Deciphering two decades of cellular reprogramming in cancer: A bibliometric analysis of evolving trends and research frontiers.

Recent research has reevaluated the traditional view of cancer's linear progression and recurrence by introducing cellular reprogramming a process in which cancer cells can their state under certain conditions. This change is driven by a combination of genetic and epigenetic factors, with pivotal roles played by key genes, and pathways, notably Wnt and Notch. The complexity of cancer's behavior is further influenced by factors such as the epithelial-mesenchymal transition (EMT) and therapy-induced stress, both of which are significant contributors to cancer recurrence. In this context bibliometric analysis emerges as a crucial tool for evaluating the impacts and trends within scientific literature. Our study utilized bibliometrics to analysis the role of cellular reprogramming oncology over the past two decades, highlighting its potential to improve cancer treatment outcomes. In conducting this analysis, we searched for literature search on cellular reprogramming (CR) in the Web of Science database, covering the years 2002-2022. We employed visualization tools like Citespace, VOSviewer, and Bibliometrix to analyze the collected data resulting in a dataset of 3102 articles. The United States and China emerged as leading contributors to this field, with the University of Texas MD Anderson Cancer Center being the most prolific institution. Menendez was the most influential scholar in this research domain. Cancers was the journal with the most publications on this subject. The most local-cited document was the article titled "Hallmarks of Cancer: The Next Generation". A comprehensive analysis has been conducted based on keywords and cited references. In recent years, the research emphasis has shifted to "extracellular vesicles," "cancer therapy," and "cellular plasticity". Therefore, this analysis uses bibliometrics to chart cutting-edge progress in cancer's cellular reprogramming, aiding experts to quickly understand and innovate in this crucial area.

Radiomics analysis of lesion-specific pericoronary adipose tissue to predict major adverse cardiovascular events in coronary artery disease.

OBJECTIVE: To investigate the prognostic performance of radiomics analysis of lesion-specific pericoronary adipose tissue (PCAT) for major adverse cardiovascular events (MACE) with the guidance of CT derived fractional flow reserve (CT-FFR) in coronary artery disease (CAD). MATERIALS AND METHODS: The study retrospectively analyzed 608 CAD patients who underwent coronary CT angiography. Lesion-specific PCAT was determined by the lowest CT-FFR value and 1691 radiomic features were extracted. MACE included cardiovascular death, nonfatal myocardial infarction, unplanned revascularization and hospitalization for unstable angina. Four models were generated, incorporating traditional risk factors (clinical model), radiomics score (Rad-score, radiomics model), traditional risk factors and Rad-score (clinical radiomics model) and all together (combined model). The model performances were evaluated and compared with Harrell concordance index (C-index), area under curve (AUC) of the receiver operator characteristic. RESULTS: Lesion-specific Rad-score was associated with MACE (adjusted HR = 1.330, p = 0.009). The combined model yielded the highest C-index of 0.718, which was higher than clinical model (C-index = 0.639), radiomics model (C-index = 0.653) and clinical radiomics model (C-index = 0.698) (all p < 0.05). The clinical radiomics model had significant higher C-index than clinical model (p = 0.030). There were no significant differences in C-index between clinical or clinical radiomics model and radiomics model (p values were 0.796 and 0.147 respectively). The AUC increased from 0.674 for clinical model to 0.721 for radiomics model, 0.759 for clinical radiomics model and 0.773 for combined model. CONCLUSION: Radiomics analysis of lesion-specific PCAT is useful in predicting MACE. Combination of lesion-specific Rad-score and CT-FFR shows incremental value over traditional risk factors.

Thymoquinone: An Effective Natural Compound for Kidney Protection.

