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1. Nutraceuticals and phytoceuticals in the treatment of schizophrenia: a systematic review and network meta-analysis “Nutra NMA SCZ”

Author

Fornaro, Michele, Caiazza, Claudio, Billeci, Martina, Berk, Michael, Marx, Wolfgang, Balanzá-Martinez, Vicent, De Prisco, Michele, Pezone, Rosanna, De Simone, Giuseppe, Solini, Niccolò, Iasevoli, Felice, Berna, Fabrice, Fond, Guillaume, Boyer, Laurent, Carvalho, Andre Fèrrer, Dragioti, Elena, FIEDOROWICZ, Jess G., de Bartolomeis, Andrea, Correll, Christoph U., and Solmi, Marco

Published
2025
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3. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm.

Author

Jiang, Yuchao, Luo, Cheng, Wang, Jijun, Palaniyappan, Lena, Chang, Xiao, Xiang, Shitong, Zhang, Jie, Duan, Mingjun, Huang, Huan, Gaser, Christian, Nemoto, Kiyotaka, Miura, Kenichiro, Hashimoto, Ryota, Westlye, Lars, Richard, Genevieve, Fernandez-Cabello, Sara, Parker, Nadine, Andreassen, Ole, Kircher, Tilo, Nenadić, Igor, Stein, Frederike, Thomas-Odenthal, Florian, Teutenberg, Lea, Usemann, Paula, Dannlowski, Udo, Hahn, Tim, Grotegerd, Dominik, Meinert, Susanne, Lencer, Rebekka, Tang, Yingying, Zhang, Tianhong, Li, Chunbo, Yue, Weihua, Zhang, Yuyanan, Yu, Xin, Zhou, Enpeng, Lin, Ching-Po, Tsai, Shih-Jen, Rodrigue, Amanda, Glahn, David, Pearlson, Godfrey, Blangero, John, Karuk, Andriana, Pomarol-Clotet, Edith, Salvador, Raymond, Fuentes-Claramonte, Paola, Garcia-León, María, Spalletta, Gianfranco, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Cheng, Jingliang, Liu, Zhening, Yang, Jie, Gonul, Ali, Uslu, Ozgul, Burhanoglu, Birce, Uyar Demir, Aslihan, Rootes-Murdy, Kelly, Calhoun, Vince, Sim, Kang, Green, Melissa, Quidé, Yann, Chung, Young, Kim, Woo-Sung, Sponheim, Scott, Demro, Caroline, Ramsay, Ian, Iasevoli, Felice, de Bartolomeis, Andrea, Barone, Annarita, Ciccarelli, Mariateresa, Brunetti, Arturo, Cocozza, Sirio, Pontillo, Giuseppe, Tranfa, Mario, Park, Min, Kirschner, Matthias, Georgiadis, Foivos, Kaiser, Stefan, Van Rheenen, Tamsyn, Rossell, Susan, Hughes, Matthew, Woods, William, Carruthers, Sean, Sumner, Philip, Ringin, Elysha, Spaniel, Filip, Skoch, Antonin, Tomecek, David, Homan, Philipp, Homan, Stephanie, Omlor, Wolfgang, Cecere, Giacomo, Nguyen, Dana, Preda, Adrian, Thomopoulos, Sophia, Jahanshad, Neda, Cui, Long-Biao, and Yao, Dezhong

Subjects
Humans, Schizophrenia, Male, Female, Adult, Algorithms, Magnetic Resonance Imaging, Gray Matter, Machine Learning, Middle Aged, Brain, Cross-Sectional Studies, Europe, Neuroimaging, Reproducibility of Results, North America, Hippocampus
Abstract

