Deeper Layers Research Articles

It all began in Issaquah 50 years ago

Abstract “Somehow scientists still pursue the same questions, if now on higher levels of theoretical abstraction rooted in deeper layers of empirical evidence… To paraphrase an old philosophy joke, science is more like it is today than it has ever been. In other words, science remains as challenging as ever to human inquiry. And the need to communicate its progress… remains as essential now as then.” — Tom Siegfried, Science News 2021 In fact, essential questions about pain have not changed since IASP's creation in Issaquah: what causes it and how can we treat it? Are we any closer to answering these questions, or have we just widened the gap between bench and bedside? The technology used to answer questions about pain mechanisms has certainly changed, whether the focus is on sensory neurons, spinal cord circuitry, descending controls or cortical pain processing. In this paper, we will describe how transgenics, transcriptomics, optogenetics, calcium imaging, fMRI, neuroimmunology and in silico drug development have transformed the way we examine the complexity of pain processing. But does it all, as our founders hoped, help people with pain? Are voltage-gated Na channels the new holy grail for analgesic development, is there a pain biomarker, can we completely replace opioids, will proteomic analyses identify novel targets, is there a “pain matrix,” and can it be targeted? Do the answers lie in our tangible discoveries, or in the seemingly intangible? Our founders could barely imagine what we know now, yet their questions remain.

Anatomical consideration and techniques in thread nose augmentation with mesh scaffold implant

Introduction Non-surgical rhinoplasty has evolved with the introduction of volumizing threads, which offer a less invasive alternative to traditional methods by enhancing nasal contours while minimizing filler use. This technique is gaining popularity, particularly in Southeast Asia, due to its shorter recovery time, reduced risk profile, and ability to prevent the ‘Avatar nose’ effect. However, there is limited anatomical guidance available for its application, especially in the Asian population. Materials and Methods This study analyzes the anatomical layers of the nose to guide the proper placement of volumizing threads. Three cases are presented, highlighting different approaches to nasal bridge enhancement, nasal tip augmentation, and combined use of threads and fillers. The placement of threads in the deep fat layer beneath the fibromuscular layer was emphasized to avoid vascular complications. Results The cases demonstrated with mesh thread (Tess Inc., Korea) successful outcomes with well-defined nasal contours and patient satisfaction. The techniques used allowed for precise enhancements while minimizing risks associated with superficial thread placement and vascular injury. Conclusion Volumizing threads provide an effective and safe method for non-surgical rhinoplasty, particularly when informed by a thorough understanding of nasal anatomy. The results support the growing use of this technique in esthetic practice, especially in regions like Southeast Asia.

Fast‐MedNeXt: Accelerating the MedNeXt Architecture to Improve Brain Tumour Segmentation Efficiency

ABSTRACTWith the rapid development of medical imaging technology, 3D image segmentation technology has gradually become a mainstream method, especially in brain tumour detection and diagnosis showing its unique advantages. The technique makes full use of 3D spatial information to locate and analyze tumours more accurately, thus playing an important role in improving diagnostic accuracy, optimising treatment planning and promoting research. However, it also suffers from significant computational expenditure and delayed processing pace. In this paper, we propose an innovative optimisation scheme to address this problem. We thoroughly investigate the MedNeXt network and propose Fast‐MedNeXt, which aims to increase the processing speed while maintaining accuracy. First, we introduce the partial convolution (PConv) technique, which replaces the deep convolutional layers in the network. This improvement effectively reduces computation and memory requirements while maintaining efficient feature extraction. Second, based on PConv, we propose PConv‐Down and PConv‐Up modules, which are applied to the up‐sampling and down‐sampling modules to further optimise the network structure and improve efficiency. To confirm the efficacy of the approach, we carried out a sequence of tests in the multimodal brain tumour segmentation challenge 2021 (BraTS2021). By comparing with the MedNeXt series network, the Fast‐MedNeXt reduced the latency by 22.1%, 20.5%, 15.8%, and 11.4% respectively, while the average accuracy also increased by 0.475% and 0.2% respectively. These significant performance improvements demonstrate the effectiveness of Fast‐MedNeXt in 3D medical image segmentation tasks and provide a new and more efficient solution for the field.

