ObjectiveTo investigate the correlation between sleep patterns and myopia progression among younger school-age children at a primary school in Changning District of Shanghai, based on the data from the Shanghai Students’ Common Diseases and Health Influencing Factors Monitoring System and a sleep-specific survey, so as to provide data support for myopia prevention and control in this age group. MethodsOne primary school was selected from the common diseases and health influencing factors monitoring system for students in Changning District, Shanghai. A total of 230 first-grade students were included in the study. Myopia and refractive parameters were examined, and sleep patterns were investigated. General demographic characteristics and myopia-related behavior data of the students were also collected. Sleep patterns were evaluated in terms of sleep duration, sleep efficiency, and sleep quality, with the latter assessed using the Chinese version of the Children’s Sleep Habits Questionnaire (CSHQ). Multiple linear regression and binary logistic regression models were used to analyze the association between sleep patterns and myopia progression among these students. ResultsThe results of the regression analyses revealed that the total CSHQ score of the students at baseline survey was (48.85±7.15) points. Their sleep efficiency was (94.49±8.48)%, sleep duration was (9.58±0.93) hours, and the proportion of those with insufficient sleep (<10 hours) was 78.26%. At baseline survey, students’ higher daytime sleepiness scores were associated with lower spherical equivalent (SE) ( β=-0.18, 95%CI: -0.31 to -0.04) and an increased risk of axial length (AL) / corneal radius (CR) ratio >3 (OR=1.52, 95%CI: 1.00 to 2.29), whereas longer sleep duration and higher sleep efficiency were associated with higher SE (β=0.18, 95%CI: 0.05 to 0.32; β=0.17, 95%CI: 0.04 to 0.31, respectively), shorter (AL) (β=-0.15, 95%CI: -0.27 to -0.03; β=-0.13, 95%CI: -0.25 to 0, respectively) and a reduced risk of AL /CR>3 (OR=0.70, 95%CI: 0.51 to 0.96; OR=0.73, 95%CI: 0.53 to 0.99, respectively). At baseline survey, children’s higher propensity for sleep problems (OR=1.70, 95%CI: 1.04 to 2.78), sleep resistance (OR=2.26, 95%CI: 1.36 to 3.75), and sleep anxiety scores (OR=2.15, 95%CI: 1.33 to 3.48) were all associated with an increased risk of AL/CR >3 at follow-up (all P<0.05). Furthermore, higher sleep anxiety scores predicted prolonged AL at follow-up (β=0.03, 95%CI: 0 to 0.05). According to the mixed-effects model, higher daytime sleepiness scores and prolonged sleep duration were independently linked to reduced right-eye SE (β=-0.05, 95%CI: -0.10 to 0, P<0.05) and shorter right-eye AL (β=-0.05, 95%CI: -0.10 to 0, P<0.05). ConclusionIn this school in Shanghai, there are problems of insufficient and poor-quality sleep among young children. Sleep problems such as sleep resistance, delayed sleep onset, sleep anxiety, and daytime sleepiness among children may accelerate the risk of myopia progression, while longer sleep duration and higher sleep efficiency may serve as protective factors against the occurrence and development of myopia.

Synthetic biology is a crucial tool for the development of the bio-industry and bio-economy, representing a significant aspect of new quality productive forces. As a core course for graduate students in bioengineering, Synthetic Biology plays a vital role in ensuring the supply of essential talents for the development of the bio-industry in the new era. To better serve regional economic development and provide high-level talents for China's progress in the bio-industry, we analyzed typical issues encountered in the past teaching activities, set up a multi-disciplinary teaching team, optimized the course contents, adjusted the teaching mode, and mobilized students' learning interest. With the application of scientific research project as the starting point, we guided students to think and discuss deeply through the simulation of application writing and project defense, which improved students' critical thinking and innovative thinking. With industrialization as a focus, we explored a new training model combining production, education, and research through the joint practice base of the university and enterprises introduced typical cases of biomanufacturing to encourage students to engage in scientific research. The teaching reform significantly enhances the comprehensive abilities and national sentiments of graduate students. This paper hopes to serve as a reference for colleagues engaged in teaching in this field.
Synthetic Biology/education* ; Teaching ; China ; Humans

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

The PA-PB1 interface of the influenza polymerase is an attractive site for antiviral drug design. In this study, we designed and synthesized a mini-library of indazole-containing compounds based on rational structure-based design to target the PB1-binding interface on PA. Biological evaluation of these compounds through a viral yield reduction assay revealed that compounds 27 and 31 both had a low micromolar range of the half maximal effective concentration (EC₅₀) values against A/WSN/33 (H1N1) (8.03 μmol/L for 27; 14.6 μmol/L for 31), while the most potent candidate 24 had an EC₅₀ value of 690 nM. Compound 24 was effective against different influenza strains including a pandemic H1N1 strain and an influenza B strain. Mechanistic studies confirmed that compound 24 bound PA with a K _d which equals to 1.88 μmol/L and disrupted the binding of PB1 to PA. The compound also decreased the lung viral titre in mice. In summary, we have identified a potent anti-influenza candidate with potency comparable to existing drugs and is effective against different viral strains. The therapeutic options for influenza infection have been limited by the occurrence of antiviral resistance, owing to the high mutation rate of viral proteins targeted by available drugs. To alleviate the public health burden of this issue, novel anti-influenza drugs are desired. In this study, we present our discovery of a novel class of indazole-containing compounds which exhibited favourable potency against both influenza A and B viruses. The EC₅₀ of the most potent compounds were within low micromolar to nanomolar concentrations. Furthermore, we show that the mouse lung viral titre decreased due to treatment with compound 24. Thus our findings identify promising candidates for further development of anti-influenza drugs suitable for clinical use.