Kidney disease is a common health problem worldwide. Acute or chronic injuries may interfere with kidney functions, eventually resulting in irreversible kidney damage. A number of recent studies have shown that the plant-derived natural products have an extensive potential for renal protection. Thymoquinone (TQ) is an essential compound derived from Nigella Sativa (NS), which is widely applied in the Middle East as a folk medicine. Previous experiments have demonstrated that TQ has a variety of potential pharmacological effects, including anti-oxidant, antibacterial, antitumor, immunomodulatory, and neuroprotective activities. In particular, the prominent renal protective efficacy of TQ has been demonstrated in both in vivo and in vitro experiments. TQ can prevent acute kidney injuries from various xenobiotics through anti-oxidation, anti-inflammatory, and anti-apoptosis effects. In addition, TQ exhibited significant pharmacological effects on renal cell carcinoma, renal fibrosis, and urinary calculi. The essential mechanisms involve scavenging ROS and increasing anti-oxidant activity, decreasing inflammatory mediators, inducing apoptosis, and inhibiting migration and invasion. The purpose of this review is to conclude the pharmacological effects and the potential mechanisms of TQ in renal protection, shedding new light on the exploration of medicinal phyto-protective agents targeting kidneys.

Intravenous administration of IL-12 encoding self-replicating RNA-lipid nanoparticle complex leads to safe and effective antitumor responses.

Interleukin 12 (IL-12) is a potent immunostimulatory cytokine mainly produced by antigen-presenting cells (e.g., dendritic cells, macrophages) and plays an important role in innate and adaptive immunity against cancers. Therapies that can synergistically modulate innate immunity and stimulate adaptive anti-tumor responses are of great interest for cancer immunotherapy. Here we investigated the lipid nanoparticle-encapsulated self-replicating RNA (srRNA) encoding IL-12 (referred to as JCXH-211) for the treatment of cancers. Both local (intratumoral) and systemic (intravenous) administration of JCXH-211 in tumor-bearing mice induced a high-level expression of IL-12 in tumor tissues, leading to modulation of tumor microenvironment and systemic activation of antitumor immunity. Particularly, JCXH-211 can inhibit the tumor-infiltration of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). When combined with anti-PD1 antibody, it was able to enhance the recruitment of T cells and NK cells into tumors. In multiple mouse solid tumor models, intravenous injection of JCXH-211 not only eradicated large preestablished tumors, but also induced protective immune memory that prevented the growth of rechallenged tumors. Finally, intravenous injection of JCXH-211 did not cause noticeable systemic toxicity in tumor-bearing mice and non-human primates. Thus, our study demonstrated the feasibility of intravenous administration of JCXH-211 for the treatment of advanced cancers.

A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer.

PURPOSE: To develop and validate a nomogram for the preoperative diagnosis of T2 and T3 stage rectal cancer using MRI radiomics features of mesorectal fat. METHODS: The data of 288 patients with T2 and T3 stage rectal cancer were retrospectively collected. Radiomics features were extracted from the lesion region of interest (ROI) in the MRI high-resolution T2WI, apparent diffusion coefficient (ADC), and diffusion-weighted imaging (DWI) sequences. After using ICC inter-group consistency analysis and Pearson correlation analysis to reduce dimensions, LASSO regression analysis was performed to select features and calculate Rad-score for each sequence. Then, Combined_Radscore and nomogram were constructed based on the LASSO-selected features and clinical data for each sequence. Receiver operating characteristic curve (ROC) area under the curve (AUC) was used to evaluate the performance of the Rad-score model and nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical usability of the radiomics nomogram, which were combined with calibration curves to evaluate the prediction accuracy. RESULTS: The nomogram based on MRI-report T status and Combined_Radscore achieved AUCs of 0.921 and 0.889 in the training and validation cohorts, respectively. CONCLUSION: The nomogram can be stated that the radiomics nomogram based on multi-sequence MRI imaging of the mesorectal fat has excellent diagnosing performance for preoperative differentiation of T2 and T3 stage rectal cancer.

The Effects of PICALM rs3851179 and Age on Brain Atrophy and Cognition Along the Alzheimer's Disease Continuum.

