Analyzing the Interactions between Environmental Parameters and Cardiovascular Diseases Using Random Forest and SHAP Algorithms

Background: Cardiovascular diseases (CVD) remain the predominant global cause of mortality, with both low and high temperatures increasing CVD-related mortalities. Climate change impacts human health directly through temperature fluctuations and indirectly via factors like disease vectors. Elevated and reduced temperatures have been linked to increases in CVD-related hospitalizations and mortality, with various studies worldwide confirming the significant health implications of temperature variations and air pollution on cardiovascular outcomes. Methods: A database of daily Emergency Room admissions at the Giovanni XIII Polyclinic in Bari (Southern Italy) was developed, spanning from 2013 to 2019, including weather and air quality data. A Random Forest (RF) supervised machine learning model was used to simulate the trend of hospital admissions for CVD. The Seasonal and Trend decomposition using Loess (STL) decomposition model separated the trend component, while cross-validation techniques were employed to prevent overfitting. Model performance was assessed using specific metrics and error analysis. Additionally, the SHapley Additive exPlanations (SHAP) method, a feature importance technique within the eXplainable Artificial Intelligence (XAI) framework, was used to identify the feature importance. Results: An R2 of 0.97 and a Mean Absolute Error of 0.36 admissions were achieved by the model. Atmospheric pressure, minimum temperature, and carbon monoxide were found to collectively contribute about 74% to the model’s predictive power, with atmospheric pressure being the dominant factor at 37%. Conclusions: This research underscores the significant influence of weather-climate variables on cardiovascular diseases. The identified key climate factors provide a practical framework for policymakers and healthcare professionals to mitigate the adverse effects of climate change on CVD and devise preventive strategies

Tissuue Engineering in Maxillar Sinus Lifting: A Comparation of Differents Grafts and Confocal Laser Scanning Microscopic Evaluation

Bone is a specialized connective tissue, most prominently characterized by its mineralized organic matrix that imparts the physical properties that allow bone tissue to resist load, to support functional organs, and to protect highly sensitive body parts. Bone loss and bone damage may occur as a result of genetic conditions, infectious diseases, tumours, and trauma. Bone healing and repair, involves integrative activity of native tissues and living cells, and lends itself to the incorporation of naturally derived or biocompatible synthetic scaffolds, aimed at replacing missing or damaged osseous tissues. There are several modalities of bone regeneration including tissue engineering, guided bone regeneration, distraction ontogenesis, and bone grafting. This book concentrates on such procedures that may well be counted among the recent outstanding breakthroughs in bone regenerative therapy

The long noncoding RNA linc-NeD125 controls the expression of medulloblastoma driver genes by microRNA sponge activity

Long noncoding RNAs (lncRNAs) are major regulators of physiological and disease-related gene expression, particularly in the central nervous system. Dysregulated lncRNA expression has been documented in several human cancers, and their tissue-specificity makes them attractive candidates as diagnostic/prognostic biomarkers and/or therapeutic agents. Here we show that linc-NeD125, which we previously characterized as a neuronal-induced lncRNA, is significantly overexpressed in Group 4 medulloblastomas (G4 MBs), the largest and least well characterized molecular MB subgroup. Mechanistically, linc-NeD125 is able to recruit the miRNA-induced silencing complex (miRISC) and to directly bind the microRNAs miR-19a-3p, miR-19b-3p and miR-106a-5p. Functionally, linc-NeD125 acts as a competing endogenous RNA (ceRNA) that, sequestering the three miRNAs, leads to de-repression of their targets CDK6, MYCN, SNCAIP, and KDM6A, which are major driver genes of G4 MB. Accordingly, linc-NeD125 downregulation reduces G4 cell proliferation. Moreover, we also provide evidence that linc-NeD125 ectopic expression in the aggressive Group 3 MB cells attenuates their proliferation, migration and invasion. This study unveils the first lncRNA-based ceRNA network in central nervous system tumours and provides a novel molecular circuit underlying the enigmatic Group 4 medulloblastoma

Oral lichen planus in children: An Italian case series

Oral lichen planus usually occurs in adults; there are no clear data regarding the incidence and the clinical features of oral lichen planus in children. This paper reports clinical findings, treatments, and outcomes of 13 Italian patients with oral lichen planus in childhood diagnosed between 2001 and 2021. The most common finding was keratotic lesions with reticular or papular/plaque-like patterns, confined to the tongue in seven patients. Although oral lichen planus in childhood is rare and the malignant transformation index is unknown, specialists must be aware of its characteristics and oral mucosal lesions must be correctly diagnosed and managed

Insecticide resistance and the future of malaria control in Zambia.

