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ABSTRACT - We report a case of Burkholderia mallei causing glanders in a 73-year-old patient from the Northeast Region of Brazil. The patient was hospitalized with severe pneumonia. PCR and genomic sequencing confirmed B. mallei in pleural drainage. Genotyping revealed a novel genotype, emphasizing the need for genetic surveillance in zoonotic infections.

The number of druggable tumor-specific molecular aberrations has grown substantially in the past decade, with a significant survival benefit obtained from biomarker matching therapies in several cancer types. Molecular pathology has therefore become fundamental not only to inform on tumor diagnosis and prognosis but also to drive therapeutic decisions in daily practice. The introduction of next-generation sequencing technologies and the rising number of large-scale tumor molecular profiling programs across institutions worldwide have revolutionized the field of precision oncology. As comprehensive genomic analyses become increasingly available in both clinical and research settings, healthcare professionals are faced with the complex tasks of result interpretation and translation. This review summarizes the current and upcoming approaches to implement precision cancer medicine, highlighting the challenges and potential solutions to facilitate the interpretation and to maximize the clinical utility of molecular profiling results. We describe novel molecular characterization strategies beyond tumor DNA sequencing, such as transcriptomics, immunophenotyping, epigenetic profiling, and single-cell analyses. We also review current and potential applications of liquid biopsies to evaluate blood-based biomarkers, such as circulating tumor cells and circulating nucleic acids. Last, lessons learned from the existing limitations of genotype-derived therapies provide insights into ways to expand precision medicine beyond genomics.

Human pluripotent stem cells have the potential to change the way in which human diseases are cured. Clinical-grade human embryonic stem cells and human induced pluripotent stem cells have to be created according to current good manufacturing practices and regulations. Quality and safety must be of the highest importance when humans’ lives are at stake. With the rising number of clinical trials, there is a need for a consensus on hPSCs characterization. Here, we summarize mandatory and ′for information only′ characterization methods with release criteria for the establishment of clinical-grade hPSC lines.

In the last 20 years, surface plasmon resonance (SPR) and its advancement with imaging (SPRi) emerged as a suitable and reliable platform in clinical analysis for label-free, sensitive, and real-time monitoring of biomolecular interactions. Thus, we report in this review the state of the art of clinical target detection with SPR-based biosensors in complex matrices (e.g., serum, saliva, blood, and urine) as well as in standard solution when innovative approaches or advanced instrumentations were employed for improved detection. The principles of SPR-based biosensors are summarized first, focusing on the physical properties of the transducer, on the assays design, on the immobilization chemistry, and on new trends for implementing system analytical performances (e.g., coupling with nanoparticles (NPs). Then we critically review the detection of analytes of interest in molecular diagnostics, such as hormones (relevant also for anti-doping control) and biomarkers of interest in inflammatory, cancer, and heart failure diseases. Antibody detection is reported in relation to immune disorder diagnostics. Subsequently, nucleic acid targets are considered for revealing genetic diseases (e.g., point mutation and single nucleotides polymorphism, SNPs) as well as new emerging clinical markers (microRNA) and for pathogen detection. Finally, examples of pathogen detection by immunosensing were also analyzed. A parallel comparison with the reference methods was duly made, indicating the progress brought about by SPR technologies in clinical routine analysis.

