Speechformer-CTC: Sequential Modeling of Depression Detection with Speech Temporal Classification.

Speech-based automatic depression detection systems have been extensively explored over the past few years. Typically, each speaker is assigned a single label (Depressive or Non-depressive), and most approaches formulate depression detection as a speech classification task without explicitly considering the non-uniformly distributed depression pattern within segments, leading to low generalizability and robustness across different scenarios. However, depression corpora do not provide fine-grained labels (at the phoneme or word level) which makes the dynamic depression pattern in speech segments harder to track using conventional frameworks. To address this, we propose a novel framework, Speechformer-CTC, to model non-uniformly distributed depression characteristics within segments using a Connectionist Temporal Classification (CTC) objective function without the necessity of input-output alignment. Two novel CTC-label generation policies, namely the Expectation-One-Hot and the HuBERT policies, are proposed and incorporated in objectives on various granularities. Additionally, experiments using Automatic Speech Recognition (ASR) features are conducted to demonstrate the compatibility of the proposed method with content-based features. Our results show that the performance of depression detection, in terms of Macro F1-score, is improved on both DAIC-WOZ (English) and CONVERGE (Mandarin) datasets. On the DAIC-WOZ dataset, the system with HuBERT ASR features and a CTC objective optimized using HuBERT policy for label generation achieves 83.15% F1-score, which is close to state-of-the-art without the need for phoneme-level transcription or data augmentation. On the CONVERGE dataset, using Whisper features with the HuBERT policy improves the F1-score by 9.82% on CONVERGE1 (in-domain test set) and 18.47% on CONVERGE2 (out-of-domain test set). These findings show that depression detection can benefit from modeling non-uniformly distributed depression patterns and the proposed framework can be potentially used to determine significant depressive regions in speech utterances.

Mesenchymal stem cell-derived extracellular vesicles targeting irradiated intestine exert therapeutic effects.

Background: Radiation-induced intestinal injuries are common in patients with pelvic or abdominal cancer. However, these injuries are currently not managed effectively. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have been extensively used in regenerative medicine. However, the results of MSC-EVs in the repair of radiation-induced intestinal damage have been unsatisfactory. We here investigated the nanotherapeutic functions of MSC-EVs in radiation-induced intestinal injury. Methods: We visualized the biodistribution and trend of MSC-EVs through in vivo imaging. A radiation-induced intestinal injury model was constructed, and the therapeutic effect of MSC-EVs was explored through in vivo and in vitro experiments. Immunofluorescence and qRT-PCR assays were conducted to explore the underlying mechanisms. Results: MSC-EVs exhibited a dose-dependent tendency to target radiation-injured intestines while providing spatiotemporal information for the early diagnosis of the injury by quantifying the amount of MSC-EVs in the injured intestines through molecular imaging. Meanwhile, MSC-EVs displayed superior nanotherapeutic functions by alleviating apoptosis, improving angiogenesis, and ameliorating the intestinal inflammatory environment. Moreover, MSC-EVs-derived miRNA-455-5p negatively regulated SOCS3 expression, and the activated downstream Stat3 signaling pathway was involved in the therapeutic efficacy of MSC-EVs in radiation-induced intestinal injuries. Conclusion: MSC-EVs can dose-dependently target radiation-injured intestinal tissues, allow a spatiotemporal diagnosis in different degrees of damage to help guide personalized therapy, offer data for designing EV-based theranostic strategies for promoting recovery from radiation-induced intestinal injury, and provide cell-free treatment for radiation therapy.

l-2-Hydroxyglutarate contributes to tumor radioresistance through regulating the hypoxia-inducible factor-1α signaling pathway.

l-2-Hydroxyglutarate (l-2-HG) has been regarded as a tumor metabolite, and it plays a crucial role in adaptation of tumor cells to hypoxic conditions. However, the role of l-2-HG in tumor radioresistance and the underlying mechanism have not yet been revealed. Here, we found that l-2-HG exhibited to have radioresistance effect on U87 human glioblastoma cells, which could reduce DNA damage and apoptosis caused by irradiation, promote cell proliferation and migration, and impair G2/M phase arrest. Mechanistically, l-2-HG upregulated the protein level of hypoxia-inducible factor-1α (HIF-1α) and the expression levels of HIF-1α downstream target genes. The knockdown of l-2-hydroxyglutarate dehydrogenase (L2HGDH) gene promoted the tumor growth and proliferation of U87 cells in nude mice by increasing HIF-1α expression level in vivo. In addition, the low expression level of L2HGDH gene was correlated with the short survival of patients with glioma or kidney cancer. In conclusion, our study revealed the role and mechanism of l-2-HG in tumor radioresistance and may provide a new perspective for overcoming tumor radioresistance and broaden our comprehension of the role of metabolites in tumor microenvironment.

