Preliminary Data Research Articles

Protocol for a single-arm, pilot trial of creatine monohydrate supplementation in patients with Alzheimer's disease.

Impaired brain bioenergetics is a pathological hallmark of Alzheimer's disease (AD) and is a compelling target for AD treatment. Patients with AD exhibit dysfunction in the brain creatine (Cr) system, which is integral in maintaining bioenergetic flux. Recent studies in AD mouse models suggest Cr supplementation improves brain mitochondrial function and may be protective of AD peptide pathology and cognition. The Creatine to Augment Bioenergetics in Alzheimer's disease (CABA) study is designed to primarily assess the feasibility of supplementation with 20g/day of creatine monohydrate (CrM) in patients with cognitive impairment due to AD. Secondary aims are designed to generate preliminary data investigating changes in brain Cr levels, cognition, peripheral and brain mitochondrial function, and muscle strength and size. CABA is an 8-week, single-arm pilot study that will recruit 20 patients with cognitive impairment due to AD. Participants attend five in-person study visits: two visits at baseline to conduct screening and baseline assessments, a 4-week visit, and two 8-week visits. Outcomes assessment includes recruitment, retention, and compliance, cognitive testing, magnetic resonance spectroscopy of brain metabolites, platelet and lymphocyte mitochondrial function, and muscle strength and morphology at baseline and 8weeks. CABA is the first study to investigate CrM as a potential treatment in patients with AD. The pilot data generated by this study are pertinent to inform the design of future large-scale efficacy trials. ClinicalTrials.gov, NCT05383833 , registered on 20 May 2022.

Machine learning methods in differential diagnosis of ACTH-dependent hypercortisolism

To develop a noninvasive method of differential diagnosis of ACTH-dependent hypercortisolism, as well as to evaluate the effectiveness of an optimal algorithm for predicting the probability of ectopic ACTH syndrome (EAS) obtained using machine learning methods based on the analysis of clinical data. As part of a single-center, one-stage, cohort study, a retrospective prediction of the probability of EAS among patients with ACTH-dependent hypercortisolism was carried out. Patients were randomly stratified into 2 samples: training (80%) and test (20%). Eleven machine learning algorithms were used to develop predictive models: Linear Discriminant Analysis, Logistic Regression, elastic network (GLMNET), Support Vector machine (SVM Radial), k-nearest neighbors (kNN), Naive Bayes, binary decision tree (CART), C5.0 decision tree algorithms, Bagged CART, Random Forest, Gradient Boosting (Stochastic Gradient Boosting, GBM). The study included 223 patients (163 women, 60 men) with ACTH-dependent hypercortisolism, of which 175 patients with Cushing's disease (CD), 48 - with EAS. As a result of preliminary data processing and selection of the most informative signs, the final variables for the classification and prediction of EAS were selected: ACTH level at 08:00 hours, potassium level (the minimum value of potassium in the active stage of the disease), 24-h urinary free cortisol, late-night serum cortisol, late-night salivary cortisol, the largest size of pituitary adenoma according to MRI of the brain. The best predictive ability in a training sample of all trained machine learning models for all three final metrics (ROC-AUC (0.867), sensitivity (90%), specificity (56.4%)) demonstrated a model of gradient boosting (Generalized Boosted Modeling, GBM). In the test sample, the AUC, sensitivity and specificity of the model in predicting EAS were 0.920; 77.8% and 97.1%, respectively. The prognostic model based on machine learning methods makes it possible to differentiate patients with EAS and CD based on basic clinical results and can be used as a primary screening of patients with ACTH-dependent hypercortisolism.

Stereotactic Electroencephalogram Recordings in Temporal Lobectomy Patients Demonstrates the Predictive Value of Interictal Cross-Frequency Correlations: A Retrospective Study.