BACKGROUND: In line with the Global trend to improve malaria control efforts a major campaign of insecticide treated net distribution was initiated in 1999 and indoor residual spraying with DDT or pyrethroids was reintroduced in 2000 in Zambia. In 2006, these efforts were strengthened by the President's Malaria Initiative. This manuscript reports on the monitoring and evaluation of these activities and the potential impact of emerging insecticide resistance on disease transmission. METHODS: Mosquitoes were captured daily through a series of 108 window exit traps located at 18 sentinel sites. Specimens were identified to species and analyzed for sporozoites. Adult Anopheles mosquitoes were collected resting indoors and larva collected in breeding sites were reared to F1 and F0 generations in the lab and tested for insecticide resistance following the standard WHO susceptibility assay protocol. Annual cross sectional household parasite surveys were carried out to monitor the impact of the control programme on prevalence of Plasmodium falciparum in children aged 1 to 14 years. RESULTS: A total of 619 Anopheles gambiae s.l. and 228 Anopheles funestus s.l. were captured from window exit traps throughout the period, of which 203 were An. gambiae malaria vectors and 14 An. funestus s.s.. In 2010 resistance to DDT and the pyrethroids deltamethrin, lambda-cyhalothrin and permethrin was detected in both An. gambiae s.s. and An. funestus s.s.. No sporozoites were detected in either species. Prevalence of P. falciparum in the sentinel sites remained below 10% throughout the study period. CONCLUSION: Both An. gambiae s.s. and An. funestus s.s. were controlled effectively with the ITN and IRS programme in Zambia, maintaining a reduced disease transmission and burden. However, the discovery of DDT and pyrethroid resistance in the country threatens the sustainability of the vector control programme

The Changing Landscape of Neonatal Diabetes Mellitus in Italy Between 2003 and 2022

Context In the last decade the Sanger method of DNA sequencing has been replaced by next-generation sequencing (NGS). NGS is valuable in conditions characterized by high genetic heterogeneity such as neonatal diabetes mellitus (NDM).Objective To compare results of genetic analysis of patients with NDM and congenital severe insulin resistance (c.SIR) identified in Italy in 2003-2012 (Sanger) vs 2013-2022 (NGS).Methods We reviewed clinical and genetic records of 104 cases with diabetes onset before 6 months of age (NDM + c.SIR) of the Italian dataset.Results Fifty-five patients (50 NDM + 5 c.SIR) were identified during 2003-2012 and 49 (46 NDM + 3 c.SIR) in 2013-2022. Twenty-year incidence was 1:103 340 (NDM) and 1:1 240 082 (c.SIR) live births. Frequent NDM/c.SIR genetic defects (KCNJ11, INS, ABCC8, 6q24, INSR) were detected in 41 and 34 probands during 2003-2012 and 2013-2022, respectively. We identified a pathogenic variant in rare genes in a single proband (GATA4) (1/42 or 2.4%) during 2003-2012 and in 8 infants (RFX6, PDX1, GATA6, HNF1B, FOXP3, IL2RA, LRBA, BSCL2) during 2013-2022 (8/42 or 19%, P = .034 vs 2003-2012). Notably, among rare genes 5 were recessive. Swift and accurate genetic diagnosis led to appropriate treatment: patients with autoimmune NDM (FOXP3, IL2RA, LRBA) were subjected to bone marrow transplant; patients with pancreas agenesis/hypoplasia (RFX6, PDX1) were supplemented with pancreatic enzymes, and the individual with lipodystrophy caused by BSCL2 was started on metreleptin.Conclusion NGS substantially improved diagnosis and precision therapy of monogenic forms of neonatal diabetes and c.SIR in Italy

Has COVID-19 Delayed the Diagnosis and Worsened the Presentation of Type 1 Diabetes in Children?

