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Simple Summary: This review explores the wide-ranging applications of Next-Generation Sequencing (NGS) techniques in veterinary medicine for companion animals. It addresses the need for advanced diagnostic and treatment approaches in veterinary care. The aims include understanding parasitic transmission, infectious disease dynamics, metabolic disorders, autoimmune diseases, oncological processes, and genetic predispositions in animals. The article demonstrates NGS's efficacy in comprehensive parasite profiling, rapid pathogen identification, personalized tumor analysis, and genetic disease elucidation. Conclusions highlight the transformative potential of NGS in enhancing veterinary diagnostics, treatment planning, and disease management for companion animals. The review's insights promise to revolutionize veterinary care, enabling precise and tailored treatments, improving animal health outcomes, and advancing overall societal well-being through healthier and happier companion animals. Next-Generation Sequencing (NGS) techniques have revolutionized veterinary medicine for cats and dogs, offering insights across various domains. In veterinary parasitology, NGS enables comprehensive profiling of parasite populations, aiding in understanding transmission dynamics and drug resistance mechanisms. In infectious diseases, NGS facilitates rapid pathogen identification, characterization of virulence factors, and tracking of outbreaks. Moreover, NGS sheds light on metabolic processes by elucidating gene expression patterns and metabolic pathways, essential for diagnosing metabolic disorders and designing tailored treatments. In autoimmune diseases, NGS helps identify genetic predispositions and molecular mechanisms underlying immune dysregulation. Veterinary oncology benefits from NGS through personalized tumor profiling, mutation analysis, and identification of therapeutic targets, fostering precision medicine approaches. Additionally, NGS plays a pivotal role in veterinary genetics, unraveling the genetic basis of inherited diseases and facilitating breeding programs for healthier animals. Physiological investigations leverage NGS to explore complex biological systems, unraveling gene–environment interactions and molecular pathways governing health and disease. Application of NGS in treatment planning enhances precision and efficacy by enabling personalized therapeutic strategies tailored to individual animals and their diseases, ultimately advancing veterinary care for companion animals. [ABSTRACT FROM AUTHOR]

Biomaterials embody a groundbreaking paradigm shift in the field of drug delivery and human applications. Their versatility and adaptability have not only enriched therapeutic outcomes but also significantly reduced the burden of adverse effects. This work serves as a comprehensive overview of biomaterials, with a particular emphasis on their pivotal role in drug delivery, classifying them in terms of their biobased, biodegradable, and biocompatible nature, and highlighting their characteristics and advantages. The examination also delves into the extensive array of applications for biomaterials in drug delivery, encompassing diverse medical fields such as cancer therapy, cardiovascular diseases, neurological disorders, and vaccination. This work also explores the actual challenges within this domain, including potential toxicity and the complexity of manufacturing processes. These challenges emphasize the necessity for thorough research and the continuous development of regulatory frameworks. The second aim of this review is to navigate through the compelling terrain of recent advances and prospects in biomaterials, envisioning a healthcare landscape where they empower precise, targeted, and personalized drug delivery. The potential for biomaterials to transform healthcare is staggering, as they promise treatments tailored to individual patient needs, offering hope for improved therapeutic efficacy, fewer side effects, and a brighter future for medical practice. [ABSTRACT FROM AUTHOR]

Gliomas, a prevalent category of primary malignant brain tumors, pose formidable clinical challenges due to their invasive nature and limited treatment options. The current therapeutic landscape for gliomas is constrained by a "one-size-fits-all" paradigm, significantly restricting treatment efficacy. Despite the implementation of multimodal therapeutic strategies, survival rates remain disheartening. The conventional treatment approach, involving surgical resection, radiation, and chemotherapy, grapples with substantial limitations, particularly in addressing the invasive nature of gliomas. Conventional diagnostic tools, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), play pivotal roles in outlining tumor characteristics. However, they face limitations, such as poor biological specificity and challenges in distinguishing active tumor regions. The ongoing development of diagnostic tools and therapeutic approaches represents a multifaceted and promising frontier in the battle against this challenging brain tumor. The aim of this comprehensive review is to address recent advances in diagnostic tools and therapeutic approaches for gliomas. These innovations aim to minimize invasiveness while enabling the precise, multimodal targeting of localized gliomas. Researchers are actively developing new diagnostic tools, such as colorimetric techniques, electrochemical biosensors, optical coherence tomography, reflectometric interference spectroscopy, surface-enhanced Raman spectroscopy, and optical biosensors. These tools aim to regulate tumor progression and develop precise treatment methods for gliomas. Recent technological advancements, coupled with bioelectronic sensors, open avenues for new therapeutic modalities, minimizing invasiveness and enabling multimodal targeting with unprecedented precision. The next generation of multimodal therapeutic strategies holds potential for precision medicine, aiding the early detection and effective management of solid brain tumors. These innovations offer promise in adopting precision medicine methodologies, enabling early disease detection, and improving solid brain tumor management. This review comprehensively recognizes the critical role of pioneering therapeutic interventions, holding significant potential to revolutionize brain tumor therapeutics. [ABSTRACT FROM AUTHOR]