Positive correlations between low- and high-frequency spectra from stereotactic electroencephalogram (SEEG) recordings have been implicated in pathological brain activity interictally and have been used for ictal detection in both focal and network models. We evaluated SEEG signals in patients who ultimately underwent temporal lobectomy to evaluate their utility in seizure localization and prediction of seizure freedom post-resection. We retrospectively analyzed cross-frequency correlations between beta and high gamma (HG) interictal SEEG signals from 22 patients. We compared signals based on temporal versus extra-temporal locations, seizure-free (SF) versus non-seizure-free (NSF) outcomes, and mesial (M) versus mesial temporal-plus (M+) onset. Positive cross-correlations were increased in temporal areas. NSF patients showed a higher proportion of positive electrodes in temporal areas. SF patients had a greater proportion of significant channels in mesial versus lateral temporal areas. HG/Beta correlations in mesial versus lateral temporal areas predicted seizure freedom better than ictal SEEG seizure onset localization to M or M+ locations. We present preliminary data that local HG/Beta correlations may predict epilepsy focus and surgical outcome and may have utility as adjunct methods to conventional SEEG analysis. Further studies are needed to determine strategies for prospective studies and clinical use.

STUDENTS’ USAGE OF CHATBOT IN WRITING ASSIGNMENTS: ISSUES RELATED TO ACADEMIC INTEGRITY

The rise of artificial intelligence (AI), like ChatGPT chatbot, has generated heated discussions in the education field. While ChatGPT has gained popularity among students for its ability to provide instant and lengthy responses to academic questions, several teachers and researchers have voiced concerns regarding the authenticity and quality of the AI generated or facilitated works. This study investigates students’ attitudes towards using chatbots, their common practices of using chatbots in writing assignments, and the impacts on academic integrity. A questionnaire was issued to 80 first year students enrolling in a Global Citizenship Education course (in which students have Academic Writing module) at an international university in Hanoi. After that, 30 of these participants were interviewed. The preliminary data analysis revealed that while students had overwhelmingly positive attitudes toward the tool, they lacked a thorough understanding of the risks involved in using the chatbot. The study aims to contribute to the conversation of using AI in education as well as provide recommendations for promoting academic integrity while using Chatbots and similar tools. It calls for due attention be paid to developing procedures for or best practices of using Chatbots in the classrooms without compromising authenticity and academic integrity.

Avifaunal diversity in urban greenspaces within Cotabato city, Mindanao Island, Philippines

Information about the diversity of avifauna in urban green spaces in the Philippines needs to be more extensive. More so, data on birds in green spaces of the country’s Bangsamoro Region in Muslim Mindanao (BARMM) remain largely unreported. This gap highlights the need to document the avifaunal diversity in the urban green spaces of Cotabato City. Bird species were accounted for using the point count method from September to December 2021 in three different urban green spaces within the commercial center of Cotabato City. Twenty-one avian species representing 17 families were documented. Among the surveyed three green spaces within Cotabato City, Notre Dame University (NDU) has the highest species richness (N = 20), followed by PC Hill (N = 14), and Mother Barangay Rosary Heights (N = 9). Of the 21 species of birds documented, 19% are Philippine endemic, and all of these were recorded only at Notre Dame University. Data from the present study suggest the capacity of green spaces in urban Cotabato City to cater to different bird species, including the endemic ones. Since the results present preliminary data, intensive surveys can be done on these sites by future researchers. Also, surveying more urban green spaces in Cotabato City may add information on the city’s urban birds. Substantial data from these future surveys may be helpful in the urban planning of Cotabato.

Machine learning approaches to evaluate infants’ general movements in the writhing stage—a pilot study

The goals of this study are to describe machine learning techniques employing computer-vision movement algorithms to automatically evaluate infants’ general movements (GMs) in the writhing stage. This is a retrospective study of infants admitted 07/2019 to 11/2021 to a level IV neonatal intensive care unit (NICU). Infant GMs, classified by certified expert, were analyzed in two-steps (1) determination of anatomic key point location using a NICU-trained pose estimation model [accuracy determined using object key point similarity (OKS)]; (2) development of a preliminary movement model to distinguish normal versus cramped-synchronized (CS) GMs using cosine similarity and autocorrelation of major joints. GMs were analyzed using 85 videos from 74 infants; gestational age at birth 28.9 ± 4.1 weeks and postmenstrual age (PMA) at time of video 35.9 ± 4.6 weeks The NICU-trained pose estimation model was more accurate (0.91 ± 0.008 OKS) than a generic model (0.83 ± 0.032 OKS, p < 0.001). Autocorrelation values in the lower limbs were significantly different between normal (5 videos) and CS GMs (5 videos, p < 0.05). These data indicate that automated pose estimation of anatomical key points is feasible in NICU patients and that a NICU-trained model can distinguish between normal and CS GMs. These preliminary data indicate that machine learning techniques may represent a promising tool for earlier CP risk assessment in the writhing stage and prior to hospital discharge.

