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IntroductionGroundcover management plays a crucial role in improving water retention and soil nutrition in orchard systems, thereby preventing environmental constrains by non-point source pollution. However, effectiveness of groundcover management in citrus orchards developed on sloping farmland with eroded purple soil has not been studied in detail. In particular, information on the soil nutrient losses, e.g., nitrogen (N) and phosphorus (P), through interflow and its effects on growth and nutrition of citrus plants has not been reported.MethodsThe present study evaluated the effects of different cover crops, i.e., Lolium perenne L. (Lolium), Vicia villosa Roth (Vicia) and Orychophragmus violaceus (Ory), on nutrition and growth of citrus trees as well as water, soil and nutrient retention in an orchard developed in sloping farmland during two consecutive years.Results and discussionThe results show that the groundcover species Lolium and Vicia mediated nursing effects on nutrition and growth of citrus trees. These nursing effects included enhanced foliar levels of carbon(C), N and P as well as increased tree height, stem diameter, and crown width. Groundcover management generally reduced the annual surface runoff, interflow, soil loss, total N loss and total P loss. Among the cover crop species studied, Lolium and Vicia were overall more efficient than Ory in this context. Lolium reduced the average annual total loss of N and P by 42.53% and 49.23%, respectively, compared with clean tillage. The estimated annual reduction potentials of soil, N and P losses in Southwestern China were 16.3, 3.4 and 8.5 million tons yr-1, respectively. Obviously, Lolium and Vicia provide highly beneficial ground coverage on sloping farmland and, thus, can be used for future sustainable development of citrus orchards.

BackgroundThe bulbs of Allium sativum are widely used as food or seasoning (garlic), while they have also been utilized as a famous traditional medicine since ancient eras for the treatment of scabies, tuberculosis, pertussis, diarrhea and dysentery, etc. However, very few studies focus on their abundant aerial parts, which are normally discarded during the harvest season.MethodsThe hyperlipidemic mice model has been used to study the lipid-lowering effect of the aerial parts in this article. 180 mice were randomly divided into 18 groups, including blank control (BC), model (Mod), positive control (PC), and low-, medium-, and high-dose groups of the crude extract, petroleum ether, ethyl acetate, n-butanol, and residual water extracts (corresponding to CE, PEE, EAE, NBE, WE), with 10 mice in each group. The preventive effects of the extracts on hyperlipidemic mice lasted for four weeks. Ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) and gas chromatography tandem mass spectrometry (GC-MS/MS) were used to analyze the chemical components of NBE and PEE respectively.ResultsThe results of the mice experiment showed that n-butanol extract (NBE) and petroleum ether extract (PEE) from the aerial parts could significantly reduce the contents of total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT) and aspartate transaminase (AST) in serum of hyperlipidemic mice, and increase the contents of high density lipoprotein cholesterol (HDL-C). They could enhance the activity of superoxide dismutase (SOD) in liver and reduce the level of malondialdehyde (MDA). At the same time, they could improve steatosis and inflammation of liver cells. The results of phytochemical components analysis showed that NBE was rich in organic acids, flavonoids and nitrogen-containing constituents, while PEE contained organic sulfur compounds, aliphatic acids and derivatives, alkaloids, phytosterols, etc.ConclusionThese results support that the aerial parts of A. sativum are an interesting source of bioactive ingredients that may be useful in the prevention and treatment of hyperlipidemia.

BackgroundPolatuzumab vedotin, the first FDA-approved antibody-drug conjugate (ADC) targeting CD79b, is utilized in the treatment of previously untreated diffuse large B-cell lymphoma (DLBCL) or high-grade B-cell lymphoma (HGBL), as well as relapsed or refractory (R/R) DLBCL. Despite its approval, concerns persist regarding the long-term safety profile of polatuzumab vedotin. This study aims to evaluate the adverse events (AEs) associated with polatuzumab vedotin since its approval in 2019, utilizing data mining strategies applied to the FDA Adverse Event Reporting System (FAERS).MethodsSignal detection employed four methodologies, including reporting odds ratio (ROR), proportional reporting ratio (PRR), bayesian confidence propagation neural network (BCPNN), and multi-item gamma poisson shrinker (MGPS), to evaluate and quantify the signals of polatuzumab vedotin-associated AEs. Additionally, subgroup analyses based on patients age, gender, and fatal cases were conducted to investigate AEs occurrences in specific subpopulations.ResultsA total of 1,521 reports listing polatuzumab vedotin as a “principal suspect (PS)” drug were collected from the FAERS database. Through concurrent compliance with four algorithms, 19 significant Standardized MedDRA Query (SMQ) AEs and 92 significant Preferred Term (PT) AEs were detected. Subgroup analyses revealed a higher incidence of PTs in male patients compared to female patients, increased likelihood of polatuzumab vedotin-associated AEs in elder patients (>65 years), and AEs with a high risk of fatal cases include: blood lactate dehydrogenase increased, cytopenia, and hydronephrosis. The median time to AEs occurrence following polatuzumab vedotin initiation was 18.5 (5∼57.75) days, with 95% of AEs occurred within 162 days.ConclusionThis study identified various AEs associated with polatuzumab vedotin, offering critical insights for clinical monitoring and risk identification in patients receiving polatuzumab vedotin therapy.

Adipose tissue, an indispensable organ, fulfils the pivotal role of energy storage and metabolism and is instrumental in maintaining the dynamic equilibrium of energy and health of the organism. Adipocyte hypertrophy and adipocyte hyperplasia (adipogenesis) are the two primary mechanisms of fat deposition. Mature adipocytes are obtained by differentiating mesenchymal stem cells into preadipocytes and redifferentiation. However, the mechanisms orchestrating adipogenesis remain unclear. Autophagy, an alternative cell death pathway that sustains intracellular energy homeostasis through the degradation of cellular components, is implicated in regulating adipogenesis. Furthermore, adipose tissue functions as an endocrine organ, producing various cytokines, and certain inflammatory factors, in turn, modulate autophagy and adipogenesis. Additionally, autophagy influences intracellular redox homeostasis by regulating reactive oxygen species, which play pivotal roles in adipogenesis. There is a growing interest in exploring the involvement of autophagy, inflammation, and oxidative stress in adipogenesis. The present manuscript reviews the impact of autophagy, oxidative stress, and inflammation on the regulation of adipogenesis and, for the first time, discusses their interactions during adipogenesis. An integrated analysis of the role of autophagy, inflammation and oxidative stress will contribute to elucidating the mechanisms of adipogenesis and expediting the exploration of molecular targets for treating obesity-related metabolic disorders.

BackgroundCell phone addiction presents a widespread and severe physical and mental health concern, now recognized as a global public health issue. Among medical college students, the issue of poor sleep quality has become particularly prevalent. This study aimed to investigate the relationship between cell phone addiction and sleep disturbance in a population of medical college students, exploring the potential mediating role of psychological resilience and the moderating impact of gender.MethodsA random cluster sampling method was employed to survey 5,048 students from four medical colleges in Jiangsu Province, China, utilizing the Mobile Phone Addiction Index (MPAI), Connor-Davidson Resilience Scale (CD-RISC), and Pittsburgh Sleep Quality Index (PSQI) for data collection. Statistical analyses were conducted using SPSS 26.0 and the PROCESS macro version 4.1. To assess mediation, Model 4 of the PROCESS macro was utilized, while Model 15 was employed to investigate the moderating effect of gender.ResultsThe results revealed a significant positive correlation between cell phone addiction and sleep disturbance, with psychological resilience found to partially mediate this relationship. Moreover, gender was observed to significantly moderate the impact of cell phone addiction on sleep disturbance. Specifically, bootstrap analysis indicated a significant interaction between cell phone addiction and gender (Coeff. = -0.0215, P< 0.001), with a stronger relationship found in males (simple slope = 0.0616, t = 16.66, P< 0.001) compared to females (simple slope = 0.0401, t = 9.51, P< 0.001).ConclusionUltimately, psychological resilience was identified as a partial mediator between cell phone addiction and sleep disturbance in medical students from Jiangsu Province, with gender playing a significant moderating role in this association.

