Totally laparoscopic versus laparoscopy-assisted distal gastrectomy: the KLASS-07, a randomized controlled trial.

BACKGROUNDS: Strong evidence is lacking as no confirmatory randomized controlled trials (RCTs) have compared the efficacy of totally laparoscopic distal gastrectomy (TLDG) with laparoscopy-assisted distal gastrectomy (LADG). We performed an RCT to confirm if TLDG is different from LADG. METHODS: The XXXXX trial is a multicentre, open-label, parallel-group, phase III, RCT of 442 patients with clinical stage I gastric cancer. Patients were enrolled from 21 cancer care centers in South Korea between January 2018 and September 2020 and randomized to undergo TLDG or LADG using blocked randomization with a 1:1 allocation ratio, stratified by the participating investigators. Patients were treated through R0 resections by TLDG or LADG as the full analysis set of the XXXXX trial. The primary endpoint was morbidity within postoperative day 30, and the secondary endpoint was QoL for 1 year. This trial is registered at ClinicalTrials.gov (NCT XXXXXXXX). RESULTS: 442 patients were randomized (222 to TLDG, 220 to LADG), and 422 patients were included in the pure analysis (213 and 209, respectively). The overall complication rate did not differ between the two groups (TLDG vs. LADG: 12.2% vs. 17.2%). However, TLDG provided less postoperative ileus and pulmonary complications than LADG (0.9% vs. 5.7%, P=0.006; and 0.5% vs. 4.3%, P=0.035, respectively). The QoL was better after TLDG than after LADG regarding emotional functioning at 6 months, pain at 3 months, anxiety at 3 and 6 months, and body image at 3 and 6 months (all P<0.05). However, these QoL differences were resolved at 1 year. CONCLUSIONS: The XXXXX trial confirmed that TLDG is not different from LADG in terms of postoperative complication but has advantages to reduce ileus and pulmonary complications. TLDG can be a good option to offer better QoL in terms of pain, body image, emotion, and anxiety at 3-6 months.

Sparse Graph Representation Learning based on Reinforcement Learning for Personalized Mild Cognitive Impairment (MCI) Diagnosis.

Resting-state functional magnetic resonance imaging (rs-fMRI) has gained attention as a reliable technique for investigating the intrinsic function patterns of the brain. It facilitates the extraction of functional connectivity networks (FCNs) that capture synchronized activity patterns among regions of interest (ROIs). Analyzing FCNs enables the identification of distinctive connectivity patterns associated with mild cognitive impairment (MCI). For MCI diagnosis, various sparse representation techniques have been introduced, including statistical- and deep learningbased methods. However, these methods face limitations due to their reliance on supervised learning schemes, which restrict the exploration necessary for probing novel solutions. To overcome such limitation, prior work has incorporated reinforcement learning (RL) to dynamically select ROIs, but effective exploration remains challenging due to the vast search space during training. To tackle this issue, in this study, we propose an advanced RL-based framework that utilizes a divide-and-conquer approach to decompose the FCN construction task into smaller subproblems in a subject-specific manner, enabling efficient exploration under each sub-problem condition. Additionally, we leverage the learned value function to determine the sparsity level of FCNs, considering individual characteristics of FCNs. We validate the effectiveness of our proposed framework by demonstrating its superior performance in MCI diagnosis on publicly available cohort datasets.

TEAD1 is crucial for developmental myelination, Remak bundles, and functional regeneration of peripheral nerves.

Previously we showed that the hippo pathway transcriptional effectors, YAP and TAZ, are essential for Schwann cells (SCs) to develop, maintain and regenerate myelin . Although TEAD1 has been implicated as a partner transcription factor, the mechanisms by which it mediates YAP/TAZ regulation of SC myelination are unclear. Here, using conditional and inducible knockout mice, we show that TEAD1 is crucial for SCs to develop and regenerate myelin. It promotes myelination by both positively and negatively regulating SC proliferation, enabling Krox20/Egr2 to upregulate myelin proteins, and upregulating the cholesterol biosynthetic enzymes FDPS and IDI1. We also show stage-dependent redundancy of TEAD1 and that non-myelinating SCs have a unique requirement for TEAD1 to enwrap nociceptive axons in Remak bundles. Our findings establish TEAD1 as a major partner of YAP/TAZ in developmental myelination and functional nerve regeneration and as a novel transcription factor regulating Remak bundle integrity.

