Neural Networks in Neurological and Psychiatric Diseases

DTNPD: A comprehensive database of drugs and targets for neurological and psychiatric disorders

In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.

Amisulpride augmentation therapy improves cognitive performance and psychopathology in clozapine-resistant treatment-refractory schizophrenia: a 12-week randomized, double-blind, placebo-controlled trial

BACKGROUND

Although clozapine is an effective option for treatment-resistant schizophrenia (TRS), there are still 1/3 to 1/2 of TRS patients who do not respond to clozapine. The main purpose of this randomized, double-blind, placebo-controlled trial was to explore the amisulpride augmentation efficacy on the psychopathological symptoms and cognitive function of clozapine-resistant treatment-refractory schizophrenia (CTRS) patients.

METHODS

A total of 80 patients were recruited and randomly assigned to receive initial clozapine plus amisulpride (amisulpride group) or clozapine plus placebo (placebo group). Positive and Negative Syndrome Scale (PANSS), Scale for the Assessment of Negative Symptoms (SANS), Clinical Global Impression (CGI) scale scores, Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Treatment Emergent Symptom Scale (TESS), laboratory measurements, and electrocardiograms (ECG) were performed at baseline, at week 6, and week 12.

RESULTS

Compared with the placebo group, amisulpride group had a lower PANSS total score, positive subscore, and general psychopathology subscore at week 6 and week 12 (P_Bonferroni < 0.01). Furthermore, compared with the placebo group, the amisulpride group showed an improved RBANS language score at week 12 (P_Bonferroni < 0.001). Amisulpride group had a higher treatment response rate (P = 0.04), lower scores of CGI severity and CGI efficacy at week 6 and week 12 than placebo group (P_Bonferroni < 0.05). There were no differences between the groups in body mass index (BMI), corrected QT (QTc) intervals, and laboratory measurements. This study demonstrates that amisulpride augmentation therapy can safely improve the psychiatric symptoms and cognitive performance of CTRS patients.

CONCLUSION

This study indicates that amisulpride augmentation therapy has important clinical significance for treating CTRS to improve clinical symptoms and cognitive function with tolerability and safety. Trial registration Clinicaltrials.gov identifier- NCT03652974. Registered August 31, 2018, https://clinicaltrials.gov/ct2/show/NCT03652974.

Inhibition of neuronal nitric oxide synthase protects against hippocampal neuronal injuries by increasing neuropeptide Y expression in temporal lobe epilepsy mice

Neuronal nitric oxide synthase (nNOS) plays a pivotal role in the pathological process of neuronal injury in the development of epilepsy. Our previous study has demonstrated that nitric oxide (NO) derived from nNOS in the epileptic brain is neurotoxic due to its reaction with the superoxide radical with the formation of peroxynitrite. Neuropeptide Y (NPY) is widely expressed in the mammalian brain, which has been implicated in energy homeostasis and neuroprotection. Recent studies suggest that nNOS may act as a mediator of NPY signaling. Here in this study, we sought to determine whether NPY expression is regulated by nNOS, and if so, whether the regulation of NPY by nNOS is associated with the neuronal injuries in the hippocampus of epileptic brain. Our results showed that pilocarpine-induced temporal lobe epilepsy (TLE) mice exhibited an increased level of nNOS expression and a decreased level of NPY expression along with hippocampal neuronal injuries and cognition deficit. Genetic deletion of nNOS gene, however, significantly upregulated hippocampal NPY expression and reduced TLE-induced hippocampal neuronal injuries and cognition decline. Knockdown of NPY abolished nNOS depletion-induced neuroprotection and cognitive improvement in the TLE mice, suggesting that inhibition of nNOS protects against hippocampal neuronal injuries by increasing neuropeptide Y expression in TLE mice. Targeting nNOS-NPY signaling pathway in the epileptic brain might provide clinical benefit by attenuating neuronal injuries and preventing cognitive deficits in epilepsy patients.

Forecasting COVID-19 Epidemic Trends by Combining a Neural Network with Rt Estimation

On 31 December 2019, a cluster of pneumonia cases of unknown etiology was reported in Wuhan (China). The cases were declared to be Coronavirus Disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 has been defined as SARS Coronavirus 2 (SARS-CoV-2). Some countries, e.g., Italy, France, and the United Kingdom (UK), have been subjected to frequent restrictions for preventing the spread of infection, contrary to other ones, e.g., the United States of America (USA) and Sweden. The restrictions afflicted the evolution of trends with several perturbations that destabilized its normal evolution. Globally, Rt has been used to estimate time-varying reproduction numbers during epidemics. Methods: This paper presents a solution based on Deep Learning (DL) for the analysis and forecasting of epidemic trends in new positive cases of SARS-CoV-2 (COVID-19). It combined a neural network (NN) and an Rt estimation by adjusting the data produced by the output layer of the NN on the related Rt estimation. Results: Tests were performed on datasets related to the following countries: Italy, the USA, France, the UK, and Sweden. Positive case registration was retrieved between 24 February 2020 and 11 January 2022. Tests performed on the Italian dataset showed that our solution reduced the Mean Absolute Percentage Error (MAPE) by 28.44%, 39.36%, 22.96%, 17.93%, 28.10%, and 24.50% compared to other ones with the same configuration but that were based on the LSTM, GRU, RNN, ARIMA (1,0,3), and ARIMA (7,2,4) models, or an NN without applying the Rt as a corrective index. It also reduced MAPE by 17.93%, the Mean Absolute Error (MAE) by 34.37%, and the Root Mean Square Error (RMSE) by 43.76% compared to the same model without the adjustment performed by the Rt. Furthermore, it allowed an average MAPE reduction of 5.37%, 63.10%, 17.84%, and 14.91% on the datasets related to the USA, France, the UK, and Sweden, respectively.

Cariprazine Add-on in Inadequate Clozapine Response: A Report on Two Cases

Cariprazine is a novel antipsychotic drug that exerts partial agonism of dopamine D₂/D₃ receptors with preferential binding to the D₃ receptor, antagonism of 5HT_2B receptors, and partial agonism of 5HT_1A. Currently, cariprazine has shown clinical efficacy in patients with schizophrenia and with bipolar disorder, as well as adjunctive treatment in patients with Major Depressive Disorder (MDD) and drug-resistant MDD. In the present case series, we report on two patients with treatment-resistant schizophrenia and partial response to clozapine who benefit from combination with cariprazine. The effects of cariprazine combination were remarkable also concerning the adverse metabolic effects of clozapine.