Background and aimsIn China, a significant number of undergraduates are experiencing poor sleep quality. This study was designed to investigate the prevalence of poor sleep quality and identify associated factors among undergraduates in Jiangsu Province, China.MethodsA total of 8,457 participants were collected in 2022 using whole-group convenience sampling. The factors studied included basic demographics, family and social support, personal lifestyles, physical and mental health, mobile phone addiction index (MPAI), and the Connor-Davidson resilience scale (CD-RISC). The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. Four models, including weighted multiple linear regression, binary logistic regression, weighted linear mixed model, and logistic regression with random effects, were applied to identify associated factors for sleep quality.ResultsOf the 8,457 participants analyzed, 26.64% (2,253) were classified into the poor sleep quality group with a PSQI score >7. No significant relationship was found between sleep quality and gender, native place, economic level of family, physical exercise, dormitory light, dormitory hygiene, and amativeness matter. Risk factors for sleep quality identified by the four models included lower CD-RISC, higher MPAI, fourth grade or above, smoking, drinking, greater academic pressure, greater employment pressure, roommate sleeping late, noisy dormitory, poorer physical health status, poorer mental health status, and psychological counseling.ConclusionsThese findings provide valuable insights for university administrators, enabling them to better understand the risk factors associated with poor sleep quality in undergraduates. By identifying these factors, administrators can provide targeted intervention measures and counseling programs to improve students' sleep quality.

IntroductionThis study aims to explore the important factors affecting the characteristics of different parts of pork.MethodsLipidomics and proteomics methods were used to analyze DAL (differential lipids) and DAPs (differential proteins) in five different parts (longissimus dorsi, belly meat, loin, forelegs and buttocks) of Duhua pig (Duroc × Guangdong small spotted pig), to identify potential pathways affecting meat quality, investigating fat deposition in pork and its lipid-protein interactions.ResultsThe results show that TG (triglyceride) is the lipid subclass with the highest proportion in muscle, and the pathway with the most significantly enriched lipids is GP. DAP clustered on several GO terms closely related to lipid metabolism and lipogenesis (lipid binding, lipid metabolism, lipid transport, and lipid regulation). In KEGG analysis, there are two main DAP aggregation pathways related to lipid metabolism, namely Fatty acid degradation and oxidative phosphorylation. In PPI analysis, we screened out 31 core proteins, among which NDUFA6, NDUFA9 and ACO2 are the most critical.DiscussionPC (phosphatidylcholine) is regulated by SNX5, THBS1, ANXA7, TPP1, CAVIN2, and VDAC2 in the phospholipid binding pathway. TG is regulated by AUH/HADH/ACADM/ACADL/HADHA in the lipid oxidation and lipid modification pathways. Potential biomarkers are rich in SFA, MUFA and PUFA respectively, the amounts of SFA, MUFA and PUFA in the lipid measurement results are consistent with the up- and down-regulation of potential biomarker lipids. This study clarified the differences in protein and lipid compositions in different parts of Duhua pigs and provided data support for revealing the interactions between pork lipids and proteins. These findings provide contributions to the study of intramuscular fat deposition in pork from a genetic and nutritional perspective.

BackgroundThe preoperative inflammatory condition significantly influences the prognosis of malignancies. We aimed to investigate the potential significance of preoperative inflammatory biomarkers in forecasting the long-term results of lung carcinoma after microwave ablation (MWA).MethodThis study included patients who received MWA treatment for lung carcinoma from Jan. 2012 to Dec. 2020. We collected demographic, clinical, laboratory, and outcome information. To assess the predictive capacity of inflammatory biomarkers, we utilized the area under the receiver operating characteristic curve (AUC-ROC) and assessed the predictive potential of inflammatory biomarkers in forecasting outcomes through both univariate and multivariate Cox proportional hazard analyses.ResultsA total of 354 individuals underwent MWA treatment, of which 265 cases were included in this study, whose average age was 69.1 ± 9.7 years. The AUC values for the Systemic Inflammatory Response Index (SIRI) to overall survival (OS) and disease-free survival (DFS) were 0.796 and 0.716, respectively. The Cox proportional hazards model demonstrated a significant independent association between a high SIRI and a decreased overall survival (hazard ratio [HR]=2.583, P

ObjectiveThis study aims to establish the precise prevalence of sleep disorders among university students in Jiangsu Province. Utilizing a representative sample of students, we measured their sleep quality based on the Pittsburgh Sleep Quality Index (PSQI). Our objective is to quantitatively assess the magnitude of sleep quality and identify key factors. By detailed analysis of these relationships, our study seeks to provide actionable insights for the development of targeted interventions to enhance sleep quality within this population.MethodsFrom October to November 2022, we conducted a cross-sectional web-based survey in Jiangsu Province, China. Using convenient cluster sampling in each college, a total of 8457 participants were selected. The PSQI was applied to assess sleep quality among university students. Data collected included sociodemographic details, scores from the Mobile Phone Dependence Index (MPAI) and psychological resilience measured by the Connor-Davidson Resilience Scale (CD-RISC).ResultsThe overall prevalence of poor sleep quality among the participants was 39.30%. Binary logistic regression analysis revealed that higher physical activity (OR = 0.921; 95% CI: 0.779-1.090), earlier roommate bedtimes (OR = 0.799; 95% CI: 0.718-0.888), quieter dormitories (OR = 0.732; 95% CI: 0.647-0.828) and higher psychological resilience (OR = 0.982; 95% CI, 0.979-0.984) were protective factors linked to lower risk of poor sleep quality. Conversely, being a female student (OR = 1.238; 95% CI: 1.109-1.382), being a senior (OR = 1.582; 95% CI: 1.344-1.863), single-child status (OR = 1.195; 95% CI: 1.077-1.326), regular smoking (OR = 1.833; 95% CI: 1.181-2.847), regular alcohol consumption (OR = 1.737; 95% CI: 1.065-2.833), high academic stress (OR = 1.326; 95% CI: 1.012-1.736), high employment stress (OR = 1.352; 95% CI: 1.156-1.582), dissatisfaction with dormitory hygiene (OR = 1.140; 95% CI: 1.028-1.265), poor self-rated physical health (OR = 1.969; 95% CI: 1.533-2.529), poor self-rated mental health (OR = 2.924; 95% CI: 2.309-3.702) and higher mobile phone dependency were risk factors associated with an increased likelihood of poor sleep quality.ConclusionThe sleep quality among university students should attract immediate attention. The development of public services and mental health education initiatives is crucial in enhancing the sleep health of this population.

The molecular mechanisms underlying the initiation of natural rubber synthesis and laticifer differentiation have not been fully elucidated. In this study, we conducted a time-series transcriptome analysis of five rubber tree tissues at four stages of seed germination. A total of 161,199 DEGs were identified between the two groups, including most 16,673 DEGs (A3 vs B3 and A3 vs C3) and lest 1,210 DEGs (C2 vs D2). We found that the maturation of the seed is accompanied by the formation of laticifer cells in cotyledon. Meanwhile, the analysis of hormones related genes expression may provide effective clues for us to promote the differentiation of laticifer cells in seeds by hormones in the future. In this study, hormone-related gene enrichment analyses revealed that IAA, GA, and CTK were activated in laticifer containing tissues. Similarly, GO and GEGG analysis showed that hormone pathways, especially the auxin pathway, are enriched. Gene expression clustering was analyzed using the short time-series expression miner (STEM), and the analysis revealed four distinct trends in the gene expression profiles. Moreover, we enriched transcription factor (TF) enrichment in cotyledon and embryonic axis tissues, and the MYB type exhibited the most significant difference. Furthermore, our findings revealed that genes related to rubber synthesis exhibited tissue-specific expression patterns during seed germination. Notably, key genes associated with rubber biosynthesis, specifically small rubber particle protein (SRPP) and cis-prenyltransferase (CPT), exhibited significant changes in expression in cotyledon and embryonic axis tissues, suggesting synchronous rubber synthesis with seed germination. Our staining results reveled that laticifer cells were exits in the cotyledon before seed imbibition stage. In conclusion, these results lay the foundation for exploring the molecular mechanisms underlying laticifer differentiation and rubber synthesis during seed germination, deepening our understanding of the initiation stages of rubber biosynthesis and laticifer differentiation.

ObjectiveTo analyze the effects of different family environmental backgrounds and mental health problems on academic buoyancy and to explore the potential mechanisms of their effects, using a sample of 2085 medical students in Jiangsu province.MethodsUsing the multiple linear regression to analyze the impact of mental health problems on academic buoyancy in different family environment contexts.Results(1) Higher family income and parental literacy implied higher levels of academic buoyancy in children; (2) mental health problems and academic buoyancy were negatively related, and generalized anxiety and uncertainty stress negatively predicted academic buoyancy levels; (3) uncertainty stress may have an indirect effect on academic buoyancy levels through a partially mediating effect of generalized anxiety.

