Real-world analysis of afatinib as a first-line treatment for patients with advanced stage non-small-cell lung cancer with uncommon EGFR mutations: a multicenter study in Vietnam.

Background: Afatinib is indicated for advanced-stage non-small-cell lung cancer (NSCLC) with Epidermal Growth Factor Receptor (EGFR) and uncommon mutations. However, real-world studies on this topic are limited. This study aimed to evaluate afatinib as first-line therapy for locally advanced and metastatic NSCLC with uncommon EGFR mutations. Patients and methods: A retrospective study included 92 patients with advanced NSCLC with uncommon and compound EGFR mutations, treated with afatinib as first-line therapy. Patients were followed up and evaluated every 3 months or when symptoms of progressive disease arose. The endpoints were objective response rate (ORR), time-to-treatment failure (TTF), and adverse events. Results: The G719X EGFR mutation had the highest occurrence rate (53.3% for both monotherapy and the compound). By contrast, the compound mutation G719X-S768I was observed at a rate of 22.8%. The ORR was 75%, with 15.2% of patients achieving complete response. The overall median TTF was 13.8 months. Patients with the G719X EGFR mutation (single and compound) had a median TTF of 19.3 months, longer than that of patients with other mutations, who had a median TTF of 11.2 months. Patients with compound EGFR mutations (G719X and S768I) demonstrated a median TTF of 23.2 months compared to that of 12.3 months for other mutations. Tolerated doses of 20 or 30 mg achieved a longer median TTF of 17.1 months compared to 11.2 months with 40 mg. Median TTF differed between patients with and without brain metastasis, at 11.2 and 16.9 months, respectively. Rash (55.4%) and diarrhea (53.3%) were the most common adverse events, primarily grades 1 and 2. Other side effects occurred at a low rate. Conclusion: Afatinib is effective for locally advanced metastatic NSCLC with uncommon EGFR mutations. Patients with G719X, compound G719X-S768I mutations, and tolerated doses of 20 or 30 mg had a longer median TTF than those with other mutations.

Deep-learning model for evaluating histopathology of acute renal tubular injury.

Tubular injury is the most common cause of acute kidney injury. Histopathological diagnosis may help distinguish between the different types of acute kidney injury and aid in treatment. To date, a limited number of study has used deep-learning models to assist in the histopathological diagnosis of acute kidney injury. This study aimed to perform histopathological segmentation to identify the four structures of acute renal tubular injury using deep-learning models. A segmentation model was used to classify tubule-specific injuries following cisplatin treatment. A total of 45 whole-slide images with 400 generated patches were used in the segmentation model, and 27,478 annotations were created for four classes: glomerulus, healthy tubules, necrotic tubules, and tubules with casts. A segmentation model was developed using the DeepLabV3 architecture with a MobileNetv3-Large backbone to accurately identify the four histopathological structures associated with acute renal tubular injury in PAS-stained mouse samples. In the segmentation model for four structures, the highest Intersection over Union and the Dice coefficient were obtained for the segmentation of the "glomerulus" class, followed by "necrotic tubules," "healthy tubules," and "tubules with cast" classes. The overall performance of the segmentation algorithm for all classes in the test set included an Intersection over Union of 0.7968 and a Dice coefficient of 0.8772. The Dice scores for the glomerulus, healthy tubules, necrotic tubules, and tubules with cast are 91.78 ± 11.09, 87.37 ± 4.02, 88.08 ± 6.83, and 83.64 ± 20.39%, respectively. The utilization of deep learning in a predictive model has demonstrated promising performance in accurately identifying the degree of injured renal tubules. These results may provide new opportunities for the application of the proposed methods to evaluate renal pathology more effectively.

Improving nitrogen content in soil and lemon balm (Melissa officinalis L.) yield by purple nonsulfur bacteria Rhodopseudomonas palustris in two consecutive seasons.

