A lncRNA from the FTO locus acts as a suppressor of the m6A writer complex and p53 tumor suppression signaling.

N6-methyladenosine (m6A) of mRNAs modulated by the METTL3-METTL14-WTAP-RBM15 methyltransferase complex and m6A demethylases such as FTO play important roles in regulating mRNA stability, splicing, and translation. Here, we demonstrate that FTO-IT1 long noncoding RNA (lncRNA) was upregulated and positively correlated with poor survival of patients with wild-type p53-expressing prostate cancer (PCa). m6A RIP-seq analysis revealed that FTO-IT1 knockout increased mRNA m6A methylation of a subset of p53 transcriptional target genes (e.g., FAS, TP53INP1, and SESN2) and induced PCa cell cycle arrest and apoptosis. We further showed that FTO-IT1 directly binds RBM15 and inhibits RBM15 binding, m6A methylation, and stability of p53 target mRNAs. Therapeutic depletion of FTO-IT1 restored mRNA m6A level and expression of p53 target genes and inhibited PCa growth in mice. Our study identifies FTO-IT1 lncRNA as a bona fide suppressor of the m6A methyltransferase complex and p53 tumor suppression signaling and nominates FTO-IT1 as a potential therapeutic target of cancer.

Phosphorylated RB Promotes Cancer Immunity by Inhibiting NF-κB Activation and PD-L1 Expression.

Aberrant expression of programmed death ligand-1 (PD-L1) in tumor cells promotes cancer progression by suppressing cancer immunity. The retinoblastoma protein RB is a tumor suppressor known to regulate the cell cycle, DNA damage response, and differentiation. Here, we demonstrate that RB interacts with nuclear factor κB (NF-κB) protein p65 and that their interaction is primarily dependent on CDK4/6-mediated serine-249/threonine-252 (S249/T252) phosphorylation of RB. RNA-seq analysis shows a subset of NF-κB pathway genes including PD-L1 are selectively upregulated by RB knockdown or CDK4/6 inhibitor. S249/T252-phosphorylated RB inversely correlates with PD-L1 expression in patient samples. Expression of a RB-derived S249/T252 phosphorylation-mimetic peptide suppresses radiotherapy-induced upregulation of PD-L1 and augments therapeutic efficacy of radiation in vivo. Our findings reveal a previously unrecognized tumor suppressor function of hyperphosphorylated RB in suppressing NF-κB activity and PD-L1 expression and suggest that the RB-NF-κB axis can be exploited to overcome cancer immune evasion triggered by conventional or targeted therapies.

DUB3 Promotes BET Inhibitor Resistance and Cancer Progression by Deubiquitinating BRD4.

The bromodomain and extra-terminal domain (BET) protein BRD4 is emerging as a promising anticancer therapeutic target. However, resistance to BET inhibitors often occurs, and it has been linked to aberrant degradation of BRD4 protein in cancer. Here, we demonstrate that the deubiquitinase DUB3 binds to BRD4 and promotes its deubiquitination and stabilization. Expression of DUB3 is transcriptionally repressed by the NCOR2-HDAC10 complex. The NCOR2 gene is frequently deleted in castration-resistant prostate cancer patient specimens, and loss of NCOR2 induces elevation of DUB3 and BRD4 proteins in cancer cells. DUB3-proficient prostate cancer cells are resistant to the BET inhibitor JQ1 in vitro and in mice, but this effect is diminished by DUB3 inhibitory agents such as CDK4/6 inhibitor in a RB-independent manner. Our findings identify a previously unrecognized mechanism causing BRD4 upregulation and drug resistance, suggesting that DUB3 is a viable therapeutic target to overcome BET inhibitor resistance in cancer.

Genomic analysis of spermatocytic tumors demonstrates recurrent molecular alterations in cases with malignant clinical behavior.

