Relationship between coronary microvascular dysfunction (CMD) and left ventricular diastolic function in patients with symptoms of myocardial ischemia with non-obstructive coronary artery disease (INOCA) by cardiovascular magnetic resonance feature-tracking

AIM

To investigate whether there was an association between coronary microvascular dysfunction (CMD) and left ventricular (LV) diastolic function in patients with myocardial ischemia with non-obstructive coronary artery disease (INOCA).

MATERIALS AND METHODS

Our study included 115 subjects with suspected myocardial ischemia that underwent stress perfusion cardiac magnetic resonance (CMR). They were divided into non-CMD and CMD two groups. CMR-derived volume-time curves and CMR-FT parameters were used to assess LV diastolic function using CVI42 software. The latter included global/regional LV peak longitudinal, circumferential, radial diastolic strain rate (LDSR, CDSR, RDSR). Logistic regression analysis was performed with CMR-FT strain parameters as independent variables and CMD as dependent variables, and the effect value was expressed as an odds ratio (OR).

RESULTS

Of the 115 patients, we excluded data from 23 patients and 92 patients (56.5% male；52 ± 12 years) were finally included in the study. Of these, 19 patients were included in the non-CMD group (49 ± 11 years) and CMD group included 73patient (52 ± 12 years). The regional CDSR (P=0.019), and regional RDSR (P=0.006) were significantly lower in the CMD group than in non-CMD group. But, regional LDSR in CMD group was higher than non-CMD (P=0.003). In logistic regression analysis, regional LDSR (adjusted β= 0.1, 95%CI 0.077, 0.349, p=0.002) and RDSR (adjusted β= 0.1, 95 % CI 0.066, 0.356, p=0.004) were related to CMD.

CONCLUSIONS

LV myocardial perfusion parameter MPRI was negatively correlated with LV diastolic function (CDSR) which needs to take into account the degree of diastolic dysfunction.

[Impact of autologous hematopoietic stem cell transplantation on the efficacy of CAR-T treatment of relapsed/refractory multiple myeloma]

Objective: To evaluate the effect of autologous hematopoietic stem cell transplantation (ASCT) on the treatment of relapsed/refractory multiple myeloma (RRMM) with chimeric antigen receptor T cell (CAR-T) therapy. Methods: A retrospective cohort study. The clinical data of 168 patients with RRMM who underwent CAR-T therapy at the Department of Hematology, Xuzhou Medical University Hospital from 3 January 2020 to 13 September 2022 were analyzed. Patients were classified into a transplantation group (TG; n=47) and non-transplantation group (NTG; n=121) based on whether or not they had undergone ASCT previously. The objective response rate (ORR), progression-free survival (PFS), overall survival (OS) and the levels of CD3, CD4, CD8, CD19, CD56 and natural killer (NK) cells before CAR-T infusion were analyzed by χ2 test, Kaplan-Meier method and independent sample t-test. Results: Among 168 patients with RRMM, 98 (58.3%) were male. The median age of onset was 57 (range 30-70) years. After CAR-T therapy, the ORR of patients was 89.3% (92/103) in the NTG and 72.9% (27/73) in the TG. The ORR of the NTG was better than that of the TG (χ2=5.71, P=0.017). After 1 year of CAR-T therapy, the ORR of the NTG was 78.1% (75/96), and that of the TG was 59.4% (19/32). The ORR of the NTG was better than that of the TG (χ2=4.32, P=0.038). The median OS and PFS in the NTG were significantly longer than those in the TG (OS, 30 vs. 20 months; PFS, 26 vs. 12 months; both P<0.05). The CD4 level before CAR-T infusion in the TG was significantly lower than that in the NTG (25.65±13.56 vs. 32.64±17.21; t=-2.15, P=0.034), and there were no significant differences in the counts of CD3, CD8, CD19, CD56, and NK cells between the TG and NTG (all P>0.05). Conclusion: Among patients suffering from RRMM who received CAR-T therapy, patients who did not receive ASCT had significantly better outcomes than those who had received ASCT previously, which may have been related to the CD4 level before receiving CAR-T therapy.

Classification of coma/brain-death EEG dataset based on one-dimensional convolutional neural network

Electroencephalography (EEG) evaluation is an important step in the clinical diagnosis of brain death during the standard clinical procedure. The processing of the brain-death EEG signals acquisition always carried out in the Intensive Care Unit (ICU). The electromagnetic environmental noise and prescribed sedative may erroneously suggest cerebral electrical activity, thus effecting the presentation of EEG signals. In order to accurately and efficiently assist physicians in making correct judgments, this paper presents a band-pass filter and threshold rejection-based EEG signal pre-processing method and an EEG-based coma/brain-death classification system associated with One Dimensional Convolutional Neural Network (1D-CNN) model to classify informative brain activity features from real-world recorded clinical EEG data. The experimental result shows that our method is well performed in classify the coma patients and brain-death patients with the classification accuracy of 99.71%, F1-score of 99.71% and recall score of 99.51%, which means the proposed model is well performed in the coma/brain-death EEG signals classification task. This paper provides a more straightforward and effective method for pre-processing and classifying EEG signals from coma/brain-death patients, and demonstrates the validity and reliability of the method. Considering the specificity of the condition and the complexity of the EEG acquisition environment, it presents an effective method for pre-processing real-time EEG signals in clinical diagnoses and aiding the physicians in their diagnosis, with significant implications for the choice of signal pre-processing methods in the construction of practical brain-death identification systems.

