SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data.

The survival path mapping approach has been proposed for dynamic prognostication of cancer patients using time-series survival data. The SurvivalPath R package was developed to facilitate building personalized survival path models. The package contains functions to convert time-series data into time-slices data by fixed interval based on time information of input medical records. After the pre-processing of data, under a user-defined parameters on covariates, significance level, minimum bifurcation sample size and number of time slices for analysis, survival paths can be computed using the main function, which can be visualized as a tree diagram, with important parameters annotated. The package also includes function for analyzing the connections between exposure/treatment and node transitions, and function for screening patient subgroup with specific features, which can be used for further exploration analysis. In this study, we demonstrate the application of this package in a large dataset of patients with hepatocellular carcinoma, which is embedded in the package. The SurvivalPath R package is freely available from CRAN, with source code and documentation hosted at https://github.com/zhangt369/SurvivalPath.

Enhanced near-infrared optical transmission in zinc germanium phosphide crystals via precise magnesium doping.

A zinc germanium phosphorus (ZnGeP2) crystal with a chalcopyrite structure is an efficient frequency converter in the mid-infrared region. However, point defect-induced optical absorption at the pumping wavelength (near infrared region) blocked the further application of ZnGeP2. To alleviate the absorption losses caused by point defects, in situ magnesium doping compensation was presented during the ZnGeP2 bulk crystal growth process via the vertical Bridgman method. Combined with theoretical calculations, the structural distortion of the magnesium-doped ZnGeP2 crystals in different orientations was illustrated. The thermodynamic and kinetic stability of the magnesium-doped ZnGeP2 structure were demonstrated. The transmission results indicated the improvement of transmittance within a wavelength range of 1.8-2.4 µm when doped with magnesium, which revealed the powerful ability of the appropriate dopant in optimizing near-infrared optical properties. Thus, the introduction of magnesium is a practical approach to improve the transmittance performance and extend the pumping source wavelengths of ZnGeP2 crystals.

Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training.

BACKGROUND: Currently, the diagnosis of invasive pulmonary aspergillosis (IPA) mainly depends on the integration of clinical, radiological and microbiological data. Artificial intelligence (AI) has shown great advantages in dealing with data-rich biological and medical challenges, but the literature on IPA diagnosis is rare. OBJECTIVE: This study aimed to provide a non-invasive, objective and easy-to-use AI approach for the early diagnosis of IPA. METHODS: We generated a prototype diagnostic deep learning model (IPA-NET) comprising three interrelated computation modules for the automatic diagnosis of IPA. First, IPA-NET was subjected to transfer learning using 300,000 CT images of non-fungal pneumonia from an online database. Second, training and internal test sets, including clinical features and chest CT images of patients with IPA and non-fungal pneumonia in the early stage of the disease, were independently constructed for model training and internal verification. Third, the model was further validated using an external test set. RESULTS: IPA-NET showed a marked diagnostic performance for IPA as verified by the internal test set, with an accuracy of 96.8%, a sensitivity of 0.98, a specificity of 0.96 and an area under the curve (AUC) of 0.99. When further validated using the external test set, IPA-NET showed an accuracy of 89.7%, a sensitivity of 0.88, a specificity of 0.91 and an AUC of 0.95. CONCLUSION: This novel deep learning model provides a non-invasive, objective and reliable method for the early diagnosis of IPA.

Li2PbB2O5: A Pyroborate with Large Birefringence Induced by the Synergistic Effect of Stereochemical Active Lone Pair Cations and π-Conjugated [B2O5] Groups.

Through the inclusion of two kinds of birefringence reactive groups, that is, Pb2+ cations with stereochemically active lone pairs and π-conjugated [B2O5] groups, a new pyroborate Li2PbB2O5 used to be acquired by the usage of the high-temperature solution method. The three-dimensional structural framework of Li2PbB2O5 is made up of highly distorted [PbO5] polyhedra and parallelly arranged π-conjugated [B2O5] groups via the connection of four- and five-coordinated Li+ cations. The birefringence of Li2PbB2O5 is 0.091 at 1064 nm, which is relatively large and revealed by the first-principles calculations. The contribution from the synergistic effect of the two kinds of birefringence reactive groups was substantiated via the analysis of the real-space atom cutting method. Also, the diffuse reflectance spectrum suggests that Li2PbB2O5 features a band gap of 4.0 eV, which corresponds to an ultraviolet (UV) cutoff edge. We hope that this work will foster further improvements in the design of UV birefringent crystal materials in the borate system.

