Obg-like ATPase 1 exacerbated gemcitabine drug resistance of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant disease with a poor prognosis due to inefficient diagnosis and tenacious drug resistance. Obg-like ATPase 1 (OLA1) is overexpressed in many malignant tumors. The molecular mechanism of OLA1 underlying gemcitabine (GEM)-induced drug resistance was investigated in this study. An enhanced expression of OLA1 was observed in a GEM acquired resistant pancreatic cancer cell lines and in patients with pancreatic cancer. Overexpressed OLA1 showed poor overall survival rates in patients with pancreatic cancer. Dysregulation of the OLA1 reduced expression of CD44+/CD133+, and improved the sensitivity of pancreatic cancer cells to GEM. OLA1 highly expression facilitated the formation of the OLA1/Sonic Hedgehog (SHH)/Hedgehog-interacting protein (HHIP) complex in nuclei, resulting in the inhibition of negative feedback of Hedgehog signaling induced by HHIP. This study suggests that OLA1 may be developed as an innovative drug target for an effective therapy of pancreatic cancer.

Bose-Einstein Condensation by Polarization Gradient Laser Cooling.

Attempts to create quantum degenerate gases without evaporative cooling have been pursued since the early days of laser cooling, with the consensus that polarization gradient cooling (PGC, also known as "optical molasses") alone cannot reach condensation. In the present work, we report that simple PGC can generate a small Bose-Einstein condensate (BEC) inside a corrugated micrometer-sized optical dipole trap. The experimental parameters enabling BEC creation were found by machine learning, which increased the atom number by a factor of 5 and decreased the temperature by a factor of 2.5, corresponding to almost 2 orders of magnitude gain in phase space density. When the trapping light is slightly misaligned through a microscopic objective lens, a BEC of ∼250 ^{87}Rb atoms is formed inside a local dimple within 40 ms of PGC after MOT loading.

Haplotype analysis on association between C-reactive protein gene and susceptibility to type 2 diabetes mellitus in Chinese Han population : CRP gene and type 2 diabetes mellitus.

AIMS: We aimed to evaluate the impact of C-reactive protein (CRP) gene polymorphism, additional gene-gene interaction, and haplotypes on susceptibility to type 2 diabetes mellitus (T2DM). METHODS: SNPstats online software ( https://www.snpstats.net/start.htm ) was employed to evaluate the association between CRP gene and T2DM risk. High-order interactions among SNPs was tested using generalized multifactor dimensionality reduction, and the testing balanced accuracy, training balanced accuracy and cross-validation consistency were calculated. The SHEsisPlus ( http://shesisplus.bio-x.cn/SHEsis.html ) online software was used for haplotype analysis. RESULTS: A total of 730 T2DM patients and 765 controls were enrolled. The T allele of rs1205 is associated with increased susceptibility to T2DM, OR (95% CI) were 1.51 (1.13-2.01), 1.44 (1.10-1.89) and 1.25 (1.01-1.54) for codominant, dominant and over-dominant models, respectively. We also found that minor allele of rs2794521 is associated with decreased susceptibility to T2DM under codominant and recessive models, OR (95%CI) were 0.38 (0.18-0.79) and 0.37 (0.16-0.80) for codominant and recessive models, respectively. No significant gene-gene interaction existed among CRP gene SNPs, all interaction p- values were more than 0.05. Haplotype analyses suggested the CGCA haplotype containing rs1205-C, rs1130864-G, rs2794521- C and rs3093059- A allele was associated with decreased risk of T2DM, OR (95% CI) = 0.83 (0.68-0.98), P = 0.047. CONCLUSIONS: Minor allele of rs1205 was associated with increased T2DM risk. Minor allele of rs2794521 and the CGCA haplotype were associated with decreased T2DM risk.

Crystal epitaxy-confined Pd, Ti-bimetallic sites in the MFI zeolite for benzylalcohol oxidation.

A general strategy for confining Pd, Ti-bimetallic sites in the MFI zeolite by crystal epitaxy was developed. The tailored spatial intimacy of the bimetallic sites demonstrated distinct catalytic performance for the oxidation of benzylalcohol. The related mechanism was clarified and afforded a valuable pathway for rational catalyst design.

