Small Sample Size Research Articles

A Contrastive-Learning-Based Deep Neural Network for Cancer Subtyping by Integrating Multi-Omics Data.

Accurate identification of cancer subtypes is crucial for disease prognosis evaluation and personalized patient management. Recent advances in computational methods have demonstrated that multi-omics data provides valuable insights into tumor molecular subtyping. However, the high dimensionality and small sample size of the data may result in ambiguous and overlapping cancer subtypes during clustering. In this study, we propose a novel contrastive-learning-based approach to address this issue. The proposed end-to-end deep learning method can extract crucial information from the multi-omics features by self-supervised learning for patient clustering. By applying our method to nine public cancer datasets, we have demonstrated superior performance compared to existing methods in separating patients with different survival outcomes (p < 0.05). To further evaluate the impact of various omics data on cancer survival, we developed an XGBoost classification model and found that mRNA had the highest importance score, followed by DNA methylation and miRNA. In the presented case study, our method successfully clustered subtypes and identified 14 cancer-related genes, of which 12 (85.7%) were validated through literature review. Our findings demonstrate that our method is capable of identifying cancer subtypes that are both statistically and biologically significant. The code about COLCS is given at: https://github.com/Mercuriiio/COLCS .

Artificial Intelligence in Dermatopathology: a systematic review.

Medical research, driven by advancing technologies like Artificial Intelligence (AI), is transforming healthcare. Dermatology, known for its visual nature, benefits from AI, especially in dermatopathology with digitized slides. This review explores into AI's role, challenges, opportunities, and future potential in enhancing dermatopathological diagnosis and care. Adhering to PRISMA and Cochrane Handbook standards, this systematic review explored AI's function in dermatopathology. It employed an interdisciplinary method, encompassing diverse study types and comprehensive database searches. Inclusion criteria encompassed peer-reviewed articles from 2000 to 2023, with a focus on practical AI use in dermatopathology. Numerous studies have investigated AI's potential in dermatopathology. We reviewed 112 papers. Notable applications include AI classifying histopathological images of nevi and melanomas, although challenges exist regarding subtype differentiation and generalizability. AI achieved high accuracy in melanoma recognition from formalin-fixed paraffin-embedded samples but faced limitations due to small datasets. Deep learning algorithms showed diagnostic accuracy for specific skin conditions, but challenges persisted, such as small sample sizes and the need for prospective validation. This systematic review underscores AI's potential in enhancing dermatopathology for better diagnosis and patient care. Addressing challenges like limited datasets and potential biases is essential. Future directions involve expanding datasets, conducting validation studies, promoting interdisciplinary collaboration, and creating patient-centred AI tools to enhance dermatopathology's accuracy, accessibility, and patient-focused care.

Safety and efficacy comparison of Tenecteplase and Alteplase for clinically suspected large vessel occlusion strokes without thrombectomy.