The study was conducted to assess the effects of nitrogen (N)-fixing purple nonsulfur bacteria (PNSB) Rhodopseudomonas palustris TLS06, VNW02, VNW64, and VNS89 on soil fertility, N uptake, essential oil (EO) content, growth, and yield of lemon balm. The experiment followed a completely randomized block design with 9 treatments and 3 replications. The treatments consisted of (i) applying 100% N as the recommended fertilizer rate (RFR), (ii) applying 85% N as RFR, (iii) applying 70% N as RFR, (iv) applying 55% N as RFR, (v) the treatment ii combined with N-PNSB, (vi) the treatment iii combined with N-PNSB, (vii) the treatment iv combined with N-PNSB, (viii) 0% as RFR combined with N-PNSB, and (ix) 0% N as RFR. The results showed that applying N-PNSB increased the plant height, and the number of primary branches in both seasons. In addition, the treatment without N fertilizer combined with N-PNSB increased stem leaf biomass by 41.2 and 50.3% in both seasons as compared with the treatment without neither N fertilizer nor N-PNSB. For soil properties, among treatments without N fertilizer, the treatment with N-PNSB increased concentrations of NH4+, soluble P, and exchangeable K+ by 41.3, 41.4, and 26.8%, respectively, as compared with the treatment without N-PNSB at the end of the second season. Applying 85% N as RFR combined with N-PNSB had a greater yield by 5.78-11.8% as compared with the treatment with 100% N as RFR, and a greater EO content by 23% as compared with the treatment with 85% N as RFR.

High biocompatible FITC-conjugated silica nanoparticles for cell labeling in both in vitro and in vivo models.

Fluorescence nanosilica-based cell tracker has been explored and applied in cell biological research. However, the aggregation of these nanoparticles at physiological pH is still the main limitation. In this research, we introduced a novel fluorescence nano-based cell tracker suitable for application in live cells. The silica-coated fluorescein isothiocyanate isomer (FITC-SiO2) nanoparticles (NPs) were modified with carboxymethylsilanetriol disodium salt (FITC-SiO2-COOH), integrating the dianion form of FITC molecules. This nanosystem exhibited superior dispersion in aqueous solutions and effectively mitigated dye leakage. These labeled NPs displayed notable biocompatibility and minimal cytotoxicity in both in vitro and in vivo conditions. Significantly, the NPs did not have negative implications on cell migration or angiogenesis. They successfully penetrated primary fibroblasts, human umbilical vein endothelial cells and HeLa cells in both 2D and 3D cultures, with the fluorescence signal enduring for over 72 h. Furthermore, the NP signals were consistently observed in the developing gastrointestinal tract of live medaka fish larvae for extended periods during phases of subdued digestive activity, without manifesting any apparent acute toxicity. These results underscore the promising utility of FITC-SiO2-COOH NPs as advanced live cell trackers in biological research.

Cognitively Driven Autonomous Flow Chemistry for Producing On-Demand Perovskite Quantum Dots Via Advanced Closed-Loop Feedback Control.

Recent developments in the synthesis of hybrid organic-inorganic halide perovskite quantum dots (HP-QDs) through compositional adjustments have highlighted their potential applications in the fields of photovoltaics and light sources due to their unique optoelectronic properties. However, traditional methods to fine-tune their composition involve repetitive, labor-intensive, and costly processes. Herein, the utilization of a continuous flow chemistry approach is developed, in combination with a Proportional-Integral (PI) feedback control system as an effective method for producing on-demand methylammonium lead bromoiodide (MAPbBrx I3-x ) HP-QDs. The PI feedback control allows for real-time optimization of the flow rates of halide precursor solutions (halide PSs), enabling the precise tuning of the emission wavelength of HP-QDs. HP-QDs having an emission wavelength of 550 and 650 nm are synthesized through a blue-shifted and red-shifted algorithm, respectively, from any arbitrary reaction condition within 400 s. The iterative process through the PI feedback control produces the target HP-QDs with short rise time and low overshoot. The proposed automatic flow chemistry system integrated with a universal and accessible control algorithm of PI can generate the target HP-QDs with high accuracy, stability, and robustness, demonstrating a significant advancement in constructing an autonomous flow chemistry synthetic system.

A complex case of necrotizing pneumonia and parapneumonic effusion in a healthy 20-month-old child: Successful management with video-assisted thoracoscopic surgery and chest tube placement.

