3- to 24-month Follow-up on COVID-19 with Pulmonary Tuberculosis Survivors after Discharge: Results from a Prospective, Multicenter Study.

Objective: Coronavirus disease 2019 (COVID-19) and tuberculosis (TB) are major public health and social issues worldwide. The long-term follow-up of COVID-19 with pulmonary TB (PTB) survivors after discharge is unclear. This study aimed to comprehensively describe clinical outcomes, including sequela and recurrence at 3, 12, and 24 months after discharge, among COVID-19 with PTB survivors. Methods: From January 22, 2020 to May 6, 2022, with a follow-up by August 26, 2022, a prospective, multicenter follow-up study was conducted on COVID-19 with PTB survivors after discharge in 13 hospitals from four provinces in China. Clinical outcomes, including sequela, recurrence of COVID-19, and PTB survivors, were collected via telephone and face-to-face interviews at 3, 12, and 24 months after discharge. Results: Thirty-two COVID-19 with PTB survivors were included. The median age was 52 (45, 59) years, and 23 (71.9%) were men. Among them, nearly two-thirds (62.5%) of the survivors were moderate, three (9.4%) were severe, and more than half (59.4%) had at least one comorbidity (PTB excluded). The proportion of COVID-19 survivors with at least one sequela symptom decreased from 40.6% at 3 months to 15.8% at 24 months, with anxiety having a higher proportion over a follow-up. Cough and amnesia recovered at the 12-month follow-up, while anxiety, fatigue, and trouble sleeping remained after 24 months. Additionally, one (3.1%) case presented two recurrences of PTB and no re-positive COVID-19 during the follow-up period. Conclusion: The proportion of long symptoms in COVID-19 with PTB survivors decreased over time, while nearly one in six still experience persistent symptoms with a higher proportion of anxiety. The recurrence of PTB and the psychological support of COVID-19 with PTB after discharge require more attention.

Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China.

OBJECTIVE: Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear. METHODS: A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients' medical records. Multivariable logistic regression models were used to estimate the odds ratio ( OR) and 95% confidence interval (95% CI) of the associations between comorbidities (cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of COVID-19. RESULTS: Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30-6.32), type 2 diabetes (T2DM) (3.57, 2.32-5.49), cardiovascular disease (CVD) (3.78, 1.81-7.89), fatty liver disease (7.53, 1.96-28.96), hyperlipidemia (2.15, 1.26-3.67), other lung diseases (6.00, 3.01-11.96), and electrolyte imbalance (10.40, 3.00-26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89-12.75), CVD (8.47, 6.03-11.89), and electrolyte imbalance (19.44, 11.47-32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25-9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46-29.64) within two weeks. CONCLUSION: Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

The application of next-generation sequencing techniques in studying transcriptional regulation in embryonic stem cells.

The mechanism of transcriptional regulation has been the focus of many studies in the post-genomic era. The development of sequencing-based technologies for chromatin profiling enables current researchers to experimentally measure chromatin properties. Moreover, many studies aim at annotating the state of the chromatin into broad categories based on observed chromatin features and/or DNA sequences, then associating the resultant distal regulatory regions with the correct target genes based on DNA sequences, and predicting the dependence of epigenetic features on genetic variation. Stem cell biology has many applications in the area of regenerative medicine and tumorigenesis. In this review, we summarize recent research progresses on the application of next-generation sequencing techniques in studying transcriptional regulation in embryonic stem cells. This review mainly focuses on four areas: (1) microarray or RNA-seq; (2) chromatin immunoprecipitation (ChIP); (3) Dnase I hypersensitive sites (DHSs); (4) high-throughput chromosome conformation capture (Hi-C). These technologies have been utilized in studying chromatin on three levels, i.e., gene expression, transcription factor binding and genome three-dimensional structure. We especially emphasize three master transcription factors of pluripotency: Oct4, Sox2 and Nanog. We aim to track the frontier of stem cell transcriptional regulation research and share important progresses in this field.

Sequence-based prediction of DNA-binding residues in proteins with conservation and correlation information.

The recognition of DNA-binding residues in proteins is critical to our understanding of the mechanisms of DNA-protein interactions, gene expression, and for guiding drug design. Therefore, a prediction method DNABR (DNA Binding Residues) is proposed for predicting DNA-binding residues in protein sequences using the random forest (RF) classifier with sequence-based features. Two types of novel sequence features are proposed in this study, which reflect the information about the conservation of physicochemical properties of the amino acids, and the correlation of amino acids between different sequence positions in terms of physicochemical properties. The first type of feature uses the evolutionary information combined with the conservation of physicochemical properties of the amino acids while the second reflects the dependency effect of amino acids with regards to polarity charge and hydrophobic properties in the protein sequences. Those two features and an orthogonal binary vector which reflect the characteristics of 20 types of amino acids are used to build the DNABR, a model to predict DNA-binding residues in proteins. The DNABR model achieves a value of 0.6586 for Matthew's correlation coefficient (MCC) and 93.04 percent overall accuracy (ACC) with a68.47 percent sensitivity (SE) and 98.16 percent specificity (SP), respectively. The comparisons with each feature demonstrate that these two novel features contribute most to the improvement in predictive ability. Furthermore, performance comparisons with other approaches clearly show that DNABR has an excellent prediction performance for detecting binding residues in putative DNA-binding protein. The DNABR web-server system is freely available at http://www.cbi.seu.edu.cn/DNABR/.

[Studies on the ultraviolet light induced absorption change in nearly stoichiometric LiNbO3 : Fe: Mn crystals].

The ultraviolet light induced absorption change (UV-LIA) of nearly stoichiometric LiNbO3 : Fe : Mn crystals was investigated. The experimental results show that the UV-LIA coefficient change of LiNbO3 : Fe : Mn crystal is not large for congruent sample, increases with increasing Li2 O concentration, reaches the maximum 4. 2 cm(-1) at about 49.57 mol% Li2 O, and then decreases with further increasing Li2 O content. Because the UV-LIA change has a direct relationship with the nonvolatile holographic sensitivity, the experimental results indicate that the nearly stoichiometric LiNbO3 : Fe : Mn crystal with 49.57 mol% Li2 O is the appropriate candidate material for the nonvolatile holographic storage. The visible light induced bleaching results also prove that the suitable composition is 49.57 mol%. With the increase in Li2 O concentration in the LiNbO3 : Fe : Mn crystal, the amount of the bipolaron increases. Bipolarons may be dissociated either optically or thermally so that metastable small polarons are formed. The energy level for biopolaron and small polaron is at about 2.5 and 1.6 eV respectively. When the Li2 O concentration continues to increase, the small polarons are dominating intrinsic defects. The bipolarons have stronger photorefractive capability than the small polarons. The amount of bipolaron is the most with 49.57 mol% Li2 O concentration in the LiNbO3 : Fe : Mn crystal. Based on these experimental results, a three-photorefractive-centers model in nearly stoichimetric LiNbO3 : Fe : Mn crystal is suggested: besides Fe2+/Fe3+ and Mn2+ /Mn3+, bipolarons/small polarons are considered as the third photoactive center.