Tenecteplase is a thrombolytic with higher fibrin affinity, and is potentially better in clot lysis. A higher spontaneous recanalization rate for large vessel occlusions strokes (LVO) had been shown in comparison studies with Alteplase. Results of the LVO studies reflect the composite effect of the thrombolytic and thrombectomy, as patients would be treated by thrombectomy had they not been recanalized by intravenous thrombolysis alone. Thrombectomy is not readily available in many parts of the world. Our study aimed to compare the outcomes of suspected LVO patients treated with Tenecteplase versus Alteplase only, without the confounding effect of thrombectomy. This is a retrospective review. Data of patients given Tenecteplase from May 2020 to August 2023, and those given Alteplase 0.9 mg/kg from January 2019 to August 2023 were retrieved. (Due to fluctuation in supply of Tenecteplase during the COVID pandemic, some large vessel occlusion patients were given Alteplase.) Patients with anterior circulation, clinically suspected large vessel occlusion strokes (defined as National Institutes Health Stroke Scale (NIHSS) score &gt;= 6, plus cortical signs or hyperdense vessel sign), with thrombolysis given within 4.5 hours of stroke onset were analyzed. Patients with thrombectomy done were excluded. Safety and efficacy outcomes were compared. There were 245 Tenecteplase treated patients treated between 1st May 2020 and 31st August 2023, and 732 patients were treated with Alteplase between 1st January 2019 to 31st August 2023. Out of these, 148 Tenecteplase patients and 138 Alteplase 0.9 mg/kg patients fulfilled the study criteria. The symptomatic intracerebral haemorrhage rate was non-significantly lower in the Tenecteplase group (2.1% versus 5.8%, p=0.13). There were no significant differences in the rate of &gt;=8 points NIHSS improvement (23.6% versus 23.7%, p=1) or the &gt;= 4 points improvement (40.5% versus 40.7%, p=1) at 24 hours. At 3 months, 21.6% of Tenecteplase patients had good functional outcome (modified Rankin scale (mRS) 0-2), compared to 26.3% in the Alteplase group (p=0.40). In this pragmatic study of clinically suspected anterior circulation LVO patients without thrombectomy, outcome solely reflects the effects of Tenecteplase. Tenecteplase showed comparable safety and efficacy to Alteplase. But the result should be interpreted with caution in view of its small sample size and non-randomized study design.

Increased packed cell volume alters point of care viscoelastic clotting parameters in horses.

Polycythaemia and coagulopathy are identified risk factors for non-survival in critically ill horses. Assessment of coagulation is recommended for critical care monitoring but may be affected by concurrent polycythaemia. To evaluate the effects of induced polycythaemia on coagulation parameters as measured by a point-of-care viscoelastic coagulation device (VCM Vet™). Prospective interventional study. Healthy adult horses (n = 7) were given 6 mcg/kg of phenylephrine IV over 15 min to induce transient polycythaemia. Samples for packed cell volume (PCV), total solids (TS), complete blood count (CBC), activated partial thromboplastin time (PTT), prothrombin (PT) and VCM Vet™ viscoelastic testing were collected at baseline (T0), 5 min (T1) and 2 h (T2) post-phenylephrine infusion. Splenic volume was measured by transabdominal ultrasonography. VCM Vet™ and plasma-based coagulation parameters, splenic volume and haematologic values were compared within and between time points. Splenic volume decreased from T0 (11.5 ± 4.8 L) to T1 (6.1 ± 2 L, p = 0.04) and returned to baseline volume by T2 (12.1 ± 3.9 L, p = 0.8), consistent with phenylephrine-induced splenic contraction. PCV increased from T0 (37% ± 4%) to T1 (56.3% ± 5.3%; p < 0.001) and returned to baseline at T2 (41.6% ± 3.6%; p = 0.1). A10 and A20 (amplitude at 10 and 20 min, VCM units) were decreased from T0 (12.6 ± 1.6, 18.9 ± 5) to T1 (5.4 ± 1.9, 7.6 ± 2.4; both p < 0.001) and remained lower than baseline at T2 (9.3 ± 2.1, 12.7 ± 3; both p = 0.01). PT and PTT remained within reference ranges with no significant difference over time (p = 0.5 and 0.09, respectively). PCV was negatively correlated with CFT (R = -0.61, p = 0.003), A10 (R = -0.9, p < 0.001) and A20 (R = -0.87, p < 0.001). Small sample size, limited to healthy mares. Phenylephrine-induced polycythaemia was associated with hypocoagulable viscoelastic traces using the VCM Vet™ device without effect on plasma-based coagulation assessments or platelet number. Further investigation of viscoelastic testing is needed in horses with increased PCV due to clinical illness.

Assessing masseter muscle volume and activity in relation to craniofacial morphology: a 3D CBCT study.