BackgroundHuman gut microbiota play a crucial role in the immune response of the host to respiratory viral infection. However, evidence regarding the association between the gut microbiome, host immune responses, and disease severity in coronavirus disease 2019 (COVID-19) remains insufficient.MethodsTo better comprehend the interactions between the host and gut microbiota in COVID-19, we conducted 16S rRNA sequencing and characterized the gut microbiome compositions in stool samples from 40 COVID-19 patients and 33 non-pneumonia controls. We assessed several hematological parameters to determine the immune status.ResultsWe found that the gut microbial composition was significantly changed in COVID-19 patients, which was characterized by increased opportunistic pathogens and decreased commensal bacteria. The frequency of prevalent opportunistic pathogens Enterococcus and Lactobacillus increased, especially in severe patients; yet the abundance of butyrate-producing bacteria, Faecalibacterium, Roseburia, and Anaerostipes, decreased significantly, and Faecalibacterium prausnitzii might help discriminate severe patients from moderate patients and non-pneumonia people. Furthermore, we then obtained a correlation map between the clinical characteristics of COVID-19 and severity-related gut microbiota. We observed a notable correlation between the abundance of Enterococcus faecium and abnormal neutrophil or lymphocyte percentage in all COVID-19 patients. Faecalibacterium was positively correlated with lymphocyte counts, while negatively correlated with neutrophil percentage.ConclusionThese results suggested that the gut microbiome could have a potential function in regulating host immune responses and impacting the severity or consequences of diseases.

BackgroundGastroduodenal ulcers are associated with Helicobacter pylori infection and the use of nonsteroidal anti-inflammatory drugs (NSAIDs). However, the causal relationship between gastroduodenal ulcers and gut microbiota, especially specific gut microbiota, remains unclear.MethodsWe conducted an analysis of published data on the gut microbiota and Gastroduodenal ulcer using genome-wide association studies (GWAS). Two-sample Mendelian randomization (MR) analysis was performed to determine the causal relationship between gut microbiota and Gastroduodenal ulcer. Sensitivity, heterogeneity, and pleiotropy analyses were conducted to confirm the accuracy of the research findings.ResultsOur study showed that the abundance of Enterobacteriaceae, Butyricicoccus, Candidatus Soleaferrea, Lachnospiraceae NC2004 group, Peptococcus, and Enterobacteriales was negatively correlated with the risk of Gastroduodenal ulcer. Conversely, the abundance of Streptococcaceae, Lachnospiraceae UCG010, Marvinbryantia, Roseburia, Streptococcus, Mollicutes RF9, and NB1n was positively correlated with the risk of Gastroduodenal ulcer. MR analysis revealed causal relationships between 13 bacterial genera and Gastroduodenal ulcer.ConclusionThis study represents a groundbreaking endeavor by furnishing preliminary evidence regarding the potentially advantageous or detrimental causal link between the gut microbiota and Gastroduodenal ulcer, employing Mendelian Randomization (MR) analysis for the first time. These discoveries have the potential to yield fresh perspectives on the prevention and therapeutic approaches concerning Gastroduodenal ulcer, with a specific focus on the modulation of the gut microbiota.

Objective: While several drugs have been linked to acute pancreatitis (AP), the AP-related risk of most drugs remains unclear. This study investigated the risk factors for drug-induced AP by analyzing a large dataset from the FDA Adverse Event Reporting System (FAERS).Methods: The reporting odds ratios (ROR) were used to assess the reports of drug-induced AP from the first quarter of 2004 to the second quarter of 2022. Single-factor, LASSO, and multi-factor regression analysis were performed to explore drug-related AP-related risk factors. Bonferroni correction was applied for the multiple comparisons performed.Results: A total of 264 drugs associated with AP, including antineoplastic drugs (35/264), antidiabetic drugs (28/264), antibacterial drugs (24/264), immunomodulatory drugs (11/264), antipsychotic drugs (6/264), and other drugs (160/264) were retrieved. Multi-factor analysis showed that males, age 41–54 years old, and 36 drugs, including Tigecycline, were risk factors for drug-related AP. The median time to drug-related AP onset was 31 days (interquartile range [IQR] 7–102 days) and about 75% of adverse events occurred within 100 days.Conclusion: These findings may help clinicians to identify drug-related AP at the early stage and can be used to inform future studies of drug-related AP pathogenesis.

Water is a promising working fluid for high-temperature heat pumps (HTHPs) with the advantages of being cheap, safe, stable, environmentally friendly, non-toxic, and non-flammable. HTHPs using water as a refrigerant not only can reduce greenhouse gas emissions in the industrial sectors by recovering waste heat but also have no adverse effect on the environment if the refrigerant leaks. This article evaluates the safety, energy, and exergy performance of six designed HTHP configurations with water refrigerant by analyzing the discharge superheat, power consumption, heating capacity, COP, and exergy efficiency—at different condensation and evaporation temperatures. The results indicated that water injection and intercooling can effectively decrease the discharge superheat to ensure safety performance. Among these systems, two-stage cycles can supply higher output temperatures and have better system performance compared to single-stage cycles at high-temperature lifts and large compression ratio conditions. The two-stage system with a flash tank (TS-FT) has the biggest heating capacity, the best COP, and the best exergy efficiency. With an evaporation temperature of 80°C and condensation temperature of 140°C, the COP is 4.14 and the exergy efficiency is 70.9% for the TS-FT. Compared with the single-stage ordinary system (SS-OS), the COP of the TS-FT has an increment of 36.6%. The exergy efficiency of the TS-FT is 19.8% higher than that of the SS-OS. Considering the aforementioned theoretical analysis, the TS-FT with the best safety, energy, and exergy performance is the optimal HTHP system with water refrigerant for high-temperature applications.

AimRecent observational and small-sample case-control studies have shown a relationship between gut microbiota composition and prostatic cancer (PCa). Nevertheless, the causal association between gut microbiota and PCa is still unclear. Herein, we used the Mendelian randomization (MR) method to explore the potential causal relationship between gut microbiota and PCa.MethodsIn this two-sample MR study, data were extracted from the summary statistics of gut microbiota from the largest available genome-wide association study meta-analysis conducted by the MiBioGen consortium (n = 14,306) and the Dutch Microbiome Project (n = 8,208). Summary statistics for PCa were obtained from the FinnGen consortium release data (n = 95,213). Inverse variance weighted (IVW), MR-Egger, strength test (F), and MR-PRESSO were used to examine the potential causal association between gut microbiota and PCa. Cochran's Q statistics were used to quantify the heterogeneity of instrumental variables.ResultsIVW estimates suggested that the relative abundance of Akkermansia muciniphila (odds ratio [OR] = 0.7926, 95% confidence interval [CI]: 0.6655–0.9440) and Bacteroides salyersiae (OR = 0.9023, 95% CI: 0.8262–0.9853) were negatively associated with the odds of PCa, while that of Eubacterium biforme (OR = 1.1629, 95% CI: 1.0110–1.3376) was positively associated with the odds of PCa. In addition, we explored these relationships among patients without other cancers and similarly found that the relative abundance of Akkermansia muciniphila, Bacteroides salyersiae, and Eubacterium biforme were linked to PCa (all P < 0.05).ConclusionGut microbiota potentially influenced the occurrence of PCa. Our findings may provide some new ideas for researching the methods of PCa prevention. In addition, further studies are needed to explore the causal association and specific underlying mechanisms between gut microbiota and PCa.

Fibrosis could happen in every organ, leading to organic malfunction and even organ failure, which poses a serious threat to global health. Early treatment of fibrosis has been reported to be the turning point, therefore, exploring potential correlates in the pathogenesis of fibrosis and how to reverse fibrosis has become a pressing issue. As a mechanism-sensitive cationic calcium channel, Piezo1 turns on in response to changes in the lipid bilayer of the plasma membrane. Piezo1 exerts multiple biological roles, including inhibition of inflammation, cytoskeletal stabilization, epithelial-mesenchymal transition, stromal stiffness, and immune cell mechanotransduction, interestingly enough. These processes are closely associated with the development of fibrotic diseases. Recent studies have shown that deletion or knockdown of Piezo1 attenuates the onset of fibrosis. Therefore, in this paper we comprehensively describe the biology of this gene, focusing on its potential relevance in pulmonary fibrosis, renal fibrosis, pancreatic fibrosis, and cardiac fibrosis diseases, except for the role of drugs (agonists), increased intracellular calcium and mechanical stress using this gene in alleviating fibrosis.

