Semantic Information Recovery in Wireless Networks

Motivated by the recent success of Machine Learning (ML) tools in wireless communications, the idea of semantic communication by Weaver from 1949 has gained attention. It breaks with Shannon's classic design paradigm by aiming to transmit the meaning of a message, i.e., semantics, rather than its exact version and, thus, enables savings in information rate. In this work, we extend the fundamental approach from Basu et al. for modeling semantics to the complete communications Markov chain. Thus, we model semantics by means of hidden random variables and define the semantic communication task as the data-reduced and reliable transmission of messages over a communication channel such that semantics is best preserved. We consider this task as an end-to-end Information Bottleneck problem, enabling compression while preserving relevant information. As a solution approach, we propose the ML-based semantic communication system SINFONY and use it for a distributed multipoint scenario; SINFONY communicates the meaning behind multiple messages that are observed at different senders to a single receiver for semantic recovery. We analyze SINFONY by processing images as message examples. Numerical results reveal a tremendous rate-normalized SNR shift up to 20 dB compared to classically designed communication systems.

Statistical inference of the rates of cell proliferation and phenotypic switching in cancer

Recent evidence suggests that nongenetic (epigenetic) mechanisms play an important role at all stages of cancer evolution. In many cancers, these mechanisms have been observed to induce dynamic switching between two or more cell states, which commonly show differential responses to drug treatments. To understand how these cancers evolve over time, and how they respond to treatment, we need to understand the state-dependent rates of cell proliferation and phenotypic switching. In this work, we propose a rigorous statistical framework for estimating these parameters, using data from commonly performed cell line experiments, where phenotypes are sorted and expanded in culture. The framework explicitly models the stochastic dynamics of cell division, cell death and phenotypic switching, and it provides likelihood-based confidence intervals for the model parameters. The input data can be either the fraction of cells or the number of cells in each state at one or more time points. Through a combination of theoretical analysis and numerical simulations, we show that when cell fraction data is used, the rates of switching may be the only parameters that can be estimated accurately. On the other hand, using cell number data enables accurate estimation of the net division rate for each phenotype, and it can even enable estimation of the state-dependent rates of cell division and cell death. We conclude by applying our framework to a publicly available dataset.

Seasonal variations of intensity of avian malaria infection in the Thousand Island Lake System, China

BACKGROUND

Migratory birds play an important part in the spread of parasites, with more or less impact on resident birds. Previous studies focus on the prevalence of parasites, but changes in infection intensity over time have rarely been studied. As infection intensity can be quantified by qPCR, we measured infection intensity during different seasons, which is important for our understanding of parasite transmission mechanisms.

METHODS

Wild birds were captured at the Thousand Island Lake with mist nets and tested for avian hemosporidiosis infections using nested PCR. Parasites were identified using the MalAvi database. Then, we used qPCR to quantify the infection intensity. We analyzed the monthly trends of intensity for all species and for different migratory status, parasite genera and sexes.

RESULTS

Of 1101 individuals, 407 were infected (37.0%) of which 95 were newly identified and mainly from the genus Leucocytozoon. The total intensity trend shows peaks at the start of summer, during the breeding season of hosts and during the over-winter season. Different parasite genera show different monthly trends. Plasmodium causes high prevalence and infection intensity of winter visitors. Female hosts show significant seasonal trends of infection intensity.

CONCLUSIONS

The seasonal changes of infection intensity is consistent with the prevalence. Peaks occur early and during the breeding season and then there is a downward trend. Spring relapses and avian immunity are possible reasons that could explain this phenomenon. In our study, winter visitors have a higher prevalence and infection intensity, but they rarely share parasites with resident birds. This shows that they were infected with Plasmodium during their departure or migration and rarely transmit the disease to resident birds. The different infection patterns of different parasite species may be due to vectors or other ecological properties.

Gut barrier-microbiota imbalances in early life lead to higher sensitivity to inflammation in a murine model of C-section delivery

BACKGROUND

Most interactions between the host and its microbiota occur at the gut barrier, and primary colonizers are essential in the gut barrier maturation in the early life. The mother-offspring transmission of microorganisms is the most important factor influencing microbial colonization in mammals, and C-section delivery (CSD) is an important disruptive factor of this transfer. Recently, the deregulation of symbiotic host-microbe interactions in early life has been shown to alter the maturation of the immune system, predisposing the host to gut barrier dysfunction and inflammation. The main goal of this study is to decipher the role of the early-life gut microbiota-barrier alterations and its links with later-life risks of intestinal inflammation in a murine model of CSD.

RESULTS

The higher sensitivity to chemically induced inflammation in CSD mice is related to excessive exposure to a too diverse microbiota too early in life. This early microbial stimulus has short-term consequences on the host homeostasis. It switches the pup's immune response to an inflammatory context and alters the epithelium structure and the mucus-producing cells, disrupting gut homeostasis. This presence of a too diverse microbiota in the very early life involves a disproportionate short-chain fatty acids ratio and an excessive antigen exposure across the vulnerable gut barrier in the first days of life, before the gut closure. Besides, as shown by microbiota transfer experiments, the microbiota is causal in the high sensitivity of CSD mice to chemical-induced colitis and in most of the phenotypical parameters found altered in early life. Finally, supplementation with lactobacilli, the main bacterial group impacted by CSD in mice, reverts the higher sensitivity to inflammation in ex-germ-free mice colonized by CSD pups' microbiota.

CONCLUSIONS

Early-life gut microbiota-host crosstalk alterations related to CSD could be the linchpin behind the phenotypic effects that lead to increased susceptibility to an induced inflammation later in life in mice. Video Abstract.

Novel Application of 3D Scaffolds of Poly(E-Caprolactone)/Graphene as Osteoinductive Properties in Bone Defect

OBJECTIVE

 Scaffolds provided a surface on which cells could attach, proliferate, and differentiate. Nowadays, bone tissue engineering offers hope for treating bone cancer. Poly(e-caprolactone) (PCL)/graphene have capability as an osteogenic and regenerative therapy. It could be used to produce bone tissue engineering scaffolds. The purpose of this study was to investigate the ability of PCL/graphene to enhance the osteoinductive mechanism.

MATERIALS AND METHODS

 The PCL/graphene scaffold was developed utilizing a particulate-leaching process and cultured with osteoblast-like cells MG63 at 0.5, 1.5, and 2.5 wt% of graphene. We evaluated the porosity, pore size, migratory cells, and cell attachment of the scaffold.

STATISTICAL ANALYSIS

 Data was expressed as the mean ± standard error of the mean and statistical analyses were performed using one-way analysis of variance and Tukey's post hoc at a level of p-value < 0.05.

RESULTS

 Porosity of scaffold with various percentage of graphene was nonsignificant (p > 0.05). There were differences in the acceleration of cell migration following wound closure between groups at 24 hours (p < 0.01) and 48 hours (p < 0.00). Adding the graphene on the scaffolds enhanced migration of osteoblast cells culture and possibility to attach. Graphene on 2.5 wt% exhibited good characteristics over other concentrations.

CONCLUSION

 This finding suggests that PCL/graphene composites may have potential applications in bone tissue engineering.

Novel 3D printable PEEK-HA-Mg2SiO4 composite material for spine implants: biocompatibility and imaging compatibility assessments

PURPOSE

To develop a novel 3D printable polyether ether ketone (PEEK)-hydroxyapatite (HA)-magnesium orthosilicate (Mg2SiO4) composite material with enhanced properties for potential use in tumour, osteoporosis and other spinal conditions. We aim to evaluate biocompatibility and imaging compatibility of the material.

METHODS

Materials were prepared in three different compositions, namely composite A: 75 weight % PEEK, 20 weight % HA, 5 weight % Mg2SiO4; composite B: 70 weight% PEEK, 25 weight % HA, 5 weight % Mg2SiO4; and composite C: 65 weight % PEEK, 30 weight % HA, 5 weight % Mg2SiO4. The materials were processed to obtain 3D printable filament. Biomechanical properties were analysed as per ASTM standards and biocompatibility of the novel material was evaluated using indirect and direct cell cytotoxicity tests. Cell viability of the novel material was compared to PEEK and PEEK-HA materials. The novel material was used to 3D print a standard spine cage. Furthermore, the CT and MR imaging compatibility of the novel material cage vs PEEK and PEEK-HA cages were evaluated using a phantom setup.