Rs3851179, a variant of PICALM gene, and age are the risk factors of Alzheimer's disease (AD). AD is divided into early-onset AD (EOAD, < 65 years) and late-onset AD (LOAD, ≥ 65 years) by age. The purpose was to investigate the impact of different genotypes of PICALM rs3851179 on brain atrophy and cognitive decline across the AD continuum in different age groups. Four hundred seven cognitive normal (CN) controls, 362 mild cognitive impairment (MCI) patients, and 94 AD patients were enrolled to assess the interaction between AD continuum, age status, and PICALM on gray matter volume (GMV), global cognition, memory function, and executive function using full factorial ANCOVA (3 × 2 × 2). The interaction between AD continuum and PICALM significantly affected the GMV of the left putamen (PUT.L). rs3851179 A-allele carriers did not show a significant decrease in PUT.L GMV from CN to MCI to AD, while GG-allele carriers did. The interaction between AD continuum and age status was significant on GMV of the left angular gyrus (ANG.L) and right superior occipital gyrus (SOG.R). LOAD had higher GMV of ANG.L and SOG.R than EOAD. The interactive effects among AD continuum, age status, and PICALM were not significant on GMV but were significant on global cognition and executive function. The A-allele was found to have a protective effect on global cognition and executive function in EOAD, but not significantly so in LOAD. PICALM rs3851179 A-allele might alleviate the atrophy of PUT.L across the AD continuum than GG-allele. Age status did not affect the interaction between AD continuum and PICALM on brain atrophy. The ANG.L and SOG.R atrophied more severely in EOAD than in LOAD. Rs3851179 A-allele was protective for global cognition and executive function in EOAD.

Resting-State fMRI Study of Vigilance Under Circadian and Homeostatic Modulation Based on Fractional Amplitude of Low-Frequency Fluctuation and Regional Homogeneity in Humans Under Normal Entrained Conditions.

BACKGROUND: How brain neural activity changes at multiple time points throughout the day and the neural mechanisms underlying time-dependent modulation of vigilance are less clear. PURPOSE: To explore the effect of circadian rhythms and homeostasis on brain neural activity and the potential neural basis of time-dependent modulation of vigilance. STUDY TYPE: Prospective. SUBJECTS: A total of 30 healthy participants (22-27 years old). FIELD STRENGTH/SEQUENCE: A 3.0 T, T1-weighted imaging, echo-planar functional MRI (fMRI). ASSESSMENT: Six resting-state fMRI (rs-fMRI) scanning sessions were performed at fixed times (9:00 h, 13:00 h, 17:00 h, 21:00 h, 1:00 h, and 5:00 h) to investigate fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) diurnal variation. The fALFF/ReHo and the result of the psychomotor vigilance task were used to assess local neural activity and vigilance. STATISTICAL TESTS: One-way repeated measures analysis of variance (ANOVA) was used to assess changes in vigilance (P < 0.05) and neural activity in the whole brain (P < 0.001 at the voxel level and P < 0.01 at the cluster level, Gaussian random field [GRF] corrected). Correlation analysis was used to examine the relationship between neural activity and vigilance at all-time points of the day. RESULTS: The fALFF/ReHo in the thalamus and some perceptual cortices tended to increase from 9:00 h to 13:00 h and from 21:00 h to 5:00 h, whereas the key nodes of the default mode network (DMN) tended to decrease from 21:00 h to 5:00 h. The vigilance tended to decrease from 21:00 h to 5:00 h. The fALFF/ReHo in the thalamus and some perceptual cortices was negatively correlated with vigilance at all-time points of the day, whereas the fALFF/ReHo in the key nodes of the DMN was positively correlated with vigilance. DATA CONCLUSION: Neural activities in the thalamus and some perceptual cortices show similar trends throughout the day, whereas the key nodes of the DMN show roughly opposite trends. Notably, diurnal variation of the neural activity in these brain regions may be an adaptive or compensatory response to changes in vigilance. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: 1.

Regulatory mechanism of macrophage polarization based on Hippo pathway.

