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Introduction: Any alteration in nutritional status can compromise the progression of breast cancer, as well as the tolerance and efficacy of chemotherapy. The aims of our study were to assess the nutritional status of breast cancer patients treated with chemotherapy and to identify nutritional factors that may exacerbate chemo-induced digestive toxicity. Methods: This descriptive cross-sectional study was conducted within the medical oncology department of the National Institute of Salah Azaiez. A Mediterranean Diet Score (MDS) was used to evaluate the level of adherence to the Mediterranean Diet. Nutritional status was assessed using 2 methods; body composition evaluation utilising the TANITA BC 601 impedance metre and High authority of health (HAS) criteria of malnutrition. Digestive effects were assessed with World Health Organization (WHO) grades ranging from 0 to 4. High grades 3 and 4 signified toxic grades. Results: We enrolled 107 adult women diagnosed with breast cancer undergoing the same chemotherapy protocol. The participants had an average age of 52.56 ± 9.75 years and an average BMI of 29.85 ± 5.72 kg/m2 with 78.5% classified as overweight. Malnutrition was observed in 41% of patients, while sarcopenia was present in 12%. Chemotherapy-related adverse effects were predominantly constipation (80%), diarrhea (73%), nausea (70%) and vomiting (63.4%) with one-third experiencing high-grade toxicity. Strong adherence to Mediterranean Diet was observed in 48.6% of cases and higher MDS scores were inversely correlated with the severity of nausea (P =.01) and constipation (P =.02). Malnutrition was significantly associated with all digestive toxicities except with constipation. Sarcopenia was associated only with vomiting (P =.005). Conclusion: There is a relationship between nutritional status and digestive toxicity, justifying early nutritional treatment to improve the tolerance and efficacy of chemotherapy. [ABSTRACT FROM AUTHOR]

Tissue hysteresivity is an important marker for determining the onset and progression of respiratory diseases, calculated from forced oscillation lung function test data. This study aims to reduce the number and duration of required measurements by combining multivariate data from various sensing devices. We propose using the Forced Oscillation Technique (FOT) lung function test in both a low-frequency prototype and the commercial RESMON device, combined with continuous monitoring from the Equivital (EQV) LifeMonitor and processed by artificial intelligence (AI) algorithms. While AI and deep learning have been employed in various aspects of respiratory system analysis, such as predicting lung tissue displacement and respiratory failure, the prediction or forecasting of tissue hysteresivity remains largely unexplored in the literature. In this work, the Long Short-Term Memory (LSTM) model is used in two ways: (1) to estimate the hysteresivity coefficient η using heart rate (HR) data collected continuously by the EQV sensor, and (2) to forecast η values by first predicting the heart rate from electrocardiogram (ECG) data. Our methodology involves a rigorous two-hour measurement protocol, with synchronized data collection from the EQV, FOT, and RESMON devices. Our results demonstrate that LSTM networks can accurately estimate the tissue hysteresivity parameter η , achieving an R 2 of 0.851 and a mean squared error (MSE) of 0.296 for estimation, and forecast η with an R 2 of 0.883 and an MSE of 0.528, while significantly reducing the number of required measurements by a factor of three (i.e., from ten to three) for the patient. We conclude that our novel approach minimizes patient effort by reducing the measurement time and the overall ambulatory time and costs while highlighting the potential of artificial intelligence methods in respiratory monitoring. [ABSTRACT FROM AUTHOR]

Little research has been carried out in terms of modeling and control of analgesia. However, emerging new technology and recent prototypes paved the way for several ideas on pain modeling for control. Recently, such an idea has been proposed for measuring the Depth of Analgesia (DoA). In this paper, that solution is further exploited towards obtaining a novel fractional-order model and dedicated controller for DoA. First, clinical data from patients undergoing general anesthesia are used to determine a commensurate fractional-order model of the skin impedance at each sampling period. Second, we provide a proof of concept indicating that fractional order changes due to variations in the infused opioid drug (Remifentanil). Third, a fractional-order model for DoA is developed correlating the changes in the pain index (as the output signal) and the Remifentanil infusion rate (as the input signal). Standard optimization routines are used to estimate the parameters. A database of 19 real patients is used. Lastly, a preliminary fractional-order controller is designed and tested in simulation for the 19 patients. The closed-loop simulation results correspond to the expected clinical outcomes. [ABSTRACT FROM AUTHOR]

Traditionally, amber (Succinite) has been used to alleviate all types of pain, skin allergies, and headaches. However, no studies have been conducted on its antidiabetic and antioxidant effects. In this study, differentiated skeletal muscle C2C12 cells were used to demonstrate the protective effects of amber (AMB) against H2O2-induced cell death. In addition, the effects of AMB on glucose uptake and ATP production were investigated. Our results showed that AMB at 10, 25, and 50 μg/mL suppressed the elevation of ROS production induced by H2O2 in a dose-dependent manner. Moreover, AMB enhanced glucose utilization in C2C12 cells through the improvement of ATP production and an increase in PGC-1α gene expression resulting in an amelioration of mitochondrial activity. On the other hand, AMB significantly increased the gene expression of glucose transporters GLUT4 and GLUT1. Our finding suggests that AMB can be used as a natural supplement for diabetes treatment and for the promotion of skeletal muscle function. [ABSTRACT FROM AUTHOR]

