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Objectives: This study aimed to explore the preferences and influencing factors of self-management behaviors in patients with recurrent gout and provide a theoretical basis for developing targeted strategies to improve self-management preferences. Methods: A total of 10 patients with recurrent gout were recruited from the gout specialist outpatient clinic at a tertiary hospital in Shenyang, Liaoning Province, China. Semi-structured interviews were conducted with these patients, and the Kawakita Jiro (KJ) method was used to analyze the interview data. Results: After four rounds of screening by five researchers, 35 codes were selected from an initial 132. After three rounds of discussion and induction, the KJ method identified seven domains of self-management behavior preferences in patients with recurrent gout: 1) extensive knowledge of gout, yet difficulty in distinguishing between accurate and inaccurate information; 2) a passive attitude of “no pain, no management”; 3) the challenge of changing entrenched daily habits; 4) the optimistic but unrealistic belief of “self-delusion”; 5) a tendency to seek medical attention late due to hopelessness of cure and familiarity with recurrences; 6) preference for analgesics for gout recurrences while neglecting long-term urate-lowering therapy (ULT); and 7) gout-related stigma. Conclusion: The results of this study showed that the self-management behavior of patients with recurrent gout could be improved, especially in the aspects of medical seeking behavior, medication compliance, daily management and emotional management. At the same time, we found that gout stigma, difficulty in distinguishing true and false knowledge of gout and negative attitude of “ignoring pain” were significantly associated with self-management behavior.

Abstract Precise regulation of gene expression is crucial to development. Enhancers, the core of gene regulation, determine the spatiotemporal pattern of gene transcription. Since many disease-associated mutations are characterized in enhancers, the research on enhancer will provide clues to precise medicine. Rapid advances in high-throughput sequencing technology facilitate the characterization of enhancers at genome wide, but understanding the functional mechanisms of enhancers remains challenging. Herein, we provide a panorama of enhancer characteristics, including epigenetic modifications, enhancer transcripts, and enhancer-promoter interaction patterns. Furthermore, we outline the applications of high-throughput sequencing technology and functional genomics methods in enhancer research. Finally, we discuss the role of enhancers in human disease and their potential as targets for disease prevention and treatment strategies.

Abstract ‘Boju’ and ‘Huaiju’ are cultivars of the Chrysanthemum (Chrysanthemum morifolium Ramat.) in the family Asteraceae, valued for their medicinal, tea, and ornamental properties, and valued by individuals. However, the yield and quality of medicinal chrysanthemums are limited by the characteristics of the germplasm resources, including the identification at the varieties and cultivation levels. Currently, research characterizing the chloroplast genomes of medicinal Chrysanthemum flowers is relatively limited. This study conducted chloroplast whole-genome sequencing on two cultivars of Chrysanthemum, ‘Boju’ and ‘Huaiju’, and compared them with the previously published chloroplast genomes of ‘Hangbaiju’ and ‘Gongju’. The study analyzed the chloroplast genome structures of these four medicinal Chrysanthemums, identifying mutation hotspots and clarifying their phylogenetic relationships. The chloroplast genome sizes of four medicinal Chrysanthemum cultivation products ranged from 151,057 to 151,109 bp, with GC content ranging from 37.45% to 37.76%. A total of 134 genes were identified, including 89 protein-coding genes, 37 ribosomal RNA genes, and 8 transfer RNA genes. Comparative genomic analysis revealed 159 large repeat sequences, 276 simple sequence repeats, 1 gene, and 8 intergenic regions identified as highly variable regions. Nucleotide diversity (Pi) values were high (≥ 0.004) for the petN-psbM, trnR-UCU-trnT-GGU, trnT-GGU-psbD, ndhC-trnV-UCA, ycf1, ndhI-ndhG, trnL-UGA-rpl32, rpl32-ndhF, and ndhF-ycf1 fragments, aiding in variety identification. Phylogenetic analysis revealed consistent results between maximum likelihood and Bayesian inference trees, showing that the four medicinal Chrysanthemum cultivars, along with their wild counterparts and related species, evolved as a monophyletic group, forming a sister clade to Artemisia and Ajania. Among the six Chrysanthemum species, the wild Chrysanthemum diverged first (Posterior probability = 1, bootstrap = 1,000), followed by Ajania, while C. indicum and C. morifolium clustered together (Bootstrap = 100), indicating their closest genetic relationship. The chloroplast whole-genome data and characteristic information provided in this study can be used for variety identification, genetic conservation, and phylogenetic analysis within the family Asteraceae.

Creating ferroelectricity in centrosymmetric and paramagnetic materials through nanostructures presents a challenge in materials science due to their high symmetry and paired spins. Herein, the induction of chirality‐induced ferroelectricity and photoelectric chiral anisotropy in chiral mesostructured MnWO4 films (CMWFs) resulting from spin chiral anisotropy in chiral mesostructures is reported. The CMWFs, prepared via a hydrothermal route induced by chiral molecules, consists of densely packed MnWO4 nanoparticle crystals exhibiting long‐range ordered helical lattice distortion grown perpendicularly along the 010 axis on the substrates. These CMWFs exhibit ferroelectric properties with a Curie temperature of ≈60 °C and photoelectric chiral anisotropy with an anisotropy factor of ≈0.5. The findings pave the way for ferroelectricity through long‐range spin current via chirality.