Optimizing cyanine dye properties for enhanced dyeing and inkjet printing on diverse Substrates: Photophysical and colorimetric investigations.

Cyanine-based cationic dyes with different substituents in the donor unit were easily synthesized using readily available starting materials. The prepared dye molecules were spectroscopically characterized by NMR, FT-IR, and HR-Mass, and their thermal stability was measured by TGA, DSC, and XRD. Based on the TGA and DSC measurements, it was concluded that all the dyes are thermally stable up to 200 °C. Also, powder XRD was studied for all dyes to identify the explicit crystallinity and morphological nature of the dyes. A dye dispersion solution was prepared for the proper dyeing of modacrylic fabric and the dyed fabric showed good color strength K/S for dyes R1, R2, and R6 and fragile color strength for R3, R4,and R5. These dyes are also used for printing on substrates like paper and fabric using ink-jet printing. These dyes were also used for transferability printing applications on various fabrics.

Comparison of perioperative adverse events following suburethral sling placement using synthetic mesh, autologous rectus fascia, and autologous fascia lata in a national surgical registry.

AIMS: To assess and compare 30-day perioperative adverse events following suburethral sling surgery using synthetic mesh, autologous rectus fascia, and autologous fascia lata in women. METHODS: This was a retrospective cohort study of patients who underwent fascial or synthetic sling placement for stress urinary incontinence between 2008 and 2021 using the American College of Surgeons' National Surgical Quality Improvement Program database. Current Procedural Terminology codes were used to identify patients undergoing each type of sling procedure. Multivariable regression analysis with stepwise regression was used to assess the odds of composite adverse events (e.g., urinary tract infection, surgical site infection, pulmonary embolism, and other reportable events) between cohorts. RESULTS: Of the 41 533 female patients who underwent isolated suburethral sling placement without concurrent procedures, 41 292 (99.4%) received a synthetic mesh sling, and 241 (0.6%) received an autologous facial sling. In the fascial sling cohort, 160 (66.4%) underwent rectus fascia harvest and 81 (33.6%) underwent fascia lata harvest. Sling surgeries involving autologous fascia were associated with increased odds of adverse events compared to those involving synthetic mesh, even after adjusting for confounders (adjusted odds ratio [aOR]: 3.63, 95% confidence interval [CI]: 2.56-5.15). Compared to fascial slings from rectus fascia, slings from fascia lata were associated with increased odds of composite adverse events (aOR: 2.11, 95% CI: 1.03-4.04). However, with the exclusion of urinary tract infections, the adverse event rate was similar between slings using the two fascial harvest techniques (aOR: 1.93, 95% CI: 0.81-4.63). CONCLUSIONS: In this retrospective database study, suburethral sling surgeries using autologous fascia were independently associated with a 3.6-fold increase in odds of 30-day perioperative adverse events compared to sling surgeries using synthetic mesh.

Renal mass imaging modalities: does body mass index (BMI) matter?

PURPOSE: Accurate measurement of renal mass size is crucial in the management of renal cancer. With the burdensome cost of imaging yet its need for management, a better understanding of the variability among patients when determining mass size remains of urgent importance. Current guidelines on optimal imaging are limited, especially with respect to body mass index (BMI). The aim of this study is to discern which modalities accurately measure renal mass size and whether BMI influences such accuracy. METHODS: A multi-institutional chart review was performed for adult patients undergoing partial or radical nephrectomy between 2018 and 2021, with 236 patients ultimately included. Patients were categorized by BMI (BMI 1: 18.5-24.9, BMI 2: 25-29.9, BMI 3: 30-34.9, and BMI 4: ≥ 35). The greatest mass lengths were compared between the pathology report and the following: computerized tomography (CT), renal ultrasound, and magnetic resonance imaging (MRI). RESULTS: The difference between greatest length on CT with contrast and MRI were significantly different when compared to pathologic measurement. BMI groups 3 and 4 were found to have a significant difference in size estimates compared to BMI 2 for CT with contrast. No difference was found between size estimates by BMI group for any other imaging modality. CONCLUSION: CT with contrast becomes less accurate at estimating mass size for patients with BMI > 30. While contrast-enhanced CT remains a vital imaging modality for tissue enhancement in the context of unknown renal masses, caution must be used for mass size estimation in the obese population.

