Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.

BACKGROUND: The detection and management of intracranial aneurysms (IAs) are vital to prevent life-threatening complications like subarachnoid hemorrhage (SAH). Artificial Intelligence (AI) can analyze medical images, like CTA or MRA, spotting nuances possibly overlooked by humans. Early detection facilitates timely interventions and improved outcomes. Moreover, AI algorithms offer quantitative data on aneurysm attributes, aiding in long-term monitoring and assessing rupture risks. METHODS: We screened four databases (PubMed, Web of Science, IEEE and Scopus) for studies using artificial intelligence algorithms to identify IA. Based on algorithmic methodologies, we categorized them into classification, segmentation, detection and combined, and then their merits and shortcomings are compared. Subsequently, we elucidate potential challenges that contemporary algorithms might encounter within real-world clinical diagnostic contexts. Then we outline prospective research trajectories and underscore key concerns in this evolving field. RESULTS: Forty-seven studies of IA recognition based on AI were included based on search and screening criteria. The retrospective results represent that current studies can identify IA in different modal images and predict their risk of rupture and blockage. In clinical diagnosis, AI can effectively improve the diagnostic accuracy of IA and reduce missed detection and false positives. CONCLUSIONS: The AI algorithm can detect unobtrusive IA more accurately in communicating arteries and cavernous sinus arteries to avoid further expansion. In addition, analyzing aneurysm rupture and blockage before and after surgery can help doctors plan treatment and reduce the uncertainties in the treatment process.

Methylisothiazolinone pollution inhibited root stem cells and regeneration through auxin transport modification in Arabidopsis thaliana.

Methylisothiazolinone (MIT) is a widely used preservative and biocide to prevent product degradation, yet its potential impact on plant growth remains poorly understood. In this study, we investigated MIT's toxic effects on Arabidopsis thaliana root growth. Exposure to MIT significantly inhibited Arabidopsis root growth, associated with reduced root meristem size and root meristem cell numbers. We explored the polar auxin transport pathway and stem cell regulation as key factors in root meristem function. Our findings demonstrated that MIT suppressed the expression of the auxin efflux carrier PIN1 and major root stem cell regulators (PLT1, PLT2, SHR, and SCR). Additionally, MIT hindered root regeneration by downregulating the quiescent center (QC) marker WOX5. Transcriptome analysis revealed MIT-induced alterations in gene expression related to oxidative stress, with physiological experiments confirming elevated reactive oxygen species (ROS) levels and increased cell death in root tips at concentrations exceeding 50 µM. In summary, this study provides critical insights into MIT's toxicity on plant root development and regeneration, primarily linked to modifications in polar auxin transport and downregulation of genes associated with root stem cell regulation.

Efficient pyramid channel attention network for pathological myopia recognition with pretraining-and-finetuning.

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, the characteristics of pathology distribution in PM are global-local on the fundus image, which plays a significant role in assisting clinicians in diagnosing PM. However, most existing deep neural networks focused on designing complex architectures but rarely explored the pathology distribution prior of PM. To tackle this issue, we propose an efficient pyramid channel attention (EPCA) module, which fully leverages the potential of the clinical pathology prior of PM with pyramid pooling and multi-scale context fusion. Then, we construct EPCA-Net for automatic PM recognition based on fundus images by stacking a sequence of EPCA modules. Moreover, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM recognition by freezing them and treating the EPCA and other attention modules as adapters. In addition, we construct a PM recognition benchmark termed PM-fundus by collecting fundus images of PM from publicly available datasets. The comprehensive experiments demonstrate the superiority of EPCA-Net over state-of-the-art methods in the PM recognition task. For example, EPCA-Net achieves 97.56% accuracy and outperforms ViT by 2.85% accuracy on the PM-fundus dataset. The results also show that our method based on the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of previous methods based on traditional fine-tuning paradigm with fewer tunable parameters, which has the potential to leverage more natural image foundation models to address the PM recognition task in limited medical data regime.

