCV) will only be possible if rapid and efficient actions are taken. Artificial neural networks (ANNs) are computing systems based on the topology of the biological brain, containing connected artificial neurons that can be tasked with solving medical problems. AIM: We expanded the previously presented HCV micro-elimination project started in September 2020 that aimed to identify HCV infection through coordinated screening in asymptomatic populations and developed two ANN models able to identify at-risk subjects selected through a targeted questionnaire. MATERIAL AND METHOD: Our study included 14,042 screened participants from a southwestern region of Oltenia, Romania. Each participant completed a 12-item questionnaire along with anti-HCV antibody rapid testing. Hepatitis-C-positive subjects were linked to care and ultimately could receive antiviral treatment if they had detectable viremia. We built two ANNs, trained and tested on the dataset derived from the questionnaires and then used to identify patients in a similar, already existing dataset. RESULTS: We found 114 HCV-positive patients (81 females), resulting in an overall prevalence of 0.81%. We identified sharing personal hygiene items, receiving blood transfusions, having dental work or surgery and re-using hypodermic needles as significant risk factors. When used on an existing dataset of 15,140 persons (119 HCV cases), the first ANN models correctly identified 97 (81.51%) HCV-positive subjects through 13,401 tests, while the second ANN model identified 81 (68.06%) patients through only 5192 tests. CONCLUSIONS: The use of ANNs in selecting screening candidates may improve resource allocation and prioritize cases more prone to severe disease.

Depressive and Anxious Symptoms in Hepatitis C Virus Infected Patients Receiving DAA-Based Therapy.

Hepatitis C virus (HCV) represents the most important etiologic factor for advanced fibrosis/cirrhosis and hepatocellular carcinoma associated with a psychological dimension. Our study aims to assess, on a sample comprising of 90 HCV-infected subjects (96.67% F3-F4 METAVIR), the relationship between Direct-Acting Antiviral (DAA) therapies and the psychological effects of the liver disease, focused on the anxious and depressive symptoms. The comprehensive evaluation was done before starting the DAA treatment (BSL), after 12 weeks (End of Treatment-EOT), respectively after another 12 weeks (Sustained Viral Response-SVR). Presumable depressive and/or anxious symptoms were evaluated by Hospital Anxiety and Depression Scale (HADS). The reported depressive symptoms decreased from 21.11% (BSL) to 1.11% (SVR) (p < 0.00001), while the anxious ones dropped from 43.34% (BSL) to 4.44% (SVR) (p < 0.00001), without a clear evolutionary pattern. We identified no statistically significant interaction between comorbidities (anemia, CKD, obesity) over HADS scores evolution (p > 0.05), while the DAAs side-effects (fatigue, headache, pruritus) significantly influenced the anxious and depressive symptoms (p < 0.05). During and after the DAA-based therapy, patients with HCV infection presented a significantly reduced rate of the associated depressive and anxious relevant symptoms.

Micro-Elimination: Updated Pathway to Global Elimination of Hepatitis C in Small Communities and Industrial Settings during the COVID 19 Pandemic.

BACKGROUND: In response to the goal of the World Health Organisation to eliminate hepatitis C virus infections by 2030, Romania is striving for national elimination. An already successful micro-elimination project was expanded to test-and-treat specific populations and at-risk groups. The aim of this project was to identify the individuals with HCV infection in disadvantaged regions who do not have proper medical care access. MATERIALS AND METHODS: Our two-arm interventional cross-sectional study used rapid anti-HCV antibody testing on two population groups from the Romanian southwestern region of Oltenia, approached between September 2020 and May 2021. The first group consisted of predominantly over 40 years old individuals, recruited through five family doctors from two medium-sized towns (community lot-CL). We approached a second group, aged 18-65, through 11 medical offices of five large factories in the same region (industry lot, IL). A 12-items questionnaire was given to each participant, to determine risk factors and record demographic data. Eligible patients initiated antiviral therapy using direct-acting antivirals (DAAs). RESULTS: We enrolled 15,383 individuals between all 16 locations. The overall prevalence by antibody testing was 0.77% (119 cases). Of these, 57 subsequently received treatment with DAAs. We identified blood transfusions as a risk factor within the CL. Participants in the IL reported a relatively high risk for the following situations: sharing of personal hygiene belongings with another person, performing previous blood transfusions, dental interventions and previous surgery. CONCLUSIONS: In this global context, the use of micro-elimination allows interventions to be faster and more efficient. This is possible by targeting smaller and specific HCV risk groups.