Spermatocytic tumor (ST) is a rare type of germ cell tumor that occurs exclusively in the postpubertal testis and typically affects elderly men. Most STs are benign, but rare cases exhibit aggressive clinical behavior, often in association with transition to sarcomatoid histology. Limited molecular analyses have been performed on STs; therefore, their genomic and epigenomic features remain incompletely described. Twenty-seven samples from 25 individual patients were analyzed with a combination of DNA sequencing panels, genomic methylation profiling, SNP array, isochromosome (12p) [i(12p)] FISH, and immunohistochemistry. The series included five metastasizing tumors (three with sarcomatoid transformation, one anaplastic, and one conventional) and 20 non-metastasizing tumors (14 anaplastic and six conventional). Anaplastic tumors comprised a monomorphic population of intermediate-sized neoplastic cells, as previously described. Multiomic analyses demonstrated that there were two genomic subgroups of STs: one with diploid genomes and hotspot RAS/RAF variants and the other with global ploidy shift and absence of recurrent mutations. Relative gain of chromosome 9 was a consistent finding in both subgroups. A comparison of metastasizing and non-metastasizing cases demonstrated that aggressive behavior was associated with the acquisition of pathogenic TP53 mutations and/or relative gains of 12p/i(12p). In cases with sarcomatoid transformation, TP53 mutations seem to underlie the transition to sarcomatoid histology. Genomic methylation analysis demonstrated that aggressive cases with gains of 12p cluster closer to pure seminomas than to STs without gains of 12p. In conclusion, STs include two genomic subgroups, characterized by global ploidy shifts without recurrent mutations and diploid genomes with RAS/RAF hotspot mutations, respectively. Biologic progression was associated with relative gains of 12p and TP53 mutations. The findings in STs with relative gains of 12p suggest that they may exhibit biologic characteristics akin to those seen in germ cell neoplasia in situ-related germ cell tumors rather than non-germ cell neoplasia in situ-derived STs. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Optical Camera Communications in Healthcare: A Wearable LED Transmitter Evaluation during Indoor Physical Exercise.

This paper presents an experimental evaluation of a wearable light-emitting diode (LED) transmitter in an optical camera communications (OCC) system. The evaluation is conducted under conditions of controlled user movement during indoor physical exercise, encompassing both mild and intense exercise scenarios. We introduce an image processing algorithm designed to identify a template signal transmitted by the LED and detected within the image. To enhance this process, we utilize the dynamics of controlled exercise-induced motion to limit the tracking process to a smaller region within the image. We demonstrate the feasibility of detecting the transmitting source within the frames, and thus limit the tracking process to a smaller region within the image, achieving an reduction of 87.3% for mild exercise and 79.0% for intense exercise.

Cost-Effective Optical Wireless Sensor Networks: Enhancing Detection of Sub-Pixel Transmitters in Camera-Based Communications.

In the domain of the Internet of Things (IoT), Optical Camera Communication (OCC) has garnered significant attention. This wireless technology employs solid-state lamps as transmitters and image sensors as receivers, offering a promising avenue for reducing energy costs and simplifying electronics. Moreover, image sensors are prevalent in various applications today, enabling dual functionality: recording and communication. However, a challenge arises when optical transmitters are not in close proximity to the camera, leading to sub-pixel projections on the image sensor and introducing strong channel dependence. Previous approaches, such as modifying camera optics or adjusting image sensor parameters, not only limited the camera's utility for purposes beyond communication but also made it challenging to accommodate multiple transmitters. In this paper, a novel sub-pixel optical transmitter discovery algorithm that overcomes these limitations is presented. This algorithm enables the use of OCC in scenarios with static transmitters and receivers without the need for camera modifications. This allows increasing the number of transmitters in a given scenario and alleviates the proximity and size limitations of the transmitters. Implemented in Python with multiprocessing programming schemes for efficiency, the algorithm achieved a 100% detection rate in nighttime scenarios, while there was a 89% detection rate indoors and a 72% rate outdoors during daylight. Detection rates were strongly influenced by varying transmitter types and lighting conditions. False positives remained minimal, and processing times were consistently under 1 s. With these results, the algorithm is considered suitable for export as a web service or as an intermediary component for data conversion into other network technologies.

Deepfake Histologic Images for Enhancing Digital Pathology.

