A cyclic di-GMP-binding adaptor protein interacts with a N5-glutamine methyltransferase to regulate the pathogenesis in Xanthomonas citri subsp. citri.

The second messenger cyclic diguanylate monophosphate (c-di-GMP) regulates a wide range of bacterial behaviours through diverse mechanisms and binding receptors. Single-domain PilZ proteins, the most widespread and abundant known c-di-GMP receptors in bacteria, act as trans-acting adaptor proteins that enable c-di-GMP to control signalling pathways with high specificity. This study identifies a single-domain PilZ protein, XAC3402 (renamed N5MapZ), from the phytopathogen Xanthomonas citri subsp. citri (Xcc), which modulates Xcc virulence by directly interacting with the methyltransferase HemK. Through yeast two-hybrid, co-immunoprecipitation and immunofluorescent staining, we demonstrated that N5MapZ and HemK interact directly under both in vitro and in vivo conditions, with the strength of the protein-protein interaction decreasing at high c-di-GMP concentrations. This finding distinguishes N5MapZ from other characterized single-domain PilZ proteins, as it was previously known that c-di-GMP enhances the interaction between those single-domain PilZs and their protein partners. This observation is further supported by the fact that the c-di-GMP binding-defective mutant N5MapZR10A can interact with HemK to inhibit the methylation of the class 1 translation termination release factor PrfA. Additionally, we found that HemK plays an important role in Xcc pathogenesis, as the deletion of hemK leads to extensive phenotypic changes, including reduced virulence in citrus plants, decreased motility, production of extracellular enzymes and stress tolerance. Gene expression analysis has revealed that c-di-GMP and the HemK-mediated pathway regulate the expression of multiple virulence effector proteins, uncovering a novel regulatory mechanism through which c-di-GMP regulates Xcc virulence by mediating PrfA methylation via the single-domain PilZ adaptor protein N5MapZ.

Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation.

BACKGROUND: Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15-20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with recurrent HCC to identify differentially expressed genes (DEGs), the involved pathways, biological functions, and potential gene signatures of recurrent HCC post-transplant using deep machine learning (ML) methodology. MATERIALS AND METHODS: We analyzed the transcriptomic profiles of primary and recurrent tumor samples from 7 pairs of patients who underwent LT. Following differential gene expression analysis, we performed pathway enrichment, gene ontology (GO) analyses and protein-protein interactions (PPIs) with top 10 hub gene networks. We also predicted the landscape of infiltrating immune cells using Cibersortx. We next develop pathway and GO term-based deep learning models leveraging primary tissue gene expression data from The Cancer Genome Atlas (TCGA) to identify gene signatures in recurrent HCC. RESULTS: The PI3K/Akt signaling pathway and cytokine-mediated signaling pathway were particularly activated in HCC recurrence. The recurrent tumors exhibited upregulation of an immune-escape related gene, CD274, in the top 10 hub gene analysis. Significantly higher infiltration of monocytes and lower M1 macrophages were found in recurrent HCC tumors. Our deep learning approach identified a 20-gene signature in recurrent HCC. Amongst the 20 genes, through multiple analysis, IL6 was found to be significantly associated with HCC recurrence. CONCLUSION: Our deep learning approach identified PI3K/Akt signaling as potentially regulating cytokine-mediated functions and the expression of immune escape genes, leading to alterations in the pattern of immune cell infiltration. In conclusion, IL6 was identified to play an important role in HCC recurrence.

Whole-genome Sequencing Reveals Autooctoploidy in Chinese Sturgeon and Its Evolutionary Trajectories.

The order Acipenseriformes, which includes sturgeons and paddlefishes, represents "living fossils" with complex genomes that are good models for understanding whole-genome duplication (WGD) and ploidy evolution in fishes. Here, we sequenced and assembled the first high-quality chromosome-level genome for the complex octoploid Acipenser sinensis (Chinese sturgeon), a critically endangered species that also represents a poorly understood ploidy group in Acipenseriformes. Our results show that A. sinensis is a complex autooctoploid species containing four kinds of octovalents (8n), a hexavalent (6n), two tetravalents (4n), and a divalent (2n). An analysis taking into account delayed rediploidization reveals that the octoploid genome composition of Chinese sturgeon results from two rounds of homologous WGDs, and further provides insights into the timing of its ploidy evolution. This study provides the first octoploid genome resource of Acipenseriformes for understanding ploidy compositions and evolutionary trajectories of polyploid fishes.