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Published
2024

4. Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium

Author

Lamsma, Jelle, Raine, Adrian, Kia, Seyed M, Cahn, Wiepke, Arold, Dominic, Banaj, Nerisa, Barone, Annarita, Brosch, Katharina, Brouwer, Rachel, Brunetti, Arturo, Calhoun, Vince D, Chew, Qian H, Choi, Sunah, Chung, Young-Chul, Ciccarelli, Mariateresa, Cobia, Derin, Cocozza, Sirio, Dannlowski, Udo, Dazzan, Paola, de Bartolomeis, Andrea, Di Forti, Marta, Dumais, Alexandre, Edmond, Jesse T, Ehrlich, Stefan, Evermann, Ulrika, Flinkenflügel, Kira, Georgiadis, Foivos, Glahn, David C, Goltermann, Janik, Green, Melissa J, Grotegerd, Dominik, Guerrero-Pedraza, Amalia, Ha, Minji, Hong, Elliot L, Pol, Hilleke Hulshoff, Iasevoli, Felice, Kaiser, Stefan, Kaleda, Vasily, Karuk, Andriana, Kim, Minah, Kircher, Tilo, Kirschner, Matthias, Kochunov, Peter, Kwon, Jun Soo, Lebedeva, Irina, Lencer, Rebekka, Marques, Tiago R, Meinert, Susanne, Murray, Robin, Nenadić, Igor, Nguyen, Dana, Pearlson, Godfrey, Piras, Fabrizio, Pomarol-Clotet, Edith, Pontillo, Giuseppe, Potvin, Stéphane, Preda, Adrian, Quidé, Yann, Rodrigue, Amanda, Rootes-Murdy, Kelly, Salvador, Raymond, Skoch, Antonin, Sim, Kang, Spalletta, Gianfranco, Spaniel, Filip, Stein, Frederike, Thomas-Odenthal, Florian, Tikàsz, Andràs, Tomecek, David, Tomyshev, Alexander, Tranfa, Mario, Tsogt, Uyanga, Turner, Jessica A, van Erp, Theo GM, van Haren, Neeltje EM, van Os, Jim, Vecchio, Daniela, Wang, Lei, Wroblewski, Adrian, and Nickl-Jockschat, Thomas

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Schizophrenia, Brain Disorders, Neurosciences, Biomedical Imaging, Serious Mental Illness, Mental Health, Mental Illness, Mental health
Abstract

BACKGROUND: Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. METHODS: This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. RESULTS: Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. CONCLUSIONS: This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.

Published
2024

6. Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia

Author

Jiang, Yuchao, Luo, Cheng, Wang, Jijun, Palaniyappan, Lena, Chang, Xiao, Xiang, Shitong, Zhang, Jie, Duan, Mingjun, Huang, Huan, Gaser, Christian, Nemoto, Kiyotaka, Miura, Kenichiro, Hashimoto, Ryota, Westlye, Lars T, Richard, Genevieve, Fernandez-Cabello, Sara, Parker, Nadine, Andreassen, Ole A, Kircher, Tilo, Nenadić, Igor, Stein, Frederike, Thomas-Odenthal, Florian, Teutenberg, Lea, Usemann, Paula, Dannlowski, Udo, Hahn, Tim, Grotegerd, Dominik, Meinert, Susanne, Lencer, Rebekka, Tang, Yingying, Zhang, Tianhong, Li, Chunbo, Yue, Weihua, Zhang, Yuyanan, Yu, Xin, Zhou, Enpeng, Lin, Ching-Po, Tsai, Shih-Jen, Rodrigue, Amanda L, Glahn, David, Pearlson, Godfrey, Blangero, John, Karuk, Andriana, Pomarol-Clotet, Edith, Salvador, Raymond, Fuentes-Claramonte, Paola, Garcia-León, María Ángeles, Spalletta, Gianfranco, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Cheng, Jingliang, Liu, Zhening, Yang, Jie, Gonul, Ali Saffet, Uslu, Ozgul, Burhanoglu, Birce Begum, Demir, Aslihan Uyar, Rootes-Murdy, Kelly, Calhoun, Vince D, Sim, Kang, Green, Melissa, Quidé, Yann, Chung, Young Chul, Kim, Woo-Sung, Sponheim, Scott R, Demro, Caroline, Ramsay, Ian S, Iasevoli, Felice, de Bartolomeis, Andrea, Barone, Annarita, Ciccarelli, Mariateresa, Brunetti, Arturo, Cocozza, Sirio, Pontillo, Giuseppe, Tranfa, Mario, Park, Min Tae M, Kirschner, Matthias, Georgiadis, Foivos, Kaiser, Stefan, Van Rheenen, Tamsyn E, Rossell, Susan L, Hughes, Matthew, Woods, William, Carruthers, Sean P, Sumner, Philip, Ringin, Elysha, Spaniel, Filip, Skoch, Antonin, Tomecek, David, Homan, Philipp, Homan, Stephanie, Omlor, Wolfgang, Cecere, Giacomo, Nguyen, Dana D, Preda, Adrian, Thomopoulos, Sophia, Jahanshad, Neda, Cui, Long-Biao, and Yao, Dezhong