Connectedness, feeling At home, and joyful Play (CAP): A place-based wellness model for cognitive health promotion in the community by the community

ABSTRACT As populations age, leveraging community resources to reduce dementia risk is increasingly vital for brain health. Using community-based participatory research methods, we co-developed and tested a pilot program with older adults in Metro Vancouver, Canada, to better understand and address brain health needs in community settings. Over 12 focus groups, older adults provided input which led to a place-based wellness model ‘Connectedness, feeling At home, and joyful Play’ (CAP). The CAP model was incorporated into an 8-week feasibility study, testing various components of a multi-domain realist controlled trial (n = 78). Older adults were recommended various existing activities in the community based on their CAP profiles. A ‘Finding Meaning in Aging’ mindful discussion program was added in response to older adults’ feedback on current gaps. Path analysis of preliminary data suggests that total attendance (β = .196, p = .070) improved brain health at week 8 by increasing a sense of playfulness at week 4 (β = .284, p = .002). Mindfulness (β = .215, p = .046) improved brain health by increasing a sense of at-homeness (β = .227, p = .025). Both pre- and post-implementation feedback from older adults centred the importance of friendship in late life, specifically to address late-life losses. The community-generated CAP model shows promise for place-based cognitive health promotion.

Injury-severity analysis of crashes involving defective vehicles and accounting for the underlying socioeconomic mediators

Crashes occur from a combination of factors related to the driver, roadway, and vehicle factors. The impact of vehicles on road crashes is a critical consideration within road safety analysis, even though not much studies have been conducted in this area. This study assessed how various vehicle and other crash factors are significantly associated with crash outcomes. To do this, historical vehicle defect-related crashes were obtained for the state of Alabama from 2016 to 2020. After data cleaning, a crash injury severity model was developed using the random parameters multinomial logit with heterogeneity in means approach to account for possible unobserved heterogeneity in the data. A spatial analysis was further conducted to better understand vehicle defect crashes as a broader societal issue and potentially explore their connection with the socio-demographic characteristics of the drivers of these vehicles. The preliminary data analysis showed that brake and tire defects accounted for about 65% of the vehicle defects associated with the crashes. The model estimation results revealed that improper tread depth and headlight defects were associated with major injury outcomes, while brake defects were more associated with minor injuries. Also, crashes associated with speeding, drunk driving, failure to use seatbelts, and those that occurred on curved roads left with downgrades were likely to result in major injuries. Findings from the spatial analysis showed that postal codes with higher median incomes are more likely to record lower vehicle defect-related crashes, unlike those that have higher proportions of females and African Americans. The study's findings provide data-driven evidence for sustained safety campaigns, workshops, and training on basic vehicle maintenance practices in the low-income communities in the state.

Validation of the Italian version of the Dark Tetrad at Work scale.

This study presents and validates the Italian adaptation of the Dark Tetrad at Work (DTW) scale, an instrument for assessing four socially aversive personality traits (narcissism, Machiavellianism, psychopathy and sadism) in the context of the workplace. A total of 300 Italian-speaking participants (50% female, M age = 32 years ± 9.2) and 253 English-speaking participants (38% female, M age = 39 years ± 12.1) were recruited via an online survey platform. The Italian-speaking sample was used to test the factorial structure, reliability and criterion-related validity of the Italian version of the DTW, whereas the English-speaking sample was used to test cross-language measurement invariance. Results from confirmatory factor analysis showed that the original four-factor model provided the best fit to the data. The Italian DTW scale demonstrated acceptable internal consistency, with reliability coefficients of ω = .77 for narcissism, ω = .80 for Machiavellianism, and ω = .81 for both psychopathy and sadism. Concurrent associations between the DTW scales and negative and positive workplace outcomes supported the criterion validity of the scale. Machiavellianism, psychopathy, and sadism positively correlated with counterproductive work behaviors and workplace bullying, and negatively with organizational citizenship behaviors and affective organizational commitment. In contrast, narcissism exhibited a unique pattern: It correlated positively with positive workplace behaviors and negatively with counterproductive behaviors toward the organization, but it was also found to be a significant predictor of workplace bullying. This finding may reflect multidimensional nature of narcissism, but a note of caution is warranted in interpreting this result, as all measurements relied on self-report instruments, introducing the possibility of socially desirable associations influencing the outcomes. Finally, the comparison with the English sample established configural, full metric and partial scale invariance, allowing for valid cross-language comparisons between Italian and English-speaking populations in the future. Preliminary Italian normative data were provided to offer a benchmark for the interpretation of DTW values. This study provides a reliable and valid instrument tailored to the Italian workforce, enhancing our understanding of dark personality traits within organizational contexts and providing organizations with an effective means to address and manage dark personality traits for a healthier workplace culture.