Abstract Background Enhancers are important gene regulatory elements that promote the expression of critical genes in development and disease. Aberrant enhancer can modulate cancer risk and activate oncogenes that lead to the occurrence of various cancers. However, the underlying mechanism of most enhancers in cancer remains unclear. Here, we aim to explore the function and mechanism of a crucial enhancer in melanoma. Methods Multi-omics data were applied to identify an enhancer (enh17) involved in melanoma progression. To evaluate the function of enh17, CRISPR/Cas9 technology were applied to knockout enh17 in melanoma cell line A375. RNA-seq, ChIP-seq and Hi-C data analysis integrated with luciferase reporter assay were performed to identify the potential target gene of enh17. Functional experiments were conducted to further validate the function of the target gene ETV4. Multi-omics data integrated with CUT&Tag sequencing were performed to validate the binding profile of the inferred transcription factor STAT3. Results An enhancer, named enh17 here, was found to be aberrantly activated and involved in melanoma progression. CRISPR/Cas9-mediated deletion of enh17 inhibited cell proliferation, migration, and tumor growth of melanoma both in vitro and in vivo. Mechanistically, we identified ETV4 as a target gene regulated by enh17, and functional experiments further support ETV4 as a target gene that is involved in cancer-associated phenotypes. In addition, STAT3 acts as a transcription factor binding with enh17 to regulate the transcription of ETV4. Conclusions Our findings revealed that enh17 plays an oncogenic role and promotes tumor progression in melanoma, and its transcriptional regulatory mechanisms were fully elucidated, which may open a promising window for melanoma prevention and treatment.

Sea state bias (SSB) is a crucial error of satellite radar altimetry over the ocean surface. For operational nonparametric SSB (NPSSB) models, such as two-dimensional (2D) or three-dimensional (3D) NPSSB, the solution process becomes increasingly complex and the construction of their regression functions pose challenges as the dimensionality of relevant variables increases. And most current SSB correction models for altimeters still follow those of traditional nadir radar altimeters, which limits their applicability to Synthetic Aperture Radar altimeters. Therefore, to improve this situation, this study has explored the influence of multi-dimensional SSB models on Synthetic Aperture Radar altimeters. This paper proposes a deep learning-based SSB estimation model called SNSSB, which employs a Siamese network framework, takes various multi-dimensional variables related to sea state as inputs, and uses the difference in sea surface height (SSH) at self-crossover points as the label. Experiments were conducted using Sentinel-6 self-crossover data from 2021 to 2023, and the model is evaluated using three main metrics: the variance of the SSH difference, the explained variance, and the SSH difference variance index (SVDI). The experimental results demonstrate that the proposed SNSSB model can further improve the accuracy of SSB estimation. On a global scale, compared to the traditional NPSSB, the multi-dimensional SNSSB not only decreases the variance of the SSH difference by over 11%, but also improves the explained variance by 5-10 cm2 in mid- and low-latitude regions. And the regional SNSSB also performs well, reducing the variance of the SSH difference by over 10% compared to the NPSSB. Additionally, the SNSSB model improves the computational efficiency by approximately 100 times. The favorable results highlight the potential of the multi-dimensional SNSSB in constructing SSB models, particularly the five-dimensional (5D) SNSSB, representing a breakthrough in overcoming the limitations of traditional NPSSB for constructing high-dimensional models. This study provides a novel approach to exploring the multiple influencing factors of SSB.

Inversion of the underwater temperature anomaly of mesoscale eddies from sea surface remote sensing data plays an important role in understanding the three-dimensional structure of eddies. In this article, a neural network structure, named the eddy temperature anomaly inversion network (EddyTAINet), is proposed and established to invert the vertical temperature anomalies of eddies using 20-year (2002–2022) Argo profiles and multi-source remote sensing data in the northwestern Pacific Ocean. Vertical temperature anomaly profiles with 45 depth levels ranging from 10 to 1000 m are derived as the outputs of the inversion networks. The input feature sequences are extracted from the mesoscale eddy product based on sea level anomaly (SLA) data, and sea surface temperature (SST) data are also introduced into the proposed network structure to improve its accuracy. For the problem of inconsistent sizes of the 2D matrix SST data corresponding to mesoscale eddies, the spatial pyramid pooling (SPP) network module is introduced, which allows different sizes of SST data to be simply convolved and then subjected to hierarchical feature extraction to obtain fixed-size feature vectors. Validation and comparison of the network structure are performed and show the improved performance of EddyTAINet. The average root mean square error (RMSE) and mean absolute error (MAE) are 0.63 °C/0.66 °C and 0.48 °C/0.51 °C for cyclonic and anticyclonic eddies, respectively, which are more than 20% lower than the results of the network using the SLA-based data.

Zn2P2O7, a representative material in the A2P2O7 family, exhibits negative thermal expansion (NTE) and possesses a remarkable negative linear expansion coefficient. Here we employ variable temperature and high-pressure Raman spectroscopy to investigate the phonon anomalies arising from the α- to β-phase transition in Zn2P2O7. Combing with the refinement results of our X-ray diffraction (XRD) experiment, we have identified the specific variations of the bond lengths, bond angles and the polyhedral distortion indexes that result in the phonon anomalies. Some certain phonons, whose energy decreases with increasing pressure, have been demonstrated to give rise to negative Grüneisen parameters that can characterize phonon anharmonicity and lead to lower thermal expansion in the α-phase of Zn2P2O7 compared to the β-phase. These results provide new insight into the relationship between lattice deformation and phonon anomalies during the structural phase transition in the NTE material Zn2P2O7.

