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BACKGROUND: Studies have demonstrated that exercise can mitigate the intensity of menstrual pain in primary dysmenorrhea, but the most effective type of exercise remains unclear. The objective of this systematic review and network meta-analysis was to evaluate the effectiveness of different exercise regimens in reducing pain associated with primary dysmenorrhoea. METHODS: Randomized controlled trials investigating the relationship between menstrual pain and exercise were selected from major electronic databases until February 2, 2024. The primary outcome was the effect of exercise on pain intensity measured by the mean difference on a 10-cm visual analogue scale at 4 and 8 weeks after intervention. The secondary outcome was the difference in risk of dropout at 8 weeks. The study protocol was registered as INPLASY202330050. RESULTS: This systematic review and network meta-analysis included 29 randomized controlled trials, which involved 1808 participants with primary dysmenorrhea. Exercise interventions included relaxation exercise, strength training, aerobic activity, yoga, mixed exercise, and the Kegel maneuver. Relaxation exercise was the most effective in reducing menstrual pain in 4 weeks (- 3.56; 95% confidence interval: - 5.03 to - 2.08). All exercise interventions were effective in reducing menstrual pain at 8 weeks, with reductions ranging from - 3.87 (95% CI - 5.51 to - 2.22) for relaxation exercise to - 2.75 (95% CI - 4.00 to - 1.51) for yoga, compared to the control group. Relaxation exercises were found to have a significantly lower dropout risk (- 0.11; 95% CI - 0.20 to 0.02), while none of the exercise types was associated with a higher dropout risk than the control group. CONCLUSION: All exercise interventions were effective in reducing menstrual pain in primary dysmenorrhea after 8 weeks of intervention. However, relaxation exercise was found to be the most effective intervention at 4 and 8 weeks and had the lowest risk of dropout.
This analysis aimed to see how effective different types of exercise are in reducing pain in women with primary dysmenorrhea. The researchers looked at 29 studies involving 1808 participants and evaluated six different types of exercise. The main outcome was the effect of pain reduction after 4 and 8 weeks of exercise. The researchers found that all types of exercise were effective in reducing menstrual pain after 8 weeks, with relaxation exercises being the most effective at both 4 and 8 weeks. None of the exercise types were associated with higher dropout risks than the control group, and relaxation exercise had a lower dropout risk than the other types of exercise.
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OBJECTIVE: This meta-analysis aimed to ascertain the efficacy of non-invasive brain stimulation (NIBS)-comprising repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS)-for depression in traumatic brain injury (TBI) patients. METHODS: Comprehensive searches were conducted in PubMed, Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials up to 28 January 2023. Random-effects models assessed the treatment effects, and heterogeneity was evaluated through I2 statistics and funnel plot inspection. RESULTS: From 10 trials (234 participants; 8 rTMS, 2 tDCS), NIBS was found significantly more effective than sham in alleviating depressive symptoms (SMD: 0.588, 95% CI: 0.264-0.912; p < 0.001). rTMS, specifically, showed higher efficacy (SMD: 0.707, 95% CI: 0.306-1.108; p = 0.001) compared to sham, whereas tDCS outcomes were inconclusive (SMD: 0.271, 95% CI: -0.230 to 0.771; p = 0.289). Meta-regression found no correlation with the number of sessions, treatment intensity, or total dose. Notably, while post-treatment effects were significant, they diminished 1-2 months post intervention. Adverse events associated with NIBS were minimal, with no severe outcomes like seizures and suicide reported. CONCLUSIONS: rTMS emerged as a potent short-term intervention for depression in TBI patients, while tDCS findings remained equivocal. The long-term efficacy of NIBS is yet to be established, warranting further studies. The low adverse event rate reaffirms NIBS's potential safety.
