Diagnoses and Treatment of Acquired Undescended Testes: A Review.

Acquired undescended testes were once considered a sporadic disease. In recent years, reports suggest that they are not uncommon, with an incidence rate about 3 times that of congenital undescended testes. The etiology of acquired undescended testes remains inconclusive, clinical diagnostic standards are unclear, and treatment approaches are still controversial. There is ongoing debate about the mechanism of testicular ascent. The prevailing view is that acquired undescended testes occur due to the partial absorption of the gubernaculum, which forms part of the parietal peritoneum. The residual gubernacular fibers continuously pull on the spermatic cord, preventing the spermatic cord from elongating proportionately to somatic growth, leading to a re-ascent of the testis. Acquired undescended testes may increase the risk of testicular cancer, but this is still debated. The preferred treatment method is also controversial. However, surgical fixation has an immediate effect; no studies have proven that early surgery improves fertility in patients. The etiology of acquired undescended testes is closely related to the continuous pull of the residual gubernacular fibers on the spermatic cord, which prevents the cord from extending proportionately to body growth. There are no clear diagnostic standards for acquired undescended testes yet, and spontaneous descent is possible, so testicular fixation surgery may not be the preferred treatment method.

Utilizing ChatGPT for Curriculum Learning in Developing a Clinical Grade Pneumothorax Detection Model: A Multisite Validation Study.

Background: Pneumothorax detection is often challenging, particularly when radiographic features are subtle. This study introduces a deep learning model that integrates curriculum learning and ChatGPT to enhance the detection of pneumothorax in chest X-rays. Methods: The model training began with large, easily detectable pneumothoraces, gradually incorporating smaller, more complex cases to prevent performance plateauing. The training dataset comprised 6445 anonymized radiographs, validated across multiple sites, and further tested for generalizability in diverse clinical subgroups. Performance metrics were analyzed using descriptive statistics. Results: The model achieved a sensitivity of 0.97 and a specificity of 0.97, with an area under the curve (AUC) of 0.98, demonstrating a performance comparable to that of many FDA-approved devices. Conclusions: This study suggests that a structured approach to training deep learning models, through curriculum learning and enhanced data extraction via natural language processing, can facilitate and improve the training of AI models for pneumothorax detection.

Boosting All-Perovskite Tandem Solar Cells by Revitalizing the Buried Tin-Lead Perovskite Interface.

Narrow-bandgap (NBG) mixed tin-lead (Sn-Pb) perovskite solar cells (PSCs) serve as crucial top subcells in all-perovskite tandem solar cells (TSCs). However, the prevalent use of poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT: PSS) hole transport layers (HTLs) in NBG PSCs compromises device efficiency and stability. To address this, the study proposes a revitalizing strategy for the buried interface of Sn-Pb perovskites by directly immersing acetylcholine chloride (ACh) into PEDOT: PSS. ACh acts as a proficient "diver," not only modulating the bottom PEDOT: PSS HTLs but also facilitating the reconstruction of the buried interface and significantly enhancing the quality of the top perovskite layers. This intervention with ACh prevents Sn2+ oxidation, mitigates buried defects, and encourages the growth of large, densely packed grains within Sn-Pb perovskites. Consequently, the optimized NBG PSCs exhibit significantly improved hole transport and reduced carrier recombination, achieving a steady-state efficiency of 22.98% with enhanced stability. Furthermore, these optimized NBG Sn-Pb cells enable highly efficient two-terminal and four-terminal all-perovskite TSCs, boasting steady-state efficiencies of 27.54% (certified at 26.41%) and 28.01%, respectively. This study emphasizes the importance of optimizing NBG PSCs through buried interface reconstruction, propelling the advancement of all-perovskite TSCs.

Organic Ligand Engineering for Tailoring Electron-Phonon Coupling in 2D Hybrid Perovskites.

In the emerging two-dimensional organic-inorganic hybrid perovskites, the electronic structures and carrier behaviors are strongly impacted by intrinsic electron-phonon interactions, which have received inadequate attention. In this study, we report an intriguing phenomenon of negative carrier diffusion induced by electron-phonon coupling in (2T)2PbI4. Theoretical calculations reveal that the electron-phonon coupling drives the band alignment in (2T)2PbI4 to alternate between type I and type II heterostructures. As a consequence, photoexcited holes undergo transitions between the organic ligands and inorganic layers, resulting in abnormal carrier transport behavior compared to other two-dimensional hybrid perovskites. These findings provide valuable insights into the role of electron-phonon coupling in shaping the band alignments and carrier behaviors in two-dimensional hybrid perovskites. They also open up exciting avenues for designing and fabricating functional semiconductor heterostructures with tailored properties.

