Computerised modified paramedian approach technique versus conventional midline approach technique of lumbar puncture: a randomised control trial protocol.

INTRODUCTION: The lumbar puncture (LP) technique is widely used for diagnostic and therapeutic purposes. In recent years, the paramedian approach technique (PAT) has gained increasing interest due to its advantages over the conventional midline approach technique (MAT) that has been traditionally employed in clinical practice for LP. However, there have been inconsistent discussions regarding the efficacy of different LP techniques. Based on digital virtual human and computer simulation techniques, a new approach called computerised modified PAT (CMPAT) was proposed. Therefore, the aim of this study is to discuss a randomised controlled trial (RCT) protocol to investigate and compare the effects of CMPAT and MAT in patients undergoing LP. METHODS AND ANALYSIS: We will conduct a prospective, multicentre RCT. The study will recruit 84 patients aged 18-99 years who require LP. Participants will be randomly assigned to either the CMPAT treatment group (group A) or the MAT treatment group (group B). The primary outcome measure will be the number of needle insertion attempts required for a successful LP. Secondary outcomes will include the puncture success rate, pain assessment in the back, head, and legs, and the occurrence of complications. The measurement of these secondary outcomes will be taken during the procedure, as well as at specific time points: 30 min, 6 hours, 1 day, 3 days, 7 days, 2 weeks and 4 weeks after the procedure. Pain levels will be assessed using a Numerical Rating Scale. ETHICS AND DISSEMINATION: Ethical approval (2022YF052-01) has been obtained from the Ethics Committee of Fujian Medical University Union Hospital, Fuzhou, China. The research findings will be published in an international peer-reviewed scientific journal and presented at scientific conferences. TRIAL REGISTRATION NUMBER: ChiCTR2300067937.

Quality assessment of non-mydriatic fundus photographs for glaucoma screening in primary healthcare centres: a real-world study.

BACKGROUND: This study assessed the quality distribution of non-mydriatic fundus photographs (NMFPs) in real-world glaucoma screening and analysed its influencing factors. METHODS: This cross-sectional study was conducted in primary healthcare centres in the Yinzhou District, China, from 17 March to 3 December 2021. The quality distribution of bilateral NMFPs was assessed by the Digital Reading Department of the Eye Hospital of Wenzhou Medical University. Generalised estimating equations and logistic regression models identified factors affecting image quality. RESULTS: A total of 17 232 photographs of 8616 subjects were assessed. Of these, 11.9% of images were reliable for the right eyes, while only 4.6% were reliable for the left eyes; 93.6% of images were readable in the right eyes, while 90.3% were readable in the left eyes. In adjusted models, older age was associated with decreased odds of image readability (adjusted OR (aOR)=1.07, 95% CI 1.06~1.08, p<0.001). A larger absolute value of spherical equivalent significantly decreased the odds of image readability (all p<0.001). Media opacity and worse visual acuity had a significantly lower likelihood of achieving readable NMFPs (aOR=1.52, 95% CI 1.31~1.75; aOR=1.70, 95% CI 1.42~2.02, respectively, all p<0.001). Astigmatism axes within 31°~60° and 121°~150° had lower odds of image readability (aOR=1.35, 95% CI 1.11~1.63, p<0.01) than astigmatism axes within 180°±30°. CONCLUSIONS: The image readability of NMFPs in large-scale glaucoma screening for individuals 50 years and older is comparable with relevant studies, but image reliability is unsatisfactory. Addressing the associated factors may be vital when implementing ophthalmological telemedicine in underserviced areas. TRIAL REGISTRATION NUMBER: ChiCTR2200059277.

Overlooked effect of ordinary inorganic ions on polyaluminum-chloride coagulation treatment.

