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Abstract Background In research to improve the quality of transgenic crops, it is often necessary to introduce multiple functionally related genes into recipient plants simultaneously to improve crop genetic traits effectively. Compared with unidirectional promoters, bidirectional promoters simultaneously regulate the expression of multiple genes and improve the efficiency of biotechnology. Therefore, in this study, bidirectional gene pairs were systematically analyzed in Gossypium hirsutum TM-1, and the structure, function and evolutionary relationships of the bidirectional genes were analyzed. The endogenous bidirectional promoters of cotton were mined, and their specific regulatory elements and biological functions were explored to provide useful promoter resources and a theoretical basis for cultivating new cotton germplasms with excellent fiber quality. Results Using an improved search model, a total of 1,383 bidirectional transcript pairs were identified in the Gossypium hirsutum TM-1 genome, and their gene structure and functional annotations were systematically analyzed. Thirty bidirectional intergenic sequences were randomly screened for promoter activity analysis via a transient expression system, and 25 intergenic sequences were found to have bidirectional promoter activity. Comparative analysis of the bidirectional gene profiles of the four cotton subspecies revealed that these subspecies presented abundant bidirectional gene pairs with high homology and that the bidirectional genes in the cotton subspecies were more similar in terms of their molecular functions, cellular components and biological processes. In addition, parallel analysis of bidirectional genes in dicotyledons and monocotyledons revealed that abundant bidirectional gene pairs exist in different species. Although the total number of orthologous bidirectional genes was similar, there was a significant difference in the number of orthologous bidirectional gene pairs between dicotyledons and monocotyledons. This evolutionary analysis of the function and structure of homologous bidirectional gene pairs in different varieties and different subspecies of the same species revealed potential pathways by which these gene pairs originated, which may be necessary for the evolution of a new species. Conclusion In this study, many bidirectional gene pairs in Gossypium hirsutum TM-1 were identified using computer programming, and systematic analysis was conducted to explore their functions and evolutionary relationships. In addition, the promoter activity of the bidirectional intergenic sequences was verified. The combination of computer programming screening, experimental validation and other methods is expected to provide preferred bidirectional promoters for transgenic breeding work via multigene cotransformation methods, and this information is valuable for genetic engineering research and applications.

Introduction Sentinel lymph node biopsy (SLNB) is a standard procedure for patients with clinically assessed negative axillary lymph nodes (cN0) during early-stage breast cancer (EBC). However, the majority of EBC patients have a negative pathological confirmation of the sentinel lymph node (SLN), and axillary surgery is inevitably associated with postoperative complications. Considering that SLNB has no therapeutic benefit, this trial aims to determine the safety of omitting SLNB in patients with cN0 early invasive breast cancer.Methods and analysis The OMSLNB trial is a prospective, single-arm, non-inferiority, phase II, open-label study design involving female breast cancer patients with a tumor of ≤3 cm in diameter, who are considered axillary lymph-node-negative based on two or more radiological examinations, including axillary lymph node ultrasonography. Eligible patients will avoid axillary surgery but will undergo breast surgery, which is not limited to breast-conserving surgery. The trial begins in 2023 and is scheduled to end in 2027. The primary endpoint is 3 year invasive disease-free survival (iDFS). The secondary endpoints include the incidence of breast cancer-related lymphoedema, patient-reported outcomes, locoregional recurrence, local recurrence and regional recurrence. It is expected that the 3 year iDFS in patients undergoing SLNB is about 90%, combined with a non-inferiority cut-off of 5%, 80% power, 95% CIs, 0.05 test level, and 10% loss to follow-up rate, the planned enrollment is 311 patients. All enrolled patients will be included in the intention-to-treat analysis.Ethics and dissemination This trial was approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (No.2023-SR-193). All participants must provide written informed consent to be eligible. The protocol will be described in a peer-reviewed manuscript, and the results will be published in scientific journals and/or at academic conferences.Trial registration number NCT05935150.