Microfluidic paper-based devices (μPADs) and wearable devices have been highly studied to be used as diagnostic tools due to their advantages such as simplicity and ability to provide instrument-free fast results. Diseases such as periodontitis and diabetes mellitus can potentially be detected through these devices by the detection of important biomarkers. This study describes the development of μPADs through craft cutter printing for glucose and nitrite salivary diagnostics. In addition, the use of μPADs integrated into a mouthguard as a wearable sensor for glucose monitoring is also presented. μPADs were designed to contain two detection zones for glucose and nitrite assays and a sampling zone interconnected by microfluidic channels. Initially, the analytical performance of the proposed μPADs was investigated and it provided linear behavior (r2 ≥ 0.994) in the concentration ranges between 0 to 2.0 mmol L−1 and 0 to 400 μmol L−1 for glucose and nitrite, respectively. Under the optimized conditions, the limits of detection achieved for glucose and nitrite were 27 μmol L−1 and 7 μmol L−1, respectively. Human saliva samples were collected from healthy individuals and patients previously diagnosed with periodontitis or diabetes and then analyzed on the proposed μPADs. The results found using μPADs revealed higher glucose concentration values in saliva collected from patients diagnosed with diabetes mellitus and greater nitrite concentrations in saliva collected from patients diagnosed with periodontitis, as expected. The results obtained on μPADs did not differ statistically from those measured by spectrophotometry. With the aim of developing paper-based wearable sensors, μPADs were integrated, for the first time, into a silicone mouthguard using a 3D-printed holder. The proof of concept was successfully demonstrated through the monitoring of the glucose concentration in saliva after the ingestion of chocolate. According to the results reported herein, paper-based microfluidic devices offer great potential for salivary diagnostics, making their integration into a silicone mouthguard possible, generating simple, low-cost, instrument-free, and powerful wearable sensors.

Introduction Coronavirus disease 2019 (COVID-19) is an unprecedented pandemic, threatening human health worldwide. The need to produce novel small-molecule inhibitors against the ongoing pandemic has resulted in the use of drugs such as chloroquine, azithromycin, dexamethasone, favipiravir, ribavirin, remdesivir and azithromycin. Moreover, the reports of the clinical trials of these drugs proved to produce detrimental effects on patients with side effects like nephrotoxicity, retinopathy, cardiotoxicity and cardiomyopathy. Recognizing the need for effective and non-harmful therapeutic candidates to combat COVID-19, we aimed to develop promising drugs against SARS-COV-2. Discussion In the current investigation, high-throughput virtual screening was performed using the Comprehensive Marine Natural Products Database against five non-structural proteins: Nsp3, Nsp5, Nsp12, Nsp13 and Nsp15. Furthermore, standard precision (SP) docking, extra precision (XP) docking, binding free energy calculation and absorption, distribution, metabolism, excretion and toxicity studies were performed using the Schrӧdinger suite. The top-ranked 5 hits obtained by computational studies exhibited to possess a greater binding affinity with the selected non-structural proteins. Amongst the five hits, CMNPD5804, CMNPD20924 and CMNPD1598 hits were utilized to design a novel molecule ( D ) that has the capability of interacting with all the key residues in the pocket of the selected non-structural proteins. Furthermore, 200 ns of molecular dynamics simulation studies provided insight into the binding modes of D within the catalytic pocket of selected proteins. Conclusion Hence, it is concluded that compound D could be a promising inhibitor against these non-structural proteins. Nevertheless, there is still a need to conduct in vitro and in vivo studies to support our findings.

Despite having been underappreciated in favor of their protein-coding counterparts for a long time, long noncoding RNAs (lncRNAs) have emerged as functional molecules, which defy the central dogma of molecular biology, with clear implications in cancer. Altered expression levels of some of these large transcripts in human body fluids have been related to different cancer conditions that turns them into potential noninvasive cancer biomarkers. In this review, a brief discussion about the importance and current challenges in the determination of lncRNAs associated to cancer is provided. Different electrochemical nucleic acid-based strategies for lncRNAs detection are critically described. Future perspectives and remaining challenges for the practical implementation of these methodologies in clinical medicine are also discussed.