Tailored fluorophore design: Enhancing selectivity for cyanide ion sensing in water and food samples, and innovative device development.

A rigid fluorophore unit of Julolidine/coumarin fused with an indolium-conjugated system was built for the immediate and effective recognition of cyanide ions in a 90 % aq. DMSO solution. The probes are capable of displaying better sensitivity/selectivity for the cyanide ion over a wide range of other interfering ions. The probe JI showed an instant colorimetric variation, whereas the modified probe JCI showed both colorimetric and fluorimetric variation with cyanide ion. The observed detection limit values indicated excellent sensitivity of the probe to the cyanide ion. HRMS and 1H NMR studies confirmed that the mechanism of detection of CN- is via the nucleophilic attack on the electron-deficient indolium moiety of the molecule. Moreover, the probes are well proficient in selective recognition of cyanide in various real time applications (test strips, electronic sensor kit, food and water sample analysis).

Senolytic therapeutics: An emerging treatment modality for osteoarthritis.

Osteoarthritis (OA), a chronic joint disease affecting millions of people aged over 65 years, is the main musculoskeletal cause of diminished joint mobility in the elderly. It is characterized by lingering pain and increasing deterioration of articular cartilage. Aging and accumulation of senescent cells (SCs) in the joints are frequently associated with OA. Apoptosis resistance; irreversible cell cycle arrest; increased p16INK4a expression, secretion of senescence-associated secretory phenotype factors, senescence-associated ß-galactosidase levels, secretion of extracellular vesicles, and levels of reactive oxygen and reactive nitrogen species; and mitochondrial dysregulation are some common changes in cellular senescence in joint tissues. Development of OA correlates with an increase in the density of SCs in joint tissues. Senescence-associated secretory phenotype has been linked to OA and cartilage breakdown. Senolytics and therapeutic pharmaceuticals are being focused upon for OA management. SCs can be selectively eliminated or killed by senolytics to halt the pathogenesis and progression of OA. Comprehensive understanding of how aging affects joint dysfunction will benefit OA patients. Here, we discuss age-related mechanisms associated with OA pathogenesis and senolytics as an emerging modality in the management of age-related SCs and pathogenesis of OA in preclinical and clinical studies.

FTMMR: Fusion Transformer for Integrating Multiple Molecular Representations.

Molecular property prediction has gained substantial attention due to its potential for various bio-chemical applications. Numerous attempts have been made to enhance the performance by combining multiple molecular representations (1D, 2D, and 3D). However, most prior works only merged a limited number of representations or tried to embed multiple representations through a single network without using representation-specific networks. Furthermore, the heterogeneous characteristics of each representation made the fusion more challenging. Addressing these challenges, we introduce the Fusion Transformer for Multiple Molecular Representations (FTMMR) framework. Our strategy employs three distinct representation-specific networks and integrates information from each network using a fusion transformer architecture to generate fused representations. Additionally, we use self-supervised learning methods to align heterogeneous representations and to effectively utilize the limited chemical data available. In particular, we adopt a combinatorial loss function to leverage the contrastive loss for all three representations. We evaluate the performance of FTMMR using seven benchmark datasets, demonstrating that our framework outperforms existing fusion and self-supervised methods.

Feasibility of images acquired using smartphone camera for marginal and internal fit of fixed dental prosthesis: comparison and correlation study.

This study aimed to measure marginal and internal fit using images captured with both an optical microscope and a smartphone camera, comparing the fit measurement performance of these devices and analyzing their correlation. Working casts (with 10 posterior and 10 anterior teeth) created to fabricate fixed dental prostheses were used. These working casts were scanned using a desktop scanner (E1) to design an interim crown, and the designed interim crown was fabricated using a three-dimensional (3D) printer. Utilizing the silicone replica technique, the fabricated interim crown replicated the fit, which was then captured using both an optical microscope and a smartphone camera. The captured images were used to measure the marginal and internal fit according to the imaging device. Intraclass correlation coefficients (ICC) were used for reliability analysis according to the imaging device. Furthermore, the Wilcoxon signed-rank test was adopted for the comparative evaluation of the marginal and internal fit between the imaging devices (α = 0.05). The measurement results of the marginal and internal fit according to the optical microscope and smartphone camera did exhibit a significant difference (P < 0.05). The ICC between the two devices showed an "excellent" agreement of over 0.9 at all measurement points (P < 0.001). A smartphone camera could be used to obtain images for evaluating the marginal and internal fit.

