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Computational modeling of behavior has revolutionized psychology and neuroscience. By fitting models to experimental data we can probe the algorithms underlying behavior, find neural correlates of computational variables and better understand the effects of drugs, illness and interventions. But with great power comes great responsibility. Here, we offer ten simple rules to ensure that computational modeling is used with care and yields meaningful insights. In particular, we present a beginner-friendly, pragmatic and details-oriented introduction on how to relate models to data. What, exactly, can a model tell us about the mind? To answer this, we apply our rules to the simplest modeling techniques most accessible to beginning modelers and illustrate them with examples and code available online. However, most rules apply to more advanced techniques. Our hope is that by following our guidelines, researchers will avoid many pitfalls and unleash the power of computational modeling on their own data.

Human African trypanosomiasis, or sleeping sickness, is caused by infection with parasites of the genus Trypanosoma, transmitted by the tsetse fly. The disease has two forms, Trypanosoma brucei (T b) rhodesiense and T b gambiense; and is almost always fatal if untreated. Despite a recent reduction in the number of reported cases, patients with African trypanosomiasis continue to present major challenges to clinicians. Because treatment for CNS-stage disease can be very toxic, diagnostic staging to distinguish early-stage from late-stage disease when the CNS in invaded is crucial but remains problematic. Melarsoprol is the only available treatment for late-stage T b rhodesiense infection, but can be lethal to 5% of patients owing to post-treatment reactive encephalopathy. Eflornithine combined with nifurtimox is the first-line treatment for late-stage T b gambiense. New drugs are in the pipeline for treatment of CNS human African trypanosomiasis, giving rise to cautious optimism.

This meta-analysis was conducted to investigate whether heart failure is associated with an increased risk of fractures by summarizing all the available evidence. The PubMed, EMBASE, and Cochrane Library databases were searched for all relevant studies published from the date of database inception to April 2018. Studies that investigated the association between heart failure and fracture risk and conducted a comparison with controls were included. Seven cohort studies were finally identified as eligible for inclusion in the meta-analysis. All included studies were of high quality as evaluated by the Newcastle-Ottawa Scale. There was a significantly higher risk of any fracture in patients diagnosed with heart failure (N = 53,038) than in controls (N = 126,727) (RR 1.66, 95% CI 1.14–2.43, I2 = 94%, P = 0.008). The results were the same for hip (RR 3.45, 95% CI: 1.86–6.40, I2 = 95%, P < 0.0001) and humerus fractures (RR 1.91, 95% CI 1.07–3.40, I2 = 39%, P = 0.03) but not for vertebral and forearm fractures. To conclude, this meta-analysis demonstrated that patients with heart failure had an increased risk of fractures, especially hip and humerus fractures. Patients with heart failure may need to pay greater attention to their bone health. This meta-analysis found a significantly higher risk of fractures in patients with heart failure than in those without heart failure. Greater attention should be paid to bone health in patients with heart failure.

Aiming at problems of low accuracy and strong detection interference of the existing safety helmet wearing detection algorithms, an object detection algorithm by adding the squeeze-and-excitation block based on the YOLOv5 algorithm is proposed in this paper. The proposed method can not only obtain the weight of picture channel, but also accurately separate the foreground and background of the picture. Keeping all parameters unchanged, the proposed method and the YOLOv5 algorithm are applied to detect the safety helmet data set in the experiment. The result shows that the YOLOv5 algorithm with the squeeze-and-excitation block has an average detection accuracy of 94.5% for safety helmets and an average detection accuracy of 92.7% for human heads. The mAP value detected by the proposed method is 2% ∼2.5% higher than using YOLOv5 algorithm directly.

Necroptosis is a type of programmed necrosis regulated by receptor interacting protein kinase 1 （RIP1） and RIP3. Necroptosis is found to be accompanied by an overproduction of reactive oxygen species （ROS）, but the role of ROS in regulation of necroptosis remains elusive. In this study, we investigated how shikonin, a necroptosis inducer for cancer cells, regulated the signaling leading to necroptosis in glinoma cells in vitro. Treatment with shikonin （2-10 pmol/L） dose-dependently triggered necrosis and induced overproduction of intracellular ROS in rat C6 and human SHG-44, U87 and U251 glioma cell lines. Moreover, shikonin treatment dose- dependently upregulated the levels of RIP1 and RIP3 and reinforced their interaction in the glioma cells. Pretreatment with the specific RIP1 inhibitor Nec-1 （100 pmol/L） or the specific RIP3 inhibitor GSK-872 （5 pmol/L） not only prevented shikonin-induced glioma cell necrosis but also significantly mitigated the levels of intraceliular ROS and mitochondrial superoxide. Mitigation of ROS with MnTBAP （40 pmol/L）, which was a cleaner of mitochondrial superoxide, attenuated shikonin-induced glioma cell necrosis, whereas increasing ROS levels with rotenone, which improved the mitochondrial generation of superoxide, significantly augmented shikonin-caused glioma cell necrosis. Furthermore, pretreatment with MnTBAP prevented the shikonin-induced upregulation of RIP1 and RIP3 expression and their interaction while pretreatment with rotenone reinforced these effects. These findings suggest that ROS is not only an executioner of shikonin-induced glioma cell necrosis but also a regulator of RIP1 and RIP3 expression and necrosome assembly.

