Long-term exposure to particulate matter and all-cause and cause-specific mortality in an analysis of multiple Asian cohorts

BACKGROUND

Exposure to ambient air pollution is associated with a significant number of deaths. Much of the evidence associating air pollution with adverse effects is from North American and Europe, partially due to incomplete data in other regions limiting location specific examinations. The aim of the current paper is to leverage satellite derived air quality data to examine the relationship between ambient particulate matter and all-cause and cause-specific mortality in Asia.

METHODS

Six cohorts from the Asia Cohort Consortium provided residential information for participants, recruited between 1991 and 2008, across six countries (Bangladesh, India, Iran, Japan, South Korea, and Taiwan). Ambient particulate material (PM2·5) levels for the year of enrolment (or 1998 if enrolled earlier) were assigned utilizing satellite and sensor-based maps. Cox proportional models were used to examine the association between ambient air pollution and all-cause and cause-specific mortality (all cancer, lung cancer, cardiovascular and lung disease). Models were additionally adjusted for urbanicity (representing urban and built characteristics) and stratified by smoking status in secondary analyses. Country-specific findings were pooled via random-effects meta-analysis.

FINDINGS

More than 300,000 participants across six cohorts were included, representing more than 4-million-person years. A positive relationship was observed between a 5 µg/m (Dockery et al., 1993) increase in PM2·5 and cardiovascular mortality (HR: 1·06, 95 % CI: 0.99, 1·13). The additional adjustment for urbanicity resulted in increased associations between PM2.5 and mortality outcomes, including all-cause mortality (1·04, 95 % CI: 0·97, 1·11). Results were generally similar regardless of whether one was a current, never, or ex-smoker.

INTERPRETATION

Using satellite and remote sensing technology we showed that associations between PM2.5 and all-cause and cause-specific Hazard Ratios estimated are similar to those reported for U.S. and European cohorts.

FUNDING

This project was supported by the Health Effects Institute. Grant number #4963-RFA/18-5. Specific funding support for individual cohorts is described in the Acknowledgements.

Guidelines for Manufacturing and Application of Organoids: Liver

Recent amendments to regulatory frameworks have placed a greater emphasis on the utilization of in vitro testing platforms for preclinical drug evaluations and toxicity assessments. This requires advanced tissue models capable of accurately replicating liver functions for drug efficacy and toxicity predictions. Liver organoids, derived from human cell sources, offer promise as a reliable platform for drug evaluation. However, there is a lack of standardized quality evaluation methods, which hinders their regulatory acceptance. This paper proposes comprehensive quality standards tailored for liver organoids, addressing cell source validation, organoid generation, and functional assessment. These guidelines aim to enhance reproducibility and accuracy in toxicity testing, thereby accelerating the adoption of organoids as a reliable alternative or complementary tool to animal testing in drug development. The quality standards include criteria for size, cellular composition, gene expression, and functional assays, thus ensuring a robust hepatotoxicity testing platform.

Validation and responsiveness of the English version of the Chemotherapy-Induced Alopecia Distress Scale (CADS) in breast cancer patients

PURPOSE

This study aimed to validate the Chemotherapy-Induced Alopecia Distress Scale (CADS) in a diverse English-speaking population and patients with endocrine treatment-induced alopecia (EIA).

OBJECTIVE

Chemotherapy and endocrine therapy commonly cause alopecia in breast cancer patients, leading to significant psychological and social challenges. The CADS was developed to assess the psychosocial impact of alopecia, but its generalizability beyond Korean patients requires further investigation.

METHODS

Data from the CHANCE study (NCT02530177), which focused on non-metastatic breast cancer, was used. The cohort included 256 patients, and CADS data were collected at baseline, 6 months after chemotherapy completion, or 12 months after initiating endocrine therapy. The CADS questionnaire comprised 17 items covering physical and emotional health, daily activities, and relationships. Reliability was assessed using Cronbach's alpha, and responsiveness was measured by effect size.

