Advanced Functional Electromagnetic Shielding Materials:A Review Based on Micro‑Nano Structure Interface Control of Biomass Cell Walls

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

Corrigendum to“Structural geometry of orogenic gold deposits:Implications for exploration of world-class and giant deposits”[Geoscience Frontiers 9,(2018)1163e1177]

Fig.8e in our paper(Groves et al.,2018)was incorrectly ascribed to Caddey et al.(1995).It is actually taken from Figure 3 in Morelli et al.(2010).In turn,this was derived from Bell(2013).The authors apologise for this unintentional error.

Philosophy of Science for Scientists: The Probabilistic Interpretation of Science

Recently we proposed “quantum language” (or, “the linguistic Copenhagen interpretation of quantum mechanics”, “measurement theory”) as the language of science. This theory asserts the probabilistic interpretation of science (=the linguistic quantum mechanical worldview), which is a kind of mathematical generalization of Born’s probabilistic interpretation of quantum mechanics. In this paper, we consider the most fundamental problems in philosophy of science such as Hempel’s raven paradox, Hume’s problem of induction, Goodman’s grue paradox, Peirce’s abduction, flagpole problem, which are closely related to measurement. We believe that these problems can never be solved without the basic theory of science with axioms. Since our worldview (=quantum language) has the axiom concerning measurement, these problems can be solved easily. Thus we believe that quantum language is the central theory in philosophy of science. Hence there is a reason to assert that quantum language gives the mathematical foundations to science.

Treatment Results of Adjuvant Brachytherapy as Monotherapy in Endometrial Cancer: A Retrospective Study from Faculty of Medicine, Chiang Mai University

Purpose: To report the retrospective study of using intravaginal brachytherapy as adjuvant monotherapy for endometrial cancer. Materials and Methods: From 2001-2009, 47 patients who received completely surgical staging for endometrial carcinoma and were designed by multidisciplinary team were enrolled. All patients received intravaginal brachytherapy (IVBT) with the dose of 5.5 - 7 Gy in 2 - 6 fractions. The treatment results and late toxicities were evaluated and recorded. Results: At the median follow-up time of 44 months, the local control, disease-free survival, metastasis-free survival and overall survival rates were 100%, 97.9%, 97.9% and, 97.9%, respectively. Only age showed the statistical significance with the p-value of 0.046. Two patients (4.3%) developed late genitourinary toxicity. Conclusion: The using of adjuvant IVBT as monotherapy for endometrial carcinoma is feasible.

Promising use of metformin in treating neurological disorders:biomarker-guided therapies

Neurological disorders are a diverse group of conditions that affect the nervous system and include neurodegenerative diseases(Alzheimer’s disease,multiple sclerosis,Parkinson’s disease,Huntington’s disease),cerebrovascular conditions(stroke),and neurodevelopmental disorders(autism spectrum disorder).Although they affect millions of individuals around the world,only a limited number of effective treatment options are available today.Since most neurological disorders express mitochondria-related metabolic perturbations,metformin,a biguanide type II antidiabetic drug,has attracted a lot of attention to be repurposed to treat neurological disorders by correcting their perturbed energy metabolism.However,controversial research emerges regarding the beneficial/detrimental effects of metformin on these neurological disorders.Given that most neurological disorders have complex etiology in their pathophysiology and are influenced by various risk factors such as aging,lifestyle,genetics,and environment,it is important to identify perturbed molecular functions that can be targeted by metformin in these neurological disorders.These molecules can then be used as biomarkers to stratify subpopulations of patients who show distinct molecular/pathological properties and can respond to metformin treatment,ultimately developing targeted therapy.In this review,we will discuss mitochondria-related metabolic perturbations and impaired molecular pathways in these neurological disorders and how these can be used as biomarkers to guide metformin-responsive treatment for the targeted therapy to treat neurological disorders.