Background Platycodon grandiflorus belongs to the genus Platycodon and has many pharmacological effects, such as expectorant, antitussive, and anti-tumor properties. Among transcription factor families peculiar to eukaryotes, the basic leucine zipper (bZIP) family is one of the most important, which exists widely in plants and participates in many biological processes, such as plant growth, development, and stress responses. However, genomic analysis of the bZIP gene family and related stress response genes has not yet been reported in P. grandiflorus. Methods P. grandiflorus bZIP (PgbZIP) genes were first identified here, and the phylogenetic relationships and conserved motifs in the PgbZIPs were also performed. Meanwhile, gene structures, conserved domains, and the possible protein subcellular localizations of these PgbZIPs were characterized. Most importantly, the cis-regulatory elements and expression patterns of selected genes exposed to two different stresses were analyzed to provide further information on PgbZIPs potential biological roles in P. grandiflorus upon exposure to environmental stresses. Conclusions Forty-six PgbZIPs were identified in P. grandiflorus and divided into nine groups, as displayed in the phylogenetic tree. The results of the chromosomal location and the collinearity analysis showed that forty-six PgbZIP genes were distributed on eight chromosomes, with one tandem duplication event and eleven segmental duplication events identified. Most PgbZIPs in the same phylogenetic group have similar conserved motifs, domains, and gene structures. There are cis-regulatory elements related to the methyl jasmonate (MeJA) response, low-temperature response, abscisic acid response, auxin response, and gibberellin response. Ten PgbZIP genes were selected to study their expression patterns upon exposure to low-temperature and MeJA treatments, and all ten genes responded to these stresses. The real-time quantitative polymerase chain reaction (RT-qPCR) results suggest that the expression levels of most PgbZIPs decreased significantly within 6 h and then gradually increased to normal or above normal levels over the 90 h following MeJA treatment. The expression levels of all PgbZIPs were significantly reduced after 3 h of the low-temperature treatment. These results reveal the characteristics of the PgbZIP family genes and provide valuable information for improving P. grandiflorus’s ability to cope with environmental stresses during growth and development.

Chrysanthemum morifolium is a perennial herbaceous plant in the Asteraceae family that is used as a medicine and food owing to its superior pharmacological properties. Irrespective of its application, C. morifolium must be dried before use. Shade drying (YG) and heat drying (HG) are the two drying methods used in most origins. Given the abundance of flavonoids, phenolic acids, and terpenoids, the primary medicinal active constituents of C. morifolium, it is important to determine whether the composition and content of these compounds are altered during the drying processes. To test this, the changes in the chemical composition of C. morifolium flowers after YG and HG using full-spectrum, non-targeted LC/GC–MS−based metabolomics and, subsequently, the three indicator components of C. morifolium—chlorogenic acid, 3,5−dicaffeoylquinic acid, and luteolin−7−O−glucoside—were accurately quantified by HPLC. The results of the non-targeted metabolomics analysis revealed that YG- and HG-processed C. morifolium differed significantly with respect to chemical contents, especially flavonoids, phenolic acids, and terpenoids. The levels of the indicator components and their precursors also differed significantly between the YG and HG treatments. The contents of most of the flavonoids and key phenolic acids, terpenoids, and carbohydrates were higher with YG than with HG pre-treatment. These results revealed the changes in the chemical composition of C. morifolium during the YG and HG processes, thus providing a reference for the further optimization of the production and processing of chrysanthemums.

IntroductionIn shallow-water environments, the reliability of underwater communication links is often compromised by significant multipath effects. Some equalization techniques such as decision feedback equalizer, and deep neural network equalizer suffer from slow convergence and high computational complexity.MethodsTo address this challenge, this paper proposes a simplified decision feedback Chebyshev function link neural network equalizer (SDF-CFLNNE). The structure of the SDF-CFLNNE employs Chebyshev polynomial function expansion modules to directly and non-linearly transform the input signals into the output layer, without the inclusion of hidden layers. Additionally, it feeds the decision signal back to the input layer rather than the function expansion module, which significantly reduces computational complexity. Considering that, in the training phase of neural networks, the random initialization of weights and biases can substantially impact the training process and the ultimate performance of the network, this paper proposes a chaotic sparrow search algorithm combining the osprey optimization algorithm and Cauchy mutation (OCCSSA) to optimize the initial weights and thresholds of the proposed equalizer. The OCCSSA utilizes the Piecewise chaotic population initialization and combines the exploration strategy of the ospreywith the Cauchy mutation strategy to enhance both global and local search capabilities. RseultsSimulations were conducted using underwater multipath signals generated by the Bellhop Acoustic Toolbox. The results demonstrate that the performance of the SDFCFLNNE initialized by OCCSSA surpasses that of CFLNN-based and traditional nonlinear equalizers, with a notable improvement of 2-6 dB in terms of signal-to-noise ratio at a bit error rate (BER) of 10−4 and a reduced mean square error (MSE). Furthermore, the effectiveness of the proposed equalizer was validated using the lake experimental data, demonstrating lower BER and MSE with improved stability. DiscussionThis underscores thepromise of employing the SDFCFLNNE initialized by OCCSSA as a promising solution to enhance the robustness of underwater communication in challenging environments.

Mesoscale eddies are ubiquitous oceanic phenomena and play an important role in ocean circulation, ocean dynamics, and the transport of material energy. Temperature anomalies are a crucial parameter that reflects the state of mesoscale eddies. This study proposes a Gaussian function model to fit the vertical temperature anomaly (TA) profile to facilitate the analysis of variations, and the principle of the model is based on the fact that each TA profile tends to fluctuate around one or more peaks. The model is extracted and validated using Argo profiles within cyclonic and anticyclonic eddies in the Northwest Pacific Ocean spanning over the period from 2002 to 2021. The validation demonstrates that the model can accurately recover the vertical TA profiles with a limited number of parameters. This makes it suitable for analysing the spatial distribution patterns that require a large sample count. The analysis indicates that eddies with different TA profiles have a spatial aggregation effect in geographic distribution. Eddies with lower extreme temperature anomalies, at depths of 200–300 m, are mainly distributed along two bands on the north side of the Kuroshio Extension (KE) and the North Equatorial Current. Eddies with extreme TAs at the deepest depth (500–600 m) are distributed along the KE.

