Assessing respiratory airflow unsteadiness under different tidal respiratory frequencies using large eddy simulation method.

Unsteady respiratory airflow characteristics play a crucial role in understanding the deposition of toxic particles and inhaled aerosol drugs in the human respiratory tract. Considering the variations in respiratory flow rate and glottis motion under different respiratory frequencies, these respiratory airflow characteristics are studied by large-eddy simulations, including pressure field, power loss, modal spatial patterns, and vortex structures. Firstly, the results reveal that varying respiratory frequencies significantly affect airflow unsteadiness, turbulent evolution, and vortex structure dissipation, as they increase the complexity and butterfly effect introduced by the turbulent disturbance. Secondly, the pressure drops and flow rate at the glottis also conform to a power-law relationship considering the respiratory physiological characteristics, especially under low respiratory frequencies. Glottis motion plays different roles in energy consumption during inspiration and expiration, and its magnitude can be predicted using a polynomial function based on glottis area and respiratory flowrate under different respiratory frequencies. Finally, modal decomposition can be effectively applied to the study of respiratory flow characteristics, but we recommend separately studying the inspiration and expiration. The spatial distribution of the dominant mode characterizes the majority of respiratory flow characteristics and are influenced by respiratory frequency. Spectral entropy results indicate that glottis motion and slow breathing both delay the transitions in the upper respiratory tract during inspiration and expiration. These results confirm that the respiratory physiology characteristics under different respiratory frequencies have a significant impact on the unsteady respiratory airflow characteristics and warrant further study.

Optical Surface-guided Radiation Therapy for Upper and Lower Limb Sarcomas: An Analysis of Setup Errors and Clinical Target Volume-To-Planning Target Volume Margins.

Purpose: To assess the clinical benefits of surface-guided radiation therapy (SGRT) in terms of setup error, positioning time, and clinical target volume-to-planning target volume (CTV-PTV) margin in extremity soft tissue sarcoma (STS). Methods and Materials: Fifty consecutive patients treated with radiation therapy were selected retrospectively. Treatment setup was performed with either laser-based imaging only (control group), or with laser-based and daily optical surface-based imaging (SGRT group). Pretreatment cone beam computed tomography images were acquired daily for the first 3 to 5 fractions and weekly thereafter, with the frequency adjusted as necessary. Translational and rotational errors were collected. CTV-PTV margin was calculated using the formula, 2.5Σ + 0.7σ. Results: Each group consisted of 10 and 15 upper and lower limb STSs, respectively. For patients with upper limb sarcomas, the translation errors were 1.64 ± 1.34 mm, 1.10 ± 1.50 mm, and 1.24 ± 1.45 mm in the SGRT group, and 1.48 ± 3.16 mm, 2.84 ± 2.85 mm, and 3.14 ± 3.29 mm in control group in the left-right, supero-inferior, and antero-posterior directions, respectively. Correspondingly, for patients with lower limb sarcomas, the translation errors were 1.21 ± 1.65 mm, 1.39 ± 1.71 mm, and 1.48 ± 2.10 mm in the SGRT group, and 1.81 ± 2.60 mm, 2.93 ± 3.28 mm, and 3.53 ± 3.75 mm in control group, respectively. The calculated CTV-PTV margins of the SGRT group and control group were 5.0, 3.8, 4.1 versus 5.9, 9.1, 10.1 mm for upper limb sarcomas; and 4.2, 4.7, 5.2 mm versus 6.3, 9.6, and 11.4 mm for lower limb sarcomas in the left-right, supero-inferior, and antero-posterior directions, respectively. Conclusions: Daily optical surface guidance can effectively improve the setup accuracy of extremity STS patients, and safely reduce the required CTV-PTV margins.

Non-targeted GC-MS metabolomics-based differences in Indica rice seeds of different varieties.