Study on structured method of Chinese MRI report of nasopharyngeal carcinoma.

BACKGROUND: Image text is an important text data in the medical field at it can assist clinicians in making a diagnosis. However, due to the diversity of languages, most descriptions in the image text are unstructured data. The same medical phenomenon may also be described in various ways, such that it remains challenging to conduct text structure analysis. The aim of this research is to develop a feasible approach that can automatically convert nasopharyngeal cancer reports into structured text and build a knowledge network. METHODS: In this work, we compare commonly used named entity recognition (NER) models, choose the optimal model as our triplet extraction model, and present a Chinese structuring algorithm. Finally, we visualize the results of the algorithm in the form of a knowledge network of nasopharyngeal cancer. RESULTS: In NER, both accuracy and recall of the BERT-CRF model reached 99%. The structured extraction rate is 84.74%, and the accuracy is 89.39%. The architecture based on recurrent neural network does not rely on medical dictionaries or word segmentation tools and can realize triplet recognition. CONCLUSIONS: The BERT-CRF model has high performance in NER, and the triplet can reflect the content of the image report. This work can provide technical support for the construction of a nasopharyngeal cancer database.

Candidemia in Adults at a Tertiary Hospital in China: Clinical Characteristics, Species Distribution, Resistance, and Outcomes.

BACKGROUND: Candidemia is one of the most common nosocomial bloodstream infections. Early diagnosis and antifungal treatment improve clinical outcomes in some studies but not all, with diverse data reported from different institutions. Similarly, antifungal resistance is more common in the USA than in Europe, but there is little data regarding the microbiology and clinical course of candidemia in adult patients in Asia. AIMS: (1) To capture species distribution and drug resistance rates among Candida bloodstream isolates, (2) to describe clinical features of candidemia, and (3) to identify factors associated with all-cause mortality, with emphasis on early initiation of antifungal treatment, at a large tertiary University Hospital in China. METHODS: In this single-center retrospective study, we identified all patients with candidemia, between 2008 and 2014. Demographic and clinical characteristics, microbiological information, details of antifungal therapy and clinical outcomes were collected. RESULTS: We studied 166 patients. 71 (42.8%) had cancer. Candida albicans was the most frequent species (37.3%), followed by C. parapsilosis (24.1%), C. tropicalis (22.8%), and C. glabrata (14.5%). Antifungal resistance was more frequent in non-albicans strains and especially C. glabrata. Twenty patients received inappropriate treatment with all-cause mortality of 35%. The remaining 146 patients had significantly lower mortality (21.9%, P = 0.045). Among patients who received antifungal treatment, mortality rate increased with time to appropriate antifungal therapy (AAT): 13.7%, for < 24 h, 21.1% for 24-48 h, 23.1% for > 48 h, and 32.4% among patients who received no AT (χ2 for trend P = 0.039). Initiating AAT more than 24 h after blood culture collection was an independent risk factor for mortality, after adjustment for other confounders (OR 7.1, 95% CI 1.3-39.4, P = 0.024). CONCLUSIONS: Candida albicans was the most frequent cause of candidemia at a large tertiary hospital in China, but antifungal resistance is a growing concern among non-albicans Candida species. The mortality rate of patients treated with ineffective antifungal agents based on in vitro susceptibilities was similar to that of patients who received no treatment at all, and delayed initiation of antifungal treatment was associated with increased risk of death.

Candida spp. airway colonization: A potential risk factor for Acinetobacter baumannii ventilator-associated pneumonia.