Understanding the factors influencing craniofacial structure growth is crucial for addressing craniofacial deformities. This study evaluates masseter muscle volume, activity, and maximum bite force across different skeletal malocclusion groups and aims to evaluate the masseter muscle volume, activity, and maximum bite force (BF) according to different skeletal malocclusion groups. This study aimed to assess masseter muscle volume, activity, and maximum bite force (BF) across different skeletal malocclusion groups in 60 young adults (18-30 years) seeking treatment at Kirikkale University Faculty of Dentistry. Cone-Beam Computed Tomography (CBCT) imaging, radiological measurements, surface electromyography (sEMG), and force sensor measurements were employed. Results revealed significant differences in sEMG measurements based on sagittal classification. Vertical direction groups showed notable results in muscle volume and BF, though no significant differences were observed in sEMG values. A correlation was identified between BF and sEMG, but no correlation was found between muscle volume and other parameters. The findings obtained in this study suggest that the significant relationship between EMG and sagittal skeletal classification could be a valuable diagnostic tool. However, concerns about reliability were raised due to uneven distribution in muscle volume and BF among vertical direction groups. The lack of significant results in muscle volume, sEMG, and BF was attributed to CBCT limitations in soft tissue imaging and the small sample size, emphasizing caution in interpreting the findings.

A fault diagnosis method based on an improved diffusion model under limited sample conditions.

As a critical component in mechanical systems, the operational status of rolling bearings plays a pivotal role in ensuring the stability and safety of the entire system. However, in practical applications, the fault diagnosis of rolling bearings often encounters limitations due to the constraint of sample size, leading to suboptimal diagnostic accuracy. This article proposes a rolling bearing fault diagnosis method based on an improved denoising diffusion probability model (DDPM) to address this issue. The practical value of this research lies in its ability to address the limitation of small sample sizes in rolling bearing fault diagnosis. By leveraging DDPM to generate one-dimensional vibration data, the proposed method significantly enriches the datasets and consequently enhances the generalization capability of the diagnostic model. During the model training process, we innovatively introduce the feature differences between the original vibration data and the predicted vibration data generated based on prediction noise into the loss function, making the generated data more directional and targeted. In addition, this article adopts a one-dimensional convolutional neural network (1D-CNN) to construct a fault diagnosis model to more accurately extract and focus on key feature information related to faults. The experimental results show that this method can effectively improve the accuracy and reliability of rolling bearing fault diagnosis, providing new ideas and methods for fault detection and prevention in industrial applications. This advancement in diagnostic technology has the potential to significantly reduce the risk of system failures, enhance operational efficiency, and lower maintenance costs, thus contributing significantly to the safety and efficiency of mechanical systems.

Epilepsy surgery below the age of 5 years: Are we still in time to preserve developmental and intellectual functions?

The aim of this study is to describe the pre- and post-operative developmental and intellectual functions in a cohort of patients who underwent surgery for drug-resistant epilepsy (DRE) before the age of 5 years. We retrospectively reviewed the medical records and neurodevelopmental assessments of a cohort of 80 surgically treated pediatric patients with DRE. We included patients if they had at least one pre- and one post-surgical neuropsychological assessments; 27 met the inclusion criteria. We evaluated Developmental Quotient (DQ) and Intelligence Quotient (IQ) before and after surgery. We identified two groups based on psychological evaluation outcome: Group 1, with stable or improved developmental and intellectual functions, and Group 2, experiencing developmental and intellectual loss. The mean age at seizure onset was 1.2 ± 1.0 years, and the mean age at surgery was 2.9 ± 1.2 years. At the last follow-up (mean 4 years, SD ± 2), 19/27 (70%) patients were seizure- and drug-free; 18/27 patients (67%) fit in Group 1, and 9/27 (33%) fit in Group 2. The mean age at surgery was 2.6 years (SD ± 1.1; range 1.2-5.1) in Group 1 and 3.4 years in Group 2 (SD ± 1.1; range 1.6-5.0). Group 1 had a lower pre-operative DQ/IQ total score than Group 2 (median DQ/IQ respectively 82 vs 108, p = 0.05). Between pre- and post-assessments, we found that in Group 1, Performance scores improved (82.7 vs 102, p = 0.001), while in Group 2, the Total and Verbal scores worsened (respectively 108 vs 75, p = 0.008, and 100 vs 76, p = 0.021). Our study's results emphasize the positive impact of surgery before the age of 5 years on developmental and intellectual outcomes. Despite limitations such as a small sample size, lack of a control group, and diverse etiologies, our findings support the crucial role of early intervention in preserving or enhancing developmental and intellectual functions in young patients with DRE. This retrospective study, conducted at the Bambino Gesù Children Hospital in Italy, reports neuropsychological and developmental and/or cognitive data for children undergoing early epilepsy surgery (before the age of 5). It found that children with lower developmental or cognitive profiles gained the highest scores on post-operative neuropsychological evaluations. This study provides information on the potential benefits of early surgery in shortening the duration of epilepsy, preventing or arresting deterioration, and enhancing plasticity and recovery.