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Introduction: The effects of repetitive transcranial magnetic stimulation (rTMS) on the left dorsolateral prefrontal cortex (DLPFC) in patients with major depressive disorder (MDD) have been proved to have antidepressant effects. However, the absence of biomarkers to assess treatment response remains a challenge. This research aims to explore the relationship between frontal lobe activity, measured using near infrared spectroscopy (NIRS), and changes in symptoms among MDD patients following rTMS treatment. Methods: A total of 26 MDD patients underwent 20 sessions of 10 Hz rTMS targeting the left DLPFC. NIRS was used to measure frontal lobe activity during a verbal fluency test at baseline, after 10 rTMS sessions, and after 20 rTMS sessions. Responders were defined as individuals with more than a 50% reduction in symptoms based on the 21-item Hamilton Depression Rating Scale after 20 rTMS sessions. Results: Among the 14 responders, an increase in frontal lobe activity was significantly correlated with improvements in depressive symptoms following 10 (p = 0.0001) and 20 rTMS sessions (p = 0.007). Additionally, frontal lobe activity after 10 rTMS sessions was significantly associated with symptom improvement after 20 sessions (p = 0.001). These associations were not observed among non-responders. Conclusion: The findings from this study indicate distinct patterns of frontal lobe activity between responders and non-responders to rTMS treatment, suggesting that NIRS has the potential to serve as a biomarker for monitoring treatment response in MDD patients undergoing rTMS.
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BACKGROUND This report is of a 30-year-old woman with an 8-week history of anxiety, depression, insomnia, and mild cognitive impairment following COVID-19 infection, who responded to accelerated bilateral theta-burst transcranial magnetic stimulation (TBS) over the prefrontal cortex. CASE REPORT A previously healthy 30-year-old woman visited our psychiatric clinic for symptoms including anxiety, depression, insomnia, and brain fog (mild cognitive impairment) for more than 8 weeks after being diagnosed with COVID-19 on May 9, 2022. Continuous TBS of the right dorsolateral prefrontal cortex (DLPFC), followed by intermittent TBS of the left DLPFC, was performed twice daily over 5 days for a total of 10 sessions. The Beck Depression Inventory (BDI), Hamilton Depression Rating Scale (HAMD), Beck Anxiety Inventory (BAI), Pittsburgh Sleep Quality Index (PSQI), and subsets of the Wechsler Memory Scale (WMS)-Third Edition were administered at baseline and at the end of treatment. After 10 sessions of treatment, her BAI, BDI, HAMD, PSQI, WMS-Logical Memory, WMS-Faces, WMS-Verbal Paired Associates, and WMS-Family Pictures scores had improved from 4, 18, 10, 14, 8, 10, 12, and 8, respectively, to 0, 7, 1, 10, 15, 15, 15, and 10, respectively. CONCLUSIONS Accelerated TBS over the bilateral DLPFC may ameliorate long-COVID-associated neuropsychiatric symptoms. Additional trials are warranted to evaluate the effect of neuropsychiatric symptoms following COVID-19.
Subject(s)
COVID-19 , Cognitive Dysfunction , Sleep Initiation and Maintenance Disorders , Female , Humans , Adult , Sleep Initiation and Maintenance Disorders/etiology , Sleep Initiation and Maintenance Disorders/therapy , Depression/etiology , Transcranial Magnetic Stimulation , Post-Acute COVID-19 Syndrome , COVID-19/complications , Anxiety/etiology , Prefrontal Cortex/physiology , Cognitive Dysfunction/etiologyABSTRACT
Background: Theta-burst transcranial magnetic stimulation has demonstrated promising effectiveness as treatment for post-traumatic stress disorder (PTSD) and depression. However, the effect of accelerated theta-burst stimulation (TBS) in comorbid with PTSD and depression remains unknown. Case presentation: We report a case of a 25-year-old woman with PTSD and depression whose symptoms markedly improved after continuous TBS of the right dorsolateral prefrontal cortex (DLPFC) and intermittent TBS (iTBS) over the left DLPFC, and then with 20 min break before the 2nd iTBS session. Conclusions: Accelerated TBS over the bilateral DLPFC may improve severe PTSD and depression. Accelerated TBS may have more improvement of depression symptoms than PTSD symptoms. Further trials are warranted to investigate the effect and safety for patients with complicated PTSD and depression.
