Feasibility of Simultaneous Bilateral Endoscopic Surgery in Prone Split-Leg Position for Bilateral Upper Urinary Tract Calculi: A Pilot Study.

INTRODUCTION: We explored the viability of simultaneous bilateral endoscopic surgery (SBES) in the prone split-leg position for managing bilateral calculi. METHODS: We retrospectively reviewed 72 patients who underwent SBES, with procedures involving ureteroscopy (URS) and contralateral percutaneous nephrolithotomy (PNL) simultaneously, in prone split-leg position. RESULTS: Operative times averaged 109.38 ± 30.76 min, with an average hospital stay of 7.79 ± 3.78 days. The bilateral stone-free rate (SFR) was 70.83%, while URS and PNL demonstrated comparable unilateral SFR (83.33% and 79.17%, respectively). Receiver operating characteristics curves for predicting unilateral residual fragments yielded an area under the curve of 0.84 (URS) and 0.81 (PNL) with respective cutoff values of stone diameter of 11.55 mm and 23.52 mm. Fifty-seven (79.17%) and 15 (20.83%) patients encountered grade 0-1/2 complications, with no severe complications (grade 3-5) recorded. No significant changes in blood count or renal function were observed post-SBES. CONCLUSIONS: SBES in the prone split-leg position is a viable option for managing bilateral upper tract urolithiasis. Larger scale studies are needed to further assess safety and efficacy in various positions.

In-situ construction of fluorescent probes for hydrogen peroxide detection in mitochondria and lysosomes with on-demand modular assembling and double turn-on features.

Due to the diverse H2O2 distribution in organelles, fluorescent probes were usually required to be prepared separately, which limited the convenience and practicability. Herein, we reported a flexible strategy to in-situ construct H2O2 fluorescent probes in different organelles. A tetrazine fused probe TP was developed with rapid click reaction capacity and sensitive H2O2 response. When treated with H2O2, the turn-on fluorescence was effectively quenched by the tetrazine part. Only after click reaction with dienophiles, the fluorescence resumed. In application, cells were firstly treated with triphenylphosphorus tagged norbornene (TPP-NB) to label mitochondria, which was followed by the introduction of probe TP to trigger click reaction. The in-situ constructed probe P1 served as a local H2O2 sensor. In a similar way, probe P2 was in-situ constructed in lysosomes via probe TP and morpholine tagged norbornene (MP-NB). With this on-demand modular assembling and double turn-on features, our strategy to construct fluorescent probes presented high flexibility and anti-interference performance, which was expected to inspired more applications in biological studies.

Machine-learning screening of luminogens with aggregation-induced emission characteristics for fluorescence imaging.

Due to the excellent biocompatible physicochemical performance, luminogens with aggregation-induced emission (AIEgens) characteristics have played a significant role in biomedical fluorescence imaging recently. However, screening AIEgens for special applications takes a lot of time and efforts by using conventional chemical synthesis route. Fortunately, artificial intelligence techniques that could predict the properties of AIEgen molecules would be helpful and valuable for novel AIEgens design and synthesis. In this work, we applied machine learning (ML) techniques to screen AIEgens with expected excitation and emission wavelength for biomedical deep fluorescence imaging. First, a database of various AIEgens collected from the literature was established. Then, by extracting key features using molecular descriptors and training various state-of-the-art ML models, a multi-modal molecular descriptors strategy has been proposed to extract the structure-property relationships of AIEgens and predict molecular absorption and emission wavelength peaks. Compared to the first principles calculations, the proposed strategy provided greater accuracy at a lower computational cost. Finally, three newly predicted AIEgens with desired absorption and emission wavelength peaks were synthesized successfully and applied for cellular fluorescence imaging and deep penetration imaging. All the results were consistent successfully with our expectations, which demonstrated the above ML has a great potential for screening AIEgens with suitable wavelengths, which could boost the design and development of novel organic fluorescent materials.

BIX-01294 enhances the effect of chemotherapy on colorectal cancer by inhibiting the expression of stemness genes.