A Bayesian approach for estimating the uncertainty on the contribution of nitrogen fixation and calculation of nutrient balances in grain legumes

BackgroundThe proportion of nitrogen (N) derived from the atmosphere (Ndfa) is a fundamental component of the plant N demand in legume species. To estimate the N benefit of grain legumes for the subsequent crop in the rotation, a simplified N balance is frequently used. This balance is calculated as the difference between fixed N and removed N by grains. The Ndfa needed to achieve a neutral N balance (hereafter θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta$$\\end{document}) is usually estimated through a simple linear regression model between Ndfa and N balance. This quantity is routinely estimated without accounting for the uncertainty in the estimate, which is needed to perform formal statistical inference about θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta$$\\end{document}. In this article, we utilized a global database to describe the development of a novel Bayesian framework to quantify the uncertainty of θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta$$\\end{document}. This study aimed to (i) develop a Bayesian framework to quantify the uncertainty of θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta$$\\end{document}, and (ii) contrast the use of this Bayesian framework with the widely used delta and bootstrapping methods under different data availability scenarios.ResultsThe delta method, bootstrapping, and Bayesian inference provided nearly equivalent numerical values when the range of values for Ndfa was thoroughly explored during data collection (e.g., 6–91%), and the number of observations was relatively high (e.g., ≥100\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge 100$$\\end{document}). When the Ndfa tested was narrow and/or sample size was small, the delta method and bootstrapping provided confidence intervals containing biologically non-meaningful values (i.e. < 0% or > 100%). However, under a narrow Ndfa range and small sample size, the developed Bayesian inference framework obtained biologically meaningful values in the uncertainty estimation.ConclusionIn this study, we showed that the developed Bayesian framework was preferable under limited data conditions ─by using informative priors─ and when uncertainty estimation had to be constrained (regularized) to obtain meaningful inference. The presented Bayesian framework lays the foundation not only to conduct formal comparisons or hypothesis testing involving θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta$$\\end{document}, but also to learn about its expected value, variance, and higher moments such as skewness and kurtosis under different agroecological and crop management conditions. This framework can also be transferred to estimate balances for other nutrients and/or field crops to gain knowledge on global crop nutrient balances.

‘How anxious I am’: the effect of different online modalities on Chinese language beginners’ classroom anxiety

ABSTRACT Foreign language classroom anxiety (FLCA) is ‘a distinct complex set of self-perceptions, beliefs, feelings and behaviours related to classroom language learning arising from the uniqueness of the language learning process’ (Horwitz, Horwitz and Cope 1986: 128) [Foreign language classroom anxiety. The Modern Language Journal 70, no. 2: 125–32] which potentially has a negative impact on achievement and engagement in language learning. The purpose of the investigation reported here was to examine how two online modalities – Zoom video conferencing and the virtual world, Second Life – affected FLCA among Chinese language beginners performing tasks using the different modes. Through statistical and thematical analyses of survey data along with open-ended questions from 55 participants, it was found that the relationship between FLCA levels experienced by learners on these modalities was influenced by various factors such as gender differences, task-related language skills, and self-perceived language proficiency. The study also suggests that FLCA is dependent on the learners’ immediate learning experience, particularly in relation to their level of engagement and task awareness. Despite the small sample size, the study sheds light on the advantages and limitations of each modality in terms of its effect on students’ FLCA and performance in task-based language teaching.

