A review of the peak-end rule in mental health contexts.

The peak-end rule, a memory heuristic in which the most emotionally salient part of an experience (i.e., peak) and conclusion of an experience (i.e., end) are weighted more heavily in summary evaluations, has been understudied in mental health contexts. The recent growth of intensive longitudinal methods has provided new opportunities for examining the peak-end rule in the retrospective recall of mental health symptoms, including measures often used in measurement-based care initiatives. Additionally, principles of the peak-end rule have significant potential to be applied to exposure-based therapy procedures. Additional research is needed to better understand the contexts in which, and persons for whom, the peak-end rule presents a greater risk of bias, to ultimately improve assessment strategies and clinical care.

Exploring the relationship between marital quality and cognitive function: A systematic review.

Cognitive function is an important indicator of healthy aging as it is central to maintaining functional independence, performing job-related tasks, decision-making, and improving quality of life. Therefore, researchers seek to identify biopsychosocial factors that can help preserve cognitive function in aging individuals. One such factor is the maintenance of good quality marital relationships. Research has consistently shown that married individuals fare better in terms of both physical and psychological health compared to their unmarried counterparts. However, being married is not universally beneficial - the quality of a marriage is also important to consider. To explore the issue further, we conducted a systematic review to examine the association between marital quality and cognitive function. PubMed, PsycINFO, and Scopus were searched for eligible articles examining any measure of marital quality and any cognitive outcome from the inception of each database to January 9th, 2024. Following two levels of citation screening by two independent reviewers, we included 15 articles representing 11 unique studies. Data were synthesized narratively following the Synthesis without Meta-Analysis guidelines and a risk of bias assessment was conducted using the Joanna Briggs Institute checklist. Most articles had a low risk of bias. Although some findings suggested more positive marital quality was associated with improved cognitive function, the results were not uniformly positive; some results were inverse or null, depending upon factors such as differences in study designs and measures of marital quality or cognition. This review is the first attempt to synthesize the literature on this topic. Our findings highlight that any examination of marital status and cognition should also consider contextual factors such as marital quality.

Lattice radiotherapy in inflammatory breast cancer: report of a first case treated with curative aim.

Inflammatory breast cancer (IBC) is a rare, aggressive form of breast cancer characterized by poor prognosis. The treatment requires a multidisciplinary approach, with neoadjuvant chemotherapy, surgery, and radiation therapy (RT). Particularly, high doses of conventional RT have been historically delivered in the adjuvant setting after chemotherapy and mastectomy or as radical treatment in patients ineligible for surgery. Here, we report the case of a 49-year-old woman patient with IBC unsuitable for surgery and treated with a combination of lattice RT and fractionated external beam RT concurrent with trastuzumab, with a curative aim. One year after RT, the patient showed a complete response and tolerable toxicities. This is the first reported case of a not-operable IBC patient treated with this particular kind of RT.

The Role of ArtificiaI Intelligence in Brain Tumor Diagnosis: An Evaluation of a Machine Learning Model.

