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Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

Using multigroup structural equation modeling, this study examines whether family-work-school conflicts directly or indirectly predict transfer students’ well-being (via self-regulation) across the periods of pre-, during, and post-COVID-19 lockdown in the Chicago metropolitan area in Illinois, United States. The results indicate that family-school conflict predicted well-being regardless of lockdown status, but work-school conflict predicted well-being only during the lockdown period. This study also discusses the importance of cognitive regulation for transfer students’ transition in the middle of the pandemic.

Predictive modeling using neuroimaging data has the potential to improve our understanding of the neurobiology underlying psychiatric disorders and putatively information interventions. Accordingly, there is a plethora of literature reviewing published studies, the mathematics underlying machine learning, and the best practices for using these approaches. As our knowledge of mental health and machine learning continue to evolve, we instead aim to look forward and “predict” topics that we believe will be important in current and future studies. Some of the most discussed topics in machine learning, such as bias and fairness, the handling of dirty data, and interpretable models, may be less familiar to the broader community using neuroimaging-based predictive modeling in psychiatry. In a similar vein, transdiagnostic research and targeting brain-based features for psychiatric intervention are modern topics in psychiatry that predictive models are well-suited to tackle. In this work, we target an audience who is a researcher familiar with the fundamental procedures of machine learning and who wishes to increase their knowledge of ongoing topics in the field. We aim to accelerate the utility and applications of neuroimaging-based predictive models for psychiatric research by highlighting and considering these topics. Furthermore, though not a focus, these ideas generalize to neuroimaging-based predictive modeling in other clinical neurosciences and predictive modeling with different data types (e.g., digital health data).

Purpose: This study investigated whether family−school conflict, directly and indirectly, predicts behavioral regulatory strategies (via emotion regulation) among women in higher education. The authors aim to hypothesize that the direct and indirect effects would vary by race/ethnicity. Design/methodology/approach: Participants were 1,872 incoming first-year female students from a large, racially/ethnically diverse urban public university. They were classified into four racial/ethnic groups: 22% Asian American (n= 403), 11% Black (n= 209), 46% Latina (n= 865), and 21% White (n= 395). Data were collected from institutional records and an online student pre-matriculation survey. Multigroup structural equation modeling (SEM) was performed to explore the structural relations among key variables. Findings: Family−school conflict was negatively associated with help-seeking in all racial/ethnic groups, whereas family−school conflict was negatively associated with time management only for Latina students. In addition, family−school conflict indirectly predicted time management and help-seeking through increased emotion regulation, particularly among Latina students. Originality/value: In considering racial heterogeneity, the results showed the importance of analyzing racial/ethnic groups separately to obtain more accurate information on self-regulation mechanisms in family−school conflict contexts.

Primary autoimmune neutropenia (pAN) is typified by onset in early infancy and a mild/moderate phenotype that resolves within 3 years of diagnosis. In contrast, secondary AN is classically an adult disease associated with malignancy, autoimmunity, immunodeficiency, viral infection, or drugs. This study describes a cohort of 79 children from the Italian Registry who, although resembling pAN, did not fully match the criteria for pAN because neutropenia either appeared after age 5 years (LO-Np) or lasted longer than 3 years (LL-Np). These 2 categories compared with classical pAN showed a far inferior rate of resolution (P < .001), lower severity of neutropenia (P = .03), leukopenia (P < .001), lymphopenia (P < .001) with low B+ (P = .001), increased need of granulocyte colony-stimulating factor (P = .04), and increased frequency of autoimmunity over the disease course (P < .001). A paired comparison between LO-Np and LL-Np suggested that LO-Np had a lower rate of resolution (P < .001) and lower white blood cell (P < .001) and lymphocyte (P < .001) values, higher occurrence of apthae (P = .008), and a stronger association with autoimmune diseases/markers (P = .001) than LL-Np, thus suggesting a more pronounced autoimmune signature for LO-Np. A next-generation sequencing panel applied in a small subgroup of LO-Np and LL-Np patients identified variants related to immune dysregulations. Overall, these findings indicate that there are important differences among pAN LL-Np and LO-Np. Forms rising after 3 years of age, with low tendency to resolution, require tight monitoring and extensive immune investigations aimed to early identify underlying immunologic disease.