Necrotizing pneumonia (NP) is characterized by destruction of pulmonary tissue, resulting in multiple thin-walled cavities. There are limited reports on NP and parapneumonic effusion cases in children associated with Pseudomonas aeruginosa. Currently, there is no consensus regarding the optimal timing for video-assisted thoracoscopic surgery (VATS) following failure of chest tube placement and antibiotic treatment. A healthy 20-month-old child was hospitalized with symptoms of community-acquired pneumonia, progressing to severe NP and parapneumonic effusion. Despite receiving broad-spectrum antibiotics and chest tube placement on the third day of treatment, the condition continued to deteriorate, prompting VATS intervention on the sixth day. The presence of a "split pleural sign" and extensive lung necrosis on chest computed tomography contributed to initial treatment failure. Multidrug resistance P. aeruginosa was identified through nasal trachea aspiration specimens on the eighth day of treatment, leading to an adjustment in antibiotic therapy to high-dose meropenem and amikacin. Subsequently, the patient became afebrile, showed clinical improvement, and was discharged after 35 days of treatment. Through this case, we aim to emphasize an unusual pathogenic bacteria in the context of NP and the need for standardized surgical interventions in pediatric patients with NP.

Photochemical oxidation of VOCs and their source impact assessment on ozone under de-weather conditions in Western Taiwan.

The application of statistical models has excellent potential to provide crucial information for mitigating the challenging issue of ozone (O3) pollution by capturing its associations with explanatory variables, including reactive precursors (VOCs and NOX) and meteorology. Considering the large contribution of O3 in degrading the air quality of western Taiwan, three-year (2019-2021) hourly concentration data of VOC, NOX and O3 from 4 monitoring stations of western Taiwan: Tucheng (TC), Zhongming (ZM), Taixi (TX) and Xiaogang (XG), was evaluated to identify the effect of anthropogenic emissions on O3 formation. Owing to the high-ambient reactivity of VOCs on the underestimation of sources, photochemical oxidation was assessed to calculate the consumed VOC (VOCcons) which was followed by the source identification of their initial concentrations. VOCcons was observed to be highest in the summer season (16.7 and 22.7 ppbC) at north (TC and ZM) and in the autumn season (17.8 and 11.4 ppbC) in southward-located stations (TX and XG, respectively). Results showed that VOCs from solvents (25-27%) were the major source at northward stations whereas VOCs-industrial emissions (30%) dominated in south. Furthermore, machine learning (ML): eXtreme Gradient Boost (XGBoost) model based de-weather analysis identified that meteorological factors favor to reduce ambient O3 levels at TC, ZM and XG stations (-67%, -47% and -21%, respectively) but they have a major role in accumulating the O3 (+38%) at the TX station which is primarily transported from the upwind region of south-central Taiwan. Crucial insights using ML outputs showed that the finding of the study can be utilized for region-specific data-driven control of emission from VOCs-sources and prioritized to limit the O3-pollution at the study location-ns as well as their accumulation in distant regions.

A real-world cohort study of first-line afatinib in patients with EGFR-mutant advanced non-small cell lung cancer in Vietnam.

BACKGROUND: This study aimed to evaluate the efficacy and side effects of first-line afatinib treatment in a real-world setting in Vietnam. METHODS: This retrospective study was conducted across nine hospitals in Vietnam. Advanced epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) patients who received afatinib as first-line therapy between April 2018 and June 2022 were included, and patient medical records were reviewed. Key outcomes were overall response rate (ORR), time-to-treatment failure (TTF), and tolerability. RESULTS: A total of 343 patients on first-line afatinib were eligible for the study. EGFR exon 19 deletion (Del19) alone was detected in 46.9% of patients, L858R mutation alone in 26.3%, and other uncommon EGFR mutations, including compound mutations, in 26.8%. Patients with brain metastases at baseline were 25.4%. Patients who received 40 mg, 30 mg, and 20 mg as starting doses of afatinib were 58.6%, 39.9%, and 1.5%, respectively. The ORR was 78.1% in the overall population, 82.6% in the Del19 mutation subgroup, 73.3% in the L858R mutation subgroup, and 75.0% in the uncommon mutation subgroup (p > 0.05). The univariate and multivariate analyses indicate that the ORR increased when the starting dose was 40 mg compared to starting doses below 40 mg (83.9% vs. 74.3%, p = 0.034). The median TTF (mTTF) was 16.7 months (CI 95%: 14.8-18.5) in all patients, with a median follow-up time of 26.2 months. The mTTF was longer in patients in the common EGFR mutation subgroup (Del19/L858R) than in those in the uncommon mutation subgroup (17.5 vs. 13.8 months, p = 0.045) and in those without versus with brain metastases at baseline (17.5 vs. 15.1 months, p = 0.049). There were no significant differences in the mTTF between subgroups based on the starting dose of 40 mg and < 40 mg (16.7 vs. 16.9 months, p > 0.05). The most common treatment-related adverse events (any grade/grade ≥ 3) were diarrhea (55.4%/3.5%), rash (51.9%/3.2%), paronychia (35.3%/5.0%), and stomatitis (22.2%/1.2%). CONCLUSIONS: Afatinib demonstrated clinical effectiveness and good tolerability in Vietnamese EGFR-mutant NSCLC patients. In our real-world setting, administering a starting dose below 40 mg might result in a reduction in ORR; however, it might not have a significant impact on TTF.