The current estrus detection method is generally time-consuming and has low accuracy. As such, a deeper understanding of the physiological processes during the estrous cycle accelerates the development of estrus detection efficiency and accuracy. In this study, the label-free acquisition mass spectrometry was used to explore salivary proteome profiles during the estrous cycle (day −3, day 0, day 3, and day 8) in pigs, and the parallel reaction monitoring (PRM) was applied to verify the relative profiles of protein expression. A total of 1,155 proteins were identified in the label-free analysis, of which 115 were identified as differentially expressed proteins (DEPs) among different groups (p ≤ 0.05). Functional annotation revealed that the DEPs were clustered in calcium ion binding, actin cytoskeleton, and lyase activity. PRM verified the relative profiles of protein expression, in which PHB domain-containing protein, growth factor receptor-bound protein 2, elongation factor Tu, carboxypeptidase D, carbonic anhydrase, and trefoil factor 3 were confirmed to be consistent in both label-free and PRM approaches. Comparative proteomic assays on saliva would increase our knowledge of the estrous cycle in sows and provide potential methods for estrus detection.

ObjectiveTo understand the satisfaction and the current status of the training of scientific research ability of Master of Public Health students in universities, analyze the influencing factors and explore their solutions, in order to provide reference for improving the scientific research ability of Master of Public Health students.MethodsA questionnaire was used to survey Master of Public Health students in nine universities. The data were analyzed by descriptive statistics and multifactor logistic regression.ResultsThe overall satisfaction self-rating score for research capacity of Master of Public Health students was (3.29 ± 0.87), with the highest score for mentor exchange (3.78 ± 0.81) and the lowest score for subsidized treatment (1.86 ± 0.96). Satisfaction with the practice unit and school dimensions was significantly lower than the mentor dimension. The length of practice in the practice unit, subsidy treatment, importance of research capacity development, development tendency, and current status of research were influential factors contributing to the difference in satisfaction with research capacity development of Master of Public Health students (P < 0.05).ConclusionThe overall scientific training quality of Master of Public Health students is high, but there are still many aspects that need to be solved. Colleges and universities should join the funding system adapted to the practice process of Master of Public Health students and guarantee the construction of the system of student subsidy treatment. Secondly, they should strengthen the construction of public health supervisory team and improve the frequency and quality of scientific research exchanges between teachers and students. In addition, colleges and universities should improve the existing research incentives and policies, and adopt multiple forms and types of research incentives. Finally, colleges and universities should improve the research training system and the construction of research resources for Master of Public Health.

BackgroundFrailty is a dynamic and complex geriatric condition characterized by multi-domain declines in physiological, gait and cognitive function. This study examined whether digital health technology can facilitate frailty identification and improve the efficiency of diagnosis by optimizing analytical and machine learning approaches using select factors from comprehensive geriatric assessment and gait characteristics.MethodsAs part of an ongoing study on observational study of Aging, we prospectively recruited 214 individuals living independently in the community of Southern China. Clinical information and fragility were assessed using comprehensive geriatric assessment (CGA). Digital tool box consisted of wearable sensor-enabled 6-min walk test (6MWT) and five machine learning algorithms allowing feature selections and frailty classifications.ResultsIt was found that a model combining CGA and gait parameters was successful in predicting frailty. The combination of these features in a machine learning model performed better than using either CGA or gait parameters alone, with an area under the curve of 0.93. The performance of the machine learning models improved by 4.3–11.4% after further feature selection using a smaller subset of 16 variables. SHapley Additive exPlanation (SHAP) dependence plot analysis revealed that the most important features for predicting frailty were large-step walking speed, average step size, age, total step walking distance, and Mini Mental State Examination score.ConclusionThis study provides evidence that digital health technology can be used for predicting frailty and identifying the key gait parameters in targeted health assessments.

ObjectiveTo analyze the time series in the correlation between search terms related to tuberculosis (TB) and actual incidence data in China. To screen out the “leading” terms and construct a timely and efficient TB prediction model that can predict the next wave of TB epidemic trend in advance.MethodsMonthly incidence data of tuberculosis in Jiangsu Province, China, were collected from January 2011 to December 2020. A scoping approach was used to identify TB search terms around common TB terms, prevention, symptoms and treatment. Search terms for Jiangsu Province, China, from January 2011 to December 2020 were collected from the Baidu index database.1 Correlation coefficients between search terms and actual incidence were calculated using Python 3.6 software. The multiple linear regression model was constructed using SPSS 26.0 software, which also calculated the goodness of fit and prediction error of the model predictions.ResultsA total of 16 keywords with correlation coefficients greater than 0.6 were screened, of which 11 were the leading terms. The R2 of the prediction model was 0.67 and the MAPE was 10.23%.ConclusionThe TB prediction model based on Baidu Index data was able to predict the next wave of TB epidemic trends and intensity 2 months in advance. This forecasting model is currently only available for Jiangsu Province.

Chimonanthus grammatus is used as Hakka traditional herb to treat cold, flu, etc. So far, the phytochemistry and antimicrobial compounds have not been well investigated. In this study, the orbitrap-ion trap MS was used to characterize its metabolites, combined with a computer-assisted structure elucidation method, and the antimicrobial activities were assessed by a broth dilution method against 21 human pathogens, as well as the bioassay-guided purification work to clarify its main antimicrobial compounds. A total of 83 compounds were identified with their fragmentation patterns, including terpenoids, coumarins, flavonoids, organic acids, alkaloids, and others. The plant extracts can strongly inhibit the growth of three Gram-positive and four Gram-negative bacteria, and nine active compounds were bioassay-guided isolated, including homalomenol C, jasmonic acid, isofraxidin, quercitrin, stigmasta-7,22-diene-3β,5α,6α-triol, quercetin, 4-hydroxy-1,10-secocadin-5-ene-1,10-dione, kaempferol, and E-4-(4,8-dimethylnona-3,7-dienyl)furan-2(5H)-one. Among them, isofraxidin, kaempferol, and quercitrin showed significant activity against planktonic Staphylococcus aureus (IC50 = 13.51, 18.08 and 15.86 µg/ml). Moreover, their antibiofilm activities of S. aureus (BIC50 = 15.43, 17.31, 18.86 µg/ml; BEC50 = 45.86, ≥62.50, and 57.62 µg/ml) are higher than ciprofloxacin. The results demonstrated that the isolated antimicrobial compounds played the key role of this herb in combating microbes and provided benefits for its development and quality control, and the computer-assisted structure elucidation method was a powerful tool for chemical analysis, especially for distinguishing isomers with similar structures, which can be used for other complex samples.

IntroductionDeep-learn methods based on convolutional neural networks (CNNs) have demonstrated impressive performance in depression analysis. Nevertheless, some critical challenges need to be resolved in these methods: (1) It is still difficult for CNNs to learn long-range inductive biases in the low-level feature extraction of different facial regions because of the spatial locality. (2) It is difficult for a model with only a single attention head to concentrate on various parts of the face simultaneously, leading to less sensitivity to other important facial regions associated with depression. In the case of facial depression recognition, many of the clues come from a few areas of the face simultaneously, e.g., the mouth and eyes.MethodsTo address these issues, we present an end-to-end integrated framework called Hybrid Multi-head Cross Attention Network (HMHN), which includes two stages. The first stage consists of the Grid-Wise Attention block (GWA) and Deep Feature Fusion block (DFF) for the low-level visual depression feature learning. In the second stage, we obtain the global representation by encoding high-order interactions among local features with Multi-head Cross Attention block (MAB) and Attention Fusion block (AFB).ResultsWe experimented on AVEC2013 and AVEC2014 depression datasets. The results of AVEC 2013 (RMSE = 7.38, MAE = 6.05) and AVEC 2014 (RMSE = 7.60, MAE = 6.01) demonstrated the efficacy of our method and outperformed most of the state-of-the-art video-based depression recognition approaches.DiscussionWe proposed a deep learning hybrid model for depression recognition by capturing the higher-order interactions between the depression features of multiple facial regions, which can effectively reduce the error in depression recognition and gives great potential for clinical experiments.

Background: Lung adenocarcinoma (LUAD) is the most common variant of non–small cell lung cancer (NSCLC) across the world. Recently, the rapid development of immunotherapy has brought a new dawn for LUAD patients. Closely related to the tumor immune microenvironment and immune cell functions, more and more new immune checkpoints have been discovered, and various cancer treatment studies targeting these novel immune checkpoints are currently in full swing. However, studies on the phenotype and clinical significance of novel immune checkpoints in LUAD are still limited, and only a minority of patients with LUAD can benefit from immunotherapy.Methods: The LUAD datasets were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, and the immune checkpoints score of each sample were calculated based on the expression of the 82 immune checkpoints-related genes (ICGs). The weighted gene co-expression network analysis (WGCNA) was used to obtain the gene modules closely related to the score and two different LUAD clusters were identified based on these module genes by the Non-negative Matrix Factorization (NMF) Algorithm. The differentially expressed genes between the two clusters were further used to construct a predictive signature for prognosis, immune features, and the response to immunotherapy for LUAD patients through a series of regression analyses.Results: A new immune checkpoints-related signature was finally established according to the expression of 7 genes (FCER2, CD200R1, RHOV, TNNT2, WT1, AHSG, and KRTAP5-8). This signature can stratify patients into high-risk and low-risk groups with different survival outcomes and sensitivity to immunotherapy, and the signature has been well validated in different clinical subgroups and validation cohorts.Conclusion: We constructed a novel immune checkpoints-related LUAD risk assessment system, which has a good predictive ability and significance for guiding immunotherapy. We believe that these findings will not only aid in the clinical management of LUAD patients but also provide some insights into screening appropriate patients for immunotherapy.