RESULTS

Composite A resulted in optimal material processing to obtain a 3D printable filament, while composite B and C resulted in non-optimal processing. Composite A enhanced cell viability up to ~ 20% compared to PEEK and PEEK-HA materials. Composite A cage generated minimal/no artefacts on CT and MR imaging and the images were comparable to that of PEEK and PEEK-HA cages.

CONCLUSION

Composite A demonstrated superior bioactivity vs PEEK and PEEK-HA materials and comparable imaging compatibility vs PEEK and PEEK-HA. Therefore, our material displays an excellent potential to manufacture spine implants with enhanced mechanical and bioactive property.

Spotlight on contributory role of host immunogenetic profiling in SARS-CoV-2 infection: Susceptibility, severity, mortality, and vaccine effectiveness

BACKGROUND

The SARS-CoV-2 virus has spread continuously worldwide, characterized by various clinical symptoms. The immune system responds to SARS-CoV-2 infection by producing Abs and secreting cytokines. Recently, numerous studies have highlighted that immunogenetic factors perform a putative role in COVID-19 pathogenesis and implicate vaccination effectiveness.

AIM

This review summarizes the relevant articles and evaluates the significance of mutation and polymorphism in immune-related genes regarding susceptibility, severity, mortality, and vaccination effectiveness of COVID-19. Furthermore, the correlation between host immunogenetic and SARS-CoV-2 reinfection is discussed.

METHOD

A comprehensive search was conducted to identify relevant articles using five databases until January 2023, which resulted in 105 total articles.

KEY FINDINGS

Taken to gather this review summarized that: (a) there is a plausible correlation between immune-related genes and COVID-19 outcomes, (b) the HLAs, cytokines, chemokines, and other immune-related genes expression profiles can be a prognostic factor in COVID-19-infected patients, and (c) polymorphisms in immune-related genes have been associated with the effectiveness of vaccination.

SIGNIFICANCE

Regarding the importance of mutation and polymorphisms in immune-related genes in COVID-19 outcomes, modulating candidate genes is expected to help clinical decisions, patient outcomes management, and innovative therapeutic approach development. In addition, the manipulation of host immunogenetics is hypothesized to induce more robust cellular and humoral immune responses, effectively increase the efficacy of vaccines, and subsequently reduce the incidence rates of reinfection-associated COVID-19.

Pediatric multisystem inflammatory syndrome associated with COVID-19: Insights in pathogenesis and clinical management

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been a major challenge to be faced in recent years. While adults suffered the highest morbidity and mortality rates of coronavirus disease 2019, children were thought to be exclusively asymptomatic or to present with mild conditions. However, around April 2020, there was an outbreak of a new clinical syndrome related to SARS-CoV-2 in children - multisystemic inflammatory syndrome in children (MIS-C) - which comprises a severe and uncon-trolled hyperinflammatory response with multiorgan involvement. The Centers for Disease Control and Prevention considers a suspected case of MIS-C an individual aged < 21 years presenting with fever, high inflammatory markers levels, and evidence of clinically severe illness, with multisystem (> 2) organ involvement, no alternative plausible diagnoses, and positive for recent SARS-CoV-2 infection. Despite its severity, there are no definitive disease management guidelines for this condition. Conversely, the complex pathogenesis of MIS-C is still not completely understood, although it seems to rely upon immune dysregulation. Hence, in this study, we aim to bring together current evidence regarding the pathogenic mechanisms of MIS-C, clinical picture and management, in order to provide insights for clinical practice and implications for future research directions.

Leveraging multi-tier healthcare facility network simulations for capacity planning in a pandemic

The COVID-19 pandemic has placed severe demands on healthcare facilities across the world, and in several countries, makeshift COVID-19 centres have been operationalised to handle patient overflow. In developing countries such as India, the public healthcare system (PHS) is organised as a hierarchical network with patient flows from lower-tier primary health centres (PHC) to mid-tier community health centres (CHC) and downstream to district hospitals (DH). In this study, we demonstrate how a network-based modelling and simulation approach utilising generic modelling principles can (a) quantify the extent to which the existing facilities in the PHS can effectively cope with the forecasted COVID-19 caseload; and (b) inform decisions on capacity at makeshift COVID-19 Care Centres (CCC) to handle patient overflows. We apply the approach to an empirical study of a local PHS comprising ten PHCs, three CHCs, one DH and one makeshift CCC. Our work demonstrates how the generic modelling approach finds extensive use in the development of simulations of multi-tier facility networks that may contain multiple instances of generic simulation models of facilities at each network tier. Further, our work demonstrates how multi-tier healthcare facility network simulations can be leveraged for capacity planning in health crises.

Inference on a Multi-Patch Epidemic Model with Partial Mobility, Residency, and Demography: Case of the 2020 COVID-19 Outbreak in Hermosillo, Mexico

Most studies modeling population mobility and the spread of infectious diseases, particularly those using meta-population multi-patch models, tend to focus on the theoretical properties and numerical simulation of such models. As such, there is relatively scant literature focused on numerical fit, inference, and uncertainty quantification of epidemic models with population mobility. In this research, we use three estimation techniques to solve an inverse problem and quantify its uncertainty for a human-mobility-based multi-patch epidemic model using mobile phone sensing data and confirmed COVID-19-positive cases in Hermosillo, Mexico. First, we utilize a Brownian bridge model using mobile phone GPS data to estimate the residence and mobility parameters of the epidemic model. In the second step, we estimate the optimal model epidemiological parameters by deterministically inverting the model using a Darwinian-inspired evolutionary algorithm (EA)-that is, a genetic algorithm (GA). The third part of the analysis involves performing inference and uncertainty quantification in the epidemic model using two Bayesian Monte Carlo sampling methods: t-walk and Hamiltonian Monte Carlo (HMC). The results demonstrate that the estimated model parameters and incidence adequately fit the observed daily COVID-19 incidence in Hermosillo. Moreover, the estimated parameters from the HMC method yield large credible intervals, improving their coverage for the observed and predicted daily incidences. Furthermore, we observe that the use of a multi-patch model with mobility yields improved predictions when compared to a single-patch model.

Are Measles-Mumps-Rubella (MMR) Antibodies Friends or Foes for Covid-19 Disease?

Many factors have been implicated in the pathogenesis and severity of COVID-19 pandemic. A wide variation in the susceptibility for SARS-CoV-2 infection among different population, gender and age has been observed. Multiple studies investigated the relationship between the antibody's titre of previously vaccinated individuals and the susceptibility of coronavirus infection, to find a rapid effective therapy for this pandemic. This study focused on the association between measles-mumps-rubella (MMR) antibodies titre and the severity of COVID-19 infection. We aimed to investigate the correlation between the antibody's titre of MMR and the SARS-CoV-2 infection susceptibility and disease severity, in a cohort of COVID-19 Egyptian patients, compared to a control group. MMR antibody titre was measured using enzyme Linked Immune Sorbent Assay; (ELISA) for 136 COVID-19 patients and 44 healthy individuals, as control group. There were high levels of measles and mumps antibodies titer in the deteriorating cases, which could not protect from SARS-CoV-2 infection. However, the rubella antibodies might protect from SARS-CoV-2 infection, but once the infection occurs, it may aggravate the risk of case deterioration. MMR antibodies could be used as a guideline for COVID-19 symptom-severity and, in turn, may be considered as an economic prognostic marker used for early protection from multiple autoimmune organ failure.