Genetic association analysis of human median voice pitch identifies a common locus for tonal and non-tonal languages.

The genetic influence on human vocal pitch in tonal and non-tonal languages remains largely unknown. In tonal languages, such as Mandarin Chinese, pitch changes differentiate word meanings, whereas in non-tonal languages, such as Icelandic, pitch is used to convey intonation. We addressed this question by searching for genetic associations with interindividual variation in median pitch in a Chinese major depression case-control cohort and compared our results with a genome-wide association study from Iceland. The same genetic variant, rs11046212-T in an intron of the ABCC9 gene, was one of the most strongly associated loci with median pitch in both samples. Our meta-analysis revealed four genome-wide significant hits, including two novel associations. The discovery of genetic variants influencing vocal pitch across both tonal and non-tonal languages suggests the possibility of a common genetic contribution to the human vocal system shared in two distinct populations with languages that differ in tonality (Icelandic and Mandarin).

Association of added sugar intake and its forms and sources with handgrip strength decline among middle-aged and older adults: A prospective cohort study.

PURPOSE: The consumption of added sugar has increased rapidly in recent years. Limited knowledge exists regarding the association between added sugar intake and muscle strength, although the latter is a predictor of physical disability in older adults. This study aimed to investigate the association between added sugar intake and longitudinal changes in handgrip strength among middle-aged and elderly Chinese adults. METHODS: This prospective cohort study included 5298 adults aged 40 years and older (62.6% men) from the TCLSIH (Tianjin Chronic Low-grade Systemic Inflammation and Health) cohort study. Added sugar intake was obtained through a frequency questionnaire containing 100 items of food. Handgrip strength is measured annually using a handheld digital dynamometer. Multivariate linear regression models were used to examine the association between added sugars intake and the annual changes in handgrip strength and weight-adjusted handgrip strength. RESULTS: In the fully adjusted model, the annual change in handgrip strength for one unit increase in total added sugar, solid added sugar, and liquid added sugar intake was -0.0353 kg, (95% confidence intervals (CI) -0.000148, -0.0000164; P = 0.01), -0.0348 kg (95% CI: -0.000227, -0.0000269; P = 0.01) and -0.0189 kg (95% CI -0.000187, 0.0000338; P = 0.17), respectively. Added sugar from bread and biscuits sources were remarkably associated with a decline in handgrip strength (ß = -0.0498; 95%CI -0.00281, -0.000787) and (ß = -0.0459; 95%CI 0.00158, 0.00733) (P < 0.01). CONCLUSIONS: Our data suggest that the higher the intake of solid added sugars, but not liquid sugars, were associated with the declined handgrip strength in the Chinese middle-aged and elderly population. In addition, the consumption of added sugars from bread and biscuits sources was also associated with a decline in grip strength.

A Privacy-Preserving Unsupervised Speaker Disentanglement Method for Depression Detection from Speech.

The proposed method focuses on speaker disentanglement in the context of depression detection from speech signals. Previous approaches require patient/speaker labels, encounter instability due to loss maximization, and introduce unnecessary parameters for adversarial domain prediction. In contrast, the proposed unsupervised approach reduces cosine similarity between latent spaces of depression and pre-trained speaker classification models. This method outperforms baseline models, matches or exceeds adversarial methods in performance, and does so without relying on speaker labels or introducing additional model parameters, leading to a reduction in model complexity. The higher the speaker de-identification score (DeID), the better the depression detection system is in masking a patient's identity thereby enhancing the privacy attributes of depression detection systems. On the DAIC-WOZ dataset with ComparE16 features and an LSTM-only model, our method achieves an F1-Score of 0.776 and a DeID score of 92.87%, outperforming its adversarial counterpart which has an F1Score of 0.762 and 68.37% DeID, respectively. Furthermore, we demonstrate that speaker-disentanglement methods are complementary to text-based approaches, and a score-level fusion with a Word2vec-based depression detection model further enhances the overall performance to an F1-Score of 0.830.

