Network meta-analysis of acupuncture for tinnitus.

OBJECTIVE: To provide evidence for medical management of tinnitus based on an assessment of the evidence concerning the effectiveness of acupuncture as a treatment for tinnitus using network meta-analysis (NMA). METHODS: We conducted a systematic literature review by searching 8 national and international databases (inception to February 2023) for randomized controlled trials (RCTs) for tinnitus. Only RCTs that recruited participants aged over 18 and diagnosed with tinnitus, and that evaluated acupuncture or acupuncture in combination with conventional western medical therapy were included. We used response rate and tinnitus handicap inventory (THI) to examine efficacy. We conducted NMA with random effects, and the rate ratio or mean difference with its 95% credible interval was calculated. In addition, we ranked all treatments via their SUCRA and assessed the quality of evidence according to the GRADE criteria. RESULTS: A total of 2575 patients were included in the study. The main findings of the current NMA were that acupoint injection combined with warm acupuncture was the most effective for response rate, followed by warm acupuncture and acupoint injection combined with western medical treatment. Acupuncture combined with western medical treatment was the most effective for THI, followed by electroacupuncture combined with warm acupuncture and acupuncture combined with moxibustion. CONCLUSION: Acupuncture seems to be a better trend treatment for tinnitus. Further rigorous RCT studies that include direct comparisons for different acupuncture-related treatments are encouraged to provide the most promising evidence for patients with tinnitus. PROTOCOL REGISTRATION: CRD42023398745.

A global meta-analysis of greenhouse gas emissions and carbon and nitrogen losses during livestock manure composting: Influencing factors and mitigation strategies.

The management of manure composting contributes to alleviate the global greenhouse effect. To improve our understanding of this process, we conducted a meta-analysis of 371 observations from 87 published studies in 11 countries. The results showed that the difference in nitrogen content in feces significantly affected the greenhouse gas (GHG) emissions and nutrient losses of subsequent composting, with NH3-N, CO2-C, and CH4-C losses all increasing with its rise. Windrow pile composting (especially compared to trough composting) had lower GHG emissions and nutrient loss. C/N ratio, aeration rate, and pH value significantly affected NH3 emission, and a decrease in the latter two can reduce it by 31.8 % and 42.5 %, respectively. Decreasing the moisture content or increasing the turning frequency could decrease CH4 by 31.8 % and 62.6 %, respectively. The addition of biochar or superphosphate had a synergistic emission reduction. The emission reduction of N2O and CH4 by biochar was more prominent (44 % and 43.6 %), while superphosphate on NH3 (38.0 %) was better. And the latter was more suitable if added in 10-20 % of dry weight. Dicyandiamide was the only chemical additive (59.4 %) with better N2O emission reduction performance. Microbial agents with different functions had certain effects on NH3-N emission reduction, while the mature compost had a certain effect on N2O-N emissions (67.0 %). In general, N2O had the highest contribution to the greenhouse effect during composting (74.22 %).

Effects of cornstalk and sawdust coverings on greenhouse gas emissions during sheep manure storage.

Manure covered by organic materials during the storage has shown that it can effectively reduce emissions of greenhouse gases, but few studies have focused on the bacterial communities in manure or the coverage and mechanism responsible for reducing gas emissions. Therefore, this study investigated the impacts and mechanisms of cornstalk and sawdust coverings on greenhouse gas emissions during sheep manure storage. Sheep manure covered by organic material reduced nitrous oxide (N2O) emissions (42.27%-42.55%) relative to uncovered control through physical adsorption and biological transformation of Acinetobacter, Corynebacterium, Brachybacterium, Dietzia and Brevibacterium. Sheep manure covered by organic materials also increased methane (CH4) emissions (16.31%-43.07%) by increasing anaerobic zones of coverage. Overall, coverings reduced carbon dioxide equivalent (CO2eq) by 29.87%-33.60%. Coverings had less effect on the bacterial diversity and community of sheep manure, and the number of bacteria shared by sheep manure and the covering material increased with storage progress, indicating that these bacteria were transferred to the covering materials with gas emissions and moisture volatilization. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) images showed that functional group intensities of the covering materials increased and the fibrous structures became more disordered during the storage period. In general, it was safe to use organic materials as coverages during sheep manure storage, which was conducive to reducing greenhouse gas emissions.