ObjectiveTo systematically review the differences between radiofrequency ablation and partial nephrectomy in patients with early-stage renal cell carcinoma, and to provide evidence-based medical evidence for the choice of surgery for patients with early-stage renal cell carcinoma.MethodsAccording to the search strategy recommended by the Cochrane Collaboration, Chinese databases such as CNKI, VIP Chinese Science and Technology Periodicals Database (VIP), and Wanfang Full-text Database were searched with Chinese search terms. And PubMed and MEDLINE as databases for English literature retrieval. Retrieve the relevant literature on renal cell carcinoma surgical methods published before May 2022, and further screen radiofrequency ablation and partial nephrectomy in patients with renal cell carcinoma The relevant literature on the application is analyzed. RevMan5.3 software was used for heterogeneity test and combined statistical analysis, sensitivity analysis, and subgroup analysis. Analysis, and draw forest plot, using Stata software Begger quantitative assessment of publication bias.ResultsA total of 11 articles were involved, including 2958 patients. According to the Jadad scale, 2 articles were of low quality, and the remaining 9 articles were of high quality. Results of this study demonstrates the advantages of radiofrequency ablation in early-stage renal cell carcinoma. The results of this meta-analysis showed that compared with partial nephrectomy, there was significant difference in the 5-year overall survival rate between radiofrequency ablation and partial nephrectomy and there was a statistically significant difference between the two surgical methods in the 5-year relapse free survival rate of early renal cell carcinoma.Conclusion1. Compared with partial nephrectomy, the 5-year relapse-free survival rate, the 5-year cancer specific survival rate and the overall 5-year survival rate were higher in the radiofrequency ablation group. 2. Compared with partial nephrectomy, there was no significant difference in the postoperative local tumor recurrence rate of radiofrequency ablation. 3. Compared with partial resection, radiofrequency ablation is more beneficial to patients with renal cell carcinoma.

Introduction: Tyrosine kinase inhibitor drugs (TKIs) are highly effective cancer drugs, yet many TKIs are associated with various forms of cardiotoxicity. The mechanisms underlying these drug-induced adverse events remain poorly understood. We studied mechanisms of TKI-induced cardiotoxicity by integrating several complementary approaches, including comprehensive transcriptomics, mechanistic mathematical modeling, and physiological assays in cultured human cardiac myocytes.Methods: Induced pluripotent stem cells (iPSCs) from two healthy donors were differentiated into cardiac myocytes (iPSC-CMs), and cells were treated with a panel of 26 FDA-approved TKIs. Drug-induced changes in gene expression were quantified using mRNA-seq, changes in gene expression were integrated into a mechanistic mathematical model of electrophysiology and contraction, and simulation results were used to predict physiological outcomes.Results: Experimental recordings of action potentials, intracellular calcium, and contraction in iPSC-CMs demonstrated that modeling predictions were accurate, with 81% of modeling predictions across the two cell lines confirmed experimentally. Surprisingly, simulations of how TKI-treated iPSC-CMs would respond to an additional arrhythmogenic insult, namely, hypokalemia, predicted dramatic differences between cell lines in how drugs affected arrhythmia susceptibility, and these predictions were confirmed experimentally. Computational analysis revealed that differences between cell lines in the upregulation or downregulation of particular ion channels could explain how TKI-treated cells responded differently to hypokalemia.Discussion: Overall, the study identifies transcriptional mechanisms underlying cardiotoxicity caused by TKIs, and illustrates a novel approach for integrating transcriptomics with mechanistic mathematical models to generate experimentally testable, individual-specific predictions of adverse event risk.

Osteoarthritis (OA) is one of the common degenerative joint diseases in clinic. It mainly damages articular cartilage, causing pain, swelling and stiffness around joints, and is the main cause of disability of the elderly. Due to the unclear pathogenesis of osteoarthritis and the poor self-healing ability of articular cartilage, the treatment options for this disease are limited. At present, NSAIDs, Glucocorticoid and Duloxetine are the most commonly used treatment choice for osteoarthritis. Although it is somewhat effective, the adverse reactions are frequent and serious. The development of safer and more effective anti-osteoarthritis drugs is essential and urgent. This review summarizes recent advances in the pharmacological treatment of OA, focusing on small molecule inhibitors targeting cartilage remodeling in osteoarthritis as well as the research idea of reducing adverse effects by optimizing the dosage form of traditional drugs for the treatment of osteoarthritis. It should provide a reference for exploration of new potential treatment options.

ObjectiveTo evaluate the impact of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) on abdominal CT radiomic features acquired in portal venous phase in liver tumor patients.MethodsSixty patients with liver tumors who underwent contrast-enhanced abdominal CT were retrospectively enrolled. Six groups including filtered back projection (FBP), ASIR-V (30%, 70%) and DLIR at low (DLIR-L), medium (DLIR-M and high (DLIR-H), were reconstructed using portal venous phase data. CT-based radiomic features (first-order, texture and wavelet features) were extracted from 2D and 3D liver tumors, peritumor and liver parenchyma. All features were analyzed for comparison. P < 0.05 indicated statistically different. The consistency of 3D lesion feature extraction was assessed by calculating intraclass correlation coefficient (ICC).ResultsDifferent reconstruction algorithms influenced most radiomic features. The percentages of first-order, texture and wavelet features without statistical difference among 2D and 3D lesions, peritumor and liver parenchyma for all six groups were 27.78% (5/18), 5.33% (4/75) and 5.56% (1/18), respectively (all p > 0.05), and they decreased while the level of reconstruction strengthened for both ASIR-V and DLIR. Compared with FBP, the features of ASIR-V30% and 70% without statistical difference decreased from 71.31% to 23.95%, and DLIR-L, DLIR-M, and DLIR-H decreased from 31.65% to 27.11% and 23.73%. Among texture features, unaffected features of peritumor were larger than those of lesions and liver parenchyma, and unaffected 3D lesions features were larger than those of 2D lesions. The consistency of 3D lesion first-order features was excellent, with intra- and inter-observer ICCs ranging from 0.891 to 0.999 and 0.880 to 0.998.ConclusionsBoth ASIR-V and DLIR algorithms with different strengths influenced the radiomic features of abdominal CT images in portal venous phase, and the influences aggravated as reconstruction strength increased.

IntroductionAs a biomarker of depression, speech signal has attracted the interest of many researchers due to its characteristics of easy collection and non-invasive. However, subjects’ speech variation under different scenes and emotional stimuli, the insufficient amount of depression speech data for deep learning, and the variable length of speech frame-level features have an impact on the recognition performance.MethodsThe above problems, this study proposes a multi-task ensemble learning method based on speaker embeddings for depression classification. First, we extract the Mel Frequency Cepstral Coefficients (MFCC), the Perceptual Linear Predictive Coefficients (PLP), and the Filter Bank (FBANK) from the out-domain dataset (CN-Celeb) and train the Resnet x-vector extractor, Time delay neural network (TDNN) x-vector extractor, and i-vector extractor. Then, we extract the corresponding speaker embeddings of fixed length from the depression speech database of the Gansu Provincial Key Laboratory of Wearable Computing. Support Vector Machine (SVM) and Random Forest (RF) are used to obtain the classification results of speaker embeddings in nine speech tasks. To make full use of the information of speech tasks with different scenes and emotions, we aggregate the classification results of nine tasks into new features and then obtain the final classification results by using Multilayer Perceptron (MLP). In order to take advantage of the complementary effects of different features, Resnet x-vectors based on different acoustic features are fused in the ensemble learning method.ResultsExperimental results demonstrate that (1) MFCC-based Resnet x-vectors perform best among the nine speaker embeddings for depression detection; (2) interview speech is better than picture descriptions speech, and neutral stimulus is the best among the three emotional valences in the depression recognition task; (3) our multi-task ensemble learning method with MFCC-based Resnet x-vectors can effectively identify depressed patients; (4) in all cases, the combination of MFCC-based Resnet x-vectors and PLP-based Resnet x-vectors in our ensemble learning method achieves the best results, outperforming other literature studies using the depression speech database.DiscussionOur multi-task ensemble learning method with MFCC-based Resnet x-vectors can fuse the depression related information of different stimuli effectively, which provides a new approach for depression detection. The limitation of this method is that speaker embeddings extractors were pre-trained on the out-domain dataset. We will consider using the augmented in-domain dataset for pre-training to improve the depression recognition performance further.

