Comparison of two peptide radiotracers for prostate carcinoma targeting

OBJECTIVES: Scintigraphy is generally not the first choice treatment for prostate cancer, although successful studies using bombesin analog radiopeptides have been performed. Recently, a novel peptide obtained using a phage display library demonstrated an affinity for prostate tumor cells. The aim of this study was to compare the use of a bombesin analog to that of a phage display library peptide (DUP-1) radiolabeled with technetium-99m for the treatment of prostate carcinoma. The peptides were first conjugated to S-acetyl-MAG3 with a 6-carbon spacer, namely aminohexanoic acid. METHODS: The technetium-99m labeling required a sodium tartrate buffer. Radiochemical evaluation was performed using ITLC and was confirmed by high-performance liquid chromatography. The coefficient partition was determined, and in vitro studies were performed using human prostate tumor cells. Biodistribution was evaluated in healthy animals at various time points and also in mice bearing tumors. RESULTS: The radiochemical purity of both radiotracers was greater than 95%. The DUP-1 tracer was more hydrophilic (log P = -2.41) than the bombesin tracer (log P = -0.39). The biodistribution evaluation confirmed this hydrophilicity by revealing the greater kidney uptake of DUP-1. The bombesin concentration in the pancreas was greater than that of DUP-1 due to specific gastrin-releasing peptide receptors. Bombesin internalization occurred for 78.32% of the total binding in tumor cells. The DUP-1 tracer showed very low binding to tumor cells during the in vitro evaluation, although tumor uptake for both tracers was similar. The tumors were primarily blocked by DUP1 and the bombesin radiotracer primarily targeted the pancreas. CONCLUSION: Further studies with the radiolabeled DUP-1 peptide are recommended. With further structural changes, this molecule could become an efficient alternative tracer for prostate tumor diagnosis

Embryo selection through artificial intelligence versus embryologists: a systematic review

STUDY QUESTION What is the present performance of artificial intelligence (AI) decision support during embryo selection compared to the standard embryo selection by embryologists? SUMMARY ANSWER AI consistently outperformed the clinical teams in all the studies focused on embryo morphology and clinical outcome prediction during embryo selection assessment. WHAT IS KNOWN ALREADY The ART success rate is ∼30%, with a worrying trend of increasing female age correlating with considerably worse results. As such, there have been ongoing efforts to address this low success rate through the development of new technologies. With the advent of AI, there is potential for machine learning to be applied in such a manner that areas limited by human subjectivity, such as embryo selection, can be enhanced through increased objectivity. Given the potential of AI to improve IVF success rates, it remains crucial to review the performance between AI and embryologists during embryo selection. STUDY DESIGN, SIZE, DURATION The search was done across PubMed, EMBASE, Ovid Medline, and IEEE Xplore from 1 June 2005 up to and including 7 January 2022. Included articles were also restricted to those written in English. Search terms utilized across all databases for the study were: (‘Artificial intelligence’ OR ‘Machine Learning’ OR ‘Deep learning’ OR ‘Neural network’) AND (‘IVF’ OR ‘in vitro fertili*’ OR ‘assisted reproductive techn*’ OR ‘embryo’), where the character ‘*’ refers the search engine to include any auto completion of the search term. PARTICIPANTS/MATERIALS, SETTING, METHODS A literature search was conducted for literature relating to AI applications to IVF. Primary outcomes of interest were accuracy, sensitivity, and specificity of the embryo morphology grade assessments and the likelihood of clinical outcomes, such as clinical pregnancy after IVF treatments. Risk of bias was assessed using the Modified Down and Black Checklist. MAIN RESULTS AND THE ROLE OF CHANCE Twenty articles were included in this review. There was no specific embryo assessment day across the studies—Day 1 until Day 5/6 of embryo development was investigated. The types of input for training AI algorithms were images and time-lapse (10/20), clinical information (6/20), and both images and clinical information (4/20). Each AI model demonstrated promise when compared to an embryologist’s visual assessment. On average, the models predicted the likelihood of successful clinical pregnancy with greater accuracy than clinical embryologists, signifying greater reliability when compared to human prediction. The AI models performed at a median accuracy of 75.5% (range 59–94%) on predicting embryo morphology grade. The correct prediction (Ground Truth) was defined through the use of embryo images according to post embryologists’ assessment following local respective guidelines. Using blind test datasets, the embryologists’ accuracy prediction was 65.4% (range 47–75%) with the same ground truth provided by the original local respective assessment. Similarly, AI models had a median accuracy of 77.8% (range 68–90%) in predicting clinical pregnancy through the use of patient clinical treatment information compared to 64% (range 58–76%) when performed by embryologists. When both images/time-lapse and clinical information inputs were combined, the median accuracy by the AI models was higher at 81.5% (range 67–98%), while clinical embryologists had a median accuracy of 51% (range 43–59%). LIMITATIONS, REASONS FOR CAUTION The findings of this review are based on studies that have not been prospectively evaluated in a clinical setting. Additionally, a fair comparison of all the studies were deemed unfeasible owing to the heterogeneity of the studies, development of the AI models, database employed and the study design and quality. WIDER IMPLICATIONS OF THE FINDINGS AI provides considerable promise to the IVF field and embryo selection. However, there needs to be a shift in developers’ perception of the clinical outcome from successful implantation towards ongoing pregnancy or live birth. Additionally, existing models focus on locally generated databases and many lack external validation. STUDY FUNDING/COMPETING INTERESTS This study was funded by Monash Data Future Institute. All authors have no conflicts of interest to declare. REGISTRATION NUMBER CRD4202125633

