Long COVID, also referred to as post-acute sequelae of SARS-CoV-2 infection (PASC), is characterized by persistent multi-systemic symptoms such as fatigue, cognitive impairment, and respiratory dysfunction. Accumulating evidence indicates that gut and oral microbiota play an important role in its pathogenesis. Patients with long COVID consistently exhibit reduced microbial diversity, depletion of beneficial short-chain fatty acid (SCFA)-producing species such as Faecalibacterium prausnitzii and Bifidobacterium spp. and enrichment of proinflammatory taxa including Ruminococcus gnavus, Bacteroides vulgatus, and Veillonella. These alterations may disrupt intestinal barrier integrity, sustain low-grade systemic inflammation, and influence host immune and neuroendocrine pathways through the gut–brain and gut–lung axes. Distinct microbial signatures have also been associated with symptom clusters, including neuropsychiatric, respiratory, and gastrointestinal manifestations. Proposed mechanisms linking dysbiosis to long COVID include impaired SCFA metabolism, tryptophan depletion, microbial translocation, and interactions with host immune and inflammatory responses, including autoantibody formation and viral antigen persistence. Preliminary interventional studies using probiotics, synbiotics, and fecal microbiota transplantation suggest that microbiome-targeted therapies may alleviate symptoms, although evidence remains limited and heterogeneous. This review synthesizes current literature on the role of gut and oral microbiota in long COVID, highlights emerging microbial biomarkers, and discusses therapeutic implications. While causality remains to be firmly established, restoring microbial balance represents a promising avenue for diagnosis, prevention, and management of long COVID.

Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), has emerged as a significant health concern following the COVID-19 pandemic. Molecular mechanisms underlying the occurrence and progression of long COVID include viral persistence, immune dysregulation, endothelial dysfunction, and neurological involvement, and highlight the need for further research to develop targeted therapies for this condition. While a clearer picture of the clinical symptomatology is shaping, many molecular mechanisms are yet to be unraveled, given their complexity and high level of interaction with other metabolic pathways. This review summarizes some of the most important symptoms and associated molecular mechanisms that occur in long COVID, as well as the most relevant molecular techniques that can be used in understanding the viral pathogen, its affinity towards the host, and the possible outcomes of host-pathogen interaction.

The COVID-19 (C-19) pandemic has highlighted the significance of understanding the long-term effects of this disease on the quality of life of those infected. Long COVID-19 (L-C19) presents as persistent symptoms that continue beyond the main illness period, usually lasting weeks to years. One of the lesser-known but significant aspects of L-C19 is its impact on neuropsychiatric manifestations, which can have a profound effect on an individual’s quality of life. Research shows that L-C19 creates neuropsychiatric issues such as mental fog, emotional problems, and brain disease symptoms, along with sleep changes, extreme fatigue, severe head pain, tremors with seizures, and pain in nerves. People with cognitive problems plus fatigue and mood disorders experience great difficulty handling everyday activities, personal hygiene, and social interactions. Neuropsychiatric symptoms make people withdraw from social activity and hurt relationships, thus causing feelings of loneliness. The unpredictable state of L-C19 generates heavy psychological pressure through emotional suffering, including depression and anxiety. Neuropsychiatric changes such as cognitive impairment, fatigue, and mood swings make it hard for people to work or study effectively, which decreases their output at school or work and lowers their job contentment. The purpose of this narrative review is to summarize the clinical data present in the literature regarding the neuropsychiatric manifestations of L-C19, to identify current methods of diagnosis and treatment that lead to correct management of the condition, and to highlight the impact of these manifestations on patients’ quality of life.