Spectral Graph Neural Network-Based Multi-Atlas Brain Network Fusion for Major Depressive Disorder Diagnosis.

Major Depressive Disorder (MDD) imposes a substantial burden within the healthcare domain, impacting millions of individuals worldwide. Functional Magnetic Resonance Imaging (fMRI) has emerged as a promising tool for the objective diagnosis of MDD, enabling the investigation of functional connectivity patterns in the brain associated with this disorder. However, most existing methods focus on a single brain atlas, which limits their ability to capture the complex, multi-scale nature of functional brain networks. To address these limitations, we propose a novel multi-atlas fusion method that incorporates early and late fusion in a unified framework. Our method introduces the concept of the holistic Functional Connectivity Network (FCN), which captures both intra-atlas relationships within individual atlases and inter-regional relationships between atlases with different brain parcellation scales. This comprehensive representation enables the identification of potential disease-related patterns associated with MDD in the early stage of our framework. Moreover, by decoding the holistic FCN from various perspectives through multiple spectral Graph Convolutional Neural Networks and fusing their results with decision-level ensembles, we further improve the performance of MDD diagnosis. Our approach is easily implemented with minimal modifications to existing model structures and demonstrates a robust performance across different baseline models. Our method, evaluated on public resting-state fMRI datasets, surpasses the current multi-atlas fusion methods, enhancing the accuracy of MDD diagnosis. The proposed novel multi-atlas fusion framework provides a more reliable MDD diagnostic technique. Experimental results show our approach outperforms both single- and multi-atlas-based methods, demonstrating its effectiveness in advancing MDD diagnosis.

Persistent B Cell-Derived MHC Class II Signaling Is Required for the Optimal Maintenance of Tissue-Resident Helper T Cells.

Emerging studies have identified the critical roles of tissue-resident memory CD8+ T (TRM) and B (BRM) cells in the protection against mucosal viral infections, but the underlying mechanisms regulating robust development of TRM and BRM cells remain incompletely understood. We have recently shown that tissue-resident helper CD4+ T (TRH) cells, developed following influenza virus infection, function to sustain the optimal maintenance of TRM and BRM cells at the mucosal surface. In this study, we have explored the cellular and molecular cues modulating lung TRH persistence after influenza infection in C57BL/6 mice. We found that TRH cells were colocalized in tertiary lymphoid structures (TLSs) with local B cells. Abolishing TLSs or the depletion of B cells impaired lung TRH cell numbers. Of note, we found that persistent TCR signaling is needed for the maintenance of TRH cells after the clearance of infectious influenza virus. Furthermore, selective ablation of B cell-derived MHC class II resulted in partial reduction of lung TRH cell number after influenza infection. Our findings suggest that the interaction between lung-resident TRH cells and B cells, along with persistent Ag stimulation, is required to maintain TRH cells after respiratory viral infection.

Flow arrest during carotid artery stenting with a distal embolic protection device: A single-center experience and clinical implications.

Objective: We aimed to investigate the incidence of flow arrest during carotid artery stenting (CAS) with filter-type embolic protection device (EPD), identify any predisposing factors for those situations, and contemplate intraprocedural precautionary steps. Methods: CAS was performed in 128 patients with 132 arteries using filter-type EPD. The characteristics of treated patients and arteries were compared between groups with and without flow arrest. Results: The incidence of flow arrest during CAS with filter-type EPD was 17.4%. In flow arrest group, cases of vulnerable plaques (p=0.02) and symptomatic lesions (p=0.01) were significantly more common, and there were more cases of debris captured by EPD in a planar pattern (p<0.01). Vulnerable plaques were significantly more common in the procedures showing a planar pattern than in the cases with other patterns (p<0.01). Flow arrest group showed a significantly higher rate of ischemic complications (p<0.05), although there were no significant periprocedural neurological changes. The planar pattern of captured debris in filter-type EPD was the only significant risk factor for flow arrest (adjusted odds ratio 88.44, 95% confidence interval 15.21-514.45, p<0.05). Conclusions: Flow arrest during CAS with filter-type EPD is not uncommon and associated with increased ischemic complications. Symptomatic stenoses and vulnerable plaque are related to this event. The planar pattern of captured debris on the EPD was the only significant risk factor for the flow arrest. Clinicians must pay attention to the occurrence of flow arrest and react quickly when performing CAS.