Application of poly-aluminum chloride (PACl) coagulant is a popular mode of water treatment worldwide because of the high capacity of PACl to neutralize charge. The manufacture and use of PACls with various basicities in different regions around the world suggest that the characteristics of the raw water are important determinants of the efficacy of PACl application. However, attention has not been fully paid to the effects of water quality other than the substances to be removed. In this study, two typical PACls with different basicities were used to investigate why the performance of PACls depends on the characteristics of the raw water. We focused on the concentrations of inorganic ions in the raw water. Use of high-basicity PACl (HB-PACl) with a high content of polymeric-colloidal species (Alb+Alc) resulted in very slow floc formation and little turbidity removal in raw water with low concentrations of sulfate ions. The performance of the HB-PACl was inferior to that of normal-basicity PACl (NB-PACl), although the charge-neutralization capacity of the HB-PACl was higher. Rates of floc formation were strongly correlated with the rate of aluminum precipitation by hydrolysis reaction, which was identified as an indicator for evaluating the compatibility of raw water with PACl treatment. Among the common ions in natural water, the sulfate ion had the greatest ability to hydrolyze and precipitate PACl because of its divalency and tetrahedral structure. This conclusion followed from experimental results showing similar effects for selenate and chromate ions as for sulfate ions and somewhat smaller effects for thiosulfate ions. Bicarbonate ions and natural organic matter affected PACl hydrolysis-precipitation, but chloride ions, nitrate ions, and cations had little effect on PACl hydrolysis-precipitation. Interestingly, the abilities of sulfate ions to hydrolyze HB-PACl and NB-PACl were very similar, but bicarbonate ions were less effective in hydrolyzing HB-PACl than NB-PACl, and bicarbonate ions contributed little to the hydrolysis-precipitation of HB-PACl in raw water with normal alkalinity. Therefore, sufficient coagulation with HB-PACl therefore usually requires a certain concentration of sulfate ions in water to be treated. The implication is that which anions are most influential to the hydrolysis-precipitation of PACl, and thus to PACl's coagulation ability depends on the constituents of the PACl.

Facilitators and Barriers to Using Selective Laser Trabeculoplasty (SLT) as First-Line Treatment for Glaucoma: Physician and Patient Views Gathered during an Exploratory Descriptive Qualitative Study.

PURPOSE: To explore the perception of selective laser trabeculoplasty (SLT) among physicians and patients and the acceptance of using SLT as first-line treatment for glaucoma. METHODS: Exploratory descriptive qualitative study based on semi-structured interviews with glaucoma specialists and patients in two eye hospital of Zhejiang and Guangdong Provinces, China. Data were analyzed using the thematic analysis framework approach. RESULTS: 11 glaucoma specialists and 12 glaucoma patients were interviewed. Four themes were identified in the data: Physicians' preferences for treatment types, patient views on treatment types, decision-making during the physician-patient encounter and feasibility of SLT as a first-line therapy. Advantages of SLT include safety and repeatability with limited side effects. However, concerns about the durability of the effect of the treatment were often mentioned by both physicians and patients. Some factors such as practice preference, personal motivation and patient characteristics may influence treatment choice. Most patients lack knowledge about SLT and hold high expectations of their treatments. Physicians report insufficient evidence supporting the use of SLT as first line therapy. Physicians report the need for locally relevant, evidence-based guidelines regarding the use of SLT in the treatment of glaucoma. CONCLUSIONS: SLT was suggested as the first-line treatment of glaucoma due to its reliable efficacy and potential advantage. Results from our study offer important insight into barriers of increasing the uptake of SLT, which also provides some guidance for the use of SLT in the future.

Automated segmentation of the optic disc from fundus images using an asymmetric deep learning network.

Accurate segmentation of the optic disc (OD) regions from color fundus images is a critical procedure for computer-aided diagnosis of glaucoma. We present a novel deep learning network to automatically identify the OD regions. On the basis of the classical U-Net framework, we define a unique sub-network and a decoding convolutional block. The sub-network is used to preserve important textures and facilitate their detections, while the decoding block is used to improve the contrast of the regions-of-interest with their background. We integrate these two components into the classical U-Net framework to improve the accuracy and reliability of segmenting the OD regions depicted on color fundus images. We train and evaluate the developed network using three publicly available datasets (i.e., MESSIDOR, ORIGA, and REFUGE). The results on an independent testing set (n=1,970 images) show a segmentation performance with an average Dice similarity coefficient (DSC), intersection over union (IOU), and Matthew's correlation coefficient (MCC) of 0.9377, 0.8854, and 0.9383 when trained on the global field-of-view images, respectively, and 0.9735, 0.9494, and 0.9594 when trained on the local disc region images. When compared with the other three classical networks (i.e., the U-Net, M-Net, and Deeplabv3) on the same testing datasets, the developed network demonstrates a relatively higher performance.