Support Through Remote Observation and Nutrition Guidance (STRONG), a digital health intervention to reduce malnutrition among pancreatic cancer patients: A study protocol for a pilot randomized controlled trial

BackgroundMalnutrition is a common and distressing condition among pancreatic cancer patients. Fewer than a quarter of pancreatic cancer patients receive medical nutrition therapy (MNT), important for improving nutritional status, weight maintenance, quality of life and survival. System, provider, and patient level barriers limit access to MNT. We propose to examine the feasibility of a 12-week multi-level, digital health intervention designed to expand MNT access among pancreatic cancer patients. MethodsIndividuals with advanced pancreatic cancer starting chemotherapy (N = 80) will be 1:1 randomized to the intervention or usual care. The Support Through Remote Observation and Nutrition Guidance (STRONG) intervention includes system-level (e.g., routine malnutrition and screening), provider-level (e.g., dietitian training and web-based dashboard), and patient-level strategies (e.g., individualized nutrition plan, self-monitoring of dietary intake via Fitbit, ongoing goal monitoring and feedback). Individuals receiving usual care will be referred to dietitians based on their oncologists’ discretion. Study assessments will be completed at baseline, 4-, 8-, 12-, and 16-weeks. ResultsPrimary outcomes will be feasibility (e.g., recruitment, retention, assessment completion) and acceptability. We will collect additional implementation outcomes, such as intervention adherence, perceived usability, and feedback on intervention quality via an exit interview. We will collect preliminary data on outcomes that may be associated with the intervention including malnutrition, quality of life, treatment outcomes, and survival. ConclusionThis study will advance our knowledge on the feasibility of a digital health intervention to reduce malnutrition among individuals with advanced pancreatic cancer. Trial registration: NCT05675059, registered on December 9, 2022.

The explore/exploit trade-off: An ecologically valid and translational framework that can advance mechanistic understanding of eating disorders.

The explore/exploit trade-off is a decision-making process that is conserved across species and balances exploring unfamiliar choices of unknown value with choosing familiar options of known value to maximize reward. This framework is rooted in behavioral ecology and has traditionally been used to study maladaptive versus adaptive non-human animal foraging behavior. Researchers have begun to recognize the potential utility of understanding human decision-making and psychopathology through the explore/exploit trade-off. In this article, we propose that explore/exploit trade-off holds promise for advancing our mechanistic understanding of decision-making processes that confer vulnerability for and maintain eating pathology due to its neurodevelopmental bases, conservation across species, and ability to be mathematically modeled. We present a model for how suboptimal explore/exploit decision-making can promote disordered eating and present recommendations for future research applying this framework to eating pathology. Taken together, the explore/exploit trade-off provides a translational framework for expanding etiologic and maintenance models of eating pathology, given developmental changes in explore/exploit decision-making that coincide in time with the emergence of eating pathology and evidence of biased explore/exploit decision-making in psychopathology. Additionally, understanding explore/exploit decision-making in eating disorders may improve knowledge of their underlying pathophysiology, informing targeted clinical interventions such as neuromodulation and pharmacotherapy. PUBLIC SIGNIFICANCE STATEMENT: The explore/exploit trade-off is a cross-species decision-making process whereby organisms choose between a known option with a known reward or sampling unfamiliar options. We hypothesize that imbalanced explore/exploit decision-making can promote disordered eating and present preliminary data. We propose that explore/exploit trade-off has significant potential to advance understanding of the neurocognitive and neurodevelopmental mechanisms of eating pathology, which could ultimately guide revisions of etiologic models and inform novel interventions.

