A follow-up study of post-COVID-19 syndrome in hospitalized children with Omicron variant infection in Wuhan

BackgroundSince the Chinese government changed its COVID-19 prevention and control policies, the rapid spread of the omicron variant resulted in a pervasive surge of infections throughout the nation, particularly affecting children. Although the acute symptoms of children infected with COVID-19 are milder compared to adults, the impact of post-COVID-19 syndromes (PCS) on the growth and development of children should not be ignored. The clinical manifestations, treatment methods, and long-term effects of children are significantly different from those of adults, making it necessary to understand the phenotype of children with PCS in order to effectively manage their health.MethodsThe study focuses on hospitalized children infected with omicron variant in Zhongnan Hospital of Wuhan University from December 7, 2022, to January 5, 2023. Three telephone follow-ups with the guardians was conducted at 4–5 weeks, 12–13 weeks, and 24–25 weeks after the patients' discharge to understand their prevalence, clinical characteristics, and risk factors of PCS.ResultsThe age range of the 112 hospitalized pediatric patients was 0–13 years, with a median age of 19 months. After three follow-ups, 49.1% patients had PCS, while the incidence of PCS persisting 3 month was 21.4%, with a prevalence of PCS persisting 6 month of 10.7%. From the first follow-up phase to the third phase, there was a significant decrease in the incidence of PCS. In infants, the most common persistent symptom was sleep disorder (19.2%), followed by respiratory symptoms, diarrhea (8.2%), and decreased appetite (6.8%). In children and adolescents, decreased appetite was the most common persistent symptom (30.8%), followed by respiratory symptoms, fatigue (15.4%), and mood changes (15.4%). Decreased appetite was more common in the children and adolescents, while diarrhea and sleep disorders were more common in the infants. Binary logistic regression analysis and ordered logistic regression analysis showed that times of illness (OR = 1.671, 95% CI: 1.339–2.086) were positively correlated with the duration of symptoms. Times of illness was positively correlated with cough/expectoration (OR = 1.491, 95% CI: 1.039–2.138). Age (OR = 0.844, 95% CI: 0.755–0.944) and re-hospitalization (OR = 0.146, 95% CI: 0.022–0.969) were positively correlated with sleep disorders.ConclusionsChildren with Omicron variant may still experience PCS, but the incidence is lower compared to adults and compared to other variants and the incidence of PCS will gradually decrease over time. The symptoms of PCS differ between older children and infants and it is necessary to prevent recurrent illness for at least half a year after COVID-19 recovery. In order to further understand and ameliorate the impact of PCS on the health of children infected with COVID-19, subsequent follow-up studies will expand the scope, combine with objective follow-up contents, and establish an assessment and management system especially for children of different ages

Anisodamine combined with lidocaine improves healing of myocardial ischemia reperfusion injury in rats via PI3K/Akt signaling pathway

Purpose: To study the effects of anisodamine (Ad) combined with lidocaine (Ldc) on myocardial ischemia-reperfusion injury (MIRI) in rats, and its correlation with PI3K/AKT signaling pathway.Methods: A total of 70 healthy rats were randomly divided into S group, M group, Ad group, Ldc group, Ad + Ldc group, Ad + Ldc + LY group, and LY group. The cardiac hemodynamic indices in each group were determined, and the area of myocardial infarction measured. Serum biochemical indices were also determined. Furthermore, the protein expressions of p-Akt, T-Akt, Bcl-2, and Bax in myocardial cells were determined by Western blotting.Results: Compared with those in M group, Ad group, Ldc group, Ad + Ldc + LY group, and LY group, cardiac hemodynamic indices significantly improved, while the area of myocardial infarction was significantly reduced (p < 0.01). Furthermore, serum malondialdehyde (MDA) concentration but the activities of CK, CK-MB, TNF-α, and IL-6 declined, while the activities of superoxide dismutase (SOD), CAT and GSH-Px rose in Ad + Ldc group (p < 0.01). In Ad + Ldc group, p-Akt, T-Akt, and Bcl-2 increased, while Bax significantly decreased. Through comparison LY294002 significantly inhibited the protective effect of Ad combined with Ldc against MIRI in rats (p < 0.01).Conclusion: Anisodamine combination with lidocaine has a protective effect against MIRI in rats via PI3K/Akt signaling pathway, thus indicating that it is a potential therapeutic strategy for the management of myocardial ischemia-reperfusion

