Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

ObjectiveTo explore the main mechanism of self-precipitation formed during the decoction of Sinitang（SNT）， and to provide a research basis for exploring the differences in the toxic and effective components of this compound. MethodsThe average precipitation yields of SNT， Glycyrrhizae Radix et Rhizoma（GRR）-Aconiti Lateralis Radix Praeparata（ALRP） decoction（GF）， ALRP-Zingiberis Rhizoma（ZR） decoction（FJ）， GRR-ZR decoction（GJD）， ALRP decoction（FZ）， ZR decoction（GJ） and GRR decoction（GC） were determined. The four main self-precipitation samples of SNT， GF， FZ and GC were physically characterized by particle size， scanning electron microscopy（SEM）， pH， total dissolved solids（TDS）， conductivity， and Fourier transform infrared spectroscopy（FT-IR） analysis. The chemical compositions of SNT decoction and its different phases was identified by ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive Orbitrap-MS） for SNT， SNT self-precipitation and SNT supernatant， and the contents of its main toxic and effective components were determined by high performance liquid chromatography（HPLC）. ResultsPrecipitation yield results of the 7 samples of SNT decoction and single decoction showed that SNT had the highest self-precipitation yield. The formation of SNT self-precipitation was mainly related to the reaction between ALRP and GRR components to form complexes， and FT-IR showed that GRR had the greatest influence on the formation of self-precipitation. A total of 110 components were identified in the SNT decoction， including 100 components in the SNT self-precipitation and 106 components in the SNT supernatant. And quantitative results of the main toxic and effective components revealed that the reaction between ALRP and GRR components formed complexes， resulting in the following content hierarchy for free components：SNT decoctionsupernatantself-precipitation， these components included free liquiritin， benzoylmesaconine， benzoylaconitine， benzoylhypacoitine， liquiritigenin， aconitine， hypoaconitine， isoliquiritigenin and ammonium glycyrrhizinate. ConclusionSNT exhibits spontaneous precipitation during compound decoction， with GRR exerting the greatest influence on its formation. This suggests GRR plays a significant role in the detoxification of SNT. The differences in the self-precipitated toxic-effective components of SNT compound decoction primarily manifest as changes in component content， reflecting the characteristics of SNT "deposition in vitro and sustained release in vivo" and the importance of "administered at draught" in the clinical application of SNT.

BACKGROUND: T-cell lymphoblastic lymphoma/acute lymphoblastic leukemia (T-LBL/ALL) is an aggressive form of hematological malignancy associated with poor prognosis in adult patients. Histone deacetylases (HDACs) are aberrantly expressed in T-LBL/ALL and are considered potential therapeutic targets. Here, we investigated the antitumor effect of a novel HDAC inhibitor, chidamide, on T-LBL/ALL. METHODS: HDAC1, HDAC2 and HDAC3 levels in T-LBL/ALL cell lines and patient samples were compared with those in normal controls. Flow cytometry, transmission electron microscopy, and lactate dehydrogenase release assays were conducted in Jurkat and MOLT-4 cells to assess apoptosis and pyroptosis. A specific forkhead box O1 (FOXO1) inhibitor was used to rescue pyroptosis and upregulated gasdermin E (GSDME) expression caused by chidamide treatment. The role of the FOXO1 transcription factor was evaluated by dual-luciferase reporter and chromatin immunoprecipitation assays. The efficacy of chidamide in vivo was evaluated in a xenograft mouse. RESULTS: The expression of HDAC1, HDAC2 and HDAC3 was significantly upregulated in T-LBL/ALL. Cell viability was obviously inhibited after chidamide treatment. Pyroptosis, characterized by cell swelling, pore formation on the plasma membrane and lactate dehydrogenase leakage, was identified as a new mechanism of chidamide treatment. Chidamide triggered pyroptosis through caspase 3 activation and GSDME transcriptional upregulation. Chromatin immunoprecipitation assays confirmed that chidamide led to the increased transcription of GSDME through a more relaxed chromatin structure at the promoter and the upregulation of FOXO1 expression. Moreover, we identified the therapeutic effect of chidamide in vivo . CONCLUSIONS This study suggested that chidamide exerts an antitumor effect on T-LBL/ALL and promotes a more inflammatory form of cell death via the FOXO1/GSDME axis, which provides a novel choice of targeted therapy for patients with T-LBL/ALL.
Humans ; Pyroptosis/drug effects* ; Forkhead Box Protein O1/genetics* ; Aminopyridines/pharmacology* ; Animals ; Mice ; Benzamides/pharmacology* ; Cell Line, Tumor ; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma/drug therapy* ; Phosphate-Binding Proteins/metabolism* ; Histone Deacetylase Inhibitors/pharmacology* ; Jurkat Cells ; Histone Deacetylases/metabolism* ; Apoptosis/drug effects* ; Gasdermins

