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The COVID-19 pandemic, which emerged in early 2020, has had a profound and lasting impact on global health, resulting in over 7.0 million deaths and persistent challenges. In addition to acute concerns, there is growing attention being given to the long COVID health consequences for survivors of COVID-19 with documented cases of cardiovascular abnormalities, liver disturbances, lung complications, kidney issues, and noticeable cognitive deficits. Recent studies have investigated the physiological changes in various organs following prolonged exposure to murine hepatitis virus-1 (MHV-1), a coronavirus, in mouse models. One significant finding relates to the effects on the gastrointestinal tract, an area previously understudied regarding the long-lasting effects of COVID-19. This research sheds light on important observations in the intestines during both the acute and the prolonged phases following MHV-1 infection, which parallel specific changes seen in humans after exposure to SARS-CoV-2. Our study investigates the histopathological alterations in the small intestine following MHV-1 infection in murine models, revealing significant changes reminiscent of inflammatory bowel disease (IBD), celiac disease. Notable findings include mucosal inflammation, lymphoid hyperplasia, goblet cell hyperplasia, and immune cell infiltration, mirroring pathological features observed in IBD. Additionally, MHV-1 infection induces villous atrophy, altered epithelial integrity, and inflammatory responses akin to celiac disease and IBD. SPIKENET (SPK) treatment effectively mitigates intestinal damage caused by MHV-1 infection, restoring tissue architecture and ameliorating inflammatory responses. Furthermore, investigation into long COVID reveals intricate inflammatory profiles, highlighting the potential of SPK to modulate intestinal responses and restore tissue homeostasis. Understanding these histopathological alterations provides valuable insights into the pathogenesis of COVID-induced gastrointestinal complications and informs the development of targeted therapeutic strategies.

The COVID-19 pandemic has been one of the most impactful events in our lifetime, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Multiple SARS-CoV-2 variants were reported globally, and a wide range of symptoms existed. Individuals who contract COVID-19 continue to suffer for a long time, known as long COVID or post-acute sequelae of COVID-19 (PASC). While COVID-19 vaccines were widely deployed, both unvaccinated and vaccinated individuals experienced long-term complications. To date, there are no treatments to eradicate long COVID. We recently conceived a new approach to treat COVID in which a 15-amino-acid synthetic peptide (SPIKENET, SPK) is targeted to the ACE2 receptor binding domain of SARS-CoV-2, which prevents the virus from attaching to the host. We also found that SPK precludes the binding of spike glycoproteins with the receptor carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) of a coronavirus, murine hepatitis virus-1 (MHV-1), and with all SARS-CoV-2 variants. Further, SPK reversed the development of severe inflammation, oxidative stress, tissue edema, and animal death post-MHV-1 infection in mice. SPK also protects against multiple organ damage in acute and long-term post-MHV-1 infection. Our findings collectively suggest a potential therapeutic benefit of SPK for treating COVID-19.

Severe disease from SARS-CoV-2 infection often progresses to multi-organ failure and results in an increased mortality rate amongst these patients. However, underlying mechanisms of SARS- CoV-2-induced multi-organ failure and subsequent death are still largely unknown. Cytokine storm, increased levels of inflammatory mediators, endothelial dysfunction, coagulation abnormalities, and infiltration of inflammatory cells into the organs contribute to the pathogenesis of COVID-19. One potential consequence of immune/inflammatory events is the acute progression of generalized edema, which may lead to death. We, therefore, examined the involvement of water channels in the development of edema in multiple organs and their contribution to organ dysfunction in a Murine Hepatitis Virus-1 (MHV-1) mouse model of COVID-19. Using this model, we recently reported multi-organ pathological abnormalities and animal death similar to that reported in humans with SARS-CoV-2 infection. We now identified an alteration in protein levels of AQPs 1, 4, 5, and 8 and associated oxidative stress, along with various degrees of tissue edema in multiple organs, which correlate well with animal survival post-MHV-1 infection. Furthermore, our newly created drug (a 15 amino acid synthetic peptide, known as SPIKENET) that was designed to prevent the binding of spike glycoproteins with their receptor(s), angiotensin- converting enzyme 2 (ACE2), and carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) (SARS-CoV-2 and MHV-1, respectively), ameliorated animal death and reversed altered levels of AQPs and oxidative stress post-MHV-1 infection. Collectively, our findings suggest the possible involvement of altered aquaporins and the subsequent edema, likely mediated by the virus-induced inflammatory and oxidative stress response, in the pathogenesis of COVID- 19 and the potential of SPIKENET as a therapeutic option.