This study aimed to analyse clinical and laboratory findings in primary care patients with respiratory tract infections to distinguish the group more likely to receive antibiotic treatment. The study group consisted of 631 patients (264 males; 367 females) with a median age of 48 years (IQR 36–63 years). Analysed groups included patients treated with antibiotics (n = 269 patients; 43%) and those who recovered without antibiotic treatment (n = 362 patients; 57%). Patients receiving antibiotics were older (median 51 vs. 47 years; p = 0.008) and more commonly developed fever (77% vs. 25%, p < 0.0001) and cough (63% vs. 30%; p = 0.0014). Moreover, they more frequently presented wheezing and crackles upon physical examination (28% vs. 4% and 9% vs. 0.3%; p < 0.0001 and p < 0.0001, respectively). They also had more comorbidities and came to more follow-up visits (median of 4 vs. 3 and 2 vs. 1, p < 0.0001 and p < 0.0001, respectively). Patients receiving symptomatic therapy more often had positive point-of-care tests (POCTS)—20% vs. 7%; p = <0.0001. Multivariate analysis in our cohort found comorbidities complexity (odds ratio—OR 2.62; 95% confidence interval—1.54–4.46), fever (OR 32.59; 95%CI 19.15–55.47), crackles (OR 26.35; 95%CI 2.77–250.81) and the number of visits (OR 4.15; 95%CI 2.39–7.20) as factors increasing the probability of antibiotic treatment. Positive influenza POCTS reduced the risk of antibiotic therapy (OR 0.0015; 95%CI 0.0001–0.0168). [ABSTRACT FROM AUTHOR]

Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens. [ABSTRACT FROM AUTHOR]

Cryptococcus species are a major cause of life-threatening infections in immunocompromised and immunocompetent hosts. While most disease is caused by Cryptococcus neoformans, Cryptococcus gattii, a genotypically and phenotypically distinct species, is responsible for 11–33% of global cases of cryptococcosis. Despite best treatment, C. gattii infections are associated with early mortality rates of 10–25%. The World Health Organization's recently released Fungal Priority Pathogen List classified C. gattii as a medium-priority pathogen due to the lack of effective therapies and robust clinical and epidemiological data. This narrative review summarizes the latest research on the taxonomy, epidemiology, pathogenesis, laboratory testing, and management of C. gattii infections. [ABSTRACT FROM AUTHOR]

Simple Summary: Luteal deficiency is defined as reduced progesterone production by the corpus luteum, either in the amount or duration, or both. The clinical manifestations include primary infertility and pregnancy loss during the late embryonic/early fetal period (30–50 days post-AI). This work provides a clinical overview of the current understanding of luteal deficiency and its association with low fertility in dairy cows. Luteal deficiency is defined as reduced progesterone (P4) steroidogenesis by the corpus luteum (CL), either in the amount or duration, or both. This work provides a clinical overview of the current understanding of luteal deficiency and its association with low fertility in dairy cows. Low plasma P4 concentrations during the luteal phase post-artificial insemination (AI) are associated with lower conception rates. Treatments post-AI with P4, gonadotropin-releasing hormone (GnRH) or human chorionic gonadotropin (hCG) improve fertility in some conditions. Sub-luteal function during the late embryonic period (at pregnancy diagnosis, i.e., 28–34 days post-AI), is just one factor among other factors associated with pregnancy loss. Treatment with P4 in cows with one CL favors pregnancy maintenance, while GnRH treatment does the same in cows carrying twins. The diagnosis of sub-luteal function can be made clinically on the basis of plasma or milk P4 concentrations. Automated in-line milk P4 analysis systems to diagnose luteal activity emerge as a very interesting tool in dairy herds. Monitoring plasma or milk P4 concentrations with the help of Doppler ultrasonography to assess the CL function would allow individualizing the luteal phase support. [ABSTRACT FROM AUTHOR]

