Identification of proteins' expression pathway and the effective miRNAs for the treatment of human papillomavirus-induced cervical cancer: in-silico analyses-experimental research.

Introduction: Cervical cancer is the fourth most common cancer in women. The risk factors for cervical cancer include human papillomavirus (HPV) infection, age, smoking, number of pregnancies, use of oral contraceptives, and diet. However, long-term HPV infection appears to be the main risk factor for developing cervical cancer.

Complement protein expression changes in various conditions of breast cancer: in-silico analyses-experimental research.

Introduction: Breast cancer is the most prevalent cancer diagnosed in females worldwide. The known biomarkers are insufficient to understand the actual prognosis of breast cancer, and identifying new biomarkers is desirable and valuable data to improve the patient's survival. Many inflammatory biomarkers, such as the complement system, can be regarded as prognostic values and as potent inflammatory mediators; complement proteins have a critical role in tumorigenesis.

Prediction of immune molecules activity during burn wound healing among elderly patients: in-silico analyses: experimental research.

Introduction: Burn injuries lead to dysregulation of immune molecules, impacting cellular and humoral immune pathways. This study aims to determine the prediction of immune molecule activity during burn wound healing among elderly patients.

Methods: The current study utilized the Gene Expression Omnibus (GEO) database to extract the proper gene set.

Identification of a valuable gene network for the diagnosis and treatment of non-obstructive azoospermia: in-silico analyses - experimental research.

Introduction: Non-obstructive azoospermia (NOA) is an etiology of infertility in men. NOA may have various classifications; however, hypogonadotropic hypogonadism can be regarded as a class of NOA associated with genetic factors. Former studies have shown that noncoding RNA (ncRNA) plays an essential role in NOA incidence, but few studies have been performed on the NOA-related ncRNA interaction network.

Lateral habenula deep brain stimulation alleviates depression-like behaviors and reverses the oscillatory pattern in the nucleus accumbens in an animal model of depression.

Depression is a series of symptoms that influence mood, thinking, and behavior and create unpleasant emotions like hopelessness and apathy. Treatment-resistant depression (TRD) affects 30 % of depression patients despite the availability of several non-invasive therapies. Deep brain stimulation (DBS) is a novel therapy for TRD.

Risk predictions of hospital-acquired pressure injury in the intensive care unit based on a machine learning algorithm.

Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in intensive care units (ICUs) were frequently reported to suffer PIs, with a heavy burden on their life and expenditures. Machine learning (ML) is a Section of artificial intelligence (AI) that has emerged in nursing practice and is increasingly used for diagnosis, complications, prognosis, and recurrence prediction.

Stem cell-conditioned medium is a promising treatment for Alzheimer's disease.

Background And Aim: Alzheimer's disease (AD), a prevalent progressive neurodegenerative disease, is mainly characterized by dementia, memory loss, and cognitive disorder. Rising research was performed to develop pharmacological or non-pharmacological approaches to treat or improve AD complications. Mesenchymal stem cells (MSCs) are stromal cells that can self-renew and exhibit multilineage differentiation.