Macrophages are found to infiltrate and migrate in a large number of Tumor-associated macrophages (TMEs) and other macrophages in the microenvironment of tumors and related diseases, and undergo phenotypic changes in response to a variety of cytokines, mainly including the primary phenotype M2 and the anti-tumor phenotype M1. The Hippo signaling pathway affects the development of cancer and other diseases through various biological processes, such as inhibition of cell growth. In this review, we focus on immune cells within the microenvironment of tumors and other diseases, and the role of the Hippo pathway in tumors on macrophage polarization in the tumor microenvironment (TME) and other diseases.

Preoperative predicting invasiveness of lung adenocarcinoma manifesting as ground-glass nodules based on multimodal images of dual-layer spectral detector CT radiomics models.

OBJECTIVE: To construct and validate conventional and radiomics models based on dual-layer spectral CT radiomics for preoperative prediction of lung ground glass nodules (GGNs) invasiveness. MATERIALS AND METHODS: A retrospective study was conducted on 176 GGNs patients who underwent chest non-contrast enhancement scan on dual-layer spectral detector CT at our hospital within 2 weeks before surgery. Patients were randomized into the training cohort and testing cohort. Clinical features, imaging features and spectral quantitative parameters were collected to establish a conventional model. Radiomics models were established by extracting 1781 radiomics features form regions of interest of each spectral image [120 kVp poly energetic images (PI), 60 keV images and electron density maps], respectively. After selecting the optimal radiomic features and integrating multiple machine learning models, the conventional model, PI model, 60 keV model, electron density (ED) model and combined model based on multimodal spectral images were finally established. The performance of these models was assessed through the evaluation of discrimination, calibration, and clinical application. RESULTS: In the conventional model, age, vacuole sign, 60 keV and ED were independent risk factors of invasiveness. The combined model using logistic regression-least absolute shrinkage and selection operator classifiers was the optimal model with a higher area under the curve of the training (0.961, 95% confidence interval, CI: 0.932-0.991) and testing set (0.944, 0.890-0.999). CONCLUSION: The combined models are helpful to predict the invasiveness of GGNs before surgery and guide the individualized treatment of patients.

Multiregional-based magnetic resonance imaging radiomics model for predicting tumor deposits in resectable rectal cancer.

PURPOSE: To establish and validate an integrated model incorporating multiregional magnetic resonance imaging (MRI) radiomics features and clinical factors to predict tumor deposits (TDs) preoperatively in resectable rectal cancer (RC). METHODS: This study retrospectively included 148 resectable RC patients [TDs+ (n = 45); TDs- (n = 103)] from August 2016 to August 2022, who were divided randomly into a testing cohort (n = 45) and a training cohort (n = 103). Radiomics features were extracted from the volume of interest on T2-weighted images (T2WI) and diffusion-weighted images (DWI) from pretreatment MRI. Model construction was performed after feature selection. Finally, five classification models were developed by support vector machine (SVM) algorithm to predict TDs in resectable RC using the selected clinical factor, single-regional radiomics features (extracted from primary tumor), and multiregional radiomics features (extracted from the primary tumor and mesorectal fat). Receiver-operating characteristic (ROC) curve analysis was employed to assess the discrimination performance of the five models. The AUCs of five models were compared by DeLon's test. RESULTS: The training and testing cohorts included 31 (30.1%) and 14 (31.1%) patients with TDs, respectively. The AUCs of multiregional radiomics, single-regional radiomics, and the clinical models for predicting TDs were 0.839, 0.765, and 0.793, respectively. An integrated model incorporating multiregional radiomics features and clinical factors showed good predictive performance for predicting TDs in resectable RC (AUC, 0.931; 95% CI, 0.841-0.988), which demonstrated superiority over clinical model (P = 0.016), the single-regional radiomics model (P = 0.042), and the multiregional radiomics model (P = 0.025). CONCLUSION: An integrated model combining multiregional MRI radiomic features and clinical factors can improve prediction performance for TDs and guide clinicians in implementing treatment plans individually for resectable RC patients.

Risk prediction of intraoperative pain in percutaneous microwave ablation of lung tumors under CT guidance.