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Machine Learning and Artificial Intelligence, Mental Illness, Clinical Research, Brain Disorders, Serious Mental Illness, Neurosciences, Schizophrenia, Mental Health, Behavioral and Social Science, Biomedical Imaging, Mental health, Good Health and Well Being, ENIGMA, artificial intelligence, brain gray matter, schizophrenia, structural MRI, subtype
Abstract

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Published
2023

17. Cooling and lubrication technologies for machining advanced alloys

Author

De Bartolomeis, Andrea, Shokrani Chaharsooghi, Alborz, and Newman, Stephen

Subjects
Machining, MQL, EHDA MQL, Inconel 718, Milling
Abstract

High temperatures generated during machining processes reduce productivity, cause increased cutting tool wear and damage the machined surfaces. Cutting fluids are used to reduce the cutting temperature, provide lubrication, guarantee chip flushing and chemically protect the machined surface. In the industrial practice, flood cooling is the technique of immersing the entire cutting zone with cutting fluids that provides significant increases in cutting tool life and improved surface finish. However, cutting fluids are expensive and pollutants. Machining without these fluids, also known as dry machining, can be implemented for easy-to-cut materials. This is not the case with difficult-to-cut alloys that still require an abundance of cutting fluids to be machined. Today, the machining of Inconel 718 and Ti-6Al-4V represent two of the greatest challenges faced by the machining industry. More than 50% of the modern aeroengines are made from Inconel 718 and the machining of those advanced alloys using flood cooling conditions is not environmentally conscious nor economically sustainable. To machine Inconel 718 and Ti-6Al-4V alloys, as an alternative to flood cooling, Minimum Quantity Lubrication (MQL) has been shown to be most promising. Despite providing significant improvements when compared with other alternatives, machining performance with MQL is still far from the advantages provided by cutting fluids in flood cooling conditions. The research reported in this thesis explores novel nozzle designs and systems, investigating the feasibility of applying EHDA MQL in milling Inconel 718 and Ti-6Al-4V. EHDA MQL is a novel technique that can improve MQL performance and eliminate the use of water-based cutting fluids. The novelty is the development of a new MQL system called Electrohydrodynamic Atomization for Minimum Quantity Lubrication (EHDA MQL) that provides charged oil based on a two-electrode configuration and testing it on the machining of Inconel 718 and Ti-6Al-4V. Results show that this new technology for EHDA MQL can provide an extension of 52% in tool life when compared with conventional MQL in end milling Inconel 718. The extension in tool life observed when machining Ti-6Al-4V was over 2200% in comparison with conventional flood cooling application. The results showed that tool life is about 170 min when high-speed machining Ti-6Al-4V at 120 m/min. This poses a milestone in the removal of cutting fluids from manufacturing. The research revealed that EHDA MQL has provided significant advantages in the case of Inconel 718 and Ti-6Al-4V over conventional MQL.