Insulin-like growth factor 2 (IGF2) is a critical endocrine mediator implicated in male reproductive physiology. To investigate the correlation between IGF2 protein levels and various aspects of male infertility, specifically focusing on sperm quality, inflammation, and DNA damage, a cohort of 320 male participants was recruited from the Women's Hospital, Zhejiang University School of Medicine (Hangzhou, China) between 1 st January 2024 and 1 st March 2024. The relationship between IGF2 protein concentrations and sperm parameters was assessed, and Spearman correlation and linear regression analysis were employed to evaluate the independent associations between IGF2 protein levels and risk factors for infertility. Enzyme-linked immunosorbent assay (ELISA) was used to measure IGF2 protein levels in seminal plasma, alongside markers of inflammation (tumor necrosis factor-alpha [TNF-α] and interleukin-1β [IL-1β]). The relationship between seminal plasma IGF2 protein levels and DNA damage marker phosphorylated histone H2AX (γ-H2AX) was also explored. Our findings reveal that IGF2 protein expression decreased notably in patients with asthenospermia and teratospermia. Correlation analysis revealed nuanced associations between IGF2 protein levels and specific sperm parameters, and low IGF2 protein concentrations correlated with increased inflammation and DNA damage in sperm. The observed correlations between IGF2 protein levels and specific sperm parameters, along with its connection to inflammation and DNA damage, underscore the importance of IGF2 in the broader context of male reproductive health. These findings lay the groundwork for future research and potential therapeutic interventions targeting IGF2-related pathways to enhance male fertility.
Humans ; Male ; Insulin-Like Growth Factor II/metabolism* ; Infertility, Male/genetics* ; DNA Damage ; Adult ; Inflammation/metabolism* ; Spermatozoa/metabolism* ; Semen Analysis ; Semen/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Histones/metabolism* ; Interleukin-1beta/metabolism*

OBJECTIVE: Psoriasis, a common chronic inflammatory skin condition with genetic underpinnings, is traditionally managed with cupping therapy. Although used historically, the precise mechanical effects and therapeutic mechanisms of cupping in psoriasis remain largely unexamined. This study aimed to evaluate cupping therapy's efficacy for psoriasis and investigate its role in modulating inflammatory responses and cellular metabolism. METHODS: Psoriasis was induced in mice using topical imiquimod (IMQ). The effects of cupping on psoriatic lesions were assessed using the Psoriasis Area and Severity Index score, histology, immunohistochemistry, and immunofluorescence staining. polymerase chain reaction sequencing (RNA-seq) and Western blotting were conducted to examine changes in mRNA expression and the AMP-activated protein kinase (AMPK) signaling pathway. RESULTS: Cupping therapy significantly reduced inflammation, epidermal thickness, and inflammatory cell infiltration in mice with IMQ-induced psoriasis. Immunohistochemistry and immunofluorescence showed lower expression of inflammatory markers and a shift in T-cell populations. RNA-seq and Western blotting indicated that cupping upregulated Piezo1 and activated the AMPK pathway, improving energy metabolism in psoriatic skin. CONCLUSION Cupping therapy reduces epidermal hyperproliferation and inflammation in psoriasis, rebalancing the local immune microenvironment. Mechanistically, cupping promotes calcium influx via Piezo1, activates AMPK signaling, and supports metabolic homeostasis, suggesting therapeutic potential for psoriasis. Please cite this article as: Xi RF, Liu X, Wang Y, Lu HZ, Yuan SJ, Guo DJ, Zhu JY, Li FL, Duan YJ. Mechanosensory activation of Piezo1 via cupping therapy: Harnessing neural networks to modulate AMPK pathway for metabolic restoration in a mouse model of psoriasis. J Integr Med. 2025; 23(6):721-732.
Animals ; Psoriasis/chemically induced* ; Mice ; AMP-Activated Protein Kinases/metabolism* ; Disease Models, Animal ; Cupping Therapy/methods* ; Signal Transduction ; Imiquimod ; Ion Channels/genetics* ; Male ; Mechanotransduction, Cellular

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

Objective:Given the high incidence and mortality rate of sepsis,early identification of high-risk patients and timely intervention are crucial.However,existing mortality risk prediction models still have shortcomings in terms of operation,applicability,and evaluation on long-term prognosis.This study aims to investigate the risk factors for death in patients with sepsis,and to construct the prediction model of short-term and long-term mortality risk. Methods:Patients meeting sepsis 3.0 diagnostic criteria were selected from the Medical Information Mart for Intensive Care-IV(MIMIC-IV)database and randomly divided into a modeling group and a validation group at a ratio of 7?3.Baseline data of patients were analyzed.Univariate Cox regression analysis and full subset regression were used to determine the risk factors of death in patients with sepsis and to screen out the variables to construct the prediction model.The time-dependent area under the curve(AUC),calibration curve,and decision curve were used to evaluate the differentiation,calibration,and clinical practicability of the model. Results:A total of 14 240 patients with sepsis were included in our study.The 28-day and 1-year mortality were 21.45%(3 054 cases)and 36.50%(5 198 cases),respectively.Advanced age,female,high sepsis-related organ failure assessment(SOFA)score,high simplified acute physiology score II(SAPS II),rapid heart rate,rapid respiratory rate,septic shock,congestive heart failure,chronic obstructive pulmonary disease,liver disease,kidney disease,diabetes,malignant tumor,high white blood cell count(WBC),long prothrombin time(PT),and high serum creatinine(SCr)levels were all risk factors for sepsis death(all P<0.05).Eight variables,including PT,respiratory rate,body temperature,malignant tumor,liver disease,septic shock,SAPS II,and age were used to construct the model.The AUCs for 28-day and 1-year survival were 0.717(95%CI 0.710 to 0.724)and 0.716(95%CI 0.707 to 0.725),respectively.The calibration curve and decision curve showed that the model had good calibration degree and clinical application value. Conclusion:The short-term and long-term mortality risk prediction models of patients with sepsis based on the MIMIC-IV database have good recognition ability and certain clinical reference significance for prognostic risk assessment and intervention treatment of patients.