Decade Milestone Advancement of Defect-Engineered g-C_(3)N_(4) for Solar Catalytic Applications

Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultraactive coordinated environment(M–N_(x), M–C_(2)N_(2), M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra(fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C_(3)N_(4) “customization”, motivating more profound thinking and flourishing research outputs on g-C_(3)N_(4)-based photocatalysis.

The influence of resistance exercise training prescription variables on skeletal muscle mass,strength,and physical function in healthy adults:An umbrella review

Purpose:The aim of this umbrella review was to determine the impact of resistance training(RT)and individual RT prescription variables on muscle mass,strength,and physical function in healthy adults.Methods:Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines,we systematically searched and screened eligible systematic reviews reporting the effects of differing RT prescription variables on muscle mass(or its proxies),strength,and/or physical function in healthy adults aged>18 years.Results:We identified 44 systematic reviews that met our inclusion criteria.The methodological quality of these reviews was assessed using A Measurement Tool to Assess Systematic Reviews;standardized effectiveness statements were generated.We found that RT was consistently a potent stimulus for increasing skeletal muscle mass(4/4 reviews provide some or sufficient evidence),strength(4/6 reviews provided some or sufficient evidence),and physical function(1/1 review provided some evidence).RT load(6/8 reviews provided some or sufficient evidence),weekly frequency(2/4 reviews provided some or sufficient evidence),volume(3/7 reviews provided some or sufficient evidence),and exercise order(1/1 review provided some evidence)impacted RT-induced increases in muscular strength.We discovered that 2/3 reviews provided some or sufficient evidence that RT volume and contraction velocity influenced skeletal muscle mass,while 4/7 reviews provided insufficient evidence in favor of RT load impacting skeletal muscle mass.There was insufficient evidence to conclude that time of day,periodization,inter-set rest,set configuration,set end point,contraction velocity/time under tension,or exercise order(only pertaining to hypertrophy)influenced skeletal muscle adaptations.A paucity of data limited insights into the impact of RT prescription variables on physical function.Conclusion:Overall,RT increased muscle mass,strength,and physical function compared to no exercise.RT intensity(load)and weekly frequency impacted RT-induced increases in muscular strength but not muscle hypertrophy.RT volume(number of sets)influenced muscular strength and hypertrophy.

Reevaluation of dialect boundaries in the Yellowhammer(Emberiza citrinella)based on citizen science data:Should we split or lump?

Dialects are a specific form of geographic variation of birdsong with relatively sharp boundaries between distinct song characteristics,which provide opportunities for focused studies of processes underlying the emergence of spatial patterns in vocalization.Several songbird species that exhibit dialects became models for such research,and for some of them large-scale datasets were assembled that included recordings provided by the public.Among them,the Yellowhammer(Emberiza citrinella,Emberizidae) is particularly prominent,as it has been recently a subject of dedicated citizen science projects focusing on its dialect distribution.The most successful,in terms of public participation as well as the number and density of obtained recordings,was the Dialects of Czech Yellowhammers(DCY) project,which assembled detailed data at the whole-country level.A mosaic of almost all common song variants known across Europe was observed in Czechia,but the results indicated that some of the traditionally recognized Yellowhammer dialects may not represent geographically clustered song variants,at least not in Central Europe.We quantitatively analysed variation(frequency and temporal characteristics and modulation) of the terminal song element in three dialects defined by arbitrary frequency thresholds in DCY.Multivariate analyses indicated that pooling these to two distinct groups reflects the variation in the songs,as well as their spatial distribution,better than retaining the current classification to three dialects or their finer splitting to even more categories.We provide simple measures that may be used for classification of these Yellowhammer song variants in Central Europe.However,we warn from indiscriminate transposing of results from one region to another,as that may lead to substantial biases.Future studies of birdsong variation will benefit from big data assembled by citizen scientists,but to maximise their usefulness for further dialect research,careful delineation of dialect boundaries is essential.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Engineering of Self-Supported Electrocatalysts on a Three-Dimensional Nickel Foam Platform for Efficient Water Electrolysis