An open dataset on individual perceptions of transport policies.

Many cities are facing challenges caused by the increasing use of motorised transport and Hanoi, Vietnam, is no exception. The proliferation of petrol powered motorbikes has caused serious problems of congestion, pollution, and road safety. This paper reports on a new survey dataset that was created as part of the Urban Transport Modelling for Sustainable Well-Being in Hanoi (UTM-Hanoi) project. The survey of nearly 30,000 respondents gathers data on households' demographics, perceptions, opinions and stated behaviours. The data are informative in their own right and have also been used to experiment with multi-scale spatial statistics, synthetic population generation and machine learning approaches to predicting an individual's perceptions of potential government policies. The paper reports on the key findings from the survey and conducts a technical validation to contrast the outcomes to similar datasets that are available.

Neutrophil: Lymphocyte and Platelet: Lymphocyte ratios measured before transplantation and their correlation with new-onset diabetes post-transplantation in renal transplant recipients.

PURPOSE: Our goal was to evaluate the neutrophil:lymphocyte (NLR) and platelet:lymphocyte (PLR) ratios measured before transplantation and their correlation with new-onset diabetes after transplantation (NODAT) in renal transplant recipients. PATIENTS AND METHODS: We conducted our study in 324 adult patients consecutively admitted to Military Hospital 103, Ha Noi, Viet Nam, who received kidney allografts from living donors. These patients were followed-up during the first 2 years post-transplantation for NODAT. We examined the association between NLR and PLR measured prior to transplantation in patients with NODAT: NLR and PLR were calculated based on the results of the complete blood count. The criteria for diagnosis of a fully symptomatic NODAT case were based on the guidelines established by the American Diabetes Association and included fasting venous blood glucose and glycosylated hemoglobin A1c (HbA1c) levels, with or without an oral glucose tolerance test. RESULTS: The overall rate of NODAT during the two years after kidney transplantation was 13.6%. We found mean values of age and body mass index (BMI), and median values of NLR, PLR, high sensitivity C-reactive protein (hs-CRP) levels, and the arteriosclerosis ratio in the NODAT group to be significantly higher than those of the non-NODAT group (all p < 0.05). Furthermore, an adjusted multivariate regression analysis showed that age (area under the curve [AUC] = 0.727, p < 0.001), BMI (AUC = 0.846, p < 0.001), serum hs-CRP levels (AUC = 0.884, p < 0.001), NLR (AUC = 0.888; p < 0.001), and PLR (AUC = 0.818; p < 0.001) had predictive value for NODAT. CONCLUSION: NLR and PLR measured before transplantation were good predictors for NODAT in the first 2 years post-renal transplantation.

KTt-45, a T-type calcium channel blocker, acts as an anticancer agent by inducing apoptosis on HeLa cervical cancer cell line.

The abnormal expression in the T-type calcium channels is involved in various cancer types, thus inhibiting T-type calcium channels is one of approaches in cancer treatment. The fact that KTt-45 acted as a T-type calcium channel inhibitor as well as a pain-relief agent prompts us to address if KTt-45 plays any role against cancer cells. The results showed that KTt-45 caused cytotoxic effects towards HeLa cervical, Raji lymphoma, MCF-7 breast cancer, and A549 lung cancer cell lines with IC50 values less than 100 µM, in which highly selective toxicity was against HeLa cells (IC50 = 37.4 µM, SI > 3.2). Strikingly, the KTt-45 induced an accumulation of cytoplasmic vacuoles after 48 h treatment and mitochondrial-dependent apoptosis activation as evidenced by morphological features, chromatin condensation, nuclear fragmentation, and significant activation of caspase-9 as well as caspase-3. In conclusion, KTt-45 could inhibit cell growth and trigger mitochondrial-dependent apoptosis in HeLa cervical cancer cells. The results, taken together, strongly demonstrated that KTt-45 is a potential agent for further study on anticancer drug development which not only targets cancer cells but also helps to relieve neuropathic pain in cancer patients.

