Nanomedicine: towards development of patient-friendly drug-delivery systems for oncological applications

The focus on nanotechnology in cancer treatment and diagnosis has intensified due to the serious side effects caused by anticancer agents as a result of their cytotoxic actions on normal cells. This nonspecific action of chemotherapy has awakened a need for formulations capable of definitive targeting with enhanced tumor-killing. Nanooncology, the application of nanobiotechnology to the management of cancer, is currently the most important area of nanomedicine. Currently several nanomaterial-based drug-delivery systems are in vogue and several others are in various stages of development. Tumor-targeted drug-delivery systems are envisioned as magic bullets for cancer therapy and several groups are working globally for development of robust systems

Genome-wide expression profiling reveals transcriptomic variation and perturbed gene networks in androgen-dependent and androgen-independent prostate cancer cells.

Previously, we have developed a unique in vitro LNCaP cell model, which includes androgen-dependent (LNCaP-C33), androgen-independent (LNCaP-C81) and an intermediate phenotype (LNCaP-C51) cell lines resembling the stages of prostate cancer progression to hormone independence. This model is advantageous in overcoming the heterogeneity associated with the prostate cancer up to a certain extent. We characterized and compared the gene expression profiles in LNCaP-C33 (androgen-dependent) and LNCaP-C81 (androgen-independent) cells using Affymetrix GeneChip array analyses. Multiple genes were identified exhibiting differential expression during androgen-independent progression. Among the important genes upregulated in androgen-independent cells were PCDH7, TPTE, TSPY, EPHA3, HGF, MET, EGF, TEM8, etc., whereas many candidate tumor suppressor genes (HTATIP2, CDKN2A, CDKN2B, CDKN1C, TP53, TP73, ICAM1, SOCS1/2, SPRY2, PPP2CA, PPP3CA, etc.) were decreased. Pathway prediction analysis identified important gene networks associated with growth-promoting and apoptotic signaling that were perturbed during androgen-independent progression. Further investigation of one of the genes, PPP2CA, which encodes the catalytic subunit of a serine phosphatase PP2A, a potent tumor suppressor, revealed that its expression was decreased in prostate cancer compared to adjacent normal/benign tissue. Furthermore, the downregulated expression of PPP2CA was significantly correlated with tumor stage and Gleason grade. Future studies on the identified differentially expressed genes and signaling pathways may be helpful in understanding the biology of prostate cancer progression and prove useful in developing novel prognostic biomarkers and therapy for androgen-refractory prostate cancer

Monoclonal Antibodies Recognizing the Non-Tandem Repeat Regions of the Human Mucin MUC4 in Pancreatic Cancer

The MUC4 mucin is a high molecular weight, membrane-bound, and highly glycosylated protein. It is a multi-domain protein that is putatively cleaved into a large mucin-like subunit (MUC4α) and a C-terminal growth-factor like subunit (MUC4β). MUC4 plays critical roles in physiological and pathological conditions and is aberrantly overexpressed in several cancers, including those of the pancreas, cervix, breast and lung. It is also a potential biomarker for the diagnosis, prognosis and progression of several malignancies. Further, MUC4 plays diverse functional roles in cancer initiation and progression as evident from its involvement in oncogenic transformation, proliferation, inhibition of apoptosis, motility and invasion, and resistance to chemotherapy in human cancer cells. We have previously generated a monoclonal antibody 8G7, which is directed against the TR region of MUC4, and has been extensively used to study the expression of MUC4 in several malignancies. Here, we describe the generation of anti-MUC4 antibodies directed against the non-TR regions of MUC4. Recombinant glutathione-S-transferase (GST)-fused MUC4α fragments, both upstream (MUC4α-N-Ter) and downstream (MUC4α-C-Ter) of the TR domain, were used as immunogens to immunize BALB/c mice. Following cell fusion, hybridomas were screened using the aforementioned recombinant proteins ad lysates from human pancreatic cell lines. Three anti MUC4α-N-Ter and one anti-MUC4α-C-Ter antibodies were characterized by several inmmunoassays including enzyme-linked immunosorbent assay (ELISA), immunoblotting, immunofluorescene, flow cytometry and immunoprecipitation using MUC4 expressing human pancreatic cancer cell lines. The antibodies also reacted with the MUC4 in human pancreatic tumor sections in immunohistochemical analysis. The new domain-specific anti-MUC4 antibodies will serve as important reagents to study the structure-function relationship of MUC4 domains and for the development of MUC4-based diagnostics and therapeutics

Beyond self-report: a review of physiological and neuroscientific methods to investigate consumer behavior

The current paper investigates the value and application of a range of physiological and neuroscientific techniques in applied marketing research and consumer science, highlighting new insights from research in social psychology and neuroscience. We review measures of sweat secretion, heart rate, facial muscle activity, eye movements, and electrical brain activity, using techniques including skin conductance, pupillometry, eyetracking, and magnetic brain imaging. For each measure, after a brief explanation of the underlying technique, we illustrate concepts and mechanisms that the measure allows researchers in marketing and consumer science to investigate, with a focus on consumer attitudes and behavior. By providing reviews on recent research that applied these methods in consumer science and relevant related fields, we also highlight methodological and theoretical strengths and limitations, with an emphasis on ecological validity. We argue that the inclusion of physiological and neuroscientific techniques can advance consumer research by providing insights into the often unconscious mechanisms underlying consumer behavior. Therefore, such technologies can help researchers and marketing practitioners understand the mechanisms of consumer behavior and improve predictions of consumer behavior

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Traffic aware resource allocation for multi-antenna OFDM systems