Verification of a clinical decision support system for the diagnosis of headache disorders based on patient-computer interactions: a multi-center study.

BACKGROUND: Although headache disorders are common, the current diagnostic approach is unsatisfactory. Previously, we designed a guideline-based clinical decision support system (CDSS 1.0) for diagnosing headache disorders. However, the system requires doctors to enter electronic information, which may limit widespread use. METHODS: In this study, we developed the updated CDSS 2.0, which handles clinical information acquisition via human-computer conversations conducted on personal mobile devices in an outpatient setting. We tested CDSS 2.0 at headache clinics in 16 hospitals in 14 provinces of China. RESULTS: Of the 653 patients recruited, 18.68% (122/652) were suspected by specialists to have secondary headaches. According to "red-flag" responses, all these participants were warned of potential secondary risks by CDSS 2.0. For the remaining 531 patients, we compared the diagnostic accuracy of assessments made using only electronic data firstly. In Comparison A, the system correctly recognized 115/129 (89.15%) cases of migraine without aura (MO), 32/32 (100%) cases of migraine with aura (MA), 10/10 (100%) cases of chronic migraine (CM), 77/95 (81.05%) cases of probable migraine (PM), 11/11 (100%) cases of infrequent episodic tension-type headache (iETTH), 36/45 (80.00%) cases of frequent episodic tension-type headache (fETTH), 23/25 (92.00%) cases of chronic tension-type headache (CTTH), 53/60 (88.33%) cases of probable tension-type headache (PTTH), 8/9 (88.89%) cases of cluster headache (CH), 5/5 (100%) cases of new daily persistent headache (NDPH), and 28/29 (96.55%) cases of medication overuse headache (MOH). In Comparison B, after combining outpatient medical records, the correct recognition rates of MO (76.03%), MA (96.15%), CM (90%), PM (75.29%), iETTH (88.89%), fETTH (72.73%), CTTH (95.65%), PTTH (79.66%), CH (77.78%), NDPH (80%), and MOH (84.85%) were still satisfactory. A patient satisfaction survey indicated that the conversational questionnaire was very well accepted, with high levels of satisfaction reported by 852 patients. CONCLUSIONS: The CDSS 2.0 achieved high diagnostic accuracy for most primary and some secondary headaches. Human-computer conversation data were well integrated into the diagnostic process, and the system was well accepted by patients. The follow-up process and doctor-client interactions will be future areas of research for the development of CDSS for headaches.

Clinical characteristics and psychoacoustic analysis of acute and chronic subjective tinnitus.

Objective: This study aimed to understand the demographics, clinical characteristics, and psychoacoustic status of subjective tinnitus patients to explore the factors associated with acute and chronic tinnitus in the general hospitals of Shanghai. Methods: A cross-sectional study was conducted to investigate the clinical characteristics and psychoacoustic status of subjective tinnitus patients with history greater than 1 month. Data were collected during January 2021 and January 2022 from eight general hospitals in five districts of Shanghai, China. All patients accepted questionnaires and acoustic examination, then SPSS 22.0 and GraphPad Prism 8.0.2 were applied for data analysis. Results: Among the 359 tinnitus patients, 126 cases were diagnosed with acute tinnitus, 58 cases were subacute tinnitus, and 175 cases were chronic tinnitus. Patients with acute and chronic tinnitus differed in terms of side of tinnitus, hearing loss, frequency of tinnitus, severity of tinnitus, anxiety, depression, and sleep status. Different characteristics were included in the multivariate ordinal logistic regression analysis. Persistent tinnitus (OR = 2.00, p = .008), high frequency hearing loss (OR = 4.77, p < .001), depression (OR = 1.23, p < .001) were found to be positively associated with the course of tinnitus. Unilateral tinnitus (OR = 0.48, p = .003), mild (OR = 0.29, p = .001) and moderate (OR = 0.46, p = .038) hearing loss, VAS scores (OR = 0.82, p = .032), anxiety (OR = 0.81, p < .001), THI scores (OR = 0.98, p = .002), and sleep disorders (OR = 0.94, p = .025) were found to be negatively associated with the course of tinnitus. Conclusion: Patients with acute tinnitus were at greater risk for anxiety, sleep disturbances, and exacerbation of tinnitus perception, and those with chronic tinnitus were at greater risk for depression. Lay Summary: Our study demonstrated that patients with acute tinnitus were at greater risk for anxiety, sleep disturbances, and exacerbation of tinnitus perception, and those with chronic tinnitus were at greater risk for depression.