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Coenzyme Q10 (CoQ10) is a popular nutritional supplement, an antioxidant and an essential component of the mitochondrial electron transport chain. Several clinical studies have suggested that fatigue can be reduced by antioxidant supplementation. However, the data on this topic has been sparse to date. Hence, we conducted this meta-analysis with the aim of investigating the effectiveness of fatigue reduction via CoQ10 supplementation. More specifically, we searched electronic databases for randomized controlled trials (RCTs) published from the database inception to January 2022. A random effects model was implemented to conduct the meta-analysis among 13 RCTs (with a total of 1,126 participants). As compared with the placebo groups evaluated in each RCT, the CoQ10 group showed a statistically significant reduction in fatigue scores (Hedges' g = -0.398, 95% confidence interval = -0.641 to -0.155, p = 0.001). The directions of the treatment effects were consistent between the healthy and diseased participants. Compared with the placebo group, the effect of reducing fatigue was statistically significant in the subgroup using the CoQ10-only formulation but not in the subgroup using CoQ10 compounds. The results of our meta-regression demonstrate that increases in the daily dose (coefficient = -0.0017 per mg, p < 0.001) and treatment duration (coefficient = -0.0042 per day, p = 0.007) of CoQ10 supplementation were correlated with greater fatigue reduction. There was only one adverse (gastrointestinal) event in the 602 participants who underwent the CoQ10 intervention. Based on the results of this meta-analysis, we conclude that CoQ10 is an effective and safe supplement for reducing fatigue symptoms. Systematic Review Registration: https://inplasy.com/inplasy-2022-1-0113/, identifier INPLASY202210113.
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In this research, a microfluid-based extended gate field-effect transistor (EGFET) biosensor with an on-chip sensing window (OCSW) was fabricated. The detection window was composed of six metal layers, and a ruthenium dioxide (RuO2) film was spattered on the surface and functionalized with lactase to detect lactic acid (LA). To detect LA in a more diversified way, a microfluidic system was integrated with the biosensor. Moreover, a special package was used to seal the sensing window and microfluidic tube and insulate it from other parts to prevent water molecule invasion and chip damage. The sensitivity analysis of the EGFET biosensor was studied by a semiconductor parameter analyzer (SPA). The static and dynamic measurements of the EGFET with sensing windows on a chip were analyzed. The sensing characteristics of the EGFET biosensor were verified by the experimental results. The proposed biosensor is suitable for wearable applications due to the advantages of its low weight, low voltage, and simple manufacturing process.
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Biosensing Techniques , Microfluidics , Biosensing Techniques/methods , Lactic AcidABSTRACT
OBJECTIVE: Dementia is a progressive neurocognitive disorder that currently affects approximately 50 million people globally and causes a heavy burden for their families and societies. This study analyzed mobile apps for dementia care in different languages and during the COVID-19 pandemic. METHODS: We searched PubMed, Cochrane Collaboration Central Register of Con-trolled Clinical Trials, Cochrane Systematic Reviews, Google Play Store, Apple App Store, and Huawei App Store for mobile applications for dementia care. The Mobile Application Rating Scale (MARS) was used to assess the quality of applications. RESULTS: We included 99 apps for dementia care. No significant difference in MARS scores was noted between the two language apps (Overall MARS: English: 3.576 ± 0.580, Chinese: 3.569 ± 0.746, p = 0.962). In the subscale analysis, English apps had higher scores of perceived impact than Chinese apps but these were not significant (2.654 ± 1.372 vs. 2.000 ± 1.057, p = 0.061). (2) Applications during the COVID-19 pandemic had higher MARS scores than those before the COVID-19 pandemic but these were not significant (during the COVID-19 pandemic: 3.722 ± 0.416; before: 3.699 ± 0.615, p = 0.299). In the sub-scale analysis, apps during the COVID-19 pandemic had higher scores of engagement than apps before the COVID-19 pandemic but these were not significant (3.117 ± 0.594 vs. 2.698 ± 0.716, p = 0.068). CONCLUSIONS: Our results revealed that there is a minor but nonsignificant difference between different languages and during the COVID-19 pandemic. Further cooperation among dementia professionals, technology experts, and caregivers is warranted to provide evidence-based and user-friendly information to meet the needs of users.