Discrimination of polysorbate 20 by high-performance liquid chromatography-charged aerosol detection and characterization for components by expanding compound database and library.

Analyzing polysorbate 20 (PS20) composition and the impact of each component on stability and safety is crucial due to formulation variations and individual tolerance. The similar structures and polarities of PS20 components make accurate separation, identification, and quantification challenging. In this work, a high-resolution quantitative method was developed using single-dimensional high-performance liquid chromatography (HPLC) with charged aerosol detection (CAD) to separate 18 key components with multiple esters. The separated components were characterized by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) with an identical gradient as the HPLC-CAD analysis. The polysorbate compound database and library were expanded over 7-time compared to the commercial database. The method investigated differences in PS20 samples from various origins and grades for different dosage forms to evaluate the composition-process relationship. UHPLC-Q-TOF-MS identified 1329 to 1511 compounds in 4 batches of PS20 from different sources. The method observed the impact of 4 degradation conditions on peak components, identifying stable components and their tendencies to change. HPLC-CAD and UHPLC-Q-TOF-MS results provided insights into fingerprint differences, distinguishing quasi products.

A compact tri-notched flexible UWB antenna based on an inkjet-printable and plasma-activated silver nano ink.

The rapid development of ultrawideband (UWB) communication systems has resulted in increasing performance requirements for the antenna system. In addition to a wide bandwidth, fast propagation rates and compact dimensions, flexibility, wearability or portability are also desirable for UWB antennas, as are excellent notch characteristics. Although progress has been made in the development of flexible/wearable antennas desired notch properties are still rather limited. Moreover, most presently available flexible UWB antennas are fabricated using environmentally not attractive subtractive etching-based processes. The usage of facile additive sustainably inkjet printing processes also utilizing low temperature plasma-activated conductive inks is rarely reported. In addition, the currently used tri-notched flexible UWB antenna designs have a relatively large footprint, which poses difficulties when integrated into miniaturized and compact communication devices. In this work, a silver nano ink is used to fabricate the antenna via inkjet printing and an efficient plasma sintering procedure. For the targeted UWB applications miniaturized tri-notched flexible antenna is realized on a flexible polyethylene terephthalate (PET) substrate with a compact size of 17.6 mm × 16 mm × 0.12 mm. The antenna operates in the UWB frequency band (2.9-10.61 GHz), and can shield interferences from WiMAX (3.3-3.6 GHz), WLAN (5.150-5.825 GHz) and X-uplink (7.9-8.4 GHz) bands, as well as exhibits a certain of bendability. Three nested "C" slots of different sizes were adopted to achieve notch features. The simulation and test results demonstrate that the proposed antenna can generate signal radiation in the desired UWB frequency band while retaining the desired notch properties and having acceptable SAR values on-body, making it a viable candidate for usage in flexible or wearable communication transmission devices. The research provides a facile and highly efficient method for fabricating flexible/wearable UWB antennas, that is, the effective combination of inkjet printing processing, flexible substrates, low temperature-activated conductive ink and antenna structure design.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data.

Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition, improving forest productivity, and comprehending ecological processes. However, accurately depicting the spatiotemporal variability of light under complex forest structural conditions poses a challenge, especially for precise forest management decisions that require a quantitative study of the relationship between fine-scale individual tree structure and light. 3D RTMs (3-dimensional radiative transfer models), which accurately characterize the interaction between solar radiation and detailed forest scenes, provide a reliable means for depicting such relationships. This study employs a 3D RTM and LiDAR (light detection and ranging) data to characterize the light environment of larch plantations at a fine spatiotemporal scale, further investigating the relationship between absorbed photosynthetically active radiation (APAR) and forest structures. The impact of specific tree structural parameters, such as crown diameter, crown area, crown length, crown ratio, crown volume, tree height, leaf area index, and a distance parameter assessing tree competition, on the daily-scale cumulative APAR per tree was investigated using a partial least squares regression (PLSR) model. Furthermore, variable importance in projection (VIP) was also calculated from the PLSR. The results indicate that among the individual tree structure parameters, crown volume is the most important one in explaining individual tree APAR (VIP = 4.19), while the competition from surrounding trees still plays a role in explaining individual tree APAR to some extent (VIP = 0.15), and crown ratio contributes the least (VIP = 0.03). Regarding the spatial distribution of trees, the average cumulative APAR per tree of larch plots does not increase with an increase in canopy gap fraction. Tree density and average cumulative APAR per tree were fitted using a natural exponential equation, with a coefficient of determination (R2 = 0.89), and a small mean absolute percentage error (MAPE = 0.03). This study demonstrates the potential of combining 3D RTM with LiDAR data to quantify fine-scale APAR in plantations, providing insights for optimizing forest structure, enhancing forest quality, and implementing precise forest management practices, such as selective breeding for superior tree species.