Response characteristics of indigenous microbial community in polycyclic aromatic hydrocarbons (PAHs) contaminated aquifers under polyethylene microplastics stress: A microcosmic experimental study

To understand the response characteristics of indigenous microbial community in PAH-contaminated aquifers to the coexistence of microplastics. In this paper, we constructed a groundwater microecosystem using lithologic media collected from the field and subjected it to the stress of a polyethylene microplastics (PE-MPs) concentration gradient. By conducting adsorption experiments and 16S rRNA sequencing, we revealed the growth, structure, metabolism, and resistance mechanisms of the indigenous microbial community in the aquifer lithologic media exposed to varying levels of co-stress from PE-MPs and phenanthrene. Our findings suggest that the adsorption capacity of aquifer lithologic media for phenanthrene is significantly weaker than that of PE-MPs. Additionally, our observations indicated that small particle lithologic media had a greater adsorption capacity for phenanthrene than large particle lithologic media. The presence of PE-MPs was found to increase both the abundance and diversity of microbial communities, although the relationship was not linear with the content of PE-MPs. When exposed to the combined stress of PE-MPs and phenanthrene, the relative abundance of Proteobacteria decreased while that of Bacteroidetes increased. Several genera belonging to Proteobacteria (Aeromonas, Desulfovibrio, Klebsiella, Pantoea, and Microvirgula) and Bacteroidetes (Macellibacteroides and Bacteroides) occupied a central position in the microbial community interaction network and showed significant correlations with other genera. Furthermore, an increase in the proportion of genera capable of degrading various refractory organics was observed. The presence of PE-MPs increased the phenanthrene content in the aquifer lithologic media, thereby intensifying the inhibitory effect on indigenous microbial community in this environment. Despite an increase in the phenanthrene content of aquifer lithologic media due to the presence of PE-MPs, indigenous microbial community in this environment exhibited resistance to the combined inhibition of PE-MPs and phenanthrene through a series of resistance mechanisms. These mechanisms included strengthening the N-cycle process, enhancing metabolic capacity for phenanthrene, improving perception, response, and adaptation to changes in the external environment or intracellular state, modifying the transmembrane transport of the cell membrane to the substrate, and regulating life processes.

Functionalized hydrogels in neural injury repairing

Repairing injuries to the nervous system has always been a prominent topic in clinical research. Direct suturing and nerve displacement surgery are the primary treatment options, but they may not be suitable for long nerve injuries and may require sacrificing the functionality of other autologous nerves. With the emergence of tissue engineering, hydrogel materials have been identified as a promising technology with clinical translation potential for repairing nervous system injuries due to their excellent biocompatibility and ability to release or deliver functional ions. By controlling their composition and structure, hydrogels can be Functionalized and almost fully matched with nerve tissue and even simulate nerve conduction function and mechanical properties. Thus, they are suitable for repairing injuries to both the central and peripheral nervous systems. This article provides a review of recent research progress in functionalized hydrogels for nerve injury repair, highlighting the design differences among various materials and future research directions. We strongly believe that the development of functionalized hydrogels has great potential for improving the clinical treatment of nerve injuries.

Classification of Diabetes Using Feature Selection and Hybrid Al-Biruni Earth Radius and Dipper Throated Optimization

INTRODUCTION

In public health, machine learning algorithms have been used to predict or diagnose chronic epidemiological disorders such as diabetes mellitus, which has reached epidemic proportions due to its widespread occurrence around the world. Diabetes is just one of several diseases for which machine learning techniques can be used in the diagnosis, prognosis, and assessment procedures.

METHODOLOGY

In this paper, we propose a new approach for boosting the classification of diabetes based on a new metaheuristic optimization algorithm. The proposed approach proposes a new feature selection algorithm based on a dynamic Al-Biruni earth radius and dipper-throated optimization algorithm (DBERDTO). The selected features are then classified using a random forest classifier with its parameters optimized using the proposed DBERDTO.

RESULTS

The proposed methodology is evaluated and compared with recent optimization methods and machine learning models to prove its efficiency and superiority. The overall accuracy of diabetes classification achieved by the proposed approach is 98.6%. On the other hand, statistical tests have been conducted to assess the significance and the statistical difference of the proposed approach based on the analysis of variance (ANOVA) and Wilcoxon signed-rank tests.

CONCLUSIONS

The results of these tests confirmed the superiority of the proposed approach compared to the other classification and optimization methods.

Research progress of electrode shapes in EWOD-based digital microfluidics

Digital microfluidics (DMF) is an innovative technology used for precise manipulation of liquid droplets. This technology has garnered significant attention in both industrial applications and scientific research due to its unique advantages. Among the key components of DMF, the driving electrode plays a role in facilitating droplet generation, transportation, splitting, merging, and mixing. This comprehensive review aims to present an in-depth understanding of the working principle of DMF particularly focusing on the Electrowetting On Dielectric (EWOD) method. Furthermore, it examines the impact of driving electrodes with varying geometries on droplet manipulation. By analyzing and comparing their characteristics, this review offers valuable insights and a fresh perspective on the design and application of driving electrodes in DMF based on the EWOD approach. Lastly, an assessment of the development trend and potential applications of DMF concludes the review, providing an outlook for future prospects in the field.

Preparation and characterization of different micro/nano structures on the surface of bredigite scaffolds

The preparation of controllable micro/nano structures on the surface of the bredigite scaffold is expected to exhibit the same support and osteoconductive capabilities as living bone. However, the hydrophobicity of the white calciμm silicate scaffold surface restricts the adhesion and spreading of osteoblasts. Furthermore, during the degradation process of the bredigite scaffold, the release of Ca2+ results in an alkaline environment around the scaffold, which inhibits the growth of osteoblasts. In this study, the three-dimensional geometry of the Primitive surface in the three-periodic minimal surface with an average curvature of 0 was used as the basis for the scaffold unit cell, and a white hydroxyapatite scaffold was fabricated via photopolymerization-based 3D printing. Nanoparticles, microparticles, and micro-sheet structures with thicknesses of 6 μm, 24 μm, and 42 μm, respectively, were prepared on the surface of the porous scaffold through a hydrothermal reaction. The results of the study indicate that the micro/nano surface did not affect the morphology and mineralization ability of the macroporous scaffold. However, the transition from hydrophobic to hydrophilic resulted in a rougher surface and an increase in compressive strength from 45 to 59-86 MPa, while the adhesion of the micro/nano structures enhanced the scaffold's ductility. In addition, after 8 days of degradation, the pH of the degradation solution decreased from 8.6 to around 7.6, which is more suitable for cell growth in the hμman body. However, there were issues of slow degradation and high P element concentration in the degradation solution for the microscale layer group during the degradation process, so the nanoparticle and microparticle group scaffolds could provide effective support and a suitable environment for bone tissue repair.

Systematics and biogeography of Anoura cultrata (Mammalia, Chiroptera, Phyllostomidae): a morphometric, niche modeling, and genetic perspective, with a taxonomic reappraisal of the genus

The nectar-feeding bats of the genus Anoura are widely distributed in the Neotropics, but are most speciose in the Andes. Anoura cultrata is a rare mid-elevation bat occurring in South and Central America. It is thought to be one of the few bat species exemplifying a latitudinal cline in body size. We address three systematic and biogeographic questions: 1) is the geographic variation in A. cultrata continuous, as argued to justify its current monotypic status? 2) do ecogeographic barriers to dispersal affect such variation? and 3) how do the genetic divergence and biogeography of the species compare to those of other members of the genus? To answer these questions, we used morphometric analyses, ecological niche modeling, and DNA barcoding. We divided the samples of A. cultrata into six geographic groups, delimited by topographic depressions separating mountain systems. We did not find significant correlations between body size and the geographic coordinates within five groups. Therefore, we conclude that ecogeographic barriers to dispersal between the regions occupied by such groups influenced morphometric variation in A. cultrata, and that despite its general north to south reduction in body size, the species does not show continuous clinal variation. A recent phylogenetic study of the genus Anoura concluded that it contains seven valid species. Our DNA barcoding analysis and morphological examination indicated that at least 10 species should be recognized, including A. peruana distinct from A. geoffroyi, and A. aequatoris and A. luismanueli distinct from A. caudifer. Moreover, we show that Central and South American populations of A. cultrata differ from each other at least at the subspecific level, thus we respectively refer to them as A. cultrata cultrata and as A. c. brevirostrum. Similarly, we refer to Central American and Mexican populations of 'A. geoffroyi' as A. peruana lasiopyga, and to their South American counterparts as A. p. peruana. The range of the latter subspecies reaches northeastern Venezuela. The Andes from southern Colombia to northern Peru appear to be the ancestral range of the genus.