OBJECTIVES: To evaluate the effect of intraoperative pain in microwave ablation of lung tumors (MWALT) on local efficacy and establish the pain risk prediction model. METHODS: It was a retrospectively study. Consecutive patients with MWALT from September 2017 to December 2020 were divided into mild and severe pain groups. Local efficacy was evaluated by comparing technical success, technical effectiveness, and local progression-free survival (LPFS) in two groups. All cases were randomly allocated into training and validation cohorts at a ratio of 7:3. A nomogram model was established using predictors identified by logistics regression in training dataset. The calibration curves, C-statistic, and decision curve analysis (DCA) were used to evaluate the accuracy, ability, and clinical value of the nomogram. RESULTS: A total of 263 patients (mild pain group: n = 126; severe pain group: n = 137) were included in the study. Technical success rate and technical effectiveness rate were 100% and 99.2% in the mild pain group and 98.5% and 97.8% in the severe pain group. LPFS rates at 12 and 24 months were 97.6% and 87.6% in the mild pain group and 91.9% and 79.3% in the severe pain group (p = 0.034; HR: 1.90). The nomogram was established based on three predictors: depth of nodule, puncture depth, and multi-antenna. The prediction ability and accuracy were verified by C-statistic and calibration curve. DCA curve suggested the proposed prediction model was clinically useful. CONCLUSIONS: Severe intraoperative pain in MWALT reduced the local efficacy. An established prediction model could accurately predict severe pain and assist physicians in choosing a suitable anesthesia type. CLINICAL RELEVANCE STATEMENT: This study firstly provides a prediction model for the risk of severe intraoperative pain in MWALT. Physicians can choose a suitable anesthesia type based on pain risk, in order to improve patients' tolerance as well as local efficacy of MWALT. KEY POINTS: • The severe intraoperative pain in MWALT reduced the local efficacy. • Predictors of severe intraoperative pain in MWALT were the depth of nodule, puncture depth, and multi-antenna. • The prediction model established in this study can accurately predict the risk of severe pain in MWALT and assist physicians in choosing a suitable anesthesia type.

[Hydrochemical Characteristics and Control Factors of Groundwater in Shunping County, Hebei Province].

In order to study the chemical characteristics and ion source of groundwater and further serve the scientific development and management of water resources in Shunping County. A total of 33 groups of karst water and 12 groups of pore water samples were collected systematically in Shunping County, and the hydrochemical types, composition characteristics, and main controlling factors of various types of groundwater were analyzed by using Gibbs diagram, ion ratio relation, and multivariate statistical analysis methods, and the contribution rates of various sources to groundwater solutes were evaluated. The results showed that the pore water and karst water in the study area were weakly alkaline, with TDS ranging from 245.89 to 430.00 mg·L-1 and 223.54 to 1347.80 mg·L-1, respectively. The anion components of groundwater were mainly HCO3- and Ca2+. Groundwater in the study area could be grouped into PW1 and PW2 pore water and KW1, KW2, and KW3 karst water. PW1 and KW1 were HCO3-Ca·Mg type, PW2 was HCO3·Cl-Ca·Mg type, KW2 was HCO3·NO3-Ca·Mg type, and KW3 was SO4-Ca·Mg type with high salinity. The weathering of carbonate rock mainly composed of dolomite and silicate rock mainly composed of albiar and potassium feldspar were the main material sources of groundwater, and their contributions to each water body were 39.69% to 66.13% and 11.87% to 58.38%. Sewage discharge and fertilizer use in human activities had significant effects on KW2 groundwater and PW1, PW2, and KW1 groundwater, respectively. In addition, the contribution rate of atmospheric precipitation to each water body ranged from 1.09% to 7.94% on average.

[Hydrochemical Characteristics and Control Factors of Pore-water in the Middle and Upper Reaches of Muwen River].

