Occupational therapy's role in promoting the "Learn the Signs. Act Early." developmental monitoring program to public health employees.

Background: Occupational therapists can play a key role in early identification of delay at the population health level by providing education to public health employees on how to implement developmental monitoring with caregivers of children birth to age 5. Methods: A pretest posttest design was utilized to assess the online education and training that was provided to Department of Public Health employees (N = 339), including Head Start, Special Supplemental Nutrition Program for Women, Infants and Children, Home Visiting, and Early Intervention. Results: Analysis of pretest-posttest survey data showed significant results for all 12 key learning outcomes. Six out of 12 outcomes were found to have a large effect size (d > 0.8), 4 outcomes indicated a medium effect size (d > 0.5), and 2 outcomes had a small effect size (d > 0.2). Participants gained knowledge of the "Learn the Signs. Act Early." (LTSAE) developmental monitoring program, the difference between developmental monitoring and screening, the state's referral system and age-appropriate parental engagement activities through knowledge of child development. Conclusions: Occupational therapists are child development specialists who can provide education on developmental monitoring and activities for parental engagement. The online course proved to be an effective platform to promote LTSAE within state agencies.

Sport-related concussions in baseball and softball: do mechanisms of injury affect recovery?

OBJECTIVE: Baseball and softball pose unique risks for sport-related concussion (SRC). Although these are not collision sports, concussions in baseball and softball can nonetheless involve high-speed impacts. In a regional, single-institution cohort of baseball and softball athletes who sustained an SRC, the current study sought to 1) describe the mechanisms of injury that led to SRC, and 2) compare initial symptom burden and recovery metrics across mechanisms, including time to return to learn (RTL), time to symptom resolution, and time to return to play (RTP) by mechanism of injury. METHODS: A retrospective cohort study was performed of baseball and softball athletes 12 to 23 years old who sustained an SRC between November 2017 and April 2022. Mechanisms of injury were divided into two categories: 1) contact mechanism (i.e., what initiated contact with the injured player, such as head-to-ball), and 2) player mechanism (i.e., the action the injured player was performing at the time of injury, such as fielding). The recovery outcomes of time to RTL, symptom resolution, and RTP were compared between mechanisms using bivariate analysis and multivariable regression analysis, controlling for sex, age, time to present to concussion clinic, and initial total symptom score. RESULTS: The sample included 58 baseball and softball players (60.3% female, mean age 16.0 ± 1.9 years). Most SRCs (62.1%) occurred during competition. Head-to-ball (50.0%) was the most common contact mechanism, followed by head-to-head/body (31.0%) and head-to-wall/ground/equipment (17.2%). Fielding (63.8%) was the most common player mechanism, followed by drills (20.7%) and running (13.8%). SRCs sustained in practice had significantly longer RTL (median 10.0 [interquartile range (IQR) 3.3-16.3] vs 4.0 [IQR 2.0-8.0] days; U = 421.5, p = 0.031) and symptom resolution (37.0 [IQR 18.0-90.0] vs 14.0 [IQR 7.0-41.0] days; U = 406.5, p = 0.025) compared with SRCs sustained in competition. Multivariable regression analysis revealed that head-to-wall/ground/equipment contact mechanism was associated with longer RTL (ß = 0.30, 95% CI 0.07-0.54, p = 0.013). CONCLUSIONS: The current study found that SRCs in baseball and softball occurred more often in competition than in practice. Head-to-ball and fielding were the most common contact and player mechanisms, respectively. SRCs sustained in practice were associated with longer time to RTL and symptom resolution, and head-to-wall/ground/equipment was associated with longer RTL in multivariable regression analysis. These results provide empirical data to improve concussion safety in baseball/softball.

Acute psychological symptom profiles in high school athletes following sport-related concussion.

