The microbiome – the community of microorganisms that is associated with an individual animal – has been an important driver of insect biodiversity globally, enabling insects to specialize on narrow, nutrient deficient diets. The importance of maternally inherited, obligate bacterial endosymbionts to provisioning nutrients missing from these narrow dietary niches has been well studied in insects. However, we know comparatively little about the processes that dictate the composition of non-maternally inherited bacteria in insect microbiomes, despite the importance of these bacteria in insect health, fitness, and vector competence. Here, we used two species of obligate insect ectoparasites of bats, the bat flies (Streblidae) Trichobius sphaeronotus and Nycterophilia coxata, to examine whether the microbiome, beyond obligate bacterial endosymbionts, is conserved or variable across geographic space, between ectoparasite species, or covaries with the external microbiome of their bat hosts or the cave environment. Our results indicate that ectoparasite microbiomes are highly conserved and specific to ectoparasite species, despite these species feeding on the blood of the same bat individuals in some cases. In contrast, we found high geographic variation in the fur microbiome of host bats and that the bat fur microbiome mimics the cave microbiomes. This research suggests that there is constraint on blood-feeding insect ectoparasites to maintain a specific microbiome distinct from their host and the environment, potentially to meet their nutritional needs. Given many of these bacteria are not known to be maternally inherited, this research lays the foundation for future examinations of how blood-feeding arthropods acquire and maintain bacteria in their microbiomes.

Cyber-physical threats to unmanned aerial vehicles (UAVs) involve manipulating control, communication, and sensor data through evil actions that an intruder can carry out. Drone cyber-physical systems rely on wireless connections, which can be attacked in many ways. The intruder can take advantage of the inherent vulnerabilities in the Global Positioning System (GPS) to spoof it and generate a fake signal that is transmitted to the receiver. The routes of UAV dynamic movements that are predicted, hijacked, and mitigated are presented in this work. The dynamic and adaptive GPS spoofing threat detection and mitigation system for networked UAVs has been proposed in this research. The suggested design technique finds the deviation in the flying path at different altitudes that cyber threats could cause. Drone route design based on multi-logit regression has been suggested to consider the spoofing errors between the waypoints of the expected and spoofed (hijacked) path to predict elevations and angles. By generating the appropriate thrusts of the drone’s rotor and then responding with a new rectified path to a spoof position detection, a proportional and derivative (PD) control has been developed for the attitude and position control of drones. For the swarm of drones, blockchain-based delegated proof of location (DPoL) as a consensus mechanism with GPS spoofing mitigation capability, at various waypoints and intervals, has been proposed. The effectiveness of the proposed work has been tested with simulation work supported by UAV testbed.

Background Allergic rhinitis (AR) is a highly prevalent chronic inflammatory disease of the nasal mucosa and a growing public health, medical and economic problem worldwide. Currently, allergen-specific immunotherapy was referred to as etiological treatment, which could restore immune homeostasis but limited by specific allergens. The development of potential therapeutic targets and drugs for allergic rhinitis is urgently needed. Methods A proteome-wide Mendelian randomization (MR) study was used to identify potential therapeutic targets and drugs for AR. The statistics were obtained from three European AR consortiums and then validated the results by the FinnGen and UK Biobank cohorts. The genetic tools for 1699 plasma proteins were from genome-wide studies and validated by deCODE proteins. To ensure the robustness of the results and the reliability of the conclusions, we performed sensitivity analyses, including bidirectional Mendelian randomization, heterogeneity testing, pleiotropy testing, Steiger filtering, phenotype scanning and colocalization analyses. Results MR analysis revealed that expression of C1GALT1C1, CLEC5A and IL1R1 were associated with an increased risk of AR, while the expression of B2M, VCAM1 and IGF1R were associated with a decreased risk of AR. Then the small molecule ochratoxin-a, ZG-10, pidorubicin and the JAK3 inhibitor VI were identified to be potential drugs for AR treatment through joint analysis by connectivity map (cMAP) and selected plasma proteins. Conclusion The identified proteins are causally related to the risk of AR and are promising potential drug targets for AR. In addition, the identified small molecules show potential as effective drugs and warrant further clinical investigation.

A document by Jiahui Wang. Click on the document to view its contents.