3D and 4D Bioprinting Technologies: A Game Changer for the Biomedical Sector?

Bioprinting is an innovative and emerging technology of additive manufacturing (AM) and has revolutionized the biomedical sector by printing three-dimensional (3D) cell-laden constructs in a precise and controlled manner for numerous clinical applications. This approach uses biomaterials and varying types of cells to print constructs for tissue regeneration, e.g., cardiac, bone, corneal, cartilage, neural, and skin. Furthermore, bioprinting technology helps to develop drug delivery and wound healing systems, bio-actuators, bio-robotics, and bio-sensors. More recently, the development of four-dimensional (4D) bioprinting technology and stimuli-responsive materials has transformed the biomedical sector with numerous innovations and revolutions. This issue also leads to the exponential growth of the bioprinting market, with a value over billions of dollars. The present study reviews the concepts and developments of 3D and 4D bioprinting technologies, surveys the applications of these technologies in the biomedical sector, and discusses their potential research topics for future works. It is also urged that collaborative and valiant efforts from clinicians, engineers, scientists, and regulatory bodies are needed for translating this technology into the biomedical, pharmaceutical, and healthcare systems.

Community dynamics of bumblebee across elevation gradients and habitat mosaics in Chitwan Annapurna Landscape, Nepal

The species composition of bumblebees (Bombus species) across the elevation gradients in Chitwan-Annapurna Landscape (CHAL) was studied from April to November 2019. We performed opportunistic surveys to collect the bumblebee specimens. The walking transects were followed in the accessible places along the Kaligandaki, Marshyandi, and Budhigandaki river basins in different habitats (e.g., agricultural, forest, grassland and home garden). We identified 16 Bombus species from the sampling areas. The highest relative abundance was of B. haemorrhoidalis (20%), followed by B. festivus (20%) and B. eximius (19%). The least abundant species were B. branickii, B. miniatus, B. novus, and B. pressus with 1% relative abundance of each. We examined the effects of elevation on bumblebee richness and found a significant relationship. The Highest species richness was detected in the mid-elevation. Likewise, the highest species richness and diversity were found in the forest habitat in Gorkha site (n = 12, Shannon index H' = 2.18) followed by the grassland habitat of the Mustang site (n = 11, Shannon index H' = 2.10). Whereas, comparatively, species diversity was higher in habitats of the Gorkha site comparing Manang and Mustang. The elevation gradients create immense variations in microclimatic conditions and vegetation dynamics, which influence bumblebee abundance, species richness and diversities in different habitats in the study area. The mid-elevation range (2000-3000 m asl) of CHAL exhibited the highest species richness probably due to the higher availability of pollinator-dependent flowering plants in this range. The landcover composition and anthropogenic activities along the elevation gradient is the governing factor for the species composition, distribution and diversity of bumblebees in CHAL. We recommend to decision-makers for formulating their conservation strategies under a socio-ecological framework.

A multi-model forecasting approach for solid waste generation by integrating demographic and socioeconomic factors: a case study of Prayagraj, India

Projecting municipal solid waste generation and identifying socioeconomic factors affecting waste generation is crucial for integrated waste management strategies. The present research work focuses on the projection of municipal solid waste (MSW) generation in Prayagraj, India, based on demographics and socioeconomic factors, using long short-term memory (LSTM), autoregressive integrated moving average (ARIMA), and incremental increase models (IIM). The model was integrated with nine socioeconomic variables to improve accuracy. The influence of socioeconomic variables on MSW generation was evaluated using correlation and fuzzy logic approaches. Waste generation data collected from the Central Pollution Control Board (CPCB) from 1997 to 2015 were used to train the models. The results of the correlation study indicate that population growth, employment, and households have a substantial impact on waste generation rates. Root mean squared error (RMSE), mean absolute percent error (MAPE), and coefficient of determination (R²) suggest that LSTM is the best model to forecast MSW generation in Prayagraj, India. The R² value indicates that the LSTM is more accurate (0.92) than ARIMA (0.72) and IIM (0.70). LSTM projection indicates that the city will have a population of 1.6 million by 2031, and waste generation will increase by 70.6% in 2031.

Production of monoclonal antibodies for therapeutic purposes: A review

Monoclonal antibodies (mAbs) have been used in the development of immunotherapies that target a variety of diseases, such as cancer, autoimmune diseases, and even viral infections; they play a key role in immunization and are expected after vaccination. However, some conditions do not promote the development of neutralizing antibodies. Production and use of mAbs, generated in biofactories, represent vast potential as aids in immunological responses when the organism cannot produce them on their own, these convey unique specificity by recognizing and targeting specific antigen. Antibodies can be defined as heterotetrametric glycoproteins of symmetric nature, and they participate as effector proteins in humoral responses. Additionally, there are different types of mAbs (murine, chimeric, humanized, human, mAbs as Antibody-drug conjugates and bispecific mAbs) discussed in the present work. When these molecules are produced in vitro as mAbs, several common techniques, such as hybridomas or phage display are used. There are several preferred cell lines that function as biofactories, for the production of mAbs, the selection of which rely on the variation of adaptability, productivity and both phenotypic and genotypic shifts. After the cell expression systems and culture techniques are used, there are diverse specialized downstream processes to achieve desired yield and isolation as well as product quality and characterization. Novel perspectives regarding these protocols represent a potential improvement for mAbs high-scale production.

Removing siloxanes and hydrogen sulfide from landfill gases with biochar and activated carbon filters

Landfill gas (LFG) is formed by microorganisms within a landfill; it can be utilized as a renewable fuel in power plants. Impurities such as hydrogen sulfide and siloxanes can cause significant damage to gas engines and turbines. The aim of this study was to determine the filtration efficiencies of biochar products made of birch and willow to remove hydrogen sulfides, siloxanes, and volatile organic compounds from the gas streams compared to activated carbon. Experiments were conducted on a laboratory scale with model compounds and in a real LFG power plant where microturbines are used to generate power and heat. The biochar filters removed heavier siloxanes effectively in all of the tests. However, the filtration efficiency for volatile siloxane and hydrogen sulfide declined quickly. Biochars are promising filter materials but require further research to improve their performance.

A Critical Review on Classified Excipient Sodium-Alginate-Based Hydrogels: Modification, Characterization, and Application in Soft Tissue Engineering

Alginates are polysaccharides that are produced naturally and can be isolated from brown sea algae and bacteria. Sodium alginate (SA) is utilized extensively in the field of biological soft tissue repair and regeneration owing to its low cost, high biological compatibility, and quick and moderate crosslinking. In addition to their high printability, SA hydrogels have found growing popularity in tissue engineering, particularly due to the advent of 3D bioprinting. There is a developing curiosity in tissue engineering with SA-based composite hydrogels and their potential for further improvement in terms of material modification, the molding process, and their application. This has resulted in numerous productive outcomes. The use of 3D scaffolds for growing cells and tissues in tissue engineering and 3D cell culture is an innovative technique for developing in vitro culture models that mimic the in vivo environment. Especially compared to in vivo models, in vitro models were more ethical and cost-effective, and they stimulate tissue growth. This article discusses the use of sodium alginate (SA) in tissue engineering, focusing on SA modification techniques and providing a comparative examination of the properties of several SA-based hydrogels. This review also covers hydrogel preparation techniques, and a catalogue of patents covering different hydrogel formulations is also discussed. Finally, SA-based hydrogel applications and future research areas concerning SA-based hydrogels in tissue engineering were examined.