Reinforcement Learning (RL) models have revolutionized the cognitive and brain sciences, promising to explain behavior from simple conditioning to complex problem solving, to shed light on developmental and individual differences, and to anchor cognitive processes in specific brain mechanisms. However, the RL literature increasingly reveals contradictory results, which might cast doubt on these claims. We hypothesized that many contradictions arise from two commonly-held assumptions about computational model parameters that are actually often invalid: That parameters generalize between contexts (e.g. tasks, models) and that they capture interpretable (i.e. unique, distinctive) neurocognitive processes. To test this, we asked 291 participants aged 8–30 years to complete three learning tasks in one experimental session, and fitted RL models to each. We found that some parameters (exploration / decision noise) showed significant generalization: they followed similar developmental trajectories, and were reciprocally predictive between tasks. Still, generalization was significantly below the methodological ceiling. Furthermore, other parameters (learning rates, forgetting) did not show evidence of generalization, and sometimes even opposite developmental trajectories. Interpretability was low for all parameters. We conclude that the systematic study of context factors (e.g. reward stochasticity; task volatility) will be necessary to enhance the generalizability and interpretability of computational cognitive models.

Varicella zoster virus (VZV) is a pathogenic human herpes virus which causes varicella as a primary infection, following which it becomes latent in peripheral autonomic, sensory, and cranial nerve ganglionic neurons from where it may reactivate after decades to cause herpes zoster. VZV reactivation may also cause a wide spectrum of neurological syndromes, in particular, acute encephalitis and vasculopathy. While there is potentially a large number of coding viral mutations that might predispose certain individuals to VZV infections, in practice, a variety of host factors are the main determinants of VZV infection, both disseminated and specifically affecting the nervous system. Host factors include increasing age with diminished cell-mediated immunity to VZV, several primary immunodeficiency syndromes, secondary immunodeficiency syndromes, and drug-induced immunosuppression. In some cases, the molecular immunological basis underlying the increased risk of VZV infections has been defined, in particular, the role of POL III mutations, but in other cases, the mechanisms have yet to be determined. The role of immunization in immunosuppressed individuals as well as its possible efficacy in preventing both generalized and CNS-specific infections will require further investigation to clarify in such patients.

In this clinical trial, apixaban, an oral factor Xa inhibitor, was shown to be superior to enoxaparin for the prevention of thromboembolism after hip replacement, without an increase in the risk of bleeding. Patients undergoing hip-replacement surgery require effective thromboprophylaxis, and low-molecular-weight heparins, vitamin K antagonists, and mechanical methods are now standard therapies. Despite prophylaxis, however, subclinical deep-vein thrombosis develops in approximately 15 to 20% of patients soon after surgery, and symptomatic venous thromboembolism develops in 2 to 4% during the first 3 months after surgery. 1 Practical limitations of current prophylactic techniques have stimulated a search for simpler methods. Low-molecular-weight heparins and fondaparinux require subcutaneous injection. Warfarin has a delayed onset of action and is relatively ineffective soon after surgery. Mechanical methods are cumbersome and relatively ineffective after hip surgery. The development of . . .

Family caregivers are crucial for supporting home death. We reviewed published qualitative research on home-based family caregiving at end of life (1998—2008), synthesizing key findings and identifying gaps where additional research is needed. Multiple databases were searched and abstracts reviewed for a focus on family caregiving and palliative care; full articles were reviewed to extract data for this review. In total, 105 articles were included. Findings are presented in the following areas: the caregiving experience and contextual features; supporting family caregivers at end of life; caregiving roles and decision-making; and rewards, meaning and coping. We noted a lack of definitional clarity; a reliance on interview methods and descriptive, thematic analyses, and a relative lack of diversity of patient conditions. Research needs are identified in several areas, including the bereavement experience, caregiver ambivalence, access to services, caregiver meaning-making, and relational and contextual influences on family caregiving at end of life.

Background The aim of this review was to investigate the impact of short message service (SMS)-based interventions on childhood and adolescent vaccine coverage and timeliness. Methods A pre-defined search strategy was used to identify all relevant publications up until July 2022 from electronic databases. Reports of randomised trials written in English and involving children and adolescents less than 18 years old were included. The review was conducted in accordance with PRISMA guidelines. Results Thirty randomised trials were identified. Most trials were conducted in high-income countries. There was marked heterogeneity between studies. SMS-based interventions were associated with small to moderate improvements in vaccine coverage and timeliness compared to no SMS reminder. Reminders with embedded education or which were combined with monetary incentives performed better than simple reminders in some settings. Conclusion Some SMS-based interventions appear effective for improving child vaccine coverage and timeliness in some settings. Future studies should focus on identifying which features of SMS-based strategies, including the message content and timing, are determinants of effectiveness.