Critical roles for WDR72 in calcium transport and matrix protein removal during enamel maturation

Defects in WDR72 (WD repeat‐containing protein 72) cause autosomal recessive hypomaturation amelogenesis imperfecta. We generated and characterized Wdr72‐knockout/lacZ‐knockin mice to investigate the role of WDR72 in enamel formation. In all analyses, enamel formed by Wdr72 heterozygous mice was indistinguishable from wild‐type enamel. Without WDR72, enamel mineral density increased early during the maturation stage but soon arrested. The null enamel layer was only a tenth as hard as wild‐type enamel and underwent rapid attrition following eruption. Despite the failure to further mineralize enamel deposited during the secretory stage, ectopic mineral formed on the enamel surface and penetrated into the overlying soft tissue. While the proteins in the enamel matrix were successfully degraded, the digestion products remained inside the enamel. Interactome analysis of WDR72 protein revealed potential interactions with clathrin‐associated proteins and involvement in ameloblastic endocytosis. The maturation stage mandibular incisor enamel did not stain with methyl red, indicating that the enamel did not acidify beneath ruffle‐ended ameloblasts. Attachment of maturation ameloblasts to the enamel layer was weakened, and SLC24A4, a critical ameloblast calcium transporter, did not localize appropriately along the ameloblast distal membrane. Fewer blood vessels were observed in the papillary layer supporting ameloblasts. Specific WDR72 expression by maturation stage ameloblasts explained the observation that enamel thickness and rod decussation (established during the secretory stage) are normal in the Wdr72 null mice. We conclude that WDR72 serves critical functions specifically during the maturation stage of amelogenesis and is required for both protein removal and enamel mineralization.We generated knockout mice lacking the ability to make WDR72. Deletion of WDR72 caused retention of degraded enamel proteins within the mineral layer and significantly reduced mineralization. The null enamel layer was only a tenth as hard as wild‐type enamel and underwent rapid attrition following eruption. Attachment of maturation ameloblasts to the enamel layer was weakened, and SLC24A4, a critical ameloblast calcium transporter, did not localize appropriately along the ameloblast distal membrane. Interactome analysis of WDR72 protein revealed potential involvement in ameloblastic endocytosis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112233/1/mgg3143.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/112233/2/mgg3143-sup-0001-SuppInfo.pd

Is race medically relevant? A qualitative study of physicians' attitudes about the role of race in treatment decision-making