Confidence Intervals for the Mean and Difference of Means of Birnbaum-Saunders Distributions with Application to Wind Speed Data

This paper proposes the confidence intervals for the mean and difference of means of Birnbaum-Saunders (BirSau) distributions based on the Bootstrap confidence interval (BCI), Percentile bootstrap confidence interval (PBCI), Generalized confidence interval (GCI), Bayesian credible interval (BayCrI) and the highest posterior density (HPD). The simulation study used R statistical software to evaluate the coverage probabilities and average lengths. The concerning results of the mean suggest that HPD is the recommended method for constructing confidence intervals in the BirSau distributions, except for small sample sizes where the GCI method proves more efficient. For the difference of means, PBCI emerges as the preferred way to construct confidence intervals, except in some cases where small sample sizes with the HPD method are more efficient. Moreover, the average lengths of these proposed confidence intervals decreased as both sample size and shape parameters increased. To illustrate the effectiveness of the suggested confidence intervals, we applied them to wind speed datasets collected in Ayutthaya and Ratchaburi provinces, Thailand.

Association between exposure to antidepressants and stimulants and age at onset of mania or psychosis: A retrospective population-based cohort study

This study investigated the impact of prior antidepressant and stimulant exposure on the age at onset (AAO) of first episode mania (FEM) or psychosis (FEP). Patients with FEP and FEM born after 1985 in Olmsted County, Minnesota, were identified using the Rochester Epidemiology Project. Duration and peak dose of antidepressant and stimulant exposure were quantified by review of the electronic health record. Peak doses were converted to defined daily dose (DDD), and cumulative exposure was calculated as DDD multiplied by treatment duration. Linear models were used to assess relationships between AAO with any exposures, and cumulative antidepressant and stimulant exposures. A total of 190 FEM/FEP patients (mean AAO=20.8 ± 3.7 years) were included. There was no significant difference in AAO with vs. without exposure to antidepressants or stimulants. Cumulative antidepressant exposure correlated with a later AAO in overall sample (r = 0.28, p < 0.001), and in FEP (r = 0.33, p < 0.001). No significant correlation emerged between cumulative stimulant exposure and AAO. Multivariable modeling confirmed that cumulative antidepressant exposure (Estimate=2.42, 95 %CI=1.66–3.18, p < 0.001), but not cumulative stimulant exposure (Estimate=-0.04, 95 %CI=-1.10–1.02, p = 0.94), was associated with later AAO. Antidepressant and stimulant exposures were not associated with earlier AAO. However, cumulative antidepressant exposure was associated with later AAO. Limitations include retrospective design and relatively small sample size. Our findings may inform adolescent treatment recommendations when assessing risk for psychotropic-related adverse events. Further risk modeling investigations of antidepressants and stimulants with larger sample sizes are needed to explore the role of antidepressant and stimulant exposure in the trajectory leading to FEM/FEP.

Effectiveness of a short, intensive, art-based group intervention on attention level in children with autism spectrum disorders: a pre-post experimental study

Background The rate of autism spectrum disorder (ASD) is dramatically rising globally, especially in the Middle East and North Africa. There has been little research on the effects of art-based interventions on attention impairments among children with ASD. Objective To examine the effectiveness of a short, intensive, art-based intervention on attention switching and attention to detail in children with moderate-severe ASD. Methods In this pre- and post-experimental study, children previously diagnosed with levels 2 and 3 ASD were invited to join a one-month, art-based course. The art-based intervention was held 3 days/week for 2 hours per day. Results The mean age of subjects was 8.33 (range 5 to 11) years; there were 10 (83.33%) males and 2 (16.67%) females. The total Autism Spectrum Quotient (AQ-Child) scores from baseline to one week after completion of the art-based course were not significantly different. In addition, mean social skills scores of attention switching and attention to detail, as well as communication scores were not significantly changed from baseline to after course completion. However, the children had significantly worse median imagination scores after the course compared to baseline scores (18.0 vs. 16.0, respectively) (P=0.0020). Conclusion After a one-month, art-based, group intervention, AQ-Child scores did not change significantly in total score, social skills, attention switching, attention to detail, or communication. The median imagination score worsened after, compared to before, the intervention. However, these results need to be interpreted with caution due to the very small sample size.