A Gallbladder Cancer Survival Prediction Model Based on Multimodal Fusion Analysis.

BACKGROUND: Gallbladder cancer is the sixth most common malignant gastrointestinal tumor. Radical surgery is currently the only effective treatment, but patient prognosis is poor, with a 5-year survival rate of only 5-10%. Establishing an effective survival prediction model for gallbladder cancer patients is crucial for disease status assessment, early intervention, and individualized treatment approaches. The existing gallbladder cancer survival prediction model uses clinical data-radiotherapy and chemotherapy, pathology, and surgical scope-but fails to utilize laboratory examination and imaging data, limiting its prediction accuracy and preventing sufficient treatment plan guidance. AIMS: The aim of this work is to propose an accurate survival prediction model, based on the deep learning 3D-DenseNet network, integrated with multimodal medical data (enhanced CT imaging, laboratory test results, and data regarding systemic treatments). METHODS: Data were collected from 195 gallbladder cancer patients at two large tertiary hospitals in Shanghai. The 3D-DenseNet network extracted deep imaging features and constructed prognostic factors, from which a multimodal survival prediction model was established, based on the Cox regression model and incorporating patients' laboratory test and systemic treatment data. RESULTS: The model had a C-index of 0.787 in predicting patients' survival rate. Moreover, the area under the curve (AUC) of predicting patients' 1-, 3-, and 5-year survival rates reached 0.827, 0.865, and 0.926, respectively. CONCLUSIONS: Compared with the monomodal model based on deep imaging features and the tumor-node-metastasis (TNM) staging system-widely used in clinical practice-our model's prediction accuracy was greatly improved, aiding the prognostic assessment of gallbladder cancer patients.

A novel pyroptosis-related gene signature for predicting laryngeal carcinoma prognosis.

Pyroptosis, a newly-defined mode of cell death related to inflammation, is closely related to cancers but has not yet been studied in laryngeal carcinoma (LC). We investigated pyroptosis in LC and constructed a prognostic model. Using RNA sequencing data, we identified differentially expressed genes (DEGs) in LC and normal tissues to construct a prognostic risk model. The model's accuracy and independent prognostic value were evaluated using survival- and receiver operating characteristic (ROC)- curves; and univariate and multivariate Cox regression analyses, respectively. Gene Expression Omnibus (GEO) data was utilized as a model validation set. Differential analysis revealed 37 DEGs, and consistent clustering showed that pyroptosis-related genes could predict LC prognosis. Six genes (CHMP7, GSDME, GZMB, CASP9, IL6, and NLRP1) were obtained by Lasso Cox regression analysis to construct a prognostic model. The high-risk group had a poor prognosis with areas under the ROC curve at 1-, 3-, and 5-years of 0.619, 0.692, and 0.656, respectively. Univariate and multivariate Cox analyses showed that the risk score was an independent prognostic factor. Enrichment analysis of GO and KEGG pathways revealed that differentially expressed genes may be related to infection, T cell differentiation, immunity, and inflammation. It was further found that the low survival rate of the high-risk group may be related to the significant reduction of immune cell infiltration and immune function. With the bioinformatic method, six genes related to pyroptosis affecting LC prognosis were screened and a prognostic risk model was constructed, which laid a foundation for pyroptosis study in LC.

Gradually shifting clinical phenomics in migraine spectrum: a cross-sectional, multicenter study of 5438 patients.

