Targeting of multiple tumor-associated antigens by individual T cell receptors during successful cancer immunotherapy.

The T cells of the immune system can target tumors and clear solid cancers following tumor-infiltrating lymphocyte (TIL) therapy. We used combinatorial peptide libraries and a proteomic database to reveal the antigen specificities of persistent cancer-specific T cell receptors (TCRs) following successful TIL therapy for stage IV malignant melanoma. Remarkably, individual TCRs could target multiple different tumor types via the HLA A∗02:01-restricted epitopes EAAGIGILTV, LLLGIGILVL, and NLSALGIFST from Melan A, BST2, and IMP2, respectively. Atomic structures of a TCR bound to all three antigens revealed the importance of the shared x-x-x-A/G-I/L-G-I-x-x-x recognition motif. Multi-epitope targeting allows individual T cells to attack cancer in several ways simultaneously. Such "multipronged" T cells exhibited superior recognition of cancer cells compared with conventional T cell recognition of individual epitopes, making them attractive candidates for the development of future immunotherapies.

Right frontal cingulate cortex mediates the effect of prenatal complications on youth internalizing behaviors.

Prenatal and perinatal complications represent well-known risk factors for the future development of psychiatric disorders. Such influence might become manifested during childhood and adolescence, as key periods for brain and behavioral changes. Internalizing and externalizing behaviors in adolescence have been associated with the risk of psychiatric onset later in life. Both brain morphology and behavior seem to be affected by obstetric complications, but a clear link among these three aspects is missing. Here, we aimed at analyzing the association between prenatal and perinatal complications, behavioral issues, and brain volumes in a group of children and adolescents. Eighty-two children and adolescents with emotional-behavioral problems underwent clinical and 3 T brain magnetic resonance imaging (MRI) assessments. The former included information on behavior, through the Child Behavior Checklist/6-18 (CBCL/6-18), and on the occurrence of obstetric complications. The relationships between clinical and gray matter volume (GMV) measures were investigated through multiple generalized linear models and mediation models. We found a mutual link between prenatal complications, GMV alterations in the frontal gyrus, and withdrawn problems. Specifically, complications during pregnancy were associated with higher CBCL/6-18 withdrawn scores and GMV reductions in the right superior frontal gyrus and anterior cingulate cortex. Finally, a mediation effect of these GMV measures on the association between prenatal complications and the withdrawn dimension was identified. Our findings suggest a key role of obstetric complications in affecting brain structure and behavior. For the first time, a mediator role of frontal GMV in the relationship between prenatal complications and internalizing symptoms was suggested. Once replicated on independent cohorts, this evidence will have relevant implications for planning preventive interventions.

Meaningful cognitive change for the Minimal Assessment of Cognitive Function in Multiple Sclerosis.

BACKGROUND: There is limited information on interpretation of cognitive changes over time in multiple sclerosis (MS). OBJECTIVE: This study aimed to provide normative data for the assessment of statistically meaningful change in all tests of the Minimal Assessment of Cognitive Function in MS (MACFIMS). METHODS: We applied the reliable change methodology to a healthy Italian cohort, assessed with two alternate versions of the MACFIMS 1 year apart. We calculated confidence intervals of retest score variance using the reliable change index (RCI). Moreover, multivariable linear regression models adjusted for age, sex, education, and baseline score were built to calculate the regression-based change index (RB-CI). RESULTS: Overall, 200 healthy individuals were enrolled. Thresholds for interpreting change in each test were calculated. In the multivariable models, baseline score was associated with retest score in all tests (B from 0.439 to 0.760; p < 0.001). RB-CI can be calculated with data of the multivariable models. CONCLUSION: We provide normative data for reliable cognitive change evaluation for all the tests of the MACFIMS, which includes the Symbol Digit Modalities Test and Brief International Cognitive Assessment in MS, two widely used tools for screening and monitoring cognition in MS. Our findings can significantly improve the interpretation of cognitive changes in MS.

Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar.

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.

A Higher Kick Frequency Swimming Training Program Optimizes Swim-to-Cycle Transition in Triathlon.