During the development of colorectal cancer, tumor cells will generate some cancer stem cells with self-renewal ability because they adapt to the environment. Therefore, in the treatment of colorectal cancer, it has certain potential clinical application value to effectively inhibit cancer stem cells. A small molecule EHMT-2 inhibitor, BIX-01294, was evaluated for its activity in inhibiting cancer stem cells in human colorectal cancer by in vitro and in vivo experiments. Transcriptome analysis was performed on BIX-01294 treated cells for holistic analysis to elucidate how BIX-01294 inhibits the expression of genes related to cancer stem cells. The results show that BIX-01294 significantly inhibited the proliferative phenotype of human colorectal cancer in vivo and in vitro, reduced the proportion of cancer stem cells, and inhibited some stemness-related gene. Morever, it is synergistic with 5-fluorouracil in inhibiting the proliferation of colorectal cancer. In summary, EHMT-2 is a novel target of anti-tumor drugs. The combination of BIX-01294 and 5-fluorouracil has a synergistic therapeutic effect on human colorectal cancer.

A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications.

Background: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, and ingestible and implantable sensors are increasingly used by individuals and clinicians to capture the health outcomes or behavioral and physiological characteristics of individuals. Time series classification (TSC) is very commonly used for modeling digital clinical measures. While deep learning models for TSC are very common and powerful, there exist some fundamental challenges. This review presents the non-deep learning models that are commonly used for time series classification in biomedical applications that can achieve high performance. Objective: We performed a systematic review to characterize the techniques that are used in time series classification of digital clinical measures throughout all the stages of data processing and model building. Methods: We conducted a literature search on PubMed, as well as the Institute of Electrical and Electronics Engineers (IEEE), Web of Science, and SCOPUS databases using a range of search terms to retrieve peer-reviewed articles that report on the academic research about digital clinical measures from a five-year period between June 2016 and June 2021. We identified and categorized the research studies based on the types of classification algorithms and sensor input types. Results: We found 452 papers in total from four different databases: PubMed, IEEE, Web of Science Database, and SCOPUS. After removing duplicates and irrelevant papers, 135 articles remained for detailed review and data extraction. Among these, engineered features using time series methods that were subsequently fed into widely used machine learning classifiers were the most commonly used technique, and also most frequently achieved the best performance metrics (77 out of 135 articles). Statistical modeling (24 out of 135 articles) algorithms were the second most common and also the second-best classification technique. Conclusions: In this review paper, summaries of the time series classification models and interpretation methods for biomedical applications are summarized and categorized. While high time series classification performance has been achieved in digital clinical, physiological, or biomedical measures, no standard benchmark datasets, modeling methods, or reporting methodology exist. There is no single widely used method for time series model development or feature interpretation, however many different methods have proven successful.

Metal organic framework-coated gold nanorod as an on-demand drug delivery platform for chemo-photothermal cancer therapy.

Chemo-photothermal therapy based on nanoparticles has emerged as a promising strategy for cancer treatment. However, its therapeutic efficacy and application potential are largely subjected to the uncontrollability and biotoxicity of functional nanoplatforms. Herein, a novel biocompatible and biodegradable metal organic framework (MOF), which was constructed by growing crystalline zeolitic imidazolate framework-8 on gold nanoroad (Au@ZIF-8), was designed and fabricated for efficient drug loading and controlled release. Owing to the large surface area and guest-matching pore size of ZIF-8, doxorubicin (DOX) was successfully loaded into the Au@ZIF-8 with a high drug loading efficiency of ~ 37%. Under NIR light or weakly acidic environment, the ZIF-8 layer was quickly degraded, which resulted in an on-demand drug release in tumour site. More importantly, under the irradiation of near infrared (NIR) laser, highly efficient cancer treatment was achieved in both in vitro cell experiment and in vivo tumour-bearing nude mice experiment due to the synergistic effect of photothermal (PTT) therapy and chemotherapy. In addition, the in vivo study revealed the good biocompatibility of Au@ZIF-8. This work robustly suggested that Au@ZIF-8 could be further explored as a drug delivery system for chemo-photothermal synergistic therapy.

Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review.

BACKGROUND: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. OBJECTIVE: We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. METHODS: We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. RESULTS: The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. CONCLUSIONS: Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.

EventDTW: An Improved Dynamic Time Warping Algorithm for Aligning Biomedical Signals of Nonuniform Sampling Frequencies.

The dynamic time warping (DTW) algorithm is widely used in pattern matching and sequence alignment tasks, including speech recognition and time series clustering. However, DTW algorithms perform poorly when aligning sequences of uneven sampling frequencies. This makes it difficult to apply DTW to practical problems, such as aligning signals that are recorded simultaneously by sensors with different, uneven, and dynamic sampling frequencies. As multi-modal sensing technologies become increasingly popular, it is necessary to develop methods for high quality alignment of such signals. Here we propose a DTW algorithm called EventDTW which uses information propagated from defined events as basis for path matching and hence sequence alignment. We have developed two metrics, the error rate (ER) and the singularity score (SS), to define and evaluate alignment quality and to enable comparison of performance across DTW algorithms. We demonstrate the utility of these metrics on 84 publicly-available signals in addition to our own multi-modal biomedical signals. EventDTW outperformed existing DTW algorithms for optimal alignment of signals with different sampling frequencies in 37% of artificial signal alignment tasks and 76% of real-world signal alignment tasks.

[Application of NGAL and Cys c in predicting graft function during early period after kidney transplantation].

OBJECTIVE: To assess the diagnostic values of novel biomarkers, such as neutrophil gelatinase-associated lipocalin (NGAL) and cystatin c (Cys c), in the diagnosis of delayed graft function (DGF). METHODS: A total of 114 patients undergoing kidney transplantation from deceased donors from October 2012 to October 2013 were enrolled. Recipients on dialysis during the first postoperative week were included into DGF group while those without DGF into early graft function (EGF) group. sNGAL, sCys c and serum creatinine (sCr) were measured pre-operation, as well as at 4, 12, 24, 72 and 168 h post-operation. Furthermore, uNGAL leveks were measured at 4, 12 and 24 h post-transplantation. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the predictive value of DGF. RESULTS: Among 114 recipients enrolled, 23 presented DGF and 91 EGF. In EGF group, within 4 h post-transplantation sNGAL and sCys c decreased more significantly than sCr (51.31% (40.30%, 62.31%), 56.39% (50.02%, 68.40%) vs 21.40% (6.77%, 27.44%), P = 0.009 and 0.029 respectively). Between two groups, differences of sequential decrease were observed earlier in sNGAL and sCys c than uNGAL and sCr. It demonstrated better performance in predicting DGF. The AUC of sCr was between uNGAL and sNGAL, sCys c. Combination of both sNGAL and sCys c yielded a ROC-AUC of 1.000. CONCLUSIONS: sNGAL and sCys are ideal for predicting the recovery of graft function during early period after kidney transplantation. And a combination of both biomarkers may dramatically improve the specificity and sensitivity of diagnosing DGF.

Managing multi-lateral, intergovernmental projects and programmes: the case of the UNEP/GEF South China Sea project.

The management of comprehensive and extensive, multi-lateral and multi-national programmes and projects in the field of coastal and ocean management poses numerous organisational problems encompassing co-ordination between: the actions of individual participating countries at the regional level; the national level actions of institutions from different sectors; and actions that are designed to address issues as diverse as: biological diversity conservation and sustainable use; fisheries management; maritime transport; and the control of land based pollution. Most large multi-lateral projects focus on sound scientific knowledge and information, and pay less attention to the design of a management structure that will ensure coherence and co-ordination of the interventions once the programme or project is under implementation. The project entitled "Reversing Environmental Degradation Trends in the South China Sea and Gulf of Thailand" was complex since it addressed three priority areas of concern namely the loss and degradation of coastal habitats, over-exploitation of fisheries in the Gulf of Thailand, and land-based pollution. It is suggested that the success of the management framework reflects the following key design elements:•The framework permitted and encouraged both "horizontal" (inter-country) and "vertical" (intra-country) interactions and networking between individuals at all levels of project implementation and execution;•Inclusion of a body (the Regional Scientific and Technical Committee) that served as a forum for reconciling both sectorial and national interests and priorities;•The clear separation between discussions of scientific and technical matters from discussions dealing with policy and principles at both the national and regional levels;•The framework facilitated the incorporation of sound scientific and technical advice and information into politically based decision-making;•The use of regional experts and consultants from the participating countries fostered "ownership" of the activities and outputs;•Restriction of the membership of the Project Steering Committee to government representatives only, and exclusion of observers from regional and international agencies and institutions other than UNEP; and,•The framework allowed for adaptive management and was not a rigid unchanging structure.