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Background: Repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic potential for treating patients with methamphetamine use disorder (MUD). However, the most effective target and stimulation frequency of rTMS for treating MUD remains unclear. This meta-analysis explored the effect of rTMS on MUD. Methods: In this study, PubMed, Cochrane Systematic Reviews, and the Cochrane Collaboration Central Register of Controlled Clinical Trials were searched electronically for double-blind randomized controlled trials that used rTMS for treating MUD. We used published trials to investigate the efficacy of rTMS in MUD up to March 5, 2022, and pooled studies using a random-effect model to compare rTMS treatment effects. Patients who were diagnosed with MUD according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders were recruited. Clinical craving scores between baseline and after rTMS were compared using the standardized mean difference (SMD) with 95% confidence intervals (CIs). The heterogeneity of the included trials was evaluated through a visual inspection of funnel plots and the I2 statistic. Results: We identified seven trials with 462 participants with MUD that met the inclusion criteria. All the studies evaluated craving scores, with rTMS demonstrating a more significant effect than the sham treatment on reducing craving scores (SMD = 0.983, CI = 0.620-1.345, p ≤ 0.001). A subgroup meta-analysis revealed that intermittent theta-burst stimulation (iTBS) had a greater positive effect than 10-Hz rTMS. A metaregression revealed that the SMDs increased with the increase in baseline craving scores, whereas they decreased with the increase in the proportion of men and duration of abstinence. Conclusion: The meta-analysis suggests that rTMS may be associated with treatment effect on craving symptoms in patients with MUD. iTBS may have a greater positive effect on craving reduction than 10-z rTMS.
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Repetitive transcranial magnetic stimulation (rTMS) has been widely used as a promising therapy for tinnitus. However, the exact target and stimulation sequence of rTMS that is most effective for treating tinnitus remains unclear. Here, we report a case of a 62-year-old man with treatment-refractory tinnitus and depression whose symptoms markedly improved after undergoing low-frequency rTMS over the right-side dorsolateral prefrontal cortex and left auditory cortex area. Our report indicates that low-frequency rTMS treatment that stimulates multiple brain regions sequentially is feasible and may clinically benefit patients with tinnitus and depression.
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BACKGROUND: During the COVID-19 pandemic, the use of telemedicine as a way to reduce COVID-19 infections was noted and consequently deregulated. However, the degree of telemedicine regulation varies from country to country, which may alter the widespread use of telemedicine. This study aimed to clarify the telepsychiatry regulations for each collaborating country/region before and during the COVID-19 pandemic. METHODS: We used snowball sampling within a global network of international telepsychiatry experts. Thirty collaborators from 17 different countries/regions responded to a questionnaire on barriers to the use and implementation of telepsychiatric care, including policy factors such as regulations and reimbursement at the end of 2019 and as of May 2020. RESULTS: Thirteen of 17 regions reported a relaxation of regulations due to the pandemic; consequently, all regions surveyed stated that telepsychiatry was now possible within their public healthcare systems. In some regions, restrictions on prescription medications allowed via telepsychiatry were eased, but in 11 of the 17 regions, there were still restrictions on prescribing medications via telepsychiatry. Lower insurance reimbursement amounts for telepsychiatry consultations v. in-person consultations were reevaluated in four regions, and consequently, in 15 regions telepsychiatry services were reimbursed at the same rate (or higher) than in-person consultations during the COVID-19 pandemic. CONCLUSIONS: Our results confirm that, due to COVID-19, the majority of countries surveyed are altering telemedicine regulations that had previously restricted the spread of telemedicine. These findings provide information that could guide future policy and regulatory decisions, which facilitate greater scale and spread of telepsychiatry globally.
