bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of 3D real-IR delayed post gadolinium MRI parameterisation on the diagnostic performance and optimal descriptor selection in Ménière’s disease
Authors: Connor Steve , Pai Irumee , Touska Philip , Price David , Ourselin Sebastien , Hajnal Joseph V.
Published: December 2024

Objectives

To compare the performance and optimal combination of MRI descriptors used for the diagnosis of Ménière’s disease (MD) between a real-IR sequence with “zero-point” endolymph (ZPE), and an optimised real-IR sequence with negative signal endolymph (NSE).

Materials and methods

This retrospective single-centre cross-sectional study evaluated delayed post-gadolinium ZPE and NSE real-IR MRI in consecutive patients with Ménièriform symptoms (8/2020–10/2023). Two observers assessed 14 MRI descriptors. “Definite MD” (2015 criteria) and “all MD” ears (wider clinical criteria) were compared to controls. Cohen’s kappa and risk ratios (RR) were evaluated for each descriptor. Forward stepwise logistic regression established which combination of descriptors best predicted MD.

Results

The study included 132 patients (57 men; mean age 57.7 ± 13.6), with 87 “all MD” (56 “definite”) and 39 control ears. The NSE sequence demonstrated increased perilymph SNR, and improved both diagnostic performance and reliability for 9/14 descriptors. However, ZPE demonstrated superior diagnostic performance for the best descriptor of “saccule absent, large as or confluent with the utricle” (RR 6.571, ZPE; 6.300, NSE) and that of “asymmetric perilymphatic enhancement” (RR 3.628, ZPE; 2.903, NSE). Both sequences combined these two descriptors in the optimal predictive model for “definite MD”, with “grade 2 cochlear hydrops” also significant for NSE. ZPE and NSE descriptor combinations both correctly classified 95.8% of ears. The ZPE descriptor combination performed better for “all MD” (ZPE, AUC-ROC 0.914; NSE, AUC-ROC 0.893).

Conclusion

Parameter optimisation with NSE Real-IR influenced the optimal selection of MRI descriptors but did not improve their diagnostic performance in definite MD.

Key Points

Question

Delayed post-gadolinium ZPE (FLAIR) and NSE (REAL-IR) sequences are widely applied for diagnosing MD, but their relative benefits remain unclear.

Findings

Optimised NSE sequences improve perilymphatic depiction and influence the selection of the optimal MRI descriptors, but do not improve diagnostic performance.

Clinical relevance

Radiologists may continue to apply either ZPE or NSE sequences since they offer similar diagnostic abilities, but the choice of the sequence will influence which MRI features should be evaluated to support the diagnosis of MD.
Characterization of a family IV esterase from extremely halophilic archaeon Haloarcula japonica
Authors: Kato Hiromichi , Ambai Shota , Ikeda Fumiya , Abe Koji , Nakamura Satoshi , Yatsunami Rie
Published: December 2024

The novel esterase gene lipP1, which encodes HjEstP1, was discovered in the genome of the extremely halophilic archaeon Haloarcula japonica. A homology search and sequence alignment revealed that HjEstP1 is a member of family IV esterases with conserved GXSXG and HGGG motifs. lipP1 was expressed in its parental strain, and recombinant HjEstP1 was purified and characterized. Optimal pH and temperature of HjEstP1 were 6.0 and > 60 °C, respectively. HjEstP1 showed higher activity with increasing NaCl concentration, and optimal NaCl concentration was > 4.5 M. Furthermore, HjEstP1 preferentially hydrolyzed pNP and glycerol esters with short chain fatty acids. To our knowledge, this is the first report of an esterase from an extremely halophilic archaeon obtained via homologous expression.
The use of cloud based machine learning to predict outcome in intracerebral haemorrhage without explicit programming expertise
Authors: Hegde Ajay , Vijaysenan Deepu , Mandava Pitchaiah , Menon Girish
Published: December 2024

Machine Learning (ML) techniques require novel computer programming skills along with clinical domain knowledge to produce a useful model. We demonstrate the use of a cloud-based ML tool that does not require any programming expertise to develop, validate and deploy a prognostic model for Intracerebral Haemorrhage (ICH). The data of patients admitted with Spontaneous Intracerebral haemorrhage from January 2015 to December 2019 was accessed from our prospectively maintained hospital stroke registry. 80% of the dataset was used for training, 10% for validation, and 10% for testing. Seventeen input variables were used to predict the dichotomized outcomes (Good outcome mRS 0–3/ Bad outcome mRS 4–6), using machine learning (ML) and logistic regression (LR) models. The two different approaches were evaluated using Area Under the Curve (AUC) for Receiver Operating Characteristic (ROC), Precision recall and accuracy. Our data set comprised of a cohort of 1000 patients. The data was split 8:1 for training & testing respectively. The AUC ROC of the ML model was 0.86 with an accuracy of 75.7%. With LR AUC ROC was 0.74 with an accuracy of 73.8%. Feature importance chart showed that Glasgow coma score (GCS) at presentation had the highest relative importance, followed by hematoma volume and age in both approaches. Machine learning models perform better when compared to logistic regression. Models can be developed by clinicians possessing domain expertise and no programming experience using cloud based tools. The models so developed lend themselves to be incorporated into clinical workflow.
Toward harmonization of aging and technology research: German adaptation of the mobile device proficiency questionnaire (MDPQ) for older adults
Authors: Schlomann Anna , Wahl Hans-Werner , Schmidt Laura I. , Memmer Nicole , Rietz Christian , Charness Neil , Boot Walter R.
Published: December 2024

