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Near-infrared spectroscopy (NIR) has become one of the most important methods for counterfeit drugs identification for its low cost, non-destructive, and on-site detection. However, it is often invalid for unknown samples beyond the scope of modeling samples, as well as it is not efficient in conditions of insufficient samples (insufficient number of samples within the class), unbalanced samples (large difference in the number of samples between classes), and sensitivity of identification results (different tolerance for different errors in application scenarios). To solve these problems, this paper proposes a general method for on-site identification of counterfeit drugs based on Siamese-network modeling with near-infrared spectroscopy, which especially constructs the train set and test set, learning the general knowledge of spectral differences to identify the different drugs by a costumed one-dimensional convolution neural network (1D-CNN), and finally answered the question of whether the on-site two spectra are pointed to the same drug. Based on experimental modeling samples of 1314 spectra, which are involved 9 drugs produced by 25 manufacturers, this paper has constructed and fully trained its model. Then, not known at the time of modeling, 4 drugs produced by 9 manufacturers are used for testing in the on-site application, and the accuracy rate amounts to 97.3%. For generalizing consideration, randomly divided into training and testing categories, the 32015 spectra of 135 drugs produced by 391 manufacturers in the spectral library are handled by the same processing. The generalization model is equally applicable, and the accuracy is above 97%. Compared with traditional binary classification identification methods such as SVM, PLS-DA, Auto-encoding, and one class (OC) threshold identification algorithms such as SVM-OC, SIMCA, conformity test (CT), the proposed method has the best identification ability for unknown samples in modeling.

Background: Premature ovarian insufficiency (POI) is a refractory disease that severely affects female fertility. The PERK/eIF-2α/ATF4/CHOP pathway is one of the classical pathways involved in the unfolded protein response to endoplasmic reticulum stress by regulating protein synthesis and promoting apoptosis. This study aimed to investigate the functional role and mechanism of human umbilical cord mesenchymal stem cells (hUCMSCs) in the POI animal model through the PERK/eIF-2α/ATF4/CHOP pathway. Methods and results: Forty-five sexually mature female C57 mice were divided into a blank control group, POI model group, and hUCMSCs intervention group. To establish the POI model, mice received intraperitoneal injections of cyclophosphamide (CTX) (70 mg/kg) daily for 14 consecutive days, while the control group received saline only. In the hUCMSC intervention group, mice were given hUCMSCs on days 14 and 28, based on CTX modeling in the POI model group. The hUCMSCs were isolated, labeled with 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindotricarbocyanine iodide (DiR) fluorescent dye, and tail vein-injected, and the distribution of the DiR signal was monitored in the mice using a fluorescence imaging detection method. The ovarian tissues were hematoxylin and eosin stained to observe the ovarian structure, and the number of primordial follicles were counted. An enzyme-linked immunosorbent assay was used to detect the serum levels of estradiol, anti-mullerian hormone, and follicle-stimulating hormone. Terminal deoxynucleotidyl transferase dUTP nick end labeling was used to detect the apoptosis of granulosa cells (GCs). The reactive oxygen species (ROS) content of ovarian tissue was detected by flow cytometry assay. The RNA expression of PERK, eIF-2α, ATF4, and CHOP was determined by quantitative real-time polymerase chain reaction, and protein levels of the targets were determined by western blot and immunohistochemistry. We identified hUCMSCs using surface antigenic markers (CD90, CD44, CD105, and CD73), and osteoblasts and chondroplast differentiation assays. Our studies demonstrated that hUCMSC intervention significantly restored ovarian function by improving the irregular estrous cycle, increasing the number of follicles, decreasing ROS, and inhibiting GC apoptosis in POI mice. Moreover, hUCMSCs suppressed CTX-induced PERK/eIF-2a/ATF4/CHOP pathway activation. Conclusions: HUCMSCs can migrate to the damaged ovaries of POI mice, and improve the ovarian function of POI mice by inhibiting oxidative stress, down-regulating the expression of the PERK/eIF-2α/ATF4/CHOP pathway, and reducing the apoptosis of GCs. [ABSTRACT FROM AUTHOR]

In this study, the shelf life of cereal auxiliary food for infants and young children made by drum drying and packed in tinplate cans with nitrogen filling was studied. Through accelerated destructive experiment, the chemical quality decay kinetic model was established for the first time, and the shelf life at room temperature was inferred according to the decay of nutrients. The results show that the water activity of cereal auxiliary food for infants is between 0.2～0.3. During the accelerated test period of 4.5 months, the decay rates of DHA and AA are the fastest. According to the variation of each nutrient index, we conclude that the shelf life of products can exceed 20 months.

Bridge cable is an important force transmission component of bridge, but it is easy to be damaged during service, such as fatigue damage and corrosion damage, which seriously threatens the safety of bridge structure. Therefore, it is necessary to identify damage of cable force. Generally, the damage of cable force can be identified by the change of cable frequency. This paper establishes a cable force damage identification model based on Bayesian inference and uses Metropolis‐Hastings (MH) algorithm to solve the posterior probability function of unknown parameter. In the Bayesian inference model, the influence of the priori function of unknown parameters on the posterior probability distribution model is discussed. In the MH algorithm, the influence of different proposed distributions (Normal distribution, Gamma distribution and Weibull distribution) on the sampling results is discussed based on three numerical simulation studies, and the influence of burned sample proportion on the establishment of a posteriori distribution function is analyzed. Furthermore, the influence of monitoring noise data and missing data on cable force damage identification is considered, and the robustness of the proposed method is analyzed. [ABSTRACT FROM AUTHOR]

Background: Internet hospitals (IHs) have rapidly developed as a promising strategy to address supply-demand imbalances in China's medical industry, with their capabilities directly dependent on information platform functionality. Furthermore, a novel theory of "Trinity" smart hospital has provided advanced guidelines on IH constructions. Objective: This study aimed to explore the construction experience, construction models, and development prospects based on operational data from IHs. Methods: Based on existing information systems and internet service functionalities, our hospital has built a "Smart Hospital Internet Information Platform (SHIIP)" for IH operations, actively to expand online services, digitalize traditional health care, and explore health care services modes throughout the entire process and lifecycle. This article encompasses the platform architecture design, technological applications, patient service content and processes, health care professional support features, administrative management tools, and associated operational data. Results: Our platform has presented a set of data, including 82,279,669 visits, 420,120 online medical consultations, 124,422 electronic prescriptions, 92,285 medication deliveries, 6,965,566 prediagnosis triages, 4,995,824 offline outpatient appointments, 2025 medical education articles with a total of 15,148,310 views, and so on. These data demonstrate the significant role of IH as an indispensable component of our physical hospital services, with deep integration between online and offline health care systems. Conclusions: The upward trends in various data metrics indicate that our IH has gained significant recognition and usage among both the public and healthcare workers, and may have promising development prospects. Additionally, the platform construction approach, which prioritizes comprehensive service digitization and the 'Trinity' of the public, healthcare workers, and managers, serves as an effective means of promoting the development of Internet Hospitals. Such insights may prove invaluable in guiding the development of IH and facilitating the continued evolution of the Internet healthcare sector. [ABSTRACT FROM AUTHOR]