In order to study the hydrochemical characteristics and ion sources of pore water in the middle and upper reaches of the Mouwen River, 29 groups of pore-water samples were collected in the Laiwu Basin. The main ion characteristics and their controlling factors of pore-water in this area were analyzed by using correlation and principal component analysis, Piper trigram, and Gibbs diagram methods. The main material sources of pore water in this area were revealed. The results showed that HCO3-, NO3-, SO42-, and Ca2+ were the main anions and cations in the pore water of the middle and upper reaches of the Mouwen River. With TDS >1000 mg·L-1 as the standard, the normal water chemistry type was mainly HCO3·NO3·SO4-Ca and HCO3·SO4-Ca·Mg, whereas the abnormal water chemistry type was mainly NO3·Cl-Ca. The chemical evolution of groundwater was mainly influenced by rock weathering, cation alternation adsorption, and human activities. Na++K+ mainly came from silicate weathering and dissolution, and HCO3-, Ca2+, and Mg2+ came from calcite weathering and dissolution involving carbonate and sulfuric acid. Alternation adsorption of cations and weathering of silicate rock provided a surplus of Ca2+ and Mg2+ for pore water. Industrial and mining activities such as domestic sewage mixing, agricultural planting activities, and iron and coal mining changed the chemical composition of pore water, especially NO3- exceeding the standard, which has become the main problem of the local groundwater chemical environment.

Altered static and dynamic indices of intrinsic brain activity in patients with subcortical ischemic vascular disease: a resting-state functional magnetic resonance imaging analysis.

PURPOSE: To explore the static and dynamic characteristics of intrinsic brain activity (IBA) in subcortical ischemic vascular disease (SIVD) patients with or without cognitive impairment. METHODS: In total, 90 participants were recruited, including 32 SIVD patients with cognitive impairment (SIVD-CI, N = 32), 26 SIVD patients with no cognitive impairment (SIVD-NCI, N = 26), and 32 healthy controls (HC, N = 32) matched for age, gender, and education. All subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and neuropsychological tests. Amplitude of low-frequency fluctuation (ALFF) was calculated to reflect static alterations of regional IBA. Sliding window analysis was conducted in order to explore the dynamic characteristics. RESULTS: Both SIVD-CI and SIVD-NCI group showed significantly decreased ALFF in left angular gyrus (ANG), whereas SIVD-CI group showed increased ALFF in right superior frontal gyrus (SFG), compared with HCs. Furthermore, SIVD-CI group showed significantly decreased ALFF dynamics (dALFF) in right precuneus (PreCu) and left dorsal anterior cingulate cortex (dACC), compared with HC and SIVD-NCI groups (Gaussian random field-corrected, voxel-level P < 0.001, cluster-level P < 0.05). No dynamic changes were detected between SIVD-NCI group and HC group. The mean ALFF value in left ANG of SIVD-CI group was correlated with the score of delayed memory scale. CONCLUSION: ANG may be a vulnerable brain region in SIVD patients. Temporal dynamic analysis could serve as a sensitive and promising method to investigate IBA alterations in SIVD patients.

Effects of race and test preparation resources on standardized test scores, a pilot study.

BACKGROUND: Little research exists on the relationship between pre-examination resources, race, and standardized test outcomes. This study aimed to determine the effect of test preparation resources and race on test scores. METHODS: We surveyed medical students at an allopathic institution on the use of test preparation materials and their test scores. Students were grouped by self-identified race. Underrepresented in Medicine (URiM) students were defined as Black/African American (AA), Hispanic/Latino (HL), Native American (NA) and multiple races. Univariate analysis and linear regression were used for statistical analysis. RESULTS: 192 students completed the survey (response rate = 33%). URiM students reported more MCAT attempts than other students. No differences between scores existed between races. There was no association between scores and the use of test preparation resources. CONCLUSIONS: We found that URiM students took the MCAT more times than their peers; however, we found no racial/ethnic differences in examination preparation resources or scores.

Digital gait markers to potentially distinguish fragile X-associated tremor/ataxia syndrome, Parkinson's disease, and essential tremor.