The Mobile Device Proficiency Questionnaire (MDPQ) is a well-established, reliable, and valid instrument to measure basic and advanced mobile device skills among older adults. We offer a German adaptation of the MDPQ and report reliability and validity findings. A controlled translation procedure was applied. The translated scale was tested in two analytical samples with an age range of 50–95 years in 2020 (n = 548) and 2022 (n = 276). To assess reliabilities, internal consistencies and test–retest reliabilities are reported. To assess validity, we analyze the scale in the context of gender, age, and educational differences and its associations with measures of technology use and attitudes towards technology (convergent and divergent validity). The German adaptation of the MDPQ was found to be reliable and valid as the original version. The scale demonstrated an excellent internal consistency in both studies with α = 0.95 (study 2: α = 0.92) and ω = 0.95 (study 2: ω = 0.93). Subscale internal consistencies were all ≥ 0.65. Test–retest reliabilities with measurement waves 2 years apart showed excellent values (MDPQ full scale: rtt = 0.84, p < 0.001). We also found the expected factorial structure of the scale, positive associations with education, mobile device use and technology attitudes, and negative associations with age. Women scored lower than men. The German adaptation of the MDPQ can serve as a useful tool to estimate mobile device skills in older adults in German speaking countries in a reliable and valid way, for example in survey research, research projects, and practice contexts. Translating and implementing the MDPQ in other European countries will help to further strengthen internationally harmonized assessments in technology and aging research.
On the obstruction to the Hasse principle for multinorm equations
Authors: Macedo André
Published: December 2024

We investigate local-global principles for multinorm equations over a global field. To this extent, we generalize work of Drakokhrust and Platonov to provide explicit and computable formulae for the obstructions to the Hasse principle and weak approximation for multinorm equations. We illustrate the scope of this technique by extending results of Bayer-Fluckiger–Lee–Parimala [1], Demarche–Wei [5] and Pollio [19].
Covid-19 mortality: the Proportionality Hypothesis
Authors: Cairns Andrew J. G. , Blake David , Kessler Amy , Kessler Marsha , Mathur Rohit
Published: December 2024

We introduce and provide evidence to support the Proportionality Hypothesis which states that Covid-19 infection fatality rates are approximately proportional to all-cause death rates by age and subgroup (e.g., socio-economic class). We also show that vaccination played a very significant role in preventing people infected with Covid-19 from needing to be hospitalised, since it reduced the average severity of an infection. Death rates involving Covid-19 were very significantly lower for people in the fully vaccinated group compared to the unvaccinated group. During the pandemic, death rates from other causes were in some cases reduced (e.g., flu and pneumonia), in some cases unchanged (e.g., lung cancer) and in some cases elevated (e.g., heart disease). We discuss the implications of our findings both for potential adjustments to extrapolative mortality models which allow for future pandemics in a way that is consistent with the Proportionality Hypothesis and for insurance companies in terms of both modelling extreme scenarios and the design of mortality catastrophe bonds.
From Theory to Practice: Leveraging Digital Twin Technologies and Supply Chain Disruption Mitigation Strategies for Enhanced Supply Chain Resilience with Strategic Fit in Focus
Authors: Hossain Md. Ismail , Talapatra Subrata , Saha Palash , Belal H. M.
Published: December 2024

Supply chain resilience (SCR) has been a topic of enormous interest among researchers for almost two decades. Still, there’s been limited focus on the impact of digital twin (DT) technologies and supply chain disruption mitigation (SCDM) strategies on SCR. This study addresses this gap by examining how DT and SCDM strategies enhance SCR and whether strategic fit (SF) moderates these relationships. Using the dynamic capability view (DCV) as the theoretical foundation, we developed our conceptual framework and research hypotheses. Data were collected from 200 Bangladeshi manufacturing organizations through a survey-based approach, and the partial least square (PLS) technique was utilized to assess the framework and research hypotheses. The findings reveal that both DT technologies and SCDM strategies significantly boost SCR. Besides, while SF plays a critical moderating role in the relationship between DT and SCR, it does not moderate the association between SCDM strategies and SCR. This study contributes to the theoretical understanding of SCR by integrating DT and SCDM strategies within the DCV framework, offering insights into their roles in managing supply chain disruptions. Additionally, it provides practical guidance for managers on effectively leveraging DT and SCDM strategies to build resilient supply chains while emphasizing the importance of strategic alignment in optimizing digital interventions.
Mediterranean diet and osteoarthritis: an update
Authors: Veronese Nicola , Ragusa Francesco Saverio , Dominguez Ligia J. , Cusumano Claudia , Barbagallo Mario
Published: December 2024