Rice seeds of different varieties exhibited distinct metabolic profiles in our study. We analyzed the metabolites in seeds of six rice varieties (CH, HM, NX, YX, HY, and MX) using non-targeted GC-MS. Our findings revealed that amino acids, sugars, and organic acids were predominant in all varieties, with significant differences observed in CH compared to the others. Specifically phenylalanine and glycine content differed notably in NX and YX, respectively. Additionally, 1,5-anhydroglucitol content in NX, and glutamate, aspartate, and lactulose in NX, YX, HM, HY, and MX were up-regulated. Due to the biological functions of these amino acids and sugars, these indicated that compared to CH, rice of NX were more conducive to metabolism of carbohydrate and fat, and healthy growth maintenance in the human body, but mightThese variations suggest that NX rice may be more beneficial for carbohydrate and fat metabolism and overall health maintenance compared to CH. However, it may not be suitable for diabetic patients. YX rice may not be an ideal glycine supplement, rice ofwhile HM, HY, and MX rice could serve as potential lactulose sources. Furthermore, NX and YX rice exhibited higher levels of main storage proteins compared to CH. This study offers valuable insights into the metabolic differences among various rice varieties.

Ginkgolide B effectively mitigates neuropathic pain by suppressing the activation of the NLRP3 inflammasome through the induction of mitophagy in rats.

Neuropathic pain is a pathological state induced by the aberrant generation of pain signals within the nervous system. Ginkgolide B(GB), an active component found of Ginkgo. biloba leaves, has neuroprotective properties. This study aimed to explore the effects of GB on neuropathic pain and its underlying mechanisms. In the in vivo study, we adopted the rat chronic constriction injury model, and the results showed that GB(4 mg/kg) treatment effectively reduced pain sensation in rats and decreased the expressions of Iba-1 (a microglia marker), NLRP3 inflammasome, and inflammatory factors, such as interleukin (IL)-1ß, in the spinal cord 7 days post-surgery. In the in vitro study, we induced microglial inflammation using lipopolysaccharide (500 ng/mL) / adenosine triphosphate (5 mM) and treated it with GB (10, 20, and 40 µM). GB upregulated the expression of mitophagy proteins, such as PINK1, Parkin, LC3 II/I, Tom20, and Beclin1, and decreased the cellular production of reactive oxygen species. Moreover, it lowered the expression of inflammation-related proteins, such as Caspase-1, IL-1ß, and NLRP3 in microglia. However, this effect was reversed by Parkin shRNA/siRNA or the autophagy inhibitor 3-methyladenine (5 mM). These findings reveal that GB alleviates neuropathic pain by mitigating neuroinflammation through the activation of PINK1-Parkin-mediated mitophagy.

Prognostic value of lymphocytes in patients with breast cancer receiving radiotherapy after breast-conserving surgery: A post hoc analysis of a phase III randomized trial.

PURPOSE: To evaluate the prognostic value of peripheral lymphocyte count (PLC) in the breast cancer patients after breast-conserving surgery (BCS) with radiotherapy (RT). METHODS AND MATERIALS: This post hoc analysis was performed using data of 628 patients from a phase III, randomized controlled trial comparing hypofractionated RT (HFRT) with conventional fractionated RT (CFRT) after BCS. PLCs were obtained before, during, and after RT until the 1-year follow-up. The optimal cut-off PLCs were determined using the maxstat package in R. Survival rates were estimated using the Kaplan-Meier method and compared with the log-rank test. RESULTS: A total of 275 (46.1 %) patients developed lymphopenia during RT, among them, 17 (2.8 %) had grade 3 lymphopenia and no one developed grade 4 lymphopenia. With a median follow-up of 110.8 months, patients with pre-RT PLCs of < 1.77 × 109/L had a significantly lower 10-year breast cancer-specific survival (BCSS) rate (P = 0.013) and overall survival (OS) rate (P = 0.026). Patients with a nadir PLC of < 1.35 × 109/L had a significantly poorer 10-year OS rate (P = 0.048). Multivariate analysis showed that a pre-RT PLC of < 1.77 × 109/L was an independent factor influencing BCSS and OS, while the effect of the nadir PLC did not remain significant. Neither PLC nor lymphopenia recovery at post-RT 1, 3, and 6 months and 1 year was associated with survival. CONCLUSIONS: Radiation-induced lymphopenia in patients with breast cancer after BCS tends to be mild. The lower pre-RT PLC predicted poorer survival.

DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images.

