Gene editing, especially with clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR-Cas9), has advanced gene function science. Gene editing’s rapid advancement has increased its medical/clinical value. Due to its great specificity and efficiency, CRISPR/Cas9 can accurately and swiftly screen the whole genome. This simplifies disease-specific gene therapy. To study tumor origins, development, and metastasis, CRISPR/Cas9 can change genomes. In recent years, tumor treatment research has increasingly employed this method. CRISPR/Cas9 can treat cancer by removing genes or correcting mutations. Numerous preliminary tumor treatment studies have been conducted in relevant fields. CRISPR/Cas9 may treat gene-level tumors. CRISPR/Cas9-based personalized and targeted medicines may shape tumor treatment. This review examines CRISPR/Cas9 for tumor therapy research, which will be helpful in providing references for future studies on the pathogenesis of malignancy and its treatment.

As medical science and technology progress towards the era of “big data”, a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC’s diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process.

The emergence of novel variants of SARS-CoV-2 and their abilities to evade the immune response elicited through presently available vaccination makes it essential to recognize the mechanisms through which SARS-CoV-2 interacts with the human immune response. It is essential not only to comprehend the infection mechanism of SARS-CoV-2 but also for the generation of effective and reliable vaccines against COVID-19. The effectiveness of the vaccine is supported by the adaptive immune response, which mainly consists of B and T cells, which play a critical role in deciding the prognosis of the COVID-19 disease. T cells are essential for reducing the viral load and containing the infection. A plethora of viral proteins can be recognized by T cells and provide a broad range of protection, especially amid the emergence of novel variants of SARS-CoV-2. However, the hyperactivation of the effector T cells and reduced number of lymphocytes have been found to be the key characteristics of the severe disease. Notably, excessive T cell activation may cause acute respiratory distress syndrome (ARDS) by producing unwarranted and excessive amounts of cytokines and chemokines. Nevertheless, it is still unknown how T-cell-mediated immune responses function in determining the prognosis of SARS-CoV-2 infection. Additionally, it is unknown how the functional perturbations in the T cells lead to the severe form of the disease and to reduced protection not only against SARS-CoV-2 but many other viral infections. Hence, an updated review has been developed to understand the involvement of T cells in the infection mechanism, which in turn determines the prognosis of the disease. Importantly, we have also focused on the T cells’ exhaustion under certain conditions and how these functional perturbations can be modulated for an effective immune response against SARS-CoV-2. Additionally, a range of therapeutic strategies has been discussed that can elevate the T cell-mediated immune response either directly or indirectly.

Tuberculosis (TB) is accountable for considerable global morbidity and mortality. Effective TB therapy with multiple drugs completes in about six months. The longer duration of TB therapy challenges patient compliance and contributes to treatment collapse and drug resistance (DR) progress. Therefore, new medications with an innovative mechanism of action are desperately required to shorten the TB therapy’s duration and effective TB control. The mycobacterial membrane protein Large 3 (MmpL3) is a novel, mycobacteria-conserved and recognized promiscuous drug target used in the development of better treatments for multi-drug resistance TB (MDR-TB) and extensively drug-resistant TB (XDR-TB). This article spotlights MmpL3, the clinical studies of its inhibitor (SQ109), and the patent literature. The literature on MmpL3 inhibitors was searched on PubMed and freely available patent databases (Espacenet, USPTO, and PatentScope). SQ109, an analog of ethambutol (EMB), is an established MmpL3 inhibitor and has completed Phase 2b-3 clinical trials. Infectex and Sequella are developing orally active SQ109 in partnership to treat MDR pulmonary TB. SQ109 has demonstrated activity against drug-sensitive (DS) and drug-resistant (DR) Mycobacterium tuberculosis (Mtb) and a synergistic effect with isoniazid (INH), rifampicin (RIF), clofazimine (CFZ), and bedaquiline (BNQ). The combination of SQ109, clofazimine, bedaquiline, and pyrazinamide (PZA) has been patented due to its excellent anti-TB activity against MDR-TB, XDR-TB, and latent-TB. The combinations of SQ109 with other anti-TB drugs (chloroquine, hydroxychloroquine, and sutezolid) have also been claimed in the patent literature. SQ109 is more potent than EMB and could substitute EMB in the intensive stage of TB treatment with the three- or four-drug combination. Developing MmpL3 inhibitors is a promising approach to fighting the challenges associated with DS-TB and DR-TB. The authors foresee MmpL3 inhibitors such as SQ109 as future drugs for TB treatment.

Monkeypox virus has remained the most virulent poxvirus since the elimination of smallpox approximately 41 years ago, with distribution mostly in Central and West Africa. Monkeypox (Mpox) in humans is a zoonotically transferred disease that results in a smallpox-like disease. It was first diagnosed in 1970 in the Democratic Republic of the Congo (DRC), and the disease has spread over West and Central Africa. The purpose of this review was to give an up-to-date, thorough, and timely overview on the genomic diversity and evolution of a re-emerging infectious disease. The genetic profile of Mpox may also be helpful in targeting new therapeutic options based on genes, mutations, and phylogeny. Mpox has become a major threat to global health security, necessitating a quick response by virologists, veterinarians, public health professionals, doctors, and researchers to create high-efficiency diagnostic tests, vaccinations, antivirals, and other infection control techniques. The emergence of epidemics outside of Africa emphasizes the disease’s global significance. Increased monitoring and identification of Mpox cases are critical tools for obtaining a better knowledge of the ever-changing epidemiology of this disease.

Conventional anticancer treatments, such as radiotherapy and chemotherapy, have significantly improved cancer therapy. Nevertheless, the existing traditional anticancer treatments have been reported to cause serious side effects and resistance to cancer and even to severely affect the quality of life of cancer survivors, which indicates the utmost urgency to develop effective and safe anticancer treatments. As the primary focus of cancer nanotheranostics, nanomaterials with unique surface chemistry and shape have been investigated for integrating cancer diagnostics with treatment techniques, including guiding a prompt diagnosis, precise imaging, treatment with an effective dose, and real-time supervision of therapeutic efficacy. Several theranostic nanosystems have been explored for cancer diagnosis and treatment in the past decade. However, metal-based nanotheranostics continue to be the most common types of nonentities. Consequently, the present review covers the physical characteristics of effective metallic, functionalized, and hybrid nanotheranostic systems. The scope of coverage also includes the clinical advantages and limitations of cancer nanotheranostics. In light of these viewpoints, future research directions exploring the robustness and clinical viability of cancer nanotheranostics through various strategies to enhance the biocompatibility of theranostic nanoparticles are summarised.