RESULTS

The CADS exhibited good reliability, with Cronbach's alpha of 0.91 for the overall score, indicating acceptable internal consistency in both chemotherapy (0.89) and endocrine therapy (0.86) groups. Longitudinal responsiveness was supported by an effect size of 0.49 between decreasing satisfaction with hair growth and increasing emotional distress. Cross-sectional validity was confirmed, with effect sizes of 0.91 and 0.92 for satisfaction with hair growth and emotional and activity domains, respectively.

CONCLUSION

The CADS is a valid and responsive tool for assessing the psychosocial impact of chemotherapy-induced alopecia and endocrine treatment-induced alopecia in a diverse Western patient population.

Observation of Seven Astrophysical Tau Neutrino Candidates with IceCube

We report on a measurement of astrophysical tau neutrinos with 9.7 yr of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate ν_{τ} events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent ν_{τ} energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from π^{±}/K^{±} decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-ν_{τ} astrophysical neutrinos. Thus, we rule out the absence of astrophysical ν_{τ} at the 5σ level. The measured astrophysical ν_{τ} flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations.

The secreted protein Amuc_1409 from Akkermansia muciniphila improves gut health through intestinal stem cell regulation

Akkermansia muciniphila has received great attention because of its beneficial roles in gut health by regulating gut immunity, promoting intestinal epithelial development, and improving barrier integrity. However, A. muciniphila-derived functional molecules regulating gut health are not well understood. Microbiome-secreted proteins act as key arbitrators of host-microbiome crosstalk through interactions with host cells in the gut and are important for understanding host-microbiome relationships. Herein, we report the biological function of Amuc_1409, a previously uncharacterised A. muciniphila-secreted protein. Amuc_1409 increased intestinal stem cell (ISC) proliferation and regeneration in ex vivo intestinal organoids and in vivo models of radiation- or chemotherapeutic drug-induced intestinal injury and natural aging with male mice. Mechanistically, Amuc_1409 promoted E-cadherin/β-catenin complex dissociation via interaction with E-cadherin, resulting in the activation of Wnt/β-catenin signaling. Our results demonstrate that Amuc_1409 plays a crucial role in intestinal homeostasis by regulating ISC activity in an E-cadherin-dependent manner and is a promising biomolecule for improving and maintaining gut health.

Validation and Responsiveness of the English version of the Chemotherapy-Induced Alopecia Distress Scale (CADS) in Breast Cancer Patients

Purpose

This study aimed to validate the chemotherapy-induced alopecia distress scale (CADS) in a diverse English-speaking population and patients with endocrine treatment- induced alopecia (EIA).

Objective

Chemotherapy and endocrine therapy commonly cause alopecia in breast cancer patients, leading to significant psychological and social challenges. The CADS was developed to assess the psychosocial impact of alopecia, but its generalizability beyond Korean patients requires further investigation.

Methods

Data from the CHANCE study ( NCT02530177 ), which focused on non-metastatic breast cancer, was used. The cohort included 256 patients, and CADS data were collected at baseline, six months after chemotherapy completion, or 12 months after initiating endocrine therapy. The CADS questionnaire comprised 17 items covering physical and emotional health, daily activities, and relationships. Reliability was assessed using Cronbach's alpha, and responsiveness was measured by effect size.

Results

The CADS exhibited good reliability, with a Cronbach's alpha of 0.91 for the overall score, indicating acceptable internal consistency in both chemotherapy (0.89) and endocrine therapy (0.86) groups. Longitudinal responsiveness was supported by an effect size of 0.49 between decreasing satisfaction with hair growth and increasing emotional distress. Cross-sectional validity was confirmed, with effect sizes of 0.91 and 0.92 for satisfaction with hair growth and emotional and activity domains, respectively.

Conclusion

The CADS is a valid and responsive tool for assessing the psychosocial impact of chemotherapy-induced alopecia and endocrine treatment-induced alopecia in a diverse Western patient population.