Bone proliferation is an important pathological feature of inflammatory rheumatic diseases. Although recent advance in high-resolution peripheral quantitative computed tomography (HR-pQCT) enables physicians to study microarchitectures, physicians' annotation of proliferation suffers from slice inconsistency and subjective variations. Also, there are only few effective automatic or semi-automatic tools for proliferation detection. In this study, by integrating pathological knowledge of proliferation formation with the advancement of statistical shape analysis theory, we present an unsupervised method, named Deformation-Controllable Elastic Shape model, for 3D bone Proliferation Analysis (DCES-PA). Unlike previous shape analysis methods that directly regularize the smoothness of the displacement field, DCES-PA regularizes the first and second-order derivative of the displacement field and decomposes these vector fields according to different deformations. For the first-order elastic metric, DCES-PA orthogonally decomposes the first-order derivative of the displacement field by shearing, scaling and bending deformation, and then penalize deformations triggering proliferation formation. For the second-order elastic metric, DCES-PA encodes both intrinsic and extrinsic surface curvatures into the second-order derivative of the displacement field to control the generation of high-curvature regions. By integrating the elastic shape metric with the varifold distances, DCES-PA achieves correspondence-free shape analysis. Extensive experiments on both simulated and real clinical datasets demonstrate that DCES-PA not only shows an improved accuracy than other state-of-the-art shape-based methods applied to proliferation analysis but also produces highly sensitive proliferation annotations to assist physicians in proliferation analysis.

Novel inflammatory and insulin resistance indices provide a clue in cerebral amyloid angiopathy.

This study investigated the correlation of newly identified inflammatory and insulin resistance indices with cerebral amyloid angiopathy (CAA), and explored their potential to differentiate CAA from hypertensive arteriopathy (HA). We retrospectively analyzed 514 consecutive patients with cerebral small vessel disease (CSVD)-related haemorrhage, comparing the differences in novel inflammatory and insulin resistance indices between patients with CAA and HA. Univariate regression, LASSO and multivariate regression were used to screen variables and construct a classification diagnosis nomogram. Additionally, these biomarkers were explored in patients with mixed haemorrhagic CSVD. Inflammatory indices were higher in CAA patients, whereas insulin resistance indices were higher in HA patients. Further analysis identified neutrophil-to-lymphocyte ratio (NLR, OR 1.17, 95% CI 1.07-1.30, P < 0.001), and triglyceride-glucose index (TyG, OR = 0.56, 95% CI 0.36-0.83, P = 0.005) as independent factors for CAA. Therefore, we constructed a CAA prediction nomogram without haemorrhagic imaging markers. The nomogram yielded an area under the curve (AUC) of 0.811 (95% CI 0.764-0.865) in the training set and 0.830 (95% CI 0.718-0.887) in the test set, indicating an ability to identify high-risk CAA patients. These results show that CSVD patients can be phenotyped using novel inflammatory and insulin resistance indices, potentially allowing identification of high-risk CAA patients without haemorrhagic imaging markers.

A Joint Time-Frequency Domain Transformer for multivariate time series forecasting.

In order to enhance the performance of Transformer models for long-term multivariate forecasting while minimizing computational demands, this paper introduces the Joint Time-Frequency Domain Transformer (JTFT). JTFT combines time and frequency domain representations to make predictions. The frequency domain representation efficiently extracts multi-scale dependencies while maintaining sparsity by utilizing a small number of learnable frequencies. Simultaneously, the time domain (TD) representation is derived from a fixed number of the most recent data points, strengthening the modeling of local relationships and mitigating the effects of non-stationarity. Importantly, the length of the representation remains independent of the input sequence length, enabling JTFT to achieve linear computational complexity. Furthermore, a low-rank attention layer is proposed to efficiently capture cross-dimensional dependencies, thus preventing performance degradation resulting from the entanglement of temporal and channel-wise modeling. Experimental results on eight real-world datasets demonstrate that JTFT outperforms state-of-the-art baselines in predictive performance.

Identification of osteoporosis ferroptosis-related markers and potential therapeutic compounds based on bioinformatics methods and molecular docking technology.