<p>Abstract</p> <p>Background</p> <p>The role of patient race in medical decision-making is heavily debated. While some evidence suggests that patient race can be used by physicians to predict disease risk and determine drug therapy, other studies document bias and stereotyping by physicians based on patient race. It is critical, then, to explore physicians' attitudes regarding the medical relevance of patient race.</p> <p>Methods</p> <p>We conducted a qualitative study in the United States using ten focus groups of physicians stratified by self-identified race (black or white) and led by race-concordant moderators. Physicians were presented with a medical vignette about a patient (whose race was unknown) with Type 2 diabetes and untreated hypertension, who was also a current smoker. Participants were first asked to discuss what medical information they would need to treat the patient. Then physicians were asked to explicitly discuss the importance of race to the hypothetical patient's treatment. To identify common themes, codes, key words and physician demographics were compiled into a comprehensive table that allowed for examination of similarities and differences by physician race. Common themes were identified using the software package NVivo (QSR International, v7).</p> <p>Results</p> <p>Forty self-identified black and 50 self-identified white physicians participated in the study. All physicians - regardless of their own race - believed that medical history, family history, and weight were important for making treatment decisions for the patient. However, black and white physicians reported differences in their views about the relevance of race. Several black physicians indicated that patient race is a central factor for choosing treatment options such as aggressive therapies, patient medication and understanding disease risk. Moreover, many black physicians considered patient race important to understand the patient's views, such as alternative medicine preferences and cultural beliefs about illness. However, few white physicians explicitly indicated that the patient's race was important over-and-above medical history. Instead, white physicians reported that the patient should be treated aggressively regardless of race.</p> <p>Conclusions</p> <p>This investigation adds to our understanding about how physicians in the United States consider race when treating patients, and sheds light on issues physicians face when deciding the importance of race in medical decision-making.</p

Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches

Agricultural water management (AWM) is an interdisciplinary concern, cutting across traditional domains such as agronomy, climatology, geology, economics, and sociology. Each of these disciplines has developed numerous process-based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross-disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM — the actual practice of conserving water while maximizing productivity

Risk factors for household food insecurity in the Eastern Caribbean Health Outcomes Research Network cohort study

BackgroundGlobally, 1.3 billion people were considered food insecure as of 2022. In the Caribbean region, the prevalence of moderate or severe food insecurity was 71.3% as of 2020, the highest of all subregions in Latin America. Experienced based measurement scales, like the Latin American and Caribbean Food Security Scale, are efficient measurement tools of food insecurity used globally. The Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study is a population-based longitudinal cohort study in the two Caribbean U.S. territories of Puerto Rico and the U.S. Virgin Islands, as well as in Barbados and Trinidad &amp; Tobago. The purpose of this research was to examine the demographic, psychosocial, behavioral, and environmental risk factors associated with household food insecurity (HFI) among adults ≥40 years of age in the ECHORN cohort.MethodsA cross-sectional analysis of baseline ECHORN cohort study data was conducted. The primary outcome was household food insecurity (none, mild, moderate/severe). A total of 16 known and potential risk factors were examined for their association with HFI. The ANOVA and chi-square statistics were used in bivariate analysis. Ordinal logistic regression was used for the multivariable and sex stratified analyses.ResultsMore than one-quarter of the sample (27.3%) experienced HFI. In bivariate analyses, all risk factors examined except for sex, were significantly associated with HFI status. In the multivariable analysis, all variables except sex, education, marital status, smoking status, and residing in Puerto Rico were significant predictors of HFI in the adjusted model. In sex stratified analysis, depression, food availability, self-rated physical health, and island site were significantly associated with increased odds of worsening HFI for women, but not for men. Source of potable water was an important risk factor for both men and women.DiscussionThe prevalence of HFI in the ECHORN cohort study is comparable to other studies conducted in the region. While women did not have an increased risk of HFI compared to men, a different set of risk factors affected their vulnerability to HFI. More research is needed to understand how water and food security are interrelated in the ECHORN cohort

Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid Flow

We review modeling of astrocyte ion dynamics with a specific focus on the implications of so-called spatial potassium buffering, where excess potassium in the extracellular space (ECS) is transported away to prevent pathological neural spiking. The recently introduced Kirchoff-Nernst-Planck (KNP) scheme for modeling ion dynamics in astrocytes (and brain tissue in general) is outlined and used to study such spatial buffering. We next describe how the ion dynamics of astrocytes may regulate microscopic liquid flow by osmotic effects and how such microscopic flow can be linked to whole-brain macroscopic flow. We thus include the key elements in a putative multiscale theory with astrocytes linking neural activity on a microscopic scale to macroscopic fluid flow.Comment: 27 pages, 7 figure