Radiomic signatures associated with tumor immune heterogeneity predict survival in locally recurrent nasopharyngeal carcinoma.

BACKGROUND: The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma (lrNPC) is limited due to their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in lrNPC. METHODS: This multicenter, retrospective study included 921 patients with lrNPC. A machine learning signature and nomogram based on pretreatment MRI features were developed for predicting overall survival (OS) in a training cohort and validated in two independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index (C-index) and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA sequencing (RNA-seq) analysis. RESULTS: The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving C-indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables significantly improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with significantly distinct OS rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-seq analysis revealed differences in interferon response and lymphocyte infiltration between risk groups. CONCLUSIONS: An MRI-based radiomic signature predicted OS more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for lrNPC patients.

Permanent fluidic magnets for liquid bioelectronics.

Brownian motion allows microscopically dispersed nanoparticles to be stable in ferrofluids, as well as causes magnetization relaxation and prohibits permanent magnetism. Here we decoupled the particle Brownian motion from colloidal stability to achieve a permanent fluidic magnet with high magnetization, flowability and reconfigurability. The key to create such permanent fluidic magnets is to maintain a stable magnetic colloidal fluid by using non-Brownian magnetic particles to self-assemble a three-dimensional oriented and ramified magnetic network structure in the carrier fluid. This structure has high coercivity and permanent magnetization, with long-term magnetization stability. We establish a scaling theory model to decipher the permanent fluid magnet formation criteria and formulate a general assembly guideline. Further, we develop injectable and retrievable permanent-fluidic-magnet-based liquid bioelectronics for highly sensitive, self-powered wireless cardiovascular monitoring. Overall, our findings highlight the potential of permanent fluidic magnets as an ultrasoft material for liquid devices and systems, from bioelectronics to robotics.

Insight into the Types of Alkanolamines on the Properties of Copper(II) Formate-Based Conductive Ink.

Conductive inks are one of the most important functional materials for printed flexible electronic devices, and their properties determine the methods of subsequent patterning and metallization. In comparison with copper nanoparticle or nanowire inks, copper particle-free inks employing copper(II) formate (Cuf) as a precursor have attracted the interest of researchers due to their flexibility in preparation, excellent stability, and lower conversion temperature. Alkanolamines can provide Cuf with excellent solubility in alcohols while being less toxic and having a certain reducibility, making them preferable ligands in comparison with aliphatic amines and pyridine. However, there have been few studies on the effects of the alkanolamine types on the performance of Cuf inks. Also, the decomposition mechanism of copper-alkanolamine complex inks is not clear. In this work, different kinds of alkanolamines were chosen as ligands to formulate Cuf inks to address the mentioned issues. The influences of amine types on the stability, wettability, thermal decomposition behavior, and electrical performance of the formulated Cuf particle-free inks were investigated in detail. The results show that the utilization of alkanolamines could provide Cuf with excellent solubility in alcohols, resulting in an ink with good stability and favorable wetting properties. The thermal decomposition temperature and electrical performance of the formulated copper ink are largely dependent on the amine used. When amines with a longer carbon chain and more branches were utilized to prepare the ink, a decreased decomposition temperature was observed on the derived inks because of the steric hindrance effect. Copper films with good morphology and conductivity could be obtained at low temperatures by selecting the appropriate alkanolamine. Copper particle-free conductive ink from 2-amino-2-methyl-1-propanol demonstrated better morphology and electrical performance (16.09 µΩ·cm) and was successfully used for conductive circuits by direct-writing.

