DiatomNet v1.0: A novel approach for automatic diatom testing for drowning diagnosis in forensically biomedical application.

BACKGROUND AND OBJECTIVE: Diatom testing is supportive for drowning diagnosis in forensic medicine. However, it is very time-consuming and labor-intensive for technicians to identify microscopically a handful of diatoms in sample smears, especially under complex observable backgrounds. Recently, we successfully developed a software, named DiatomNet v1.0 intended to automatically identify diatom frustules in a whole slide under a clear background. Here, we introduced this new software and performed a validation study to elucidate how DiatomNet v1.0 improved its performance with the influence of visible impurities. METHODS: DiatomNet v1.0 has an intuitive, user-friendly and easy-to-learn graphical user interface (GUI) built in the Drupal and its core architecture for slide analysis including a convolutional neural network (CNN) is written in Python language. The build-in CNN model was evaluated for diatom identification under very complex observable backgrounds with mixtures of common impurities, including carbon pigments and sand sediments. Compared to the original model, the enhanced model following optimization with limited new datasets was evaluated systematically by independent testing and random control trials (RCTs). RESULTS: In independent testing, the original DiatomNet v1.0 was moderately affected, especially when higher densities of impurities existed, and achieved a low recall of 0.817 and F1 score of 0.858 but good precision of 0.905. Following transfer learning with limited new datasets, the enhanced version had better results, with recall and F1 score values of 0.968. A comparative study on real slides showed that the upgraded DiatomNet v1.0 obtained F1 scores of 0.86 and 0.84 for carbon pigment and sand sediment, respectively, slightly worse than manual identification (carbon pigment: 0.91; sand sediment: 0.86), but much less time was needed. CONCLUSIONS: The study verified that forensic diatom testing with aid of DiatomNet v1.0 is much more efficient than traditionally manual identification even under complex observable backgrounds. In terms of forensic diatom testing, we proposed a suggested standard on build-in model optimization and evaluation to strengthen the software's generalization in potentially complex conditions.

Research Progress of Automatic Diatom Test by Artificial Intelligence.

Diatom test is the main laboratory test method in the diagnosis of drowning in forensic medicine. It plays an important role in differentiating the antemortem drowning from the postmortem drowning and inferring drowning site. Artificial intelligence (AI) automatic diatom test is a technological innovation in forensic drowning diagnosis which is based on morphological characteristics of diatom, the application of AI algorithm to automatic identification and classification of diatom in tissues and organs. This paper discusses the morphological diatom test methods and reviews the research progress of automatic diatom recognition and classification involving AI algorithms. AI deep learning algorithm can assist diatom testing to obtain objective, accurate, and efficient qualitative and quantitative analysis results, which is expected to become a new direction of diatom testing research in the drowning of forensic medicine in the future.

Comparison among Four Deep Learning Image Classification Algorithms in AI-based Diatom Test.

OBJECTIVES: To select four algorithms with relatively balanced complexity and accuracy among deep learning image classification algorithms for automatic diatom recognition, and to explore the most suitable classification algorithm for diatom recognition to provide data reference for automatic diatom testing research in forensic medicine. METHODS: The "diatom" and "background" small sample size data set (20 000 images) of digestive fluid smear of corpse lung tissue in water were built to train, validate and test four convolutional neural network (CNN) models, including VGG16, ResNet50, InceptionV3 and Inception-ResNet-V2. The receiver operating characteristic curve (ROC) of subjects and confusion matrixes were drawn, recall rate, precision rate, specificity, accuracy rate and F1 score were calculated, and the performance of each model was systematically evaluated. RESULTS: The InceptionV3 model achieved much better results than the other three models with a balanced recall rate of 89.80%, a precision rate of 92.58%. The VGG16 and Inception-ResNet-V2 had similar diatom recognition performance. Although the performance of diatom recall and precision detection could not be balanced, the recognition ability was acceptable. ResNet50 had the lowest diatom recognition performance, with a recall rate of 55.35%. In terms of feature extraction, the four models all extracted the features of diatom and background and mainly focused on diatom region as the main identification basis. CONCLUSIONS: Including the Inception-dependent model, which has stronger directivity and targeting in feature extraction of diatom. The InceptionV3 achieved the best performance on diatom identification and feature extraction compared to the other three models. The InceptionV3 is more suitable for daily forensic diatom examination.