An improved method of searching inferior parathyroid gland for the patients with papillary thyroid carcinoma based on a retrospective study

ObjectiveMany surgeons knew the importance of parathyroid gland (PG) in the thyroid surgery, but it was even more difficult to be protected. This study aimed at evaluating the effectiveness of the improved method of searching inferior parathyroid gland (IPG).Methods213 patients were enrolled and divided into test and control groups according to different methods of searching IPG in the surgery. Consequently, we compared the surgical outcome parameters between the two groups, including the operative time, numbers of PG identifying (PG protection in situ, PG auto-transplantation, and PG accidental removal), numbers of the total lymph node (LN) and metastatic LN, parathyroid hormone (PTH), transient hypoparathyroidism, transient recurrent laryngeal nerve palsy, and postoperative bleeding.ResultsWe identified 194 (194/196, 98.98%) and 215 (215/230, 93.48%) PGs in the test group and control group, respectively, and there was a significant difference (P = 0.005), and this result was due to IPG identification differences (96/98, 97.96% vs. 100/115, 86.96%, P = 0.004). Meanwhile, there was a lower ratio of IPG auto-transplantation in the test group compared with that in the control group (46.94% vs. 64.35%, P = 0.013). Serum PTH one day after the operation was 3.65 ± 1.86 vs. 2.96 ± 1.64 (P = 0.043) but with no difference at 6 months. There were no differences in metastatic LN and recurrent laryngeal nerve palsy between two groups.ConclusionThe improved method of searching IPG was simple, efficient, and safe, which was easy to be implemented for searching IPG and protecting it well

Ground microtremor test in shaking table experimental investigation on the steel corrugated utility tunnel

Shaking table test is an important method to study the seismic performance of structures. The accuracy of the test model which is designed based on the similarity ratio theory has a crucial impact on the reliability of the shaking table test results. In this paper, a steel corrugated utility tunnel model was made. Before it was fixed to the shaking table, the natural frequency of the model structure was measured by ground microtremor test, and the natural frequency of the prototype structure was obtained by numerical simulation. The ratio between test value and simulate value was calculated and compared with a pre-set similarity ratio to verify the accuracy of the model. The results demonstrate that the natural frequency of the model structure could be effectively obtained by ground microtremor test. The method of comparing frequency can comprehensively evaluate whether there gets some problem in designing and manufacturing the model structure. This paper can provide some references for the preliminary model design and preparation of the shaking table tests

Online monitoring and prediction of complex time series events from nonstationary time series data