Very-early detection of atrial fibrillation after ablation evaluated by a wearable ECG-patch predicts late blanking period recurrence: Preliminary data from a prospective registry

IntroductionAtrial fibrillation (AF) ablation represents a safe and effective procedure to restore sinus rhythm. The idea that post-procedural AF episodes - during theblanking period-are not considered treatment failure has been increasingly challenged. The E-Patch, a single-use adhesive electrode, facilitates extended continuous ECG monitoring for 120 h. This pilot study aims to assess the effectiveness of this ambulatory monitoring device and investigate whether very-early AF recurrence correlates with delayed blanking period ablation outcomes. MethodsWe conducted a single-center, prospective, longitudinal study, including consecutive post-ablation patients monitored with the E-patch. The ability of the device to continuously record was analyzed, as well as the occurrence of AF episodes during external 7-day loop-recorder in the 2nd-month post-ablation. ResultsWe included 40 patients, median age 62 years (IQR 56–70). E-Patch monitoring was obtained for a median of 118 h (IQR 112–120), with no discomfort nor interpretation artefacts. Very-early AF recurrence was detected in 11 (27.5 %) patients, with a median AF burden of 7 % (IQR 6 %–33 %). Late-blanking period AF was detected in 13 (33 %) of theexternal 7-day looprecordings.Of the 11 patients that had very-early AF recurrence, 10 (91 %) had late-blanking AF. Very-early AF detectionshowed77 % (95 % CI 64 %-90 %) sensitivityand 96 % (95 % CI 90–100 %) specificity inpredictinglate-blanking AF, with a non-parametric ROCcurve AUC of 0.903 (95 % 0.797––1.0). ConclusionThe E-Patch was able to detect very-early AF during an extended period. Very-early AF detection emerges as a predictor of AF recurrence during the late blanking period post-ablation.

Acupuncture for Combat-Related Posttraumatic Stress Disorder

Current interventions for posttraumatic stress disorder (PTSD) are efficacious, yet effectiveness may be limited by adverse effects and high withdrawal rates. Acupuncture is an emerging intervention with positive preliminary data for PTSD. To compare verum acupuncture with sham acupuncture (minimal needling) on clinical and physiological outcomes. This was a 2-arm, parallel-group, prospective blinded randomized clinical trial hypothesizing superiority of verum to sham acupuncture. The study was conducted at a single outpatient-based site, the Tibor Rubin VA Medical Center in Long Beach, California, with recruitment from April 2018 to May 2022, followed by a 15-week treatment period. Following exclusion for characteristics that are known PTSD treatment confounds, might affect biological assessment, indicate past nonadherence or treatment resistance, or indicate risk of harm, 93 treatment-seeking combat veterans with PTSD aged 18 to 55 years were allocated to group by adaptive randomization and 71 participants completed the intervention protocols. Verum and sham were provided as 1-hour sessions, twice weekly, and participants were given 15 weeks to complete up to 24 sessions. The primary outcome was pretreatment to posttreatment change in PTSD symptom severity on the Clinician-Administered PTSD Scale-5 (CAPS-5). The secondary outcome was pretreatment to posttreatment change in fear-conditioned extinction, assessed by fear-potentiated startle response. Outcomes were assessed at pretreatment, midtreatment, and posttreatment. General linear models comparing within- and between-group were analyzed in both intention-to-treat (ITT) and treatment-completed models. A total of 85 male and 8 female veterans (mean [SD] age, 39.2 [8.5] years) were randomized. There was a large treatment effect of verum (Cohen d, 1.17), a moderate effect of sham (d, 0.67), and a moderate between-group effect favoring verum (mean [SD] Δ, 7.1 [11.8]; t90 = 2.87, d, 0.63; P = .005) in the intention-to-treat analysis. The effect pattern was similar in the treatment-completed analysis: verum d, 1.53; sham d, 0.86; between-group mean (SD) Δ, 7.4 (11.7); t69 = 2.64; d, 0.63; P = .01). There was a significant pretreatment to posttreatment reduction of fear-potentiated startle during extinction (ie, better fear extinction) in the verum but not the sham group and a significant correlation (r = 0.31) between symptom reduction and fear extinction. Withdrawal rates were low. The acupuncture intervention used in this study was clinically efficacious and favorably affected the psychobiology of PTSD in combat veterans. These data build on extant literature and suggest that clinical implementation of acupuncture for PTSD, along with further research about comparative efficacy, durability, and mechanisms of effects, is warranted. ClinicalTrials.gov Identifier: NCT02869646.