Chiral mesostructured inorganic crystals exhibit distinctive twisting and helical hierarchical stacking. Here, the authors report a general approach for the synchronous quantitative analysis of rotation axis, torsion angle, pitch length, and arrangement modes.

BackgroundPrevious studies found that Jinlida granules could significantly reduce blood glucose levels and enhance the low-glucose action of metformin. However, the role of Jinlida in the standard-reaching rate of blood glucose and improving clinical symptoms has yet to be studied. We aimed to elaborate on the efficacy of Jinlida in type 2 diabetes (T2D) patients who experience clinical symptoms based on secondary analysis of a randomized controlled trial.MethodsData were analyzed from a 12-week, randomized, placebo-controlled study of Jinlida. The standard-reaching rate of blood glucose, the symptom disappearance rate, the symptom improvement rate, the efficacy of single symptoms, and the total symptom score were evaluated. The correlation between HbA1c and the improvement of clinical symptoms was analyzed.ResultsFor 12 weeks straight, 192 T2D patients were randomly assigned to receive either Jinlida or a placebo. The treatment group showed statistically significant differences in the standard-reaching rate of HbA1c < 6.5% (p = 0.046) and 2hPG (< 10 mmol/L, 11.1 mmol/L) (p < 0.001), compared with the control group. The standard-reaching rate of HbA1c < 7% (p = 0.06) and FBG < 7.0 mmol/L (p = 0.079) were not significantly different between the treatment and control groups. Five symptoms exhibited a statistical difference in symptom disappearance rate (p < 0.05). All the symptoms exhibited a significant difference in symptom improvement rate (p < 0.05). The mean change in total symptom score from baseline to week 12 was −5.45 ± 3.98 in the treatment group and −2.38 ± 3.11 in the control group, with statistically significant differences (p < 0.001). No significant correlations were noted between symptom improvement and HbA1c after 12 weeks of continuous intervention with Jinlida granules or placebo.ConclusionJinlida granules can effectively improve the standard-reaching rate of blood glucose and clinical symptoms of T2D patients, including thirst, fatigue, increased eating with rapid hungering, polyuria, dry mouth, spontaneous sweating, night sweat, vexing heat in the chest, palms, and soles, and constipation. Jinlida granules can be used as an effective adjuvant treatment for T2D patients who experience those symptoms.

Emulsification is increasingly emphasized for heavy oil recovery through chemical flooding. However, whether systems with fine-emulsification (FE) properties significantly outperform conventional ultra-low interfacial tension (IFT) systems, especially under varying water-oil viscosity ratios, remains unclear. In this research, two FE systems and one conventional ultra-low IFT system are compared in terms of their IFTs, emulsification properties, foaming behaviors, and heavy oil recovery (in the form of combination flooding and foam flooding). The results show that FE systems 1# and 2# can generate more stable emulsions of heavy oil than the traditional ultra-low IFT variant 3#. During the first combination flooding, FE systems recover 24.5% and 27.9% of the oil after water, obviously surpassing 21.0% of the ultra-low IFT system 3#; but as this ratio increases to 0.45, those factors become very similar to ones of 33.2%, 34.5% and 32.9%, with the former no longer outperforming the latter. In the second trials of foam flooding, at a lower water-oil viscosity ratio of 0.05, FE foam 1# becomes less effective than the ultra-low IFT 3#, with oil recovery factors of 27.2% and 31.6%, respectively; but foam 2# (combining medium emulsification and ultra-low IFT) remains optimal, with the highest recovery factor of 40.0%. Again, as this ratio becomes 0.45, the advantages of FE systems over the ultra-low IFT system are almost negligible, generating similar oil recoveries of 39.2%, 41.0% and 39.4%.

Abstract Since the outbreak of coronavirus disease 2019 (COVID-19), traditional Chinese medicine (TCM) has made an important contribution to the prevention and control of the epidemic. This review aimed to evaluate the efficacy and explore the mechanisms of TCM for COVID-19. We systematically searched 7 databases from their inception up to July 21, 2021, to distinguish randomized controlled trials (RCTs), cohort studies (CSs), and case–control studies (CCSs) of TCM for COVID-19. Two reviewers independently completed the screening of literature, extraction of data, and quality assessment of included studies. Meta-analysis was performed using Review Manager 5.4 software. Eventually, 29 RCTs involving 3060 patients and 28 retrospective studies (RSs) involving 12,460 patients were included. The meta-analysis demonstrated that TCM could decrease the proportion of patients progressing to severe cases by 55% and the mortality rate of severe or critical patients by 49%. Moreover, TCM could relieve clinical symptoms, curtail the length of hospital stay, improve laboratory indicators, and so on. In addition, we consulted the literature and obtained 149 components of Chinese medicinal herbs that could stably bind to antiviral targets or anti-inflammatory or immune-regulating targets by the prediction of molecular docking. It suggested that the mechanisms involved anti-virus, anti-inflammation, and regulation of immunity. Our study made a systematic review on the efficacy of TCM for COVID-19 and discussed the possible mechanisms, which provided clinical reference and theoretical basis for further research on the mechanism of TCM for COVID-19.