ABSTRACT: Ambrosini, L, Presta, V, Vitale, M, Menegatti, E, Guarnieri, A, Bianchi, V, De Munari, I, Condello, G, and Gobbi, G. A higher kick frequency swimming training program optimizes swim-to-cycle transition in triathlon. J Strength Cond Res 38(5): 976-984, 2024-The purpose of this study was to evaluate the effect of an 8-week swimming training program on biomechanical and physiological responses during a swim-to-cycle simulation. Fifteen triathletes were randomly allocated to 3 groups: a 6-beat-kick group (K6), a 4-beat-kick group (K4), and a control group (CG). Biomechanical and physiological parameters were evaluated during a 400-m swim and a 10-minute cycle segment before (Pretraining) and after (Posttraining) the program. A lower stroke frequency ( p = 0.004) and a higher stroke length ( p = 0.002) was found in K6 compared with CG at Posttraining. A reduction in the K6 emerged between Pretraining and Posttraining during cycling for heart rate ( p = 0.005), V̇O 2 ( p = 0.014), and energy expenditure ( p = 0.008). A positive association emerged between swim kick index and cycling cadence in the K6 group. The improvement in stroke frequency and length observed in the K6 group could be explained as an improvement in swimming technique. Similarly, the reduction in energy expenditure during cycling at Posttraining for the K6 group suggests an improvement in the working economy. Triathlon coaches and athletes should consider the inclusion of high swim kick into their training programs to enhance swim and cycling performance, which can ultimately lead to an improvement in the swim-to-cycle transition and the overall triathlon performance.

Bridge Therapy before Liver Transplant for Advanced Hepatocellular Carcinoma.

Hepatocellular carcinoma is the most common primary liver tumor. Orthotopic liver transplant is one of the best treatment options, but its waiting list has to be considered. Bridge therapies have been introduced in order to limit this issue. The aim of this study is to evaluate if bridge therapies in advanced hepatocellular carcinoma can improve overall survival and reduce de-listing. We selected 185 articles. The search was limited to English articles involving only adult patients. These were deduplicated and articles with incomplete text or irrelevant conclusions were excluded. Sorafenib is the standard of care for advanced hepatocellular carcinoma and increases overall survival without any significant drug toxicity. However, its survival benefit is limited. The combination of transarterial chemoembolization + sorafenib, instead, delays tumor progression, although its survival benefit is still uncertain. A few studies have shown that patients undergoing transarterial chemoembolization + radiation therapy have similar or even better outcomes than those undergoing transarterial chemoembolization or sorafenib alone for rates of histopathologic complete response (89% had no residual in the explant). Also, the combined therapy of transarterial chemoembolization + radiotherapy + sorafenib was compared to the association of transarterial chemoembolization + radiotherapy and was associated with a better survival rate (24 vs. 17 months). Moreover, immunotherapy revealed new encouraging perspectives. Combination therapies showed the most encouraging results and could become the gold standard as a bridge to transplant for patients with advanced hepatocellular carcinoma.

Perforated peptic ulcer (PPU) treatment: an Italian nationwide propensity score-matched cohort study investigating laparoscopic vs open approach.

BACKGROUND: Perforated peptic ulcer (PPU) remain a surgical emergency accounting for 37% of all peptic ulcer-related deaths. Surgery remains the standard of care. The benefits of laparoscopic approach have been well-established even in the elderly. However, because of inconsistent results with specific regard to some technical aspects of such technique surgeons questioned the adoption of laparoscopic approach. This leads to choose the type of approach based on personal experience. The aim of our study was to critically appraise the use of the laparoscopic approach in PPU treatment comparing it with open procedure. METHODS: A retrospective study with propensity score matching analysis of patients underwent surgical procedure for PPU was performed. Patients undergoing PPU repair were divided into: Laparoscopic approach (LapA) and Open approach (OpenA) groups and clinical-pathological features of patients in the both groups were compared. RESULTS: A total of 453 patients underwent PPU simple repair. Among these, a LapA was adopted in 49% (222/453 patients). After propensity score matching, 172 patients were included in each group (the LapA and the OpenA). Analysis demonstrated increased operative times in the OpenA [OpenA: 96.4 ± 37.2 vs LapA 88.47 ± 33 min, p = 0.035], with shorter overall length of stay in the LapA group [OpenA 13 ± 12 vs LapA 10.3 ± 11.4 days p = 0.038]. There was no statistically significant difference in mortality [OpenA 26 (15.1%) vs LapA 18 (10.5%), p = 0.258]. Focusing on morbidity, the overall rate of 30-day postoperative morbidity was significantly lower in the LapA group [OpenA 67 patients (39.0%) vs LapA 37 patients (21.5%) p = 0.002]. When stratified using the Clavien-Dindo classification, the severity of postoperative complications was statistically different only for C-D 1-2. CONCLUSIONS: Based on the present study, we can support that laparoscopic suturing of perforated peptic ulcers, apart from being a safe technique, could provide significant advantages in terms of postoperative complications and hospital stay.

