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Immunohistochemical insights into hypothermia-related deaths: a systematic review
Full text linkMechanical asphyxia refers to the internal or external obstruction of the airways,resulting in the subsequent interruption of respiratory exchanges and hypoxia, whichmay be due to homicidal, suicidal, or accidental actions (1). From ahistomorphological perspective, the microscopic changes observable withhematoxylin-eosin staining in cases of mechanical asphyxia (such as acute pulmonaryemphysema, interalveolar hemorrhage, and vascular congestion) have been welldescribed and, if documented, can provide valuable support to macroscopic findings(2). Concurrently, in forensic medicine, there has been notable advancement in theapplication of immunohistochemical techniques, which are already widely used inclinical practice for diagnosing and characterizing neoplasms (3).
Therefore, immunohistochemical techniques employed in forensic pathology todetermine the post-mortem interval and lesion dating have been complemented byadditional techniques used as valuable diagnostic aids in cases of natural or violentdeaths. Noteworthy are the numerous studies conducted on secondary deaths such assepsis or drowning (4,5). In the case of mechanical asphyxia, variations in several alveolar proteins have beendescribed, including surfactant protein-A (SP-A), P-selectin, E-selectin, Heat ShockProteins (HSPs), and hypoxia-inducible factor 1-α (HIF1-α) (6–8).
This study aims to investigate immunohistochemical changes in alveolar proteins inindividuals who have died from mechanical asphyxia and compare these findings withthose in living subjects suffering from chronic obstructive pulmonary disease (COPD)or chronic hypoxia. It employs an observational cohort design with stratified clustersampling, categorizing subjects into two main groups: one consisting of individualswho have died from mechanical asphyxia (such as drowning, hanging, orstrangulation) and the other including living patients with COPD or other conditionsleading to chronic hypoxia.
The primary objective of the study is to determine, by comparing the two groups,whether immunohistochemistry objectively reflects hypoxia induced by the asphyxialmechanism or if the expression of the markers is influenced by other factors such aspre-existing chronic hypoxia or modifications resulting from post-mortem changes. Itis essential to highlight that the use of immunohistochemistry on samples fromcadavers has been questioned due to the alterations that proteins undergo during post-mortem changes (9).
The study employs an observational cohort design with stratified cluster sampling. Itcategorizes subjects into two main groups: one comprising individuals who have diedfrom mechanical asphyxia, including cases of drowning, hanging, or strangulation, andthe other including living patients with COPD or other conditions leading to chronichypoxia.
The research will utilize hematoxylin-eosin staining and advancedimmunohistochemical techniques to evaluate the expression levels of the proteinsmentioned above in tissue samples. By comparing these protein expressions betweenthe two groups, the study aims to establish a reliable framework for understanding howpost-mortem changes and pre-existing conditions affect the immunohistochemicalmarkers used in forensic diagnostics.
The anticipated outcomes of this research are twofold: first, to provide a solidfoundation for future studies in forensic pathology by elucidating the variations inprotein expression due to mechanical asphyxia and chronic hypoxia, and second, toenhance the diagnostic accuracy for asphyxial deaths by determining the impact ofpost-mortem changes and chronic conditions on protein expression
Effect of dietary microalgae on growth performance and health in meat-type quails
Full text linkThe purpose of this work was to ascertain the impact of dietary inclusion of Dunaliella salina
(Ds) and Arthrospira platensis (Ap) mixture as growth promoters on growth performance,
carcass traits, liver and renal function, lipid profile, immunology and economics in quail
chicks. 240 Un -sexed seven-day quail chicks were separated into four treatment groups with
six replicates of ten chicks per group. The treatment groups are: control: basal diet; DsAp0.5:
basal diet + 0.25 g Ds+ 0.25 g Ap/kg diet; DsAp1: basal diet + 0.50 g Ds+ 0.50 g Ap/kg diet;
and DsAp2: basal diet + 1.00 g Ds+ 1.00 g Ap/kg diet. The outcomes of dietary inclusion of
Ds plus Ap revealed a significant difference in live body weight at 5 week and body weight
gain from (1-5wk) (P=0.049) and the group DsAp1 recorded the best results (191.19g, 5.69g).