Background: Fragile X-associated tremor/ataxia syndrome (FXTAS), a neurodegenerative disease that affects carriers of a 55-200 CGG repeat expansion in the fragile X messenger ribonucleoprotein 1 (FMR1) gene, may be given an incorrect initial diagnosis of Parkinson's disease (PD) or essential tremor (ET) due to overlapping motor symptoms. It is critical to characterize distinct phenotypes in FXTAS compared to PD and ET to improve diagnostic accuracy. Fast as possible (FP) speed and dual-task (DT) paradigms have the potential to distinguish differences in gait performance between the three movement disorders. Therefore, we sought to compare FXTAS, PD, and ET patients using quantitative measures of functional mobility and gait under self-selected (SS) speed, FP, and DT conditions. Methods: Participants with FXTAS (n = 22), PD (n = 23), ET (n = 20), and controls (n = 20) underwent gait testing with an inertial sensor system (APDM™). An instrumented Timed Up and Go test (i-TUG) was used to measure movement transitions, and a 2-min walk test (2MWT) was used to measure gait and turn variables under SS, FP, and DT conditions, and dual-task costs (DTC) were calculated. ANOVA and multinomial logistic regression analyses were performed. Results: PD participants had reduced stride lengths compared to FXTAS and ET participants under SS and DT conditions, longer turn duration than ET participants during the FP task, and less arm symmetry than ET participants in SS gait. They also had greater DTC for stride length and velocity compared to FXTAS participants. On the i-TUG, PD participants had reduced sit-to-stand peak velocity compared to FXTAS and ET participants. Stride length and arm symmetry index during the DT 2MWT was able to distinguish FXTAS and ET from PD, such that participants with shorter stride lengths were more likely to have a diagnosis of PD and those with greater arm asymmetry were more likely to be diagnosed with PD. No gait or i-TUG parameters distinguished FXTAS from ET participants in the regression model. Conclusion: This is the first quantitative study demonstrating distinct gait and functional mobility profiles in FXTAS, PD, and ET which may assist in more accurate and timely diagnosis.

PICALM rs3851179 Variants Modulate Left Postcentral Cortex Thickness, CSF Amyloid ß42, and Phosphorylated Tau in the Elderly.

PICALM rs3851179, one of the genes most frequently linked to susceptibility of late-onset Alzheimer's disease (LOAD), plays a crucial role in regulating amyloid precursor protein, and amyloid ß (Aß) transcytosis. To explore the effects of PICALM and AD continuum stage on cortex thickness, CSF Aß, and tau, 188 cognitively normal controls, 261 MCI patients, and 140 early LOAD patients were recruited, and each group was divided into rs3851179 A-carriers and GG-carriers. A full factorial ANCOVA was used to analyze the main effects and interactive effects of AD continuum stage, and PICALM. The interactive effects of AD continuum stage and PICALM on cortex thickness and CSF biomarkers were not significant. The main effect of PICALM was significant on the left postcentral cortex thickness, and the cortex thickness of A-carriers was less than that of GG-carriers. The rs3851179 A-carriers displayed higher Aß42 levels and Aß42/40 ratios, and lower P/T-tau ratios, compared with GG-carriers. A higher MMSE score was found in A-carriers among the LOAD patients. In conclusion, the main effects of PICALM were independent of AD continuum stage, and PICLAM rs3851179 genotypes may modulate left postcentral cortex thickness, Aß42 level, and P/T-tau ratio. The rs3851179 A-allele may protect the cognitive function of LOAD patients.

The role of bactericidal and opsonic activity in immunity against Bordetella pertussis.

INTRODUCTION: Pertussis vaccines have drastically reduced the disease burden in humans since their implementation. Despite their success, pertussis remains an important global public health challenge. Bordetella pertussis resurgence could be a result of greater surveillance combined with improved diagnosis methods, changes in Bordetella pertussis biology, vaccine schedules, and/or coverage. Additionally, mechanisms of protection conferred by acellular pertussis (aP) and whole-cell pertussis (wP) vaccines differ qualitatively. There are no clear immune correlates of protection for pertussis vaccines. Pertussis antigens can induce toxin neutralizing antibodies, block adherence or engage complement mediated phagocytic/bactericidal killing. AREAS COVERED: We reviewed the existing evidence on antibody-mediated serum bactericidal and opsonophagocytic activity and discussed the relevance of these functional antibodies in the development of next-generation pertussis vaccines. EXPERT OPINION: Current paradigm proposes that wP vaccines may confer greater herd protection than aP vaccines due to their enhanced clearance of bacteria from the nasopharynx in animal models. Functional antibodies may contribute to the reduction of nasal colonization, which differentiates aP and wP vaccines. Understanding the intrinsic differences in protective immune responses elicited by each class of vaccines will help to identify biomarkers that can be used as immunological end points in clinical trials.