Economical water electrolysis requires highly active non-noble electrocatalysts to overcome the sluggish kinetics of the two half-cell reactions,oxygen evolution reaction,and hydrogen evolution reaction.Although intensive efforts have been committed to achieve a hydrogen economy,the expensive noble metal-based catalysts remain under consideration.Therefore,the engineering of self-supported electrocatalysts prepared using a direct growth strategy on three-dimensional(3D)nickel foam(NF)as a conductive substrate has garnered significant interest.This is due to the large active surface area and 3D porous network offered by these electrocatalysts,which can enhance the synergistic eff ect between the catalyst and the substrate,as well as improve electrocatalytic performance.Hydrothermal-assisted growth,microwave heating,electrodeposition,and other physical methods(i.e.,chemical vapor deposition and plasma treatment)have been applied to NF to fabricate competitive electrocatalysts with low overpotential and high stability.In this review,recent advancements in the development of self-supported electrocatalysts on 3D NF are described.Finally,we provide future perspectives of self-supported electrode platforms in electrochemical water splitting.

Reservoir quality evaluation of the Narimba Formation in Bass Basin,Australia:Implications from petrophysical analysis,sedimentological features,capillary pressure and wetting fluid saturation

The evaluation of reservoir quality was accomplished on the Late Paleocene to Early Eocene Narimba Formation in Bass Basin,Australia.This study involved combination methods such as petrophysical analysis,petrography and sedimentological studies,reservoir quality and fluid flow units from derivative parameters,and capillary pressure and wetting fluid saturation relationship.Textural and diagenetic features are affecting the reservoir quality.Cementation,compaction,and presence of clay minerals such as kaolinite are found to reduce the quality while dissolution and secondary porosity are noticed to improve it.It is believed that the Narimba Formation is a potential reservoir with a wide range of porosity and permeability.Porosity ranges from 3.1%to 25.4%with a mean of 15.84%,while permeability ranges between 0.01 mD and 510 mD,with a mean of 31.05 mD.Based on the heterogenous lithology,the formation has been categorized into five groups based on permeability variations.Group I showed an excellent to good quality reservoir with coarse grains.The impacts of both textural and diagenetic features improve the reservoir and producing higher reservoir quality index(RQI)and flow zone indicators(FZI)as well as mostly mega pores.The non-wetting fluid migration has the higher possibility to flow in the formation while displacement pressure recorded as zero.Group II showed a fair quality reservoir with lower petrophysical properties in macro pores.The irreducible water saturation is increasing while the textural and digenetic properties are still enhancing the reservoir quality.Group III reflects lower quality reservoir with mostly macro pores and higher displacement pressure.It may indicate smaller grain size and increasing amount of cement and clay minerals.Group IV,and V are interpreted as a poor-quality reservoir that has lower RQI and FZI.The textural and digenetic features are negatively affecting the reservoir and are leading to smaller pore size and pore throat radii(r35)values to be within the range of macro,meso-,micro-,and nano pores.The capillary displacement pressure curves of the three groups show increases reaching the maximum value of 400 psia in group V.Agreement with the classification of permeability,r35 values,and pore type can be used in identifying the quality of reservoir.

Efficacy of exercise rehabilitation for managing patients with Alzheimer's disease

Alzheimer's disease(AD) is a progressive and degenerative neurological disease characterized by the deterioration of cognitive functions. While a definitive cure and optimal medication to impede disease progression are currently unavailable, a plethora of studies have highlighted the potential advantages of exercise rehabilitation for managing this condition. Those studies show that exercise rehabilitation can enhance cognitive function and improve the quality of life for individuals affected by AD. Therefore, exercise rehabilitation has been regarded as one of the most important strategies for managing patients with AD. Herein, we provide a comprehensive analysis of the currently available findings on exercise rehabilitation in patients with AD, with a focus on the exercise types which have shown efficacy when implemented alone or combined with other treatment methods, as well as the potential mechanisms underlying these positive effects. Specifically, we explain how exercise may improve the brain microenvironment and neuronal plasticity. In conclusion, exercise is a cost-effective intervention to enhance cognitive performance and improve quality of life in patients with mild to moderate cognitive dysfunction. Therefore, it can potentially become both a physical activity and a tailored intervention. This review may aid the development of more effective and individualized treatment strategies to address the challenges imposed by this debilitating disease, especially in low-and middle-income countries.