Low-grade myofibroblastic sarcoma is a rare malignant tumor that arises from mesenchymal tissue and affects the head (particularly the tongue and oral cavity) and neck. It is characterized by local recurrence, with metastases being uncommon. We present a 72-year-old man who initially complained of a painless and progressive mass in the right inguinal region and came for consultation, and a malignant tumor was suspected based on the clinical and pelvic MRI manifestations. The 18F-FDG PET/CT revealed that the multiple lesions were located in the mediastinum, retroperitoneum, pelvis, and inguinal lymph nodes; hence, lymphoma was considered to be a combination of the symptoms. However, the histology of the ultrasound-guided puncture indicated low-grade myofibroblastic sarcoma. The patient was next administered chemotherapy, but the lesions did not undergo remission.

Ipomoeapes-caprae (L.) (IPC) is a common species in tropical and subtropical coastal areas and one of the world’s most widely distributed plants. It has attracted researchers for its outstanding biological, ecological and medicinal values. It has been reported that the genetic diversity of IPCs located on different continents is very low because of their frequent gene flow. During the long journey of evolution, every aspect of the plant morphologies has evolved to the best adaptivity to the environment, seeking their survival and progeny expansion. However, the fundamental genetic characteristics of IPC and how their seed adapted to the success of population expansion remain unknown. In this study, the fundamental genetic characteristics, including the genome size and the chromosome number of IPC, were investigated. The results showed that IPC’s genome size is approximately 0.98-1.08 GB, and the chromosome number is 2n=30, providing the basic information for further genome analysis. In order to decipher the long-distance dispersal secret of this species, the fruit and seed developments, seed morphology, and seed germination were extensively investigated and described. The results showed an exquisite adaptive mechanism of IPC seeds to fulfil the population expansion via ocean currents. The large cavity inside the seeds and the dense tomenta on the surface provide the buoyancy force for the seeds to float on the seawater. The hard seed coats significantly obstructed the water absorption, thus preventing the seed from germination during the dispersal. Meanwhile, the fully developed embryos of IPC also have physiological dormancy. The physical and physiological characteristics of IPC seeds provide insight into the mechanism of their long-distance dispersal across the oceans. Moreover, based on morphological observation and semi-section microscopy, the development pattern of IPC glander trichomes was described, and their physiological functions were also discussed.

Gut microbiota not only helps the hosts to perform many key physiological functions such as food digestion, energy harvesting and immune regulation, but also influences host ecology and facilitates adaptation of the host to extreme environments. Plateau zokors epitomize successful physiological adaptation to their living environment in the face of the harsh environment characterized by low temperature, low pressure and hypoxia in the Tibetan plateau region and high concentrations of CO2 in their burrows. Therefore, here we used a metagenomic sequencing approach to explore how gut microbiota contributed to the adaptive evolution of the plateau zokor on the Qinghai-Tibet Plateau. Our metagenomic results show that the gut microbiota of plateau zokors on the Tibetan plateau is not only enriched in a large number of species related to energy metabolism and production of short-chain fatty acids (SCFAs), but also significantly enriched the KO terms that involve carbohydrate uptake pathways, which well address energy uptake in plateau zokors while also reducing inflammatory responses due to low pressure, hypoxia and high CO2 concentrations. There was also a significant enrichment of tripeptidyl-peptidase II (TPPII) associated with antigen processing, apoptosis, DNA damage repair and cell division, which may facilitate the immune response and tissue damage repair in plateau zokors under extreme conditions. These results suggest that these gut microbiota and their metabolites together contribute to the physiological adaptation of plateau zokors, providing new insights into the contribution of the microbiome to the evolution of mammalian adaptation.

BackgroundThe resources available to fight an epidemic are typically limited, and the time and effort required to control it grow as the start date of the containment effort are delayed. When the population is afflicted in various regions, scheduling a fair and acceptable distribution of limited available resources stored in multiple emergency resource centers to each epidemic area has become a serious problem that requires immediate resolution.MethodsThis study presents an emergency medical logistics model for rapid response to public health emergencies. The proposed methodology consists of two recursive mechanisms: (1) time-varying forecasting of medical resources and (2) emergency medical resource allocation. Considering the epidemic's features and the heterogeneity of existing medical treatment capabilities in different epidemic areas, we provide the modified susceptible-exposed-infected-recovered (SEIR) model to predict the early stage emergency medical resource demand for epidemics. Then we define emergency indicators for each epidemic area based on this. By maximizing the weighted demand satisfaction rate and minimizing the total vehicle travel distance, we develop a bi-objective optimization model to determine the optimal medical resource allocation plan.ResultsDecision-makers should assign appropriate values to parameters at various stages of the emergency process based on the actual situation, to ensure that the results obtained are feasible and effective. It is necessary to set up an appropriate number of supply points in the epidemic emergency medical logistics supply to effectively reduce rescue costs and improve the level of emergency services.ConclusionsOverall, this work provides managerial insights to improve decisions made on medical distribution as per demand forecasting for quick response to public health emergencies.

Direct mass spectrometry (MS) analysis of human tissue at the molecular level could gain insight into biomarker discovery and disease diagnosis. Detecting metabolite profiles of tissue sample play an important role in understanding the pathological properties of disease development. Because the complex matrices in tissue samples, complicated and time-consuming sample preparation processes are usually required by conventional biological and clinical MS methods. Direct MS with ambient ionization technique is a new analytical strategy for direct sample analysis with little sample preparation, and has been proven to be a simple, rapid, and effective analytical tools for direct analysis of biological tissues. In this work, we applied a simple, low-cost, disposable wooden tip (WT) for loading tiny thyroid tissue, and then loading organic solvents to extract biomarkers under electrospray ionization (ESI) condition. Under such WT-ESI, the extract of thyroid was directly sprayed out from wooden tip to MS inlet. In this work, thyroid tissue from normal and cancer parts were analyzed by the established WT-ESI-MS, showing lipids were mainly detectable compounds in thyroid tissue. The MS data of lipids obtained from thyroid tissues were further analyzed with MS/MS experiment and multivariate variable analysis, and the biomarkers of thyroid cancer were also investigated.

Sea buckthorn berries are important ingredients in Chinese medicine and food processing; however, their high moisture content can reduce their shelf life. Effective drying is crucial for extending their shelf life. In the present study, we investigated the effects of hot-air drying (HAD), infrared drying (IRD), infrared-assisted hot-air drying (IR-HAD), pulsed-vacuum drying (PVD), and vacuum freeze-drying (VFD) on the drying kinetics, microstructure, physicochemical properties (color, non-enzyme browning index, and rehydration ratio), and total phenol, total flavonoid, and ascorbic acid contents of sea buckthorn berries. The results showed that the IR-HAD time was the shortest, followed by the HAD, IRD, and PVD times, whereas the VFD time was the longest. The value of the color parameter L* decreased from 53.44 in fresh sea buckthorn berries to 44.18 (VFD), 42.60 (PVD), 37.58 (IRD), 36.39 (HAD), and 36.00 (IR-HAD) in dried berries. The browning index also showed the same trend as the color change. Vacuum freeze-dried berries had the lowest browning index (0.24 Abs/g d.m.) followed by that of pulsed-vacuum–(0.28 Abs/g d.m.), infrared- (0.35 Abs/g d.m.), hot-air–(0.42 Abs/g d.m.), and infrared-assisted hot-air–dried berries (0.59 Abs/g d.m.). The ascorbic acid content of sea buckthorn berries decreased by 45.39, 53.81, 74.23, 77.09, and 79.93% after VFD, PVD, IRD, IR-HAD, and HAD, respectively. The vacuum freeze-dried and pulsed-vacuum–dried sea buckthorn berries had better physicochemical properties than those dried by HAD, IRD, and IR-HAD. Overall, VFD and PVD had the highest ascorbic acid and total phenolic contents, good rehydration ability, and bright color. Nonetheless, considering the high cost of VFD, we suggest that PVD is an optimal drying technology for sea buckthorn berries, with the potential for industrial application.