Understanding the complex influencing factors of soil erosion is critical for maintaining regional ecological security. The revised wind erosion equation (RWEQ) and partial least squares regression (PLSR) model were used to reveal the primary factors affecting soil erosion. Based on the results of the RWEQ model, the wind erosion area was 8,439.3 km2 in 2018, accounting for 54.3% of the total planning area, and mild erosion, moderate erosion, intense erosion, very intense erosion, and fierce erosion accounted for 18.22%, 11.43%, 11.78%, 10.16%, and 2.74% of the total planning area, respectively. Based on the results of the PLSR model, the results indicate that the proportion of mining land, meteorological indicators, and mean square deviation of slope difference were positively correlated with the soil erosion area, intensity, and severity, respectively. The proportion of grassland and forest land was negatively correlated with the soil erosion area, intensity, and severity. The mean square deviation of slope difference, the mean square deviation of difference in elevation, and the proportion of urban land use contributed the most to the soil erosion severity index, with variable importance in projection (VIP) scores of 1.55, 1.44 and 1.43, respectively. The mean square deviation of slope difference, the proportion of urban land, and the mean square deviation of difference in elevation contributed the most to the soil erosion area, with VIP scores of 1.53, 1.26 and 1.24, respectively. The results provide new insights into wind erosion and the influences of weather conditions and human influences, which can guide regional soil and water conservation planning in wind erosion regions.

Peripheral blood mononuclear cell (PBMC) are recognized as a conveniently collected reprogramming resource. Several methods are available in academia to reprogram PBMC into induced pluripotent stem cells (iPSC). In this research, we reprogrammed PBMC of different genders by using non-integrative non-viral liposome electrotransfer containing the reprogramming factors OCT4, SOX2, KLF4, and c-MYC. The three obtained iPSC cell lines were karyotypically normal and showed significant tritiated differentiation potential in vitro and in vivo. Our study provided an efficient procedure for reprogramming PBMC into iPSC and obtained three well-functioning iPSC, that may contribute to advance personalized cell therapy in the future.

Abstract Background We explored the potential novel anticancer mechanisms of 25‐hydroxyvitamin D (25(OH)D), a vitamin D metabolite with antitumour effects in breast cancer. It is stable in serum and is used to assess vitamin D levels in clinical practice. Transfer RNA‐derived small RNAs are small noncoding RNAs that generate various distinct biological functions, but more research is needed on their role in breast cancer. Methods Small RNA microarrays were used to explore the novel regulatory mechanism of 25(OH)D. High‐throughput RNA‐sequencing technology was used to detect transcriptome changes after 25(OH)D treatment and tRF‐1‐Ser knockdown. RNA pull‐down and high‐performance liquid chromatography–mass spectrometry/mass spectrometry were used to explore the proteins bound to tRF‐1‐Ser. In vitro and in vivo functional experiments were conducted to assess the influence of 25(OH)D and tRF‐1‐Ser on breast cancer. Semi‐quantitative PCR was performed to detect alternative splicing events. Western blot assay and qPCR were used to assess protein and mRNA expression. Results The expression of tRF‐1‐Ser is negatively regulated by 25(OH)D. In our breast cancer (BRCA) clinical samples, we found that the expression of tRF‐1‐Ser was higher in cancer tissues than in paired normal tissues, and was significantly associated with tumour invasion. Moreover, tRF‐1‐Ser inhibits the function of MBNL1 by hindering its nuclear translocation. Functional experiments and transcriptome data revealed that the downregulation of tRF‐1‐Ser plays a vital role in the anticancer effect of 25(OH)D. Conclusions In brief, our research revealed a novel anticancer mechanism of 25(OH)D, unveiled the vital function of tRF‐1‐Ser in BRCA progression, and suggested that tRF‐1‐Ser could emerge as a new therapeutic target for BRCA.

Digitalization has enabled the potential for artificial intelligence techniques to lead the power system to a sustainable transition by extracting the data generated by widely deployed edge devices, including advanced sensing and metering. Due to the increasing concerns about data privacy, federated learning has attracted much attention and is emerging as an innovative application for machine learning solutions in the power and energy sector. This paper presents a holistic analysis of federated learning applications in the energy sector, ranging from applications in generation, microgrids, and distribution systems to the energy market and cyber security. The following federated learning-based services for energy sectors are analyzed: non-intrusive load monitoring, fault detection, energy theft detection, demand forecasting, generation forecasting, energy management systems, voltage control, anomaly detection, and energy trading. The identification and classification of the data-driven methods are conducted in collaboration with federated learning implemented in these services. Furthermore, the interrelation is mapped between the categories of machine learning, data-driven techniques, the application domain, and application services. Finally, the future opportunities and challenges of applying federated learning in the energy sector will be discussed.