Smart Immunosensors for Point-of-Care Serological Tests Aimed at Assessing Natural or Vaccine-Induced SARS-CoV-2 Immunity.

Innovative and highly performing smart voltammetric immunosensors for rapid and effective serological tests aimed at the determination of SARS-CoV-2 antibodies were developed and validated in human serum matrix. Two immunosensors were developed for the determination of immunoglobulins directed against either the nucleocapsid or the spike viral antigen proteins. The immunosensors were realized using disposable screen-printed electrodes modified with nanostructured materials for the immobilization of the antigens. Fast quantitative detection was achieved, with analysis duration being around 1 h. Signal readout was carried out through a smart, compact and battery-powered potentiostat, based on a Wi-Fi protocol and devised for the Internet of Things (IoT) paradigm. This device is used for the acquisition, storage and sharing of clinical data. Outstanding immunosensors' sensitivity, specificity and accuracy (100%) were assessed, according to the diagnostic guidelines for epidemiological data. The overall performance of the sensing devices, combined with the portability of the IoT-based device, enables their suitability as a high-throughput diagnostic tool. Both of the immunosensors were validated using clinical human serum specimens from SARS-CoV-2 infected patients, provided by IRCCS Ospedale San Raffaele.

Peptide-MHC Class I Tetramers Can Fail To Detect Relevant Functional T Cell Clonotypes and Underestimate Antigen-Reactive T Cell Populations.

Peptide-MHC (pMHC) multimers, usually used as streptavidin-based tetramers, have transformed the study of Ag-specific T cells by allowing direct detection, phenotyping, and enumeration within polyclonal T cell populations. These reagents are now a standard part of the immunology toolkit and have been used in many thousands of published studies. Unfortunately, the TCR-affinity threshold required for staining with standard pMHC multimer protocols is higher than that required for efficient T cell activation. This discrepancy makes it possible for pMHC multimer staining to miss fully functional T cells, especially where low-affinity TCRs predominate, such as in MHC class II-restricted responses or those directed against self-antigens. Several recent, somewhat alarming, reports indicate that pMHC staining might fail to detect the majority of functional T cells and have prompted suggestions that T cell immunology has become biased toward the type of cells amenable to detection with multimeric pMHC. We use several viral- and tumor-specific pMHC reagents to compare populations of human T cells stained by standard pMHC protocols and optimized protocols that we have developed. Our results confirm that optimized protocols recover greater populations of T cells that include fully functional T cell clonotypes that cannot be stained by regular pMHC-staining protocols. These results highlight the importance of using optimized procedures that include the use of protein kinase inhibitor and Ab cross-linking during staining to maximize the recovery of Ag-specific T cells and serve to further highlight that many previous quantifications of T cell responses with pMHC reagents are likely to have considerably underestimated the size of the relevant populations.

The minimal neuropsychological assessment of MS patients (MACFIMS): normative data of the Italian population.

Cognitive impairment is common in multiple sclerosis (MS), and research has emphasized the crucial role of cognitive assessment in disease monitoring. The minimal neuropsychological assessment of MS (MACFIMS) represents one of the neuropsychological batteries most widely used throughout the world. To date, a complete validation, as well as normative values of an alternative form, is lacking in the Italian population, limiting the use of this tool in longitudinal assessment. A total of 200 healthy subjects (127 females and 73 males) were recruited from the community in 8 Italian cities and were evaluated with the MACFIMS at baseline and reassessed with an alternate form of the same battery after 12 months. Regression-based norms that account for demographic influences on test performance were calculated at each time point (baseline and follow-up). The study provides, for the first time, normative values of two forms of the MACFIMS battery for the Italian population. Data application allows clinicians to monitor the performance of cognitive functions over time and to better understand the efficacy of both pharmacological and non-pharmacological interventions in clinical practice and research.

A Model-Based Design Floating-Point Accumulator. Case of Study: FPGA Implementation of a Support Vector Machine Kernel Function.

Recent research in wearable sensors have led to the development of an advanced platform capable of embedding complex algorithms such as machine learning algorithms, which are known to usually be resource-demanding. To address the need for high computational power, one solution is to design custom hardware platforms dedicated to the specific application by exploiting, for example, Field Programmable Gate Array (FPGA). Recently, model-based techniques and automatic code generation have been introduced in FPGA design. In this paper, a new model-based floating-point accumulation circuit is presented. The architecture is based on the state-of-the-art delayed buffering algorithm. This circuit was conceived to be exploited in order to compute the kernel function of a support vector machine. The implementation of the proposed model was carried out in Simulink, and simulation results showed that it had better performance in terms of speed and occupied area when compared to other solutions. To better evaluate its figure, a practical case of a polynomial kernel function was considered. Simulink and VHDL post-implementation timing simulations and measurements on FPGA confirmed the good results of the stand-alone accumulator.