OBJECTIVE: Psychological symptoms following a sport-related concussion may affect recovery in adolescent athletes. Therefore, the aims of this study were to 1) describe the proportion of athletes with acute psychological symptoms, 2) identify potential predictors of higher initial psychological symptoms, and 3) determine whether psychological symptoms affect recovery in a cohort of concussed high school athletes. METHODS: A retrospective cohort study of high school athletes (14-18 years of age) who sustained a sport-related concussion from November 2017 to April 2022 and presented to a multidisciplinary concussion center was performed. The main independent variable was psychological symptom cluster score, calculated by summing the four affective symptoms on the initial Post-Concussion Symptom Scale (PCSS) (i.e., irritability, sadness, nervousness, feeling more emotional). The psychological symptom ratio was defined as the ratio of the psychological symptom cluster score divided by the total initial PCSS score. The outcomes included time to return to learn (RTL), symptom resolution, and time to return to play (RTP). Univariable and multivariable regressions were performed to adjust for demographic factors and health history. RESULTS: A total of 431 athletes (58.0% female, mean age 16.2 ± 1.3 years) were included. Nearly half of the sample (45%) reported at least one psychological symptom, with a mean psychological symptom cluster score of 4.2 ± 5.2 and psychological symptom cluster ratio of 0.10 ± 0.11. Irritability was the most commonly endorsed psychological symptom (38.1%), followed by feeling more emotional (30.2%), nervousness (25.3%), and sadness (22.0%). Multivariable regression showed that female sex (B = 2.15, 95% CI 0.91-3.39; p < 0.001), loss of consciousness (B = 1.91, 95% CI 0.11-3.72; p = 0.037), retrograde/anterograde amnesia (B = 1.66, 95% CI 0.20-3.11; p = 0.026), and psychological history (B = 2.96, 95% CI 1.25-4.70; p < 0.001) predicted an increased psychological symptom cluster score. Female sex (B = 0.03, 95% CI 0.00-0.06; p = 0.031) and psychological history (B = 0.06, 95% CI 0.02-0.10; p = 0.002) predicted an increased psychological symptom ratio. Multivariable linear regression showed that both higher psychological symptom cluster score and ratio were associated with longer times to RTL, symptom resolution, and RTP. CONCLUSIONS: In a cohort of high school athletes, 45% reported at least one psychological symptom, with irritability being most common. Female sex, loss of consciousness, amnesia, and a psychological history were significantly associated with an increased psychological symptom cluster score. Higher psychological symptom cluster score and psychological symptom ratio independently predicted longer recovery. These results reinforce the notion that psychological symptoms after concussion are common and may negatively impact recovery.

Examining for gender differences in return to learn following sport-related concussion in high school student athletes.

OBJECTIVE: Prior studies have investigated associations between gender, symptom resolution, and time to return to play following sport-related concussion (SRC). However, there is a notable gap in research regarding the association between gender and return to learn (RTL) in adolescents. Therefore, this study 1) compared the patterns of RTL between boys and girls who are high school student athletes, and 2) evaluated the possible association between gender and time to RTL after adjusting for covariates. METHODS: A retrospective cohort study of a prospective surveillance program that monitored concussion recovery of athletes in high schools throughout the state of Maine between February 2015 and January 2023 was performed. The primary independent variable was gender, dichotomized as boys and girls. The primary outcome was time to RTL, defined by the number of days for an athlete to return to school without accommodations. Mann-Whitney U-tests were used to compare RTL between the boys and girls. Each athlete's RTL status was dichotomized (i.e., returned vs had not returned) at several time points following injury (i.e., 1, 2, 3, and 4 weeks), and chi-square tests were performed to compare the proportions who achieved RTL between groups. Multivariable linear regression analyses were performed to evaluate the predictive value of gender on RTL. Covariates included age, number of previous concussions, history of learning disability or attention-deficit disorder or attention-deficit/hyperactivity disorder, history of a psychological condition, history of headaches or migraines, initial Sport Concussion Assessment Tool (SCAT3/SCAT5) score, and days to evaluation. RESULTS: Of 895 high school athletes, 488 (54.5%) were boys and 407 (45.5%) were girls. There was no statistically significant difference in median [IQR] days to RTL between genders (6.0 [3.0-11.0] vs 6.0 [3.0-12.0] days; U = 84,365.00, p < 0.375). A greater proportion of boys successfully returned to learn without accommodations by 3 weeks following concussion (93.5% vs 89.4%; χ2 = 4.68, p = 0.030), but no differences were found at 1, 2, or 4 weeks. A multivariable model predicting days to RTL showed that gender was not a significant predictor of RTL (p > 0.05). Longer days to evaluation (ß = 0.10, p = 0.021) and higher initial SCAT3/SCAT5 scores (ß = 0.15, p < 0.001) predicted longer RTL. CONCLUSIONS: In a cohort of high school athletes, RTL did not differ between boys and girls following SRC. Gender was not a significant predictor of RTL. Longer days to evaluation and higher initial symptom scores were associated with longer RTL.

