BACKGROUND: The optimal antidepressant dosages remain controversial. This study aimed to analyze the efficacy of antidepressants and characterize their dose-response relationships in the treatments of major depressive disorders (MDD). METHODS: We searched multiple databases, including the Embase, Cochrane Central Register of Controlled Trials, PubMed, and Web of Science, for the studies that were conducted between January 8, 2016, and April 30, 2023. The studies are double-blinded, randomized controlled trials (RCTs) involving the adults (≥18 years) with MDD. The primary outcomes were efficacy of antidepressant and the dose-response relationships. A frequentist network meta-analysis was conducted, treating participants with various dosages of the same antidepressant as a single therapy. We also implemented the model-based meta-analysis (MBMA) using a Bayesian method to explore the dose-response relationships. RESULTS: The network meta-analysis comprised 135,180 participants from 602 studies. All the antidepressants were more effective than the placebo; toludesvenlafaxine had the highest odds ratio (OR) of 4.52 (95% confidence interval [CI]: 2.65-7.72), and reboxetine had the lowest OR of 1.34 (95%CI: 1.14-1.57). Moreover, amitriptyline, clomipramine, and reboxetine showed a linear increase in effect size from low to high doses. The effect size of toludesvenlafaxine increased significantly up to 80 mg/day and subsequently maintained the maximal dose up to 160 mg/day while the predictive curves of nefazodone were fairly flat in different dosages. CONCLUSIONS: Although most antidepressants were more efficacious than placebo in treating MDD, no consistent dose-response relationship between any antidepressants was observed. For most antidepressants, the maximum efficacy was achieved at lower or middle prescribed doses, rather than at the upper limit. REGISTRATION No. CRD42023427480; https://www.crd.york.ac.uk/prospero/display_record.php?
Humans ; Antidepressive Agents/therapeutic use* ; Depressive Disorder, Major/drug therapy* ; Dose-Response Relationship, Drug ; Randomized Controlled Trials as Topic

Neuropathic pain is frequently comorbidity with cognitive deficits. Neuralized1 (Neurl1)-mediated ubiquitination of CPEB3 in the hippocampus is critical in learning and memory. However, the role of Neurl1 in the cognitive impairment in neuropathic pain remains elusive. Herein, we found that lumbar 5 spinal nerve ligation (SNL) in male rat-induced neuropathic pain was followed by learning and memory deficits and LTP impairment in the hippocampus. The Neurl1 expression in the hippocampal CA1 was decreased after SNL. And this decrease paralleled the reduction of ubiquitinated-CPEB3 level and reduced production of GluA1 and GluA2. Overexpression of Neurl1 in the CA1 rescued cognitive deficits and LTP impairment, and reversed the reduction of ubiquitinated-CPEB3 level and the decrease of GluA1 and GluA2 production following SNL. Specific knockdown of Neurl1 or CPEB3 in bilateral hippocampal CA1 in naïve rats resulted in cognitive deficits and impairment of synaptic plasticity. The rescued cognitive function and synaptic plasticity by the treatment of overexpression of Neurl1 before SNL were counteracted by the knockdown of CPEB3 in the CA1. Collectively, the above results suggest that the downregulation of Neurl1 through reducing CPEB3 ubiquitination and, in turn, repressing GluA1 and GluA2 production and mediating synaptic plasticity impairment in hippocampal CA1 leads to the genesis of cognitive deficits in neuropathic pain.
Animals ; Male ; Neuralgia/metabolism* ; Rats ; Down-Regulation/physiology* ; Ubiquitination/physiology* ; Neuronal Plasticity/physiology* ; Rats, Sprague-Dawley ; CA1 Region, Hippocampal/metabolism* ; Cognitive Dysfunction/metabolism* ; RNA-Binding Proteins/metabolism* ; Receptors, AMPA/metabolism*