This retrospective study was conducted to identify potential risk factors for Acinetobacter baumannii (A. baumannii) ventilator-associated pneumonia (VAP) and evaluate the association between Candida spp. airway colonization and A. baumannii VAP. Intensive care unit (ICU) patients who were on mechanical ventilation (MV) for ≥48 hours were divided into the following groups: patients with and without Candida spp. airway colonization; colonized patients receiving antifungal treatment or not; patients with A. baumannii VAP and those without VAP. Logistic regression analysis and propensity score matching were used to identify factors independently associated with A. baumannii VAP. Among 618 eligible patients, 264 (43%) had Candida spp. airway colonization and 114 (18%) developed A. baumannii VAP. Along with MV for ≥7 days (adjusted odds ratio [aOR] 8.9, 95% confidence intervals [95% CI] 4.9-15.8) and presence of a central venous catheter (aOR 3.2, 95% CI 1.1-9), Candida spp. airway colonization (aOR 2.6, 95% CI 1.6-4.3) was identified as an independent risk factor for A. baumannii VAP. Patients with Candida spp. airway colonization were more likely to develop A. baumannii VAP than non-colonized patients (23% vs 15%, P=.01 and 34% vs. 15%, P<.001 in propensity score-matched subgroups). Administration of antifungal agents was not associated with A. baumannii VAP (29% vs. 21%, P=.153) but with higher in-hospital mortality (53% vs. 39%, P=.037). Candida spp. airway colonization (43%) and A. baumannii VAP (18%) were common in ICU patients who were on mechanical ventilation for at least 48 hours. Candida spp. airway colonization was an independent risk factor for subsequent A. baumannii VAP.

Three Polyborates with High-Symmetry [B12O24] Units Featuring Different Dimensions of Anion Groups.

Three polyborates, namely, LiNa11B28O48, Li1.45Na7.55B21O36, and Li2Na4Ca7Sr2B13O27F9, were synthesized via the high-temperature solution method. All of them feature high-symmetry [B12O24] units, yet their anion groups exhibit distinct dimensions. LiNa11B28O48 features a three-dimensional anionic structure of 3[B28O48]∞ framework, which is composed of three units: [B12O24], [B15O30], and [BO3]. Li1.45Na7.55B21O36 possesses a one-dimensional anionic structure of 1[B21O36]∞ chain consisting of [B12O24] and [B9O18] units. The anionic structure of Li2Na4Ca7Sr2B13O27F9 is composed of two zero-dimensional isolated units, namely, [B12O24] and [BO3]. The novel FBBs [B15O30] and [B21O39] are present in LiNa11B28O48 and Li1.45Na7.55B21O36, respectively. The anionic groups in these compounds exhibit a high degree of polymerization, thereby augmenting the structural diversity of borates. And the crystal structure, synthesis, thermal stability, and optical properties were meticulously discussed to guide the synthesis and characterization of novel polyborates.

More optimal but less regulated dorsal and ventral visual networks in patients with major depressive disorder.

Previous studies indicate that major depressive disorder (MDD) can profoundly modify the visual cortices as well as the visuo-attentional systems of brain. However, little is known on the specific pattern of the whole-network-level abnormalities. In this study, resting-state functional magnetic resonance imaging data were collected from 159 participants, including 86 medication-free MDD patients and 73 matched healthy controls. The dorsal/ventral visual networks were defined based on our previously published brain coordinates from activation likelihood estimation analyses. The static and dynamic network properties were respectively calculated and compared between MDD and control groups. Moreover, the inter-network connectivities quantified using the multivariate distance correlation between the dorsal attention network (DAN) and the two visual networks were also analyzed. Results indicated that both of the two visual networks in MDD were found with significantly increased clustering coefficient (dorsal: p = 0.002; ventral: p = 0.004) and higher small-worldness (dorsal: p = 0.001; ventral: p = 0.002) as compared with control group. A higher mean variability of dynamic functional connectivity was found in both two networks in MDDs (dorsal: p < 0.001; ventral: p = 0.001). Moreover, the two visual networks in MDD group showed decreased inter-network connectivities to DAN (dorsal: p = 0.004; ventral: p = 0.013). Taken together, these results may support that the ventral and dorsal visual systems under the pathological effect of depression are possibly characterized by a status of increased autonomy, i.e., a more optimal, economical, and efficient intra-network organization combining with increased independency and receiving less outside regulation from attention network, thus indicating the increased functional role of the brain visual systems in MDD.

[Analysis of DICOM and its application in teleradiology].

Digital Imaging Communications in Medicine(DICOM) was brought forward by ACR and NEMA to solve the joining problem of medical equipment. It is a public international standard now. Using DICOM in teleradiology is very important, especially for China. In this paper the authors analyze the contents and specialty of DICOM and make comments on how to use it in teleradiology and picture access and communication system(PACS).