Identification of hub glycolysis-related genes in acute myocardial infarction and their correlation with immune infiltration using bioinformatics analysis.

PURPOSE: Glycolysis and immune metabolism play important roles in acute myocardial infarction (AMI). Therefore, this study aimed to identify and experimentally validate the glycolysis-related hub genes in AMI as diagnostic biomarkers, and further explore the association between hub genes and immune infiltration. METHODS: Differentially expressed genes (DEGs) from AMI peripheral blood mononuclear cells (PBMCs) were analyzed using R software. Glycolysis-related DEGs (GRDEGs) were identified and analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) for functional enrichment. A protein-protein interaction network was constructed using the STRING database and visualized using Cytoscape software. Immune infiltration analysis between patients with AMI and stable coronary artery disease (SCAD) controls was performed using CIBERSORT, and correlation analysis between GRDEGs and immune cell infiltration was performed. We also plotted nomograms and receiver operating characteristic (ROC) curves to assess the predictive accuracy of GRDEGs for AMI occurrence. Finally, key genes were experimentally validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting using PBMCs. RESULTS: A total of 132 GRDEGs and 56 GRDEGs were identified on the first day and 4-6 days after AMI, respectively. Enrichment analysis indicated that these GRDEGs were mainly clustered in the glycolysis/gluconeogenesis and metabolic pathways. Five hub genes (HK2, PFKL, PKM, G6PD, and ALDOA) were selected using the cytoHubba plugin. The link between immune cells and hub genes indicated that HK2, PFKL, PKM, and ALDOA were significantly positively correlated with monocytes and neutrophils, whereas G6PD was significantly positively correlated with neutrophils. The calibration curve, decision curve analysis, and ROC curves indicated that the five hub GRDEGs exhibited high predictive value for AMI. Furthermore, the five hub GRDEGs were validated by RT-qPCR and western blotting. CONCLUSION: We concluded that HK2, PFKL, PKM, G6PD, and ALDOA are hub GRDEGs in AMI and play important roles in AMI progression. This study provides a novel potential immunotherapeutic method for the treatment of AMI.

Performance of low shrinkage Bis-EFMA based bulk-fill dental resin composites.

OBJECTIVES: The purpose of this study was evaluating the performance of new Bis-EFMA based bulk-fill composites with common methacrylate based composites and commercial dental composites. METHODS: The Bis-EFMA monomer was synthesized and the novel Bis-EFMA based bulk-fill composites were prepared. The resin composite samples were co-cultured with human gingival epithelial cells and human dental pulp stem cells to test the biocompatibility. The edge adaptation was observed under a combination of stereoscope and scanning electron microscope. The internal hardness was measured using a Vickers microhardness tester after one-time filling of cavities prepared in extracted teeth. After friction and wear test on the surface of the resin composites, the surface morphology and volume wear of each group were measured by the optical profilometer. The color stability was measured by a colorimeter. RESULTS: Direct contact with human gingival epithelial cells and human dental pulp stem cells did not cause significant changes in their growth density and morphology, indicating good biocompatibility of Bis-EFMA group (p > 0.05). The continuous margin proportion of the Bis-EFMA group was as good as commercial bulk-fill composites (p > 0.05). The sectional microhardness results showed that the Bis-EFMA group had the highest microhardness. After the friction and wear test, the volume wear of the Bis-EFMA group was minimal, indicating its good wear resistance and mechanical strength. Color changes in all resin groups after 28 days of immersion were within the clinically acceptable range. SIGNIFICANCE: The addition of Bis-EFMA demonstrated excellent biocompatibility, edge adaptation and color stability comparable to commonly used clinical bulk-fill composites, along with preferable mechanical strength, friction and wear resistance. Bis-EFMA based bulk-fill composites have the potential to be employed as a bulk filling material in commercial dental composite applications.