A review on control and abatement of soil pollution by heavy metals: Emphasis on artificial intelligence in recovery of contaminated soil

"Save Soil Save Earth" is not just a catchphrase; it is a necessity to protect soil ecosystem from the unwanted and unregulated level of xenobiotic contamination. Numerous challenges such as type, lifespan, nature of pollutants and high cost of treatment has been associated with the treatment or remediation of contaminated soil, whether it be either on-site or off-site. Due to the food chain, the health of non-target soil species as well as human health were impacted by soil contaminants, both organic and inorganic. In this review, the use of microbial omics approaches and artificial intelligence or machine learning has been comprehensively explored with recent advancements in order to identify the sources, characterize, quantify, and mitigate soil pollutants from the environment for increased sustainability. This will generate novel insights into methods for soil remediation that will reduce the time and expense of soil treatment.

Construction of an endoplasmic reticulum stress-related signature in lung adenocarcinoma by comprehensive bioinformatics analysis

BACKGROUND

Lung Adenocarcinoma (LUAD) is a major component of lung cancer. Endoplasmic reticulum stress (ERS) has emerged as a new target for some tumor treatments.

METHODS

The expression and clinical data of LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) database, followed by acquiring ERS-related genes (ERSGs) from the GeneCards database. Differentially expressed endoplasmic reticulum stress-related genes (DE-ERSGs) were screened and used to construct a risk model by Cox regression analysis. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were plotted to determine the risk validity of the model. Moreover, enrichment analysis of differentially expressed genes (DEGs) between the high- and low- risk groups was conducted to investigate the functions related to the risk model. Furthermore, the differences in ERS status, vascular-related genes, tumor mutation burden (TMB), immunotherapy response, chemotherapy drug sensitivity and other indicators between the high- and low- risk groups were studied. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the mRNA expression levels of prognostic model genes.

RESULTS

A total of 81 DE-ERSGs were identified in the TCGA-LUAD dataset, and a risk model, including HSPD1, PCSK9, GRIA1, MAOB, COL1A1, and CAV1, was constructed by Cox regression analysis. K-M and ROC analyses showed that the high-risk group had a low survival, and the Area Under Curve (AUC) of ROC curves of 1-, 3- and 5-years overall survival was all greater than 0.6. In addition, functional enrichment analysis suggested that the risk model was related to collagen and extracellular matrix. Furthermore, differential analysis showed vascular-related genes FLT1, TMB, neoantigen, PD-L1 protein (CD274), Tumor Immune Dysfunction and Exclusion (TIDE), and T cell exclusion score were significantly different between the high- and low-risk groups. Finally, qRT-PCR results showed that the mRNA expression levels of 6 prognostic genes were consistent with the analysis.

CONCLUSION

A novel ERS-related risk model, including HSPD1, PCSK9, GRIA1, MAOB, COL1A1, and CAV1, was developed and validated, which provided a theoretical basis and reference value for ERS-related fields in the study and treatment of LUAD.

An application of social marketing for promoting HIV testing in Iran

BACKGROUND

It has been estimated that 60,000 Iranians have been infected with HIV/AIDS and only 36% of them are aware of their status. This study aimed to design, implement and evaluate a social marketing campaign to promote HIV testing in Boyer-Ahmad County, Kohgiluyeh, and Boyer-Ahmad Province, southwest of Iran.

MATERIALS AND METHODS

This study was a quasi-experimental pretest-posttest without a control group, developed based on a social marketing assessment and response tool. To design the intervention formative research was conducted, comprised of four focus group discussion sessions with 42 participants of the target community along with seven in-depth semi-structured personal interviews with health care providers involved in the HIV/AIDS Program. Data analysis was done manually using content analysis and the main content was formulated for the campaign. Afterward, the slogan and messages of the campaign were developed. The campaign's materials including banners, posters, pamphlets, referral forms, and short messages were designed, pretested, and revised. Ultimately, the campaign was conducted for one month in October 2019. To determine the effectiveness of the campaign, the rate of referrals to the Center for Behavioral Health Counseling Services (CBHCS), for three months before and after the campaign, was compared.

RESULTS

Qualitative findings identified that the majority of the interviewees mentioned that the main reasons for the low rate of referrals to get tested for HIV were lack of awareness and information about HIV/AIDS and its diagnosis as well as the free and confidential tests available from the CBHCS. Moreover, the stigma associated with HIV/AIDS was another important reason for low referrals for testing. The rate of referrals for HIV testing in the three months leading up to the campaign was 18, 32, and 23 people, and three months after the campaign was 64, 81, and 44 individuals; respectively. The results of the multivariate analysis demonstrated that the campaign had increased the rates of referrals for HIV testing through its significant influence on females, and individuals with academic degrees.

CONCLUSION

It can be concluded that the social marketing campaign was successful in persuading people to get tested for HIV.

Next Generation Sequencing Revolutionizes Organismal Biology Research in Bats

The advent of next generation sequencing technologies (NGS) has greatly accelerated our understanding of critical aspects of organismal biology from non-model organisms. Bats form a particularly interesting group in this regard, as genomic data have helped unearth a vast spectrum of idiosyncrasies in bat genomes associated with bat biology, physiology, and evolution. Bats are important bioindicators and are keystone species to many eco-systems. They often live in proximity to humans and are frequently associated with emerging infectious diseases, including the COVID-19 pandemic. Nearly four dozen bat genomes have been published to date, ranging from drafts to chromosomal level assemblies. Genomic investigations in bats have also become critical towards our understanding of disease biology and host-pathogen coevolution. In addition to whole genome sequencing, low coverage genomic data like reduced representation libraries, resequencing data, etc. have contributed significantly towards our understanding of the evolution of natural populations, and their responses to climatic and anthropogenic perturbations. In this review, we discuss how genomic data have enhanced our understanding of physiological adaptations in bats (particularly related to ageing, immunity, diet, etc.), pathogen discovery, and host pathogen co-evolution. In comparison, the application of NGS towards population genomics, conservation, biodiversity assessment, and functional genomics has been appreciably slower. We reviewed the current areas of focus, identifying emerging topical research directions and providing a roadmap for future genomic studies in bats.

Bioprinting in Microgravity

Bioprinting as an extension of 3D printing offers capabilities for printing tissues and organs for application in biomedical engineering. Conducting bioprinting in space, where the gravity is zero, can enable new frontiers in tissue engineering. Fabrication of soft tissues, which usually collapse under their own weight, can be accelerated in microgravity conditions as the external forces are eliminated. Furthermore, human colonization in space can be supported by providing critical needs of life and ecosystems by 3D bioprinting without relying on cargos from Earth, e.g., by development and long-term employment of living engineered filters (such as sea sponges-known as critical for initiating and maintaining an ecosystem). This review covers bioprinting methods in microgravity along with providing an analysis on the process of shipping bioprinters to space and presenting a perspective on the prospects of zero-gravity bioprinting.

High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing

Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative RNA splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, a method that removes most artifact cDNAs and concatenates multiple cDNAs for PacBio circular consensus sequencing (CCS) to achieve high-throughput and high-accuracy single-cell RNA isoform sequencing. HIT-scISOseq can yield >10 million high-accuracy long-reads in a single PacBio Sequel II SMRT Cell 8M. We also report the development of scISA-Tools that demultiplex HIT-scISOseq concatenated reads into single-cell cDNA reads with >99.99% accuracy and specificity. We apply HIT-scISOseq to characterize the transcriptomes of 3375 corneal limbus cells and reveal cell-type-specific isoform expression in them. HIT-scISOseq is a high-throughput, high-accuracy, technically accessible method and it can accelerate the burgeoning field of long-read single-cell transcriptomics.

City-scale model for COVID-19 epidemiology with mobility and social activities represented by a set of hidden Markov models

BACKGROUND AND OBJECTIVE

SARS-CoV-2 emerged by the end of 2019 and became a global pandemic due to its rapid spread. Various outbreaks of the disease in different parts of the world have been studied, and epidemiological analyses of these outbreaks have been useful for developing models with the aim of tracking and predicting the spread of epidemics. In this paper, an agent-based model that predicts the local daily evolution of the number of people hospitalized in intensive care due to COVID-19 is presented.