Reconstruction residual network with a fused spatial-channel attention mechanism for automatically classifying diabetic foot ulcer.

Diabetic foot ulcer (DFU) is a common chronic complication of diabetes. This complication is characterized by the formation of ulcers that are difficult to heal on the skin of the foot. Ulcers can negatively affect patients' quality of life, and improperly treated lesions can result in amputation and even death. Traditionally, the severity and type of foot ulcers are determined by doctors through visual observations and on the basis of their clinical experience; however, this subjective evaluation can lead to misjudgments. In addition, quantitative methods have been developed for classifying and scoring are therefore time-consuming and labor-intensive. In this paper, we propose a reconstruction residual network with a fused spatial-channel attention mechanism (FARRNet) for automatically classifying DFUs. The use of pseudo-labeling and Data augmentation as a pre-processing technique can overcome problems caused by data imbalance and small sample size. The developed model's attention was enhanced using a spatial channel attention (SPCA) module that incorporates spatial and channel attention mechanisms. A reconstruction mechanism was incorporated into the developed residual network to improve its feature extraction ability for achieving better classification. The performance of the proposed model was compared with that of state-of-the-art models and those in the DFUC Grand Challenge. When applied to the DFUC Grand Challenge, the proposed method outperforms other state-of-the-art schemes in terms of accuracy, as evaluated using 5-fold cross-validation and the following metrics: macro-average F1-score, AUC, Recall, and Precision. FARRNet achieved the F1-score of 60.81%, AUC of 87.37%, Recall of 61.04%, and Precision of 61.56%. Therefore, the proposed model is more suitable for use in medical diagnosis environments with embedded devices and limited computing resources. The proposed model can assist patients in initial identifications of ulcer wounds, thereby helping them to obtain timely treatment.

Childhood maltreatment as predictor and moderator for treatment outcome in patients with major depressive disorders treated with metacognitive therapy or behavioral activation

BackgroundChildhood maltreatment (CM) is a risk factor for developing and maintaining depression. It is unclear whether CM influences the effect of treatments for depression. This study examined CM's predictor and moderator effect in Behavioral Activation (BA) and Metacognitive Therapy (MCT). MethodCM was analyzed in a trial comparing a six months treatment program of either BA or MCT for 122 outpatients with major depressive disorder (MDD). Depression was assessed by the Hamilton Rating Scale for Depression (HRSD-24). CM was assessed using the Childhood Trauma Questionnaire (CTQ). ResultsLinear mixed models showed no predictor or moderator effects for the CTQ total score (all p > .58) but revealed a moderator effect for ‘sexual abuse’ on the reduction of depressive symptoms (β = 10.98, SE = 4.48, p = .015) indicating that patients with experiences of childhood sexual abuse benefited more from BA. There also was a predictor effect for ‘physical neglect’ (β = −3.35, SE = 1.70, p = .049): patients without the experience of physical neglect benefited more from treatment regardless of condition. Exploratory analyses indicated no predictor or moderator effects for the onset or persistence of depression, comorbid anxiety disorders or Cluster-C PDs (all p > .28). LimitationsLimitations include small sample sizes for some of the subsamples. ConclusionChildhood sexual abuse seems to moderate treatment effectiveness in a sample of severely affected outpatients with MDD treated with MCT or BA. If confirmed in further trials, a history of sexual abuse might guide the choice between MCT and BA. Trial registrationGerman Clinical Trials Register DRKS-ID: DRKS00011536 (retrospectively registered on February 13, 2017, without changes to the study protocol).