This research study explores of the effectiveness of a machine learning image classification model in the accurate identification of various types of brain tumors. The types of tumors under consideration in this study are gliomas, meningiomas, and pituitary tumors. These are some of the most common types of brain tumors and pose significant challenges in terms of accurate diagnosis and treatment. The machine learning model that is the focus of this study is built on the Google Teachable Machine platform (Alphabet Inc., Mountain View, CA). The Google Teachable Machine is a machine learning image classification platform that is built from Tensorflow, a popular open-source platform for machine learning. The Google Teachable Machine model was specifically evaluated for its ability to differentiate between normal brains and the aforementioned types of tumors in MRI images. MRI images are a common tool in the diagnosis of brain tumors, but the challenge lies in the accurate classification of the tumors. This is where the machine learning model comes into play. The model is trained to recognize patterns in the MRI images that correspond to the different types of tumors. The performance of the machine learning model was assessed using several metrics. These include precision, recall, and F1 score. These metrics were generated from a confusion matrix analysis and performance graphs. A confusion matrix is a table that is often used to describe the performance of a classification model. Precision is a measure of the model's ability to correctly identify positive instances among all instances it identified as positive. Recall, on the other hand, measures the model's ability to correctly identify positive instances among all actual positive instances. The F1 score is a measure that combines precision and recall providing a single metric for model performance. The results of the study were promising. The Google Teachable Machine model demonstrated high performance, with accuracy, precision, recall, and F1 scores ranging between 0.84 and 1.00. This suggests that the model is highly effective in accurately classifying the different types of brain tumors. This study provides insights into the potential of machine learning models in the accurate classification of brain tumors. The findings of this study lay the groundwork for further research in this area and have implications for the diagnosis and treatment of brain tumors. The study also highlights the potential of machine learning in enhancing the field of medical imaging and diagnosis. With the increasing complexity and volume of medical data, machine learning models like the one evaluated in this study could play a crucial role in improving the accuracy and efficiency of diagnoses. Furthermore, the study underscores the importance of continued research and development in this field to further refine these models and overcome any potential limitations or challenges. Overall, the study contributes to the field of medical imaging and machine learning and sets the stage for future research and advancements in this area.

Mutagenic Azido Impurities in Drug Substances: A Perspective.

Contamination of drug products and substances containing impurities is a significant concern in the pharmaceutical industry because it may impact the quality and safety of medicinal products. Special attention is required when mutagenic impurities are present in pharmaceuticals, as they may pose a risk of carcinogenicity to humans. Therefore, controlling potential mutagenic impurities in active pharmaceutical ingredients to an acceptable safety limit is mandatory to ensure patient safety. As per the International Council for Harmonization (ICH) M7 (R2)3 Guideline, mutagenic impurities are those compounds or materials that induce point mutations. In 2018, the sartan class of drugs was recalled due to the presence of N-nitrosamine impurities, which are potential mutagens. In addition to the primary impurities being detected, this class of products, especially losartan, irbesartan and valsartan, have been identified as having organic azido contaminants, which are again highly reactive toward DNA, leading to an increased risk of cancer. These azido impurities form during the preparation of the tetrazole moiety via the reaction of a nitrile intermediate with sodium azide. Given that this is a newly raised issue in the pharmaceutical world, it should be noteworthy to review the related literature. Thus, this review article critically accounts for (i) the toxicity of azido impurities and the proposed mechanism of mutagenicity, (ii) the regulatory perspective, and (iii) the sources and control strategies used during the preparation of drug substances and (iv) future perspectives.

Forward versus backward recall: Modality testing.

OBJECTIVES: One of the most frequently applied paradigms in the clinical and experimental fields for assessing working memory is the simple span task, composed of forward and backward recall conditions. However, the utility of the simple span measures and their relation to working memory modalities has yet to be elucidated. The current study aimed to address which of the span measures is more sensitive to the differentiation between forward and backward recall in the tactile, verbal, and visuo-spatial modalities, and to test if working memory modalities differ in the disparity between the two conditions. METHODS: 134 healthy young adults performed the Tactual, Digit, and Visuo-spatial Span tasks, producing Total Correct scores and Longest Sequence score measures. RESULTS: There was an interaction effect for condition and modality type, showing better performance for the forward compared to the backward recall in both measures. However, the effect size of the Longest Sequence score was significantly higher than the Total Correct score in all tasks. Furthermore, the Visuo-spatial Span exhibited a larger difference between forward and backward recall compared to the Digit and Tactual Span, whereas no difference was found between the latter two. CONCLUSIONS: Forward and backward recall are distinguished in all three modalities, and the Longest Sequence score is more sensitive to differentiate between storage and manipulation components of working memory than the Total Correct score. Additionally, the cognitive demand imposed by manipulation compared to storage is the greatest in the visuo-spatial modality.

