Eligibility for antiamyloid treatment: preparing for disease-modifying therapies for Alzheimer's disease.

BACKGROUND: Disease-modifying therapies (DMTs) for Alzheimer's disease (AD) have early evidence of efficacy. Widespread delivery of DMTs will require major service reconfiguration. Treatment pathways will need to include triaging for eligibility, regular infusions and baseline and follow-up MRI scanning. A critical step in planning is provision of real-world estimates of patients likely to be eligible for triaging, but these are challenging to obtain. METHODS: We performed a retrospective service evaluation of patients attending five memory services across North and East London and a national specialist cognitive disorders service. We examined the likely proportion of patients who would (1) be referred for triaging for DMTs and (2) potentially be suitable for treatments. RESULTS: Data from a total of 1017 patients were included, 517 of whom were seen in community memory services and 500 in a specialist clinic. In the memory services, 367/517 (71%) were diagnosed with possible AD. After exclusions of those in whom cognitive and frailty scores, MRI contraindications or anticoagulant use indicated they would be unlikely to be suitable, an estimated 32% would be eligible for triaging. In the specialist cognitive clinic, where additional investigations are available, 14% of those seen (70/500) would be potentially eligible for treatment. CONCLUSIONS: While a sizeable proportion of patients attending memory clinics may be referred for triaging for DMTs for AD, only a minority are likely to be suitable for these, as demonstrated in patients seen in specialist cognitive services. This will need to be considered when designing pathways for DMT delivery.

Severe obesity in a specialist type 2 diabetes outpatient clinic: an Australian retrospective cohort study.

BACKGROUND: Obesity is a major risk factor for the development of type 2 diabetes (T2DM) and its complications. Significant weight loss has been shown to improve glycaemia in people with T2DM and obesity. National and international guidelines recommend considering bariatric surgery for body mass index (BMI) ≥ 35 kg/m2. We assessed the proportion of people with T2DM meeting criteria for surgery, how many had been offered a bariatric/obesity service referral, and compared the characteristics of people with BMI ≥ 35 kg/m2 and BMI < 35 kg/m2. METHODS: Retrospective data were collected for all people with T2DM aged ≥18 years, attending a hospital specialist diabetes outpatient service over three calendar years, 2017-2019. RESULTS: Of 700 people seen in the service, 291 (42%) had BMI ≥ 35 kg/m2 (the "BMI ≥ 35 group") and met criteria for bariatric surgery, but only 54 (19%) of them were offered referral to an obesity service. The BMI ≥ 35 group was younger than those with a BMI < 35 kg/m2 (56.1 ± 14.8 vs 61.4 ± 14.6 years, p < 0.001) (mean ± SD), with similar diabetes duration (11.0 ± 9.0 vs 12.3 ± 8.9 years, p = 0.078), and there was no significant difference in initial HbA1c (75 ± 27 vs 72 ± 26 mmol/mol, p = 0.118) (9.0 ± 2.5 vs 8.7 ± 2.4%) or proportion treated with insulin (62% vs 58%). There was more GLP1 agonist use in the BMI ≥ 35 group (13% vs 7%, p = 0.003) but similar rates of SGLT2 inhibitor use (25% vs 21%, p = 0.202). The BMI ≥ 35 group received more new medication and/or dose adjustments (74% vs 66%, p = 0.016). Only 29% in the BMI ≥ 35 kg group achieved HbA1c < 53 mmol/mol (7.0%). CONCLUSIONS: In spite of frequently meeting the criteria for bariatric surgery and not achieving glycaemic targets, people with T2DM in this specialist clinic received limited medical or surgical management of their obesity. This study suggests opportunities for improvement in care of people with T2DM at several levels including increased referrals from T2DM services to weight management/bariatric services, as well as an increased use of GLP1 agonists and SGLT2 inhibitors where appropriate. Our data support the need to prioritise obesity management in the treatment of type 2 diabetes.

A deep learning network for Gleason grading of prostate biopsies using EfficientNet.