Overview of Treatment Options for Mild Traumatic Brain Injury: A Literature Review.

The incidence and prevalence of concussion, a type of mild traumatic brain injury (mTBI), have steadily increased among athletes, both students and professionals, across a wide variety of sports, including, but not limited to, swimming, tennis, football, and boxing. Recent data have demonstrated that sports are one of the leading causes of concussions among student athletes. While the exact mechanism of concussion onset has yet to be fully elucidated, data suggest that the pathophysiology involves rotational acceleration and deceleration of the brain, leading to axon tearing and disturbance in the metabolic cascade of glucose. Concussive events can have debilitating effects on an athlete, including chronic traumatic encephalopathy (gradual degeneration of brain tissue) that is related to personality changes, emotional disorders, and even dementia. Common symptoms associated with concussion include dizziness, nausea, vomiting, and headaches. The physical assessment consists of a combination of tools involving the mental status examination, vital signs, cervical spine exam, eye exam, and neurological testing. The use of osteopathic manipulative medicine (OMM), pharmacotherapy, hyperbaric oxygen therapy (HBOT), aerobic exercise, balance, and/or vestibular therapy are many common treatment approaches for concussion and post-concussion sequelae. This literature review aims to provide insight into concussions, the current treatment options available, and the new developments in concussions per the Amsterdam 2022 International Consensus Statement on Concussion in Sport published in 2023.

Variables associated with days of school missed following concussion: results from the Sport Concussion Outcomes in PEdiatrics (SCOPE) study.

OBJECTIVE: To understand factors associated with missed academic time after concussion to improve support for patients. Our goal was to assess patient-specific predictors of total school time lost after pediatric/adolescent concussion. STUDY DESIGN: We performed a prospective cohort study of children and adolescents (8-18 years of age) seen within 14 days of concussion from seven pediatric medical centers across the United States. We collected outcomes via the Concussion Learning Assessment & School Survey (CLASS) and constructed a multivariable predictive model evaluating patient factors associated with school time loss. RESULTS: 167 patients participated (mean age = 14.5 ± 2.2 years; 46% female). Patients were assessed initially at 5.0 ± 3.0 days post-injury and had a final follow-up assessment 24.5 ± 20.0 days post-concussion. Participants missed a median of 2 days of school (IQR = 0.5-4), and 21% reported their grades dropped after concussion. Higher initial symptom severity rating (ß = 0.06, 95% CI = 0.03-0.08, p < 0.001) and perception of grades dropping after concussion (ß = 1.37, 95% CI = 0.28-2.45, p = 0.01) were significantly associated with more days of school time missed after concussion. Those who reported their grades dropping reported missing significantly more school (mean = 5.0, SD = 4.7 days missed of school) than those who reported their grades did not drop (mean = 2.2, SD = 2.6 days missed of school; p < 0.001; Cohen's d = 0.87). CONCLUSIONS: Children and adolescents reported missing a median of 2 days of school following concussion, and more missed school time after a concussion was associated with more severe concussion symptoms and perception of grades dropping. These findings may support recommendations for minimal delays in return-to-learn after concussion.

Thermogravimetric experiments based prediction of biomass pyrolysis behavior: A comparison of typical machine learning regression models in Scikit-learn.

A variety of machine learning (ML) models have been extensively utilized in predicting biomass pyrolysis owing to their prowess in deciphering complex non-linear relationships between inputs and outputs, but there is still a lack of consensus on the optimal methods. This study elaborates on the development, optimization, and evaluation of three ML methodologies, namely, artificial neural networks, random forest (RF), and support vector machines, aimed to determine the optimal model for accurate prediction of biomass pyrolysis behavior using thermogravimetric data. This work assesses the utility of thermal data derived from these models in the computation of kinetic and thermodynamic parameters, alongside an analysis of their statistical performance. Eventually, the RF model exhibits superior physical interpretability and the least discrepancy in predicting kinetic and thermodynamic parameters. Furthermore, a feature importance analysis conducted within the RF model framework quantitatively reveals that temperature and heating rate account for 98.5 % and 1.5 %, respectively.