Effect of layered fertilizer strategies on rapeseed (Brassica napus L.) productivity and soil macropore characteristics under mechanical direct-sowing

Layered fertilization parameters affects crop root system configuration and growth distribution, which in turn affects soil pore properties and aggregate structure. Therefore, understanding the spatial distribution of the root system and soil pore space is helpful in choosing a reasonable fertilization ratio in production practice, which ensures high and stable crop yields and at the same time improves fertilizer utilization and soil health. Albeit the impact of layered fertilization ratio at varied rates on soil pore characteristics in the soil profile at a microscale level remains limited. This study quantifies the impacts of layered fertilization ratio under on rapeseed root distribution and soil pore characteristics using the root analysis system and X-ray computed tomography (XCT). A new fertilization pattern that shallow-deep layer synchronized mechanical sowing was using, rotary tillage mixed fertilization in the shallow layer and 10 cm side-deep band fertilization in the deeper layer. It set five ratios of fertilizer amounts between shallow and deep layers as 0:4 (FD), 1:3 (FL), 2:2 (FM), 3:1 (FH), and 4:0 (F0), with non-fertilization (CK) as the control treatment. The results indicated that layered fertilization effectively improved the rape root conformation and spatial distribution, significantly increased total soil porosity and moisture content, and reduced soil bulk density and resistance (P < 0.05). Additionally, root configuration is closely related to soil pore structure and crop yield. Notably, compared with other treatments, the macroscopic porosity, equivalent pore diameter, hydraulic radius and roundness of FM treatment are significantly improved, and it effectively improves the yield and quality of rapeseed. Correlation analysis showed that the root system configuration parameters were negatively correlated with soil bulk density and resistance but positively correlated with soil moisture content, and macropore morphology parameters and rapeseed yield. Our study demonstrate that layered fertilization can improved rape growth and soil macropore porosity, but its effect depends on good tillage macropore characteristics and distribution created by reasonable fertilization ratio, which provided a theoretical basis for high-yield, efficient, green, and sustainable mechanized direct-sowing production of rapeseed.

Image Denoising Using Deblur Generative Adversarial Network Denoising U-Net

Convolutional neural networks (CNNs) are becoming increasingly popular for image denoising. U-Nets, a type of CNN architecture, have been shown to be effective for this task. However, the impact of shallow layers on deeper layers decreases as the depth of the network increases. To address this issue, the authors propose a new image denoising method called DGANDU-Net. DGANDU-Net combines the DeblurGAN design with a U-Net architecture. This combination allows DGANDU-Net to effectively remove noise from images while preserving fine details. The authors also propose the use of two loss functions, mean square error (MSE) and perceptual loss, to improve the performance of DGANDU-Net. MSE is used to learn and improve the extracted features, while perceptual loss is used to produce the final denoised image. The authors evaluate the performance of DGANDU-Net on a variety of noise levels and find that it outperforms other state-of-the-art denoising algorithms in terms of both visual quality and two evaluation indices, including peak signal-to-noise ratio (PSNR) and Structural Similarity Index Measure (SSIM). Specifically, for extremely noisy environments with a noise standard deviation of 75, DGANDU-Net achieves an average PSNR of 37.39[Formula: see text]dB in the test dataset. The authors conclude that DGANDU-Net is a promising new method for image denoising that has the potential to significantly improve the quality of medical images used for diagnosis and treatment.

Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model

Abstract. We evaluate the vertical turbulent-kinetic-energy (TKE) mixing scheme of the NEMO-SI3 ocean–sea-ice model in sea-ice-covered regions of the Arctic Ocean. Specifically, we assess the parameters involved in TKE mixed-layer-penetration (MLP) parameterization. This ad hoc parameterization aims to capture processes that impact the ocean surface boundary layer, such as near-inertial oscillations, ocean swells, and waves, which are often not well represented in the default TKE scheme. We evaluate this parameterization for the first time in three regions of the Arctic Ocean: the Makarov, Eurasian, and Canada basins. We demonstrate the strong effect of the scaling parameter that accounts for the presence of sea ice. Our results confirm that TKE MLP must be scaled down below sea ice to avoid unrealistically deep mixed layers. The other parameters evaluated are the percentage of energy penetrating below the mixed layer and the length scale of its decay with depth. All these parameters affect mixed-layer depth and its seasonal cycle, surface temperature, and salinity, as well as underlying stratification. Shallow mixed layers are associated with stronger stratification and fresh surface anomalies, and deeper mixed layers correspond to weaker stratification and salty surface anomalies. Notably, we observe significant impacts on sea-ice thickness across the Arctic Ocean in two scenarios: when the scaling parameter due to sea ice is absent and when the TKE mixed-layer-penetration process vanishes. In the former case, we observe an increase of several meters in mixed-layer depth, along with a reduction in sea-ice thickness ranging from 30 to 40 cm, reflecting the impact of stronger mixing. Conversely, in the latter case, we notice that a shallower mixed layer is accompanied by a moderate increase in sea-ice thickness, ranging from 10 to 20 cm, as expected from weaker mixing. Additionally, interannual variability suggests that experiments incorporating a scaling parameter based on sea-ice concentration display an increased mixed-layer depth during periods of reduced sea ice, which is consistent with observed trends. These findings underscore the influence of enhanced ocean mixing, through specific parameterizations, on the physical properties of the upper ocean and sea ice.

Laminar fMRI in the locked-in stage of amyotrophic lateral sclerosis shows preserved activity in layer Vb of primary motor cortex

Amyotrophic lateral sclerosis (ALS) affects the cerebral cortex layer-dependently, most notably by the foremost targeting of upper motor neurons (UMNs) sited in layer Vb. Previous studies have shown a retained ability of paralysed patients to activate cortical motor networks, even in late-stage ALS. However, it is currently unknown whether such activation reflects a retained capacity to process sensorimotor inputs or if it is a result of actual motor output. Given the distinct function of individual cortical layers, layer-specific functional measurements may provide insight to this question. In this study, using submillimetre resolution laminar fMRI, we assessed the layer-dependent activation associated with attempted (motor) and passive (somatosensory) movements in a locked-in stage ALS patient. We found robust activation in both superficial and deep layers of primary motor cortex (M1). The peak activation in deep layers was localised to layer Vb. These findings demonstrate preserved activity in deep output layers of M1, possibly reflecting a retained ability to engage surviving UMNs despite years of paralysis. Our study underscores the capacity of laminar fMRI to discern subtle cortical activity and elucidates a promising pathway for probing in vivo human ALS pathology with unprecedented resolution.

Utilizing Attention-Enhanced Deep Neural Networks for Large-Scale Preliminary Diabetes Screening in Population Health Data

Early screening for diabetes can promptly identify potential early stage patients, possibly delaying complications and reducing mortality rates. This paper presents a novel technique for early diabetes screening and prediction, called the Attention-Enhanced Deep Neural Network (AEDNN). The proposed AEDNN model incorporates an Attention-based Feature Weighting Layer combined with deep neural network layers to achieve precise diabetes prediction. In this study, we utilized the Diabetes-NHANES dataset and the Pima Indians Diabetes dataset. To handle significant missing values and outliers, group median imputation was applied. Oversampling techniques were used to balance the diabetes and non-diabetes groups. The data were processed through an Attention-based Feature Weighting Layer for feature extraction, producing a feature matrix. This matrix was subjected to Hadamard product operations with the raw data to obtain weighted data, which were subsequently input into deep neural network layers for training. The parameters were fine-tuned and the L2 regularization and dropout layers were added to enhance the generalization performance of the model. The model’s reliability was thoroughly assessed through various metrics, including the accuracy, precision, recall, F1 score, mean squared error (MSE), and R2 score, as well as the ROC and AUC curves. The proposed model achieved a prediction accuracy of 98.4% in the Pima Indians Diabetes dataset. When the test dataset was expanded to the large-scale Diabetes-NHANES dataset, which contains 52,390 samples, the test precision of the model improved further to 99.82%, with an AUC of 0.9995. A comparative analysis was conducted using multiple models, including logistic regression with L1 regularization, support vector machine (SVM), random forest, K-nearest neighbors (KNNs), AdaBoost, XGBoost, and the latest semi-supervised XGBoost. The feature extraction method using attention mechanisms was compared with the classical feature selection methods, Lasso and Ridge. The experiments were performed on the same dataset, and the conclusion was that the Attention-based Ensemble Deep Neural Network (AEDNN) outperformed all the aforementioned methods. These results indicate that the model not only performs well on smaller datasets but also fully leverages its advantages on larger datasets, demonstrating strong generalization ability and robustness. The proposed model can effectively assist clinicians in the early screening of diabetes patients. This is particularly beneficial for the preliminary screening of high-risk individuals in large-scale, extensive healthcare datasets, followed by detailed examination and diagnosis. Compared to the existing methods, our AEDNN model showed an overall performance improvement of 1.75%.