Objective:To investigate the impact of four registration methods on the accuracy of virtual occlusal records (VOR) in intraoral scanning for implant restorations with multiple missing teeth.Methods:A mandibular model simulating clinical conditions with multiple missing teeth (right first molar, left second premolar, left first molar, left second molar) and a maxillary compete dentition model were mounted on a semi-adjustable articulator. Subsequently, twelve 0.5 mm stainless steel spheres were adhered to reference positions (16, 46, 13, 43, 23, 33, 25, 35, 26, 36, 27, 37) as fiducial markers. Following this, a laboratory scanner generated reference datasets by digitizing the models in maximum intercuspation (MIP). Meanwhile, ten maxillary and mandibular scans were acquired using an intraoral scanner, with all nonarticulated scans duplicated four times to ensure data consistency. Forty VOR intraoral scans were performed in MIP using four registration protocols: left-side, right-side, anterior, and bilateral registration ( n=10 per group), randomized via a computer-generated pseudo-random sequence. For measurement, linear distances (D16-46, D13-43, D23-33, D25-35, D26-36, D27-37, D16-46 represented the single-tooth defect position, whereas D25-35, D26-36, D27-37 reflected positions in free-end edentulism areas) between opposing markers were measured in a reverse engineering software, with deviations (ΔD) from the reference scan calculated to assess accuracy. Specifically, negative ΔD values indicated vertical dimension underestimation. Given that non-normally distributed data were analyzed using medians [interquartile ranges (IQR)], trueness (median ΔD) and precision (IQR) were evaluated. The interaction effect between the registration method and the position of the measurement items was evaluated by using the generalized linear model. The accuracy was compared overall by the Kruskal-Wallis test with the two-sided significance level of α=0.05. For pairwise comparisons, post-hoc tests were conducted by Dunn′s t-test with the Bonferroni correction for the significance level. Results:The accuracy of VOR was affected by registration method ( P<0.05), with a significant position×registration method interaction observed ( P<0.05). In particular, in all four groups, only the bilateral registration group showed trueness of less than 0.1 mm for both free-end edentulism and the single tooth defect, with ΔD16-46, ΔD25-35, ΔD26-36, and ΔD27-37 being 0.059 (0.015), -0.082 (0.052), -0.065 (0.032), -0.070 (0.050) mm, respectively. Moreover, trueness in free-end edentulism showed negative values across all groups, with the largest negative deviations observed in the right-side registration group, with ΔD25-35, ΔD26-36 and ΔD27-37 being -0.410 (0.174), -0.442 (0.225), -0.439 (0.262) mm, respectively. Conclusions:In fully digital workflows of implant restorations for mandibular free-end edentulism with multiple missing teeth, registration method critically influences VOR accuracy. While four registration methods exhibited underestimation of occlusal vertical dimension, bilateral registration achieved the highest accuracy.

Objective To observe the value of cervical lymph node ultrasound network model based on deep learning(DL)for diagnosing cervical lymph node metastasis of papillary thyroid carcinoma(PTC).Methods Totally 444 PTC patients with suspected cervical lymph node enlargement on ultrasonography were retrospectively enrolled and divided into metastasis group(n=253)and non-metastasis group(n=191)based on fine needle aspiration pathology and thyroglobulin detection.And 1 754 cervical lymph node ultrasonic images were divided into training set(n=1 404),validation set(n=175)and test set(n=175)at the ratio of 8∶1∶1.Ultrasonic features of cervical lymph nodes were extracted,then ultrasound network model was established using DL,and the diagnostic efficacy of this model for diagnosing lymph node metastasis was analyzed.Results The sensitivity,specificity,accuracy and area under the curve of ultrasound network model for diagnosing cervical lymph node metastasis of PTC was 93.06％,97.05％,95.04％and 0.858 in validation set,which was 86.14％,78.67％,88.49％and 0.828 in test set,respectively.Conclusion Cervical lymph node ultrasound network model based on DL was helpful for diagnosing cervical lymph node metastasis of PTC.