Virus pandemics have happened, are happening and will happen again. In recent decades, the rate of zoonotic viral spillover into humans has accelerated, mirroring the expansion of our global footprint and travel network, including the expansion of viral vectors and the destruction of natural spaces, bringing humans closer to wild animals. Once viral cross-species transmission to humans occurs, transmission cannot be stopped by cement walls but by developing barriers based on knowledge that can prevent or reduce the effects of any pandemic. Controlling a local transmission affecting few individuals is more efficient that confronting a community outbreak in which infections cannot be traced. Genetic detection, identification, and characterization of infectious agents using next-generation sequencing (NGS) has been proven to be a powerful tool allowing for the development of fast PCR-based molecular assays, the rapid development of vaccines based on mRNA and DNA, the identification of outbreaks, transmission dynamics and spill-over events, the detection of new variants and treatment of vaccine resistance mutations, the development of direct-acting antiviral drugs, the discovery of relevant minority variants to improve knowledge of the viral life cycle, strengths and weaknesses, the potential for becoming dominant to take appropriate preventive measures, and the discovery of new routes of viral transmission. [ABSTRACT FROM AUTHOR]

The role of E-cadherin in Hereditary Diffuse Gastric Cancer (HDGC) is unequivocal. Germline alterations in its encoding gene (CDH1) are causative of HDGC and occur in about 40% of patients. Importantly, while in most cases CDH1 alterations result in the complete loss of E-cadherin associated with a well-established clinical impact, in about 20% of cases the mutations are of the missense type. The latter are of particular concern in terms of genetic counselling and clinical management, as the effect of the sequence variants in E-cadherin function is not predictable. If a deleterious variant is identified, prophylactic surgery could be recommended. Therefore, over the last few years, intensive research has focused on evaluating the functional consequences of CDH1 missense variants and in assessing E-cadherin pathogenicity. In that context, our group has contributed to better characterize CDH1 germline missense variants and is now considered a worldwide reference centre. In this review, we highlight the state of the art methodologies to categorize CDH1 variants, as neutral or deleterious. This information is subsequently integrated with clinical data for genetic counseling and management of CDH1 variant carriers. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading diseases, causing deaths worldwide. Nearly 10 million deaths were reported in 2020 due to cancer alone. Several factors are involved in cancer progressions, such as lifestyle and genetic characteristics. According to a recent report, extracellular vesicles (EVs) are involved in cancer initiation, progression, and therapy failure. EVs can play a major role in intracellular communication, the maintenance of tissue homeostasis, and pathogenesis in several types of diseases. In a healthy person, EVs carry different cargoes, such as miRNA, lncRNA etc., to help other body functions. On the other hand, the same EV in a tumor microenvironment carries cargoes such as miRNA, lncRNA, etc., to initiate or help cancer progression at various stages. These stages may include the proliferation of cells and escape from apoptosis, angiogenesis, cell invasion, and metastasis, reprogramming energy metabolism, evasion of the immune response, and transfer of mutations. Tumor-derived EVs manipulate by altering normal functions of the body and affect the epigenetics of normal cells by limiting the genetic makeup through transferring mutations, histone modifications, etc. Tumor-derived EVs also pose therapy resistance through transferring drug efflux pumps and posing multiple drug resistances. Such EVs can also help as biomarkers for different cancer types and stages, which ultimately help with cancer diagnosis at early stages. In this review, we will shed light on EVs' role in performing normal functions of the body and their position in different hallmarks of cancer, in altering the genetics of a normal cell in a tumor microenvironment, and their role in therapy resistance, as well as the importance of EVs as diagnostic tools. [ABSTRACT FROM AUTHOR]