RESEARCH BACKGROUND AND PURPOSE: Osteoporosis (OP) is one of the most common bone diseases worldwide, characterized by low bone mineral density and susceptibility to pathological fractures, especially in postmenopausal women and elderly men. Ferroptosis is one of the newly discovered forms of cell death regulated by genes in recent years. Many studies have shown that ferroptosis is closely related to many diseases. However, there are few studies on ferroptosis in osteoporosis, and the mechanism of ferroptosis in osteoporosis is still unclear. This study aims to identify biomarkers related to osteoporosis ferroptosis from the GEO (Gene Expression Omnibus) database through bioinformatics technology, and to mine potential therapeutic small molecule compounds through molecular docking technology, trying to provide a basis for the diagnosis and treatment of osteoporosis in the future. MATERIALS AND METHODS: We downloaded the ferroptosis-related gene set from the FerrDb database ( http://www.zhounan.org/ferrdb/index.html ), downloaded the data sets GSE56815 and GSE7429 from the GEO database, and used the R software "limma" package to screen differentially expressed genes (DEGs) from GSE56815, and intersected with the ferroptosis gene set to obtain ferroptosis-related DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by the R software "clusterProfiler" package. The random forest model was further screened to obtain essential ferroptosis genes. R software "corrplot" package was used for correlation analysis of essential ferroptosis genes, and the Wilcox test was used for significance analysis. The lncRNA-miRNA-mRNA-TF regulatory network was constructed using Cytoscape software. The least absolute shrinkage and selection operator (LASSO) was used to construct a disease diagnosis model, and a Receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic performance, and then GSE7429 was used to verify the reliability of the diagnosis model. Molecular docking technology was used to screen potential small molecule compounds from the Drugbank database. Finally, a rat osteoporosis model was constructed, and peripheral blood mononuclear cells were extracted for qRT-PCR detection to verify the mRNA expression levels of crucial ferroptosis genes. RESULT: Six DEGs related to ferroptosis were initially screened out. GO function and KEGG pathway enrichment analysis showed that ferroptosis-related DEGs were mainly enriched in signaling pathways such as maintenance of iron ion homeostasis, copper ion binding function, and ferroptosis. The random forest model identified five key ferroptosis genes, including CP, FLT3, HAMP, HMOX1, and SLC2A3. Gene correlation analysis found a relatively low correlation between these five key ferroptosis genes. The lncRNA-miRNA-mRNA-TF regulatory network shows that BAZ1B and STAT3 may also be potential molecules. The ROC curve of the disease diagnosis model shows that the model has a good diagnostic performance. Molecular docking technology screened out three small molecule compounds, including NADH, Midostaurin, and Nintedanib small molecule compounds. qRT-PCR detection confirmed the differential expression of CP, FLT3, HAMP, HMOX1 and SLC2A3 between OP and normal control group. CONCLUSION: This study identified five key ferroptosis genes (CP, FLT3, HAMP, HMOX1, and SLC2A3), they were most likely related to OP ferroptosis. In addition, we found that the small molecule compounds of NADH, Midostaurin, and Nintedanib had good docking scores with these five key ferroptosis genes. These findings may provide new clues for the early diagnosis and treatment of osteoporosis in the future.

Development and characterization of discontinuous atmospheric pressure interface - Dual pressure chamber miniature mass spectrometer.

Miniaturized mass spectrometers have become increasingly prevalent for real-time detection and analysis, owing to their compact size and portability. The pursuit of performance enhancement in these instruments is a pivotal objective within the domain of mass spectrometry miniaturization. This study introduces a novel miniature mass spectrometer featuring a discontinuous atmospheric pressure interface and a dual pressure chamber. Compared to conventional single-chamber, discontinuous sampling interface mass spectrometers, the newly developed instrument demonstrates a more than tenfold improvement in detection efficiency. This significant enhancement is achieved without the need for complex control of switch coupling time series, thereby streamlining the circuit design and improving the instrument's fault tolerance. Furthermore, by capitalizing on the benefits of discontinuous sampling, the instrument reduces the operational pressure relative to traditional continuous sampling in differential pressure vacuum chambers. It accommodates larger inlet capillary (0.38 mm) and skimmer (0.5 mm) diameters, leading to a ninefold increase in response strength for risperidone and lowering the detection limit to 0.5 ppb. The instrument's capacity for rapid drug detection, along with enhanced resolution and detection limits, underscores its potential utility. Additionally, it facilitates the use of smaller mechanical pumps, significantly diminishing both the instrument's volume and power consumption. This presents a promising avenue for further miniaturization of mass spectrometers.