Enhancing deep learning classification performance of tongue lesions in imbalanced data: mosaic-based soft labeling with curriculum learning.

BACKGROUND: Oral potentially malignant disorders (OPMDs) are associated with an increased risk of cancer of the oral cavity including the tongue. The early detection of oral cavity cancers and OPMDs is critical for reducing cancer-specific morbidity and mortality. Recently, there have been studies to apply the rapidly advancing technology of deep learning for diagnosing oral cavity cancer and OPMDs. However, several challenging issues such as class imbalance must be resolved to effectively train a deep learning model for medical imaging classification tasks. The aim of this study is to evaluate a new technique of artificial intelligence to improve the classification performance in an imbalanced tongue lesion dataset. METHODS: A total of 1,810 tongue images were used for the classification. The class-imbalanced dataset consisted of 372 instances of cancer, 141 instances of OPMDs, and 1,297 instances of noncancerous lesions. The EfficientNet model was used as the feature extraction model for classification. Mosaic data augmentation, soft labeling, and curriculum learning (CL) were employed to improve the classification performance of the convolutional neural network. RESULTS: Utilizing a mosaic-augmented dataset in conjunction with CL, the final model achieved an accuracy rate of 0.9444, surpassing conventional oversampling and weight balancing methods. The relative precision improvement rate for the minority class OPMD was 21.2%, while the relative [Formula: see text] score improvement rate of OPMD was 4.9%. CONCLUSIONS: The present study demonstrates that the integration of mosaic-based soft labeling and curriculum learning improves the classification performance of tongue lesions compared to previous methods, establishing a foundation for future research on effectively learning from imbalanced data.

Higher sclerostin is associated with pulmonary hypertension in pre-dialysis end-stage kidney disease patients: a cross-sectional prospective observational cohort study.

BACKGROUND: Pulmonary hypertension (PH) is a complication of chronic kidney disease (CKD) that contributes to mortality. Sclerostin, a SOST gene product that reduces osteoblastic bone formation by inhibiting Wnt/ß-catenin signaling, is involved in arterial stiffness and CKD-bone mineral disease, but scanty evidence to PH. This study explored the relationship between sclerostin and PH in CKD 5, pre-dialysis end-stage kidney disease (ESKD) patients. METHODS: This cross-sectional prospective observational cohort study included 44 pre-dialysis ESKD patients between May 2011 and May 2015. Circulating sclerostin levels were measured using an enzyme-linked immunosorbent assay. PH was defined as an estimated pulmonary artery systolic pressure > 35 mmHg on echocardiography. RESULTS: Patients with higher sclerostin levels ≥ 218.18pmol/L had echocardiographic structural cardiac abnormalities, especially PH (P < 0.01). On multivariate logistic analysis, sclerostin over 218.19pmol/L was significantly associated with PH (odds ratio [OR], 41.14; 95% confidence interval [CI], 4.53-373.89, P < 0.01), but multivariate Cox regression analysis showed the systemic vascular calcification score over 1 point (Hazard ratio [HR] 11.49 95% CI 2.48-53.14, P = 0.002) and PH ([HR] 5.47, 95% CI 1.30-23.06, P = 0.02) were risk factors for all-cause mortality in pre-dialysis ESKD patients. CONCLUSIONS: Serum sclerostin and PH have a positive correlation in predialysis ESKD patients. The higher systemic vascular calcification score and PH have an association to increase all-cause mortality in pre-dialysis ESKD patients.

Establishment of a Dual-Vector System for Gene Delivery Utilizing Prototype Foamy Virus.

