The COVID-19 pandemic has infected millions worldwide, leaving a global burden for long-term care of COVID-19 survivors. It is thus imperative to study post-COVID (i.e., short-term) and long-COVID (i.e., long-term) effects, specifically as local and systemic pathophysiological outcomes of other coronavirus-related diseases (such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS)) were well-cataloged. We conducted a comprehensive review of adverse post-COVID health outcomes and potential long-COVID effects. We observed that such adverse outcomes were not localized. Rather, they affected different human systems, including: (i) immune system (e.g., Guillain–Barré syndrome, rheumatoid arthritis, pediatric inflammatory multisystem syndromes such as Kawasaki disease), (ii) hematological system (vascular hemostasis, blood coagulation), (iii) pulmonary system (respiratory failure, pulmonary thromboembolism, pulmonary embolism, pneumonia, pulmonary vascular damage, pulmonary fibrosis), (iv) cardiovascular system (myocardial hypertrophy, coronary artery atherosclerosis, focal myocardial fibrosis, acute myocardial infarction, cardiac hypertrophy), (v) gastrointestinal, hepatic, and renal systems (diarrhea, nausea/vomiting, abdominal pain, anorexia, acid reflux, gastrointestinal hemorrhage, lack of appetite/constipation), (vi) skeletomuscular system (immune-mediated skin diseases, psoriasis, lupus), (vii) nervous system (loss of taste/smell/hearing, headaches, spasms, convulsions, confusion, visual impairment, nerve pain, dizziness, impaired consciousness, nausea/vomiting, hemiplegia, ataxia, stroke, cerebral hemorrhage), (viii) mental health (stress, depression and anxiety). We additionally hypothesized mechanisms of action by investigating possible molecular mechanisms associated with these disease outcomes/symptoms. Overall, the COVID-19 pathology is still characterized by cytokine storm that results to endothelial inflammation, microvascular thrombosis, and multiple organ failures.

The bacterial communities in a wide range of environmental niches sense and respond to numerous external stimuli for their survival. Primarily, a source they require to follow up this communication is the two-component signal transduction system (TCS), which typically comprises a sensor Histidine kinase for receiving external input signals and a response regulator that conveys a proper change in the bacterial cell physiology. For numerous reasons, TCSs have ascended as convincing targets for antibacterial drug design. Several studies have shown that TCSs are essential for the coordinated expression of virulence factors and, in some cases, for bacterial viability and growth. It has also been reported that the expression of antibiotic resistance determinants may be regulated by some TCSs. In addition, as a mode of signal transduction, phosphorylation of histidine in bacteria differs from normal serine/threonine and tyrosine phosphorylation in higher eukaryotes. Several studies have shown the molecular mechanisms by which TCSs regulate virulence and antibiotic resistance in pathogenic bacteria. In this review, we list some of the characteristics of the bacterial TCSs and their involvement in virulence and antibiotic resistance. Furthermore, this review lists and discusses inhibitors that have been reported to target TCSs in pathogenic bacteria.

: In this era of multi-drug resistance (MDR), antimicrobial peptides (AMPs) are one of the most promising classes of potential drug candidates to combat communicable as well as noncommunicable diseases such as cancers and diabetes. AMPs show a wide spectrum of biological activities which include antiviral, antifungal, anti-mitogenic, anticancer, and anti-inflammatory properties. Apart from these prospective therapeutic potentials, the AMPs can act as food preservatives and immune modulators. Therefore, AMPs have the potential to replace conventional drugs and may gain a significant global drug market share. Although several AMPs have shown therapeutic potential in vitro or in vivo, in most cases they have failed the clinical trial owing to various issues. In this review, we discuss in brief (i) molecular mechanisms of AMPs in various diseases, (ii) importance of AMPs in pharmaceutical industries, (iii) the challenges in using AMPs as therapeutics and how to overcome, (iv) available AMP therapeutics in market, and (v) AMPs under clinical trials. Here, we specifically focus on the therapeutic AMPs in the areas of dermatology, surgery, oncology and metabolic diseases.

Significant growth in Electronic Health Records (EHR) over the last decade has provided an abundance of clinical text that is mostly unstructured and untapped. This huge amount of clinical text data has motivated the development of new information extraction and text mining techniques. Named Entity Recognition (NER) and Relationship Extraction (RE) are key components of information extraction tasks in the clinical domain. In this paper, we highlight the present status of clinical NER and RE techniques in detail by discussing the existing proposed NLP models for the two tasks and their performances and discuss the current challenges. Our comprehensive survey on clinical NER and RE encompass current challenges, state-of-the-art practices, and future directions in information extraction from clinical text. This is the first attempt to discuss both of these interrelated topics together in the clinical context. We identified many research articles published based on different approaches and looked at applications of these tasks. We also discuss the evaluation metrics that are used in the literature to measure the effectiveness of the two these NLP methods and future research directions.

Multimodal classification research has been gaining popularity with new datasets in domains such as satellite imagery, biometrics, and medicine. Prior research has shown the benefits of combining data from multiple sources compared to traditional unimodal data that has led to the development of many novel multimodal architectures. However, the lack of consistent terminologies and architectural descriptions makes it difficult to compare different solutions. We address these challenges by proposing a new taxonomy for describing multimodal classification models based on trends found in recent publications. Examples of how this taxonomy could be applied to existing models are presented as well as a checklist to aid in the clear and complete presentation of future models. Many of the most difficult aspects of unimodal classification have not yet been fully addressed for multimodal datasets, including big data, class imbalance, and instance-level difficulty. We also provide a discussion of these challenges and future directions of research.

Cardiac glycosides (CGs) are a diverse family of naturally derived compounds having a steroid and glycone moiety in their structures. CG molecules inhibit the α-subunit of ubiquitous transmembrane protein Na⁺/K⁺-ATPase and are clinically approved for the treatment of cardiovascular diseases. Recently, the CGs were found to exhibit selective cytotoxic effects against cancer cells, raising interest in their use as anti-cancer molecules. In this current study, we explored the underlying mechanism responsible for the anti-cancer activity of Lanatoside C against breast (MCF-7), lung (A549), and liver (HepG2) cancer cell lines. Using Real-time PCR, western blot, and immunofluorescence studies, we observed that (i) Lanatoside C inhibited cell proliferation and induced apoptosis in cell-specific and dose-dependent manner only in cancer cell lines; (ii) Lanatoside C exerts its anti-cancer activity by arresting the G2/M phase of cell cycle by blocking MAPK/Wnt/PAM signaling pathways; (iii) it induces apoptosis by inducing DNA damage and inhibiting PI3K/AKT/mTOR signaling pathways; and finally, (iv) molecular docking analysis shows significant evidence on the binding sites of Lanatoside C with various key signaling proteins ranging from cell survival to cell death. Our studies provide a novel molecular insight of anti-cancer activities of Lanatoside C in human cancer cells.