The influence of emotion on temporal context models.

Temporal context models (TCMs) have been influential in understanding episodic memory and its neural underpinnings. Recently, TCMs have been extended to explain emotional memory effects, one of the most clinically important findings in the field of memory research. This review covers recent advances in hypotheses for the neural representation of spatiotemporal context through the lens of TCMs, including their ability to explain the influence of emotion on episodic and temporal memory. In recent years, simplifying assumptions of "classical" TCMs - with exponential trace decay and the mechanism by which temporal context is recovered - have become increasingly clear. The review also outlines how recent advances could be incorporated into a future TCM, beyond classical assumptions, to integrate emotional modulation.

The Role of Prefrontal Ensembles in Memory Across Time: Time-Dependent Transformations of Prefrontal Memory Ensembles.

The medial prefrontal cortex (mPFC) plays a critical role in recalling recent and remote fearful memories. Modern neuroscience techniques, such as projection-specific circuit manipulation and activity-dependent labeling, have illuminated how mPFC memory ensembles are reorganized over time. This chapter discusses the implications of new findings for traditional theories of memory, such as the systems consolidation theory and theories of memory engrams. It also examines the specific contributions of mPFC subregions, like the prelimbic and infralimbic cortices, in fear memory, highlighting how their distinct connections influence memory recall. Further, it elaborates on the cellular and molecular changes within the mPFC that support memory persistence and how these are influenced by interactions with the hippocampus. Ultimately, this chapter provides insights into how lasting memories are dynamically encoded in prefrontal circuits, arguing for a key role of memory ensembles that extend beyond strict definitions of the engram.

The receiver operating characteristic curve accurately assesses imbalanced datasets.

Many problems in biology require looking for a "needle in a haystack," corresponding to a binary classification where there are a few positives within a much larger set of negatives, which is referred to as a class imbalance. The receiver operating characteristic (ROC) curve and the associated area under the curve (AUC) have been reported as ill-suited to evaluate prediction performance on imbalanced problems where there is more interest in performance on the positive minority class, while the precision-recall (PR) curve is preferable. We show via simulation and a real case study that this is a misinterpretation of the difference between the ROC and PR spaces, showing that the ROC curve is robust to class imbalance, while the PR curve is highly sensitive to class imbalance. Furthermore, we show that class imbalance cannot be easily disentangled from classifier performance measured via PR-AUC.

Application of the Japanese Verbal Learning Test to Patients With Alzheimer's Disease in the Early Stage.

INTRODUCTION: This study aimed to investigate the mechanism of memory function in the context of explicit memory in early-stage Alzheimer's disease (AD) using the short-form Japanese Verbal Learning Test (JVLT-9). METHODS: Participants were 20 patients with early-stage AD and a control group of 23 healthy older adults (normal controls: NC), each of whom was administered the JVLT-9, which is a verbal list learning task used to assess explicit memory comprehensively. Between-group differences for each score were investigated using the Mann-Whitney U test. A two-way analysis of variance (ANOVA) was performed for the number of correct recalls by group (AD/NC) × JVLT-9 task. In addition, the AD group was divided into a CDR 0.5 group and a CDR 1.0 group, and it was performed as a group (CDR 0.5/1.0) × JVLT-9 task two-way ANOVA. RESULTS: The results demonstrated that the AD group had lower immediate recall, learning rate, semantic clustering, and recognition discrimination and significantly higher intrusion errors compared to the NC group. Further, JVLT-9 recall and recognition rates were found to be lower with higher CDR (an index of dementia severity). CONCLUSION: These results are largely consistent with the features of explicit memory in AD reported in the English version, confirming the clinical utility of the JVLT-9 as a test of explicit memory function.

If Engrams Are the Answer, What Is the Question?