Hepatic encephalopathy (HE) is a neurological condition linked to liver failure. Acute HE (Type A) occurs with acute liver failure, while chronic HE (Type C) is tied to cirrhosis and portal hypertension. HE treatments lag due to gaps in understanding its development by gender and age. We studied how sex and age impact HE and its severity with combined liver toxins. Our findings indicate that drug-induced (thioacetamide, TAA) brain edema was more severe in aged males than in young males or young/aged female rats. However, adding alcohol (ethanol, EtOH) worsens TAA’s brain edema in both young and aged females, with females experiencing a more severe effect than males. These patterns also apply to Type A HE induced by azoxymethane (AZO) in mice. Similarly, TAA-induced behavioral deficits in Type C HE were milder in young and aged females than in males. Conversely, EtOH and TAA in young/aged males led to severe brain edema and fatality without noticeable behavioral changes. TAA metabolism was slower in aged males than in young or middle-aged rats. When TAA-treated aged male rats received EtOH, there was a slow and sustained plasma level of thioacetamide sulfoxide (TASO). This suggests that with EtOH, TAA-induced HE is more severe in aged males. TAA metabolism was similar in young, middle-aged, and aged female rats. However, with EtOH, young and aged females experience more severe drug-induced HE as compared to middle-aged adult rats. These findings strongly suggest that gender and age play a role in the severity of HE development and that the presence of one or more liver toxins may aggravate the severity of the disease progression.

Membrane-bound proteins integrate and coordinate various signalling activities to maintain tissue architecture. In recent years, research updates indicate that these proteins undergo post-translational modification like glycosylation to maintain tissue integrity. Here we discuss research updates from Drosophila, about two essential membrane-bound proteins, Notch and Crumbs, that undergo such modifications to interact with each other and their implications in tumorigenesis.

Xanthomonas oryzae pv. oryzae (Xoo) is a plant bacterial pathogen that causes bacterial blight (BB) disease, resulting in serious production losses of rice. The crystal structure of malonyl CoA-acyl carrier protein transacylase (XoMCAT), encoded by the gene fabD (Xoo0880) from Xoo, was determined at 2.3 angstrom resolution in complex with N-cyclohexyl-2-aminoethansulfonic acid. Malonyl CoA-acyl carrier protein transacylase transfers malonyl group from malonyl CoA to acyl carrier protein (ACP). The transacylation step is essential in fatty acid synthesis. Based on the rationale, XoMCAT has been considered as a target for antibacterial agents against BB. Protein-protein interaction between XoMCAT and ACP was also extensively investigated using computational docking, and the proposed model revealed that ACP bound to the cleft between two XoMCAT subdomains.

Aminopeptidases are metalloproteinases that degrade N-terminal residues from protein and play important roles in cell growth and development by controlling cell homeostasis and protein maturation. We determined the crystal structure of XoLAP, a leucyl aminopeptidase, at 2.6 Å resolution from Xanthomonas oryzae pv. oryzae, causing the destructive rice disease of bacterial blight. It is the first crystal structure of aminopeptidase from phytopathogens as a drug target. XoLAP existed as a hexamer and the monomer structure consisted of an N-terminal cap domain and a C-terminal peptidase domain with two divalent zinc ions. XoLAP structure was compared with BlLAP and EcLAP (EcPepA) structures. Based on the structural comparison, the molecular model of XoLAP in complex with the natural aminopeptidase inhibitor of microginin FR1 was proposed. The model structure will be useful to develop a novel antibacterial drug against Xoo.