Objective:To analyze the non-motor symptom characteristics of patients with different subtypes of progressive supranuclear palsy (PSP).Methods:Demographic data were collected from patients diagnosed with probable or possible PSP in the PSP cohort at Qilu Hospital of Shandong University from June 2019 to June 2023. Motor symptoms were evaluated using the Progressive Supranuclear Palsy Rating Scale (PSPRS), Unified Parkinson′s Disease Rating Scale-Ⅲ , and the Freezing of Gait Questionnaire. Non-motor symptoms were assessed using the Non-Motor Symptoms Scale (NMSS), the Montreal Cognitive Assessment, the Hamilton Depression Rating Scale, and the Hamilton Anxiety Rating Scale. Patients were grouped into PSP with Richardson syndrome (PSP-RS), PSP with Parkinsonism (PSP-P), PSP with progressive gait freezing (PSP-PGF), and other subtypes (PSP-other) based on clinical classification. The study compared the non-motor symptom characteristics among the 4 groups and used linear regression models to evaluate the influencing factors of PSP non-motor symptoms.Results:A total of 153 PSP patients were included in this study, with a male-to-female ratio of 89∶64 and an age of (66.0±6.6) years. Among them, 83 were in the PSP-RS group (54.2%), 32 in the PSP-P group (20.9%), 27 in the PSP-PGF group (17.6%), and 11 in the PSP-other group (7.2%). The total NMSS score for non-motor symptoms in PSP patients was 62.6±38.5, with 8.8±4.7 non-motor symptoms per patient. The most common non-motor symptoms among all PSP patients were sleep/fatigue [130/153 (85.0%)], gastrointestinal symptoms [129/153 (84.3%)], urinary symptoms [113/153 (73.9%)], attention/memory impairment [112/153 (73.2%)], and mood symptoms [108/153 (70.6%)]. The total NMSS score of the PSP-RS group (70.8±36.0) was higher than that of the PSP-PGF group (49.4±40.3; t=2.561, P=0.011). The number of non-motor symptoms in the PSP-RS group (9.9±4.4) was greater than that in the PSP-P group (7.7±5.5; t=2.365, P=0.019) and the PSP-PGF group (6.9±4.3; t=2.978, P=0.003). The incidence of memory decline in the PSP-RS group [52/83 (62.7%)] was higher than that in the PSP-P group [10/32 (31.3%); χ 2=9.165, Bonferroni-corrected P=0.012], and the incidence of constipation in the PSP-RS group [49/83 (59.0%)] was higher than that in the PSP-PGF group [8/27 (29.6%); χ 2=7.056, Bonferroni-corrected P=0.048]. Multivariate regression analysis showed that the bulbar symptom score ( β=5.591, 95% CI 1.792-9.389, P=0.005), limb motor score ( β=1.786, 95% CI 0.398-3.174, P=0.013), and gait/axial score ( β=1.956, 95% CI 0.149-3.763, P=0.036) in PSPRS were all associated with non-motor symptom scores. Conclusions:Different PSP subtypes exhibit distinct non-motor symptom profiles. PSP-RS patients bear a heavier non-motor symptom burden, with higher incidences of memory decline and constipation than other subtypes. These findings may aid in the early recognition and clinical diagnosis of PSP.

ObjectiveTo investigate the chemical hazards in the production line of lithium batteries, so as to provide a scientific basis for the management of occupational-health risk and to promote the healthy and sustainable development of the lithium battery industry. MethodsAn on-site survey on the process flow of the production of lithium battery was conducted in an enterprise. Volatile organic compounds (VOCs) in the occupational environment were collected by Summa canisters, carbonates and N-methyl pyrrolidone (NMP) were collected using activated carbon tubes, and airborne metals were collected using filter membranes. VOCs, carbonates and NMP were detected by gas chromatography-mass spectrometry (GC-MS), and airborne metal elements in the dust samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). ResultsNon-targeted environmental monitoring results indicated that NMP was detected in the negative /positive electrode coating, assembly and drying filling workstations, dimethyl carbonate (DMC) was detected in the assembly, drying and electrolyte injection workstations, and ethyl methyl carbonate (EMC) was detected solely in the electrolyte injection workstation. Semi-quantitative analyses of VOCs identified 136 pollutants, including acrylonitrile and halohydrocarbons. Quantitative targeted environmental monitoring results revealed the highest geometric mean (GM) concentration of EMC (31.450 mg·m^-3) was found in the assembly and drying workstations, diethyl carbonate (DEC) was detected in all workstations. While vinylene carbonate (VC) and ethylene carbonate (EC) were detected only in electrolyte injection, assembly and drying workstations. NMP was detected in all positive electrode coating samples, with a GM concentration of 5.68 mg·m^-3 (concentration range: 4.0‒ 7.4 mg·m^-³). Lithium was exclusively detected in dust samples from the liquid injection workstation (GM: 0.014 μg·m^-³). ConclusionNMP, EMC, DEC, and other chemicals are identified at the key workstations such as the positive electrode coating, electrolyte injection, assembly and drying in the lithium production line. Furthermore, semi-quantitative VOCs analyses identified 136 pollutants, demonstrating a characteristic of multicomponent chemical exposure.

Objective:The purpose of this study was to develop a dynamic prediction model for patients with gastric signet ring cell cancer (GSRCC)following laparoscopic radical gastrectomy in order to improve the precision and usefulness of prognoses prediction for overall survival and disease-free survival.Methods:From 2011 to 2018, 914 National Cancer Center patients participated in the study. To find independent prognostic indicators and create a prognostic nomogram model, univariate and multivariate regression analyses were performed. Calibration curves, receiver operating characteristic curves, and consistency indices were used to assess the model's performance. To make clinical application more convenient, two web-based prediction tools were created.Results:A training set of 639 cases and a validation set of 275 instances were randomly selected from among the patients. Important predictive variables such as age, tumor size, location, pN and pT staging, and postoperative chemotherapy were all incorporated in the model (all P<0.05). The model's consistency index and area under the receiver operating characteristic curves were both higher than 0.7, and the calibration curves demonstrated a good fit between the expected and actual values, indicating high accuracy and consistency in postoperative survival prediction for patients with gastric signet ring cell carcinoma. Conclusion:We successfully developed two dynamic prediction models in this study, which improved its clinical practicability using web-based tools and is anticipated to be crucial to clinical practice going forward.