The psychiatric diagnostic procedure is currently based on self-reports that are subject to personal biases. Therefore, the diagnostic process would benefit greatly from data-driven tools that can enhance accuracy and specificity. In recent years, many studies have achieved promising results in detecting and diagnosing depression based on machine learning (ML) analysis. Despite these favorable results in depression diagnosis, which are primarily based on ML analysis of neuroimaging data, most patients do not have access to neuroimaging tools. Hence, objective assessment tools are needed that can be easily integrated into the routine psychiatric diagnostic process. One solution is to use behavioral data, which can be easily collected while still maintaining objectivity. The current paper summarizes the main ML-based approaches that use behavioral data in diagnosing depression and other psychiatric disorders. We classified these studies into two main categories: (a) laboratory-based assessments and (b) data mining, the latter of which we further divided into two sub-groups: (i) social media usage and movement sensors data and (ii) demographic and clinical information. The paper discusses the advantages and challenges in this field and suggests future research directions and implementations. The paper's overarching aim is to serve as a first step in synthetizing existing knowledge about ML-based behavioral diagnosis studies in order to develop interventions and individually tailored treatments in the future. [ABSTRACT FROM AUTHOR]

While investigating a signal of adaptive evolution in humans at the gene LARGE, we encountered an intriguing finding by Dr. Stefan Kunz that the gene plays a critical role in Lassa virus binding and entry. This led us to pursue field work to test our hypothesis that natural selection acting on LARGE—detected in the Yoruba population of Nigeria—conferred resistance to Lassa Fever in some West African populations. As we delved further, we conjectured that the "emerging" nature of recently discovered diseases like Lassa fever is related to a newfound capacity for detection, rather than a novel viral presence, and that humans have in fact been exposed to the viruses that cause such diseases for much longer than previously suspected. Dr. Stefan Kunz's critical efforts not only laid the groundwork for this discovery, but also inspired and catalyzed a series of events that birthed Sentinel, an ambitious and large-scale pandemic prevention effort in West Africa. Sentinel aims to detect and characterize deadly pathogens before they spread across the globe, through implementation of its three fundamental pillars: Detect, Connect, and Empower. More specifically, Sentinel is designed to detect known and novel infections rapidly, connect and share information in real time to identify emerging threats, and empower the public health community to improve pandemic preparedness and response anywhere in the world. We are proud to dedicate this work to Stefan Kunz, and eagerly invite new collaborators, experts, and others to join us in our efforts. [ABSTRACT FROM AUTHOR]

Background. Developmental Language Disorder (DLD) is frequent in childhood and may have long-term sequelae. By employing an evidence-based approach, this scoping review aims at identifying (a) early predictors of DLD; (b) the optimal age range for the use of screening and diagnostic tools; (c) effective diagnostic tools in preschool children. Methods. We considered systematic reviews, meta-analyses, and primary observational studies with control groups on predictive, sensitivity and specificity values of screening and diagnostic tools and psycholinguistic measures for the assessment of DLD in preschool children. We identified 37 studies, consisting of 10 systematic reviews and 27 primary studies. Results. Delay in gesture production, receptive and/or expressive vocabulary, syntactic comprehension, or word combination up to 30 months emerged as early predictors of DLD, a family history of DLD appeared to be a major risk factor, and low socioeconomic status and environmental input were reported as risk factors with lower predictive power. Optimal time for screening is suggested between age 2 and 3, for diagnosis around age 4. Because of the high variability of sensitivity and specificity values, joint use of standardized and psycholinguistic measures is suggested to increase diagnostic accuracy. Conclusions. Monitoring risk situations and employing caregivers' reports, clinical assessment and multiple linguistic measures are fundamental for an early identification of DLD and timely interventions. [ABSTRACT FROM AUTHOR]

The mitochondrial respiratory chain is the main site of reactive oxygen species (ROS) production in the cell. Although mitochondria possess a powerful antioxidant system, an excess of ROS cannot be completely neutralized and cumulative oxidative damage may lead to decreasing mitochondrial efficiency in energy production, as well as an increasing ROS excess, which is known to cause a critical imbalance in antioxidant/oxidant mechanisms and a "vicious circle" in mitochondrial injury. Due to insufficient energy production, chronic exposure to ROS overproduction consequently leads to the oxidative damage of life-important biomolecules, including nucleic acids, proteins, lipids, and amino acids, among others. Different forms of mitochondrial dysfunction (mitochondriopathies) may affect the brain, heart, peripheral nervous and endocrine systems, eyes, ears, gut, and kidney, among other organs. Consequently, mitochondriopathies have been proposed as an attractive diagnostic target to be investigated in any patient with unexplained progressive multisystem disorder. This review article highlights the pathomechanisms of mitochondriopathies, details advanced analytical tools, and suggests predictive approaches, targeted prevention and personalization of medical services as instrumental for the overall management of mitochondriopathy-related cascading pathologies. [ABSTRACT FROM AUTHOR]