IntroductionAnti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. MethodsUltra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. ResultsA partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. DiscussionThis study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

In recent years, the frequent occurrence of public health emergencies has affected people’s daily lives. In response, this paper evaluates the risk of logistics terminal distribution and puts forward the corresponding countermeasures. Firstly, this paper summarizes relevant literature and analyzes the characteristics of public health emergencies and logistics terminal distribution. This paper constructs the risk index system of logistics terminal distribution under public health emergencies for the first time. Secondly, this paper conducts a questionnaire survey on a domestic e-commerce enterprise. In this paper, the intuitionistic fuzzy entropy weight method is applied to the obtained data to determine the weight of risk index. Finally, this paper adopts the grey fuzzy comprehensive evaluation method to evaluate the risk index of logistics terminal distribution under public health emergencies. This paper takes the impact of public health emergencies into account for the risk of logistics terminal distribution for the first time. Some suggestions are provided for preventing the logistics terminal distribution from stagnation and paralysis when public health emergencies occur. This paper supplements the existing research in this field.

The fungal genus Nigrospora is known to be a plant pathogen, endophyte, and saprobe, and it is usually isolated from various substrates like soil and air. During the surveys of soil fungi in Hebei Province of China, two isolates of Nigrospora were obtained. A multi-locus phylogeny of combined loci of the 5.8S nuclear ribosomal gene with the two flanking transcribed spacers (ITS), part of the translation elongation factor 1-alpha (tef1), and the beta-tubulin (tub2) loci, in conjunction with morphological characters were used to identify the newly collected isolates. Nigrospora humicola sp. Nov. is described and proposed herein, which differs from its phylogenetically close species N. chinensis and N. globosa by the sequences of ITS, tef1, and tub2.

This paper presents an efficient and compact Matlab code for 2D and 3D topology optimization of multi-materials. We extend a classical 88-line-based educational code to the multi-material problem using the mapping-based interpolation function, with which each material is modeled equally and can obtain a clear 0, 1 result for each material of the optimized structures that can be manufactured easily. A solution of topology optimization of multi-materials with minimum compliance under volume constraints is documented, including the details of the optimization model, filtering, projection, and sensitivity analysis procedures. Several numerical examples are also conducted to demonstrate the effectiveness of the code, and the influence of the parameter on the optimized results is also analyzed. Complete 2D and 3D Matlab codes are provided.

Objective: The study analyzed the impact of urbanization on epidemiological characteristics of respiratory infectious disease in Tongzhou District, Beijing during 2014–2022 to provide reference for prevention and control priorities of respiratory infectious diseases during the innovative urbanization process in China. Methods: The incidence data of notifiable respiratory infectious diseases (NRIDs) in Tongzhou Beijing during 2014–2022 were summarized. The trend of incidence rate was analyzed by Joinpoint regression model, and entropy method was performed to construct the comprehensive index of urbanization (CIU) and generalized linear model was used to analyze the influence of CIU on the incidence rate of respiratory infectious diseases. Results: Totally 72616 NRIDs cases were reported in Tongzhou District during 2014–2022, and the incidence rate of NRIDs was higher during 2017–2019 (153/100 000) than during 2014–2016 (930/100 000) and during 2020–2022 (371/100 000), respectively (both P

The aroma types of cream cheese affect its commercial value and consumer acceptability. However, the types of volatile substances and sensory characteristics of cream cheese at different fermentation stages are still unclear. Therefore, in this study, headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) were used to analyze the volatile substances in cream cheese fermentation. Orthogonal partial least squares discriminant analysis (OPLS-DA), odor activity value (OAV), relative odor activity value (ROAV) and variable projection importance (VIP) were used to identify the characteristic flavor substances in cream cheese fermentation. Finally, the relationship between key flavor substances and sensory characteristics was determined by partial least squares (PLS) analysis. A total of 34 and 36 volatile organic compounds were identified by HS-SPME-GC-MS and HS-GC-MS, respectively, and 14 characteristic flavor substances were found, based on VIP, ROAV and OAV models. Combined with sensory analysis and flavor substance changes, it was found that the cream cheese fermented for 15 d had the best flavor and taste. This study reveals the characteristics and contribution of volatile substances in cream cheese at different fermentation stages, which provides new insights into improving flavor and quality control.