A new method for identification of traditional Chinese medicine constitution based on tongue features with machine learning.

BACKGROUND: The theory of Chinese medicine (TCM) constitution contributes to the optimisation of individualised healthcare programmes. However, at present, TCM constitution identification mainly relies on inefficient questionnaires with subjective bias. Efficient and accurate TCM constitution identification can play an important role in individualised medicine and healthcare. OBJECTIVE: Building an efficient model for identifying traditional Chinese medicine constitutions using objective tongue features and machine learning techniques. METHODS: The DS01-A device was applied to collect tongue images and extract features. We trained and evaluated five machine learning models: Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), LightGBM (LGBM), and CatBoost (CB). Among these, we selected the model with the best performance as the base classifier for constructing our heterogeneous ensemble learning model. Using various performance metrics, including classification accuracy, precision, recall, F1 score, and area under curve (AUC), to comprehensively evaluate model performance. RESULTS: A total of 1149 tongue images were obtained and 45 features were extracted, forming dataset 1. RF, LGBM, and CB were selected as the base learners for the RLC-Stacking. On dataset 1, RLC-Stacking1 achieved an accuracy of 0.8122, outperforming individual classifiers. After feature selection, the classification accuracy of RLC-Stacking2 improved to 0.8287, an improvement of 0.00165 compared to RLC-Stacking1. RLC-Stacking2 achieved an accuracy exceeding 0.85 for identifying each TCM constitution type, indicating excellent identification performance. CONCLUSION: The study provides a reliable method for the accurate and rapid identification of TCM constitutions and can assist clinicians in tailoring individualized medical treatments based on personal constitution types and guide daily health care. The information extracted from tongue images serves as an effective marker for objective TCM constitution identification.

Phylodynamics unveils invading and diffusing patterns of dengue virus serotype-1 in Guangdong, China from 1990 to 2019 under a global genotyping framework.

BACKGROUND: The strong invasiveness and rapid expansion of dengue virus (DENV) pose a great challenge to global public health. However, dengue epidemic patterns and mechanisms at a genetic scale, particularly in term of cross-border transmissions, remain poorly understood. Importation is considered as the primary driver of dengue outbreaks in China, and since 1990 a frequent occurrence of large outbreaks has been triggered by the imported cases and subsequently spread to the western and northern parts of China. Therefore, this study aims to systematically reveal the invasion and diffusion patterns of DENV-1 in Guangdong, China from 1990 to 2019. METHODS: These analyses were performed on 179 newly assembled genomes from indigenous dengue cases in Guangdong, China and 5152 E gene complete sequences recorded in Chinese mainland. The genetic population structure and epidemic patterns of DENV-1 circulating in Chinese mainland were characterized by phylogenetics, phylogeography, phylodynamics based on DENV-1 E-gene-based globally unified genotyping framework. RESULTS: Multiple serotypes of DENV were co-circulating in Chinese mainland, particularly in Guangdong and Yunnan provinces. A total of 189 transmission clusters in 38 clades belonging to 22 subgenotypes of genotype I, IV and V of DENV-1 were identified, with 7 Clades of Concern (COCs) responsible for the large outbreaks since 1990. The epidemic periodicity was inferred from the data to be approximately 3 years. Dengue transmission events mainly occurred from Great Mekong Subregion-China (GMS-China), Southeast Asia (SEA), South Asia Subcontinent (SASC), and Oceania (OCE) to coastal and land border cities respectively in southeastern and southwestern China. Specially, Guangzhou was found to be the most dominant receipting hub, where DENV-1 diffused to other cities within the province and even other parts of the country. Genome phylogeny combined with epidemiological investigation demonstrated a clear local consecutive transmission process of a 5C1 transmission cluster (5C1-CN4) of DENV-1 in Guangzhou from 2013 to 2015, while the two provinces of Guangdong and Yunnan played key roles in ongoing transition of dengue epidemic patterns. In contextualizing within Invasion Biology theories, we have proposed a derived three-stage model encompassing the stages of invasion, colonization, and dissemination, which is supposed to enhance our understanding of dengue spreading patterns. CONCLUSIONS: This study demonstrates the invasion and diffusion process of DENV-1 in Chinese mainland within a global genotyping framework, characterizing the genetic diversities of viral populations, multiple sources of importation, and periodic dynamics of the epidemic. These findings highlight the potential ongoing transition trends from epidemic to endemic status offering a valuable insight into early warning, prevention and control of rapid spreading of dengue both in China and worldwide.