Direct oxidation of methane to methanol using CuMoO4.

Upgrading methane into methanol or other high value-added chemicals is not only beneficial to mitigate the greenhouse effect, but also provides basic raw materials for industrial production. Nowadays, most research is limited to zeolite systems, and it is a considerable challenge to extend the support to metal oxides while achieving a high yield of methanol. In this paper, we take advantage of impregnation methods to synthesise a novel Cu/MoO3 catalyst, which can convert methane to methanol in the gaseous phase. At 600 °C, the Cu(2)/MoO3 catalyst can achieve a maximum STYCH3OH of 47.2 µmol (g-1 h-1) with a molar ratio CH4 : O2 : H2O = 5 : 1.4 : 10. Consequences of SEM, TEM, HRTEM and XRD substantiate that Cu is incorporated into the lattice of MoO3 to form CuMoO4. And transmission infrared spectroscopy, Raman spectroscopy together with XPS characterization techniques confirm the generation of CuMoO4, which is the main active site provider. This work provides a new support platform for Cu-based catalyst research in the methane-to-methanol system.

Highly Conductive Ultrathin Layers of Conjugated Polymers for Metal-Free Coplanar Transistors with Single-Polymer Transport Layers.

Although metal or oxide conductive films are widely used as electrodes of electronic devices, organic electrodes would be more favorable for next-generation organic electronics. Here, using some model conjugated polymers as examples, we report a class of highly conductive and optically transparent polymer ultrathin layers. Vertical phase separation of semiconductor/insulator blends leads to a highly ordered two-dimensional (2D) ultrathin layer of conjugated-polymer chains on the insulator. Afterwards, the thermally evaporated dopants on the ultrathin layer lead to a conductivity of up to 103 S cm-1 and a sheet resistance 103 Ω/square for a model conjugated polymer poly(2,5-bis(3-hexadecylthiophen-2-yl)thieno[3,2-b]thiophenes) (PBTTT). The high conductivity is due to the high hole mobility (∼ 20 cm2 V-1 s-1), although doping-induced charge density is still in the moderate range of 1020 cm-3 with a 1 nm thick dopant. Metal-free monolithic coplanar field-effect transistors using the same conjugated-polymer ultrathin layer with alternatively doped regions as electrodes and a semiconductor layer are realized. The field-effect mobility of this monolithic transistor is over 2 cm2 V-1 s-1 for PBTTT, one order higher than that of the conventional PBTTT transistor using metal electrodes. The optical transparency of the single conjugated-polymer transport layer is over 90%, demonstrating a bright future for all-organic transparent electronics.

Investigating the accuracy of blood oxygen saturation measurements in common consumer smartwatches.