A Self-Calibrating IoT Portable Electrochemical Immunosensor for Serum Human Epididymis Protein 4 as a Tumor Biomarker for Ovarian Cancer.

Nowadays, analytical techniques are moving towards the development of smart biosensing strategies for the point-of-care accurate screening of disease biomarkers, such as human epididymis protein 4 (HE4), a recently discovered serum marker for early ovarian cancer diagnosis. In this context, the present work represents the first implementation of a competitive enzyme-labelled magneto-immunoassay exploiting a homemade IoT Wi-Fi cloud-based portable potentiostat for differential pulse voltammetry readout. The electrochemical device was specifically designed to be capable of autonomous calibration and data processing, switching between calibration, and measurement modes: in particular, firstly, a baseline estimation algorithm is applied for correct peak computation, then calibration function is built by interpolating data with a four-parameter logistic function. The calibration function parameters are stored on the cloud for inverse prediction to determine the concentration of unknown samples. Interpolation function calibration and concentration evaluation are performed directly on-board, thus reducing the power consumption. The analytical device was validated in human serum, demonstrating good sensing performance for analysis of HE4 with detection and quantitation limits in human serum of 3.5 and 29.2 pM, respectively, reaching the sensitivity that is required for diagnostic purposes, with high potential for applications as portable and smart diagnostic tool for point-of-care testing.

A Molecular Switch Abrogates Glycoprotein 100 (gp100) T-cell Receptor (TCR) Targeting of a Human Melanoma Antigen.

Human CD8(+) cytotoxic T lymphocytes can mediate tumor regression in melanoma through the specific recognition of HLA-restricted peptides. Because of the relatively weak affinity of most anti-cancer T-cell receptors (TCRs), there is growing emphasis on immunizing melanoma patients with altered peptide ligands in order to induce strong anti-tumor immunity capable of breaking tolerance toward these self-antigens. However, previous studies have shown that these immunogenic designer peptides are not always effective. The melanocyte differentiation protein, glycoprotein 100 (gp100), encodes a naturally processed epitope that is an attractive target for melanoma immunotherapies, in particular peptide-based vaccines. Previous studies have shown that substitutions at peptide residue Glu(3) have a broad negative impact on polyclonal T-cell responses. Here, we describe the first atomic structure of a natural cognate TCR in complex with this gp100 epitope and highlight the relatively high affinity of the interaction. Alanine scan mutagenesis performed across the gp100(280-288) peptide showed that Glu(3) was critically important for TCR binding. Unexpectedly, structural analysis demonstrated that the Glu(3) → Ala substitution resulted in a molecular switch that was transmitted to adjacent residues, abrogating TCR binding and T-cell recognition. These findings help to clarify the mechanism of T-cell recognition of gp100 during melanoma responses and could direct the development of altered peptides for vaccination.

Antibody stabilization of peptide-MHC multimers reveals functional T cells bearing extremely low-affinity TCRs.

Fluorochrome-conjugated peptide-MHC (pMHC) multimers are commonly used in combination with flow cytometry for direct ex vivo visualization and characterization of Ag-specific T cells, but these reagents can fail to stain cells when TCR affinity and/or TCR cell-surface density are low. pMHC multimer staining of tumor-specific, autoimmune, or MHC class II-restricted T cells can be particularly challenging, as these T cells tend to express relatively low-affinity TCRs. In this study, we attempted to improve staining using anti-fluorochrome unconjugated primary Abs followed by secondary staining with anti-Ab fluorochrome-conjugated Abs to amplify fluorescence intensity. Unexpectedly, we found that the simple addition of an anti-fluorochrome unconjugated Ab during staining resulted in considerably improved fluorescence intensity with both pMHC tetramers and dextramers and with PE-, allophycocyanin-, or FITC-based reagents. Importantly, when combined with protein kinase inhibitor treatment, Ab stabilization allowed pMHC tetramer staining of T cells even when the cognate TCR-pMHC affinity was extremely low (KD >1 mM) and produced the best results that we have observed to date. We find that this inexpensive addition to pMHC multimer staining protocols also allows improved recovery of cells that have recently been exposed to Ag, improvements in the recovery of self-specific T cells from PBMCs or whole-blood samples, and the use of less reagent during staining. In summary, Ab stabilization of pMHC multimers during T cell staining extends the range of TCR affinities that can be detected, yields considerably enhanced staining intensities, and is compatible with using reduced amounts of these expensive reagents.