METHODS

An agent-based model has been developed, taking into consideration the most relevant characteristics of the geography and climate of a mid-size city, its population and pathology statistics, and its social customs and mobility, including the state of public transportation. In addition to these inputs, the different phases of isolation and social distancing are also taken into account. By means of a set of hidden Markov models, the system captures and reproduces virus transmission associated with the stochastic nature of people's mobility and activities in the city. The spread of the virus in the host is also simulated by following the stages of the disease and by considering the existence of comorbidities and the proportion of asymptomatic carriers.

RESULTS

As a case study, the model was applied to Paraná city (Entre Ríos, Argentina) in the second half of 2020. The model adequately predicts the daily evolution of people hospitalized in intensive care due to COVID-19. This adequacy is reflected by the fact that the prediction of the model (including its dispersion), as with the data reported in the field, never exceeded 90% of the capacity of beds installed in the city. In addition, other epidemiological variables of interest, with discrimination by age range, were also adequately reproduced, such as the number of deaths, reported cases, and asymptomatic individuals.

CONCLUSIONS

The model can be used to predict the most likely evolution of the number of cases and hospital bed occupancy in the short term. By adjusting the model to match the data on hospitalizations in intensive care units and deaths due to COVID-19, it is possible to analyze the impact of isolation and social distancing measures on the disease spread dynamics. In addition, it allows for simulating combinations of characteristics that would lead to a potential collapse in the health system due to lack of infrastructure as well as predicting the impact of social events or increases in people's mobility.

Computational cross-species views of the hippocampal formation

The discovery of place cells and head direction cells in the hippocampal formation of freely foraging rodents has led to an emphasis of its role in encoding allocentric spatial relationships. In contrast, studies in head-fixed primates have additionally found representations of spatial views. We review recent experiments in freely moving monkeys that expand upon these findings and show that postural variables such as eye/head movements strongly influence neural activity in the hippocampal formation, suggesting that the function of the hippocampus depends on where the animal looks. We interpret these results in the light of recent studies in humans performing challenging navigation tasks which suggest that depending on the context, eye/head movements serve one of two roles-gathering information about the structure of the environment (active sensing) or externalizing the contents of internal beliefs/deliberation (embodied cognition). These findings prompt future experimental investigations into the information carried by signals flowing between the hippocampal formation and the brain regions controlling postural variables, and constitute a basis for updating computational theories of the hippocampal system to accommodate the influence of eye/head movements.

Application of a sustainable location index approach to landfill site selection in Monterrey, Mexico

Landfilling is the main method to manage municipal solid waste (MSW) in Latin America due to the economic, technological and political characteristics of the region. The disposal of MSW in landfill sites may affect the quality of the environment and compromise a considerable share of the municipal budgets. The selection of suitable sites reduces the environmental and economic impact of landfills. In the present study the sustainable location index (SLI) is proposed as a methodology to assess environmentally, and economically, sanitary landfill site selection in the Metropolitan Area of Monterrey, a representative large-size city of Latin America. EVIAVE methodology was modified to include administrative and economic dimensions, which are assessed as a sustainable approach using together the SLI integrated with geospatial and multicriteria analysis tools. The assessment showed that the zones with the lowest SLI changes drastically when the importance of the economic or environmental factor varies. This result suggest that the inclusion of sustainability in landfill site selection decision-making is complex and it may requires the inclusion of local particularities such as municipal budgets, policies of MSW management and public perception about environmental deterioration.

MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication

With the evolution of multicellularity, communication among cells in different tissues and organs became pivotal to life. Molecular basis of such communication has long been studied, but genome-wide screens for genes and other biomolecules mediating tissue-tissue signaling are lacking. To systematically identify inter-tissue mediators, we present a novel computational approach MultiCens (Multilayer/Multi-tissue network Centrality measures). Unlike single-layer network methods, MultiCens can distinguish within- vs. across-layer connectivity to quantify the "influence" of any gene in a tissue on a query set of genes of interest in another tissue. MultiCens enjoys theoretical guarantees on convergence and decomposability, and performs well on synthetic benchmarks. On human multi-tissue datasets, MultiCens predicts known and novel genes linked to hormones. MultiCens further reveals shifts in gene network architecture among four brain regions in Alzheimer's disease. MultiCens-prioritized hypotheses from these two diverse applications, and potential future ones like "Multi-tissue-expanded Gene Ontology" analysis, can enable whole-body yet molecular-level systems investigations in humans.

Structural Mechanical Properties of 3D Printing Biomimetic Bone Replacement Materials

One of the primary challenges in developing bone substitutes is to create scaffolds with mechanical properties that closely mimic those of regenerated tissue. Scaffolds that mimic the structure of natural cancellous bone are believed to have better environmental adaptability. In this study, we used the porosity and thickness of pig cancellous bone as biomimetic design parameters, and porosity and structural shape as differential indicators, to design a biomimetic bone beam scaffold. The mechanical properties of the designed bone beam model were tested using the finite element method (FEM). PCL/β-TCP porous scaffolds were prepared using the FDM method, and their mechanical properties were tested. The FEM simulation results were compared and validated, and the effects of porosity and pore shape on the mechanical properties were analyzed. The results of this study indicate that the PCL/β-TCP scaffold, prepared using FDM 3D printing technology for cancellous bone tissue engineering, has excellent integrity and stability. Predicting the structural stability using FEM is effective. The triangle pore structure has the most stability in both simulations and tests, followed by the rectangle and honeycomb shapes, and the diamond structure has the worst stability. Therefore, adjusting the porosity and pore shape can change the mechanical properties of the composite scaffold to meet the mechanical requirements of customized tissue engineering.

Development of top-down cortical propagations in youth

Hierarchical processing requires activity propagating between higher- and lower-order cortical areas. However, functional neuroimaging studies have chiefly quantified fluctuations within regions over time rather than propagations occurring over space. Here, we leverage advances in neuroimaging and computer vision to track cortical activity propagations in a large sample of youth (n = 388). We delineate cortical propagations that systematically ascend and descend a cortical hierarchy in all individuals in our developmental cohort, as well as in an independent dataset of densely sampled adults. Further, we demonstrate that top-down, descending hierarchical propagations become more prevalent with greater demands for cognitive control as well as with development in youth. These findings emphasize that hierarchical processing is reflected in the directionality of propagating cortical activity and suggest top-down propagations as a potential mechanism of neurocognitive maturation in youth.

A survey on agents applications in healthcare: Opportunities, challenges and trends

BACKGROUND AND OBJECTIVE

The agent abstraction is a powerful one, developed decades ago to represent crucial aspects of artificial intelligence research. The meaning has transformed over the years and now there are different nuances across research communities. At its core, an agent is an autonomous computational entity capable of sensing, acting, and capturing interactions with other agents and its environment. This review examines how agent-based techniques have been implemented and evaluated in a specific and very important domain, i.e. healthcare research.

METHODS

We survey key areas of agent-based research in healthcare, e.g. individual and collective behaviours, communicable and non-communicable diseases, and social epidemiology. We propose a systematic search and critical review of relevant recent works, introduced by an exploratory network analysis.

RESULTS

Network analysis enables to devise out 5 main research clusters, the most active authors, and 4 main research topics.

CONCLUSIONS

Our findings support discussion of some future directions for increasing the value of agent-based approaches in healthcare.