Quantitative and Qualitative Analysis of Neurotransmitter and Neurosteroid Production in Cerebral Organoids during Differentiation

In the human brain, neurophysiological activity is modulated by the movement of neurotransmitters and neurosteroids. To date, the similarity between cerebral organoids and actual human brains has been evaluated using comprehensive multiomics approaches. However, a systematic analysis of both neurotransmitters and neurosteroids from cerebral organoids has not yet been reported. Here, we performed quantitative and qualitative assessments of neurotransmitters and neurosteroids over the course of cerebral organoid differentiation. Our multiomics approaches revealed that the expression levels of neurotransmitter-related proteins and RNA, including neurosteroids, increase as cerebral organoids mature. We also found that the electrophysiological activity of human cerebral organoids increases in tandem with the expression levels of both neurotransmitters and neurosteroids. Our study demonstrates that the expression levels of neurotransmitters and neurosteroids can serve as key factors in evaluating the maturity and functionality of human cerebral organoids.

Feature extraction of time series data on functional near-infrared spectroscopy and comparison of deep learning performance for classifying patients with Alzheimer's-related mild cognitive impairment: a post-hoc analysis of a diagnostic interventional trial

OBJECTIVE

This study aimed to define a method of classifying patients with mild cognitive impairment caused by Alzheimer's disease by the retrieval of functional near-infrared spectroscopy (fNIRS) signal characteristics obtained during olfactory stimulation and the validation of deep learning findings.

PATIENTS AND METHODS

Participants were recruited for the study from March 02 and August 30, 2021. A total of 78 participants met the criteria for categorization. The Mini-Mental State Examination and the Seoul Neuropsychological Scale were used to distinguish between patients with mild Alzheimer's disease-related cognitive impairment and healthy controls. fNIRS data received during olfactory stimulation were used to create 1,680 time-series sample values. A total of 150 indices with a p-value ≤ 0.1 were used as deep learning features to construct the result values for 120 models accounting for all conceivable combinations of data ratios.

RESULTS

For this trial, 78 participants were recruited for the original intervention trial. The average accuracy of the 120 deep-learning models for classifying patients with Alzheimer's-related mild cognitive impairment ranged from 0.78 to 0.90. Sensitivity ranged from 0.88 to 0.96 for the 120 models, while specificity ranged from 0.86 to 0.94. The F1 scores ranged from 0.74 to 0.88. At 0.78 to 0.90, the precision and recall were equivalent.

CONCLUSIONS

This trial using a deep-learning model found that the representative value extracted from the time series data of each channel could distinguish between healthy people and patients with mild cognitive impairment caused by Alzheimer's disease.

Observation of high-energy neutrinos from the Galactic plane

The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.