The mixture of Ds plus Ap did not significantly (P>0.05) change the feed intake during the
experiment. The DsAp0.5 group significantly (P=0.019) presented the best feed conversion
ratio during (1-5 wk of age) compared to the control and other groups. The finding showed a
non-significant difference in carcass traits (P>0.05). Liver and kidney function markers were
affected by the supplements, and DsAp2 group recorded the highest levels of total protein and
albumin. The DsAp1 group significantly (P=0.003) presented the lowest level of alanine
aminotransferase (ALT) and the DsAp2 group significantly (P<0.001) presented the lowest
levels of aspartate aminotransferase (AST) and urea. Dietary supplementation of Ds plus Ap
affected the lipid profiles of the quail. Dietary supplementation of Ds plus Ap mixture
reduced the concentration of total cholesterol (TC), low-density lipoprotein (LDL),
triglyceride (TG) and high-density lipoprotein (HDL) when compared to control (P<0.001).
Furthermore, the immune parameters, complement 3 (C3) and lysozyme showed a nonsignificant
variation with Ds plus Ap supplementation. The net revenue and economic
efficiency of treated quails was significantly increased during the experiment (1-5 wks of
age); the best values were observed in DsAp0.5 group. In conclusion, the use of Ds plus Ap
mixture as growth promoters in quail diets improves the growth performance, liver functions
and lipid profile
EMPOWERING COMMUNITIES THROUGH DIGITAL INNOVATION AND SMALL-SCALE ARCHITECTURE
No full textThe housing crisis that typically results from a disaster is typically addressed through “temporary” prefabricated housing. These structures are usually designed for a short to medium-term lifespan and are
often arranged in dormitory-style suburbs that lack basic facilities. When the rebuilding process extends over time, as in many cases, these settlements can lead to a “second emergency” with serious repercussions for community health and cohesion (Ruggiero et al., 2021).
To tackle this issue, some international initiatives have experimented with digital technologies and lightweight building systems and local unskilled labour to create innovative temporary constructions. Notably, the work of Hiroto Kobayashi in the Far East and his “veneer building system” stands out among these studies.
Italy is a seismic country where the “reconstruction” process has historically been contentious, often requiring people to remain in temporary settlements for extended periods. A recent example is the aftermath of the Central Italy earthquake in 016/2017. Eight years later, only a small percentage of uninhabitable houses have been rebuilt or restored. Some individuals continue to live in provisional settlements, while others have relocated, all facing an uncertain future.
This chapter introduces a methodology for establishing temporary settlements through participatory construction processes for small facilities. This methodology was implemented in a pilot project carried out
in collaboration between the Italian University of Camerino and the Japanese Keio University. Two innovative “mobile” pavilions for cultural activities were constructed in Amandola, one of the villages severely affected by the 2016/2017 earthquake. Local students were involved in the project, digital technologies were applied,
and the veneer system was tested. This work represents a unique application of digital technologies in the disaster-impacted area of Central Italy, as well as an original implementation of the veneer syste
Hierarchical Vector Mixtures for Electricity Day-Ahead Market Prices Scenario Generation
No full textIn this paper, a class of fully probabilistic time series models based on Gaussian Vector Mixtures (VMs), i.e., on linear combinations of multivariate Gaussian distributions, is proposed to model electricity Day Ahead Market (DAM) hourly prices and to generate consistent related DAM prices dynamic scenarios. These models, based on latent variables, intrinsically allow for organizing DAM data in hierarchically organized clusters, and for recreating the delicate balance of price spikes and baseline price dynamics present in the DAM data. The latent variables and the parameters of these models have a simple and clear interpretation in terms of market phenomenology, like market conditions, spikes and night/day seasonality. In the machine learning community, different to current deep learning models, VMs and the other members of the class discussed in the paper could be seen as just ‘oldish’ probabilistic models. In this paper it is shown, on the contrary, that they are still worthy models, excellent at extracting relevant features from data, and directly interpretable as a subset of the regime switching autoregressions still currently largely used in the econometric community. In addition, it is shown how they can include mixtures of mixtures, thus allowing for the unsupervised detection of hierarchical structures in the data. It is also pointed out that, as such, VMs cannot fully accommodate the autocorrelation information intrinsic to DAM data time series, hence extensions of VMs are needed. The paper is thus divided into two parts. In the first part, VMs are estimated and used to model daily vector sequences of 24 prices, thus assessing their scenario generation capability. In this part, it is shown that VMs can very well preserve and encode infra-day dynamic structure like autocorrelation up to 24 lags, but also that they cannot handle inter-day structure. In the second part, these mixtures are dynamically extended to incorporate dynamic features typical of hidden Markov models, thus becoming Vector Hidden Markov Mixtures (VHMMs) of Gaussian