The Mediterranean diet has gained significant attention for its potential health benefits on diverse pathological conditions including osteoarthritis (OA), a prevalent degenerative joint disease characterized by cartilage breakdown and inflammation. Numerous observational studies have suggested that adherence to the Mediterranean diet, may have protective effects against OA. The abundance of antioxidants and anti-inflammatory compounds and omega-3 fatty acids, among the Mediterranean diet components is believed to contribute to its beneficial effects on OA. Research investigating the association between the Mediterranean diet and OA has shown promising results. Several observational studies have reported that adherence to the Mediterranean diet is associated with a reduced risk of developing OA and with lower severity of OA symptoms. Additionally, intervention studies have demonstrated improvements in pain, function, and quality of life among OA patients following a Mediterranean diet intervention. Furthermore, emerging evidence suggests potential mechanisms underlying the protective effects of the Mediterranean diet against OA, including its ability to reduce inflammation, oxidative stress, and cartilage degradation. However, further well-designed randomized controlled trials and mechanistic studies are needed to elucidate the precise mechanisms and establish causality. In conclusion, the Mediterranean diet appears to be a promising dietary approach for the prevention and management of OA. Its rich array of nutrients and bioactive compounds may exert protective effects against OA development and progression, although more research is warranted to confirm these findings and elucidate underlying mechanisms.

Graphical abstract
Comparative study on muscle-tendon stiffness and balance impairment in postmenopausal women: a focus on osteosarcopenia and osteoporosis
Authors: Yekta Elham Bagheri , Torkaman Giti , Aghaghazvini Leila
Published: December 2024

Background and aims

This study set out to examine the stiffness of the gastrocnemius medialis (GM) and Achilles tendon across postmenopausal women with osteosarcopenia (OS), osteoporosis (OP), and normal bone mineral density. Furthermore, we explored the relationship between muscle-tendon stiffness and postural sway during a curve-tracking task in both sagittal (AP) and frontal (ML) planes.

Methods

Seventy-three women volunteered to participate in this study. The participants were classified into OS (T-score ≤ − 2.5 and muscle mass below 5.5 kg/m2), OP (T-score ≤ − 2.5), and healthy (T-score >-1) groups. The shear wave elastography was used to determine GM and Achilles tendon stiffness during rest and activation. The postural sway was recorded using a force plate during the performance-based curve tracking (CT) task.

Results

The stiffness of the GM and Achilles tendon was found to be significantly lower in the OS group compared to the OP and healthy groups (P < 0.05). In the CT task, the OS group exhibited a significant decrease in the mean absolute (P = 0.011) and RMS error (P = 0.022) in the ML direction compared to the OP group. Additionally, a positive correlation was found between the ML mean absolute error and both GM and Achilles’s stiffness during rest and activation (P < 0.05).

Discussion and conclusion

The OS group exhibited the lowest muscle-tendon stiffness. The GM and Achilles stiffness was positively correlated with poor performance-based balance, particularly in the ML direction. This may increase the risk of falls and subsequent hip fractures during simple daily weight- shifting activities in women with osteosarcopenia.
Anti-Swelling Polyelectrolyte Hydrogel with Submillimeter Lateral Confinement for Osmotic Energy Conversion
Authors: Liu Yongxu , Song Jiangnan , Liu Zhen , Chen Jialin , Wang Dejuan , Zhi Hui , Tang Jiebin , Zhang Yafang , Li Ningbo , Zhou Weijia , An Meng , Liu Hong , Xue Guobin
Published: December 2024

Harvesting the immense and renewable osmotic energy with reverse electrodialysis (RED) technology shows great promise in dealing with the ever-growing energy crisis. One key challenge is to improve the output power density with improved trade-off between membrane permeability and selectivity. Herein, polyelectrolyte hydrogels (channel width, 2.2 nm) with inherent high ion conductivity have been demonstrated to enable excellent selective ion transfer when confined in cylindrical anodized aluminum pore with lateral size even up to the submillimeter scale (radius, 0.1 mm). The membrane permeability of the anti-swelling hydrogel can also be further increased with cellulose nanofibers. With real seawater and river water, the output power density of a three-chamber cell on behalf of repeat unit of RED system can reach up to 8.99 W m−2 (per unit total membrane area), much better than state-of-the-art membranes. This work provides a new strategy for the preparation of polyelectrolyte hydrogel-based ion-selective membranes, owning broad application prospects in the fields of osmotic energy collection, electrodialysis, flow battery and so on.
Angle of Attack Effects on the Induced Structural Loads of a Weapons Bay
Authors: Bacci David , Saddington Alistair J.
Published: December 2024

Aero-acoustic analysis was conducted on a weapons bay numerical model with doors, incorporating radar cross section reduction features. The effect of the angle of attack on the aero-acoustic response of the cavity was analysed at Mach numbers of 0.85 and 1.20. It was found that incidence influenced both mean-flow features and acoustic response. Further, linear and angular accelerations induced by the flow on the bay doors revealed potential adverse fluid–structure coupling when the results were compared with modal analysis. Again, the angle of attack did influence the aeroacoustic effects on the cavity door structure.
Proteomics analysis in rats reveals convergent mechanisms between major depressive disorder and dietary zinc deficiency
Authors: Gąsior Łukasz , Pochwat Bartłomiej , Zaręba-Kozioł Monika , Włodarczyk Jakub , Grabrucker Andreas Martin , Szewczyk Bernadeta
Published: December 2024

Background

Preclinical and clinical studies have shown that dietary zinc deficiency can lead to symptoms similar to those observed in major depressive disorder (MDD). However, the underlying molecular mechanisms remain unclear. To investigate these mechanisms, we examined proteomic changes in the prefrontal cortex (PFC) and hippocampus (HP) of rats, two critical brain regions implicated in the pathophysiology of depression.