A, Barbano A, Barwick SW, Bastian B, Basu V, Baur S, Bay R, Beatty JJ, Becker KH, Becker Tjus J, Bellenghi C, BenZvi S, Berley D, Bernardini E, Besson DZ, Binder G, Bindig D, Blaufuss E, Blot S, Boddenberg M, Bontempo F, Borowka J, Böser S, Botner O, Böttcher J, Bourbeau E, Bradascio F, Braun J, Brinson B, Bron S, Brostean-Kaiser J, Browne S, Burgman A, Burley RT, Busse RS, Campana MA, Carnie-Bronca EG, Chen C, Chen Z, Chirkin D, Choi K, Clark BA, Clark K, Classen L, Coleman A, Collin GH, Conrad JM, Coppin P, Correa P, Cowen DF, Cross R, Dappen C, Dave P, De Clercq C, DeLaunay JJ, Delgado López D, Dembinski H, Deoskar K, Desai A, Desiati P, de Vries KD, de Wasseige G, de With M, DeYoung T, Diaz A, Díaz-Vélez JC, Dittmer M, Dujmovic H, Dunkman M, DuVernois MA, Dvorak E, Ehrhardt T, Eller P, Engel R, Erpenbeck H, Evans J, Evenson PA, Fan KL, Fazely AR, Fedynitch A, Feigl N, Fiedlschuster S, Fienberg AT, Filimonov K, Finley C, Fischer L, Fox D, Franckowiak A, Friedman E, Fritz A, Fürst P, Gaisser TK, Gallagher J, Ganster E, Garcia A, Garrappa S, Gerhardt L, Ghadimi A, Glaser C, Glauch T, Glüsenkamp T, Goldschmidt A, Gonzalez JG, Goswami S, Grant D, Grégoire T, Griswold S, Günther C, Gutjahr P, Haack C, Hallgren A, Halliday R, Halve L, Halzen F, Ha Minh M, Hanson K, Hardin J, Harnisch AA, Haungs A, Hebecker D, Helbing K, Henningsen F, Hettinger EC, Hickford S, Hignight J, Hill C, Hill GC, Hoffman KD, Hoffmann R, Hokanson-Fasig B, Hoshina K, Huang F, Huber M, Huber T, Hultqvist K, Hünnefeld M, Hussain R, Hymon K, In S, Iovine N, Ishihara A, Jansson M, Japaridze GS, Jeong M, Jin M, Jones BJP, Kang D, Kang W, Kang X, Kappes A, Kappesser D, Kardum L, Karg T, Karl M, Karle A, Katz U, Kauer M, Kellermann M, Kelley JL, Kheirandish A, Kin K, Kintscher T, Kiryluk J, Klein SR, Koirala R, Kolanoski H, Kontrimas T, Köpke L, Kopper C, Kopper S, Koskinen DJ, Koundal P, Kovacevich M, Kowalski M, Kozynets T, Kun E, Kurahashi N, Lad N, Lagunas Gualda C, Lanfranchi JL, Larson MJ, Lauber F, Lazar JP, Lee JW, Leonard K, Leszczyńska A, Li Y, Lincetto M, Liu QR, Liubarska M, Lohfink E, Lozano Mariscal CJ, Lu L, Lucarelli F, Ludwig A, Luszczak W, Lyu Y, Ma WY, Madsen J, Mahn KBM, Makino Y, Mancina S, Mariş IC, Martinez-Soler I, Maruyama R, Mase K, McElroy T, McNally F, Mead JV, Meagher K, Mechbal S, Medina A, Meier M, Meighen-Berger S, Micallef J, Mockler D, Montaruli T, Moore RW, Morse R, Moulai M, Naab R, Nagai R, Nahnhauer R, Naumann U, Necker J, Nguyen LV, Niederhausen H, Nisa MU, Nowicki SC, Nygren D, Obertacke Pollmann A, Oehler M, Oeyen B, Olivas A, O’Sullivan E, Pandya H, Pankova DV, Park N, Parker GK, Paudel EN, Paul L, Pérez de los Heros C, Peters L, Peterson J, Philippen S, Pieper S, Pittermann M, Pizzuto A, Plum M, Popovych Y, Porcelli A, Prado Rodriguez M, Price PB, Pries B, Przybylski GT, Raab C, Rack-Helleis J, Raissi A, Rameez M, Rawlins K, Rea IC, Rehman A, Reichherzer P, Reimann R, Renzi G, Resconi E, Reusch S, Rhode W, Richman M, Riedel B, Roberts EJ, Robertson S, Roellinghoff G, Rongen M, Rott C, Ruhe T, Ryckbosch D, Rysewyk Cantu D, Safa I, Saffer J, Sanchez Herrera SE, Sandrock A, Sandroos J, Santander M, Sarkar S, Sarkar S, Satalecka K, Schaufel M, Schieler H, Schindler S, Schmidt T, Schneider A, Schneider J, Schröder FG, Schumacher L, Schwefer G, Sclafani S, Seckel D, Seunarine S, Sharma A, Shefali S, Silva M, Skrzypek B, Smithers B, Snihur R, Soedingrekso J, Soldin D, Spannfellner C, Spiczak GM, Spiering C, Stachurska J, Stamatikos M, Stanev T, Stein R, Stettner J, Steuer A, Stezelberger T, Stokstad R, Stürwald T, Stuttard T, Sullivan GW, Taboada I, Ter-Antonyan S, Tilav S, Tischbein F, Tollefson K, Tönnis C, Toscano S, Tosi D, Trettin A, Tselengidou M, Tung CF, Turcati A, Turcotte R, Turley CF, Twagirayezu JP, Ty B, Unland Elorrieta MA, Valtonen-Mattila N, Vandenbroucke J, van Eijndhoven N, Vannerom D, van Santen J, Verpoest S, Walck C, Watson TB, Weaver C, Weigel P, Weindl A, Weiss MJ, Weldert J, Wendt C, Werthebach J, Weyrauch M, Whitehorn N, Wiebusch CH, Williams DR, Wolf M, Woschnagg K, Wrede G, Wulff J, Xu XW, Yanez JP, Yoshida S, Yu S, Yuan T, Zhang Z, Zhelnin P. Evidence for neutrino emission from the nearby active galaxy NGC 1068