Synergistic effect of carbon nanotube and encapsulated carbon layer enabling high-performance SnS_2-based anode for lithium storage

Tin disulfide(SnS_(2)),due to large interlayer spacing and high theoretical capacity,is regarded as a prospective anode material for lithium-ion batteries.Nevertheless,the poor electron conductivity of SnS_(2) and huge volumetric change during the lithiation/delithiation process lead to a rapid capacity decay of the battery,hindering its commercialization.To address these issues,herein,SnS_(2) is in-situ grown on the surface of carbon nanotubes(CNT)and then encapsulated with a layer of porous amorphous carbon(CNT/SnS_(2)@C)by simple solvothermal and further carbonization treatment.The synergistic effect of CNT and porous carbon layer not only enhances the electrical co nductivity of SnS_(2) but also limits the huge volumetric change to avoid the pulverization and detachment of SnS_(2).Density functional theo ry calculations show that CNT/SnS_(2)@C has high Li^(+)adsorption and lithium storage capacity achieving high reaction kinetics.Consequently,cells with the CNT/SnS_(2)@C anode exhibit a high lithium storage capacity of 837mAh/g after 100 cycles at 0.1 A/g and retaining a capacity of 529.8 mAh/g under 1.0 A/g after 1000 cycles.This study provides a fundamental understanding of the electrochemical processes and beneficial guidance to design high-performance SnS_(2)-based anodes for LIBs.

MXene@c-MWCNT Adhesive Silica Nanofiber Membranes Enhancing Electromagnetic Interference Shielding and Thermal Insulation Performance in Extreme Environments

A lightweight flexible thermally stable composite is fabricated by com-bining silica nanofiber membranes(SNM)with MXene@c-MWCNT hybrid film.The flexible SNM with outstanding thermal insulation are prepared from tetraethyl orthosilicate hydrolysis and condensation by electrospinning and high-temperature calcination;the MXene@c-MWCNT_(x:y)films are prepared by vacuum filtration tech-nology.In particular,the SNM and MXene@c-MWCNT_(6:4)as one unit layer(SMC_(1))are bonded together with 5 wt%polyvinyl alcohol(PVA)solution,which exhibits low thermal conductivity(0.066 W m^(-1)K^(-1))and good electromagnetic interference(EMI)shielding performance(average EMI SE_(T),37.8 dB).With the increase in func-tional unit layer,the overall thermal insulation performance of the whole composite film(SMC_(x))remains stable,and EMI shielding performance is greatly improved,especially for SMC_(3)with three unit layers,the average EMI SET is as high as 55.4 dB.In addition,the organic combination of rigid SNM and tough MXene@c-MWCNT_(6:4)makes SMC_(x)exhibit good mechanical tensile strength.Importantly,SMC_(x)exhibit stable EMI shielding and excellent thermal insulation even in extreme heat and cold environment.Therefore,this work provides a novel design idea and important reference value for EMI shielding and thermal insulation components used in extreme environmental protection equipment in the future.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.

Acute worsening of microvascular complications of diabetes mellitus during rapid glycemic control:The pathobiology and therapeutic implications

While chronic hyperglycaemia resulting from poorly controlled diabetes mellitus(DM)is a well-known precursor to complications such as diabetic retinopathy,neuropathy(including autonomic neuropathy),and nephropathy,a paradoxical intensification of these complications can rarely occur with aggressive glycemic management resulting in a rapid reduction of glycated haemoglobin.Although,acute onset or worsening of retinopathy and treatment induced neuropathy of diabetes are more common among these complications,rarely other problems such as albuminuria,diabetic kidney disease,Charcot’s neuroarthropathy,gastroparesis,and urinary bladder dysfunction are also encountered.The World Journal of Diabetes recently published a rare case of all these complications,occurring in a young type 1 diabetic female intensely managed during pregnancy,as a case report by Huret et al.It is essential to have a comprehensive understanding of the pathobiology,prevalence,predisposing factors,and management strategies for acute onset,or worsening of microvascular complications when rapid glycemic control is achieved,which serves to alleviate patient morbidity,enhance disease management compliance,and possibly to avoid medico-legal issues around this rare clinical problem.This editorial delves into the dynamics surrounding the acute exacerbation of microvascular complications in poorly controlled DM during rapid glycaemic control.