Initiating PeriCBD to probe perinatal influences on neurodevelopment during 3-10 years in China.

Adverse perinatal factors can interfere with the normal development of the brain, potentially resulting in long-term effects on the comprehensive development of children. Presently, the understanding of cognitive and neurodevelopmental processes under conditions of adverse perinatal factors is substantially limited. There is a critical need for an open resource that integrates various perinatal factors with the development of the brain and mental health to facilitate a deeper understanding of these developmental trajectories. In this Data Descriptor, we introduce a multicenter database containing information on perinatal factors that can potentially influence children's brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development associated with perinatal factors among children aged 3-10 years. Ultimately, our goal is to help understand how different adverse perinatal factors specifically impact cognitive development and neurodevelopment. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD.

hnRNPU is required for spermatogonial stem cell pool establishment in mice.

The continuous regeneration of spermatogonial stem cells (SSCs) underpins spermatogenesis and lifelong male fertility, but the developmental origins of the SSC pool remain unclear. Here, we document that hnRNPU is essential for establishing the SSC pool. In male mice, conditional loss of hnRNPU in prospermatogonia (ProSG) arrests spermatogenesis and results in sterility. hnRNPU-deficient ProSG fails to differentiate and migrate to the basement membrane to establish SSC pool in infancy. Moreover, hnRNPU deletion leads to the accumulation of ProSG and disrupts the process of T1-ProSG to T2-ProSG transition. Single-cell transcriptional analyses reveal that germ cells are in a mitotically quiescent state and lose their unique identity upon hnRNPU depletion. We further show that hnRNPU could bind to Vrk1, Slx4, and Dazl transcripts that have been identified to suffer aberrant alternative splicing in hnRNPU-deficient testes. These observations offer important insights into SSC pool establishment and may have translational implications for male fertility.

GSDME-mediated keratinocyte pyroptosis participates in the pathogenesis of psoriasis by promoting skin inflammation.

OBJECTIVE: Psoriasis is a common, chronic inflammatory disease with unclear etiology. Keratinocytes in psoriasis are susceptible to exogenous triggers that induce inflammatory cell death. This study investigated whether GSDME-mediated pyroptosis in keratinocytes contributes to the pathogenesis of psoriasis. METHODS: Skin samples from patients with psoriasis and healthy controls were collected to evaluate the expression of GSDME, cleaved-caspase-3, and inflammatory factors. We then analyzed the data series, GSE41662, to further compare the expression of GSDME between lesional and non-lesional skin samples in those with psoriasis. In vivo, caspase-3 inhibitor and GSDME deficiency mice (Gsdme-/-) were applied to block caspase-3/GSDME activation in the imiquimod-induced psoriasis model. Skin inflammation, disease severity, and pyroptosis-related proteins were analyzed. In vitro, tumor necrosis factor-α (TNF-α)-induced caspase-3/GSDME-mediated pyroptosis in the HACAT cell line was explored. RESULTS: Our analysis of the GSE41662 data series found that GSDME were upregulated in psoriasis lesions, compared to normal skin. High levels of inflammatory cytokines such as IL-1ß, IL-6, and TNF-α were also found in psoriasis lesions. In mice of Gsdme-/- and caspase-3 inhibitor groups, the severity of skin inflammation was attenuated, and GSDME and C-caspase-3 levels decreased after imiquimod treatment. Similarly, IL-1ß, IL-6, and TNF-α were decreased in Gsdme-/- and caspase-3 inhibitor groups. In vitro, TNF-α induced HACAT cell pyroptosis through caspase-3/GSDME pathway activation, which was suppressed by blocking caspase-3 or silencing GSDME. CONCLUSION: Our study provides a novel explanation that TNF-α/caspase-3/GSDME-mediated keratinocyte pyroptosis is highly responsible for the initiation and acceleration of skin inflammation and progression of psoriasis.

Multimodal Dual-Embedding Networks for Malware Open-Set Recognition.