Objective:To investigate the impact of four registration methods on the accuracy of virtual occlusal records (VOR) in intraoral scanning for implant restorations with multiple missing teeth.Methods:A mandibular model simulating clinical conditions with multiple missing teeth (right first molar, left second premolar, left first molar, left second molar) and a maxillary compete dentition model were mounted on a semi-adjustable articulator. Subsequently, twelve 0.5 mm stainless steel spheres were adhered to reference positions (16, 46, 13, 43, 23, 33, 25, 35, 26, 36, 27, 37) as fiducial markers. Following this, a laboratory scanner generated reference datasets by digitizing the models in maximum intercuspation (MIP). Meanwhile, ten maxillary and mandibular scans were acquired using an intraoral scanner, with all nonarticulated scans duplicated four times to ensure data consistency. Forty VOR intraoral scans were performed in MIP using four registration protocols: left-side, right-side, anterior, and bilateral registration ( n=10 per group), randomized via a computer-generated pseudo-random sequence. For measurement, linear distances (D16-46, D13-43, D23-33, D25-35, D26-36, D27-37, D16-46 represented the single-tooth defect position, whereas D25-35, D26-36, D27-37 reflected positions in free-end edentulism areas) between opposing markers were measured in a reverse engineering software, with deviations (ΔD) from the reference scan calculated to assess accuracy. Specifically, negative ΔD values indicated vertical dimension underestimation. Given that non-normally distributed data were analyzed using medians [interquartile ranges (IQR)], trueness (median ΔD) and precision (IQR) were evaluated. The interaction effect between the registration method and the position of the measurement items was evaluated by using the generalized linear model. The accuracy was compared overall by the Kruskal-Wallis test with the two-sided significance level of α=0.05. For pairwise comparisons, post-hoc tests were conducted by Dunn′s t-test with the Bonferroni correction for the significance level. Results:The accuracy of VOR was affected by registration method ( P<0.05), with a significant position×registration method interaction observed ( P<0.05). In particular, in all four groups, only the bilateral registration group showed trueness of less than 0.1 mm for both free-end edentulism and the single tooth defect, with ΔD16-46, ΔD25-35, ΔD26-36, and ΔD27-37 being 0.059 (0.015), -0.082 (0.052), -0.065 (0.032), -0.070 (0.050) mm, respectively. Moreover, trueness in free-end edentulism showed negative values across all groups, with the largest negative deviations observed in the right-side registration group, with ΔD25-35, ΔD26-36 and ΔD27-37 being -0.410 (0.174), -0.442 (0.225), -0.439 (0.262) mm, respectively. Conclusions:In fully digital workflows of implant restorations for mandibular free-end edentulism with multiple missing teeth, registration method critically influences VOR accuracy. While four registration methods exhibited underestimation of occlusal vertical dimension, bilateral registration achieved the highest accuracy.

Objective To observe the value of cervical lymph node ultrasound network model based on deep learning(DL)for diagnosing cervical lymph node metastasis of papillary thyroid carcinoma(PTC).Methods Totally 444 PTC patients with suspected cervical lymph node enlargement on ultrasonography were retrospectively enrolled and divided into metastasis group(n=253)and non-metastasis group(n=191)based on fine needle aspiration pathology and thyroglobulin detection.And 1 754 cervical lymph node ultrasonic images were divided into training set(n=1 404),validation set(n=175)and test set(n=175)at the ratio of 8∶1∶1.Ultrasonic features of cervical lymph nodes were extracted,then ultrasound network model was established using DL,and the diagnostic efficacy of this model for diagnosing lymph node metastasis was analyzed.Results The sensitivity,specificity,accuracy and area under the curve of ultrasound network model for diagnosing cervical lymph node metastasis of PTC was 93.06％,97.05％,95.04％and 0.858 in validation set,which was 86.14％,78.67％,88.49％and 0.828 in test set,respectively.Conclusion Cervical lymph node ultrasound network model based on DL was helpful for diagnosing cervical lymph node metastasis of PTC.