Machine to brain: facial expression recognition using brain machine generative adversarial networks

The human brain can effectively perform Facial Expression Recognition (FER) with a few samples by utilizing its cognitive ability. However, unlike the human brain, even the well-trained deep neural network is data-dependent and lacks cognitive ability. To tackle this challenge, this paper proposes a novel framework, Brain Machine Generative Adversarial Networks (BM-GAN), which utilizes the concept of brain's cognitive ability to guide a Convolutional Neural Network to generate LIKE-electroencephalograph (EEG) features. More specifically, we firstly obtain EEG signals triggered from facial emotion images, then we adopt BM-GAN to carry out the mutual generation of image visual features and EEG cognitive features. BM-GAN intends to use the cognitive knowledge learnt from EEG signals to instruct the model to perceive LIKE-EEG features. Thereby, BM-GAN has a superior performance for FER like the human brain. The proposed model consists of VisualNet, EEGNet, and BM-GAN. More specifically, VisualNet can obtain image visual features from facial emotion images and EEGNet can obtain EEG cognitive features from EEG signals. Subsequently, the BM-GAN completes the mutual generation of image visual features and EEG cognitive features. Finally, the predicted LIKE-EEG features of test images are used for FER. After learning, without the participation of the EEG signals, an average classification accuracy of 96.6 % is obtained on Chinese Facial Affective Picture System dataset using LIKE-EEG features for FER. Experiments demonstrate that the proposed method can produce an excellent performance for FER.

Chromosome-level genome assembly and characterization of the Calophaca sinica genome

Calophaca sinica is a rare plant endemic to northern China which belongs to the Fabaceae family and possesses rich nutritional value. To support the preservation of the genetic resources of this plant, we have successfully generated a high-quality genome of C. sinica (1.06 Gb). Notably, transposable elements (TEs) constituted ~73% of the genome, with long terminal repeat retrotransposons (LTR-RTs) dominating this group of elements (~54% of the genome). The average intron length of the C. sinica genome was noticeably longer than what has been observed for closely related species. The expansion of LTR-RTs and elongated introns emerged had the largest influence on the enlarged genome size of C. sinica in comparison to other Fabaceae species. The proliferation of TEs could be explained by certain modes of gene duplication, namely, whole genome duplication (WGD) and dispersed duplication (DSD). Gene family expansion, which was found to enhance genes associated with metabolism, genetic maintenance, and environmental stress resistance, was a result of transposed duplicated genes (TRD) and WGD. The presented genomic analysis sheds light on the genetic architecture of C. sinica, as well as provides a starting point for future evolutionary biology, ecology, and functional genomics studies centred around C. sinica and closely related species.

Administration of Atosiban, an oxytocin receptor antagonist, ameliorates autistic-like behaviors in a female rat model of valproic acid-induced autism

Autism spectrum disorder (ASD) is a pervasive developmental disorder with gender differences. Oxytocin (OXT) is currently an important candidate drug for autism, but the lack of data on female autism is a big issue. It has been reported that the effect of OXT is likely to be different between male and female ASD patients. In the study, we specifically explored the role of the OXT signaling pathway in a VPA-induced female rat's model of autism. The data showed that there was an increase of either oxytocin or its receptor expressions in both the hippocampus and the prefrontal cortex of VPA-induced female offspring. To determine if the excess of OXT signaling contributed to autism symptoms in female rats, exogenous oxytocin and oxytocin receptor antagonists Atosiban were used in the experiment. It was found that exogenous oxytocin triggered autism-like behaviors in wild-type female rats by intranasal administration. More interestingly, several autism-like deficits including social interaction, anxiety, and repeat stereotypical sexual behavior in the VPA female offspring were significantly attenuated by oxytocin receptor antagonists Atosiban. Moreover, Atosiban also effectively improved the synaptic plasticity impairment induced by VPA in female offspring. Our results suggest that oxytocin receptor antagonists significantly improve autistic-like behaviors in a female rat model of valproic acid-induced autism.

Resolvin D1 inhibits T follicular helper cell expansion in systemic lupus erythematosus

OBJECTIVE

Resolvin D1 (RvD1) is one of the specialized pro-resolving lipid mediators, which control inflammation resolution and regulate immune responses. Previous research showed that RvD1 could block the progression of systemic lupus erythematosus (SLE). However, the detailed mechanism remains to be fully understood.

METHOD

Plasma RvD1 levels, and proportions of T follicular helper cells (Tfh cells) were measured in SLE patients and healthy controls. Plasma RvD1 levels and proportions of Tfh cells were quantitated in an MRL/lpr mouse model of lupus treated with RvD1. Naïve CD4+ T cells were purified from MRL/lpr mice to study the effect of RvD1 on Tfh cell differentiation in vitro.