Context Chronic inflammation is a risk factor for diabetes, but it can also be a complication of diabetes, leading to severe diabetes and causing many other clinical manifestations. Inflammation is a major emerging complication in both type I and type II diabetes, which causes increasing interest in targeting inflammation to improve and control diabetes. Diabetes with insulin resistance and impaired glucose utilization in humans and their underlying mechanism is not fully understood. But a growing understanding of the intricacy of the insulin signaling cascade in diabetic inflammatory cells reveals potential target genes and their proteins responsible for severe insulin resistance. With this baseline concept, the current project explores the binding affinities of the hyaluronic acid anti-diabetic compounds conjugates to such target proteins in diabetic inflammatory cells and their molecular geometries. A range of 48 anti-diabetic compounds was screened against aldose reductase binding pocket 3 protein target through in silico molecular docking, and results revealed that three compounds viz, metformin (CID:4091), phenformin (CID:8249), sitagliptin (CID:4,369,359), possess significant binding affinity out of 48 chosen drugs. Further, these three anti-diabetic compounds were conjugated with hyaluronic acid (HA), and their binding affinity and their molecular geometrics towards aldose reductase enzyme were screened compared with the free form of the drug. The molecular geometries of three shortlisted drugs (metformin, phenformin, sitagliptin) and their HA conjugates were also explored through density functional theory studies, and it proves their good molecular geometry towards pocket 3 of aldose reductase target. Further, MD simulation trajectories affirm that HA conjugates possess good binding affinity and simulation trajectories with protein target aldose reductase than a free form of the drug. Our current study unravels the new mechanism of drug targeting for diabetes through HA conjugation for inflammatory diabetes. HA conjugates act as novel drug candidates for treating inflammatory diabetes; however, it needs further human clinical trials. Methods For ligand structure, PubChem, ACD chem sketch, and online structure file generator platform are utilized for ligand preparation. Target protein aldose reductase obtained from protein database (PDB). For molecular docking analysis, AutoDock Vina (Version 4) was utilized. pKCSM online server used to predict ADMET properties of the above three shortlisted drugs from the docking study. Using mol-inspiration software (version 2011.06), three shortlisted compounds’ bioactivity scores were predicted. DFT analysis for three shortlisted anti-diabetic drugs and their hyaluronic acid conjugates were calculated using a functional B3LYP set of Gaussian 09 software. Molecular dynamics simulation calculations for six chosen protein–ligand complexes were done through YASARA dynamics software and AMBER14 force field.

Purpose The aim was to describe the prevalence, molecular epidemiology and clinical manifestations of human bocavirus (HBoV) in patients attended at a tertiary hospital in Barcelona, Spain. Methods From October 2014 to May 2017, respiratory specimens from paediatric patients were collected for respiratory viruses’ laboratory-confirmation. Phylogenetic analyses from partial VP1 sequences were performed from all HBoV laboratory-confirmed specimens. Clinical features were retrospectively studied. Results 178/10271 cases were HBoV laboratory-confirmed. The median age was 1.53 (IQR 1.0–2.3). Co-detection was highly reported (136; 76%). All viruses belonged into HBoV1 genotype but one into HBoV2. Non-reported mutations were observed and two sites were suggestive to be under negative selection. 61% (109/178) cases had lower RTI (LRTI), of whom 84 had co-detections (77%) and 76 had comorbidities (70%). LRTI was the cause of hospitalization in 85 out of 109 cases (78%), and no differences were found regarding severity factors during hospitalization between co- and single-detections, except for median length of respiratory support, which was longer in cases with co-detections. Conclusions Close monitoring of predominant HBoV1 showed a high similarity between viruses. The presence of comorbidities might explain the high prevalence of LRTI. Symptomatology in HBoV single-detected cases suggest that HBoV is a true pathogen.

The epidemic of infectious diseases caused by contagious pathogens is a life-threatening hazard to the entire human population worldwide. A timely and accurate diagnosis is the critical link in the fight against infectious diseases. Aptamer-based biosensors, the so-called aptasensors, employ nucleic acid aptamers as bio-receptors for the recognition of target pathogens of interest. This review focuses on the design strategies as well as state-of-the-art technologies of aptasensor-based diagnostics for infectious pathogens (mainly bacteria and viruses), covering the utilization of three major signal transducers, the employment of aptamers as recognition moieties, the construction of versatile biosensing platforms (mostly micro and nanomaterial-based), innovated reporting mechanisms, and signal enhancement approaches. Advanced point-of-care testing (POCT) for infectious disease diagnostics are also discussed highlighting some representative ready-to-use devices to address the urgent needs of currently prevalent coronavirus disease 2019 (COVID-19). Pressing issues in aptamer-based technology and some future perspectives of aptasensors are provided for the implementation of aptasensor-based diagnostics into practical application. Graphical Abstract