Exploring the Role of Inulin in Targeting the Gut Microbiota: An Innovative Strategy for Alleviating Colonic Fibrosis Induced By Irradiation.

The use of radiation therapy to treat pelvic and abdominal cancers can lead to the development of either acute or chronic radiation enteropathy. Radiation-induced chronic colonic fibrosis is a common gastrointestinal disorder resulting from the above radiation therapy. In this study, we establish the efficacy of inulin supplements in safeguarding against colonic fibrosis caused by irradiation therapy. Studies have demonstrated that inulin supplements enhance the proliferation of bacteria responsible to produce short-chain fatty acids (SCFAs) and elevate the levels of SCFAs in feces. In a mouse model of chronic radiation enteropathy, the transplantation of gut microbiota and its metabolites from feces of inulin-treated mice were found to reduce colonic fibrosis in validation experiments. Administering inulin-derived metabolites from gut microbiota led to a notable decrease in the expression of genes linked to fibrosis and collagen production in mouse embryonic fibroblast cell line NIH/3T3. In the cell line, inulin-derived metabolites also suppressed the expression of genes linked to the extracellular matrix synthesis pathway. The results indicate a novel and practical approach to safeguarding against chronic radiation-induced colonic fibrosis.

Enhancing accuracy and privacy in speech-based depression detection through speaker disentanglement.

Speech signals are valuable biomarkers for assessing an individual's mental health, including identifying Major Depressive Disorder (MDD) automatically. A frequently used approach in this regard is to employ features related to speaker identity, such as speaker-embeddings. However, over-reliance on speaker identity features in mental health screening systems can compromise patient privacy. Moreover, some aspects of speaker identity may not be relevant for depression detection and could serve as a bias factor that hampers system performance. To overcome these limitations, we propose disentangling speaker-identity information from depression-related information. Specifically, we present four distinct disentanglement methods to achieve this - adversarial speaker identification (SID)-loss maximization (ADV), SID-loss equalization with variance (LEV), SID-loss equalization using Cross-Entropy (LECE) and SID-loss equalization using KL divergence (LEKLD). Our experiments, which incorporated diverse input features and model architectures, have yielded improved F1 scores for MDD detection and voice-privacy attributes, as quantified by Gain in Voice Distinctiveness GV D and De-Identification Scores (DeID). On the DAIC-WOZ dataset (English), LECE using ComparE16 features results in the best F1-Scores of 80% which represents the audio-only SOTA depression detection F1-Score along with a GV D of -1.1 dB and a DeID of 85%. On the EATD dataset (Mandarin), ADV using raw-audio signal achieves an F1-Score of 72.38% surpassing multi-modal SOTA along with a GV D of -0.89 dB dB and a DeID of 51.21%. By reducing the dependence on speaker-identity-related features, our method offers a promising direction for speech-based depression detection that preserves patient privacy.

A comprehensive review on the source, ingestion route, attachment and toxicity of microplastics/nanoplastics in human systems.

Microplastics (MPs)/nanoplastics (NPs) are widely found in the natural environment, including soil, water and the atmosphere, which are essential for human survival. In the recent years, there has been a growing concern about the potential impact of MPs/NPs on human health. Due to the increasing interest in this research and the limited number of studies related to the health effects of MPs/NPs on humans, it is necessary to conduct a systematic assessment and review of their potentially toxic effects on human organs and tissues. Humans can be exposed to microplastics through ingestion, inhalation and dermal contact, however, ingestion and inhalation are considered as the primary routes. The ingested MPs/NPs mainly consist of plastic particles with a particle size ranging from 0.1 to 1 µm, that distribute across various tissues and organs within the body, which in turn have a certain impact on the nine major systems of the human body, especially the digestive system and respiratory system, which are closely related to the intake pathway of MPs/NPs. The harmful effects caused by MPs/NPs primarily occur through potential toxic mechanisms such as induction of oxidative stress, generation of inflammatory responses, alteration of lipid metabolism or energy metabolism or expression of related functional factors. This review can help people to systematically understand the hazards of MPs/NPs and related toxicity mechanisms from the level of nine biological systems. It allows MPs/NPs pollution to be emphasized, and it is also hoped that research on their toxic effects will be strengthened in the future.