Primary autoimmune neutropenia (pAN) is typified by onset in early infancy and a mild/moderate phenotype that resolves within 3 years of diagnosis. In contrast, secondary AN is classically an adult disease associated with malignancy, autoimmunity, immunodeficiency, viral infection, or drugs. This study describes a cohort of 79 children from the Italian Registry who, although resembling pAN, did not fully match the criteria for pAN because neutropenia either appeared after age 5 years (LO-Np) or lasted longer than 3 years (LL-Np). These 2 categories compared with classical pAN showed a far inferior rate of resolution (P< .001), lower severity of neutropenia (P= .03), leukopenia (P< .001), lymphopenia (P< .001) with low B+ (P= .001), increased need of granulocyte colony-stimulating factor (P= .04), and increased frequency of autoimmunity over the disease course (P< .001). A paired comparison between LO-Np and LL-Np suggested that LO-Np had a lower rate of resolution (P< .001) and lower white blood cell (P< .001) and lymphocyte (P< .001) values, higher occurrence of apthae (P= .008), and a stronger association with autoimmune diseases/markers (P= .001) than LL-Np, thus suggesting a more pronounced autoimmune signature for LO-Np. A next-generation sequencing panel applied in a small subgroup of LO-Np and LL-Np patients identified variants related to immune dysregulations. Overall, these findings indicate that there are important differences among pAN LL-Np and LO-Np. Forms rising after 3 years of age, with low tendency to resolution, require tight monitoring and extensive immune investigations aimed to early identify underlying immunologic disease.

Background: Prevailing models of obesity posit that hedonic signals override homeostatic mechanisms to promote overeating in today’s food environment. What researchers mean by “hedonic” varies considerably, but most frequently refers to an aggregate of appetitive events including incentive salience, motivation, reinforcement, and perceived pleasantness. Here we define hedonic as orosensory pleasure experienced during eating and set out to test whether there is a relationship between adiposity and the perceived pleasure of a palatable and energy-dense milkshake. Methods: The perceived liking, wanting, and intensity of two palatable and energy-dense milkshakes were assessed using the Labeled Hedonic Scale (1), visual analog scale (VAS), and Generalized Labeled Magnitude Scale (2) in 110 individuals ranging in body mass index (BMI) from 19.3 to 52.1 kg/m2. Waist circumference, waist–hip ratio, and percent body fat were also measured. Importantly, unlike the majority of prior studies, we attempted to standardize internal state by instructing participants to arrive to the laboratory neither hungry nor full and at least 1-h fasted. Data were analyzed with general linear and linear mixed effects models (GLMs). Hunger ratings were also examined prior to hedonic measurement and included as covariates in our analyses. Results: We identified a significant association between ratings of hunger and milkshake liking and wanting. By contrast, we found no evidence for a relationship between any measure of adiposity and ratings of milkshake liking, wanting, or intensity. Conclusions: We conclude that adiposity is not associated with the pleasure experienced during consumption of our energy-dense and palatable milkshakes. Our results provide further evidence against the hypothesis that heightened hedonic signals drive weight gain.

Rasburicase is a recombinant urate oxidase enzyme indicated for tumor lysis syndrome, a potential life-threatening oncologic emergency that occurs most commonly during initial chemotherapy for hematological malignancies. As a result of the defects in the physiological antioxidant pathway, erythrocytes of patients with glucose-6-phosphate dehydrogenase deficiency are not protected against the oxidizing stress exerted by hydrogen peroxide generated with the administration of rasburicase. The authors report a 14-year-old patient, diagnosed with T-cell acute lymphoblastic leukemia, who developed methemoglobinemia and hemolytic anemia with low oxygen saturation after starting steroids, hyperhydratation, and rasburicase administration. The complications resolved with supportive therapy only.