Methods

Rats were fed diets either adequate in zinc (ZnA, 50 mg Zn/kg) or deficient in zinc (ZnD, <3 mg/kg) for four weeks. High-throughput proteomic analysis was used to detect changes in protein expression, supplemented by enzyme activity assay for mitochondrial complexes I and IV, examining their functional impacts.

Results

ZnD led to significant alterations in protein expression related to zinc transport and mitochondrial function. Proteomic analysis revealed changes in zinc transporter family members such as Slc30a1 (6.64 log2FC), Slc30a3 (-2.32 log2FC), Slc30a4 (2.87 log2FC), Slc30a5 (5.90 log2FC), Slc30a6 (1.50 log2FC), and Slc30a7 (2.17 log2FC) in the PFC, and Slc30a3 (-1.02 log2FC), Slc30a5 (-1.04 log2FC), and Slc30a7 (1.08 log2FC) in the HP of rats subjected to ZnD. Furthermore, ZnD significantly affected essential mitochondrial activity proteins, including Atp5pb (3.25 log2FC), Cox2 (2.28 log2FC), Atp5me (2.04 log2FC), Cyc1 (2.30 log2FC), Cox4i1 (1.23 log2FC), Cox7c (1.63 log2FC), and Cisd1 (1.55 log2FC), with a pronounced decrease in complex I activity in the PFC.

Conclusions

Our study demonstrates that ZnD leads to significant proteomic changes in the PFC and HP of rats. Specifically, ZnD alters the expression of zinc transporter proteins and proteins critical for mitochondrial function. The significant decrease in complex I activity in the PFC further underscores the impact of ZnD on mitochondrial function. These results highlight the molecular mechanisms by which ZnD can influence brain function and contribute to symptoms similar to those observed in depression.
Etidronate for arterial calcification due to deficiency of CD73 (ACDC): a step in the right direction
Authors: Qureshi Ali Akram , Munir Luqman , Alvi Zainab
Published: December 2024

Arterial calcification due to deficiency of CD73 (ACDC) is a rare genetic calcification disorder. Recently, a pilot study was conducted which utilized etidronate, a bisphosphonate, to treat ACDC. The results of this study indicated a significant effect on slowing arterial calcification and disease progression in a cohort of affected individuals, thereby favoring the use of etidronate as a potential treatment option for this disease. This would mark etidronate to possibly become the first standard treatment for this rare, vascular disorder. Although further research is needed to prove its efficacy, this landmark study symbolizes a step in the right direction and underscores the need for continued investigation.
Integration of large language models in Nigeria's healthcare: doctors early perspectives, operational barriers, and privacy concerns
Authors: Nri-Ezedi Chisom Adaobi , Ezidiegwu Ugochukwu Stanley , Ohuche Ijeoma Onyinyechukwu , Musa Sani , Chikani Ugo Nnebba , Okonkwo Ifeanyi Ogochukwu , Anarado Chikodi Felicitas , Nwaneli Ezinne Ifeyinwa , Ulasi Nnaemeka Izuchukwu , Nwachukwu Amaechi Chinedu , Ulasi Arinze Ejike , Ulasi Thomas Obiajulu
Published: December 2024

The advent of large language models (LLMs) like ChatGPT has the potential to revolutionize healthcare, offering opportunities for improved patient engagement, clinical decision support, and administrative efficiency. This pioneering study aimed to capture the early perspectives of Nigerian medical professionals on LLMs, particularly ChatGPT, immediately following its 2022 introduction by OpenAI. It explores initial responses, anticipated barriers, and data privacy concerns during this transformative period. A nationwide cross-sectional survey was conducted between February and March 2023, involving 406 medical doctors across Nigeria's six geopolitical zones. Among those aware of ChatGPT, 66.9% were willing to use it. Most (41.4%) were "not very confident" using LLMs for patient care. The majority (54.0%) rated LLMs "somewhat important" for healthcare integration, and 76.6% believed they could improve outcomes. No explored factors significantly influenced willingness to use LLMs. Primary perceived benefits included improved patient information access (65.2%), clinical decision-making efficiency (57.7%), and patient-provider communication (46.4%). Major concerns were misinterpretation (80.1%), technology dependence (66.3%), liability (65.5%), lack of human interaction (60.7%), and privacy/security (51.3%). These findings highlight both optimism and apprehension towards LLMs, recognizing potential benefits and concerns about misinterpretation, overreliance, legal implications, and privacy, thus underscoring the need for educational programs, ethical frameworks, and robust data protection.
Elements of Purity
Authors: Arana Andrew
Published: December 2024

A proof of a theorem can be said to be pure if it draws only on what is 'close' or 'intrinsic' to that theorem. In this Element we will investigate the apparent preference for pure proofs that has persisted in mathematics since antiquity, alongside a competing preference for impurity. In Section 1, we present two examples of purity, from geometry and number theory. In Section 2, we give a brief history of purity in mathematics. In Section 3, we discuss several different types of purity, based on different measures of distance between theorem and proof. In Section 4 we discuss reasons for preferring pure proofs, for the varieties of purity constraints presented in Section 3. In Section 5 we conclude by reflecting briefly on purity as a preference for the local and how issues of translation intersect with the considerations we have raised throughout this work.
Neurosurgical Handovers and Standards for Emergency Care
Authors: Lammy Simon , Brown Jennifer
Published: December 2024