BackgroundThe Controlled Nutritional Status (CONUT) score is a valid scoring system for assessing nutritional status and has been shown to correlate with clinical outcomes in many surgical procedures; however, no studies have reported a correlation between postoperative complications of bronchiectasis and the preoperative CONUT score. This study aimed to evaluate the value of the CONUT score in predicting postoperative complications in patients with bronchiectasis.MethodsWe retrospectively analyzed patients with localized bronchiectasis who underwent lung resection at our hospital between April 2012 and November 2021. The optimal nutritional scoring system was determined by receiver operating characteristic (ROC) curves and incorporated into multivariate logistic regression. Finally, independent risk factors for postoperative complications were determined by univariate and multivariate logistic regression analyses.ResultsA total of 240 patients with bronchiectasis were included, including 101 males and 139 females, with an average age of 49.83 ± 13.23 years. Postoperative complications occurred in 59 patients (24.6%). The incidence of complications, postoperative hospital stay and drainage tube indwelling time were significantly higher in the high CONUT group than in the low CONUT group. After adjusting for sex, BMI, smoking history, lung function, extent of resection, intraoperative blood loss, surgical approach and operation time, multivariate analysis showed that the CONUT score remained an independent risk factor for postoperative complications after bronchiectasis.ConclusionsThe preoperative CONUT score is an independent predictor of postoperative complications in patients with localized bronchiectasis.

In the Convolvulaceae family, around 1650 species belonging to 60 genera are widely distributed globally, mainly in the tropical and subtropical regions of America and Asia. Although a series of chloroplast genomes in Convolvulaceae were reported and investigated, the evolutionary and genetic relationships among the chloroplast genomes of the Convolvulaceae family have not been extensively elucidated till now. In this study, we first reported the complete chloroplast genome sequence of Ipomoea pes-caprae, a widely distributed coastal plant with medical values. The chloroplast genome of I. pes-caprae is 161667 bp in length, and the GC content is 37.56%. The chloroplastic DNA molecule of I. pes-caprae is a circular structure composed of LSC (large-single-copy), SSC (small-single-copy), and IR (inverted repeat) regions, with the size of the three regions being 88210 bp, 12117 bp, and 30670 bp, respectively. The chloroplast genome of I. pes-caprae contains 141 genes, and 35 SSRs are identified in the chloroplast genome. Our research results provide important genomic information for the molecular phylogeny of I. pes-caprae. The Phylogenetic analysis of 28 Convolvulaceae chloroplast genomes showed that the relationship of I. pes-caprae with I. involucrata or I. obscura was much closer than that with other Convolvulaccae species. Further comparative analyses between the Ipomoea species and Cuscuta species revealed the mechanism underlying the formation of parasitic characteristics of Cuscuta species from the perspective of the chloroplast genome.

Objective: During inspiration, mechanical energy generated from respiratory muscle produces a negative pressure gradient to fulfill enough pulmonary ventilation. The pressure loss, a surrogate for energy loss, is considered as the portion of negative pressure without converting into the kinetic energy of airflow. Mouth opening (MO) during sleep is a common symptom in patients with obstructive sleep apnoea-hypopnea syndrome (OSAHS). This study aimed to evaluate the effects of mouth opening on pharyngeal pressure loss using computational fluid dynamics (CFD) simulation.Methods: A total of four subjects who were morphologically distinct in the pharyngeal characteristics based on Friedman tongue position (FTP) grades were selected. Upper airway computed tomography (CT) scan was performed under two conditions: Mouth closing (MC) and mouth opening, in order to reconstruct the upper airway models. computational fluid dynamics was used to simulate the flow on the two different occasions: Mouth closing and mouth opening.Results: The pharyngeal jet was the typical aerodynamic feature and its formation and development were different from mouth closing to mouth opening in subjects with different Friedman tongue position grades. For FTP I with mouth closing, a pharyngeal jet gradually formed with proximity to the velopharyngeal minimum area plane (planeAmin). Downstream the planeAmin, the jet impingement on the pharyngeal wall resulted in the frictional loss associated with wall shear stress (WSS). A rapid luminal expansion led to flow separation and large recirculation region, corresponding to the interior flow loss. They all contributed to the pharyngeal total pressure loss. While for FTP I with mouth opening, the improved velopharyngeal constriction led to smoother flow and a lower total pressure loss. For FTP IV, the narrower the planeAmin after mouth opening, the stronger the jet formation and its impingement on the pharyngeal wall, predicting a higher frictional loss resulted from higher WSS. Besides, a longer length of the mouth opening-associated constant constrictive segment was another important morphological factor promoting frictional loss.Conclusion: For certain OSAHS patients with higher Friedman tongue position grade, mouth opening-related stronger jet formation, more jet breakdown and stronger jet flow separation might contribute to the increased pharyngeal pressure loss. It might require compensation from more inspiratory negative static pressure that would potentially increase the severity of OSAHS.

Vaccine allocation strategy for COVID-19 is an emerging and important issue that affects the efficiency and control of virus spread. In order to improve the fairness and efficiency of vaccine distribution, this paper studies the optimization of vaccine distribution under the condition of limited number of vaccines. We pay attention to the target population before distributing vaccines, including attitude toward the vaccination, priority groups for vaccination, and vaccination priority policy. Furthermore, we consider inventory and budget indexes to maximize the precise scheduling of vaccine resources. A mixed-integer programming model is developed for vaccine distribution considering the target population from the viewpoint of fairness and efficiency. Finally, a case study is provided to verify the model and provide insights for vaccine distribution.

In recent decades, damming has become one of the most important anthropogenic activities for river regulation, and reservoirs have become hotspots for biogeochemical cycling. The construction of dams changes riverine hydrological conditions and alters the physical, chemical, and biological characteristics of rivers, eventually leading to significant variations in nutrient cycling. This review mainly explores the effects of river damming on nutrient transport and transformation, including i) nutrient (N, P, Si, and C) retention in reservoirs, ii) greenhouse gas (GHG) emissions, and iii) interactions between the nutrient stoichiometry ratio and the health of the reservoir ecosystem. The important drivers of nutrient transport and transformation, such as river connectivity, hydraulic residence time, hydropower development mode, microbial community variation, and anthropogenic pollution, have also been discussed. In addition, strategies to recover from the negative effects of damming on aquatic ecosystems are summarized and analyzed. To provide theoretical and scientific support for the ecological and environmental preservation of river-reservoir systems, future studies should focus on nutrient accumulation and GHG emissions in cascade reservoirs.

BackgroundThe differential diagnosis between autoimmune encephalitis and low-grade diffuse astrocytoma remains challenging. We aim to develop a quantitative model integrating radiomics and spatial distribution features derived from MRI for discriminating these two conditions.MethodsIn our study, we included 188 patients with confirmed autoimmune encephalitis (n = 81) and WHO grade II diffuse astrocytoma (n = 107). Patients with autoimmune encephalitis (AE, n = 59) and WHO grade II diffuse astrocytoma (AS, n = 79) were divided into training and test sets, using stratified sampling according to MRI scanners. We further included an independent validation set (22 patients with AE and 28 patients with AS). Hyperintensity fluid-attenuated inversion recovery (FLAIR) lesions were segmented for each subject. Ten radiomics and eight spatial distribution features were selected via the least absolute shrinkage and selection operator (LASSO), and joint models were constructed by logistic regression for disease classification. Model performance was measured in the test set using the area under the receiver operating characteristic (ROC) curve (AUC). The discrimination performance of the joint model was compared with neuroradiologists.ResultsThe joint model achieved better performance (AUC 0.957/0.908, accuracy 0.914/0.840 for test and independent validation sets, respectively) than the radiomics and spatial distribution models. The joint model achieved lower performance than a senior neuroradiologist (AUC 0.917/0.875) but higher performance than a junior neuroradiologist (AUC 0.692/0.745) in the test and independent validation sets.ConclusionThe joint model of radiomics and spatial distribution from a single FLAIR could effectively classify AE and AS, providing clinical decision support for the differential diagnosis between the two conditions.