Reshaping Phosphatase Substrate Preference for Controlled Biosynthesis Using a "Design-Build-Test-Learn" Framework.

Biosynthesis is the application of enzymes in microbial cell factories and has emerged as a promising alternative to chemical synthesis. However, natural enzymes with limited catalytic performance often need to be engineered to meet specific needs through a time-consuming trial-and-error process. This study presents a quantum mechanics (QM)-incorporated design-build-test-learn (DBTL) framework to rationally design phosphatase BT4131, an enzyme with an ambiguous substrate spectrum involved in N-acetylglucosamine (GlcNAc) biosynthesis. First, mutant M1 (L129Q) is designed using force field-based methods, resulting in a 1.4-fold increase in substrate preference (kcat/Km) toward GlcNAc-6-phosphate (GlcNAc6P). QM calculations indicate that the shift in substrate preference is caused by a 13.59 kcal mol-1 reduction in activation energy. Furthermore, an iterative computer-aided design is conducted to stabilize the transition state. As a result, mutant M4 (I49Q/L129Q/G172L) with a 9.5-fold increase in kcat-GlcNAc6P/Km-GlcNAc6P and a 59% decrease in kcat-Glc6P/Km-Glc6P is highly desirable compared to the wild type in the GlcNAc-producing chassis. The GlcNAc titer increases to 217.3 g L-1 with a yield of 0.597 g (g glucose)-1 in a 50-L bioreactor, representing the highest reported level. Collectively, this DBTL framework provides an easy yet fascinating approach to the rational design of enzymes for industrially viable biocatalysts.

School Readiness Among United States Children: Results From the 2022 National Survey of Children's Health.

OBJECTIVE: Provide the latest national and state estimates and correlates of the proportion of young children who are healthy and ready to learn (HRTL) using a revised measure from the National Survey of Children's Health (NSCH). METHODS: Data were analyzed for 11,121 children ages 3 to 5 years from the 2022 NSCH, an address-based, parent-completed survey on the health and well-being of children in the United States. A total of 27 items across 5 domains (early learning skills, social emotional development, self-regulation, motor development, and health) were used to calculate domain-specific assessments scored as "on track," "emerging," or "needs support" according to age-appropriate developmental expectations. Children "on track" in 4 to 5 domains with no domain that "needs support" were considered HRTL. RESULTS: In 2022, 63.6% of 3- to 5-year-old children were HRTL. The proportion of children "on track" ranged from just over two thirds for early learning skills and motor development to 88.9% for health. One million children, or 9.0%, needed support in multiple domains. Being HRTL was associated with child, family, community factors including participation in early childhood education, special health care needs status/type, male sex, reading/singing/storytelling by family members, adverse childhood experiences, parental mental health and education, food insufficiency, outdoor play, household language, neighborhood amenities, rural residence, medical home access. CONCLUSIONS: Nearly two thirds of young children are reported to be HRTL, meeting the Title V National Outcome Measure for School Readiness. Using a revised measure, modifiable factors are identified which offer a range of intervention opportunities at the child, family, and community levels.

Mechanisms underlying the relations between parents' perfectionistic tendencies and young children's mathematical abilities.

BACKGROUND: Parents' high academic expectations are positively associated with young children's mathematical abilities. However, minimal attention has been devoted to whether, and how, different ways of conveying the performance targets would result in different outcomes. AIMS: The current study investigated whether and how parents' perfectionistic strivings and concerns were associated with young children's mathematical abilities through home mathematical activities, children's approach motivation to learn mathematics, and children's avoidance motivation to learn mathematics. SAMPLE: Participants included 211 kindergarteners in Hong Kong and their parents. METHODS: Data were collected through individual child tests and parent questionnaires. RESULTS: Structural equation modelling revealed that parents' perfectionistic strivings had a direct positive link with children's mathematical abilities, an indirect link via approach motivation to learn mathematics, and an indirect link via home mathematical activities, and then approach motivation. Parents' perfectionistic concerns had a direct negative link with children's mathematical abilities, an indirect link via approach motivation to learn mathematics, and an indirect link via avoidance motivation to learn mathematics. CONCLUSIONS: Early childhood practitioners are recommended to raise parents' awareness of how to communicate high-performance targets to children in a constructive manner.