Abstract This thesis focuses on two important challenges in wireless downlink transmission: multi-user (MU) precoder design and scheduling of users over time, frequency, and spatial resources at any given instant. Data streams intended for different users are transmitted by a multiple-input multiple-output (MIMO) multi-antenna orthogonal frequency division multiplexing (OFDM) system. The transmit precoders are designed jointly across space-frequency resources to minimize the number of backlogged packets waiting at the coordinating base stations (BSs), thereby implicitly performing user scheduling. Then the problem of multicast beamformer design is considered wherein a subset of users belonging to a multicasting group are served by a common group-specific data. The design objective is to either minimize the transmit power for a guaranteed quality-of-service, or to maximize the minimum achievable rate among users for a given transmit power. Unlike existing techniques, the proposed design utilizes both the spatial and frequency resources jointly while designing multi-group beamformers. As an extension to coordinated precoding, the problem of beamformer design for cloud radio access network is considered wherein beamformers are designed centrally, quantized and sent along with data to the respective BSs via backhaul. Since the users can be served by multiple BSs, beamformer design becomes a nonconvex combinatorial problem. Unlike existing solutions, beamformer overhead is also included in the backhaul utilization along with the associated data. As the number of antennas increases, backhaul utilization is dominated by the beamformers. Thus, to reduce the overhead, two techniques are proposed: varying the quantization precision, and reducing the number of active antennas used for transmission. Finally, to reduce the complexity involved in the design of joint space- frequency approach, a two-step procedure is proposed, where a MU-MIMO scheduling algorithm is employed to find a subset of users for each scheduling block. The precoders are then designed only for the chosen users, thus reducing the complexity without compromising much on the throughput. In contrast to the null-space-based existing techniques, a low-complexity scheduling algorithm is proposed based on vector projections. The real-time performance of all the schedulers are evaluated by implementing them on both Xilinx ZYNQ-ZC702 system-on-chip (SoC) and TI TCI6636K2H multi-core SoC.Tiivistelmä Tässä väitöskirjassa keskitytään kahteen tärkeään langattoman tiedonsiirron haasteeseen alalinkkilähetyksissä: usean käyttäjän (MU) esikooderisuunnitteluun ja käyttäjien skedulointiin aika-, taajuus- ja tilaresurssien yli. Eri käyttäjille tarkoitettuja datavirtoja lähetetään käyttämällä monitulo-monilähtötekniikkaa (MIMO) yhdistettynä monikantoaaltomodulointiin (OFDM). Lähettimien esikooderit suunnitellaan yhteisesti tila- ja taajuusresurssien yli, jotta keskenään yhteistoiminnallisten tukiasemien jonossa olevien pakettien määrää voitaisiin minimoida samalla kun tehdään epäsuorasti käyttäjien skedulointia. Tämän jälkeen työssä paneudutaan monilähetysten (multicast) keilanmuodostussuunnitteluun, jossa monilähetysryhmään kuuluvien käyttäjien alijoukolle lähetetään yhteistä ryhmäspesifistä dataa. Suunnittelun päämääränä on joko minimoida kokonaislähetysteho tietyllä palvelunlaatuvaatimuksella tai maksimoida pienin saavutettavissa oleva siirtonopeus käyttäjien joukossa tietyllä lähetysteholla. Toisin kuin olemassa olevat menetelmät, ehdotetussa mallissa käytetään yhteisesti sekä aika- että taajuusresursseja usean ryhmän keilanmuodostusta suunniteltaessa. Laajennuksena yhteistoiminnalliselle esikoodaukselle, väitöskirjassa käsitellään myös keilanmuodostusta pilvipohjaisessa radioliityntäverkkoarkkitehtuurissa. Keilanmuodostajat suunnitellaan keskitetysti, kvantisoidaan ja lähetetään datan mukana tukiasemille käyttäen runkoverkkoyhteyttä. Koska käyttäjiä voidaan palvella usealta tukiasemalta, keilanmuodostussuunnittelu muuttuu ei-konveksiksi kombinatoriseksi ongelmaksi. Toisin kuin olemassa olevissa ratkaisuissa, ehdotettu malli sisällyttää käyttäjien datan lisäksi keilanmuodostajien resursoinnin tarpeen runkoverkkoon. Tukiaseman antennien määrän lisääntyessä, keilanmuodostajien osuus runkoverkon käyttöasteesta kasvaa suureksi. Jotta keilanmuodostajien aiheuttamaa ylimääräistä tiedonsiirtotarvetta voitaisiin minimoida, esitellään kaksi tekniikkaa: kvantisointitarkkuuden muunteleminen sekä lähetykseen käytettävien aktiivisten antennien määrän vähentäminen. Lopuksi, jotta yhdistetyn tila-taajuussuunnittelun aiheuttamaa kompleksisuutta saataisiin vähennettyä, ehdotetaan kaksivaiheista menetelmää. MU-MIMO skedulointialgoritmin avulla etsitään ensin alijoukko käyttäjiä jokaiselle skedulointilohkolle. Esikooderit suunnitellaan vain valituille käyttäjille, mikä vähentää kompleksisuutta, heikentämättä suorituskykyä kuitenkaan olennaisesti. Poiketen nolla-avaruuteen perustuvista tekniikoista, esitetään yksinkertainen vektoriprojektioihin perustuva skeduleri. Kaikkien skedulerien reaaliaikasuorituskykyä on arvioitu toteuttamalla ne ohjelmoitavilla Xilinx ZYNQ-ZC702 system-on-chip (SoC) ja TI TCI6636K2H moniydinalustoilla

Optimal bit allocation for source/channel coding in joint trellis coded quantization/modulation

Abstract not availabl