Blood oxygen saturation (SpO2) is an important measurement for monitoring patients with acute and chronic conditions that are associated with low blood oxygen levels. While smartwatches may provide a new method for continuous and unobtrusive SpO2 monitoring, it is necessary to understand their accuracy and limitations to ensure that they are used in a fit-for-purpose manner. To determine whether the accuracy of and ability to take SpO2 measurements from consumer smartwatches is different by device type and/or by skin tone, our study recruited patients aged 18-85 years old, with and without chronic pulmonary disease, who were able to provide informed consent. The mean absolute error (MAE), mean directional error (MDE) and root mean squared error (RMSE) were used to evaluate the accuracy of the smartwatches as compared to a clinical grade pulse oximeter. The percent of data unobtainable due to inability of the smartwatch to record SpO2 (missingness) was used to evaluate the measurability of SpO2 from the smartwatches. Skin tones were quantified based on the Fitzpatrick (FP) scale and Individual Typology Angle (ITA), a continuous measure of skin tone. A total of 49 individuals (18 female) were enrolled and completed the study. Using a clinical-grade pulse oximeter as the reference standard, there were statistically significant differences in accuracy between devices, with Apple Watch Series 7 having measurements closest to the reference standard (MAE = 2.2%, MDE = -0.4%, RMSE = 2.9%) and the Garmin Venu 2s having measurements farthest from the reference standard (MAE = 5.8%, MDE = 5.5%, RMSE = 6.7%). There were also significant differences in measurability across devices, with the highest data presence from the Apple Watch Series 7 (88.9% of attempted measurements were successful) and the highest data missingness from the Withings ScanWatch (only 69.5% of attempted measurements were successful). The MAE, RMSE and missingness did not vary significantly across FP skin tone groups, however, there may be a relationship between FP skin tone and MDE (intercept = 0.04, beta coefficient = 0.47, p = 0.04). No statistically significant difference was found between skin tone as measured by ITA and MAE, MDE, RMSE or missingness.

Direct Catalytic Oxidation of Low-Concentration Methane to Methanol in One Step on Ni-Promoted BiOCl Catalysts.

The direct oxidation of low-concentration methane (CH4) to methanol (CH3OH) is often regarded as the "holy grail". However, it still is very difficult and challenging to oxidize methane to methanol in one step. In this work, we present a new approach to directly oxidize CH4 to generate CH3OH in one step by doping non-noble metal Ni sites on bismuth oxychloride (BiOCl) equipped with high oxygen vacancies. Thereinto, the conversion rate of CH3OH can reach 39.07 µmol/(gcat·h) under 420 °C and flow conditions on the basis of O2 and H2O. The crystal morphology structure, physicochemical properties, metal dispersion, and surface adsorption capacity of Ni-BiOCl were explored, and the positive effect on the oxygen vacancy of the catalyst was proved, thus improving the catalytic performance. Furthermore, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) was also performed to study the surface adsorption and reaction process of methane to methanol in one step. Results demonstrate that the key to keep good activity lies in the oxygen vacancies of unsaturated Bi atoms, which can adsorb and active CH4 and to produce methyl groups and adsorbing hydroxyl groups in methane oxidation process. This study broadens the application of oxygen-deficient catalysts in the catalytic conversion of CH4 to CH3OH in one step, which provides a new perspective on the role of oxygen vacancies in improving the catalytic performance of methane oxidation.

Mercury biomagnification at higher rates than the global average in aquatic ecosystems of the Qinghai-Tibet Plateau.

Mercury biomagnification in aquatic ecosystems is a global issue. Biomagnification patterns and drivers in alpine regions remain poorly understood. Hg biomagnification in the aquatic food web of the Qinghai-Tibetan Plateau (Q-T Plateau) was investigated. A total of 302 fish and macroinvertebrate tissue samples were analysed for total mercury (THg) and nitrogen (δ15N) stable isotope ratios. Overall, 26.75% of fish individuals exceeded the USFWS consumption guidelines. A total of 52.17% of the sampling sites covering different habitats exhibited a significantly positive THg-δ15N relationship, which confirmed the Hg biomagnification potential of Q-T Plateau aquatic ecosystems. The Q-T Plateau Hg biomagnification rates were generally far higher than global averages regardless of the habitat type. Hg in sediments, elevation and population density were positively related to the Hg biomagnification magnitude on the Q-T Plateau, which could be attributed to the disproportionate response of Hg concentrations in macroinvertebrates and fishes along environmental gradients. Our findings offer empirical evidence that fish consumption on the Q-T Plateau poses a substantial Hg exposure risk to people living along river and lake shores. Higher biomagnification rates could further disproportionately accelerate Hg pollution in Q-T Plateau aquatic ecosystems under future anthropogenic activities and climate warming trajectories.