RESULTS

In patients, there were significant negative correlations between plasma RvD1 levels and Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score, as well as between plasma RvD1 and anti-double-stranded DNA antibody levels, and numbers of peripheral Tfh cells and plasma cells. In MRL/lpr mice, the expected amelioration of disease phenotype and inflammatory response with RvD1 treatment correlated with decreased percentages of Tfh cells and plasma cells. In addition, the differentiation and proliferation of Tfh cells were markedly suppressed by RvD1 in vitro.

CONCLUSION

RvD1 may control SLE progression through the suppression of Tfh cell differentiation and subsequent inhibition of B-cell responses.

[Clinical features and surgical treatment of right cardiac system tumors]

A total of 25 patients with right cardiac system tumors in the Department of Cardiac Surgery, Beijing Anzhen Hospital from January 2012 to October 2022 were retrospectively included in the study. The preoperative data, and information of surgical treatment and perioperative management on these patients were analyzed and summarized. One patient developed pulmonary embolism and died before surgery, and the other 24 patients (16 males and 8 females) received surgical treatment, with an average age of (44.7±10.2) years (24-74 years). Nine patients were diagnosed with malignant tumors. Among the 24 patients who received surgical treatment, two patients died during the perioperative period, in-situ tumor recurrence was seen in three patients within about 1 year after surgery (two patients died without surgery, and one patient died 3 months after surgery), two patients had distant metastasis, and 17 patients had a good prognosis. Right cardiac system tumors are rare, with a high malignant rate, and the clinical manifestations vary greatly. Active surgical intervention is found to be effective, and the prognosis is closely related to the pathological type and extent of tumor invasion.

Improving image quality of triple-low-protocol renal artery CT angiography with deep-learning image reconstruction: a comparative study with standard-dose single-energy and dual-energy CT with adaptive statistical iterative reconstruction

AIM

To investigate the improvement in image quality of triple-low-protocol (low radiation, low contrast medium dose, low injection speed) renal artery computed tomography (CT) angiography (RACTA) using deep-learning image reconstruction (DLIR), in comparison with standard-dose single- and dual-energy CT (DECT) using adaptive statistical iterative reconstruction-Veo (ASIR-V) algorithm.

MATERIALS AND METHODS

Ninety patients for RACTA were divided into different groups: standard-dose single-energy CT (S group) using ASIR-V at 60% strength (60%ASIR-V), DECT (DE group) with 60%ASIR-V including virtual monochromatic images at 40 keV (DE40 group) and 70 keV (DE70 group), and the triple-low protocol single-energy CT (L group) with DLIR at high level (DLIR-H). The effective dose (ED), contrast medium dose, injection speed, standard deviation (SD), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal aorta (AA), and left/right renal artery (LRA, RRA), and subjective scores were compared among the different groups.

RESULTS

The L group significantly reduced ED by 37.6% and 31.2%, contrast medium dose by 33.9% and 30.5%, and injection speed by 30% and 30%, respectively, compared to the S and DE groups. The L group had the lowest SD values for all arteries compared to the other groups (p<0.001). The SNR of RRA and LRA in the L group, and the CNR of all arteries in the DE40 group had highest value compared to others (p<0.05). The L group had the best comprehensive score with good consistency (p<0.05).

CONCLUSIONS

The triple-low protocol RACTA with DLIR-H significantly reduces the ED, contrast medium doses, and injection speed, while providing good comprehensive image quality.

Coronary microvascular dysfunction: prevalence and aetiology in patients with suspected myocardial ischaemia

AIM

To evaluate the prevalence, aetiology, and corresponding morbidity of coronary microvascular dysfunction (CMD) in patients with suspected myocardial ischaemia.

MATERIALS AND METHODS

The present study included 115 patients with suspected myocardial ischaemia who underwent stress perfusion cardiac magnetic resonance imaging. CMD was assessed visually based on the myocardial perfusion results. The CMR-derived myocardial perfusion reserve index (MPRI) and left ventricular (LV) strain parameters obtained using the post-processing software CVI42 were employed to evaluate LV myocardial perfusion and deformation. LV strain parameters included global longitudinal, circumferential, and radial strain (GLS, GCS, and GRS), global systolic/diastolic longitudinal, circumferential, and radial strain rates (SLSR, SCSR, SRSR, DLSR, DCSR, and DRSR).

RESULTS

Of the 115 patients, 12 patients were excluded and 103 patients were finally included in the study. CMD was observed in 79 % (81 patients, aged 53 ± 12 years) of patients. Regarding aetiology, 91 (88 %) patients had non-obstructive coronary artery disease (CAD), eight (8 %) had obstructive CAD, and four (4 %) had hypertrophic cardiomyopathy (HCM). The incidence of CMD was highest (100 %) in patients with HCM, followed by those with non-obstructive CAD (up to 79 %). There were no statistical differences between CMD and non-CMD groups in GCS, GRS, GLS, SRSR, SCSR, SLSR, DCSR, DRSR and DLSR.

CONCLUSION

The incidence of CMD was higher in patients with signs and symptoms of ischaemia. CMD occurred with non-obstructive CAD, obstructive CAD, and HCM, with the highest prevalence of CMD in HCM.