One of the biggest challenges as a neurosurgical trainee is to master the handover. This requires developing an organisational efficiency to concisely relay relevant patient information to a suitably qualified person to execute a given task. A trainee can work extremely hard during an on call, making suitable decisions, implementing previous plans to perfection and covering slack in a team. But if the presentation of this work is unclear then it undoes a lot of that hard work and generates an impression of a trainee being disorganised. Success in a handover requires an understanding of whom you are talking to, what you are saying, how you are saying it and if the way you are communicating gains and maintains interest. Above all a handover should ensure the smooth continuity of care of a patient.
Norm reinforcement, not conformity or environmental factors, is predicted to sustain cultural variation
Authors: Manning Mason L. , Thompson Bill , Morgan Thomas J. H.
Published: December 2024

The maintenance of cross-cultural variation and arbitrary traditions in human populations is a key question in cultural evolution. Conformist transmission, the tendency to follow the majority, was previously considered central to this phenomenon. However, recent theory indicates that cognitive biases can greatly reduce its ability to maintain traditions. Therefore, we expanded prior models to investigate two other ways that cultural variation can be sustained: payoff-biased transmission and norm reinforcement. Our findings predict that both payoff-biased transmission and reinforcement can enhance conformist transmission's ability to maintain traditions. However, payoff-biased transmission can only sustain cultural variation if it is functionally related to environmental factors. In contrast, norm reinforcement readily generates and maintains arbitrary cultural variation. Furthermore, reinforcement results in path-dependent cultural dynamics, meaning that historical traditions influence current practices, even though group behaviours have changed. We conclude that environmental variation probably plays a role in functional cultural traditions, but arbitrary cultural variation is more plausibly due to the reinforcement of norm compliance.
Final two MH370 communications suggest controlled eastward descent
Authors: Lyne Vincent
Published: December 2024

Official interpretations of Doppler shifts from the final satellite communications of missing Malaysian Airlines MH370 were based on a motion-decoupled ‘Up-Down model’. That model predicted an uncontrolled high-speed gravitationally accelerated dive following fuel starvation. Here, I challenge that model using a more-realistic motion-coupled ‘Declination model’. Aerial, satellite and underwater searches failed to find the predicted official violent crash-site near the 7th arc. Meticulous re-examination of debris damage by air-crash investigator Larry Vance concluded that the aircraft glide-landed under power with extended wing-flaps. The trailing-edges were then damaged, broke off their mountings, flailing about and retracted along the guides to cause the observed wing-flap damage. Larry's conclusions complement interpretations from the ‘Declination model’ which we demonstrate here with three example flight tracks. Our revised Doppler-shift analyses support the hypothesis of a controlled eastward descent. We conclude that the official theory of fuel starvation and a high-speed dive are fundamentally flawed.
Position and heading estimation for indoor navigation of a micro aerial vehicle using vanishing point
Authors: Anbarasu B.
Published: December 2024

Indoor navigation for micro aerial vehicles (MAVs) is challenging in GPS signal-obstructed indoor corridor environments. Position and heading estimation for a MAV is required to navigate without colliding with obstacles. The connected components algorithm and k-means clustering algorithm have been integrated for line and vanishing point detection in the corridor image frames to estimate the position and heading of the MAV. The position of the vanishing point indicates the position of the MAV (centre, left or right) in the corridor. Furthermore, the Euclidean distance between the image centre and mid-pixel coordinates at the last row of the image and the detected vanishing point pixel coordinates in the successive corridor image frames are used to compute the heading of the MAV. When the MAV deviates from the corridor centre, the position and heading measurement can send a suitable control signal to the MAV and align the MAV at the centre of the corridor. When compared with a grid-based vanishing point detection method heading accuracy of ±1⋅5°, the k-means clustering-based vanishing point detection is suitable for real-time heading measurement for indoor MAVs with an accuracy of ±0⋅5°.
Climate tipping points: Tracing the limits of political discretion
Authors: Ritz Violetta
Published: December 2024

States’ current emission policies are far from being aligned with what is needed to meet the Paris Agreement’s temperature goal. Against this backdrop, an increasing number of lawsuits have been filed around the world. As of March 2024, most courts have exercised restraint in imposing substantive limits on the legislator’s discretion in determining emission levels. Judicial restraint commonly rests on two premises: Climate models yield wide uncertainty ranges and choosing emission reduction levels is a normative decision belonging to the political domain. By engaging best available science on climate tipping points, this article examines the reasoning in favour of political discretion through a due diligence and equity lens. The analysis concludes that all factual requirements are met for states to be under an obligation to align their mitigation policies with a global carbon budget which is expected to limit global warming to 1.5°C at a likelihood as high as state capacities allow for.
Is Ecuador facing a non-international armed conflict against organized crime groups? Reality, inconsistencies and jurisprudential developments
Authors: Cahueñas Muñoz Hugo , Idrovo Romo Juan Felipe
Published: December 2024