An oxygenating colloidal bioink for the engineering of biomimetic tissue constructs

Ensuring a sufficient oxygen supply is pivotal for the success of bioprinting applications since it fosters tissue integration and natural regeneration.Variation in oxygen concentration among diverse tissues necessitates the precise recreation of tissue-specific oxygen levels in imprinted constructs to support the survival of targeted cells.Although oxygen-releasing biomaterials,such as oxygen-generating microparticles(OMPs),have shown promise for enhancing the oxygen supply of microenvironments in injured tissues,whether this approach is scalable for large tissues and whether tissue-specific bioinks with varying OMP concentrations remain printable remain unknown.This study addresses this critical gap by introducing an innovative class of engineered oxygenated bioinks that combine colloidal-based microgels with OMPs.We report that incorporating nanosized calcium peroxide(nCaO_(2))and manganese oxide nanosheets(nMnO_(2))into hydrophobic polymeric microparticles enables precise modulation of oxygen release while controlling hydrogen peroxide release.Moreover,the fabrication of oxygenating and cytocompatible colloidal gels is achieved using an aqueous two-phase system.This study thoroughly evaluates the fundamental characteristics of the resulting bioink,including its rheological behaviors,printability,shape fidelity,mechanical properties,and oxygen release properties.Moreover,this study demonstrates the macroscopic scalability and cytocompatibility of printed constructs produced via cell-laden oxygenating colloidal bioinks.By showcasing the effectiveness of extrusion-based bioprinting,this study underscores how it can be used to fabricate biomimetic tissues,indicating its potential for new applications.The findings presented here advance the bioprinting field by achieving scalability with both high cell viability and the possibility of mimicking specifically oxygenated tissues.This work thereby offers a promising avenue for the development of functional tissues with enhanced physiological relevance.

First Light Curve Analysis of NSVS 8294044,V1023 Her,and V1397 Her Contact Binary Systems

The first photometric light curve investigation of the NSVS 8294044,V1023 Her,and V1397 Her binary systems is presented.We used ground-based observations for the NSVS 8294044 system and Transiting Exoplanet Survey Satellite data for V1023 Her and V1397 Her.The primary and secondary times of minima were extracted from al the data,and,by collecting the literature,a new ephemeris was computed for each system.Linear fits for the O-C diagrams were conducted using the Markov Chain Monte Carlo (MCMC) method.Light curve solutions were performed using the PHysics Of Eclipsing BinariEs Python code and the MCMC approach.The systems were found to be contact binary stars based on the fillout factor and mass ratio.V1023 Her showed the O’Connell effect and a cold starspot on the secondary component was required for the light curve solution.The absolute parameters of the system were estimated based on an empirical relationship between orbital period and mass.We presented a new T–M equation based on a sample of 428 contact binary systems and found that our three target systems were in good agreement with the fit.The positions of the systems were also depicted on the M–L,M–R,q–L_(ratio),and M_(tot)–J_(0)diagrams in the logarithmic scales.