Diabetic peripheral neuropathy (DPN) is a chronic and prevalent metabolic disease that gravely endangers human health and seriously affects the quality of life of hyperglycemic patients. More seriously, it can lead to amputation and neuropathic pain, imposing a severe financial burden on patients and the healthcare system. Even with strict glycemic control or pancreas transplantation, peripheral nerve damage is difficult to reverse. Most current treatment options for DPN can only treat the symptoms but not the underlying mechanism. Patients with long-term diabetes mellitus (DM) develop axonal transport dysfunction, which could be an important factor in causing or exacerbating DPN. This review explores the underlying mechanisms that may be related to axonal transport impairment and cytoskeletal changes caused by DM, and the relevance of the latter with the occurrence and progression of DPN, including nerve fiber loss, diminished nerve conduction velocity, and impaired nerve regeneration, and also predicts possible therapeutic strategies. Understanding the mechanisms of diabetic neuronal injury is essential to prevent the deterioration of DPN and to develop new therapeutic strategies. Timely and effective improvement of axonal transport impairment is particularly critical for the treatment of peripheral neuropathies.

The severe acute respiratory syndrome coronavirus - 2 (SARS - CoV - 2) was reported to cause the Wuhan outbreak of the corona virus disease 2019(COVID-19). To date, the COVID-19 has infected more than 600 million people gloabally. As a growing number of patients recover from acute infections and are discharged from hospitals, the proportion of patients in the recovery period is gradually increasing. Many of these individuals have been reported to experience multiple symptoms during the convalescence, such as fatigue, dyspnea and pain which are designated as “long-COVID”, “post-COVID syndrome” or “recovery sequelae. We searched for recent articles published in PubMed on COVID-19 convalescence and found that the pathogenesis of COVID-19 convalescence is not yet well recognized. It may be associated with incomplete recovery of immune system, parenchymal organ damage (liver or lung), coagulation abnormalities, “second hit” caused by viral infection, and Phenomenon of Cell Senescence-Associated Secretory Phenotype (SASP). Some drugs and psychological factors of patients also play a non-negligible role in it. We also found that the effect of traditional Chinese medicine (TCM) is effective in the treatment of the COVID-19 recovery phase, which can not only relieve the corresponding symptoms, but also improve the indicators and pulmonary fibrosis. Bufei Huoxue Capsule, as the only drug explicitly mentioned for COVID-19 recovery period, can exert strong rehabilitative effects on physiological activity in patients recovering from COVID-19. In addition, in previous studies, traditional Chinese medicine has been confirmed to have the ability to resist cytokine storms, as well as improve coagulation and myocardial damage, which makes it have potential therapeutic advantages in targeting the hyperimmune response, coagulation abnormalities and myocardial damage existing in the recovery period. In conclusion, the clinical symptoms of patients convalescing from COVID-19 are complex, and its pathogenesis has not been elucidated. traditional Chinese medicine, as a traditional treatment, its specific action and mechanism need to be confirmed by more studies, so that it can play a better role.

The concise concept and good optimization performance are the advantages of particle swarm optimization algorithm (PSO), which makes it widely used in many fields. However, when solving complex multimodal optimization problems, it is easy to fall into early convergence. The rapid loss of population diversity is one of the important reasons why the PSO algorithm falls into early convergence. For this reason, this paper attempts to combine the PSO algorithm with wavelet theory and levy flight theory to propose a new hybrid algorithm called PSOLFWM. It applies the random wandering of levy flight and the mutation operation of wavelet theory to enhance the population diversity and seeking performance of the PSO to make it search more efficiently in the solution space to obtain higher quality solutions. A series of classical test functions and 19 optimization algorithms proposed in recent years are used to evaluate the optimization performance accuracy of the proposed method. The experimental results show that the proposed algorithm is superior to the comparison method in terms of convergence speed and convergence accuracy. The success of the high-dimensional function test and dynamic shift performance test further verifies that the proposed algorithm has higher search stability and anti-interference performance than the comparison algorithm. More importantly, both t-Test and Wilcoxon's rank sum test statistical analyses were carried out. The results show that there are significant differences between the proposed algorithm and other comparison algorithms at the significance level α = 0.05, and the performance is better than other comparison algorithms.

In terms of treatment, a particularly targeted drug is needed to combat the COVID-19 pandemic. Although there are currently no specific drugs for COVID-19, traditional Chinese medicine(TCM) is clearly effective. It is recommended that through data analysis and mining of TCM cases (expert experience) and population evidence (RCT and cohort studies), core prescriptions for various efficacy can be obtained. Starting from a multidimensional model of regulating immunity, improving inflammation, and protecting multiple organs, this paper constructs a multidimensional model of targeted drug discovery, integrating molecular, cellular, and animal efficacy evaluation. Through functional activity testing, biophysical detection of compound binding to target proteins, multidimensional pharmacodynamic evaluation systems of cells (Vero E6, Vero, Vero81, Huh7, and caca2) and animals (mice infected with the new coronavirus, rhesus macaques, and hamsters), the effectiveness of effective preparations was evaluated, and various efficacy effects including lung moisturizing, dehumidification and detoxification were obtained. Using modern technology, it is now possible to understand how the immune system is controlled, how inflammation is reduced, and how various organs are protected. Complete early drug characterization and finally obtain effective targeted TCM. This article provides a demonstration resource for the development of new drugs specifically for TCM.