distributions, endowed with daily latent dynamics. VHMMs are thus shown to be very much able to model both infra-day and inter-day phenomenology, hence able to include autocorrelation beyond 24 lags. Building on the VM discussion on latent variables and mixtures of mixtures, these models are also shown to possess enough internal structure to exploit and carry forward hierarchical clustering also in their dynamics, their small number of parameters still preserving a simple and clear interpretation in terms of market phenomenology and in terms of standard econometrics. All these properties are thus also available to their regime switching counterparts from econometrics. In practice, these very simple models, bridging machine learning and econometrics, are able to learn latent price regimes from historical data in an unsupervised fashion, enabling the generation of realistic market scenarios while maintaining straightforward econometrics-like explainability
State of the Art and Future Directions of Small Language Models: A Systematic Review
No full textSmall Language Models (SLMs) have emerged as a critical area of study within natural language processing, attracting growing attention from both academia and industry. This systematic literature review provides a comprehensive and reproducible analysis of recent developments and advancements in SLMs post-2023. Drawing on 70 English-language studies published between January 2023 and January 2025, identified through Scopus, IEEE Xplore, Web of Science, and ACM Digital Library, and focusing primarily on SLMs (including those with up to 7 billion parameters), this review offers a structured overview of the current state of the art and potential future directions. Designed as a resource for researchers seeking an in-depth global synthesis, the review examines key dimensions such as publication trends, visual data representations, contributing institutions, and the availability of public datasets. It highlights prevailing research challenges and outlines proposed solutions, with a particular focus on widely adopted model architectures, as well as common compression and optimization techniques. This study also evaluates the criteria used to assess the effectiveness of SLMs and discusses emerging de facto standards for industry. The curated data and insights aim to support and inform ongoing and future research in this rapidly evolving field
BIOLOGICAL EVALUATION OF Cu(I) AND Ag(I) COMPLEXES WITH β-DIKETONE LIGANDS FEATURING MESITYL AND TRIFLUOROMETHYL SUBSTITUTENTS
No full textRecent advances in medicinal inorganic chemistry have led to the development of innovative chelating ligands and delivery systems to enhance the potency and selectivity of metal-based anticancer drugs. In this regard, group 11 metal complexes have emerged as promising candidates due to their unique therapeutic potential.[1] Although β-diketones represent one of the oldest classes of chelating ligands, their coordination chemistry continues to attract much interest. Therefore, as part of our investigation on the chemical and biological properties of metal-based anticancer complexes supported by β-diketonate ligands,[2,3] we synthesized a series of Cu(I) and Ag(I) complexes stabilized by β-diketone ligands (Figure 1): 1,3-dimesitylpropane-1,3-dione (HLMes), 1,3-bis(3,5-bis(trifluoromethyl)phenyl)-3-hydroxyprop-2-en-1-one (HLCF3), and 1,3-diphenylpropane-1,3-dione (HLPh). As co-ligands to stabilize the metal in the +1 oxidation state and to modulate lipophilicity, we employed triphenylphosphine (PPh3) and 1,3,5-triaza-7-phosphaadamantane (PTA).
X-ray crystallographic analysis revealed that [Cu(LCF3)(PPh3)2] and [Ag(LPh)(PPh3)2] adopt distorted tetrahedral geometries (Figure 2). The planar CuO2C3 metallacycle of [Cu(LCF3)(PPh3)2] and the half-boat AgO2C3 core of [Ag(LPh)(PPh3)2] point out the variability in coordination environments. While the influence of coordination geometry on biological activity remains to be fully elucidated, the observed differences may contribute to the distinct cytotoxic profiles of these complexes. Biological evaluation demonstrated that Ag(I) and Cu(I) complexes with PPh3 as the phosphane coligand possessed greater antitumor activity against human tumor cell lines derived from solid tumors, compared to cisplatin. Among them, copper complexes with HLCF3 and HLMes ligands were the most active derivatives. Particularly, [Cu(LMes)(PPh3)2] was up to 16 times more active than cisplatin in inhibiting the cell proliferation of 2D testicular carcinoma cell cultures (NTERA-2). Furthermore, cytotoxicity experiments performed on HCT-15 spheroids indicated that [Cu(LCF3)(PPh3)2] possessed remarkable antiproliferative activity, confirming its ability to penetrate the whole spheroid domain and reach the inner hypoxic core.[4] These results indicate Cu(I) complexes with fluorinated or bulky β-diketone ligands as promising candidates for anticancer applications, underscoring the importance of ligand design in improving biological activity
Life+ AGREENet Projects and Results
No full textThis Zenodo repository contains data and visualizations related to the LIFE A_GreeNet project (LIFE20 CCA/IT/001752). The LIFE A_GreeNet project, co-funded by the European Union's LIFE Programme, aims to enhance the resilience of Middle Adriatic coastal cities to climate change. Finisci con metodologia This is achieved through the implementation of urban green infrastructures, soil recovery, the planting of forests and green areas, and the adoption of Nature-Based Solutions (NBS) such as vertical greening and green roofs.The project also promotes the implementation of Sustainable Energy and Climate Action Plans (SECAPs).