A General Factor of Hypnotizability Revealed by Confirmatory Factor Analysis

ABSTRACT The objective of this study was to determine the model fit of a standardized hypnotizability measure in a targeted clinical sample. The Stanford Hypnotic Susceptibility Scale, Form C (SHSS:C) was administered to 168 post-menopausal women aged 39 to 75 years. Confirmatory factor analysis was conducted, and comparative fit index (CFI) and root mean square error of approximation (RMSEA) were used to determine goodness of fit. Results indicated that the single-factor structure modeled with twelve indicators based on the individual items on the SHSS:C provided the best description of fit. Results of the present study demonstrate that the SHSS:C has a single-factor structure. These findings suggest that new scales of hypnotizability can be optimized by focusing on the use of items that correlate highly with the overall score representing the unidimensional construct of hypnotizability. The findings should be interpreted with caution due to the small sample size, and further research is needed with other populations to clarify generalizability.

Hypoactive sexual desire disorder in women: new possibilities to ensure better understanding, diagnosis, and response to treatment.

Hypoactive Sexual Desire Disorder (HSDD) is a frequent sex-related problem in women; however, a specific tool to characterize HSDD subtypes based on sexual inhibitory and excitatory factors is still lacking. (1) To find a cutoff value in Sexual Inhibition Scale (SIS)/Sexual Excitation Scale (SES) scores predicting a diagnosis of HSDD in women consulting for sexual symptoms, (2) to explore the sexual inhibitory and excitatory profiles in women referred to a clinic for female sexual dysfunction by stratifying the sample according to the newfound cutoffs, and (3) to identify biopsychosocial factors significantly associated with the 2 profiles. An overall 133 women consulting for sexual symptoms were retrospectively evaluated for clinical, biochemical, and psychosexologic data collected at the first visit. A subgroup of 55 women treated with transdermal testosterone was retrospectively analyzed at baseline and the 6-month visit. Patients underwent physical and laboratory examinations and completed the SIS/SES, Female Sexual Function Index, Female Sexual Distress Scale-Revised, Emotional Eating Scale, and Middlesex Hospital Questionnaire. Specific cutoffs for SIS1 (≥32.5; indicating threat of performance failure) andSES (≤46.5) predicted HSDD diagnosis with an accuracy of 66.4% (P = .002) and 68.7% (P < .0001), respectively. Patients with impaired SIS1 scores showed higher distress and psychopathologic symptoms, while those with impaired SES scores demonstrated lower desire and arousal and a negative association with some metabolic and hormonal parameters. SES score also showed a significant predictive value on testosterone treatment efficacy for HSDD. A better characterization of HSDD would enable individualized treatment based on the main underlying etiologies. Limitations of the study include the small sample size and cross-sectional retrospective design, with the choice of treatment for HSDD limited to transdermal testosterone. Strengths comprise the thorough and multifactorial evaluation of every aspect potentially affecting inhibitory and excitatory components of sexual desire. Validated cutoffs of SIS/SES scores could allow deep characterization of women diagnosed with HSDD, thus ensuring better tailoring of therapy and prediction of the probability of response to specific treatments.

Development and content validation of the Youth Australian and New Zealand Evaluation of Fitness to Stand Trial–Revised (Youth ANZ–EFST–R)

The Youth Australian and New Zealand Evaluation of Fitness to Stand Trial–Revised (Youth ANZ–EFST–R) was developed to address the lack of forensic assessment standardisation. Following development, 36 legal and mental health practitioners reviewed the proposed interview items to test the face, content and factor validity. Overall, 71% of items passed the validity thresholds. Items with poor validity related to the courtroom layout and psychotic symptoms affecting the defendant’s communication. Removing these items resulted in a 93% validity pass rate. There was moderate agreement about the proposed factor structure despite randomising the order and blinding participants to the administration rules (Gwet’s AC2 = .61, p < .001). The results provide preliminary support for the Youth ANZ–EFST–R with specified refinements made to enhance validity. Key limitations include the small sample size and the assumption of no crossloading items despite overlaps between the Presser criteria.