Engram labelling and manipulation methodologies are now a staple of contemporary neuroscientific practice, giving the impression that the physical basis of engrams has been discovered. Despite enormous progress, engrams have not been clearly identified, and it is unclear what they should look like. There is an epistemic bias in engram neuroscience toward characterizing biological changes while neglecting the development of theory. However, the tools of engram biology are exciting precisely because they are not just an incremental step forward in understanding the mechanisms of plasticity and learning but because they can be leveraged to inform theory on one of the fundamental mysteries in neuroscience-how and in what format the brain stores information. We do not propose such a theory here, as we first require an appreciation for what is lacking. We outline a selection of issues in four sections from theoretical biology and philosophy that engram biology and systems neuroscience generally should engage with in order to construct useful future theoretical frameworks. Specifically, what is it that engrams are supposed to explain? How do the different building blocks of the brain-wide engram come together? What exactly are these component parts? And what information do they carry, if they carry anything at all? Asking these questions is not purely the privilege of philosophy but a key to informing scientific hypotheses that make the most of the experimental tools at our disposal. The risk for not engaging with these issues is high. Without a theory of what engrams are, what they do, and the wider computational processes they fit into, we may never know when they have been found.

A four-year assessment of the characteristics of Rwandan FDA drug recalls.

BACKGROUND: A drug recall is an act of removing products from the market and/or returning them to the manufacturer for disposal or correction when they violate safety laws. Action can be initiated by the manufacturing company or by the order of a regulatory body. This study aimed to assess the characteristics of Rwanda FDA drug recall and determine the association between classes of recall and recall characteristics. METHODOLOGY: This was a retrospective descriptive cross-sectional study. Data about recalled drugs were collected from the official website of the Rwanda FDA in the section assigned to "Safety alerts". The search included data reported between February 2019 and February 2023 covering four years. Data cleaning was conducted in Microsoft Excel to address missing data and inconsistencies, followed by importation into STATA/SE software version 17.0 for further cleaning and subsequent analysis. Descriptive statistics were computed for independent variables. Categorical variables were described in terms of counts and relative frequencies. Bivariate analyses used Pearson's chi-square test to illustrate the associations between categorical independent variables and recall classes. RESULTS: The study revealed that a large proportion (33.0%) of the recalled products belonged to Class I. Antibiotics constituted 35.8% of the recalled products, with contamination emerging as a leading cause and responsible for 26.4% of the recalls. India was the leading manufacturing country for the recalled products (29.2%), followed by France (17.9%), China (17.0%), Kenya (13.2%), and Russia (6.6%). An association was found between the class of recall and several recall characteristics, including the year of recall, drug category, safety issues, reporter, and manufacturing country. CONCLUSION: This study provides a comprehensive overview of the characteristics of drug recalls in Rwanda. The insights gained contribute to a nuanced understanding of recall dynamics and provide evidence-based strategies to enhance drug quality, safety, efficacy, regulatory compliance, and patient welfare.

The impact of sleep quality on visual working memory varied with the duration of maintenance.

Objective: Sleep quality can affect the performance of visual working memory. However, the effect of sleep quality on the maintenance stage, which is the key to maintain the quality and efficiency of visual working memory representation, remains unclear. This study is the first to explore the effect of sleep quality on the maintenance of visual working memory information. Method: 60 healthy college students completed the Pittsburgh Sleep Quality Index (PSQI) and color recall task of visual working memory. A mixed experimental design of sleep quality (high or low) and delay duration (1, 4, or 6 s) was used to assess the effect of sleep quality on the maintenance phase of visual working memory. Results: The main effects of sleep quality were significant on visual working memory quantity, precision and offset indexes. Among the quantity index, the interaction between sleep quality and delay duration was also significant. This suggests that prolonging the delay time in the maintenance phase leads to difficulty in maintaining attention to the task for those with lower sleep quality, which results in poorer working memory quantitative representations. Conclusion: Increases in the delay duration of the maintenance phase in visual working memory intensify the impact of sleep quality on task performance. Our study provides evidence to reveal the relationship between sleep quality and visual working memory and offers recommendations for improving sleep quality and cognitive functioning in individuals.