1. In the evolutionary arms race between plants and herbivores, sophisticated mechanisms of indirect defense play a pivotal role. This study investigated the intricate ecological dynamics between Aristolochia contorta, Sericinus montela, and Ooencyrtus spp., with a special focus on the role of volatile organic compounds (VOCs) in plant. 2. This study utilized field surveys, olfactometer experiments, and Gas Chromatography-Mass Spectrometry (GC-MS) analysis to investigate the role of volatile organic compounds. 3. Field surveys showed a 54.6% egg parasitism rate, with quadrats containing A. contorta and larvae attracting more Ooencyrtus spp. than those with the plant alone. In olfactometer bioassays, Ooencyrtus spp. demonstrated a notable preference for leaves damaged by a pattern wheel, attracting 46.8% of Ooencyrtus spp. compared to undamaged controls. Moreover, leaves treated with larval saliva were found to be similarly attractive, drawing in 48.7% of Ooencyrtus spp.. In addition, the difference in attraction between leaves with and without larval saliva did not reach statistical significance. GC-MS analysis identified essential VOCs in the damaged leaves, including hexyl acetate, cyclohexene, δ-cadinene, α-pinene, and β-caryophyllene. Additionally, leaves treated with larval saliva revealed the presence of exo-isocitral (0.61%), and β-pinene (0.14%), though in minimal amounts. Despite these complex responses, our analysis suggests that the compounds introduced or increased in concentration by larval saliva do not significantly boost the attraction of Ooencyrtus spp. 4. This finding implies that while the VOCs response to damage and saliva application is multifaceted, serving multiple defensive functions, the quantities of these saliva-induced compounds could be insufficient to substantially influence the behavior of Ooencyrtus spp. towards the damaged leaves. This research furthers our understanding of the indirect defense strategies of plants, particularly highlighting the vital roles of VOCs in A. contorta. Moreover, our findings suggest new avenues for exploring the ecological and evolutionary roles of chemical signals, shedding light on the complex interactions facilitated by these chemical cues in plant defense mechanisms.

Behavioral variation within a population is generally maintained by frequency dependent selection allowing various personalities to coexist. Bolder individuals usually engage in more risky behaviors that can gain fitness benefits such as growth under certain conditions. Therefore, it has been suggested that there should be a link between personality and dietary niches, but the results so far are inconsistent. In addition, the equilibrium of the distribution of behavioral traits and the trophic niche of native populations may shift following the introduction of an invasive species. Here, using the invasive brook trout (Salvelinus fontinalis) and native brown trout (Salmo trutta) as model species in two different natural streams in Sweden, we aimed to test whether 1) the trophic niche of native brown trout living in allopatry and brown trout living in sympatry with brook trout differ and 2) bolder brown trout individuals utilize a different foraging niche. Our results suggest that there is a dietary niche convergence between brown trout and brook trout, which likely is a result of brook trout invasion, but that the trophic niche of native brown trout varies across streams, possibly due to difference invasion impact (varying ratio of brook trout to brown trout). We also found a strong positive correlation between trophic position and personality of brown trout irrespective of the presence of brook trout.

not-yet-known not-yet-known not-yet-known unknown This article presents an algebraic method for designing an initial bed profile to ensure minimal sediment deposition in open channels. We address the hyperbolic system of partial differential equations, known as the Saint-Venant-Exner system, which describes the behavior of water flow and sediment transport. By applying a priori estimation techniques and reformulating the problem as an optimal control problem, we construct a minimizing control law, via the adjoint method. This control law ensures the stability of the system and minimizes sediment deposition. In addition, a finite volume scheme is implemented to numerically solve both the direct system (SVE) and its adjoint system. Numerical simulations are provided for illustration.

This paper presents the synthesis and electrochemical evaluation of nickel sulfide (NiS 2) nanosheet encapsulated polyaniline (PANI) nanofiber nanocomposites. These nanocomposites, synthesized via chemical reflux at 70℃ in varying NiS 2 to PANI mass ratios (1:1, 1:2, 1:3), are designated as NiP1, NiP2, and NiP3. X-ray diffraction (XRD) data reveals the greater crystallite size of NiP2 which further leads to higher surface area. Scanning electron microscopy (SEM) analysis shows that NiP2 is more porous due to well assembled morphology of NiS 2 nanosheets over PANI nanofibers. Among the composites, the NiP2 variant demonstrates superior electrochemical performance, achieving a specific capacitance of 217.88 F g -1 at a current density of 1 A g -1 in a 2M KOH electrolyte. Further enhancing the energy density of supercapacitors for advanced applications, the structure-modulated NiP2 (positive potential electrode) is integrated with functionalized carbon nanotubes (f-CNT) as the negative potential material, extending the voltage window from 0.65 to 1.4V. The NiP2//f-CNT supercapacitor displays an energy density of 16 Wh kg -1 at a power density of 1318.53 W kg -1, maintaining 90.7% of its initial capacitance after 5000 charge-discharge cycles. These findings highlight the transformative potential of NiS 2/PANI nanocomposites, leveraging the synergistic effects between NiS 2 and PANI to significantly enhance ion transport and charge storage capabilities, thus providing a viable solution to the shortcomings of conventional supercapacitor electrodes.