IntroductionDiabetic kidney disease (DKD) is a severe and growing health problem, associated with a worse prognosis and higher overall mortality rates than non-diabetic renal disease. Chinese herbs possess promising clinical benefits in alleviating the progression of DKD due to their multi-target effect. This real-world retrospective cohort trial aimed to investigate the efficacy and safety of Naoxintong (NXT) capsules in the treatment of DKD. Our study is the first real-world study (RWS) of NXT in the treatment of DKD based on a large database, providing a basis for clinical application and promotion.MethodsThe data was collected from Tianjin Healthcare and Medical Big Data Platform. Patients with DKD were enrolled from January 1, 2011, to March 31, 2021. NXT administration was defined as the exposure. The primary outcome was the change in estimated glomerular filtration rate (eGFR). We employed the propensity score matching (PSM) method to deal with confounding factors.ResultsA total of 1,798 patients were enrolled after PSM, including 899 NXT users (exposed group) and 899 non-users (control group). The eGFR changes from baseline to the end of the study were significantly different in the exposed group compared to the control group (-1.46 ± 21.94 vs -5.82 ± 19.8 mL/(min·1.73m2), P< 0.01). Patients in the NXT group had a lower risk of composite renal outcome event (HR, 0.71; 95%CI, 0.55 to 0.92; P = 0.009) and deterioration of renal function (HR, 0.74; 95% CI, 0.56 to 0.99; P = 0.039).ConclusionNXT can significantly slow the decline of eGFR and reduce the risk of renal outcomes. However, large cohort studies and RCTs are needed to further confirm our results.

BackgroundColon cancer is common worldwide, with high morbidity and poor prognosis. Ferroptosis is a novel form of cell death driven by the accumulation of iron-dependent lipid peroxides, which differs from other programmed cell death mechanisms. Programmed cell death is a cancer hallmark, and ferroptosis is known to participate in various cancers, including colon cancer. Novel ferroptosis markers and targeted colon cancer therapies are urgently needed. To this end, we performed a preliminary exploration of ferroptosis-related genes in colon cancer to enable new treatment strategies.MethodsFerroptosis-related genes in colon cancer were obtained by data mining and screening for differentially expressed genes (DEGs) using bioinformatics analysis tools. We normalized the data across four independent datasets and a ferroptosis-specific database. Identified genes were validated by immunohistochemical analysis of pathological and healthy clinical samples.ResultsWe identified DEGs in colon cancer that are involved in ferroptosis. Among these, five core genes were found: ELAVL1, GPX2, EPAS1, SLC7A5, and HMGB1. Bioinformatics analyses revealed that the expression of all five genes, except for EPAS1, was higher in tumor tissues than in healthy tissues.ConclusionsThe preliminary exploration of the five core genes revealed that they are differentially expressed in colon cancer, playing an essential role in ferroptosis. This study provides a foundation for subsequent research on ferroptosis in colon cancer.

Abstract The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), first broke out in Wuhan, China, in 2019. SARS-CoV-2 develops many types of mutations (such as B.1.1.7), making diagnosis and treatment challenging. Although we now have a preliminary understanding of COVID-19, including pathological changes, clinical manifestations, and treatment measures, we also face new difficulties. The biggest problem is that most COVID-19 patients might face sequelae (e.g., fatigue, sleep disturbance, pulmonary fibrosis) during the recovery phase. We aimed to test six Chinese patent medicines to treat three major abnormal symptoms in COVID-19 patients during the recovery phase, including cardiopulmonary function, sleep disturbance, and digestive function. We launched the “three syndromes and six Chinese patent medicines” randomized, double-blind, placebo-controlled, multicenter clinical trial on April 10, 2020. The results showed that Jinshuibao tablets and Shengmaiyin oral liquid significantly improved the cardiopulmonary function of recovering COVID-19 patients. Shumian capsules, but not Xiaoyao capsules, significantly improved patients’ sleep disorders. This might be because the indication of Xiaoyao capsules is liver qi stagnation rather than psychological or emotional problems. Xiangsha Liujun pills and Ludangshen oral liquid significantly improved digestive function. Our research provides a guideline for treating COVID-19 sequelae in patients during the recovery period based on high-quality evidence.

BackgroundDiabetic retinopathy (DR), one of the commonest microvascular complications in diabetic patients, is featured by a series of fundus lesions. Conventional Western medicine therapies for DR are always with modest treatment outcome. This paper is to assess the ocular fundus signs, vision and safety of Chinese patent medicines (CPMs) as an add-on treatment for DR.Method7 electronic databases were searched to determine eligible trials. Randomized controlled trials (RCTs) of non-proliferative diabetic retinopathy (NPDR) in which the intervention group received CPMs combined with calcium dobesilate (CD), and the control group received only CD were included for analysis. Two reviewers extracted the data independently. Results expressing as mean differences (MD) and relative risks (RR) were analyzed with a fixed-effects or random-effects models.Results19 RCTs involved 1568 participants with 1622 eyes met our inclusion criteria. The results suggested that compared with CD alone, CPMs plus CD for NPDR was superior at reducing the microaneurysm volume (MD -3.37; 95% confidence interval [CI], -3.59 to -3.14), microaneurysm counts (MD -2.29; 95%CI -2.97 to -1.61), hemorrhage area (MD -0.79; 95%CI -0.83 to -0.75), and macular thickness (MD -59.72; 95%CI -63.24 to -56.20). Participants in CPMs plus CD group also achieved a better vision. No obvious adverse events occurred.ConclusionCPMs as an add-on therapy for NPDR have additional benefits and be generally safe. This meta‐analysis demonstrated that CPMs combined with CD could improve retinal microaneurysm, hemorrhage, macular thickness, visual acuity, fasting blood glucose (FBG), and glycosylated hemoglobin (HbAlc) compared with CD alone. Further studies are needed to provide more conclusive evidence.Systematic Review RegistrationPROSPERO https://www.crd.york.ac.uk/prospero/, identifier CRD42021257999.