A new spider species of Belisana Thorell, 1898 (Araneae, Pholcidae) from Guizhou Province, south-western China.

Background: China exhibits remarkable diversity of the spider genus Belisana Thorell, 1898, with 62 species recorded to date. However, the largest number of Belisana species was found in Yunnan Province (23 ssp.), while only seven species were found in Guizhou Province. New information: In this paper, Belisanawangchengi sp. nov. as a new species is described from Guizhou Province, China.

Enhancing anti-angiogenic immunotherapy for melanoma through injectable metal-organic framework hydrogel co-delivery of combretastatin A4 and poly(I:C).

The interplay between vascularization and macrophage-induced immune suppression plays a crucial role in melanoma treatment. In this study, we propose a novel combination approach to combat melanoma by simultaneously inhibiting tumor vascularization and enhancing macrophage-mediated anti-tumor responses. We investigate the potential of combining combretastatin A4 (CA4), a vascular-disrupting agent, with poly(I:C) (PIC), an immunostimulatory adjuvant. This combination approach effectively suppresses melanoma cell proliferation, disrupts vascularization, and promotes macrophage polarization towards the M1 phenotype for melanoma suppression. To facilitate efficient co-delivery of CA4 and PIC for enhanced anti-angiogenic immunotherapy, we develop an injectable metal-organic framework hydrogel using Zeolitic Imidazolate Framework-8 (ZIF-8) and hyaluronic acid (HA) (ZIF-8/HA). Our findings demonstrate that ZIF-8 enables efficient loading of CA4 and enhances the stability of PIC against RNAase degradation in vitro. Furthermore, the developed co-delivery hydrogel system, PIC/CA4@ZIF-8/HA, exhibits improved rheological properties, good injectability and prolonged drug retention. Importantly, in vivo experiments demonstrate that the PIC/CA4@ZIF-8/HA formulation significantly reduces the dosage and administration frequency while achieving a more pronounced therapeutic effect. It effectively inhibits melanoma growth by suppressing angiogenesis, destroying blood vessels, promoting M1 macrophage infiltration, and demonstrating excellent biocompatibility. In conclusion, our study advances anti-angiogenic immunotherapy for melanoma through the potent combination of PIC/CA4, particularly when administered using the PIC/CA4@ZIF-8/HA formulation. These findings provide a new perspective on clinical anti-angiogenic immunotherapy for melanoma, emphasizing the importance of targeting tumor vascularization and macrophage-mediated immune suppression simultaneously.

Synthetic Microbial Community Promotes Bacterial Communities Leading to Soil Multifunctionality in Desertified Land.