Malware open-set recognition (MOSR) is an emerging research domain that aims at jointly classifying malware samples from known families and detecting the ones from novel unknown families, respectively. Existing works mostly rely on a well-trained classifier considering the predicted probabilities of each known family with a threshold-based detection to achieve the MOSR. However, our observation reveals that the feature distributions of malware samples are extremely similar to each other even between known and unknown families. Thus, the obtained classifier may produce overly high probabilities of testing unknown samples toward known families and degrade the model performance. In this article, we propose the multi \ modal dual-embedding networks, dubbed MDENet, to take advantage of comprehensive malware features from different modalities to enhance the diversity of malware feature space, which is more representative and discriminative for down-stream recognition. Concretely, we first generate a malware image for each observed sample based on their numeric features using our proposed numeric encoder with a re-designed multiscale CNN structure, which can better explore their statistical and spatial correlations. Besides, we propose to organize tokenized malware features into a sentence for each sample considering its behaviors and dynamics, and utilize language models as the textual encoder to transform it into a representable and computable textual vector. Such parallel multimodal encoders can fuse the above two components to enhance the feature diversity. Last, to further guarantee the open-set recognition (OSR), we dually embed the fused multimodal representation into one primary space and an associated sub-space, i.e., discriminative and exclusive spaces, with contrastive sampling and ρ -bounded enclosing sphere regularizations, which resort to classification and detection, respectively. Moreover, we also enrich our previously proposed large-scaled malware dataset MAL-100 with multimodal characteristics and contribute an improved version dubbed MAL-100 + . Experimental results on the widely used malware dataset Mailing and the proposed MAL-100 + demonstrate the effectiveness of our method.

The ARID1A-METTL3-m6A axis ensures effective RNase H1-mediated resolution of R-loops and genome stability.

R-loops are three-stranded structures that can pose threats to genome stability. RNase H1 precisely recognizes R-loops to drive their resolution within the genome, but the underlying mechanism is unclear. Here, we report that ARID1A recognizes R-loops with high affinity in an ATM-dependent manner. ARID1A recruits METTL3 and METTL14 to the R-loop, leading to the m6A methylation of R-loop RNA. This m6A modification facilitates the recruitment of RNase H1 to the R-loop, driving its resolution and promoting DNA end resection at DSBs, thereby ensuring genome stability. Depletion of ARID1A, METTL3, or METTL14 leads to R-loop accumulation and reduced cell survival upon exposure to cytotoxic agents. Therefore, ARID1A, METTL3, and METTL14 function in a coordinated, temporal order at DSB sites to recruit RNase H1 and to ensure efficient R-loop resolution. Given the association of high ARID1A levels with resistance to genotoxic therapies in patients, these findings open avenues for exploring potential therapeutic strategies for cancers with ARID1A abnormalities.

MiRNA-100 ameliorates diabetes mellitus-induced erectile dysfunction by modulating autophagy, anti-inflammatory, and antifibrotic effects.

BACKGROUND: Diabetes mellitus-induced erectile dysfunction (DMED) has become a common disease in adult men that can seriously reduce the quality of life of patients, and new therapies are urgently needed. miRNA-100 has many targets and can induce autophagy and reduce fibrosis by inhibiting the mTOR pathway and the TGF-ß pathway. However, no research has been conducted with miR-100 in the field of DMED, and the specific mechanism of action is still unclear. OBJECTIVES: To ascertain the effects of miR-100 on corpus cavernosum tissue of DMED rats and vascular endothelial cells in a high glucose environment and to elucidate the relevant mechanisms in autophagy, fibrosis and inflammation to find a new approach for the DMED therapy. METHODS: Thirty rats were divided into three groups: the control group, the DMED group, and the DMED + miR-100 group. Using intraperitoneal injections of streptozotocin, all rats except the control group were modeled with diabetes mellitus, which was verified using the apomorphine (APO) test. For rats in the DMED + miR-100 group, rno-miR-100-5p agomir (50 nmol/kg, every 2 days, 6 times in total) was injected via the tail vein. After 13 weeks, the erectile function of each rat was assessed using cavernous manometry, and the corpus cavernosum tissue was harvested for subsequent experiments. For cellular experiments, human coronary microartery endothelial cells (HCMEC) were divided into four groups: the control group, the high-glucose (HG, 40 mM) group, the HG + mimic group, and the HG + inhibitor group. The cells were cultured for 6 days and collected for subsequent experiments 2 days after transfection. RESULTS: Diabetic modeling impaired the erectile function in rats, and miR-100 reversed this effect. By measuring autophagy-related proteins such as mTOR/Raptor/Beclin1/p62/LC3B, we found that miR-100 could suppress the expression of mTOR and induce autophagy. The analysis of the eNOS/NO/cGMP axis function indicated that impaired endothelial function was improved by miR-100. By evaluating the TGF-ß1/CTGF/Smad2/3 and NF-κB/TNF-α pathways, we found that miR-100 could lower the level of inflammation and fibrosis, which contributed to the improvement of the erectile function. Cellular experiments can be used as supporting evidence for these findings. CONCLUSION: MiR-100 can improve the erectile function by inhibiting mTOR and thus inducing autophagy, improving the endothelial function through the eNOS/NO/cGMP axis, and exerting antifibrotic and anti-inflammatory effects, which may provide new ideas and directions for the treatment of DMED.