Sex-Specific Differences in Serum Kallikrein-8 (KLK8): An Exploratory Study.

Background: There are indications for sex-specific differences regarding the association between kallikrein-8 (KLK8) and cognitive impairment in early stages of Alzheimer's disease for which KLK8 may be an early blood-based biomarker. These may be due to different levels of sex hormones. To correctly interpret KLK8 blood concentrations, sex-specific analyses are needed. Objective: The aim of our exploratory study was to investigate sex-specific differences in blood-based KLK8 in participants of the population-based Heinz Nixdorf Recall study with different cognitive status and the association between KLK8 and sex hormones. Methods: In 290 participants (45% women, 69.7±7.4 years (mean±SD)) we investigated sex-specific serum KLK8 differences between cognitively unimpaired (CU, 43%) and cognitively impaired (CI) participants and the association between KLK8 and dehydroepiandrosteronsulfate (DHEAS), estradiol and testosterone, using adjusted multiple linear regression. Results: The mean±SD KLK8 was similar for CU men (808.1±729.6 pg/ml) and women (795.9±577.7 pg/ml); adjusted mean-difference [95%-CI]: -95.3 [-324.1;133.5] pg/ml. KLK8 was lower in CI women (783.5±498.7 pg/ml) than men (1048.4±829 pg/ml); -261 [-493.1; -29] pg/ml. In men but not women, there was a weak indication for a positive slope between estradiol (11.9 [-0.4;24.3] pg/ml) and DHEAS (1.4 [-0.5;3.3] pg/ml) with KLK8, while testosterone had no impact. Conclusions: The results suggested a different role for KLK8 in the development of cognitive impairment in men and women, potentially influenced by sex hormones. To use blood KLK8 as an early biomarker, further research on hormonal regulation of KLK8 expression is needed as a part of the investigation of the KLK8 involvement in cognitive impairment and Alzheimer's disease pathology.

Statistical Analysis of Self-Reported Health Conditions in Cohort Studies: Handling of Missing Onset Age.

OBJECTIVE: This paper discusses methodological challenges in epidemiological association analysis of a time-to-event outcome and hypothesized risk factors, where age/time at the onset of the outcome may be missing in some cases, a condition commonly encountered when the outcome is self-reported. STUDY DESIGN AND SETTING: A cohort study with long-term follow-up for outcome ascer- tainment such as the Childhood Cancer Survivor Study (CCSS), a large cohort study of 5-year survivors of childhood cancer diagnosed in 1970-1999 in which occurrences and age at onset of various chronic health conditions (CHCs) are self-reported in surveys. Simple methods for handling missing onset age and their potential bias in the exposure-outcome association infer- ence are discussed. The interval-censored method is discussed as a remedy for handling this problem. The finite sample performance of these approaches is compared through Monte Carlo simulations. Examples from the CCSS include four CHCs (diabetes, myocardial infarction, osteoporosis/osteopenia, and growth hormone deficiency). RESULTS: The interval-censored method is usable in practice using the standard statisti- cal software. The simulation study showed that the regression coefficient estimates from the 'Interval censored' method consistently displayed reduced bias and, in most cases, smaller stan- dard deviations, resulting in smaller mean square errors, compared to those from the simple approaches, regardless of the proportion of subjects with an event of interest, the proportion of missing onset age, and the sample size. CONCLUSION: The interval-censored method is a statistically valid and practical approach to the association analysis of self-reported time-to-event data when onset age may be missing. While the simpler approaches that force such data into complete data may enable the standard analytic methods to be applicable, there is considerable loss in both accuracy and precision relative to the interval-censored method.

Temporal organization of narrative recall is present but attenuated in adults with hippocampal amnesia.