Soil desertification is an important challenge in global soil management, and effectively and stably restoring soil function is an urgent problem. Using synthetic microbial communities (SynComs) is a burgeoning microbial strategy aimed at enhancing soil nutrients through functional synergies among diverse microorganisms; nevertheless, their effectiveness in restoring desertified soils remains unknown. In this study, we conducted a two-year field experiment using a SynCom constructed by in situ probiotic bacteria and set up control, chemical fertilizer, and combined SynCom-chemical fertilizer (combined fertilizer) treatments to investigate the linkage between microbial communities and soil multifunctionality in the soil surface layer (0-10 cm). Both the bacterial and fungal communities differed the most under the combined fertilizer treatment compared to the control. The bacterial communities differed more under treatments of the SynCom than the chemical fertilizer, while the fungal communities differed more under the chemical fertilizer treatment than the SynCom treatment. Regarding soil function, the SynCom strengthened the correlation between enzyme activities and both bacterial communities and functional properties. pH and available potassium were the main influencing factors under the chemical fertilizer and combined fertilizer treatments. The beta-diversity of the bacterial communities was significantly correlated with soil multifunctionality. Random forest analyses showed that the SynCom significantly enhanced the bacterial communities, driving soil multifunctionality, and that some potential microbial taxa drove multiple nutrient cycles simultaneously. In summary, the SynCom effectively increased the abundance of most carbon, nitrogen, and phosphorus functional genes as well as soil enzyme activities. The bacterial community composition contributed significantly to soil multifunctionality. Hence, the development of novel microbial agents holds significant potential for improving soil functionality and managing desertification.

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Biological nitrogen (N) fixation is an important source of N in terrestrial ecosystems, but the response of soil microbial N fixation rate to N deposition in different forest ecosystems still remains uncertain. We conducted a field N addition experiment to simulate atmosphere N deposition in subtropical Pinus taiwanensis and Castanopsis faberi forests. We set up three levels of nitrogen addition using urea as the N source: 0 (control), 40 (low N), and 80 g N·hm-2·a-1(high N) to examine the chemical properties, microbial biomass C, enzyme activities, and nifH gene copies of top soils (0-10 cm). We also measured the microbial N fixation rate using the 15N labeling method. Results showed that N addition significantly reduced the soil microbial N fixation rate in the P. taiwanensis and C. faberi forests by 29%-33% and 10%-18%, respectively. Nitrogen addition significantly reduced N-acquiring enzyme (i.e., ß-1, 4-N-acetylglucosaminidase) activity and nifH gene copies in both forest soils. There was a significant positive correlation between the microbial N fixation rate and soil dissolved organic C content in the P. taiwanensis forest, but a significant negative relationship between the rate of soil microbial nitrogen fixation and NH4+-N content in the C. faberi forest. Overall, soil microbial N fixation function in the P. taiwanensis forest was more sensitive to N addition than that in the C. faberi forest, and the factors affecting microbial N fixation varied between the two forest soils. The study could provide insights into the effects of N addition on biological N fixation in forest ecosystems, and a theoretical basis for forest management.

Optimization of High-Activity earthworm fibrinolytic enzyme extraction methods and protein component analysis.

OBJECTIVE: Optimize the extraction process of earthworm fibrinolytic enzyme. METHODS: Chinese common earthworms underwent a series of purification processes, including grinding, salting out, hydrophobic medium chromatography, ammonium sulfate precipitation, and ion exchange chromatography, to obtain purified earthworm fibrinolytic enzyme. RESULTS: Utilizing Pheretima aspergillum as the starting material, we discovered that the specific activity of lumbrokinase extracted via ammonium sulfate precipitation was 58 U/mg, noticeably surpassing that achieved through heat precipitation and ethanol precipitation methods. After undergoing two rounds of chromatographic separations employing hydrophobic affinity chromatography and anion exchange chromatography, the specific activity of the lumbrokinase protein soared to 9267 U/mg, significantly exceeding the 3,178 U/mg specific activity attained through industrial extraction methods. DISCUSSION: The development of a novel crude extraction method for lumbrokinase protein can significantly boost its activity and purity. The discovery of a high-efficiency purification method and the identification of protein components within highly active lumbrokinase pave the way for further investigations into these proteins.

Study on the enhancement of citric acid chemical leaching of contaminated soil by modified nano zero-valent iron.