Preoperative Ki-67 proliferation index prediction with a radiomics nomogram in stage T1a-b lung adenocarcinoma.

OBJECTIVES: To establish a radiomics nomogram for preoperative prediction of Ki-67 proliferation index in stage T1a-b lung adenocarcinoma. METHODS: A total of 206 patients with pathologically confirmed lung adenocarcinoma who underwent CT scans within 2 weeks preoperatively from January 2016 to June 2020 were retrospectively included. Ki-67 index ≤ 10% was considered low expression, and Ki-67 index > 10% was considered high expression. The primary cohort was randomized with a 7:3 ratio into a training cohort (n = 145) and a validation cohort (n = 61). The minimum redundancy maximum relevance (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used for feature selection, and radiomics signature was constructed. Univariate and multivariate logistic regression analyses were used to identify clinically important risk factors and radiomics signature associated with Ki-67 proliferation index, which were then combined into radiomics nomogram. RESULTS: Tumor maximum diameter (P = 0.005), lobulation (P = 0.002), absent of vacuole (P < 0.001), and Radscore (P < 0.001) were independent risk predictors of high Ki-67 proliferation index expression. The radiomics nomogram showed good predictive efficacy. The AUC, sensitivity, specificity and accuracy of radiomics nomogram in the training and validation cohorts were 0.91 (95% CI: 0.86-0.96), 87.9%, 80.5%, 83.4% and 0.85 (95% CI: 0.75-0.94), 71.9%, 82.8% and 77.0%. Decision curve analysis further demonstrated the clinical utility of the nomogram. CONCLUSIONS: Radiomics nomogram provide a non-invasive method to predict Ki-67 proliferation index preoperatively in stage T1a-b lung adenocarcinoma, which might be the supplementary information for clinicians to choose the appropriate treatment program.

A Nomogram Combined Radiomics and Clinical Features as Imaging Biomarkers for Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma.

Objectives: To develop and validate a nomogram model based on radiomics features for preoperative prediction of visceral pleural invasion (VPI) in patients with lung adenocarcinoma. Methods: A total of 659 patients with surgically pathologically confirmed lung adenocarcinoma underwent CT examination. All cases were divided into a training cohort (n = 466) and a validation cohort (n = 193). CT features were analyzed by two chest radiologists. CT radiomics features were extracted from CT images. LASSO regression analysis was applied to determine the most useful radiomics features and construct radiomics score (radscore). A nomogram model was developed by combining the optimal clinical and CT features and the radscore. The model performance was evaluated using ROC analysis, calibration curve and decision curve analysis (DCA). Results: A total of 1316 radiomics features were extracted. A radiomics signature model with a selection of the six optimal features was developed to identify patients with or without VPI. There was a significant difference in the radscore between the two groups of patients. Five clinical features were retained and contributed as clinical feature models. The nomogram combining clinical features and radiomics features showed improved accuracy, specificity, positive predictive value, and AUC for predicting VPI, compared to the radiomics model alone (specificity: training cohort: 0.89, validation cohort: 0.88, accuracy: training cohort: 0.84, validation cohort: 0.83, AUC: training cohort: 0.89, validation cohort: 0.89). The calibration curve and decision curve analyses suggested that the nomogram with clinical features is beyond the traditional clinical and radiomics features. Conclusion: A nomogram model combining radiomics and clinical features is effective in non-invasively prediction of VPI in patients with lung adenocarcinoma.