Studies of the impact of brain injury on memory processes often focus on the quantity and episodic richness of those recollections. Here, we argue that the organization of one's recollections offers critical insights into the impact of brain injury on functional memory. It is well-established in studies of word list memory that free recall of unrelated words exhibits a clear temporal organization. This temporal contiguity effect refers to the fact that the order in which word lists are recalled reflects the original presentation order. Little is known, however, about the organization of recall for semantically rich materials, nor how recall organization is impacted by hippocampal damage and memory impairment. The present research is the first study, to our knowledge, of temporal organization in semantically rich narratives in three groups: (1) Adults with bilateral hippocampal damage and severe declarative memory impairment, (2) adults with bilateral ventromedial prefrontal cortex (vmPFC) damage and no memory impairment, and (3) demographically matched non-brain-injured comparison participants. We find that although the narrative recall of adults with bilateral hippocampal damage reflected the temporal order in which those narratives were experienced above chance levels, their temporal contiguity effect was significantly attenuated relative to comparison groups. In contrast, individuals with vmPFC damage did not differ from non-brain-injured comparison participants in temporal contiguity. This pattern of group differences yields insights into the cognitive and neural systems that support the use of temporal organization in recall. These data provide evidence that the retrieval of temporal context in narrative recall is hippocampal-dependent, whereas damage to the vmPFC does not impair the temporal organization of narrative recall. This evidence of limited but demonstrable organization of memory in participants with hippocampal damage and amnesia speaks to the power of narrative structures in supporting meaningfully organized recall despite memory impairment.

Managing cow's milk protein allergy during the 2022 formula shortage: decision-making among pediatric healthcare providers.

Introduction: Cow's milk protein allergy (CMPA) affects 2%-7% of infants and is managed with hypoallergenic formulas. The 2022 recalls of infant formulas due to factors including contamination led to specialty formula shortages, highlighting CMPA management challenges. Understanding healthcare providers' (HCPs) decision-making in transitioning to alternative formulas during shortages is crucial. Limited attention has been given to how pediatric physicians make these choices. Methods: This study utilized US HCPs' de-identified survey data to assess driving factors when switching extensively hydrolyzed formulas during shortages. Results: 104 eligible HCPs participated, including general pediatrics, pediatric allergy/immunology, and pediatric gastroenterology specialists. Safety, tolerability, and efficacy were identified as top factors for switching formulas. Formula 1 was considered well-tolerated, patient-accepted, and safe by all HCPs. Most expressed strong belief in Formula 1's safety and effectiveness. Discussion: Findings inform CMPA management during shortages, offering guidance to HCPs for suitable formula selection and enhanced infant care.

A theory of hippocampal function: New developments.

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

Cognitive performance trends among European older adults: exploring variations across cohorts, gender, and educational levels (2007-2017).

BACKGROUND: This study explores recent cohort trends in cognitive performance among older Europeans from 2007 to 2017, addressing three key questions: (1) Did cognitive performance improve universally and across the performance distribution during this period? (2) Did these improvements occur across educational levels and for both men and women? (3) Can established risk factors explain these performance gains? METHODS: Using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) across 12 European countries, we assessed immediate recall, delayed recall, and verbal fluency in individuals aged 60 to 94 in both 2007 and 2017 (n = 32 773). Differences between the two time points were estimated with linear mixed effects regression models and quantile regression. RESULTS: Cognitive performance improved in all age groups, across educational levels, and for both men and women between 2007 and 2017. Notably, improvements were more pronounced at the upper end of the performance distribution for delayed recall and verbal fluency. Education explained approximately 20% of the observed improvements. Risk factors did not explain the observed improvements. CONCLUSIONS: European cohorts of both younger-old and older adults continue to exhibit improvements in cognitive performance. Variation in the size of the cohort improvements across the performance distributions in delayed recall and in verbal fluency may contribute to growing inequalities in cognitive outcomes. Future research should further investigate the potential heterogeneity in cognitive performance gains. TRIAL REGISTRATION: Not applicable.