Bibliometrics Analysis in English and Chinese Literature on Drowning in Forensic Medicine from 1991 to 2020.

OBJECTIVES: To explore the research hotspots and development trends of the field of forensic drowning from 1991 to 2020 by bibliometrics methods. METHODS: Based on Web of Science, CNKI database, Wanfang Data knowledge service platform, python 3.9.2, CiteSpace 5.8.R3, Gephi 0.9.2, etc. were used to analyze the publishing trends, countries/regions, institutions, authors and topics of the study on drowning. RESULTS: A total of 631 English literature were obtained, including 59 articles from Chinese authors, and 386 Chinese literature were obtained. The Chinese and English journals with the largest number of related literatures were Chinese Journal of Forensic Science (80 articles) and Forensic Science International (106 articles), respectively. Japan published the most articles in English, and China ranked third. Osaka City Univ (Japan, 28 articles) published the most English articles, and Guangzhou Forens Sci Inst (China, 22 articles) ranked second. Among Chinese literature, Guangzhou Forens Sci Inst (32 articles) published the most. The topic analysis of Chinese and English literature showed that diatom examination, virtual autopsy, postmortem biochemical examination, the nature of death, and postmortem submersion interval were the hot spots of current research, but English literature had more studies on new technologies and methods, while Chinese literature was more inclined to practice, application and experience summary. CONCLUSIONS: The number of literature in forensic medicine on drowning is relatively stable. The scope of international and domestic collaborations in this field is still limited. The automated examination of diatoms, the establishment of diatom DNA barcodes and virtual autopsy will be the most important research hotspots in the coming period and are expected to achieve breakthroughs in drowning diagnosis, drowning location inference, postmortem submersion interval estimation, etc.

Effectiveness of acupuncture for multiple sclerosis: A protocol for systematic review and meta-analysis.

BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease characterized by white matter inflammatory demyelination in the central nervous system (CNS). Its clinical manifestations include decreased vision, diplopia, and limb weakness. As a green and simple traditional Chinese medicine method, acupuncture is gradually recognized by the public. At present, there is still a lack of systematic evaluation on acupuncture treatment of MS. This study aims to evaluate the safety and effectiveness of acupuncture in the treatment of MS, in order to provide a basis for clinical decision-making. METHODS: Randomized controlled trials (RCTs) of acupuncture for MS will be searched in the relevant database, including PubMed, MEDLINE, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure Database (CNKI), WanFang Database, China Biology Medicine Database (CBM), Chinese Scientific Journals Database (VIP), regardless of publication date, or language. All relevant RCTs of electronic searches will be exported to EndNote X9.1 software. Data analysis will be performed using RevMan 5.4 and STATA 14.2 software. RESULTS: Our study aims to explore the efficacy of acupuncture for MS and to provide up-to-date evidence for clinical of MS. We will publish our research results in peer review journals. CONCLUSION: This study will perform a comprehensive systematic review and meta-analysis on the efficacy of acupuncture for MS, making up for the lack of relevant evidence of the clinical use of acupuncture.

The effect of acupuncture used for cervical spondylosis of vertebral artery type: A protocol for systematic review and meta-analysis.

BACKGROUND: Cervical spondylosis of vertebral artery type is a common clinical disease. With the change of people's lifestyle and the improvement of people who work at desks, its incidence is also increasing, which can seriously affect people's normal life and work. Acupuncture has been gradually accepted and recognized by the public for its green, simple and safe characteristics. In this systematic review, we aimed to evaluate the effect and safety for patients with cervical spondylosis of vertebral artery type to provide evidence for clinical decision making. METHODS: We will search the following 8 databases from their inception to November 2021: Web of Science, the Cochrane Library, PubMed, Embase, Chinese Biomedicine, China National Knowledge Infrastructure, Chinese Scientific Journals Database, and the WanFang Database. All relevant randomized controlled trials (RCTs) that meet the inclusion criteria will be included in our analysis. Literature screening, data extraction and literature quality assessment will be carried out in a step. Data analysis will be performed using RevMan 5.4 software. RESULTS: Based on the results of this study, we will evaluate the safety and effectiveness of acupuncture in the treatment of vertebral artery type cervical spondylosis. CONCLUSION: This study will provide strong evidence-based medical evidence for acupuncture in treating cervical spondylosis of vertebral artery type. PROSPERO REGISTRATION NUMBER: CRD42021293053.