Prevalence and Predicting Factors of Pretreatment Dysphagia in Veterans With Head and Neck Cancer: A Pilot Study

Background: Dysphagia is a common sequela in individuals with a diagnosis of head and neck cancer. However, the prevalence and predicting factors for pretreatment dysphagia have not been well identified in the literature. A priori knowledge of the presence of a pretreatment dysphagia is advantageous and can have clinically significant implications for management of this patient population. The ability to predict pretreatment dysphagia in this population would allow more targeted interventions and potential improvements in clinical outcomes. Participants: This pilot study investigated the prevalence and predicting factors of pretreatment dysphagia in 67 veterans with head and neck cancer through the West Haven, CT, Veterans Affairs cancer database. Method: Data for this study were acquired via retrospective medical record review. Results: The prevalence of pretreatment dysphagia in our sample was found to be 49.3%. Age and pretreatment percutaneous endoscopic gastrostomy placement were found to have a statistically significant relationship with pretreatment dysphagia. Stage of cancer diagnosis and the diagnosis of pretreatment dysphagia were found to have a statistically significant relationship with posttreatment dysphagia. Conclusions: Findings offer important preliminary data and clinical considerations about this issue and serve as a foundation for future research. There are a limited number of factors associated with pretreatment dysphagia, and clinicians should consider a conservative referral approach when considering the need for dysphagia assessment prior to the initiation of oncologic treatment.

Комбинация Nivo-DHAP с последующей высокодозной химиотерапией и трансплантацией аутологичных гемопоэтических стволовых клеток у пациентов с рецидивами и рефрактерным течением классической лимфомы Ходжкина: результаты многоцентрового проспективного клинического исследования (ClinicalTrials.gov, NCT04091490)

Background. High-dose chemotherapy (HDCT) with autologous hematopoietic stem cell transplantation (auto-HSCT) is currently regarded as a standard treatment for patients with relapsed/refractory classical Hodgkin lymphoma (cHL). The efficacy of transplantation correlates with the depth of antitumor response achieved on pre-transplantation chemotherapy. A combination of PD-1 inhibitors with chemotherapy is a new forward-looking approach ensuring a higher rate of complete responses prior to auto-HSCT as well as better outcomes of the treatment in general.&#x0D; Aim. To assess the efficacy and safety of the combined program with Nivo-DHAP and subsequent HDCT and auto-HSCT in patients with relapsed/refractory cHL.&#x0D; Materials &amp; Methods. From March 2020 to January 2022, 38 patients were enrolled in the study. The Nivo-DHAP program consisted of two stages. At stage 1 nivolumab immunotherapy was administered: two 240 mg/day IV infusions as a monoregimen 14 days apart. Stage 2, Nivo-DHAP immunochemotherapy, started in 14 days after stage 1: nivolumab 480 mg/day IV infusion on Day 1 in combination with DHAP chemotherapy, total of 4 cycles. The efficacy of this therapy was evaluated after 2 nivolumab infusions as well as after 2 and 4 Nivo-DHAP cycles. The program was fully implemented in 36 patients. HSCs were collected after remission had been reported, in most cases it was after 2 Nivo-DHAP cycles. For various reasons, auto-HSCT was performed only in 23 out of 36 patients. The median follow-up of patients after auto-HSCT was 24 months.&#x0D; Results. After completing the pre-transplantation stage of the program to the full extent, which included Nivo, Nivo, and 4 Nivo-DHAP cycles, 36 patients showed a 100 % overall objective response. Complete response was achieved in 27 (75 %) patients, and partial response was reported in 9 (25 %) patients. The signs of hematological toxicity grade 3/4 were manifested in 26 % of patients. In the total cohort of 36 patients with (n = 23) and without (n = 13) auto-HSCT, progression-free survival (PFS) was 81 % with the follow-up of 12 months, 78 % with the follow-up of 24 months, and 74 % with the follow-up of 36 months. Overall survival (OS) in the total cohort with the same follow-up end-points was 95 %. A comparative assessment revealed that PFS was 87 % in the cohort with auto-HSCT with the follow-up of 12, 24, and 36 months and 70 %, 64 %, and 48 % in the cohort without auto-HSCT with the same follow-up end-points, respectively (p = 0.056).&#x0D; Conclusion. A combination of PD-1 inhibitors with chemotherapy as a stage prior to HDCT followed by auto-HSCT is a promising strategy resulting in high PFS and OS rates. Preliminary data on using PD-1 inhibitors combined with chemotherapy cannot yet provide substantial basis for disregarding HDCT with subsequent auto-HSCT which is considered to be the optimal method for remission consolidation.