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COVID-19 , Psychiatry , Telemedicine , Humans , Telemedicine/methods , Pandemics , Referral and ConsultationABSTRACT
Curcumin is a polyphenol with strong antioxidant and anti-inflammatory effects that has been shown to be effective in ameliorating cognitive decline in animal studies. However, its clinical effectiveness is inconclusive, and relevant gastrointestinal adverse events (AEs) have been reported. The aim of this meta-analysis was to summarize the existing evidence from randomized controlled trials (RCTs) of effects of curcumin on overall cognitive function, individual cognitive domains, and gastrointestinal AE. The study includes 8 RCTs and 389 participants. A random-effects model was used for the meta-analysis. Compared with the placebo group, the curcumin group was associated with an improvement in working memory (Hedges' g = 0.396, 95% confidence interval (CI) = 0.078 to 0.714, p = 0.015) and a borderline benefit in processing speed (Hedges' g = 0.303, 95% CI = -0.013 to 0.619, p = 0.06). In the domains of language, episodic memory/visual learning, verbal memory, cognitive flexibility/problem solving, and overall cognitive function, no significant difference existed for the comparison between the curcumin and placebo groups. The curcumin group had a significantly higher risk of gastrointestinal AEs than the placebo group (odds ratio = 3.019, 95% CI = 1.118 to 8.150, p = 0.029). In the future, the effects of curcumin on working memory, processing speed, and gastrointestinal AE should be further investigated.
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Multiple N-methyl-D-aspartate (NMDA) receptor enhancing agents have had promising effects on cognition among patients with dementia. However, the results remain inconsistent. This exploratory meta-analysis investigated the effectiveness of NMDA receptor enhancing agents for cognitive function. PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews were searched for randomized controlled trials (RCTs). Controlled trials assessing add-on NMDA receptor enhancing agent treatment in patients with dementia and using cognition rating scales were eligible and pooled using a random-effect model for comparisons. The standardized mean difference (SMD) was calculated in each study from the effect size; positive values indicated that NMDA receptor enhancing agent treatment improved cognitive function. Funnel plots and the I2 statistic were evaluated for statistical heterogeneity. Moderators were evaluated using meta-regression. We identified 14 RCTs with 2224 participants meeting the inclusion criteria. Add-on NMDA receptor enhancing agents had small positive significant effects on overall cognitive function among patients with dementia (SMD = 0.1002, 95% CI 0.0105-0.1900, P = 0.02860). Subgroup meta-analysis showed patients with Alzheimer's Disease and trials using the Alzheimer Disease Assessment Scale-cognitive subscale as the primary outcome had small positive significant effects (SMD = 0.1042, 95% CI 0.0076-0.2007, P = 0.03451; SMD = 0.1267, 95% CI 0.0145-0.2388, P = 0.2686). This exploratory meta-analysis showed a very small, positive, and significant effect on overall cognition function in patients with dementia. Studies with larger samples are needed to evaluate different cognitive domains and phases of dementia.
Subject(s)
Cognition Disorders/drug therapy , Dementia/complications , Randomized Controlled Trials as Topic/statistics & numerical data , Receptors, N-Methyl-D-Aspartate/agonists , Cognition Disorders/etiology , Cognition Disorders/pathology , HumansABSTRACT
ABSTRACT: This study evaluated the severe hepatic outcome (SHO) in patients with schizophrenia and viral hepatitis who received antipsychotics.Using the nationwide Taiwan National Health Insurance Research Database, patients first diagnosed with schizophrenia between 2002 and 2013 were identified. Patients diagnosed with schizophrenia who had viral hepatitis, including hepatitis B virus (HBV) or hepatitis C virus (HCV), were designated as the viral hepatitis group. A control group without viral hepatitis was matched for age, sex, and index year in a 2:1 ratio. Patients with severe hepatic outcomes before enrollment were excluded. The 2 cohorts were observed until December 31, 2013. The primary endpoint was occurrence of a SHO, including liver cancer, liver failure, liver decompensation, or transplantation.Among the 16,365 patients newly diagnosed with schizophrenia between January 2002 and December 2013, we identified 614 patients with viral hepatitis and 1228 matched patients without viral hepatitis. Of these 1842 patients, 41 (2.22%) developed SHOs, including 26 (4.23%) in the viral hepatitis group and 15 (1.22%) in the control group, during the mean follow-up period of 3.71â±â2.49âyears. Cox proportional hazard analysis indicated that the SHO risk increased by 3.58 (95% confidence interval [CI]: 1.859-6.754; Pâ<â.001) in patients with schizophrenia and viral hepatitis. Moreover, patients with schizophrenia having HCV had a higher SHO risk than those without viral hepatitis (hazard ratio: 5.07, 95% CI: 1.612-15.956; Pâ<â.0001). Patients having both schizophrenia and viral hepatitis, especially HCV, had a higher risk of SHOs.