Disparities in mortality risk after diagnosis of hematological malignancies in 185 countries: A global data analysis.

This study was to report proxy measures for mortality risk in patients with hematological malignancies across 185 countries globally and explore its association with their socioeconomic status and treatment. The incidence, mortality, and 5-year prevalence data were extracted from the GLOBOCAN database. The data regarding the human development index (HDI), gross national income (GNI), vulnerability index, and concordance with cancer Essential Medicines List (EML) were obtained from open-source reports. The ratio of mortality to 5-year-prevalence (MPR) and that of mortality to incidence (MIR) were calculated and age-standardized using Segi's world standard population. Finally, the possible associations were assessed using Pearson correlation analyses. In 2020, the global incidence, mortality, and 5-year prevalence of HMs were 1,278,362, 711,840, and 3,616,685, respectively. Global age-standardized MPR and MIR were 0.15 and 0.44, respectively; they varied significantly among 6 regions, 185 countries, 4 HM types, and 4 HDI groups worldwide. Older populations always had higher ratios. The correlation of MPRs and MIRs with HDI, GNI, and concordance with cancer EML was negative, whereas it was positive with the vulnerability index (lower was better). Increasing access to cancer drugs in resource-limited regions with a focus on vulnerable children may aid in reducing HM-related mortality risk.

Treatment outcome, toxicity, and quality of life of patients with bronchus-associated lymphoid tissue lymphoma.

The disease failure patterns and optimal treatment of bronchus-associated lymphoid tissue (BALT) lymphoma are unknown. This retrospective study involved 71 patients with primary BALT lymphoma who had received radiotherapy (RT), surgery, immunochemotherapy (IC), or observation. The median follow-up time was 66 months. The 5-year overall survival and lymphoma-specific survival were 91.2% and 96.1%, respectively, and were not significantly different among treatments. The 5-year cumulative incidence of overall failure for RT, surgery, IC, and observation was 0%, 9.7% (p = .160), 30.8% (p = .017), and 31.3% (p = .039). There was no grade ≥3 toxicity in RT group according to the CTCAE 5.0 reporting system. Quality of life (QoL) was at similarly good levels among the treatment groups. BALT lymphoma had a favorable prognosis but persistent risk of relapse after IC or observation. Given the very low disease failure risk and good QoL, RT remains an effective initial treatment for BALT lymphoma.

BALT lymphoma has a favorable prognosis but a persistent progression and relapse risk.Radiotherapy is associated with lower failure of disease progression and relapse, low toxicity and good quality of life.

Subtypes of Blastocystis in Tibetan Antelope (Pantholops hodgsonii).

Blastocystis is a protist that is distributed in the gut tract of humans and animals. However, the reports about Blastocystis infection in Tibetan antelope are scarce. We collected 173 Tibetan antelope feces samples from Xinjiang, Qinghai and Xizang, and amplified the SSU rRNA gene of 600 bp region of Blastocystis in our research. Fifty-one samples in total were positive for Blastocystis, with all subtypes being ST31. The lowest prevalence of Blastocystis was observed in Xizang (2/20, 9.1%), followed by Qinghai (18/92, 16.4%), Xinjiang (31/61, 33.7%). The highest prevalence of Blastocystis in Tibetan antelope was detected during the summer was (19/30, 38.8%). This is the first research work regarding the Blastocystis subtypes ST31 in Tibetan antelope. Our research provides information for future researches on the distribution of this Blastocystis subtype and the control of Blastocystis infection.

Adaptive ultra-hypofractionated whole-pelvic radiotherapy in high-risk and very high-risk prostate cancer on 1.5-Tesla MR-Linac: Estimated delivered dose and early toxicity results.