On 9 January 2024, the president of the Republic of Ecuador decreed a state of exception in which he recognized the existence of a non-international armed conflict (NIAC) involving twenty-two criminal groups. By July 2024, the president had declared four additional states of exception. The Constitutional Court examined the decrees and ruled against the existence of a NIAC. In this context, the objective of this article is to present, contrast and analyze the positions of the president and the Constitutional Court and highlight the most notable jurisprudential developments. This case study is relevant to exploring some of the challenges of classifying armed conflicts involving organized crime. In respect of the position of the president, inconsistencies were identified between the recognition of the armed conflict and the actions taken to confront it. As to the Court's jurisprudence, some notable developments identified include the incorporation of international humanitarian law treaties into the block of constitutionality and the ruling on challenges of contemporary armed conflicts such as spillovers, coalition formation and the participation of criminal groups in armed conflicts.
Unraveling a Novel Formation Pathway of Hydroxymethanesulfonate (HMS) in the Marine Atmosphere
Authors: Zhu Yucheng , Li Hao , Xing Chengzhi , Dong Xinyi , Liu Cheng , Qin Xiaofei , Wang Guochen , Liu Ziwei , Ding Zhijian , Tian Mengke , Deng Congrui , Huang Kan
Published: December 2024

Hydroxymethanesulfonate (HMS, CH2(OH)SO3−) is an important contributor to organosulfates with the potential to impact the biogeochemical sulfur cycle and global climate. However, its characteristics in the marine atmosphere have rarely been investigated. This study investigated the abundances of HMS over the Yellow and East China Seas based on island and cruise observations, showing weak seasonal variations but significant spatial patterns. Aerosol pH was diagnosed as the limiting factor governing the production rates of HMS via the traditional aqueous processing. However, the disparities between the theoretical formation rates and observed concentrations implied the possibility of a new formation mechanism for HMS. Strong correlations were found between methanesulfonate (MSA) and HMS, with machine learning simulation indicating MSA as the most pivotal contributor. Through the density functional theory calculations, HMS can be generated by gas‐phase organic reactions between the •OOCH2SO3H radical (formed from the isomerization of methylsulfonoxyl radical (CH3SO3•) and oxidation) and NO or CH3OO• radical, leading to the cogeneration of HMS and MSA. The HMS production rate via the gas phase process was 3.7–55 times larger than that of aqueous processing, which extends the understanding of formation mechanisms of atmospheric organosulfur compounds.
TNFα-CXCR1/2 partners in crime in insulin resistance conditions
Authors: Castelli Vanessa , Kacem Housem , Brandolini Laura , Giorgio Cristina , Scenna Marta Sofia , Allegretti Marcello , Cimini Annamaria , d’Angelo Michele
Published: December 2024

Type 2 diabetes mellitus (T2D) is defined by chronic hyperglycemia due to insufficient insulin secretion or activity and decreased insulin sensitivity, known as insulin resistance (IR). This condition leads to oxidative stress and inflammation, increasing the risk of systemic inflammatory diseases. Obesity and a sedentary lifestyle are major risk factors for IR and T2D. Various metabolites act as mediators of IR by disrupting communication between organs. Lipids, including free fatty acids and short-chain fatty acids, along with intracellular lipotoxins, impair insulin function and mitochondrial activity, contributing to IR through direct and indirect mechanisms such as oxidative stress and inflammation. Our research explores the role of TNFα and CXCR1/2 in IR conditions, emphasizing their interactions and potential as therapeutic targets. In this study we selected two models of IR, adipocytes and hepatocytes, since are key players in glucose and lipid metabolism. To develop IR model, TNFα was used as challenge and we focused on investigating the role of CXCR1/2 inhibition. We assessed glucose uptake, insulin signaling pathways, and gene expression related to IR. Cells treated with TNFα showed reduced p-Akt and increased p-JNK levels, indicative of IR. In contrast, CXCR1/2 inhibition restored p-Akt levels and reduced p-JNK levels, suggesting improvements in insulin signaling and glucose uptake. Furthermore, CXCR1/2 inhibition counteracted the TNFα-induced decrease in IGF expression and restored GLUT2 expression, indicating enhanced insulin sensitivity. These results underscore the pivotal role of CXCR1/2 in modulating the inflammatory response and insulin signaling in IR conditions in both IR models. CXCR1/2 inhibition can mitigate IR and improve glucose metabolism. Thus, targeting the TNFα-CXCR1/2 pathway presents a promising therapeutic approach for managing IR and T2D. Further investigation is necessary to understand the clinical implications of these findings and develop effective treatments for patients with IR and T2D.
Dynamic anti-correlations of water hydrogen bonds
Authors: Gunkel Lucas , Ehrhard Amelie A. , Krevert Carola S. , Marekha Bogdan A. , Bonn Mischa , Grechko Maksim , Hunger Johannes
Published: December 2024

Water is characterized by strong intermolecular hydrogen bonds (H-bonds) between molecules. The two hydrogen atoms in one water molecule can form H-bonds of dissimilar length. Although intimately connected to water’s anomalous properties, the details and the origins of the asymmetry have remained elusive. We study water’s H-bonds using the O-D stretching vibrations as sensitive reporters of H-bonding of D2O and HOD in dimethylformamide. Broader inhomogeneous linewidths of the OD band of HOD compared to the symmetric and asymmetric OD stretching modes of D2O together with density functional theory calculations provide evidence for markedly anti-correlated H-bonds: water preferentially forms one weak and one strong H-bond. Coupling peaks in the spectra for D2O directly demonstrate anti-correlated H-bonds and these anti-correlations are modulated by thermal motions of water on a sub-picosecond timescale. Experimentally inferred H-bond distributions suggest that the anti-correlations are a direct consequence of the H-bonding potential of XH2 groups, which we confirm for the ND2 group of urea. These structural and dynamic insights into H-bonding are essential for understanding the relationship between the H-bonded structure and phase behavior of water.
Protein engineering using variational free energy approximation
Authors: Lobzaev Evgenii , Herrera Michael A. , Kasprzyk Martyna , Stracquadanio Giovanni
Published: December 2024