A pathologist's optical microscopic examination of thinly cut, stained tissue on glass slides prepared from a formalin-fixed paraffin-embedded tissue blocks is the gold standard for tissue diagnostics. In addition, the diagnostic abilities and expertise of pathologists is dependent on their direct experience with common and rarer variant morphologies. Recently, deep learning approaches have been used to successfully show a high level of accuracy for such tasks. However, obtaining expert-level annotated images is an expensive and time-consuming task, and artificially synthesized histologic images can prove greatly beneficial. In this study, we present an approach to not only generate histologic images that reproduce the diagnostic morphologic features of common disease but also provide a user ability to generate new and rare morphologies. Our approach involves developing a generative adversarial network model that synthesizes pathology images constrained by class labels. We investigated the ability of this framework in synthesizing realistic prostate and colon tissue images and assessed the utility of these images in augmenting the diagnostic ability of machine learning methods and their usability by a panel of experienced anatomic pathologists. Synthetic data generated by our framework performed similar to real data when training a deep learning model for diagnosis. Pathologists were not able to distinguish between real and synthetic images, and their analyses showed a similar level of interobserver agreement for prostate cancer grading. We extended the approach to significantly more complex images from colon biopsies and showed that the morphology of the complex microenvironment in such tissues can be reproduced. Finally, we present the ability for a user to generate deepfake histologic images using a simple markup of sematic labels.

Reporting on Race and Racial Disparities in Breast Cancer: The Neglect of Racism as a Driver of Inequitable Care.

OBJECTIVE: This study reviews the surgical literature on racial disparities in breast cancer mortality, specifically evaluating the inclusion, justification, and discussion of race and ethnicity as a driver of disparities. SUMMARY OF BACKGROUND DATA: The volume of research on racial disparities has increased over the past 2 decades, but we hypothesize that there is considerable variation in how race is contextualized, defined, and captured in the disparities literature, leading to its questionable validity and relevance as a covariate. Recent guidelines for reporting have been suggested, but not yet applied. METHODS: A rubric was developed to evaluate the reporting of race and/or ethnicity. A systematic review (2010-2020) was performed to identify studies reporting on racial disparities in breast cancer surgery and mortality. We then evaluated these original articles based on key domains of race and/or ethnicity: justification for inclusion, formal definition, methodology used for classification, and type of racism contributing to disparity. RESULTS: Of the 52 studies assessed, none provided a formal definition for race and/or ethnicity. A justification for the inclusion of race and/or ethnicity was provided in 71% of the studies. Although 81% of studies discussed at least 1 potential driver of observed racial disparities, only 1 study explicitly named racism as a driver of racial disparities. CONCLUSIONS: Significant improvement in the reporting on racial disparities in breast cancer surgical literature is warranted. A more rigorous framework should be applied by both researchers and publishers in reporting on race, racial health disparities, and racism.

Cell adhesion and immune response, two main functions altered in the transcriptome of seasonally regressed testes of two mammalian species.

In species with seasonal breeding, male specimens undergo substantial testicular regression during the nonbreeding period of the year. However, the molecular mechanisms that control this biological process are largely unknown. Here, we report a transcriptomic analysis on the Iberian mole, Talpa occidentalis, in which the desquamation of live, nonapoptotic germ cells is the major cellular event responsible for testis regression. By comparing testes at different reproductive states (active, regressing, and inactive), we demonstrate that the molecular pathways controlling the cell adhesion function in the seminiferous epithelium, such as the MAPK, ERK, and TGF-ß signaling, are altered during the regression process. In addition, inactive testes display a global upregulation of genes associated with immune response, indicating a selective loss of the "immune privilege" that normally operates in sexually active testes. Interspecies comparative analyses using analogous data from the Mediterranean pine vole, a rodent species where testis regression is controlled by halting meiosis entry, revealed a common gene expression signature in the regressed testes of these two evolutionary distant species. Our study advances in the knowledge of the molecular mechanisms associated to gonadal seasonal breeding, highlighting the existence of a conserved transcriptional program of testis involution across mammalian clades.

miRNA as biomarker in lung cancer.