Streptomyces sungeiensis SD3 as a Microbial Chassis for the Heterologous Production of Secondary Metabolites.

We present the newly isolated Streptomyces sungeiensis SD3 strain as a promising microbial chassis for heterologous production of secondary metabolites. S. sungeiensis SD3 exhibits several advantageous traits as a microbial chassis, including genetic tractability, rapid growth, susceptibility to antibiotics, and metabolic capability supporting secondary metabolism. Genomic and transcriptomic sequencing unveiled the primary metabolic capabilities and secondary biosynthetic pathways of S. sungeiensis SD3, including a previously unknown pathway responsible for the biosynthesis of streptazone B1. The unique placement of S. sungeiensis SD3 in the phylogenetic tree designates it as a type strain, setting it apart from other frequently employed Streptomyces chassis. This distinction makes it the preferred chassis for expressing biosynthetic gene clusters (BGCs) derived from strains within the same phylogenetic or neighboring phylogenetic clade. The successful expression of secondary biosynthetic pathways from a closely related yet slow-growing strain underscores the utility of S. sungeiensis SD3 as a heterologous expression chassis. Validation of CRISPR/Cas9-assisted genetic tools for chromosomal deletion and insertion paved the way for further strain improvement and BGC refactoring through rational genome editing. The addition of S. sungeiensis SD3 to the heterologous chassis toolkit will facilitate the discovery and production of secondary metabolites.

A PilZ domain protein interacts with the transcriptional regulator HinK to regulate type VI secretion system in Pseudomonas aeruginosa.

Type VI secretion systems (T6SS) are bacterial macromolecular complexes that secrete effectors into target cells or the extracellular environment, leading to the demise of adjacent cells and providing a survival advantage. Although studies have shown that the T6SS in Pseudomonas aeruginosa is regulated by the Quorum Sensing system and second messenger c-di-GMP, the underlying molecular mechanism remains largely unknown. In this study, we discovered that the c-di-GMP-binding adaptor protein PA0012 has a repressive effect on the expression of the T6SS HSI-I genes in P. aeruginosa PAO1. To probe the mechanism by which PA0012 (renamed TssZ, Type Six Secretion System -associated PilZ protein) regulates the expression of HSI-I genes, we conducted yeast two-hybrid screening and identified HinK, a LasR-type transcriptional regulator, as the binding partner of TssZ. The protein-protein interaction between HinK and TssZ was confirmed through co-immunoprecipitation assays. Further analysis suggested that the HinK-TssZ interaction was weakened at high c-di-GMP concentrations, contrary to the current paradigm wherein c-di-GMP enhances the interaction between PilZ proteins and their partners. Electrophoretic mobility shift assays revealed that the non-c-di-GMP-binding mutant TssZR5A/R9A interacts directly with HinK and prevents it from binding to the promoter of the quorum-sensing regulator pqsR. The functional connection between TssZ and HinK is further supported by observations that TssZ and HinK impact the swarming motility, pyocyanin production, and T6SS-mediated bacterial killing activity of P. aeruginosa in a PqsR-dependent manner. Together, these results unveil a novel regulatory mechanism wherein TssZ functions as an inhibitor that interacts with HinK to control gene expression.

Initial cyclic-di-GMP upregulation triggers sporadic cellular expansion leading to improved cellular survival.

Bacterial second messenger c-di-GMP upregulation is associated with the transition from planktonic to sessile microbial lifestyle, inhibiting cellular motility, and virulence. However, in-depth elucidation of the cellular processes resulting from c-di-GMP upregulation has not been fully explored. Here, we report the role of upregulated cellular c-di-GMP in promoting planktonic cell growth of Escherichia coli K12 and Pseudomonas aeruginosa PAO1. We found a rapid expansion of cellular growth during initial cellular c-di-GMP upregulation, resulting in a larger planktonic bacterial population. The initial increase in c-di-GMP levels promotes bacterial swarming motility during the growth phase, which is subsequently inhibited by the continuous increase of c-di-GMP, and ultimately facilitates the formation of biofilms. We demonstrated that c-di-GMP upregulation triggers key bacterial genes linked to bacterial growth, swarming motility, and biofilm formation. These genes are mainly controlled by the master regulatory genes csgD and csrA. This study provides us a glimpse of the bacterial behavior of evading potential threats through adapting lifestyle changes via c-di-GMP regulation.