Discovery and Preclinical Characterization of BIIB129, a Covalent, Selective, and Brain-Penetrant BTK Inhibitor for the Treatment of Multiple Sclerosis.

Multiple sclerosis (MS) is a chronic disease with an underlying pathology characterized by inflammation-driven neuronal loss, axonal injury, and demyelination. Bruton's tyrosine kinase (BTK), a nonreceptor tyrosine kinase and member of the TEC family of kinases, is involved in the regulation, migration, and functional activation of B cells and myeloid cells in the periphery and the central nervous system (CNS), cell types which are deemed central to the pathology contributing to disease progression in MS patients. Herein, we describe the discovery of BIIB129 (25), a structurally distinct and brain-penetrant targeted covalent inhibitor (TCI) of BTK with an unprecedented binding mode responsible for its high kinome selectivity. BIIB129 (25) demonstrated efficacy in disease-relevant preclinical in vivo models of B cell proliferation in the CNS, exhibits a favorable safety profile suitable for clinical development as an immunomodulating therapy for MS, and has a low projected total human daily dose.

Optoelectronic tuning of plasmon resonances via optically modulated hot electrons.

Fast optical modulation of nanoplasmonics is fundamental for on-chip integration of all-optical devices. Although various strategies have been proposed for dynamic modulation of surface plasmons, critical issues of device compatibility and extremely low efficiency in the visible spectrum hamper the application of optoplasmonic nanochips. Here we establish an optoplasmonic system based on Au@Cu2-xS hybrid core-shell nanoparticles. The optical excitation of hot electrons and their charge transfer to the semiconductor coating (Cu2-xS) lead to lowered electron density of Au, which results in the red shift of the localized surface plasmon resonance. The hot electrons can also transport through the Cu2-xS layer to the metal substrate, which increases the conductance of the nanogap. As such, the coupled gap plasmon blue-shifts with a magnitude of up to ∼15 nm, depending on the excitation power and the thickness of the coatings, which agrees with numerical simulations. All of this optoelectronic tuning process is highly reversible, controllable and fast with a modulated laser beam, which is highly compatible and sufficiently useful for on-chip integration of nanophotonic devices.

Deep learning model for pleural effusion detection via active learning and pseudo-labeling: a multisite study.

BACKGROUND: The study aimed to develop and validate a deep learning-based Computer Aided Triage (CADt) algorithm for detecting pleural effusion in chest radiographs using an active learning (AL) framework. This is aimed at addressing the critical need for a clinical grade algorithm that can timely diagnose pleural effusion, which affects approximately 1.5 million people annually in the United States. METHODS: In this multisite study, 10,599 chest radiographs from 2006 to 2018 were retrospectively collected from an institution in Taiwan to train the deep learning algorithm. The AL framework utilized significantly reduced the need for expert annotations. For external validation, the algorithm was tested on a multisite dataset of 600 chest radiographs from 22 clinical sites in the United States and Taiwan, which were annotated by three U.S. board-certified radiologists. RESULTS: The CADt algorithm demonstrated high effectiveness in identifying pleural effusion, achieving a sensitivity of 0.95 (95% CI: [0.92, 0.97]) and a specificity of 0.97 (95% CI: [0.95, 0.99]). The area under the receiver operating characteristic curve (AUC) was 0.97 (95% DeLong's CI: [0.95, 0.99]). Subgroup analyses showed that the algorithm maintained robust performance across various demographics and clinical settings. CONCLUSION: This study presents a novel approach in developing clinical grade CADt solutions for the diagnosis of pleural effusion. The AL-based CADt algorithm not only achieved high accuracy in detecting pleural effusion but also significantly reduced the workload required for clinical experts in annotating medical data. This method enhances the feasibility of employing advanced technological solutions for prompt and accurate diagnosis in medical settings.

Anti-epileptic drug use during adjuvant chemo-radiotherapy is associated with poorer survival in patients with glioblastoma: A nationwide population-based cohort study.