Much of the world’s supply of data is in the form of time series. In the last decade, there has been an explosion of interest in time series data mining. Time series prediction has been widely used in engineering, economy, industrial manufacturing, finance, manage- ment and many other fields. Many new algorithms have been developed to classify, cluster, segment, index, discover rules, and detect anomalies/novelties in time series. However, traditional time series analysis methods are limited by the requirement of stationarity of the time series and normality and independence of the residuals. Be- cause they attempt to characterize and predict all time series observations, traditional time series analysis methods are unable to identify complex (nonperiodic, nonlinear, irregular, and chaotic) characteristics. As a result, the prediction of multivariate noisy time series (such as physiological signals) is still very challenging due to high noise, non-stationarity, and non-linearity. The objective of this research is to develop new reliable frameworks for analyzing multivariate noisy time series, and to apply the framework to online monitor noisy time series and predict critical events online. In particular, this research made an extensive study on one important form of multivariate time series: electrocorticogram (EEG) data, based on which two new online monitoring and prediction frameworks for multivariate time series were introduced and evaluated. The new online monitoring and prediction frameworks overcome the limitations of traditional time series analysis techniques, and adapt and innovate data mining concepts to analyzing multivariate time series data. The proposed approaches can be general frameworks to create a set of methods that reveal hidden temporal patterns that are characteristic and predictive of time series events. In second part of this dissertation provide an overview of the state-of-the-art pre- diction approaches. In the third part of this dissertation, we perform an extensive data mining study on multivariate EEG data, which indicates that EEG may be predictable for some events. In chapter 4, a reinforcement learning-based online monitoring and prediction framework is introduced and applied to solve the challenging seizure pre- diction problem from multivariate EEG data. In chapter 5, it first overview of the most popular representation methods for time series data, and then introduce two new robust algorithms for offline and online segmentation of a time series, respectively. Chapter 6 proposes a general online monitoring and prediction framework, which com- bines temporal feature extraction, feature selection, online pattern identification, and adaptive learning theory to achieve online prediction of complex time series events. Two prediction-rule construction schemes are proposed. In chapter 7, the proposed framework is applied to solve two challenging problems including seizure prediction and ’anxiety’ prediction in a simulated driving environment. The significant prediction results demonstrated the superior prediction capability of the proposed framework to predict complex target events from online streams of nonstationary and chaotic time series.Ph. D.Includes bibliographical referencesby Shouyi Wan

Translation in China: A Motivating Force

Au cours de ses 5000 ans d'histoire, la Chine a connu quatre différentes vagues d'activité traductionnelle. La première a commencé avec la traduction des classiques bouddhistes par des moines d'Inde et d'Asie centrale et par des moines chinois à l'aise tant avec ces doctrines qu'avec le sanscrit. La traduction des écrits bouddhiques s'étale sur plus de 1000 ans (à partir de la fin de la dynastie Han) et a laissé des traces indélébiles sur la religion, la philosophie et la vie sociale en Chine. La deuxième vague de traduction débute à la fin de la dynastie Ming (fin du xvie siècle) quand les missionnaires jésuites arrivèrent de l'Occident pour prêcher le catholicisme et enseigner la science et la technologie. La signature imposée du traité de Nanking marque le début de la troisième vague qui se caractérise par la traduction d'ouvrages de sciences sociales, de science militaire et de littérature. Enfin, la dernière vague commence à la fin des années 1950, elle est interrompue par la révolution culturelle et reprend à la fin des années 1970. Dans un certain sens, la traduction a donné au pays une impulsion vers le progrès.Four waves of translation activities have marked China's 5,000-year-long history. The first wave began with the translation of Buddhist classics by Indian and Central Asian Buddhist monks by Chinese monks conversant in both the doctrines and Sanskrit. The translation of Buddhist scriptures began in the late Han Dynasty and continued for more than 1,000 years, leaving a permanent influence on China's religion, philosophy and social life. The second wave of translating started in the late Ming Dynasty of the 16th century, when the Jesuit missionaries from the West came to China to spread Catholicism and teach science and technology. The signing, at gunpoint, of the Treaty of Nanking ushered in a third wave of translation activity, this one focused on works of social sciences, military sciences, and literature. The fourth wave of translation activity began in the late 1950s, was interrupted by the outbreak of the cultural revolution, but resumed its momentum in the late 1970s. In a sense, translation in China has served as a sort of motivating force, giving impetus to the country's progress

Decision aided compensation of residual frequency offset for MIMO-OFDM systems with nonlinear channel

In this paper, we propose a new approach to compensate the residual frequency offset (RFO) in multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system with nonlinear channel working in the burst mode. The proposed approach consists of two stages. Firstly a decision aided method is proposed to eliminate the nonlinearity introduced by high power transmit amplifier (HPA). Then a new decision aided approach is employed to achieve the RFO compensation on the nonlinearity-free symbols. The effectiveness of the proposed approach has been verified by computer simulations