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Artificial intelligence and machine learning applications are emerging as transformative technologies in medicine. With greater access to a diverse range of big datasets, researchers are turning to these powerful techniques for data analysis. Machine learning can reveal patterns and interactions between variables in large and complex datasets more accurately and efficiently than traditional statistical methods. Machine learning approaches open new possibilities for studying SLE, a multifactorial, highly heterogeneous and complex disease. Here, we discuss how machine learning methods are rapidly being integrated into the field of SLE research. Recent reports have focused on building prediction models and/or identifying novel biomarkers using both supervised and unsupervised techniques for understanding disease pathogenesis, early diagnosis and prognosis of disease. In this review, we will provide an overview of machine learning techniques to discuss current gaps, challenges and opportunities for SLE studies. External validation of most prediction models is still needed before clinical adoption. Utilisation of deep learning models, access to alternative sources of health data and increased awareness of the ethics, governance and regulations surrounding the use of artificial intelligence in medicine will help propel this exciting field forward.

Cell migration is the major driver of invasion and metastasis during cancer progression. For cells to migrate, they utilize the actin–myosin cytoskeleton and adhesion molecules, such as integrins and CD44, to generate traction forces in their environment. CD44 primarily binds to hyaluronic acid (HA) and integrins primarily bind to extracellular matrix (ECM) proteins such as collagen. However, the role of CD44 under integrin-mediated conditions and vice versa is not well known. Here, we performed traction force microscopy (TFM) on U251 cells seeded on collagen I-coated polyacrylamide gels to assess the functional mechanical relationship between integrins and CD44. Performing TFM on integrin-mediated adhesion conditions, i.e., collagen, we found that CD44KO U251 cells exerted more traction force than wild-type (WT) U251 cells. Furthermore, untreated WT and CD44-blocked WT exhibited comparable results. Conversely, in CD44-mediated adhesive conditions, integrin-blocked WT cells exerted a higher traction force than untreated WT cells. Our data suggest that CD44 and integrins have a mutually antagonistic relationship where one receptor represses the other's ability to generate traction force on its cognate substrate. [ABSTRACT FROM AUTHOR]

Genomic instability is a hallmark of cancer, and has a central role in the initiation and development of breast cancer.sup.1,2. The success of poly-ADP ribose polymerase inhibitors in the treatment of breast cancers that are deficient in homologous recombination exemplifies the utility of synthetically lethal genetic interactions in the treatment of breast cancers that are driven by genomic instability.sup.3. Given that defects in homologous recombination are present in only a subset of breast cancers, there is a need to identify additional driver mechanisms for genomic instability and targeted strategies to exploit these defects in the treatment of cancer. Here we show that centrosome depletion induces synthetic lethality in cancer cells that contain the 17q23 amplicon, a recurrent copy number aberration that defines about 9% of all primary breast cancer tumours and is associated with high levels of genomic instability.sup.4-6. Specifically, inhibition of polo-like kinase 4 (PLK4) using small molecules leads to centrosome depletion, which triggers mitotic catastrophe in cells that exhibit amplicon-directed overexpression of TRIM37. To explain this effect, we identify TRIM37 as a negative regulator of centrosomal pericentriolar material. In 17q23-amplified cells that lack centrosomes, increased levels of TRIM37 block the formation of foci that comprise pericentriolar material--these foci are structures with a microtubule-nucleating capacity that are required for successful cell division in the absence of centrosomes. Finally, we find that the overexpression of TRIM37 causes genomic instability by delaying centrosome maturation and separation at mitotic entry, and thereby increases the frequency of mitotic errors. Collectively, these findings highlight TRIM37-dependent genomic instability as a putative driver event in 17q23-amplified breast cancer and provide a rationale for the use of centrosome-targeting therapeutic agents in treating these cancers. TRIM37 overexpression promotes centrosome dysfunction that drives genomic instability in breast cancer cell lines containing the recurrent 17q23 amplicon, revealing a vulnerability that can be targeted to eliminate cancer cells., Author(s): Zhong Y. Yeow [sup.1] [sup.2] , Bramwell G. Lambrus [sup.3] , Rebecca Marlow [sup.4] [sup.5] , Kevin H. Zhan [sup.3] , Mary-Anne Durin [sup.1] [sup.2] , Lauren T. Evans [...]