Engineering proteins is a challenging task requiring the exploration of a vast design space. Traditionally, this is achieved using Directed Evolution (DE), which is a laborious process. Generative deep learning, instead, can learn biological features of functional proteins from sequence and structural datasets and return novel variants. However, most models do not generate thermodynamically stable proteins, thus leading to many non-functional variants. Here we propose a model called PRotein Engineering by Variational frEe eNergy approximaTion (PREVENT), which generates stable and functional variants by learning the sequence and thermodynamic landscape of a protein. We evaluate PREVENT by designing 40 variants of the conditionally essential E. coli phosphotransferase N-acetyl-L-glutamate kinase (EcNAGK). We find 85% of the variants to be functional, with 55% of them showing similar growth rate compared to the wildtype enzyme, despite harbouring up to 9 mutations. Our results support a new approach that can significantly accelerate protein engineering.
Unleashed from constrained optimization: quantum computing for quantum chemistry employing generator coordinate inspired method
Authors: Zheng Muqing , Peng Bo , Li Ang , Yang Xiu , Kowalski Karol
Published: December 2024

Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.
Simultaneous discovery of quantum error correction codes and encoders with a noise-aware reinforcement learning agent
Authors: Olle Jan , Zen Remmy , Puviani Matteo , Marquardt Florian
Published: December 2024

In the ongoing race towards experimental implementations of quantum error correction (QEC), finding ways to automatically discover codes and encoding strategies tailored to the qubit hardware platform is emerging as a critical problem. Reinforcement learning (RL) has been identified as a promising approach, but so far it has been severely restricted in terms of scalability. In this work, we significantly expand the power of RL approaches to QEC code discovery. Explicitly, we train an RL agent that automatically discovers both QEC codes and their encoding circuits for a given gate set, qubit connectivity and error model, from scratch. This is enabled by a reward based on the Knill-Laflamme conditions and a vectorized Clifford simulator, showing its effectiveness with up to 25 physical qubits and distance 5 codes, while presenting a roadmap to scale this approach to 100 qubits and distance 10 codes in the near future. We also introduce the concept of a noise-aware meta-agent, which learns to produce encoding strategies simultaneously for a range of noise models, thus leveraging transfer of insights between different situations. Our approach opens the door towards hardware-adapted accelerated discovery of QEC approaches across the full spectrum of quantum hardware platforms of interest.
Three mechanisms of language comprehension are revealed through cluster analysis of individuals with language deficits
Authors: Vyshedskiy Andrey , Venkatesh Rohan , Khokhlovich Edward , Satik Deniz
Published: December 2024

Analysis of linguistic abilities that are concurrently impaired in individuals with language deficits allows identification of a shared underlying mechanism. If any two linguistic abilities are mediated by the same underlying mechanism, then both abilities will be absent if this mechanism is broken. Clustering techniques automatically arrange these abilities according to their co-occurrence and therefore group together abilities mediated by the same mechanism. This study builds upon the discovery of three distinct mechanisms of language comprehension in 31,845 autistic individuals1. The current clustering analysis of a more diverse group of individuals with language impairments resulted in the three mechanisms identical to those found previously: (1) the most-basic command-language-comprehension-mechanism; (2) the intermediate modifier-language-comprehension-mechanism mediating comprehension of color, size, and number modifiers; and (3) the most-advanced syntactic-language-comprehension-mechanism. This discovery calls for mapping of the three empirically-defined language-comprehension-mechanisms in the context of cognitive neuroscience, which is the main goal of this study.
Stakeholder perspectives on the costs and benefits of circular construction
Authors: Karaca Ferhat , Tleuken Aidana , Awan Hamad Hassan , Askar Rand , Çıdık Mustafa Selçuk , Iskakova Anel , Turkyilmaz Ali , Laudal Thomas , Durdyev Serdar , Varol Huseyin Atakan , Salles Adriana , Bajāre Diāna , Tambovceva Tatjana , Zsembinszki Gabriel , Puma Genesis Camila Cervantes , Kapsalyamova Zhanna , Kripa Dorina , Azhgaliyeva Dina , Nano Xhesila , Cabeza Luisa F. , Bragança Luís
Published: December 2024

The construction industry significantly impacts the environment through natural resource depletion and energy consumption, leading to environmental degradation. Circular Economy (CE) material efficiency strategies—such as material reuse, design for disassembly, prefabrication, and recycling—offer promising solutions for reducing resource consumption and waste. This paper explores stakeholders’ perspectives on the costs and benefits of implementing CE material efficiency strategies in the construction industry, using the 3-R (Reduce, Reuse, Recycle) framework. By analyzing data from 382 participants, it assesses perceptions of costs and benefits, uncovering regional differences. The findings highlight that studied European stakeholders prioritize reuse and design for disassembly, while studied non-European countries focus on offsite production and material reuse optimization. Despite these differences, both groups view waste reduction as a key benefit, due to the cost savings it provides. By highlighting regional drivers and barriers to CE adoption, this research establishes a foundation for developing targeted policies and collaborative strategies to advance CE implementation in construction worldwide.
Built-in Bernal gap in large-angle-twisted monolayer-bilayer graphene
Authors: Boschi Alex , Gebeyehu Zewdu M. , Slizovskiy Sergey , Mišeikis Vaidotas , Forti Stiven , Rossi Antonio , Watanabe Kenji , Taniguchi Takashi , Beltram Fabio , Fal’ko Vladimir I. , Coletti Camilla , Pezzini Sergio
Published: December 2024