Label-Free Diagnosis of Pulmonary Fat Embolism Using Fourier Transform Infrared (FT-IR) Spectroscopic Imaging.

The diagnosis of pulmonary fat embolism (PFE) is of great significance in the field of forensic medicine because it can be considered a major cause of death or a vital reaction. Conventional histological analysis of lung tissue specimens is a widely used method for PFE diagnosis. However, variable and labor-intensive tissue staining procedures impede the validity and informativeness of histological image analysis. To obtain complete information from tissues, a method based on infrared imaging of unlabeled tissue sections was developed to identify pulmonary fat emboli in the present study. We selected 15 PFE-positive lung samples and 15 PFE-negative samples from real cases. Oil red O (ORO) staining and infrared spectral imaging collection were both performed on all lung tissue samples. And the fatty tissue of the abdominal wall and the embolized lipid droplets in the lungs were taken for comparison. The results of the blind, evaluation by pathologists, showed good agreement between the infrared spectral imaging of the lung tissue and the standard histological stained images. Fourier transform infrared (FT-IR) spectroscopic imaging significantly simplifies the typical painstakingly laborious histological staining procedure. And we found a difference between lipid droplets embolized in abdominal wall fat and lung tissue.

Interfacial behavior of phospholipid monolayers revealed by mesoscopic simulation.

A mesoscopic model with molecular resolution is presented for dipalmitoyl phosphatidylcholine (DPPC) and palmitoyl oleoyl phosphatidylcholine (POPC) monolayer simulations at the air-water interface using many-body dissipative particle dynamics (MDPD). The parameterization scheme is rigorously based on reproducing the physical properties of water and alkane and the interfacial property of the phospholipid monolayer by comparison with experimental results. Using much less computing cost, these MDPD simulations yield a similar surface pressure-area isotherm as well as similar pressure-related morphologies as all-atom simulations and experiments. Moreover, the compressibility modulus, order parameter of lipid tails, and thickness of the phospholipid monolayer are quantitatively in line with the all-atom simulations and experiments. This model also captures the sensitive changes in the pressure-area isotherms of mixed DPPC/POPC monolayers with altered mixing ratios, indicating that the model is promising for applications with complex natural phospholipid monolayers. These results demonstrate a significant improvement of quantitative phospholipid monolayer simulations over previous coarse-grained models.

Machine learning assisted fast prediction of inertial lift in microchannels.

Inertial effect has been extensively used in manipulating both engineered particles and biocolloids in microfluidic platforms. The design of inertial microfluidic devices largely relies on precise prediction of particle migration that is determined by the inertial lift acting on the particle. In spite of being the only means to accurately obtain the lift forces, direct numerical simulation (DNS) often consumes high computational cost and even becomes impractical when applied to microchannels with complex geometries. Herein, we proposed a fast numerical algorithm in conjunction with machine learning techniques for the analysis and design of inertial microfluidic devices. A database of inertial lift forces was first generated by conducting DNS over a wide range of operating parameters in straight microchannels with three types of cross-sectional shapes, including rectangular, triangular and semicircular shapes. A machine learning assisted model was then developed to gain the inertial lift distribution, by simply specifying the cross-sectional shape, Reynolds number and particle blockage ratio. The resultant inertial lift was integrated into the Lagrangian tracking method to quickly predict the particle trajectories in two types of microchannels in practical devices and yield good agreement with experimental observations. Our database and the associated codes allow researchers to expedite the development of the inertial microfluidic devices for particle manipulation.

An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm.

Seasonal or monthly databases of the diatom populations in specific bodies of water are needed to infer the drowning site of a drowned body. However, existing diatom testing methods are laborious, time-consuming, and costly and usually require specific expertise. In this study, we developed an artificial intelligence (AI)-based system as a substitute for manual morphological examination capable of identifying and classifying diatoms at the species level. Within two days, the system collected information on diatom profiles in the Huangpu and Suzhou Rivers of Shanghai, China. In an animal experiment, the similarities of diatom profiles between lung tissues and water samples were evaluated through a modified Jensen-Shannon (JS) divergence measure for drowning site inference, reaching a prediction accuracy of 92.31%. Considering its high efficiency and simplicity, our proposed method is believed to be more applicable than existing methods for seasonal or monthly water monitoring of diatom populations from sections of interconnected rivers, which would help police narrow the investigation scope to confirm the identity of an immersed body.