This study aimed to evaluate the effect of modified nanoscale zero-valent iron (SAS-nZVI) on chemical leaching of lead and cadmium composite contaminated soil by citric acid (CA). The synthesized SAS-nZVI was used as a leaching aid to improve the removal rate of soil heavy metals (HMs) by CA chemical leaching. The effects of various factors such as SAS-nZVI dosage, elution temperature and elution time were studied. At the same time, the effect of chemical leaching on the basic physical and chemical properties of soil and the morphology of HMs was evaluated. The results show that when the SAS-nZVI dosage is 2.0 g/L, the leaching temperature is 25 °C, and the leaching time is 720 min, the maximum removal rates of Pb and Cd in the soil are 77.64% and 97.15% respectively. The experimental results were evaluated using elution and desorption kinetic models (Elovich model, double constant model, diffusion model). The elution and desorption process of Pb and Cd in soil by SAS-nZVI-CA fitted well with the double-constant model, indicating that the desorption kinetic process of Pb and Cd is a heterogeneous diffusion process, and the elution process is controlled by diffusion factors. After leaching with SAS-nZVI-CA, the physical and chemical properties of the soil changed little, the mobility and toxicity of HMs in the soil were reduced, and the HMs content in the leaching waste liquid was reduced. It can be concluded that SAS-nZVI enhances the efficiency of CA in extracting Pb and Cd from soil, minimizes soil damage resulting from chemical leaching technology, and alleviates the challenges associated with treating leaching waste liquid.

Feeding live yeast (Saccharomyces cerevisiae) improved performance of mid-lactation dairy cows by altering ruminal bacterial communities and functions of serum antioxidation and immune responses.

BACKGROUND: The utilization of live yeast (Saccharomyces cerevisiae, YE) in dairy cows is gaining traction in dairy production as a potential strategy to improve feed efficiency and milk yield. However, the effects of YE on dairy cow performance remain inconsistent across studies, leaving the underlying mechanisms unclear. Hence, the primary aim of this study was to investigate the impact of YE supplementation on lactation performance, ruminal microbiota composition and fermentation patterns, as well as serum antioxidant capacity and immune functions in dairy cows. RESULTS: Supplementation with YE (20 g/d/head) resulted in enhancements in dairy cow's dry matter intake (DMI) (P = 0.016), as well as increased yields of milk (P = 0.002) and its components, including solids (P = 0.003), fat (P = 0.014), protein (P = 0.002), and lactose (P = 0.001) yields. The addition of YE led to significant increases in the concentrations of ammonia nitrogen (NH3-N) (P = 0.023), acetate (P = 0.005), propionate (P = 0.025), valerate (P = 0.003), and total volatile fatty acids (VFAs) (P < 0.001) in rumen fermentation parameters. The analysis of 16s rRNA gene sequencing data revealed that the administration of YE resulted in a rise in the relative abundances of three primary genera including Ruminococcus_2 (P = 0.010), Rikenellaceae_RC9_gut_group (P = 0.009), and Ruminococcaceae_NK4A214_group (P = 0.054) at the genus level. Furthermore, this increase was accompanied with an enriched pathway related to amino acid metabolism. Additionally, enhanced serum antioxidative (P < 0.05) and immune functionalities (P < 0.05) were also observed in the YE group. CONCLUSIONS: In addition to improving milk performance, YE supplementation also induced changes in ruminal bacterial community composition and fermentation, while enhancing serum antioxidative and immunological responses during the mid-lactation stage. These findings suggest that YE may exert beneficial effects on both rumen and blood metabolism in mid-lactation dairy cows.

Pyramid Pixel Context Adaption Network for Medical Image Classification With Supervised Contrastive Learning.