Symptom resolution following a repeat concussion within the same athlete.

INTRODUCTION: Repeat sport-related concussion (SRC) is anecdotally associated with prolonged recovery. Few studies have examined repeat concussion within the same athlete. We sought to explore differences in symptom burden and recovery outcomes in an individual athlete's initial and repeat SRC. METHODS: A retrospective within-subject cohort study of athletes aged 12-23 years diagnosed with two separate SRCs from 11/2017-10/2020 was conducted. Primary outcomes were initial symptom severity and time-to-symptom-resolution. Secondary outcomes included return-to-learn (RTL) and return-to-play (RTP) duration. RESULTS: Of 868 athletes seen, 47 athletes presented with repeat concussions. Median time between concussions was 244 days (IQR 136-395). Comparing initial to repeat concussion, no differences were observed in time-to-clinic (4.3 ± 7.3vs.3.7 ± 4.6 days, p = 0.56) or initial PCSS (26.2 ± 25.3 vs. 30.5 ± 24.1, p = 0.32). While a difference was observed in time-to-symptom resolution between initial/repeat concussion (21.2 ± 16.3 vs. 41.7 ± 86.0 days, p = 0.30), this did not reach statistical significance. No significant differences were observed in time-to-RTL (17.8 ± 60.6 vs. 6.0 ± 8.3 days, p = 0.26) and RTP (33.2 ± 44.1 vs. 29.4 ± 39.1 days, p = 0.75). Repeat concussion was not associated with symptom resolution on univariate (HR 1.64, 95% CI 0.96-2.78, p = 0.07) and multivariable (HR 0.85, 95% CI 0.49-1.46, p = 0.55) Cox regression. CONCLUSION: No significant differences in symptom duration and RTP/RTL were seen between initial/repeat concussion.

Academic adjustments and concussion recoveries in NCAA student-athletes: a LIMBIC MATARS investigation.

OBJECTIVE: The aim of this study was to investigate the association between academic adjustments and recovery from sport-related concussions (SRCs) in collegiate athletes. MATERIALS AND METHODS: A retrospective medical chart review was performed between the 2015-2016 and 2019-2020 sport seasons at 11 Long-term Impact of Military-relevant Brain Injury Consortium Military and Tactical Athlete Research Study (LIMBIC MATARS) sites. Days between injury and symptom resolution, and injury and return to sport (dependent variables) for collegiate athletes who did or did not receive academic adjustments (independent variable) were analyzed using Mann-Whitney U tests. RESULTS: The number of days between date of injury and symptom-resolution between those who did (median = 9 [interquartile range = 5,16]) and did not have (7[3,12]) academic adjustments were statistically different (z=-2.76, p < 0.01, r=-0.17). However, no differences were observed between days to return to sport among those who did (14[10,22]) and did not (13[8,20]) receive assigned academic adjustments (z= -1.66, p = 0.10, r= -.10). CONCLUSIONS: Recovery trajectories were similar between athletes diagnosed with a SRC who did or did not receive academic adjustments.. Our findings suggest academic adjustments supported recovery for those who needed academic adjustments. Clinicians and healthcare professionals should assist and support collegiate athletes after SRCs on an individual basis, including academic adjustments when appropriate based on patient presentation.

Sport-related concussion in 8- to 12-year-olds: an understudied population.