ObjectiveThis study aimed at examining the long-term effects of non-pharmacological interventions on reducing the diabetes incidence among patients with prediabetes and chronic complications events among patients with hyperglycemia (pre-diabetes and diabetes) by performing a systematic review and meta-analysis of randomized controlled trials (RCTs).MethodsPubMed, MEDLINE, EMBASE, the Cochrane Library, and the Web of Science Core Collection were searched for studies published between January 1990 and November 2021, looking for RCTs to evaluate the effects of non-pharmacological interventions on preventing the incidence of diabetes and chronic complications in comparison with medical therapy, placebo, or usual diabetes care. Two independent reviews extracted relevant data and quality assessment. Any discrepancies were resolved by a third reviewer.ResultsIn total, 20 articles involved 16 RCTs (follow-up ranged from 2 to 30 years) were included. Pooled analysis of intervention studies demonstrated clearly that non-pharmacological interventions have a significant effect on reducing the diabetes events in patients with prediabetes (RR 0.62; 95% CI 0.54, 0.71). Pooled analysis of extended follow-up studies showed that non-pharmacological interventions could effectively reduce the diabetes incidence in patients with prediabetes (RR 0.78; 95% CI 0.63, 0.96). Meta-regression and subgroup analysis indicates that the diabetes incidence of the long-term group (duration > 3 years) was clearly reduced by 0.05% compared with the relatively short-term group (duration ≤ 3 years). The incidence of microvascular complications in patients with hyperglycemia was effectively lowered by non-pharmacological interventions (RR 0.60; 95% CI 0.43, 0.83).ConclusionNon-pharmacological interventions have a long-term effect on reducing the diabetes incidence among prediabetic patients and effectively preventing microvascular complications on hyperglycemia.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/.

BackgroundDiabetic renal fibrosis (DRF) is an irreversible renal pathological change in the end-stage of diabetic kidney disease (DKD), which plays a significant role in the development and deterioration of the disease. However, data for bibliometric analysis of renal fibrosis in DKD is currently missing. This study aimed to provide a comprehensive and visualized view of DRF research and lay the foundation for further studies.Materials and MethodsFirstly, the data was collected from the Web of Science Core Collection (WoSCC) database. Secondly, the Web of Science analytic tool was performed to analyze publication years, authors, countries/regions, organizations, and citation frequency. Finally, CiteSpace was employed to construct a visualization bibliometric network to reveal the emerging trends and hotspots of DRF.ResultsA total of 3,821 publications from 1985 to 2020 were included in this study. The number of publications has maintained a growth trend since 2003. Cooper is the most prolific author in this field, and the American Journal of Physiology-Renal Physiology ranking as first place compared with other journals. In terms of the number of publications, China contributed the most to DRF. Monash University is the organization that published the most papers. The top 5 clusters of keyword co-appearance are “chronic kidney disease”, “primary biliary cirrhosis”, “receptor”, “TGF-beta”, “renal tubulointerstitium”. The top 5 clusters of reference co-citation are “microRNAs”, “bone morphogenetic protein”, “hypertrophy”, “glomerulosclerosis”, “diabetic kidney disease”. The strongest citation burst of keyword is “diabetic kidney disease” and the strongest burst of cited reference is “Meng, 2016”.ConclusionsThe present study analyzed the research hotspots, Frontiers, and development trend of DRF and have important implications for future research.

Food is people’s primal want. A reasonable diet and healthy food not only provide nutrients for human growth but also contribute to disease prevention and treatment, while following an unhealthy diet can lead to an increased risk of many diseases, especially metabolic disorders, such as diabetes. Nature is enriched with different food sources, and it seems that purely natural products are more in line with the current concept of health, which enhance the formation of the notion that “Food/Diet Supplements from Natural Sources as a Medicine.” As a delicious fruit, the medicinal values such as anticancer, antibacterial, antioxidation, and antiglycating properties of lychee have been found. Lychee (Litchi in Chinese) is a subtropical fruit plant belonging to the family Sapindaceae. It has been widely cultivated in warm climates worldwide, particularly in China, for thousands of years. In recent years, various phytochemical components such as quercetin, procyanidin A2, and (2R)-naringenin-7-O-(3-O-αL-rhamnopyranosyl-β-D-glucopyranoside) have been identified in a lychee seed, which may lend a lychee seed as a relatively safe and inexpensive adjuvant treatment for diabetes and diabetic complications. In fact, accumulating evidence has shown that lychee seed, lychee seed extracts, and related compounds have promising antihyperglycemic activities, including improving insulin resistance, anti-inflammatory effect, lipid regulation, neuroprotection, antineurotoxic effect, and renoprotection effect. In this review, we summarized publications on antiglycemic effects and mechanisms of lychee seed, lychee seed extracts, and related compounds, which included their efficacies as a cure for diabetes and diabetic complications in cells, animals, and humans, attempting to obtain a robust evidence basis for the clinical application and value of lychee seed.