Spatial attention (SA) mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency modeling. However, it may perform poorly in medical image analysis. Unfortunately, the existing efforts are often unaware that long-range dependency modeling has limitations in highlighting subtle lesion regions. To overcome this limitation, we propose a practical yet lightweight architectural unit, pyramid pixel context adaption (PPCA) module, which exploits multiscale pixel context information to recalibrate pixel position in a pixel-independent manner dynamically. PPCA first applies a well-designed cross-channel pyramid pooling (CCPP) to aggregate multiscale pixel context information, then eliminates the inconsistency among them by the well-designed pixel normalization (PN), and finally estimates per pixel attention weight via a pixel context integration. By embedding PPCA into a DNN with negligible overhead, the PPCA network (PPCANet) is developed for medical image classification. In addition, we introduce supervised contrastive learning to enhance feature representation by exploiting the potential of label information via supervised contrastive loss (CL). The extensive experiments on six medical image datasets show that the PPCANet outperforms state-of-the-art (SOTA) attention-based networks and recent DNNs. We also provide visual analysis and ablation study to explain the behavior of PPCANet in the decision-making process.

Performance test and analysis of tetracycline degradation using a Micro-Nano Bubble system.

Antibiotics and organic residues from Tetracycline (TC) and other pharmaceuticals administered to aquatic living organism have negative impacts on aquatic environment by killing-off non-target living organisms and developing antibiotic-resistant bacteria. In this study, Micro-Nano Bubble (MNB) system was used to remove TC residues. MNB system demonstrated good level of degradation efficiency, as resulted in experiment where in time of 100 min, the TC degraded at rate of 82.66% from its initial concentration of TC when the initial concentration was 1 mg/L. When the initial concentration was increased to 10 mg/L, MNB system degraded TC at 64.35% of their initial, this means MNB system demonstrated good level of efficiency for TC removal and indicated that it is more efficient in TC degradation under the conditions of low initial TC concentration and high availability of dissolved oxygen (DO). In the system as the temperature increased there was a significant decrease in DO saturation which was related to the TC complex structure that contain multiple function groups such as amino groups, hydroxyl and carboxyl which possess high strong affinity with oxygen that leads to their adsorption onto bubble surface. This study provides significant insights into the application of MNB system for the removal of organic residues within aquatic ecosystem and underscores the need for further exploration of MNB technology for environmental remediation.

A Lindley-binomial model for analyzing the proportions with sparseness and excessive zeros.

Proportional data arise frequently in a wide variety of fields of study. Such data often exhibit extra variation such as over/under dispersion, sparseness and zero inflation. For example, the hepatitis data present both sparseness and zero inflation with 19 contributing non-zero denominators of 5 or less and with 36 having zero seropositive out of 83 annual age groups. The whitefly data consists of 640 observations with 339 zeros (53%), which demonstrates extra zero inflation. The catheter management data involve excessive zeros with over 60% zeros averagely for outcomes of 193 urinary tract infections, 194 outcomes of catheter blockages and 193 outcomes of catheter displacements. However, the existing models cannot always address such features appropriately. In this paper, a new two-parameter probability distribution called Lindley-binomial (LB) distribution is proposed to analyze the proportional data with such features. The probabilistic properties of the distribution such as moment, moment generating function are derived. The Fisher scoring algorithm and EM algorithm are presented for the computation of estimates of parameters in the proposed LB regression model. The issues on goodness of fit for the LB model are discussed. A limited simulation study is also performed to evaluate the performance of derived EM algorithms for the estimation of parameters in the model with/without covariates. The proposed model is illustrated through three aforementioned proportional datasets.

Application of the TaqMan ARMS-PCR Approach for Genotyping Drug-Induced Hearing Loss Using Dried Blood Samples.

A single nucleotide variant in mitochondrial DNA (mtDNA) 1555A>G is associated with drug-induced hearing loss. For the 1555A>G mutation site, 1555A wild-type and 1555G mutant-type plasmids were constructed, respectively. In this study, a PCR method based on the TaqMan amplification refractory mutation system was proposed to detect mtDNA 1555A>G. A common upstream primer, a common TaqMan probe, and two downstream allele-specific primers with mismatched bases were designed. One-step amplification and detection of the wild-type and mutant type at the 1555 site were realized for the deafness-related gene through two reactions. Based on this detection method, the minimum detection limit of the wild-type and mutant type detection systems for plasmids was 50 copies/µL. The minimum sensitivity for the detection of nucleic acids in real dried blood spot (DBS) samples was 0.1 ng/µL. In the normal DBS DNA sample, the detection limit of the mutation abundance reached 0.78%. The specificity of the detection method was 100%, and the coefficient of variation was less than 3.36%. This approach was validated using clinical DNA extracted from 113 DBS samples of newborns. Additionally, it showed 100% agreement with bi-directional Sanger sequencing. It can be used as an optional method for the clinical detection of deafness-related genes.