Objective: To evaluate whether the diagnosis of pediatric type 1 diabetes or its acute complications changed during the early phase of the coronavirus disease 2019 (COVID-19) pandemic in Italy. Research design and methods: This was a cross-sectional, Web-based survey of all Italian pediatric diabetes centers to collect diabetes, diabetic ketoacidosis (DKA), and COVID-19 data in patients presenting with new-onset or established type 1 diabetes between 20 February and 14 April in 2019 and 2020. Results: Fifty-three of 68 centers (77.9%) responded. There was a 23% reduction in new diabetes cases in 2020 compared with 2019. Among those newly diagnosed patient who presented in a state of DKA, the proportion with severe DKA was 44.3% in 2020 vs. 36.1% in 2019 (P = 0.03). There were no differences in acute complications. Eight patients with asymptomatic or mild COVID-19 had laboratory-confirmed severe acute respiratory syndrome coronavirus 2. Conclusions: The COVID-19 pandemic might have altered diabetes presentation and DKA severity. Preparing for any "second wave" requires strategies to educate and reassure parents about timely emergency department attendance for non-COVID-19 symptoms

A Multicenter Retrospective Survey regarding Diabetic Ketoacidosis Management in Italian Children with Type 1 Diabetes

We conducted a retrospective survey in pediatric centers belonging to the Italian Society for Pediatric Diabetology and Endocrinology. The following data were collected for all new-onset diabetes patients aged 0-18 years: DKA (pH < 7.30), severe DKA (pH < 7.1), DKA in preschool children, DKA treatment according to ISPAD protocol, type of rehydrating solution used, bicarbonates use, and amount of insulin infused. Records (n = 2453) of children with newly diagnosed diabetes were collected from 68/77 centers (87%), 39 of which are tertiary referral centers, the majority of whom (n = 1536, 89.4%) were diagnosed in the tertiary referral centers. DKA was observed in 38.5% and severe DKA in 10.3%. Considering preschool children, DKA was observed in 72%, and severe DKA in 16.7%. Cerebral edema following DKA treatment was observed in 5 (0.5%). DKA treatment according to ISPAD guidelines was adopted in 68% of the centers. In the first 2 hours, rehydration was started with normal saline in all centers, but with different amount. Bicarbonate was quite never been used. Insulin was infused starting from third hour at the rate of 0.05-0.1 U/kg/h in 72% of centers. Despite prevention campaign, DKA is still observed in Italian children at onset, with significant variability in DKA treatment, underlying the need to share guidelines among centers

Deep Learning for Sleep State Detection Using CW Doppler Radar Technology

Sleep is an essential function of the body to protect the mental and physical health of an individual. Monitoring and understanding the sleep patterns can help preventing diseases and designing tailored treatments for patients with sleep disorders. The goal of this work is to detect sleep and wake stages using deep learning techniques from radar data provided by the Swiss company Sleepiz AG. The aim is to understand the applicability of deep learning techniques for the sleep staging task and to evaluate the classification performance as well as time-requirements of the proposed approaches. For this purpose, raw signals and a time-frequency representation of the signals were used as input for several deep learning approaches to classify single segments of the input signal. Then, a sequential deep learning approach was introduced to generate predictions by processing an entire recording and generating predictions per each time step that were dependent on the previous and next inputs. The best model, named RawSeqEnsemble, uses night recordings data as input and it automatically generates predictions for the entire recording in a single moment. RawSeqEnsemble outperforms the existing model at Sleepiz AG based on a conventional random forest classifier applied on hand-engineered. Specifically, RawSeqEnsemble yielded approximately to 10 and 11 percentage points increase in Cohen’s kappa and wake F1-score, respectively, on a test set with 73 recordings. The results show that, using a sequential deep learning method, it is possible to learn spatial and temporal features directly from raw Sleepiz data based on radar-technology without the need of hand-crafted features. Also, the proposed approach not only generalizes well on different recordings, but it also predicts classes about 70 time faster for an entire recording on the same hardware

TRADITIONAL AND CLSM EXAMINATIONS IN A CASE OF ELECTROCUTION: NEW HISTOPATHOLOGICAL SIGNS

We described for the first time the morphological alterations of epicardic cardiac nerve trunks due to electricity. All these alterations can seriously interfere with transmission mechanism of nerve impulses. Central endoneural clefts of the nerve fibers with perineurium detachment could be used in future as specific signs of the passage of the electrical current through the heart. We recommend heart specimens at the level of common trunk of the left coronary artery in all the cases of suspected electrocution, to better evaluate cardiac nerve trunks damages and alterations