[Quantitative analysis of risk assessment indicators for re-introduction of imported malaria in China]

OBJECTIVE

To quantitatively analyze the risk indicators of re-introduction of imported malaria in China and their weighting coefficients, so as to investigate the difference in the contribution of risk indicators included in the current risk assessment framework for re-introduction of imported malaria in China to the risk assessment of re-introduction of imported malaria.

METHODS

Publications pertaining to the risk assessment framework for re-introduction of imported malaria in China that reported the risk indicators and their weighting coefficients were retrieved in PubMed, Web of Science, CNKI, Wanfang Data, and VIP with terms of "malaria", "re-introduction/re-transmission/re-establishment", "risk assessment/risk evaluation/risk prediction" from the inception of the database through 3 August 2023, and literature search was performed in Google Scholar to ensure the comprehensiveness of the retrieval. Basic characteristics of included studies were extracted using pre-designed information extraction forms by two investigators, and data pertaining to risk indicators of re-introduction of imported malaria were cross-checked by these two investigators. The risk indicators included in the risk assessment framework for re-introduction of imported malaria in China and their weighting coefficients were visualized with the Nightingale's rose diagrams using the software R 4.2.1, and the importance of risk indictors was evaluated with the frequency of risk indicators included in the risk assessment framework and the ranking of weighting coefficients of risk indicators. In addition, the capability of risk indicators screened by different weighting methods was compared by calculating the ratio of the maximum to the minimum of the weighting coefficients of the risk indicators screened by different weighting methods.

RESULTS

A total of 2 138 publications were retrieved, and following removal of duplications and screening, a total of 8 publications were included in the final analysis. In these 8 studies, 8 risk assessment frameworks for re-introduction of imported malaria in China and 52 risk indicators of re-introduction of imported malaria were reported, in which number of imported malaria cases (n = 8) and species of malaria vectors were more frequently included in the risk assessment frameworks (n = 8), followed by species of imported malaria parasites (n = 6) and population density of local malaria vectors (n = 6), and species of local malaria vectors (n = 6), number of imported malaria cases (n = 5) and species of imported malaria parasites had the three highest weighting coefficients (n = 4). The weighting methods included expert scoring method, combination of expert scoring method and analytic hierarchy process, and combination of expert scoring method and entropy weight method in these 8 studies, and the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by the expert scoring method were 1.143 to 2.241, while the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by combination of the expert scoring method and analytic hierarchy process were 34.970 to 162.000.

CONCLUSIONS

Number of imported malaria cases, species of imported malaria parasites, species of local malaria vectors and population density of local malaria vectors are core indicators in the current risk assessment framework for re-introduction of imported malaria in China. Combination of the expert scoring method and analytic hierarchy process is superior to the expert scoring method alone for weighting the risk indicators.

Genetic, haplotype and phylogenetic analysis of Ligula intestinalis by using mt-CO1 gene marker: ecological implications, climate change and eco-genetic diversity

Abstract Ligula intestinalis is a cestode parasite that affects freshwater fish in different countries of the world. The current study aims to reveal the phylogenetic, genetic and haplotype diversity of mt-CO1 gene sequences sent to the NCBI database from different countries by using in-silico analysis. The 105 mt-CO1 (371 bp) gene sequences of L. intestinalis obtained from NCBI were used for bioinformatics analyses. Sequences were subjected to phylogenetic and haplotype analysis. As a result of the haplotype analysis of L. intestinalis, 38 haplotypes were obtained from 13 different countries. Hap24 constituted 44.76% of the obtained haplotype network. Changes in nucleotides between haplotypes occurred at 1-84 different points. China and Turkey have highest fixation index (Fst) values of 0.59761, while the lowest (-0.10526) was found between Russia and Turkey. This study provides a baseline for future studies on extensive scale on the epidemiology, ecological aspects, distribution pattern, transmission dynamics and population dispersion of L. intestinalis worldwide.

[Analysis of the prevalence of dyslipidemia and correlative factors in Tajik population in Pamir Plateau of Xinjiang]

Objective: To investigate the prevalence of dyslipidemia and the level of blood lipids among Tajik people in Pamir Plateau, Xinjiang, and explore the related factors of dyslipidemia. Methods: It is a retrospective cross-sectional study. A multi-stage cluster random sampling survey was conducted among 5 635 Tajiks over 18 years old in Tashkorgan Tajik Autonomous County, Xinjiang Province from May to October 2021. Data were collected through questionnaire survey (general information, medical history, and personal history), physical examination (height, weight, waist, and blood pressure) and blood test (total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density cholesterol (HDL-C)) to analyze the dyslipidemia and its risk factors among Tajiks. Results: The age of Tajik participants was (41.9±15.0) years, including 2 726 males (48.4%). The prevalence of borderline high TC, high LDL-C and high TG levels were 17.2%, 14.7% and 8.9%, respectively. The prevalence of high TC, high LDL-C, high TG and low HDL-C were 4.1%, 4.9%, 9.4% and 32.4%, respectively, and the prevalence of dyslipidemia was 37.0%. There is a positive correlation between male,higher education level, higher body mass index (BMI) value,waist circumference, living in town, smoking and dyslipidemia. Conclusions: The low prevalence of high TC, high LDL-C, high TG and high prevalence of low HDL-C was a major characteristic of Tajik people in Pamir Plateau of Xinjiang. The lower rates of overweight and obesity may be one of the reasons for the lower prevalence of dyslipidemia among Tajik.