Glutathione Depletion-Induced Versatile Nanomedicine for Potentiating the Ferroptosis to Overcome Solid Tumor Radioresistance and Enhance Immunotherapy.

A high level of reduced glutathione is a major factor contributing to the radioresistance observed in solid tumors. To address this radioresistance associated with glutathione, a cinnamaldehyde (CA) polymer prodrug, referred to as PDPCA, is fabricated. This prodrug is created by synthesizing a pendent CA prodrug with acetal linkages in a hydrophobic block, forming a self-assembled into a core-shell nanoparticle in aqueous media. Additionally, it encapsulates all-trans retinoic acid (ATRA) for synchronous delivery, resulting in PDPCA@ATRA. The PDPCA@ATRA nanoparticles accumulate reactive oxygen species through both endogenous and exogenous pathways, enhancing ferroptosis by depleting glutathione. This approach demonstrates efficacy in overcoming tumor radioresistance in vivo and in vitro, promoting the ferroptosis, and enhancing the cytotoxic T lymphocyte (CTL) response for lung tumors to anti-PD-1 (αPD-1) immunotherapy. Furthermore, this study reveals that PDPCA@ATRA nanoparticles promote ferroptosis through the NRF2-GPX4 signaling pathway, suggesting the potential for further investigation into the combination of radiotherapy and αPD-1 immune checkpoint inhibitors in cancer treatment.

NRF2 promotes radiation resistance by cooperating with TOPBP1 to activate the ATR-CHK1 signaling pathway.

Background: Radiation resistance is the main limitation of the application of radiotherapy. Ionizing radiation (IR) kills cancer cells mainly by causing DNA damage, particularly double-strand breaks (DSBs). Radioresistant cancer cells have developed the robust capability of DNA damage repair to survive IR. Nuclear factor erythroid 2-related factor 2 (NRF2) has been correlated with radiation resistance. We previously reported a novel function of NRF2 as an ATR activator in response to DSBs. However, little is known about the mechanism that how NRF2 regulates DNA damage repair and radiation resistance. Methods: The TCGA database and tissue microarray were used to analyze the correlation between NRF2 and the prognosis of lung cancer patients. The radioresistant lung cancer cells were constructed, and the role of NRF2 in radiation resistance was explored by in vivo and in vitro experiments. Immunoprecipitation, immunofluorescence and extraction of chromatin fractions were used to explore the underlying mechanisms. Results: In this study, the TCGA database and clinical lung cancer samples showed that high expression of NRF2 was associated with poor prognosis in lung cancer patients. We established radioresistant lung cancer cells expressing NRF2 at high levels, which showed increased antioxidant and DNA repair abilities. In addition, we found that NRF2 can be involved in the DNA damage response independently of its antioxidant function. Mechanistically, we demonstrated that NRF2 promoted the phosphorylation of replication protein A 32 (RPA32), and DNA topoisomerase 2-binding protein 1 (TOPBP1) was recruited to DSB sites in an NRF2-dependent manner. Conclusion: This study explored the novel role of NRF2 in promoting radiation resistance by cooperating with RPA32 and TOPBP1 to activate the ATR-CHK1 signaling pathway. In addition, the findings of this study not only provide novel insights into the molecular mechanisms underlying the radiation resistance of lung cancer cells but also validate NRF2 as a potential target for radiotherapy.

Small extracellular vesicles from irradiated lung epithelial cells promote the activation of fibroblasts in pulmonary fibrosis.