Extracting the Ultradeep Oil: David Mitchell’s The Bone Clocks

ABSTRACT David Mitchell’s The Bone Clocks reworks the novel form with its generic experimentation, a gesture in response to the transformed geosocial contours of the Anthropocene. Straddling between the realist and the fantastical, the novel decentralizes human perspective that proves increasingly unsatisfactory to confront the complex causality of climate change for imaginative and conceptual limits. In this essay, I argue that Mitchell attends to a conceptual limit imposed by petroculture, one that refuses to connect the future warming climate with the present large-scale combustion of fossil fuels. The temporal disjunction evolves into a strong antagonism between present and future, which can be tellingly revealed by the coupling of realist and fantastical traditions. Mitchell’s genre-blending device therefore pushes the novel form beyond its usual near-sightedness, excavating a deeper layer of climate-induced crisis of human imagination, namely the present’s inability to recognize the delayed effects of its unsustainable consumption pattern. Viewed through an energy-oriented perspective, The Bone Clocks engages with modernity’s ultradeep relationship with oil, complicating our understanding of climate temporality that matters in terms of intergenerational justice.

Robinia pseudoacacia Quickly Adjusts Its Water Uptake after Rainfall in Seasonally Dry Regions

Precipitation is a key factor affecting plant growth and development in seasonally arid regions. However, most of the traditional hydrological methods mainly select typically sunny days for sampling, and the immediate water absorption strategy of plants during and after rainfall is still unclear. This study used stable hydrogen and oxygen isotope technology to study the soil moisture absorption rates of Robinia pseudoacacia and the soil moisture content at different soil layers at different sampling times (0, 6, 12, 18 and 24 h) after rainfall. The results showed that the moisture content of the shallow soil layer decreased, while that of the deep soil layer increased over time after rainfall. R. pseudoacacia mainly utilized water from the 0–20 and 20–40 cm soil layers at 6 h after rainfall, which accounted for 36.52% and 22.25% of the rainfall, respectively. At 24 h, the 40–60, 60–80 and 80–100 cm soil layers contributed 25.25%, 18.44% and 24.45% of the water content, respectively. The shallow soil layer retained more rainfall within 6 h after rain fell, and the water retention ratio of the medium–shallow soil layer (0–60 cm) increased to 48.4%, retaining more water at 14–20 h. At 12 h, the medium–shallow soil layer (0–60 cm), runoff and groundwater constituted 37.1%, 14.4% and 15.7% of the precipitation, respectively, and rainfall retained in the deep soil layer (60–100 cm) accounted for 32.8%. In summary, R. pseudoacacia tends to use a large amount of shallow soil water in seasonally arid regions when precipitation supplements the surface soil moisture content and it utilizes deep soil water when the rainfall infiltrates and recharges the deep soil layer. Since R. pseudoacacia is sensitive to precipitation, it can quickly adjust its water absorption depth range during the short-term rainfall period to absorb as much precipitation as possible.