The hydrologic community uses geochemical tracers to determine the age distribution of water exiting a catchment, with transit time distributions (TTDs) important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages. Here, we present a ‘sequential precipitation input tagging’ (SPIT) framework to tag all input precipitation events at regular intervals over an extended period (monthly tags over seven years). SPIT is applied at six National Ecological Observatory Network sites to calculate TTDs and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations (δQ-δ18O and δ2H) within a water-tagging enabled version of the Weather Research and Forecast hydrologic model. Throughout seven simulation years, the fraction of simulated discharge derived from tagged events increased each year, with the final year’s tagged stream water fraction (TSWF) ranging 21% to 100%. When the TSWF was ≥75%, simulated MTTs range 190 days to 850 days and Fyw 1% to 24%, with a root mean squared error (RMSE) of 456 days and 14.5%. The RMSE for δ18O is 1.08‰ and δ2H 6.58‰. Low TSWF values early in the simulation period highlights the need to apply SPIT over many years to fully understand the TTD. At daily timescales, model MTT and Fyw exhibit a power-law relationship with precipitation, discharge, and groundwater. The successful implementation of SPIT within a tracer-enabled version of an operational hydrologic model allows for a reproducible approach to calculate water transit times and hydrologic tracers.

A document by Matteo Broccoli. Click on the document to view its contents.

Title: From Resistance to Relief: IV Levothyroxine in Refractory Hypothyroidism ManagementMohammad Amro1Elias Edward Lahham2Ahmed Jalal Sawafta1Motaz Saifi1Nooreddin Saifi1Fadi Atrash2Salem Billan3Affiliations1: Faculty of Medicine, An Najah National University, Nablus, Palestine.2: Department of Radiation Oncology, Augusta Victoria Hospital, East Jerusalem, Palestine territories.3: Head and Neck Unit, Joseph Fishman Oncology Center, Rambam Health Care Campus*Corresponding Author:Elias Edward Lahham, Augusta Victoria Hospital, East Jerusalem, Palestine territories, eliaslahham2011@hotmail.com, ORCID:0000-0002-6514-5206Funding sources: No specific grant from funding agencies was received for this work.Acknowledgment: We express our deep gratitude to the medical ward staff for their invaluable support in completing this report.Conflict of Interest: The authors state that they have no conflict of interest to be mentioned.Ethics approval: Our institution does not require ethical approval for reporting individual cases or case series.Informed consent: Written informed consent was obtained from the patient herself for her anonymized information to be published in this article.Title: From Resistance to Relief: IV Levothyroxine in Refractory Hypothyroidism Management

Linear disturbances within boreal Canada (e.g., seismic lines) have the potential to significantly alter carbon cycling in Canada’s northern peatlands, creating the potential to switch these significant carbon stocks from long term carbon sinks to carbon sources. While efforts have been made to quantify the impacts of linear disturbance on ecosystem, vegetation, soil composition and GHG emissions, little is currently known about the specific interactions between the disturbance to peat hydrophysical structure and composition and the resulting alterations to CO 2 and CH 4 dynamics. To this end, 16 poor fen peat cores representing the top 10 cm of the peat profile were collected on and adjacent to a seismic line reflecting four degrees of disturbance complete mulch covering, partial mulch covering, mechanical roughing only, and undisturbed. In controlled laboratory conditions cores were then subjected to two subsequent static water table conditions (3 and 8 cm below core surface) for a period of ~30 days each with GHG flux measurements occurring 2-3 days. Cores were then subdivided into 5 cm segments and underwent detailed hydro physical (i.e., bulk density, porosity, water retention) and compositional (i.e., C:N, vegetational assemblage) analysis. Results show that both peat composition and hydrophysical structure were strong predictors of greenhouse gas emissions. Higher CO 2 emissions were related to both peat with high bulk density, low total and effective porosity and low C:N ratios, which occurred at depth in the undisturbed cores and at the surface where mechanical mulching and mixing occurred. Increased CH 4 emissions occurred in disturbed cores characterized by a reduction in macropores and effective porosity near the surface; these emissions were episodic in nature and occurred where trapped gas was released during pore desaturation when water tables were lowered. Additional work should therefore be conducted at field scale to further assess the interrelationships between direct changes to hydrophysical structure and these other impacts, to better determine the long-term changes to carbon cycling in systems disturbed by seismic line creation.