A new method for estimating Sharpe ratio function via local maximum likelihood.

The Sharpe ratio function is a commonly used risk/return measure in financial econometrics. To estimate this function, most existing methods take a two-step procedure that first estimates the mean and volatility functions separately and then applies the plug-in method. In this paper, we propose a direct method via local maximum likelihood to simultaneously estimate the Sharpe ratio function and the negative log-volatility function as well as their derivatives. We establish the joint limiting distribution of the proposed estimators, and moreover extend the proposed method to estimate the multivariate Sharpe ratio function. We also evaluate the numerical performance of the proposed estimators through simulation studies, and compare them with existing methods. Finally, we apply the proposed method to the three-month US Treasury bill data and that captures a well-known covariate-dependent effect on the Sharpe ratio.

UTDNet: A unified triplet decoder network for multimodal salient object detection.

Image Salient Object Detection (SOD) is a fundamental research topic in the area of computer vision. Recently, the multimodal information in RGB, Depth (D), and Thermal (T) modalities has been proven to be beneficial to the SOD. However, existing methods are only designed for RGB-D or RGB-T SOD, which may limit the utilization in various modalities, or just finetuned on specific datasets, which may bring about extra computation overhead. These defects can hinder the practical deployment of SOD in real-world applications. In this paper, we propose an end-to-end Unified Triplet Decoder Network, dubbed UTDNet, for both RGB-T and RGB-D SOD tasks. The intractable challenges for the unified multimodal SOD are mainly two-fold, i.e., (1) accurately detecting and segmenting salient objects, and (2) preferably via a single network that fits both RGB-T and RGB-D SOD. First, to deal with the former challenge, we propose the multi-scale feature extraction unit to enrich the discriminative contextual information, and the efficient fusion module to explore cross-modality complementary information. Then, the multimodal features are fed to the triplet decoder, where the hierarchical deep supervision loss further enable the network to capture distinctive saliency cues. Second, as to the latter challenge, we propose a simple yet effective continual learning method to unify multimodal SOD. Concretely, we sequentially train multimodal SOD tasks by applying Elastic Weight Consolidation (EWC) regularization with the hierarchical loss function to avoid catastrophic forgetting without inducing more parameters. Critically, the triplet decoder separates task-specific and task-invariant information, making the network easily adaptable to multimodal SOD tasks. Extensive comparisons with 26 recently proposed RGB-T and RGB-D SOD methods demonstrate the superiority of the proposed UTDNet.

Tumor microenvironment crosstalk between tumors and the nervous system in pancreatic cancer: Molecular mechanisms and clinical perspectives.