Background: Magnetic resonance (MR)-guided ultra-hypofractionated radiotherapy with whole-pelvic irradiation (UHF-WPRT) is a novel approach to radiotherapy for patients with high-risk (HR) and very high-risk (VHR) prostate cancer (PCa). However, the inherent complexity of adaptive UHF-WPRT might inevitably result in longer on-couch time. We aimed to estimate the delivered dose, study the feasibility and safety of adaptive UHF-WPRT on a 1.5-Tesla MR-Linac. Methods: Ten patients with clinical stage T3a-4N0-1M0-1c PCa, who consecutively received UHF-WPRT, were enrolled prospectively. The contours of the target and organ-at-risks on the position verification-MR (PV-MR), beam-on 3D-MR(Bn-MR), and post-MR (after radiotherapy delivery) were derived from the pre-MR data by deformable image registration. The physician then manually adjusted them, and dose recalculation was performed accordingly. GraphPad Prism 9 (GraphPad Prism Software Inc.) was utilized for conducting statistical analyses. Results: In total, we collected 188 MR scans (50 pre-MR, 50 PV-MR, 44 Bn-MR, and 44 post-MR scans). With median 59 min, the mean prostate clinical target volume (CTV)-V100% was 98.59% ± 2.74%, and the mean pelvic CTVp-V100% relative percentages of all scans was 99.60% ± 1.18%. The median V29 Gy change in the rectal wall was -2% (-18% to 20%). With a median follow-up of 9 months, no patient had acute Common Terminology Criteria for Adverse Events (CTCAE) grade 2 or more severe genitourinary (GU) or gastrointestinal (GI) toxicities (0%). Conclusion: UHF-RT to the prostate and the whole pelvis with concomitant boost to positive nodes using an Adapt-To-Shape (ATS) workflow was technically feasible for patients with HR and VHR PCa, presenting only mild GU and GI toxicities. The estimated target dose during the beam-on phase was clinically acceptable based on the 3D-MR-based dosimetry analysis. Clinical trial registration: Chinese Clinical Trial Registry ChiCTR2000033382.

Relationship-Guided Knowledge Transfer for Class-Incremental Facial Expression Recognition.

Human emotions contain both basic and compound facial expressions. In many practical scenarios, it is difficult to access all the compound expression categories at one time. In this paper, we investigate comprehensive facial expression recognition (FER) in the class-incremental learning paradigm, where we define well-studied and easily-accessible basic expressions as initial classes and learn new compound expressions incrementally. To alleviate the stability-plasticity dilemma in our incremental task, we propose a novel Relationship-Guided Knowledge Transfer (RGKT) method for class-incremental FER. Specifically, we develop a multi-region feature learning (MFL) module to extract fine-grained features for capturing subtle differences in expressions. Based on the MFL module, we further design a basic expression-oriented knowledge transfer (BET) module and a compound expression-oriented knowledge transfer (CET) module, by effectively exploiting the relationship across expressions. The BET module initializes the new compound expression classifiers based on expression relevance between basic and compound expressions, improving the plasticity of our model to learn new classes. The CET module transfers expression-generic knowledge learned from new compound expressions to enrich the feature set of old expressions, facilitating the stability of our model against forgetting old classes. Extensive experiments on three facial expression databases show that our method achieves superior performance in comparison with several state-of-the-art methods.

DeGCN: Deformable Graph Convolutional Networks for Skeleton-Based Action Recognition.

Graph convolutional networks (GCN) have recently been studied to exploit the graph topology of the human body for skeleton-based action recognition. However, most of these methods unfortunately aggregate messages via an inflexible pattern for various action samples, lacking the awareness of intra-class variety and the suitableness for skeleton sequences, which often contain redundant or even detrimental connections. In this paper, we propose a novel Deformable Graph Convolutional Network (DeGCN) to adaptively capture the most informative joints. The proposed DeGCN learns the deformable sampling locations on both spatial and temporal graphs, enabling the model to perceive discriminative receptive fields. Notably, considering human action is inherently continuous, the corresponding temporal features are defined in a continuous latent space. Furthermore, we design an innovative multi-branch framework, which not only strikes a better trade-off between accuracy and model size, but also elevates the effect of ensemble between the joint and bone modalities remarkably. Extensive experiments show that our proposed method achieves state-of-the-art performances on three widely used datasets, NTU RGB+D, NTU RGB+D 120, and NW-UCLA.