OBJECTIVE: Most studies regarding sport-related concussion (SRC) focus on high school and collegiate athletes; however, little has been published on children younger than 12 years of age. In a cohort of children aged 8-12 years with SRC, the authors sought to describe demographics, initial presentation, and recovery in this understudied population. METHODS: A retrospective cohort study of children aged 8-12 years who sustained an SRC between November 2017 and April 2022 and were treated at a regional sports concussion center was conducted. Demographic information, injury characteristics, traditional Sport Concussion Assessment Tool 5 (SCAT5) and Child/Parent SCAT5 scores, and outcomes, defined as days to return to learn (RTL), symptom resolution, and return to play (RTP), were reported. Outcomes in boys and girls were compared using effect size analyses given sample size constraints. RESULTS: Forty-seven athletes were included. The mean age was 11.0 ± 0.8 years, and the majority were male (34, 72.3%). A sizable proportion of patients visited an emergency department (19, 40.4%), and many received head imaging (16, 34.0%), mostly via CT (n = 13). The most common sport for boys was football (15, 44.1%), and the most common sports for girls were soccer (4, 30.8%) and cheerleading (4, 30.8%). These athletes reported a variety of symptoms on presentation. It took a mean of 8.8 ± 10.8 days to RTL, 27.3 ± 38.3 days to reach symptom resolution, and 35.4 ± 41.9 days to RTP. When comparing boys versus girls, there appeared to be moderate differences in symptom severity scores (Cohen's d = 0.44 for SCAT5, 0.13 for Child SCAT5, and 0.38 for Parent SCAT5) and minimal differences in recovery (Cohen's d = 0.11 for RTL, n = 35; 0.22 for symptom resolution, n = 22; and 0.12 for RTP, n = 21). CONCLUSIONS: In this cohort of concussed athletes aged 8-12 years, a little less than half of the athletes initially presented to the emergency department, and approximately one-third received acute head imaging. Across all athletes, the mean RTL was slightly more than a week and the mean symptom resolution and RTP were both approximately 1 month; however, much of the cohort is missing recovery outcome measures. This study demonstrated a strong positive correlation between Child SCAT5 and Parent SCAT5 symptom reporting. Future efforts are needed to evaluate differences in clinical presentation and outcomes following SRC between children and older populations.

Climate and disease: tackling coffee brown-eye spot with advanced forecasting models.

BACKGROUND: Climate influences the interaction between pathogens and their hosts significantly. This is particularly evident in the coffee industry, where fungal diseases like Cercospora coffeicola, causing brown-eye spot, can reduce yields drastically. This study focuses on forecasting coffee brown-eye spot using various models that incorporate agrometeorological data, allowing for predictions at least 1 week prior to the occurrence of disease. Data were gathered from eight locations across São Paulo and Minas Gerais, encompassing the South and Cerrado regions of Minas Gerais state. In the initial phase, various machine learning (ML) models and topologies were calibrated to forecast brown-eye spot, identifying one with potential for advanced decision-making. The top-performing models were then employed in the next stage to forecast and spatially project the severity of brown-eye spot across 2681 key Brazilian coffee-producing municipalities. Meteorological data were sourced from NASA's Prediction of Worldwide Energy Resources platform, and the Penman-Monteith method was used to estimate reference evapotranspiration, leading to a Thornthwaite and Mather water-balance calculation. Six ML models - K-nearest neighbors (KNN), artificial neural network multilayer perceptron (MLP), support vector machine (SVM), random forests (RF), extreme gradient boosting (XGBoost), and gradient boosting regression (GradBOOSTING) - were employed, considering disease latency to time define input variables. RESULTS: These models utilized climatic elements such as average air temperature, relative humidity, leaf wetness duration, rainfall, evapotranspiration, water deficit, and surplus. The XGBoost model proved most effective in high-yielding conditions, demonstrating high precision and accuracy. Conversely, the SVM model excelled in low-yielding scenarios. The incidence of brown-eye spot varied noticeably between high- and low-yield conditions, with significant regional differences observed. The accuracy of predicting brown-eye spot severity in coffee plantations depended on the biennial production cycle. High-yielding trees showed superior results with the XGBoost model (R2 = 0.77, root mean squared error, RMSE = 10.53), whereas the SVM model performed better under low-yielding conditions (precision 0.76, RMSE = 12.82). CONCLUSION: The study's application of agrometeorological variables and ML models successfully predicted the incidence of brown-eye spot in coffee plantations with a 7 day lead time, illustrating that they were valuable tools for managing this significant agricultural challenge. © 2024 Society of Chemical Industry.

Model-based learn and confirm: designing effective treatment regimens against multidrug resistant Gram-negative pathogens.