BACKGROUND: The aim of the study was to investigate whether MwoA and MwA are different manifestations of a single disease, distinct clinical entities, or located at two poles of a spectrum. METHODS: In this cross-sectional study, 5438 patients from 10 hospitals in China were included: 4651 were diagnosed with migraine without aura (MwoA) and 787 with migraine with aura (MwA). We used a validated standardized electronic survey to collect multidimensional data on headache characteristics and evaluated the similarities and differences between migraine subtypes. To distinguish migraine subtypes, we employed correlational analysis, factor analysis of mixed data (FAMD), and decision tree analysis. RESULTS: Compared to MwA, MwoA had more severe headaches, predominantly affected females, were more easily produced by external factors, and were more likely to have accompanying symptoms and premonitory neck stiffness. Patients with MwA are heterogeneous, according to correlation analysis; FAMD divided the subjects into three clear clusters. The majority of the differences between MwoA and MwA were likewise seen when typical aura with migraine headache (AWM) and typical aura with non-migraine headache (AWNM) were compared. Furthermore, decision trees analysis revealed that the chaotic MwA data reduced the decision tree's accuracy in distinguishing MwoA from MwA, which was significantly increased by splitting MwA into AWM and AWNM. CONCLUSIONS: The clinical phenomics of headache phenotype varies gradually from MwoA to AWM and AWNM, and AWM is a mid-state between MwoA and AWNM. We tend to regard migraine as a spectrum disorder, and speculate that different migraine subtypes have different "predominant regions" that generate attacks.

Effects of dicyandiamide, phosphogypsum and superphosphate on greenhouse gas emissions during pig manure composting.

This study investigated the effects of dicyandiamide, phosphogypsum and superphosphate on greenhouse gas emissions and compost maturity during pig manure composting. The results indicated that the addition of dicyandiamide and phosphorus additives had no negative effect on organic matter degradation, and could improve the compost maturity. Adding dicyandiamide alone reduced the emissions of ammonia (NH3), methane (CH4) and nitrous oxide (N2O) by 9.37 %, 9.60 % and 31.79 %, respectively, which was attributed that dicyandiamide effectively inhibited nitrification to reduce the formation of N2O. Dicyandiamide combined with phosphogypsum or superphosphate could enhance mitigation of the total greenhouse gas (29.55 %-37.46 %) and NH3 emission (18.28 %-21.48 %), which was mainly due to lower pH value and phosphoric acid composition. The combination of dicyandiamide and phosphogypsum exhibited the most pronounced emission reduction effect, simultaneously decreasing the NH3, CH4 and N2O emissions by 18.28 %, 38.58 % and 36.14 %, respectively. The temperature and C/N content of the compost were significantly positively correlated with greenhouse gas emissions.

Lower motor neuron involvement in patients with neuromyelitis optica spectrum disorders.

BACKGROUND: Involvement of the central gray matter of spinal cord is a characteristic magnetic resonance imaging (MRI) feature of aquaporin-4-immunoglobulin G antibodies (AQP4-IgG) positive neuromyelitis optica spectrum disorders (NMOSD). However, there has been no systemic electrophysiological study investigating the frequency of lower motor neuron involvement in NMOSD patients. METHODS: We retrospectively reviewed a cohort of 59 NMOSD patients with results of concentric needle electromyography (EMG) and nerve conduction studies (NCS) that were admitted to the Department of Neurology of Chinese PLA General Hospital between January 2016 and December 2019. RESULTS: Acute and/or chronic denervation was found in 22.0% (13/59) of the NMOSD patients by EMG. Peripheral or cranial neuropathy indicated by abnormal NCS changes was found in 11.9% (7/59) of the NMOSD patients. Denervation indicated by EMG that can be accounted for by abnormal NCS was found in 6.8% (4/59) of the NMOSD patients, while 3.4% (2/59) of the NMOSD patients had NCS abnormality without denervation indicated by EMG. Accordingly, 9 of the 59 NMOSD patients (15.3%) had lower motor neuron involvement, and moreover, 6.8% (4/59) of the NMOSD patients had corresponding spinal cord or brainstem lesions on MRI. CONCLUSION: Not uncommon lower motor neuron involvement exists in NMOSD patients, so needle EMG and NCS studies should be performed in NMOSD patients with suspected lower motor neuron involvement.

Premonitory symptoms in migraine from China: A multi-clinic study of 4821 patients.