Lung cancer has a high prevalence and mortality due to its late diagnosis and limited treatment, so it is essential to find biomarkers that allow a faster diagnosis and improve the survival of these patients. In this sense, biomarkers based on miRNAs have supposed a considerable advance. miRNAs, which are small RNA sequences, can regulate gene expression, so they play an essential role not only as a diagnostic biomarker but also as a therapeutic and prognostic one. Also, miRNA biomarkers can be obtained from liquid biopsies, which are less intrusive than lung biopsies, and have better accessibility, safety and repeatability, which allows using those biomarkers both for diagnosis and monitoring of patients. In this review, we highlight the importance of miRNAs and collect the existing evidence of their relationship with lung cancer.

Curved OLED-based NLOS optical camera communications links.

In this paper, for the first time, to the best of our knowledge, we experimentally demonstrate the use of a curved organic light emitting diode (OLED) as a transmitter (Tx) in the non-line-of-sight (NLOS) optical camera communication (OCC) link for an indoor environment using a camera as a receiver. The proposed NLOS-OCC scheme is evaluated for the signal-to-noise ratio (SNR) and the reception success rates R r s under key photographic and communication parameters, including exposure times t e x p and gain values G v, as well as the transmission frequency f s and the distance L. The SNR analysis is performed using a binary classification procedure based on a Gaussian mixture model for the first time, to the best of our knowledge, for OLED-based NLOS-OCC links. We also derive and demonstrate that the effect of G v on the SNR with respect to L is minimal based on the pixel illumination model. The initial analysis suggests that, for a wall reflector-based NLOS-OCC link that is 2 m long, the SNR and R r s increase by 1 dB and 4% (83-87%) for f s of 600 Hz, with an increase in t e x p of 1000-1500 µs and G v of 25-45 dB.

An Encoder-Decoder Architecture within a Classical Signal-Processing Framework for Real-Time Barcode Segmentation.

In this work, two methods are proposed for solving the problem of one-dimensional barcode segmentation in images, with an emphasis on augmented reality (AR) applications. These methods take the partial discrete Radon transform as a building block. The first proposed method uses overlapping tiles for obtaining good angle precision while maintaining good spatial precision. The second one uses an encoder-decoder structure inspired by state-of-the-art convolutional neural networks for segmentation while maintaining a classical processing framework, thus not requiring training. It is shown that the second method's processing time is lower than the video acquisition time with a 1024 × 1024 input on a CPU, which had not been previously achieved. The accuracy it obtained on datasets widely used by the scientific community was almost on par with that obtained using the most-recent state-of-the-art methods using deep learning. Beyond the challenges of those datasets, the method proposed is particularly well suited to image sequences taken with short exposure and exhibiting motion blur and lens blur, which are expected in a real-world AR scenario. Two implementations of the proposed methods are made available to the scientific community: one for easy prototyping and one optimised for parallel implementation, which can be run on desktop and mobile phone CPUs.

Selection on Phalanx Development in the Evolution of the Bird Wing.

The frameshift hypothesis is a widely accepted model of bird wing evolution. This hypothesis postulates a shift in positional values, or molecular-developmental identity, that caused a change in digit phenotype. The hypothesis synthesized developmental and paleontological data on wing digit homology. The "most anterior digit" (MAD) hypothesis presents an alternative view based on changes in transcriptional regulation in the limb. The molecular evidence for both hypotheses is that the MAD expresses Hoxd13 but not Hoxd11 and Hoxd12. This digit I "signature" is thought to characterize all amniotes. Here, we studied Hoxd expression patterns in a phylogenetic sample of 18 amniotes. Instead of a conserved molecular signature in digit I, we find wide variation of Hoxd11, Hoxd12, and Hoxd13 expression in digit I. Patterns of apoptosis, and Sox9 expression, a marker of the phalanx-forming region, suggest that phalanges were lost from wing digit IV because of early arrest of the phalanx-forming region followed by cell death. Finally, we show that multiple amniote lineages lost phalanges with no frameshift. Our findings suggest that the bird wing evolved by targeted loss of phalanges under selection. Consistent with our view, some recent phylogenies based on dinosaur fossils eliminate the need to postulate a frameshift in the first place. We suggest that the phenotype of the Archaeopteryx lithographica wing is also consistent with phalanx loss. More broadly, our results support a gradualist model of evolution based on tinkering with developmental gene expression.