Magnetite nanoparticles decorated on cellulose aerogel for p-nitrophenol Fenton degradation: Effects of the active phase loading, cross-linker agent and preparation method.

Magnetite nanoparticles (Fe3O4 NPs) are among the most effective Fenton-Like heterogeneous catalysts for degrading environmental contaminants. However, Fe3O4 NPs aggregate easily and have poor dispersion stability because of their magnetic properties, which seriously decrease their catalytic efficiency. In this study, a novel environmentally friendly method for synthesising Fe3O4@CA was proposed. Fe3O4 NPs were immobilized on the 3D cellulose aerogels (CAs) in order to augment the degradation efficiency of p-nitrophenol (PNP) treatment and make the separation of the catalyst accessible by vacuum filtration method. Besides, CAs were fabricated from a cellulose source extracted from water hyacinth by using different cross-linking agents, such as kymene (KM) and polyvinyl alcohol-glutaraldehyde system (PVA-GA), and other drying methods, including vacuum thermal drying and freeze drying, were evaluated in the synthesis process. As-synthesized samples were analysed by various methods, including Powder X-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, energy dispersive X-ray analysis and Brunauer-Emmett-Teller. Then, using ultraviolet-visible spectroscopy, the difference in the degradability of PNP of the obtained material samples was also investigated to determine their potential applications. Results highlighted that the Fe3O4-3@CA-KF catalyst with an Fe3O4 loading of 0.40 g/gCA used KM as a cross-linker and the freeze-drying method demonstrated the highest PNP removal efficiency (92.5 %) in all Fe3O4@CA samples with a H2O2 content of 5 g/L. The degradation kinetics and well-fitted pseudo-first-order model were investigated. Notably, after five successive PNP degradation experiments, this catalyst retained ∼80 % of the ability to degrade PNP, indicating its outstanding reusability. In environmental remediation, this study provides valuable insights into the development of simply separated and high-efficiency catalysts for heterogeneous catalytic reactions.

Long noncoding RNAs as versatile molecular regulators of cellular stress response and homeostasis.

Normal cell and body functions need to be maintained and protected against endogenous and exogenous stress conditions. Different cellular stress response pathways have evolved that are utilized by mammalian cells to recognize, process and overcome numerous stress stimuli in order to maintain homeostasis and to prevent pathophysiological processes. Although these stress response pathways appear to be quite different on a molecular level, they all have in common that they integrate various stress inputs, translate them into an appropriate stress response and eventually resolve the stress by either restoring homeostasis or inducing cell death. It has become increasingly appreciated that non-protein-coding RNA species, such as long noncoding RNAs (lncRNAs), can play critical roles in the mammalian stress response. However, the precise molecular functions and underlying modes of action for many of the stress-related lncRNAs remain poorly understood. In this review, we aim to provide a framework for the categorization of mammalian lncRNAs in stress response and homeostasis based on their experimentally validated modes of action. We describe the molecular functions and physiological roles of selected lncRNAs and develop a concept of how lncRNAs can contribute as versatile players in mammalian stress response and homeostasis. These concepts may be used as a starting point for the identification of novel lncRNAs and lncRNA functions not only in the context of stress, but also in normal physiology and disease.

Complement receptor type 1 and 2 (CR1 and CR2) gene polymorphisms and plasma protein levels are associated with the Dengue disease severity.

The pathological outcome of dengue disease results from complex interactions between dengue virus (DENV) and host genetics and immune response. Complement receptor types 1 and 2 (CR1 and CR2) mediate complement activation through the alternative pathway. This study investigated the possible association of genetic polymorphisms and plasma levels of CR1 and CR2 with dengue disease. A total of 267 dengue patients and 133 healthy controls were recruited for this study. CR1 and CR2 gene polymorphisms were analyzed by Sanger sequencing, while plasma CR1 and CR2 levels were measured by ELISA. The frequency of the CR1 minor allele rs6691117G was lower in dengue patients and those with severe dengue compared to healthy controls. Plasma CR1 and CR2 levels were decreased in dengue patients compared to healthy controls (P < 0.0001) and were associated with platelet counts. CR1 levels were lower in dengue patients with warning signs (DWS) compared to those without DWS, while CR2 levels were decreased according to the severity of the disease and after 5 days (T1) and 8 days (T2) of follow-up. CR2 levels were decreased in dengue patients positive for anti-DENV IgG and IgM and patients with bleeding and could discriminate DWS and SD from dengue fever patients (AUC = 0.66). In conclusion, this study revealed a reduction in CR2 levels in dengue patients and that the CR1 SNP rs6691117A/G is associated with the dengue severity. The correlation of CR2 levels with platelet counts suggests that CR2 could be an additional biomarker for the prognosis of severe dengue disease.