Gynecological cancer is a life-threatening malignancy among women. Traditional therapies, including chemotherapy, often face challenges in terms of chemotherapeutic drug solubility and resistance, specificity, tumor site targeting, and toxicity to healthy tissues, leading to shortened efficacy and unfavorable patient outcomes and survival rates in patients with gynecologic malignancies. Recently, nanotechnology-based therapeutic methods such as targeted drug delivery and phototherapies have emerged as an appropriate alternative to overcome issues associated with traditional therapeutic methods. Specifically, nanomaterials and nanomaterial-based methods enhance the delivery of therapeutic/targeting agents to tumor sites and cellular uptakes and improve the tumor-suppressing effect. This review aims to provide an overview and future perspective on the potential impact of nanotechnology-based therapeutic methods for effective therapies for gynecologic cancer.

Gynecological cancer is a life-threatening malignancy among women. Traditional therapies, including chemotherapy, often face challenges in terms of chemotherapeutic drug solubility and resistance, specificity, tumor site targeting, and toxicity to healthy tissues, leading to shortened efficacy and unfavorable patient outcomes and survival rates in patients with gynecologic malignancies. Recently, nanotechnology-based therapeutic methods such as targeted drug delivery and phototherapies have emerged as an appropriate alternative to overcome issues associated with traditional therapeutic methods. Specifically, nanomaterials and nanomaterial-based methods enhance the delivery of therapeutic/targeting agents to tumor sites and cellular uptakes and improve the tumor-suppressing effect. This review aims to provide an overview and future perspective on the potential impact of nanotechnology-based therapeutic methods for effective therapies for gynecologic cancer.

Gynecological cancer is a life-threatening malignancy among women. Traditional therapies, including chemotherapy, often face challenges in terms of chemotherapeutic drug solubility and resistance, specificity, tumor site targeting, and toxicity to healthy tissues, leading to shortened efficacy and unfavorable patient outcomes and survival rates in patients with gynecologic malignancies. Recently, nanotechnology-based therapeutic methods such as targeted drug delivery and phototherapies have emerged as an appropriate alternative to overcome issues associated with traditional therapeutic methods. Specifically, nanomaterials and nanomaterial-based methods enhance the delivery of therapeutic/targeting agents to tumor sites and cellular uptakes and improve the tumor-suppressing effect. This review aims to provide an overview and future perspective on the potential impact of nanotechnology-based therapeutic methods for effective therapies for gynecologic cancer.

Gynecological cancer is a life-threatening malignancy among women. Traditional therapies, including chemotherapy, often face challenges in terms of chemotherapeutic drug solubility and resistance, specificity, tumor site targeting, and toxicity to healthy tissues, leading to shortened efficacy and unfavorable patient outcomes and survival rates in patients with gynecologic malignancies. Recently, nanotechnology-based therapeutic methods such as targeted drug delivery and phototherapies have emerged as an appropriate alternative to overcome issues associated with traditional therapeutic methods. Specifically, nanomaterials and nanomaterial-based methods enhance the delivery of therapeutic/targeting agents to tumor sites and cellular uptakes and improve the tumor-suppressing effect. This review aims to provide an overview and future perspective on the potential impact of nanotechnology-based therapeutic methods for effective therapies for gynecologic cancer.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Objective:To determine the prevalence of self-reported food allergies among children in the grasslands of North China and to analyze its associated risk factors.Methods:In this study, a cross-sectional epidemiological survey method was used to select children under 14 years old by multi-stage, stratified and random cluster sampling in the grassland ecological area of Zhangbei County, Hebei Province, China from May to July 2018. Face-to-face questionnaires were administered to gather food allergy-related information from the participants. Multivariate logistic regression analysis was used to analyze the risk factors associated with self-reported food allergy.Results:A total of 2 086 children completed the survey. The prevalence of self-reported food allergies was 22.0%(459/2 086). The prevalence of multiple food allergies (≥3 types) was 3.1%(64/2 086) versus 16.3% (341/2 086) for a single food allergy among all children. Mango allergy (6.1%, 127/2 086) was the most common, followed by peach allergy (4.1%, 85/2 086). Children who reported food allergies had a significantly higher prevalence of all 4 atopic disorders (eczema, asthma, allergic rhinitis, and allergic conjunctivitis than those without food allergies(35.73% vs. 20.65%, 5.88% vs. 2.77%, 17.86% vs. 7.38%, 16.78% vs. 10.45%, χ2 =44.663 1, 10.434 3, 45.038 3, 13.728 4, all P<0.001).Significantly associated risk factors of food allergy were found to be pollen allergy ( OR: 2.29; 95% CI: 1.80-2.92) and drug allergy ( OR: 1.53; 95% CI: 1.12-2.09). Conclusions:The prevalence of self-reported food allergies among children in the Zhangbei County area of the North China Grassland was relatively high. Pollen allergy and drug allergy are major risk factors.