OBJECTIVE: To observe the prevalence and characteristics of premonitory symptoms in Chinese migraineurs and explore their associations with migraine-related factors. METHOD: Migraineurs who visited a tertiary headache clinic and one of nine neurology clinics between May 2014 and November 2019 were studied. RESULT: Among the 4821 patients meeting the migraine criteria (International Classification of Headache Disorders, 3rd edition), 1038 (21.5%) patients experienced at least one premonitory symptom. The most common premonitory symptoms were neck stiffness, dizziness, yawning and drowsiness. The logistic regression analysis demonstrated that aura, photophobia, aggravation by routine physical activity, triggers, family history, depression, coffee consumption and physical exercise were associated with an increased probability of experiencing premonitory symptoms (p ≤ 0.001). The premonitory symptoms of migraine with and without aura differ in prevalence and most common symptoms. The cluster analysis revealed pairwise clustering of the following premonitory symptoms: Photophobia/phonophobia, concentration change/dysesthesia, loquacity/overactivity, yawning/drowsiness, fatigue/dizziness, and mood change/irritability. The correlation analysis of triggers and premonitory symptoms revealed that temperature change, environment change, sleep disorder, activity and stress were related to multiple premonitory symptoms, and that food, light, menstruation, alcohol and odor were related to special premonitory symptoms (p ≤ 0.001). CONCLUSION: The prevalence of premonitory symptoms among migraineurs in China is 21.5%. Some factors influence the probability of experiencing premonitory symptoms. Paired premonitory symptoms in the clustering analysis may share similar origins. Certain triggers associated with multiple premonitory symptoms may induce brain dysfunction; however, other triggers that overlap with corresponding special premonitory symptoms may be premonitory symptoms or a form of premonitory symptom.

A clinical decision support system for the diagnosis of probable migraine and probable tension-type headache based on case-based reasoning.

BACKGROUND: The overlap between probable migraine (PM) and probable tension-type headache (PTTH) often confuses physicians in clinical practice. Although clinical decision support systems (CDSSs) have been proven to be helpful in the diagnosis of primary headaches, the existing guideline-based headache disorder CDSSs do not perform adequately due to this overlapping issue. Thus, in this study, a CDSS based on case-based reasoning (CBR) was developed in order to solve this problem. METHODS: First, a case library consisting of 676 clinical cases, 56.95% of which had been diagnosed with PM and 43.05% of which had been diagnosed with PTTH, was constructed, screened by a three-member panel, and weighted by engineers. Next, the resulting case library was used to diagnose current cases based on their similarities to the previous cases. The test dataset was composed of an additional 222 historical cases, 76.1% of which had been diagnosed with PM and 23.9% of which had been diagnosed with PTTH. The cases that comprised the case library as well as the test dataset were actual clinical cases obtained from the International Headache Center in Chinese PLA General Hospital. RESULTS: The results indicated that the PM and PTTH recall rates were equal to 97.02% and 77.78%, which were 34.31% and 16.91% higher than that of the guideline-based CDSS, respectively. Furthermore, the PM and PTTH precision rates were equal to 93.14% and 89.36%, which were7.09% and 15.68% higher than that of the guideline-based CDSS, respectively. Comparing CBR CDSS and guideline-based CDSS, the p-value of PM diagnoses was equal to 0.019, while that of PTTH diagnoses was equal to 0.002, which indicated that there was a significant difference between the two approaches. CONCLUSIONS: The experimental results indicated that the CBR CDSS developed in this study diagnosed PM and PTTH with a high degree of accuracy and performed better than the guideline-based CDSS. This system could be used as a diagnostic tool to assist general practitioners in distinguishing PM from PTTH.

A hybrid intelligent diagnosis approach for quick screening of Alzheimer's disease based on multiple neuropsychological rating scales.

Neuropsychological testing is an effective means for the screening of Alzheimer's disease. Multiple neuropsychological rating scales should be used together to get subjects' comprehensive cognitive state due to the limitation of a single scale, but it is difficult to operate in primary clinical settings because of the inadequacy of time and qualified clinicians. Aiming at identifying AD's stages more accurately and conveniently in screening, we proposed a computer-aided diagnosis approach based on critical items extracted from multiple neuropsychological scales. The proposed hybrid intelligent approach combines the strengths of rough sets, genetic algorithm, and Bayesian network. There are two stages: one is attributes reduction technique based on rough sets and genetic algorithm, which can find out the most discriminative items for AD diagnosis in scales; the other is uncertain reasoning technique based on Bayesian network, which can forecast the probability of suffering from AD. The experimental data set consists of 500 cases collected by a top hospital in China and each case is determined by the expert panel. The results showed that the proposed approach could not only reduce items drastically with the same classification precision, but also perform better on identifying different stages of AD comparing with other existing scales.