This study explores the impact of rapid population growth and urbanization on land use change and carbon stocks in Hunan Province from 2000 to 2020, with predictions for 2030 under three scenarios: natural evolution (NE), farmland protection (FP), and ecological protection (EP). Using the Future Land Use Simulation Model (FLUS) and the In-VEST Model, the analysis reveals that from 2000 to 2020, land use in Hunan was dominated by forests and farmland, with significant changes, including a notable decline in farmland and a 32.03% increase in built-up land. By 2030, under the NE scenario, farmland is expected to continue decreasing, forest areas will expand, and built-up land will diminish. Under the EP scenario, both forest and water areas will increase, while built-up land will rise slightly. The FP scenario predicts a substantial increase in farmland, highlighting its significant impact. The carbon stock analysis shows a decrease of 14.3×10 6 Mg from 2000 to 2020. By 2030, carbon stock is projected to increase by 10.1×10 6 Mg under the NE scenario and by 2.54×10 6 Mg under the EP scenario, due to limited forest and grassland conversion, preserving vegetation carbon pools. Conversely, under the FP scenario, carbon stock is expected to decrease further by 1.2×10 6 Mg, driven by farmland expansion. This study sheds light on the complex dynamics between land use change and carbon storage, offering valuable insights for sustainable development policy formulation. By integrating ecological and socio-economic factors, the findings provide a critical foundation for policymaking aimed at achieving carbon neutrality while supporting sustainable growth in Hunan Province. The results underscore the need to balance socio-economic development with environmental sustainability, particularly in the context of rapid urbanization and its impact on land use and carbon stocks.

Note: One-dimensional structures such as nanotubes, nanowires, and quantum wires are noteworthy structures in the fields of nanospintronics, nanophotonics, nanoelectronics, etc. The reason for this attention is their large length-to-diameter ratio and the difference in their electrical, optical, chemical, and magnetic properties, which has led to their use as building blocks in nanoscale electronic and  optoelectronic devices. Different methods for obtaining one-dimensional nanoarrays have been mentioned, among them are methods based on lithography (electron beam lithography, optical lithography, electric lithography, ion beam lithography, lithography by  scanning microscopes), vapor phase deposition method. (Physical vapor deposition and chemical vapor deposition) and methods based on the use of templates. The electron in the atom, in addition to rotating around it under the influence of the gravitational force of the nucleus, also has a rotational movement around itself. This type of rotation in the structure of nanowires is called electron nanospin. 

The SCO phenomenon exhibits significant aggregation-dependent behavior between isolated molecule and cooperative supramolecular interaction. It is crucial for complete control of the variables that affect the spin switching based on aggregology for precision design of SCO materials, including the contribution of the nature of the ligands, the non-coordinating anions, the solvent molecules and the crystal packing. Herein, we report the aggregate-responsive spin crossover switching in a spin-labile iron(II) complex Fe(HL) 2(NCS) 2·2DMF ( 1), where HL adopt an intermediate pyridyl benzimidazole ligand, namely methyl 2-(2-Pyridinyl)-1H-benzimidazole-6-carboxylate. The SCO behavior of 1 can be on-off between solution and crystallization. By introducing poor solvents to achieve aggregation control, it was found that compound 1 exhibits aggregation induced spin crossover switching. Meanwhile, because of the spin-labile iron(II) nature in 1, a reversible proton-induced magnetic response in sold and solution was fully investigated by Faraday method and Evans’ method, which indicated the completely reversible switching from low-spin to high-spin in accompany with the optical response.

not-yet-known not-yet-known not-yet-known unknown Studies on Ganoderma applanatum yield twelve terpenoids including a rare scaffold of 6/6/5/6 rearranged ganoderic acid and an unprecedented aromatic diterpenoid. The absolute configurations for compounds 1 and 4 were ascertained using X-ray and DTF calculations, respectively. Among all compounds, ganorcleiol ( 4) and applanoic acid C ( 6) demonstrated significant neuroprotective activity in inhibiting glutamate-induced HT22 cell death. Biochemical assays suggest that applanoic acid C may exert protective effects by activating the Nrf2/HO-1 pathway, whereas ganorcleiol does not appear to be associated with this pathway. Surface Plasmon Resonance (SPR) analysis were used to predict its potential target proteins. A set of 49 targets was identified from over 20,000 proteins in HT22 cell. These findings indicated that ganorcleiol may mitigate neuronal damage by reducing glutamate absorption and transport through the regulation of the SLC family of transporters. Additionally, it has been involved in the modulation of oxidative stress, apoptosis, via the AKT pathway. In the following Western blot (WB) experiments, it was further verified that ganorcleiol can exert neuroprotective effects through the PI3K-AKT-mTOR pathway. These outcomes offer valuable insights for the study of action of trace bioactive components from edible materials and contribute to the broader understanding of neuroprotective compounds.