Background: Diabetic peripheral neuropathy (DPN) characterized by nerve damage is a common and disabling chronic microvascular complication in patients with type 2 diabetic mellitus (T2DM), affecting at least half of patients diagnosed with T2DM. Unfortunately, the current treatment for DPN is not ideal. Traditional Chinese medicine (TCM), with a unique theoretical system, has made outstanding contributions in the treatment of T2DM and related complications. Mudan granule, a Chinese patent medicine, has been previously validated that could ameliorate the symptoms, promote nerve tissue repair, increase nerve conduction velocity (NCV) in patients with DPN. However, the previous studies are of variable quality, which limits the clinical application of Mudan granule. Therefore, we designed a double-blind, randomized, placebo-controlled, parallel-arm, multi-center trial to estimate the safety and efficacy of Mudan granule in conjunction with methylcobalamin in individuals suffering from type 2 diabetic peripheral neuropathy.Methods: This work is conducted as a 14-center, double-blind, randomized, placebo-controlled, parallel-arm trial. In all, 402 subjects (aged 30–70 years) will be recruited and randomized in a 1:1 ratio to an intervention group (n = 201; Mudan granule + methylcobalamin) and a control group (n = 201; placebo + methylcobalamin). Treatment is administered in 24 weeks cycles without any treatment interruption between cycles. Michigan Diabetic Neuropathy Score (MDNS) as the primary outcome will be evaluated at baseline, 12 weeks during the intervention period, and after 24 weeks of the intervention. Adverse events and safety assessments will be also documented. The analysis of all data will be carried out based on a predefined statistical analysis plan.Discussion: The outcomes from this study will offer important evidence regarding the safety and efficacy that Mudan granule can be used as an alternative and complementary therapeutic intervention in patients with type 2 diabetic peripheral neuropathy.Clinical trial registration: Registered at https://clinicaltrials.gov/. Trial registration number: NCT04711980. Registered January 2021.

Background: Coronavirus Disease 2019 (COVID-19) is still a relevant global problem. Although some patients have recovered from COVID-19, the sequalae to the SARS-CoV-2 infection may include pulmonary fibrosis, which may contribute to considerable economic burden and health-care challenges. Convalescent Chinese Prescription (CCP) has been widely used during the COVID-19 recovery period for patients who were at high risk of pulmonary fibrosis and is recommended by the Diagnosis and Treatment Protocol for COVID-19 (Trial Version sixth, seventh). However, its underlying mechanism is still unclear.Methods: In this study, an integrated pharmacology approach was implemented, which involved evaluation of absorption, distribution, metabolism and excretion of CCP, data mining of the disease targets, protein-protein interaction (PPI) network construction, and analysis, enrichment analysis, and molecular docking simulation, to predict the bioactive components, potential targets, and molecular mechanism of CCP for pulmonary fibrosis associated with SARS-CoV-2 infection.Results: The active compound of CCP and the candidate targets, including pulmonary fibrosis targets, were obtained through database mining. The Drug-Disease network was constructed. Sixty-five key targets were identified by topological analysis. The findings of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation suggested that the VEGF, Toll-like 4 receptor, MAPK signaling pathway, and TGF-β1 signaling pathways may be involved in pulmonary fibrosis. In the molecular docking analyses, VEGF, TNF-α, IL-6, MMP9 exhibited good binding activity. Findings from our study indicated that CCP could inhibit the expression of VEGF, TNF-α, IL-6, MMP9, TGF-β1 via the VEGF, Toll-like 4 receptor, MAPK, and TGF-β1 signaling pathways.Conclusion: Potential mechanisms involved in CCP treatment for COVID-19 pulmonary fibrosis associated with SARS-CoV-2 infection involves multiple components and multiple target points as well as multiple pathways. These findings may offer a profile for further investigations of the anti-fibrotic mechanism of CCP.

Ecosystem modelling based on membrane computing is emerging as a powerful way to study the dynamics of (real) ecological populations. These models, providing distributed parallel devices, have shown a great potential to imitate the rich features observed in the behaviour of species and their interactions and key elements to understand and model ecosystems. Compared with differential equations, membrane computing models, also known as P systems, can model more complex biological phenomena due to their modularity and their ability to enclose the evolution of different environments and simulate, in parallel, different interrelated processes. In this paper, a comprehensive survey of membrane computing models for ecosystems is given, taking a giant panda ecosystem as an example to assess the model performance. This work aims at modelling a number of species using P systems with different membrane structure types to predict the number of individuals depending on parameters such as reproductive rate, mortality rate, and involving processes as rescue or release. Firstly, the computing models are introduced conceptually, describing the main elements constituting the syntax of these systems and explaining the semantics of the rules involved. Next, various modelled species (including endangered animals, plants, and bacteria) are summarized, and some computer tools are presented. Then, a discussion follows on the use of P systems for ecosystem modelling. Finally, a case study on giant pandas in Chengdu Base is analysed, concluding that the study in this field by using PDP systems can provide a valuable tool to deepen into the knowledge about the evolution of the population. This could ultimately help in the decision-making processes of the managers of the ecosystem to increase the species diversity and modify the adaptability. Besides, the impacts of natural disasters on the population dynamics of the species should also be considered. The analysis performed throughout the paper has taken into consideration this fact in order to increase the reliability of the prospects making use of the models designed.

The fabrication of optically active inorganic nanomaterials with chiral superstructures attracts attention because of their potential applications in chemical sensing and non-linear optics. Here, we present a facile way to prepare TiO2 nanofibres, in which the nanocrystals are helically arranged into a chiral superstructure. Notably, the chiral superstructure shows strong optical activity due to the difference of absorbing left- and right-handed circularly polarized light. This special optical activity resulted from electron transition from the valence band to the conduction band of TiO2 through a vicinal effect of helically arranged TiO2 nanocrystals.