Decoding Multi-Brain Motor Imagery From EEG Using Coupling Feature Extraction and Few-Shot Learning

Electroencephalography (EEG)-based motor imagery (MI) is one of brain computer interface (BCI) paradigms, which aims to build a direct communication pathway between human brain and external devices by decoding the brain activities. In a traditional way, MI BCI replies on a single brain, which suffers from the limitations, such as low accuracy and weak stability. To alleviate these limitations, multi-brain BCI has emerged based on the integration of multiple individuals' intelligence. Nevertheless, the existing decoding methods mainly use linear averaging or feature integration learning from multi-brain EEG data, and do not effectively utilize coupling relationship features, resulting in undesired decoding accuracy. To overcome these challenges, we proposed an EEG-based multi-brain MI decoding method, which utilizes coupling feature extraction and few-shot learning to capture coupling relationship features among multi-brains with only limited EEG data. We performed an experiment to collect EEG data from multiple persons who engaged in the same task simultaneously and compared the methods on the collected data. The comparison results showed that our proposed method improved the performance by 14.23% compared to the single-brain mode in the 10-shot three-class decoding task. It demonstrated the effectiveness of the proposed method and usability of the method in the context of only small amount of EEG data available.

Multivariate analysis of milk metabolite measures shows potential for deriving new resilience phenotypes

In a context of growing interest in breeding more resilient animals, a noninvasive indicator of resilience would be very valuable. We hypothesized that the time-course of concentrations of several milk metabolites through a short-term underfeeding challenge could reflect the variation of resilience mechanisms to such a challenge. We submitted 138 one-year-old primiparous goats, selected for extreme functional longevity (i.e., productive longevity corrected for milk yield [60 low longevity line goats and 78 high longevity line goats]), to a 2-d underfeeding challenge during early lactation. We measured the concentration of 13 milk metabolites and the activity of 1 enzyme during prechallenge, challenge, and recovery periods. Functional principal component analysis summarized the trends of milk metabolite concentration over time efficiently without preliminary assumptions concerning the shapes of the curves. We first ran a supervised prediction of the longevity line of the goats based on the milk metabolite curves. The partial least square analysis could not predict the longevity line accurately. We thus decided to explore the large overall variability of milk metabolite curves with an unsupervised clustering. The large year × facility effect on the metabolite concentrations was precorrected for. This resulted in 3 clusters of goats defined by different metabolic responses to underfeeding. The cluster that showed higher β-hydroxybutyrate, cholesterol, and triacylglycerols increase during the underfeeding challenge was associated with poorer survival compared with the other 2 clusters. These results suggest that multivariate analysis of noninvasive milk measures show potential for deriving new resilience phenotypes.

Phase I dose escalation and expansion study of golidocitinib, a highly selective JAK1 inhibitor, in relapsed or refractory peripheral T-cell lymphomas

BACKGROUND

Relapsed or refractory peripheral T-cell lymphomas (r/r PTCLs) are a group of rare and aggressive diseases that lack effective therapies. Constitutive activation of the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway is reported to be associated with PTCLs. Golidocitinib is an oral, potent JAK1 selective inhibitor evaluated in a phase I/II multinational study in patients with r/r PTCLs.

PATIENTS AND METHODS

Patients with r/r PTCLs were eligible. The primary objectives were to assess safety and tolerability of golidocitinib and to define its recommended phase II dose (RP2D). The secondary objectives were to evaluate its antitumor activity and pharmacokinetics (PK).

RESULTS

A total of 51 patients were enrolled and received golidocitinib treatment at 150 or 250 mg once daily (QD). The median prior lines of therapies were 2 (range: 1-8). Golidocitinib was tolerated at both doses tested, while a higher incidence of serious adverse events and dose modifications at 250 mg were observed. The most common grade ≥3 drug-related treatment-emergent adverse events were neutropenia (27.5%) and thrombocytopenia (11.8%). An objective response rate of 39.2% and a complete response rate of 21.6% were observed. With median follow-up time of 14.7 and 15.9 months, the median duration of response (DoR) and progression-free survival were 8.0 and 3.3 months, respectively. Based on these data, 150 mg QD was defined as the RP2D. Golidocitinib demonstrated a favorable PK profile as an oral agent. Biomarker analysis suggested a potential correlation between JAK/STAT pathway aberrations and clinical activity of golidocitinib.

CONCLUSIONS

In this phase I study, golidocitinib demonstrated an acceptable safety profile and encouraging antitumor efficacy in heavily pretreated patients with r/r PTCLs. These results support the initiation of the multinational pivotal study in patients with r/r PTCLs.