Post-clustering Prioritization Framework for Autonomous Decision Making in the Absence of Ground Truth via Hypothetical Probing

A generic prioritization framework is introduced for addressing the problem of automated prioritization of region of interest or target selection. The framework is based on the assumption that clustering of preliminary data for preidentified regions or targets of interest within an operational area has already occurred, i.e., post-classification, and that the clustering quality can be expressed as an energy/objective function. Region or target of interest prioritization then means to rank regions or targets of interest according to their probability of changing the energy/objective function value upon subsequent hypothetical probing as opposed to actually conducted reexamination, i.e., thorough follow-up or in-situ measurements. The mathematical formalism for calculating these probabilities to contribute to this change of the energy/objective function value is introduced and validated through numerical simulations. Moreover, these probabilities can also be understood as a confidence-check of the classification, i.e., the pre-clustering of the preliminary data. The operation of the prioritization framework is independent of the algorithm used to pre-cluster the preliminary data, and supports autonomous decision-making. It is widely applicable across many scientific disciplines and areas, ranging from the microscopic to the macroscopic scale. Due to its ability to help maximize scientific return while optimizing resource utilization, it is particularly relevant in the context of resource-constrained autonomous robotic planetary exploration as it may extend the Remaining Useful Lifetime (RUL) – a key aspect in Prognostics and Health Management (PHM) – of space missions. On a more general, PHM-relevant level, the prioritization framework may provide an additional mechanism of identifying and correcting the maintenance status of system components to assist predictive maintenance or condition-based maintenance.

Creating uniform cluster dose spread-out Bragg peaks for proton and carbon beams.

Preliminary data have shown a close association of the generalized ionization cluster size dose (in short, cluster dose) with cell survival, independent of particle type, and energy, when cluster dose is derived from an ionization detail parameter preferred for its association with cell survival. Such results suggest cluster dose has the potential to replace RBE-weighted dose in proton and ion beam radiotherapy treatment plan optimization, should a uniform cluster dose lead to comparable biological effects. However, further preclinical investigations are warranted to confirm this premise. To present an analytical approach to create uniform cluster dose spread-out Bragg peaks (SOBP) for evaluation of the potential of cluster dose to result in uniform biological effect. We modified the coefficients of the Bortfeld and Schlegel weight formula, an analytical method typically used for the creation of radiation dose SOBP in particle therapy, to produce uniform cluster dose SOBP of different widths (1-5cm) at relevant clinical proton and carbon beam energies. Optimum parameters were found by minimization of the ratio between the maximum and minimum cluster dose in the SOBP region using the Nelder-Mead method. The coefficients of the Bortfeld and Schlegel weight formula leading to uniform cluster dose SOBPs were determined for each combination of beam energy and SOBP width studied. The uniformity of the resulting cluster dose SOBPs, calculated as the relative difference between the maximum and minimum cluster dose within the SOBP, was within 0.3%-3.5% for the evaluated proton beams and 1.3%-3.4% for the evaluated carbon beams. The modifications to the analytical approach to create radiation dose SOBPs resulted in uniform cluster dose proton and carbon SOBPs over a wide range of beam energies and SOBP widths. Such SOBPs should prove valuable in preclinical investigations for the selection of nanodosimetric quantities to be used in proton and ion therapy treatment planning.

Your Body Is Your Home: The feasibility of an intuitive eating intervention for early adolescents.