Atomically thin materials offer multiple opportunities for layer-by-layer control of their electronic properties. While monolayer graphene (MLG) is a zero-gap system, Bernal-stacked bilayer graphene (BLG) acquires a finite band gap when the symmetry between the layers’ potential energy is broken, usually, via a displacement electric field applied in double-gate devices. Here, we introduce a twistronic stack comprising both MLG and BLG, synthesized via chemical vapor deposition, showing a Bernal gap in the absence of external fields. Although a large (~30°) twist angle decouples the MLG and BLG electronic bands near Fermi level, proximity-induced energy shifts in the outermost layers result in a built-in asymmetry, which requires a displacement field of 0.14 V/nm to be compensated. The latter corresponds to a ~10 meV intrinsic BLG gap, a value confirmed by our thermal-activation measurements. The present results highlight the role of structural asymmetry and encapsulating environment, expanding the engineering toolbox for monolithically-grown graphene multilayers.
Yatakemycin biosynthesis requires two deoxyribonucleases for toxin self-resistance
Authors: Dorival Jonathan , Yuan Hua , Walker Allison S. , Tang Gong-Li , Eichman Brandt F.
Published: December 2024

The natural product yatakemycin (YTM) is a potent antimicrobial DNA damaging agent. YtkR4 and YtkR5 are deoxyribonucleases that provide resistance to YTM toxicity by removing the a basic site produced by YtkR2 cleavage of a YTM-adenosine lesion.
Elucidating how trace gases interact with ice surfaces utilizing sum frequency generation
Authors: Yettapu Gurivi Reddy , Manning Luca B. , Cyran Jenée D.
Published: December 2024

The interaction between ice surfaces and trace gases plays a significant role in atmospheric chemistry, such as chemical and photochemical reactions contributing to ozone depletion and secondary aerosol formation. The...
Design and synthesis of novel cathepsin C inhibitors with anti-inflammatory activity
Authors: Shen Xiaobao , Li Nan , Liu Miao , Han Xuanzheng , Wang Yazhi , Jia Jingwen , Wu Fufang , Chen Hongwei , Liu Xinhua
Published: December 2024

Cathepsin C (Cat C) is a potential candidate for addressing inflammatory conditions associated with neutrophil serine proteases (NSPs).
Efficient electrosynthesis of alanine from α-keto acids over a self-supported electrocatalyst with superior activity
Authors: Xu Min , Zhang Shengbo , Liu Jiafang , Xu Hui , Jiang Yong , Zhang Yunxia , Wang Guozhong , Zhang Haimin
Published: December 2024

Herein, we have realized the one-step electrosynthesis of alanine using biomass-derived pyruvic acid and NH2OH as raw reactants in Na2SO4 electrolyte over a self-supported Cu/Ti electrode.
Flexible TADF-based organic X-ray scintillating films for high-resolution imaging
Authors: Xu Haoqiang , Zhao Wenjing , Zhang Xinning , Cui Jingjing , Wang Zhenhua , Liu Xiaowang , Shi Junqing , Ji Lei
Published: December 2024

Pure organic, easily processed, and flexible X-ray scintillating films based on TADF materials for high-resolution imaging with over 20 line pairs per mm.
A new tandem reaction of bifunctional peroxides enables the expedient synthesis of functionalized dihydrofurans
Authors: He Jiayi , Chen Yiwei , Zhao Yukun , Hu Lin
Published: December 2024

A new annulation reaction of bifunctional peroxides allows the rapid construction of functionalized dihydrofurans with high yields and diastereoselectivities.
Optimized operation of AC–DC microgrid cluster with modified PLL and socket protocol
Authors: Gupta Sonam , Gupta Swastik , Shukla Anup , Gonzalez‐Longatt Francisco M.
Published: December 2024

Microgrids integrating inverter based resources face challenges like stability issues during voltage fluctuations and reliance on diesel generators in islanded mode. This paper presents a novel control strategy for photovoltaic and wind‐integrated microgrids to enhance reliability and efficiency. The strategy utilizes a modified phase‐locked loop with droop control for seamless synchronization in grid‐connected and islanded modes. Central to this approach is the localized autonomous controller with a socket protocol interfaced communication layer, dynamically managing operations based on real‐time conditions such as generation, load, and battery state of charge. By integrating battery storage systems, the strategy reduces diesel generator dependency during grid outages. Comprehensive simulations and controller hardware‐in‐the‐loop testing validate its effectiveness, demonstrating improved stability and decreased reliance on diesel generators. The socket protocol enhances real‐time communication, monitoring, and optimization of microgrid operations, ensuring optimal battery storage system utilization and minimal diesel usage. The proposed strategy addresses critical microgrid challenges, offering significant advancements in enhancing system resilience.