[Observation of liver indexes in patients with relapsed/refractory multiple myeloma treated with CAR-T-cells based on BCMA]

Objective: To observe the characteristics of the evolution of liver indexes in patients with relapsed/refractory multiple myeloma (RRMM) treated with CAR-T-cells based on BCMA. Methods: Retrospective analysis was performed of patients with RRMM who received an infusion of anti-BCMA CAR-T-cells and anti-BCMA combined with anti-CD19 CAR-T-cells at our center between June 1, 2019, and February 28, 2023. Clinical data were collected to observe the characteristics of changes in liver indexes such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and direct bilirubin (DBIL) in patients, and its relationship with cytokine-release syndrome (CRS) . Results: Ninety-two patients were included in the analysis, including 41 patients (44.6%) in the group receiving a single infusion of anti-BCMA CAR-T-cells, and 51 patients (55.4%) in the group receiving an infusion of anti-BCMA combined with anti-CD19 CAR-T-cells. After infusing CAR-T-cells, 31 patients (33.7%) experienced changes in liver indexes at or above grade 2, which included 20 patients (21.7%) with changes in one index, five patients (5.4%) with changes in two indexes, and six patients (6.5%) with changes in three or more indexes. The median time of peak values of ALT and AST were d17 and d14, respectively, and the median duration of exceeding grade 2 was 5.0 and 3.5 days, respectively. The median time of peak values of TBIL and DBIL was on d19 and d21, respectively, and the median duration of exceeding grade 2 was 4.0 days, respectively. The median time of onset of CRS was d8, and the peak time of fever was d9. The ALT, AST, and TBIL of patients with CRS were higher than those of patients without CRS (P=0.011, 0.002, and 0.015, respectively). CRS is an independent factor that affects ALT and TBIL levels (OR=19.668, 95% CI 18.959-20.173, P=0.001). The evolution of liver indexes can be reversed through anti-CRS and liver-protection treatments, and no patient died of liver injury. Conclusions: In BCMA-based CAR-T-cell therapy for RRMM, CRS is an important factor causing the evolution of liver indexes. The evolution of liver indexes after CAR-T-cell infusion is transient and reversible after treatment.

30 Gy vs. 45 Gy Consolidative Thoracic Radiation (cTRT) for Extensive Stage Small Cell Lung Cancer (ES-SCLC): A Multicenter, Randomized, Phase 3 Trial

PURPOSE/OBJECTIVE(S)

Consolidative thoracic radiotherapy (cTRT) showed potential benefit to extensive stage small cell lung cancer (ES-SCLC). However, the optimum dose of cTRT is unknown. The purpose of this randomized trial was to compare the effect of 45 Gy in 15 fractions with 30 Gy in 10 fractions cTRT in ES-SCLC.

MATERIALS/METHODS

This phase III, randomized trial was conducted in 12 public hospitals in China. Eligible patients with pathologically confirmed ES-SCLC who responded to 4-6 cycles of etoposide plus cisplatin (EP) or carboplatin (EC) chemotherapy were randomized 1:1 to receive either 30 Gy in 10 fractions or 45 Gy in 15 fractions cTRT. The primary outcome was 2-year overall survival (OS). Secondary outcomes included 2-year progression-free survival (PFS), 2-year local control (LC) and radiation treatment related toxicity. The primary objective was to detect an OS improvement in 45 Gy cTRT group at 2 years from 13% to 26% assuming a two-sided a = 0.05 and power of 85%, with a planned sample size of 186 patients. This trial was registered with Clinical Trials.gov, number NCT02675088.

RESULTS

Between January 15, 2016, and September 20, 2022, 90 patients were randomly assigned either 30 Gy in 10 fractions (n = 50) or 45 Gy in 15 fractions (n = 40) cTRT group. Recruitment to the trial closed early due to slow accrual since first-line chemoimmunotherapy has become the new standard of care for ES-SCLC. The median age of patients was 58 years, 87.8% were male, 76.7% had a smoking history, 95.6% received IMRT, and 58.9% received prophylactic cranial irradiation. At a median follow-up of 39.9 months (IQR 27.2-59.2), there was no significant difference in the 2-year OS between the 45 Gy group and the 30 Gy group, at 43.4% (95% CI 29.3%-64.3%) and 40.0% (95% CI 27.9%-59.1%), respectively (log-rank p = 0.62; HR 1.13 [95% CI 0.69-1.84]). The 2-year PFS was 12.1% (95% CI 4.3%-33.8%) in the 45 Gy group and 9.0% (95% CI 3.2%-25.2%) in the 30 Gy group (log-rank p = 0.25, HR 0.76(95% CI [0.478-1.22]). There were also no significant differences in locoregional recurrence free survival (log-rank p = 0.75; HR 0.888 [95% CI 0.423-1.863]) and distant metastasis free survival (log-rank p = 0.95; HR 1.015 [95% CI 0.624-1.651]) between two groups. No grade 5 toxicity was observed in both groups. Patients treated with higher cTRT dose presented with increased incidence of grade 3+ radiation pneumonitis (10% vs 2%) and hematological toxicity (20% vs 12.5%).