The core knowledge about biomineralization is provided by studies on the advanced phases of the process mainly occurring in the extracellular matrix. Here, we investigate the early stages of biomineralization by evaluating the chemical fingerprint of the initial mineral nuclei deposition in the intracellular milieu and their evolution toward hexagonal hydroxyapatite. The study is conducted on human bone mesenchymal stem cells exposed to an osteogenic cocktail for 4 and 10 days, exploiting laboratory X-ray diffraction techniques and cutting-edge developments of synchrotron-based 2D and 3D cryo-X-ray microscopy. We demonstrate that biomineralization starts with Zn–hydroxyapatite nucleation within the cell, rapidly evolving toward hexagonal hydroxyapatite crystals, very similar in composition and structure to the one present in human bone. These results provide experimental evidence of the germinal role of Zn in hydroxyapatite nucleation and foster further studies on the intracellular molecular mechanisms governing the initial phases of bone tissue formation.

IntroductionShwachman-Diamond Syndrome (SDS) is a rare bone marrow (BM) failure disorder. SDS BM biopsies show tortuous and collapsed vessels, highlighting angiogenic abnormalities. Our group previously demonstrated that SDS BM mesenchymal stromal cells (MSCs) have in vitroand in vivoimpaired angiogenic potential compared to healthy donors (HD)-MSCs.

ABSTRACTStudents’ learning strategies predict and explain academic performance and success in university. This study employed Latent Profile Analysis (LPA) to identify students’ unique patterns of learning strategies in university. A total of 2502 first-year US university students participated in this study. LPA identified four profiles: low strategy use, high strategy use, moderate strategy use, and goal-engagement strategy use. A series of ANOVA tests revealed that students in the high strategy useprofile earned higher grades than did students in the other profiles. However, there was no significant difference between the high strategy useand goal-engagement strategy useprofiles for other academic outcomes. The distribution of profiles varied by gender, but not by race/ethnicity or financial need. Interventions designed to increase students’ academic success in university should include components that target the development of learning strategies, particularly students’ academic goal engagement.

Specific and sensitive tools for quantifying intracellular magnesium cations are needed in biochemical research. This protocol describes the synthesis and use of a fluorescent Mg2+probe based on diaza-18-crown-6-hydroxyquinoline.

Autoimmune neutropenia of infancy (AIN), also called primary autoimmune neutropenia, is a disease in which antibodies recognize membrane antigens of neutrophils, mostly located on immunoglobulin G (IgG) Fc receptor type 3b (FcγIIIb receptor), causing their peripheral destruction. It is the most frequent type of neutropenia in children under 3–4 years of age and in most cases shows a benign, self-limited course. The diagnosis is based on evidence of indirect antineutrophil antibodies, whose detection frequently remains difficult. In this review we have analyzed the literature regarding AIN and present our personal experience in diagnosis and management.

Poikiloderma with neutropenia (PN, OMIM 604173) is a rare autosomal-recessive genodermatosis. Mutations in the C16orf57gene have been recently identified as the cause. Here we describe a new case of PN in a white patient, review the literature, and point out the attention on importance of differential diagnosis.

In the last few years, wine industry has been characterised by profound changes that have determined an intensification of competition on a global scale. The aim of this study is to identify the firms’ internal factors that most influence the export intensity and the ability to fit into the international market of the Italian wineries producing sparkling wines through a resource-based view (RBV) approach. Results of our study supporting the findings of previous empirical researches presented in this paper. In particular, the main factors affecting export intensity are: innovation degree and intensity of investment in advertising and promotion, among firms’ characteristics, and abroad experience, proficiency of foreign languages, educational level, and perception barriers, among managers’ characteristics.

The study focused on learning difficulties experienced by East Asian International (EAI) students. Participants were 117 EAI students undertaking tertiary study at a major university, all were surveyed and 21 students were interviewed. The findings suggest that language limitations, academic content and learning styles were associated with difficulties in their learning. Difficulties with academic content appeared to act as the major barrier to their academic performance rather than English language. This is contrary to earlier findings, where Asian students often experienced difficulties in tasks that are particularly related to language proficiency. The study also contradicted the popular belief that Asian students are only surface learners.