A multimodal magnetoelastic artificial skin for underwater haptic sensing.

Future exploitation of marine resources in a sustainable and eco-friendly way requires autonomous underwater robotics with human-like perception. However, the development of such intelligent robots is now impeded by the lack of adequate underwater haptic sensing technology. Inspired by the populational coding strategy of the human tactile system, we harness the giant magnetoelasticity in soft polymer systems as an innovative platform technology to construct a multimodal underwater robotic skin for marine object recognition with intrinsic waterproofness and a simple configuration. The bioinspired magnetoelastic artificial skin enables multiplexed tactile modality in each single taxel and obtains an impressive classification rate of 95% in identifying seven types of marine creatures and marine litter. By introducing another degree of freedom in underwater haptic sensing, this work represents a milestone toward sustainable marine resource exploitation.

Factors predicting indistinct plane of surgical capsule in patients underwent HoLEP procedures.

PURPOSE: To evaluate factors that effectively predict indistinct plane (IP) in patients who underwent holmium laser enucleation of the prostate (HoLEP). METHODS: Data of 208 consecutive patients from our HoLEP database were reviewed and analyzed. IP was defined in 107 cases, as the plane could be identified only depending on endoscopic beak dissection rather than laser dissection in the initial stage of HoLEP, whereas the control group consisted of 101 cases. Variables including age, body mass index, prostatic volume (PV), intravesical prostatic protrusion, prostate-specific antigen, prostate-specific antigen density, bladder stones, urinary tract infection, microscopic hematuria, prior biopsy (PB), diabetes, hypertension, history of acute urinary retention, 5-alpha reductase inhibitor treatment, catheter dependency, residual urine, region, smoking, and alcohol consumption were compared between the two groups. The risk factors for predicting the presence of IP were determined using a multivariable binary logistic regression model using a forward selection approach with a focus on improvement in the area under the receiver operating characteristic curve (AUC). RESULTS: The incidence of IP was 51.4% (107/208). PV (OR = 0.977, p < 0.001) and PB (OR = 0.297, p = 0.028) were identified as the independent predictors of capsule plane status. PV with a cutoff of 54 ml had the best predictive effectiveness for IP based on AUC (0.727; 95% CI 0.659-0.795). The specificity and sensitivity of this cutoff were 82.2% and 53.3%, respectively. CONCLUSION: PV is the most reliable factor to predict IP during HoLEP procedures. There is a high possibility of IP in patients with a PV less than 54 ml.

The Application of CT Radiomics in the Diagnosis of Vein Wall Invasion in Patients With Renal Cell Carcinoma Combined With Tumor Thrombus.

OBJECTIVE: The objective of this study was to explore the application of radiomics combined with machine learning to establish different models to assist in the diagnosis of venous wall invasion in patients with renal cell carcinoma and venous tumor thrombus and to evaluate the diagnostic efficacy. MATERIALS AND METHODS: We retrospectively reviewed the data of 169 patients in Peking University Third Hospital from March 2015 to January 21, who was diagnosed as renal mass with venous invasion. According to the intraoperative findings, 111 patients were classified to the venous wall invasion group and 58 cases in the non-invasion group. ITK-snap was used for tumor segmentation and PyRadiomics 3.0.1 package was used for feature extraction. A total of 1598 features could be extracted from each CT image. The patients were divided into training set and testing set by time. The elastic-net regression with 4-fold cross-validation was used as a dimension-reduction method. After feature selection, a support vector machines (SVM) model, a logistic regression (LR) model, and an extra trees (ET) model were established. Then the sensitivity, specificity, accuracy, and the area under the curve (AUC) were calculated to evaluate the diagnostic performance of each model on the testing set. RESULTS: Patients before September 2019 were divided into the training set, of which 88 patients were in the invasion group and 42 patients were in the non-invasion group. The others were in the testing set, of which 32 patients were in the invasion group and 16 patients were in the non-invasion group. A total of 34 radiomics features were obtained by the elastic-net regression. The SVM model had an AUC value of 0.641 (95% CI, 0.463-0.769), a sensitivity of 1.000, and a specificity of 0.062. The LR model had an AUC value of 0.769 (95% CI, 0.620-0.877), a sensitivity of 0.913, and a specificity of 0.312. The ET model had an AUC value of 0.853 (95% CI, 0.734-0.948), a sensitivity of 0.783, and a specificity of 0.812. Among the 3 models, the ET model had the best diagnostic effect, with a good balance of sensitivity and specificity. And the higher the tumor thrombus grade, the better the diagnostic efficacy of the ET model. In inferior vena cava tumor thrombus, the sensitivity, specificity, accuracy, and AUC of ET model can be improved to 0.889, 0.800, 0.857, 0.878 (95% CI, 0.745-1.000). CONCLUSION: Machine learning combined with radiomics method can effectively identify whether venous wall was invaded by tumor thrombus and has high diagnostic efficacy with an AUC of 0.853 (95% CI, 0.734-0.948).

Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.

BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and there are no preoperative methods for assessment of ESTM yet. PURPOSE: This multicenter study aimed to develop a deep learning-based radiomics model to preoperatively identify ESTM and evaluate its prognostic value. METHODS: A total of 959 GC patients were enrolled from two centers and split into a training cohort (N = 551) and a test cohort (N = 236) for ESTM evaluation. Additionally, an external survival cohort (N = 172) was included for prognostic analysis. Four models were established based on clinical characteristics and multiphase computed tomography (CT) images for preoperative identification of ESTM, including a deep learning model, a hand-crafted radiomic model, a clinical model, and a combined model. C-index, decision curve, and calibration curve were utilized to assess the model performances. Survival analysis was conducted to explore the ability of stratifying overall survival (OS). RESULTS: The combined model showed good discrimination of the ESTM [C-indices (95% confidence interval, CI): 0.770 (0.729-0.812) and 0.761 (0.718-0.805) in training and test cohorts respectively], which outperformed deep learning model, radiomics model, and clinical model. The stratified analysis showed this model was not affected by patient's tumor size, the presence of lymphovascular invasion, and Lauren classification (p < 0.05). Moreover, the model score showed strong consistency with the OS [C-indices (95%CI): 0.723 (0.658-0.789, p < 0.0001) in the internal survival cohort and 0.715 (0.650-0.779, p < 0.0001) in the external survival cohort]. More interestingly, univariate analysis showed the model score was significantly associated with occult distant metastasis (p < 0.05) that was missed by preoperative diagnosis. CONCLUSIONS: The model combining CT images and clinical characteristics had an impressive predictive ability of both ESTM and prognosis, which has the potential to serve as an effective complement to the preoperative TNM staging system.

Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review.

Nasopharyngeal carcinoma is a common head and neck malignancy with distinct clinical management compared to other types of cancer. Precision risk stratification and tailored therapeutic interventions are crucial to improving the survival outcomes. Artificial intelligence, including radiomics and deep learning, has exhibited considerable efficacy in various clinical tasks for nasopharyngeal carcinoma. These techniques leverage medical images and other clinical data to optimize clinical workflow and ultimately benefit patients. In this review, we provide an overview of the technical aspects and basic workflow of radiomics and deep learning in medical image analysis. We then conduct a detailed review of their applications to seven typical tasks in the clinical diagnosis and treatment of nasopharyngeal carcinoma, covering various aspects of image synthesis, lesion segmentation, diagnosis, and prognosis. The innovation and application effects of cutting-edge research are summarized. Recognizing the heterogeneity of the research field and the existing gap between research and clinical translation, potential avenues for improvement are discussed. We propose that these issues can be gradually addressed by establishing standardized large datasets, exploring the biological characteristics of features, and technological upgrades.

Bony Congenital Nasolacrimal Duct Obstruction: A Novel Phenotype of Aplasia of Lacrimal and Major Salivary Glands.