ObjectiveThis study aims to examine the value of two-dimensional (2D) ultrasound and two-dimensional shear wave elastography (2D-SWE) in evaluating femoral nerve (FN) and saphenous nerve (SN) neuropathy in patients with type 2 diabetes mellitus (T2DM).Materials and methodsAccording to the diabetic peripheral neuropathy (DPN) diagnostic criteria, 60 patients with T2DM were enrolled and divided into 35 T2DM patients without DPN (non-DPN group) and 25 T2DM patients with DPN (DPN group). The control group consisted of another 15 healthy volunteers. The width, thickness, cross-sectional area (CSA), and perimeter of the FN and SN in the lower extremities were measured with 2D ultrasound. The average shear wave velocity (SWV) of the FN and SN was measured by 2D-SWE. Parameters of the left and right lower extremities were compared in each group, and the above parameters were compared among groups. The correlations between ultrasonographic and laboratory parameters were evaluated, and the independent influencing factors of SWV of the FN and SN were analyzed.ResultsThe width, thickness, CSA, perimeter, and SWV of FN and SN in the DPN group were greater than those in the non-DPN groups and control group (P < 0.05). The width, thickness, CSA, perimeter, and SWV of the FN and SN in the non-DPN group were greater than those in the control group (P < 0.05). The CSA of FN was positively correlated with FPG, HbA1c, and TG (r = 0.34–0.69, P < 0.01). The perimeter of FN was positively correlated with FPG, HbA1c, and TG (r = 0.37–0.68, P < 0.01). The perimeter of the FN was negatively correlated with IgF-1 (r = −0.31, P < 0.05). The CSA of the SN was positively correlated with FPG and TG (r = 0.26–0.42, P < 0.05). The perimeter of the SN was positively correlated with FPG and TG (r = 0.37–0.39, P < 0.01). The SWV of FN and SN were positively correlated with FPG and TG (r = 0.35–0.57, P < 0.01; r = 0.43–0.49, P < 0.01). FPG and TG were independent influencing factors of the SWV of the FN and SN (P < 0.05).Conclusion2D ultrasound and 2D-SWE could be used to non-invasively, objectively, and accurately evaluate the abnormal changes of the FN and SN in patients with T2DM. It has important clinical significance for the early diagnosis of DPN and the curative effect evaluation.

Natural rubber (NR) is an essential industrial raw material widely used in our life. Hevea brasiliensis (Reyan7-33-97) is an economic plant producing natural rubber. Long non-coding RNAs (lncRNAs) are emerging as crucial regulators in numerous biological processes while the characterization and analysis of lncRNAs in Hevea brasiliensis are still largely unrevealed. We integrated the transcriptome datasets from multiple tissues to identify rubber lncRNAs. As a result, 12,029 lncRNAs were found and characterized with notably distinctive features such as longer exon, lower expression levels and GC content, and more tissue specificity in comparison with mRNAs. We discovered thousands of tissue-specific lncRNAs in rubber root, latex, bark, leaf, flower, and seed tissues. The functional enrichment result reveals that tissue-specific lncRNAs are potentially referred to particular functions of tissues, while the non-tissue specific is related to the translation and metabolic processes. In the present study, a comprehensive lncRNA dataset was identified and its functional profile in Hevea brasiliensis was explored, which provides an annotation resource and important clues to understand the biological functions of lncRNAs in Hevea brasiliensis.

Halonitromethanes (HNMs) as one typical class of nitrogenous disinfection byproducts (DBPs) have been widely found in drinking water and are receiving more and more attentions because of their high cytotoxicity, genotoxicity, and developmental toxicity. However, the effects of HNMs exposure on the intestinal tract and intestinal flora remain unknown. This study comprehensively determined the effects of trichloronitromethane, bromonitromethane, and bromochloronitromethane exposure on the intestinal tract and intestinal flora. Results showed that the three HNMs induced intestinal oxidative stress and inflammatory response. Further, HNMs exposure could change the diversities and community structure of intestinal flora, thereby triggering intestinal flora dysbiosis, which might be associated with the intestinal damage such as oxidative stress and inflammation. The intestinal flora dysbiosis was accompanied with mark alterations in function of intestinal flora, such as carbohydrate, lipid, and amino acid metabolisms. This research provides a new insight into studying the toxicity of HNMs exposure based on intestinal flora, which will further improve the health risk assessment of DBPs in drinking water.

BackgroundRecently, the new World Health Organization (WHO) tumor classification removed adenocarcinoma in situ (AIS) from the diagnosis of lung cancer. However, it remains unclear whether the “malignancy” item should be assessed when the modified Caprini Risk Assessment Model (RAM) is used to assess venous thromboembolism (VTE) risk in AIS. The purpose of our study is to assess differences between AIS and stage IA adenocarcinoma (AD) from a VTE perspective.MethodsA retrospective study was performed on AIS and IA adenocarcinoma in our hospital from January 2018 to December 2021, and divided into AIS group and AD group. Propensity score matching (PSM) was used to compare the incidence of VTE and coagulation function, and to analyze whether the RAM is more effective when the “malignancy” item is not evaluated in AIS.Results491 patients were included after screening, including 104 patients in the AIS group and 387 patients in the AD group. After PSM, 83 patients were matched. The incidence of VTE and D-dimer in the AIS group was significantly lower than that in the AD group (P

Given the importance of data safety for psychology, the present study investigated the influence of data leaking scandal on campus customers’ financial consumption behaviors at intelligent tourism platforms in China, and explored the roles that individual characteristics play in this process by focusing on a set of participants from colleges. Data were collected through sending out an online questionnaire, where respondents were asked to finish a series of questions about their background information, their trust, future consuming intention, and defensive behaviors toward intelligent platforms. After they finished these questions, a short description about an online tourism platform leaking customers’ personal information was presented to the respondents, following which they were asked to report about their future consuming intentions and defensive behaviors again. In total, 236 participants of college students and teachers were recruited. Paired samples mean comparison showed that after the stimulus was presented, the respondents had a significant decrease in future financial consumption intention, and a significant increase in defensive behaviors toward online tourism platforms due to risks perceived. Multiple regression analysis was conducted subsequently to investigate individual characteristics that may account for part of the decrease (increase) in consuming intention (defensive behaviors). Results showed that, customers with higher level of trust and monthly income, as well as older customers, tend to experience higher level of decrease in consuming intention, and increase in defensive behaviors. These findings highlighted the importance of online tourism platforms guaranteeing data security of their customers.

Background: The efferocytosis-related molecules have been considered to be correlated with the resistance to cancer chemotherapy. The aim of this study was to investigate the expression and significance of efferocytosis-related molecules in cancers and the correlation of their expression with anticancer drug sensitivity, and provide new potential targets and treatment options for cancers.Methods: We investigated the differential expression of 15 efferocytosis-related molecules (Axl, Tyro3, MerTK, CX3CL1, Tim-4, BAI1, Stab2, Gas6, IDO1, Rac1, MFGE8, ICAM-1, CD47, CD31, and PD-L1) and other 12 common immune checkpoint-related molecules in tumor and normal tissues, the correlation between their expression and various clinicopathological features in 16 types of cancers using publicly available pancancer datasets in The Cancer Genome Atlas. We also analyzed the correlation of the expression of efferocytosis and immune checkpoint related molecules with 126 types of anticancer drugs sensitivity using drug-RNA-seq data.Results: There is a panel of circulating molecules among the 27 molecules. Based on the results of differential expression and correlation with various clinicopathological features of efferocytosis-related molecules in cancers, we identified new potential therapeutic targets for anticancer therapy, such as Axl for kidney renal clear cell carcinoma, Tyro3 for liver hepatocellular carcinoma, and IDO1 for renal papillary cell carcinoma. Except for BAI1, CD31, and MerTK, the enhanced expressions of Axl, Tyro3, Gas6, MFGE8, Stab2, Tim-4, CX3CL1, IDO1, Rac1, and PD-L1 were associated with decreased sensitivity of the cancer cells to many anti-cancer drugs; however, for other common immune checkpoint-related molecules, only enhanced expressions of PD-1, CD28, CTLA4, and HVEM were associated with decreased sensitivity of the cancer cells to a few drugs.Conclusion: The efferocytosis-related molecules were significantly associated with clinical outcomes in many types of cancers and played important roles in resistance to chemotherapy. Combination therapy targeting efferocytosis-related molecules and other immune checkpoint-related molecules is necessary to reduce resistance to chemotherapy.

This work aims to increase the consumption of online tourism products and promote the development of the tourism economy. Based on this, it first analyses the Internet market under the guidance of consumer psychology. Then, the influencing factors of online product decision-making for the tourism economy are discussed. Finally, based on the above analysis, it discusses and evaluates the main factors affecting the consumption of online travel products. The research method of this work is set based on psychology so that it can analyze the psychological state of consumers more deeply and promote the development of the consumer market. The results show that the main factors affecting the consumption of online travel products include online travel platforms and user characteristics. Specifically, approximately 80% of users consume online travel products based on platform reviews, approximately 10% of users consume online travel products based on platform recommended content, and approximately 5% of users consume online travel products based on platform search content. Users vary mainly by age, gender, and region and have different preferences for different platforms. Among the four major platforms, Ctrip occupies the most consumers. The conclusion is that the main way to develop the tourism economy is to build a better online travel platform. At the same time, it is necessary to promote online tourism according to the characteristics of users and increase the marketing of online tourism products. This work not only provides a reference for promoting online tourism product marketing but also helps to promote the development of the tourism economy.