Development and Validation of the Coronary Heart Disease Scale Among the System of Quality of Life Instruments for Chronic Diseases QLICD-CHD (V2.0) Based on Classical Test Theory and Generalizability Theory.

Objective: Coronary heart disease (CHD) is a common and frequent disease with a long and incurable course, and the quality of life of patients is severely reduced. This study was to develop and validate a quality of life scale for patients with CHD based on the Chinese context. Methods: The scale QLICD-CHD (V2.0) was developed based on the QLICD-CHD (V1.0), using a programmed decision procedures. Based on the data measuring QoL 3 times before and after treatments from 189 patients with CHD, the psychometric properties of the scale were evaluated with respect to validity, reliability and responsiveness employing correlation analysis, multi-trait scaling analysis, structural equation modeling, t-test and also G-study and D-study of generalizability theory analysis. The SF-36 scale was used as the criterion to evaluate the criterion-related validity. Paired t tests were conducted to evaluate the responsiveness on each domain/facet as well as the total of the scale, with Standardized Response Mean (SRM) being calculated. Results: The QLICD-CHD (V2.0) has been developed with 42 items in 4 domains. The Cronbach's α of the general module, the specific module and the total scale were 0.91, 0.92 and 0.91 respectively. The overall score and the test-retest reliability coefficients in all domains are higher than 0.60, except for the specific module. Correlation and factor analysis confirmed good construct validity and criterion-related validity. After treatments, the overall score and score of all domains have statistically significant changes (P<0.01). The SRM of domain-level score ranges from 0.27 to 0.50. Generalizability Theory further confirm the reliability of the scale through more accurate variance component studies. Conclusion: The QLICD-CHD (V2.0) could be used as a useful instrument in assessing QoL for patients with CHD, with good psychometric properties.

Transcutaneous electrical acupoint stimulation reduces postoperative patients' length of stay and hospitalization costs: A systematic review and meta-analysis.

OBJECTIVE: To study the effects of transcutaneous electrical acupoint stimulation (TEAS) on length of stay (LOS) and hospitalization costs in postoperative inpatients. METHODS: Two researchers collectively searched PubMed, Embase, Cochrane Library, China Network Knowledge Infrastructure and Wanfang Database. The search time was set from the beginning to April 25, 2023, to identify randomized controlled trials articles that met the criteria. Statistical analyses were performed using the Stata software (version 16.0). The risk of bias was assessed using the Cochrane risk-of-bias tool, and publication bias was evaluated using a funnel plot and Egger's test. The quality of evidence was assessed according to the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: Thirty-four randomized controlled trials were included. The main results showed that TEAS reduced hospitalization costs (standardized mean difference (SMD)=-1.92; 95% confidence interval (CI) -3.40, -0.43), LOS (SMD=-1.00; 95% CI -1.30, -0.70) and postoperative LOS (SMD=-0.70; 95% CI -0.91, -0.49) in postoperative patients. Subgroup analyses further revealed that TEAS was effective in reducing both the overall and postoperative LOS in patients undergoing multiple surgical procedures. It is worth noting that the observed heterogeneity in the results may be attributed to variations in surgical procedures, stimulation frequencies, and stimulation points utilized in different trials. CONCLUSIONS: TEAS can help postoperative patients reduce their LOS and hospitalization cost. However, considering the bias identified and heterogeneity, the results of this review should be interpreted with caution.