Quantum Confinement in Epitaxial Armchair Graphene Nanoribbons on SiC Sidewalls.

The integration of graphene into devices necessitates large-scale growth and precise nanostructuring. Epitaxial growth of graphene on SiC surfaces offers a solution by enabling both simultaneous and targeted realization of quantum structures. We investigated the impact of local variations in the width and edge termination of armchair graphene nanoribbons (AGNRs) on quantum confinement effects using scanning tunneling microscopy and spectroscopy (STM, STS), along with density-functional tight-binding (DFTB) calculations. AGNRs were grown as an ensemble on refaceted sidewalls of SiC mesas with adjacent AGNRs separated by SiC(0001) terraces hosting a buffer layer seamlessly connected to the AGNRs. Energy band gaps measured by STS at the centers of ribbons of different widths align with theoretical expectations, indicating that hybridization of π-electrons with the SiC substrate mimics sharp electronic edges. However, regardless of the ribbon width, band gaps near the edges of AGNRs are significantly reduced. DFTB calculations successfully replicate this effect by considering the role of edge passivation, while strain or electric fields do not account for the observed effect. Unlike idealized nanoribbons with uniform hydrogen passivation, AGNRs on SiC sidewalls generate additional energy bands with non-pz character and nonuniform distribution across the nanoribbon. In AGNRs terminated with Si, these additional states occur at the conduction band edge and rapidly decay into the bulk of the ribbon. This agrees with our experimental findings, demonstrating that edge passivation is crucial in determining the local electronic properties of epitaxial nanoribbons.

Ensemble learning-based approach for automatic classification of termite mushrooms.

Termite mushrooms are edible fungi that provide significant economic, nutritional, and medicinal value. However, identifying these mushroom species based on morphology and traditional knowledge is ineffective due to their short development time and seasonal nature. This study proposes a novel method for classifying termite mushroom species. The method utilizes Gradient Boosting machine learning techniques and sequence encoding on the Internal Transcribed Spacer (ITS) gene dataset to construct a machine learning model for identifying termite mushroom species. The model is trained using ITS sequences obtained from the National Center for Biotechnology Information (NCBI) and the Barcode of Life Data Systems (BOLD). Ensemble learning techniques are applied to classify termite mushroom species. The proposed model achieves good results on the test dataset, with an accuracy of 0.91 and an average AUCROC value of 0.99. To validate the model, eight ITS sequences collected from termite mushroom samples in An Linh commune, Phu Giao district, Binh Duong province, Vietnam were used as the test data. The results show consistent species identification with predictions from the NCBI BLAST software. The results of species identification were consistent with the NCBI BLAST prediction software. This machine-learning model shows promise as an automatic solution for classifying termite mushroom species. It can help researchers better understand the local growth of these termite mushrooms and develop conservation plans for this rare and valuable plant resource.

A Normalization Protocol Reduces Edge Effect in High-Throughput Analyses of Hydroxyurea Hypersensitivity in Fission Yeast.

Edge effect denotes better growth of microbial organisms situated at the edge of the solid agar media. Although the precise reason underlying edge effect is unresolved, it is generally attributed to greater nutrient availability with less competing neighbors at the edge. Nonetheless, edge effect constitutes an unavoidable confounding factor that results in misinterpretation of cell fitness, especially in high-throughput screening experiments widely employed for genome-wide investigation using microbial gene knockout or mutant libraries. Here, we visualize edge effect in high-throughput high-density pinning arrays and report a normalization approach based on colony growth rate to quantify drug (hydroxyurea)-hypersensitivity in fission yeast strains. This normalization procedure improved the accuracy of fitness measurement by compensating cell growth rate discrepancy at different locations on the plate and reducing false-positive and -negative frequencies. Our work thus provides a simple and coding-free solution for a struggling problem in robotics-based high-throughput screening experiments.

Two closely spaced microstrip patches with high isolation for full-duplex/MIMO applications.