Effect of Substituents on the Intramolecular n→π* Interaction in 3-[2-(Dimethylamino) phenyl] propanal: A Computational Study

n→π* non-covalent interaction (NCI) and hydrogen bond have similarity in terms of delocalization of the electron density between the two orbitals involved in the interaction. Hydrogen bond (X-H···Y) involves delocalization of the lone pair electrons (n) on the Y atom into the σ* orbital of the X-H bond. In contrast, the n→π* interaction deals with delocalizing the lone pair electrons (n) on the N, O, or S atom into the π* orbital of a C═O group or aromatic ring. Herein, we have shown a resemblance of this weak n→π* interaction with the relatively stronger hydrogen bond in terms of folding the side chains in flexible molecules. This work reports the study of folding of the flexible side-chain in 3-[2-(dimethylamino) phenyl] propanal (DMAPhP) through a N···C═O n→π* interaction using various computational approaches such as NBO, QTAIM, and NCI analyses. The folding of the molecule by the n→π* interaction observed in this study is found to be similar to that present in the secondary structures of peptides or proteins through hydrogen bonding interactions. Interestingly, the stabilization of the global minimum conformer of DMAPhP by the n→π* interaction demonstrates the importance of this NCI in providing conformational preferences in molecular systems. Another important finding of this study is that the theoretical redshift obtained in the C═O stretching frequency of the most stable conformer of the DMAPhP is contributed mostly by the n→π* interaction as the C═O group is not involved in hyperconjugation with any neighboring heteroatom, which is a common phenomenon in any ester or amide. We have also demonstrated here that the strength of the intramolecular n→π* interaction can be modulated by varying the electronic substituents at the para position of the donor group involved in the interaction.

Thermal Conductivity of Aluminum Alloys-A Review

Aluminum alloys have been extensively used as heatproof and heat-dissipation components in automotive and communication industries, and the demand for aluminum alloys with higher thermal conductivity is increasing. Therefore, this review focuses on the thermal conductivity of aluminum alloys. First, we formulate the theory of thermal conduction of metals and effective medium theory, and then analyze the effect of alloying elements, secondary phases, and temperature on the thermal conductivity of aluminum alloys. Alloying elements are the most crucial factor, whose species, existing states, and mutual interactions significantly affect the thermal conductivity of aluminum. Alloying elements in a solid solution weaken the thermal conductivity of aluminum more dramatically than those in the precipitated state. The characteristics and morphology of secondary phases also affect thermal conductivity. Temperature also affects thermal conductivity by influencing the thermal conduction of electrons and phonons in aluminum alloys. Furthermore, recent studies on the effects of casting, heat treatment, and AM processes on the thermal conductivity of aluminum alloys are summarized, in which processes mainly affect thermal conductivity by varying existing states of alloying elements and the morphology of secondary phases. These analyses and summaries will further promote the industrial design and development of aluminum alloys with high thermal conductivity.

The value of discharged case fatality rate in estimating the severity and epidemic trend of COVID-19 in China: a novel epidemiological study

Aim

The main objective of this study was to explore the value of the discharged case fatality rate (DCFR) in estimating the severity and epidemic trend of COVID-19 in China.

Subjects and methods

Epidemiological data on COVID-19 in China and Hubei Province were obtained from the National Health Commission of the People's Republic of China from January 20, 2020, to March 31, 2020. The number of daily new confirmed cases, daily confirmed deaths, daily recovered cases, the proportion of daily deaths and total deaths of discharged cases were collected, and the total discharge case fatality rate (tDCFR), daily discharge case fatality rate (dDCFR), and stage-discharge case fatality rate (sDCFR) were calculated. We used the R software (version 3.6.3, R core team) to apply a trimmed exact linear time method to search for changes in the mean and variance of dDCFR in order to estimate the pandemic phase from dDCFR.

Results

The tDCFR of COVID-19 in China was 4.16% until March 31, 2020. According to the pattern of dDCFR, the pandemic was divided into four phases: the transmission phase (from January 20 to February 2), the epidemic phase (from February 3 to February 14), the decline phase (from February 15 to February 22), and the sporadic phase (from February 23 to March 31). The sDCFR for these four phases was 43.18% (CI 39.82-46.54%), 13.23% (CI 12.52-13.94%), 5.86% (CI 5.49-6.22%), and 1.61% (CI 1.50-1.72%), respectively.

Conclusion

DCFR has great value in assessing the severity and epidemic trend of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-023-01895-4.

Dapagliflozin Versus Vildagliptin as an Adjuvant to Metformin in Patients With Type 2 Diabetes Mellitus: A Randomized, Open-label Study

INTRODUCTION

The rising burden of diabetes mellitus led to the development of novel drugs like dapagliflozin and vildagliptin. Their efficacies in chronic diabetic patients have been thoroughly studied. However, there is a paucity of comparative studies on these drugs in newly diagnosed diabetic patients. The endpoints of our study were changes in glycated hemoglobin (HbA_1c), fasting blood glucose (FBG), and postprandial blood glucose (PPBG) at 24 weeks from baseline.

METHODS

This randomized, open-label, 24-week study was conducted at Kalinga Institute of Medical Sciences, Bhubaneswar, India, from January 2021 to November 2022. The participants were randomized in a 1:1 ratio to receive tablets of either dapagliflozin 10mg once daily or vildagliptin 50mg once daily as an add-on to metformin 500-2000 mg. The analyses were performed in the per-protocol population. We used R software v. 4.1.1 (R Foundation, Indianapolis, IN) for data analysis.

RESULTS

114 (83.8%) of 136 enrolled participants completed this study. The mean age of the study population was 41.08±5.17 years. Additionally, 52 (45.6%) of them were females. The mean changes in HbA_1c from baseline were -1.19 (95% CI: -1.36 to -1.03) and -1.28 (95% CI: -1.37 to -1.18) in dapagliflozin and vildagliptin groups, respectively (p=0.21). The median changes in FBG and PPBG in both groups were -38.76, -46.13 (p=0.07), and -51.84, -53.56 (p=0.14), respectively.

CONCLUSIONS

Reductions in HbA_1c, FBG, and PPBG with add-on treatment of vildagliptin were more pronounced than dapagliflozin after a 24-week intervention. However, the differences were not statistically significant.

Modeling of the PHEMA-gelatin scaffold enriched with graphene oxide utilizing finite element method for bone tissue engineering

The development of computer-aided facilities has contributed to the optimization of tissue engineering techniques due to the reduction in necessary practical assessments and the removal of animal or human-related ethical issues. Herein, a bone scaffold based on poly (2-hydroxyethyl methacrylate) (PHEMA), gelatin and graphene oxide (GO), was simulated by SOLIDWORKS and ABAQUS under a normal compression force using finite element method (FEM). Concerning the mechanotransduction impact, GO could support the stability of the structure and reduce the possibility of the failure resulting in the integrity and durability of the scaffold efficiency which would be beneficial for osteogenic differentiation.

Biotribological behaviour, biodegradability and osteocompatibility of Mg-3Zn/HA composite based intramedullary inserts in avian model

Bioactivity, structural integrity and tribological behaviour of biodegradable orthopaedic fracture fixing accessories considerably impact their actual performance in the body environment. Immune system in the living body quickly responds to the wear debris as foreign material and begins a complex inflammatory response. Magnesium (Mg) based biodegradable implants are widely studied for temporary orthopaedic applications, due to their similar elastic modulus and density to natural bones. However, Mg is highly vulnerable to corrosion and tribological damage in actual service conditions. To address these challenges via a combined approach, the Mg-3 wt% Zinc (Zn)/x hydroxyapatite (HA, x = 0, 5 and 15 wt%) based composites (fabricated via spark plasma sintering route) are evaluated in terms of biotribocorrosion and in-vivo biodegradation and osteocompatibility behaviour in an avian model. The addition of 15 wt% HA in the Mg-3Zn matrix has significantly enhanced the wear and corrosion resistance in the physiological environment. X-ray radiograph analysis of the Mg-HA-based intramedullary inserts implanted in the humerus bone of birds showed consistent progression of degradation and positive tissue response up to 18 weeks. The 15 wt% HA reinforced composites have shown better bone regeneration properties than other inserts. This study provides new insights into developing next-generation Mg-HA-based biodegradable composites for temporary orthopaedic implants, with excellent biotribocorrosion behaviour.