Subject(s)
Antipsychotic Agents/adverse effects , Hepatitis B/psychology , Hepatitis C/psychology , Paliperidone Palmitate/therapeutic use , Schizophrenia/drug therapy , Adult , Antipsychotic Agents/therapeutic use , Case-Control Studies , Female , Follow-Up Studies , Hepacivirus/isolation & purification , Hepatitis B/complications , Hepatitis B/epidemiology , Hepatitis B virus/isolation & purification , Hepatitis C/complications , Hepatitis C/epidemiology , Humans , Liver Failure/chemically induced , Liver Failure/metabolism , Liver Neoplasms/chemically induced , Liver Neoplasms/metabolism , Liver Transplantation/statistics & numerical data , Male , Middle Aged , Paliperidone Palmitate/adverse effects , Prevalence , Proportional Hazards Models , Risk Factors , Schizophrenia/complications , Schizophrenia/diagnosis , Taiwan/epidemiologyABSTRACT
BACKGROUND: Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) levels of amyloid-ß1-42 (Aß42), total tau protein and hyperphosphorylated tau (p-tau). However, the available methods are expensive and relatively invasive. Artificial intelligence techniques like machine learning tools have being increasingly used in precision diagnosis. METHODS: We conducted a meta-analysis to investigate the machine learning and novel biomarkers for the diagnosis of AD. METHODS: We searched PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews for reviews and trials that investigated the machine learning and novel biomarkers in diagnosis of AD. RESULTS: In additional to Aß and tau-related biomarkers, biomarkers according to other mechanisms of AD pathology have been investigated. Neuronal injury biomarker includes neurofiliament light (NFL). Biomarkers about synaptic dysfunction and/or loss includes neurogranin, BACE1, synaptotagmin, SNAP-25, GAP-43, synaptophysin. Biomarkers about neuroinflammation includes sTREM2, and YKL-40. Besides, d-glutamate is one of coagonists at the NMDARs. Several machine learning algorithms including support vector machine, logistic regression, random forest, and naïve Bayes) to build an optimal predictive model to distinguish patients with AD from healthy controls. CONCLUSIONS: Our results revealed machine learning with novel biomarkers and multiple variables may increase the sensitivity and specificity in diagnosis of AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing AD in outpatient clinics.
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Alzheimer Disease , Diagnosis, Computer-Assisted , Machine Learning , Aged , Alzheimer Disease/diagnosis , Alzheimer Disease/metabolism , Biomarkers/metabolism , Chromatography, High Pressure Liquid , Female , Humans , Middle AgedABSTRACT
BACKGROUND: d-glutamate, which is involved in N-methyl-d-aspartate receptor modulation, may be associated with cognitive ageing. AIMS: This study aimed to use peripheral plasma d-glutamate levels to differentiate patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from healthy individuals and to evaluate its prediction ability using machine learning. METHODS: Overall, 31 healthy controls, 21 patients with MCI and 133 patients with AD were recruited. Serum d-glutamate levels were measured using high-performance liquid chromatography (HPLC). Cognitive deficit severity was assessed using the Clinical Dementia Rating scale and the Mini-Mental Status Examination (MMSE). We employed four machine learning algorithms (support vector machine, logistic regression, random forest and naïve Bayes) to build an optimal predictive model to distinguish patients with MCI or AD from healthy controls. RESULTS: The MCI and AD groups had lower plasma d-glutamate levels (1097.79 ± 283.99 and 785.10 ± 720.06 ng/mL, respectively) compared to healthy controls (1620.08 ± 548.80 ng/mL). The naïve Bayes model and random forest model appeared to be the best models for determining MCI and AD susceptibility, respectively (area under the receiver operating characteristic curve: 0.8207 and 0.7900; sensitivity: 0.8438 and 0.6997; and specificity: 0.8158 and 0.9188, respectively). The total MMSE score was positively correlated with d-glutamate levels (r = 0.368, p < 0.001). Multivariate regression analysis indicated that d-glutamate levels were significantly associated with the total MMSE score (B = 0.003, 95% confidence interval 0.002-0.005, p < 0.001). CONCLUSIONS: Peripheral plasma d-glutamate levels were associated with cognitive impairment and may therefore be a suitable peripheral biomarker for detecting MCI and AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing MCI and AD in outpatient clinics.