Over the last decade, there has been a growing appreciation for the use of in vitro and in vivo infection models to generate robust and informative nonclinical PK/PD data to accelerate the clinical translation of treatment regimens. The objective of this study was to develop a model-based "learn and confirm" approach to help with the design of combination regimens using in vitro infection models to optimise the clinical utility of existing antibiotics. Static concentration time-kill studies were used to evaluate the PD activity of polymyxin B (PMB) and meropenem against two carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates; BAA2146 (PMB-susceptible) and BRKP67 (PMB-resistant). A mechanism-based model (MBM) was developed to quantify the joint activity of PMB and meropenem. In silico simulations were used to predict the time-course of bacterial killing using clinically-relevant PK exposure profiles. The predictive accuracy of the model was further evaluated by validating the model predictions using a one-compartment PK/PD in vitro dynamic infection model (IVDIM). The MBM captured the reduction in bacterial burden and regrowth well in both the BAA2146 and BRKP67 isolate (R2 = 0.900 and 0.940, respectively). The bacterial killing and regrowth predicted by the MBM were consistent with observations in the IVDIM: sustained activity against BAA2146 and complete regrowth of the BRKP67 isolate. Differences observed in PD activity suggest that additional dose optimisation might be beneficial in PMB-resistant isolates. The model-based approach presented here demonstrates the utility of the MBM as a translational tool from static to dynamic in vitro systems to effectively perform model-informed drug optimisation.

Masks and Faces in the Setting at the Time of Coronavirus.

The "health emergency" forced analysts to seek new ways of continuing with analysis. The article focuses, in particular, on the changes brought about in the setting by the presence of the sanitary mask, following a line that begins with the theme of the "mask" in the collective uses of human cultures, and develops through the Jungian concept of persona, as opposed to the "face" that may convey an authentic image of oneself. A clinical vignette illustrates the issues that the mask raises in the setting by obstructing the communication of emotions. When there is no transformative processing of concrete data, "unmasking" can also lead to an uncanny encounter and to moments of darkness and confusion in analysis, when the analyst experiences the kind of "unconscious identity" between therapist and patient that Jung defined as nigredo. The article is intended as a contribution to the analytic community's current reflections on the new and unforeseen challenges encountered in analysis at the time of the Coronavirus. It is possible to learn from these experiences with a view to integrating new elements and thus modify one's own internal setting, the compass with which each analyst orientates himself.

'L'urgence sanitaire' a forcé les analystes à rechercher de nouvelles manières de poursuivre le travail analytique. Cet article met l'accent en particulier sur les changements survenus dans le cadre du fait du port du masque sanitaire; l'article suit un fil conducteur qui commence avec le thème du 'masque' dans les usages collectifs des cultures humaines et se poursuit avec le concept Jungien de persona, en opposition avec le 'visage' qui peut communiquer une image authentique de soi. Une vignette clinique illustre les problèmes que le masque soulève dans la situation analytique en entravant la communication d'émotions. Quand il n'y a pas de processus de transformation des données concrètes, 'démasquer' peut également mener à une rencontre étrange et à des moments de ténèbres et de confusion dans l'analyse, quand l'analyste fait l'expérience du type 'd'identité inconsciente' entre le thérapeute et le patient que Jung a défini comme nigredo. Cet article a pour but de contribuer aux réflexions actuelles de la communauté analytique en ce qui concerne les défis nouveaux et inattendus rencontrés dans l'analyse dans la période du Coronavirus. Il est possible de tirer des leçons de ces expériences afin d'intégrer de nouveaux éléments et ainsi de modifier notre propre cadre interne, la boussole avec laquelle chaque analyste s'oriente.

La "emergencia sanitaria" obligó a los analistas a buscar nuevas formas de continuar con el análisis. El artículo se centra, en particular, en los cambios provocados en el encuadre analítico por la presencia de la mascarilla sanitaria. Presenta un desarrollo a partir del tema de la "máscara" en los usos colectivos de las culturas humanas, y continúa a través del concepto junguiano de persona, en contraposición al de "rostro", el cual puede transmitir una imagen auténtica de uno mismo. Una viñeta clínica ilustra los problemas que plantea la máscara en el entorno al obstruir la comunicación de las emociones. Cuando no hay un procesamiento transformador de los datos concretos, el "desenmascaramiento" también puede conducir a un encuentro misterioso y a momentos de oscuridad y confusión en el análisis, cuando el analista experimenta una forma de "identidad inconsciente" entre terapeuta y paciente que Jung definió como nigredo. El artículo pretende ser una contribución a las reflexiones actuales de la comunidad analítica sobre los nuevos e imprevistos desafíos encontrados en el análisis en la época del Coronavirus. Es posible aprender de estas experiencias con vistas a integrar nuevos elementos y así modificar la propia configuración interna, la brújula con la que cada analista se orienta.