Deep Learning: a Promising Method for Histological Class Prediction of Breast Tumors in Mammography.

The objective of the study was to determine if the pathology depicted on a mammogram is either benign or malignant (ductal or non-ductal carcinoma) using deep learning and artificial intelligence techniques. A total of 559 patients underwent breast ultrasound, mammography, and ultrasound-guided breast biopsy. Based on the histopathological results, the patients were divided into three categories: benign, ductal carcinomas, and non-ductal carcinomas. The mammograms in the cranio-caudal view underwent pre-processing and segmentation. Given the large variability of the areola, an algorithm was used to remove it and the adjacent skin. Therefore, patients with breast lesions close to the skin were removed. The remaining breast image was resized on the Y axis to a square image and then resized to 512 × 512 pixels. A variable square of 322,622 pixels was searched inside every image to identify the lesion. Each image was rotated with no information loss. For data augmentation, each image was rotated 360 times and a crop of 227 × 227 pixels was saved, resulting in a total of 201,240 images. The reason why our images were cropped at this size is because the deep learning algorithm transfer learning used from AlexNet network has an input image size of 227 × 227. The mean accuracy was 95.8344% ± 6.3720% and mean AUC 0.9910% ± 0.0366%, computed on 100 runs of the algorithm. Based on the results, the proposed solution can be used as a non-invasive and highly accurate computer-aided system based on deep learning that can classify breast lesions based on changes identified on mammograms in the cranio-caudal view.

Retrospective Study of Lung Tumor Cases Presenting at a Large Tertiary Hospital in Romania between 2017 and 2020.

Lung cancer is a major health concern worldwide. A rise in smoking incidence amongst both genders, increased exposure to air pollutants and unhealthy lifestyle choices steadily contribute to this global situation. Our aim was to assess the main characteristics of this type of cancer through a retrospective analysis at a major referral center. We selected valid and complete electronic medical records of patients admitted between 2017 and 2020 at the Emergency County Hospital of Craiova, one of the largest hospitals in Romania and a major referral center for the region of Oltenia. We obtained ethical approval from both the hospital and the University and analyzed anonymized records by ICD-10 diagnostic code, extracting gender and age data, as well as associated conditions, length of stay, as well as the medical departments where the patient was hospitalized. Our results showed an increased incidence amongst men, with the majority of cases between 50 and 70 years of age. Median hospitalization period was of 6 days, with higher values for oncology and the lowest in thoracic surgery. Distant metastases, pleurisy and hemoptysis were the most prevalent comorbidities encountered. In conclusion, our study presents important data on the main characteristics of lung cancer patients in Romania.

Deep learning with transfer learning in pathology. Case study: classification of basal cell carcinoma.

Establishing basal cell carcinoma (BCC) subtype is sometimes challenging for pathologists. Deep-learning (DL) algorithms are an emerging approach in image classification due to their performance, accompanied by a new concept - transfer learning, which implies replacing the final layers of a trained network and retraining it for a new task, while keeping the weights from the imported layers. A DL convolution-based software, capable of classifying 10 subtypes of BCC, was designed. Transfer learning from three general-purpose image classification networks (AlexNet, GoogLeNet, and ResNet-18) was used. Three pathologists independently labeled 2249 patches. Ninety percent of data was used for training and 10% for testing on 100 independent training sequences. Each of the resulted networks independently labeled the whole dataset. Mean and standard deviation (SD) accuracy (ACC) [%]∕sensitivity (SN) [%]∕specificity (SP) [%]∕area under the curve (AUC) for all the networks was 82.53±2.63∕72.52±3.63∕97.94±0.3/0.99. The software was validated on another 50-image dataset, and its results are comparable with the result of three pathologists in terms of agreement. All networks had similar classification accuracies, which demonstrated that they reached a maximum classification rate on the dataset. The software shows promising results, and with further development can be successfully used on histological images, assisting pathologists' diagnosis and teaching.