Subject(s)
Alzheimer Disease/diagnosis , Cognitive Dysfunction/diagnosis , Glutamic Acid/blood , Machine Learning , Aged , Aged, 80 and over , Algorithms , Alzheimer Disease/blood , Alzheimer Disease/physiopathology , Biomarkers/blood , Case-Control Studies , Chromatography, High Pressure Liquid , Cognitive Dysfunction/blood , Cognitive Dysfunction/physiopathology , Diagnosis, Differential , Female , Humans , Male , Middle Aged , Psychiatric Status Rating Scales , Sensitivity and Specificity , Severity of Illness IndexABSTRACT
OBJECTIVE: Alzheimer's disease (AD) is a complex and severe neurodegenerative disease and still lacks effective methods of diagnosis. Dysfunction of the N-methyl-D-aspartate receptor (NMDAR) has been found to be involved in synapse dysfunction and neurotoxicity of AD mechanisms. d-Serine, an NMDAR receptor coagonist, is reported as a potential new biomarker for AD. However, the results of serum and cerebrospinal fluid (CSF) d-serine levels are conflicting. We conducted a meta-analysis to investigate the serum and CSF d-serine levels in patients with AD. METHODS: We searched PubMed, the Cochrane central register of controlled trials, and the Cochrane database of systematic reviews for trials that measured d-serine levels both in patients with AD and in controls. We included controlled trials that analyzed d-serine levels in human samples (e.g., serum and CSF). Studies were pooled using a random-effect model for comparisons between AD and control group. We used effect size (ES; expressed as d-serine levels) in each selected meta-analysis to calculate standardized mean difference (SMD). Positive values indicated increased d-serine levels in AD group. We presented results with 95% confidence intervals (CIs). The heterogeneity of the included trials was evaluated through visually inspecting funnel plots and using the I2 statistic. Moderators of effects were explored using metaregression. RESULTS: Seven trials with more than 1186 participants were included in this meta-analysis. d-serine levels in patients with AD were significantly higher than those in controls (SMD = 0.679, 95% CI = 0.335 to 1.022, p < 0.001). Subgroup analyses showed that the AD group had significantly higher d-serine levels in serum and CSF compared with the control group (SMD = 0.566 (serum) and 1.008 (CSF); 95% CI = 0.183 to 0.948 (serum) and 0.168 to 1.849 (CSF)). Moreover, a metaregression revealed a significant negative association between ES and mean mini-mental state examination score in AD group (slope = -0.1203, p = 0.0004). CONCLUSIONS: Our results revealed higher d-serine levels in the serum and CSF of patients with AD relative to the controls. Further studies with a larger sample size and longer follow-up are recommended to clarify this association.
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BACKGROUND: An increasing number of studies have shown that the brain-gut-microbiota axis may significantly contribute to Alzheimer's disease (AD) pathogenesis. Moreover, impaired memory and learning involve the dysfunction neurotransmission of glutamate, the agonist of the N-methyl-d-aspartate receptor and a major excitatory neurotransmitter in the brain. This systematic review aimed to summarize the current cutting-edge research on the gut microbiota and glutamate alterations associated with dementia. METHODS: PubMed, the Cochrane Collaboration Central Register of Controlled Clinical Trials, and Cochrane Systematic Reviews were reviewed for all studies on glutamate and gut microbiota in dementia published up until Feb 2020. RESULTS: Several pilot studies have reported alterations of gut microbiota and metabolites in AD patients and other forms of dementia. Gut microbiota including Bacteroides vulgatus and Campylobacter jejuni affect glutamate metabolism and decrease the glutamate metabolite 2-keto-glutaramic acid. Meanwhile, gut bacteria with glutamate racemase including Corynebacterium glutamicum, Brevibacterium lactofermentum, and Brevibacterium avium can convert l-glutamate to d-glutamate. N-methyl-d-aspartate glutamate receptor (NMDAR)-enhancing agents have been found to potentially improve cognition in AD or Parkinson's disease patients. These findings suggest that d-glutamate (d-form glutamate) metabolized by the gut bacteria may influence the glutamate NMDAR and cognitive function in dementia patients. CONCLUSIONS: Gut microbiota and glutamate are potential novel interventions to be developed for dementia. Exploring comprehensive cognitive functions in animal and human trials with glutamate-related NMDAR enhancers are warranted to examine d-glutamate signaling efficacy in gut microbiota in patients with AD and other neurodegenerative dementias.