Objective: Age‐related hearing loss (ARHL) is a prevalent but often underdiagnosed and undertreated condition among individuals aged 50 and above. It is associated with various sociodemographic factors and health risks including dementia, depression, cardiovascular disease, and falls. While the causes of ARHL and its downstream effects are well defined, there is a lack of priority placed by clinicians as well as guidance regarding the identification, education, and management of this condition. Purpose: The purpose of this clinical practice guideline is to identify quality improvement opportunities and provide clinicians trustworthy, evidence‐based recommendations regarding the identification and management of ARHL. These opportunities are communicated through clear actionable statements with explanation of the support in the literature, evaluation of the quality of the evidence, and recommendations on implementation. The target patients for the guideline are any individuals aged 50 years and older. The target audience is all clinicians in all care settings. This guideline is intended to focus on evidence‐based quality improvement opportunities judged most important by the guideline development group (GDG). It is not intended to be a comprehensive, general guide regarding the management of ARHL. The statements in this guideline are not intended to limit or restrict care provided by clinicians based on their experience and assessment of individual patients. Action Statements: The GDG made strong recommendations for the following key action statements (KASs): (KAS 4) If screening suggests hearing loss, clinicians should obtain or refer to a clinician who can obtain an audiogram. (KAS 8) Clinicians should offer, or refer to a clinician who can offer, appropriately fit amplification to patients with ARHL. (KAS 9) Clinicians should refer patients for an evaluation of cochlear implantation candidacy when patients have appropriately fit amplification and persistent hearing difficulty with poor speech understanding. The GDG made recommendations for the following KASs: (KAS 1) Clinicians should screen patients aged 50 years and older for hearing loss at the time of a health care encounter. (KAS 2) If screening suggests hearing loss, clinicians should examine the ear canal and tympanic membrane with otoscopy or refer to a clinician who can examine the ears for cerumen impaction, infection, or other abnormalities. (KAS 3) If screening suggests hearing loss, clinicians should identify sociodemographic factors and patient preferences that influence access to and utilization of hearing health care. (KAS 5) Clinicians should evaluate and treat or refer to a clinician who can evaluate and treat patients with significant asymmetric hearing loss, conductive or mixed hearing loss, or poor word recognition on diagnostic testing. (KAS 6) Clinicians should educate and counsel patients with hearing loss and their family/care partner(s) about the impact of hearing loss on their communication, safety, function, cognition, and quality of life (QOL). (KAS 7) Clinicians should counsel patients with hearing loss on communication strategies and assistive listening devices. (KAS 10) For patients with hearing loss, clinicians should assess if communication goals have been met and if there has been improvement in hearing‐related QOL at a subsequent health care encounter or within 1 year. The GDG offered the following KAS as an option: (KAS 11) Clinicians should assess hearing at least every 3 years in patients with known hearing loss or with reported concern for changes in hearing. [ABSTRACT FROM AUTHOR]

Background: Human papillomavirus (HPV)-mediated oropharyngeal cancer (OPC) is associated with dramatically improved survival in comparison with HPV-negative OPC and can be successfully treated with surgical and nonsurgical approaches. National treatment trends for OPC were investigated with the National Cancer Data Base (NCDB).Methods: The NCDB was reviewed for primary HPV-mediated OPC in 2010-2014. Multivariable regression was used to identify predictors of both nonsurgical therapy and receipt of adjuvant chemoradiation (CRT).Results: There were 13,363 patients identified with a median age at diagnosis of 58 years. The incidence of triple-modality treatment (surgery with adjuvant chemotherapy) decreased from 23.7% in 2010 to 16.9% in 2014 (R2  = 0.96), whereas the incidence of nonsurgical treatment increased from 63.9% to 68.7% (R2  = 0.89). Hospitals in the top treatment volume quartile (quartile 1 [Q1]; n = 29) had a lower rate of positive margins (16.3%) than bottom-quartile centers (n = 741; rate of positive margins, 36.4%; P < .001); Q1 hospitals used surgical therapy significantly more. Independent predictors of nonsurgical therapy included older age, advanced disease, lower hospital volume, and living closer to the hospital or outside the Pacific United States. In surgically treated patients, younger age, lower hospital volume, nodal disease, positive surgical margins, and extranodal extension (ENE) also predicted more adjuvant CRT use.Conclusions: The use of upfront surgical treatment decreased from 2010 to 2014. Hospital volume shows a strong, inverse correlation with the rate of positive surgical margins. The upfront treatment strategy is predicted not only by staging but also by patient-, geographic-, and hospital-specific factors. Lower hospital volume remains independently associated with increased triple-modality therapy after adjustments for positive margins, ENE, and pathologic staging. [ABSTRACT FROM AUTHOR]