Going beyond the means: Exploring the role of bias from digital determinants of health in technologies.

BACKGROUND: In light of recent retrospective studies revealing evidence of disparities in access to medical technology and of bias in measurements, this narrative review assesses digital determinants of health (DDoH) in both technologies and medical formulae that demonstrate either evidence of bias or suboptimal performance, identifies potential mechanisms behind such bias, and proposes potential methods or avenues that can guide future efforts to address these disparities. APPROACH: Mechanisms are broadly grouped into physical and biological biases (e.g., pulse oximetry, non-contact infrared thermometry [NCIT]), interaction of human factors and cultural practices (e.g., electroencephalography [EEG]), and interpretation bias (e.g, pulmonary function tests [PFT], optical coherence tomography [OCT], and Humphrey visual field [HVF] testing). This review scope specifically excludes technologies incorporating artificial intelligence and machine learning. For each technology, we identify both clinical and research recommendations. CONCLUSIONS: Many of the DDoH mechanisms encountered in medical technologies and formulae result in lower accuracy or lower validity when applied to patients outside the initial scope of development or validation. Our clinical recommendations caution clinical users in completely trusting result validity and suggest correlating with other measurement modalities robust to the DDoH mechanism (e.g., arterial blood gas for pulse oximetry, core temperatures for NCIT). Our research recommendations suggest not only increasing diversity in development and validation, but also awareness in the modalities of diversity required (e.g., skin pigmentation for pulse oximetry but skin pigmentation and sex/hormonal variation for NCIT). By increasing diversity that better reflects patients in all scenarios of use, we can mitigate DDoH mechanisms and increase trust and validity in clinical practice and research.

Interferon-γ-Induced Myeloid-Derived Suppressor Cells Aggravate Kidney Ischemia-Reperfusion Injury by Regulating Innate Immune Cells.

OBJECTIVE: Myeloid-derived suppressor cells (MDSCs) are heterogeneous cells which can suppress T-cell functionality. Herein, we evaluated the functional importance of MDSCs in the context of kidney ischemia-reperfusion injury (IRI) and explored their ability to regulate innate and adaptive immune cell function in this context. METHODS: The differentiation of MDSCs was induced in vitro by treating cells with GM-CSF and interferon (IFN)-γ. In a murine model of renal IRI, serum creatinine and blood urea nitrogen values were measured to monitor kidney function, while histopathological and immunohistochemical approaches were used to assess kidney injury severity. In addition, flow cytometry was employed to assess the phenotypes and apoptosis of kidney cells in these mice. RESULTS: MDSCs induced by treatment with GM-CSF + IFN-γ could suppress T-cell functionality in vitro. The adoptive transfer of these MDSCs into an IRI mouse model system enhanced kidney damage and impaired renal function following the recruitment of these cells to renal tissues in these mice. Following such adoptive transfer, the relative frequency of MDSCs with a CD11b+Ly6G-Ly6Chigh monocytic-MDSC phenotype decreased, whereas cells with a CD11b+Ly6G+Ly6Clow polymorphonuclear-MDSC phenotype become more prevalent within kidney tissues following IRI. Adoptive transfer also coincided with increased frequencies of macrophages and dendritic cells (DCs) in the kidney tissues. This suggested that M-MDSCs contributed to early-stage renal IRI damage by differentiating into these deleterious cell types. However, MDSC-induced suppression of CD4+ and CD8+ T-cell infiltration was not sufficient to prevent the deterioration of renal function in these mice. CONCLUSIONS: Herein, we successfully developed a protocol wherein MDSCs were differentiated in vitro through combination GM-CSF/IFN-γ treatment. When these MDSCs were subsequently adoptively transferred into a murine model of renal IRI, they aggravated kidney damage, likely owing to the differentiation of M-MDSCs into deleterious macrophages and DCs.