Subject(s)
Alzheimer Disease/etiology , Alzheimer Disease/metabolism , Disease Susceptibility , Gastrointestinal Microbiome , Glutamic Acid/metabolism , Animals , Blood-Brain Barrier/metabolism , Brain/metabolism , Diet , Humans , Metabolic Networks and Pathways , Receptors, N-Methyl-D-Aspartate/metabolism , Signal Transduction , Synaptic TransmissionABSTRACT
We investigate the feasibility and performance of photon-number-resolved photodetection employing single-photon avalanche photodiodes (SPADs) with low dark counts. While the main idea, to split n photons into m detection modes with a vanishing probability of more than one photon per mode, is not new, we investigate here a important variant of this situation where SPADs are side-coupled to the same waveguide rather than terminally coupled to a propagation tree. This prevents the nonideal SPAD quantum efficiency from contributing to photon loss. We propose a concrete SPAD segmented waveguide detector based on a vertical directional coupler design, and characterize its performance by evaluating the purities of Positive-Operator-Valued Measures (POVMs) in terms of number of SPADs, photon loss, dark counts, and electrical cross-talk.
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BACKGROUND: Sarcosine (N-methylglycine), a type 1 glycine transporter inhibitor (GlyT1), has shown therapeutic potential for treating schizophrenia; however, studies have reported conflicting results. This meta-analysis aimed to explore the efficacy and cognitive effect of sarcosine for schizophrenia. METHODS: In this study, PubMed, Cochrane Systematic Reviews, and Cochrane Collaboration Central Register of Controlled Clinical Trials were searched electronically for double-blinded randomised controlled trials that used sarcosine for treating schizophrenia. We used the published trials up to November 2019 to investigate the efficacy of sarcosine in schizophrenia. We pooled studies by using a random-effect model for comparing sarcosine treatment effects. Patients who were diagnosed with schizophrenia according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition were recruited. Clinical improvement and cognitive function scores between baseline and after sarcosine use were compared using the standardised mean difference (SMD) with 95% confidence intervals (CIs). The heterogeneity of the included trials was evaluated through visual inspection of funnel plots and through the I2 statistic. RESULTS: We identified seven trials with 326 participants with schizophrenia meeting the inclusion criteria. All these studies evaluated the overall clinical symptoms, and four of them evaluated overall cognitive functions. Sarcosine use achieved more significant effects than the use of its comparators in relieving overall clinical symptoms (SMD = 0.51, CI = 0.26-0.76, p < 0.01). Moreover, studies with the low Positive and Negative Syndrome Scale range of 70-79 showed significant effect size (ES)s of 0.67 (95% CI: 0.03-1.31, p = 0.04). In addition, trials enrolling patients with stable clinical symptoms had significant ESs: 0.53 (95% CI: 0.21-0.85, p < 0.01). Add-on sarcosine combined with first- and second-generation antipsychotics, except clozapine, had a positive effect. For overall cognitive functions, sarcosine showed a positive but insignificant effect compared with its comparators (SMD = 0.27, CI = -0.06 to 0.60, p = 0.10). The effects were correlated with increased female proportions and decreased illness duration, albeit nonsignificantly. CONCLUSIONS: The meta-analysis suggests that sarcosine may be associated with treatment effect on overall clinical symptoms in patients with schizophrenia but not cognitive functions.