A supermassive black hole, obscured by cosmic dust, powers the nearby active galaxy NGC 1068. Neutrinos, which rarely interact with matter, could provide information on the galaxy’s active core. We searched for neutrino emission from astrophysical objects using data recorded with the IceCube neutrino detector between 2011 and 2020. The positions of 110 known gamma-ray sources were individually searched for neutrino detections above atmospheric and cosmic backgrounds. We found that NGC 1068 has an excess of 79 − 20 + 22 neutrinos at tera–electron volt energies, with a global significance of 4.2σ, which we interpret as associated with the active galaxy. The flux of high-energy neutrinos that we measured from NGC 1068 is more than an order of magnitude higher than the upper limit on emissions of tera–electron volt gamma rays from this source.

Classification of Alzheimer's disease stage using machine learning for left and right oxygenation difference signals in the prefrontal cortex: a patient-level, single-group, diagnostic interventional trial

OBJECTIVE

Recent evidence shows that indicators testing conventional olfactory function have a high degree of similarity to cognitive function tests and the potential to diagnose early-stage Alzheimer's disease (AD). In this study, the efficacy of functional near-infrared spectroscopy time-series data obtained through olfactory stimulation was investigated as an early diagnostic tool for mild cognitive impairment in AD using random forest, a machine learning algorithm.

PATIENTS AND METHODS

We conducted a patient-level, single-group, diagnostic interventional trial using near-infrared signals measured during olfactory stimulation in the prefrontal cortex of 178 older adults ranging from normal to participants with AD as markers to discriminate AD stages. We first divided the participants into normal older adults, AD mild cognitive impairment, and AD groups using dementia diagnostic criteria such as the Mini-Mental State Examination and Seoul Neuropsychological Screening Battery. We compared the left and right oxygenation difference by calculating the relative oxygenation difference from the change in relative oxygen concentration.

RESULTS

A total of 168 participants met the eligibility criteria: 70 (41.6%) had normal cognitive function; 42 (25%) mild cognitive impairment; 21 (12.5%) mild AD; and 35 (20.8%) moderate AD. A random forest machine learning model was developed to predict the AD stage, with an area under the receiver operating characteristic curve of 90.7% for mild cognitive impairment and AD, 90.99% for mild cognitive impairment, and 93.34% for AD only.

CONCLUSIONS

Based on the classification of the oxygenation difference index of the left and right prefrontal cortices during olfactory stimulation through machine learning, we found that it was possible to detect early-stage mild cognitive impairment in AD. Our results highlight the potential for early AD diagnosis using near-infrared signals from the prefrontal cortex obtained upon olfactory stimulation. Moreover, the results showed high similarity to the existing cognitive function tests and high accuracy in AD stage classification.