Highly biocompatible chlorin e6-poly(dopamine) core-shell nanoparticles for enhanced cancer phototherapy.

Cancer is a life-threatening disease worldwide. Although several approaches, such as surgery, chemotherapy, and radiotherapy, have been proven effective for many patients in clinics, they usually suffer from drug resistance, severe toxic-side effects, patient discomfort, and sometimes, unsatisfactory efficacies. In recent years, phototherapy, as a less invasive but effective therapeutic method, has brought hope for cancer treatment. However, most reported photo-therapeutic agents are constructed using complex components with non-negligible toxicity risk, thus retarding the start of their clinical trials. To address this issue, herein, biocompatible photothermal/photodynamic dual-mode therapeutic nanoparticles (CBP NPs) were successfully designed and constructed based on the Food and Drug Administration (FDA)-approved ingredients, chlorin e6 (Ce6) and poly(dopamine) (PDA). Upon light irradiation, hyperthermia was induced and reactive oxygen species (ROS) were generated simultaneously by CBP NPs, contributing to synergistic phototherapy toward cancer. The in vitro and in vivo experiments have demonstrated well the antitumor effect of CBP NPs. More importantly, CBP NPs are completely harmless and degradable in vivo. Together, the CBP NPs developed by us are an ideal candidate for the enhanced phototherapy of tumors, which holds great potential for future clinical translation.

Fabry-Perot Interferometer Based on a Fiber-Tip Fixed-Supported Bridge for Fast Glucose Concentration Measurement.

Blood glucose concentration is important for metabolic homeostasis in humans and animals. Many diabetic patients need to detect blood glucose daily which burdens community hospitals and family healthcare. Optical fiber sensors are widely used in biomedical detection because of their compact structure, fast response, high sensitivity, low cost, and ease of operation. In this work, we constructed a Fabry-Perot (FP) cavity biosensor for the fast detection of glucose concentration in serum. The femtosecond laser micromachining was applied to fabricate the FP cavity by printing the fiber-tip fixed-supported bridge at the end face of the optical fiber. An additional hemisphere was printed at the center of the outer surface of the bridge to avoid multi-beam interference. The results demonstrated that the proposed biosensor had high refractive index (RI) detection sensitivity, roughly 1039 nm/RIU at a wavelength of 1590 nm, and the detection sensitivity for glucose was around 0.185 nm/ (mg/mL) at a wavelength of 1590 nm. Due to its high sensitivity, compact structure, and fast response, the FP cavity biosensor has great potential to be applied in family healthcare for glucose concentration detection of diabetic patients.

A biocompatible ratiometric fluorescent nanoprobe for intracellular hydrogen sulfide accurate detection based on rare earth nanoparticle.

Hydrogen sulfide (H2S) is an important signal molecule involved in intracellular activities. To understand the role of H2S in cellular physiological and pathological process, the development of sensitive and selective methods, especially biocompatible assays, for efficient monitoring the level of H2S is necessary. Herein, we modified novel rare earth element europium (EU) based fluorescent nanospheres with azide (-N3) based sensor to construct an ingenious ratiometric fluorescent nanoprobe EU-N3. This nanoprobe showed excellent water solubility and high biocompatibility for intracellular H2S accurate detection. Nanoprobe EU-N3 had two obvious emission peaks, the green fluorescence peak at 540 nm increased according to the increasing of H2S concentration and the red fluorescence peak at 616 nm was stable as ratiometric reference. The fluorescence intensity ratio (I540/I616) displayed good linear response (R = 0.99136) in H2S range of 0.5 âˆ¼ 30 µM. The analytes response assay demonstrated that the nanoprobe EU-N3 possessed a better specificity for H2S, compared with other 9 anions and 3 cations. The cell viability assay indicated the nanoprobe EU-N3 had an excellent biocompatibility. The cell imaging showed that the proposed nanoprobe could be applied for detecting the intracellular H2S changes accurately in live cells. Such nanoprobe provided a safe and accurate strategy for intracellular H2S detection, which is helpful for the real-time H2S visualization in the live cell activities.