Link Prediction through Deep Generative Model.

Inferring missing links based on the currently observed network is known as link prediction, which has tremendous real-world applications in biomedicine, e-commerce, social media, and criminal intelligence. Numerous methods have been proposed to solve the link prediction problem. Yet, many of these methods are designed for undirected networks only and based on domain-specific heuristics. Here we developed a new link prediction method based on deep generative models, which does not rely on any domain-specific heuristic and works for general undirected or directed complex networks. Our key idea is to represent the adjacency matrix of a network as an image and then learn hierarchical feature representations of the image by training a deep generative model. Those features correspond to structural patterns in the network at different scales, from small subgraphs to mesoscopic communities. When applied to various real-world networks from different domains, our method shows overall superior performance against existing methods.

Sulfate ion in raw water affects performance of high-basicity PACl coagulants produced by Al(OH)3 dissolution and base-titration: Removal of SPAC particles by coagulation-flocculation, sedimentation, and sand filtration.

Many PACl (poly-aluminum chloride) coagulants with different characteristics have been trial-produced in laboratories and commercially produced, but the selection of a proper PACl still requires empirical information and field testing. Even PACls with the same property sometimes show different coagulation performances. In this study, we compared PACls produced by AlCl3-titration and Al(OH)3-dissolution on their performance during coagulation-flocculation, sedimentation, and sand filtration (CSF) processes. The removal targets were particles of superfine powdered activated carbon (SPAC), which are used for efficient adsorptive removal of micropollutants, but strict removal of SPAC is required because of the high risk of their leakage after CSF. PACls of high-basicity produced by AlCl3-titration and Al(OH)3-dissolution were the same in terms of the ferron assay and colloid charge, but their performance in CSF were completely different. High-basicity Al(OH)3-dissolution PACls formed large floc particles and yielded very few remaining SPAC particles in the filtrate, whereas high-basicity AlCl3-titration PACls did not form large floc particles. High-basicity PACls produced by Al(OH)3-dissolution were superior to low-basicity PACl in lowering remaining SPAC particles by the same method because of their high charge neutralization capacity, although their floc formation ability was similar or slightly inferior. However, high-basicity Al(OH)3-dissolution PACl was inferior when the sulfate ion concentration in the raw water was low. Sulfate ions were required in the raw water for high-basicity PACls to be effective in floc formation. In particular, very high sulfate concentrations were required for high-basicity AlCl3-titration PACls. The rate of hydrolysis, which is related to the polymerization of aluminum species, is a key property, besides charge neutralization capacity, for proper coagulation, including formation of large floc particles. The aluminum species in the high-basicity PACls, in particular that produced by AlCl3-titration, was resistant to hydrolysis, but sulfate ions in raw water accelerated the rate of hydrolysis and thereby facilitated floc formation. Normal-basicity Al(OH)3-dissolution PACl was hydrolysis-prone, even without sulfate ions. Aluminum species in the high-basicity AlCl3-titration PACl were mostly those with a molecular weight (MW) of 1-10 kDa, whereas those of high-basicity Al(OH)3-dissolution PACls were mostly characterized by a MW > 10 kDa. Normal-basicity Al(OH)3-dissolution PACl was the least polymerized and contained monomeric species.

Revealing Complex Ecological Dynamics via Symbolic Regression.

Understanding the dynamics of complex ecosystems is a necessary step to maintain and control them. Yet, reverse-engineering ecological dynamics remains challenging largely due to the very broad class of dynamics that ecosystems may take. Here, this challenge is tackled through symbolic regression, a machine learning method that automatically reverse-engineers both the model structure and parameters from temporal data. How combining symbolic regression with a "dictionary" of possible ecological functional responses opens the door to correctly reverse-engineering ecosystem dynamics, even in the case of poorly informative data, is shown. This strategy is validated using both synthetic and experimental data, and it is found that this strategy is promising for the systematic modeling of complex ecological systems.