Early Literacy Developmental Activities and Pre-Kindergarten Learning Skills in the Context of Childhood Adversity.

OBJECTIVE: School readiness (SR) encompasses a wide range of skills that affect children's ability to succeed in school and later in life. Shared reading is an important strategy that assists children in gaining SR skills, whereas adverse childhood experiences (ACEs) negatively affect a child's SR. This study assessed if early literacy developmental activities (shared reading, singing, or storytelling) were associated with improved SR among children with and without ACEs. METHODS: 2020-2021 National Survey of Children's Health data were used for analysis. We identified children aged 3-5 years to assess their exposure to ACEs, participation in reading/storytelling/singing, and overall SR. RESULTS: In a sample of 17,545 children, 29% of children were exposed to one or more ACEs. Seventy-seven percent of children with no ACEs received daily early literacy developmental activities compared to 23% of children who experienced any ACE. On ordinal logistic regression, daily early literacy developmental activities were associated with 56% greater odds of higher SR among children not exposed to ACEs (OR: 1.56; 95% CI: 1.29, 1.88; P < .01). Among children exposed to ACEs, daily early literacy developmental activities were also associated with higher SR (OR: 1.50; 95% CI: 1.06, 2.13; P = .02). CONCLUSIONS: Shared reading, storytelling, and singing are associated with improved SR in both children who have and have not been exposed to ACEs. However, children exposed to ACEs had fewer experiences with early literacy developmental activities. Future efforts should address the barriers that limit shared reading, singing, or storytelling for children exposed to ACEs.

Describing High School Stakeholders' Preferences for a Return-to-School Framework Following Concussion.

BACKGROUND: Return to school supports are recommended to facilitate adolescents' re-entry to school following a concussion. However, little is known as to what school stakeholders prefer for a return-to-school process. This study sought to describe the preferences of high school students, parents, and educators for a Return-to-School Framework for adolescents following a concussion. METHODS: We conducted qualitative semi-structured, 1-on-1 or group interviews with high school students (n = 6), parents (n = 5), and educators (n = 15) from Calgary, Canada. Interviews aimed to describe participants' preferences for a Return-to-School Framework for students following a concussion. Interviews were analyzed using conventional content analysis. RESULTS: We organized the data into 4 main themes: (1) purpose of the Return-to-School Framework; (2) format and operation of the Return-to-School Framework; (3) communication about a student's concussion; and (4) necessity of concussion education for students and educators. IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: A Return-to-School Framework following concussion should be developed in consultation with families, educators, and students and supports should be tailored to each student. CONCLUSIONS: Participants preferred a standardized and consistent Return-to-School Framework including ongoing communication between stakeholders as well as feasible and individualized school supports.

Towards performance-maximizing neural network pruning via global channel attention.

Network pruning has attracted increasing attention recently for its capability of transferring large-scale neural networks (e.g., CNNs) into resource-constrained devices. Such a transfer is typically achieved by removing redundant network parameters while retaining its generalization performance in a static or dynamic manner. Concretely, static pruning usually maintains a larger and fit-to-all (samples) compressed network by removing the same channels for all samples, which cannot maximally excavate redundancy in the given network. In contrast, dynamic pruning can adaptively remove (more) different channels for different samples and obtain state-of-the-art performance along with a higher compression ratio. However, since the system has to preserve the complete network information for sample-specific pruning, the dynamic pruning methods are usually not memory-efficient. In this paper, our interest is to explore a static alternative, dubbed GlobalPru, from a different perspective by respecting the differences among data. Specifically, a novel channel attention-based learn-to-rank framework is proposed to learn a global ranking of channels with respect to network redundancy. In this method, each sample-wise (local) channel attention is forced to reach an agreement on the global ranking among different data. Hence, all samples can empirically share the same ranking of channels and make the pruning statically in practice. Extensive experiments on ImageNet, SVHN, and CIFAR-10/100 demonstrate that the proposed GlobalPru achieves superior performance than state-of-the-art static and dynamic pruning methods by significant margins.