Aims: Monitoring drug safety in real‐world settings is the primary aim of pharmacovigilance. Frequent adverse drug reactions (ADRs) are usually identified during drug development. Rare ones are mostly characterized through post‐marketing scrutiny, increasingly with the use of data mining and disproportionality approaches, which lead to new drug safety signals. Nonetheless, waves of excessive numbers of reports, often stirred up by social media, may overwhelm and distort this process, as observed recently with levothyroxine or COVID‐19 vaccines. As human resources become rarer in the field of pharmacovigilance, we aimed to evaluate the performance of an unsupervised co‐clustering method to help the monitoring of drug safety. Methods: A dynamic latent block model (dLBM), based on a time‐dependent co‐clustering generative method, was used to summarize all regional ADR reports (n = 45 269) issued between 1 January 2012 and 28 February 2022. After analysis of their intra and extra interrelationships, all reports were grouped into different cluster types (time, drug, ADR). Results: Our model clustered all reports in 10 time, 10 ADR and 9 drug collections. Based on such clustering, three prominent societal problems were detected, subsequent to public health concerns about drug safety, including a prominent media hype about the perceived safety of COVID‐19 vaccines. The dLBM also highlighted some specific drug–ADR relationships, such as the association between antiplatelets, anticoagulants and bleeding. Conclusions: Co‐clustering and dLBM appear as promising tools to explore large pharmacovigilance databases. They allow, 'unsupervisedly', the detection, exploration and strengthening of safety signals, facilitating the analysis of massive upsurges of reports. [ABSTRACT FROM AUTHOR]

Introduction: New procedures and diagnostic tests in hematopoietic stem cell transplantation (HSCT) are associated with a significant increase in costs. The last cost estimate of allogeneic HSCT done in Tunisia was in 1996 and concerned only direct medical costs. Therefore, an updated cost analysis is needed. Objective: Analysis of direct costs during the first-year post-allogeneic HSCT in two groups of patients: Bone Marrow Transplant (Allo-BMT) and Peripheral Blood Stem Cell Transplant (Allo-PBSCT) and identification of factors leading to interindividual variations in costs in order to compare these costs with the budget allocated by the payer (CNAM). Methods: Pharmacoeconomic retrospective study, concerning patients who underwent allogeneic HSCT in 2013. Clinical and unit cost data were obtained from medical and administration records. Results:This study showed that the average direct cost of allogeneic HSCT in the population during the first year reached 56 638€. The average cost of Allo-BMT was 63 612€, and Allo-PBSCT was 45 966€ (p > 0.05). The initial hospitalization counted for 88% of total direct cost with an average cost of 41 441€ in Allo-BMT and 24 672€ in Allo-PBSCT (p < 0.05). Direct medical costs represented more than 70% of total direct costs, drugs, and laboratory tests occupied the largest share. Antifungals, antitumors, and antiviral drugs were the most expensive pharmaceutical classes with a mean cost, respectively, of 4 526€; 3 737€ and 3 268€. Some clinical criteria were significantly related to total direct costs like length of aplasia (p < 0.01) and GVHD (p < 0.05). However, the type of blood disease, its risk, length of mucositis, and the treatment protocol have no effect on the costs for all allogeneic patients. Conclusion: Our results showed that the costs of Allo HSCT have exceeded by far the budget allocated by the CNAM to the center, since the 90s to this day. That's why the total reimbursement mechanism should be revised. [ABSTRACT FROM AUTHOR]

The objective of this paper is to combine dual numbers with symbolic 2-plithogenic numbers in one algebraic structure called dual symbolic 2-plithogenic real numbers. Also, many elementary properties of the suggested system such as inverses and idempotents will be handled by many related theorems and examples. [ABSTRACT FROM AUTHOR]

he objective of this paper is to use dual numbers with symbolic 3-plithogenic and 4-plithogenic numbers in one numerical system called dual symbolic 3-plithogenic/4-plithogenic numbers. Also, the elementary algebraic properties of the suggested systems will be discussed in terms of theorems and related examples that explain the validity of these algebraic number systems. [ABSTRACT FROM AUTHOR]

The correction notice addresses an error in the original publication of a study on the Mateur Plain in Northern Tunisia, acknowledging that the outline and approach were adapted from a previous reference. The study builds upon methodologies used in a previous investigation of the Fahs Aquifer, extending the application to the Mateur Plain by incorporating advanced datasets and refining the approach to identify tectonic lineaments and aquifer systems. The research aims to validate the broader applicability of these techniques while providing insights into the unique geological characteristics and hydrological dynamics of the Mateur region. [Extracted from the article]

The synthesis of a novel calix[4]arene-based chemosensor was conducted based on [Hg.sup.2} induced fluorescence resonance energy transfer (FRET) to determine its sensing behavior towards metal ions. A significantly enhanced fluorescence emission was observed when [Hg.sup.2} was added to a C[H.sub.3]CN solution of ligand chemosensor.