Intuitive eating (IE) is an emerging health promotion framework which has shown promise in the prevention and early intervention of disordered eating (DE) behavior in adults. This study sought to extend this work by assessing the feasibility and preliminary efficacy of a 5-week IE intervention, "Your Body is Your Home," delivered in school classrooms for early adolescents aged 11-13. The present study utilized a quasi-experimental design. Eligibility criteria were defined a priori and published in a registered protocol. Four classrooms (n = 128 student participants) were recruited into two streams, and self-report questionnaires were administered at pre-test, post-test, and 4-week follow-up. The questionnaires included the Intuitive Eating Scale for Early Adolescents (IES-2-EA), the Body Appreciation Scale (BAS-2), and the WHO Wellbeing Index (WHO-5). Linear mixed models were used to conduct preliminary efficacy testing. The results indicate that a brief classroom-based IE intervention is feasible and acceptable for both students and teaching staff; retention, fidelity, and attendance targets were achieved. Students and teachers rated all five sessions of the intervention as a highly feasible method of health promotion. Further, preliminary efficacy data suggest IE interventions aimed at early adolescents may be a feasible way of improving certain aspects of IE (p < .001) in male and female participants, and body appreciation (p < .001) in male participants. The study provides preliminary support for the implementation and evaluation of an IE intervention as part of school-based health promotion and offers preliminary effect size estimates for a larger-scale randomized trial. Existing evidence suggests that IE may be a useful framework through which relationships with food and the body can be improved. The present study seeks to extend this work by adapting the framework for early adolescents (among whom the framework is not well understood) and examining feasibility, acceptability, and preliminary changes to several health and well-being metrics following a 5-week school-based intervention.

Prehispanic Arid Zone Farming: Hybrid Flood and Irrigation Systems along the North Coast of Peru

As arid lands expand across the globe, scholars increasingly turn to the archaeological record for examples of sustainable farming in extreme environments. The arid north coast of Peru was the setting of early and intensive irrigation-based farming; it is also periodically impacted by sudden, heavy rainfall related to the El Niño Southern Oscillation (ENSO) phenomenon. While the sociopolitical effects, technologies, and engineering expertise of these irrigation systems have been thoroughly examined and theorized, little is known about how farmers managed periods of water stress. The aim of this study is to test whether arid zone farming was supported by hybrid, intermittent flood and perennial water source systems in the prehispanic past. An arroyo in the Chicama Valley was selected for preliminary data collection, and these data are presented here: (1) drone photography of the arroyo capturing the aftermath of a recent (2023) rain event; and (2) potassium (K) soil test kit results from samples collected near suspected prehispanic check dam features in the same area. The paper combines these data with comparative examples from the literature to suggest that the prehispanic features functioned as water-harvesting infrastructure. The paper concludes that sustainable, arid zone farming can be supported by hybrid, intermittent flood and perennial water source systems.

Combining transcranial magnetic stimulation with training to improve social cognition impairment in schizophrenia: a pilot randomized controlled trial.

Schizophrenia is a severe, chronic mental disorder that profoundly impacts patients' everyday lives. The illness's core features include positive and negative symptoms and cognitive impairments. In particular, deficits in the social cognition domain showed a tighter connection to patients' everyday functioning than the other symptoms. Social remediation interventions have been developed, providing heterogeneous results considering the possibility of generalizing the acquired improvements in patients' daily activities. In this pilot randomized controlled trial, we investigated the feasibility of combining fifteen daily cognitive and social training sessions with non-invasive brain stimulation to boost the effectiveness of the two interventions. We delivered intermittent theta burst stimulation (iTBS) over the left dorsolateral prefrontal cortex (DLPFC). Twenty-one patients were randomized into four groups, varying for the assigned stimulation condition (real vs. sham iTBS) and the type of cognitive intervention (training vs. no training). Clinical symptoms and social cognition tests were administered at five time points, i.e., before and after the treatment, and at three follow-ups at one, three, and six months after the treatments' end. Preliminary data show a trend in improving the competence in managing emotion in participants performing the training. Conversely, no differences were found in pre and post-treatment scores for emotion recognition, theory of mind, and attribution of intentions scores. The iTBS intervention did not induce additional effects on individuals' performance. The methodological approach's novelty and limitations of the present study are discussed.