E-cadherin and aquaporin 1 co-expression analysis in hepatocellular carcinoma: a pilot study.

Hepatocellular carcinoma (HCC) is the main primary liver malignancy, being associated with both health and economic burden worldwide. Recently, novel molecular markers and possible therapeutic targets were identified. Different adhesion molecules, as well as possible angiogenesis-associated targets can be prime candidates when investigating novel therapies. Considering these premises, our goal was to study the co-existence of E-cadherin and aquaporin 1 (AQP1) in a series of HCC diagnosed patients. Utilizing archived tissue fragments from 17 patients diagnosed with well-to-moderate and poorly differentiated HCC, as well as four samples of normal liver tissue and using a highly specific biotin-free tyramide amplification technique, we have assessed here the expression of E-cadherin and AQP1 during HCC carcinogenesis. Moreover, as we have observed that some of the AQP1 expression seems membrane-bound, we have sought to evaluate their co-localization. Our data showed, as expected, that E-cadherin decreases from control tissue to low-grade and respectively, high-grade HCC. AQP1 was expressed, also as already known, at the level of endothelial blood vessels and bile ducts epithelia, however, we have showed here for the first time that this water pore is also expressed in the cytoplasm and membranes of hepatocytes, both in control and HCC tissue. Moreover, AQP1 expression parallels the decrease of E-cadherin expression during carcinogenesis, but together with this downregulation, we have also found a spatial decrease in the colocalization of the two proteins. Altogether, utilizing a biotin-free tyramide signal amplification technique, this study shows for the first time that AQP1 is expressed at the level of liver epithelia, in both control and HCC tissue.

Association between Risk Factors and the Existence of Lung Malignancies in a Population from the South-West Romania: A Single-Center Study.

INTRODUCTION: Lung cancer, one of the most prominent malignancies of today worldwide, affects mainly men; however, recently women have also been increasingly afflicted by the disease. Our aim was to retrospectively analyze a series of potential risk factors for the disease and their potential to affect both genders. METHODS: Our retrospective study relied on anonymized data collected between 2017 and 2020 at a single hospital specialized on lung diseases. After receiving ethical clearance, data pertaining to risk factors as well as statistical aspects of the lot were recorded and analyzed. RESULTS: We found 493 patients (398 men) aged between 31 and 90 years (median 67) who were found with lung tumors and selected a matched cohort of patients with other diseases. We found positive associations between the presence of smoking, COPD, or pollution and the occurrence of lung cancer. Almost all lung cancer patients presented different significant associated diseases. Family history also favored the appearance of lung cancer. CONCLUSION: Several risk factors remain high in lung tumor patients, and rapid measures to diminish the impact of such factors are needed in order to decrease the overall incidence of this pathology.

The Effect of Silver Nanoparticles on Antioxidant/Pro-Oxidant Balance in a Murine Model.

This study aimed to evaluate the subacute effect of two types of Ag-NPs(EG-AgNPs and PVP-EG-AgNPs) on antioxidant/pro-oxidant balance in rats. Seventy Wistar rats (35 males and 35 females) were divided in 7 groups and intraperitoneally exposed for 28 days to 0, 1, 2 and 4 mg/kg bw/day EG-Ag-NPs and 1, 2 and 4 mg/kg bw/day PVP- EG-Ag-NPs. After 28 days, the blood was collected, and the total antioxidant capacity (TAC), thiobarbituric reactive species (TBARS),protein carbonyl (PROTC) levels, reduced glutathione (GSH) levels and catalase (CAT) activity were determined. EG-Ag-NPs determined protective antioxidant effects in a dose-dependent manner. The exposure to the 4 mg/kg bw/day EG-Ag-NPs determines both in males and females a significant increase in TAC and CAT and a significant decrease in TBARS and PROTC only in females. The PVP-EG-AgNPs showed a different trend compared to EG-AgNPs. At 4 mg/kg bw/day the PVP-EG-AgNPs induce increased PROTC levels and decreased GSH (males and females) and TAC levels (males). The different mechanisms of EG-AgNPs and PVP-EG-AgNPs on antioxidant-/pro-oxidant balance can be explained by the influence of coating agent used for the preparation of the nanoparticles in the formation and composition of protein corona that influence their pathophysiology in the organism.

