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In the quest for early cancer diagnosis, early identification and treatment are paramount. Recently, ctDNA detection has emerged as a viable avenue for early screening of cancer. The examination of ctDNA in fluid biopsies has gained substantial attention in tumor diagnosis and therapy. Both the scientific community and industry are actively exploring this field. However, developing cost-effective, portable, and real-time ctDNA measurement methods using conventional gene detection equipment poses a significant challenge. This challenge has led to the exploration of alternative approaches. Electrochemical biosensors, distinguished by their heightened sensitivity, remarkable specificity, affordability, and excellent portability, have emerged as a promising avenue for ctDNA detection. This review is dedicated to the specific focus on ctDNA detection, highlighting recent advancements in this evolving detection technology. We aimed to reference previous studies related to ctDNA-targeted cancer detection using electrochemical biosensors to advocate the utilization of electrochemical biosensors in healthcare diagnostics. Further research is imperative for the effective integration of ctDNA analysis into point-of-care cancer testing. Innovative approaches utilizing multiple markers need to be explored to advance this technology and make substantial contributions to societal well-being. [ABSTRACT FROM AUTHOR]

Scrub typhus is an acute illness caused by the bacteria Orientia tsutsugamushi and is transmitted by mites. Scrub typhus propagates via infected chigger bites (larval stage). Diagnosing scrub typhus is challenging due to its ability to mimic symptoms of other febrile illnesses. Conventional methods such as Weil‐Felix, ELISA, and PCR are available for diagnosing scrub typhus. The Weil‐Felix test was formerly used in developing nations to diagnose scrub typhus, but it is not recommended since it lacks both specificity and sensitivity. IFA and ELISA are superior for detecting scrub typhus; however, they are not as effective at detecting the illness in its early stages and require convalescent sampling to confirm positive samples. However, because the Orientia tsutsugamushi serotypes differ in their genetic makeup, PCR‐based approaches have become less applicable despite their higher specificity and sensitivity. Nanomaterial‐based biosensing could help detect scrub typhus early due to its high surface area, electrical conductance, and chemical stability. This study emphasizes the need for point‐of‐care detection of this under‐diagnosed but fatal disease, emphasizing the importance of nanobiosensors in early diagnosis. The pathophysiology of scrub typhus, standard diagnostic procedures, and the critical role that nanobiosensors play in the early detection of scrub typhus are discussed. [ABSTRACT FROM AUTHOR]

Globally, people are in great threat due to the highly spreading of viral infectious diseases. Every year like 100–300 million cases of infections are found, and among them, above 80% are not recognized and irrelevant. Dengue virus (DENV) is an arbovirus infection that currently infects people most frequently. DENV encompasses four viral serotypes, and they each express comparable sign. From a mild febrile sickness to a potentially fatal dengue hemorrhagic fever, dengue can induce a variety of symptoms. Presently, the globe is being challenged by the untimely identification of dengue infection. Therefore, this review summarizes advances in the detection of dengue from conventional methods (nucleic acid‐based, polymerase chain reaction‐based, and serological approaches) to novel biosensors. This work illustrates an extensive study of the current designs and fabrication approaches involved in the formation of electrochemical biosensors for untimely identifications of dengue. Additionally, in electrochemical sensing of DENV, we skimmed through significances of biorecognition molecules like lectins, nucleic acid, and antibodies. The introduction of emerging techniques such as the CRISPR/Cas' system and their integration with biosensing platforms has also been summarized. Furthermore, the review revealed the importance of electrochemical approach compared with traditional diagnostic methods. [ABSTRACT FROM AUTHOR]

A major goal of cancer biology is to understand the mechanisms underlying tumorigenesis driven by somatically acquired mutations. Two distinct types of computational methodologies have emerged: one focuses on analyzing clustering of mutations within protein sequences and 3D structures, while the other characterizes mutations by leveraging the topology of protein-protein interaction network. Their insights are largely non-overlapping, offering complementary strengths. Here, we established a unified, end-to-end 3D structurally-informed protein interaction network propagation framework, NetFlow3D, that systematically maps the multiscale mechanistic effects of somatic mutations in cancer. The establishment of NetFlow3D hinges upon the Human Protein Structurome, a comprehensive repository we compiled that incorporates the 3D structures of every single protein as well as the binding interfaces of all known protein interactions in humans. NetFlow3D leverages the Structurome to integrate information across atomic, residue, protein and network levels: It conducts 3D clustering of mutations across atomic and residue levels on protein structures to identify potential driver mutations. It then anisotropically propagates their impacts across the protein interaction network, with propagation guided by the specific 3D structural interfaces involved, to identify significantly interconnected network "modules", thereby uncovering key biological processes underlying disease etiology. Applied to 1,038,899 somatic protein-altering mutations in 9,946 TCGA tumors across 33 cancer types, NetFlow3D identified 1,4444 significant 3D clusters throughout the Human Protein Structurome, of which ~55% would not have been found if using only experimentally-determined structures. It then identified 26 significantly interconnected modules that encompass ~8-fold more proteins than applying standard network analyses. NetFlow3D and our pan-cancer results can be accessed from http://netflow3d.yulab.org.