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Clinical research reports serve as the presentation of scientific research findings and directly reflect the quality of the research. This article describes the writing of different types of clinical research reports， such as observational studies and randomized controlled trial studies， with a particular focus on randomized controlled trials. Each scientific research design has its reporting focus， and the writing of scientific research papers has uniform requirements and a specific writing format. Mastering the proper format of drafting research reports is of practical value and significant importance for conduction high-quality clinical research.

ObjectiveTo determine the influence of COVID-19 prevention and control on the epidemic characteristics and dynamics of notifiable infectious diseases in the first quarters， Zhejiang Province， and to explore more effective countermeasures against infectious diseases.MethodsDescriptive epidemiology was conducted to determine the change in notifiable infectious diseases during the prevention and control of COVID-19 in Zhejiang Province by retrieving the data of notifiable infectious diseases from 2017 to 2022 in the Chinese information system for disease control and prevention. Cumulative reported new cases of notifiable infectious diseases in the first quarters of 2017‒2019 were compared with that of 2020‒2022.ResultsA total of 546 753 cases of notifiable infectious diseases were newly reported in the first quarters of 2017‒2019， with an average incidence of 321.92/105. In contrast， a total of 509 908 cases of notifiable infectious diseases were newly reported in the first quarters of 2020‒2022， during which the COVID-19 epidemic occurred， with an average incidence of 270.39/105. The incidence in 2020‒2022 significantly declined by 51.53/105， compared with that in 2017‒2019 （χ²=8 072.06， P

ObjectiveTo compare the annual and age trends of the age-standard incidence rate （ASIR） and the age-standard mortality rate （ASMR） of lung cancer in countries with different human development index （HDI） from 1990 to 2019.MethodsThe data were collected from the global burden of disease study and GLOBOCAN 2020. The average annual percentage change （AAPC） and age trends of ASIR and ASMR in lung cancer were analyzed by the Joinpoint regression model， and the comparison between the four groups was analyzed by Kruskale-Wallis analysis.ResultsIn 2020， the incidence and mortality of lung cancer gradually increased with age and HDI grade. From 1990 to 2019， the global ASIR and ASMR of lung cancer decreased， and the ASIR of lung cancer among male decreased， while the ASIR of lung cancer among female increased. The results showed that ASIR of lung cancer in female residents in countries with very high HDI increased significantly from 1996 to 2011， resulting in an overall upward trend in female ASIR， while the other groups showed a downward trend. It was found that ASIR and ASMR of lung cancer in China and India were on the rise， while ASIR and ASMR of lung cancer in Russia and the United States were on the decline.ConclusionAlthough very high/high HDI countries face a higher burden of lung cancer occurrence and death， the accumulation of lung cancer burden is completed in the transitioning period. Therefore， lung cancer prevention measures in countries in transition are critical for global lung cancer control.

Chronic diseases have become an important public health problem for people under 70 years of age worldwide， while also causing a great economic burden. The establishment of clinical prediction models can help to predict the risk of a disease or the prognostic effect of a study subject in advance by means of index testing at the early stage of chronic diseases， and plays an increasingly important role in clinical practice. This study introduces clinical diagnostic prediction models and clinical prognostic prediction models， and reviews clinical data processing， clinical prediction model building， visualization methods and model evaluation from the perspective of the application of clinical prediction models， which contribute to the correct and reasonable use of prediction models in clinical research.

Corona virus disease 2019 （COVID-19） has led to more than 500 million cases， including 6.19 million deaths. Mutated strains of SARS-CoV-2 （alpha， beta， gamma， delta and omicron） have successively emerged. Currently the omicron variant is gradually replacing the delta variant， driving a surge of cases in most countries including China， posing a great challenge to the prevention and treatment of COVID-19. In the face of the severe pandemic situation， a large number of non-medical volunteers are fighting on the front lines of the war against the pandemic and are vulnerable to exposure due to lack of professional knowledge. This paper introduces the routine skills training of volunteers and emergency response， aiming to provide behavioral guidance for non-medical volunteers in designated isolation facilities.

COVID-19 has emerged around the world since December 2019 and rapidly evolves as a major global public health challenge. SARS-CoV-2 is a positive single-stranded RNA virus with a relatively high natural mutation rate. The emergence of SARS-CoV-2 variants is generally considered as the outcome of a “mutation-selection-adaption” process. The enzyme APOBECs that is activated in the inflammatory microenvironment may facilitate viral mutagenesis. Currently， the major SARS-CoV-2 variants that impose public health significance are B.1.1.7， B.1.351， P.1， B.1.6.7.2， B.1.1.529 and so on， with probably increasing transmissibility， decreasing reactivity to the neutralizing antibodies， immune escape， and enhancing disease severity and mortality. Consequently， it warrants up-to-date countermeasures against evolving SARS-CoV-2， including tracing viral mutagenesis， developing vaccines against major variants， and enhancing social distancing.