The project partnership includes the Abruzzo Region (coordinator), the University of Camerino, ResAgraria, Legambiente, and the municipalities of Ancona, Pescara, San Benedetto del Tronto, and Silvi, along with other coastal municipalities in the province of Teramo.
Repository Contents:
This repository includes the following files, providing a visual and detailed overview of the project:
Projects views.zip: This archive contains images and plans illustrating the project areas and planned interventions at the urban scale. These visualizations provide a spatial representation of the project's climate adaptation strategy.
Books.zip: This archive contains documents and reports detailing the project, the A_GreeNet methodology, the strategic vision, climate adaptation objectives, and the selection of NBS. It also includes information on the climate data used for detailed design.
Envimet projects views.zip: This archive contains visualizations and data related to simulations performed with the ENVI-MET software. These simulations were used to evaluate the impact of improvement interventions (pre- and post-intervention) on aspects such as vegetation, mobility, and social interaction. The simulations provide an assessment of the performance of green areas in terms of ecosystem services (carbon storage and sequestration, runoff reduction, energy savings, oxygen production, pollutant removal). I-Tree was utilized for the evaluation of ecosystem services.
Methodology:
The project utilizes the A_GreeNet methodology, which involves the combined use of tools such as ENVI-MET (for thermo-fluid dynamic modeling) and i-Tree (for urban forest management). This methodology allows for pre- and post-intervention simulations to optimize project interventions and evaluate climate and economic benefits. The design process is structured in several phases, including site assessment, strategic vision definition, NBS selection, climate data analysis, pre-intervention scenario construction, ENVI-MET pre-intervention simulation, post-intervention scenario construction, ENVI-MET post-intervention simulation, and cost calculation
Data-driven LPV control based on Quadratic Matrix Inequalities: Experimental application to the Quanser Aero
No full textThis paper presents the application of a recently proposed data-driven Linear Parameter Varying (LPV) controller design method to the Quanser Aero. The employed approach is based on Quadratic Matrix Inequalities (QMIs) and the strict matrix S-lemma. The existing approach is tweaked with the aim of forcing a higher control aggressiveness. Simulation and experimental results involving stabilization and multi-step-reference tracking are used to illustrate the validity and performance of the design
La sanità digitale
No full textSommario: 1. I servizi pubblici digitali. – 1.1. Generalità e contesto di riferimento.
– 1.2. Le componenti della digitalizzazione pubblica. – 1.3. Principi e diritti digitali. – 2.
L’innovazione tecnologica in sanità e il suo governo: dai sistemi informativi e informatici alla
sanità digitale. – 3. Gli strumenti della sanità digitale. – 3.1. Il nuovo sistema informativo
sanitario (NSIS). – 3.2. Il fascicolo sanitario elettronico (FSE). – 3.3. La cartella clinica dema-
terializzata. – 3.4. La telemedicina. – 4. Intelligenza artificiale (IA) e tutela della salute. – 5. Il
patrimonio informativo sanitario: i dati e il loro trattamento. Cenni
Distributed Lag Non-Linear Models for the impact of heat waves on elderly people living in the regions of central-eastern Italy
Full text linkBackground: Prolonged periods of extreme heat, usually referred to as heat waves, have a significant
impact on health, especially in the most vulnerable populations. In the present study, we investigated the
effect of heat waves on mortality in the elderly population living in the regions of central-eastern Italy.
Methods: We considered 10 cities located between the Marche and Abruzzo regions during the period
2011–2021. The association between heat waves and mortality risk was analysed for each city using
non-linear distributed lagged temperature and humidity functions, a method that accounts for non-linear
lagged effects, including the harvest effect, a phenomenon where mortality decreases temporarily after an
initial peak due to early deaths of vulnerable individuals. We then performed a multivariate meta-analysis
on all cities to jointly synthesise multiple results on mortality risk during heat waves, taking into account
their correlation.
Results: In the first days after the heat wave, the relative risk (RR) tends to increase, then decreases with a
lag of about 4 days and then stabilises around the reference value (RR = 1), with a slight increase around
day 21–22.
Conclusion: The study shows a significant increase in risk in the presence or after the occurrence of a heat
wave. The heterogeneous behaviour of some cities could be due to other factors (e.g. pollution) that need
to be investigated. The aggregate analysis allows a more robust estimate of the overall effect, reducing
the uncertainty arising from individual local analyses