INTRODUCTION: There are emerging but inconsistent evidences about anti-epileptic drugs (AEDs) as radio- or chemo-sensitizers to improve survival in glioblastoma patients. We conducted a nationwide population-based study to evaluate the impact of concurrent AED during post-operative chemo-radiotherapy on outcome. MATERIAL AND METHODS: A total of 1057 glioblastoma patients were identified by National Health Insurance Research Database and Cancer Registry in 2008-2015. Eligible criteria included those receiving surgery, adjuvant radiotherapy and temozolomide, and without other cancer diagnoses. Survival between patients taking concurrent AED for 14 days or more during chemo-radiotherapy (AED group) and those who did not (non-AED group) were compared, and subgroup analyses for those with valproic acid (VPA), levetiracetam (LEV), or phenytoin were performed. Multivariate analyses were used to adjust for confounding factors. RESULTS: There were 642 patients in the AED group, whereas 415 in the non-AED group. The demographic data was balanced except trend of more patients in the AED group had previous drug history of AEDs (22.6% vs. 18%, P 0.078). Overall, the AED group had significantly increased risk of mortality (HR = 1.18, P 0.016) compared to the non-AED group. Besides, an adverse dose-dependent relationship on survival was also demonstrated in the AED group (HR = 1.118, P 0.0003). In subgroup analyses, the significant detrimental effect was demonstrated in VPA group (HR = 1.29,P 0.0002), but not in LEV (HR = 1.18, P 0.079) and phenytoin (HR = 0.98, P 0.862). CONCLUSIONS: Improved survival was not observed in patients with concurrent AEDs during chemo-radiotherapy. Our real-world data did not support prophylactic use of AEDs for glioblastoma patients.

Diet Outcome in Patients With Hypopharyngeal Defects Repaired With Different Reconstruction Flaps: A Comparative Study.

OBJECTIVES: To assess potential risk factors influencing diet outcomes after reconstruction of subtotal hypopharyngeal defects using free patch- or tube-shaped anterolateral thigh (ALT) fasciocutaneous flaps. STUDY DESIGN: Retrospective cohort study. SETTING: First-level referral hospital. METHODS: Between January 2011 and December 2020, we studied hypopharyngeal cancer patients who underwent the reconstruction of hypopharyngeal defects using free patch- or tube-shaped ALT fasciocutaneous flaps. The choice between patch- or tube-shaped ALT flaps depended on the defect's nature, favoring patch-shaped for subtotal defects and tube-shaped for circumferential defects. A restricted diet was characterized by a history of enterostomy or endoscopic esophageal dilation treatment postreconstruction. We analyzed patients with restricted diets at 1- and 3-year follow-up visits. RESULTS: Ninety-eight patients were enrolled; 39 patch-shaped flaps, and 59 tube-shaped flaps. No significances were noted in demographics, postoperative radiotherapy (RT) or chemotherapy, rates of free flap reoperation/salvage, or complications. However, a significant difference emerged in diet outcomes at the 1-year follow-up (P = .005). The rate of a restricted diet was 6.08 times higher in patients with tube-shaped flaps compared to patch-shaped flaps (95% confidence interval [CI]: 1.95-18.94). Stratifying based on postoperative RT revealed a 5.47 times higher rate of a restricted diet in tube-shaped flap recipients compared to patch-shaped flap recipients (95% CI: 1.44-20.48). No significances were observed in 5-year survival rates. CONCLUSION: Concerning postoperative RT, patch-shaped flaps exhibited a lower incidence of a restricted diet compared to tube-shaped flaps. Preservation of the posterior mucosa may play a crucial role in preventing RT-induced esophageal stricture.

5G Indoor Positioning Error Correction Based on 5G-PECNN.

With the development of the mobile network communication industry, 5G has been widely used in the consumer market, and the application of 5G technology for indoor positioning has emerged. Like most indoor positioning techniques, the propagation of 5G signals in indoor spaces is affected by noise, multipath propagation interference, installation errors, and other factors, leading to errors in 5G indoor positioning. This paper aims to address these issues by first constructing a 5G indoor positioning dataset and analyzing the characteristics of 5G positioning errors. Subsequently, we propose a 5G Positioning Error Correction Neural Network (5G-PECNN) based on neural networks. This network employs a multi-level fusion network structure designed to adapt to the error characteristics of 5G through adaptive gradient descent. Experimental validation demonstrates that the algorithm proposed in this paper achieves superior error correction within the error region, significantly outperforming traditional neural networks.

Mixed tin-lead perovskites with balanced crystallization and oxidation barrier for all-perovskite tandem solar cells.