Unveiling the tailorable electrochemical properties of zeolitic imidazolate framework-derived Ni-doped LiCoO_(2) for lithium-ion batteries in half/full cells

As a prevailing cathode material of lithium-ion batteries(LIBs),LiCoO_(2)(LCO)still encounters the tricky problems of structural collapse,whose morphological engineering and cation doping are crucial for surmounting the mechanical strains and alleviating phase degradation upon cycling.Hereinafter,we propose a strategy using a zeolitic imidazolate framework(ZIF)as the self-sacrificing template to directionally prepare a series of LiNi_(0.1)Co_(0.9)O_(2)(LNCO)with tailorable electrochemical properties.The rational selection of sintering temperature imparts the superiority of the resultant products in lithium storage,during which the sample prepared at 700℃(LNCO-700)outperforms its counterparts in cyclability(156.8 mA h g^(-1)at 1 C for 200 cycles in half cells,1 C=275 mA g^(-1))and rate capability due to the expedited ion/electron transport and the strengthen mechanical robustness.The feasibility of proper Ni doping is also divulged by half/full cell tests and theoretical study,during which LNCO-700(167 mA h g^(-1)at 1 C for 100 cycles in full cells)surpasses LCO-700 in battery performance due to the mitigated phase deterioration,stabilized layered structu re,ameliorated electro nic co nductivity,a nd exalted lithium sto rage activity.This work systematically unveils tailorable electrochemical behaviors of LNCO to better direct their practical application.

Comparative efficacy of sodium glucose cotransporter-2 inhibitors in the management of type 2 diabetes mellitus:A real-world experience

BACKGROUND Sodium glucose cotransporter-2 inhibitors(SGLT-2i)are a class of drugs with modest antidiabetic efficacy,weight loss effect,and cardiovascular benefits as proven by multiple randomised controlled trials(RCTs).However,real-world data on the comparative efficacy and safety of individual SGLT-2i medications is sparse.AIM To study the comparative efficacy and safety of SGLT-2i using real-world clinical data.METHODS We evaluated the comparative efficacy data of 3 SGLT-2i drugs(dapagliflozin,canagliflozin,and empagliflozin)used for treating patients with type 2 diabetes mellitus.Data on the reduction of glycated hemoglobin(HbA1c),body weight,blood pressure(BP),urine albumin creatinine ratio(ACR),and adverse effects were recorded retrospectively.RESULTS Data from 467 patients with a median age of 64(14.8)years,294(62.96%)males and 375(80.5%)Caucasians were analysed.Median diabetes duration was 16.0(9.0)years,and the duration of SGLT-2i use was 3.6(2.1)years.SGLT-2i molecules used were dapagliflozin 10 mg(n=227;48.6%),canagliflozin 300 mg(n=160;34.3%),and empagliflozin 25 mg(n=80;17.1).Baseline median(interquartile range)HbA1c in mmol/mol were:dapagliflozin-78.0(25.3),canagliflozin-80.0(25.5),and empagliflozin-75.0(23.5)respectively.The respective median HbA1c reduction at 12 months and the latest review(just prior to the study)were:66.5(22.8)&69.0(24.0),67.0(16.3)&66.0(28.0),and 67.0(22.5)&66.5(25.8)respectively(P<0.001 for all comparisons from baseline).Significant improvements in body weight(in kilograms)from baseline to study end were noticed with dapagliflozin-101(29.5)to 92.2(25.6),and canagliflozin 100(28.3)to 95.3(27.5)only.Significant reductions in median systolic and diastolic BP,from 144(21)mmHg to 139(23)mmHg;(P=0.015),and from 82(16)mmHg to 78(19)mmHg;(P<0.001)respectively were also observed.A significant reduction of microalbuminuria was observed with canagliflozin only[ACR 14.6(42.6)at baseline to 8.9(23.7)at the study end;P=0.043].Adverse effects of SGLT-2i were as follows:genital thrush and urinary infection-20(8.8%)&17(7.5%)with dapagliflozin;9(5.6%)&5(3.13%)with canagliflozin;and 4(5%)&4(5%)with empagliflozin.Diabetic ketoacidosis was observed in 4(1.8%)with dapagliflozin and 1(0.63%)with canagliflozin.CONCLUSION Treatment of patients with SGLT-2i is associated with statistically significant reductions in HbA1c,body weight,and better than those reported in RCTs,with low side effect profiles.A review of large-scale real-world data is needed to inform better clinical practice decision making.