Search for Unstable Sterile Neutrinos with the IceCube Neutrino Observatory

We present a search for an unstable sterile neutrino by looking for a resonant signal in eight years of atmospheric ν_{μ} data collected from 2011 to 2019 at the IceCube Neutrino Observatory. Both the (stable) three-neutrino and the 3+1 sterile neutrino models are disfavored relative to the unstable sterile neutrino model, though with p values of 2.8% and 0.81%, respectively, we do not observe evidence for 3+1 neutrinos with neutrino decay. The best-fit parameters for the sterile neutrino with decay model from this study are Δm_{41}^{2}=6.7_{-2.5}^{+3.9}  eV^{2}, sin^{2}2θ_{24}=0.33_{-0.17}^{+0.20}, and g^{2}=2.5π±1.5π, where g is the decay-mediating coupling. The preferred regions of the 3+1+decay model from short-baseline oscillation searches are excluded at 90% C.L.

Strong Constraints on Neutrino Nonstandard Interactions from TeV-Scale ν_{μ} Disappearance at IceCube

We report a search for nonstandard neutrino interactions (NSI) using eight years of TeV-scale atmospheric muon neutrino data from the IceCube Neutrino Observatory. By reconstructing incident energies and zenith angles for atmospheric neutrino events, this analysis presents unified confidence intervals for the NSI parameter ε_{μτ}. The best-fit value is consistent with no NSI at a p value of 25.2%. With a 90% confidence interval of -0.0041≤ε_{μτ}≤0.0031 along the real axis and similar strength in the complex plane, this result is the strongest constraint on any NSI parameter from any oscillation channel to date.

Search for Relativistic Magnetic Monopoles with Eight Years of IceCube Data

We present an all-sky 90% confidence level upper limit on the cosmic flux of relativistic magnetic monopoles using 2886 days of IceCube data. The analysis was optimized for monopole speeds between 0.750c and 0.995c, without any explicit restriction on the monopole mass. We constrain the flux of relativistic cosmic magnetic monopoles to a level below 2.0×10^{-19}  cm^{-2} s^{-1} sr^{-1} over the majority of the targeted speed range. This result constitutes the most strict upper limit to date for magnetic monopoles with β≳0.8 and up to β∼0.995 and fills the gap between existing limits on the cosmic flux of nonrelativistic and ultrarelativistic magnetic monopoles.

Average SAR prediction, validation, and evaluation for a compact MR scanner head-sized RF coil

A recently developed compact 3 T (C3T) MRI scanner with high performance gradients [1, 2] has a dedicated radiofrequency (RF) transmit coil that exposes only the head, neck and a small portion of the upper body region during head-first scanning. Due to the unique coil geometry and patient positioning, the established SAR model used for a conventional whole-body scanner cannot be directly translated to the C3T. Here a specific absorption rate (SAR) estimation and validation framework was developed and used to implement a dedicated and accurate SAR prediction model for the C3T. Two different SAR prediction models for the C3T were defined and evaluated: one based on an anatomically derived exposed mass, and one using a fixed anatomical position located caudally to the RF coil to determine the exposed mass. After coil modeling and virtual human body simulation, the designed SAR prediction model was implemented on the C3T and verified with calorimetry and in vivo scan power monitoring. The fixed-demarcation exposed mass model was selected as appropriate exposed mass region to accurately estimate the SAR deposition in the patient on the C3T.

Glioblastoma patient-derived cell-based phenotypic drug screening and identification of possible action mechanisms through proteomic analysis

Because glioblastoma (GBM) exhibits high heterogeneity, it is desirable to use patient-derived cells from the first stage of screening for GBM drug discovery. Here, we describe a protocol to culture patient-derived GBM cells on the extracellular matrix-coated plates to allow high-throughput screening. Further, we detail approaches to identify the mechanism of action (MOA) of the selected effective drug through proteomics. This protocol will be useful for researchers interested in drug screening and the MOA of drugs.

For complete details on the use and execution of this protocol, please refer to Nam et al. (2021).