Published
2021

26. Treatment-resistant schizophrenia: Addressing white matter integrity, intracortical glutamate levels, clinical and cognitive profiles between early- and adult-onset patients

Author

Matrone, Marta, Kotzalidis, Georgios D., Romano, Andrea, Bozzao, Alessandro, Cuomo, Ilaria, Valente, Francesca, Gabaglio, Chiara, Lombardozzi, Ginevra, Trovini, Giada, Amici, Emanuela, Perrini, Filippo, De Persis, Simone, Iasevoli, Felice, De Filippis, Sergio, and de Bartolomeis, Andrea

Published
2022
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27. Factors associated with lifetime suicide attempts in bipolar disorder: results from an Italian nationwide study

Author

Buoli, Massimiliano, Cesana, Bruno Mario, Bolognesi, Simone, Fagiolini, Andrea, Albert, Umberto, Di Salvo, Gabriele, Maina, Giuseppe, de Bartolomeis, Andrea, Pompili, Maurizio, Palumbo, Claudia, Bondi, Emi, Steardo, Jr, Luca, De Fazio, Pasquale, Amore, Mario, Altamura, Mario, Bellomo, Antonello, Bertolino, Alessandro, Di Nicola, Marco, Di Sciascio, Guido, Fiorillo, Andrea, Sacchetti, Emilio, Sani, Gabriele, Siracusano, Alberto, Di Lorenzo, Giorgio, Tortorella, Alfonso, Altamura, A. Carlo, and Dell’Osso, Bernardo

Published
2022
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35. Design and testing of a high power piezo pump for hydraulic actuation.

Author

Sell, Nathan, Feehally, Tom, Plummer, Andrew, Wilson, Peter, du Bois, Jonathan, Johnston, Nigel, Roesner, Jens, De Bartolomeis, Andrea, and Love, Tom

Subjects
HYDRAULIC cylinders, POWER electronics, SINE waves, ACTUATORS, HYDRAULICS
Abstract

Traditional valve-controlled hydraulic cylinders are usually very inefficient due to power loss through the control valve. An efficient alternative architecture is to distribute power electrically rather than hydraulically to a group of cylinders and drive each cylinder via individual servomotor-driven pumps. This arrangement is called electrohydrostatic actuation. Such actuators are currently available for power ratings of several hundred watts or greater, but not in the sub-100 W range. This paper details the design, simulation and testing of a piezopump which is intended to address this gap. The motivation is for aerospace applications, and in particular accessory actuators used in the landing gear system. The 10–100 W range is a high-power output for a piezopump, and to achieve this a novel design using disc-style reed valves was developed to allow pumping frequencies above 1 kHz. These high frequencies necessitated the development of custom power electronics capable of delivering 950 V peak-peak sine wave excitation to a largely capacitive load. Experimental results show that the piezopump is capable of delivering over 30 W of hydraulic power, and at no-load can deliver up to 2 L/min of flow at 1250 Hz. Future development includes a transition to multi-cylinder pumps, and improved reed-valve modelling to improve the accuracy of simulated performance. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Symptom Severity Changes in Obsessive-Compulsive Patients during COVID-19 Pandemic Are Associated with Shorter Illness Duration and Benzodiazepine Use: Possible Evolutionary Advantage of a Psychiatric Disorder

Author

D’Urso, Giordano, primary, Magliacano, Alfonso, additional, Manzo, Marco, additional, Pomes, Mattia Vittorio, additional, Iuliano, Carla, additional, Iasevoli, Felice, additional, Dell'Osso, Bernardo, additional, and De Bartolomeis, Andrea, additional

Published
2024
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41. Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium

Author

Lamsma, Jelle, primary, Raine, Adrian, additional, Kia, Seyed M., additional, Cahn, Wiepke, additional, Arold, Dominic, additional, Banaj, Nerisa, additional, Barone, Annarita, additional, Brosch, Katharina, additional, Brouwer, Rachel, additional, Brunetti, Arturo, additional, Calhoun, Vince D., additional, Chew, Qian H., additional, Choi, Sunah, additional, Chung, Young-Chul, additional, Ciccarelli, Mariateresa, additional, Cobia, Derin, additional, Cocozza, Sirio, additional, Dannlowski, Udo, additional, Dazzan, Paola, additional, de Bartolomeis, Andrea, additional, Forti, Marta Di, additional, Dumais, Alexandre, additional, Edmond, Jesse T., additional, Ehrlich, Stefan, additional, Evermann, Ulrika, additional, Flinkenflügel, Kira, additional, Georgiadis, Foivos, additional, Glahn, David C., additional, Goltermann, Janik, additional, Green, Melissa J., additional, Grotegerd, Dominik, additional, Guerrero-Pedraza, Amalia, additional, Ha, Minji, additional, Hong, Elliot L., additional, Pol, Hilleke Hulshoff, additional, Iasevoli, Felice, additional, Kaiser, Stefan, additional, Kaleda, Vasily, additional, Karuk, Andriana, additional, Kim, Minah, additional, Kircher, Tilo, additional, Kirschner, Matthias, additional, Kochunov, Peter, additional, Kwon, Jun Soo, additional, Lebedeva, Irina, additional, Lencer, Rebekka, additional, Marques, Tiago R., additional, Meinert, Susanne, additional, Murray, Robin, additional, Nenadić, Igor, additional, Nguyen, Dana, additional, Pearlson, Godfrey, additional, Piras, Fabrizio, additional, Pomarol-Clotet, Edith, additional, Pontillo, Giuseppe, additional, Potvin, Stéphane, additional, Preda, Adrian, additional, Quidé, Yann, additional, Rodrigue, Amanda, additional, Rootes-Murdy, Kelly, additional, Salvador, Raymond, additional, Skoch, Antonin, additional, Sim, Kang, additional, Spalletta, Gianfranco, additional, Spaniel, Filip, additional, Stein, Frederike, additional, Thomas-Odenthal, Florian, additional, Tikàsz, Andràs, additional, Tomecek, David, additional, Tomyshev, Alexander, additional, Tranfa, Mario, additional, Tsogt, Uyanga, additional, Turner, Jessica A., additional, van Erp, Theo G. M., additional, van Haren, Neeltje E. M., additional, van Os, Jim, additional, Vecchio, Daniela, additional, Wang, Lei, additional, Wroblewski, Adrian, additional, and Nickl-Jockschat, Thomas, additional

Published
2024
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49. Decreased free D-aspartate levels in the blood serum of patients with schizophrenia.

Author

Garofalo, Martina, De Simone, Giuseppe, Motta, Zoraide, Nuzzo, Tommaso, De Grandis, Elisa, Bruno, Claudio, Boeri, Silvia, Riccio, Maria Pia, Pastore, Lucio, Bravaccio, Carmela, Iasevoli, Felice, Salvatore, Francesco, Pollegioni, Loredano, Errico, Francesco, de Bartolomeis, Andrea, and Usiello, Alessandro

Subjects
PEOPLE with schizophrenia, AUTISM spectrum disorders, METHYL aspartate receptors, AMINO acids, ANTI-NMDA receptor encephalitis
Abstract

Introduction: Schizophrenia (SCZ) and autism spectrum disorder (ASD) are neurodevelopmental diseases characterized by different psychopathological manifestations and divergent clinical trajectories. Various alterations at glutamatergic synapses have been reported in both disorders, including abnormal NMDA and metabotropic receptor signaling. Methods: We conducted a bicentric study to assess the blood serum levels of NMDA receptors-related glutamatergic amino acids and their precursors, including L-glutamate, L-glutamine, D-aspartate, L-aspartate, L-asparagine, Dserine, L-serine and glycine, in ASD, SCZ patients and their respective control subjects. Specifically, the SCZ patients were subdivided into treatment-resistant and non-treatment-resistant SCZ patients, based on their responsivity to conventional antipsychotics. Results: D-serine and D-aspartate serum reductions were found in SCZ patients compared to controls. Conversely, no significant differences between cases and controls were found in amino acid concentrations in the two ASD cohorts analyzed. Discussion: This result further encourages future research to evaluate the predictive role of selected D-amino acids as peripheral markers for SCZ pathophysiology and diagnosis. [ABSTRACT FROM AUTHOR]

Published
2024
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