Introduction to advances in multicomponent plasmonic hybrid nanoarchitectures for versatile applications.

An introduction to the Nanoscale Advances themed collection on multicomponent plasmonic hybrid nanoarchitectures with precisely tailored properties for emerging applications, featuring burgeoning research on a variety of multifunctional plasmonic nanoparticles with synergistically reinforced properties.

Inetetamab combined with tegafur as second-line treatment for human epidermal growth factor receptor-2-positive gastric cancer: A case report.

BACKGROUND: Human epidermal growth factor receptor-2 (HER-2) plays a vital role in tumor cell proliferation and metastasis. However, the prognosis of HER2-positive gastric cancer is poor. Inetetamab, a novel anti-HER2 targeting drug independently developed in China, exhibits more potent antibody-dependent cell-mediated cytotoxicity than trastuzumab, which is administered as the first-line treatment for HER2-positive gastric cancer in combination with chemotherapy. In this case, the efficacy and safety of inetetamab combined with tegafur was investigated as a second-line treatment for HER2-positive gastric cancer. CASE SUMMARY: A 52-year-old male patient with HER2-positive gastric cancer presented with abdominal distension, poor appetite, and fatigue two years after receiving six cycles of oxaliplatin combined with tegafur as first-line treatment after surgery, followed by tegafur monotherapy for six months. The patient was diagnosed with postoperative recurrence of gastric adenocarcinoma. He received 17 cycles of a combination of inetetamab, an innovative domestically developed anti-HER2 monoclonal antibody, and tegafur chemotherapy as the second-line treatment (inetetamab 200 mg on day 1, every 3 wk combined with tegafur twice daily on days 1-14, every 3 wk). Evaluation of the efficacy of the second-line treatment revealed that the patient achieved a stable condition and progression-free survival of 17 months. He tolerated the treatment well without exhibiting any grade 3-4 adverse events. CONCLUSION: Inetetamab combined with chemotherapy for the treatment of metastatic HER2-positive gastric cancer demonstrates significant survival benefits and acceptable safety.

Optimizing the prognostic capacity of baseline 18F-FDG PET/CT metabolic parameters in extranodal natural killer/T-cell lymphoma by using relative and absolute thresholds.

Objectives: To investigate the prognostic capacity of baseline 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters in extranodal natural killer/T-cell lymphoma (ENKTCL), and the influence of relative thresholds (RT) and absolute thresholds (AT) selection on prognostic capacity. Materials and methods: Metabolic tumor volume (MTV)-based parameters were defined using RTs (41 % or 25 % of maximum standardized uptake value [SUVmax]), ATs (SUV 2.5, 3.0, 4.0, or mean liver uptake) in 133 patients. Metabolic parameters were classified into avidity-related parameters (SUVmax, mean SUV [SUVmean], standard deviation of SUV [SUVsd]), volume-related parameters (RT-MTV), and avidity- and volume-related parameters (total lesion glycolysis [TLG] and AT-MTV). The prognostic capacity of the metabolic parameters and the effects of different threshold types (RT vs. AT) were evaluated. Results: All metabolic parameters were moderately associated with prognosis. However, the area under the receiver operating characteristic curve of MTV and TLG was slightly higher than that of avidity-related parameters for predicting 5-year progression-free survival (PFS) (0.614-0.705 vs. 0.563-0.609) and overall survival (OS) (0.670-0.748 vs. 0.562-0.593). Correlations of MTV and avidity-related parameters differed between RTs (r < 0.06, P = 0.324-0.985) and ATs (r 0.56-0.84, P ≤ 0.001). AT-MTV was the optimal predictor for PFS and OS, while RT-TLG was the optimal predictor for PFS, and the combination of RT-MTV with SUVmax was the optimal predictor for OS. Conclusion: The incorporation of volume and avidity significantly improved the prognostic capacity of PET in ENKTCL. Composite parameters that encompassed both avidity and volume were recommended.