Mixed tin-lead perovskite solar cells have driven a lot of passion for research because of their vital role in all-perovskite tandem solar cells, which hold the potential for achieving higher efficiencies compared to single-junction counterparts. However, the pronounced disparity in crystallization processes between tin-based perovskites and lead-based perovskites, coupled with the easy Sn2+ oxidation, has long been a dominant factor contributing to high defect densities. In this study, we propose a multidimensional strategy to achieve efficient tin-lead perovskite solar cells by employing a functional N-(carboxypheny)guanidine hydrochloride molecule. The tailored N-(carboxypheny)guanidine hydrochloride molecule plays a pivotal role in manipulating the crystallization and grain growth of tin-lead perovskites, while also serving as a preservative to effectively inhibit Sn2+ oxidation, owing to the strong binding between N-(carboxypheny)guanidine hydrochloride and tin (II) iodide and the elevated energy barriers for oxidation. Consequently, single-junction tin-lead cells exhibit a stabilized power conversion efficiency of 23.11% and can maintain 97.45% of their initial value even after 3500 h of shelf storage in an inert atmosphere without encapsulation. We further integrate tin-lead perovskites into two-terminal monolithic all-perovskite tandem cells, delivering a certified efficiency of 27.35%.

Tailoring Perovskite Surface Potential and Chelation Advances Efficient Solar Cells.

Modifying perovskite surface using various organic ammonium halide cations has proven to be an effective approach for enhancing the overall performance of perovskite solar cells. Nevertheless, the impact of the structural symmetry of these ammonium halide cations on perovskite interface termination has remained uncertain. Here, this work investigates the influence of symmetry on the performance of the devices, using molecules based on symmetrical bis(2-chloroethyl)ammonium cation (B(CE)A+) and asymmetrical 2-chloroethylammonium cation (CEA+) as interface layers between the perovskite and hole transport layer. These results reveal that the symmetrical B(CE)A+ cations lead to a more homogeneous surface potential and more comprehensive chelation with uncoordinated Pb2+ compared to the asymmetrical cations, resulting in a more favorable energy band alignment and strengthened defect healing. This strategy, leveraging the spatial geometrical symmetry of the interface cations, promotes hole carrier extraction between functional layers and reduces nonradiative recombination on the perovskite surface. Consequently, perovskite solar cells processed with the symmetrical B(CE)A+ cations achieve a power conversion efficiency (PCE) of 25.60% and retain ≈91% of their initial PCE after 500 h of maximum power point operation. This work highlights the significant benefits of utilizing structurally symmetrical cations in promoting the performance and stability of perovskite solar cells.

Enhancing Light Out-coupling in Perovskite Light-Emitting Diodes through Plasmonic Nanostructures.

Perovskite light-emitting diodes (PeLEDs) have emerged as promising candidates for lighting and display technologies owing to their high photoluminescence quantum efficiency and high carrier mobility. However, the performance of planar PeLEDs is limited by the out-coupling efficiency, predominantly governed by photonic losses at device interfaces. Most notably, the plasmonic loss at the metal electrode interfaces can account for up to 60% of the total loss. Here, we investigate the use of plasmonic nanostructures to improve the light out-coupling in PeLEDs. By integrating these nanostructures with PeLEDs, we have demonstrated an effectively reduced plasmonic loss and enhanced light out-coupling. As a result, the nanostructured PeLEDs exhibit an average 1.5-fold increase in external quantum efficiency and an ∼20-fold improvement in device lifetime. This finding offers a generic approach for enhancing light out-coupling, promising great potential to go beyond existing performance limitations.

[Review of UAV-based Atmospheric Fine Particulate Matter and Ozone Pollution Detection and Source Localization].

In recent years, the management of atmospheric fine particulate matter(PM2.5) pollution in China has achieved staged success, but ozone(O3) pollution has increased rapidly. Detection and source localization of atmospheric pollutants is the basis and key to controlling the combined pollution of PM2.5 and O3. With the rapid development of UAV technology and sensor technology, air pollution detection based on UAV platforms can effectively obtain the structural characteristics of PM2.5 and O3 near the surface and accurately trace the source of air pollution events by applying the computer algorithms, with the characteristics of high timeliness, flexibility, and spatial and temporal resolution. This will help researchers understand the distribution, changes, and sources of regional pollutants and provide a scientific basis for the synergistic control of combined air pollution. This study reviewed the traditional air pollution detection methods, summarized the types of UAV platforms and detection instruments commonly used in pollution detection, concluded the applications of UAV-based PM2.5 and O3 pollution detection and the algorithms of pollution source localization, and discussed the future trends of UAV-based air pollution detection.