Despite being treatable and preventable, tuberculosis (TB) affected one-fourth of the world population in 2019, and it took the lives of 1.4 million people in 2019. It affected 1.2 million children around the world in the same year. As it is an infectious bacterial disease, the early diagnosis of TB prevents further transmission and increases the survival rate of the affected person. One of the standard diagnosis methods is the sputum culture test. Diagnosing and rapid sputum test results usually take one to eight weeks in 24 h. Using posterior-anterior chest radiographs (CXR) facilitates a rapid and more cost-effective early diagnosis of tuberculosis. Due to intraclass variations and interclass similarities in the images, TB prognosis from CXR is difficult. We proposed an early TB diagnosis system (tbXpert) based on deep learning methods. Deep Fused Linear Triangulation (FLT) is considered for CXR images to reconcile intraclass variation and interclass similarities. To improve the robustness of the prognosis approach, deep information must be obtained from the minimal radiation and uneven quality CXR images. The advanced FLT method accurately visualizes the infected region in the CXR without segmentation. Deep fused images are trained by the Deep learning network (DLN) with residual connections. The largest standard database, comprised of 3500 TB CXR images and 3500 normal CXR images, is utilized for training and validating the recommended model. Specificity, sensitivity, Accuracy, and AUC are estimated to determine the performance of the proposed systems. The proposed system demonstrates a maximum testing accuracy of 99.2%, a sensitivity of 98.9%, a specificity of 99.6%, a precision of 99.6%, and an AUC of 99.4%, all of which are pretty high when compared to current state-of-the-art deep learning approaches for the prognosis of tuberculosis. To lessen the radiologist’s time, effort, and reliance on the level of competence of the specialist, the suggested system named tbXpert can be deployed as a computer-aided diagnosis technique for tuberculosis.

Cervical cancer is a major cause of mortality among women, particularly in low-income countries with insufficient screening programs. Manual cytological examination is time-consuming, error-prone and subject to inter-observer variability. Automated and robust classification of the whole slide cytology images for cervical cancer is essential for detecting precancerous and malignant lesions. We propose a novel deep learning framework, the Compound Scaling Hypergraph Neural Network model (CSHG-CervixNet), for robust classification of cervical cancer subtypes. The model integrates a Compound Scaling Convolutional Neural Network (CSCNN) with a k-dimensional Hypergraph Neural Network (kd-HGNN) architecture. CSCNN balances the network’s depth, width, and resolution, supporting effective feature representation with minimal computational overhead. kd-HGNN captures higher-order relationships between the features, and its propagation mechanism ensures better feature diffusion across distant nodes. The model is evaluated on the benchmark Sipakmed dataset and achieves an accuracy of 99.31%, with a macro-averaged precision of 98.97%, recall of 99.38%, and F1-score of 99.34%, demonstrating its robustness in cervical cancer subtype classification. Pathologists and other medical experts will find this study helpful in distinguishing cervical cancer subtypes so that targeted treatment may be provided and effective disease management is made possible.

Tuberculosis (TB) elimination is possible with the discovery of accurate biomarkers that define the stages of infection. Drug-resistant TB impair the current treatment strategies and worsen the unfavourable outcomes. The knowledge on host immune responses between drug-sensitive and drug-resistant infection is inadequate to understand the pathophysiological differences and disease severity. The secreted proteins, cytokines display versatile behaviour upon infection with Mycobacterium tuberculosis (MTB) and their imbalances often tend to assist disease pathology than protection. Therefore, studying these soluble proteins across TB infection spectrum (drug-resistant TB, drug-sensitive TB, and latent TB) may unveil the disease mediated responses and unique stage specific cytokine signatures. Thus, we sought to determine the plasma cytokine levels from healthy, latently infected, drug-sensitive, and drug-resistant TB individuals. Our study revealed top 8 cytokines (IL-17, IL-1α, IL-2, IL-10, IL-5, IFN-γ, TNF-α and IL-6) and their biomarker abilities to discriminate different stages of infection.