Accelerated Wound Healing of Tetrahedral-Framework Nucleic Acid Nanozymes with High Penetration and Antioxidant Capacity

The wound repair process usually leads to a non-functioning mass of fibrotic tissue because of the oxidative imbalance of deep tissue layers. However, how to improve the penetration of active ingredients into deeper layers and regulate oxidative imbalances to create a regenerative microenvironment still remains a challenge. In this study, we designed a novel tetrahedral-framework nucleic acid (tFNA) nanozyme that could penetrate the skin/mucosa barrier as deep as 450 μm within 24 h. We also demonstrated the protective role of tFNAs on the mitochondrial structural and functional integrity and inhibition of reactive oxygen species production to repair oxidative imbalances through ERK1/2-Nrf2-HO-1 during repair processes. It was found that the proliferative state and the migration ability of postburn cells in vitro were accelerated, and the early closure of wounds in vivo was significantly promoted. This study therefore provides a promising strategy to efficiently regulate the oxidative imbalances in the deep layers of the skin during wound healing.

Advanced Security Framework for 6G Networks: Integrating Deep Learning and Physical Layer Security

This paper presents an advanced framework for securing 6G communication by integrating deep learning and physical layer security (PLS). The proposed model incorporates multi-stage detection mechanisms to enhance security against various attacks on the 6G air interface. Deep neural networks and a hybrid model are employed for sequential learning to improve classification accuracy and handle complex data patterns. Additionally, spoofing, jamming, and eavesdropping attacks are simulated to refine detection mechanisms. An anomaly detection system is developed to identify unusual signal patterns indicating potential attacks. The results demonstrate that machine learning (ML) and hybrid models outperform conventional approaches, showing improvements of up to 85% in bit error rate (BER) and 24% in accuracy, especially under attack conditions. This research contributes to the advancement of secure 6G communication systems, offering details on effective defence mechanisms against physical layer attacks.

Natural and agricultural disturbances differentially impact seedling emergence from soil seed banks in hyperarid ecosystems

Saudi Arabia has implemented ambitious environmental protection programs by creating numerous nature reserves throughout the country. Establishment of the latter nature reserves has led to farm abandonment and the initiation of ecosystem recovery processes. Agricultural practices are known to impact the structure and physicochemical properties of soils while also often markedly affecting natural ecosystem restoration processes. Moreover, weed proliferation in crop fields may modify soil seed banks (SSB), thereby impacting subsequent vegetation recovery. Therefore, it is essential to assess SSB compositions in degraded sites, such as abandoned farms (AF), so as to identify weed species and design efficient restoration strategies in hyperarid ecosystems. In this study, SSB compositions in upper and deep soil layers, standing vegetation compositions, and soil chemical properties were analyzed and compared for two natural ecosystems (NE), two abandoned orchards (AO), two AF, and two natural evaporite basins (EB). NE, AO, AF, and EB all exhibited similar chemical properties, suggesting that former agricultural activities have been guided by a fine understanding of the local environments. Agriculture had impacted the species composition of the observed standing vegetation and germinable SSBs, which could be partly explained by soil property modifications. The findings highlighted that SSBs would warrant detailed study prior to designing ecological restoration strategies, and that the drivers of horizontal and vertical weed dissemination in hyperarid ecosystems should also be explored to gain further insight into weed proliferation patterns and to adapt restoration strategies accordingly.

Depth-dependent effects of forest diversification on soil functionality and microbial community characteristics in subtropical forests

Soil microbes are critical to the maintenance of forest ecosystem function and stability. Forest diversification, such as monocultures versus mixed forests stands, can strongly influence microbial community patterns and processes, as well as their role in soil ecosystem multifunctionality, such as in subtropical forest ecosystems. However, less is known about these patterns and processes vary with soil depth. Here, we investigated the results of an eight-year forest diversification field experiment comparing the soil ecosystem multifunctionality, bacterial and fungal community assembly, and network patterns in mixed versus monoculture plantations along vertical profiles (0–80 cm depth) in a subtropical region. We found that the introduction of broadleaf trees in coniferous monocultures led to enhanced synergies between multiple functions, thus improving soil multifunctionality. The effects of mixed plantations on the functional potential in top soils were greater than in deep soils, especially for carbon degradation genes (apu, xylA, cex, and glx). Microbial community assembly in the top layer, particularly in mixed plantations, was dominated by stochastic processes, whereas deterministic were more important in the deep layer. Soil microbial network complexity and stability were higher in the top layer of mixed plantations, but in the deep layer was monoculture. Interestingly, the changes in microbial communities and multifunctionality in the top layer were mainly related to variation in nutrients, whereas those in the deep were more influenced by soil moisture. Overall, we reveal positive effects of mixed forest stands on soil microbial characteristics and functionality compared to that of monocultures. Our findings highlighted the importance of enhancing functional diversity through the promotion of tree species diversity, and managers can better develop forest management strategies to promote soil health under global change scenarios.