Latent classes of emotional and behavioural problems in epidemiological and referred samples and their relations to DSM-IV diagnoses.

Researchers' interest have recently moved toward the identification of recurrent psychopathological profiles characterized by concurrent elevations on different behavioural and emotional traits. This new strategy turned to be useful in terms of diagnosis and outcome prediction. We used a person-centred statistical approach to examine whether different groups could be identified in a referred sample and in a general-population sample of children and adolescents, and we investigated their relation to DSM-IV diagnoses. A latent class analysis (LCA) was performed on the Child Behaviour Checklist (CBCL) syndrome scales of the referred sample (N = 1225), of the general-population sample (N = 3418), and of the total sample. Models estimating 1-class through 5-class solutions were compared and agreement in the classification of subjects was evaluated. Chi square analyses, a logistic regression, and a multinomial logistic regression analysis were used to investigate the relations between classes and diagnoses. In the two samples and in the total sample, the best-fitting models were 4-class solutions. The identified classes were Internalizing Problems (15.68%), Severe Dysregulated (7.82%), Attention/Hyperactivity (10.19%), and Low Problems (66.32%). Subsequent analyses indicated a significant relationship between diagnoses and classes as well as a main association between the severe dysregulated class and comorbidity. Our data suggested the presence of four different psychopathological profiles related to different outcomes in terms of psychopathological diagnoses. In particular, our results underline the presence of a profile characterized by severe emotional and behavioural dysregulation that is mostly associated with the presence of multiple diagnosis.

Multiple Sclerosis: Changes in Thalamic Resting-State Functional Connectivity Induced by a Home-based Cognitive Rehabilitation Program.

Purpose To investigate thalamic connectivity changes after use of a video game-based cognitive rehabilitation program, as thalamic damage and alterations in thalamocortical functional connectivity (FC) are important factors in cognitive dysfunction in patients with multiple sclerosis (MS). Materials and Methods This prospective study was approved by the local ethical committee. Twenty-four patients with MS and cognitive impairment were randomly assigned to either an intervention or a wait-list group. Patients were evaluated with cognitive tests and 3-T resting-state functional magnetic resonance (MR) imaging at baseline and after an 8-week period. In addition, 11 healthy subjects underwent baseline resting-state functional MR imaging. Patients in the intervention group performed the video game-based cognitive rehabilitation program, while those in the wait-list group served as control subjects. Repeated measures analysis of variance was used to test efficacy of the intervention. The thalamic resting-state network was identified with a seed-based method; both first-level and high-level analyses were performed by using software tools. Results Patients showed lower baseline FC compared with healthy subjects. A significant improvement was seen in results of the Paced Auditory Serial Addition Test and the Stroop Test after 8 weeks of cognitive rehabilitation (F = 6.616, [P = .018] and F = 5.325 [P = .030], respectively). At follow-up, the intervention group had an increased FC in the cingulum, precuneus, and bilateral parietal cortex and a lower FC in the cerebellum and in left prefrontal cortex compared with the wait-list group (P < .05, family-wise error corrected); correlations were found between FC changes in these regions and cognitive improvement (P < .05, family-wise error corrected). Conclusion The results of this study show the relevance of thalamic regulation of the brain networks involved in cognition and suggest that changes in thalamic resting-state network connectivity may represent a functional substrate for cognitive improvement associated with a video game-based cognitive rehabilitation program. (©) RSNA, 2016.

The cognitive reserve theory in the setting of pediatric-onset multiple sclerosis.