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Methods for patient-derived GBM cell culture

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Automated high-throughput screening methods using chemical libraries

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Quantitative mass spectrometry to elucidate mechanism of action of drugs

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Methods to perform data analysis from mass spectrometry

Identification of BRAF p. V600E-Mutant and Wild-Type by MR Imaging in Pleomorphic Xanthoastrocytoma and Anaplastic Pleomorphic Xanthoastrocytoma

BACKGROUND AND PURPOSE

Compared with BRAF p. V600E wild-type pleomorphic xanthoastrocytoma, BRAF p. V600E-mutant pleomorphic xanthoastrocytoma showed a higher survival rate. In this study, we focused on finding preoperative MR imaging differences between BRAF p. V600E mutant and wild-type in pleomorphic xanthoastrocytoma and anaplastic pleomorphic xanthoastrocytoma.

MATERIALS AND METHODS

Twenty-three patients with pathologically confirmed pleomorphic xanthoastrocytoma or anaplastic pleomorphic xanthoastrocytoma in our hospital were retrospectively analyzed from January 2015 to December 2020. They were divided into a BRAF p. V600E-mutant group (including 6 pleomorphic xanthoastrocytomas and 5 anaplastic pleomorphic xanthoastrocytomas) and a wild-type group (including 8 pleomorphic xanthoastrocytomas and 4 anaplastic pleomorphic xanthoastrocytomas). The preoperative MR imaging characteristics of these groups were statistically compared.

RESULTS

The wild-type pleomorphic xanthoastrocytoma group presented with more aggressive conventional and advanced MR imaging features than the mutant pleomorphic xanthoastrocytoma group, including greater mean maximum tumor diameter (3.1 [SD, 0.9] cm versus 1.7 [SD, 0.4 ] cm, P < .05), more frequent heterogeneous contrast enhancement of solid portions (100% versus 0%, P < .001), more obvious peritumoral edema (mean, [2.1 SD, 0.7] cm versus 0.6 [SD, 0.2] cm, P < .01), and lower mean minimum relative ADC (896 [SD, 86] versus 988 [SD, 73], P < .05) and mean relative ADC (1060 [SD, 159] versus 1248 [SD, 116], P < .05) on DWI. However, there was no significant difference in either conventional or advanced MR imaging features between the wild-type anaplastic pleomorphic xanthoastrocytoma group and the mutant anaplastic pleomorphic xanthoastrocytoma group.

CONCLUSIONS

Neurosurgeons should carefully interpret MR images before an operation and select appropriate surgical strategies according to genotype prediction.

Quantitative proteomic profiling of Cervicovaginal fluid from pregnant women with term and preterm birth

Background

Preterm birth (PTB) is one of major causes of perinatal mortality and neonatal morbidity, but knowledge of its complex etiology is still limited. Here we present cervicovaginal fluid (CVF) protein profiles of pregnant women who subsequently delivered at spontaneous preterm or term, aiming to identify differentially expressed CVF proteins in PTB and term birth.

Methods

The CVF proteome of women who sequentially delivered at preterm and term was analyzed using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with two-dimensional nanoflow liquid chromatography-tandem mass spectrometry (2D-nLC-MS/MS). We compared the CVF proteome of PTB (n = 5) and control subjects (term birth, n = 7) using pooled control CVF (term birth, n = 20) as spike-in standard.

Results

We identified 1294 CVF proteins, of which 605 were newly identified proteins. Of 990 proteins quantified in both PTB and term birth, 52 proteins were significantly up/down-regulated in PTB compared to term birth. The differentially expressed proteins were functionally associated to immune response, endopeptidase inhibitors and structural constituent of cytoskeleton. Finally, we confirm the down-regulation of SERPINB7 (a serine-type protease inhibitor) in PTB compared to control by Western blot.

Conclusions

Taken together, our study provide quantitative CVF proteome profiles of pregnant women who ultimately delivered at preterm and term. These promising results could help to improve the understanding of PTB etiology and to discover biomarkers for asymptomatic PTB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12953-021-00171-1.