Comparative Study on Enhanced Skin Permeation Efficiency of Phenylephrine via Novel Lipid Vesicles: A Promising Approach in Preventing Chemotherapy-Induced Alopecia Management.

Chemotherapy-induced alopecia (CIA) significantly impacts patients' emotional and psychological well-being and treatment regimen. Phenylephrine, a topical vasoconstrictor, can potentially reduce hair loss by limiting chemotherapy drug delivery to hair follicles. However, effective delivery of Phenylephrine through the skin remains challenging. This study investigates lipid vesicles as delivery vehicles to enhance Phenylephrine's skin permeation and sustained release due to their biocompatibility and encapsulation capabilities. This study aimed to formulate and compare different lipid vesicles of Phenylephrine HCl for enhanced permeation through the skin for deep dermal delivery with sustained release of the drug so as to achieve local vasoconstriction. Phenylephrine-loaded ethosomes, invasomes, and transfersomes were prepared and characterized for particle size (PS), polydispersity index (PDI), and entrapment efficiency (EE %). These lipid vesicles were incorporated into hydrogels to facilitate sustained drug release to deep dermal layers where they could target local vasculature and cause vasoconstriction. The prepared vesicular gels were evaluated for various permeation parameters. The entrapment efficiencies of the developed vesicles ranged from 49.51 ± 3.25% to 69.09 ± 2.32%, with vesicle sizes ranging from 162.5 ± 5.21 nm to 321.32 ± 3.75 nm. Statistical analysis revealed significantly higher flux values (Jss, μg/cm2 h) of 0.6251, 0.6314, and 0.4075 for invasomal gel, ethosomal gel, and transfersomal gel, respectively, compared to plain gel (0.1254) (p < 0.005). The enhancement factors were 4.9848, 5.0350, and 3.2496 for invasomal gel, ethosomal gel, and transfersomal gel, respectively, indicating superior permeation abilities of ethosomal and invasomal formulations. The results demonstrate that ethosomal and invasomal formulations were efficient in delivering the drug to deep dermal layers of skin in a sustained manner. These findings suggest that these Lipidic vesicles would be able to target the local vasoconstrictor to vasculature, causing reduced hair loss by limiting chemotherapy drug delivery to hair follicles and managing chemotherapy-induced alopecia.

An investigation on the surface properties of B4C for advancing its nuclear applications

B4C is an important material in diverse nuclear applications. However, a systematic examination of its surface properties is still missing. In this work, we employ first-principles simulations to investigate the energetic stability of 16 distinct slab models representing (001), (100), (101), (110), and (111) surfaces, which are constructed by minimizing dangling bonds. Our results show that C-terminated (001) surface exhibits significantly greater stability than other surfaces under both the carbon and boron-rich conditions. Besides, we also study the defect formation energies on the C-terminated (001) surface and compare them with the cases in bulk. The high formation energies of the defects suggest a low likelihood of their occurrence on this surface, despite their formation energies being lower compared to bulk cases. Furthermore, mid-gap surface states are revealed for the top atomic layers of the C-terminated (001) surface, which are deduced at the deeper layers, and the band structures of the middle layers of this slab recover to the bulk band gap. These surface mid-gap states allow electron excitation from the valence band to these states, resulting in a reduced optical band gap compared to the bulk band gap of B4C. This provides a plausible explanation for the significantly smaller band gap observed in experiments compared to the larger gap predicted by theoretical models. Our study not only sheds light on the surface properties of B4C but also lays the groundwork for advancing this material for more advanced nuclear applications.