BACKGROUND: The study of cognitive reserve (CR) in relationship with cognitive impairment (CI) in pediatric-onset multiple sclerosis (POMS) may provide cues to identifying subjects at higher risk of impairment and scope for therapeutic strategies. OBJECTIVES: To assess the potential impact of CR on cognition in a cohort of POMS patients. METHODS: In all, 48 POMS patients were followed up for 4.7 ± 0.4 years. CI was defined as the failure of ⩾3 tests on an extensive neuropsychological battery. Change of neuropsychological performance was assessed through the Reliable Change Index (RCI) method. At baseline, CR was estimated by measuring the intelligence quotient (IQ). The relationships were assessed through multivariable regression analyses. RESULTS: At baseline, CI was detected in 14/48 (29.2%) patients. Two out of 57 healthy control (HC; 3.5%) met the same criteria of CI (p < 0.001). A deteriorating cognitive performance using the RCI method was observed in 18/48 patients (37.6%). Among the 34 cases who were cognitively preserved at baseline, a higher reserve predicted stable/improving performance (odds ratio (OR) = 1.11; 95% confidence interval (CI): 1.03-1.20; p = 0.006). CONCLUSION: Our results suggest that higher CR in POMS patients may protect from CI, particularly in subjects with initial cognitive preservation, providing relevant implications for counseling and rehabilitation strategies.

More tricks with tetramers: a practical guide to staining T cells with peptide-MHC multimers.

Analysis of antigen-specific T-cell populations by flow cytometry with peptide-MHC (pMHC) multimers is now commonplace. These reagents allow the tracking and phenotyping of T cells during infection, autoimmunity and cancer, and can be particularly revealing when used for monitoring therapeutic interventions. In 2009, we reviewed a number of 'tricks' that could be used to improve this powerful technology. More recent advances have demonstrated the potential benefits of using higher order multimers and of 'boosting' staining by inclusion of an antibody against the pMHC multimer. These developments now allow staining of T cells where the interaction between the pMHC and the T-cell receptor is over 20-fold weaker (K(D) > 1 mm) than could previously be achieved. Such improvements are particularly relevant when using pMHC multimers to stain anti-cancer or autoimmune T-cell populations, which tend to bear lower affinity T-cell receptors. Here, we update our previous work to include discussion of newer tricks that can produce substantially brighter staining even when using log-fold lower concentrations of pMHC multimer. We further provide a practical guide to using pMHC multimers that includes a description of several common pitfalls and how to circumvent them.

Regulating emotions about secrets.

Secrecy is common and psychologically costly. Research shows that secrets have high emotional stakes, but no research has directly tested how people regulate their emotions about secrets. To fill this gap, we conducted an experimental study (Study 1), then moved to studying secrecy "in the wild" to capture regulatory processes as they unfold in everyday life (Studies 2 and 3). In Study 1 (N = 498), people reported using different strategies to regulate emotions about secrets compared to matched nonsecrets. In two daily diary studies (NStudy 2 = 174, 1,059 surveys; NStudy 3 = 240, 2,764 surveys), participants reported engaging in acceptance, distraction, and expressive suppression most-and social sharing least-to manage emotions about secrets. Moreover, in testing which kinds of secrets required most regulation, Study 3 suggested that significant, negative, controllable, and socially harmful secrets were associated with greater use of rumination, distraction, and suppression; perceived immorality of keeping secrets was associated with greater use of reappraisal; and secret discoverability did not differentially predict regulation strategies. Our findings indicate that when regulating emotions about their secrets, people appear to prioritize their intention to keep secret information hidden, despite potential well-being costs that may come with enacting this intention. Understanding the regulatory processes involved in secrecy is a foundation on which future research can build to identify ways of alleviating the burden of secrecy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.

Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and interpreting data from clinical trials and research projects to identify subtle but meaningful trends beyond ordinary perception. Artificial intelligence refers to the simulation of human intelligence in computers, where systems of artificial intelligence can perform tasks that require human-like intelligence like speech recognition, visual perception, pattern-recognition, decision-making, and language processing. Artificial intelligence has several subdivisions, including machine learning, natural language processing, computer vision, and robotics. By automating specific routine tasks, artificial intelligence can improve healthcare efficiency. By leveraging machine learning algorithms, the systems of artificial intelligence can offer new opportunities for enhancing both the efficiency and effectiveness of surgical procedures, particularly regarding training of minimally invasive surgery. As artificial intelligence continues to advance, it is likely to play an increasingly significant role in the field of surgical learning. Physicians have assisted to a spreading role of artificial intelligence in the last decade. This involved different medical specialties such as ophthalmology, cardiology, urology, but also abdominal surgery. In addition to improvements in diagnosis, ascertainment of efficacy of treatment and autonomous actions, artificial intelligence has the potential to improve surgeons' ability to better decide if acute surgery is indicated or not. The role of artificial intelligence in the emergency departments has also been investigated. We considered one of the most common condition the emergency surgeons have to face, acute appendicitis, to assess the state of the art of artificial intelligence in this frequent acute disease. The role of artificial intelligence in diagnosis and treatment of acute appendicitis will be discussed in this narrative review.