CONCLUSION

This randomized trial did not find a higher probability of survival improvement in patients with ES-SCLC receiving cTRT of 45 Gy in 15 fractions compared with 30 Gy in 10 fractions. In contrast, there was an increase in toxicity, especially radiation pneumonitis. Additional randomized studies investigating the role of cTRT in ES-SCLC after a response to chemoimmunotherapy are warranted.

Ceruloplasmin regulating fibrosis in orbital fibroblasts provides a novel therapeutic target for Graves' orbitopathy

PURPOSE

In diagnosing the pathogenesis of Graves' orbitopathy (GO), there is a growing interest in fibrosis generated by orbital fibroblasts (OFs); nevertheless, the involvement of ceruloplasmin (CP) in OFs remains unknown.

METHODS

Differentially expressed genes (DEGs) were identified through bioinformatic analysis. OFs were isolated from orbital tissue and identified with immunofluorescent staining. The levels of DEGs were validated in GO tissue samples and TGF-β-challenged OFs, and CP was selected for the following laboratory investigations. CP overexpression or knockdown was achieved, and cell viability and fibrosis-associated proteins were investigated to assess the cell phenotype and function. Signaling pathways were subsequently investigated to explore the mechanism of CP function in OFs.

RESULTS

CP and cathepsin C (CTSC) are two overlapped DEGs in GSE58331 and GSE105149. OFs were isolated and identified through fibrotic biomarkers. CP and CTSC were downregulated in GO tissue samples and TGF-β-challenged OFs. CP overexpression or knockdown was achieved in OFs by transducing a CP overexpression vector or small interfering RNA against CP (si1-CP or si2-CP) and verified using a qRT-PCR. CP overexpression inhibited cell viability and reduced the levels of α-SMA, vimentin, fibronectin, and collagen I, whereas CP knockdown exerted opposite effects on OFs. CP overexpression inhibited the phosphorylation of Smad3, Erk1/2, p38, JNK, and AKT; conversely, CP knockdown exerted opposite effects on the phosphorylation of factors mentioned above.

CONCLUSION

CP was downregulated in GO and suppressed the expression of fibrosis-associated proteins in both GO and normal OFs. CP might serve as a promising therapeutic agent in the treatment regimens for GO.

Intercellular Mechanisms of Therapeutic Resistance at the Tumor-Stromal Interface Using Ultra High-Plex Single-Cell Spatial Transcriptomics and Genetically-Engineered Tumoroids

PURPOSE/OBJECTIVE(S)

There is a major gap in knowledge regarding how intercellular interactions in the tumor microenvironment (TME) mediate therapeutic resistance. Achievement of this goal has been limited by a lack of (1) spatial context in dissociated single-cell methods; (2) single-cell resolution in spatial profiling approaches; (3) high quality data and yield with FFPE patient specimens; and (4) computational methods for ligand-receptor analyses that consider both gene expression and spatial coordinates.

MATERIALS/METHODS

We developed an innovative spatial biology paradigm that combines cutting-edge experimental and computational methods to enable high-resolution, spatially-guided discovery of critical mediators of therapeutic resistance. We applied this approach to dissect the single-cell spatial transcriptomic landscape of untreated vs. chemoradiotherapy-treated primary human pancreatic ductal adenocarcinoma (PDAC; n = 21) using ultra-high plex spatial molecular imaging (SMI) optimized for high-sensitivity, subcellular detection of up to 6000 gene transcripts in FFPE sections-an order of magnitude greater than contemporary methods.

RESULTS

We recovered over 1,000,000 high-quality single cells in situ representing more than 20 distinct cell types, including epithelial, immune, endothelial, endocrine, and diverse stromal cells. We developed an optimal transport-based computational method to infer cell-cell communication at the cancer-stromal interface. Treatment with chemoradiotherapy was associated with the largest increase in fibroblast-malignant interactions. Comparing the SMI data with orthogonal single-nucleus RNA-sequencing and digital spatial profiling data, we identified CLCF1-CNTFR as the fibroblast-malignant interaction most associated with resistance to chemoradiotherapy in PDAC. CLCF1 is a gp130-family cytokine that activates Jak-STAT signaling and acts as a potent neurotrophic factor. Notably, the CLCF1-CNTRF (fibroblast-malignant) interaction has prominent pro-oncogenic effects in lung adenocarcinoma and an engineered CNTFR decoy receptor with therapeutic potential has been developed. To functionally validate the role of the CLCF1-CNTFR (fibroblast-malignant) interaction in mediating resistance to cytotoxic therapy, we created CRISPR-engineered cancer-fibroblast tumoroids and modulated expression of this ligand-receptor pair. Pancreatic cancer cell viability in the presence of 5-fluorouracil was better maintained with increased CLCF1-CNTFR signaling.

CONCLUSION

In this study, we integrated ultra high-plex single-cell spatial transcriptomics, optimal transport ligand-receptor predictions, and genetically-engineered stromal tumoroids to identify and validate CLCF1-CNTFR as an important intercellular mechanism of resistance to chemoradiotherapy in PDAC-pioneering a paradigm for translating single-cell spatial biology to clinical oncology.