Lmo2 expression defines tumor cell identity during T-cell leukemogenesis.

The impact of LMO2 expression on cell lineage decisions during T-cell leukemogenesis remains largely elusive. Using genetic lineage tracing, we have explored the potential of LMO2 in dictating a T-cell malignant phenotype. We first initiated LMO2 expression in hematopoietic stem/progenitor cells and maintained its expression in all hematopoietic cells. These mice develop exclusively aggressive human-like T-ALL In order to uncover a potential exclusive reprogramming effect of LMO2 in murine hematopoietic stem/progenitor cells, we next showed that transient LMO2 expression is sufficient for oncogenic function and induction of T-ALL The resulting T-ALLs lacked LMO2 and its target-gene expression, and histologically, transcriptionally, and genetically similar to human LMO2-driven T-ALL We next found that during T-ALL development, secondary genomic alterations take place within the thymus. However, the permissiveness for development of T-ALL seems to be associated with wider windows of differentiation than previously appreciated. Restricted Cre-mediated activation of Lmo2 at different stages of B-cell development induces systematically and unexpectedly T-ALL that closely resembled those of their natural counterparts. Together, these results provide a novel paradigm for the generation of tumor T cells through reprogramming in vivo and could be relevant to improve the response of T-ALL to current therapies.

Surveillance mammography after treatment for male breast cancer.

PURPOSE: To identify the practice patterns related to use of surveillance mammography in male breast cancer (MaBC) survivors. METHODS: Using administrative claims data from OptumLabs Data Warehouse, we identified men who underwent surgery for breast cancer during 2007-2017. We calculated the proportion of men who had at least one mammogram (a) within 13 months for all patients and (b) within 24 months amongst those who maintained their insurance coverage for at least that length of time after surgery. Multivariate logistic regression modeling was used to identify factors associated with mammography within each timeframe. RESULTS: Out of 729 total MaBC survivors, 209 (29%) underwent mammography within 13 months after surgery. Among those who had lumpectomy, 41% underwent mammography, whereas among those who had mastectomy, 27% had mammography. Amongst 526 men who maintained consistent insurance coverage for 24 months after surgery, 215 (41%) underwent mammography at least once during that 24-month period. In this cohort, the proportion who had at least one mammogram during the 24-month period was 49% after lumpectomy and 40% after mastectomy. In a multivariate logistic regression model, more recent diagnosis (2015+) and older age at diagnosis were associated with lower odds of undergoing mammography, while receipt of radiation was associated with higher odds of undergoing mammography. CONCLUSIONS: Although recent ASCO guidelines recommend surveillance mammography after lumpectomy, a minority of MaBC survivors undergo surveillance mammography, even after lumpectomy. This is likely due to the paucity of data regarding the true benefits and harms of surveillance/screening mammography for MaBC.

Deep learning for signal clock and exposure estimation in rolling shutter optical camera communication.

In rolling shutter (RS)-based optical camera communication (OCC) links, selecting the appropriate camera's exposure time is critical, as it limits the reception bandwidth. In long exposures, the pixels accumulate over time the incoming irradiance of several consecutive symbols. As a result, a harmful intersymbol interference corrupts the received signal. Consequently, reducing the exposure time is required to increase the reception bandwidth at the cost of producing dark images with impracticable light conditions for human or machine-supervised applications. Alternatively, deep learning (DL) equalizers can be trained to mitigate the exposure-related ISI. These equalizers must be trained considering the transmitter clock and the camera's exposure, which can be exceptionally challenging if those parameters are unknown in advance (e.g., if the camera does not reveal its internal settings). In those cases, the receiver must estimate those parameters directly from the images, which are severely distorted by the exposure time. This work proposes a DL estimator for this purpose, which is trained using synthetic images generated for thousands of representative cases. This estimator enables the receiver operation under multiple possible configurations, regardless of the camera used. The results obtained during the validation, using more than 7000 real images, registered relative errors lower than 1% and 2% when estimating the transmitter clock and the exposure time, respectively. The obtained errors guarantee the optimal performance of the following equalization and decoding receiver stages, keeping bit error rates below the forward error correction limit. This estimator is a central component of any OCC receiver that operates over moderate exposure conditions. It decouples the reception routines from the cameras used, ultimately enabling cloud-based receiver architectures.