This paper shows an effective method to significantly enhance the isolation of a closely spaced two-port patch antenna, which can be deployed for full-duplex transceivers as well as multiple-input-multiple-output (MIMO) systems. Two rectangular microstrip patches are arranged in the E-plane configuration. To achieve high isolation, a grounded stub is positioned between the radiating patches. For validation of the proposed concept, an antenna prototype is fabricated for measurements. The measured data demonstrates that the port-to-port mutual coupling can be suppressed to -50 dB, which is useful in self-interference cancellation for full-duplex communication systems. Compared with the coupled design, the isolation is significantly enhanced by 43 dB with an inter-element spacing of 0.034λc, where λc is a free-space wavelength at the center operating frequency. Regarding MIMO metrics, the antenna also shows good MIMO diversity performance based on an envelope correlation coefficient and a diversity gain.

Effectiveness and safety of CD22 and CD19 dual-targeting chimeric antigen receptor T-cell therapy in patients with relapsed or refractory B-cell malignancies: A meta-analysis.

BACKGROUND: The efficacy of CD22 or CD19 chimeric antigen receptor T (CAR-T) cells in the management of acute lymphoblastic leukemia (ALL) and non-Hodgkin lymphoma (NHL) was observed. Because antigen loss and lack of CAR-T-cell persistence are the leading causes of progressive disease following single-antigen targeting, we evaluated CD22/CD19 dual-targeting CAR-T-cell therapy efficacy and safety in relapsed/refractory B-cell malignancies. METHODS: The Web of Science, PubMed, Cochrane, and Embase databases were searched until July 2022. Patients confirmed with any relapsed/refractory B-cell hematological malignancies were included regardless of age, gender, or ethnicity, receiving CD22 and CD19-dual-targeting CAR-T-cell therapy. The studies conducted on patients with coexisting other cancer were excluded. We used random-effect models to explore the outcome, and heterogeneity was investigated by subgroup analysis. RESULTS: Fourteen studies (405 patients) were included. The pooled overall response (OR) and complete remission (CR) were 97% and 93%, respectively, for ALL patients. The 1-year proportions of overall survival (OS) and progression-free survival (PFS) were 70% and 49%, respectively. For NHL, OR occurred in 85% of patients, and 57% experienced CR. The results illustrated that the 1-year OS and 1-year PFS were 77% and 65%, respectively. The subgroup analysis showed that the dual-targeting modality achieved higher CR in the following cases: coadministration of CD22/CD19-CAR-T cells and third-generation CAR-T cells combined with ASCT and BEAM pretreatment. The ALL and NHL groups seemed similar in treatment-related toxicity: all grade cytokine release syndrome (CRS), severe CRS, and neurotoxicity occurred in 86%, 7%, and 12% of patients, respectively. CONCLUSIONS: Our meta-analysis demonstrated that the CD22/CD19 dual-targeting CAR-T-cell strategy has high efficiency with tolerable adverse effects in B-cell malignancies.

Stem cell therapies for periodontal tissue regeneration: A meta-analysis of clinical trials.

Objective: Stem cell therapy in periodontal tissue regeneration has reported optimistic regenerative results; evidence supporting its superiority over conventional methods is still ambiguous. Therefore, this meta-analysis aims to evaluate the therapeutic effects of stem cells in human periodontal regeneration. Design: A literature search was conducted to retrieve relevant articles on periodontal regeneration in stem cell therapy. A meta-analysis of the studies was conducted using the Stata software. Results: Fifteen studies that examined the effect of stem cell therapies on periodontal tissue regeneration in 369 patients were selected from databases. Regardless of the various types of cells, both odontogenic (periodontal ligament, dental pulp, gingiva stem cell) and non-odontogenic (bone marrow, periosteum-derived, and umbilical cord stem cells), the cell therapies witnessed significant improvements in terms of clinical attachment level (SMD, -0.67; 95CI, -0.90 to -0.43), probing depth (SMD, -0.76; 95% CI, -1.21 to - 0.31), radiographic intrabony defect depth (SMD, -0.87; 95% CI, -1.52 to -0.23), and histomorphometric analysis of mineralized bone (SMD, 0.80; 95% CI, 0.42 to 1.19) when compared to traditional without-cell treatment in patients. However, evidence on gingival recession, alveolar thickness gain, bone mineral density of bone core, and bone volume fraction of bone core outcomes did not reach statistical significance. Conclusions: Evidence suggests that the implementation of stem cell therapies in reconstructing compromised gingiva and alveolar bone tissue produces positive outcomes compared with conventional approaches. However, further well-designed investigations are needed to comprehensively identify the most effective source of cells and biomaterials for each case.