Immune-related toxic epidermal necrolysis affecting trachea mucosal epithelium: a case report and literature review

BackgroundMonoclonal antibodies against programmed cell death protein-1 (PD-1)/programmed death-ligand-1 (PD-L1) have emerged as critical tools in cancer treatment. However, concerns regarding their potential cutaneous and mucosal toxicity, along with severe complications, have drawn clinical attention. Further research is warranted to investigate the adverse reactions and treatment strategies associated with PD-1 monoclonal antibodies.MethodsWe present a detailed case report of a laryngeal cancer patient who developed toxic epidermal necrolysis (TEN) after treatment with PD-1 monoclonal antibody. We analyzed the etiology, diagnosis, and treatment approaches by integrating clinical manifestations, pathological examinations, and literature research.ResultsAfter PD-1 monoclonal antibody therapy, the patient exhibited systemic rash, bullae, and epidermal detachment, which subsequently involved the tracheal and bronchial mucosa, resulting in dyspnea. The patient recovered after treatments with steroids, macrolides, immunoglobulins, and etanercept, along with repeated removal of scabs via bronchoscopy. Literature reviewing suggests a potential association between PD-1 monoclonal antibodies and the pathogenesis of Steven Johnson’s Syndrome (SJS) and Toxic epidermal necrolysis (TEN), possibly due to immune dysregulation. Treatment consists of immediate discontinuation of suspicious drugs, essential supportive therapy, and systemic corticosteroid administration, with the addition of immunosuppressants and/or immunoglobulins needed.ConclusionThe mucocutaneous toxicity induced by PD-1 monoclonal antibodies is not limited to the surface of the skin but also in deep mucosal layers, potentially leading to life-threatening complications. Therefore, when using PD-1 monoclonal antibodies, clinicians should closely monitor adverse events and apply appropriate treatments as soon as possible to prevent severe complications.

Microvascular alterations of the ocular surface and retina in connective tissue disease-related interstitial lung disease.

To examine the disparities in macular retinal vascular density between individuals with connective tissue disease-related interstitial lung disease (CTD-ILD) and healthy controls (HCs) by optical coherence tomography angiography (OCTA) and to investigate the changes in microvascular density in abnormal eyes. For a retrospective case-control study, a total of 16 patients (32 eyes) diagnosed with CTD-ILD were selected as the ILD group. The 16 healthy volunteers with 32 eyes, matched in terms of age and sex with the patients, were recruited as control group. The macular retina's superficial retinal layer (SRL) and deep retinal layer (DRL) were examined and scanned using OCTA in each individual eye. The densities of retinal microvascular (MIR), macrovascular (MAR), and total microvascular (TMI) were calculated and compared. Changes in retinal vascular density in the macular region were analyzed using three different segmentation methods: central annuli segmentation method (C1-C6), hemispheric segmentation method [uperior right (SR), superior left (SL), inferior left (IL), and inferior right (IR)], and Early Treatment Diabetic Retinopathy Study (ETDRS) methods [superior (S), inferior (I), left (L), and right (R)]. The data were analyzed using Version 9.0 of GraphPad prism and Pearson analysis. The OCTA data demonstrated a statistically significant difference (P<0.05) in macular retinal microvessel density between the two groups. Specifically, in the SRL and DRL analyses, the ILD group exhibited significantly lower surface density of MIR and TMI compared to the HCs group (P<0.05). Furthermore, using the hemispheric segmentation method, the ILD group showed notable reductions in SL, SR, and IL in the superficial retina (P<0.05), as well as marked decreases in SL and IR in the deep retina (P<0.05). Similarly, when employing the ETDRS method, the ILD group displayed substantial drops in superficial retinal S and I (P<0.05), along with notable reductions in deep retinal L, I, and R (P<0.05). In the central annuli segmentation method, the ILD group exhibited a significant decrease in the superficial retinal C2-4 region (P<0.05), whereas the deep retina showed a notable reduction in the C3-5 region (P<0.05). Additionally, there was an observed higher positive likelihood ratio in the superficial SR region and deep MIR. Furthermore, there was a negative correlation between conjunctival vascular density and both deep and superficial retinal TMI (P<0.001). Patients with CTD-ILD exhibits a significantly higher conjunctival vascular density compared to the HCs group. Conversely, their fundus retinal microvascular density is significantly lower. Furthermore, CTD-ILD patients display notably lower superficial and deep retinal vascular density in comparison to the HCs group. The inverse correlation between conjunctival vascular density and both superficial and deep retinal TMI suggests that detecting subtle changes in ocular microcirculation could potentially serve as an early diagnostic indicator for connective tissue diseases, thereby enhancing disease management.