Pancreatic ductal adenocarcinoma (PDAC) exhibits the highest incidence of perineural invasion among all solid tumors. The intricate interplay between tumors and the nervous system plays an important role in PDAC tumorigenesis, progression, recurrence, and metastasis. Various clinical symptoms of PDAC, including anorexia and cancer pain, have been linked to aberrant neural activity, while the presence of perineural invasion is a significant prognostic indicator. The use of conventional neuroactive drugs and neurosurgical interventions for PDAC patients is on the rise. An in-depth exploration of tumor-nervous system crosstalk has revealed novel therapeutic strategies for mitigating PDAC progression and effectively relieving symptoms. In this comprehensive review, we elucidate the regulatory functions of tumor-nervous system crosstalk, provide a succinct overview of the relationship between tumor-nervous system dialogue and clinical symptomatology, and deliberate the current research progress and forthcoming avenues of neural therapy for PDAC.

TXNIP-NLRP3-GSDMD axis-mediated inflammation and pyroptosis of islet ß-cells is involved in cigarette smoke-induced hyperglycemia, which is alleviated by andrographolide.

Epidemiologic surveys have indicated that cigarette smoking is an important risk factor for diabetes, but its mechanisms remain unclear. Andrographolide, an herb traditionally utilized in medicine, provides anti-inflammatory benefits for various diseases. In the present work, 265 patients with Type 2 diabetes (T2D) were investigated, and male C57BL/6 mice were exposed to cigareete smoke (CS) and/or to intraperitoneally injected andrographolide for 3 months. To elucidate the mechanism of CS-induced hyperglycemia and the protective mechanism of andrographolide, MIN6 cells were exposed to cigarette smoke extract (CSE) and/or to andrographolide. Our data from 265 patients with T2D showed that urinary creatinine and serum inflammatory cytokines (interleukin 6 (IL-6), IL-8, IL-1ß, and tumor necrosis factor α (TNF-α)) increased with smoking pack-years. In a mouse model, CS induced hyperglycemia, decreased insulin secretion, and elevated inflammation and pyroptosis in ß-cells of mice. Treatment of mice with andrographolide preserved pancreatic function by reducing the expression of inflammatory cytokines; the expression of TXNIP, NLRP3, cleaved caspase 1, IL-1ß; and the N-terminal of gasdermin D (GSDMD) protein. For MIN6 cells, CSE caused increasing secretion of the inflammatory cytokines IL-6 and IL-1ß, and the expression of TXNIP and pyroptosis-related proteins; however, andrographolide alleviated these changes. Furthermore, silencing of TXNIP showed that the blocking effect of andrographolide may be mediated by TXNIP. In sum, our results indicate that CS induces hyperglycemia through TXNIP-NLRP3-GSDMD axis-mediated inflammation and pyroptosis of islet ß-cells and that andrographolide is a potential therapeutic agent for CS-induced hyperglycemia.

Negative emotions increase unhealthy eating: Evidence from the Wuhan lockdown during COVID-19.

This paper studies how negative emotions like stress, anxiety, and boredom can affect unhealthy food consumption. Using the Wuhan lockdown as an external shock, we examine the changes in food consumption in a city that was not in lockdown. We applied the difference-in-differences method to a large scanner dataset from a retail monopoly in China. Our findings reveal that negative emotions induced by the pandemic lockdown significantly elevated consumer spending on unhealthy food items such as crisps, sugary beverages, regular soda, and low-alcohol beverages. Notably, the effect of unhealthy food consumption was more pronounced among younger and wealthier demographics. Triggering factors, like information about confirmed new deaths and infections as well as proximity to local hospitals, were found to strongly influence the consumption of unhealthy foods. Overall, the lockdown's impact extended beyond short-term increases in snack consumption to substantial increases in overall dietary and nutritional intake.

Research trends and hotspots in prostate cancer associated exosome: a bibliometric analysis.