A Survey on harnessing the Applications of Mobile Computing in Healthcare during the COVID-19 Pandemic: Challenges and Solutions

The COVID-19 pandemic ravaged almost every walk of life but it triggered many challenges for the healthcare system, globally. Different cutting-edge technologies such as Internet of things (IoT), machine learning, Virtual Reality (VR), Big data, Blockchain etc. have been adopted to cope with this menace. In this regard, various surveys have been conducted to highlight the importance of these technologies. However, among these technologies, the role of mobile computing is of paramount importance which is not found in the existing literature. Hence, this survey in mainly targeted to highlight the significant role of mobile computing in alleviating the impacts of COVID-19 in healthcare sector. The major applications of mobile computing such as software-based solutions, hardware-based solutions and wireless communication-based support for diagnosis, prevention, self-symptom reporting, contact tracing, social distancing, telemedicine and treatment related to coronavirus are discussed in detailed and comprehensive fashion. A state-of-the-art work is presented to identify the challenges along with possible solutions in adoption of mobile computing with respect to COVID-19 pandemic. Hopefully, this research will help the researchers, policymakers and healthcare professionals to understand the current research gaps and future research directions in this domain. To the best level of our knowledge, this is the first survey of its type to address the COVID-19 pandemic by exploring the holistic contribution of mobile computing technologies in healthcare area.

Free-ranging livestock affected the spatiotemporal behavior of the endangered snow leopard (Panthera uncia)

Long recognized as a threat to wildlife, particularly for large carnivores, livestock grazing in protected areas can potentially undermine conservation objectives. The interspecific interactions among livestock, snow leopards (Panthera uncia), and their wild prey in fragile Asian highland ecosystems have been a subject of debate. We strategically deployed 164 camera traps in the Wolong National Nature Reserve to systematically investigate the activities of snow leopards, their primary wild ungulate prey species, and free-ranging livestock. We found that snow leopard habitat use was influenced by both wild prey and livestock. Blue sheep served as the main wild prey that spatially attracted snow leopards and coexisted with yaks while free-ranging yaks significantly restricted snow leopard habitat use both temporally and spatially. This study challenges the conventional understanding that livestock indirectly impacts large carnivores by competing with and displacing wild prey. Our findings highlight that free-ranging yaks within the alpine canyon terrain could directly limit snow leopard habitat use, suggesting a potential risk of grazing in reducing apex predator distribution and jeopardizing their populations. Consequently, managing their coexistence in shared habitats requires a more nuanced approach. Furthermore, our research underscores the importance of further research efforts aimed at enhancing our comprehension of the complex interplay within animal communities and ecosystems. This knowledge will contribute to the development of informed, evidence-based conservation strategies and policies.

Chronic stress is associated with specific path integration deficits

Repeated exposure to stress (chronic stress) can cause excess levels of circulating cortisol and has detrimental influences on various cognitive functions including long-term memory and navigation. However, it remains an open question whether chronic stress affects path integration, a navigational strategy that presumably relies on the functioning of grid cells in the medial entorhinal cortex. The entorhinal cortex is a brain region in the medial temporal lobe, which contains multiple cell types involved in spatial navigation (and episodic memory), and a high number of corticosteroid receptors, predisposing it as a potential target of cortisol effects. Here, our goal was to investigate the association between chronic stress and path integration performance. We assessed chronic stress via hair cortisol concentration (physiological measure) and the Perceived Stress Questionnaire (subjective measure) in 52 female participants aged 22-65 years. Path integration was measured using a virtual homing task. Linear mixed models revealed selective impairments associated with chronic stress that depended on error type and environmental features. When focusing on distance estimations in the path integration task, we observed a significant relationship to hair cortisol concentrations indicating impaired path integration particularly during trials with higher difficulty in participants with high hair cortisol concentrations. This relationship especially emerged in the absence of spatial cues (a boundary or a landmark), and particularly in participants who reported high levels of subjectively experienced chronic stress. The findings are in line with the hypothesis that chronic stress compromises path integration, possibly via an effect on the entorhinal grid cell system.

An integrated single-cell transcriptomic dataset for non-small cell lung cancer

As single-cell RNA sequencing (scRNA-seq) has emerged as a great tool for studying cellular heterogeneity within the past decade, the number of available scRNA-seq datasets also rapidly increased. However, reuse of such data is often problematic due to a small cohort size, limited cell types, and insufficient information on cell type classification. Here, we present a large integrated scRNA-seq dataset containing 224,611 cells from human primary non-small cell lung cancer (NSCLC) tumors. Using publicly available resources, we pre-processed and integrated seven independent scRNA-seq datasets using an anchor-based approach, with five datasets utilized as reference and the remaining two, as validation. We created two levels of annotation based on cell type-specific markers conserved across the datasets. To demonstrate usability of the integrated dataset, we created annotation predictions for the two validation datasets using our integrated reference. Additionally, we conducted a trajectory analysis on subsets of T cells and lung cancer cells. This integrated data may serve as a resource for studying NSCLC transcriptome at the single cell level.

Development of Boron-Containing PVA-Based Cryogels with Controllable Boron Releasing Rate and Altered Influence on Osteoblasts

Cryogel formation is an effective approach to produce porous scaffolds for tissue engineering. In this study, cryogelation was performed to produce boron-containing scaffolds for bone tissue engineering. A combination of the synthetic polymer, poly(vinyl alcohol) (PVA), and the natural polymers, chitosan and starch, was used to formulate the cryogels. Boron was used with a dual purpose: as an additive to alter gelation properties, and to exploit its bioactive effect since boron has been found to be involved in several metabolic pathways, including the promotion of bone growth. This project designs a fabrication protocol enabling the competition of both physical and chemical cross-linking reactions in the cryogels using different molecular weight PVA and borax content (boron source). Using a high ratio of high-molecular-weight PVA resulted in the cryogels exhibiting greater mechanical properties, a lower degradation rate (0.6–1.7% vs. 18–20%) and a higher borax content release (4.98 vs. 1.85, 1.08 nanomole) in contrast to their counterparts with low-molecular-weight PVA. The bioactive impacts of the released borax on cellular behaviour were investigated using MG63 cells seeded into the cryogel scaffolds. It was revealed that the borax-containing scaffolds and their extracts induced MG63 cell migration and the formation of nodule-like aggregates, whilst cryogel scaffolds without borax did not. Moreover, the degradation products of the scaffolds were analysed through the quantification of boron release by the curcumin assay. The impact on cellular response in a scratch assay confirmed that borax released by the scaffold into media (~0.4 mg/mL) induced bone cell migration, proliferation and aggregation. This study demonstrated that boron-containing three-dimensional PVA/starch–chitosan scaffolds can potentially be used within bone tissue engineering applications.

Pedot:PSS/Graphene Oxide (GO) Ternary Nanocomposites for Electrochemical Applications

Among conductive polymers, poly(3,4 ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) has been widely used as an electrode material for supercapacitors, solar cells, sensors, etc. Although PEDOT:PSS-based thin films have acceptable properties such as good capacitive and electrical behaviour and biocompatibility, there are still several challenges to be overcome in their use as an electrode material for supercapacitors. For this reason, the aim of this work is to fabricate and characterise ternary nanocomposites based on PEDOT:PSS and graphene oxide (GO), blended with green additives (glucose (G) or ascorbic acid (AA)), which have the benefits of being environmentally friendly, economical, and easy to use. The GO reduction process was first accurately investigated and demonstrated by UV-Vis and XRD measurements. Three-component inks have been developed, and their morphological, rheological, and surface tension properties were evaluated, showing their printability by means of Aerosol Jet® Printing (AJ®P), an innovative direct writing technique belonging to the Additive Manufacturing (AM) for printed electronics applications. Thin films of the ternary nanocomposites were produced by drop casting and spin coating techniques, and their capacitive behaviour and chemical structures were evaluated through Cyclic Voltammetry (CV) tests and FT-IR analyses. CV tests show an increment in the specific capacitance of AAGO-PEDOT up to 31.4 F/g and excellent overtime stability compared with pristine PEDOT:PSS, suggesting that this ink can be used to fabricate supercapacitors in printed (bio)-electronics. The inks were finally printed by AJ®P as thin films (10 layers, 8 × 8 mm) and chemically analysed by FT-IR, demonstrating that all components of the formulation were successfully aerosolised and deposited on the substrate.