The Fungal Side of the Story: Saprotrophic- vs. Symbiotrophic-Predicted Ecological Roles of Fungal Communities in Two Meromictic Hypersaline Lakes from Romania

Over three-quarters of Earth’s surface exhibits extreme environments where life thrives under harsh physicochemical conditions. While prokaryotes have often been investigated in these environments, only recent studies have revealed the remarkable adaptability of eukaryotes, in particular fungi. This study explored the mycobiota of two meromictic hypersaline lakes, Ursu and Fără Fund, in Transylvania (Romania). The intrinsic and extrinsic fungal diversity was assessed using amplicon sequencing of environmental DNA samples from sediments, water columns, surrounding soils, and an associated rivulet. The fungal communities, illustrated by the 18S rRNA gene and ITS2 region, exhibited contrasting patterns between the lakes. The ITS2 region assessed better than the 18S rRNA gene the fungal diversity. The ITS2 data showed that Ascomycota was the most abundant fungal group identified in both lakes, followed by Aphelidiomycota, Chytridiomycota, and Basidiomycota. Despite similar α-diversity levels, significant differences in fungal community structure were observed between the lakes, correlated with salinity, total organic carbon, total nitrogen, and ammonium. Taxonomic profiling revealed depth-specific variations, with Saccharomycetes prevalent in Ursu Lake’s deeper layers and Lecanoromycetes prevalent in the Fără Fund Lake. The functional annotation using FungalTraits revealed diverse ecological roles within the fungal communities. Lichenized fungi were dominant in Fără Fund Lake, while saprotrophs were abundant in Ursu Lake. Additionally, wood and soil saprotrophs, along with plant pathogens, were more prevalent in the surrounding soils, rivulet, and surface water layers. A global overview of the trophic relations in each studied niche was impossible to establish due to the unconnected graphs corresponding to the trophic interactions of the analyzed fungi. Plotting the unweighted connected subgraphs at the genus level suggests that salinity made the studied niches similar for the identified taxa. This study shed light on the understudied fungal diversity, distribution, and ecological functions in hypersaline environments.

Hydrological processes in multi-layered aquifers of a karst watershed with coal mining activity: Insights from hydrochemistry and isotopes

Study regionThe Laochang Karst watershed (LCKW) is located in eastern Yunnan Province, southwestern China. It is the representative karst area affected by coal-mining activities in southwestern China. Study focusIdentifying hydrological processes of multi-layered aquifers in karst watersheds is challenging due to complex natural and anthropogenic processes. This study attempts to clarify the hydrological conceptual model of the LCKW using hydrochemistry and D, O, Sr, S, and C isotopes. New hydrological insights for the regionSurface water and multi-layered groundwater have the hydrochemical types of SO4-Ca·Mg, HCO3·SO4-Ca, and HCO3-Ca. Meteoric water and condensate were the major recharge sources. The main processes dominating hydrochemical compositions consist of sulfide oxidative dissolution, carbonate dissolution, positive cation exchange, and agricultural activities. Elevated SO42− concentration in the mine water, river water and shallow coalbed water mainly originated from the oxidation of pyrite in the coal-bearing strata of the Longtan Formation. whereas the deeper layers and groundwater away from the mines were hardly contaminated by SO42− due to the presence of aquiclude. HCO3− concentrations of surface water and multi-layered groundwater were mainly derived from carbonate dissolution and soil CO2, and mine water was also influenced by atmospheric CO2. Positive cation exchange contributed to increasing Na+ concentration. Agricultural activities contributed NO3−, Cl−, and K+ ions in aquifers, especially near large karst fallout caves. A hydrological model of multi-layered aquifers in the LCKW was built based on the above results. These findings will provide valuable guidance for understanding the hydrological processes of complex karst watersheds worldwide.