Brain-Machine Coupled Learning Method for Facial Emotion Recognition

Neural network models of machine learning have shown promising prospects for visual tasks, such as facial emotion recognition (FER). However, the generalization of the model trained from a dataset with a few samples is limited. Unlike the machine, the human brain can effectively realize the required information from a few samples to complete the visual tasks. To learn the generalization ability of the brain, in this article, we propose a novel brain-machine coupled learning method for facial emotion recognition to let the neural network learn the visual knowledge of the machine and cognitive knowledge of the brain simultaneously. The proposed method utilizes visual images and electroencephalogram (EEG) signals to couple training the models in the visual and cognitive domains. Each domain model consists of two types of interactive channels, common and private. Since the EEG signals can reflect brain activity, the cognitive process of the brain is decoded by a model following reverse engineering. Decoding the EEG signals induced by the facial emotion images, the common channel in the visual domain can approach the cognitive process in the cognitive domain. Moreover, the knowledge specific to each domain is found in each private channel using an adversarial strategy. After learning, without the participation of the EEG signals, only the concatenation of both channels in the visual domain is used to classify facial emotion images based on the visual knowledge of the machine and the cognitive knowledge learned from the brain. Experiments demonstrate that the proposed method can produce excellent performance on several public datasets. Further experiments show that the proposed method trained from the EEG signals has good generalization ability on new datasets and can be applied to other network models, illustrating the potential for practical applications.

Use of peripheral blood eosinophils to guide post-operative glucocorticoid therapy in patients with chronic rhinosinusitis with nasal polyps: a randomised, controlled trial

OBJECTIVE

This study aimed to explore the utility of the eosinophil percentage in peripheral blood for guiding post-operative glucocorticoid therapy in patients with chronic rhinosinusitis with nasal polyps.

METHODS

Forty-four patients with chronic rhinosinusitis with nasal polyps underwent functional endoscopic sinus surgery and were randomly divided into two groups. Patients in the standard treatment group used oral and nasal spray glucocorticoids. In the biomarker treatment group, patients with peripheral blood eosinophil percentage values less than 3.05 per cent did not receive glucocorticoid treatment, whereas patients with values 3.05 per cent or above were part of the standard treatment group. Visual Analogue Scale, Sino-Nasal Outcome Test-22 scores, endoscopic Lund-Kennedy scores, eosinophils, interleukin-5 and eosinophil cationic protein in peripheral blood, and nasal secretions were measured.

RESULTS

After functional endoscopic sinus surgery, the Visual Analogue Scale, Sino-Nasal Outcome Test-22 and Lund-Kennedy scores were significantly reduced in both groups; there were no significant differences in those indicators between the groups during the three follow-up visits.

CONCLUSION

Peripheral blood eosinophil percentage offers a potential biomarker to guide post-operative glucocorticoid therapy in patients with chronic rhinosinusitis with nasal polyps.

[Risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on the machine learning]

OBJECTIVE

To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province.

METHODS

Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency.

RESULTS

A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%).

CONCLUSIONS

Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.

[Prevalence and genotyping of Cryptosporidium spp. and Giardia lamblia in dogs and cats from a pet hospital in Shanghai Municipality]

OBJECTIVE

To investigate the prevalence and genotypes of Cryptosporidium spp. and Giardia lamblia in dogs and cats from a pet hospital in Shanghai Municipality.

METHODS

A total of 145 fresh fecal samples were collected from pet dogs and cats in a pet hospital in Shanghai Municipality during the period from November 2021 to June 2022, including 99 dog fecal samples and 46 cat fecal samples. The small subunit ribosomal ribonucleic acid (SSU rRNA) gene of Cryptosporidium and the triose phosphate isomerase (TPI) gene of G. lamblia were amplified using nested PCR assay, and the positive amplification products were sequenced from both directions. The sequence assembly was performed using the software Clustal X 2.1, and sequence alignment was conducted using BLAST. A phylogenetic tree was created with the Neighbor-Joining method using MEGA 11.0 to identify parasite species or genotype.

RESULTS

The overall prevalence of Cryptosporidium and G. lamblia was 20.00% (29/145) in 145 pet dog and cat fecal samples, with the prevalence of 0.69% (1/145) and 19.31% (28/145) in Cryptosporidium and G. lamblia, respectively. G. lamblia was only detected in dog fecal samples, with prevalence of 18.18% (18/99), while the detection rates of Cryptosporidium and G. lamblia were 2.17% (1/46) and 21.74% (10/46) in cat fecal samples. Nucleotide sequence analysis showed that one Cryptosporidium positive sample was characterized as C. felis, and 28 G. lamblia positive samples were all characterized as Giardia assemblage A, which showed 100% sequence homology with human isolates of Giardia. Phylogenetic analysis revealed that the sequences obtained in this study belonged to the same branch with the reported Giardia assemblage A.

CONCLUSIONS

Cryptosporidium and G. lamblia infection was prevalent in pet dogs and cats from the study pet hospital in Shanghai Municipality, and there is a zoonotic risk for the species and genotype. Intensified surveillance of Cryptosporidium and Giardia infection is recommended in pets and their owners, and improved management of pet keeping is required.