Value of endoscopy with narrow-band imaging and probe-based confocal laser endomicroscopy in the diagnosis of preneoplastic lesions of gastrointestinal tract.

INTRODUCTION: Amongst all malignant tumors, cancers of the digestive tract rank first in terms of yearly deaths. Patients above 60 years of age are the most affected, as the diagnosis is frequently made in advanced stages of the disease when therapy is less effective. Our study aimed to evaluate the efficiency of narrow-band imaging (NBI) endoscopy and probe-based confocal laser endomicroscopy (pCLE) in the correct diagnosis of preneoplastic lesions in the upper and lower digestive tract. PATIENTS, MATERIALS AND METHODS: We included 46 patients with digestive preneoplastic lesions, who underwent either upper or lower digestive endoscopy, followed by NBI and pCLE. We recorded 5-10 frames per each lesion, from different angles and distances during white-light endoscopy and selected frames from full recordings of NBI and pCLE. Usual preparation was used for the endoscopic procedures; pCLE required in vivo administration of 10% Sodium Fluorescein as a contrast agent. Pathology was performed in case of solid tumors. Three medical professionals with different levels of training, blinded to the results, interpreted the data. RESULTS: The experienced physician correlated very well the NBI findings with pathology (0.93, p=0.05), while the resident physician and the experienced nurse obtain lower, albeit still statistically significant, values (0.73 and 0.62, respectively). For pCLE, the experienced physician obtained near-perfect correlation with pathology (0.96), followed closely by the resident physician (0.93). The nurse obtained a modest correlation (0.42). All examiners obtained approximately equal performances in discerning between malignant and benign lesions. CONCLUSIONS: Digestive endoscopy in NBI mode proved its effectiveness. Even less experienced endoscopists can achieve good results, while an experienced nurse can positively influence the diagnosis. In the case of pCLE, when available, it can greatly reduce diagnostic times, while requiring higher expertise and specialty training.

The quality of colorectal polypectomy. Is it enough to have just a visual assessment of the site?

INTRODUCTION: Performing a colonoscopy allows the examination of the entire colon and the assessment of polyps. PATIENTS, MATERIALS AND METHODS: We performed a retrospective analysis of prospectively collected data from January 2018 until February 2020 (two years), in which we enrolled a number of 210 patients performing colonoscopy in the Research Center of Gastroenterology and Hepatology, University of Medicine and Pharmacy of Craiova, Romania. We performed 326 polypectomies. RESULTS: We classified the polyps into diminutive (n=169), small (n=103) and large polyps (n=54). Regarding the polypectomy technique, our results indicated that 40 out of 48 (83.3%) polypectomies with the biopsy forceps were complete, as well as 27 out of 31 (87.1%) cold snare polypectomies and 12 out of 14 (85.7%) hot snare polypectomies. The differences were not statistically significant (p=0.116). Regarding the number of incomplete polypectomies, our data suggests that the high expertise endoscopist had two incomplete resections (5.1% of total), the medium expertise endoscopist 1 had also two incomplete resections (11.1% of total), the medium expertise endoscopist 2 had three incomplete resections (15% of total), the limited expertise endoscopist 1 had three incomplete resections (27.27% of total) and the limited expertise endoscopist 2 had four incomplete resections (30.76% of total). Analyzing the data, the differences were statistically significant (p=0.006). CONCLUSIONS: Our study is able to suggest that high-definition white-light endoscopy (HD-WLE) macroscopic visualization of the polyp resection site is not enough to assess complete polyp resection and follow-up colonoscopy should be performed for cases with incomplete margins of resection.