Surveying haemoperfusion impact on COVID-19 from machine learning using Shapley values.

BACKGROUND: Haemoperfusion (HP) is an innovative extracorporeal therapy that utilizes special cartridges to filter the blood, effectively removing pro-inflammatory cytokines, toxins, and pathogens in COVID-19 patients. This retrospective cohort study aimed to assess the clinical benefits of HP for severe COVID-19 cases using Shapley values for machine learning models. METHODS: The research involved 578 inpatients (≥ 20 years old) admitted to Baqiyatallah hospital (Tehran, Iran). The control group (359 patients) received standard treatment, including high doses of corticosteroids (a single 500 mg methylprednisolone pulse, followed by 250 mg for 2 days), categorized as regimen (I). On the other hand, the HP group (219 patients) received regimen II, consisting of the same corticosteroid treatment (regimen I) along with haemoperfusion using Cytosorb H300. The frequency of haemoperfusion sessions varied based on the type of lung involvement determined by chest CT scans. In addition, the value function v defines the Shapley value of the i th feature for the query point x , where the input matrix features represent individual characteristics, drugs, and history and clinical conditions of the patient. RESULTS: Our data showed a favorable clinical response in the HP group compared to the control group. Notably, one-to-three sessions of HP using the CytoSorb® 300 cartridge led to reduced ventilation requirements and mortality rates in severe COVID-19 patients. Shapley values were calculated to evaluate the contribution of haemoperfusion among other factors, such as side effects, medications, and individual characteristics, to COVID-19 patient outcomes. In addition, there is a significant difference between the two groups among the treatments and medications used remdesivir, adalimumab, tocilizumab, favipiravir, Interferon beta-1a, enoxaparin prophylaxis, enoxaparin full dose, heparin prophylaxis, and heparin full dose (P < 0.05). It seems that haemoperfusion has a positive impact on the reduction of inflammation markers and renal functional such as ferritin and creatinine, respectively, as well as D-dimer and WBC levels in the HP group were significantly lower than the control group. CONCLUSION: The findings indicated that haemoperfusion played a crucial role in predicting patient survival, making it a significant feature in classifying patients' prognoses.

Quantitative assessment of traumatic brain injury risk in diverse age groups of females: Insights from computational biomechanics.

Traumatic Brain Injury (TBI) stands as a multifaceted health concern, exhibiting varying influences across human population. This study delves into the biomechanical complexities of TBI within gender-specific contexts, focusing on females. Our primary objective is to investigate distinctive injury mechanisms and risks associated with females, emphasizing the imperative for tailored investigations within this cohort. By employing Fluid-Structure Interaction (FSI) Analysis, we conducted simulations to quantify biomechanical responses to traumatic forces across diverse age groups of females. The study utilized a scaling technique to create finite element models (FEMs). The young female FEM, based on anthropometric data, showcased a 15 % smaller head geometry compared to the young male FEM. Moreover, while the elderly female FEM closely mirrored the young female FEM in most structural aspects, it showed distinctive features such as brain atrophy and increased cerebrospinal fluid (CSF) layer thickness. Notably, the child female FEM (ages 7-11 years) replicated around 95 % of the young female FEM's geometry. These structural distinctions meticulously captured age-specific variations across our modeled female age groups. It's noteworthy that identical conditions, encompassing impact intensity, loading type, and boundary conditions, were maintained across all FEMs in this biomechanical finite element analysis, ensuring comparative results. The findings unveiled significant variations in frontal and occipital pressures among diverse age groups, highlighting potential age-related discrepancies in TBI susceptibility among females. These variations were primarily linked to differences in anatomical features, including brain volume, CSF thickness, and brain condition, as the same material properties were used in the FEMs. These results were approximately 4.70, 6.33 and 6.43 % in frontal area of brain in diverse age groups of females (young, elderly, and child) respectively compared to young male FEM. Comparing the FEM results between the young female and the elderly female, we observed a decrease in occipital brain pressure at the same point, reducing from 171,993 to 167,793 Pa, marking an approximate 2.5 % decrease. While typically the elderly exhibit greater brain vulnerability compared to the young, our findings showcase a reduction in brain pressure. Notably, upon assessing the relative movement between the brain and the skull at the point located in occipital area, we observed greater relative movement in the elderly (1.8 mm) compared to the young female (1.04 mm). Therefore, brain atrophy increases the range of motion of the brain within the cranial space. The study underscores the critical necessity for nuanced TBI risk assessment tailored to age and gender, emphasizing the importance of age-specific protective strategies in managing TBIs across diverse demographics. Future research employing individual modeling techniques and exploring a wider age spectrum holds promise in refining our understanding of TBI mechanisms and adopting targeted approaches to mitigate TBI in diverse groups.

Glassy carbon electrode modified with hybrid nanofibers containing carbon nanotubes trapped in chitosan for the voltammetric sensing of nicotine at biological pH.

In this paper, nicotine (NIC) was detected by cyclic voltammetry (CV) using a modified glassy carbon (GC) electrode. To do this, the surface of the GC electrode was modified by hybrid nanofiber obtained from the electrospinning method. Hybrid nanofibers were produced through the dispersion of carboxylated multi-walled carbon nanotube (MWCNT-COOH) as an inorganic component in the chitosan (CS) polymer matrix as an organic component. The nanofibers showed unique morphology and high surface area value. With the increase of functionalized carbon nanotube content in the nanofibers, the mean pore diameter and average nanofiber diameter increased. The electrochemical properties of nanofibers towards the sensing of NIC were investigated by the CV method. NIC was irreversibly reduced with the use of a CS/MWCNT-COOH electrode, a controlled process with two protons and two electrons. An oxidation signal at lower potential with higher current was obtained for NIC with the use of a polymer-modified electrode compared to a GC electrode. This was as a result of the electrocatalytic effect of the hybrid nanofibers due to the ability of carbon nanotubes to increase the rate of electron transfer. Under optimum conditions, the oxidation of NIC occurred at 0.82 eV with a pH of 7.4. The linear calibration curve was in the concentration range of 0.1-100 µM NIC (R 2 = 0.9987) with a detection limit of 30 nM. For 100 parallel 10 µM NIC diagnoses for five replicates, 97.2% with a standard deviation of 4.08 maintained their stability over the first cycle. This indicates that the CS/MWCNT-COOH electrode has excellent reproducibility and stability.