General framework for calculating irradiance distributions of symmetric surface sources.

Symmetries in system modeling can be exploited to obtain analytical results on the system behavior and to speed up computations using the symmetric model. This work explores the use of symmetries in radiant surfaces for calculating the induced irradiance distributions by developing a general mathematical expression. The obtained model is applied to flat, cylindrical, and spherical sources to obtain explicit expressions. An experimental evaluation of the flat source is carried out and compared with a traditional point source, and the obtained procedure for the flat scenario is compared with the direct integration approach, which shows an improvement in the computation time of at least two orders of magnitude with a relative root mean square error of less than 10%. The results show that the proposed approach enhances short-range predictions for extended sources. To demonstrate the impact of this in optical wireless communications we have outlined a few applications.

Clustering-based data detection for spectral signature multiplexing in multispectral camera communication.

Optical camera communication (OCC) is a promising technology to be used in future wireless communication systems. In this work, a cluster-based data detection procedure is applied to enhance the performance of an OCC system. A multispectral camera is employed to capture the spectral variations in light-emitting diodes (LEDs) caused by temperature. This strategy's system performance is compared with a system that uses traditional linear methods, such as zero-forcing (ZF) and minimum mean square error (MMSE) equalizers. The findings of this study indicate that an improvement in the bit error rate (BER) can be achieved by applying a clustering approach.

Convolutional autoencoder for exposure effects equalization and noise mitigation in optical camera communication.

In rolling shutter-based optical camera communication (OCC), the camera's exposure time limits the achievable reception bandwidth. In long-exposure settings, the image sensor pixels average the incident received power, producing inter-symbol interference (ISI), which is perceived in the images as a spatial mixture of the symbol bands. Hence, the shortest possible exposure configuration should be selected to alleviate ISI. However, in these conditions, the camera produces dark images with impracticable light conditions for human or machine-supervised applications. In this paper, a novel convolutional autoencoder-based equalizer is proposed to alleviate exposure-related ISI and noise. Furthermore, unlike other systems that use artificial neural networks for equalization and decoding, the training procedure is conducted offline using synthetic images for which no prior information about the deployment scenario is used. Hence the training can be performed for a wide range of cameras and signal-to-noise ratio (SNR) conditions, using a vast number of samples, improving the network fitting and the system decoding robustness. The results obtained in the experimental validation record the highest ISI mitigation potential for Manchester encoded on-off keying signals. The system can mitigate the ISI produced by exposure time windows that are up to seven times longer than the transmission symbol duration, with bit error rates (BER) lower than 10-5 under optimal SNR conditions. Consequently, the reception bandwidth improves up to 14 times compared to non-equalized systems. In addition, under harsh SNRs conditions, the system achieves BERs below the forward error correction limit for 1dB and 5 dB while operating with exposure times that are 2 and 4 times greater than the symbol time, respectively.

Sandstorm effect on experimental optical camera communication.

Sandstorms can severely affect the reliability of outdoor optical wireless communications (OWC) by diminishing large regions' visibility. In this work, the effect of a real sandstorm on optical camera communications (OCC) links is experimentally evaluated. Two link ranges are essayed using a cost-efficient telescope-based camera setup with commercial LEDs. Using on-off keying modulation, a data rate of 1035 and 630 bps with error probabilities of 9.14⋅10-5 and 4.1⋅10-3 for 100 m and 200 m, respectively, can be achieved. The signal-to-noise ratio of the links was optimized by tuning the analog amplifier's gain of the camera, increasing it by up to 9 dB. It is shown that scattering due to the sandstorm can even be beneficial for increasing the data rate in OCC (contrary to classical photodetector-based OWC links), thanks to an increment of 33% on the region of interest dimensions compared to the expected clear air link.