Background: Prostate cancer is viewed as the second most common cancer in men worldwide. In our study, we used bibliometric analysis to construct a visual map of the relationship between prostate cancer and exosomes with the intent of uncovering research trends and current hotspots in this field. Method: We searched the Web of Science Core Collection for all publications in the prostate cancer associated with exosome field came out since 2010. With the assistance of bibliometric analysis software such as VOSviewer and CiteSpace, we conducted data extraction and analysis for countries/regions, institutions, authors, journals, references and keywords. Results: A bibliometric analysis of 990 publications was performed. Since 2010, the published quantity and cited frequency of the prostate cancer-associated exosome field have revealed an increasing tendency. In this field, we visualized the research trends by the means of analyzing the references and keywords. We obtained the statistical data: the total citations of publications have increased to 55,462, the average citation per article has reached 55.3 times, and the H-index has amounted to 110. Our findings supported that USA, China and Italy rank the top countries with both the maximum publications and strongest cooperations. Harvard Medical School, Cedars Sinai Med Ctr, Johns Hopkins University, are top institutions in the center of research as they are held to be. Thery C, Skog J and Taylor DD are the leading and outstanding professors and researchers. And top journals like Prostate, Plos One and Journal of Extracellular Vesicle expressed keen interests in this field. Based on our analysis and research, we believe that this field is attracting more and more attention and will focus on tumor bone metastasis, drug delivery, and tumor suppressor. Conclusion: In the past 12 years, researchers have dedicated their efforts to prostate cancer associated exosome. On the basis of previous studies, scientists are showing increasingly solicitude for the role of exosome in prostate cancer progression and potential therapy such as drug delivery.

Global research trends of the application of artificial intelligence in bladder cancer since the 21st century: a bibliometric analysis.

Introduction: Since the significant breakthroughs in artificial intelligence (AI) algorithms, the application of AI in bladder cancer has rapidly expanded. AI can be used in all aspects of the bladder cancer field, including diagnosis, treatment and prognosis prediction. Nowadays, these technologies have an excellent medical auxiliary effect and are in explosive development, which has aroused the intense interest of researchers. This study will provide an in-depth analysis using bibliometric analysis to explore the trends in this field. Method: Documents regarding the application of AI in bladder cancer from 2000 to 2022 were searched and extracted from the Web of Science Core Collection. These publications were analyzed by bibliometric analysis software (CiteSpace, Vosviewer) to visualize the relationship between countries/regions, institutions, journals, authors, references, keywords. Results: We analyzed a total of 2368 publications. Since 2016, the number of publications in the field of AI in bladder cancer has increased rapidly and reached a breathtaking annual growth rate of 43.98% in 2019. The U.S. has the largest research scale, the highest study level and the most significant financial support. The University of North Carolina is the institution with the highest level of research. EUROPEAN UROLOGY is the most influential journal with an impact factor of 24.267 and a total citation of 11,848. Wiklund P. has the highest number of publications, and Menon M. has the highest number of total citations. We also find hot research topics within the area through references and keywords analysis, which include two main parts: AI models for the diagnosis and prediction of bladder cancer and novel robotic-assisted surgery for bladder cancer radicalization and urinary diversion. Conclusion: AI application in bladder cancer is widely studied worldwide and has shown an explosive growth trend since the 21st century. AI-based diagnostic and predictive models will be the next protagonists in this field. Meanwhile, the robot-assisted surgery is still a hot topic and it is worth exploring the application of AI in it. The advancement and application of algorithms will be a massive driving force in this field.

PARylated PDHE1α generates acetyl-CoA for local chromatin acetylation and DNA damage repair.

Chromatin relaxation is a prerequisite for the DNA repair machinery to access double-strand breaks (DSBs). Local histones around the DSBs then undergo prompt changes in acetylation status, but how the large demands of acetyl-CoA are met is unclear. Here, we report that pyruvate dehydrogenase 1α (PDHE1α) catalyzes pyruvate metabolism to rapidly provide acetyl-CoA in response to DNA damage. We show that PDHE1α is quickly recruited to chromatin in a polyADP-ribosylation-dependent manner, which drives acetyl-CoA generation to support local chromatin acetylation around DSBs. This process increases the formation of relaxed chromatin to facilitate repair-factor loading, genome stability and cancer cell resistance to DNA-damaging treatments in vitro and in vivo. Indeed, we demonstrate that blocking polyADP-ribosylation-based PDHE1α chromatin recruitment attenuates chromatin relaxation and DSB repair efficiency, resulting in genome instability and restored radiosensitivity. These findings support a mechanism in which chromatin-associated PDHE1α locally generates acetyl-CoA to remodel the chromatin environment adjacent to DSBs and promote their repair.