PURPOSE: Aplasia of lacrimal and salivary glands (ALSG) is a syndromic disorder characterized by aplasia of lacrimal and salivary systems. Reported ophthalmic manifestations of ALSG include aplasia of lacrimal glands, punctal agenesis, lacrimal sac mucocele, and membranous congenital nasolacrimal duct obstruction (CNLDO). Bony CNLDO, a rare clinical entity, has not been associated with any syndromic disorder. This study investigated the relationship between genetic mutations and bony CNLDO in 3 Chinese families with ALSG. DESIGN: Single-center observational case study. PARTICIPANTS: Three Chinese families with bony CNLDO, including 7 affected and 9 healthy family members. METHODS: Slit-lamp ophthalmic examination, comprehensive physical examination, orbital computed tomography (CT) imaging, cervicofacial magnetic resonance imaging, audiometry, and whole exome sequencing on periphery blood were performed. Variants were cross-referenced with 1000 control genomes and various population databases. Pathologic variants were identified using bioinformatic tools. MAIN OUTCOME MEASURES: Clinical examination, diagnostic imaging, whole exome sequencing, and bioinformatic analysis findings. RESULTS: Affected patients showed decreased tear production on the Schimer I test and reduced tear breakup time. Bony CNLDO was observed on CT, showing unilateral or bilateral bony termination at the middle or terminal segment of the nasolacrimal canal. Magnetic resonance imaging showed aplasia or absence of lacrimal, parotid, and submandibular glands. Physical examination revealed normal ears, digits, and facial morphology. Audiometry and dental assessment were conducted on the pediatric patients and yielded normal results. The clinical characteristics of patients aligned with a diagnosis of ALSG. Genomic analysis revealed 3 novel heterozygous missense mutations of the Fgf10 gene: c.316T→C, c.327C→G, and c.332T→G. The inheritance pattern was autosomal dominant with variable penetrance. These variants were not observed in 1000 control genomes and population databases. These variant positions also were shown to be highly conserved across various animal species. Mutated genes and proteins were predicted as deleterious with most computational models, with a few suggesting they may be benign. CONCLUSIONS: Bony CNLDO was identified as a novel phenotype of ALSG implicated by missense mutations of highly conserved residues in the Fgf10 gene. These cases broadened our knowledge of Fgf10-related phenotypes and prompted clinicians to consider syndromic associations in patients with bony CNLDO. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Physiologic changes in the hepatopulmonary syndrome before and after liver transplant: A longitudinal and predictor analysis.

BACKGROUND AND AIMS: Hepatopulmonary syndrome (HPS) is a common complication of liver disease defined by abnormal oxygenation and intrapulmonary vascular dilatation, treated with liver transplantation. Little is known about changes in HPS physiological parameters over time. We sought to describe baseline clinical and physiological characteristics in HPS and their relationships, temporal changes in physiological parameters before and after transplant, and predictors of changes in oxygenation. APPROACH AND RESULTS: This was a retrospective cohort study in the Canadian HPS Program (n = 132). Rates of change after diagnosis were: -3.7 (-6.4, -0.96) mm Hg/year for partial pressure of arterial oxygen (PaO 2 ); -26 (-96, 44) m/year for 6-minute walk distance, and 3.3% (-6.6, -0.011) predicted/year for diffusion capacity. Noninvasive shunt of ≥ 20% predicted a slower PaO 2 decline by 0.88 (0.36, 1.4) mm Hg/month. We identified 2 PaO 2 deterioration classes-"very severe disease, slow decliners" (PaO 2 45.0 mm Hg; -1.0 mm Hg/year); and "moderate disease, steady decliners" (PaO 2 65.5 mm Hg; -2.5 mm Hg/year). PaO 2 increased by 6.5 (5.3, 7.7) mm Hg/month in the first year after transplant. The median time to normalization was 149 (116, 184) days. Posttransplant improvement in PaO 2 was 2.5 (0.1, 4.9) mm Hg/month faster for every 10 mm Hg greater pretransplant orthodeoxia. CONCLUSIONS: We present a large and long longitudinal data analysis in HPS. In addition to rates of physiological decline and improvement before and after liver transplantation, we present novel predictors of PaO 2 decline and improvement rates. Our findings enhance our understanding of the natural history of HPS and provide pathophysiologic clues. Importantly, they may assist providers in prognostication and prioritization before and after transplant.