Foamy viruses (FVs) are generally recognized as non-pathogenic, often causing asymptomatic or mild symptoms in infections. Leveraging these unique characteristics, FV vectors hold significant promise for applications in gene therapy. This study introduces a novel platform technology using a pseudo-virus with single-round infectivity. In contrast to previous vector approaches, we developed a technique employing only two vectors, pcHFV lacking Env and pCMV-Env, to introduce the desired genes into target cells. Our investigation demonstrated the efficacy of the prototype foamy virus (PFV) dual-vector system in producing viruses and delivering transgenes into host cells. To optimize viral production, we incorporated the codon-optimized Env (optEnv) gene in pCMV-Env and the Woodchuck Hepatitis Virus Posttranscriptional Regulatory Element (WPRE) at the 3' end of the transgene in the transfer vector. Consequently, the use of optEnv led to a significant enhancement in transgene expression in host cells. Additionally, the WPRE exhibited an enhancing effect. Furthermore, the introduced EGFP transgene was present in host cells for a month. In an effort to expand transgene capacity, we further streamlined the viral vector, anticipating the delivery of approximately 4.3 kbp of genes through our PFV dual-vector system. This study underscores the potential of PFVs as an alternative to lentiviruses or other retroviruses in the realm of gene therapy.

Reverse fabrication method of thin-film composite membranes for hydrogen separation.

A reverse method involves the pre-formation of an Matrimid (MI)-selective layer, followed by a porous polysulfone (PSF) support deposition. The membrane exhibited a high H2/CH4 selectivity and a moderate H2 permeance. This study introduces a facile method to produce membranes with inexpensive materials.

TEAD1 is crucial for developmental myelination, Remak bundles, and functional regeneration of peripheral nerves.

Previously we showed that the hippo pathway transcriptional effectors, YAP and TAZ, are essential for Schwann cells (SCs) to develop, maintain and regenerate myelin (Grove et al., 2017; Grove, Lee, Zhao, & Son, 2020). Although TEAD1 has been implicated as a partner transcription factor, the mechanisms by which it mediates YAP/TAZ regulation of SC myelination are unclear. Here, using conditional and inducible knockout mice, we show that TEAD1 is crucial for SCs to develop and regenerate myelin. It promotes myelination by both positively and negatively regulating SC proliferation, enabling Krox20/Egr2 to upregulate myelin proteins, and upregulating the cholesterol biosynthetic enzymes FDPS and IDI1. We also show stage-dependent redundancy of TEAD1 and that non-myelinating SCs have a unique requirement for TEAD1 to enwrap nociceptive axons in Remak bundles. Our findings establish TEAD1 as a major partner of YAP/TAZ in developmental myelination and functional nerve regeneration and as a novel transcription factor regulating Remak bundle integrity.

Identification and validation of putative biomarkers by in silico analysis, mRNA expression and oxidative stress indicators for negative energy balance in buffaloes during transition period.

OBJECTIVE: Transition period is considered from 3 weeks prepartum to 3 weeks postpartum, characterized with dramatic events (endocrine, metabolic, and physiological) leading to occurrence of production diseases (negative energy balance/ketosis, milk fever etc). The objectives of our study were to analyze the periodic concentration of serum beta-hydroxy butyric acid (BHBA), glucose and oxidative markers along with identification, and validation of the putative markers of negative energy balance in buffaloes using in-silico and quantitative real time-polymerase chain reaction (qRT-PCR) assay. METHODS: Out of 20 potential markers of ketosis identified by in-silico analysis, two were selected and analyzed by qRT-PCR technique (upregulated; acetyl serotonin o-methyl transferase like and down regulated; guanylate cyclase activator 1B). Additional two sets of genes (carnitine palmotyl transferase A; upregulated and Insulin growth factor; downregulated) that have a role of hepatic fatty acid oxidation to maintain energy demands via gluconeogenesis were also validated. Extracted cDNA (complementary deoxyribonucleic acid) from the blood of the buffaloes were used for validation of selected genes via qRTPCR. Concentrations of BHBA, glucose and oxidative stress markers were identified with their respective optimized protocols. RESULTS: The analysis of qRT-PCR gave similar trends as shown by in-silico analysis throughout the transition period. Significant changes (p<0.05) in the levels of BHBA, glucose and oxidative stress markers throughout this period were observed. This study provides validation from in-silico and qRT-PCR assays for potential markers to be used for earliest diagnosis of negative energy balance in buffaloes. CONCLUSION: Apart from conventional diagnostic methods, this study improves the understanding of putative biomarkers at the molecular level which helps to unfold their role in normal immune function, fat synthesis/metabolism and oxidative stress pathways. Therefore, provides an opportunity to discover more accurate and sensitive diagnostic aids.