SILAC-Based Quantitative Proteomic Analysis of Oxaliplatin-Resistant Pancreatic Cancer Cells

Simple Summary

Resistance to oxaliplatin remains a major challenge in pancreatic cancer therapy. However, molecular mechanisms underlying oxaliplatin resistance in pancreatic cancer is still unclear. The aim of this study was to identify global changes of proteins involved in oxaliplatin resistance in pancreatic cancer cells, thereby elucidating the multiple mechanisms of oxaliplatin resistance in pancreatic cancer. We presented the quantitative proteomic profiling of oxaliplatin-resistant pancreatic cancer cells via a stable isotope labelling by amino acids in cell culture (SILAC)-based shotgun proteomic approach. Multiple biological processes including DNA repair, cell cycle process, and type I interferon signaling pathway were enriched in oxaliplatin-resistant pancreatic cancer cells. Furthermore, we demonstrated that both Wntless homolog protein (WLS) and myristoylated alanine-rich C-kinase substrate (MARCKS) could participate in oxaliplatin resistance in pancreatic cancer cells.

Abstract

Oxaliplatin is a commonly used chemotherapeutic drug for the treatment of pancreatic cancer. Understanding the cellular mechanisms of oxaliplatin resistance is important for developing new strategies to overcome drug resistance in pancreatic cancer. In this study, we performed a stable isotope labelling by amino acids in cell culture (SILAC)-based quantitative proteomics analysis of oxaliplatin-resistant and sensitive pancreatic cancer PANC-1 cells. We identified 107 proteins whose expression levels changed (thresholds of 2-fold changes and p-value ≤ 0.05) between oxaliplatin-resistant and sensitive cells, which were involved in multiple biological processes, including DNA repair, cell cycle process, and type I interferon signaling pathway. Notably, myristoylated alanine-rich C-kinase substrate (MARCKS) and Wntless homolog protein (WLS) were upregulated in oxaliplatin-resistant cells compared to sensitive cells, as confirmed by qRT-PCR and Western blot analysis. We further demonstrated the activation of AKT and β-catenin signaling (downstream targets of MARCKS and WLS, respectively) in oxaliplatin-resistant PANC-1 cells. Additionally, we show that the siRNA-mediated suppression of both MARCKS and WLS enhanced oxaliplatin sensitivity in oxaliplatin-resistant PANC-1 cells. Taken together, our results provide insights into multiple mechanisms of oxaliplatin resistance in pancreatic cancer cells and reveal that MARCKS and WLS might be involved in the oxaliplatin resistance.

[Short-term effect of sodium zirconium cyclosilicate on potassium lowering in chronic kidney disease patients with hyperkalemia]

Objective: To investigate the efficacy of sodium zirconium cyclosilicate on emergency correction of hyperkalemia in chronic kidney disease patients. Methods: Patients with chronic kidney disease who were admitted to the Department of Nephrology of the First Affiliated Hospital of Zhengzhou University from May to June 2020 were selected. Those who had hyperkalemia and took sodium zirconium cyclosilicate powder were finally included. The patient's clinical data and laboratory results were collected. Results: A total of 24 results were included from 21 patients. The age of patients was (48.9±13.5) years old. Fourteen patients were male, and 7 patients were female. After 2 hours of administration, the venous potassium level decreased from (5.85±0.52) mmol/L to (5.15±0.43) mmol/L (P<0.001, n=21), with an average decline of (0.71±0.43) mmol/L. Meanwhile, the arterial potassium level decreased from (5.50±0.40) mmol/L to (4.88±0.33) mmol/L (P<0.001, n=10), with an average decline of (0.62±0.29) mmol/L. Based on the initial venous potassium level, the patients were further divided into three groups. The average potassium decrease in<5.5 mmol/L group (4 patients), 5.5-<6.0 mmol/L group (11 patients) and ≥6.0 mmol/L group (6 patients) was (0.46±0.26) mmol/L, (0.62±0.38) mmol/L and (1.04±0.45) mmol/L, respectively. There was statistically significant difference of potassium reduction among the three groups (P=0.045). Moreover, the extent of potassium reduction was positively correlated with baseline venous potassium level (r=0.603, P=0.004, n=21). The study did not reveal any treatment-related adverse event. Conclusion: Sodium zirconium cyclosilicate powder can rapidly and effectively reduce the serum potassium level in chronic kidney disease patients with hyperkalemia.