Efficacy and safety of acupuncture for urinary retention: A protocol for systematic review and meta analysis.

BACKGROUND: Many postoperative patients and males suffer urinary retention (UR) symptom, which directly affects their quality of life. Acupuncture is widely used by Traditional Chinese Medicine doctors to treat various postoperative urinary retention and elderly male urinary retention patients. However, acupuncture treatment of urinary retention symptoms lacks relevant multi-center clinical studies and lacks a more comprehensive meta-analysis report, which contradicts clinical practice. To confirm the safety and efficacy of acupuncture treatment of urinary retention caused by various reasons requires more comprehensive and strong evidence-based medical evidence. METHODS: Databases including CNKI, PubMed, Web of Science, Cochrane Central Register of Controlled Trials, Scopus, EBSCO were retrieved for relevant literature, with the retrieval deadline being June 23, 2020. The 2 conducted independent reading of the retrieved literature and removed the duplications, and then used the Cochrane Handbook to score the randomized controlled trials (RCTs). Only when the score is greater than 5 points can they be included. Then extract the basic information of the included literature, post-voided residual urine (PVR), maximal cystometric capacity (MCC), maximal flow rate (MFR), bladder compliance (BC), adverse events (AE), and effective rate data, and make a literature feature table. The methodological quality was evaluated with the "Risk of Bias" tool, and the meta-analysis was performed by using the RevMan 5.3.5 software. Use Stata 15 for regression analysis to find the source of heterogeneity, and try to resolve it using subgroup analysis. RESULTS: The analysis of PVR, MCC, MFR, BC, AE and effective rate data can provide high-quality evidence for high-quality synthesis and/or descriptive analysis of the effectiveness and safety of acupuncture treatment of various causes of urinary retention. CONCLUSION: This study can provide more comprehensive evidence to prove whether acupuncture is effective and safe for patients with UR. REGISTRATION: The research has been registered and approved on the PROSPERO website. The registration number is CRD42019119238.

Acupuncture for the treatment of dry eye: Protocol for systematic review and meta-analysis.

BACKGROUND: As a common ophthalmic disease, dry eye (DE) may bring several adverse effects on the quality of life for patients. In recent years, Acupuncture (AC) is becoming increasingly popular for treating DE. Thus, we conceived this systematic review aims to evaluate the effectiveness and safety of AC for DE objectively. METHODS: The search results are restricted to randomized controlled trials and human studies. We will establish the inclusion criteria through discussion and design a detailed literature search strategy for each database. Articles are searched from 4 English databases (the Cochrane Library, PubMed, Web of Science, and EMBASE) and 4 Chinese databases (Wangfang, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and Chinese scientific and technical journals database). The relevant studies published from the date of database inception until January 2020 will be collected. We will also search (International Clinical Trials Registry Platform), PROSPERO, and potential gray literature. Two reviewers independently perform literature screening, information extraction, and assessment of study quality. The outcome measures include primary outcome measures (Schirmer I test and break-up time), secondary outcome measures (Ocular Surface Disease Index, corneal fluorescein staining, and tear osmolarity), and safety outcome measures. Assessment of bias risk and data processing are performed using RevMan 5.3 software ( the Nordic Cochrane Centre, Copenhagen, Denmark). RESULTS: We will evaluate the curative effect of AC for DE comprehensively based on multiple outcome measures. CONCLUSION: This systematic review will provide evidence for the effectiveness and safety of AC in the treatment of DE. PROSPERO NUMBER: CRD42019144790.

Synthesis and photonic band calculations of NCP face-centered cubic photonic crystals of TiO2 hollow spheres.

With the help of self-assembly, thermal sintering, selective etching techniques and sol-gel process, the non-close packed (ncp) face-centered cubic (fcc) photonic crystals of titanium dioxide (TiO2) hollow spheres connected by TiO2 cylindrical tubes have been fabricated using silica template. The photonic bandgap calculations indicate that the ncp structure of TiO2 hollow spheres was easier to open the pseudogaps than close packed system at the lowest energy.