Validation of a guideline-based decision support system for the diagnosis of primary headache disorders based on ICHD-3 beta.

BACKGROUND: China may have the largest population of headache sufferers and therefore the most serious burden of disease worldwide. However, the rate of diagnosis for headache disorders is extremely low, possibly due to the relative complexity of headache subtypes and diagnostic criteria. The use of computerized clinical decision support systems (CDSS) seems to be a better choice to solve this problem. METHODS: We developed a headache CDSS based on ICHD-3 beta and validated it in a prospective study that included 543 headache patients from the International Headache Center at the Chinese PLA General hospital, Beijing, China. RESULTS: We found that the CDSS correctly recognized 159/160 (99.4%) of migraine without aura, 36/36 (100%) of migraine with aura, 20/21 (95.2%) of chronic migraine, and 37/59 (62.7%) of probable migraine. This system also correctly identified 157/180 (87.2%) of patients with tension-type headache (TTH), of which infrequent episodic TTH was diagnosed in 12/13 (92.3%), frequent episodic TTH was diagnosed in 99/101 (98.0%), chronic TTH in 18/20 (90.0%), and probable TTH in 28/46 (60.9%). The correct diagnostic rates of cluster headache and new daily persistent headache (NDPH) were 90.0% and 100%, respectively. In addition, the system recognized 32/32 (100%) of patients with medication overuse headache. CONCLUSIONS: With high diagnostic accuracy for most of the primary and some types of secondary headaches, this system can be expected to help general practitioners at primary hospitals improve diagnostic accuracy and thereby reduce the burden of headache in China.

A guideline-based decision support system for headache diagnosis.

The ratio of correct diagnosis for primary headache has always been relatively low for general practitioners due to the unacquaintance with headache guideline in Chinese primary hospitals. This study proposed a computerized headache guideline method using SAGE module and developed a decision support system for headache diagnosis, which could be expected to help general practitioners of primary hospitals improve diagnostic accuracy. 282 previously diagnosed cases from EMR were used to evaluate the diagnostic accuracy of the system, the result is: migraine 144/153 (94.1%), tension-type headache 89/100 (89.0%), cluster headache 10/11 (90.9%) and chronic daily headache 53/57(93.0%). The proposed system is in the starting phase of the implementation at the outpatient department of Neurology in Chinese PLA general hospital.

BST-2 binding with cellular MT1-MMP blocks cell growth and migration via decreasing MMP2 activity.

MT1-MMP (membrane type 1-matrix metalloproteinase) plays important roles in cell growth and tumor invasion via mediating cleavage of MMP2/gelatinase A and a variety of substrates including type I collagen. BST-2 (bone marrow stromal cell antigen 2) is a membrane tetherin whose expression dramatically reduces the release of a broad range of enveloped viruses including HIV from infected cells. In this study, we provided evidence that both transient and IFN-α induced BST-2 could decrease the activity of MMP2 via binding to cellular MT1-MMP on its C-terminus and inhibiting its proteolytic activity; and finally block cell growth and migration. Zymography gel and Western blot experiments demonstrated that BST-2 decreased MMP2 activity, but no effect on the expression of MMP2 and MT1-MMP genes. Confocal and immunoprecipitation data showed that BST-2 co-localized and interacted with MT1-MMP. This interaction inhibited the proteolytic enzyme activity of MT1-MMP, and blocked the activation of proMMP2. Experimental results of C-terminus deletion mutant of MT1-MMP showed that activity of MMP2 was no change and also no interaction existed between the mutant and BST-2 after co-transfection with the mutant and BST-2. It meant that C-terminus of MT1-MMP played a key role in the interaction with BST-2. In addition, cell growth in 3D type I collagen gel lattice and cell migration were all inhibited by BST-2. Taken together, BST-2, as a membrane protein and a tetherin of enveloped viruses, was a novel inhibitor of MT1-MMP and could be considerable as an inhibitor of cancer cell growth and migration on clinic.