Joint estimation for multisource Gaussian graphical models based on transfer learning

This study considers data from multiple sources for Gaussian graphical models with one target graph and several auxiliary graphs. We propose a method called joint estimation for multisource Gaussian graphical models (JEM-GGM) to achieve a stable and accurate estimate of the target graph. Using the information from the auxiliary graphs, the proposed method is used to effectively solve the problem of small sample sizes. In this method, equivalent regression models are developed for graphs and the difference between the auxiliary and target graphs was penalized to ensure computational efficiency and improve estimation accuracy. Simulations revealed that the proposed method always outperformed other methods in terms of estimation and prediction accuracy. The application of this method to breast and lymphatic cancer cell lines reveals that the proposed method always obtains a sparse collection of important genome pairs.

The Best Start Trial: A randomised controlled trial of ultra-early parent-administered physiotherapy for infants at high risk of cerebral palsy or motor delay

BackgroundIt is unknown whether ultra-early physiotherapy commenced during neonatal intensive care unit admission is of value for optimising developmental outcomes in preterm/term infants at high-risk of cerebral palsy or motor-delay. AimsTo determine whether ultra-early parent-administered physiotherapy to preterm/term high- risk infants commenced at earliest from 34-weeks post menstrual age, improves motor outcomes at 16-weeks corrected age (CA) compared to usual care. MethodsSingle-blind randomised controlled pilot study with 30 infant participants. The primary outcome was the Alberta Infant Motor Scale (AIMS) total score at 16-weeks CA. Secondary outcomes included (i) parent Depression Anxiety and Stress Score and Parent Perceptions Survey at 16-weeks CA; and (ii) Bayley Scales of Infant Development at 12-months CA. ResultsThere were no clinically worthwhile effects at 16-weeks CA on the AIMS (mean between-group difference, 95% CI: -0.2, -2.4 to 2.0) or most secondary outcomes. However, the parents' “perception of treatment effectiveness” and “perception of change” favoured the experimental group. ConclusionsIn this pilot trial, there was no clinically worthwhile effect of ultra-early parent-administered physiotherapy over usual care on the AIMS. However, the intervention was feasible for infants, acceptable to parents and parents perceived a benefit of treatment. Whilst this trial did not demonstrate treatment effectiveness using the AIMS, these findings should be interpreted cautiously because of the small sample size, the low responsivity of the AIMS to change in motor performance and the heterogeneity of the participants. Therefore, the intervention should not be abandoned on the basis of this trial, but rather further evaluated in a larger trial that addresses some of the learnings from this one.

Lessons learned: drive-through COVID-19 clinic testing during an adaptive epidemic response and a point-of-care test assessment of a computer-read rapid lateral flow immunoassay with fluorescence-based detection.

Background. The COVID-19 pandemic demonstrated a need for robust SARS-CoV-2 test evaluation infrastructure to underpin biosecurity and protect the population during a pandemic health emergency.Gap statement. The first generation of rapid antigen tests was less accurate than molecular methods due to their inherent sensitivity and specificity shortfalls, compounded by the consequences of self-testing. This created a need for more accurate point-of-care SARS-CoV-2 detection methods.Aim. Here we present the lessons-learned during the COVID-19 emergency response in Western Australia including the detailed set-up, evaluation and operation of rapid antigen test in a state-run drive-through sample collection service during the COVID-19 pandemic after the strict border shutdown ended.Methods. We report a conformity assessment of a novel, second-generation rapid antigen test (Virulizer) comprising a technician-operated rapid lateral flow immunoassay with fluorescence-based detection.Results. The Virulizer rapid antigen test demonstrated up to 100% sensitivity (95% CI: 61.0-100%), 91.94% specificity (95% CI: 82.5-96.5%) and 92.65% accuracy when compared to a commercial PCR assay method. Wide confidence intervals in our series reflect the limits of small sample size. Nevertheless, the Virulizer assay performance was well-suited to point-of-care screening for SARS-CoV-2 in a drive-through clinic setting.Conclusion. The adaptive evaluation process necessary under changing pandemic conditions enabled assessment of a simple sample collection and point-of-care testing process, and showed how this system could be rapidly deployed for SARS-CoV-2 testing, including to regional and remote settings.