BACKGROUND: Alveolar epithelial injury and dysfunction are the risk factors for radiation-induced pulmonary fibrosis (RIPF). However, it is not clear about the relationship between RIPF and the small extracellular vesicles (sEV) secreted by irradiated alveolar epithelial cells. Based on the activation of fibroblasts, this study explored the role of sEV derived from alveolar epithelial cells in RIPF and the potential mechanisms. METHODS: Transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blotting were used to characterize sEV. Western blotting was used to detect fibrosis-associated proteins. Cell counts and transwell assays were used to evaluate the proliferation and migration ability of fibroblasts. RT-PCR was used to observe the extracellular matrix (ECM) synthesized by fibroblasts, miRNA changes in the sEV were determined by second-generation sequencing. RESULTS: TEM, NTA, and western blotting showed the extracellular vesicles with a double-layer membrane structure of approximately 100 nm in diameter. The sEV derived from irradiated A549, HBEC3-KT, and MLE12 cells upregulated FN1 and alpha-SMA proteins expression in fibroblasts and drove the fibroblast to myofibroblast transition, and the sEV from irradiated mouse bronchoalveolar lavage fluid (BALF) affirmed the same results. In addition, the sEV derived from irradiated alveolar epithelial cells significantly increased the migration ability of fibroblasts and the expression of extracellular matrix proteins such as FN1. The results of miRNA sequencing of sEV in BALF of rats with RIPF showed that the metabolic pathway may be important for miRNA to regulate the activation of fibroblasts. CONCLUSION: The sEV derived from radiated pulmonary epithelial cells promote the activation, migration and extracellular matrix proteins expression of lung fibroblasts; miRNA in sEV may be an important molecular that affects the activation of lung fibroblasts.

Non-uniform Speaker Disentanglement For Depression Detection From Raw Speech Signals.

While speech-based depression detection methods that use speaker-identity features, such as speaker embeddings, are popular, they often compromise patient privacy. To address this issue, we propose a speaker disentanglement method that utilizes a non-uniform mechanism of adversarial SID loss maximization. This is achieved by varying the adversarial weight between different layers of a model during training. We find that a greater adversarial weight for the initial layers leads to performance improvement. Our approach using the ECAPA-TDNN model achieves an F1-score of 0.7349 (a 3.7% improvement over audio-only SOTA) on the DAIC-WoZ dataset, while simultaneously reducing the speaker-identification accuracy by 50%. Our findings suggest that identifying depression through speech signals can be accomplished without placing undue reliance on a speaker's identity, paving the way for privacy-preserving approaches of depression detection.

Association of low-dose ionising radiation with site-specific solid cancers: Chinese medical X-ray workers cohort study, 1950-1995.

BACKGROUND: The dose-response relationship between cancers and protracted low-dose rate exposure to ionising radiation is still uncertain. This study aims to estimate quantified relationships between low-dose radiation exposures and site-specific solid cancers among Chinese medical X-ray workers. METHODS: This cohort study included 27 011 individuals who were employed at major hospitals in 24 provinces in China from 1950 to 1980 and had been exposed to X-ray equipment, and a control group of 25 782 physicians who were not exposed to X-ray equipment. Person-years of follow-up were calculated from the year of employment to the date of the first diagnosis of cancer or the end of follow-up, whichever occurred first. All cancers were obtained from medical records during 1950-1995. This study used Poisson regression models to estimate the excess relative risk (ERR) and excess absolute risk (EAR) for incidence of site-specific solid cancers associated with cumulative dose. RESULTS: 1643 solid cancers were developed, the most common being lung, liver and stomach cancer. Among X-ray workers, the average cumulative colon dose was 0.084 Gy. We found a positive relationship between cumulative organ-specific dose and liver (ERR/Gy=1.48; 95% CI 0.40 to 2.83), oesophagus (ERR/Gy=18.1; 95% CI 6.25 to 39.1), thyroid (ERR/Gy=2.96; 95% CI 0.44 to 8.18) and non-melanoma skin cancers (ERR/Gy=7.96; 95% CI 2.13 to 23.12). We found no significant relationship between cumulative organ-specific doses and other cancers. Moreover, the results showed a statistically significant EAR for liver, stomach, breast cancer (female), thyroid and non-melanoma skin cancers. CONCLUSIONS: These findings provided more useful insights into the risks of site-specific cancers from protracted low-dose rate exposure to ionising radiation.

Impact of apolipoprotein A1 on tumor immune microenvironment, clinical prognosis and genomic landscape in hepatocellular carcinoma.