This review highlights the anti-inflammatory and antioxidant effects of probiotics and their complex health-related impacts. The main health areas targeted are gastrointestinal inflammation, neuroinflammation, systemic metabolic disorders, and liver conditions. Probiotics work mechanistically to regulate key inflammatory pathways by suppressing nuclear factor (NF-κb) and mitogen-activated protein kinase (MAPK) pathways and activating antioxidant defenses through nuclear erythroid 2-related factor (Nrf2). They stimulate anti-inflammatory cytokines (including interleukin 10 (IL-10) and inhibit pro-inflammatory mediators such as tumor necrosis factor-α (TNF-α), partly through the regulation of T cells. Probiotics also produce antioxidant metabolites (e.g., exopolysaccharides and short-chain fatty acids), which enhance the host’s resistance to oxidative stress. Supplementation with probiotics improves intestinal inflammation and oxidative injury in gut disorders. Clinical trials suggest that probiotic supplements may reduce neuroinflammation and oxidative stress, while improving cognitive or behavioral outcomes in neurodegenerative disorders. Overall, this review underscores that probiotics have potent anti-inflammatory and antioxidant effects within the gut–brain axis and across various organ systems, supporting their use as valuable adjunctive therapies for inflammatory and oxidative stress-related conditions. It further emphasizes that additional mechanistic research and controlled clinical trials are essential to translate these findings into the most effective therapeutic strategies.

Plitidepsin has shown potent preclinical activity against severe acute respiratory syndrome coronavirus 2 and was generally well tolerated in a phase I trial of hospitalized patients with coronavirus disease 2019 (COVID-19). NEPTUNO, a phase III, multicenter, randomized, controlled trial, was designed to evaluate the efficacy and safety of plitidepsin in the management of moderate COVID-19 in hospitalized adult patients. Included patients had documented severe acute respiratory syndrome coronavirus 2 infection, required oxygen therapy, and had adequate organ function. The planned sample size was 609 patients. Patients were randomized 1:1:1 to at least 3 days of dexamethasone plus either plitidepsin (1.5 mg/day or 2.5 mg/day, for 3 days) or standard of care (control). The primary endpoint was the time to sustained withdrawal of supplemental oxygen. Secondary endpoints included time to sustained hospital discharge, clinical status, duration of oxygen support, percentage of patients requiring admission to the intensive care unit, and safety. After randomizing 205 patients, NEPTUNO was discontinued due to a notable drop in COVID-19–related hospitalizations. Available data suggest a 2-day improvement in the median time to sustained oxygen therapy discontinuation (5 vs 7 days) favoring both plitidepsin arms (hazard ratio, 1.37; 95% confidence interval, .96–1.96; P = .08 for plitidepsin 1.5 mg vs control; hazard ratio, 1.06; 95% confidence interval, .73–1.53; P = .78 for plitidepsin 2.5 mg vs control). Plitidepsin was generally well tolerated. Despite the trial limitations, these results suggest that plitidepsin may have a positive benefit-risk ratio in the management of patients requiring oxygen therapy. Further studies with plitidepsin, including those in immunosuppressed patients, are warranted. Results from this phase III trial suggest that plitidepsin, a first-in-class antiviral, may have a positive benefit-risk ratio in the management of hospitalized patients requiring oxygen therapy for moderate COVID-19.

The rapid spread of COVID-19 increased the need for speedy diagnostic tools, which led scientists to conduct extensive research on deep learning (DL) applications that use chest imaging, such as chest X-ray (CXR) and computed tomography (CT). This review examines the development and performance of DL architectures, notably convolutional neural networks (CNNs) and emerging vision transformers (ViTs), in identifying COVID-19-related lung abnormalities. Individual ResNet architectures, along with CNN models, demonstrate strong diagnostic performance through the transfer protocol; however, ViTs provide better performance, with improved readability and reduced data requirements. Multimodal diagnostic systems now incorporate alternative methods, in addition to imaging, which use lung ultrasounds, clinical data, and cough sound evaluation. Information fusion techniques, which operate at the data, feature, and decision levels, enhance diagnostic performance. However, progress in COVID-19 detection is hindered by ongoing issues stemming from restricted and non-uniform datasets, as well as domain differences in image standards and complications with both diagnostic overfitting and poor generalization capabilities. Recent developments in COVID-19 diagnosis involve constructing expansive multi-noise information sets while creating clinical process-oriented AI algorithms and implementing distributed learning protocols for securing information security and system stability. While deep learning-based COVID-19 detection systems show strong potential for clinical application, broader validation, regulatory approvals, and continuous adaptation remain essential for their successful deployment and for preparing future pandemic response strategies.