Authors : Hanfu Zhang 1 2

Early in our scientific careers, we learn about the many advantages of working abroad to upskill and expand our research horizons. Born and raised in Montevideo, Uruguay, I always had a clear passion for science and foreign cultures, nurtured by my family. I had been preparing for a career in science and living abroad all my life, so when the time came, I felt ready. Looking back a decade, I realize how little I knew about the challenges ahead and how much I learned ‘on the go’. The significant personal and professional transition of continuing your career abroad is exciting but also challenging, especially for those coming from countries with limited budgets and more flexible research environments. The exposure to state-of-the-art technologies, new ways of thinking, and working within unfamiliar regulatory frameworks without your usual support network, at times can feel overwhelming. Like navigating uncharted waters, succeeding abroad requires not only planning but resilience and adaptability. Embracing uncertainty and learning to slow down when needed can be invaluable. By sharing my experiences, I hope to offer useful insights for those preparing to emigrate or establish themselves elsewhere.

Title PageTITLE: Ovarian Lipoma: A rare case report and literature review .

A document by Kamal Acharya. Click on the document to view its contents.

Rapid growth in the size and complexity of language models has led to increased concerns about the presence of harmful biases and inaccuracies embedded in model outputs. Addressing these concerns autonomously, without human supervision, has become an essential challenge for improving model safety and ethical alignment. This paper introduces a novel unlearning framework that systematically reduces negative preferences, defined as undesirable behaviors learned during training, in a transformer-based model. Through the use of gradient-based adjustments, selective retraining, and reinforcement learning techniques, the model undergoes a targeted reduction of biased associations while preserving overall performance. Experimental results demonstrate significant reductions in harmful outputs, including gender and racial biases, without compromising fluency, coherence, or generalization across tasks. The methodology further shows promise for scalable application, enabling the continual improvement of models trained on diverse datasets without the need for human feedback. These findings demonstrate the potential of automated unlearning approaches in refining language models to meet ethical and operational standards.

This article develops duality principles applicable to originally non-convex primal variational formulations. More specifically, as a first application, we establish a convex dual variational formulation for a non-linear model in elasticity. The results are obtained through basic tools of functional analysis, calculus of variations, duality and optimization theory in infinite dimensional spaces. We emphasize such a convex dual formulation obtained may be applied to a large class of similar models in the calculus of variations. In a subsequent section, we present a global existence result for such a concerning model in elasticity. Finally, in the last sections, we develop duality principles and relaxation procedures for a related model in phase transition.

An Oropharyngeal Accessory Tragus in a Young Patient with Conductive Hearing LossTiffany Husman, BS1, Tania Benjamin, MD2, Evan J. Patel, MD2, Naoki Akanuma, MD3, Anastasiya Pigal MD3, Yew Song Cheng, MD2Affiliations:University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USAUniversity of California, San Francisco (UCSF) Department of Otolaryngology – Head and Neck Surgery, San Francisco, CA, USAUniversity of California, San Francisco (UCSF) Department of Pathology, San Francisco, CA, USACorresponding Author/Address:Yew Song Cheng, MDAssistant ProfessorDivision of Otology, Neurotology, and Skull Base SurgeryDepartment of Otolaryngology – Head and Neck SurgeryUniversity of California, San Francisco2380 Sutter St. 3rd FloorSan Francisco, CA 94115Phone: 415-885-7494Fax: 415-885-7546Email: yewsong.cheng@ucsf.eduConsent: Written informed consent was obtained from the patient to publish this report in accordance with the journal’s patient consent policy.

The integration of human emotions into human-computer interaction has seen significant advancements, yet the subtlety of micro-expressions remains a relatively unexplored area. This paper presents a comprehensive study on the recognition and analysis of micro-expressions using advanced computer vision and deep learning techniques. Utilizing the CASME II dataset, which consists of 247 samples of micro-expressions captured at 200 fps, we preprocess, analyze, and extract features from facial expressions to train a fine-tuned ResNet model. Our methodology includes data augmentation, face cropping, and normalization, followed by the application of TV-L1 Optical Flow Estimation to capture subtle facial changes over time. The results demonstrate the model's robust performance in real-time emotion recognition, with potential applications in gaming, advertising, healthcare, and more. By leveraging a real-time, contactless emotion recognition system, this research aims to enhance the precision and applicability of affective computing technologies.