OBJECTIVES: The most crucial part in the diagnosis of cancer is severity grading. Gleason's score is a widely used grading system for prostate cancer. Manual examination of the microscopic images and grading them is tiresome and consumes a lot of time. Hence to automate the Gleason grading process, a novel deep learning network is proposed in this work. METHODS: In this work, a deep learning network for Gleason grading of prostate cancer is proposed based on EfficientNet architecture. It applies a compound scaling method to balance the dimensions of the underlying network. Also, an additional attention branch is added to EfficientNet-B7 for precise feature weighting. RESULT: To the best of our knowledge, this is the first work that integrates an additional attention branch with EfficientNet architecture for Gleason grading. The proposed models were trained using H&E-stained samples from prostate cancer Tissue Microarrays (TMAs) in the Harvard Dataverse dataset. CONCLUSIONS: The proposed network was able to outperform the existing methods and it achieved an Kappa score of 0.5775.

Prognostic circulating proteomic biomarkers in colorectal liver metastases.

The liver is the most common site of metastasis in colorectal cancer. Multimodal treatment, including liver resection, is potentially curative and prolongs survival for selected patients with colorectal liver metastases (CRLM). However, the treatment of CRLM remains challenging because recurrence is common, and prognosis varies widely between patients despite curative-intent treatment. Clinicopathological features and tissue-based molecular biomarkers, either alone or in combination, are insufficient for accurate prognostication. As most of the functional information in cells resides in the proteome, circulating proteomic biomarkers may be useful for rationalising the molecular complexities of CRLM and identifying potentially prognostic molecular subtypes. High-throughput proteomics has accelerated a range of applications including protein profiling of liquid biopsies for biomarker discovery. Moreover, these proteomic biomarkers may provide non-invasive prognostic information even before CRLM resection. This review evaluates recently discovered circulating proteomic biomarkers in CRLM. We also highlight some of the challenges and opportunities with translating these discoveries into clinical applications.

Activated Chicken Gamma Delta T Cells Are Involved in Protective Immunity against Marek's Disease.

Gamma delta (γδ) T cells play a significant role in the prevention of viral infection and tumor surveillance in mammals. Although the involvement of γδ T cells in Marek's disease virus (MDV) infection has been suggested, their detailed contribution to immunity against MDV or the progression of Marek's disease (MD) remains unknown. In the current study, T cell receptor (TCR)γδ-activated peripheral blood mononuclear cells (PBMCs) were infused into recipient chickens and their effects were examined in the context of tumor formation by MDV and immunity against MDV. We demonstrated that the adoptive transfer of TCRγδ-activated PBMCs reduced virus replication in the lungs and tumor incidence in MDV-challenged chickens. Infusion of TCRγδ-activated PBMCs induced IFN-γ-producing γδ T cells at 10 days post-infection (dpi), and degranulation activity in circulating γδ T cell and CD8α+ γδ T cells at 10 and 21 dpi in MDV-challenged chickens. Additionally, the upregulation of IFN-γ and granzyme A gene expression at 10 dpi was significant in the spleen of the TCRγδ-activated PBMCs-infused and MDV-challenged group compared to the control group. Taken together, our results revealed that TCRγδ stimulation promotes the effector function of chicken γδ T cells, and these effector γδ T cells may be involved in protection against MD.

Ability of children to perform touchscreen gestures and follow prompting techniques when using mobile apps.

BACKGROUND: Children today get access to smartphones at an early age. However, their ability to use mobile apps has not yet been studied in detail. PURPOSE: This study aimed to assess the ability of children aged 2-8 years to perform touchscreen gestures and follow prompting techniques, i.e., ways apps provide instructions on how to use them. METHODS: We developed one mobile app to test the ability of children to perform various touchscreen gestures and another mobile app to test their ability to follow various prompting techniques. We used these apps in this study of 90 children in a kindergarten and a primary school in New Delhi in July 2019. We noted the touchscreen gestures that the children could perform and the most sophisticated prompting technique that they could follow. RESULTS: Two- and 3-year-old children could not follow any prompting technique and only a minority (27%) could tap the touchscreen at an intended place. Four- to 6-year-old children could perform simple gestures like a tap and slide (57%) and follow instructions provided through animation (63%). Sevenand 8-year-old children could perform more sophisticated gestures like dragging and dropping (30%) and follow instructions provided in audio and video formats (34%). We observed a significant difference between the number of touchscreen gestures that the children could perform and the number of prompting techniques that they could follow (F=544.0407, P<0.05). No significant difference was observed in the performance of female versus male children (P>0.05). CONCLUSION: Children gradually learn to use mobile apps beginning at 2 years of age. They become comfortable performing single-finger gestures and following nontextual prompting techniques by 8 years of age. We recommend that these results be considered in the development of mobile apps for children.