Background: Current knowledge on apolipoprotein A1 (APOA1) in hepatocellular carcinoma (HCC) is fragmented and even contradictory. Multi-dimensional analyses are required to comprehensively elucidate its value and underlying mechanism. Methods: We collected 49 RNA-seq datasets, 40 cell line types data and 70 scRNA pan-cancer datasets public available, including 17 HCC datasets (1754 tumor samples), and enrolled 73 pairs of HCC tissue and 516 blood samples independently from our clinics. APOA1 impacting on the HCC tumor microenvironment (TME) was analyzed using intensive data mining. Methylation sequencing, flow cytometry, quantitative PCR, western blot, immunohistochemistry and clinical chemistry assays were conducted for wet experimental investigation. Results: The APOA1 ontology fingerprint indicated that it played various crucial biological roles in HCC, primarily involved in cholesterol efflux. Consistent findings at histology, serology, and clinical follow-up revealed that high APOA1 was a good prognosis indicator of HCC. Hypermethylation in the APOA1 promoter region was found in clinical samples which is in accordance with the reduction of APOA1 in HCC. The cell cycle, DNA replication, mismatch repair pathways, and tumor cell proliferation were less observed in the HCC APOA1high subgroup. The favorable immunoregulatory abilities of APOA1 showed interesting findings: a positive correlation between APOA1 and anti-tumor immune cells (NK, CD8+ T cells) and a negative association with immune cells exerting immunosuppressive effects, including M2 macrophages. Conclusion: This is an integrative multidimensional exploration of APOA1 using bioinformatics and experiments. Both the prognostic value and anti-tumor effects based on APOA1 panoramic exploration in the HCC TME demonstrate a new potential clinical target for HCC assessment and intervention in the future.

Influence of e-waste exposure on DNA damage and DNA methylation in people living near recycling sites.

The association between long-term exposure to e-waste and poor health is well established, but how e-waste exposure affects DNA methylation is understudied. In this study, we measured the DNA damage levels and the alternation of DNA methylation in peripheral blood mononuclear cells (PBMCs) collected from a population exposed to e-waste. The concentration of 28 PCB congeners in the blood samples of e-waste recycling workers was elevated than those of the reference group. DNA damage levels were significantly higher than that of samples from the reference group by detecting the SCGE, CA, and CBMN assays. Eventually, we found that the methylation level of 1233 gene loci was changed in the exposure group. Bioinformatic analysis of differential genes revealed that the hypermethylated genes were enriched in cell component movement and regulation of cell function, and hypomethylated genes were involved in the cellular metabolic process. Among the 30 genes we tested, 14 genes showed a negative correlation between methylation level and expression level. Therefore, e-waste exposure potentially increased the levels of DNA damage and alters DNA methylation, which would likely impact human health.

Empirical Analysis of Preferences of Older Adults for Care Facilities in Japan: Focusing on Household Structure and Economic Status.

Japan is advancing into a super-aged society at an unprecedented speed, and the proportion of the elderly population will continue to rise. The number of older adults needing nursing care will also increase with the aging population. We used a cross-sectional dataset of older Japanese adults to examine their future preferences for care facilities and their relationship with individual characteristics, household structure, and economic status. We further focused on a subgroup of those who lived alone and were experiencing poverty and examined their care needs through their choice of care facilities. We found the following results from multinomial logit and probit regressions. First, compared with living alone, older adults who live with their spouses or other members prefer to live in their own houses. Second, older adults experiencing poverty preferred to choose facilities geared towards low-income groups, while wealthy older adults preferred to choose fee-based nursing homes/nursing homes with diverse services and high costs. Third, single older adults in poverty were less likely to choose to live in facilities. Covariates such as sex, age, and health status also mattered in their choices. Therefore, tailoring the formal care services to the preferences and actual needs of older adults is imperative.

Kremen2 drives the progression of non-small cell lung cancer by preventing SOCS3-mediated degradation of EGFR.