In silicon photonics, BaTiO3 (BTO) emerges as a promising electro‐optic (EO) integrated material due to its excellent EO modulation capabilities. Nevertheless, the EO response of multi‐domain BTO thin films tends to be lower than that of bulk materials. BTO thin films are fabricated with strong EO responses utilizing the pulsed laser deposition technique. Considering the importance of the SrTiO3 (STO) buffer layer, a series of epitaxial BTO thin films are deposited on STO substrates with engineered domain alignment. Given the contribution of domain variants in BTO thin films to their EO response, specific electrode patterns are designed to enhance their performance. An effective Pockels coefficient of 286 pm V−1 is determined for the BTO thin film via the transmission geometry method, which surpasses recent reports. Through domain engineering in the BTO thin film, the remarkable enhancement in the EO response arising from in‐plane polarization (a‐axis) characteristics is confirmed. Simultaneously, utilizing the Second Harmonic Generation (SHG) optical probe, deep exploration into the domain dynamics within BTO thin films is conducted. These findings provide insights into the contribution of domain variants to the EO response and shed light on further developing silicon‐based heterogeneously integrated devices. [ABSTRACT FROM AUTHOR]

Simple Summary: Liver metastasis remains a major hurdle to the long-lasting survival of patients with colorectal cancer (CRC). When CRC spreads to the liver, tumor cells undergo a series of changes to adapt to the new environment, leading to evident heterogeneity. Therefore, understanding the features of metastatic tumor cells in the liver is valuable for the overall control of patients with colorectal cancer liver metastasis (CRLM). In this review, we provide a comprehensive overview of the spatial heterogeneity of CRLM at different molecular levels, including genetics, transcriptomics, proteomics, metabolism, and immune levels. While genetic heterogeneity may not be apparent, the other four levels demonstrate significant heterogeneity. Compared to primary CRC, the epithelial–mesenchymal transition (EMT)-related proteins are significantly altered. Moreover, the metabolic activity is enhanced and the infiltration of immuno-suppressive cells is increased in CRLM. All these changes promote the metastasis and colonization of CRC cells. Based on these findings, we also summarize preclinical therapeutic modalities targeting the heterogeneity of CRLM, aiming to provide new directions for clinical interventions and improve the survival rates of these patients. Colorectal cancer liver metastasis (CRLM) is a highly heterogeneous disease. Therapies that target both primary foci and liver metastasis are severely lacking. Therefore, understanding the features of metastatic tumor cells in the liver is valuable for the overall control of CRLM patients. In this review, we summarize the heterogeneity exhibited in CRLM from five aspects (gene, transcriptome, protein, metabolism, and immunity). In addition to genetic heterogeneity, the other four aspects exhibit significant heterogeneity. Compared to primary CRC, the dysregulation of epithelial–mesenchymal transition (EMT)-related proteins, the enhanced metabolic activity, and the increased infiltration of immunosuppressive cells are detected in CRLM. Preclinical evidence shows that targeting the EMT process or enhancing cellular metabolism may represent a novel approach to increasing the therapeutic efficacy of CRLM. [ABSTRACT FROM AUTHOR]

The emergence of COVID-19 has broken the silence of humanity and people are gradually becoming concerned about pneumonia-related diseases; thus, improving the recognition rate of pneumonia-related diseases is an important task. Neural networks have a remarkable effectiveness in medical diagnoses, though the internal parameters need to be set in accordance to different data sets; therefore, an important challenge is how to further improve the efficiency of neural network models. In this paper, we proposed a learning exponential distribution optimizer based on chaotic evolution, and we optimized Resnet50 for COVID classification, in which the model is abbreviated as IEDO-net. The algorithm introduces a criterion for judging the distance of the signal-to-noise ratio, a chaotic evolution mechanism is designed according to this criterion to effectively improve the search efficiency of the algorithm, and a rotating flight mechanism is introduced to improve the search capability of the algorithm. In the computed tomography (CT) image data of COVID-19, the accuracy, sensitivity, specificity, precision, and F1 score of the optimized Resnet50 were 94.42%, 93.40%, 94.92%, 94.29% and 93.84%, respectively. The proposed network model is compared with other algorithms and models, and ablation experiments and convergence and statistical analyses are performed. The results show that the diagnostic performance of IEDO-net is competitive, which validates the feasibility and effectiveness of the proposed network. [ABSTRACT FROM AUTHOR]