Chronic wounds represent a major public health issue, with an extremely high cost worldwide. In healthy individuals, the wound healing process takes place in different stages: inflammation, cell proliferation (fibroblasts and keratinocytes of the dermis), and finally remodeling of the extracellular matrix (equilibrium between metalloproteinases and their inhibitors). In chronic wounds, the chronic inflammation favors exudate persistence and bacterial film has a special importance in the dynamics of chronic inflammation in wounds that do not heal. Recent advances in biopolymer-based materials for wound healing highlight the performance of specific alginate forms. An ideal wound dressing should be adherent to the wound surface and not to the wound bed, it should also be non-antigenic, biocompatible, semi-permeable, biodegradable, elastic but resistant, and cost-effective. It has to give protection against bacterial, infectious, mechanical, and thermal agents, to modulate the level of wound moisture, and to entrap and deliver drugs or other molecules This paper explores the roles of alginates in advanced wound-dressing forms with a particular emphasis on hydrogels, nanofibers networks, 3D-scaffolds or sponges entrapping fibroblasts, keratinocytes, or drugs to be released on the wound-bed. The latest research reports are presented and supported with in vitro and in vivo studies from the current literature.
Background: The COVID-19 pandemic has challenged the treatment of Clostridioides Difficile (CD)-infected patients given the increasing number of co-infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this context, fecal microbiota transplantation (FMT) shows promise in modulating the immune system’s function and alleviating the burdens associated with this condition. Methods: To achieve this goal, we performed a comparative, retrospective, single-center study on 86 patients (admitted between January 2020 and March 2022). We based our approach on specific inclusion criteria: 1. The study group included 46 co-infected patients (COVID-19 and CD) receiving antibiotics and FMT; 2. In the control group, 40 co-infected patients received antibiotics only. Our results showed no significant group differences in terms of gender, age, risk factors such as cardiovascular and neurological diseases, type 2 diabetes, and obesity (p > 0.05), or in pre-treatment inflammatory status, evaluated by white blood cell (WBC) count and C-reactive protein (CRP) levels. We report a significant decrease in inflammatory syndrome (CRP, WBC) in coinfected patients receiving FMT in addition to antibiotics (p < 0.05), with a lower relapse rate and mitigation of cramping and abdominal pain (91.3%). In addition, a higher level of fibrinogen, persistent moderate abdominal pain (82.5%), and a significantly higher CD infection relapse rate (42.5%) were recorded in co-infected patients treated only with antibiotics (p < 0.05). Conclusion: Our study provides new data to support the multiple benefits of FMT in the case of COVID-19 and CD co-infection by improving patients’ quality of life and inflammatory syndrome.
At present, it is necessary to identify specific biochemical, molecular, and genetic markers that can reliably aid in screening digestive cancer and correlate with the degree of disease development. Has-miR-129-5p is a small, non-coding molecule of RNA, circulating in plasma, gastric juice, and other biological fluids; it plays a protective role in tumoral growth, metastasis, etc. Furthermore, it is involved in various diseases, from the development of digestive cancer in cases of downregulation to neurodegenerative diseases and depression. Methods: We examined meta-analyses, research, and studies related to miR-129-5-p involved in digestive cancer and its implications in cancer processes, as well as metastasis, and described its implications in neurological diseases. Conclusions: Our review outlines that miR-129-5p is a significant controller of different pathways, genes, and proteins and influences different diseases. Some important pathways include the WNT and PI3K/AKT/mTOR pathways; their dysregulation results in digestive neoplasia and neurodegenerative diseases.
Neonatal brain injury or neonatal encephalopathy (NE) is a significant morbidity and mortality factor in preterm and full-term newborns. NE has an incidence in the range of 2.5 to 3.5 per 1000 live births carrying a considerable burden for neurological outcomes such as epilepsy, cerebral palsy, cognitive impairments, and hydrocephaly. Many scoring systems based on different risk factor combinations in regression models have been proposed to predict abnormal outcomes. Birthweight, gestational age, Apgar scores, pH, ultrasound and MRI biomarkers, seizures onset, EEG pattern, and seizure duration were the most referred predictors in the literature. Our study proposes a decision-tree approach based on clinical risk factors for abnormal outcomes in newborns with the neurological syndrome to assist in neonatal encephalopathy prognosis as a complementary tool to the acknowledged scoring systems. We retrospectively studied 188 newborns with associated encephalopathy and seizures in the perinatal period. Etiology and abnormal outcomes were assessed through correlations with the risk factors. We computed mean, median, odds ratios values for birth weight, gestational age, 1-min Apgar Score, 5-min Apgar score, seizures onset, and seizures duration monitoring, applying standard statistical methods first. Subsequently, CART (classification and regression trees) and cluster analysis were employed, further adjusting the medians. Out of 188 cases, 84 were associated to abnormal outcomes. The hierarchy on etiology frequencies was dominated by cerebrovascular impairments, metabolic anomalies, and infections. Both preterms and full-terms at risk were bundled in specific categories defined as high-risk 75–100%, intermediate risk 52.9%, and low risk 0–25% after CART algorithm implementation. Cluster analysis illustrated the median values, profiling at a glance the preterm model in high-risk groups and a full-term model in the inter-mediate-risk category. Our study illustrates that, in addition to standard statistics methodologies, decision-tree approaches could provide a first-step tool for the prognosis of the abnormal outcome in newborns with encephalopathy.
Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality.
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