BACKGROUND: The transmembrane receptor Kremen2 has been reported to participate in the tumorigenesis and metastasis of gastric cancer. However, the role of Kremen2 in non-small cell lung cancer (NSCLC) and the underlying mechanism remain unclear. This study aimed to explore the biological function and regulatory mechanism of Kremen2 in NSCLC. METHODS: The correlation between Kremen2 expression and NSCLC was assessed by analyzing the public database and clinical tissue samples. Colony formation and EdU assays were performed to examine cell proliferation. Transwell and wound healing assays were used to observe cell migration ability. Tumor-bearing nude mice and metastatic tumor models were used to detect the in vivo tumorigenic and metastatic abilities of the NSCLC cells. An immunohistochemical assay was used to detect the expression of proliferation-related proteins in tissues. Western blot, immunoprecipitation and immunofluorescence were conducted to elucidate the Kremen2 regulatory mechanisms in NSCLC. RESULTS: Kremen2 was highly expressed in tumor tissues from NSCLC patients and was positively correlated with a poor patient prognosis. Knockout or knockdown of Kremen2 inhibited cell proliferation and migration ability of NSCLC cells. In vivo knockdown of Kremen2 inhibited the tumorigenicity and number of metastatic nodules of NSCLC cells in nude mice. Mechanistically, Kremen2 interacted with suppressor of cytokine signaling 3 (SOCS3) to maintain the epidermal growth factor receptor (EGFR) protein levels by preventing SOCS3-mediated ubiquitination and degradation of EGFR, which, in turn, promoted activation of the PI3K-AKT and JAK2-STAT3 signaling pathways. CONCLUSIONS: Our study identified Kremen2 as a candidate oncogene in NSCLC and may provide a potential target for NSCLC treatment.

Dyslipidemia in diffuse large B-cell lymphoma based on the genetic subtypes: a single-center study of 259 Chinese patients.

Background: Diffuse large B-cell lymphoma (DLBCL) is a kind of highly heterogeneous non-Hodgkin lymphoma, both in clinical and genetic terms. DLBCL is admittedly categorized into six subtypes by genetics, which contain MCD, BN2, EZB, N1, ST2, and A53. Dyslipidemia is relevant to a multitude of solid tumors and has recently been reported to be associated with hematologic malignancies. We aim to present a retrospective study investigating dyslipidemia in DLBCL based on the molecular subtypes. Results: This study concluded that 259 patients with newly diagnosed DLBCL and their biopsy specimens were available for molecular typing. Results show that the incidence of dyslipidemia (87.0%, p <0.001) is higher in the EZB subtype than in others, especially hypertriglyceridemia (78.3%, p = 0.001) in the EZB subtype. Based on the pathological gene-sequencing, patients with BCL2 gene fusion mutation are significantly correlative with hyperlipidemia (76.5%, p = 0.006) and hypertriglyceridemia (88.2%, p = 0.002). Nevertheless, the occurrence of dyslipidemia has no remarkable influence on prognosis. Conclusion: In summary, dyslipidemia correlates with genetic heterogeneity in DLBCL without having a significant influence on survival. This research first connects lipids and genetic subtypes in DLBCL.

Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data: Longitudinal Observational Study.

BACKGROUND: The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise in lessening participation burden to provide actively contributed patient-reported outcome (PRO) information. OBJECTIVE: The aim of this study was to develop machine learning models to classify and predict PRO scores using Fitbit data from a cohort of patients with rheumatoid arthritis. METHODS: Two different models were built to classify PRO scores: a random forest classifier model that treated each week of observations independently when making weekly predictions of PRO scores, and a hidden Markov model that additionally took correlations between successive weeks into account. Analyses compared model evaluation metrics for (1) a binary task of distinguishing a normal PRO score from a severe PRO score and (2) a multiclass task of classifying a PRO score state for a given week. RESULTS: For both the binary and multiclass tasks, the hidden Markov model significantly (P<.05) outperformed the random forest model for all PRO scores, and the highest area under the curve, Pearson correlation coefficient, and Cohen κ coefficient were 0.750, 0.479, and 0.471, respectively. CONCLUSIONS: While further validation of our results and evaluation in a real-world setting remains, this study demonstrates the ability of physical activity tracker data to classify health status over time in patients with rheumatoid arthritis and enables the possibility of scheduling preventive clinical interventions as needed. If patient outcomes can be monitored in real time, there is potential to improve clinical care for patients with other chronic conditions.